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BIOLOGICAL SCIENCES

NOTE: PRACTICALLY STUDENTS AND INSTRUCTORS/PROFESSORS WILL MAKE USE OF MULTIPLE SOFTWARE AND DATA SOURCES OUT OF THE LISTS PROVIDED FOR COURSES AND ACTIVITIES. A PARTICULAR SOFTWARE OR DATA SOURCE HAS ITS RESPECTIVE FOCUSES AND STRENGTHS. Biology degree pursuits concern environments that invite, assimilate, nurture and sustains advancement beyond cultural and racial settings. The biology environment is not a place for de-facto vice sororities nor vice fraternities. The biology environment concerns cerebral functional growth, ingenuity, adaptation and advancement in laboratory activity and technology from acquired knowledge and skills. BIOLOGY REALM Courses GENERAL BIOLOGY I & II, GENERAL CHEMISTRY I & II, ORGANIC CHEMISTRY I & II, to be accompanied by lab instruction; other courses with given syllabuses to have lab instruction if expressed. Of interest: https://www.raspberrypi.org/magpi/digital-microscope/

Calculus for Biological Sciences I Limits, continuity, derivatives, mean value theorem, extrema, curve sketching, related rates, differentiation of the trig, log, and exponential functions, basic integration techniques, with particular motivations from and application to the Biological Sciences. Mandatory enrolment for beginner freshmen Typical Text: Calculus for Biology and Medicine, by Claudia Neuhauser, Pearson Course to be taught with use for scientific/graphing calculators and immersion into RStudio Problem Sets --> Problem Sets: There will be (mostly) weekly homework assignments. Exams --> There will be 2 midterms at the end of week 4, and at the end of week 8. There will be a two-hour final exam at the time scheduled by the registrar’s final exam calendar. Topics List: 1.2 Elementary Functions 1.3/2.1 Graphing/Exponential Growth and Decay 2.2 Sequences 3.1-3.4 Limits and Continuity 3.5 Properties of Continuous Functions 4.1 Derivatives 4.2-4.3 Rules of Differentiation, Product and Quotient Rules 4.4 Chain Rule and Higher Derivatives 4.5-4.7 Derivatives of Special Functions and Inverse Functions 5.1-5.3 Extrema, Mean Value Theorem, Monotonicity, Concavity, Inflection Points 5.4 Optimization 5.5 L'Hospital's Rule 5.8 Antiderivatives 6.1 The Definite Integral 6.2 The Fundamental Theorem of Calculus 6.3 Applications of Integration 7.1-7.2 Integration Techniques Also: Small-group Projects Calculus for Biological Sciences II Mandatory enrolment for upper level freshmen granted that they have successful completed Calculus for Biological Sciences I Learning Outcomes: in this class we will learn how to -Find the family of antiderivatives (if possible) for a continuous function -Approximate definite integrals using Riemann sums -Use substitution and integration by parts to compute indefinite and definite integrals -Compute and interpret definite integrals with finite and infinite limits of integration -Set up single and coupled differential equations based on written descriptions including predator/prey models, population ecology, competitive selection, and chemical exchange across a membrane -Solve certain pure-time, autonomous, and non-autonomous differential equations using integration and separation of variables -Find and determine the stability of equilibria in autonomous differential equations; draw relevant phaseline diagrams -Sketch solutions to single and coupled differential equations from an initial condition -Verify solutions to, and use Euler’s method with, differential equations in two dependent variables -Use nullclines and find equilibria of systems of differential equations in two dependent variables -Sketch phase-plane trajectories for systems of differential equations Typical Text: Text: Calculus for the Life Sciences, by Frederick Adler. Course to be taught with use for scientific/graphing calculators and immersion into RStudio Problem Sets --> Will be (mostly) weekly homework assignments. Quizzes --> We have 4-5 quizzes Exams --> There will be 2 midterms at the end of week 4, and at the end of week 8. There will be a two-hour final exam at the time scheduled by the registrar’s final exam calendar. Approximate Schedule --> Week 1: Differential equations and antiderivatives. (4.1-4.2.) Week 2: Integration: how to compute antiderivatives. (4.3-4.4.) Week 3: Definite integrals. Applications of integrals. (4.5-4.6.) Week 4: Improper integrals. (4.7.). Midterm I. Week 5: More complicated (and interesting) differential equations. 5.1-5.2. Week 6: Autonomous differential equations. (5.3-5.4.) Week 7: Differential equations in dimension 2. (5.5-5.6.) Week 8: Solving DEs graphically or approximately. (5.7.). Midterm II. Week 9: The dynamics of a neuron. (5.8.) Week 10: Review. Week 11: Final exam A. MICROBIOLOGY degree. Apply additional lab instruction or compliment lab hours wherever needed for courses. Students will proceed with courses based on prerequisites they have successfully completed with satisfactory grade requirement. Curriculum: --Core Courses Scientific Writing I & II, General Biology I & II, General Chemistry I & II, Organic Chemistry I (with labs), Biochemistry (with labs), Organic Synthesis Laboratory, Biostatistics I & II, Advanced Statistical Modelling and Machine Learning for Biostatistics --Professional Necessities Cell Biology (with labs), Molecular Biology I & II, Microbiology I & II (with labs), Environmental Microbiology, Clinical Microbiology, Microbiology of the Digestive System, Bacteriology, Virology, Tissue Culture & Virology Lab, Genetic Engineering & Technology, Comparative Genomics (check METAB BIO), Biotechnology Laboratory, Advanced Biotechnology Laboratory, Tissue Engineering, Microbiology Research --Mandatory Courses Calculus for the Biological Sciences I & II, ODE, General Physics I Note: if students are interested in Molecular Biology II, such course to be electives, granted that student have the academic time to pursue them. Description of particular listed courses: Biostatistics I Course concerns probability and statistics applied to problems in biology, industrial/occupational health, and epidemiology. Use of statistical software R for data analysis is emphasized extensively. Note: this course is designed for students majoring in the biological sciences with a second term calculus background. Through the extensive use of practical examples, this course is expected to motivate and teach students statistics knowledge that would be helpful for their major study. The computer program R is the standard statistical program for this course. Students will use R to complete data analysis projects. R can be downloaded and installed on your personal computer for free following instructions at http://www.r-project.org/. In addition, the R environment will be augmented by RStudio interface with other R packages. This course covers fundamental concepts in probability and statistics, including data description, design of experiment, probability rules and distributions, statistical inference and linear regression. Definitions will be learned through real-world examples and applications. Besides these traditional materials and subjects, topics and methods that are particularly applicable to the biological sciences will be introduced. Again, much focus on the applications of statistical ideas to realistic data and practices. Students are expected to use materials learned from this course to guide statistical practice for their major studies in the future. After successfully completing this course the expectation is that students will be able to: 1. To grasp concepts in probability and be able to apply basic probability rules, distributions, and laws to solve conceptual statistics questions 2. Use statistical guidelines and common sense to interpret the process of data collection, description and analysis, and to design statistically sound experiments 3. Learn various statistical inference techniques and be able to select appropriate methods for specific data sets and scientific purpose 4. Link the course materials with real-life examples, and explore the opportunities for other biological applications 5. Interpret statistical reports and carrying out data analysis using R. Several data projects will be assigned during the semester. Independent work is expected. This is not a course of “pen and paper finesse” succeeding the composition of gunk and bamboozle on a writing board. One can’t be successful in statistics by only writing down theory. Practice with an environment that applies intelligence and engagement is essential. There’s no point in doing statistics if one doesn’t know how to acquire and manipulate real data. Real data realistically outnumbers the fingers and toes one possesses. Most of grading will be based on projects (having commentary descriptions) accompanied by the analytical process development description done in a word processor. Typical Texts --> Will make use of R language Statistics texts under CRC Press and Springer publishing Tools --> R language and R Studio Note: a calculator at times may prove useful for the idealistic or the “synthetic” customary questions. “R Monograph Notebook” --> Students should maintain a notebook as they proceed through the course and learn how to do analyses in R. This assignment involves a notebook that lists the syntax and provides a brief explanation of each function that students learn during the course. Instructor will assign R maturity development questions to be in tune with course progress; you will only be allowed to use your monograph to assist with assigned questions. The notebook will be handed in near the end of the semester and handed back to the students after grading. Such a notebook can be an extremely useful resource both during and after the course to quickly refresh one’s memory on the details of a particular function. Design with R most likely will vary among students. Poor development in a such a notebook may or may not correlate with poor grades. NOTE: this course serves only to towards the perspective of students in the biological sciences, so no one in the biological sciences should be looking elsewhere. MIND YOUR DAMN BUSINESS. Grading --> Problem Sets 20% R Labs 20% R Activities 0.7 R Monograph Lab Notebook 0.3 R maturity development questions 15% End of term lecturer observation 5% 3 Exams 30% Assigned Projects 30% Exams --> Limited open notes. I don’t like setting up myself and students for embarrassment; you are not perfect with statistics, so expect exams to be primarily knowledge based and the calculus related fodder. Most of your development will come from homework and labs; it is what it is. Note: limited open notes. Students may be more comfortable with certain R packages. Again --> Several data projects will be assigned during the semester. Independent work is expected. Course Outline --> Introduction to statistics, data and R Statistical Measures and Summary Statistics for data sets Methods of data acquisition: Sources/databases (ecological & biological), file types, APIs, etc. Introspection. querying, wrangling Summary Statistics with R Applied probability theory Axioms of probability Modelling frequencies and establishing densities Simulating random variables from real experiments Probability distributions and properties Sample estimates Law of Large Numbers and the Central Limit Theorem Introduce the Law of Large Numbers (LLN) Central Limit Theorem (CLT). Identify Exponential, Poisson and Binomial data and respectively determine in a manner to confirm LLN and CLT. Routledge, R., Chebyshev’s Inequality, Encyclopaedia Britannica Is there too much reliance on assuming normal or Gaussian distribution? Towards Chebyshev’s inequality what amount of repetition (regarding LLN and CLT) of an experiment is adequate towards Chebyshev becoming relevant? Overview and goals of various concentration inequalities (just a survey). Chi-square distribution The bottom line is to establish the flow of the uses competently with applications involving real raw data. Comprehending categorical data sets and ordinal data sets Organisation of data and sensitivity of categories concerning traits of interest. Test for independence McHugh ML. (2013). The chi-square Test of Independence. Biochem Med (Zagreb). 23(2): 143-9. Test of homogeneity Test of variance Applications of the Chi-Square distribution with confidence intervals T-distribution Kim T.K. & Park J. H. (2019). More About the Basic Assumptions of T-test: Normality and Sample Size. Korean J Anesthesiol. 72(4): 331-335. Sample size determination Population parameter estimation Confidence intervals Directly logistical to understand what you’re doing in R F-distribution Assumptions for the F-distribution Relevance to the biological sciences (active data immersion) Note: not textbook finesse, rather how and when actively. Goodness of fit: fit of distributions Summary Statistics Skew and Kurtosis Box Plots Density Plots P-P and Q-Q Statistical Tests Definition, Null hypothesis One-sided & two-sided tests of hypothesis Types of test statistics Comprehending critical values for ideal distributions Significance levels Critical values for real raw data sets Does your data exonerate ideal distributions? Chi-Square Test Kolmogorov-Smirnov Test Anderson-Darling test Shapiro-Wilk Test MLE and Method of Moments Manual tasks will be limited to at most 4 element data sets Computational logistics for large data sets followed by implementation Review/probe data for goodness of fit module for appropriate distribution You may be tasked with distribution determination before parameter/point estimation Hypothesis testing (exploratory) Note: as aspiring biologists I can’t give “zombie textbook problems” and expect you to relate to a profession tangibly and fluidly. You will be exposed to raw professional data from various sources. You will develop the four mentioned steps. You should ask yourselves if the hypotheses are practical as well. Why is normal distribution assumed? Will be exploratory rather than zombie problems. Namely, knowledge and skills from Goodness of fit module. Then proceed with the following: 1.State the two hypotheses so that only one can be right 2.Formulate an analysis plan, outlining how data will be evaluated 3.Carry out the plan and physically analyze the sample data 4.Analyse the results and either reject the null, or state that the null is plausible, given the data Test of Proportions (exploratory) Comparisons of variances Directly logistical to understand what you’re doing in R Confidence limits for means. Does it require normality? Analysis of variance Must be exploratory, else it’s toxic Correlation (includes misuse of types and resolutions) Pearson Correlation Crucial Conditions Structure Implementation Spearman Correlation Crucial Conditions Structure Implementation Generating heat maps. The ggpairs() function Bivariate Regression Two and three-way analyses of variance Must be data exploratory, else it’s toxic Multiple Regression Model components Methods to select variables OLS MUST: Summary Statistics Analysis of Covariance Must be exploratory, else it’s toxic Non-parametric statistics Resampling methods Falsified Data Hartgerink C, Wicherts J, van Assen M (2016). The Value of Statistical Tools to Detect Data Fabrication. Research Ideas and Outcomes 2: e8860. Al-Marzouki, S., Evans, S., Marshall, T., & Roberts, I. (2005). Are these data real? Statistical methods for the detection of data fabrication in clinical trials. BMJ, 331(7511), 267–143. Yamamoto, K., & Lennon, M. L. (2018). Understanding and Detecting Data Fabrication in Large-Scale Assessments. Quality Assurance in Education, 26(2), 196–212. Prerequisites: General Biology II, Calculus II Biostatistics II --This succeeding course in the sequence will have more emphasis on incorporating journal articles and real world experiments. --Students will have to orchestrate inquisitions by exploratory data analysis and statistical methods involving R. There will be assigned data sets and journal articles to do just that. --This is not a “pen and paper course”. Texts and journal articles will cater to subjects both from prerequisite and this course. Means of data retrieval and manipulation are crucial; it may be the case that the data desired in inaccessible, hence students will have to resort to alternative data sources that yields much different conclusions. NOTE: personally refresh your knowledge and acquired R skills from calculus and Biostatistics I alongside ordained reacquaintances in course. NOTE: this course serves only to towards the perspective of students in the biological sciences, so no one in the biological sciences should be looking elsewhere. MIND YOUR DAMN BUSINESS, AND KEEP YOUR DAMN BUSINESS . Assessment --> Assignment Sets (prerequisite & current level from multiple sources) 15% Analytical and R based 3 Exams (prerequisite & current level) 30% Labs + Data Analysis Term Project 40% 2 Field Inquisitions with R 15% Conducted Journal Articles Computational Inquisitions Supporting data sets to be provided Gov’t administration field experiments inquisitions Assignment Sets --> Will be reacquainted with prerequisite tasks, prerequisite projects AND current level tasks (analytical and R computational). Exams --> Exams will have the same manner of administration and activities as exams from prerequisites. Yet, consisting of both prerequisite tasks AND current level tasks. Limited open notes. LABS WITH R --> Hypothesis Testing Expt. Design, Multiple Comparisons ANOVA Regression (Mult. Reg. and Dummy) ANCOVA Mantel Test & ANOVA MANOVA and DFA Clustering PCA and Kernel PCA PCA and Kernel PCA Re-analysis of DFA Data Comparing & Averaging Models Analysis of Trait Evolution Fitting models of Trait Evolution TERM PROJECT --> The term project has been broken down into multiple components due throughout the semester to provide further guidance for students. On given date, students will select a dataset to use for their term project. Students can either provide their own dataset (if they have collected data during their research), or will be given the opportunity to analyse a complex dataset supplied by faculty as their term project. For the Hypothesis Activity (given due data), students will take a close look at their dataset and formulate biological hypotheses that they would like to test statistically. The assignment will be handing in these hypotheses. For the Experimental Design assignment (given due), students will outline which analyses they will use to test their biological hypotheses and provide the specific explicit statistical hypotheses that they will test. The Term Project Report (given due having additional 1 week collection buffer) will be written after students complete their analyses. The report will include a Statistical Methods and a Results section, complete with tables and figures. Methods should include sufficient detail to redo the analyses. The results should include everything necessary for interpretation of their analyses and data, but not superfluous material. Term Project Reports for all students should include a title page with a title, student name, course number and name, and assignment name. The text of the report should be double spaced, with indented paragraphs, 1” margins, 12pt Times New Roman Font, and page numbers. Tables should be single spaced with headings above each table. Figures should have captions below each figure. Figures and tables can be embedded in the text or provided at the end of the document. Literature cited should follow the format for the journal Evolution. Assignments that do not follow these formatting instructions will be returned to the student for correction prior to grading. NOTE: most labs done serve as structure for your HA and ED NOTE: I will be collecting your R development (having sensible commentary) for the term project in PDF along with the term report in PDF. Finally, students will give a short, in-class presentation about their study, analyses and findings. Presentations will be in PowerPoint. MAJOR COURSE TOPICS --> Methods of data acquisition, data wrangling and summary statistics (prerequisite reinforcement) Goodness of Fit (prerequisite reinforcement) Hypothesis Testing Review Experimental Design & Sampling ANOVA Variations & Models Regression (multivariate) Quantile regression compared to Least Squares regression ANCOVA Resampling Techniques MANOVA Clustering (K-means or DBSCAN?) Principal Component Analysis (PCA) and Kernel PCA Model Selection & Likelihood (emphasis on computational logistics and implementation) Phylogenetic Regression Extensions of Phylogenetic Statistics Prerequisite: Biostatistics I Advanced Statistical Modelling and Machine Learning for Biostatistics This course explores advanced statistical modeling techniques and machine learning methods as applied to biostatistical problems. Topics include generalized linear models, hierarchical modeling, Bayesian statistics, and the integration of machine learning algorithms for analyzing complex biological and health data. Note: 2 lectures per week, with approximately 2 hours per lecture. Assignments -- Assignments will be quite laborious in the interest of sustainability with knowledge and skills through your journey in biostatistics. Each assignment will comprise of the following elements: A. problems and tasks encountered in both Biostatistics I & II. Such problems and tasks will also make extensive use of R. As well, being advanced biostatistics students, projects from Biostatistics I & II can/will also be considered basic assignments as well. B. Course level assignments to such given course topics. Good emphasis on ability to comprehend and specify the transition from prerequisite skills/tools to course level tools/method/skills; then implementation. Will also make extensive use of R. Data Science Basics Quizzes -- For the Data Science Basics module there will be handwritten quizzes to test knowledge, comprehension, appropriateness and T/F. Exams -- Exams will account for all modules. Assignments will be strong foresight of what’s to appear on exams. You will be making extensive use of R with open notes for all course modules. Exams will feel like projects where each “project” will involve multiple modules. Make-up Student Project -- Applying Advanced Models to Biostatistical Data. Concerns students who are interested in making up lost weight towards their final grade; the better you did in this course, the lower the value. Can regain up to 5% for final grade. Students will be given a sack to randomly (and blindly) pick a project. Students will have until 2 days before the final grade submission deadline to submit projects. Students will be privately given project details via student email where they will have to acquire the data from specified sources. Course Assessment -- Assignments 20% 4 Exams for all modules 60% 3 Data Science Basics Quizzes 15% Will be precursors to exam(s) for the Data Science Basics module Make-up Student Project (being conditional) COURSE OUTLINE -- WEEK 1-3. Introduction to Generalised Linear Models (GLMs) with model estimation and summary statistics Multilinear Regression (fast fast review) Quantile Regression Logistic Regression Poisson Regression WEEK 4-5. Hierarchical Modelling (HM) Introduction to HM Multilevel Modelling Random Effects and Mixed Models WEEK 6-7. Bayesian Statistics in Biostatics Note: I don’t introduce things to be a disgusting, miserable, viral bastard. Module will be extremely goal oriented, namely, problem, goal(s), methodology, logistics, implementation, evaluation. No social nor psychological probes/inquisitions; there are certified licensed professionals elsewhere tied to meaningful or economic interests. Bayesian Inference (to the point, constructive and economical) Markov Chain Monte Carlo (MCMC) Methods – only constructive and economical methods Bayesian Regression Models WEEK 8-9. Advanced GLMs and Extensions Negative Binomial Regression Zero-Inflated Models Generalised Estimating Equations (GEE) WEEK 10-15. Data Science Basics Note: subjects of overfitting or underfitting arise in model validation statistics. Data Acquisition. Data Probing: view(), glimpse(), str() Data Cleaning and Data Wrangling Summary Statistics, Skew, Kurtosis, Correlation Analysis and Heatmaps Machine Learning Overview Feature Selection R functions (underlying methods may not be fully comprehended, but that’s generally the world): Principal Component Analysis (PCA), Kernel PCA, Boruta, FSelectorRccp. Comparative observation among such prior three also expected. Classification Multiple Regression (very rapid review) OLS and Quantile Support Vector Machines Decision Trees Random Forests Clustering (K-Means and DBSCAN advanced repetition) Includes the Silhouette Score and Davies-Bouldin Index Prerequisites: General Biology II, General Chemistry II, Biostatistics II Organic Chemistry I In-depth study of: (i) the structure of organic compounds and the functional groups (bonding, acid-base properties, nomenclature, conformations, stereochemistry), and (ii) the synthesis and reactivity (including detailed mechanisms) of alkanes, alkenes, alkynes, halides, alcohols, ethers, epoxides, sulfides and organometallic reagents. Laboratory experiments are related to topics covered in lecture and emphasize organic laboratory techniques, synthesis and spectroscopic characterization of organic molecules. Typical Texts: McMurry, John E. Organic Chemistry. 8th Edition. Brooks/Cole, 2012. McMurry, Susan. Study Guide with Student Solutions Manual. 8th Edition. Brooks/Cole. Typical Lab Manual: Barbaro, John and Richard K. Hill. Experiments in Organic Chemistry. 3rd Edition, Contemporary Publishing Company of Raleigh, Inc., 2006 Grading: 3 Exams (50% combined) Cumulative Final Exam (25%) Labs (25%) (On the occasion of significant improvement on the final exam, more weight will be placed on the final exam) INSTRUCTIONAL METHODS: List the different instructional methods you might use, in the course of the semester. List supplementary learning options, if any: Traditional lecture with use of chalkboard Computer assisted diagrams and graphics Molecular Models Team work in the laboratory Homework assignments Solving specific questions related to content studied Written exams and distribution of study questions/previous exams Use of the Internet UNIQUE ASPECTS OF COURSE (such as equipment, specified software, space requirements, etc.): Organic chemistry laboratories and their associated equipment, instruments and chemicals. Apart from use of software in lectures, students will use software to accompany experiments that provide detailed molecular/compound structure, target sites, functional groups, etc. etc. Such exhibits will accompany lab reports. Ch. 1 Structure and Bonding Bonding; Hybridization; Drawing Chemical Structures; Functional Groups; Intro to IR Spectroscopy Ch. 2 Polar Covalent Bonds; Acids and Bases Chemical Bonding (Ionic and Covalent); Electronegativity and Dipole Moments; Formal Charges; Resonance Structures; Acid Base Theory (Bronsted-Lowry, Lewis); Acid and Base Strength (pKa); Acid-Base Reactions; Organic Acids and Organic Bases Ch. 3 Organic Compounds: Alkanes and their Stereochemistry Alkanes, Alkane Isomers, and Alkyl Groups; Properties of Alkanes; Conformations Ch. 4 Organic Compounds: Cycloalkanes and their Stereochemistry Cis-Trans Isomerism in Cycloalkanes; Stability and Conformations of Cycloalkanes; Chairs Ch. 5 Stereochemistry at Tetrahedral Centres Enantiomers, the Tetrahedral Carbon and Chirality; Optical Activity; R/S Sequence Rules; Diastereomers and Meso Compounds; Racemic Mixtures, Resolution of Enantiomers; Prochirality; Chirality in Nature Ch. 6 An Overview of Organic Reactions Kinds of Organic Reactions (Radical and Polar); Mechanisms; Describing a Reaction (Equilibria, Rates, Energy Changes, Bond Energy; Transition States, and Intermediates) Ch. 7 Alkenes: Structure and Reactivity Preparation and use of Alkenes; Cis-Trans Isomerism; Alkene Stereochemistry and E/Z Designation; Stability of Alkenes; Electrophilic Addition Reactions; Markovnikov’s Rule: Carbocation Structure and Stability; Carbocation Rearrangements Ch. 8 Alkenes: Reactions and Synthesis Preparation of Alkenes via Elimination Reactions; Addition Reactions of Alkenes (Halogenation, Hydration, Halohydrins, and Hydrogenation); Oxidation of Alkenes (Epoxidation and Hydroxylation); Addition of Carbenes; Radical Additions to Alkenes (Polymer Formation); Reaction Stereochemistry Ch. 9 Alkynes: An Introduction to Organic Synthesis Preparation of Alkynes; Addition Reactions of Alkynes (X2, HX, H2O, H2); Oxidative Cleavage; Alkyne Acidity and Alkylation; Introduction to Organic Synthesis Ch. 11 Reactions of Alkyl Halides: Nucleophilic Substitutions and Eliminations SN2, SN1, E2, E1, E1cB Reactions; Zaitsev’s Rule; Deuterium Isotope Effect Ch. 10 Organohalides Preparation of Alkyl Halides and Grignards; Radical and Allylic Halogenation; Organic Coupling Reactions, Redox in Organic Chemistry Ch. 17 Alcohols and Phenols Properties of Alcohols and Phenols; Preparation and Reactions of Alcohols; Reactions of Phenols Ch. 18 Ethers and Epoxides; Thiols and Sulfides Synthesis and Reactions of Ethers; Cyclic Ethers (Epoxides); Reactions of Epoxides: Crown Ethers; Thiols and Sulfides LABS --> Some experiments require more than one lab period to complete. Based on an instructor’s preference, availability of equipment/supplies or constraints within a given semester, this laboratory schedule is subject to change, including but not limited to, the addition or replacement of one or more of the above experiments with the following experiments: Addition of Bromine to E-Cinnamic Acid in Methylene Chloride Substitution Reactions of Alkyl Halides: Relative Rates Triphenylmethanol with Hydroiodic Acid 1. Check-in, Laboratory Safety, Practices and Waste Disposal. Simple Distillation. 2. Spectroscopy: Introduction to Infrared Spectroscopy. 3. Recrystallization, IR and Melting Point of benzoic acid. 4. Extraction of Organic Compounds from Natural Sources: Trimyristin from Nutmeg. 5. Paper Chromatography 6. Dehydration of Cyclohexanol. 7. Dimerization of 2-Methylpropene 8. Preparation of Diphenylacetylene Starting from Trans-Stilbene. 9. Preparation of Butyl Bromide/Preparation of t-Butyl Chloride (SN2/SN1). 10. Oxidation of Isoborneol to Camphor. 11. The Williamson Ether Synthesis: Preparation of Aryloxyacetic Acid from Cresol. Prerequisites: General Chemistry II Organic Synthesis Laboratory Practice of organic laboratory techniques. Three hours of laboratory per lab session, twice a week. Approved chemical safety goggles meeting whatever national standards. The purpose of this laboratory course is to introduce students to the techniques that organic chemists (as well as biochemists, physical chemists, etc.) use in their daily routines. After learning and understanding those techniques, students will apply their knowledge to new situations to understand synthesis reactions, molecular structure determination, and analysis of (un)known compounds. Organic chemistry laboratory is important for several reasons. It introduces students to many different laboratory practices and concepts that will be used in subsequent chemistry laboratory classes and in other laboratory situations in biology, pharmacy, and chemical engineering (just to name a few!). It is anticipated that by the completion of this course, students will be familiar with all of the following topics and techniques: Safety in the laboratory Interpreting and following scientific directions Keeping a proper lab notebook Names and proper usage of lab instruments Understanding of general properties of compounds (including solubility, miscibility, acid/base chemistry, etc.) Proper usage of glassware Isolation and purification techniques (including filtration, solvent removal, drying solutions, distillations, chromatography (thin-layer, column, and gas) and crystallization/recrystallization) Characterization techniques including spectroscopy and melting point determination Interpretation of scientific results including percent yield and recovery, melting point, boiling point, IR and NMR spectra, and Rf values Required Materials: A laboratory notebook with carbon(less) pages Approved safety goggles Lab coats Lab manual will be posted through Blackboard Typical text: C.F. Wilcox, M.F. Wilcox, "Experimental Organic Chemistry, A Small-Scale Approach", (3rd edition, 2010). Apart from use of software in lectures, students will use software to accompany experiments that provide detailed molecular/compound structure, target sites, functional groups, etc. etc. Such exhibits will accompany lab reports. Lectures --> Lecture sessions are designed to clarify the concepts covered in the lab, as well as give an overview of techniques that will be used in the lab. Attendance is expected: The labs are only 3 hours in duration, so these lectures will be where you learn everything that you’ll need. Lab exercises will be available on Blackboard for each week. Please be considerate of your fellow students during the lecture period. Disruptions of any kind will not be tolerated and may result in expulsion from the classroom. Laboratory --> You will be required to have appropriate clothing before being allowed to enter the lab. Pre-labs are due at the beginning of the lab, and results and postlabs are due at the beginning of the lab 1 week after completion of the experiment! You will be expected to adhere to all of the lab safety rules. You are all expected to do your part to maintain a clean lab environment as part of GLP (Good Lab Practices): All reagent and solvent bottles should be completely closed immediately after use; All spills and dribbles should be cleaned immediately; All glassware should be put away at the end of the lab, and walkways should be kept free of debris. The following is the distribution of possible points in the course: Library Searching Exercise Database Search Exercises (Spectroscopy and Chromatography) Lab Quizzes Reaction/Synthesis methods knowledge Appropriate choice of method Appropriate constituents and tools. Procedure/steps (summary and/or ordering) Stoichiometry problems Spectroscopy and/or Chromatography analysis/interpretation Applications and industries Multistep Reaction/Synthesis Labs Lab Cleanliness Pre-lab Submissions Lab Notebook and Reports Lab Final Day 1: Much resemblance to quizzes Day 2-3: Augmented with the following: Molecular modelling software exercises Two or Three Practicum Group Labs (open notes) Part A. Points deducted for incompetent questionnaire for safety procedures for respective lab Part B. 2-3 labs to be implemented with competent data recording and lab reports. YOUR LAB REPORT CONSISTS OF THREE (3) PARTS --> Part I - Prelab Report. A copy of your lab notebook pages containing the lab write-up and answers to any prelab questions. This is due at the start of each experiment. Part II - Results. A copy of your notebook pages containing observations noted during the lab experiment. Is due with Part III one week from the conclusion of the experiment. Part III - Postlab Report. A summary of results and answers to postlab questions. This can be written on separate loose-leaf paper. Is due with Part II one week from the conclusion of the experiment Course Outline: Week1 Check-in/Safety Video/ Safety Procedures and Regulations Fractional Distillation Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation, results and analysis Week 2 Measuring the Melting Points of Compounds and Mixtures Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Consider other physical and chemical properties, such as solubility and spectroscopic data, to confirm the identity of the unknown compound. Results and analysis Week 3 Purification by Recrystallization and Melting Point Measurement Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Consider other physical and chemical properties, such as solubility and spectroscopic data, to confirm the identity of the unknown compound. Results and analysis Week 4 Nucleophilic Substitution: Synthesis (SN1 Mechanism and SN2 Mechanism) Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Consider other physical and chemical properties, such as solubility and spectroscopic data, to confirm the identity of the unknown compound. Results and analysis Week 5 Oxidation of Alcohols (Primary, Secondary and Tertiary). Infrared Spectroscopy. Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Infrared Spectroscopy Results and analysis Week 6 Elimination Reaction (E1 Mechanism and E2 Mechanism) Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Consider other physical and chemical properties, such as solubility and spectroscopic data, to confirm the identity of the unknown compound. Results and analysis Week 7 Synthesis of Aspirin. Chromatography and/or Spectroscopy Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Chromatography and/or Spectroscopy Results and analysis Week 8 Solvent Extraction Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Consider other physical and chemical properties, such as solubility and spectroscopic data, to confirm the identity of the unknown compound. Results and analysis Week 9 Electrophilic Aromatic Substitution: Synthesis of o- and p-Nitrophenol. No distillation; extract product with ethyl acetate. Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Consider other physical and chemical properties, such as solubility and spectroscopic data, to confirm the identity of the unknown compound. Results and analysis Week 10 Separation and purification of o- and p-Nitrophenol by Liquid Chromatography. Use 100 mg sample, check by chromatography. Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Results and analysis Week 11 Aldol Condensation Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Consider other physical and chemical properties, such as solubility and spectroscopic data, to confirm the identity of the unknown compound. Results and analysis Week 12 Grignard Reaction: Synthesis of Phenylmagnesium Bromide. Week 1: Part 1. Add methyl benzoate and sustain the desiccator for next week. Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Consider other physical and chemical properties, such as solubility and spectroscopic data, to confirm the identity of the unknown compound. Results and analysis Week 13 HCl workup of previous week’s product. Synthesis of Triphenylmethanol and recrystallization of product. Purity check by melting point measurement. Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Consider other physical and chemical properties, such as solubility and spectroscopic data, to confirm the identity of the unknown compound. Results and analysis Week 14 -15 Wrapping up/cleaning things up. Final Exam. Prerequisite: Organic Chemistry I

Biochemistry: The study of biochemistry investigates the interplay between biological macromolecules such as proteins and nucleic acids, and low molecular weight metabolites (such as the products of glucose metabolism). In this course, you will apply your knowledge of intermolecular forces, thermodynamics (when a reaction occurs), chemical kinetics (how fast a reaction occurs), and chemical structure and functionality to understand how biological molecules (and life) work. COURSE GOALS AND OBJECTIVES (Our Roadmap!) -Be able to describe/identify the forces that direct/stabilize different levels of protein structure -Be able to predict how changes in amino acid (or nucleotide) sequence can affect macromolecular structure and function -Be able to explain how enzymes are able to affect reaction rate enhancement -Be able to articulate and apply what the enzyme parameters of KM, Vmax, kcat and kcat/KM tell us about an enzyme -Be able to describe the interactions of biomolecules both quantitatively and qualitatively (in many cases, including mechanistic details) -Be able to understand the flow of metabolic intermediates through a pathway and communicate information about metabolic pathways using diagrams -Be able to describe multiple experimental methods used in biochemistry, interpret data from these methods to form conclusions, and develop a testable hypothesis to answer a question -Be able to summarize and analyse primary literature and data, and apply gathered information to new situations -Increase problem solving skills such as: critical thinking, data analysis, graphical analysis -Increase process skills such as: communication of scientific concepts and experimental results, group dynamics and teamwork, management and self-assessment -Develop a community of active learners who are intentional about their educational choices Course Materials: Calculator Emphasis on reinforcing skills with software --> << VMD (with NAMS), GROMACS, VOTCA, Desmond, UCSF Chimera, Molsoft, CCPN, RedMD + RedMDStream >> << BLAST, Unipro UGENE, Bioclipse, Staden Package, Bioconductor >> << EMBOSS + JEMBOSS + Pise + wEMBOSS + EMBOSS-Explorer >> Typical Texts --> Nelson DL and MM Cox. Lehninger Principles of Biochemistry (5th edition). (“Lehninger”) Loertscher J and V Minderhout. Foundations of Biochemistry (3rd edition). (“FOBC”) Additional --> Blast protein databases, align protein sequences, build protein homology models, and evaluate the quality of these models Lab Manual example --> Lasseter, B. F. (2020). Biochemistry in the Lab: A Manual for Undergraduates. CRC Press Related to week 6: Edwards, P., Zhang, C., Zhang, B. et al. Smartphone based optical spectrometer for diffusive reflectance spectroscopic measurement of hemoglobin. Sci Rep 7, 12224 (2017). Course Overview --> You will frequently be given initial assignments to work on as an individual before class. These assignments must be ready at the start of class – your preparation will form part of your weekly participation grade. During our class meeting time, you will frequently function as a member of a Learning Team, developing and examining chemistry concepts as a unit. Your team effort and participation is part of your weekly participation grade. The team responses to a few Key Questions on each in-class activity will be evaluated for strength of concept and effective communication of the concept. The team will also strategize on ways to improve teamwork and team products. These responses will also form part of your weekly participation grade. Application exercises will be assigned for each activity. Together with problems from the text, they will form your weekly problem set that will be collected and graded for each individual. These homework problems and exercises are important to your success in the course. Actively working these homework problems is essential for your understanding of the material, as they bring your concept development full circle. The questions will be drawn from lectures, in-class activities, problem sets and discussions, as well as relevant primary literature that you may not have been previously assigned. The purpose of doing biochemistry is to gain experience in experimental methods that you’ll be reading about throughout the semester. Attendance on your scheduled lab day is expected. Software activities concerning biochemistry will accompany labs. Software activities concerning biochemistry will accompany labs as pre-lab development or post simulations. Grading --> Team Participation Problem Sets/Other Laboratory 2 Midterm Exams Final Exam Lecture Outline --> Week 1 Introduction to Biochemistry Week 2 Intermolecular forces and water. Amino acids and peptide bonds Week 3 Protein Folding Week 4 Working with proteins Week 5 Enzyme catalysis. Enzyme Kinetics Week 6 Enzyme inhibition. Hemoglobin Week 7 Exam 1; Carbohydrates Week 8 Glycobiology Week 9 Lipids and membranes. Transport across membranes Week 10 Signal transduction. Metabolism overview Week 11 Glycolysis. Glycolysis regulation and related pathways Week 12 Glycogen metabolism and gluconeogenesis. Citric Acid Cycle Week 13 Electron Transport Chain / Oxidative Phosphorylation; Exam 2 Week 14 Lipid metabolism. Nucleotides and nucleic acids Week 15 Nucleic acids structure and function Week 16 Final Exam Prereqs: General Biology I. Co-requisite or Prerequisite: Organic Chemistry I Cell Biology: The standard definition of a cell in most introductory biology texts includes the line that cells are “the fundamental building blocks of all organisms.” Because of this fact, trite though it may be, a detailed understanding of the fundamental processes of cellular function is critical to all specialties within biology, clinical or academic. Some of these processes, including for example the biochemical mechanisms underlying cellular energetics, are remarkably consistent from bacteria to human. Other cellular processes and structures vary from cell type to cell type or organism to organism, allowing for unique adaptations of cells and organisms to particular functions. For example, nerve cells have various properties allowing them to conduct electrical signals and therefore process information, while kidney cells are specialized for the secretion of waste, and red blood cells for the transport of oxygen and carbon dioxide. What are the differences in physiology from cell type to cell type determining these specific functions? During the first half of the semester we will focus primarily on the biochemical processes that underlie cellular function, with an emphasis on protein structure and function, ion transport mechanisms and energy metabolism. The second half of the semester will emphasize more the function of particular organelles, including cell membranes, intracellular compartments and the cytoskeleton, and the relevance of these structures on processes like cell signaling and mitosis. Throughout the course, we will emphasize how variability in these processes imbues different cell types with their unique functional abilities. We will also seek to understand the experimental evidence for the different facts and concepts we study: How do we KNOW that nerve cell signaling, for example, involves the release of neurotransmitters? Some of this experimental evidence will be explored in a hands-on way in the lab sections, some will be discussed during lecture, and some will be the subject of analysis in the reading of original scientific manuscripts. Finally, we will examine how malfunctions in the cellular processes we are studying underlie certain diseases. In particular, the final few lectures of the course will focus on the biology of cancer cells: how do changes in cellular processes allow cancer cells to proliferate and metastasize? What are some of the current clinical approaches to curing cancer by blocking or reversing these processes? Aspirations --> To understand fundamental concepts of cellular function. To understand, and be able to critically analyze, the scientific evidence underlying our current understanding of cellular processes. To develop skills, through lab experiments, in some of the specific methodologies used in the study of modern cell biology. To become skilled at formulating and testing hypotheses using these methods. To develop a preliminary ability to read and analyze the primary scientific literature: What are the major findings of a science paper? What evidence is presented to support these findings? Are there shortcomings, either in the methods used or the logic of the experiments, which might lead one to question the conclusions reached by the authors? To be able to put this knowledge into larger contexts of how disease states occur or how organisms function adaptively within their environments. Typical text: The World of the Cell, by Becker, Kleinsmith, and Hardin, 6th edition (2006), Pearson/Benjamin Cummings Class Requirements and Grading --> 1. Class Participation (10%) To include attendance, responses to questions I pose in class, participation in discussions, and simply raising your hand from time to time to ask questions or make a comment (something I DO expect you to do). 2. Quizzes (10%) Two short in-class quizzes during the first half of the course. 3. Homework/problem sets (5%) There won’t be many of these; I’ll assign them when we hit subjects that are especially involved to help you learn the material and to make sure everyone is on track. 4. Primary literature readings (10%) We will read two papers from the primary scientific literature during the second half of the course. In both cases there will be an in-class discussion of the paper and a “reading guide” set of short essay questions which will be graded. The first reading guide assignment will be due AFTER the in-class discussion; the second assignment will be due BEFORE the in-class discussion. 5. Laboratory reports (25%) The specifics of each week’s lab report will be discussed during lab section. Typically, each week’s lab report will be due the following Monday in lecture. 6. Mid-term exam (20%) TENTATIVE format to include an in-class component, a short oral component, and a take-home component. 7. Final exam (20%) LABS --> Lab instructions for each week will be handed out ahead of time, either distributed as hard copies in lecture or posted on the course Angel site (or both). You are responsible for reading the instructions before lab. Otherwise, labs tend to run late, you will have difficulty obtaining the necessary data and knowing what to do with it. Do not expect the instructor to go over every step of the lab procedure before you start. Labs will make great emphasis on strong, practical and constructive immersion into the following software to accompany hands-on activity: << VCell, TiQuant + TiConstruct + TISIM >> Such software provides strong quantitative/computational microscopic assessment of specimens (or whatever) at professional standards. Such provides better means of objectives and expectations towards hands-on labs. Each lab will be associated with an explicit lab report assignment (contained in the lab instructions), usually due in lecture the Monday following lab. Usually, you may either submit the report with your lab partner or independently. If a report is submitted jointly, both partners must have contributed equally, as per Honor Code responsibilities. Do NOT make the mistake of dashing off reports the night before in a single draft. These reports will collectively account for 25% of your course grade, so take them seriously. The lab is a potentially dangerous place and you are required to follow all instructions given by your lab instructor and presented in the lab instructions. Disregarding instructions, or coming to class late or unprepared, may result in grade penalties, in addition to being just plain dangerous for yourself and those around you. Note: students can apply stationary video recording of labs with assigned regulations (to be given). Course Topics: Chapter 1 -19, 24. Some topics will require at least one week of instruction. Labs --> Cell Culturing, Aseptic Technique Cell Culture: basic techniques, population curve Cell Counting and splitting plates Cell Staining Histology Electron microscope Cell Harvesting & Cell Lysis Fractionalization of cells Common method(s) will be implemented Discussion and logistics for immunomagnetc separation & magnetic beads Isolation of erythrocyte membrane proteins Analysis of erythrocyte membrane proteins Bradford Assay (also identifying advantages and disadvantages) SDS-PAGE Chloroplasts and the Hill reaction Prerequisites: General Biology I & II

Microbiology I Microbiology is an integral part of many different scientific studies, such as immunology, genetics, molecular biology, biochemistry, medicine, agriculture, ecology, industrial processes and many more. People working in these fields use microbiology in their daily procedures, although they aren't microbiologists. Because of the wide range of its applications, understanding the basics of microbiology is in many ways essential to our completeness as biologists, no matter what field we may pursue. Microorganisms (in the context of this course) are minute living things that are individually too small to be seen with the naked eye. The term includes bacteria, microscopic fungi (yeasts and molds), protozoans, microscopic algae, prions and viruses. Microorganisms can be associated with many diseases, infections and inconveniences such as AIDS, pimples, and spoiled food. However, the majority of microorganisms make vital contributions to the world's inhabitants. They maintain the balance of chemicals and living organisms in the global environment. For example, the algae and cyanobacteria found in the oceans and waters of the globe are the major source of oxygen for living things. In many places microorganisms are the basis for the food chain. They help to recycle chemical elements in the land and water. Microorganisms also have been used for commercial benefits. Cultured microorganisms can be used to synthesize products more cheaply than they can be manufactured by other means (biotechnology). Microorganisms have also been used to produce products that have "always" been a part of our lives, such as vinegar, wine, sauerkraut, pickles, beer, green olives, soy sauce, buttermilk bread, cheese, and yoghurt, to name a few. The purpose of this semester of Microbiology is to familiarize the student with those concepts that are basic to viruses and prokaryotic and eukaryotic cells. Lecture is the foundation of the course. Laboratories will not always coincide with the lecture topics, as the laboratories are designed to give the student the basic laboratory techniques necessary to identify microorganisms. The student is responsible for assignments (such as designated papers from the scientific literature) that add to the lecture and lab material. In order to enhance appreciation of the course, the student is encouraged to seek out related materials that are available, such as scientific journals, JoVE, etc.. There are five basic topics in this course - the general principles for microbial the growth, evolution and classification; descriptions of different prokaryotic, eukaryotic and other lifeforms and how they utilize these principles; the natural ecology of microorganisms; the human use of microorganisms; and how microorganisms function in disease. Section one covers the first topic, the second topic is covered by sections two and three, and the final three are covered in section four. Some aspects of the last two topics are woven throughout the course. In order to understand how microorganisms can live, one must know what the parameters for their existence are. In order to get a feel for the diversity and scope of the microbial world, one must have a feel for what kinds of organisms exist, and to understand the ecology, uses and dangers of microorganisms, one should have a general knowledge of the different organisms to be encountered. All of these things are useful in life, in order to make informed decisions, and to go on to professional or graduate school. Learning activities will include reading and evaluation scientific papers, learning basic Microbiological techniques, identifying unknown bacteria, answering questions in lecture and writing scientific papers. Learning Activities --> These will consist of lectures, laboratory demonstrations, laboratory work (including independent investigation to identify unknown organisms), reading assigned scientific papers, writing a final laboratory report and answering those questions that are asked in lecture and laboratory. Outside the formal lecture/ laboratory structure, the student is expected to read assignments in the text, as well as assigned papers from the scientific literature, and study the concepts presented in lecture, laboratory and in the text. Hopefully this mix of learning styles will create a deeper appreciation of Microbiology. Typical texts in Unison: Microbiology; Prescott, Harley and Klein, 6 ed. (LECTURE) Microbiology in Practice ed.6; Beishir (LAB MANUAL) Grading: 3 Exams 45% Labs 25% Final Exam 30% MATERIALS --> Standard Operating Procedure for Handling Laboratory Specimens (SOPFHLS) and so forth. All specimens will be handled using the "Standard precautions for blood and body fluids" recommended by public health (CDC) officials and government agencies. Practice will include: 1. Specimen brought into the MLT Laboratory will be carefully screened, in proper containers and labeled. 2. Proper protection will be used when processing specimen (lab coats, gloves and protective eye wear as appropriate). 3. Mechanical pipetting, use of safety engineering devices, and safe work practices at all times. 4. Decontamination of laboratory work surfaces at end of each exercise. Use bleach and/or phenol. 5. Decontamination or proper disposal of contaminated laboratory test materials. a. Blood and body fluids will be placed in biohazard bag in the trash. b. All needles, broken glass, and hemolets will be placed in a biohazardous sharps container and stored in the Prep Biohazard area for incineration and removal by commercial biohazard disposal company. c. All gauze, Kim wipes and disposable materials contaminated with blood and body fluids will be discarded in a biohazard bag and stored in the Prep Biohazard area for incineration and removal by commercial biohazard disposal company. 6. Decontamination of scientific equipment, i.e., electrodes, glassware, etc. 7. Hand washing after all laboratory procedures. 8. Accurate and proper recording and reporting of results. Reference: "Legal Implications of Universal Blood and Body Fluids Precautions", David L. Wing, Clinical Laboratory Science, Volume 1, No. 2, March/April 1988. " Needlestick Safety Act", OSHA Standards 2002 (or later version) 9. << www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi >> 10. A standard academic laboratory manual accompanied by the likes of the following << https://www.mountsinai.on.ca/education/staff-professionals/microbiology >> 11. Microbial, Viral and pathogen software (check Goody Bag post) will follow applicable and practical mathematical modelling of cultures and so forth w.r.t. to median, nutrition and other environmental factors. All such along with lab studies of cultures --> << Combase (Predictor and Modelling Toolbox) with MRV, USDA Pathogen Modeling Program, EPA Virulo >> << COPASI, Pathvisio + Cytoscape + KEGG >> << Micro-Manager Open Source Microscopy software with ImageJ, JoVE (video journals), UIUC-Virtual Microscope >> << Bioconductor >> LABORATORY EQUIPMENT --> Equipment: PPE-impervious lab coat, latex or nitrile gloves, closed toed leather shoes PERIODICALS--> 1. American Journal for Medical Technology 2. Laboratory Medicine 3. Medical Laboratory Observer (MLO) 4. Journal of Clinical Microbiology RESOURCE --> << www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi >> LABS --> The Laboratory is set up to familiarize the student with the techniques necessary to grow and identify microorganisms. The first quarter of the semester covers basic techniques of media preparation, staining and microscopy. The second quarter covers recognition and differentiation of microbial characteristics in culture. The next section is devoted to microbial identification based on metabolic differences. The student will then test his or her knowledge by using the above information to identify a mixture of two unknowns in the last section of the course. A six page research report of the unknown identification will be required, in formal scientific paper format (including bibliography), and will count for 20% of the total grade in the course. COURSE TOPICS --> SECTION ONE: The Basics of Microbial Existence and Detection Introduction – Chapter 1 Microscopy – Chapter 2 Prokaryotic Structure & Function – Chapter 3 Microbial Nutrition – Chapter 5 Microbial Growth – Chapter 6 Control of Microbes – Chapter 7 Taxonomy – Chapter 19 EXAM 1 SECTION TWO: The Bacteria Gram Negative Bacteria – Chapters 21 – 24, 20 EXAM 2: from taxonomy through the Archaea SECTION THREE: The Eukaryotes and Viruses Eukaryotic structure & Function – Chapter 4 Fungi – Chapter 25 Algae – Chapter 26 Protista – Chapter 27 Viruses – Chapter 16 Prokaryotic Viruses – Chapter 17 Eukaryotic Viruses – Chapter 18, 38 EXAM 3: from Eukaryotic Structure & Function through the viruses SECTION FOUR: Microbial Ecology; food, industrial and medical microbiology Symbiosis – Chapter 28 Aquatic Ecology – Chapter 29 Terrestrial Ecology – Chapter 30 Industrial Microbiology – Chapter 42 Food Microbiology – Chapter 41 Medical Microbiology – Chapter 34 – 37; 39 – 40 FINAL EXAM LABS TO BE DONE -- > Laboratory Safety, Microscopy, Aseptic Technique – Modules 4, 5, 6 Bacterial Cultures, Slide Preparation, Staining, Streaking – Modules 22-24 &12 Streaking, Pour Plates – Modules 7, 8, 9, 10, 12 Bacterial Characteristics – Modules 11, 12, 13, 25 Differential and Selective Media, IMViC Test – Modules 39, 40, 49, 50 Bacterial Identification – Modules 34, 37 Litmus Milk, Carbohydrate Fermentation, Hydrogen Sulfide, Agglutination Tests – Modules 34, 37 Further Tests – Modules 32, 35, 36, 38, 46 Identification of Unknowns – 56, all of the above Hašek J. (2006) Yeast Fluorescence Microscopy. In: Xiao W. (eds) Yeast Protocol. Methods in Molecular Biology, vol 313. Humana Press Prerequisites: General Biology I & II, General Chemistry I & Ii Microbiology II Applying microbiological techniques to study and identify unknown organisms and the use of molecular genetic techniques to study and manipulate microbes. Lecture material will provide the theory and background to the laboratory exercises done each week. The students will collect data from laboratory exercises and incorporate their methods and results into a research report that follows the format of research manuscript. STUDENT INTELLIGENCE --> Recognising how biochemical and genetic tests are used to identify unknown organisms. Comprehending how DNA sequencing can be used to identify microbes. Describing useful components of plasmid cloning and expression vectors. Learning the theory of PCR, how PCR primers are designed, and how to add desirable sequences to PCR products using primer modifications. Developing written communication skills by writing experimental results in manuscript form PRACTICAL SKILLS --> Develop the ability to store and maintain microbial cultures. Determine the appropriate tests to use for the identification of an unknown organism. Use genetic techniques to study and modify microbes. Clearly and concisely communicate research results. Use computer programs for bioinformatics analysis. MATERIALS --> Standard Operating Procedure for Handling Laboratory Specimens (SOPFHLS) and so forth. All specimens will be handled using the "Standard precautions for blood and body fluids" recommended by public health (CDC) officials and government agencies. Practice will include: 1. Specimen brought into the MLT Laboratory will be carefully screened, in proper containers and labeled. 2. Proper protection will be used when processing specimen (lab coats, gloves and protective eye wear as appropriate). 3. Mechanical pipetting, use of safety engineering devices, and safe work practices at all times. 4. Decontamination of laboratory work surfaces at end of each exercise. Use bleach and/or phenol. 5. Decontamination or proper disposal of contaminated laboratory test materials. a. Blood and body fluids will be placed in biohazard bag in the trash. b. All needles, broken glass, and hemolets will be placed in a biohazardous sharps container and stored in the Prep Biohazard area for incineration and removal by commercial biohazard disposal company. c. All gauze, Kim wipes and disposable materials contaminated with blood and body fluids will be discarded in a biohazard bag and stored in the Prep Biohazard area for incineration and removal by commercial biohazard disposal company. 6. Decontamination of scientific equipment, i.e., electrodes, glassware, etc. 7. Hand washing after all laboratory procedures. 8. Accurate and proper recording and reporting of results. Reference: "Legal Implications of Universal Blood and Body Fluids Precautions", David L. Wing, Clinical Laboratory Science, Volume 1, No. 2, March/April 1988. " Needlestick Safety Act", OSHA Standards 2002 (or later version) 9. << www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi >> 10. A standard academic laboratory manual accompanied by the likes of the following << https://www.mountsinai.on.ca/education/staff-professionals/microbiology >> 11. Microbial, Viral and pathogen software (check Goody Bag post) will follow applicable and practical mathematical modelling of cultures and so forth w.r.t. to median, nutrition and other environmental factors. All such along with lab studies of cultures --> << Combase (Predictor and Modelling Toolbox) with MRV, USDA Pathogen Modeling Program, EPA Virulo >> << COPASI, Pathvisio + Cytoscape + KEGG >> << Micro-Manager Open Source Microscopy software with ImageJ, JoVE (video journals), UIUC-Virtual Microscope >> << Bioconductor >> ASSESSMENT --> 3-4 Quizzes Labs (activity + lab reports) 3-4 Exams COURSE OUTLINE --> WEEK 1 Introduction to cloning Vector analysis; Computer programs; Start cultures Plasmid preps and DNA quantification WEEK 2 PCR and primer design; Primer design programs Using primer design programs WEEK 3 PCR theory; Preparing a PCR Set up PCR PCR gel electrophoresis WEEK 4 Discuss purification and quantification of DNA Purify PCR Quantify PCR; Discuss restriction enzymes and protocols WEEK 5 Restriction digestion set up (PCR and plasmid) Inactivate digests; Discuss ligation Purify digests, quantify, and perform ligation reactions WEEK 6 Discuss E. coli strains and transformation Transformation protocol E. coli transformation and plating WEEK 7 How to analyze and interpret culture results Set up colony PCR; start cultures Purify plasmids; Colony PCR and plasmid electrophoresis WEEK 8 Cryopreservation Start cultures for cryopreservation Cryopreserve cultures; Discuss conjugation protocol WEEK 9 Finalize conjugation protocol; start SM10 and E. ictaluri cultures Mix cultures, filter, and plate Resuspend conjugation, dilute, and plate WEEK 10 Analyze conjugation results and discuss analysis Set up colony PCR and start cultures Colony PCR electrophoresis; Plasmid preps; Cryopreserve WEEK 11 Project Introduction; Sampling General Techniques Refresher Choose colony of interest; Staining, motility, and other tests WEEK 12 Streak fresh cultures Start broth culture Cryopreserve; Genomic DNA purification WEEK 13 Quantify gDNA; discuss 16S PCR Set up 16S PCR Apr 28 PCR electrophoresis; PCR purification WEEK 14 Using biochemical analyses and identification systems Inoculate biochem media and Biolog Biochem and Biolog Interpretations WEEK 15 Discuss final analyses Repeat biochems or perform additional tests Interpret final tests Prerequisites: Microbiology I Genetic Engineering & Technology Course textbook: Molecular Biotechnology: principles and applications of recombinant DNA, by B.R. Glick and J.J. Pasternack Course Grade Constitution --> 3 - 6 Assignments 3 Exams Course Outline --> Week 1 Introduction-Genetic Engineering and a tour of Genome Space DNA/RNA Processing and Gene Expression (a review): Week 2 Basic Techniques of Molecular Biology Restriction Endonucleases, Vectors, Cloning Week 3 Library Screens PCR, Sequencing Week 4 Exam Review and Exam Week 5 Prokaryotic Gene Expression Eukaryotic Gene Expression Genetic Engineering in Plants I Week 6 Genetic Engineering in Plants II: Applications Genetic Engineering in Plants III: the Next Generation of Rice Week 7 Sequence Analysis, Genome Structure Comparative Genomics Week 8 Functional Genomics: Analysis of Gene Expression Modifying Gene Expression and Cellular Function Week 9 Exam review and Exam Week 10 OPV and the emergence of AIDS The Origin of AIDS, con’t; vaccine intro; Edible vaccines Vaccine targets: malaria and ebola Week 11 Human Gene therapy I Human Gene therapy II: examples Week 12 Genetic engineering in animals I: Cloning Genetic engineering in animals II: Knockouts and Knockins, Inducible Gene Targeting Week 13 Genetic engineering in animals III: examples Genetic engineering in animals IV: xeno transplantation part a Genetic engineering in animals IV: xeno transplantation part b Week 14 Ethics and Patent Law Week 15 Exam Review and Exam Prerequisites: Cell biology, General Chemistry II Molecular Biology I This Molecular Biology course is designed to give a good background in current Molecular Biology, which should allow for easy continuation to graduate or professional school courses. The major themes are Eukaryotic and Prokaryotic DNA replication, Chromosomal structure and function and Gene structure and function. Students will learn from current papers in the scientific literature, and will be expected to use concepts developed in the course in class, in the laboratory and in exams. Molecular Biology is fundamental to the study of all living things. It describes, in its most basic form, the mechanisms of how organisms live, reproduce and evolve. It is basic to much of modern Biology, no matter what the field of study. The purpose of this semester in Molecular Biology is to familiarize the student with those concepts that are basic to the functioning of prokaryotic and eukaryotic cells. Lecture is the foundation of the course. Laboratories will not always coincide with the lecture topics. The student is responsible for assignments that add to the lecture and lab material. The student is encouraged to seek out related materials that are available, such as scientific journals (e.g. Cell, Nature, Scientific American), newspapers, magazines and television programs (e.g. channels 12 and 52) that relate to course topics. Lecture notes will be published on the internet at my home page before the given lecture. There are three basic concepts in this course - the replication of DNA; the structure and function of chromosomes; and the structure and functioning of genes. They will be organized as indicated below. Students will reinforced with Molecular Biology laboratory techniques (DNA isolation and purification, recombinant DNA synthesis and cloning, gene detection, PCR and Southern and Western Blotting), which will be used to expand the student's appreciation and knowledge of the lecture material. The lectures cover Molecular Biology as a whole - the "central dogma" of Biology: DNA makes RNA which then makes protein. Out of this there arise three concepts - Eukaryotic and Prokaryotic DNA biosynthesis; Chromosomal structure and function (with associated proteins and functions); and Eukaryotic and Prokaryotic gene structure and function (mRNA, tRNA synthesis and function, including protein synthesis), and how they relate to basic biological and chemical concepts (such as the action of evolutionary processes on living things) learned in previous courses. In general, they should understand how our genomes function, including gene activation and deactivation, RNA synthesis and protein biosynthesis and be able to use this knowledge in their work and in the laboratory. Overall, emphasized and reemphasized in the course, and illustrated by specific examples and laboratory experiments, are the ways in which the above topics are interconnected, and factors used in one way are recycled to be used in another. This leads to interconnectiveness amongst the various cellular functions, and allows for signaling and controls between them. These principles should allow them to establish a firm connection between this course and other aspects of biology and give a foundation for future Molecular Biology courses and/or a good appreciation of concepts needed to make reasoned choices in their everyday lives. Typical Text: Watson et. al. Molecular Biology of the Gene ed. 5 Typical Laboratory Manual Text: Human Molecular Biology Laboratory Manual - S. Surzycki The professor's evaluation of student participation in lecture and laboratory can be used to benefit hard working students and possibly enhance their grade if they are in a borderline position. The laboratory grade is based mainly on the laboratory paper (normal scientific format, aprox. 8 - 10 pages, with a bibliography and internal referencing), as well as the instructor's assessment of the student's activity for the entire laboratory. Some laboratory based questions will appear on exams, especially including the final exam. Grading: Exams -15% of final grade (x 3 exams): 45% Laboratory -25% of final grade Final Exam -30% of final grade Emphasis in Software Immersion and Skills Enforcement --> There are various software that will serve well in this course that further encourages a modern and profession environment, extending beyond memory based studies. Will make emphasis with practically and constructively implementing software alongside labs. Likely, one particular software will not have all the qualities of interest, however, out of the following sets choosing a max of 2-3 in usage will be constructive << VMD (with NAMS), GROMACS, VOTCA, Desmond, UCSF Chimera, Molsoft, CCPN, RedMD + RedMDStream >> << BLAST, Unipro UGENE, Bioclipse, Staden Package, Bioconductor >> << EMBOSS + JEMBOSS + Pise + wEMBOSS + EMBOSS-Explorer >> Lab Outline --> Chapter 7 - Determination of Human Telomere Length (pages 164 - 195) All activities in chapter 7 must be done Chapter 8 - RT-PCR of Human Genes (pages 196 - 214) All activities in chapter 8 must be done Course Outline --> SECTION ONE: DNA replication, repair and recombination Chapters 1 – 11 SECTION TWO: Chromosome structure and function, chromatin, prokaryotic operon structure and function Chapters 7 & 16 SECTION THREE: The eukaryotic operon structure and function, gene clusters, genes in organelle Chapters 2, 3, 17 & 18 SECTION FOUR: Ribosomes, protein biosynthesis and transportation, eukaryotic and prokaryotic viruses, genetic engineering Chapters 14 & 16, 17, 13 LAB REPORT DUE & FINAL EXAM Prerequisites: Cell Biology, Organic Chemistry I

Molecular Biology II Molecular Biology is a wide term encompassing two often complementary fields of study: a) laboratory and computer-based tools that can be used to study gene and genome identity and function (“molecular tools”), and b) the underlying fundamental structure of DNA and RNA. In this class there will be about a 50:50 split between focus on molecular tools (techniques) on the one hand, and the structure and function of DNA and RNA on the other hand. Proteins are often the focus of Biochemistry classes. Molecular Biology stresses the application of advanced molecular tools in the lab, and during analysis of scientific data presented in primary literature, in addition to covering genetic topics in more detail than was done in previous classes. The major expectations of students are : • To be become familiar with molecular techniques. • Understand the use of these techniques in the discovery of DNA and RNA metabolism and function. • Become more proficient at reading and critiquing primary literature. • Become familiar with commonly used laboratory techniques in the lab during an allsemester long research project. • Emphasis is not on memorization of the details of the molecular machinery of the cell. Instead, it is on developing skills to apply the learned techniques to the understanding of scientific discovery (data interpretation), as well as to suggest ways to study the function of molecules (experimental design). Molecular research is impossible to conduct in set 4-hour increments once a week. Typical Textbook/Readings: • Burton Tropp: Molecular Biology, 4th edition, 2012 Parts of some chapters will be used in this book in lecture, and book will be a good resource for looking up details, reading ahead or after class. Emphasis in Software Immersion and Skills Enforcement --> There are various software that will serve well to this course that further encourages a modern and profession environment, extending beyond memory based studies. Will make emphasis with practically and constructively implementing software alongside labs. Likely, one particular software will not have all the qualities of interest, however, out of the following sets choosing a max of 2-3 in usage will be constructive << VMD (with NAMS), GROMACS, VOTCA, Desmond, UCSF Chimera, Molsoft, CCPN, RedMD + RedMDStream >> << BLAST, Unipro UGENE, Bioclipse, Staden Package, Bioconductor >> << EMBOSS + JEMBOSS + Pise + wEMBOSS + EMBOSS-Explorer >> Grading --> 2 Midterm exams (each 70 points) 140 points 5 Quizzes (4x10 points each, quiz 5 =20 points) 60 points 1 Research paper (lab write-up) 40 points Lecture participation 20 points Carefulness in lab and preparation for labs 20 points Lab prelabs/postlabs ~30 points 3 Paper discussion prep and participation (4x20 points + 2x10 points) 100 points LABS --> It’s important to keep a neat and bound notebook for the lab, but you do not need to buy an expensive lab notebook. At the end of the semester you will be required to turn in a research paper describing the work you did on the lab project and put it in context of a greater scientific question. Only one lab report/paper will be handed in for the semester. This report reflects multiple weeks of work. Therefore make sure to collect gel photos, instrument readings, microarray and RNA-seq data analyses, so that you have all the files you need for your final paper. While all class and lab assignments have to be written individually unless specified differently, the final lab report can be written collaboratively with your lab partner, or individually if you prefer. Preparation for labs: Labs in this class are very expensive and it is of great importance that you come prepared to lab. In the past I have simply relied on suggesting that everyone read the manual before lab. However, it only takes one un- or underprepared person to make an experiment fail – often for more students than just that one person. So I have decided that some form of enforcement of the preparation requirement is needed and have reverted to prelab assignments, which test your level of preparedness. In addition there is now a grade for “carefeulness in lab”. This grade is based on whether you are prepared for lab or excessively ask unnecessary questions that you could have answered yourself by reading the manual. I do encourage asking questions, but I also encourage self reliance and careful attention to detail. Not every experimental failure is due to operator error. Such failed experiments are common and will not influence your lab grade negatively. Again, software mentioned earlier will accompany labs. Outline Week 1: Nucleic Acid Structure, Genome Organisation Week 2: RNA techniques (hybridization, reporters) RNA techniques (qPCR) DNA sequencing methods (Sanger) DNA sequencing methods (whole genome approach) Lab1: Microarray analysis - RNA Extraction Week 3: QUIZ 1: RNA techniques DNA sequencing methods (whole genome approach) Paper Discussion 1 Lab1: Microarray analysis c - DNA production Week 4: Gene mapping, map based cloning Human genome variation, the concept of “race” Lab1: Microarray analysis - Slide hybridization Week 5 Paper Discussion 2 - Human genome variation DNA Damage Quiz 3 (mapping/cloning) Lab1: Microarray analysis Statistics of microarray analysis Slide analysis: first part in lab. Finish slide analysis/statistics on your own time after all slides are pre-analyzed after [whenever] Week 6: DNA repair, Technique: EMSA (for paper 1) Paper Discussion 3 (DNA repair) Lab 2: RNA-seq analysis - Computer workshop using iPlant tools (or by software provided) Week 7: Recombination Lab 2: RNA-seq analysis - Analysis of RNA-seq data from week 1, and comparison with array data Week 8: Transposons Paper Discussion 4 (Recombination) Lab 3: Genetic marker analysis Sequence analysis using Genome Browser Primer design CAPS search Week 9: Eukaryotic transcriptional regulation Lab 3: Genetic marker analysis - DNA extraction, PCR set up Week 10: Epigenetics (technique: Immunoprecipitation) Paper Discussion 5 (Epigenetics ) Lab 3: Genetic marker analysis CAPS digest gel analysis (on your own) Lab 4: RNAi cloning - PCR of insert Week 11: QUIZ 4: The transcription unit RNAi Lab 4: RNAi cloning PCR clean-up and cloning reaction Transformation (on your own) Week 12: Paper Discussion 6 (RNAi) Lab 4: RNAi cloning - Finish up from week 11 Week 13: Splicing Agrobacterium and gene transformation Lab 4: RNAi cloning Colony PCR of cloned insert Glycerol stocks and sequencing of positive clones Week 14: Agrobacterium and gene transformation QUIZ 5: (molecular techniques) Lab 4: RNAi cloning Finish up from week 13 Final Exam Lab report due Prerequisites: Genetic Engineering & Technology, Molecular Biology I Biotechnology Laboratory: This course covers the basics and of laboratory and analytical techniques that are used in biomedical research and the biotechnology industry. The techniques are in the following areas: (1) biochemistry of bacterial recombinant proteins, (2) mammalian cell culture, (3) molecular and cell biology, and (4) mass spectrometry. This is a laboratory course and serves as a pre-requisite for Advanced Biotechnology Laboratory. Specific topics include: general laboratory safety, record keeping, preparation of research reports, manipulation of bacteria, protein overexpression and purification, enzyme assays, highthroughput techniques, high performance liquid chromatography (HPLC) and mass spectrometry, mammalian cell culture, Western blotting, protein-protein interactions, reverse transcription-quantitative polymerase chain reaction (RT-qPCR), and assays for gene expression. Learning Objectives: -Acquire basic knowledge in protein biochemistry and bacterial molecular biology and experimentation with common equipment in a laboratory environment. -Gain basic knowledge in the use of mass spectrometry (MS), high performance liquid chromatography (HPLC), and automation in a laboratory environment. -Gain basic knowledge in mammalian cell culture and mammalian molecular and cell biology experimentation with necessary equipment in a laboratory environment. Prototypical Textbook: Basic Laboratory Methods for Biotechnology (Seidman & Moore) and additional materials. ACCOMPANIED BY LAB MANUAL(S). Assessment --> Problem Sets 10% 3 Lab Quizzes 15% Labs 45% 2 Lab Exams: mid-term (15%) and final (15%). Problem sets (25%): two problem sets will be given and are due at midnight given dates at midnight, respectively. Answers to problem sets are written concisely and clearly. Group Presentations for (15%): each student will give a 15-20 min. Oral presentation based on published articles. Course Outline: WEEK 1 Overview of modern biotechnology successes Basic experimental facets (basic instruments, buffers/solutions) I WEEK 2 Basic experimental facets (basic instruments, buffers/solutions) II Mammalian cell culture: equipment, starting cell culture, culturing and freezing cells WEEK 3 Molecular cloning: Restriction enzymes, plasmids and intro to cDNA and genomic libraries Detecting nucleic acids: agarose gel electrophoresis, PCR and qPCR, Southern/Northern blotting WEEK 4 Studying proteins (I): protein preparation, fractionation, SDSPAGE/Western blotting Studying proteins (II): protein engineering - plasmids and epitope tags and site-directed mutagenesis WEEK 5 Studying protein (III): detecting protein subcellular localization, immunofluorescence microscopy Transient transfection: endogenous vs. exogenous, principle and purpose WEEK 6 Studying protein-protein and protein-chromatin interactions: coimmunoprecipitation, GST pulldown and ChIP assays Reporter assays and qRT-PCR: studying transcription factors, protein function and drug screening WEEK 7 Knockout/knockin technologies Case study: Studying nuclear hormone receptors WEEK 8 In-class literature presentation (for ½ the group) Mid-term exam WEEK 9 Protein quantification and purity analysis WEEK 10 Protein expression in E. coli Purification of proteins by affinity tags and standard methods WEEK 11 Activity assay development Example of activity assay: β-lactamase WEEK 12 Biophysical characterization of protein-ligand interactions Fundamental aspects of mass spectrometry WEEK 13 Examples of analysis of mass spectrometry WEEK 14 Standard Operating Procedures (SOP) and record keeping in academia and industry Statistical analysis of data WEEK 15 How to prepare research reports In-class literature presentation: for other ½ of the group Prerequisites: Genetic Engineering & Technology, Molecular Biology I Advanced Biotechnology Laboratory: This course provides advance extensive hands-on laboratory experience in bacterial recombinant protein biochemistry, mammalian cell culture, molecular and cell biology, and mass spectrometry. Specific topics include: General laboratory safety, good laboratory practices (GLP), standard operating procedures (SOPs), buffers, media, and other reagent preparation, sterile technique, manipulation of bacterial and mammalian cells, mammalian cell culture, work with DNA and RNA, polymerase chain reaction (PCR) techniques including quantitative reverse transcription (RT-qPCR) and molecular cloning, protein overexpression and purification, assays (enzyme, stability, and reporter), highthroughput techniques, transfection, immunoprecipitation, immunofluorescence, DNA and protein gel electrophoresis, high performance liquid chromatography (HPLC), and mass spectrometry. Learning Objectives: -Acquire familiarity with and good laboratory practices (GLP), including use of standard operating procedures (SOPs). -Gain experience in protein biochemistry and bacterial molecular biology experimentation, including the necessary equipment in a laboratory environment. -Gain experience in mammalian cell culture and mammalian molecular and cell biology experimentation including the necessary equipment in a laboratory environment. -Gain experience in the use of mass spectrometry (MS), high performance liquid chromatography (HPLC), and automation in a laboratory environment. -Collaborate with peer scientists in a laboratory environment. -Prepare laboratory reports with an emphasis on procedures relevant to an industrial setting. This is a Monday to Friday laboratory course for 3 hours per day. Prototypical text: Basic Laboratory Methods for Biotechnology (Seidman and Moore) Required materials including laboratory protocols and standard operating procedures (SOPs) will be procured. There will be 2 exams: a lab practical exam and a written exam. The lab practical exam will be administered during the last week of classes in the laboratory space. The written exam will be administered during finals week. Laboratory notebook 30% Laboratory reports 30% Laboratory practical exam 30% Written final exam 10% Course Outline: PREMATURE FORMALITIES Biosafety training, autoclaving, sterile technique Calculations for buffers, solutions, and media Buffers, solutions, and media; autoclaving PROKARYOTIC TECHNIQUES -Nucleic acids and bacterial cell manipulation DNA quantification and polymerase chain reaction (PCR) Transformation and overnight cultures Plasmid preparation, sequencing, and restriction digestion DNA gel electrophoresis Data analysis -Recombinant protein expression in bacteria Sequence analysis; media preparation Transformation Culturing and overexpression Culturing and overexpression Spin down and collect cells -Protein purification Solution preparation Protein purification Size exclusion chromatography Size exclusion chromatography Protein gel electrophoresis and quantitation -Enzyme and stability assays Ultraviolet-visible (UV-vis) spectrophotometry assays UV-vis spectrophotometry assays Thermal shift assays Thermal shift assays Data analysis -Enzyme Assays 96-well plate assay preparation 96-well plate assay Data analysis Data analysis Data analysis and clean-up EUKARYOTIC TECHNIQUES -Maintenance of mammalian cells Making growth medium & thawing cells Making growth medium Splitting cells Making cell stocks Splitting cells -Transient transfection, immunoprecipitation, Western blotting Splitting cells, transient transfection Harvest cells & Immunoprecipitation Splitting cells, SDS-PAGE Western blotting Splitting cells -Transient transfection, immunostaining, immunofluorescence microscopy Split and seed cells Transient transfection Split cells, Immunostaining Imaging Split cells -Transient reporter assays Split cells, transient transfection Change media & add ligands Split and harvest cells & reporter assay Data analysis Split cells -Isolation of total RNA & RT-qPCR Treat cells with ligands Extract RNA from mammalian cells Reverse transcription (RT) of RNA to generate cDNA Quantitative real-time PCR (qPCR) Data analysis and clean-up MASS SPECTROMETRY -MS basics and familiarization Familiarization with mass spectrometry software Familiarization with high performance liquid chromatography (HPLC) software Tuning, standards, and optimization of direct infusion HPLC setup and operation: tuning, standards, and optimization HPLC operation -MS Assays Assays and HPLC/MS sample prep HPLC/MS runs HPLC/MS runs Data analysis Data analysis and clean-up -Wrap-up: Laboratory practical exam week Review No class; finish laboratory notebooks and laboratory reports Laboratory practical exam, part 1 Laboratory practical exam, part 2 -Last Day of Classes and Finals Week End-of-class clean-up and check-out; laboratory notebooks due Final written exam Prerequisite or Co-requisite: Techniques in Biotechnology

Environmental Microbiology: Course is highly dependent on knowledge, experience and from Microbiology I & II. Course will not be closely repetitive as prerequisite, rather, course concerns the development of competency, accuracy and efficiency for microbial observation, proper identification and removal. Apart from prerequisites reading and pre-study will be critical towards successful and efficient completion of lab obligations; outlines and other preparation documentation for a respective lab will be provided 5 to 7 days before day of respective lab administration. Instructor likely to provide a 15 – 30 minute synopsis for lab to done on day of relevance. Texts: TBA MATERIALS --> Standard Operating Procedure for Handling Laboratory Specimens (SOPFHLS) and so forth. All specimens will be handled using the "Standard precautions for blood and body fluids" recommended by public health (CDC) officials and government agencies. Practice will include: 1. Specimen brought into the MLT Laboratory will be carefully screened, in proper containers and labeled. 2. Proper protection will be used when processing specimen (lab coats, gloves and protective eye wear as appropriate). 3. Mechanical pipetting, use of safety engineering devices, and safe work practices at all times. 4. Decontamination of laboratory work surfaces at end of each exercise. Use bleach and/or phenol. 5. Decontamination or proper disposal of contaminated laboratory test materials. a. Blood and body fluids will be placed in biohazard bag in the trash. b. All needles, broken glass, and hemolets will be placed in a biohazardous sharps container and stored in the Prep Biohazard area for incineration and removal by commercial biohazard disposal company. c. All gauze, Kim wipes and disposable materials contaminated with blood and body fluids will be discarded in a biohazard bag and stored in the Prep Biohazard area for incineration and removal by commercial biohazard disposal company. 6. Decontamination of scientific equipment, i.e., electrodes, glassware, etc. 7. Hand washing after all laboratory procedures. 8. Accurate and proper recording and reporting of results. Reference: "Legal Implications of Universal Blood and Body Fluids Precautions", David L. Wing, Clinical Laboratory Science, Volume 1, No. 2, March/April 1988. " Needlestick Safety Act", OSHA Standards 2002 (or later version) 9. A standard academic laboratory manual accompanied by the likes of the following << https://www.mountsinai.on.ca/education/staff-professionals/microbiology >> 10. << www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi >> 11. Microbial, Viral and pathogen software (check Goody Bag post) will follow applicable and practical mathematical modelling of cultures and so forth w.r.t. to median, nutrition and other environmental factors. All such along with lab studies of cultures --> << Combase (Predictor and Modelling Toolbox) with MRV, USDA Pathogen Modeling Program, EPA Virulo >> << COPASI, Pathvisio + Cytoscape + KEGG >> << Micro-Manager Open Source Microscopy software with ImageJ, JoVE (video journals), UIUC-Virtual Microscope >> << Bioconductor >> Grade --> Attendance & Conduct 30% Lab Reports 30% Midterm 20% Final 20% Poor conduct in course and lab can warrant 69% percent of total grade for the course being forfeited. There are the conventional practices-- Observation & Removal Activities 1. Detection --Broth Culture, Quantal (“Most Probable Number”) Methods: Multiple Fermentation Tube (MFT) and Defined Substrate Methods and the Compartment Bag Test (CBT) --Enumerative (Colony Count) Methods: Membrane Filtration, Pour Plates and Spread Plates 2. Quantification --Quantification of Somatic and Male-specific Coliphages in Water and Wastewater 3. Microbial Survival in the Environment 4. Microbial Removals by Physical-Chemical Water Treatment Processes 5. Microbial Removals by Molecular Methods 6. Microbial Removal by Disinfection Processes, Chlorine and UV 7. Possible cases of excess, inappropriate or irresponsible implementation of removal methods, and the hazardous consequences. Note: (1), (2) and possibly (3) concern identification of target microorganisms that may vary from two or higher. Concerning topics (A) through (I) below there will be determination on how and when (1) through (3) are relevant, with the logistics, followed by experimentation procedures to confirm such. If (1) through (3) doesn’t serve appropriately then to determine which methods provide resolutions and orchestration of such lab activity; exams likely will demand such, which also may or may not depend on microorganism considered --> A. Bacterial Counts B. Water Content of Samples C. Contact Slide Assay D. Dehydrogenase Activity of Soils E. Nitrification and Denitrification F. Microbial Examination of Water G. Bacteriological Examination of Water H. Defined Substrate Technology I. Amplify 16S rRNA gene of isolates, verify via gel electrophoresis, and sequence J Biodegradation of Phenol Compounds Note: in lab reports sources of specimen must be identified and dated. Students must provide information on possible illnesses, defects or diseases related to a respective identified microorganism from respected sources and/or acquired intelligence from studies; incorporates describing the environmental parameter settings and vectors to trigger such. All such may also be asked on exams. An exam will not have questions from labs not given nor returned; all lab reports have deadlines regardless of whether students turn in lab reports or not. Each day a lab report is late warrants 5% reduction in respective lab report scoring. Prerequisites: Microbiology I & II Clinical Microbiology: The general characteristics of bacteria, protozoa, yeasts, molds, and viruses are used to understand the role of microorganisms in human health and disease. The interactions between the host and the microorganisms are emphasized as well as the physical and chemical methods of control. To develop procedural skills in Clinical Microbiology along with the thinking Processes that relate the following factors to each other --> Patient characteristics Types of infections Specimen requirements Microscopic examinations Culture media: growth characteristics and amounts Specific organisms and their identification techniques. Treatment and procedures relating to that treatment. Such 8 subjects that characterise procedural skills and thinking process to be subjugated by the following principles or guidelines--> Apply principles of safety, quality assurance and quality control in Clinical Microbiology Evaluate specimen acceptability. Describe morphology and physiology of microbes Identify and classify microorganisms Demonstrate sterile technique Perform and interpret antimicrobial susceptibility testing Select additional procedures based on preliminary results Correlate test results with patient condition(s) COURSE LITERATURE --> Typical Text: Textbook of Diagnostic Microbiology, 4th edition, Mahon C, Lehman D, Manuselis G Additional Texts/Readings: Laboratory Diagnosis of Infectious Diseases, Engelkirk P, Engelkirk,J Diagnostic Microbiology 12th edition, Forbes B, Sahm D, Weissfield A. Essentials of Diagnostic Microbiology, Shimeld, Lisa A. MATERIALS --> Standard Operating Procedure for Handling Laboratory Specimens (SOPFHLS) and so forth. All specimens will be handled using the "Standard precautions for blood and body fluids" recommended by public health (CDC) officials and government agencies. Practice will include: 1. Specimen brought into the MLT Laboratory will be carefully screened, in proper containers and labeled. 2. Proper protection will be used when processing specimen (lab coats, gloves and protective eye wear as appropriate). 3. Mechanical pipetting, use of safety engineering devices, and safe work practices at all times. 4. Decontamination of laboratory work surfaces at end of each exercise. Use bleach and/or phenol. 5. Decontamination or proper disposal of contaminated laboratory test materials. a. Blood and body fluids will be placed in biohazard bag in the trash. b. All needles, broken glass, and hemolets will be placed in a biohazardous sharps container and stored in the Prep Biohazard area for incineration and removal by commercial biohazard disposal company. c. All gauze, Kim wipes and disposable materials contaminated with blood and body fluids will be discarded in a biohazard bag and stored in the Prep Biohazard area for incineration and removal by commercial biohazard disposal company. 6. Decontamination of scientific equipment, i.e., electrodes, glassware, etc. 7. Hand washing after all laboratory procedures. 8. Accurate and proper recording and reporting of results. Reference: "Legal Implications of Universal Blood and Body Fluids Precautions", David L. Wing, Clinical Laboratory Science, Volume 1, No. 2, March/April 1988. " Needlestick Safety Act", OSHA Standards 2002 (or later version) 9. << www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi >> 10. A standard academic laboratory manual accompanied by the likes of the following << https://www.mountsinai.on.ca/education/staff-professionals/microbiology >> 11. Microbial, Viral and pathogen software (check Goody Bag post) will follow applicable and practical mathematical modelling of cultures and so forth w.r.t. to median, nutrition and other environmental factors. All such along with lab studies of cultures --> << Combase (Predictor and Modelling Toolbox) with MRV, USDA Pathogen Modeling Program, EPA Virulo >> << COPASI, Pathvisio + Cytoscape + KEGG >> << Micro-Manager Open Source Microscopy software with ImageJ, JoVE (video journals), UIUC-Virtual Microscope >> << Bioconductor >> 12. Lab attire and hygiene regulations In the laboratory, our first labs will address the basic use of the microscope, method of aseptic technique, how to perform basic staining procedures and how these common stains should appear under the microscope. This will familiarize students with several key stains and bacterial types. Students will also participate in the production of media to learn the associated math, contribute to the workload, and better understand the relationship between microbial growth and how media components that can enhance growth, select against, or differentiate different microbes Each student will perform a series of biochemical tests on an unknown bacterial sample to determine its identity. This demonstrates how microbes are characterized by their phenotypic characteristics and relates to how microbiology labs determine the causative agents in infectious disease clinical situations. Students will then work in pairs to develop a food microbiology hypothesis and design a guided experiment using serial dilution and plating methods to test their predictions with control and test food samples. To learn about normal and potentially pathogenic biota of the body, students will perform and analyse a series of experiments on their personal samples from five body sites. To study microbial control, students will test antiseptics, disinfectants and antibiotics for their effectiveness against common or personal microbial strains. Several experiments will also address the effectiveness of handwashing and alcohol-based hand sanitizing products. Mycology and parasitology will be introduced with prepared slides. Students will learn about the appearance and ratios of white blood cells by clinical differential white blood cell count methods on their own blood samples (or of prepared slides if preferred). There will be various types of microbes. Failure to observe safety rules as described above or as instructed will result in a lower grade and possible temporary or permanent expulsion from the laboratory. An unexcused lab without made-up work will result in 10% loss of laboratory points (40 points). An excused lab with the work made-up will result in a 5% loss of laboratory points. An excused lab without made-up work will also result in a 5% loss of laboratory points. Work may not be made-up without consultation with your instructor (you may not just simply come in on your own time unannounced or unplanned). Unknown Report = 60 points --> 1.You will be issued or able to select a clinically, food science, or environmentally relevant sample as an unknown. 2. You will perform staining and biochemical tests on the sample as a class. This will allow you to learn the necessary techniques and to generate data for your unknown sample. 3. A key of in-house lab test results for all possible unknowns will be provided and the creation of diagnostic keys and flow charts will be discussed. You will then devise a diagnostic key or flow chart for your unknown analysis. 4. The unknown report should consist of: a. Data chart: The chart of the results and interpretations of colony morphology, cell staining, biochemical, and oxygen requirements of the unknown. b. Flow chart: The chart should be followed by your diagnostic flow chart and the resulting determination of the unknown organism. c. Paragraph one: The analysis of the likelihood of the organism being correctly identified should then be discussed in paragraph format. This paragraph may also include mention of any difficulty in test results or interpretation analysis that could affect determination of the unknown. d. Paragraph two: Finally, you should look up the unknown in your lecture book or online. Discuss what clinical body site environmental site from which your unknown could have been isolated. If clinically important, discuss issues it could present for a patient. If an environmental or food microbe, discuss applications it may have. e. Resources: List any references used for the previous paragraph in a standard bibliography format. This reference list does not need to be on a separate page. 5. While exact identification is required for full credit, substantial partial credit will be awarded for correct interpretation of results and consistent analysis. Research Project = 40 points --> 1. This is a separate project from the Unknown Report. 2. These projects are to be designed, performed and analysed by pairs of students. The write-ups are to be done by each student independently. 3. The goal of this project is to test a hypothesis of personal interest. You and a partner will design a project to explore the issues of food poisoning and food intoxication and to practice hypotheses, predictions, sample dilutions, sample plating, scientific analysis and presentation of data. 4. Pairs of students are to create a hypothesis about the level of microorganisms in two different food samples that can be obtained or created from home. Next, predictions that can be tested should be made and a methods protocol drafted to be used in the lab set up. 5. The experiment should then be performed, and data collected. We will do this as a class together, but pairs of students will be working on different samples. Data should be analysed, and bacterial cells/ml or g of sample results determined for each concentration tested. Conclusions and further analysis of data should be considered. 6. The write-up for the research project should include an abstract and table of data collected. An entire paper is not necessary (and will result in a loss of points). An abstract is what scientists read to determine if they want/need to read a research paper any further. It is generally one page long only, but contains all of the key elements. It should contain the essential “nuts & bolts” of what was done, why it was done, how it was done, and what was found. Your abstract should be about 1 - 1.5 pages double-spaced in paragraph format and should address the following: a. What were you trying to test and why? b. What was your hypothesis? c. What were your predictions about the two different foods? d. How did you generally go about testing the food (hint, this should include the purpose of serial dilutions and not include a detailed about of every dilution you made)? e. Why do you want to calculate cells/ml or g from plates with ideally 25 – 250 colonies? f. What were your results (in cells/ml or g) and how did they compare to each other? g. What were your conclusions from your experiment? Did they support your hypothesis? h. What suggestions or modifications would you employ if you were to repeat the experiment? i. Will you change any food-related habits because of your results, or would you recommend behavioural changes to others? 7. A data table of all data collection should also be concluded. This explains how you generated final numbers for your abstract. 8. The complete assignment is due as listed on the laboratory schedule and should be typed up, printed out, and stapled to hand in. Figures can be done within the computer program used to create the document, or they may be taped into the document. Medical microbiology clinical culture lab reports = 50 points (10 points each) --> 1. These reports will be based on data and analysis on samples that you collect and process in lab. They should also provide insight into write-ups for clinical samples that might be analysed in a medical microbiology lab. They are designed to help you practice documentation of data and interpretation of results. 2. Lab reports to be filled out will be issued for the following systems: Bacteria of the Skin, Organisms of the Mouth, Bacteria of the Respiratory Tract, Bacteria of the Gastrointestinal Tract, and Bacteria of the Urogenital Tract. Academic well-being will be determined by the following --> Strictly enforced laboratory dress code Safe Laboratory behaviour and policies Laboratory safety devices Laboratory disposal Laboratory spills and accidents regulations and policies Academic Policies Laboratory attendance and participation policies Laboratory assignment policies Laboratory quiz and practical policies Prerequisites: Microbiology I & II Bacteriology: Did you know that without microorganisms, other life forms would not be possible? Did you know your body contains more bacterial cells than human cells? Did you know that one tablespoon of soil contains more microbes than people who have ever lived? Microorganisms are amazing! They were the first living cells on the planet and continue to be the most successful, living in every possible niche (including environments of pH 2 and temperatures over 100 degrees celcius) and utilizing every possible food source (even oil and plastic). During this course we will study the structure, physiology, and ecology of bacteria, viruses, protists, and fungi with an emphasis on bacteria. The course will specifically highlight areas of interaction between microbes and humans. We will gain experience with microbes in the laboratory as well. You will learn proper handling and identification techniques to help you complete longer term research projects. By the end of this course you will be able to: Remember basic taxonomic groups and key microorganisms in terrestrial, aquatic, and human environments. Connect microbe physiology to microbe ecology. Identify interactions between microbes and other living organisms. Culture, stain, identify and investigate microbes using aseptic techniques. Design a complete research project that incorporates both quantification and identification. Value the role of microbes in shaping the environment and human society. LABORATORY EQUIPMENT: Equipment: PPE-impervious lab coat, latex or nitrile gloves, closed toed leather shoes COURSE REQUIREMENTS: 1. Attend and complete all laboratory sessions. 2. Practice universal safety precautions during laboratory sessions. 3. Comply with program attendance code. 4. Complete assignments in a professional manner. 5. Complete all tests and exams given during the course in the allotted time and designated dates. COURSE GRADING: 3-4 Exams Lab Activity Lab Quizzes Lab Reports/Unknown Id/Skills Tests Lab Practicals There will be five (5) case studies presented during the course. They will presented in the “dropbox". Due dates will be assigned. Each case study has questions accompanying it that need to be answered correctly. Each case study will be worth 5 points. EXAMS --> There will be three mini-exams during the term. Each exam will be worth 40-50 points. The exams will consist of several short answer questions and one or two case studies to be analysed. LABORATORY-> We will spend the first few days learning essential skills for collecting, culturing, and analyzing bacteria from a variety of environments. You will complete two lab practicals to assess your knowledge of this information. The remainder of the semester will consist of three large projects: identifying three bacteria from a provided mix using traditional methods, identifying soil bacteria using DNA sequencing, and the completion of a research project of your own design. There will be opportunity to work with microscopic fungi and viruses, but the labs will emphasize bacterial cultures. Your attendance is expected at every class. You are responsible for any notes, announcements, or assignments that are missed. You are expected to read the assigned pages before class and be prepared to participate in class discussions. Late assignments will be accepted with a 10% penalty per class day late. PHASE 1 LABORATORY -Lab Policies; Microscope Use; Aseptic Technique; Cellular Morphology; Media Preparation; Simple Stain -Pure Culture Techniques; Colonial Morphology; Gram stain; Endospore Stain; Capsule Stain; Fungi and Protists -Oxygen Preference; Osmotic Pressure; Selective and Differential media; Antiseptics and Disinfectants; Disk Diffusion assay PHASE 2 LABORATORY -MViC; Sugar Fermentation; Sulfur Reduction; Oxidase; Catalase; Start Soil Project – plating dilution series -Freshwater microbes/Liquid Filtration; Food microbes/Standard Plate Count -Lab Practical I (7 days); Culture soil colonies on slants -Assign Bergey’s organism -DNA isolation and PCR from soil slants PHASE 3 LABORATORY -Bergey’s organism due; Receive unknowns/streak plate; Run gel of PCR results/Send for sequencing -Gram stain and slant unknowns; Continue research project -Inoculate unknowns on test media; ELISA test and epidemiology; Plaque assay; Kirby-Bauer antibiotic sensitivity test; Snyder assay; Hemolysin assay -Continue research project PHASE 4 LABORATORY -Lab practical II (7 days); Analyse DNA sequencing results -Continue research project; Finish unknown project; Finish soil microbe project -Soil project due LABORATORY QUIZZES (4) --> These quizzes will be small laboratory practicals where students will have to interpret test results that will be provided for them. Questions will be placed on index cards or printed sheet and the student will answer each question on an answer sheet. GRAM STAIN SKILLS TESTS (3) --> There will be 3 gram stain skill tests throughout the semester. The student will be graded on proper staining of the slide, interpretation and microscope focusing. ISOLATION SKILLS TESTS (3) --> There will be 3 isolation skill tests throughout the semester. The student will be graded on his/her ability to streak a colony on media using the proper technique to obtain isolated colonies. UNKNOWNS AND CLINICAL UNKNOWNS (2) --> May be adjusted based on organism availability and time. These unknowns will be simulated clinical samples in which the student has to correctly identify the organism using the correct battery of tests and submit the result on the unknown laboratory sheet provided. I. Introduction to Medical Bacteriology Review A. Classification of Medically Important Bacteria B. Steps Involved in Laboratory Diagnoses of Bacterial Infections C. Presumptive Vs Definitive Identification D. Laboratory Procedures Used in Diagnosing Bacterial Infections i. Culture Media ii. Gathering Information About an Organisms Phenotype MATERIALS --> Standard Operating Procedure for Handling Laboratory Specimens (SOPFHLS) and so forth. All specimens will be handled using the "Standard precautions for blood and body fluids" recommended by public health (CDC) officials and government agencies. Practice will include: 1. Specimen brought into the MLT Laboratory will be carefully screened, in proper containers and labeled. 2. Proper protection will be used when processing specimen (lab coats, gloves and protective eye wear as appropriate). 3. Mechanical pipetting, use of safety engineering devices, and safe work practices at all times. 4. Decontamination of laboratory work surfaces at end of each exercise. Use bleach and/or phenol. 5. Decontamination or proper disposal of contaminated laboratory test materials. a. Blood and body fluids will be placed in biohazard bag in the trash. b. All needles, broken glass, and hemolets will be placed in a biohazardous sharps container and stored in the Prep Biohazard area for incineration and removal by commercial biohazard disposal company. c. All gauze, Kim wipes and disposable materials contaminated with blood and body fluids will be discarded in a biohazard bag and stored in the Prep Biohazard area for incineration and removal by commercial biohazard disposal company. 6. Decontamination of scientific equipment, i.e., electrodes, glassware, etc. 7. Hand washing after all laboratory procedures. 8. Accurate and proper recording and reporting of results. Reference: "Legal Implications of Universal Blood and Body Fluids Precautions", David L. Wing, Clinical Laboratory Science, Volume 1, No. 2, March/April 1988. " Needlestick Safety Act", OSHA Standards 2002 (or later version) 9. << www.ncbi.nlm.nih.gov/Taxonomy/Browser/wwwtax.cgi >> 10. << Combase (Predictor and Modelling Toolbox) with MRV, USDA Pathogen Modeling Program, EPA Virulo >> 11. << COPASI, Pathvisio + Cytoscape + KEGG >> << Micro-Manager Open Source Microscopy software with ImageJ, JoVE (video journals), UIUC-Virtual Microscope >> << Bioconductor >> PERIODICALS --> 1. American Journal for Medical Technology 2. Laboratory Medicine 3. Medical Laboratory Observer (MLO) 4. Journal of Clinical Microbiology 5. Clinical Microbiology Reviews Typical test: TBA Typical Lab manuals (in unison) --> Designated lab manual + Bergey's Manual of Systematic Bacteriology COURSE OUTLINE: -Introduction/Cell Structure/Microbial Growth -Bacterial/Eukaryotic/Viral Taxonomy -Microbial Communication/Taxonomy Presentation Note: for bacterial communication the following articles may prove highly invaluable Waters CM, Bassler BL. Quorum sensing: cell-to-cell communication in bacteria. Annu Rev Cell Dev Biol. 2005; 21: 319 - 346 Miller MB, Bassler BL. Quorum sensing in bacteria. Annu Rev Microbiol. 2001; 55: 165 - 199 Taga ME, Bassler BL. Chemical communication among bacteria. Proc Natl Acad Sci U S A. 2003;100 Suppl 2 (Suppl 2): 14549 - 14554 Henke JM, Bassler BL. Bacterial social engagements. Trends Cell Biol. 2004; 14 (11): 648 - 656 -Bacterial Genetics -Bacterial Metabolism and Ecology -Microbes and Water Treatment -Microbes, Agriculture, and Food -Healthy Flora and Bacterial Infection -Epidemiology -Immune Responses/MMWR assignment due -Antibiotics and Resistance/Antivirals and Vaccines -Disease and Society -Disease Presentations -Disease and Society presentations Prerequisites: Microbiology II Virology: This class will introduce you to viruses. We will emphasize the development and life-cycle of all types of viruses, but will cover some aspects of epidemiology. We will especially emphasize (lambda), Hepatitis C (HCV), Feline Leukemia Virus (FeLV), Influenza, HIV, MERS and SARS in the course. Typical text --> Introduction to Modern Virology, 6th Edition N.J. Dimmock, A.J. Easton, and K.N. Leppard Blackwell Scientific Publications, 2007 Journal Articles --> May have to incorporate journal articles as well Software --> Microbial, Viral and pathogen software (check Goody Bag post). Many lectures AND labs will incorporate software --> << Combase (Predictor and Modelling Toolbox) with MRV, USDA Pathogen Modeling Program, EPA Virulo >> Organic Chemistry, Biochemistry & Molecular Biology software --> << VMD (with NAMS), GROMACS, VOTCA, Desmond, UCSF Chimera, Molsoft, CCPN, RedMD + RedMDStream >> << BLAST, Unipro UGENE, Bioclipse, Staden Package, Bioconductor >> << EMBOSS + JEMBOSS + Pise + wEMBOSS + EMBOSS-Explorer >> Grading --> - The Labs will count for 55% of the final grade. You will need to write up the results for each experiment. A separate handout explains the lab writeups. Attendance at all the labs is required, with points deducted for missing them. The lab write-ups are due on Friday’s, one week after the lab has finished. - Then 45% of the grade will come from your scores on 3 midterms. They cover the lecture and (most, not all) lab material. Course Outline --> WEEK 1 Introduction. Growth and assay of viruses WEEK 2 Methods of studying viruses. Methods of identification of biochemical molecules in viral structure, cell interactions, infiltration and (high-jacking) replication. Structure of viruses WEEK 3 Classifying viruses. Lab-Collect soil phages. Wear sensible shoes. Attachment and penetration WEEK 4 Replication of DNA virus genomes WEEK 5 Replication of Retroviral genomes Gene expression in DNA viruses WEEK 6 Review for Midterm #1 Gene expression in DNA viruses WEEK 7 - 8 Gene expression in DNA viruses. Gene expression in RNA viruses. Assembly of viruses WEEK 9 Assembly of viruses. The immune system. Virus-cell interactions WEEK 10 Virus-host interactions. Lambda WEEK 11 Virus latency. Transmission of viruses WEEK 12 Review for Midterm #2 Transmission of viruses. Viral evolution WEEK 13 Viruses and Human Diseases WEEK 14 Carcinogenesis and tumor viruses. Vaccines and antivirals WEEK 15 (viral communication and virus-virus interactions) Erez, Z., Steinberger-Levy, I., Shamir, M. et al. Communication Between Viruses Guides Lysis–Lysogeny Decisions. Nature 541, 488–493 (2017) Note: the prior article may just be one conveyance, where possibly other articles or texts give further elaboration. Seek out texts and journal articles for analysis, modelling and biochemical process. WEEK 16 Vaccines (viral vector, plasmid DNA, mRNA and recombinant nanoparticle) and antivirals Strategy and mechanisms (can make use of mentioned software for intimate investigation) Prions WEEK 17 Review for Midterm #3 LAB SCHEDULE --> In the labs, you will a perform research project. In one, we will purify and characterize phages from whatever environments. The emphasis in the labs is not on the correct results, but instead, it is on understanding what you are doing and why you are doing it. By understanding what the experiments can and cannot do, you can then understand original papers and seminars in molecular biology and related fields. You also get some feeling for what types of problems can occur and be solved in labs. Since exact results in the labs are not important, do not alter your data to make it look better. Preparation for the labs is important. Reading the labs over before class will not only reduce mistakes in the lab, but it will also help you work more quickly. In general, try to understand the types of uses for each technique, the range of sensitivity for each technique, and the advantages and disadvantages of similar techniques. Try to think of other uses of the experiments and techniques. We only have enough time to use a technique one way, but most of them can be used for many types of experiments. Note: construct isolated sealable tents, where professional safety and hazard protocols are present and in place, if need be. Note: video recording of labs is permissible, granted that the given regulations and protocols are upheld. Lab Week 0 Safety and walkthroughs Applicable and practical mathematical modelling of cultures w.r.t. to median, nutrition and other environmental factors; accompanied with modelling software. NOTE: such may also be involved with other labs besides lab week 4, say, lab week 7 - 12. Lab Week 1 T4 plaque assay Lab Week 2 Isolation of soil phages Lab Week 3 Soil phage. Isolation of soil phages Lab Week 4 Growth of phage Augmented by review of some modelling skils from Lab week 0 accompanied with modelling software Lab Week 5 Isolation of phage nucleic acid Lab Week 6 Analysis of phage nucleic acid Lab Weeks 7 – 9 Further analysis of phage Lab Weeks 10 – 11 Detecting viral sequences (DNA and RNA) Lab Weeks 12 – 13 Role of proteins PART A Proteins and host cell membranes Protein identification by mass spectroscopy or Edman Degradation. Protein-protein, protein-nucleic acid, protein-RNA and protein-lipid interactions determine: (1) structure of virus particles (2) the synthesis & expression of virus genomes and (3) the effects of viruses on the host cell. Relevant to the mentioned 4 types of interactions what methods and experiments discovered/confirmed the mentioned interactions towards (1) through (3)? Target sites, functional groups, protein dynamics w.r.t counterpart concerning the four types of interactions. Example viruses of interests: common cold viruses, Influenza viruses, HBV, HCV, Feline Leukemia Virus (FeLV), measles, Ebola, Zika, HIV, MERS, SARS, etc., etc. Then to make use of software out of the following for building visualizations and simulations: << VMD (with NAMS), GROMACS, VOTCA, Desmond, UCSF Chimera, Molsoft, CCPN, RedMD + RedMDStream >> << BLAST, Unipro UGENE, Bioclipse, Staden Package, Bioconductor >> << EMBOSS + JEMBOSS + Pise + wEMBOSS + EMBOSS-Explorer >> Highlighting of the following: Classification Symptoms and hazards Anatomy Genomes Sequences transferred to replicate Infiltration process (biochemical processes) Nucleous engagement and tasks Disease ailments (and pathway descriptions leading to ailments) Successful counter-responses against cellular penetration Antibodies tactics Vaccine guide development and testing Interesting article for measles: Mina, M. J. et al. (2019). Measles Virus infection Diminishes Pre-existing Antibodies that Offer Protection from other Pathogens. Science 01 Vol. 366, Issue 6465, pp. 599 - 606 Lab Week 14 PART A: Subtyping (lab activity with 1 or 2 methods) Arens, M. (1999). Methods for Subtyping and Molecular Comparison of Human Viral Genomes. Clinical Microbiology Reviews, 12 (4) 612-626 PART B: Software for genomics development following: RStudio + R packages for genome data development (BiocManager, ChemmineR, dPCP, MAPITR) --> Thodberg, M., & Sandelin, A. (2019). A Step-by-Step Guide to Analysing CAGE Data using R/Bioconductor. F1000Research, 8, 886 Cao, Y., Charisi, A. et al. (2008). ChemmineR: A Compound Mining Framework for R. Bioinformatics (Oxford, England), 24(15), 1733–1734 < manuals.bioinformatics.ucr.edu/home/R_BioCondManual > < cran.r-project.org/web/packages/BiocManager/vignettes/BiocManager.html > Students may be given anonymous pathogen sequences. Interests to be out of the most predominant or advanced or accurate methods recognised today. Lab Week 15 Vaccines and pathogen evolution (lab activity with 1 or 2 methods for strain recognition/differentiation) PART A (overview): Ojosnegros, S. & Beerenwinkel, N. (2010). Models of RNA Virus Evolution and their Roles in Vaccine Design. Immunome Research, 6 (Suppl 2), S5 PART B (overview): Vaccines and pathogen evolution Sanjuán, R., Domingo-Calap, P. (2016). Mechanisms of Viral Mutation, Cell. Mol. Life Sci. 73, 4433–4448 Hanley K. A. (2011). The Double-Edged Sword: How Evolution Can Make or Break a Live-Attenuated Virus Vaccine. Evolution, 4(4), 635–643 PART C (overview) Viral Mutation Rates Will have lab investigation of 2 - 3 “vanilla” viruses to determine mutation rates based on the following article: Sanjuán, R., Nebot, M. R., Chirico, N., Mansky, L. M., & Belshaw, R. (2010). Viral Mutation Rates. Journal of virology, 84(19), 9733–9748 PART D (activity) Database viral mutation research to develop. Replicate then pursue other viruses: Yun-Xin Fu, (2001). Estimating Mutation Rate and Generation Time from Longitudinal Samples of DNA Sequences, Molecular Biology and Evolution, Volume 18, Issue 4, Pages 620–626 General Approach Data Collection: Gather longitudinal samples of DNA sequences from the population of interest. These samples should span multiple time points to capture the changes in the genetic makeup of the population over time. Sequence Alignment Phylogenetic Analysis Molecular Clock Analysis Generation Time Estimation Statistical Methods: to quantify the uncertainty associated with mutation rate and generation time estimates. This may involve Bayesian methods (or bootstrapping) to generate confidence intervals. Model Selection: Choose appropriate evolutionary models and clock models based on the characteristics of the studied population. Different viruses or organisms may have different mutation rate patterns, and selecting an appropriate model is crucial for accurate estimation. Quality Control: Implement quality control measures to ensure the reliability of the results. This includes checking for sequence errors, contamination, and other potential sources of bias. Validation: Validate the estimates by comparing them with independent datasets or using alternative methods. This helps assess the robustness of the results. Prerequisites: Microbiology II, Cell Biology, Organic Chemistry I It will be assumed that students are well on their way passes Biochemistry I and are committed to their advancement obligations. Tissue Culture & Virology Lab: This course is different to the Virology course in the sense that this course involves highly thorough protocols and operations in active labs with cell and viral cultures. The class is divided into three modules: cell culture, fundamental virology, and identification and characterization of an unknown virus sample. Module I --> Cell culture. The objective of this module is to learn fundamental cell culture techniques including sterile technique, cell maintenance, cell-splitting, and freezing cells. Module II --> Fundamental virology. The objective of this module is to learn standard assays used in virology studies such as virus amplification, plaque assays, host-range studies, and ELISAs. In addition to learning the technical details, we will focus on how to interpret, analyse, and evaluate experimental results. Module III --> Identification and characterization of unknown viruses. The objective of this module is to identify and characterize an unknown virus sample based on the techniques and analysis methods learned in the first half of the semester. You will summarize this module by writing a journal article that emphasizes the significance and results from your work. Experiment worksheets --> Each experiment will have an accompanying worksheet. These worksheets are meant to be filled in as you are performing the experiment and guide you as you perform the experiment. These worksheets also provide a place to record data, do calculations, and analyse your results. During Module III the worksheets will guide you in identifying your unknown virus. Please see the syllabus and calendar for when worksheets are due. Homework --> The homework assignments are a combination of concepts and principles, data analysis, and are based on the lab and pre-lab lectures (see the syllabus and calendar for when worksheets are due). The homework assignments are meant to be a check-point to ensure you understand the main concepts of what is being taught. Exams --> Two exams are given in this course. The first exam is before spring break. The exam is short answer and covers the principles and concepts taught during Modules I and II. The second exam is at the end of the semester and is a lab practical. Here you are shown actual results and asked to interpret, analyse, and draw conclusions. Lab worksheets, pre-lab lectures, and homework assignments are your best guide for preparing for these exams.If you have university documentation showing you need extra time for an exam, please let me know within the first two weeks of class. Unknown virus write-up --> For Module III, Identification and Characterization of an Unknown virus, you will summarize your results as a scientific paper. You will detail how you determined the identity of your unknown virus and its properties. Results from each experiment will be summarized as a figure or table, and an appropriate introduction and discussion should be included. Guidelines for how to write this paper are at the end of the lab manual and we will discuss this more during the second half of the semester. To help you learn about scientific writing, you will be required to turn in at least one “Results” section and its corresponding Materials and Methods” section before turning in the final unknown lab write-up. Lab performance --> There are many times during the semester that you will need to come in during non-lab hours to finish an experiment or record results. Experiments can be complicated, require reagent preparation beforehand, and require care since you will be working with live virus. Your lab performance grade will be based on ability to maintain cell lines, preparing for an experiment, and returning to finish an experiment. This will be determined by both your AI and me. The five different components contribute to your final grade --> Experiment worksheets 500 points (25 points/each, 20 in total) Homeworks 400 points (50 points/each, 8 in total) Exams 400 points (200 points/each, 2 in total) Unknown virus write-up 100 points Laboratory experiments --> An experiment may take 1-2 weeks to finish. Many labs require a few days of preparation (usually getting your cells ready), a day to do the experiment, and another day to obtain and analyse the results. To help you keep track of the experiments a detailed schedule has been made. This is in the lab manual and on “Oncourse” as a .pdf file. The schedule is only a guide and should be used as the first step in planning your experiments. It is your responsibility to have your cells ready on the day needed and to come into lab and record your results when necessary. Students will work in groups of two. Each group will work in their own hood and be responsible for cleaning the hood, discarding trash and bringing pipettes and biohazard waste to front of the room at the end of each lab period. Each group will receive some initial supplies the first day which they are responsible for maintaining. Both partners must attend class and participate in the lab. If you have to miss a class (illness, job interview), please let your lab partner and myself know as soon as possible. Typical texts --> Tissue Culture and Virology laboratory, by Tuli Mukhopadhyay, published by RLSimonson Studios Gnaguly, S. (2014). A Laboratory Manual on Virology and Tissue culture Techniques. Narendra Publishing House Supporting text: O’Kelly E. (1998) Cell Culture and Diagnostic Virology. In: Clynes M. (eds) Animal Cell Culture Techniques. Springer Lab Manual. Springer, Berlin, Heidelberg Journal Articles --> May have to incorporate journal articles as well Software --> Microbial, Viral and pathogen software (check Goody Bag post) will follow applicable and practical mathematical modelling of cultures and so forth w.r.t. to median, nutrition and other environmental factors. All such along with lab studies of cultures << Combase (Predictor and Modelling Toolbox) with MRV, USDA Pathogen Modeling Program, EPA Virulo >> Course Outline --> Week 1: Experiment #1: Introduction to cells: importance of sterile technique. Check in & get supplies. Discuss lab safety and biosafety. Informational sheet. Continue/Finish Experiment #1. Experiment #2: Introduction to cells: visualizing different cell types and determining cell viability and concentration. Worksheet Experiment #2 due Week 2: Finish Experiment #1. Experiment #3: Introduction to cells: learning to passage and maintain cells. Continue Experiment #3. Worksheet Experiment #1 due. Week 3: Continue Experiment #3. Experiment #4: Introduction to cells: freezing and storing cells. Worksheet Experiment #3 due. Week 4: Continue Experiment #4. Experiment #5: Introduction to viruses - determining infectivity by plaque assay. Finish Experiment #4. Finish Experiment #5 Worksheet Experiment #4 due Worksheet Experiment #5 due Week 5: Experiment #6: Introduction to viruses - propagating virus samples Continue Experiment #6 Finish Experiment #6 Week 6: Experiment #7: Introduction to viruses - determining how MOI influences infectivity Experiment #8: Introduction to viruses - determining which hosts are susceptible to viral infection Worksheet Experiment #6 due Continue Experiment #7 and #8 Finish Experiment #7 Finish Experiment #8 Experiment #9: Introduction to viruses - determining viral growth kinetics Worksheet Experiment #7 due Worksheet Experiment #8 due Continue Experiment #9 Week 7: Continue Experiment #9 Finish Experiment #9 Worksheet Experiment #9 due Week 8: Protein-protein, protein-nucleic acid, protein- RNA and protein-lipid interactions determine the structure of virus particles, the synthesis and expression of virus genomes and the effects of viruses on the host cell. Target sites, functional groups, etc. etc. Can make use of software out of the following: << VMD (with NAMS), GROMACS, VOTCA, Desmond, UCSF Chimera, Molsoft, CCPN, RedMD + RedMDStream >> << BLAST, Unipro UGENE, Bioclipse, Staden Package, Bioconductor >> << EMBOSS + JEMBOSS + Pise + wEMBOSS + EMBOSS-Explorer >> Experiment #10: Characterization of viruses - ELISA assay Worksheet Experiment #10 due Experiment #11: Characterization of viruses - pH and lipid sensitivity Experiment #12: Characterization of viruses - hemagglutination assay Worksheet Experiment #11 due Finish Experiment #11 Finish Experiment #12 Week 9: Experiment #13: Characterization of viruses - electron microscopy Worksheet Experiment #11 due Worksheet Experiment #12 due Worksheet Experiment #13 due Week 10: Experiment #14: Identification of unknown virus Determine host-range of unknown virus Follow up: As needed for all experiments during rest of semester Turn in worksheets as you finish experiments Week 11: Characterization of pH and lipid sensitivity of unknown virus Start amplifying unknown virus Week 12: Determination of nucleic acid type in unknown virus Week 13: Determine infectivity of amplified unknown virus by plaque assay Methods and results for at least one experiment Week 14: Repeat experiments if necessary Last day for experiments Clean-up Check-out Last day to turn in worksheets #14 - #20 Week 15 EXAM II, Lab practical Write-up for Experiment #14 due Co-requisite or Prerequisite: Virology Prerequisites: Microbiology I & II, Cell Biology, Organic Chemistry I Microbiology of the Digestive System: Course Description: Study of microorganisms of the rumen and hind-gut of mammals, and their contributions to nutrient utilization of the host animal. Other topics will include nutrient metabolism by microbes, species interactions, and techniques for identification of species and populations of microbes. Student Learning Outcomes --> Develop a solid understanding of the microorganisms of the digestive tract of mammals Be able to describe how microorganisms contribute to nutrient utilization of mammals Be able to identify common digestive tract microorganisms Describe how species of microorganisms interact with one another Describe techniques to identify species of microorganisms Microbial growth models with environmental parameters versus observation (lecturing and labs) Texts--> Will make use of various professional sources that are highly comprehensive or extensive in the course topics. References --> Verhoeckx K. et al. (eds) The Impact of Food Bioactives on Health. Springer, Cham (2015) Hillman, E. T., Lu, H., Yao, T., & Nakatsu, C. H. (2017). Microbial Ecology Along the Gastrointestinal Tract. Microbes and Environments, 32(4), 300–313 Karasov, W. H., & Douglas, A. E. (2013). Comparative Digestive Physiology. Comprehensive Physiology, 3(2), 741–783 Labs --> One isn’t interested in elementary or junior high experiments; will be left to students to look up such. Nevertheless, the following example articles make strong guides for lab experiments (make appropriate order and w.r.t. course topics succession): --Processing of Vitamins, Minerals, Proteins, Sugars, Starches and Fats. Environments for stability and solubility with verification through biochemistry lab activities. Includes what parts of the digestive tracts are responsible for processing; consideration for chemical reactions and by-products as well. Temperature, pH and other variables may be considered as well. If microbes are highly prevalent in process, must have detailed analysis, modelling and simulation of the biochemical processes. NOTE: software encountered in Biochemistry I will be applied in this lab. --Cheng, C. H. K. Laboratory Experiments on the Actions of Digestive Enzymes, Biochemical Education 20(1) 1992 --Robic S. (2010). Laboratory Exploration of Survival of Probiotic Cultures Inside the Human Digestive Tract Using in vitro Models. Journal of Microbiology & biology education, 11(1), 50–55 --Liu L, Firrman J, Tanes C, Bittinger K, Thomas-Gahring A, Wu GD, et al. (2018) Establishing a Mucosal Gut Microbial Community in vitro Using an Artificial Simulator. PLoS ONE 13(7): e0197692. --Brodkorb, A., Egger, L., Alminger, M. et al. INFOGEST Static in vitro Simulation of Gastrointestinal Food Digestion. Nat Protoc 14, 991–1014 (2019). --Minekus M. (2015) The TNO Gastro-Intestinal Model (TIM). In: Verhoeckx K. et al. (eds) The Impact of Food Bioactives on Health. Springer, Cham --Bergmann, M. and Fruton, J. S. Some Synthetic and Hydrolytic Experiments with Chymotrypsin. J. Biol. Chem. 1938, 124: 321-329 --Other labs will involve particular microbial organisms involving “specified nutrition” and environmental parameters (temperature, pH, etc. etc. etc.) with dependent variables such as growth rate, rate of processing, etc. etc. etc. NOTE: software mentioned in Environmental Microbiology and Clinical Microbiology may be applicable in this lab. Grading: 3 Exams: 60% Labs: 40% Course Topics: I. Introduction to Microbiology II. Bacteria of the Digestive System III. Protozoa of the Digestive System IV. Fungi of the Digestive System V. Interactions of Digestive System Microorganisms VI. Microbial Techniques VII. Carbohydrate Fermenting Microorganisms VIII. Microorganisms Involved in Nitrogen Metabolism IX. Microorganisms Involved in Lipid Metabolism X. Methanogenic and Acetogenic Bacteria Prerequisite: Biochemistry, Microbiology II, ODE. Note: try not to take this course at the same time with Clinical Microbiology and Environmental Microbiology. Tissue Engineering Course is different from the Tissue Culture & Virology course. This course DOES NOT have virology applications. A standard tissue engineering course can be developed with not much trouble. However, many are not innovative enough to recognise that undergraduate students with laboratory skills from prior courses are highly capable of successfully completing tissue engineering laboratory activities. The skills students have serve to engage or immerse themselves in economic sensibility (professional opportunities, recognising the high value in their skills and self-worth, etc., etc.). Apart form standard lectures for crucial education with applications in medicine and engineering, interest and access can be amplified if students’ skills are put to use. From the given articles below one can recognise that the materials and tools required for tissue engineering labs are often standard and relatively inexpensive equipment used in other biological sciences courses. Department to build a course tailored to incorporating activities observed in such articles --> Saterbak, A. (2002). Laboratory Courses Focused on Tissue Engineering Applications. Proceedings of the 2002 American Society for Engineering Education Annual Conference & Exposition Copyright © 2002, American Society for Engineering Education Bodnar, C. et al (2018). Implementation and Assessment of an Undergraduate Tissue Engineering Laboratory Course. Education for Chemical Engineers 24, 52 – 59 There’s also the evolving science and technology of lab produced meat. Some of the example articles following provide strong descriptions of experiments that can be implemented in course --> Datar, I. and Betti, M. (2010). Possibilities for an In-Vitro Meat Production System, Innovative Food Science & Emerging Technologies. 11 (1): 13–22. Adamski, M. et al (2018). Two Methods for Decellularization of Plant Tissues for Tissue Engineering Applications. Journal of visualized experiments: JoVE, (135), 57586. Ben-Arye, T. et al. (2020). Textured Soy Protein Scaffolds Enable the Generation of Three-Dimensional Bovine Skeletal Muscle Tissue for Cell-Based Meat. Nat Food 1, 210–220 Kang, D. H. et al (2021). Engineered Whole Cut Meat-Like Tissue by the Assembly of Cell Fibers Using Tendon-Gel Integrated Bioprinting. Nature communications, 12(1), 5059. NOTE: one isn’t restricted to any particular activities in the articles. Based on analysis and experience one can introduce other experiment assignments for robustness. Grading Homework Quizzes Labs 3 Exams Prerequisites: Cell Biology, Biochemistry I, Genetic Engineering & Technology, Molecular Biology I

B. METABOLIC BIOLOGY (BIOCHEMISTRY) Students will proceed with courses based on prerequisites they have successfully completed with satisfactory grade requirement. Concentration Curriculum: --Core Courses Scientific Writing I & II, General Biology I & II, General Chemistry I & II, Organic Chemistry I & II (check chem post), Biochemistry with labs, Biostatistics I & II, Advanced Statistical Modelling and Machine Learning for Biostatistics --Professional Necessities Food Chemistry, Organic Synthesis Laboratory, Cell Biology (with labs), Genetic Engineering & Technology, Comparative Genomics, Molecular Biology I & II, Metabolism, Molecular Control of Metabolism & Metabolic Disease, Bioprocess Engineering, Bioprocess Engineering Lab, Drug Metabolism, Protein Engineering, Metabolic Biology Research. --Mandatory Courses Calculus for the Biological Sciences I & II, ODE, General Physics I Some course descriptions: Biostatistics I Course concerns probability and statistics applied to problems in biology, industrial/occupational health, and epidemiology. Use of statistical software R for data analysis is emphasized extensively. Note: this course is designed for students majoring in the biological sciences with a second term calculus background. Through the extensive use of practical examples, this course is expected to motivate and teach students statistics knowledge that would be helpful for their major study. The computer program R is the standard statistical program for this course. Students will use R to complete data analysis projects. R can be downloaded and installed on your personal computer for free following instructions at http://www.r-project.org/. In addition, the R environment will be augmented by RStudio interface with other R packages. This course covers fundamental concepts in probability and statistics, including data description, design of experiment, probability rules and distributions, statistical inference and linear regression. Definitions will be learned through real-world examples and applications. Besides these traditional materials and subjects, topics and methods that are particularly applicable to the biological sciences will be introduced. Again, much focus on the applications of statistical ideas to realistic data and practices. Students are expected to use materials learned from this course to guide statistical practice for their major studies in the future. After successfully completing this course the expectation is that students will be able to: 1. To grasp concepts in probability and be able to apply basic probability rules, distributions, and laws to solve conceptual statistics questions 2. Use statistical guidelines and common sense to interpret the process of data collection, description and analysis, and to design statistically sound experiments 3. Learn various statistical inference techniques and be able to select appropriate methods for specific data sets and scientific purpose 4. Link the course materials with real-life examples, and explore the opportunities for other biological applications 5. Interpret statistical reports and carrying out data analysis using R. Several data projects will be assigned during the semester. Independent work is expected. This is not a course of “pen and paper finesse” succeeding the composition of gunk and bamboozle on a writing board. One can’t be successful in statistics by only writing down theory. Practice with an environment that applies intelligence and engagement is essential. There’s no point in doing statistics if one doesn’t know how to acquire and manipulate real data. Real data realistically outnumbers the fingers and toes one possesses. Most of grading will be based on projects (having commentary descriptions) accompanied by the analytical process development description done in a word processor. Typical Texts --> Will make use of R language Statistics texts under CRC Press and Springer publishing Tools --> R language and R Studio Note: a calculator at times may prove useful for the idealistic or the “synthetic” customary questions. “R Monograph Notebook” --> Students should maintain a notebook as they proceed through the course and learn how to do analyses in R. This assignment involves a notebook that lists the syntax and provides a brief explanation of each function that students learn during the course. Instructor will assign R maturity development questions to be in tune with course progress; you will only be allowed to use your monograph to assist with assigned questions. The notebook will be handed in near the end of the semester and handed back to the students after grading. Such a notebook can be an extremely useful resource both during and after the course to quickly refresh one’s memory on the details of a particular function. Design with R most likely will vary among students. Poor development in a such a notebook may or may not correlate with poor grades. NOTE: this course serves only to towards the perspective of students in the biological sciences, so no one in the biological sciences should be looking elsewhere. MIND YOUR DAMN BUSINESS. Grading --> Problem Sets 20% R Labs 20% R Activities 0.7 R Monograph Lab Notebook 0.3 R maturity development questions 15% End of term lecturer observation 5% 3 Exams 30% Assigned Projects 30% Exams --> Limited open notes. I don’t like setting up myself and students for embarrassment; you are not perfect with statistics, so expect exams to be primarily knowledge based and the calculus related fodder. Most of your development will come from homework and labs; it is what it is. Note: limited open notes. Students may be more comfortable with certain R packages. Again --> Several data projects will be assigned during the semester. Independent work is expected. Course Outline --> Introduction to statistics, data and R Statistical Measures and Summary Statistics for data sets Methods of data acquisition: Sources/databases (ecological & biological), file types, APIs, etc. Introspection. querying, wrangling Summary Statistics with R Applied probability theory Axioms of probability Modelling frequencies and establishing densities Simulating random variables from real experiments Probability distributions and properties Sample estimates Law of Large Numbers and the Central Limit Theorem Introduce the Law of Large Numbers (LLN) Central Limit Theorem (CLT). Identify Exponential, Poisson and Binomial data and respectively determine in a manner to confirm LLN and CLT. Routledge, R., Chebyshev’s Inequality, Encyclopaedia Britannica Is there too much reliance on assuming normal or Gaussian distribution? Towards Chebyshev’s inequality what amount of repetition (regarding LLN and CLT) of an experiment is adequate towards Chebyshev becoming relevant? Overview and goals of various concentration inequalities (just a survey). Chi-square distribution The bottom line is to establish the flow of the uses competently with applications involving real raw data. Comprehending categorical data sets and ordinal data sets Organisation of data and sensitivity of categories concerning traits of interest. Test for independence McHugh ML. (2013). The chi-square Test of Independence. Biochem Med (Zagreb). 23(2): 143-9. Test of homogeneity Test of variance Applications of the Chi-Square distribution with confidence intervals T-distribution Kim T.K. & Park J. H. (2019). More About the Basic Assumptions of T-test: Normality and Sample Size. Korean J Anesthesiol. 72(4): 331-335. Sample size determination Population parameter estimation Confidence intervals Directly logistical to understand what you’re doing in R F-distribution Assumptions for the F-distribution Relevance to the biological sciences (active data immersion) Note: not textbook finesse, rather how and when actively. Goodness of fit: fit of distributions Summary Statistics Skew and Kurtosis Box Plots Density Plots P-P and Q-Q Statistical Tests Definition, Null hypothesis One-sided & two-sided tests of hypothesis Types of test statistics Comprehending critical values for ideal distributions Significance levels Critical values for real raw data sets Does your data exonerate ideal distributions? Chi-Square Test Kolmogorov-Smirnov Test Anderson-Darling test Shapiro-Wilk Test MLE and Method of Moments Manual tasks will be limited to at most 4 element data sets Computational logistics for large data sets followed by implementation Review/probe data for goodness of fit module for appropriate distribution You may be tasked with distribution determination before parameter/point estimation Hypothesis testing (exploratory) Note: as aspiring biologists I can’t give “zombie textbook problems” and expect you to relate to a profession tangibly and fluidly. You will be exposed to raw professional data from various sources. You will develop the four mentioned steps. You should ask yourselves if the hypotheses are practical as well. Why is normal distribution assumed? Will be exploratory rather than zombie problems. Namely, knowledge and skills from Goodness of fit module. Then proceed with the following: 1.State the two hypotheses so that only one can be right 2.Formulate an analysis plan, outlining how data will be evaluated 3.Carry out the plan and physically analyze the sample data 4.Analyse the results and either reject the null, or state that the null is plausible, given the data Test of Proportions (exploratory) Comparisons of variances Directly logistical to understand what you’re doing in R Confidence limits for means. Does it require normality? Analysis of variance Must be exploratory, else it’s toxic Correlation (includes misuse of types and resolutions) Pearson Correlation Crucial Conditions Structure Implementation Spearman Correlation Crucial Conditions Structure Implementation Generating heat maps. The ggpairs() function Bivariate Regression Two and three-way analyses of variance Must be data exploratory, else it’s toxic Multiple Regression Model components Methods to select variables OLS MUST: Summary Statistics Analysis of Covariance Must be exploratory, else it’s toxic Non-parametric statistics Resampling methods Falsified Data Hartgerink C, Wicherts J, van Assen M (2016). The Value of Statistical Tools to Detect Data Fabrication. Research Ideas and Outcomes 2: e8860. Al-Marzouki, S., Evans, S., Marshall, T., & Roberts, I. (2005). Are these data real? Statistical methods for the detection of data fabrication in clinical trials. BMJ, 331(7511), 267–143. Yamamoto, K., & Lennon, M. L. (2018). Understanding and Detecting Data Fabrication in Large-Scale Assessments. Quality Assurance in Education, 26(2), 196–212. Prerequisites: General Biology II, Calculus II Biostatistics II --This succeeding course in the sequence will have more emphasis on incorporating journal articles and real world experiments. --Students will have to orchestrate inquisitions by exploratory data analysis and statistical methods involving R. There will be assigned data sets and journal articles to do just that. --This is not a “pen and paper course”. Texts and journal articles will cater to subjects both from prerequisite and this course. Means of data retrieval and manipulation are crucial; it may be the case that the data desired in inaccessible, hence students will have to resort to alternative data sources that yields much different conclusions. NOTE: personally refresh your knowledge and acquired R skills from calculus and Biostatistics I alongside ordained reacquaintances in course. NOTE: this course serves only to towards the perspective of students in the biological sciences, so no one in the biological sciences should be looking elsewhere. MIND YOUR DAMN BUSINESS, AND KEEP YOUR DAMN BUSINESS . Assessment --> Assignment Sets (prerequisite & current level from multiple sources) 15% Analytical and R based 3 Exams (prerequisite & current level) 30% Labs + Data Analysis Term Project 40% 2 Field Inquisitions with R 15% Conducted Journal Articles Computational Inquisitions Supporting data sets to be provided Gov’t administration field experiments inquisitions Assignment Sets --> Will be reacquainted with prerequisite tasks, prerequisite projects AND current level tasks (analytical and R computational). Exams --> Exams will have the same manner of administration and activities as exams from prerequisites. Yet, consisting of both prerequisite tasks AND current level tasks. Limited open notes. LABS WITH R --> Hypothesis Testing Expt. Design, Multiple Comparisons ANOVA Regression (Mult. Reg. and Dummy) ANCOVA Mantel Test & ANOVA MANOVA and DFA Clustering PCA and Kernel PCA PCA and Kernel PCA Re-analysis of DFA Data Comparing & Averaging Models Analysis of Trait Evolution Fitting models of Trait Evolution TERM PROJECT --> The term project has been broken down into multiple components due throughout the semester to provide further guidance for students. On given date, students will select a dataset to use for their term project. Students can either provide their own dataset (if they have collected data during their research), or will be given the opportunity to analyse a complex dataset supplied by faculty as their term project. For the Hypothesis Activity (given due data), students will take a close look at their dataset and formulate biological hypotheses that they would like to test statistically. The assignment will be handing in these hypotheses. For the Experimental Design assignment (given due), students will outline which analyses they will use to test their biological hypotheses and provide the specific explicit statistical hypotheses that they will test. The Term Project Report (given due having additional 1 week collection buffer) will be written after students complete their analyses. The report will include a Statistical Methods and a Results section, complete with tables and figures. Methods should include sufficient detail to redo the analyses. The results should include everything necessary for interpretation of their analyses and data, but not superfluous material. Term Project Reports for all students should include a title page with a title, student name, course number and name, and assignment name. The text of the report should be double spaced, with indented paragraphs, 1” margins, 12pt Times New Roman Font, and page numbers. Tables should be single spaced with headings above each table. Figures should have captions below each figure. Figures and tables can be embedded in the text or provided at the end of the document. Literature cited should follow the format for the journal Evolution. Assignments that do not follow these formatting instructions will be returned to the student for correction prior to grading. NOTE: most labs done serve as structure for your HA and ED NOTE: I will be collecting your R development (having sensible commentary) for the term project in PDF along with the term report in PDF. Finally, students will give a short, in-class presentation about their study, analyses and findings. Presentations will be in PowerPoint. MAJOR COURSE TOPICS --> Methods of data acquisition, data wrangling and summary statistics (prerequisite reinforcement) Goodness of Fit (prerequisite reinforcement) Hypothesis Testing Review Experimental Design & Sampling ANOVA Variations & Models Regression (multivariate) Quantile regression compared to Least Squares regression ANCOVA Resampling Techniques MANOVA Clustering (K-means or DBSCAN?) Principal Component Analysis (PCA) and Kernel PCA Model Selection & Likelihood (emphasis on computational logistics and implementation) Phylogenetic Regression Extensions of Phylogenetic Statistics Prerequisite: Biostatistics I Advanced Statistical Modelling and Machine Learning for Biostatistics This course explores advanced statistical modeling techniques and machine learning methods as applied to biostatistical problems. Topics include generalized linear models, hierarchical modeling, Bayesian statistics, and the integration of machine learning algorithms for analyzing complex biological and health data. Note: 2 lectures per week, with approximately 2 hours per lecture. Assignments -- Assignments will be quite laborious in the interest of sustainability with knowledge and skills through your journey in biostatistics. Each assignment will comprise of the following elements: A. problems and tasks encountered in both Biostatistics I & II. Such problems and tasks will also make extensive use of R. As well, being advanced biostatistics students, projects from Biostatistics I & II can/will also be considered basic assignments as well. B. Course level assignments to such given course topics. Good emphasis on ability to comprehend and specify the transition from prerequisite skills/tools to course level tools/method/skills; then implementation. Will also make extensive use of R. Data Science Basics Quizzes -- For the Data Science Basics module there will be handwritten quizzes to test knowledge, comprehension, appropriateness and T/F. Exams -- Exams will account for all modules. Assignments will be strong foresight of what’s to appear on exams. You will be making extensive use of R with open notes for all course modules. Exams will feel like projects where each “project” will involve multiple modules. Make-up Student Project -- Applying Advanced Models to Biostatistical Data. Concerns students who are interested in making up lost weight towards their final grade; the better you did in this course, the lower the value. Can regain up to 5% for final grade. Students will be given a sack to randomly (and blindly) pick a project. Students will have until 2 days before the final grade submission deadline to submit projects. Students will be privately given project details via student email where they will have to acquire the data from specified sources. Course Assessment -- Assignments 20% 4 Exams for all modules 60% 3 Data Science Basics Quizzes 15% Will be precursors to exam(s) for the Data Science Basics module Make-up Student Project (being conditional) COURSE OUTLINE -- WEEK 1-3. Introduction to Generalised Linear Models (GLMs) with model estimation and summary statistics Multilinear Regression (fast fast review) Quantile Regression Logistic Regression Poisson Regression WEEK 4-5. Hierarchical Modelling (HM) Introduction to HM Multilevel Modelling Random Effects and Mixed Models WEEK 6-7. Bayesian Statistics in Biostatics Note: I don’t introduce things to be a disgusting, miserable, viral bastard. Module will be extremely goal oriented, namely, problem, goal(s), methodology, logistics, implementation, evaluation. No social nor psychological probes/inquisitions; there are certified licensed professionals elsewhere tied to meaningful or economic interests. Bayesian Inference (to the point, constructive and economical) Markov Chain Monte Carlo (MCMC) Methods – only constructive and economical methods Bayesian Regression Models WEEK 8-9. Advanced GLMs and Extensions Negative Binomial Regression Zero-Inflated Models Generalised Estimating Equations (GEE) WEEK 10-15. Data Science Basics Note: subjects of overfitting or underfitting arise in model validation statistics. Data Acquisition. Data Probing: view(), glimpse(), str() Data Cleaning and Data Wrangling Summary Statistics, Skew, Kurtosis, Correlation Analysis and Heatmaps Machine Learning Overview Feature Selection R functions (underlying methods may not be fully comprehended, but that’s generally the world): Principal Component Analysis (PCA), Kernel PCA, Boruta, FSelectorRccp. Comparative observation among such prior three also expected. Classification Multiple Regression (very rapid review) OLS and Quantile Support Vector Machines Decision Trees Random Forests Clustering (K-Means and DBSCAN advanced repetition) Includes the Silhouette Score and Davies-Bouldin Index Prerequisites: General Biology II, General Chemistry II, Biostatistics II Cell Biology: The standard definition of a cell in most introductory biology texts includes the line that cells are “the fundamental building blocks of all organisms.” Because of this fact, trite though it may be, a detailed understanding of the fundamental processes of cellular function is critical to all specialties within biology, clinical or academic. Some of these processes, including for example the biochemical mechanisms underlying cellular energetics, are remarkably consistent from bacteria to human. Other cellular processes and structures vary from cell type to cell type or organism to organism, allowing for unique adaptations of cells and organisms to particular functions. For example, nerve cells have various properties allowing them to conduct electrical signals and therefore process information, while kidney cells are specialized for the secretion of waste, and red blood cells for the transport of oxygen and carbon dioxide. What are the differences in physiology from cell type to cell type determining these specific functions? During the first half of the semester we will focus primarily on the biochemical processes that underlie cellular function, with an emphasis on protein structure and function, ion transport mechanisms and energy metabolism. The second half of the semester will emphasize more the function of particular organelles, including cell membranes, intracellular compartments and the cytoskeleton, and the relevance of these structures on processes like cell signaling and mitosis. Throughout the course, we will emphasize how variability in these processes imbues different cell types with their unique functional abilities. We will also seek to understand the experimental evidence for the different facts and concepts we study: How do we KNOW that nerve cell signaling, for example, involves the release of neurotransmitters? Some of this experimental evidence will be explored in a hands-on way in the lab sections, some will be discussed during lecture, and some will be the subject of analysis in the reading of original scientific manuscripts. Finally, we will examine how malfunctions in the cellular processes we are studying underlie certain diseases. In particular, the final few lectures of the course will focus on the biology of cancer cells: how do changes in cellular processes allow cancer cells to proliferate and metastasize? What are some of the current clinical approaches to curing cancer by blocking or reversing these processes? Aspirations --> To understand fundamental concepts of cellular function. To understand, and be able to critically analyze, the scientific evidence underlying our current understanding of cellular processes. To develop skills, through lab experiments, in some of the specific methodologies used in the study of modern cell biology. To become skilled at formulating and testing hypotheses using these methods. To develop a preliminary ability to read and analyze the primary scientific literature: What are the major findings of a science paper? What evidence is presented to support these findings? Are there shortcomings, either in the methods used or the logic of the experiments, which might lead one to question the conclusions reached by the authors? To be able to put this knowledge into larger contexts of how disease states occur or how organisms function adaptively within their environments. Typical text: The World of the Cell, by Becker, Kleinsmith, and Hardin, 6th edition (2006), Pearson/Benjamin Cummings Class Requirements and Grading --> 1. Class Participation (10%) To include attendance, responses to questions I pose in class, participation in discussions, and simply raising your hand from time to time to ask questions or make a comment (something I DO expect you to do). 2. Quizzes (10%) Two short in-class quizzes during the first half of the course. 3. Homework/problem sets (5%) There won’t be many of these; I’ll assign them when we hit subjects that are especially involved to help you learn the material and to make sure everyone is on track. 4. Primary literature readings (10%) We will read two papers from the primary scientific literature during the second half of the course. In both cases there will be an in-class discussion of the paper and a “reading guide” set of short essay questions which will be graded. The first reading guide assignment will be due AFTER the in-class discussion; the second assignment will be due BEFORE the in-class discussion. 5. Laboratory reports (25%) The specifics of each week’s lab report will be discussed during lab section. Typically, each week’s lab report will be due the following Monday in lecture. 6. Mid-term exam (20%) TENTATIVE format to include an in-class component, a short oral component, and a take-home component. 7. Final exam (20%) LABS --> Lab instructions for each week will be handed out ahead of time, either distributed as hard copies in lecture or posted on the course Angel site (or both). You are responsible for reading the instructions before lab. Otherwise, labs tend to run late, you will have difficulty obtaining the necessary data and knowing what to do with it. Do not expect the instructor to go over every step of the lab procedure before you start. Labs will make great emphasis on strong, practical and constructive immersion into the following software to accompany hands-on activity: << VCell, TiQuant + TiConstruct + TISIM >> Such software provides strong quantitative/computational microscopic assessment of specimens (or whatever) at professional standards. Such provides better means of objectives and expectations towards hands-on labs. Each lab will be associated with an explicit lab report assignment (contained in the lab instructions), usually due in lecture the Monday following lab. Usually, you may either submit the report with your lab partner or independently. If a report is submitted jointly, both partners must have contributed equally, as per Honor Code responsibilities. Do NOT make the mistake of dashing off reports the night before in a single draft. These reports will collectively account for 25% of your course grade, so take them seriously. The lab is a potentially dangerous place and you are required to follow all instructions given by your lab instructor and presented in the lab instructions. Disregarding instructions, or coming to class late or unprepared, may result in grade penalties, in addition to being just plain dangerous for yourself and those around you. Note: students can apply stationary video recording of labs with assigned regulations (to be given). Course Topics: Chapter 1 -19, 24. Some topics will require at least one week of instruction. Labs --> Cell Culturing, Aseptic Technique Cell Culture: basic techniques, population curve Cell Counting and splitting plates Cell Staining Histology Electron microscope Cell Harvesting & Cell Lysis Fractionalization of cells Common method(s) will be implemented Discussion and logistics for immunomagnetc separation & magnetic beads Isolation of erythrocyte membrane proteins Analysis of erythrocyte membrane proteins Bradford Assay (also identifying advantages and disadvantages) SDS-PAGE Chloroplasts and the Hill reaction Prerequisites: General Biology I & II Organic Chemistry I In-depth study of: (i) the structure of organic compounds and the functional groups (bonding, acid-base properties, nomenclature, conformations, stereochemistry), and (ii) the synthesis and reactivity (including detailed mechanisms) of alkanes, alkenes, alkynes, halides, alcohols, ethers, epoxides, sulfides and organometallic reagents. Laboratory experiments are related to topics covered in lecture and emphasize organic laboratory techniques, synthesis and spectroscopic characterization of organic molecules. Typical Texts: McMurry, John E. Organic Chemistry. 8th Edition. Brooks/Cole, 2012. McMurry, Susan. Study Guide with Student Solutions Manual. 8th Edition. Brooks/Cole. Typical Lab Manual: Barbaro, John and Richard K. Hill. Experiments in Organic Chemistry. 3rd Edition, Contemporary Publishing Company of Raleigh, Inc., 2006 Grading: 3 Exams (50% combined) Cumulative Final Exam (25%) Labs (25%) (On the occasion of significant improvement on the final exam, more weight will be placed on the final exam) INSTRUCTIONAL METHODS: List the different instructional methods you might use, in the course of the semester. List supplementary learning options, if any: Traditional lecture with use of chalkboard Computer assisted diagrams and graphics Molecular Models Team work in the laboratory Homework assignments Solving specific questions related to content studied Written exams and distribution of study questions/previous exams Use of the Internet UNIQUE ASPECTS OF COURSE (such as equipment, specified software, space requirements, etc.): Organic chemistry laboratories and their associated equipment, instruments and chemicals. Apart from use of software in lectures, students will use software to accompany experiments that provide detailed molecular/compound structure, target sites, functional groups, etc. etc. Such exhibits will accompany lab reports. Lecture Outline --> Ch. 1 Structure and Bonding Bonding; Hybridization; Drawing Chemical Structures; Functional Groups; Intro to IR Spectroscopy Ch. 2 Polar Covalent Bonds; Acids and Bases Chemical Bonding (Ionic and Covalent); Electronegativity and Dipole Moments; Formal Charges; Resonance Structures; Acid Base Theory (Bronsted-Lowry, Lewis); Acid and Base Strength (pKa); Acid-Base Reactions; Organic Acids and Organic Bases Ch. 3 Organic Compounds: Alkanes and their Stereochemistry Alkanes, Alkane Isomers, and Alkyl Groups; Properties of Alkanes; Conformations Ch. 4 Organic Compounds: Cycloalkanes and their Stereochemistry Cis-Trans Isomerism in Cycloalkanes; Stability and Conformations of Cycloalkanes; Chairs Ch. 5 Stereochemistry at Tetrahedral Centres Enantiomers, the Tetrahedral Carbon and Chirality; Optical Activity; R/S Sequence Rules; Diastereomers and Meso Compounds; Racemic Mixtures, Resolution of Enantiomers; Prochirality; Chirality in Nature Ch. 6 An Overview of Organic Reactions Kinds of Organic Reactions (Radical and Polar); Mechanisms; Describing a Reaction (Equilibria, Rates, Energy Changes, Bond Energy; Transition States, and Intermediates) Ch. 7 Alkenes: Structure and Reactivity Preparation and use of Alkenes; Cis-Trans Isomerism; Alkene Stereochemistry and E/Z Designation; Stability of Alkenes; Electrophilic Addition Reactions; Markovnikov’s Rule: Carbocation Structure and Stability; Carbocation Rearrangements Ch. 8 Alkenes: Reactions and Synthesis Preparation of Alkenes via Elimination Reactions; Addition Reactions of Alkenes (Halogenation, Hydration, Halohydrins, and Hydrogenation); Oxidation of Alkenes (Epoxidation and Hydroxylation); Addition of Carbenes; Radical Additions to Alkenes (Polymer Formation); Reaction Stereochemistry Ch. 9 Alkynes: An Introduction to Organic Synthesis Preparation of Alkynes; Addition Reactions of Alkynes (X2, HX, H2O, H2); Oxidative Cleavage; Alkyne Acidity and Alkylation; Introduction to Organic Synthesis Ch. 11 Reactions of Alkyl Halides: Nucleophilic Substitutions and Eliminations SN2, SN1, E2, E1, E1cB Reactions; Zaitsev’s Rule; Deuterium Isotope Effect Ch. 10 Organohalides Preparation of Alkyl Halides and Grignards; Radical and Allylic Halogenation; Organic Coupling Reactions, Redox in Organic Chemistry Ch. 17 Alcohols and Phenols Properties of Alcohols and Phenols; Preparation and Reactions of Alcohols; Reactions of Phenols Ch. 18 Ethers and Epoxides; Thiols and Sulfides Synthesis and Reactions of Ethers; Cyclic Ethers (Epoxides); Reactions of Epoxides: Crown Ethers; Thiols and Sulfides LABS --> Some experiments require more than one lab period to complete. Based on an instructor’s preference, availability of equipment/supplies or constraints within a given semester, this laboratory schedule is subject to change, including but not limited to, the addition or replacement of one or more of the above experiments with the following experiments: Addition of Bromine to E-Cinnamic Acid in Methylene Chloride Substitution Reactions of Alkyl Halides: Relative Rates Triphenylmethanol with Hydroiodic Acid 1. Check-in, Laboratory Safety, Practices and Waste Disposal. Simple Distillation. 2. Spectroscopy: Introduction to Infrared Spectroscopy. 3. Recrystallization, IR and Melting Point of benzoic acid. 4. Extraction of Organic Compounds from Natural Sources: Trimyristin from Nutmeg. 5. Paper Chromatography 6. Dehydration of Cyclohexanol. 7. Dimerization of 2-Methylpropene 8. Preparation of Diphenylacetylene Starting from Trans-Stilbene. 9. Preparation of Butyl Bromide/Preparation of t-Butyl Chloride (SN2/SN1). 10. Oxidation of Isoborneol to Camphor. 11. The Williamson Ether Synthesis: Preparation of Aryloxyacetic Acid from Cresol. Prerequisites: General Chemistry II Organic Chemistry II Evaluation of Performance --> There will be 1000 points possible in the course. Five exams will be given throughout the semester, consisting of four regular hour exams and a comprehensive final. Each of these exams will be worth 200 points, and your lowest score will be dropped. The four remaining highest scores will total 800 possible points. There will be 120 points possible from laboratory reports, 60 points possible from online D2L quizzes, and 20 points assigned to your laboratory notebook. Students will be kept updated on their performance throughout the semester. Laboratory --> Organic laboratory and lecture complement each other. The lecture supplies fundamental theory about molecular and electronic structure, chemical reactions, and their mechanisms. In the laboratory you will put this knowledge into practice to help you more fully understand the chemical process in progress. Typical text: Janice Gorzynski Smith "Organic Chemistry" with Solutions Manual, 3rd Ed. McGraw Hill Typical Lab Text: Pavia, Lampman, Kriz, and Engel "Techniques in the Organic Laboratory, Microscale and Macroscale", Harcourt College Publishing. There will be,specified software for use throughout course and labs. Apart from use of software in lectures, students will use software to accompany experiments that provide detailed molecular/compound structure, target sites, functional groups, etc. etc. Such exhibits will accompany lab reports. Course Outline --> Week 1 Mass spectroscopy. Infrared Spectroscopy Week 2 NMR: position of signals and strength of signals Spin-spin splitting, other 1 H NMR facts NMR: solving unknowns, 13C NMR Week 3 Reduction of alkenes, alkynes, R-X, and epoxides Epoxidation, dihydroxylation, oxidative alkene cleavage Oxidation of alcohols EXAM 1 Week 4 Radical reactions, alkane halogenation, chlorination of ethane Chlorination of other alkanes, bromination, allylic bromination Lipid oxidation, antioxidants, polymers Week 5 Resonance, conjugation, dienes Diene stability and the Diels-Alder reaction Week 6 Benzene nomenclature and structure Benzene’s unusual stability, criteria for aromaticity Aromatic rings of other types EXAM 2 Week 7 Halogenation, nitration and sulfonation Friedel-Crafts reactions, effects of ring substitution, limitations Disubstituted benzenes, side chain reactions, synthesis Week 8 Carboxylic acids: naming, properties, and preparation Carboxylic acid, reactions, and acidity Carbonyl chemistry: reductions of aldehydes & ketones Week 9 Reduction of carb. acid derivatives, organometallic reagents Synthesis, organometallic reactions EXAM 3 Week 10 Aldehydes and ketones: naming, properties, preparation Aldehyde/ketone reactions, nucleophilic addition, Wittig rxn Wittig rxn continued, imines Week 11 Acetal formation/hydrolysis/use in protecting C=O Carboxylic acids and their derivatives Reactions of acid chlorides, anhydrides Week 12 Reactions of carboxylic acids, esters, and amides Summary of acyl substitutions, applications Keto-enol tautomerism; the aldol reaction EXAM 4 Week 13 Review for final exam Week 14 comprehensive final exam LABS --> Spectroscopy, no lab Exp. 1 FTIR, MS: Check in. Isolation and characterization of Eugenol (essence of cloves) Exp. 2 MS, IR, NMR: Spectral Identification of Organic Compounds Exp. 3 Oxidation: Oxidation of Cyclohexanol to Cyclohexanone Exp. 4-1 Spectroscopy: Identification of a General Unknown, part 1 Exp. 4-2 Spectroscopy: Identification of a General Unknown, part 2 Exp. 5 Diels-Alder Reaction: Synthesis of 4-Cyclohexene-cis-1,2-dicarboxylic Anhydride Exp. 6 Aromatic Substitution: Electrophilic Aromatic Substitution: the Nitration of Toluene Exp. 7 Carbonyl chemistry: Reduction of Heptanal Using Sodium Borohydride Exp. 8 Organometallic Reagents: Preparation & Carbonation of a Grignard Reagent: Benzoic Acid Exp. 9 Carbonyl chemistry: The Synthesis of an Alkene Using a Wittig Reaction Exp. 10 Carboxylic Acid Derivatives: Flavours & Fragrances: Isopentyl Acetate synthesis (Banana Oil Exp. 11 Enolate Chemistry: Synthesis of 2 Methyl-2-pentenal --> An Aldol Condensation Check out Prerequisite: Organic Chemistry I Organic Synthesis Laboratory Practice of organic laboratory techniques. Three hours of laboratory per lab session, twice a week. Approved chemical safety goggles meeting whatever national standards. The purpose of this laboratory course is to introduce students to the techniques that organic chemists (as well as biochemists, physical chemists, etc.) use in their daily routines. After learning and understanding those techniques, students will apply their knowledge to new situations to understand synthesis reactions, molecular structure determination, and analysis of (un)known compounds. Organic chemistry laboratory is important for several reasons. It introduces students to many different laboratory practices and concepts that will be used in subsequent chemistry laboratory classes and in other laboratory situations in biology, pharmacy, and chemical engineering (just to name a few!). It is anticipated that by the completion of this course, students will be familiar with all of the following topics and techniques: Safety in the laboratory Interpreting and following scientific directions Keeping a proper lab notebook Names and proper usage of lab instruments Understanding of general properties of compounds (including solubility, miscibility, acid/base chemistry, etc.) Proper usage of glassware Isolation and purification techniques (including filtration, solvent removal, drying solutions, distillations, chromatography (thin-layer, column, and gas) and crystallization/recrystallization) Characterization techniques including spectroscopy and melting point determination Interpretation of scientific results including percent yield and recovery, melting point, boiling point, IR and NMR spectra, and Rf values Required Materials: A laboratory notebook with carbon(less) pages Approved safety goggles Lab coats Lab manual will be posted through Blackboard Typical text: C.F. Wilcox, M.F. Wilcox, "Experimental Organic Chemistry, A Small-Scale Approach", (3rd edition, 2010). Apart from use of software in lectures, students will use software to accompany experiments that provide detailed molecular/compound structure, target sites, functional groups, etc. etc. Such exhibits will accompany lab reports. Lectures --> Lecture sessions are designed to clarify the concepts covered in the lab, as well as give an overview of techniques that will be used in the lab. Attendance is expected: The labs are only 3 hours in duration, so these lectures will be where you learn everything that you’ll need. Lab exercises will be available on Blackboard for each week. Please be considerate of your fellow students during the lecture period. Disruptions of any kind will not be tolerated and may result in expulsion from the classroom. Laboratory --> You will be required to have appropriate clothing before being allowed to enter the lab. Pre-labs are due at the beginning of the lab, and results and postlabs are due at the beginning of the lab 1 week after completion of the experiment! You will be expected to adhere to all of the lab safety rules. You are all expected to do your part to maintain a clean lab environment as part of GLP (Good Lab Practices): All reagent and solvent bottles should be completely closed immediately after use; All spills and dribbles should be cleaned immediately; All glassware should be put away at the end of the lab, and walkways should be kept free of debris. The following is the distribution of possible points in the course: Library Searching Exercise Database Search Exercises (Spectroscopy and Chromatography) Lab Quizzes Reaction/Synthesis methods knowledge Appropriate choice of method Appropriate constituents and tools. Procedure/steps (summary and/or ordering) Stoichiometry problems Spectroscopy and/or Chromatography analysis/interpretation Applications and industries Multistep Reaction/Synthesis Labs Lab Cleanliness Pre-lab Submissions Lab Notebook and Reports Lab Final Day 1: Much resemblance to quizzes Day 2-3: Augmented with the following: Molecular modelling software exercises Two or Three Practicum Group Labs (open notes) Part A. Points deducted for incompetent questionnaire for safety procedures for respective lab Part B. 2-3 labs to be implemented with competent data recording and lab reports. YOUR LAB REPORT CONSISTS OF THREE (3) PARTS --> Part I - Prelab Report. A copy of your lab notebook pages containing the lab write-up and answers to any prelab questions. This is due at the start of each experiment. Part II - Results. A copy of your notebook pages containing observations noted during the lab experiment. Is due with Part III one week from the conclusion of the experiment. Part III - Postlab Report. A summary of results and answers to postlab questions. This can be written on separate loose-leaf paper. Is due with Part II one week from the conclusion of the experiment Course Outline: Week1 Check-in/Safety Video/ Safety Procedures and Regulations Fractional Distillation Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation, results and analysis Week 2 Measuring the Melting Points of Compounds and Mixtures Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Consider other physical and chemical properties, such as solubility and spectroscopic data, to confirm the identity of the unknown compound. Results and analysis Week 3 Purification by Recrystallization and Melting Point Measurement Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Consider other physical and chemical properties, such as solubility and spectroscopic data, to confirm the identity of the unknown compound. Results and analysis Week 4 Nucleophilic Substitution: Synthesis (SN1 Mechanism and SN2 Mechanism) Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Consider other physical and chemical properties, such as solubility and spectroscopic data, to confirm the identity of the unknown compound. Results and analysis Week 5 Oxidation of Alcohols (Primary, Secondary and Tertiary). Infrared Spectroscopy. Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Infrared Spectroscopy Results and analysis Week 6 Elimination Reaction (E1 Mechanism and E2 Mechanism) Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Consider other physical and chemical properties, such as solubility and spectroscopic data, to confirm the identity of the unknown compound. Results and analysis Week 7 Synthesis of Aspirin. Chromatography and/or Spectroscopy Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Chromatography and/or Spectroscopy Results and analysis Week 8 Solvent Extraction Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Consider other physical and chemical properties, such as solubility and spectroscopic data, to confirm the identity of the unknown compound. Results and analysis Week 9 Electrophilic Aromatic Substitution: Synthesis of o- and p-Nitrophenol. No distillation; extract product with ethyl acetate. Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Consider other physical and chemical properties, such as solubility and spectroscopic data, to confirm the identity of the unknown compound. Results and analysis Week 10 Separation and purification of o- and p-Nitrophenol by Liquid Chromatography. Use 100 mg sample, check by chromatography. Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Results and analysis Week 11 Aldol Condensation Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Consider other physical and chemical properties, such as solubility and spectroscopic data, to confirm the identity of the unknown compound. Results and analysis Week 12 Grignard Reaction: Synthesis of Phenylmagnesium Bromide. Week 1: Part 1. Add methyl benzoate and sustain the desiccator for next week. Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Consider other physical and chemical properties, such as solubility and spectroscopic data, to confirm the identity of the unknown compound. Results and analysis Week 13 HCl workup of previous week’s product. Synthesis of Triphenylmethanol and recrystallization of product. Purity check by melting point measurement. Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Consider other physical and chemical properties, such as solubility and spectroscopic data, to confirm the identity of the unknown compound. Results and analysis Week 14 -15 Wrapping up/cleaning things up. Final Exam. Prerequisite: Organic Chemistry I Biochemistry: The study of biochemistry investigates the interplay between biological macromolecules such as proteins and nucleic acids, and low molecular weight metabolites (such as the products of glucose metabolism). In this course, you will apply your knowledge of intermolecular forces, thermodynamics (when a reaction occurs), chemical kinetics (how fast a reaction occurs), and chemical structure and functionality to understand how biological molecules (and life) work. COURSE GOALS AND OBJECTIVES (Our Roadmap!) -Be able to describe/identify the forces that direct/stabilize different levels of protein structure -Be able to predict how changes in amino acid (or nucleotide) sequence can affect macromolecular structure and function -Be able to explain how enzymes are able to affect reaction rate enhancement -Be able to articulate and apply what the enzyme parameters of KM, Vmax, kcat and kcat/KM tell us about an enzyme -Be able to describe the interactions of biomolecules both quantitatively and qualitatively (in many cases, including mechanistic details) -Be able to understand the flow of metabolic intermediates through a pathway and communicate information about metabolic pathways using diagrams -Be able to describe multiple experimental methods used in biochemistry, interpret data from these methods to form conclusions, and develop a testable hypothesis to answer a question -Be able to summarize and analyse primary literature and data, and apply gathered information to new situations -Increase problem solving skills such as: critical thinking, data analysis, graphical analysis -Increase process skills such as: communication of scientific concepts and experimental results, group dynamics and teamwork, management and self-assessment -Develop a community of active learners who are intentional about their educational choices Course Materials: Calculator Emphasis on reinforcing skills with software --> << VMD (with NAMS), GROMACS, VOTCA, Desmond, UCSF Chimera, Molsoft, CCPN, RedMD + RedMDStream >> << BLAST, Unipro UGENE, Bioclipse, Staden Package, Bioconductor >> << EMBOSS + JEMBOSS + Pise + wEMBOSS + EMBOSS-Explorer >> Typical Texts --> Nelson DL and MM Cox. Lehninger Principles of Biochemistry (5th edition). (“Lehninger”) Loertscher J and V Minderhout. Foundations of Biochemistry (3rd edition). (“FOBC”) Additional --> Blast protein databases, align protein sequences, build protein homology models, and evaluate the quality of these models Lab Manual examples --> Lasseter, B. F. (2020). Biochemistry in the Lab: A Manual for Undergraduates. CRC Press Related to week 6: Edwards, P., Zhang, C., Zhang, B. et al. Smartphone based optical spectrometer for diffusive reflectance spectroscopic measurement of hemoglobin. Sci Rep 7, 12224 (2017). Course Overview --> You will frequently be given initial assignments to work on as an individual before class. These assignments must be ready at the start of class – your preparation will form part of your weekly participation grade. During our class meeting time, you will frequently function as a member of a Learning Team, developing and examining chemistry concepts as a unit. Your team effort and participation is part of your weekly participation grade. The team responses to a few Key Questions on each in-class activity will be evaluated for strength of concept and effective communication of the concept. The team will also strategize on ways to improve teamwork and team products. These responses will also form part of your weekly participation grade. Application exercises will be assigned for each activity. Together with problems from the text, they will form your weekly problem set that will be collected and graded for each individual. These homework problems and exercises are important to your success in the course. Actively working these homework problems is essential for your understanding of the material, as they bring your concept development full circle. The questions will be drawn from lectures, in-class activities, problem sets and discussions, as well as relevant primary literature that you may not have been previously assigned. The purpose of doing biochemistry is to gain experience in experimental methods that you’ll be reading about throughout the semester. Attendance on your scheduled lab day is expected. Software activities concerning biochemistry will accompany labs. Software activities concerning biochemistry will accompany labs as pre-lab development or post simulations. Grading --> Team Participation Problem Sets/Other Laboratory 2 Midterm Exams Final Exam Lecture Outline --> Week 1 Introduction to Biochemistry Week 2 Intermolecular forces and water. Amino acids and peptide bonds Week 3 Protein Folding Week 4 Working with proteins Week 5 Enzyme catalysis. Enzyme Kinetics Week 6 Enzyme inhibition. Hemoglobin Week 7 Exam 1; Carbohydrates Week 8 Glycobiology Week 9 Lipids and membranes. Transport across membranes Week 10 Signal transduction. Metabolism overview Week 11 Glycolysis. Glycolysis regulation and related pathways Week 12 Glycogen metabolism and gluconeogenesis. Citric Acid Cycle Week 13 Electron Transport Chain / Oxidative Phosphorylation; Exam 2 Week 14 Lipid metabolism. Nucleotides and nucleic acids Week 15 Nucleic acids structure and function Week 16 Final Exam Prerequisite: General Biology I. General Chemistry I & II. Co-requisite or Prereq: Organic Chemistry I Food Chemistry Water, carbohydrates, lipids, proteins, vitamins, and minerals in foods; biochemical and functional properties, enzymes, food additives (emulsifiers, pigments, colours, flavours, preservatives, and sweeteners) and texture as related to properties in food systems and during processing. Students will be able to identify the structure of food constituents, relate this structure to the constituents’ function and describe the constituents’ roll in respect to food quality, nutrition, safety, processing, etc. Students will also be able to differentiate chemical interactions, reactions of food components, their effect on sensory, nutritional and functional properties of foods, and how processing influences these reactions. The student will be able to explain how environmental factors such as temperature, pH, ionic characteristics and strength, bonding, light, etc. effect chemical changes in food systems and be able to adjust these conditions to improve or minimize chemical and biochemical deterioration of food systems. Finally, the student will be able to integrate chemistry and biochemistry principles into real-world food science and nutritional problems. Typical text: Food Chemistry, 4th Edition. 2008. S. Damodaran, K.L. Parkin, O.R. Fennema Eds. CRC Press Supplemental Reading: Introductory Food Chemistry, 2013. John Brady, Cornell University Press, New York. Typical Texts for Labs: The Food Chemistry Laboratory: A Manual for Experimental Foods, Dietetics, and food Scientists, Second Edition (Contemporary Food Science), CRC Press Food Chemistry: A Laboratory Manual. John Wiley & Sons, by Dennis, D. Miller. A total of three (3) exams will be administered over the course of the semester during the lecture period. There is no comprehensive final for this class. Each exam will be worth 13% of the final grade. The exams will be taken in “Blackboard” and you must have the Lockdown Browser downloaded onto your laptop prior to the first exam. NOTE: lab activities will run for 15 weeks; particulary for experiment 9 to acquire good data. Else, such additional time can serve as makeup for cancelled days or emergencies. Evaluation Method --> All assignments and answers on exams will be expected to be of professional quality. Laboratory reports are due generally two weeks after the lab exercise or as noted on the lab syllabus. No late assignments will be accepted without prior approval from the instructor. 3 Exams 39% Attendance and participation (lecture) 11% Laboratory 50% Course Outline: WEEK 1 (Chapter 2) Introduction. Review. Water. Water activity WEEK 2 (chapter 13, Chapter 3) Gels, emulsions, foams. Carbs intro. WEEK 3 (Chapter 3) Carbs: Starch. Other Carbs. WEEK 4 (Chapter 14, Chapter 4) Browning Reactions. Lipid components EXAM 1 WEEK 5 (Chapter 4) Review of lipid components. Lipid properties. Lipid process, functionality WEEK 6 (Chapter 4) Lipid deterioration WEEK 7 (Chapter 5) Amino acids, protein structure. Protein denaturation & functionality WEEK 8 (Chapters 5, 15, 16) Protein processing & modification. Milk & meat proteins EXAM 2 WEEK 9 (Chapter 6) Enzymes WEEK 10 (Chapter 7, Chapter 8) Vitamins. Minerals WEEK 11 (Chapters 9, 10, 11) Pigments and colorants. Flavors. Additives WEEK 12 (Chapters 11, 12, 17) Additives-sweeteners & fat replacers. Bioactive compounds. Plants EXAM 3 LABS --> First of all, food chemistry experiments very often do not work out as we planned. Chemicals are not always pure, the conditions are not extraordinarily controlled, and you could not reasonably be expected to get a “right” or “perfect” answer. Else, something is wrong with the way whatever works. In food chemistry we often have poorly characterized starting materials, food ingredients, and many reactions occurring in parallel under non-ideal conditions. Unsurprisingly the data we get is often noisy and hard to interpret. Wherever you go in life you will be trying to make difficult business decisions based on poor data. Developing these analytical skills in this this class will certainly benefit you as a manager in the food industry. Students should be able to: 1. Recognize the important reactions in food chemistry and their consequences. 2. Be familiar with methods to measure these reactions. 3. Be capable of reporting their results in an appropriate format. 4. Be capable of designing and conducting an experiment to understand a simple food chemistry problem. Lab Scoring --> Pre lab questions (12 labs x 20 points) Laboratory Participation (12 labs x 10 points) Laboratory Reports (9-10 reports x 25 points) Laboratory Notebooks (9-10 labs x 5 points) Note: each lab’s duration will be 1 week (but special case is experiment 9). Experiment 1 Physical Properties of Foods: water activity, specific gravity, viscosity and refractive index Experiment 2 Dispersions of matter: solutions, emulsions, and foams Experiment 3 Ice crystal formation Experiment 4 Carbohydrates: reducing sugars, starch morphology, and gelatinization Experiment 5 Lipid characteristics Experiment 6 Proteins: qualitative and quantitative analysis Experiment 7 Proteins: Maillard browning, effect of heat Experiment 8 Enzymatic browning Experiment 9 Fermentation: concern will be using different extracted fruit juices towards the most important phase in wine making (being fermentation). A clearly designed fermentation system will be developed and constructed. Fermentation system will have the following elements w.r.t. time: Means of determining carbon dioxide content in atmosphere Means of determining oxygen Pressure sensing Means to extract samples at different designated periods (hopefully not compromising process) Temperature sensing w.r.t. time Verification of “sum of all parts” at final stage and explanation for any possible discrepancy Will have 2-3 different types of fruit extractions Comprehensive knowledge of composition of fruit extract Average Sugar content level (accounting for different types) For the fermentation agents there will be three circumstances Without any added, sugar, water and yeast Added sugar and water Adding yeast solely Adding yeast, sugar and water For such fermentation agents type and quantity must be known. Namely, type of sugar (or honey), scientific identification of yeast type. As well, amounts to be added. Note: different benign bacteria may also come into play with a type of fermentation that’s unique to fermentation from yeast. Based on all such prior data detailed description of of metabolic processes will be acquired, which will emanate detailed biochemical processes along with the stoichiometry. Determination of microbial ecology at different stages. What type of alcohol will be produced? Can chemical process be developed analytically to give an instantaneous mathematical model for alcohol production? Determination of alcohol content and other by-products (different acids and glycerol) at different stages. Determination of ecology at end date. Note: temperature studies, and studies among various added yeast and added sugar agents may or may not fit time schedule. Note: fermentation towards yogurt can also be done as alternative or compliment, but with appropriate agents, environment construction, analysis etc. Software of interest R + R Studio Excel COCO (+ ChemSep), DWSIM (+ ChemSep) << Combase (Predictor and Modelling Toolbox) with MRV, USDA Pathogen Modeling Program, EPA Virulo >> Note: data modelling and data analysis expected (both deterministic and statistical). Experiment 10 Food flavours and precursors Experiment 11 PART A (ripeness) Das, A. et al. (2016). Ultra-Portable, Wireless Smartphone Spectrometer for Rapid, Non-Destructive Testing of Fruit Ripeness. Sci Rep 6, 32504 Note: not interested in the additive manufacturing part, rather assembling primitive prototypes out of the components to implement. Note: generally use fruits attainable in your environment as substitutes. Side component 1: It’s important to characterise what type of molecules, polymers, etc. are distinctively prevalent for ripeness (for respective fruit). Considerable variation in freshness, say, groups consisting of consumable U were stored (G °C, I% RH) for 0, 2, 4, 6, 8, 10, etc., etc. days. Apply different types of consumables. Side component 2: Experiments to conduct alongside side component 1 involving the same fruit speciments with 0, 2, 4, 6, 8, 10, etc., etc. days. Use fruits attainable in your environment as substitutes:-> Montero, T. M. et al (1996). Quality attributes of Strawberry During Ripening. Scientia Horticulturae, volume 65 Issue 4, pages 239 – 250 Ninio R. et al. (2003). Changes in Sugars, Acids, and Volatiles During Ripening of Koubo [Cereus peruvianus (L.) Miller] Fruits. J Agric Food Chem. 29; 51(3): pages 797-801 Anthon GE, LeStrange M, Barrett DM. (2011). Changes in pH, Acids, Sugars and Other Quality Parameters During Extended Vine Holding of Ripe Processing Tomatoes. J Sci Food Agric. 91(7): 1175-81. PART B (staleness) It’s important to characterise what type of molecules, polymers, etc. are distinctively prevalent for staleness (for respective consumable). Considerable variation in “age”, say, groups consisting of consumable X were stored (A °C, B% RH) for 0, 2, 4, 6, 8, 10, etc. etc. days. Apply different types of consumables. Note: generally use fruits attainable in your environment as substitutes. Note: there can be side component 2 like what is done in part A. Experiment 11 Integrative activity: Nutrient food party (pyramid challenge) Experiment 12 Integrative activity: Nutrient food party (pyramid challenge) Prerequisites: Biochemistry, Organic Chemistry I Genetic Engineering & Technology Course textbook: Molecular Biotechnology: principles and applications of recombinant DNAB.R. Glick and J.J. Pasternack, 3rd edition 2003 Course Grade Constitution --> 3 - 6 Assignments 3 Exams Course Outline --> Week 1 Introduction-Genetic Engineering and a tour of Genome Space DNA/RNA Processing and Gene Expression (a review): Week 2 Basic Techniques of Molecular Biology Restriction Endonucleases, Vectors, Cloning Week 3 Library Screens PCR, Sequencing Week 4 Exam Review and Exam Week 5 Prokaryotic Gene Expression Eukaryotic Gene Expression Genetic Engineering in Plants I Week 6 Genetic Engineering in Plants II: Applications Genetic Engineering in Plants III: the Next Generation of Rice Week 7 Sequence Analysis, Genome Structure Comparative Genomics Week 8 Functional Genomics: Analysis of Gene Expression Modifying Gene Expression and Cellular Function Week 9 Exam review and Exam Week 10 OPV and the emergence of AIDS The Origin of AIDS, con’t; vaccine intro; Edible vaccines Vaccine targets: malaria and ebola Week 11 Human Gene therapy I Human Gene therapy II: examples Week 12 Genetic engineering in animals I: Cloning Genetic engineering in animals II: Knockouts and Knockins, Inducible Gene Targeting Week 13 Genetic engineering in animals III: examples Genetic engineering in animals IV: xeno transplantation part a Genetic engineering in animals IV: xeno transplantation part b Week 14 Ethics and Patent Law Week 15 Exam Review and Exam Comparative Genomics An introduction to the concepts and experimental approaches used in microbial genomics. The laboratory will allow students to familiarize themselves with software routinely used in genomics and proteomics. Although the focus of the material is mainly on microbial genomes many of the approaches covered in the class can be applied to any system. An introduction into eukaryotic genomics is also provided. Literature: A Primer of Genome Science. Second Edition. Gibson and Muse. Sinauer Associates. Software --> << COPASI, Pathvisio + Cytoscape + KEGG >> RStudio and R packages for genome data development (BiocManager, ChemmineR, dPCP, MAPITR) Thodberg, M., & Sandelin, A. (2019). A step-by-step guide to analysing CAGE data using R/Bioconductor. F1000Research, 8, 886 Cao, Y., Charisi, A., Cheng, L. C., Jiang, T., & Girke, T. (2008). ChemmineR: a compound mining framework for R. Bioinformatics (Oxford, England), 24(15), 1733–1734 < manuals.bioinformatics.ucr.edu/home/R_BioCondManual > < cran.r-project.org/web/packages/BiocManager/vignettes/BiocManager.html > NOTE: will like to incorporate the R environment into labs as compliment to analyses. Assessment --> 3 – 4 Quizzes - 120 points Laboratory – 75 points (problem sets and software) Two exams - 100 points each. Final lab project - 50 points Group Projects - 75 Labs --> Lab reports are due ONE WEEK after the scheduled lab time. Group Projects --> 1. Students will assemble, annotate and describe a mock genome project using public and/or simulated sequence data. 2. Genome confirmation of various samples (from both animalia and plantae) for DNA sequencing the lab. Student groups with collect samples of at least 3 elements of animalia, and at least 3 elements of plantae. Will have lab DNA sequencing activities towards identification of genomes; identify possible using genetic markers to compare with databases. For animalia samples preference to be less sophisticated organisms, say, small genomes due to time constraints. NOTE: for the microbiology students lab methods will come from the following for microbial samples L. Barth Reller, Melvin P. Weinstein, Cathy A. Petti (2007). Detection and Identification of Microorganisms by Gene Amplification and Sequencing, Clinical Infectious Diseases, Volume 44, Issue 8, Pages 1108–1114 Fraser, C., Eisen, J. & Salzberg, S. (2000). Microbial Genome Sequencing. Nature 406, 799–803 C. Bertelli, G. Greub. (2013). Rapid Bacterial Genome Sequencing: Methods and Applications in Clinical Microbiology. Clinical Microbiology and Infection, Volume 19, Issue 9, Pages 803-813 Lasken, R. S., & McLean, J. S. (2014). Recent Advances in Genomic DNA Sequencing of Microbial Species from Single Cells. Nature Reviews. Genetics, 15(9), 577–584 Course Outline --> Week (1) Introduction to Genomics Microbial Genomes/Microbial databases Week 1 Lab – Introduction to lab/NCBI Week (2) Genomic webtools Sequencing and Assembly Week 2 Lab – Exploring web based tools for bioinformatics Week (3) Searching databases for homologs Tools for monitoring genome-wide gene expression Week 3 Lab – Sequence assembly Week (4) DNA microarrays DNA microarrays Week 4 Lab – BLAST & PSI-BLAST DNA microarraysProteomics Week (5) Structural Genomics Genome scale protein/protein interactions Week 5 Lab – DNA Microarrays/ Image analysis/data Week (6) High throughput genetics Comparative Genomic Week 6 Lab – Proteomics Week 7 Lab – ORF finder/genome annotation Week (9) Annotation Project/Exam Review of past exam Phylogeny of life Week 9 Lab – Lateral Gene Transfer Week (10) Molecular evolution and gene transfer Sequence alignment and phylogenetic analysis Week 10 Lab – Phylogeny Week (11) Systems Biology Genome based diagnostics Week 11 Lab – Begin Annotation project Week (12) Phylogenetic analysis (continued) April 7 – Metagenomics Week 12 Lab – Codon Bias Week (13) Eukaryotic Genomes Human Genome Project Week 13 Lab – Human Genome Project Week (14)SNPs Week 14 Lab – Annotation Project Week (15) Organellar Genomes Review Week 15 Lab – Annotation Project Prerequisites: Biochemistry, Organic Chemistry I, Genetic Engineering & Technology Molecular Biology I This Molecular Biology course is designed to give a good background in current Molecular Biology, which should allow for easy continuation to graduate or professional school courses. The major themes are Eukaryotic and Prokaryotic DNA replication, Chromosomal structure and function and Gene structure and function. Students will learn from current papers in the scientific literature, and will be expected to use concepts developed in the course in class, in the laboratory and in exams. Molecular Biology is fundamental to the study of all living things. It describes, in its most basic form, the mechanisms of how organisms live, reproduce and evolve. It is basic to much of modern Biology, no matter what the field of study. The purpose of this semester in Molecular Biology is to familiarize the student with those concepts that are basic to the functioning of prokaryotic and eukaryotic cells. Lecture is the foundation of the course. Laboratories will not always coincide with the lecture topics. The student is responsible for assignments that add to the lecture and lab material. The student is encouraged to seek out related materials that are available, such as scientific journals (e.g. Cell, Nature, Scientific American), newspapers, magazines and television programs (e.g. channels 12 and 52) that relate to course topics. Lecture notes will be published on the internet at my home page before the given lecture. There are three basic concepts in this course - the replication of DNA; the structure and function of chromosomes; and the structure and functioning of genes. They will be organized as indicated below. Students will reinforced with Molecular Biology laboratory techniques (DNA isolation and purification, recombinant DNA synthesis and cloning, gene detection, PCR and Southern and Western Blotting), which will be used to expand the student's appreciation and knowledge of the lecture material. The lectures cover Molecular Biology as a whole - the "central dogma" of Biology: DNA makes RNA which then makes protein. Out of this there arise three concepts - Eukaryotic and Prokaryotic DNA biosynthesis; Chromosomal structure and function (with associated proteins and functions); and Eukaryotic and Prokaryotic gene structure and function (mRNA, tRNA synthesis and function, including protein synthesis), and how they relate to basic biological and chemical concepts (such as the action of evolutionary processes on living things) learned in previous courses. In general, they should understand how our genomes function, including gene activation and deactivation, RNA synthesis and protein biosynthesis and be able to use this knowledge in their work and in the laboratory. Overall, emphasized and reemphasized in the course, and illustrated by specific examples and laboratory experiments, are the ways in which the above topics are interconnected, and factors used in one way are recycled to be used in another. This leads to interconnectiveness amongst the various cellular functions, and allows for signaling and controls between them. These principles should allow them to establish a firm connection between this course and other aspects of biology and give a foundation for future Molecular Biology courses and/or a good appreciation of concepts needed to make reasoned choices in their everyday lives. Typical Text: Watson et. al. Molecular Biology of the Gene ed. 5 Typical Laboratory Manual Text: Human Molecular Biology Laboratory Manual - S. Surzycki The professor's evaluation of student participation in lecture and laboratory can be used to benefit hard working students and possibly enhance their grade if they are in a borderline position. The laboratory grade is based mainly on the laboratory paper (normal scientific format, aprox. 8 - 10 pages, with a bibliography and internal referencing), as well as the instructor's assessment of the student's activity for the entire laboratory. Some laboratory based questions will appear on exams, especially including the final exam. Grading: Exams -15% of final grade (x 3 exams): 45% Laboratory -25% of final grade Final Exam -30% of final grade Emphasis in Software Immersion and Skills Enforcement --> There are various software that will serve well to this course that further encourages a modern and profession environment, extending beyond memor based studies. Will make emphasis with practically and constructively implementing software alongside labs. Likely, one particular software will not have all the qualities on e is interest, however, out of the following sets choosing a max of 2-3 in usage will be constructive << VMD (with NAMS), GROMACS, VOTCA, Desmond, UCSF Chimera, Molsoft, CCPN, RedMD + RedMDStream >> << BLAST, Unipro UGENE, Bioclipse, Staden Package, Bioconductor >> << EMBOSS + JEMBOSS + Pise + wEMBOSS + EMBOSS-Explorer >> Lab Outline --> Chapter 7 - Determination of Human Telomere Length (pages 164 - 195) All activities in chapter 7 must be done Chapter 8 - RT-PCR of Human Genes (pages 196 - 214) All activities in chapter 8 must be done Course Outline --> SECTION ONE: DNA replication, repair and recombination Chapters 1 – 11 SECTION TWO: Chromosome structure and function, chromatin, prokaryotic operon structure and function Chapters 7 & 16 SECTION THREE: The eukaryotic operon structure and function, gene clusters, genes in organelle Chapters 2, 3, 17 & 18 SECTION FOUR: Ribosomes, protein biosynthesis and transportation, eukaryotic and prokaryotic viruses, genetic engineering Chapters 14 & 16, 17, 13 LAB REPORT DUE & FINAL EXAM Prerequisites: Cell Biology, Organic Chemistry I Molecular Biology II Molecular Biology is a wide term encompassing two often complementary fields of study: a) laboratory and computer-based tools that can be used to study gene and genome identity and function (“molecular tools”), and b) the underlying fundamental structure of DNA and RNA. In this class there will be about a 50:50 split between focus on molecular tools (techniques) on the one hand, and the structure and function of DNA and RNA on the other hand. Proteins are often the focus of Biochemistry classes. Molecular Biology stresses the application of advanced molecular tools in the lab, and during analysis of scientific data presented in primary literature, in addition to covering genetic topics in more detail than was done in previous classes. The major expectations of students are : • To be become familiar with molecular techniques. • Understand the use of these techniques in the discovery of DNA and RNA metabolism and function. • Become more proficient at reading and critiquing primary literature. • Become familiar with commonly used laboratory techniques in the lab during an allsemester long research project. • Emphasis is not on memorization of the details of the molecular machinery of the cell. Instead, it is on developing skills to apply the learned techniques to the understanding of scientific discovery (data interpretation), as well as to suggest ways to study the function of molecules (experimental design). Molecular research is impossible to conduct in set 4-hour increments once a week. Typical Textbook/Readings: • Burton Tropp: Molecular Biology, 4th edition, 2012 Parts of some chapters will be used in this book in lecture, and book will be a good resource for looking up details, reading ahead or after class. Emphasis in Software Immersion and Skills Enforcement --> There are various software that will serve well to this course that further encourages a modern and profession environment, extending beyond memor based studies. Will make emphasis with practically and constructively implementing software alongside labs. Likely, one particular software will not have all the qualities on e is interest, however, out of the following sets choosing a max of 2-3 in usage will be constructive << VMD (with NAMS), GROMACS, VOTCA, Desmond, UCSF Chimera, Molsoft, CCPN, RedMD + RedMDStream >> << BLAST, Unipro UGENE, Bioclipse, Staden Package, Bioconductor >> << EMBOSS + JEMBOSS + Pise + wEMBOSS + EMBOSS-Explorer >> Grading --> 2 Midterm exams (each 70 points) 140 points 5 Quizzes (4x10 points each, quiz 5 =20 points) 60 points 1 Research paper (lab write-up) 40 points Lecture participation 20 points Carefulness in lab and preparation for labs 20 points Lab prelabs/postlabs ~30 points 3 Paper discussion prep and participation (4x20 points + 2x10 points) 100 points LABS --> It’s important to keep a neat and bound notebook for the lab, but you do not need to buy an expensive lab notebook. At the end of the semester you will be required to turn in a research paper describing the work you did on the lab project and put it in context of a greater scientific question. Only one lab report/paper will be handed in for the semester. This report reflects multiple weeks of work. Therefore make sure to collect gel photos, instrument readings, microarray and RNA-seq data analyses, so that you have all the files you need for your final paper. While all class and lab assignments have to be written individually unless specified differently, the final lab report can be written collaboratively with your lab partner, or individually if you prefer. Preparation for labs: Labs in this class are very expensive and it is of great importance that you come prepared to lab. In the past I have simply relied on suggesting that everyone read the manual before lab. However, it only takes one un- or underprepared person to make an experiment fail – often for more students than just that one person. So I have decided that some form of enforcement of the preparation requirement is needed and have reverted to prelab assignments, which test your level of preparedness. In addition there is now a grade for “carefeulness in lab”. This grade is based on whether you are prepared for lab or excessively ask unnecessary questions that you could have answered yourself by reading the manual. I do encourage asking questions, but I also encourage self reliance and careful attention to detail. Not every experimental failure is due to operator error. Such failed experiments are common and will not influence your lab grade negatively. Again, software mentioned earlier will accompany labs. Outline Week 1: Nucleic Acid Structure, Genome Organisation Week 2: RNA techniques (hybridization, reporters) RNA techniques (qPCR) DNA sequencing methods (Sanger) DNA sequencing methods (whole genome approach) Lab1: Microarray analysis - RNA Extraction Week 3: QUIZ 1: RNA techniques DNA sequencing methods (whole genome approach) Paper Discussion 1 Lab1: Microarray analysis c - DNA production Week 4: Gene mapping, map based cloning Human genome variation, the concept of “race” Lab1: Microarray analysis - Slide hybridization Week 5 Paper Discussion 2 - Human genome variation DNA Damage Quiz 3 (mapping/cloning) Lab1: Microarray analysis Statistics of microarray analysis Slide analysis: first part in lab. �� Finish slide analysis/statistics on your own time after all slides are pre-analyzed after [whenever] Week 6: DNA repair, Technique: EMSA (for paper 1) Paper Discussion 3 (DNA repair) Lab 2: RNA-seq analysis - Computer workshop uisng iPlant tools (or by software provided) Week 7: Recombination Lab 2: RNA-seq analysis - Analysis of RNA-seq data from week 1, and comparison with array data Week 8: Transposons Paper Discussion 4 (Recombination) Lab 3: Genetic marker analysis Sequence analysis using Genome Browser Primer design CAPS search Week 9: Eukaryotic transcriptional regulation Lab 3: Genetic marker analysis - DNA extraction, PCR set up Week 10: Epigenetics (technique: Immunoprecipitation) Paper Discussion 5 (Epigenetics ) Lab 3: Genetic marker analysis CAPS digest gel analysis (on your own) Lab 4: RNAi cloning - PCR of insert Week 11: QUIZ 4: The transcription unit RNAi Lab 4: RNAi cloning PCR clean-up and cloning reaction Transformation (on your own) Week 12: Paper Discussion 6 (RNAi) Lab 4: RNAi cloning - Finish up from week 11 Week 13: Splicing Agrobacterium and gene transformation Lab 4: RNAi cloning Colony PCR of cloned insert Glycerol stocks and sequencing of positive clones Week 14: Agrobacterium and gene transformation QUIZ 5: (molecular techniques) Lab 4: RNAi cloning Finish up from week 13 Final Exam Lab report due Prerequisites: Genetic Engineering & Technology, Molecular Biology I

Metabolism: Selected topics in metabolic pathways associated with carbohydrates, proteins, nucleic acids and lipid metabolism. This will include biosynthesis and degradation, cellular function, and their regulation and their physiological relevance. Additional topics will include hormones signalling pathways; cell signalling pathways and their metabolic roles and regulation. Emphasis will be given on the physiological relevance on different metabolic pathways including various clinical correlations. Direct examples from current literature will be given on a regular basis. Students who have successfully completed this course will be having thorough understanding on various metabolic pathways and their regulation and impact on physiological function and human health. Student should have fundamental knowledge on cell signalling and their regulatory mechanism. Emphasis will be given towards human health and disease correlation. Typical Text: Biochemistry with Clinical Correlations by Thomas M Devlin, 7 th Edition. Please note that additional study materials will be taken directly from current literatures and other resources. BIOCHEMICAL SOFTWARE --> Concerning particular topics and biochemical processes students will investigate with choice(s) out of the mentioned software below. Will have extensive observation and description of properties, characteristics of the processes, bonds, etc. in terms of organic chemistry and biochemistry. Each software activity goes along with a report. Multiple tasks given to each student (group). MUST connect with predominant or modern research, hence references from journal articles, etc. Each report to be 5-12 pages --> << VMD (with NAMS), GROMACS, VOTCA, Desmond, UCSF Chimera, Molsoft, CCPN, RedMD + RedMDStream >> << BLAST, Unipro UGENE, Bioclipse, Staden Package, Bioconductor >> << EMBOSS + JEMBOSS + Pise + wEMBOSS + EMBOSS-Explorer >> ESSENTIALS --> << COPASI, Pathvisio + Cytoscape + KEGG >> << Bioconductor >> Grading: Homework Assignments/quizzes 20% Exam 1 10% Exam 2 10% Exam 3 10% Software projects 25% Final Examination 25% NOTE: homework assignments concern typical problems and software practice. Course Outline: PART 1: Structure and properties of different biomolecules organelles A. Amino-acids and protein; Protein domains, post-translational modification; Protein trafficking, Protein degradation and turnover B. Nucleic acids C. Lipids, membranes and transport D. Carbohydrates E. Mitochondrial function PARTII: Signal transductions and metabolism with clinical correlations A. Cofactors and vitamins B. Fundamentals of signal transduction C. Bioenergetics and Oxidative metabolism D. Carbohydrate metabolism E. Lipid metabolism F. Amino acid metabolism G. Nucleic acids metabolism PART III: Biochemistry of hormones and nutrients A. Hormones and hormonal cascades B. Peptide hormones and amino-acid derived hormones and signaling C. Steroid hormones and signaling D. Basic nutritional constituents E. Clinical correlations PART IV: Gene regulation, epigenetics and human disease A. Chromatin remodeling and transcription through chromatin B. Histone modification and histone code hypothesis C. Epigenetic mechanism of gene activation and silencing Prerequisites: Biochemistry, Calculus II Molecular Control of Metabolism and Metabolic Disease: Examination of various physiological states and how they affect metabolic pathways. Discussion of a number of special topics related to the unique roles of various tissues and to metabolic pathways in disease states, including adipocyte biology, beta-cell biology, epigenetics, inflammation, and aging related diseases. Goals: -Understand the adjustments in fuel utilization and in the regulation of metabolic pathways required by mammalian fast-feed cycles. -Examine how various physiological states affect metabolic pathways. -Discuss the unique roles of various tissues and metabolic pathways in disease states, including diabetes, cancer, inflammation, and age-related disease processes. -Synthesize knowledge and use insight to better understand the molecular control of metabolism and metabolic disease. Grade: Course Exercises 10% Quizzes 15% Software projects 45% 2-3 Exams 30% Prototypical text: Textbook of Biochemistry with Clinical Correlations, Thomas M. Devlin BIOCHEMICAL SOFTWARE --> Concerning particular topics, bonds and biochemical processes related to metabolism. Will have extensive observation and description of properties, characteristics of the processes, mechanisms, outputs, etc. in terms of organic chemistry and biochemistry. Software activity goes along with the respective report. There will be numerous cases given to students (in groups and individually). MUST connect with predominant or modern research, hence some references from journal articles, etc. --> << VMD (with NAMS), GROMACS, VOTCA, Desmond, UCSF Chimera, Molsoft, CCPN, RedMD + RedMDStream >> << BLAST, Unipro UGENE, Bioclipse, Staden Package, Bioconductor >> << EMBOSS + JEMBOSS + Pise + wEMBOSS + EMBOSS-Explorer >> ESSENTIALS --> << COPASI, Pathvisio + Cytoscape + KEGG >> << Micro-Manager Open Source Microscopy software with ImageJ, JoVE (video journals), UIUC-Virtual Microscope >> << Bioconductor >> SIMULATION LABS --> Conventional molecular simulations play a significant role in understanding the molecular mechanisms underlying metabolic diseases. These simulations provide insights into the interactions between biological molecules, their dynamics, and structural changes. Applications of conventional molecular simulations in the context of metabolic diseases that will be pursued (where order may change to suit course progression): 1. Carbohydrate Metabolism & Carbohydrate-response element-binding protein. 2. ChREBP tasks 3.Drug Discovery and Development -- Application: Molecular simulations are used to model the interactions between small molecules (drugs) and target proteins involved in metabolic pathways. This aids in predicting binding affinities, understanding drug-receptor interactions, and optimizing drug candidates for the treatment of metabolic diseases such as diabetes and obesity. 4.Protein-Ligand Interactions -- Application: Simulations can elucidate the dynamic behavior of enzyme-substrate or receptor-ligand interactions involved in metabolic processes. This information is crucial for understanding the molecular basis of metabolic diseases and designing targeted therapies. 5.Protein Conformational Changes -- Application: Metabolic diseases are often associated with changes in protein conformations. Molecular dynamics simulations can provide insights into how proteins change their shapes over time, helping to understand the structural basis of diseases and identify potential therapeutic targets. 6.Lipid-Protein Interactions -- Application: Simulations can explore the interactions between lipids and proteins, particularly in the context of diseases like atherosclerosis. Understanding lipid-protein interactions helps in studying the formation of lipid plaques and developing strategies to prevent or treat cardiovascular diseases. 7.Metabolite Binding and Recognition -- Application: Molecular simulations can be employed to study how metabolites interact with proteins, receptors, or enzymes. This is relevant for understanding the regulatory mechanisms in metabolic pathways and identifying potential targets for intervention. 8.Protein Folding and Misfolding -- Application: Simulations can shed light on the folding pathways of proteins involved in metabolic processes. Aberrant protein folding and misfolding can lead to diseases like amyloidosis, and simulations help in understanding these processes at the molecular level. Transport Processes -- Application: Simulations can be used to study the transport of molecules across biological membranes, such as glucose transport in diabetes. Understanding the dynamics of transporters aids in developing strategies to regulate metabolic processes. 9.Enzyme Catalysis-- Application: Molecular simulations provide insights into the catalytic mechanisms of enzymes involved in metabolic pathways. Understanding enzyme kinetics and reaction mechanisms is crucial for developing interventions in metabolic diseases. 10.Structural Dynamics of Cellular Components -- Application: Simulations can explore the dynamics of cellular components, including organelles and membranes, providing a comprehensive view of how cellular structures contribute to metabolic processes and how disruptions can lead to diseases. COURSE OUTLINE --> A. INTERMEDIARY METABOLISM --Course Introduction & Carbohydrate Metabolism --Carbohydrate Metabolism --Carbohydrate Metabolism & Carbohydrate-response element-binding protein B. ChREBP --Fatty Acid to Glucose? Pyruvate Metabolism, Steady-States --Ketone Body Metabolism & b-oxidation --TCA Cycle & Carbonyl Chemistry --Glycogen Metabolism & Gluconeogenesis (Anderson/Rhoads) --Lipogenesis & Lipoprotein Metabolism --Cholesterol Metabolism C. MITOCHONDRAL METABOLISM --Mitochondrial metabolism --Mitochondrial metabolism --Mitochondrial metabolism D. METABOLIC FLEXIBILITY --The Unfolded Protein Response & Autophagy --Cycles, shuttles, and shunts --Metabolic signaling; primary & secondary messengers --GL/FFA cycle, hormonal regulation of lipolysis, lipid droplet biology --b-cell biology and diabetes E. SIGNALLING AND REGULATION --Insulin signaling & insulin resistance --mTor & Regulatory Nodes --Cold exposure and sympathetic nervous system metabolism --Cold exposure and sympathetic nervous system metabolism --Cancer Metabolism Augmented with the following: Ralph J. DeBerardinis, Navdeep S. Chandel, Fundamentals of Cancer Metabolism.Sci. Adv.2,e1600200(2016). Pavlova NN, Thompson CB. The Emerging Hallmarks of Cancer Metabolism. Cell Metab. 2016 Jan 12;23(1):27-47 F. INTEGRATED METABOLISM --Exercise, aging, & metabolic disease --Hypothalamic control of metabolism and circadian rhythms --Epigenetics --Alzheimer’s and other degenerative diseases --Inflammation Prerequisites: Metabolism, Upper Level Standing Bioprocess Engineering: Introduction to biochemical and microbiological applications to commercial and engineering processes, including industrial fermentation, enzymology, ultrafiltration, food and pharmaceutical processing and resulting waste treatment. Enzyme kinetics, cell growth, energetics and mass transfer. The objective of the course is to introduce fundamental bioprocess engineering concepts often reserved for chemical engineers. Knowledge, resources and economics are seemingly perpetual factors that drive success. The emphasis will be application of the following core chemical engineering concepts to biological problems -- A. Material and heat balances-distributed throughout B. Reaction kinetics and reactor design Enzyme kinetics, fermentation kinetics, batch/fed-batch/continuous bioreactor, recycle, bioreactors-in-series, heterogeneous catalysis, biological wastewater treatment C. Transport Immobilized enzyme/cell reactor, biofilm reactor, mixing, oxygen mass transfer, sterilization, separation and product purification D. Thermodynamics Energy efficiency, yield E. System dynamics Steady-states, Metabolic network, bioreactor stability, mixed culture F. Applied mathematics - distributed throughout G. << Combase (Predictor and Modelling Toolbox) with MRV, USDA Pathogen Modeling Program, EPA Virulo >> H. Use of Process Simulators ASPEN (or cheaper substitute) BEST: Biochemical Engineering Simulation Technology. National Renewable Energy Laboratory 1996. NREL/MP-425-20548. Task Number IP443431 Use of Process Simulators COCO (+ ChemSep) or DWSIM (+ ChemSep) or ESMO Note: conventional lectures supplemented by in-class demonstrations of computer simulations and computer simulations assignments; possibly software such as ASPEN or COCO (+ ChemSep) or DWSIM (+ ChemSep) or ESMO will have relevance. Such software will help students gain a better feel or sense of meaningfulness/purpose for the topics, various models and operating parameters. Knowledge of R + RStudio will be beneficial. Expected primitives acquired from prerequisites to accompany A through G prior throughout course -- 1.Knowledge of relevant ODEs and general solutions 2.Ability to solve simple ODEs using explicit numerical methods 3.Working knowledge of RStudio along with a working knowledge of Excel. For R will likely incorporate biological & ecological packages if constructive 4.Ability to solve sets of linear and nonlinear algebraic equations numerically via CAS such as R + RStudio 5.Familiarity with matrix multiplication structure Priorities are not the whosoever in a mathematics department Ability with 2 by 2 matrices shows you know what you’re doing M by N matrices concern graphing calculators and R + RStudio Professionals don’t care about pig pen finesse on a board, but rather the purpose of the models; understand your priorities and real talent/ability. Course Text: Bioprocess Engineering, Basic Concepts, Michael L. Shuler and Fikret Kargi, Prentice Hall, 2001 Assisting Text (whenever deemed practical and malleable): John Villadsen, Jens Nielsen, and Gunnar Lidén. Bioreaction Engineering Principles, Third Edition, Springer Publishing, 2011. We will touch upon the issues of the balance between biotechnology's benefit to the society and profiteering, and the regulatory issues. Course Assessment: Homework 10% Computer simulation assignments 35% Structured and administered to construct and implement practical and sustainable simulations and crucial observations often encountered in Bioprocess Engineering Immersion and Retention Activities Labs 3 Midterm exams 30% Term Project 25% Note: labs with software tools use will accompany course topics extensively. Will develop simulation processes/projects relevant to topics. Each simulation project to accompany a specific set of course topics. Course Outline: -Biochemical & Bioprocess Engineering (Ch 1) -Biology & Biochemistry (Ch 2) -Enzyme Kinetics & Immobilization (Ch 3) -Genetics & Cellular Control Systems (Ch 4) -Genetic Engineering (Ch 8, 14) -Metabolism (Ch 5) -Stoichiometry (Ch 7) -Cell Growth Kinetics (Ch 6) -Bioreactor Design & Operation (Ch 9) -Scale-up, Heat/Mass Transfer, Instrumentation, Control (Ch 10) -Product Purification & Recovery (Ch 11) -Mixed Culture (Ch 16) Prerequisites: Genetic Engineering & Technology, Organic Chemistry I, Biochemistry, ODE, Upper Level Standing. Bioprocess Engineering Lab: Goals of Course --> 1. Understand the experimental and mathematical frameworks underlying the growth of biological organisms and the production of macro and small molecule products. 2. Analyse reaction stoichiometry for biochemical processes. 3. Evaluate different methods for producing biological molecules, including cell culture and protein expression systems. 4. Develop strategies for metabolic engineering of biological organisms, to manufacture useful chemicals. 5. Select and sequence purification processes for biological products. 6. Design and evaluate drug delivery pathways and tissue engineering methods. 7. Understand protein and cellular engineering approaches. Software Tools --> R + RStudio Excel << Combase (Predictor and Modelling Toolbox) with MRV, USDA Pathogen Modeling Program, EPA Virulo >> Use of Process Simulators ASPEN (or cheaper substitute) BEST: Biochemical Engineering Simulation Technology. National Renewable Energy Laboratory 1996. NREL/MP-425-20548. Task Number IP443431 COCO (+ ChemSep) or DWSIM (+ ChemSep) or ESMO Note: conventional lectures supplemented by in-class demonstrations of computer simulations and computer simulations assignments; possibly software such as ASPEN or COCO (+ ChemSep) or DWSIM (+ ChemSep) or ESMO will have relevance. Such software will help students gain a better feel or sense of meaningfulness/purpose for the topics, various models and operating parameters. Knowledge of R + RStudio will be beneficial. Expected primitives acquired from prerequisites to accompany A through G prior throughout course -- 1.Knowledge of relevant ODEs and general solutions 2.Ability to solve simple ODEs using explicit numerical methods 3.Working knowledge of RStudio along with a working knowledge of Excel. For R will likely incorporate biological & ecological packages if constructive 4.Ability to solve sets of linear and nonlinear algebraic equations numerically via CAS such as R + RStudio 5.Familiarity with matrix multiplication structure Priorties are not the whosoever in a mathematics department Ability with 2 by 2 matrices shows you know what you’re doing M by N matrices concern graphing calculators and R + RStudio Professionals don’t care about pig pen finesse on a board, but rather the purpose of the models; understand your priorites and real talent/ability. Course Text: TBD. Additionally, literature from prerequisite can assist well. Syllabus --> ---Introduction to Biochemical Engineering Historical background, Interdisciplinary approach, Integrated Bioprocess systems, Unit Operations in Bio-processes. ---Microbial Growth Kinetics Batch Culture Continuous Culture –Multistage systems, Feedback systems Fed Batch Culture –Variable volume, fixed volume, Cyclic. Applications. ---Design of Fermentor Introduction, Basic Functions, Body construction, Aeration and Agitation, Maintenance of aseptic conditions, Control of parameters, Valves and steam traps, Variants of fermentation vessels. ---Aeration and Agitation Introduction, Oxygen requirement in fermentations, Oxygen supply, Determination of K-La values, Fluid rheology, Factors affecting K-La values, Balance between oxygen demand and supply, Scale up and Scale down. ---Basic Outline of fermentation process and purification of fermentation products Introduction, Range of fermentation process, Components of fermentation process, Disruption of cells, Precipitation, Filtration, Centrifugation, Liquid-Liquid Extraction, Chromatography, Membrane processes, Drying, Crystallization. Laboratory Experiments --> Note: software tools use will accompany lab experiments extensively as precursor or pre-labs; assumed high knowledge and skills from prerequisite. Will develop (advance and extensive) simulation processes/projects relevant to labs. Each advance and extensive simulation project to accompany a specific set of labs. 1. Determination of Oxygen Transfer rate 2. Determination of K-La value 3. To obtain growth curve of bacteria under batch culture 4. To obtain growth curve of bacteria under fed batch culture 5. To carry out precipitation of protein 6. To perform column chromatography 7. To perform drying operation. 8. To perform crystallization operation Prerequisites: Bioprocess Engineering Drug Metabolism: The proposed course in Drug Metabolism is designed to provide the students an understanding of (i) the key role played by metabolic processes in the design and development of safe and efficacious therapeutic agents (ii) the relevant metabolic transformations and the enzymes (enzymology) responsible for these transformations (iii) the contemporary techniques in cell and molecular biology, chromatography, mass spectrometry, and spectroscopy used to study metabolic processes and the role of specific metabolic enzymes in the metabolism of drug molecules. Course to be instructed by industry professionals (scientists from pharmaceutical companies and faculty). Texts & Notes: TBA Tools --> << COPASI, Pathvisio + Cytoscape + KEGG >> << Bioconductor >> Assessment --> Group Assignments: 20% 4 Development phases 0.4 Report 0.5 Presentation 0.1 Lab: 20% 4 Exams: 60% Lab --> PART A OPTIONS The following articles will be applied to develop lab experimentation. It’s important that they are harmonic with lecturing Farrell, S and Hesketh, R. (2002). An Introduction to Drug Delivery for Chemical Engineers. Chemical Engineering Education http://users.rowan.edu/~hesketh/hesketh/cee%20drug%20delivery.pdf Farrell, S., Savelski, M., Hesketh, R. and Slater, C. S. (2006). Experiments in Drug Delivery for Undergraduate Engineering Students. American Society for Engineering Education Farrell, S. and Vernengo, J. (2012). A Controlled Drug-Delivery Experiment Using Alginate Beads. Chemical Engineering Education, v46 n2 p97-109 Farrell, S. et al (2013). An Experiment to Introduce pH-responsive Hydrogels for Controlled Drug Delivery: Mechanical Testing. 120th ASEE Annual Conference and Exposition Puperi, D. (2019). Extending an Alginate Drug Delivery Experiment to Teach Computational Modelling and Engineering Analysis to 1st Year Biomedical Engineering Students. Paper Presented at 2018 ASEE Gult-Southwest Section Annual Meeting, AT&T Executive Education and Conference Center, Austin, TX 78705 < https://peer.asee.org/31598 > Ranjan, A. and Jha, P.K. (2020). Experiments and Modelling of Controlled Release Behaviour of Commercial and Model Polymer-Drug Formulations using Dialysis Membrane Method. Drug Deliv. and Transl. Res. 10, 515–528. Werzer, O. et al (2019). Drug Release from Thin Films Encapsulated by a Temperature-Responsive Hydrogel. Soft Matter, 15, 1853-1859 PART B OPTIONS Note: for the following two subjects in particular, after analysis to pursue modelling and simulation of the delivery processes with software encountered in the biochemistry course and metabolism course. Vilar G, Tulla-Puche J, Albericio F. (2012). Polymers and Drug Delivery Systems. Curr Drug Deliv. 9(4): 367-94 Drug Delvery by Supramolecular Sesign Group Assignments --> For known authorized drugs in a given market, after medical profiling, student groups will pursue modelling and simulation of the delivery processes with software encountered in the biochemistry course and metabolism course. Includes ideal environments for optimal function, mechanisms, functional groups, activation sites, by-products, etc., etc., etc. Topics --> LECTURE 1 Introduction to Drug metabolism --Historical Perspective and General Principles --Drug metabolism as a mechanism for clearance of therapeutic agents; pharmacokinetic concepts, metabolic clearance, its role in the total clearance of drug molecules, Stereochemistry in Drug Metabolism general concepts, role in drug metabolism and pharmacokinetics, regulatory issues. Role of drug metabolism in the design and development of safe and efficacious therapeutic agents, regulatory issues. LECTURES 2-5 Chemistry of Metabolic Reactions --Oxidation --Reduction --Hydrolysis --Conjugation LECTURE 6 Biochemistry of Cytochrome P450 --Classification --Isozymes --Multiplicity and Substrate Specificity --Localisation --Variability LECTURES 7-8 Induction of Drug Metabolizing Enzymes --Mechanisms --in vitro models to asses induction --Clinical considerations/implications LECTURE 9 Intestinal Oxidative Metabolism --Intestinal cytochrome P450 enzymes --Role of intestinal cytochrome P450 enzymes in drug-drug interactions LECTURE 10 Phase I (non-P450) Enzymes --Oxidative --Reductive --Hydrolytic LECTURE 11 Inhibition of Drug Metabolizing Enzymes --Mechanisms --In vitro assessment --Clinical considerations/implications LECTURE 12 Phase II Enzymes --Introduction --Glutathione Transferases --Reaction and substrates --Physiological considerations --Expression and Regulation --Species and strain differences LECTURE 13 Glucuronosyl transferases and sulfotransferases: --Classification --Reactions and classes of substrates --Physiological considerations and cofactors --Expression and regulation --Species and strain differences LECTURE 14 In Vitro Model Systems for Transport --In vitro techniques to study drug transport --Transport models to elucidate and predict transporter-based drug interactions LECTURES 15-16 Hepatobiliary and Renal Disposition – Hepatic and Renal Transport --First Pass Effect --Mechanisms --Hepatic and renal clearance --Classes of drugs excreted --Pharmacological factors influencing biliary excretion of xenobiotics: methods for examining biliary and renal excretion enterohepatic recirculation and actors that influence enterohepatic cycling. --Transporter-based hepatic and renal toxicity LECTURE 17 Intestinal Transport and Transporters --Intestinal transport mechanisms --Absorptive and Barrier properties of intestinal epithelium --Absorptive and Secretory transporters --Uptake and efflux transporters --Transporter-based drug-drug interactions LECTURE 18 -20 Analytical Techniques for Studying Drug Metabolism --NMR --LC/MS --Stable isotopes --Radioisotopes LECTURES 21-22 Metabolism-based Drug Toxicity --Mechanisms of toxicity - reactive metabolites --Genotoxicity --In vitro systems to assess toxicity --Drug- and metabolite-induced hepatotoxicity --Implications in drug discovery/development LECTURES 23-25 Pharmacogenomics of Drug Metabolizing Enzymes and Transporters --Basic Concepts --Pharmacogenomics of Drug Metabolizing Enzymes and Transporters --Case studies and clinical implications --Regulatory impact LECTURE 26. Integration of Drug Metabolism/pharmacokinetic Function in Drug --Discovery and Development --Review of the DM/PK function within pharmaceutical R & D --DM/PK studies in drug discovery and development --Case histories LECTURE 27. Review and Key Learnings from the course Prerequisites: Organic Chemistry I, Biochemistry, Metabolism, Upper level Standing Protein Engineering: Course covers the principles, techniques, and applications of designing and modifying proteins for various purposes. Applications of interest include (but not limited to): vaccines, therapeutics, diagnostics, drugs, material science, industrial processes. Course outline dictates the types of applications and labs. Each lab will include software development as a precursor or pre-lab to the detailed labs throughout the term. Emphasis on reinforcing skills with software: << VMD (with NAMS), GROMACS, VOTCA, Desmond, UCSF Chimera, Molsoft, CCPN, RedMD + RedMDStream >> << BLAST, Unipro UGENE, Bioclipse, Staden Package, Bioconductor >> << EMBOSS + JEMBOSS + Pise + wEMBOSS + EMBOSS-Explorer >> << Bioinformatics tools. Note: could be R based >> ASSESSMENT --> Lab Quizzes 25% Labs Operations 50% Attendance Punctuality Behaviour Content/Substance Student Groups Projects 25% Attendance Punctuality Behaviour Content/Substance Presentations COURSE OUTLINE --> WEEK 1: Introduction to Protein Engineering Overview: Introduction to the field of protein engineering, historical context, and key principles. Topics: Importance of protein engineering, applications in biotechnology and medicine. WEEK 2: Protein Structure and Function Lectures: Review of protein structure and function. Lab Activity: Use bioinformatics tools to analyze protein structures and predict functional domains. WEEK 3-4: Rational Protein Design Lectures: Principles of rational protein design. Lab Activity: Design a protein variant using rational design principles and modeling tools. Prerequisites: WEEK 5-6: Directed Evolution Lectures: Overview of directed evolution techniques. Lab Activity: Perform a directed evolution experiment using a model protein target. WEEK 7-8: Enzyme Engineering Lectures: Engineering enzymes for enhanced catalytic activity and specificity. Lab Activity: Design and optimize an enzyme through directed evolution. WEEK 9-10: Antibody Engineering Lectures: Engineering antibodies for therapeutic applications. Lab Activity: Design antibody variants with improved affinity or altered effector functions. WEEK 11-12: Protein Expression and Purification Lectures: Strategies for efficient protein expression and purification. Lab Activity: Express and purify engineered proteins using different expression systems. WEEK 13: Computational Approaches in Protein Engineering Lectures: Introduction to computational tools for protein engineering. Lab Activity: Use computational methods to predict protein stability, binding sites, and design variants. WEEK 14-15: Protein-Protein Interaction Engineering Lectures: Strategies for modifying and engineering protein-protein interactions. Lab Activity: Design and analyze protein variants to alter or enhance protein-protein interactions. WEEK 16-18: Student Groups Research Projects Project Assignment: Students design and propose a protein engineering research project. Proposal Presentation: Students present their project proposals to the class for feedback. Lab Activities: Students execute their protein engineering research projects. Progress Reports: Periodic progress reports and discussions. Presentations: Students present their research projects to the class. Prerequisites: Calculus II, ODE, General Physics I, Organic Chemistry I, Genetic Engineering & Technology, Molecular Biology II, Senior Standing.

Note: augmenting curriculum of biological and biochemical sciences with the critical hands on research areas, starting from upper level sophomore students for “winter and “summer” semesters. Likely to be collaboration among constituents (of free will) under biology. FOR ACTIVITIES IN THE “SUMMER” AND WINTER” SESSIONS ALL PARTICIPATING STUDENTS, ASSISTING/ADVISING INSTRUCTORS AND PROFESSORS MUST BE OFFICIALLY RECOGNISED; REQUIRES BOTH CIVILIAN ID AND STUDENT/FACULTY ID FOR CONFIRMATION OF INDIVIDUAL. THERE WILL ALSO BE USE OF IDENTIFICATIONS FOR ACTIVITIES FOR RESPECTIVE SESSION. SECURITY AND NON-PARTICIPATING ADMINISTRATION WILL ONLY IDENTIFY RESPECTIVE ACTIVITY BY IDENTIFICATION CODE. SECURITY AND NON-PARTICIPATING ADMINISTRATION MUST NEVER KNOW WHAT ACTIVITIES IDENTIFICATION CODES IDENTIFY: < Alpha, Alpha, Alpha, Alpha > - < # # # # # > - < session > - < yyyy > Such biological sciences activities will also warrant criminal background check (CBC) in order to participate. Severely threshold may vary depending on administration. Administrators will provide dated letters of confirmation of thorough CBC to student affairs and other appropriate administration. Such may also include screening that’s parallel to customs & immigration processing where certain levels of criminal history warrants rejection. Email and physical letters with data. Such CBC protocol will not explicitly identify any particular titles or descriptions of any activity, rather, will only convey code as above. Innovation and technology being key, projects may not be confined to the mentioned two curriculum areas, if they are constructive, practical, economic, and appealing to progressive and developed society. For projects establish control (group, specimen, samples, etc.) whenever relevant. There will be a secure database archive for all participants and supervision constituents for respective activity chronologized. Activities will be classified. VARIOUS SOFTWARE AVAILABLE It may be the case some activities can be grouped and given a major title together; however, detailed descriptions will be required. Activities repeated can be added to transcripts upon successful completion. Repeated activities later on can be given a designation such as Advance “Name” I, Advance “Name” II. As well, particular repeated activities serve to towards developing true comprehension, competency and professionalism. Any media developed is not geared to pop culture and minority trends or stereotypes. Activities will be field classified. Particular activities of interest being stationary: 1. Transduction Lab Orchestrating the process and observing the results, namely the effectiveness or the intended quality or characteristic pursued in a bacterial or mammalian cell. Useful by-products would be cnstructive. Keep economic as much as possible. 2. Bacterial Conjugation reinforcement https://www.sas.upenn.edu/LabManuals/biol275/Table_of_Contents_files/16-BacterialConjugation.pdf Will incorporate competent use of microbial, viral, pathogen and EPA software from software portfolio. Can be compared with curve fitting of data, and regression modelling can also be done. 3. Polymerase Chain Reaction and common tactics involving the process (analysis and experimentation) -Operational Theory & Logistics and exponential amplification -Parameters that affect PCR -Denaturation -Annealing of primers to template DNA -Number of cycles -Experimentation: http://www2.southeastern.edu/Academics/Faculty/jtemple/486/experiment%203.pdf What role do each of the following play in PCR - dNTPs, taq polymerase, primers? If temperature rises above 94 C there’s chance of water evaporation. How is it prevented? What is the use of buffer in the reaction mixture? Police investigates a homicide. From crime scene they got hair samples and semen from the body. What could be done to identify the murderer? Note: interested in other types of DNA for PCR experimentation as well. Strawberry DNA as one example is easy to extract. -Simulation examples: Animated Tutorial 9.5 Polymerase Chain Reaction Simulation Fellermann, H. et al, The PCR Simulator: An On-line Application for Teaching Design of Experiments and the Polymerase Chain Reaction, bioRxiv 415042. Concerns a run through then testing of understanding with simulator. Succeed with actual processing regardless. -Actual lab processing version of simulation above to be done. 4. Cellular Signalling Svoboda, K. K., & Reenstra, W. R. (2002). Approaches to Studying Cellular Signaling: a Primer for Morphologists. The Anatomical record, 269(2), 123–139. 5. CRISPR A revolutionary new technology for genome editing that provides unheard-of ease, efficiency, and low cost. It’s now universal use in laboratories worldwide has led to subsequent breakthroughs in inherited disease, HIV, malaria, retinitis, and cancer. Pursuit towards adopting the technology for in-house experimentation. To focus on applications of CRISPR technology as a platform for [genome editing] and functional genomics. The activity will consist of lectures from experts in the field and a hands-on laboratory experience demonstrating CRISPR editing both in vitro and in vivo. Expert professional leadership will address topics in genome editing and CRISPR-Cas9 research, including basic and enhanced CRISPR methods, cellular repair mechanisms, regulation of gene expression, bioinformatics, applications to various organisms, and bioethics. TBD, will include: All protocols for lab works, rubric for grading lab report, major CRISPR publications, news articles and popular science CRISPR articles. Lap reports and participation with integrity are crucial towards any measure of real accomplishment. Constitution to advantage of biochemistry, cellular biology, molecular biology and microbiology software and tools mentioned. Pursue CRISPR design tools as well. -Acquisition Assay (operations sequence) Instruction: Welcome, Course Introduction, Lab Safety In Lab: Transformation of Cas1 and Casa2 plasmids, plating of bacteria, take initial sample Instruction: CRISPR immunity In Lab: Take additional samples, PCR of CRISPR locus, run agarose gel, pick colonies for overnight cultures Instruction: Structure and Function of Cas9 In Lab: miniprep cultures and send for sequencing Instruction: Genome Editing and DNA repair In Lab: Analyse sequencing results and present. -In Vitro Cleavage Assay Instruction: gRNA Design In Lab: PCR, Run agarose gel, Set up ivt overnight Instruction: Reducing Off-Target Effects In Lab: Purification, Run RNA gel to check product Instructor: CRISPR Application - Plants In Lab: in vitro cleavage assay Instruction: CRISPR Applications: Human Therapeutics In Lab: Presentation of results. Bioinformatics Practical - gRNA design -In Vivo Editing Instruction: CRISPR Applications: Bioenergy In Lab: Transformation of control RFP expression plasmid, Transformation of Cas9 gRNA RFP editing plasmid, Plate cells. Instruction: CRISPR Applications: Model Systems In Lab: Observe results, pick colonies, inoculate overnight cultures with and without selection. Instruction: CRISPR Ethics/ Policy In Lab: Plate cultures, Ethics discussion Instruction: CRISPR Ethics/ Policy In Lab: Observe results. Presentations of final project. The next phase will be designing and implementing experiments(s) to critique or validate the following: Gebre, M., Nomburg, J., L., and Gerwurz, B., E., CRISPR-Cas9 Genetic Analysis of Virus-Host Interactions, Viruses 2018 Jan 30; 10(2) Applying PCR to amplify CRISPR arrays and analyse spacer content for specifically targeted CRISPRs and for organisms with sufficient representation in public databases to design reliable PCR primers. 6. Immunoproteomics & Immunochemistry --Host and Viral Determination of Infection Outcome Consider common place viruses. How does the interaction between host and virus influence infection outcome and disease progression? What are the genetic immunological signatures of an effective host immune response against such viruses? Utilizing samples from well characterized cohorts. Samples to be assayed via sequencing, single-cell technologies and cellular immunology tests. Concerns means to inform vaccine design and future immune-therapy. --Design and implement experiment(s) to critique or validate the following: Falisse-Poirrier, N. et al, Advances in Immunoproteomics for Serological Characterization of Microbial Antigens, Journal of Microbiological Methods 67 (2006) 593–596 --For the following link provided design and implement experiments(s) of the model described for broad range detection of various viruses or bacteria (instead of Helicobacter Pylori): Haas, G., et al, Immunoproteomics of Helicobacter Pylori Infection and Relation to Gastric Disease, Proteomics 2002, 2, 313–324 --Design and implement experiment(s) to critique or validate the following: Israr, B., Kim, J., Anam, S., and Anjum, F., R., Lactic Acid Bacteria as Vectors: A Novel Approach for Mucosal Vaccine Delivery, J Clin Cell Immunol 2018, 9:2 --Design and implement experiment(s) to critique or validate the following: Shonyela, S., M. et al, New Progress Regarding the Use of Lactic Acid Bacteria as Live Delivery Vectors, Treatment of Diseases and Induction of Immune Responses in Different Host Species Focusing on Lactobacillus Species, J Prob Health 2017, 5:4 7. Biochemistry of anaesthetics and antiseptics Note: for the case of antiseptics treatment, treat accordingly for natural and synthesizingsources, and the associated automatic control. Note: much interest in the metabolic pathways Note: biochemical software will accompany development Modelling Simulations, reactions, chemical characteristics ---Phase 1 Comprehension of the terms hypoalgesia and hyperalgesia Comprehension of the biological automatic control regulation relevant involving organs, nociceptors, enzymes and pathways concerning involving anaesthetics/analgesics, endorphins, enkephalins, and dynorphins. Processes of consideration: Transmission Upwards (thalamus & distribution, reticular formation, amygdala) Referred Pain Gate theory Phantom Pain Identification of nociceptor types: thermal nociceptors, mechanical nociceptors, chemical nociceptors, polymodal nociceptors, silent (or sleeping). Identify in nociceptors the constituents or unique design that gives the special function. When there is significant damage to tissue, several chemicals are released into the area around the nociceptors. This develops into what is called the "inflammatory soup," an acidic mixture that stimulates and sensitizes the nociceptors into a state called hyperalgesia. Some of the chemicals involved: “Inflammatory soup” (biochemical mechanism, by-products and simulation) Prostaglandins released by damaged cells (biochemical mechanism, by-products and simulation) Potassium is released by damaged cells (biochemical mechanism, by-products and simulation) Serotonin is released by the blood platelets (biochemical mechanism, by-products and simulation) Bradykinin is released by blood plasma (biochemical mechanism, by-products and simulation) Histamine is released by mast cells (biochemical mechanism, by-products and simulation) “Substance P” (biochemical mechanism, by-products and simulation) Histamine (biochemical mechanism, by-products and simulation) Antihistamines and reaction with histamine (biochemical mechanism, by-products and simulation) Marijuana will be treated concerning point, region, conditions, etc. for beginning influence in the regulatory/nervous/endocrine system. Includes biochemical mechanism, by-products and simulation. There are tissues that contain nociceptors which do not lead to pain. In the lungs, for example, there are "pain receptors" which cause you to cough, but do not cause you to feel pain. Establish the biochemical process and operation in the regulatory/nervous/endocrine system that permits coughing rather than pain. There are some people born with a genetic inability to feel pain. It’s quite rare. Identify genes associated to pain stimulus. What is the genetic structuring for the inability to have the have stimulus mechanism? What isn’t being produced? NOTE: for recognition of substances various spectroscopy types will be employed and compared with databases. Extraction of anaesthetics/analgesics from saliva and other body areas. In laboratory environment, to observe how such anaesthetics/analgesics react with the following chemicals associated to pain (rate and by-products). Extraction of endorphins, enkephalins, and dynorphins if possible. Software provided to be used as simulation prediction, whereas lab activity to validate with other empirical observations. An elaborate and economic scheme for observation to be developed and administered; possibly includes rate of reaction, by-products (quantities if feasible). Reaction analysis (rate of reaction, by-products) of such opioids to be compared with extractions from saliva, as well to industrially synthesized treatments like aspirin, naproxen sodium, acetaminophen, ibuprofen, Vicodin (if feasible), oxycodone (if feasible), codeine (if feasible), and others. Automatic control descriptions for each; heroine is also possible. Then the reaction analysis of such natural and artificial substances can be compared with natural herbs such as chamomile, willow bark, turmeric, cloves, ginger (pain & inflammation), etc. Based on automatic control of pathways determine optimal means of administering herbal remedies and synthetics, respectively. Note; for herbal remedies the uniqueness of one particular herb “bio product” its optimal administering may or may not be the same as others; same goes for synthetics. Biochemical response with melatonin, adrenaline and dopamine. Establish definitively the respective function difference for such mentioned three unique to opioids, anaesthetics/analgesics. Concerned with exercise, fear & shock, aggression, and diabetes which includes automatic control descriptions for pathways. If diabetes is to be differentiated then, so be it. For melatonin, adrenaline and dopamine, respectively, identify the concerning point, region, conditions, etc. for beginning influence in the regulatory/nervous/endocrine system; concerned with respective biochemical mechanism and simulation as well. Extraction of melatonin, adrenaline and dopamine from the most feasible places. In laboratory environment, to observe how such anaesthetics/analgesics react with the following chemicals associated to chemicals in respective process (with by-products). NOTE: Trials and/or samples for the various laboratory activities may be a necessity, and also dependent on economics (of time, money, resources, utilities, etc.). ---Phase 2 Like phase 1 study and lab activities saliva will be also used for extraction of antiseptics. However, before such, develop an analogous sequence of operations top-down observed in phase 1; likely the nervous system, adrenaline, melatonin, dopamine and such will not factor in (as much). Figure all that out. Mechanisms and processes may only remain at regions of concern at the cellular level. Saliva constituents of concern: referencing Wikipedia’s page “Wound Licking” under “Mechanism”. Other pursued interests for antimicrobial substances with experiments and methods: Fruits Sorrel, balsam of Peru, and other cultural plants/trees Iodine, hydrogen peroxide, various alcohols, phenol, Dakin’s solution, Different antibiotics Octenidine dihydrochloride Polyhexamethylene biguanide, PHMB Super oxidized solutions NOTE: for recognition of substances spectroscopy types or chemical reactions will be employed and compared with databases. Synthesis will be carried out for acquisitions. In petri dishes and what not microbial organisms to be grown coming from various sources such as river water, wastewater, dirt, bathroom surfaces, decomposing sustenance, general surfaces, etc. NOTE: Trials and/or samples for the various laboratory activities may be a necessity, and also dependent on economics (of time, money, resources, utilities, etc.). Microbial constituents (bacterial, viral or other) should be identified. Identify place in the Phylogenetic tree and genus; analogy for viruses and other microorganisms identified. Growth rates should be identified (theoretical versus actual) for respective type of bacteria, virus, etc. Software to accomodate mathematial modelling. Treatment of evolved resistance (on both biochemical and genetic level). 8. Programmable bacterial (or algae) for the bio-synthesis of compounds of interest such as insulin (or whatever interests) Laboratory production of [insulin] by recombinant DNA technology with bacteria/algae population growth. Fermentation or whatever process to be coerced in a isolated environment; characteistics of environment must be particular and stable to acquire both optimal bacteria/algae growth and optimal insulin production. Satefy protocols and regulation with microbes Review of recombinant DNA technology Process and logistics for yeast with recombinant DNA technlogy Environmental conditions regulation For optimal bacteria/algae growth & optimal insulin production Identify & comprehend models, modelling, parameters & measures Biochemistry and Organic Chemistry modelling Analysis with possible by-products Stoichiometry Growth models based on whatever parameters prefrences Production expectation at time Tfinal Tools and structure for data gathering and assurance Description and profiling of the biprocessing system Means of [insulin] separation & gathering for storage & long term stablity Walk-through of operation procedures of bioprocessing system With logistical saftey protocols for whatever phases With tools and structure for data gathering and assurance Review of preparation for the relevant phases in development Implementation of bioprocessing Means of confirming [insulin] product Means of determining gross production and if consistent with preliminary modelling expectations Economics and innovation with technologies Software of interest R + R Studio Excel COCO (+ ChemSep), DWSIM (+ ChemSep) << Combase (Predictor and Modelling Toolbox) with MRV, USDA Pathogen Modeling Program, EPA Virulo >> A possble assist: 9. Competence and economics in Viral and Bacterial detection --Symptomology of specified common viruses. --Diagnosis can be done by direct detection of a virus in clinical specimens or by detecting the presence of Ab's to the virus in serum (acute infection is diagnosed by the presence of IgM antibody or by a 4X rise in IgG titer between acute and convalescent sera). Will be done in labs. Methods for direct virus detection: i). Isolation in cell culture ii). Electron microscopic examination of specimens iii). Immunofluorescence staining of specimens and microscopic examination (presence of antigen) iv). Enzyme immunoassay (presence of antigen) v). Polymerase chain reaction (presence of nucleic acid). Possible guide, but may choose variation and targets depending on resources: Adjou Moumouni, P. F et al. (2015). Molecular detection and characterization of Babesia bovis, Babesia bigemina, Theileria species and Anaplasma marginale isolated from cattle in Kenya. Parasites & vectors, 8, 496 vi). Microchip technology (presence of nucleic acid) vii). Use of salivary with an emphasis on rapid detection of infection by using point-of-care devices. Oral mucosal transudate contains secretory immunoglobulin (Ig) A, as well as IgM and IgG. Else by < Corstjens, P., L., William, R., A., and Malamud, D., Detecting Viruses by Using Salivary Diagnosis, J Am Dent Assoc. 2012 Oct; 143 (10 Suppl): 12S-18S > --Methods for Serodiagnosis (done in labs): i). Neutralization ii). Hemagglutination inhibition (HAI) iii). Complement fixation iv). Enzyme immunoassay (IgG or IgM) v). Western blot vi). Latex agglutination vii). Immunochromatography --Detection rates in comparison versus economic costs (money from use of tools and personnel, time). --Identify growth rate of respective virus for common parameter value ranges; may have to observe different geometric exhibitions concerning the pending combinations of variation ranges with the parameters. To then from sources to determine which methods provide best detection if group of viruses considered was extended (land ecosystems, aquatic, sustenance). Will incorporate competent use of microbial, viral, pathogen and EPA software from software portfolio. Can be compared with curve fitting of data, and regression modelling can also be done. --The same can be done with bacteriology. 10. Advanced identification of bacteria, fungi and viruses (laboratory activities). Activity 9 is a prerequisite. --Identification of bacteria (including mycobacteria) is based on growth characteristics (such as the time required for growth to appear or the atmosphere in which growth occurs), colony and microscopic morphology, and biochemical, physiologic, and, in some instances, antigenic or nucleotide sequence characteristics. The selection and number of tests for bacterial identification depend upon the category of bacteria present (aerobic versus anaerobic, Gram-positive versus Gram-negative, cocci versus bacilli) and the expertise of the microbiologist examining the culture. Gram-positive cocci that grow in air with or without added CO2 may be identified by a relatively small number of tests. The identification of most Gram-negative bacilli is far more complex and often requires panels of 20 tests for determining biochemical and physiologic characteristics. --The identification of filamentous fungi is based almost entirely on growth characteristics and colony and microscopic morphology. --Identification of viruses is usually based on characteristic cytopathic effects in different cell cultures or on the detection of virus- or species-specific antigens or nucleotide sequences. Will incorporate competent use of microbial, viral, pathogen and EPA software from software portfolio. Can compared with curve fitting of data, and regression modelling can also be done. 11. Biofilms experimental research Environmental signals and regulatory pathways that influence biofilm formation. Concerns as well survival, expansion, reduction and transferral in various environments and circumstances such as (i) Soil (ii) Aquatic (iii) Extreme environments (iv) Hosts (v) Ecological significance of plant-associated (vi) Bioremediation (vii) Waste water treatment systems (viiii) Corrosion & fouling (ix) Importance for the maintenance and monitoring of freshwater health (x) Extracellular Enzymes in Aquatic Biofilms: Microbial Interactions Vs Water Quality Romaní, A. M., Artigas, J., and Irene Ylla, I., Extracellular Enzymes in Aquatic Biofilms: Microbial Interactions vs Water Quality Effects in the Use of Organic Matter, Microbial Biofilms: Current Research and Applications (Edited by: Gavin Lear and Gillian D. Lewis). Caister Academic Press, U.K. (2012) Will incorporate competent use of microbial, viral, pathogen and EPA/USDA software from software portfolio. Can be compared with curve fitting of data, and regression modelling can also be done. NOTE: dental plaque and shower curtains may be excellent sources of biofilms. 12. Experimental investigation of the following article: Liu, W., et al, Ascorbic Acid Induces Cardiac Differentiation of White Adipose Tissue-derived Stem Cells, Molecular and Cellular Biochemistry (2019) 450: 65 – 73 However, preferably no surgical means on animals, instead to find other means of acquiring such cells. Interest in expanding investigation with various animal and humans. 13. Experimental investigation of the following article: Prasad, K., Is there any evidence that AGE/sRAGE is a universal biomarker/risk marker for diseases? Molecular and Cellular Biochemistry (2019) 451: 139 – 144 Identify other “universal” biomarkers/risk markers for diseases. Identify the models, formulas or quantities for determinations. Experimentally investigate as well and observe/determine whether alternatives are consistent with (standard) determination like what is expressed in above journal article. 14. Experimental investigation of the following article: Chanphai, P., Tajmir‑Riahi, H. A., Encapsulation of Micronutrients Resveratrol, Genistein, and Curcumin by Folic Acid-PAMAM Nanoparticles, Molecular and Cellular Biochemistry (2018) 449:157–166 Be economic as possible. Some of the mentioned substances are OTCs in pharmacies. Encapsulated versus naked may be interesting 15. Smartphone to Digital Microscope Conversion Materials: 3x 4 ½” x 5/16” carriage bolts 9x 5/16” nuts 3x 5/16” wing nuts 5x 5/16” washers ¾” x 7” x 7” plywood -- for the base ⅛” x 7” x 7” plexiglass -- for the camera stage ⅛” x 3” x 7” plexiglass -- for the specimen stage Scrap plexi (~ 2"x 4") for specimen slide (optional but useful) laser pointer focus lens (use at least two for increased magnification) LED click light (necessary only for viewing backlit specimens) Tools: Drill Assorted bits Ruler Note: one must acquire the lenses from laser pointers; cheap ones will do. Unlike how the lenses are fixed in place as shown in link, towards increasing certainty that smartphone isn’t compromised physical add-ons, one can possibly create a surface chamber for the two lenses in a means where the smartphone camera can be synchronized well on top of the lenses. If there is a better alternative to wood for the base, then so be it. Note: nobody cares what brand of smartphone you have as long as it has decent view. https://www.instructables.com/id/10-Smartphone-to-digital-microscope-conversion/ Such an apparatus must be sanitize capable where lenses and plexi glass will not be damaged; for metals in foundation corrosion resilience is will appreciated. Such a contraption with smartphone is easily portable for field observation and to serve as a financial backup when traditional microscopes are unavailable. There will be live recordings for various durations for various interests and to be archived. Play times must have the ability to be highly accelerated to one’s choosing without compromising the recordings. Note: this will be one of the first activities a student will do. One can readily take microscopic view photos and projector video recordings for data and archives. 16. H2O2 Cellular Signalling H2O2 is well known as a disinfectant both towards the skin and oral applications, and bleaching. Now, to investigate the role of H202 at the intracellular level. --Literature journal articles: Gough, D. R., and Cotter, T. G., Hydrogen Peroxide: A Jekyll and Hyde Signalling Molecule, Cell Death & Disease volume 2, page 213 (2011) Sies, H., Hydrogen Peroxide as a Central Redox Signalling Molecule in Physiological Oxidative Stress: Oxidative Eustress, Redox Biology 2017 Apr; 11: 613–619 Lennicke, C., Rahn, J., Lichtenfels, R., Wessjohann, L. A., & Seliger, B. (2015), Hydrogen Peroxide - Production, Fate and Role in Redox Signalling of Tumour Cells, Cell Communication and Signalling: CCS, 13, 39. --Biochemical history, Industry Standing and experimentation parameters: National Center for Biotechnology Information (2020). PubChem Compound Summary for CID 784, Hydrogen peroxide. --Journal Articles for developing experiments: Huang, B. K, and Sikes, H. D., Quantifying Intracellular Hydrogen Peroxide Perturbations in Terms of Concentration, Redox Biology 2 (2014) 955–962 Tomalin, L. E. et al, Increasing Extracellular H2O2 Produces a Bi-Phasic Response in Intracellular H2O2, with Peroxiredoxin Hyperoxidation Only Triggered Once the Cellular H2O2-Buffering Capacity is Overwhelmed, Free Radical Biology and Medicine 95 (2016) 333–348 Experimentation journal articles concern investigative experimentation towards comparative findings. 17. Comprehending how microbial enzymes function to drive ecosystem nutrient availability Exploring how key enzymes made by soil microbes function in the soil environment. They are important, because they induce the decay of organic compounds in soil that contain nutrients important for microbial and vegetation functioning. As such, they ultimately provide a large fraction of any ecosystem’s nutrient demand. We do not know how many of them respond to temperature, soil pH, soil mineralogy, or moisture availability. A set of projects exploring these questions. Will incorporate competent use of microbial, viral, pathogen and EPA software from software portfolio. Can be compared with curve fitting of data, and regression modelling can also be done. 18. Plant Biochemistry & Phytochemistry Properties of phytochemicals in plants, trees, fruits and vegetables...including all taxonomic distributions. Phytochemical knowledge and experimental labs about the natural source, classification, detection, extraction, isolation, nutritional, pharmacological and toxicological effects. Discriminate samples from different places for a respective plant by significantly distant residencies from each other. If plants used in journal articles are inaccessible, then substitute with local revered plants. There must be integrity with data findings (specimen identification, specimen samples, ambiance). Ambiance concerns Customary temperature ranges Sunlight exposure Water supply Soil constituents PH Microbial residents General ecology Identified chemicals, compounds, etc., will be cross-referenced with professional databases which will include uses, properties, etc. Findings can possibly be integrated into a GIS. Data will be securely archived and developed in a manner to discriminate from future data. However, data must be integrable with computational tools for different models, parameters estimations, trends, etc. Journal article example: (I). Lab development Senguttuvan, J., Paulsamy, S., & Karthika, K. (2014). Phytochemical analysis and evaluation of leaf and root parts of the medicinal herb, Hypochaeris radicata L. for in vitro antioxidant activities. Asian Pacific journal of tropical biomedicine, 4(Suppl 1), S359-67. Multiple plants/trees will be observed (including sorrel buds) besides what is observed in sources and articles (whether accessible or not). A supporting text for intelligence and experimentation practices Harborne JB 1998. Phytochemical methods. Chapman and Hall Pharmacognosy, Phytochemistry, Medicinal plants By Jean Bruneton (1995), English edition. Levoisier Publishing, Pari Mandatory range of interest: Sugars, soluble fibers and organic acids Fats and oils, Carotenoids Flavonoids, anthocyanins and polyphenolics Antiseptics Steroids Alkaloids and Seed storage proteins May extend to natural pesticides and cleaning agents For such range of interest students will be pursue determination of the metabolic process for each. Will also make use of biochemical software for amination models with properties and simulation of conventional chemical reactions. (II). The increase in antibiotic resistance bacteria and synthetic drugs has urged the search of new antibacterial and antioxidant agents from medicinal plants. To study the antibacterial activity and antioxidant activity of leaf extract of Andrographis paniculata. In this study, the powdered leaves are subjected to sequential Soxhlet extraction by increasing polarity index of solvents (hexane, chloroform, ethyl acetate and methanol). Prove or disprove: The methanol extract gave the highest percentage yield of extraction in the sequential extraction. All the solvent extracts were then used in phytochemicals screening tests, antioxidant and antibacterial assays as well as thin layer chromatography analysis. Prove or disprove: for the phytochemicals screening test, terpenoids was found to be the most abundant compounds in chloroform, ethyl acetate and methanol extracts. The DPPH assay was carried out to determine the antioxidant activity of all solvent extracts. Prove or disprove: Hexane extract found to exhibit the highest antioxidant activity with the lowest half maximal inhibitory concentration, IC50 value of 2.80 mg/ml. The antibacterial activity was evaluated qualitatively through agar disc diffusion toward Staphylococcus aureus, Staphylococcus epidermidis and Escherichia coli. Prove or disprove: the ethyl acetate extract showed the highest zone of inhibition value (17.0 mm) in S. epidermidis treatment. Prove or disprove: the potential of antibacterial activity decreases with chloroform and hexane. The methanol extract was failed to exhibit any antibacterial activity. Prove or disprove: all the solvent extracts showed no antibacterial activity against E. coli. The antibacterial activity is evaluated quantitatively through minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) tests. Prove or disprove: the MIC values of the ethyl acetate and chloroform extracts for S. aureus and S. epidermidis were ranged from 375 µg/ml to 750 µg/ml. Both solvent extracts were bacteriostatic toward the S. aureus and S. epidermidis. Prove or disprove: In conclusion, high extraction yield does not indicate that it has high antibacterial and antioxidant activities. Prove or disprove: The ethyl acetate extract performs the best antibacterial activity and hexane extract perform the best antioxidant activity. One may find simple elements as well. Concerning elements, molecules, compounds, etc. found in plants/trees to identify the role of each (if any) for metabolism, regulation, biochemical mechanisms, etc. 19. Ecological and evolutionary feedbacks between plants and beneficial fungi Lab investigation of the ecological and evolutionary consequences of plant-microbe interactions. Much of our work focuses soil fungi (called mycorrhizal fungi) that commonly improve plant growth through increased access to soil resources. We are particularly interested in how the benefits that plants receive from these fungi change over time and the potential role of these fungi in maintenance of plant species diversity. We often work in native prairie, where we have found that these fungi play primary roles in plant dynamics and in the restoration of native diversity. Work on this problem could involve work in the field, greenhouse, lab (at microscope work or DNA analysis) or computer (modeling). Will incorporate competent use of microbial, viral, pathogen and EPA software from software portfolio. Can be compared with curve fitting of data, and regression modelling can also be done. 20. Evaluation of natural repellents Sumangala Bhat, K. and Aravind G., Evolution, Current Status and Prospects of Phyto-Repellents against Mosquitoes, International Journal of Pharmacology, Phytochemistry and Ethnomedicine, Vol. 8, pp 54-73, 2017 https://www.scipress.com/IJPPE.8.54.pdf To analysis the given article and replicate experimentation to the best as possible. Specimen mosquitoes with controls and concealment required. 21. Parasitic Analysis Phase 1 (Urine testing)-- Activity concerns parasite findings or determination by urinary tests. If applied chemicals, substances in journal articles and sources are in accessible, then substitute with local economic alternatives. Will also incorporate professional microbiology and medical databases to make conclusions about findings. Multiple samples are required. Sources and journal article examples to emulate for experimentation: https://www.cdc.gov/dpdx/diagnosticprocedures/other/urine.html Lodh, N. et al, Diagnosis of Strongyloides stercoralis: Detection of Parasite-Derived DNA in Urine, Acta Tropica 163 (2016) 9–13 Will not be restricted to identification or sole pursuit of organisms encountered in sources and journal articles. Research host-parasite relationships in urinary tract infections. Based on observations or findings from urinary tests are there any coinciding findings with your research on host-parasite relationships in urinary tract infections? Phase 2 (Stool Examinations)-- The stool will be checked for colour, consistency, amount, shape, odour, and the presence of mucus. The stool may be examined for hidden (occult) blood, fat, meat fibers, bile, white blood cells and sugars called reducing substances. As well, the pH of the stool also may be measured. A stool culture is done to find out if bacteria may be causing an infection. Journal article example: Koontz, F., and Weinstock, J. V., The Approach to Stool Examination for Parasites, Gastroenterology Clinics of North America, Volume 25, Issue 3, 1 September 1996, pages 435-449 Will also incorporate professional microbiology and medical databases to make conclusions about findings. Note: for the same hosts urinary testing and stool testing can be cross-compared to observe which is more sensitive, or accurate. Phase 3 (other types of testing)-- Will also identify other types of tests and determine their economic standing. May proceed with experimentation (time permitting and if economically feasible). Will also incorporate professional microbiology and medical databases to make conclusions about findings, if done. 22. Infiltration and neutralization of microorganisms by biochemcal means (i) Peptidoglycan Biosynthesis Animation Make use of journal articles as sources as well. Phases warrant lab activities as well. Assist: --> Peptidoglycan Biosynthesis [HD Animation] - YouTube (ii) Apart from E coli will identify the unique compounds and/or processes involved with other chosen types of bacteria. (iii) Will then analyses and simulate the (bio)chemistry of antibiotics towards Peptidoglycan and bacterial DNA replication. Concerning molecular exhibitions and simulations various software have been mentioned throughout. Will try to identify why some antibiotics are more effective than others concerning Peptidoglycan and bacterial DNA replication; accompanying analysis molecular exhibitions and simulations for such reasons should also be developed. (iv) If one can model rate of effectiveness for each chosen antibiotic such would be nice. Of consequence environmental conditions can have influence on performance of antibiotic and welfare of different bacterial, respectively. Conditions examples are temperature, Ph, salinity, ionic level, presence of other molecules, light interaction (different from thermal), dosage, etc. (v) Will compare the (bio)chemistry of antiseptics versus antibiotics towards Peptidoglycan, bacterial DNA replication and generate sterilization. Will try to identify how effective antiseptics still are concerning bacteria evolution/mutations; environmental conditions to accounted for as well. Activity can also be extended to treat virology. For viruses with envelops one must establish definitively the role of such envelops. Examples of functions: Protecting the RNA or DNA molecule(s) Evading recognition by the immune system Facilitating virus entry Note: non-enveloped viruses will also be treated. Entry, transmission, and exit pathways of the (101) viral families on the 2013 International Committee on Taxonomy of Viruses (ICTV) list. A article assist: Buchmann, J. P. and Holmes, E. C. (2015). Cell Walls and the Convergent Evolution of the Viral Envelope. Microbiology and Molecular Biology Reviews, Volume 79 Number 4 One may need to review the mechanism of cell penetration by viruses if needed. To establish the (bio)chemistry with antibiotics and antiseptics concerning such envelope functions (and treatment also for nonenveloped viruses). The activities phases detailed for bacteria will also be ��emulated”. Activity can be further extended towards general microrganisms known to be harmful to humans and animalia of interest. 23. Protein & DNA Imaging NOTE: at this level we are not interested on experimentation with rats and such sorts of things, neither any pursuit of cancerous cells. Part I -Review of of the Watson-Crick Experiment -Strawberry DNA extraction is one of easiest means; same likely to be for other fruits and vegetables, however, such may not be applicable to the type of methodologies of other parts of this activity. Nevertheless. It’s a good kindergarten activity to star with towards DNA imaging (to be done). There may issues of preserving the extracted DNA for long periods. Will compare such “kindergarten” extraction means to extraction with Phenol-Chloroform and NaClO4. Will determine whether the latter two methods are practical for extraction of DNA from produce. If so, logistics, economics and detailed chemistry will be treated; likely, lab exercises for the latter two if methods are applicable. Will then move on the human DNA extraction will the latter two methods, where respective logistics, economics and detailed chemistry will be treated. Will apply direct Raman spectroscopy to determine make up and, recognition o functional groups and other things. Hopefully, window of stability of nucleotides is enough to directly apply the Raman spectroscopy which doesn’t destroy the sample or specimen, consider preparation that can be employed in order to apply such Raman spectroscopy scheme. Part II Raman Scattering Microscopy The following journal articles provide economic means of access to DNA imaging. --Zhang, X. et al, Label-Free Live-Cell Imaging of Nucleic Acids Using Stimulated Raman Scattering Microscopy, ChemPhysChem 2012, 13, 1054 – 1059 --Lu, F. et al (2015). Label-free DNA Imaging In Vivo with Stimulated Raman Scattering Microscopy, PNAS Volume 112 Number 37 --Wang, O. et al, Mechanisms of Epi-Detected Stimulated Raman Scattering Microscopy, IEEE Journal of Selected Topics IN Quantum electronics, Vol. 18, NO. 1, January/February 2012 Proceed with development of active imaging. Part III Use of bright-field and ultraviolet (UV) induced fluorescence modes Abstract: “Imaging protein crystals and distinguishing them from salt crystals is an important task for protein crystallographers. The conventional tool used for this purpose is a dual-mode microscope composed of bright-field and ultraviolet (UV) induced fluorescence modes. The distinction between a protein and a salt crystal is made based upon the fluorescence response to the UV excitation, where most protein crystals absorb the UV excitation and emit fluorescence, unlike salt crystals. These dual-mode optical microscopes are sensitive; however, they are relatively bulky and expensive as they require UV-grade optics. As an alternative, here we demonstrate that on-chip UV holographic imaging offers a low-cost, portable, and robust technique to image and distinguish protein crystals from salt crystals, without the need for any expensive and bulky optical components. Only composed of a UV light-emitting-diode at 280 nm and a consumer-grade complementary metal–oxide–semiconductor image sensor decapped and interfaced to a Raspberry Pi single-board computer, the necessary information from the crystal samples (placed very close to the sensor active area) is captured in the form of in-line holograms and extracted through digital back-propagation. In these holographic amplitude reconstructions, protein crystals appear significantly darker compared to the background due to the strong UV absorption, unlike salt crystals which do not show any contrast, enabling us to clearly distinguish between them. We believe that the on-chip UV holographic microscope could serve as a low-cost, sensitive, and robust alternative to conventional lens-based UV-microscopes used in protein crystallography.” Journal article --> Daloglu, M. U. et al (2019). Low-Cost and Portable UV Holographic Microscope for High-contrast Protein Crystal Imaging. APL Photon. 4, 030804 Will develop all such in a lab for active imaging Part IV Immunofluorescence Methods What are such methods? Identification of the various uses of immunofluorescence Methods A major accomplishment will be imaging DNA or RNA or proteins; that would be a tremendous start. Then Lab experimentation similar to what is analysis in the following guides to be pursued. Analysis of biochemistry and organic chemistry for functional and competent activities is mandatory; accompany with visualization and simulation software expressed in many cases before. Optics and physics however for biological sciences students may be too technical and elusive for them. Imaginig labs will be done. --Boutorine, A. S. et al. Fluorescent Probes for Nucleic Acid Visualization in Fixed and Live Cells. Molecules 2013, 18, 15357-15397 --Pollex T, Piolot T, Heard E. Live-cell imaging combined with immunofluorescence, RNA, or DNA FISH to study the nuclear dynamics and expression of the X-inactivation Center. Methods Mol Biol. 2013;1042:13-3 --Kishi, J.Y., Lapan, S.W., Beliveau, B.J. et al. SABER amplifies FISH: enhanced multiplexed imaging of RNA and DNA in cells and tissues. Nat Methods 16, 533–544 (2019) --Bennett, B. T., Bewersdorf, J., & Knight, K. L. (2009). Immunofluorescence imaging of DNA Damage Response Proteins: Optimizing Protocols for Super-resolution Microscopy. Methods (San Diego, Calif.), 48(1), 63–71 --Smolka, J. A. et al. Recognition of Cellular RNAs by the S9.6 Antibody Creates Pervasive Artefacts when Imaging RNA:DNA Hybrids. bioRxiv 2020.01.11.902981 --Lin, J. et al. Highly Multiplexed Immunofluorescence Imaging of Human Tissues and Tumors using t-CyCIF and Conventional Optical Microscopes. bioRxiv 151738 24. Role of Oxidation-Reduction The ability of an organism to carry out oxidation-reduction reactions depends on the oxidation-reduction state of the environment. i. Consider the following journal article: Pezeshki, S. R., & DeLaune, R. D. (2012). Soil Oxidation-Reduction in Wetlands and its Impact on Plant Functioning. Biology, 1(2), 196–221 The pursuit is development of various model experimentation to confirm or disprove such article. Technicality and intricacy may go well beyond analytical knowledge and assumed time frame for operations. ii. Concerning oxidation-reduction will carry out environmental and laboratory investigation concerning the following parameters: << dissolved oxygen, alkalinity, biological CO2 pump, acidity, eutrophication, metal nutrition, metal pollution, excessive carbon emissions >> Will look at various land and aquatic environments concerning, microorganisms and vegetation. Definitive measures must be identified with data gathering towards conveyance of proof. Likely to have various test samples, test specimens, and trials. Will not necessarily seek extremes towards terminal cases of vegetation, but such is acceptable for microorganisms. As well, pursuit of analytical mathematical models relating various parameter, where field and lab investigation will be compared with such. Correlation analysis and causality determination can be incorporated. 25. Honey as a cloning agent Apart from the common knowledge will establish the comprehensive biochemical process involving DNA/RNA. Make use of journal articles and professional sources to support activity. Software can complement. Plant types to experiment with must naturally have high regeneration or growth rates. What are the similarities and differences between sophisticated conventional biological methods (SCBMs) and honey (as the cloning agent)? How effective is honey compared to the SCBMs? There must be experimental controls and trials to acquire significant statistical data? Is honey only applicable to plants? If not identify or favourable environments and process to fit the organism environment in question. Determine what other basic household “commodities” can be substitutes for honey. Establish the thorough biochemistry for such with appropriate processes and environments(s). Pursue experimentation with controls and trials as done with honey. 26. Reinforcement of Foundational Biochemistry Experiments Activity will assume successful completion of biochemistry II. Activity serves to reinforce basic biochemistry lab skills but will be a highly accelerated environment with experiments. Likely will be one of the earlier activities done (but not necessarily a prerequisite for various other activities). Experiment 1: Introduction to Techniques Use of pipetman Spectroscopy and dilutions Analysis of experiment 1 results Experiment 2: Protein Purification Purification of LDH LDH Enzyme assays Protein assays Calculation hints: Purification table Experiment 3: Characterization of LDH SDS PAGE Western blotting Gel filtration chromatography Protein crystallography Experiment 4: Enzyme Kinetics Km determination Lactate Km determination (continued) Pyruvate Km determination Inhibition kinetics Inhibitor type determination Chemical modification of LDH Experiment 5: Cloning of LDH PCR and plasmid preparation Agarose gels and restriction digests Ligation and transformation Selection and screening Screening and sequencing Activity measurements Other possible experiments: Amino Acid Composition of a Dipeptide pH Dependence of [whatever enzyme] Stereochemistry of the Fumarase Reaction — an NMR Study NOTE: proteins or other polymers of interest or choice can be substitutes in the future, or if more economic. 27. Inquiry-based Undergraduate Biochemistry Despite the following journal article being structured for a course, instead it will be in a setting like the other prior activities. Gray, C. et al (2015). Known Structure, Unknown Function: An Inquiry-based Undergraduate Biochemistry Laboratory Course. Biochemistry & Molecular Biology Education. Volume 43, Issue 4, pages 245 - 262 NOTE: various biochemical software from software portfolio are available to complement activity. 28. Knowledge and professionalism with dexterous biochemical software mentioned in software portfolio. Will identify major issues with observational and modelling of biochemicals, polymers and entities in molecular biology. Includes chemical and behavioural properties. Will have interactive investigation of how software (in the software portfolio) can resolve or assist with issues. Will also include inquiry on purpose or function of substances in question. Activity will not focus solely on proteins, yet decent guides for such: -Zacharias, Martin. Protein-Protein Complexes: Analysis, Modeling and Drug Design. Imperial College Press, 2010. Hence, activity may also creep into molecular modelling software --Dobson, Christopher M (2003). "Protein folding and misfolding". Nature. 426 (6968): 884–90 --Marsh JA, Hernández H, Hall Z, Ahnert SE, Perica T, Robinson CV, Teichmann SA (2013). Protein Complexes are Under Evolutionary Selection to Assemble via Ordered. Cell. 153 (2): 461–470 --Sudha, Govindarajan; Nussinov, Ruth; Srinivasan, Narayanaswamy. "An overview of recent advances in structural bioinformatics of protein-protein interactions and a guide to their principles". Progress in Biophysics and Molecular Biology. 116 (2–3): 141–50. --Marsh, Joseph; Teichmann, Sarah A (2014). Protein Flexibilty Facilitates Quaternary Structure Assembly and Evolution. PLOS Biology. 12 (5): e1001870 --Levy, Emmanuel D; Boeri Erba, Elisabetta; Robinson, Carol V; Teichmann, Sarah A (2008). Assembly Reflects Evolution of Protein Complexes. Nature. 453 (7199); 1262-5 NOTE: It’s not possible to be confined to a single software. This activity will be pushed early as possible, contingent upon students being recognised with background to manage activity. Activity will also be pushed to be repeated by students. Activity may or may not be done before activity 29. 29. Spectroscopy Methods Will be administrated by the Chemistry “department”. Outline for students in the biological sciences will be different to students in chemistry; chemistry students concern a foundation that’s more connected to physics, and the mathematics that involve such. The biological sciences out line will have no influence on chemistry students. See details under chemistry. 30. Foundation for clinical drug metabolism Part A The following two articles provided economical quality experimentation or drug metabolism. However, experiments can possibly incorporate other types of drugs (if able), but methods and/or strategies must be valid for them --> Juvonen, R. O., Pennanen, S. and Pasanen, M. A Convenient Laboratory Experiment for Teaching the Fundamentals of Drug Metabolism. American Journal of Pharmaceutical Education Vol. 61, Fall 1997 Zhang, D. et al (2012). Preclinical experimental models of drug metabolism and disposition in drug discovery and development. Acta Pharmaceutica Sinica B; 2(6): 549–561 Part B The following journal can provide a strong overview for cellular and molecular mechanisms of drug dependence (may actually be limited): Gupta, S., & Kulhara, P. (2007). Cellular and molecular mechanisms of drug dependence: An overview and update. Indian journal of psychiatry, 49(2), 85–90. For drugs experimented with in part A, without immediate confirmation by established professional data, to investigate methods or tools that are conventional or modern to identify target receptors, one’s vulnerability to drug dependence related to receptors, and possible toxic conditions. For those methods that are economically feasible and practical students to implement them, and compare results with established professional data. 31. Synthesizing Antibiotics PART A Making penicillin, ampicillin and other “off-shoots” of penicillin. Advanced stoichiometry will be heavily enforced. Chemical kinetics and energetics involved in processes. Various mentioned software in the “Goody Bag” post can assist. Spectroscopy tests (likely Raman) with multiple samples and comparison with professional databases. Tests on microbial, viral organisms. Will acquire specimen from various sources and cultured to substantial population. Generally, one has an ambiance where antibiotics are known to be behave optimally. Will like chronological imaging for a chosen duration. Penicillin and the “off-shoots” of penicillin will be tested against various cultures, where at least three sample tests per culture. Students will then have considerable theoretical development of large production by process design via simulators. Students must be creative with means of replicating environments possibly the acceleration of processes; possible hazards and volatilities identified. Accommodating simulation will be analytical quantitative modelling of systems; models and values have decisive role concerning materials, energy usage, quantity of products (and possible by-products), pollution, etc.. PART B Synthesizing sulfonamides. From the following link and journal articles will make great efforts towards the production of sulfonamides in the most economic and safe manner. Various mentioned software in the “Goody Bag” post can assist. Advanced stoichiometry will be heavily enforced. Chemical kinetics and energetics involved in processes. For sulfonamides there are many variants depending on the process applied. Spectroscopy tests (likely Raman) with multiple samples and comparison with professional databases. One will like multiple variables, hence difference processes of synthesizing. Tests on microbial, viral organisms. Will acquire specimen from various sources and cultured to substantial population. Generally, one has an ambiance where antibiotics are known to be behave optimally. Will like chronological imaging for a chosen duration. Likely each type of sulfonamide will be tested against various cultures, where at least three sample tests per culture--> https://www.organic-chemistry.org/synthesis/N1S/sulfonamides.shtm Reza Massah, A., Sayadi, S., & Ebrahimi, S. (2012). A green, mild and efficient one-pot method for the synthesis of sulfonamides from thiols and disulfides in water. RSC Advances, 2(16), 6606-6616. Naredla, R. R., & Klumpp, D. A. (2013). Preparation of sulfonamides from N-silylamines. Tetrahedron letters, 54(45), 5945–5947 Students will then have considerable theoretical development of large production by process design via simulators. Students must be creative with means of replicating environments, and possibly the acceleration of processes; possible hazards and volatilities identified. Accommodating simulation will be analytical quantitative modelling of systems; models and values have decisive role concerning materials, energy usage, quantity of products (and possible by-products), pollution, etc. PART C Antibiotics resistance modelling The following articles can be applied to antibiotics of part A and part B with a second stage of experiments, or to make use of the acquired data from the total process of the antibiotics administered towards modelling. Apart from differential equations will apply both linear regression, multilinear regression and possibly exponential regression. Make the adjustments to accommodate the antibiotics mentioned in part A and part B --> Spalding, C., Keen, E., Smith, D. J., Krachler, A. M., & Jabbari, S. (2018). Mathematical modelling of the antibiotic-induced morphological transition of Pseudomonas aeruginosa. PLoS computational biology, 14(2), e1006012 Bruce R. Levin, Klas I. Udekwu. Population Dynamics of Antibiotic Treatment: a Mathematical Model and Hypotheses for Time-Kill and Continuous-Culture Experiments. Antimicrobial Agents and Chemotherapy Jul 2010, 54 (8) 3414 – 3426 Jeffrey J. Campion, Patrick J. McNamara, Martin E. Evans. Pharmacodynamic Modelling of Ciprofloxacin Resistance in Staphylococcus aureus. Antimicrobial Agents and Chemotherapy Dec 2004, 49 (1) 209 – 219 Jeffrey J. Campion, Philip Chung, Patrick J. McNamara, William B. Titlow, Martin E. Evans. Pharmacodynamic Modelling of the Evolution of Levofloxacin Resistance in Staphylococcus aureus. Antimicrobial Agents and Chemotherapy May 2005, 49 (6) 2189 – 2199 PART D It’s only responsible that one investigates the performance of antibiotics in environments not optimal for respective antibiotic. That part will be somewhat and extension of part C, namely, modelling for environmental factors that can influence microbial populations subjected to antibiotics administered. Factors, such as sustenance, competition among species, temperature and so forth. One type of control may or may not be a culture without competition; there will be other controls in the experimentation process. Multiple regression will be employed for such a case with treatment of causal inference and possibility of lurking variables. 32. Biochemical tests In other actives samples of blood, urine and saliva are gathered to determine cases of infections. In this activity. Biochemical tests will be conducted in a hospital or health clinic to find out the individual’s status health. These biochemical test results are used by medical practitioners to perform diagnosis, prognosis and to monitor the disease. Kidney function test (Renal Profile Test) -The kidneys have important roles in regulating the electrolytes balance and acid-base homeostasis in the human body. The kidneys also monitor the body’s blood pressure and involved in excretion of waste products through urine and reabsorbing some substance that needed by the body. Kidneys also are able to filter the metabolic products such as urea and creatinine. Parameters tested in kidney function tests are sodium, potassium, urea and creatinine. -Sodium is the major electrolyte in water regulation in the body. No special preparation is required, and the patient’s blood can be taken at any time to run the test. Normal serum sodium levels are between 135-145 mmol/L. Hypernatremia is defined by an elevated sodium level in the blood while hyponatremia is a condition that occurs when the level of sodium less than 135 mmol/L. -Potassium helps nerves and muscles communicate. It also helps move nutrients into cells and waste products out of cells. The normal potassium level in the blood is 3.3-5.3 mmol/L. Hyperkalaemia is an excessive level of potassium in the bloodstream while hypokalaemia is a condition that occurs when the level of potassium is abnormally low. -Urea and creatinine have been used by clinician as a marker of renal function. Urea is a waste product formed from the breakdown of proteins while creatinine is a specific product for muscle metabolism. Increase concentration of urea in the blood may indicate acute and chronic renal dysfunction meanwhile increase creatinine level may indicate chronic renal dysfunction. A normal range for urea is 2.5 – 8.0 mmol/L while for creatinine is 62-106 umol/L (men) and 44-80 umol/L (women). Concerning the means to measure levels of sodium, potassium, urea and creatinine respectively, students will thoroughly establish the biochemistry analysis involved for credibility of such tests. Are kidney tests also good indicators of abnormalities or diseases of the nervous system? Pursue research that supports or refutes such. Lipid Profile test -Triglycerides are a type of fat found in the blood that the body uses for energy. Mostly, triglycerides are made in the liver and some are come from the diet. High triglyceride levels are associated with coronary heart disease. Many factors affect blood triglyceride levels including less physical activity, smoking, excessive alcohol consumption, intake of high carbohydrate diet, medication and some types of diseases and genetic disorders. The normal range for triglycerides is between 0.5 – 1.8 -Cholesterol is a type of lipid that is found throughout the body. It is produced by the liver and can be get from certain foods. Cholesterol is required in the body’s metabolic processes for the formation of new cells and synthesis hormones. However, excess cholesterol will form plaque between layers of artery walls, making it harder for heart to circulate blood. Thus, a clot blocks an artery will causes a stroke and heart attack. Hypercholesterolemia is a condition that occurs when the cholesterol level is high. A normal range for cholesterol is between 3.9 – 5.5 mmol / l. -Low density lipoprotein (LDL) contains mostly 75% of cholesterol and a smaller proportion of protein. LDL is responsible for delivering cholesterol to the parts of your body that need it. Excess LDL, however, causes a build-up of cholesterol in the walls of your arteries, contributing to the development of atherosclerosis. It is also known as a bad cholesterol. The normal range for LDL is <3.3 mmol/L. -High-density lipoprotein (HDL) is known as a good cholesterol. The job of HDL is to remove excess cholesterol from the cells and the walls of the arteries and then transport the cholesterol back to the liver for disposal. It may actually slow or even reverse the development of atherosclerosis. The normal range for HDL is between 1.0 – 2.2 mmol/L. Concerning the means to measure levels of Triglycerides, Cholesterol, LDL and HDL respectively, students will thoroughly establish the biochemistry analysis involved for credibility of such tests. As well does test for cholesterol count distinguish between good and bad cholesterol? If not, how is such done? Glucose test Blood glucose test measures the amount of a sugar called glucose in a sample of blood and this test may also be used to screen a person for diabetes. There are several types of glucose test included: -Fasting Blood Sugar (FBS). FBS are measured by taking a blood test after a period of fasting, usually of 8 hours without food. The normal range is between 3.0 – 5.4 mmol/L. -Random Blood Sugar (RBS). A blood sample will be taken at a random time to get a picture of the glucose concentration in the bloodstream. High random blood sugar will show that a person may has diabetes. But it is not a confirmatory test to diagnose a person with diabetes or not. The normal range is between 3.0 – 7.7 mmol/L. -2- Hour Postprandial Glucose (2HPP). This test measures blood glucose exactly 2 hours after eating a meal timed from the start of the meal. This test is done to see the effectiveness of the pancreas produces insulin to control the sugar. -Oral Glucose Tolerance Test (OGTT). The test is used to determine whether the body has difficulty metabolizing intake of sugar/carbohydrate. It is a screening test for the diagnosis of diabetes among pregnant women. The patient is asked to take a glucose drink (75g glucose in 250-300ml of water) and their blood glucose level is measured before and 2 hours after the sugary drink is taken. Uncontrolled diabetes can lead to complications of eyes, kidneys and heart. Concerning each type of glucose test, students will thoroughly establish the biochemistry analysis involved for credibility of such tests. Based on all such glucose results can one acquire a valid gauge on an individual’s activeness patterns, and their rate of fat burn? Liver function tests -Liver function tests (LFT) measure the levels of certain enzymes and proteins in the blood. This test is used to help diagnose and monitor liver disease or damage. LFT also used to assess the general state of the liver and it can also indicate other diseases, such as malnutrition or bone disease. -Alanine transaminase (ALT). Large amounts of ALT are found in liver cells. ALT is an enzyme that helps to process proteins. When the liver is injured or inflamed (as in hepatitis), the blood level of ALT usually rises. The normal range of values for ALT is between 0-41U/L. -Aspartate transaminase (AST) AST is an enzyme that plays a role in alanine and amino acid metabolism. When body tissue or an organ such as the heart or liver is diseased or damaged, additional AST is released into the bloodstream. The amount of AST in the blood is directly related to the extent of the tissue damage. The normal range of values for AST is between 10-35U/L. -Alkaline Phosphatase (ALP). Alkaline phosphatase (ALP) is an enzyme found in all body tissues especially in the liver, bile ducts and bone. ALP levels are higher than normal levels indicate the occurrence of cholestasis. The normal range for ALP is between 35-104 U/L. -Albumin and Total Protein. Albumin and total protein are made mainly in the liver. It helps our body as carrier protein, fight against infection and other function. Lower than normal levels may indicate liver damage or disease. The normal range for albumin is between 35-52 g/L for adults, while the normal range for total Protein is 66-87 g/L. -Total Bilirubin. Bilirubin is a brownish yellow substance found in bile. It is produced when the liver breaks down old red blood cells. Bilirubin is then removed from the body through the stool (feces) and gives stool its normal colour. Higher than normal levels of bilirubin may indicate different types of liver problems. Occasionally, higher bilirubin levels may indicate an increased rate of destruction of red blood cells. Increased levels of bilirubin can also be viewed with the naked eye, namely skin and eyes turn yellow. The normal range is between 0.0 – 17.1 umol/L. Concerning each type of enzyme test, Albumin -total protein test, and Bilirubin tests, students will thoroughly establish the biochemistry analysis involved for credibility of such tests. 33. Biosynthesis of Vitamins in Plants and Animals Main categorization Fat-soluble vitamins (A, D, E and K) Water-soluble vitamins (B and C) Note: for a particular vitamin in a category there are variants to consider, and such will be pursued. An example article guide: Fritsche, S., Wang, X., & Jung, C. (2017). Recent Advances in our Understanding of Tocopherol Biosynthesis in Plants: An Overview of Key Genes, Functions, and Breeding of Vitamin E Improved Crops. Antioxidants (Basel, Switzerland), 6(4), 99. Galmés, S.; Serra, F.; Palou, A. Vitamin E Metabolic Effects and Genetic Variants: A Challenge for Precision Nutrition in Obesity and Associated Disturbances. Nutrients 2018, 10, 1919. Such above guides only concern tocopherols, and rather, one will like guides for other vitamins and the variants concerning biosynthesis in plants and animals. Note: some variants may require particular conditions or creation with energy requirements and temperature requirements, and abundance of materials and catalyses, hence will detail such if needed. Will also make use of software to study and analyse different variants towards predicting use unique behaviours of variants towards nutrition, metabolism, reaction with other compounds (organic and inorganic), pharmaceutical, pharmacology, etc; some software also possess spectroscopy prediction tools (to compare with professional databases). Will also pursue possible intelligence on synthetic synthesizing of vitamins and the variants. If synthetic means are possible will develop process design towards simulation of production (and may be discriminating with variants if possible). May also pursue analysis of vitamins side effects and the conditions that lead to them; biochemistry will be thorough for all such, and will determine whether increased effects are dependent on variant type. 34. Mineral Regulation Concerns the major minerals and trace elements. Purpose in body function, appropriate forms and how such forms are attainable, intake, biochemistry of digestion and distribution for the various minerals, metabolic pathways. Includes detailed analysis of particular biological systems and corresponding cellular regulation, towards metabolic products, pathways with associated biochemistry. Consequences of deficiencies; reasons for possible negative side effects with intake; overdose. Will costruct processing stations similar to digestive and absorption bodily function. Stoichemetry, chemical thermodynamics, inorganic chemistry and so forth. Will also identify what activities lead to high reduction in mineral concentration in the body; must be specific with each mineral or trace element. 35. Advance Reinforcement of labs from the Bacteriology and Virology courses Competency and success in this activity will depend on retention and constructive effort in the Bacteriology and Virology courses. Skills acquired in such courses do have real value. Labs may be augmented a bit more. 36. Bacterial and Viral Nutrition PART A Bacteria types of interest: Autotrophs (different types) Organic compounds consuming bacteria Decomposers Heterotrophs that consume inorganic chemotrophs Accurate identification of different gathered specimen cultures from various environments is crucial. The following guide may or may not encompass all prior mentioned bacteria types concerning: Gottschalk G. (1986) Nutrition of Bacteria. In: Bacterial Metabolism. Springer Series in Microbiology. Springer, New York, NY Note: some aspects of activity will involve lab observations and record keeping, Microscopes with cameras that can capture culture behaviour towards projectors will be nice. Such microscopes with cameras should be able to observe bacteria physiology, take picture in high speed frames, and video record as well. Other observations and modelling include dynamic population evolution, growth rates, etc. alongside use of mentioned pathogen/microorganisms modelling software. Particular research, observation, data collection and analysis for: Physiology of digestion or respective autotrophic process Biochemistry of digestion or biochemistry of respective autotrophic process Duration for metabolic respective process Waste products Are mutations in bacteria highly influential on the biochemistry of nutrition and metabolism? Under what conditions or threshold doe a respective bacteria type become hazardous to other organisms (micro and multicellular). For multicellular effects for plants, invertebrates and invertebrates may be unique depending on quantities, time, etc. Particularly for bacteria that acquire nutrition by photosynthesis will like various different specimen cultures exposed to different electromagnetic wavelengths for data; determine what other environmental parameters that can be controlled and investigated alongside nutrition administering. For autotrophs that rely on chemicals there will be different specimen cultures exposed to different chemicals; determine what other environmental parameters that can be controlled and investigated alongside nutrition administering. For bacteria that consume organic compounds there will be different specimen cultures exposed to different compound groups; determine what other environmental parameters that can be controlled and investigated alongside nutrition administering. For bacteria that decomposed compounds there will be analogy to prior. For heterotrophs that consume Inorganic chemotrophs there will be analogy to prior. PART B Viruses are made of three major components (and establish what the other minor components are) Nucleic acids, which include DNA and RNA and they provide a set of genetic instructions for future viral reproduction. Protein coatings that protect the nucleic acids. Lipid coatings that surround the protein coatings, but this is not present in all viruses. Viruses with lipid coatings are called enveloped viruses as opposed to naked viruses. Viruses do not carry enzymes needed to carry out the chemical reactions for life. Instead, they carry only one or two enzymes that decode their genetic instructions. Thus, viruses depend on host cells for viral production and nutrient. Concerning nutrient acquisition, emphasizing thorough biochemistry, how is such process accomplished in detail? What is the active physiology during such process? Terms that may be of interest Lytic cycle Lysogenic cycle Note: electron microscope may not be accessible in abundance, however this activity part will still be pursued. Some aspects of part A are applicable or can be parallel, while others are not; figure such out. PART C May also treat other non bacteria microorganisms, which would lead to a comprehensive study for nutrition in microbiology. 37. Botanical Hormones (I). Types (and likely each type will have variation) auxins gibberellins ethene Other examples: http://www.cannagardening.com/plant_hormones (II). Genes that are responsible for such and reasons for dominant and recessive traits. (III). Creation/metabolism of such hormones and pathways. Will pay close attention to what functional groups in such hormone compounds are responsible for influencing ideal functions of respective hormone in ideal biological environments. Will also incorporate use of software to assist with biochemical molecular modelling, where some of such software provides prediction for spectroscopy characterisation (to be compared to professional databases). (IV). How are hormone concentrations regulated along with the biochemistry for such? (V). How are hormones stored? Will also make use of software to assist with such biochemical molecular modelling to recognise the storage states and the associated bonds in sugars and fats, and what chemical reactions will lead to the synthesis from such storage. (VI). Pursuit of isolation and extraction of plant hormones. An example text that may be of use: Koshiba T. (2010). Plant Hormones. Methods and Protocols, 2nd edn. Annals of Botany, 105(4), viii. As well, pursue journal article guides for such that provide highly economic means. (VII). Will recognise commercial usage of plant hormones and inquire about how they are manufactured on large scales. Based on (vi) and assuming there are methods to preserve such hormones outside of ideal biological environments, will like comparative spectroscopy analysis between hormones extracted based on (vi) and commercially manufactured samples; will like means to definitely identify hormones without destroying samples or large quantities. (VIII). Experiments with hormones on plants based on (VII) may or may not be feasible due to time constraints with botanical development. If feasible one must consider what environmental controls are to be administered among various trials. Regression models can be applied to data and causal inference and lurking variables. (IX). The latter 2 of the 3 mentioned hormones are influential on the ripening and spoiling of fruits. Sterilized fruits with temperature and moisture experiments concerning metabolic and quantity levels of hormones can be feasible. (X). Clearly differentiate between regulation processes in single cellular/microorganisms and animalia hormone processes. What are the major gaps or significant differences? (XI). Can plant hormones be used for human medicinal purposes? Note: in the future one can pursue other types of hormones for functions such as immunity defence, competitor signalling, etc. 38. Protein Function Alberts B, Johnson A, Lewis J, et al. Molecular Biology of the Cell. 4th edition. New York: Garland Science; 2002. Protein Function. Available from: https://www.ncbi.nlm.nih.gov/books/NBK26911/ Will make use of chemistry, different biochemical software for simulations and computations, and lab experiments to confirm the 27- 29 significant statements from source above. A few of the major statements --> --All proteins bind to other molecules; significant features that make this universal. --The Details of a Protein’s Confirmation determine its chemistry --Sequence Comparisons between protein family members highlight crucial ligand biding sites --proteins bind to other protein through several types of interfaces --The binding sites of antibodies are especially versatile --Binding strength is measured by the equilibrium constant --Enzymes are powerful and highly specific catalysts --Substrate binding is the first step in enzyme catalysts --Enzymes speed reactions by selectively stabilizing transition states --Enzymes can use simultaneous acid and base catalysis --Lysozyme illustrates how an enzyme works --Tightly bound small molecules add extra functions to proteins From all encountered statements and topics will like to determine or develop a systematic method for protein identification and structure based on chemistry, software and experiments, unique to spectroscopy. May be given protein proteins to work on. Can functional groups be determined based on such developed methodology? After conclusion drawn by students, molecules will then be revealed and students will observe the spectroscopy of them from databases to determine to have a gauge on how accurate they are. Students in general will not be penalized or ridiculed as along as the applied chemistry, software usage and lab experimentation are competent and correct. How conclusive or effective is the developed methodology? How economically tasking is such methodology? Apart from analytical modelling, in labs or simulations among different molecules (and family of molecules) will like data fitting for --> Enzyme kinetics Binding energies (likely to vary with molecular bindings considered) Activation energy models (likely to vary with molecular bindings considered) Here are some of these major statements (there are crucial others in provided source) --> 39. Guide to the Expression of Uncertainty in Measurement (GUM) and transcendence Thoroughly identify and analyse GUM. Our goal is to develop a logistical framework that’s universal with any experimentation in science. Developing competence is quite important. Re-orchestrating some basic physics and chemistry labs students may encounter uncertainty treatment. Will like to extend to such particular labs with the analysis from part A. PART A Analysis from the following guides --> 1. Evaluation of measurement data — Guide to the expression of uncertainty in measurement — JCGM 100:2008 https://www.bipm.org/utils/common/documents/jcgm/JCGM_100_2008_E.pdf 2. Evaluation of measurement Data – Supplement to the “Guide to the Expression of Uncertainty in Measurement” – Propagation of Distributions using a Monte Carlo Method. JCGM.101: 2008 3. Barry N. Taylor and Chris E. Kuyatt (1994). Guidelines for Evaluating and Expressing the Uncertainty of NIST Measurement Results. NIST Technical Note 1297. 4. https://isotc.iso.org/livelink/livelink/Open/8389141 5. Ferrero, A., & Salicone, S. (2018). A Comparison Between the Probabilistic and Possibilistic Approaches: The Importance of a Correct Metrological Information. IEEE Transactions on Instrumentation and Measurement, 67(3), 607-620. Other applications ---Krouwer, J. (2003). Critique of the Guide to the expression of Uncertainty in Measurement Method of Estimating and Reporting Uncertainty in Diagnostic Assays. Clinical Chemistry, 49(11), 1818-21. ---Velychko, O., & Gordiyenko, T. (2009). The use of Guide to the Expression of Uncertainty in Measurement for Uncertainty Management in National Greenhouse Gas Inventories. International Journal of Greenhouse Gas Control, 3(4), 514-517. 40. Genome determination labs Software --> R and packages of interest (BiocManager, ChemmineR, dPCP, MAPITR) Thodberg, M., & Sandelin, A. (2019). A step-by-step guide to analysing CAGE data using R/Bioconductor. F1000Research, 8, 886 Cao, Y., Charisi, A., Cheng, L. C., Jiang, T., & Girke, T. (2008). ChemmineR: a compound mining framework for R. Bioinformatics (Oxford, England), 24(15), 1733–1734 < manuals.bioinformatics.ucr.edu/home/R_BioCondManual > < cran.r-project.org/web/packages/BiocManager/vignettes/BiocManager.html > Plant breeding and genomics < https://plant-breeding-genomics.extension.org/r-tutorials/ > PART A Brown T A. Genomes. 2nd edition. Oxford: Wiley-Liss; 2002. Chapter 7, Understanding a Genome Sequence. Available from: https://www.ncbi.nlm.nih.gov/books/NBK21136/ The mentioned outcomes from such above chapters of both texts are listed beneath, however, after reading further texts and articles may be required to analyse the intricate details and logistics. --Describe the strengths and weaknesses of the computational and experimental methods used to analyse genome sequences --Describe the basis of open reading frame (ORF) scanning, and explain why this approach is not always successful in locating genes in eukaryotic genomes --Outline the various experimental methods used to identify parts of a genome sequence that specify RNA molecules --Define the term ‘homology’ and explain why homology is important in computer-based studies of gene function --Evaluate the limitations of homology analysis, using the yeast genome project as an example --Describe the methods used to inactivate individual genes in yeast and mammals, and explain how inactivation can lead to identification of the function of a gene --Give outline descriptions of techniques that can be used to obtain more detailed information on the activity of a protein coded by an unknown gene --Describe how the transcriptome and proteome are studied --Explain how protein interaction maps are constructed and indicate the key features of the yeast map --Evaluate the potential and achievements of comparative genomics as a means of understanding a genome sequence Mentioned experiments that are deemed economic will be pursued in lab. Yeast will not be the only pursuit. There’s interest in botany, animal and human cells as well. There are various software, databases and clouds mentioned in the “Goody Bag” post to compare with. If needed the R environment with particular packages are verify useful. PART B Micro Array Analysis Micro array experiments will be pursued Alberts B, Johnson A, Lewis J, et al. Molecular Biology of the Cell. 4th edition. New York: Garland Science; 2002. Studying Gene Expression and Function. Available from: https://www.ncbi.nlm.nih.gov/books/NBK26818/ Taub, Floyd (1983). "Laboratory methods: Sequential comparative hybridizations analysed by computerized image processing can identify and quantitate regulated RNAs". DNA. Tarca, A. L., Romero, R., & Draghici, S. (2006). Analysis of Microarray Experiments of Gene Expression Profiling. American journal of obstetrics and gynecology, 195(2), 373–388 Jaksik, R., Iwanaszko, M., Rzeszowska-Wolny, J., & Kimmel, M. (2015). Microarray Experiments and Factors which Affect their Reliability. Biology direct, 10, 46 Bobashev G.V., Das S., Das A. (2002) Experimental Design for Gene Microarray Experiments and Differential Expression Analysis. In: Lin S.M., Johnson K.F. (eds) Methods of Microarray Data Analysis II. Springer, Boston, MA Júlio S. S. Bueno Filho, Steven G. Gilmour and Guilherme J. M. Rosa. Design of Microarray Experiments for Genetical Genomics Studies. Genetics, 2006 vol. 174 no. 2 945-957 Activity may go beyond genome detection. The following source provides various other applications that can be pursued --> https://en.wikipedia.org/wiki/DNA_microarray After readings, further texts and articles may be required to analyse the intricate details and logistics. There are various software, databases and clouds mentioned in the “Goody Bag” post to compare with. If needed the R environment with particular packages are verify useful. 41. Analysis, Logistics and experimentation for development of vaccines A. Basic questions --> Towards developing a vaccine, where does one start? What common methods or investigations are applied to do just that? Are vaccines more economic long term than antibiotics? Note: the adjective “economic” doesn’t only imply finance. B. Analysis of methods C. Logistics for chosen methods and investigations D. Will use very old and generic vaccines upon low threat microbes to confirm the vaccine research. One must clearly understand the applied investigation/process of prospective vaccine determination; will replicate/reproduce all such in lab. E. Testing vaccine Example sources to build activity upon --> --Detrick, B., Hamilton, R. G. and Schmitz, J. L. (2016). Manual for Molecular and Clinical Laboratory Immunology. ASM Books Series, ASM Press, 1240 pages --Grimes, S. E. A Basic Laboratory Manual for the Small-Scale Production and Testing of I-2 Newcastle Disease Vaccine. RAP publication 2002/22. FAO-APHCA --Rid, A. et al. (2014). Placebo use in vaccine trials: recommendations of a WHO expert panel. Vaccine, 32(37), 4708–4712 NOTE: will be using isolated tents. NOTE: for economic reasons chosen operations will be similar but not exact as described observations from example sources. NOTE: there may be ethical issues for some, so will try to reduce operations with elements of animal reproduction. NOTE: sterilization and annihilation of cultures or microbes after use of tools are essential; includes lab. Other things may need to be disposed of properly. 42. Guiding principles for monte carlo Analysis Students must successfully complete Biostatisitcs I & II to participate in this activity. Literature of concern --> Guiding Principles for Monte Carlo Analysis. Risk Assessment Forum U.S. Environmental Protection Agency, EPA/630/R-97/001: https://www.epa.gov/sites/production/files/2014-11/documents/montecar.pdf Literature provided is quite condense. A major goalis to develop a framework where all methods and analyses are sequential in a fluid, tangible and practical manner. Activity will be heavily reliant on data from labs and field activities. Activity will make extensive usage of R and RStudio. 43. Virology Labs Recital Activity will be based on the lab experience frm the following courses: Virology Tissue Culture & Virology Lab Hence, prerequisite will be students have taken at least the Virlogy course. Notes taken will be fast tracked and encountered labs will be replicated, however organisms may be different. Labs include use of all encountered software and journal articles. 44. Cyanobacteria Oxygen Production Involves multiple types of cyanobacteria in analysis and experimentation Environments: acquatic, quatic + ferrous A. Description of biochemical processes Will identify any uniqueness among the chosen types of cyanobacteria B. Modelling dcyanobacteria population/growth General analytical bacteria modelling Use of databases and software to refine prior For different types of cyanbacteria C. Investigtiong the role of the following variables on cyanobacteria growth and oxygen production Brightness UV Radiation Vacuum UV (100–200 nm) UVC (200–280 nm) UVB (280–315 nm) UVA (315–400 nm) Temperature Atmospheric Pressure Salinty < fresh to various levels of salinity > Acidity Carbon Dioxide concentration Nitorgen concentration What is hazardous to cyanobacteria gowth and stability? D. How do such prior variables in (C) influence our development in (B)? E. issue with toxins as by-products of cyanobacteria metabolism, and resolutions F. Cyanobacteria playing a crucial role in nitrogen fertilizer. Description of biochemical processes Will identify any uniqueness among the chosen types of cyanobacteria G. Coexistence with other organisms in environment Competition? (sustenance, terrain & competing biochemical processes) Mutualism? Detail biochemical processes H. Chloroplast being cyanobacterium living within plant cells. Research such. Following, how can we prove such with lab experiments? Lab experiments will be pursued. I. Developments from (A) through (H) will be applied to design and administer robust lab experiements. Additionally, the following literature can be very useful for activity: Salinity Intelligence --> Martin Hagemann, Molecular Biology of Cyanobacterial Salt Acclimation, FEMS Microbiology Reviews, Volume 35, Issue 1, January 2011, Pages 87–123 Shetty, P., Gitau, M. M. and Maróti, G. (219). Salinity Stress Responses and Adaptation Mechanisms in Eukaryotic Green Microalgae. Cells, 8, 1657 Pade, N., & Hagemann, M. (2014). Salt Acclimation of Cyanobacteria and their Application in Biotechnology. Life (Basel, Switzerland), 5(1), 25–49. General Intelligence --> Rantamäki S, Meriluoto J, Spoof L, Puputti EM, Tyystjärvi T, Tyystjärvi E. Oxygen produced by cyanobacteria in simulated Archaean conditions partly oxidizes ferrous iron but mostly escapes-conclusions about early evolution. Photosynth Res. 2016 Dec;130(1-3):103-111 Szeinbaum N, Toporek YJ, Reinhard CT, Glass JB. Microbial helpers allow cyanobacteria to thrive in ferruginous waters. Geobiology. 2021 Sep;19(5):510-520. Verseux, C., Heinicke, C., Ramalho, T. P., Determann, J., Duckhorn, M., Smagin, M., & Avila, M. (2021). A Low-Pressure, N2/CO2 Atmosphere Is Suitable for Cyanobacterium-Based Life-Support Systems on Mars. Frontiers in microbiology, 12, 611798. Kihara, S., Hartzler, D. A., & Savikhin, S. (2014). Oxygen Concentration Inside a Functioning Photosynthetic Cell. Biophysical Journal, 106(9), 1882–1889 45. Medical Drugs PART A: Drug Discovery Rather being a course, to operate as an activity. For mentioned tools and technologies it’s likely that generic versions can be substitutes. Fray, M. L. et al (2013). A Practical Drug Discovery Project at the Undergraduate Level. Drug Discovery Today Volume 18, Numbers 23/24 PART B: Drug Design for Undergraduates The given article is a basic guide towards drug design. Naturally, instructor can expand upon such article. Tantillo, D. J. et al (2019). Computer-Aided Drug Design for Undergraduates. Journal of Chemical Education, 96(5), pages 920 – 925 Further expansion: Sliwoski G, Kothiwale S, Meiler J, Lowe EW Jr. Computational methods in drug discovery. Pharmacol Rev. 2013 Dec 31;66(1):334-95 Concerning both prior articles any software specifically mentioned can possible be substituted by the following << Dalton, CP2k, Firefly, Gaussian, GAMESS-US, MOLDEN, NWchem, GPAW, Octopus, ORCA, FreeON, PUPIL, VOTCA, BOSS >> << VMD (with NAMS), GROMACS, VOTCA, Desmond, UCSF Chimera, Molsoft, CCPN, RedMD + RedMDStream (http://bionano.cent.uw.edu.pl/software/) >> << TINKER >> Constituents of biochemistry/metabolic biology can also expand upon this activity with comprehensive pathway mapping and associated metabolic reactions throughout; possibly, also identifying side effects throughout metabolism. PART C: Drug Delivery Determine most constructive order: Farrell, S., Savelski, M., Hesketh, R. and Slater, C. S. (2006). Experiments in Drug Delivery for Undergraduate Engineering Students. American Society for Engineering Education Farrell, S and Hesketh, R. (2002). An Introduction to Drug Delivery for Chemical Engineers. Chemical Engineering Education http://users.rowan.edu/~hesketh/hesketh/cee%20drug%20delivery.pdf Farrell, S. and Vernengo, J. (2012). A Controlled Drug-Delivery Experiment Using Alginate Beads. Chemical Engineering Education, v46 n2 p97-109 Farrell, S. et al An Experiment to Introduce pH-responsive Hydrogels for Controlled Drug Delivery: Mechanical Testing. 120th ASEE Annual Conference and Exposition 2013

46. Chemistry of Flavour and Fagrances Engineering compounds or molecules to replicate taste types and smells. Obligations --> Memory Consolidation Include sensory and neural processes Some Key Areas in Development Considerable use of biochemistry and organic chemistry Modelling and Simulation software operations Hypotheses and means of validation Synthesizing processes and production models Stablization of compounds/molecules Behaviour with other substances and hazards analysis Means of safety testing Assisting texts --> Rowe, D. J. (2004). Chemistry and Technology of Flavours and Fragrance, WileyBlackwell Berger, R.G.. (2007). Flavours and Fragrances: Chemistry, Bioprocessing and Sustainability, Springer-Verlag Berlin Heidelberg Sell. C. S. (2006). The Chemistry of Fragrances: From Perfumer to Consumer. Royal Society of Chemistry NOTE: particular laboratory methods/techniques from texts will be pursued 47. Bioprocessing PART A Experiment 9 from the Food Chemistry course can apply here, but will be extended with temperature studies, and studies among various added yeast and added sugar types agents. Will also be pursuing enzymology operations. NOTE: activity will take on a serious bioprocessing tone, hence technical features such as models, modelling, parameters, quantities and measures will be emphasized. Other possible interests: mixed atmosphere packaging, pasteurization, and waste treatment. Software of interest R + R Studio Excel COCO (+ ChemSep), DWSIM (+ ChemSep) << Combase (Predictor and Modelling Toolbox) with MRV, USDA Pathogen Modeling Program, EPA Virulo >> PART B Insulin production with yeast Laboratory production of insulin by recombinant DNA technology with yeast population growth. Fermentation or whatever process to be coerced in a isolated environment; characteistics of environment must be particular and stable to acquire both optimal yeast growth and optimal insulin production. Satefy protocols and regulation with microbes Review of recombinant DNA technology Process and logistics for yeast with recombinant DNA technlogy Environmental conditions regulation For optimal yeast growth & optimal insulin production Identify & comprehend models, modelling, parameters & measures Biochemistry and Organic Chemistry modelling Analysis with possible by-products Stoichiometry Growth models based on whatever parameters prefrences Production expectation at time Tfinal Tools and structure for data gathering and assurance Description and profiling of the biprocessing system Means of insulin separation & gathering for storage & long term stablity Walk-through of operation procedures of bioprocessing system With logistical saftey protocols for whatever phases With tools and structure for data gathering and assurance Review of preparation for the relevant phases in development Implementation of bioprocessing Means of confirming insulin product Means of determining gross production and if consistent with preliminary modelling expectations Economics and innovation with technologies Software of interest R + R Studio Excel COCO (+ ChemSep), DWSIM (+ ChemSep) << Combase (Predictor and Modelling Toolbox) with MRV, USDA Pathogen Modeling Program, EPA Virulo >> A possible assist: Baeshen, N. A. et al. (2014). Cell Factories for Insulin Production. Microbial Cell Factories, 13, 141 48. Detection of Metabolites of Narcotic Drugs Activity may be a challenge to pursue due to legal grounds and policies of medical services. PART A Profiling or characteristion of illegal drugs (cocoaine, heroine, etc.) and opiods PART B Biochemical pathways for process aliments, disease. PART C Modelling and simulation of drugs (functional groups, active sites and reactions) subject to part B. Software use modelling and simulation will follow. The following are literature of interest throughout activity (but can be augmented by others): --Braithwaite, R. A. et al (1995). Screening for Drugs of Abuse. I: Opiates, Amphetamines and Cocaine. Annals of Clinical Biochemistry, 32(2), 123–153. --Simpson D, et al. (1997). Screening for Drugs of Abuse (II): Cannabinoids, Lysergic acid Diethylamide, Buprenorphine, Methadone, Barbiturates, Benzodiazepines and Other Drugs. Ann Clin Biochem. 1997 Sep;34 ( Pt 5):460-510. --Recommended methods for the Identification and Analysis of Fentanyl and its Analogues in Biological Specimens. UNODC -Busardo, F. P. et al (2019). Ultra-High-Performance Liquid Chromatography-Tandem Mass Spectrometry Assay for Quantifying Fentanyl and 22 Analogues and Metabolites in Whole Blood, Urine, and Hair. Front Chem. 7: 184 --Hazarika, P. et al (2010). Multiplexed Detection of Metabolites of Narcotic Drugs from a Single Latent Fingermark. Anal. Chem. 82(22), 9150–9154 --Pantano, F. et al (2017). Determination of Oxycodone and its Major Metabolites Noroxycodone and Oxymorphone by Ultra-High-Performance Liquid Chromatography Tandem Mass Spectrometry in Plasma and Urine: Application to Real Cases. Clinical Chemistry and Laboratory Medicine (CCLM), 55(9), 1324-1331. 49. Bacterial Toxins Purposes and stimuli Genome, genes, pathways, synthesizing, etc. Hopefully, one can create a contained “biosphere” having both bacterial and viral cultures (and possibly other types of microorganisms present), to observe the role of “toxins”. Analysis of conditions for stability. Neutralization. Dangers of “toxins” to humans Effects (ailments and diseases) Pathways Metabolic Pathways Conditions for toxin stability Transmission possibilities Neutralization Note: may also consider analogy for plant life welfare Literature assist --> Sharma, A. K., et al. (2017). Bacterial Virulence Factors: Secreted for Survival. Indian journal of Microbiology, 57(1), 1–10 Schmitt, C. K, Meysick K.C. & O'Brien A. D. (1999). Bacterial Toxins: Friends or Foes? Emerg Infect Dis. 5(2):224-34. Rudkin J. K., McLoughlin R.M., Preston A., Massey R. C. (2017) Bacterial Toxins: Offensive, Defensive, or Something Else Altogether? PLoS Pathog 13(9): e1006452. Harms, A. et al (2018). Toxins, Targets, and Triggers: An Overview of Toxin-Antitoxin Biology. Molecular Cell 70, pp 768 – 784 Software for possible intelligence and profiling throughout development --> << COPASI, Pathvisio + Cytoscape + KEGG >> << Combase (Predictor and Modelling Toolbox) with MRV, USDA Pathogen Modeling Program, EPA Virulo >> << VCell, TiQuant + TiConstruct + TISIM >> << BLAST, Unipro UGENE, Bioclipse, Staden Package, Bioconductor >> Software to be applied for modelling and simulation (mandatory): << VMD (with NAMS), GROMACS, VOTCA, Desmond, UCSF Chimera, Molsoft, CCPN, RedMD + RedMDStream (http://bionano.cent.uw.edu.pl/software/) >> << TINKER >> << EMBOSS + JEMBOSS + Pise + wEMBOSS + EMBOSS-Explorer >> For modelling and simulation, concerned with environments of high toxin functionality. The biochemical or molecular biological processes that lead to products, by-products and effects in the overall process (against other microorganisms and humans) with high functionality. Investigating neutralization resolutions as well. 50. Viroids and Prions (COMING SOON) Note: various lab sequences or sets from microbiology courses or metabolic biology can be extended or advanced to serve as activities; for the courses built upon they will be prerequisites however. Will have chosen lab sequences or sets from courses. Note: there’s the possibility of other projects. Other activities in Microbiology and Metabolism/Biochemistry are possible. There are other activities for Life Sciences students under Chemistry. Check such section. JOINT RESEARCH VENTURE POSSIBILITY Between the Oceanography and Biological Sciences (Oceanography, Microbiology, Metabolic Biology). Of interest are “Analytical Methods” and Research Publications” from the links: Method 544: Determination of Microcystins and Nodularin in Drinking Water Method 545: Determination of Cylindrospermopsin and Anatoxin-a in Drinking Water Method 546: Determination of Total Microcystins and Nodularins in Drinking and Ambient Waters Method for Determination of Cylindrospermopsin and Anatoxin-a in Ambient Freshwaters Method for Determination of Microcystins and Nodularin in Ambient Freshwaters Models of ecophysiology (PnET) Forest growth and carbon exchange (EDII) Forest landscape processes (Landis-II) Earth systems (CLM5) C. BOTANY NOTE: this degree pursuit will have one additional course more than the other degrees, but the ends will justify such investment. --Core Courses Scientific Writing I & II, General Biology I & II, General Chemistry I & II --Mandatory Courses Calculus for the Biological Sciences I & II, ODE, General Physics I --Mandatory Bridging Foundation Organic Chemistry I (with labs), Biochemistry (with labs), Organic Synthesis Laboratory, Cell Biology (with labs), Biostatistics I & II, Advanced Statistical Modelling and Machine Learning for Biostatistics, Geographical Information Systems --Mandatory Botany Foundation General Botany; Plant Symbioses; Field Botany; Plant Systematics; Plant Physiology; Dendrology; Aquatic Botany; Plant Nutrition; Plant Biochemistry; Functional Genomics; Plant Molecular Biology (with labs); Forest Ecology; Ecology Methods; Plant Pathology; Forest Pathology; Invasive Ecology; Plant Propagation I & II; Wildlife Conservation Models --Public Administration Internships (concerns no habitat destruction in forestry and conservation grounds) Botanical Gardens & Horticulture Forestry Ranger immersion Ecological Restoration Invasive Species Analytical Chemistry methods in various environments Substances Synthetics Pollution Contamination Pesticides Plantae Studies Biochemistry Nutrition Molecular Biology Genomics Pathogens and Diseases Biostatistics I Course concerns probability and statistics applied to problems in biology, industrial/occupational health, and epidemiology. Use of statistical software R for data analysis is emphasized extensively. Note: this course is designed for students majoring in the biological sciences with a second term calculus background. Through the extensive use of practical examples, this course is expected to motivate and teach students statistics knowledge that would be helpful for their major study. The computer program R is the standard statistical program for this course. Students will use R to complete data analysis projects. R can be downloaded and installed on your personal computer for free following instructions at http://www.r-project.org/. In addition, the R environment will be augmented by RStudio interface with other R packages. This course covers fundamental concepts in probability and statistics, including data description, design of experiment, probability rules and distributions, statistical inference and linear regression. Definitions will be learned through real-world examples and applications. Besides these traditional materials and subjects, topics and methods that are particularly applicable to the biological sciences will be introduced. Again, much focus on the applications of statistical ideas to realistic data and practices. Students are expected to use materials learned from this course to guide statistical practice for their major studies in the future. After successfully completing this course the expectation is that students will be able to: 1. To grasp concepts in probability and be able to apply basic probability rules, distributions, and laws to solve conceptual statistics questions 2. Use statistical guidelines and common sense to interpret the process of data collection, description and analysis, and to design statistically sound experiments 3. Learn various statistical inference techniques and be able to select appropriate methods for specific data sets and scientific purpose 4. Link the course materials with real-life examples, and explore the opportunities for other biological applications 5. Interpret statistical reports and carrying out data analysis using R. Several data projects will be assigned during the semester. Independent work is expected. This is not a course of “pen and paper finesse” succeeding the composition of gunk and bamboozle on a writing board. One can’t be successful in statistics by only writing down theory. Practice with an environment that applies intelligence and engagement is essential. There’s no point in doing statistics if one doesn’t know how to acquire and manipulate real data. Real data realistically outnumbers the fingers and toes one possesses. Most of grading will be based on projects (having commentary descriptions) accompanied by the analytical process development description done in a word processor. Typical Texts --> Will make use of R language Statistics texts under CRC Press and Springer publishing Tools --> R language and R Studio Note: a calculator at times may prove useful for the idealistic or the “synthetic” customary questions. “R Monograph Notebook” --> Students should maintain a notebook as they proceed through the course and learn how to do analyses in R. This assignment involves a notebook that lists the syntax and provides a brief explanation of each function that students learn during the course. Instructor will assign R maturity development questions to be in tune with course progress; you will only be allowed to use your monograph to assist with assigned questions. The notebook will be handed in near the end of the semester and handed back to the students after grading. Such a notebook can be an extremely useful resource both during and after the course to quickly refresh one’s memory on the details of a particular function. Design with R most likely will vary among students. Poor development in a such a notebook may or may not correlate with poor grades. NOTE: this course serves only to towards the perspective of students in the biological sciences, so no one in the biological sciences should be looking elsewhere. MIND YOUR DAMN BUSINESS. Grading --> Problem Sets 20% R Labs 20% R Activities 0.7 R Monograph Lab Notebook 0.3 R maturity development questions 15% End of term lecturer observation 5% 3 Exams 30% Assigned Projects 30% Exams --> Limited open notes. I don’t like setting up myself and students for embarrassment; you are not perfect with statistics, so expect exams to be primarily knowledge based and the calculus related fodder. Most of your development will come from homework and labs; it is what it is. Note: limited open notes. Students may be more comfortable with certain R packages. Again --> Several data projects will be assigned during the semester. Independent work is expected. Course Outline --> Introduction to statistics, data and R Statistical Measures and Summary Statistics for data sets Methods of data acquisition: Sources/databases (ecological & biological), file types, APIs, etc. Introspection. querying, wrangling Summary Statistics with R Applied probability theory Axioms of probability Modelling frequencies and establishing densities Simulating random variables from real experiments Probability distributions and properties Sample estimates Law of Large Numbers and the Central Limit Theorem Introduce the Law of Large Numbers (LLN) Central Limit Theorem (CLT). Identify Exponential, Poisson and Binomial data and respectively determine in a manner to confirm LLN and CLT. Routledge, R., Chebyshev’s Inequality, Encyclopaedia Britannica Is there too much reliance on assuming normal or Gaussian distribution? Towards Chebyshev’s inequality what amount of repetition (regarding LLN and CLT) of an experiment is adequate towards Chebyshev becoming relevant? Overview and goals of various concentration inequalities (just a survey). Chi-square distribution The bottom line is to establish the flow of the uses competently with applications involving real raw data. Comprehending categorical data sets and ordinal data sets Organisation of data and sensitivity of categories concerning traits of interest. Test for independence McHugh ML. (2013). The Chi-square Test of Independence. Biochem Med (Zagreb). 23(2): 143-9. Test of homogeneity Test of variance Applications of the Chi-Square distribution with confidence intervals T-distribution Kim T.K. & Park J. H. (2019). More About the Basic Assumptions of T-test: Normality and Sample Size. Korean J Anesthesiol. 72(4): 331-335. Sample size determination Population parameter estimation Confidence intervals Directly logistical to understand what you’re doing in R F-distribution Assumptions for the F-distribution Relevance to the biological sciences (active data immersion) Note: not textbook finesse, rather how and when actively. Goodness of fit: fit of distributions Summary Statistics Skew and Kurtosis Box Plots Density Plots P-P and Q-Q Statistical Tests Definition, Null hypothesis One-sided & two-sided tests of hypothesis Types of test statistics Comprehending critical values for ideal distributions Significance levels Critical values for real raw data sets Does your data exonerate ideal distributions? Chi-Square Test Kolmogorov-Smirnov Test Anderson-Darling test Shapiro-Wilk Test MLE and Method of Moments Manual tasks will be limited to at most 4 element data sets Computational logistics for large data sets followed by implementation Review/probe data for goodness of fit module for appropriate distribution You may be tasked with distribution determination before parameter/point estimation Hypothesis testing (exploratory) Note: as aspiring biologists I can’t give “zombie textbook problems” and expect you to relate to a profession tangibly and fluidly. You will be exposed to raw professional data from various sources. You will develop the four mentioned steps. You should ask yourselves if the hypotheses are practical as well. Why is normal distribution assumed? Will be exploratory rather than zombie problems. Namely, knowledge and skills from Goodness of fit module. Then proceed with the following: 1.State the two hypotheses so that only one can be right 2.Formulate an analysis plan, outlining how data will be evaluated 3.Carry out the plan and physically analyze the sample data 4.Analyse the results and either reject the null, or state that the null is plausible, given the data Test of Proportions (exploratory) Comparisons of variances Directly logistical to understand what you’re doing in R Confidence limits for means. Does it require normality? Analysis of variance Must be exploratory, else it’s toxic Correlation (includes misuse of types and resolutions) Pearson Correlation Crucial Conditions Structure Implementation Spearman Correlation Crucial Conditions Structure Implementation Generating heat maps. The ggpairs() function Bivariate Regression Two and three-way analyses of variance Must be data exploratory, else it’s toxic Multiple Regression Model components Methods to select variables OLS MUST: Summary Statistics Analysis of Covariance Must be exploratory, else it’s toxic Non-parametric statistics Resampling methods Falsified Data Hartgerink C, Wicherts J, van Assen M (2016). The Value of Statistical Tools to Detect Data Fabrication. Research Ideas and Outcomes 2: e8860. Al-Marzouki, S., Evans, S., Marshall, T., & Roberts, I. (2005). Are these data real? Statistical methods for the detection of data fabrication in clinical trials. BMJ, 331(7511), 267–143. Yamamoto, K., & Lennon, M. L. (2018). Understanding and Detecting Data Fabrication in Large-Scale Assessments. Quality Assurance in Education, 26(2), 196–212. Prerequisites: General Biology II, Calculus II Biostatistics II --This succeeding course in the sequence will have more emphasis on incorporating journal articles and real world experiments. --Students will have to orchestrate inquisitions by exploratory data analysis and statistical methods involving R. There will be assigned data sets and journal articles to do just that. --This is not a “pen and paper course”. Texts and journal articles will cater to subjects both from prerequisite and this course. Means of data retrieval and manipulation are crucial; it may be the case that the data desired in inaccessible, hence students will have to resort to alternative data sources that yields much different conclusions. NOTE: personally refresh your knowledge and acquired R skills from calculus and Biostatistics I alongside ordained reacquaintances in course. NOTE: this course serves only to towards the perspective of students in the biological sciences, so no one in the biological sciences should be looking elsewhere. MIND YOUR DAMN BUSINESS, AND KEEP YOUR DAMN BUSINESS . Assessment --> Assignment Sets (prerequisite & current level from multiple sources) 15% Analytical and R based 3 Exams (prerequisite & current level) 30% Labs + Data Analysis Term Project 40% 2 Field Inquisitions with R 15% Conducted Journal Articles Computational Inquisitions Supporting data sets to be provided Gov’t administration field experiments inquisitions Assignment Sets --> Will be reacquainted with prerequisite tasks, prerequisite projects AND current level tasks (analytical and R computational). Exams --> Exams will have the same manner of administration and activities as exams from prerequisites. Yet, consisting of both prerequisite tasks AND current level tasks. Limited open notes. LABS WITH R --> Hypothesis Testing Expt. Design, Multiple Comparisons ANOVA Regression (Mult. Reg. and Dummy) ANCOVA Mantel Test & ANOVA MANOVA and DFA Clustering PCA Re-analysis of DFA Data Comparing & Averaging Models Analysis of Trait Evolution Fitting models of Trait Evolution TERM PROJECT --> The term project has been broken down into multiple components due throughout the semester to provide further guidance for students. On given date, students will select a dataset to use for their term project. Students can either provide their own dataset (if they have collected data during their research), or will be given the opportunity to analyse a complex dataset supplied by faculty as their term project. For the Hypothesis Activity (given due data), students will take a close look at their dataset and formulate biological hypotheses that they would like to test statistically. The assignment will be handing in these hypotheses. For the Experimental Design assignment (given due), students will outline which analyses they will use to test their biological hypotheses and provide the specific explicit statistical hypotheses that they will test. The Term Project Report (given due having additional 1 week collection buffer) will be written after students complete their analyses. The report will include a Statistical Methods and a Results section, complete with tables and figures. Methods should include sufficient detail to redo the analyses. The results should include everything necessary for interpretation of their analyses and data, but not superfluous material. Term Project Reports for all students should include a title page with a title, student name, course number and name, and assignment name. The text of the report should be double spaced, with indented paragraphs, 1” margins, 12pt Times New Roman Font, and page numbers. Tables should be single spaced with headings above each table. Figures should have captions below each figure. Figures and tables can be embedded in the text or provided at the end of the document. Literature cited should follow the format for the journal Evolution. Assignments that do not follow these formatting instructions will be returned to the student for correction prior to grading. NOTE: most labs done serve as structure for your HA and ED NOTE: I will be collecting your R development (having sensible commentary) for the term project in PDF along with the term report in PDF. Finally, students will give a short, in-class presentation about their study, analyses and findings. Presentations will be in PowerPoint. MAJOR COURSE TOPICS --> Methods of data acquisition, data wrangling and summary statistics (prerequisite reinforcement) Goodness of Fit (prerequisite reinforcement) Hypothesis Testing Review Experimental Design & Sampling ANOVA Variations & Models Regression (multivariate) Quantile regression compared to Least Squares regression ANCOVA Resampling Techniques MANOVA Clustering (K-means or DBSCAN?) Principal Component Analysis (PCA) and Kernel PCA Model Selection & Likelihood (emphasis on computational logistics and implementation) Phylogenetic Regression Extensions of Phylogenetic Statistics Prerequisite: Biostatistics I Advanced Statistical Modelling and Machine Learning for Biostatistics This course explores advanced statistical modeling techniques and machine learning methods as applied to biostatistical problems. Topics include generalized linear models, hierarchical modeling, Bayesian statistics, and the integration of machine learning algorithms for analyzing complex biological and health data. Note: 2 lectures per week, with approximately 2 hours per lecture. Assignments -- Assignments will be quite laborious in the interest of sustainability with knowledge and skills through your journey in biostatistics. Each assignment will comprise of the following elements: A. problems and tasks encountered in both Biostatistics I & II. Such problems and tasks will also make extensive use of R. As well, being advanced biostatistics students, projects from Biostatistics I & II can/will also be considered basic assignments as well. B. Course level assignments to such given course topics. Good emphasis on ability to comprehend and specify the transition from prerequisite skills/tools to course level tools/method/skills; then implementation. Will also make extensive use of R. Data Science Basics Quizzes -- For the Data Science Basics module there will be handwritten quizzes to test knowledge, comprehension, appropriateness and T/F. Exams -- Exams will account for all modules. Assignments will be strong foresight of what’s to appear on exams. You will be making extensive use of R with open notes for all course modules. Exams will feel like projects where each “project” will involve multiple modules. Make-up Student Project -- Applying Advanced Models to Biostatistical Data. Concerns students who are interested in making up lost weight towards their final grade; the better you did in this course, the lower the value. Can regain up to 5% for final grade. Students will be given a sack to randomly (and blindly) pick a project. Students will have until 2 days before the final grade submission deadline to submit projects. Students will be privately given project details via student email where they will have to acquire the data from specified sources. Course Assessment -- Assignments 20% 4 Exams for all modules 60% 3 Data Science Basics Quizzes 15% Will be precursors to exam(s) for the Data Science Basics module Make-up Student Project (being conditional) COURSE OUTLINE -- WEEK 1-3. Introduction to Generalised Linear Models (GLMs) with model estimation and summary statistics Multilinear Regression (fast fast review) Quantile Regression Logistic Regression Poisson Regression WEEK 4-5. Hierarchical Modelling (HM) Introduction to HM Multilevel Modelling Random Effects and Mixed Models WEEK 6-7. Bayesian Statistics in Biostatics Note: I don’t introduce things to be a disgusting, miserable, viral bastard. Module will be extremely goal oriented, namely, problem, goal(s), methodology, logistics, implementation, evaluation. No social nor psychological probes/inquisitions; there are certified licensed professionals elsewhere tied to meaningful or economic interests. Bayesian Inference (to the point, constructive and economical) Markov Chain Monte Carlo (MCMC) Methods – only constructive and economical methods Bayesian Regression Models WEEK 8-9. Advanced GLMs and Extensions Negative Binomial Regression Zero-Inflated Models Generalised Estimating Equations (GEE) WEEK 10-15. Data Science Basics Note: subjects of overfitting or underfitting arise in model validation statistics. Data Acquisition. Data Probing: view(), glimpse(), str() Data Cleaning and Data Wrangling Summary Statistics, Skew, Kurtosis, Correlation Analysis and Heatmaps Machine Learning Overview Feature Selection R functions (underlying methods may not be fully comprehended, but that’s generally the world): Principal Component Analysis (PCA), Kernel PCA, Boruta, FSelectorRccp. Comparative observation among such prior three also expected. Classification Multiple Regression (very rapid review) OLS and Quantile Support Vector Machines Decision Trees Random Forests Clustering (K-Means and DBSCAN advanced repetition) Includes the Silhouette Score and Davies-Bouldin Index Prerequisites: General Biology II, General Chemistry II, Biostatistics II General Botany The main objective of this course is to introduce the student, who is majoring in Biology, to the wonders of the Plant Kingdom and its (often) closely allied Kingdoms of Bacteria, Archaea, Fungi, and Protista. Applied Botany will be a focal point of the laboratory exercises in hopes of creating an ongoing interest in the science of plants. Literature: Mauseth, J. D. (2019). Botany: An Introduction to Plant Biology. Jones & Bartlett Learning Lab Manual: Mauseth, J. D. (2019). Botany: A Lab Manual. Jones & Bartlett Learning Assessment: 3 Exams Labs Final Exam Labs --> Lab topics will be chosen to coincide with lecture topics where possible. Leaf identification of selected tree species will also be an integral part of lab. Course Outline --> General Introduction The Development of Plant Study/What is Plant Biology? Differentiation between plantae, Protista and Fungi. Common misconceptions in aquatic environments Animal cell versus the plant cell Plant Cell Structure & Function Plant Metabolism/Photosynthesis Plant Metabolism/Respiration Plant Growth and Development Plant Hormones and Environmental Response EXAM I Plant Tissues Roots Stems Leaves EXAM II Reproductive Morphology/Flowers Reproductive Morphology/Fruit Reproductive Morphology/Seeds The Plant Life Cycle/Meiosis and Alternation of Generation Movement of Water & Solutes in Plants 9 Soils EXAM III Classification & Systematics Bacteria & Viruses Fungi & Lichens Protistans/Algae Bryophytes Ferns & Their Relatives Gymnosperms 22 Angiosperms FINAL (comprehensive) Prerequisites: General Biology I & II, General Chemistry I & II Plant Symbioses Course aims to foster a deeper comprehension of the crucial role symbioses play in shaping the diversity of life on the planet. Devoting roughly equal time to discussing broad concepts – such as generalities among symbioses, origins and establishment of symbioses, coevolution and co-speciation – and learning the specifics of well-studied exemplars of plant-bacterial, plant-fungal, plant-animal, and plant-plant symbioses. Often a 2 credit course. Upon completion of this course, you will be able to: Define symbiosis in several ways Describe the evolutionary and ecological significance of symbioses Explain our current understanding of how symbioses form and how they are maintained Discuss how symbiosis can lead to diversification Summarize the specifics of some symbioses involving Plants and bacteria Plants and fungi Plants and animals You will also practice: Evaluating and synthesizing journal articles Leading a discussion with classmates Literature: The Symbiotic Habit, Angela E. Douglas. 2010. Book excerpts and journal articles Assessment: Quizzes (10%) Attendance + Conduct + Written discussion synopses (30%) 3 Exams (60%) Course Outline Week (1) Introduction to Symbiosis; significance Case: ant plants Week (2) Example symbiosis 2 – Mycorrhizae Defining symbiosisWeek (3) Example symbiosis 3 - Grass endophytes Symbiotic spectra from antagonist to mutualist Week (4) Example symbiosis 3 – Cyanobacteria Evolution and partner capture Week (5) Example symbioses 4 - Pollination symbioses - Ficus and Yucca Costs of symbiosis and cheating Week (6) Vertical transmission and assimilation Example symbiosis 5 - Legumes and rhizobia Week (7) Establishment of symbioses Diversification and coevolution Prerequisites: General Biology I & II, General Chemistry I & II Field Botany This course is designed as an introduction to the diversity of plants found in natural systems. Since it is a field course, most of the students' time will be spent either in the field or working with specimens collected from the field. However, there are some basic ideas about systematics in general, plant systematics specifically, and plant evolution that will be presented in class. In addition, students will demonstrate proficiency with the basic terminology of plant morphology and plant taxonomy. The student will learn to collect plant specimens, preserve them, and present them in a format similar to specimens found in herbaria. Since habitat information will be taken with each specimen, students will learn to associate plants with different habitat types. In addition to the field elements, the student will learn to use the botanical literature and web-based resources needed to identify a specimen. Noteworthy: appropriate apparel and clothing expected. Please don’t insist on wearing full jet-black or heavy dark colours...but avoid white, off-white, cream or butterbean. Eco-friendly bug repellent/sunscreen, drinkable water, etc. Head gear for heat if need be, etc. A handy watch. An insulated smartphone (strictly for GPS, photos and emergencies if need be). Noteworthy: THIS IS A RAIN OR SHINE COURSE Course literature: A scholarly text of flora of the ambiance of concern A wildflower guide text Key events during course --> Initiate collections and begin preservation Examination Complete collections and preservation Complete identification Complete mounting Present collection for grading No collections or specimens will be accepted after due date Noteworthy: students should have decent and competent skills for record of specimen. Data for samples should be augmented with location, date, time, etc., etc. Objectives for Taxonomy vs Systematics --> The student will be able to: -Describe the function of classification -Distinguish between taxonomy and systematics and be able to identify a classification as systematic or taxonomic -Describe the reasons for preferring natural classifications over artificial classifications -Describe the reason that classical taxonomy is an hierarchical scheme of classification -Describe the role that key characteristics play in taxonomy -Describe why consistency is both valuable for taxonomy and hard to achieve. -Distinguish between phenetics and cladistics -Describe the essential features of a dendrogram, including its shape and the assumptions about time inherent in a dendrogram -Relate the reason that botanical taxonomy uses "division", rather than "phylum" as the hierarchical level below that of kingdom and above that of class -Define the following terms: Plant Morphology Classification Taxonomy Systematics Natural Classification Binomial Hierarchy Key Characteristic Consistency Phenetics Cladistics Dendrogram Division Phylum Objectives for Morphology --> The student will be able to: -describe and identify from a living plant the following structures: Stem, Leaf, Bud, Root, Node, Lenticle, Bract, Leaf Parts (Blade, Petiole, Midrib, Stipule), Leaf Veination (parallel, pinnate, reticulate), Leaf Margins (Smooth, Dentate, Serrate, Lobed Crenate), Leaf Arrangements (Alternate, Opposite, Whorled, Simple, Compound, Palmate, Pinnate, Bipinnate), Leaf Shapes (Elliptical, Obovate), Leaf Tip Shapes (Acute, Accuminate), Flower Types (Complete, Incomplete, Perfect, Imperfect), Flower Parts (Receptacle, Perianth, Calyx - Sepal, Corolla - Petal, Stamen, Anther, Filament, Pistil, Stigma, Style, Ovary, Carpel [Simple, Compound]), Flower Shapes (Radial, Bilateral [Zygomorphic], Superior, Inferior), Fruit Types (Drupe, Berry, Hesperidium, Pepo, Pome, Aggregate, Multiple, Samara, Nut, Grain, Achene, Capsule, Silique, Legume, Follicle) Objectives for Plant Kingdom--> The student will be able to: -Describe the common characteristics all plants share -Identify a specimen as a Bryophyte -Describe the characteristics that separate Bryophytes from other required plant divisions (see below for which plant divisions are required). -Identify a specimen as a Equisetophyte -Identify a specimen as a Lycopodiophyte -Identify a specimen as a Pteridiophyte -Describe the differences between Vascular Plants and Non-Vascular Plants. -Describe the differences between Flowering Seed Plants and Non-Flowering Seed Plants. -Identify a specimen as a Coniferophyte -Identify a specimen as a Cycadophyte -Identify a specimen as a Pteridiophyte -Identify a specimen as a Ginkophyte -Describe the differences between Monocots and Dicots in cotyledon number, leaf veination, flower part number, arrangement of stem vascular bundles, presence of secondary growth, and the manner in which roots originate.Identify a specimen as a Magnoliophyte -Identify a specimen as a Liliopsid -Identify a specimen as a Magnoliopsid -Define the following terms: Liana Epiphyte Cone Evergreen Deciduous -Diagram the Dendrogram of the Plant Kingdom presented on the web page Objectives for Plant Family --> For the following plant families (minimum): Aceraceae Cactaceae Compositae Curcubitaceae Fabaceae Fagaceae Orchidaceae Poaceae Rosaceae Solanaceae The student will be able to: Give the common and scientific names for the family; describe the general leaf, flower and fruit characteristics of members of the family; describe the importance of the family to the human economy and the uses to which members of the family have been employed. Note: there are around 24 characters for learning families of flowering plants. Objectives for Collection --> The student will collect, identify, and mount 25 specimens of local plant species. The student will present a collection that includes specimens from at least two plant taxonomic group above that of the family. The student will present a collection that includes specimens from at least ten different plant families. Course Assessment --> Evaluation will be based on a single examination and the plant collection to be done by each student. Each specimen must be presented properly preserved and identified (using the traditional hierarchical scheme of Kingdom, Division, Class, Order. Family, Genus, and Species). In addition, information on the collection date and locale and habitat must also be presented. Only specimens complying with all requirements will count toward the student's total. To learn what constitutes an acceptable specimen, go to the “Preservation”, “Mounting” and “Examples” guides. As the objective of this class is to learn about the local natural flora, horticultural cultivars (including hybrids) will not be accepted as specimens. In addition, the collection must present specimens from at least 10 different plant families and from at least two different taxa above the level of Family (i. e., from at least two different Classes or Orders). Failure to satisfy these criteria will result in the loss of particular points for the former and particular for the latter, subtracted from the total points earned. Once they are graded, the portfolios are the property of the student and can be retrieved from the instructor. They will be discarded on designated date if not picked up before. Class Attendance 5% Quizzes 15% 2 Exams 30% Collection (quantity, order, accuracy, quality) 50% NOTE: for class attendance there will be a threshold for days missed towards failure of course. For conduct in the field and in lectures there will be a policy towards pass of fail; includes, littering, pollution, texting, social media, music in the field, habitat damage, savagery upon living creatures. Prerequisites: General Biology I & II, General Botany Plant Physiology This course is designed to provide students with comprehensive exposure to the subject of plant physiology. The laboratory exercises provide hands-on experiences with experiments and training in instrumental skills. Topics include: water relations, photosynthesis, inorganic nutrition, metabolism of organic materials, and plant growth regulation, with emphasis on environmental factors in the physiology of plants. Lecturing Text --> Introduction to Plant Physiology, 3rd. William G. Hopkins Other references: Plant Physiology, 2nd. L. Taitz and E. Zeiger Plant Physiology, 4th. F. Salisbury and Cleon W. Ross Resources to accompany designated lab manual --> PHWYE – Plant Physiology/Botany: https://www.phywe.com/en/biology/university/plant-physiology-botany/ Journal of Experimental Botany (https://academic.oup.com/jxb) Park, S. (2021). Plant Tissue Culture: Techniques and Experiments. Academic Press By the end of this course, the student will be able to --> 1. Comprehend the fundamental concepts of plant physiology 2. Describe the physiological mechanisms of plant growth, function, and development 3. Recognize and describe how plants respond to their environment Assessment --> Quizzes 10% 3 Exams 60% Laboratory 30% Activities Reports and Presentations Lab reports and presentations --> Laboratory work is done in small groups. To foster learning and interaction among students, each group will design an experiment to conduct based on techniques learned in the course. Learning goals assessment--> Specific questions on exams and participation in class will be used to assess student knowledge of course learning goals, including demonstrated mastery of fundamental terms and mechanisms in plant physiology. In graded laboratory exercises, students will communicate their understanding of techniques used in the discipline. COURSE OUTLINE --> Introduction Course overview: the organization of plants and plant cells Part I: Water and mineral nutrients Water in plant cells Water relations of the whole plant Essential nutrients Nutrient uptake Exam I Part II: Photosynthesis and Respiration Photosynthesis: light and pigments Photosynthesis: light reaction Photosynthesis: carbon assimilation Photosynthesis: carbon allocation Respiration Exam II Part III: Regulation of plant growth and development Cellular basis of growth and development Plant hormones Auxin 16 Gibberellins Cytokinins Abscisic acid and ethylene Photomorphogenesis: responding to light Plant movements Photoperiodism Temperature control Part IV: Stress physiology and biotechnology Plant response to environmental stresses Biotechnology Exam III LABS --> Week 3 -- Lab 1 Water Relations Time domain reflectometry Relative water content Osmotic adjustment Transpiration rate Lab 2 How do plants/trees transport water under negative pressure? Replicate experimentation to best of ability and speculate/identify elements in plant/tree physiology that make transportation with negative pressure possible Shi, W., Dalrymple, R.M., McKenny, C.J. et al. Passive water ascent in a tall, scalable synthetic tree. Sci Rep 10, 230 (2020). If such process is innate in trees/plants can they function well in alien environments such as space, Moon’s surface, or environements with larger gravitation? Week 4 -- Lab 3 Nutrition Deficiency symptoms Nitrate-nitrogen concentration Week 5 -- Lab 4 (Part 1) Photosynthesis Photochemical efficiency Stomatal characteristics Leaf area meter Week 6 -- Lab 5 (Part 2) Photosynthesis Chlorophyll content Light meter Net photosynthetic rate Week 7 -- Lab 6 Respiration Net respiration rates Temperature and respiration Starch quantification Week 9 -- Lab 7 Plant Growth Regulators Effects of gibberellic acid on germination and growth Week 10 -- Lab 8 Plant Growth Regulators Lab 6 (cont.) Effects of auxin on rooting Week 11 -- Lab 9 Light Response Quantification Intensity/duration Direction Week 13 -- Lab 10 Abiotic Stress Drought Salinity Flooding Week 14 -- Wrap Up Prerequisites: General Botany, Organic Chemistry I and/or Biochemistry I Plant Systematics Will explore the origin and diversification of land plants while emphasizing flowering plants. You will become familiar with --Taxonomy (identification, nomenclature, classification emphasizing flowering plants), --Evolution (speciation, reproductive biology, adaptation, convergence, biogeography) --Phylogenetics (phenetics, cladistics, morphology and molecules). Labs emphasize learning representative families and genera of flowering plants in your ambiance with use of keys and manuals. A plant collection of 25 species is done. Assessment --> Labs + Lab quizzes Field Trips + Field Trip quizzes 2 Exams Texts --> Clark et al. 2014. Plant Systematics: Laboratory Manual and Supplementary Resources Judd, W. S. et al. 2008. Plant Systematics: A PhyloGenetic Approach. Sinauer Inc. Resources --> Manual for recognising the (50) most common plant families List of common plant families and major plant groups you should learn to identify Morphology vocabulary manual, and a list of plant morphology words you should know to help you identify and describe plants. Tools --> Hand lens (10X; preferably with neckband so you don’t drop it and loose it Digital camera (smartphone or tablet with camera is OK) - you will not be able to participate in class if you do not have access to a digital camera from which you can download photos Medium size notepad and lots of writing utensils; all should be sealable in a Ziplock Computer or tablet with internet access Come prepared with the following --> - Field boots or shoes (good ankle support is important, and there are rattlesnakes out there) - Hand lens - Ambiance flora (for keying practice) - Hat - Sunscreen and lip protectant - Pocket knife if you have one - Ziplock bags/containers/bags for collecting - Rain gear (if it’s threatening) - Insect repellent (eco-friendly) - Competent hydration fluid Laboratory--> Many of the laboratory sessions will be devoted to field trips. Other lab sessions will consist of a directed overview of the plant groups covered in the lecture. You can also work on identifying your plant collections during lab time. Attendance at lab is required. Most labs will have a quiz reviewing material from the lab. Periodically we will assign homework plants. These will consist of unknown plants that you attempt to key out with your textbooks. You will do this on your own time. Each lab quiz or homework will be worth 10 points, with a total of 100 lab quiz points for the semester. If we have more than a total of 100 possible lab quiz points, you may drop your lowest scores and count only the 10 best quiz grades Field Trips --> Several field trips have been scheduled during laboratory time. Attendance is required. Sometimes we may be a little late in returning. Activities take place whether rain or shine. you will collect and identify 25 plants that are in flower and/or fruit and make botanically accurate labels to accompany your specimens that note the collecting locality, date, collector, and additional attributes of the plant. More details will be forthcoming on this exercise. Quizzes and Tests --> Each field trip will include a quiz. Most of these will ask you to identify plants we have learned. Some may require you to key out “unknowns” with the help of your texts. We will also periodically hand out homework that should be done individually and out of class. We will also devote part of one lecture each week to quizzes to review your knowledge of plant families. Exams will cover lecture and lab material. Part of each exam will be a “practicum” asking you to identify various plants or answer questions about them. Prerequisite: Field Botany Dendrology Course serves to provide the student with an intensive and broad experience with respect to knowledge of trees for majors in botany. This experience will include identification and distribution of native and introduced trees, their biological characteristics, identification, habitat and ecology. Goals --> Describe important aspects of the morphology, anatomy, development and reproduction of trees using correct terminology. Describe the structure, function and importance of modern nomenclature and taxonomic systems. Describe the morphological, geographic, ecological and economic characteristics of important forest tree species of region or ambiance. Explain basic population, community ecology, and ecosystem-level concepts as it relates to the Plant Kingdom. Evaluate ecology and diversity in a global context and specifically in whatever region Demonstrate the ability to identify and classify trees and be able to problem solve and identify unknown species. Noteworthy: appropriate apparel and clothing expected. Please don’t insist on wearing full jet-black or heavy dark colours...but avoid white, off-white, cream or butterbean. Eco-friendly bug repellent/sunscreen, drinkable water, etc. Head gear for heat if need be, etc. A handy watch. An insulated smartphone (strictly for GPS, photos and emergencies if need be). Noteworthy: students should have decent and competent skills for record of specimen. Data for samples should be augmented with location, date, time, etc., etc. NOTE: THIS IS A RAIN OR SHINE COURSE Etiquette and formality in assessment for tools, analysis and data collection (procedures and rules) stemming from field activities will be given to students concerning the following attributes: Accuracy and location Quality Quantity Organisation NOTE: unique portfolio for mangroves, seashore trees and fruit bearing trees. Literature --> A Text of Dendrology Regional Dendrology resources (long range in time) Course Assessment Quizzes --> Family, Species, Genus, Common Name, geography, habitat, ecology Midterm Final Portfolio Presentation Prerequisites: General Biology I & II, General Botany, Plant Physiology. Aquatic Botany Course objectives: Aquatic plants are generally defined as those higher (vascular) plants completing their life cycles wholly or partly in a submerged state or in saturated soil. As well, course will treat algae due to similar functions as plants in the ecosystem. The goals of this course are: i) to learn the basic taxonomy of common aquatic plants and algae ii) to become familiar with the habitats where aquatic plants and algae are commonly found, iii) to understand the functioning of nutrient cycles in aquatic systems iv) to know the various definitions of wetlands, marine forests and important legislation applicable to wetlands and marine forests v) to understand the concepts of mitigation, restoration, constructed wetlands, marine forests, effluent dominated streams and wetlands, and how these are implemented vi) become familiar with control and management of aquatic plants and algae in perturbed and man-made ecosystems vii) become familiar with aquatic nuisance plant/algae species and their role in the environment viii) become familiar with the primary literature (scientific journals and reference books) in this field. The lab portion will focus on use of small ecosystems for study, short field trips to local wetlands, marine environments and familiarization with field instruments and water testing kits. NOTE: course has a rain or shine policy with any outdoor activity Literature (all necessary)--> Comprehensive texts on wetlands emphasizing, taxonomy and ecology Comprehensive texts on aquatic/marine algae emphasizing, taxonomy and ecology Comprehensive texts on the physiology and regulation of aquatic/marine plants and algae Journal articles Credible scientific agencies/ministries Exams --> Exams will be comprehensive and questions will come from lectures, textbooks, labs, student presentations, handouts and field trips. (Hint: topics which arise in two or more of these areas are the most likely to show up on exams.) Mid-terms will be reviewed in the class period following the exam. Identification and Collection --> Identification will reinforce professional scientific standards in taxonomy, vocabulary and data structure. Collection ability dependent on government policy with respective ecosystem. Labs + Field Activities --> The lab portion will focus on use of small ecosystems for study, Various short field trips to local wetlands, marine environments Familiarization with field instruments and water testing kits Under the Scope: microscopy techniques to visualize anatomies & measure structures; techniques may have some disparities to the usual micrscopy activity concerning aquatic plants, algae Photosynthesis lab with aquatic plants and algae Group Term Paper --> Term paper to be a review of a topic of interest within the fields of aquatic plants or algae or wetlands/aquatic/marine biology or ecology. Will be presented to the class. Scientific format and references (texts, journal articles and credible scientific agencies/ministries) are expected. Group Research Project --> Design, conduct and report a field or lab experiment developed with the instructors. Assessment --> 2 mid-terms 30% Final 15% Papers 20% Labs and plant/algae collection 20% Presentation & participation 15% Course Outline --> Definitions and Wetlands, Aquatic and Marine ecology/habitats Wetlands of North America Classifications, Inventory and Delineations Inland Wetlands Salt Marshes Field Trip to Herbarium Mangroves Sea plants/trees and algae Field Trip(s) to Marine ecosystems Hydrology, Water Budgets and Models Nutrient Cycling Wetlands/Aquatic/Marine Biological Adaptations Limnology Riparian Zones and Regional Wetlands Characterisation, Demography, Human interaction Sea Grass Beds Algae Field Trips to regional wetlands Riparian Zones Rivers of the region Seasonal wetlands Invasive Species - Aquatic Nuisance Species (impacts and laws) Animalia, plantae and algae Wetland Management, Laws, Protection Marine Management, Laws, Protection Control & Management of Aquatic Plants with Physical & Chemical- Handouts Control & Management of Aquatic Plants - Handouts Mechanical & Biological Controls Environmental Issues - Case Studies Student Presentations Student Presentations Prerequisites: General Botany, Plant Physiology, Analytical Chemistry Organic Chemistry I In-depth study of: (i) the structure of organic compounds and the functional groups (bonding, acid-base properties, nomenclature, conformations, stereochemistry), and (ii) the synthesis and reactivity (including detailed mechanisms) of alkanes, alkenes, alkynes, halides, alcohols, ethers, epoxides, sulfides and organometallic reagents. Laboratory experiments are related to topics covered in lecture and emphasize organic laboratory techniques, synthesis and spectroscopic characterization of organic molecules. Typical Texts: McMurry, John E. Organic Chemistry. 8th Edition. Brooks/Cole, 2012. McMurry, Susan. Study Guide with Student Solutions Manual. 8th Edition. Brooks/Cole. Typical Lab Manual: Barbaro, John and Richard K. Hill. Experiments in Organic Chemistry. 3rd Edition, Contemporary Publishing Company of Raleigh, Inc., 2006 Grading: 3 Exams (50% combined) Cumulative Final Exam (25%) Labs (25%) (On the occasion of significant improvement on the final exam, more weight will be placed on the final exam) INSTRUCTIONAL METHODS: List the different instructional methods you might use, in the course of the semester. List supplementary learning options, if any: Traditional lecture with use of chalkboard Computer assisted diagrams and graphics Molecular Models Team work in the laboratory Homework assignments Solving specific questions related to content studied Written exams and distribution of study questions/previous exams Use of the Internet UNIQUE ASPECTS OF COURSE (such as equipment, specified software, space requirements, etc.): Organic chemistry laboratories and their associated equipment, instruments and chemicals. Apart from use of software in lectures, students will use software to accompany experiments that provide detailed molecular/compound structure, target sites, functional groups, etc. etc. Such exhibits will accompany lab reports. Ch. 1 Structure and Bonding Bonding; Hybridization; Drawing Chemical Structures; Functional Groups; Intro to IR Spectroscopy Ch. 2 Polar Covalent Bonds; Acids and Bases Chemical Bonding (Ionic and Covalent); Electronegativity and Dipole Moments; Formal Charges; Resonance Structures; Acid Base Theory (Bronsted-Lowry, Lewis); Acid and Base Strength (pKa); Acid-Base Reactions; Organic Acids and Organic Bases Ch. 3 Organic Compounds: Alkanes and their Stereochemistry Alkanes, Alkane Isomers, and Alkyl Groups; Properties of Alkanes; Conformations Ch. 4 Organic Compounds: Cycloalkanes and their Stereochemistry Cis-Trans Isomerism in Cycloalkanes; Stability and Conformations of Cycloalkanes; Chairs Ch. 5 Stereochemistry at Tetrahedral Centres Enantiomers, the Tetrahedral Carbon and Chirality; Optical Activity; R/S Sequence Rules; Diastereomers and Meso Compounds; Racemic Mixtures, Resolution of Enantiomers; Prochirality; Chirality in Nature Ch. 6 An Overview of Organic Reactions Kinds of Organic Reactions (Radical and Polar); Mechanisms; Describing a Reaction (Equilibria, Rates, Energy Changes, Bond Energy; Transition States, and Intermediates) Ch. 7 Alkenes: Structure and Reactivity Preparation and use of Alkenes; Cis-Trans Isomerism; Alkene Stereochemistry and E/Z Designation; Stability of Alkenes; Electrophilic Addition Reactions; Markovnikov’s Rule: Carbocation Structure and Stability; Carbocation Rearrangements Ch. 8 Alkenes: Reactions and Synthesis Preparation of Alkenes via Elimination Reactions; Addition Reactions of Alkenes (Halogenation, Hydration, Halohydrins, and Hydrogenation); Oxidation of Alkenes (Epoxidation and Hydroxylation); Addition of Carbenes; Radical Additions to Alkenes (Polymer Formation); Reaction Stereochemistry Ch. 9 Alkynes: An Introduction to Organic Synthesis Preparation of Alkynes; Addition Reactions of Alkynes (X2, HX, H2O, H2); Oxidative Cleavage; Alkyne Acidity and Alkylation; Introduction to Organic Synthesis Ch. 11 Reactions of Alkyl Halides: Nucleophilic Substitutions and Eliminations SN2, SN1, E2, E1, E1cB Reactions; Zaitsev’s Rule; Deuterium Isotope Effect Ch. 10 Organohalides Preparation of Alkyl Halides and Grignards; Radical and Allylic Halogenation; Organic Coupling Reactions, Redox in Organic Chemistry Ch. 17 Alcohols and Phenols Properties of Alcohols and Phenols; Preparation and Reactions of Alcohols; Reactions of Phenols Ch. 18 Ethers and Epoxides; Thiols and Sulfides Synthesis and Reactions of Ethers; Cyclic Ethers (Epoxides); Reactions of Epoxides: Crown Ethers; Thiols and Sulfides LABS --> Some experiments require more than one lab period to complete. Based on an instructor’s preference, availability of equipment/supplies or constraints within a given semester, this laboratory schedule is subject to change, including but not limited to, the addition or replacement of one or more of the above experiments with the following experiments: Addition of Bromine to E-Cinnamic Acid in Methylene Chloride Substitution Reactions of Alkyl Halides: Relative Rates Triphenylmethanol with Hydroiodic Acid 1. Check-in, Laboratory Safety, Practices and Waste Disposal. Simple Distillation. 2. Spectroscopy: Introduction to Infrared Spectroscopy. 3. Recrystallization, IR and Melting Point of benzoic acid. 4. Extraction of Organic Compounds from Natural Sources: Trimyristin from Nutmeg. 5. Paper Chromatography 6. Dehydration of Cyclohexanol. 7. Dimerization of 2-Methylpropene 8. Preparation of Diphenylacetylene Starting from Trans-Stilbene. 9. Preparation of Butyl Bromide/Preparation of t-Butyl Chloride (SN2/SN1). 10. Oxidation of Isoborneol to Camphor. 11. The Williamson Ether Synthesis: Preparation of Aryloxyacetic Acid from Cresol. Prerequisites: General Chemistry II Biochemistry: The study of biochemistry investigates the interplay between biological macromolecules such as proteins and nucleic acids, and low molecular weight metabolites (such as the products of glucose metabolism). In this course, you will apply your knowledge of intermolecular forces, thermodynamics (when a reaction occurs), chemical kinetics (how fast a reaction occurs), and chemical structure and functionality to understand how biological molecules (and life) work. COURSE GOALS AND OBJECTIVES (Our Roadmap!) -Be able to describe/identify the forces that direct/stabilize different levels of protein structure -Be able to predict how changes in amino acid (or nucleotide) sequence can affect macromolecular structure and function -Be able to explain how enzymes are able to affect reaction rate enhancement -Be able to articulate and apply what the enzyme parameters of KM, Vmax, kcat and kcat/KM tell us about an enzyme -Be able to describe the interactions of biomolecules both quantitatively and qualitatively (in many cases, including mechanistic details) -Be able to understand the flow of metabolic intermediates through a pathway and communicate information about metabolic pathways using diagrams -Be able to describe multiple experimental methods used in biochemistry, interpret data from these methods to form conclusions, and develop a testable hypothesis to answer a question -Be able to summarize and analyse primary literature and data, and apply gathered information to new situations -Increase problem solving skills such as: critical thinking, data analysis, graphical analysis -Increase process skills such as: communication of scientific concepts and experimental results, group dynamics and teamwork, management and self-assessment -Develop a community of active learners who are intentional about their educational choices Course Materials: Calculator Emphasis on reinforcing skills with software --> << VMD (with NAMS), GROMACS, VOTCA, Desmond, UCSF Chimera, Molsoft, CCPN, RedMD + RedMDStream >> << BLAST, Unipro UGENE, Bioclipse, Staden Package, Bioconductor >> << EMBOSS + JEMBOSS + Pise + wEMBOSS + EMBOSS-Explorer >> Typical Texts --> Nelson DL and MM Cox. Lehninger Principles of Biochemistry (5th edition). (“Lehninger”) Loertscher J and V Minderhout. Foundations of Biochemistry (3rd edition). (“FOBC”) Additional --> Blast protein databases, align protein sequences, build protein homology models, and evaluate the quality of these models Lab Manual example --> Lasseter, B. F. (2020). Biochemistry in the Lab: A Manual for Undergraduates. CRC Press Related to week 6: Edwards, P., Zhang, C., Zhang, B. et al. Smartphone based optical spectrometer for diffusive reflectance spectroscopic measurement of hemoglobin. Sci Rep 7, 12224 (2017). Course Overview --> You will frequently be given initial assignments to work on as an individual before class. These assignments must be ready at the start of class – your preparation will form part of your weekly participation grade. During our class meeting time, you will frequently function as a member of a Learning Team, developing and examining chemistry concepts as a unit. Your team effort and participation is part of your weekly participation grade. The team responses to a few Key Questions on each in-class activity will be evaluated for strength of concept and effective communication of the concept. The team will also strategize on ways to improve teamwork and team products. These responses will also form part of your weekly participation grade. Application exercises will be assigned for each activity. Together with problems from the text, they will form your weekly problem set that will be collected and graded for each individual. These homework problems and exercises are important to your success in the course. Actively working these homework problems is essential for your understanding of the material, as they bring your concept development full circle. The questions will be drawn from lectures, in-class activities, problem sets and discussions, as well as relevant primary literature that you may not have been previously assigned. The purpose of doing biochemistry is to gain experience in experimental methods that you’ll be reading about throughout the semester. Attendance on your scheduled lab day is expected. Software activities concerning biochemistry will accompany labs. Software activities concerning biochemistry will accompany labs as pre-lab development or post simulations. Grading --> Team Participation Problem Sets/Other Laboratory 2 Midterm Exams Final Exam Lecture Outline --> Week 1 Introduction to Biochemistry Week 2 Intermolecular forces and water. Amino acids and peptide bonds Week 3 Protein Folding Week 4 Working with proteins Week 5 Enzyme catalysis. Enzyme Kinetics Week 6 Enzyme inhibition. Hemoglobin Week 7 Exam 1; Carbohydrates Week 8 Glycobiology Week 9 Lipids and membranes. Transport across membranes Week 10 Signal transduction. Metabolism overview Week 11 Glycolysis. Glycolysis regulation and related pathways Week 12 Glycogen metabolism and gluconeogenesis. Citric Acid Cycle Week 13 Electron Transport Chain / Oxidative Phosphorylation; Exam 2 Week 14 Lipid metabolism. Nucleotides and nucleic acids Week 15 Nucleic acids structure and function Week 16 Final Exam Prereqs: General Biology I. Co-requisite or Prerequisite: Organic Chemistry I Plant Nutrition Fundamentals of plant nutrient availability, uptake, assimilation, transport, function, and deficiencies. Influence of plant root environment and root physiology on plant nutrient status and subsequent effect on plant growth, crop yield, and relationship to plant diseases and pests. Texts of interest: Mengel, Konrad and Ernest a. Kirkby (eds). Principles of Plant Nutrition. Fifth edition. Dordrecht: Kluwer Academic Publishers, 2001, 849 pages 2, 651 pages Marschner, Petra( ed). Marschner’s Mineral Nutrition of Higher Plants. Amsterdam: Elselvier, Labs --> Course will have administered labs based on the following: Motsara, M. R. & Roy, R. N. (2008). Guide to Laboratory Establishment for Plant Nutrient Analysis, FAO Fertilizer and Plant Nutrition Bulletin 19 https://www.ndsu.edu/pubweb/chiwonlee/plsc211/labmanual/lab5.PDF http://schulte.faculty.unlv.edu/BIO442/Lab4Mineral.pdf https://www.globe.gov/documents/355050/41927208/BasicExperiments_MineralNutrition.pdf/85690c28-3497-4729-a659-b1e9c6230ab3 NOTE: if there is any need of Analytical Chemistry lab techniques, they will be done as a precursor to relevant chosen plant nutrition labs. Quizzes --> There will be 3 – 5 quizzes throughout the course Exams --> There will 4 exams for students partake in. There is no cumulative final exam. Assessment: 3-5 Quizzes 10% Labs 30% 4 Exams 60% Course Outline: Week (1) Introduction to Plant Nutrition (Chapter 1) The Soil as a Plant Root Medium (Chapter 17 pp. 418‐424) Nutrient Availability (Chapter 12, Chapter 11 pp. 299‐300) Week (2) The Root (Chapter 13) The Rhizosphere (Chapters 14 and 15) Week (3) Nutrient Uptake (Chapter 2) Water Relations & Long Distance Transport in the Xylem & Phloem (Ch 3) Week (4) Uptake and Release of Nutrients by Aerial Plant Parts (Chapter 4) Photosynthesis and Assimilation of Carbon Dioxide (Chapter 5 pp. 85‐95) Week (5) Yield and Source‐Sink Relationships (Chapter 5 pp. 95‐133) Week (6) Nitrogen (Chapter 6 pp. 135‐142, Chapter 16) Nitrogen (continued) (Chapter 6 pp. 142‐151) Week (7) Sulphur (Chapter 6 pp. 151‐158) Phosphorus (Chapter 6 pp. 158‐165) Week (8) Potassium (Chapter 6 pp. 178‐189) Calcium (Chapter 6 pp. 171‐178) Week (9) Magnesium (Chapter 6 pp. 165‐171) Week (10) Iron (Chapter 7 pp. 191‐200) Manganese (Chapter 7 pp. 200‐205) Week (11) Zinc (Chapter 7 pp. 212‐223) Copper (Chapter 7 pp. 206‐212) Molybdenum (Chapter 7 pp. 226‐233) Week (12) Boron (Chapter 7 pp. 233‐243) Nickel (Chapter 7 pp. 223‐226) Chlorine (Chapter 7 pp. 243‐248) Week (13) Beneficial Nutrients – Sodium, Silicon, and Cobalt (Chapter 8 pp. 249‐263) Week (14) Diagnosis of Nutrient Deficiencies and Toxicities (Chapter 11) Nutrition and Plant Quality (Chapter 9) Week (15) Plant Nutritional Status and Plant Diseases and Pests (Chapter 10) Prereqs: Calculus II, General Botany, Plant Physiology, Organic Chemistry I, Biochemistry I Plant Biochemistry Topics are taught in the context of plant biology. Successful completion of this course will provide students with fundamental knowledge of biochemistry and specific knowledge of compounds and biochemical pathways that occur in plants. Topics include 1. The biochemistry of amino acids and proteins, sugars and carbohydrates, and lipids. 2. Biochemical processes and metabolic pathways specific to plants, including photosynthesis, photorespiration, cell wall biosynthesis, nitrate and sulfate assimilation, distinctive aspects of central metabolism, and plant secondary metabolism. 3. Metabolism in a structure-function context from molecular to subcellular, cellular, organ, and whole-plant levels. 4. Quantitative aspects of biochemistry including enzyme kinetics, protein ligand binding, analytical techniques, and bioenergetics. Learning Objectives and Outcomes Students will • understand plant cell structure, organization, and apply specific biochemical functions to all compartments of the plant cell. • learn the structure, function and biosynthetic pathways of essential biochemical molecules including their key chemical and physical properties. • learn amino acid structures and relate their chemical properties to the synthesis and function of proteins and enzymes. • understand protein structural hierarchy and relate structure to function. • understand how light energy is captured and used to provide chemical forms of energy to power the functions of cells and whole plants. The importance of CO2 fixation and carbohydrate metabolism will be presented. The nature and composition of plant cell walls will be explored. • understand central metabolism, its plant-specific components, and their functional significance at multiple levels. • learn about the rich diversity of secondary compounds and metabolism in plants and how such compounds contribute to human health. • learn principles of enzyme kinetics and apply these through hands on problem sets. Students will be shown how enzyme properties contribute to metabolic processes. • explore principles of metabolic modelling. Required Textbooks 1. Biochemistry & Molecular Biology of Plants, Second edition, print or electronic version, 2015, Wiley Blackwell 2. A general biochemistry textbook Supporting Textbook Gleason, Florence K. (2012) Plant Biochemistry Lab Guide --> J. A. Bryant, P. M. Dey, Jeffrey Barry Harborne (1993). Methods in Plant Biochemistry. Academic Press Emphasis in Software Immersion and Skills Enforcement --> There are various software that will serve well to this course that further encourages a modern and profession environment, extending beyond memor based studies. Will make emphasis with practically and constructively implementing software alongside labs. Likely, one particular software will not have all the qualities on e is interest, however, out of the following sets choosing a max of 2-3 in usage will be constructive << VMD (with NAMS), GROMACS, VOTCA, Desmond, UCSF Chimera, Molsoft, CCPN, RedMD + RedMDStream >> << BLAST, Unipro UGENE, Bioclipse, Staden Package, Bioconductor >> << EMBOSS + JEMBOSS + Pise + wEMBOSS + EMBOSS-Explorer >> Additional --> Blast protein databases, align protein sequences, build protein homology models, and evaluate the quality of these models Assessment --> Homework and Quizzes 10% 5 Exams 50% Labs 40% Labs --> Software activities concerning plant biochemistry will accompany labs. Software activities concerning plant biochemistry will accompany labs as pre-lab development or post simulations. Labs (active) will have focus on Plantae Course Outline --> Plant cell structure and compartments Amino Acids Structure and properties Ionization and titration Peptides, Properties and purification methods Protein Purification Structure (example: Rubisco) Enzymes and catalysis Enzyme Structure/Function relationships Rubisco Function Oxidation/reduction, bioenergetics, ATP and NAD(P)H Photosynthesis Light absorption Electron Transport Q-cycle and ATP synthesis Bioenergetics, ATP and phosphorylation Sugar structure and function Calvin Cycle Rubisco; photorespiration C4 Metabolism, CAM Metabolism Sucrose: synthesis, transport, breakdown, signals Polysaccharides Starch structure, metabolism Cell wall structure, metabolism Glycolysis Mitochondrial functions Citric acid cycle Electron transport Other Oxidative pentose phosphate pathway Regulation of primary metabolism Nitrogen Metabolism: Fixation Nitrogen Metabolism: Assimilation and GS/GOGAT Sulphur Metabolism: Assimilation and impacts Fatty acid Structure Desaturation Synthesis I & II Oxidation I & II Health promoting secondary products Flavonoids I & II Phenolics and ESPS synthase Terpene synthesis Carotenoids Alkaloids I & II Protein-Ligand Interaction I – III Enzyme Kinetics I – VI Introduction to Metabolic Control Analysis Flux Balance Analysis I & II NOTE: all other interests during course (introduce appropriately and constructively throughout) Mevalonate pathway Shikimic Acid Pathway Methyl-Erythritol Phosphate Pathway Phenylpropanoid Pathway Polyketides Prerequisites: Biochemistry I, Organic Chemistry I Organic Synthesis Laboratory Practice of organic laboratory techniques. Three hours of laboratory per lab session, twice a week. Approved chemical safety goggles meeting whatever national standards. The purpose of this laboratory course is to introduce students to the techniques that organic chemists (as well as biochemists, physical chemists, etc.) use in their daily routines. After learning and understanding those techniques, students will apply their knowledge to new situations to understand synthesis reactions, molecular structure determination, and analysis of (un)known compounds. Organic chemistry laboratory is important for several reasons. It introduces students to many different laboratory practices and concepts that will be used in subsequent chemistry laboratory classes and in other laboratory situations in biology, pharmacy, and chemical engineering (just to name a few!). It is anticipated that by the completion of this course, students will be familiar with all of the following topics and techniques: Safety in the laboratory Interpreting and following scientific directions Keeping a proper lab notebook Names and proper usage of lab instruments Understanding of general properties of compounds (including solubility, miscibility, acid/base chemistry, etc.) Proper usage of glassware Isolation and purification techniques (including filtration, solvent removal, drying solutions, distillations, chromatography (thin-layer, column, and gas) and crystallization/recrystallization) Characterization techniques including spectroscopy and melting point determination Interpretation of scientific results including percent yield and recovery, melting point, boiling point, IR and NMR spectra, and Rf values Required Materials: A laboratory notebook with carbon(less) pages Approved safety goggles Lab coats Lab manual will be posted through Blackboard Typical text: C.F. Wilcox, M.F. Wilcox, "Experimental Organic Chemistry, A Small-Scale Approach", (3rd edition, 2010). Apart from use of software in lectures, students will use software to accompany experiments that provide detailed molecular/compound structure, target sites, functional groups, etc. etc. Such exhibits will accompany lab reports. Lectures --> Lecture sessions are designed to clarify the concepts covered in the lab, as well as give an overview of techniques that will be used in the lab. Attendance is expected: The labs are only 3 hours in duration, so these lectures will be where you learn everything that you’ll need. Lab exercises will be available on Blackboard for each week. Please be considerate of your fellow students during the lecture period. Disruptions of any kind will not be tolerated and may result in expulsion from the classroom. Laboratory --> You will be required to have appropriate clothing before being allowed to enter the lab. Pre-labs are due at the beginning of the lab, and results and postlabs are due at the beginning of the lab 1 week after completion of the experiment! You will be expected to adhere to all of the lab safety rules. You are all expected to do your part to maintain a clean lab environment as part of GLP (Good Lab Practices): All reagent and solvent bottles should be completely closed immediately after use; All spills and dribbles should be cleaned immediately; All glassware should be put away at the end of the lab, and walkways should be kept free of debris. The following is the distribution of possible points in the course: Library Searching Exercise Database Search Exercises (Spectroscopy and Chromatography) Lab Quizzes Reaction/Synthesis methods knowledge Appropriate choice of method Appropriate constituents and tools. Procedure/steps (summary and/or ordering) Stoichiometry problems Spectroscopy and/or Chromatography analysis/interpretation Applications and industries Multistep Reaction/Synthesis Labs Lab Cleanliness Pre-lab Submissions Lab Notebook and Reports Lab Final Day 1: Much resemblance to quizzes Day 2-3: Augmented with the following: Molecular modelling software exercises Two or Three Practicum Group Labs (open notes) Part A. Points deducted for incompetent questionnaire for safety procedures for respective lab Part B. 2-3 labs to be implemented with competent data recording and lab reports. YOUR LAB REPORT CONSISTS OF THREE (3) PARTS --> Part I - Prelab Report. A copy of your lab notebook pages containing the lab write-up and answers to any prelab questions. This is due at the start of each experiment. Part II - Results. A copy of your notebook pages containing observations noted during the lab experiment. Is due with Part III one week from the conclusion of the experiment. Part III - Postlab Report. A summary of results and answers to postlab questions. This can be written on separate loose-leaf paper. Is due with Part II one week from the conclusion of the experiment Course Outline: Week1 Check-in/Safety Video/ Safety Procedures and Regulations Fractional Distillation Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation, results and analysis Week 2 Measuring the Melting Points of Compounds and Mixtures Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Consider other physical and chemical properties, such as solubility and spectroscopic data, to confirm the identity of the unknown compound. Results and analysis Week 3 Purification by Recrystallization and Melting Point Measurement Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Consider other physical and chemical properties, such as solubility and spectroscopic data, to confirm the identity of the unknown compound. Results and analysis Week 4 Nucleophilic Substitution: Synthesis (SN1 Mechanism and SN2 Mechanism) Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Consider other physical and chemical properties, such as solubility and spectroscopic data, to confirm the identity of the unknown compound. Results and analysis Week 5 Oxidation of Alcohols (Primary, Secondary and Tertiary). Infrared Spectroscopy. Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Infrared Spectroscopy Results and analysis Week 6 Elimination Reaction (E1 Mechanism and E2 Mechanism) Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Consider other physical and chemical properties, such as solubility and spectroscopic data, to confirm the identity of the unknown compound. Results and analysis Week 7 Synthesis of Aspirin. Chromatography and/or Spectroscopy Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Chromatography and/or Spectroscopy Results and analysis Week 8 Solvent Extraction Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Consider other physical and chemical properties, such as solubility and spectroscopic data, to confirm the identity of the unknown compound. Results and analysis Week 9 Electrophilic Aromatic Substitution: Synthesis of o- and p-Nitrophenol. No distillation; extract product with ethyl acetate. Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Consider other physical and chemical properties, such as solubility and spectroscopic data, to confirm the identity of the unknown compound. Results and analysis Week 10 Separation and purification of o- and p-Nitrophenol by Liquid Chromatography. Use 100 mg sample, check by chromatography. Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Results and analysis Week 11 Aldol Condensation Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Consider other physical and chemical properties, such as solubility and spectroscopic data, to confirm the identity of the unknown compound. Results and analysis Week 12 Grignard Reaction: Synthesis of Phenylmagnesium Bromide. Week 1: Part 1. Add methyl benzoate and sustain the desiccator for next week. Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Consider other physical and chemical properties, such as solubility and spectroscopic data, to confirm the identity of the unknown compound. Results and analysis Week 13 HCl workup of previous week’s product. Synthesis of Triphenylmethanol and recrystallization of product. Purity check by melting point measurement. Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Consider other physical and chemical properties, such as solubility and spectroscopic data, to confirm the identity of the unknown compound. Results and analysis Week 14 -15 Wrapping up/cleaning things up. Final Exam. Prerequisite: Organic Chemistry I Functional Genomics This course will focus on execution of tools and protocols used to elucidate the biology, ecology and life histories of organisms through analysis of their genomes. Using genome research projects recently completed by the instructor and collaborators or other entities as templates, students will carry out each step of the research pipeline (unique to that project) in depth – from taxon selection, bioinformatic analysis of next-generation sequencing data, genome assembly, gene prediction/functional annotation, and finally how these data answer a functional biological hypothesis or question about the target organism. As new topics are introduced, they will be framed in the context of their applicability to the current project. At the end of the course, students will be able to select the appropriate protocols and analysis pipelines to complete the majority of today’s genome research. Each topic (or introduced research project) will consist of one or more lectures with background discussion, tool and material review, and a second hands-on computer (or dry) lab period during which students will apply the concepts and tools to complete a phase the genomic analysis. This course illustrates evolutionary concepts current tools in a hands-on manner within the confines of a goal or results-oriented genome research project. Course Goals --> Apply knowledge of genome sequencing and bioinformatics analyses to test hypotheses regarding organismal biology and evolution Communicate effectively how various bioinformatic analyses are impacted by similarities and differences in eukaryote genomes Apply appropriate bioinformatic tools and analysis protocols for individual genome sequencing projects Analyse and report on recent published research in the field of genomics Readings --> Selected scientific articles, book chapters, and writings from the popular press. Each lab will use a research paper authored by whosoever as a model for the analyses to be carried out with expected results Software --> R and packages of interest (BiocManager, ChemmineR, dPCP, MAPITR) Thodberg, M., & Sandelin, A. (2019). A step-by-step guide to analysing CAGE data using R/Bioconductor. F1000Research, 8, 886 Cao, Y., Charisi, A., Cheng, L. C., Jiang, T., & Girke, T. (2008). ChemmineR: a compound mining framework for R. Bioinformatics (Oxford, England), 24(15), 1733–1734 < manuals.bioinformatics.ucr.edu/home/R_BioCondManual > < cran.r-project.org/web/packages/BiocManager/vignettes/BiocManager.html Plant breeding and genomics < https://plant-breeding-genomics.extension.org/r-tutorials/ > NOTE: will like to incorporate the R environment into labs as compliment to analyses. Paper discussion --> Students will present a recent genome paper on a topic of their choosing and recap the methods used and conclusions inferred from the analyses. Project Part A --> Students will assemble, annotate and describe a mock genome project using public and/or simulated sequence data. Project Part B --> Apart from plants and trees serving as sustenance and nutrition for ecological consumers, various unique plants and trees are known to produce unique chemicals for defence, regulation, ecological advantage, etc, etc. Interest examples of concern Psychoactive Hallucination Paralysis Poison Blindness Blisters (mouth sores) Saps Burns (second and third degree) Anaesthetic Antiseptic Stinging nettle Tissue Digestion/Carnivorous (pineapple, insect trappers, etc., etc.) Involves taxonomy process of identification and classification, genome recognition, genetic markers related to the metabolic process for the syntheses of such chemical activity. Pathways and biochemical processes for mechanisms and responses. Includes the chemistry that takes place for the infamous or highly regarded activities, with the effects and symptoms; accompany with Organic Chemistry and Biochemcal software use for demonstration. Project Part C --> --In the wild there are various plants and trees that never garner any particular attention in horticulture and agriculture. Student groups with collect leave samples of at least 3 leaves of such plants, and at least 3 leaves of such trees. Will have lab DNA sequencing activities towards identification of genomes; identify possible using genetic markers to compare with databases. --Will gather samples of diseased specimens towards DNA sequencing to search for genetic variations and/or mutations that may play a role in the development or progression of a disease. The disease-causing change may be as small as the substitution, deletion, or addition of a single base pair or as large as a deletion of thousands of bases. Assessment --> Paper discussion: 10% Mid-term: 30% Final exam (cumulative): 30% Project (A + B + C): 30% Topics --> --Introduction / Why sequence genomes; next-gen sequencing --Basics I: Genome/transcriptome assembly; gene prediction and annotation --Basics II: Sequence alignment, phylogenetics, phylogenomics --Lab I: Illustrating the basics --The algal tree of life; origins of photosynthesis – The Cyanophora paradoxa genome --The MAT hypothesis; plastid establishment – The Cyanophora paradoxa genome --Lab II: Working with C. paradoxa genome data --Extremophilic vs. mesophilic genomes; horizontal gene transfer (HGT) – The Porphyridium purpureum genome --Lab III: Working with P. purpureum genome data --Genomic adaptation to environmental stress; HGT revisited – The Picochlorum spp. Genome --Differential expression: Lipid production, nitrogen starvation in Phaeodactylum tricornutum --Differential expression: Lipid production, nitrogen starvation in Phaeodactylum tricornutum --Lab VI: Differential expression analyses illustrated with P. tricornutum data. --Metabolism and physiology inferred from genome data – The Gambierdiscus caribaeus genome --Lab VII: Metabolic pathways, KEGG and gene ontologies illustrated with G. caribaeus data. --Paper discussion I --Paper discussion II --Single nucleotide polymorphisms and directed evolution – Chlamydomonas reinhardtii resequencing --Lab VIII: Calling SNPs and estimating functional consequences --Genetic divergence and natural selection as evidenced in genome data. --Phylogenetic networks and alignment-free methods to illustrate shared ancestry Prerequisites: General Botany, Plant Physiology, Biostatistics I & II, Plant Biochemistry Cell Biology: The standard definition of a cell in most introductory biology texts includes the line that cells are “the fundamental building blocks of all organisms.” Because of this fact, trite though it may be, a detailed understanding of the fundamental processes of cellular function is critical to all specialties within biology, clinical or academic. Some of these processes, including for example the biochemical mechanisms underlying cellular energetics, are remarkably consistent from bacteria to human. Other cellular processes and structures vary from cell type to cell type or organism to organism, allowing for unique adaptations of cells and organisms to particular functions. For example, nerve cells have various properties allowing them to conduct electrical signals and therefore process information, while kidney cells are specialized for the secretion of waste, and red blood cells for the transport of oxygen and carbon dioxide. What are the differences in physiology from cell type to cell type determining these specific functions? During the first half of the semester we will focus primarily on the biochemical processes that underlie cellular function, with an emphasis on protein structure and function, ion transport mechanisms and energy metabolism. The second half of the semester will emphasize more the function of particular organelles, including cell membranes, intracellular compartments and the cytoskeleton, and the relevance of these structures on processes like cell signaling and mitosis. Throughout the course, we will emphasize how variability in these processes imbues different cell types with their unique functional abilities. We will also seek to understand the experimental evidence for the different facts and concepts we study: How do we KNOW that nerve cell signaling, for example, involves the release of neurotransmitters? Some of this experimental evidence will be explored in a hands-on way in the lab sections, some will be discussed during lecture, and some will be the subject of analysis in the reading of original scientific manuscripts. Finally, we will examine how malfunctions in the cellular processes we are studying underlie certain diseases. In particular, the final few lectures of the course will focus on the biology of cancer cells: how do changes in cellular processes allow cancer cells to proliferate and metastasize? What are some of the current clinical approaches to curing cancer by blocking or reversing these processes? Aspirations --> To understand fundamental concepts of cellular function. To understand, and be able to critically analyze, the scientific evidence underlying our current understanding of cellular processes. To develop skills, through lab experiments, in some of the specific methodologies used in the study of modern cell biology. To become skilled at formulating and testing hypotheses using these methods. To develop a preliminary ability to read and analyze the primary scientific literature: What are the major findings of a science paper? What evidence is presented to support these findings? Are there shortcomings, either in the methods used or the logic of the experiments, which might lead one to question the conclusions reached by the authors? To be able to put this knowledge into larger contexts of how disease states occur or how organisms function adaptively within their environments. Typical text: The World of the Cell, by Becker, Kleinsmith, and Hardin, 6th edition (2006), Pearson/Benjamin Cummings Class Requirements and Grading --> 1. Class Participation (10%) To include attendance, responses to questions I pose in class, participation in discussions, and simply raising your hand from time to time to ask questions or make a comment (something I DO expect you to do). 2. Quizzes (10%) Two short in-class quizzes during the first half of the course. 3. Homework/problem sets (5%) There won’t be many of these; I’ll assign them when we hit subjects that are especially involved to help you learn the material and to make sure everyone is on track. 4. Primary literature readings (10%) We will read two papers from the primary scientific literature during the second half of the course. In both cases there will be an in-class discussion of the paper and a “reading guide” set of short essay questions which will be graded. The first reading guide assignment will be due AFTER the in-class discussion; the second assignment will be due BEFORE the in-class discussion. 5. Laboratory reports (25%) The specifics of each week’s lab report will be discussed during lab section. Typically, each week’s lab report will be due the following Monday in lecture. 6. Mid-term exam (20%) TENTATIVE format to include an in-class component, a short oral component, and a take-home component. 7. Final exam (20%) LABS --> Lab instructions for each week will be handed out ahead of time, either distributed as hard copies in lecture or posted on the course Angel site (or both). You are responsible for reading the instructions before lab. Otherwise, labs tend to run late, you will have difficulty obtaining the necessary data and knowing what to do with it. Do not expect the instructor to go over every step of the lab procedure before you start. Labs will make great emphasis on strong, practical and constructive immersion into the following software to accompany hands-on activity: << VCell, TiQuant + TiConstruct + TISIM >> Such software provides strong quantitative/computational microscopic assessment of specimens (or whatever) at professional standards. Such provides better means of objectives and expectations towards hands-on labs. Each lab will be associated with an explicit lab report assignment (contained in the lab instructions), usually due in lecture the Monday following lab. Usually, you may either submit the report with your lab partner or independently. If a report is submitted jointly, both partners must have contributed equally, as per Honor Code responsibilities. Do NOT make the mistake of dashing off reports the night before in a single draft. These reports will collectively account for 25% of your course grade, so take them seriously. The lab is a potentially dangerous place and you are required to follow all instructions given by your lab instructor and presented in the lab instructions. Disregarding instructions, or coming to class late or unprepared, may result in grade penalties, in addition to being just plain dangerous for yourself and those around you. Note: students can apply stationary video recording of labs with assigned regulations (to be given). Course Topics: Chapter 1 -19, 24. Some topics will require at least one week of instruction. Labs --> Cell Culturing, Aseptic Technique Cell Culture: basic techniques, population curve Cell Counting and splitting plates Cell Staining Histology Electron microscope Cell Harvesting & Cell Lysis Fractionalization of cells Common method(s) will be implemented Discussion and logistics for immunomagnetc separation & magnetic beads Isolation of erythrocyte membrane proteins Analysis of erythrocyte membrane proteins Bradford Assay (also identifying advantages and disadvantages) SDS-PAGE Chloroplasts and the Hill reaction Prerequisites: General Biology I & II Plant Molecular Biology The first objective of this course is to acquire a working knowledge of the molecular biology of plants (current times), being broadly photosynthetic organisms. Emphasis placed on genes/genomes and processes that are unique, or of particular importance to plants; yet to treat the “plant counterpart” to particular universally important processes, such as nuclear transcription . The second objective is to focus attention on what constitutes important ongoing research in plant molecular biology, and how does it compare to similar research on non-plant systems. Of consequence, you will learn about great successes with plant research as well as some of the current barriers to discovery and exploitation of plants. Typical course text --> Biochemistry and Molecular Biology of Plants, edited by Buchanan B., Gruissem W., and Jones R. American Society of Plant Physiologists. Lab Guides --> M.S, Punia. (2018). Plant Biochemistry and Molecular Biology: A Laboratory Manual. Scientific Publishers Carson, S. et al. (2019). Molecular Biology Techniques: A Classroom Laboratory Manual. Academic Press Schuler, M. A. and Zielinski, R. E. (2012). Methods in Plant Molecular Biology, Academic Press Maliga, P. (1995). Methods in Plant molecular biology: A Laboratory Course Manual.(A Cold spring Harbour Laboratory Course Manual). Cold spring Harbour Laboratory Press Stanton B. Gelvin (1989). Plant Molecular Biology Manual. Springer Netherlands Emphasis in Software Immersion and Skills Enforcement --> There are various software that will serve well to this course that further encourages a modern and profession environment, extending beyond memor based studies. Will make emphasis with practically and constructively implementing software alongside labs. Likely, one particular software will not have all the qualities on e is interest, however, out of the following sets choosing a max of 2-3 in usage will be constructive << VMD (with NAMS), GROMACS, VOTCA, Desmond, UCSF Chimera, Molsoft, CCPN, RedMD + RedMDStream >> << BLAST, Unipro UGENE, Bioclipse, Staden Package, Bioconductor >> << EMBOSS + JEMBOSS + Pise + wEMBOSS + EMBOSS-Explorer >> Assessment --> 4 Exams 60% Labs 40% Labs --> Labs will pursue Molecular Biology experiments for plantae augmented with software use. Other labs concern replication of chosen journal articles. Course Outline --> The Genetic Engineering of Plants: Transforming the Nucleus and Chloroplasts The Molecular Biology of Plant organelles Chloroplast Biology and Gene Structure (multiple sessions) Chloroplast Genome Evolution and Expression (multiple sessions) Organelle Self-Splicing Introns and Horizontal DNA transfer Chloroplast Gene Regulation – External & Nuclear Control Mitochondrial Genome Structure and Expression (multiple sessions) RNA Editing and Organelles Targeting of Proteins to Chloroplasts & Mitochondria The Nuclear Genome of Plants Size & Composition DNA Instability: Transposable Elements DNA Repair Gene Regulation in Development Gene Expression and Regulation PTGS (RNA Silencing & MicroRNAs) Photomorphogenisis (Leaf Development) Flower Development: Homeotic Genes The Molecular Basis of Stress Response Responses to Abiotic stress (multiple sessions) Heat & Cold Anaerobiosis, oxidative Responses to Biotic Stress (i.e., Pathogen attack) Prerequisites: Cell Biology, General Botany, Plant Physiology, Biochemistry, Organic Chemistry I Plant Pathology A study of the nature and causes of disease in plants, emphasizing the principal diseases in common plants and crops. There will be two hours of lecture and four hours of laboratory per week. Upon completion of the course the student will be able to: 1. Describe the concepts of what constitutes disease in plants. 2. Identify major principles of plant pathology. 3. Recognize the etiological agents of disease. 4. Employ methods to diagnose and manage a wide range of plant diseases. 5. Describe aspects of integrated pest management. 6. Explain the impact of plant disease on human affairs. 7. Ecological effects of pest management and resolutions NOTE: any field collection will be done in rain or sunshine Literature: Agrios G. 2005. Plant Pathology 5th edition Elsevier Academic Press. 922 pages Lab Tools: Will be given materials and instructin literature Note: all labs A through M will be done Applied Resource: FAO AGRIS Assessment 3-4 Quizzes 3 Exams Labs Topic course Outline -Introduction to Plant Pathology -Concepts of Disease -Stages in the Development of Disease (Disease Cycle) -How Pathogens Attack Plants -How Plants Defend Themselves -Fungi as Plant Pathogens -Eubacteria and Atypical Procaryotes as Plant Pathogens -Nematodes as Plant Pathogens -Viruses as Plant Pathogens -Mealy bug and similar pestilence -Parasitic Higher Plants as Plant Pathogens -Physiological or Abiotic Diseases -Control of Plant Diseases LABS --> NOTE: Some labs will also incorporate preparing of slides of plant tissue and pathogen specimen. Pathogens and diseases focus may be altered due to environment one resides in. A. Plant Disease Walk: Recognition of healthy and diseased plants is important. It is also essential to know the difference between a sign and a symptom The objective of this exercise is to find some plant diseases. The first step in this process is to familiarize yourself with diseased plants that may be in your area. Look online or in a plant disease book beforehand to find some possible plant diseases that may be in your area. Pictures can be saved for reference later. Materials needed: pen or pencil, paper, and a 10X hand lens or magnifying glass. (Hand lenses can be found at bookstores or online.) Procedure: Now go outside and begin walking around, whether it is in your backyard, a field, or a park. Look at the plants around you from the grass on the ground to the trees in the sky. Begin by looking at healthy plants. It is important to know what a healthy plant looks like to help determine when you have a sick one. Once you have found a healthy plant look for one that is out of the ordinary, such as one that is wilted or has yellowing leaves. Wilting can be associated with the plant’s inability to move water in the vascular system (xylem). Note the differences between the healthy and sick plants. Be sure to examine many different plant types. As you study these plants, list 5 symptoms you observed and 5 signs you examined. If you have a hand lens, observe closely at the plant specimen (maybe a leaf or stem). Might be able to see fruiting bodies and if you see fruiting bodies then you may have found a sign of the disease. Over the next few days (limited) note in your journal any changes with the diseased plants that you saw on your walk. Ask yourself some questions. “Have they changed in colour or shape?” “What do you think the cause of the sickness is?” “Is it related to weather, such as being too cold or too hot?” “Is only one plant sick or many plants?” Be sure to also take pictures throughout the exercise to help show what the plant looked like when you first saw it and what it looked like a few weeks later. B. Introduction to plant pathology and mycology part I C. Mycology part II D. Diseases caused by Ascomycota (4 labs) E. Diseases caused by Oomycota F. Fungal isolation techniques Part I and Nematodes G. Fungal isolation techniques Part II and abiotic plant damage H. Viral Diseases I. Bacteria part I J. Bacteria part II and Stem Rust Differential Set K. Parasitic seed plants L. Lab experiments with implementation of PCR, FISH, ELISA and IF: --Enzyme-Linked Immunosrbent Assay (ELISA) Note: choice can be different to specmen in articles Description of technique and process Clark, M. F. (1981). Immunosorbent Assay in Plant Pathology. Annual Reviews, Volume 19 pages 83 – 106 Copeland R. (1998) Assaying Levels of Plant Virus by ELISA. In: Foster G.D., Taylor S.C. (eds) Plant Virology Protocols. Methods in Molecular Biology™, vol 81. Humana Press Pataky JK, et al (2004). Ability of an ELISA-Based Seed Health Test to Detect Erwinia stewartii in Maize Seed Treated with Fungicides and Insecticides. Plant Disease. 88(6):633-640 Eibel, P., Wolf, G.A. & Koch, E. Development and evaluation of an enzyme-linked immunosorbent assay (ELISA) for the detection of loose smut of barley (Ustilago nuda). Eur J Plant Pathol 111, 113 (2005). Logistics Detecting pathogens for chosen plant speciment --Polymerase Chain Reaction (PCR) Schena, L., Duncan, J. M. and Cooke, J. E.L. (2008). Development and Application of a PCR-based ‘Molecular Tool Box’ for the Identification of Phytophthora Species Damaging Forests and Natural Ecosystems. Plant Pathology 57, 64–75 Aljawasim, B. and Vincelli, P. (2015). Evaluation of Polymerase Chain Reaction (PCR)-Based Methods for Rapid, Accurate Detection and Monitoring of Verticillium dahliae in Woody Hosts by Real-Time PCR. Plant Disease, Volume 99, Number 6 Lamarche J. et al. (2015) Molecular Detection of 10 of the Most Unwanted Alien Forest Pathogens in Canada Using Real-Time PCR. PLoS ONE 10(8): e0134265. Visnovsky, S. D. et al (2020). A PCR Diagnostic Assay for Rapid Detection of Plant Pathogenic Pseudomonads. Plant Pathology, Volume 69, Issue 7, pages 1311 – 1330 --Immunofluorescnce (IF) Wiwart, M., Mierzwa, Z. (1997). Indirect Immunofluorescence - an Useful Method in Studies on Some Fungal Pathogens. In: Dehne, HW., Adam, G., Diekmann, M., Frahm, J., Mauler-Machnik, A., van Halteren, P. (eds) Diagnosis and Identification of Plant Pathogens. Developments in Plant Pathology, vol 11. Springer, Dordrecht. Baysal-Gurel, F. et al. (2008). An Immunofluorescence Assay to Detect Urediniospores of Phakopsora Pachyrhizi. Plant Disease Vol. 92 No. 10 Janse J.D., Kokoskova B. (2009) Indirect Immunofluorescence Microscopy for the Detection and Identification of Plant Pathogenic Bacteria (In Particular for Ralstonia solanacearum). In: Burns R. (eds) Plant Pathology. Methods in Molecular Biology (Methods and Protocols), vol 508. Humana Press --Fluorescence In Situ Hybridization (FISH) Shakoori A. R. (2017). Fluorescence In Situ Hybridization (FISH) and Its Applications. Chromosome Structure and Aberrations, 343–367 Young, A. P., Jackson, D. J., & Wyeth, R. C. (2020). A Technical Review and Guide to RNA Fluorescence In Situ Hybridization. PeerJ, 8, e8806. M. Lab Final Exam Prerequisites: Cell Biology, General Botany, Plant Physiology, Field Botany, Biochemistry, Organic Chemistry I Forest Pathology The course consists of two lectures/labs (4 hours max) and, on average, 3-6 hours of field time per week. Lecture/lab time will be spent covering the biology, symptomatology and diagnosis of major fungal and bacterial diseases of particular trees, as well as mistletoes. Field identification and diagnosis is the focus of the course, with emphasis on late successional and old growth forests. Extensive required field trips will allow on-site assessment and identification of tree diseases, and quizzes and exams will take place in the field. Students are required to complete a collection of forest pathogens. Literature: Sinclair, W.A. & Lyon, H.H. 2007. Diseases of Trees and Shrubs. 2nd edition. Comstock Publishing, a Division of Cornell University Press, Ithaca, NY. 660 pp Additional: Tainter, F.H. & Baker, F.A. 1996. Principles of Forest Pathology. J. Wiley & Son, Inc. New York. 805 pp. Manion, P.D. 1991. Tree Disease Concepts. 2nd Ed. Prentice-Hall, Englewood Cliffs, New Jersey. 402 pp Assigned Readings --> Assigned readings will be made from the specified texts, research papers and Forest Service publications, etc. throughout the semester, and students are responsible for the material contained therein. Field Trips --> NOTE: will be done in rain or sunshine There will be 4-6 field trips Collection --> The purpose of the collection is to enable you to become adept at finding and identifying, on your own, forest pathogen signs, disease symptoms, and indications in the field. Rots (at least 3 on living trees) Rot diseases Rusts Foliage diseases Cankers/proliferations Mistletoes Labs --> Some labs will also incorporate preparing of slides of plant tissue and pathogen specimen. As well as identifying the biochemical/molecular biology process of such diseases/ailments. Incorporating lab experiments with PCR, FISH, ELISA and IF to be expected. Course Outline --> Introduction to forest pathology; the disease cycle Terminology: symptoms, signs, indications Wood Decay I. Brown Rots Wood Decay II. White Rots Root diseases I Root diseases II Rusts I Rusts II Foliage Diseases I Foliage Diseases II Cankers & Proliferations Mistletoes I Mistletoes II; completion of collections Prerequisites: Cell Biology, General Botany, Plant Physiology, Dendrology Forest Ecology Ecological interactions crucial to understanding forest ecosystems. Topics include: plant resources, competition, community development and dynamics, biodiversity, primary productivity, nutrient cycling, ecosystem structure and function, and impacts of global environmental change. Course examines numerous ways in which trees interact with their environments and influence ecological dynamics. We will investigate how trees sense and respond to environmental stimuli, shape patterns of biodiversity, influence ecosystem structure and function, and are impacted by global environmental change. As we focus on the science of forest ecology, we will also place strong emphasis on the professional development of each individual student. The course will offer significant opportunities to strengthen one's skills in thinking and communicating about scientific research and to consider how these skills can be employed in future careers. Each student will be expected to increase his or her understanding of best practices in scientific research and skills in formulating questions and synthesizing information. Course Literature When Forest Ecology is expressed I mean both plant and trees, with stimuli and other environmental agents. Treating only plants isn’t sensible. NOTE: course has a rain or shine policy with any outdoor activity Literature TBA Lecture Assessment: Quizzes Labs 3 Exams Projections and Species Distribution Project Projections and Species Distribution Project --> Will employ data sets for various ecosystems from unique regions; data sets subject to change. The given packages have vignettes to accompany their reference manuals; there may be supporting journal articles for each package as well. There must be competent overview and logistics to complement implementation for each packages. Students are required to apply the mentioned packages and given journal article. -simecol -popdemo -sdm or SSDM -Zhang L. et al. (2015) Consensus Forecasting of Species Distributions: The Effects of Niche Model Performance and Niche Properties. PLoS ONE 10(3): e0120056. Controversial topic research and presentation --> We can much more by having to teach and defend something to others, so you will have the opportunity to thoroughly research, present, and defend one of several topics relating to forest ecology to your peers, who will critically question both sides. Possible topics include: Transgenic Plants/Trees – Should plants be genetically modified for human use? Wildfire Suppression – Should wildfires be suppressed? Salvage Logging – Should salvage logging be allowed on federal lands? Logging Old-Growth Forests – Should logging occur in old-growth forests? Subsidization of Alternative Fuels – Should alternative fuels be federally subsidized? Forestry Based Carbon Offsets – Are forestry-based carbon offsets effective? Pre-European Settlement Benchmarks (PES) – Should PES be the benchmark for forest management and restoration efforts? Additional topics can be submitted by students until final date. On a given date all students MUST submit in order of preference three topics and whether they wish to work on the pro- or con-group. I will assign the topic, position and date to all students by whatever date. The pro- and con-position for each topic will be presented by a distinct group composed of 2-3 students. You may include economic, societal and political arguments into your discussion, but the primary focus MUST be scientific and if should directly relate to plant/forest ecology. One week prior to topic discussion a short paper (< 10 pages from either primary or secondary literature) supporting your group’s assigned viewpoint needs to be e-mailed to me or put in the appropriate “Dropbox” for the entire class to read. All papers turned in after the deadline will have 10 points deducted each day. I Course Outline: Individual Plant/Tree Interactions with Resources Light Water Mineral Nutrients & Multiple Limiting Resources Population Dynamics Population Structure & Plant/Trees Demography Species Life History Traits & "Strategies" Community Dynamics Community Assembly & Island Biogeography Succession Disturbance Species Interactions: Overview & Competition Species Interactions: Reproduction & Dispersal Species Interactions: Herbivory & Plant/Tree Pathogens Species Interactions: Plant/Tree-Soil Feedbacks Species Diversity Ecosystem Dynamics Decomposition & Soil Organic Matter Ecosystem Productivity Nutrient Cycling Human-Accelerated Environmental Change Deforestation Fire Ecology Invasions of Non-Indigenous Plants & Plant Pests Climate Change & Effect on Forests Overhunting & Overfishing Model developments based on data to exhibit cases Subject to real world constraints Invasive predators Invasive competitors Invasive consumers perturbating the ecological system Climate temperature acceleration with effects Predator-Prey Systems (ecological meaningfulness, NOT mathematical fetishes with asymptotics, chaos, bifurcations, Adjoint[Adjoint[Adjoint]], etc.). There will be much attempt to acquire real world meaningfulness for parameters w.r.t. to real data Lotka-Volterra Equations Generalised Lotka-Volterra Equations R packages of interest (deSolve, FME, primer) Restoration Ecology Controversial Topics Transgenic Plants/Trees Alternative Fuels Wildfire Suppression Salvage Logging Pre-European Settlement Benchmarks Climate Mitigation vs Adaptation Culling Class Party Labs --> Lab 1 Quantitative analysis Lab 2 Sapling growth responses to resources Field & Data work-up Lab 3 Forestry Forest succession: Field work Forest succession: Data work-up & writing Lab 4 – 5 Soil resources & forest community structure Field Trip to forest Effects of “whatever significant tree” on the establishment of inter-specific sdlg’s: Field Trip to Nature Preserve. “Whatever significant tree” lab: Field patterns, hypotheses, experimental design, writing successful research reports. Work on “whatever significant tree” experiments. Soil resources & forest community structure: Data work-up & writing. Lab 6 Perturbations Disturbance & species diversity: Field work. Disturbance & species diversity: Data work-up & writing Lab 7 Productivity Productivity: Data work-up & writing Lab 5 re-acquaintance. “Whatever significant tree” lab: Progress interview & Workshop (PowerPoint and presentation tips). Work on “whatever significant tree” experiments. “Whatever significant tree” symposium. Prerequisites: ODE, Biostatistics I & II, General Chemistry I & II, Field Botany, Dendrology Invasive Ecology Invasion Ecology is the study of introduced, non-native species and the factors that sometimes lead to their population explosions and negative ecological impacts in the new region. In this course, we will make explicit connections between fundamental concepts in ecology and evolutionary biology, topics specific to invasion ecology, and the idiosyncratic details surrounding particular invasive species. Goals for the course are to emphasize the ecological and economic importance of species invasions and to use the often-fascinating case studies from invasion biology to illustrate ecological and evolutionary principles. Layman terminologies that will resonate naturally throughout course: Pestilence Pathogens Parasitism Mass Consumption Disequilibrium Ecological feedback Trafficking Furthermore, concerning invasive ecology it’s not responsible to consider the botanic field concerns as disjoint from animalia in ecology. Ecosystems have equilibrium, dependencies, cooperation, etc., hence whatever invasive species present can perturb the ecosystem, influencing both producers and the levels of consumers, etc. By the end of this course, you should be able to: 1. Differentiate between commonly (mis)used terms used to describe introduced species. 2. Describe the major stages of, and barriers to, invasion success. 3. Describe major hypotheses used to explain invasion success. 4. Understand and explain fundamental concepts in ecology and evolutionary biology in the context of species invasions. 5. Critically assess claims regarding invasive species from the media. 6. Search for references to provide background material and support inferences, distinguishing between peer-reviewed and other sources. This course also has a service-learning component, for which all students will volunteer 8 hours assisting with invasive species management and/or monitoring and then reflect on their experiences. To facilitate this, a field day will be organised during the semester where we remove invasive species, set up long-term monitoring plots and collect baseline pre- and post-removal monitoring data. Literature: Elton, CE. 2000. The Ecology of Invasions by Animals and Plants. University of Chicago Press. Lockwood, JL, MF Hoopes and MP Marchetti. 2013. Invasion Ecology, 2nd edition (selected chapters). Wiley-Blackwell. Course Assignments --> Naturally, course assignments will be given throughout term. Will be lecture related. Exams --> This class will have both a midterm and a final exam. The midterm exam will cover topics from the first half of the class while the final will be comprehensive, covering information from throughout the semester. You will be tested on information from all aspects of the course (course readings, lectures and class discussions) and will be provided with a study guide and an in-class review to help you prepare. Exams may be multiple choice, true/false and/or short essay. Case Study Paper --> You will write a paper focused on the biology and ecology of a single non-native species (or group of closely related, ecologically similar species) of your choosing, based on peer-reviewed scientific literature. The objectives of this exercise will be to familiarize yourself with important characteristics of the species relating to its biology, the ecological role it plays in both the native and introduced regions, and the factors that facilitated its introduction to and establishment in the introduced region (referring to one or more of the major invasion hypotheses we’ve covered during the course). You will also be asked to identify key unanswered questions or areas of conflict in the literature regarding invasion success for which additional study would be useful. Case Study Poster Presentation --> Sharing research results with a larger audience is a critical component of the scientific process. You will prepare and present a poster and accompanying brief oral presentation to share your findings from the Case Study Paper with a general non-science audience in a poster session held at the end of the semester. You will be assessed based on your poster and oral explanation of your findings (40 points), as well as engagement with your fellow students about their work (10 points). Because the intended audience is the general public, this is an opportunity to be creative about how you share your findings. It will also allow you to compare-and-contrast your system with systems on which your peers have chosen to focus. Invaders --> in the News Introduced and/or invasive species are commonly mentioned in the news and popular press. Some well-known examples that you may be familiar with already. Over the course of the semester, you will identify three (3) examples of introduced species in the news and prepare a brief written summary of the story and why it is (or is not) important from an ecological and societal perspective (20 points each × 3 = 60 points). For one of these three stories, you will dig deeper into the specific claims made in the article and prepare a brief report that assesses the extent to which those claims are justified based on peer-reviewed scientific literature on the topic (40 points). The objective of this exercise is to think critically about how invasive species are portrayed in the popular press and assess how well those outlets tend to interpret scientific evidence for the general public. Computational & Empirical Development Projects (not necessarily in given order--> Peterson, A. (2003). Predicting the Geography of Species’ Invasions via Ecological Niche Modeling. The Quarterly Review of Biology, 78(4), 419-433 Robert F. Doren, Jennifer H. Richards, John C. Volin (2009). A Conceptual Ecological Model to Facilitate Understanding the Role of Invasive Species in Large-scale Ecosystem Restoration, Ecological Indicators, Volume 9, Issue 6, Supplement, Pages S150-S160 Crall, A., Jarnevich, C., Panke, B., Young, N., Renz, M., & Morisette, J. (2013). Using Habitat Suitability Models to target Invasive Plant species Surveys. Ecological Applications,23(1), 60-72. Lustig, A. (2017). Modelling Framework for the Establishment and Spread of Invasive Species in Heterogeneous Environments. Ecology and Evolution, volume 7 Issue 20, pages 8338 – 8348 Kariyawasam, C. S., Kumar, L., & Ratnayake, S. S. (2019). Invasive Plants Distribution Modeling: A Tool for Tropical Biodiversity Conservation with Special Reference to Sri Lanka. Tropical Conservation Science Roy-Dufresne, E., et al. (2019). Modelling the Distribution of aWwide-Ranging Invasive Species using the sampling Efforts of Expert and Citizen Scientists. Ecology and Evolution, 9(19), 11053–11063. Prerequisites: Biostatistics I & II, Forest Ecology Ecology Methods A survey of physical and biological processes that control the distribution and dynamics of vegetation and common methods used to understand these patterns. Through fieldwork and individual projects, students will gain hands-on experience regarding concepts and field methods in vegetation science. Based at (whatever) research station, we will spend 3 weeks exploring the ecology of the region – from tip to tip, with a focus on dynamics of various landscapes (mountainous, forest, plains, grasslands, etc, etc). Fieldwork will emphasize conceptual bases for and practicalities of vegetation research. NOTE: course will be given in “summer” and “winter” terms to not be in conflict with other courses. Course will run 3 - 5 weeks with “blue collar” hours each scheduled day. NOTE: students are expected to have proper apparel for environments to immerse into. Rehydration, eco-friendly sunscreen/bug repellent, head shade, insulated smartphone (not for music nor social media, nor passing time with entertainment), etc. etc. NOTE: It’s expected that students are competent with geographical data recording (latitude, longitude, elevation, date, time, province; such augment ecology data. Noteworthy: THIS IS A RAIN OR SHINE COURSE Course components – Background lectures Field trip (whatever altitudinal transect) Field exercises Readings Individual research projects Text: Mueller-Dombois & Ellenberg. 2003. Aims and Methods of Vegetation Ecology, Reprint of 1st edition, Blackburn Press. References: Texts from Field Botany course Texts from Dendrology course Tools: Google Maps Google Earth Assessment: Participation in field exercises (20%) Written assignments & in-class activities (45%) Project (design, implementation, and presentation) (30%) Field journal (5%) Specific objectives are to: Understand the goals and key concepts of vegetation/tree science Know how to design and implement a vegetation/trees field study Be familiar with general foundation information on common classification systems and ambiance vegetation/trees As a model for working in other ecosystems, be familiar with Colorado Front Range vegetation/trees in terms of (1) common species and plant lifeforms and (2) controls over landscape distribution of predominant vegetation types Identify common ambiance vascular plants General topics include: (1) Concepts of communities – complementary perspectives (2) Vegetation/tree classification systems – physiognomic, floristic approaches (3) Structure and function of ambiance biomes/ecoregions (4) Survey of factors controlling the distribution and dynamics of vegetation at continental, regional, landscape, and site scales – and ways to study vegetation at each of these scales Climate, physiography, soils, biotic interactions, time (succession, disturbance, etc.) (5) Concepts in field research design for Assessing vegetation/trees in space (classification, mapping, microhabitat studies) Assessment in time (vegetation dynamics, monitoring) Setting up hypotheses-driven experiments (6) Practicalities of field research Problem formulation Sampling protocol development (field technique selection, sampling design, etc.) Orienteering: map, compass, GPS, clinometer Supplemental data resources – vegetation-tree/soil maps, site histories Data management (QA) Data analysis (see Statistics) Communication of results (graphic visualization, oral and written presentation) (7) Plant/tree identification skills Major vascular plant/tree family characteristics Identification of common ambiance genera and species Use of dichotomous keys (8) Statistics – tools and design considerations Descriptive stats Exploratory stats – cluster analysis, ordination Hypotheses testing (9) How field studies interface with other areas in vegetation/landscape/ecosystem science Conservation, land management GIS, remote sensing applications Simulation (numerical) modelling – parameterization, validation Prerequisites: Field Botany, Dendrology, Biostatistics I & II, Upper Level Standing Geographic Information Systems for Biologists: The field of Geographic Information Systems, GIS, is concerned with the description, analysis, and management of geographic information. This course offers an introduction to methods of managing and processing geographic information. Emphasis will be placed on the nature of geographic information, data models and structures for geographic information, geographic data input, data manipulation and data storage, spatial analytic and modelling techniques, and error analysis. NOTE: course is focused mostly of botanical and ecological interests, with some climate/meteorological elements. The course is made of two components: lectures and labs. In the lectures, the conceptual elements of the above topics will be discussed. The labs are designed in such a way that students will gain first-hand experience in data input, data management, data analyses, and result presentation in a geographical information system. The basic objectives of this course for students are: 1. To understand the basic structures, concepts, and theories of GIS 2. To gain a hand-on experience with a variety of GIS operations Typical Texts: Longley P.A., M.F. Goodchild, D.J. Maguire, D.W. Rhind, 2011.Geographic Information Systems and Science. John Wiley and Sons Chang, K.T., 2012. Introduction to Geographic Information Systems (Sixth Edition). McGraw Hill, New York de Smith, M., Goodchild, M., Longley, P., 2013. Geospatial Analysis: A Comprehensive Guide (www.spatialanalysisonline.com) Tools --> A GIS of your choosing; students will be debriefed on operational requirements Google Earth Google Maps Resources --> https://www.google.com/earth/outreach/learn/ support.google.com/maps/answer/144349 There are highly established freeware GIS tools for use. Premier such available are SAGA GIS, ILWIS, MapWindow GIS, uDig, GRASS GIS and others; check Goody bag post. NOTE: GRASS GIS may be prerefence. Major priorities are sustainable skills in logistics, data management, accessibility & integration of data sets for project development and exhibition. Project(s) to have considerable life cycles with future use. Additionally, Google Earth and Google Maps can possibly coexist in such a instruction environment, primarily for rapid data visualisation. Course is concerned with the ability to develop meaningful professional data analysis and visualisation of sustainable value to whatever specified target audience. Unique talent development among such tools are encouraged, under the condition that the interests or demand of the target audience is appeased, of high quality. Some highly capable students will be able to develop projects with various systems, while for others finding an environment that suites them is key (highly dependent on what they comprehend and the effort they give). NOTE: in this course data from prerequisites can/will be applied to be constructive; dates and times must be instituted. Meteorological and oceanographic data may also be incorporated. Class Presentation --> Students need to review a journal article (or multiple articles) and give a presentation in the class. The article or articles can relate to GIS concepts, theories, or applications. An article in your discipline is preferred for you to review, for the reason that it would help you to think how to apply GIS in your work in the future. To present your reviewed article, you need to prepare five to eight slides in the format of PowerPoint, which would take approximately five to six minutes to present. In your slides, one of them would be how GIS is helpful in the article. You will have to give a small demonstration of some partial development for your project that substantially relates to your goals with whatever choice of tool employed. Followed by some substantial development (already done) with a GIS or other tool, or combination. You will have two or three minutes to answer the questions raised by the audience. Grading --> Lab Exercises 40% Exam I 20% Exam II 20% Presentation 20% Labs --> There are two components for labs: 1. Having GRASS GIS as preference concerns standard developments with course progression. 2. Extracurricular activities with Addons for GRASS GIS. Primarily, there must be strong development for a specific topic in (1) in order to commence with a respective Addons activity -- https://grass.osgeo.org/grass82/manuals/addons// Multicriteria decision decision analysis must be one topic for Addons extracurricular activities. An example: Massei, G., et al (2014). Decision Support Systems for Environmental Management: A Case Study on Wastewater from Agriculture, Journal of Environmental Management, Volume 146, Pages 491-504 However, PROMETHEE is not our only interest, and multiple MCDA addons will be pursued. Course Outline --> WEEK 1 Course Overview GIS Overview The Nature of Geographic Information WEEK 2 Data Representation Measuring Systems: Location – Coordinate Systems Data Representation Measuring Systems: Location – Coordinate Systems (Continue) WEEK 3 Data Representation Measuring Systems: Location – Coordinate Transformation Data Representation Measuring Systems: Topology Measuring Systems: Attributes WEEK 4 Data Representation Spatial Data Models: Introduction to spatial data models Spatial Data Models: Raster data models Data Representation Spatial Data Models: Relational Data Models Spatial Data Models: Vector Data Models (I) WEEK 5 Data Representation Spatial Data Models: Vector Data Models (II) Data Representation Spatial Data Models: TIN Summary of Spatial Data Models: Raster, Vector, TIN WEEK 6 Data Representation Linking attribute data with spatial data Recent Development of Data models WEEK 7 GIS Database Creation and Maintenance (I) Data Input & Editing GIS Database Creation and Maintenance (II) DBMS and its use in GIS WEEK 8 Review for Exam 1 Exam 1 WEEK 9 GIS Database Creation and Maintenance (III) Metadata / Database creation Guidelines / NSDI Data Analysis Measurement & Connectivity WEEK 10 Data Analysis Interpolation WEEK 11 Data Analysis Digital Terrain Analysis Data Analysis: Statistical Operations & Point Pattern Analysis WEEK 12 Data Analysis Classification Data Analysis GIS-based Modelling and Spatial Overlay (I) WEEK 13 Data Analysis GIS-based Modelling and Spatial Overlay (II) Data Analysis Summary Uncertainty WEEK 14 Geo-representation, Geo-presentation, and GeoVisualization GIS Applications WEEK 15 Student Presentations Student Presentations WEEK 16 Review for Exam Exam II Prerequisites: Field Botany, Dendrology, Aquatic Botany, Biostatistics I & II, Ecology Methods Plant Propagation I & II Principles and methods of plant propagation practiced. After completion of this class, you will have a practicable knowledge on seed germination and handling, rooting cuttings of various plant types, procedures for grafting and budding, using underground vegetative organs for plant increase, orchid propagation by rhizome and seed, and tissue culture propagation of selected plants. Students will acquire professional practice in plant propagation. Concerns being competent and professional with the implementation of grafting, cuttage, seedage and micropropagation. NOTE: this is a two term course. NOTE: Micropropagation will be treated extensively in the second term. The second term concerns interest in advance review and advance replication of labs of selected topics from prior term, but will be dominated by micropropagation pursuits. When successfully completing this course a student will be able to: Describe the principles of plant inheritance, plant reproduction and organogenesis. Recognise the physiological and anatomical changes a plant exhibits during asexual and sexual propagation. Select the appropriate methods of asexual and sexual propagation based upon biological characteristics of horticultural crops. Manipulate the propagation environment to promote the successful propagation of plants. Develop skills for using common asexual and sexual propagation techniques. Course Texts --> Plant Propagation: Principles and Practices, by Hartmann, H.T., D.E. Kester, F.T. Davies, and R.L. Geneve. Prentice Hall Plant Propagation; Concepts and Laboratory Exercises, 2nd Edition. Edited by Caula A. Beyl and Robert N. Trigiano, CRC Press Plants From Test Tubes, by Lydia Kyte & John Kleyn, Timber Press Course Assessment --> Quizzes Lab projects/experiments/reports 3 Exams Topics in the two term sequence --> Topics will be efficiently and tangibly administered to support lab activities given below. NOTE: for labs, if specimens are inaccessible or costly it’s possible to have more economic substitutes. Lab Activities -- Introduction to the greenhouse and propagation facilities, laboratory and safety procedures. Greenhouse procedures, and intermittent mist systems. Asexual Prop: Woody stem propagation Asexual Prop: Herbaceous stem propagation, leaf cuttings, root cuttings, & grass propagation Asexual Prop: Scaling of Lilium bulbs, twin-scaling of tunicate bulbs Sexual Prop: Orchid seed & fern spore germination Asexual Prop: Herbaceous plant grafting Asexual Prop: Woody plant grafting Asexual Prop: Geophytes Sexual Prop: Controlled pollination and hybridization. Sexual Prop: Seed dormancy and germination Propagation guides Micropropagation hands-on practical skills: Sterile technique Preparation of plant tissue culture nutrient media. Within vitro embryo culture (Flasking) and acclimatization techniques for growing orchids: Sterilization and sowing of orchid seeds. Learn the sequence of orchid seed germination and seedling development Planting out and managing orchid seedlings. Micropropagation via axillary shoot culture for propagation of Kalmia: Initiation Subculture and multiplication Ex vitro rooting and acclimation Lab Exercises in the given order: 1. Media Preparation 2. Initiation (Stage I) 3. Subculture and multiplication (Stage II) 4. Ex vitro rooting and acclimation (Stage IV) 5. Sterilization and sowing of orchid seeds 6. Subculture (reflasking) orchids 7. Planting out and managing orchid seedlings Prerequisites: at least upper junior Standing Wildlife Conservation Models Course introduces historical and contemporary advancements in the development of wildlife habitat models and their implementation in conservation planning. Course introduces current and effective techniques of wildlife modelling. Course will have a mixture of concepts, methodology, and applications topics towards development research and modelling for wildlife conservation. Course Literature --> Thompson, F. R. and Millspaugh, J. (2008). Models for Planning Wildlife Conservation in Large Landscapes. Netherlands: Elsevier Science Note: hopefully adjustment to ambiance of interest can be done. Tools --> GIS of choice (preferably GRASS GIS) Will be applying addons as well LANDIS II < https://www.landis-ii.org/home > Mentioned software in text will be introduced and implemented following analysis of their model structure and logistics for implementation; if software given are out of date or inaccessible, will then incorporate substitutes. USDA Natural Resources Conservation Service: Science and Technology - Conservation Tools Software (with analytical supporting documentation, then logistics overview before implementation) Wildlife Habitat Index RUSLE2 SPAW WEPS Win-PST NRL Bioenergy Models: https://bioenergymodels.nrel.gov/models/ Development in Course --> Course will be projects based where commitment and drive are crucial. Yet, there can be quizzes for concepts, developmental procedures and logistics. Labs --> Note: labs will likely require multiple sessions for completion. Groups may be assigned unique environments --Development with GRASS GIS mentioned in Tools. Due to prerequisites, development will be somewhat intensive. Will have heavy investment into Section II of course literature. --Habitat Networks for Terrestrial Wildlife --LANDIS II --USDA Natural Resources Conservation Service: Science and Technology - Conservation Tools Software (selection choices TBA) --GIS-Based Habitat Suitability Index (HSI) model (hopefully feasible in course, with need for data resources) --LCA in land use Chaplin-Kramer, R., Sim, S., Hamel, P. et al. (2017). Life Cycle Assessment Needs Predictive Spatial Modelling for Biodiversity and Ecosystem Services. Nat Commun 8, 15065 De Rosa, M. (2018). Land Use and Land-use Changes in Life Cycle Assessment: Green Modelling or Black Boxing? Ecological Economics, volume 144, pages 73 – 81 Prerequisites: Geographic Information Systems for Biologists SUMMER AND WINTER ACTIVITIES APPLICABLE TO BOTANY CONSTITUENTS: 3, 5, 15, 17, 18, 19, 20, 23, 24, 25, 26, 27, 29, 33, 37, 38, 39, 40, 42, 44 ADDITIONALLY --> The Forest Landscape Assessment Tool (FLAT) NOTE: students must successfully complete at least the Field Botany and Dendrology courses to participate in activity. Invasive Species and Pathology aspects likely to become inevitable with field observation (and among data collections), but such courses are not mandatory to participate in this activity. The Forest Landscape Assessment Tool (FLAT) is a set of procedures and tools used to rapidly determine forest ecological conditions and potential threats. FLAT enables planners and managers to understand baseline conditions, determine and prioritize restoration needs across a landscape system, and conduct ongoing monitoring to achieve land management goals. The rapid assessment process presents a cost-effective opportunity for landowners - including local governments, private owners, and nongovernmental organizations - to use ecological data to guide decision-making and improve environmental outcomes on their lands. Study Goals --> -Conduct forest assessment on over AB,000 acres of X County managed open space forest lands distributed across Y park sites -Establish baseline data that describes forest conditions per site and system wide -Identify key forest conditions that may need corrective and restorative actions -Develop long term forest stewardship recommendations for X County managers -Develop rapid forest assessment protocols that can be replicated on other public lands -Identify opportunities to collaborate with public & private agencies on forest stewardship Study Approach -Habitat Management Units (HMU) delineated for each site -Each HMU characterized by over story and under story species composition including invasive plants and other forest health indicators Ciecko, Lisa; Kimmett, David; Saunders, Jesse; Katz, Rachael; Wolf, Kathleen L.; Bazinet, Oliver; Richardson, Jeffrey; Brinkley, Weston; Blahna, Dale J. (2016). Forest Landscape Assessment Tool (FLAT): Rapid Assessment for Land Management. Gen. Tech. Rep. PNW-GTR-941. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. < https://www.fs.fed.us/pnw/pubs/pnw_gtr941.pdf? > 1. Tools and Materials Before leaving on a field assessment A team should be properly equipped with required data collection tools. All field teams should have: �� Data entry tools Hand-held electronic data recorder or field data sheets Navigation devices GPS Map (including overlay of the MU boundaries) Compass Plant identification resources Camera Tree and canopy measurement tools For training and calibration of ocular estimate: Increment borer Diameter tape Densitometer (Moosehorn) Clinometer 2.Information Systems Software GIS (proprietary or open source, preferably GRASS GIS with addons) 3. THE “11” ESSENTIALS for comfort and safety in the field Sun protection (sunglasses, lip balm, and sunscreen) Bug repellent (eco-friendly) Proper clothing & footwear for harsh terrain or inclement weather such as rain gear, waterproof hiking/work boots, gaiters, and insulation like gloves, hats, and jackets. First aid supplies Utility knife or multi-tools (e.g. Leatherman, Swiss army knife) Food (plus an extra day’s supply) Lots of Water! (plus, an extra day’s supply) Headlamp or illumination source Fire (matches or lighter in waterproof container Emergency shelter (tent, tarp, bivy, or reflective blanket) Communication device smart phone or two way radio NOTE: don’t make activity a “Jurassic Park” event where one’s inconsiderate actions to have music jeopardizes themselves and others. NOTE: aerial imagery in terms of resource will be satellite imagery and data. Along with boundary, mapping and data, etc. NOTE: in the long run FLAT activities will reside in the same calendar often with FIA, REA and NRCA. FLAT Field Manual --> Parks and Recreation Division FLAT Field Manual: The Forestry Landscape Assessment Tool. Kings County Park, Department of Natural Resources and Parks https://forterra.org/wp-content/uploads/2015/06/FLAT_Field_Manual_Final-20131209.pdf Comparing plant cells PART A Students will observe plant cells using a light microscope. Two cells will be observed, one from the skin of an onion, and the other from a common aquarium water plant (anacharis or Elodea). Students will compare both types of cells and identify structures visible in each. Preliminary Elementary questions Name three structures found in plant/tree leaves cells AND in animal cells. Name two structures found in plant/tree leaves cells but not animal cells. What structure surrounds the cell membrane (in plants/tree leaves) and gives the cell support. What is the function of chloroplasts? Observation questions Describe the location and shape of chloroplasts. Why were no chloroplasts found in the onion cells? (hint: think about where you find onions) Determination of cell sizes Did you notice the chloroplasts moving within the cytoplasm of the elodea plant? Do they all move in the same pattern or direction? Suggest a reason why these structures move. Develop a quick experiment to test your hypothesis. Describe the test below, and if you have time conduct the test. PART B Pursue lab investigation based on the following: Wymer C.L., Beven A.F., Boudonck K., Lloyd C.W. (1999) Confocal Microscopy of Plant Cells. In: Paddock S.W. (eds) Confocal Microscopy Methods and Protocols. Methods in Molecular Biology, vol 122. Humana Press. PART D Metal shadowing and Freeze Fracture (if able) Visualize the surface of isolated subcellular structures or macromolecules in the transmission electron microscope. The specimen is coated with a thin layer of evaporated metal, such as platinum. The metal is sprayed onto the specimen from an angle so that surfaces of the specimen that face the source of evaporated metal molecules are coated more heavily than others. This differential coating creates a shadow effect, giving the specimen a three-dimensional appearance in electron micrographs. The preparation of samples by freeze fracture, in combination with metal shadowing, has been particularly important in studies of membrane structure. Specimens are frozen in liquid nitrogen (at -196°C) and then fractured with a knife blade. This process frequently splits the lipid bilayer, revealing the interior faces of a cell membrane. The specimen is then shadowed with platinum, and the biological material is dissolved with acid, producing a metal replica of the surface of the sample. Examination of such replicas in the electron microscope reveals many surface bumps, corresponding to proteins that span the lipid bilayer. A variation of free fracture called freeze etching allows visualization of the external surfaces of cell membranes in addition to their interior faces. Followed by biochemical and organic chemistry software to model and simulate macromolecules. Simulating the behaviour or reactions with common stimuli, penetration, etc, etc., etc. PART D Subcellular Fractionation Organelles extraction and centrifugation methods pursued towards observation PART E Plant cells can be grown and manipulated in culture. Such in vitro cell culture systems have enabled scientists to study cell growth and differentiation, as well as to perform genetic manipulations required to understand gene structure and function. Plant cells can also be cultured in nutrient media containing appropriate growth regulatory molecules. In contrast to the polypeptide growth factors that regulate the proliferation of most animal cells, the growth regulators of plant cells are small molecules that can pass through the plant cell wall. When provided with appropriate mixtures of these growth regulatory molecules, many types of plant cells proliferate in culture, producing a mass of undifferentiated cells called a callus. A striking feature of plant cells that contrasts sharply to the behaviour of animal cells is the phenomenon called totipotency. Differentiated animal cells, such as fibroblasts, cannot develop into other cell types, such as nerve cells. Many plant cells, however, are capable of forming any of the different cell types and tissues ultimately needed to regenerate an entire plant. Consequently, by appropriate manipulation of nutrients and growth regulatory molecules, undifferentiated plant cells in culture can be induced to form a variety of plant tissues, including roots, stems, and leaves. In many cases, even an entire plant can be regenerated from a single cultured cell. The ability to produce a new plant from a single cell that has been manipulated in culture makes it easy to introduce genetic alterations into plants, opening important possibilities for agricultural genetic engineering. PART F Xia Y., Petti C., Williams, M A. and DeBolt, S. (2014). Experimental Approaches to Study Plant Cell Walls During Plant-Microbe Interactions. Frontiers in Plant Science, Volume 5, Pages 540 Ecology Methods Reinforcement Reinforcement of field activities from course. There will be some preliminary Field Botany, Dendrology and Plant Systematics activity elements involved as well before implementing the ecology methods. Pesticide metabolism in Plants The following articles provide intelligence on pesticide metabolism in plants; however, interests also concerns experimental/laboratory pursuits. -Menn, J. (1978). Comparative Aspects of Pesticide Metabolism in Plants and Animals. Environmental Health Perspectives, 27, 113-124. -Van Eerd, Laura & Hoagland, Robert & Zablotowicz, Robert & Hall, J.. (2009). Pesticide Metabolism in Plants and Microorganisms: An Overview. Weed Science. 51. 472-495 -Katagi T. (2020). In vitro Metabolism of Pesticides and Industrial Chemicals in Fish. Journal of pesticide science, 45(1), 1–15. Xenobiotics metabolism in plants The following articles provide intelligence on xenobiotics metabolism in plants; however, interests also concern experimental/laboratory pursuits. Shimabukuro, R. H. and Walsh, W. C. (1979). Xenobiotic Metabolism in Plants: In Vitro Tissue, Organ, and Isolated Cell Techniques. Metabolism and Radiation Research Laboratory, Agricultural Research, Science and Education Administration, U. S. Department of Agriculture, Fargo, ND 58105 Sandermann H., Diesperger H., Scheel D. (1977) Metabolism of Xenobiotics by Plant Cell Cultures. In: Barz W., Reinhard E., Zenk M.H. (eds) Plant Tissue Culture and Its Bio-technological Application. Proceedings in Life Sciences. Springer, Berlin, Heidelberg. Sandermann H Jr. Plant Metabolism of xenobiotics. Trends Biochem Sci. 1992 Feb;17(2):82-4. Sandermann H. (1999) Plant Metabolism of Organic Xenobiotics. Status and Prospects of the ‘Green Liver’ Concept. In: Altman A., Ziv M., Izhar S. (eds) Plant Biotechnology and In Vitro Biology in the 21st Century. Current Plant Science and Biotechnology in Agriculture, vol 36. Springer, Dordrecht Rcompadre, Rage and popbio packages for botany and zoology Applying the R package Rcompadre and Rage to faciliate the use of the COMPADRE AND COMADRE databases and calculation of life history traits from matrix population models Owen R. Jones et al (2021). Rcompadre and Rage - Two R packages to Facilitate the Use of the COMPADRE and COMADRE Databases and Calculation of Life History Traits from Matrix Population Models. bioRxiv 2021.04.26.441330: https://www.biorxiv.org/content/10.1101/2021.04.26.441330v2.full.pdf Note: the Rcompadre and Rage packages are accompanied by vignettes; always observe the reference manuals as well because the vignettes don’t necessarily exhibit their full potential (which also involves your imagination and R skills) towards independent projects. Will pursue projects of interest. Note: the R package popbio can also serve well for additional interests. Observe its reference manual and the following: Stubben, C. and Milligan, B. (2007). Estimating and Analysing Demographic Models Using the popbio Package in R. Journal of Statistical Software, Volume 22, Issue 11 Such package also may have vignettes. Other R packages of interest (with analysis and logistics from supporting literature): -simecol -popdemo -sdm or SSDM Lab experiments with implementation of PCR, FISH, ELISA and IF Pathogens and diseases may be different to journal articles due to environment one resides in. Nevertheless, will also identify possible or ongoing threats in the ambiance. Will apply the mentioned techniques. Will also identify economic and ecologically friendly resolutions to such threats. --Enzyme-Linked Immunosrbent Assay (ELISA) Note: choice can be different to specmen in articles Description of technique and process Clark, M. F. (1981). Immunosorbent Assay in Plant Pathology. Annual Reviews, Volume 19 pages 83 – 106 Copeland R. (1998) Assaying Levels of Plant Virus by ELISA. In: Foster G.D., Taylor S.C. (eds) Plant Virology Protocols. Methods in Molecular Biology™, vol 81. Humana Press Pataky JK, et al (2004). Ability of an ELISA-Based Seed Health Test to Detect Erwinia stewartii in Maize Seed Treated with Fungicides and Insecticides. Plant Disease. 88(6):633-640 Eibel, P., Wolf, G.A. & Koch, E. Development and evaluation of an enzyme-linked immunosorbent assay (ELISA) for the detection of loose smut of barley (Ustilago nuda). Eur J Plant Pathol 111, 113 (2005). Logistics Detecting pathogens for chosen plant specimen --Polymerase Chain Reaction (PCR) Schena, L., Duncan, J. M. and Cooke, J. E.L. (2008). Development and Application of a PCR-based ‘Molecular Tool Box’ for the Identification of Phytophthora Species Damaging Forests and Natural Ecosystems. Plant Pathology 57, 64–75 Aljawasim, B. and Vincelli, P. (2015). Evaluation of Polymerase Chain Reaction (PCR)-Based Methods for Rapid, Accurate Detection and Monitoring of Verticillium dahliae in Woody Hosts by Real-Time PCR. Plant Disease, Volume 99, Number 6 Lamarche J. et al. (2015) Molecular Detection of 10 of the Most Unwanted Alien Forest Pathogens in Canada Using Real-Time PCR. PLoS ONE 10(8): e0134265. Visnovsky, S. D. et al (2020). A PCR Diagnostic Assay for Rapid Detection of Plant Pathogenic Pseudomonads. Plant Pathology, Volume 69, Issue 7, pages 1311 – 1330 --Immunofluorescnce (IF) Wiwart, M., Mierzwa, Z. (1997). Indirect Immunofluorescence - an Useful Method in Studies on Some Fungal Pathogens. In: Dehne, HW., Adam, G., Diekmann, M., Frahm, J., Mauler-Machnik, A., van Halteren, P. (eds) Diagnosis and Identification of Plant Pathogens. Developments in Plant Pathology, vol 11. Springer, Dordrecht. Baysal-Gurel, F. et al. (2008). An Immunofluorescence Assay to Detect Urediniospores of Phakopsora Pachyrhizi. Plant Disease Vol. 92 No. 10 Janse J.D., Kokoskova B. (2009) Indirect Immunofluorescence Microscopy for the Detection and Identification of Plant Pathogenic Bacteria (In Particular for Ralstonia solanacearum). In: Burns R. (eds) Plant Pathology. Methods in Molecular Biology (Methods and Protocols), vol 508. Humana Press --Fluorescence In Situ Hybridization (FISH) Shakoori A. R. (2017). Fluorescence In Situ Hybridization (FISH) and Its Applications. Chromosome Structure and Aberrations, 343–367 Young, A. P., Jackson, D. J., & Wyeth, R. C. (2020). A Technical Review and Guide to RNA Fluorescence In Situ Hybridization. PeerJ, 8, e8806. NOTE: other possible interests to develop Boothroyd, C. W., & Kelman, A. (1966). Laboratory Experiments in Plant Pathology. The American Biology Teacher, 28(6), 478–491. Structural Equation Modelling in Ecology Fan, Y., Chen, J., Shirkey, G. et al. (2016). Applications of Structural Equation Modeling (SEM) in Ecological Studies: an updated review. Ecol Process 5, 19 R environment assists: https://bookdown.org/bean_jerry/using_r_for_social_work_research/structural-equation-modeling.html https://quantdev.ssri.psu.edu/tutorials/structural-equation-modeling-r-using-lavaan https://stats.oarc.ucla.edu/r/seminars/rsem/ Ripeness and Staleness Also open to Biochemistry/Metabolic Biology students PART A (ripeness) Das, A. et al. (2016). Ultra-Portable, Wireless Smartphone Spectrometer for Rapid, Non-Destructive Testing of Fruit Ripeness. Sci Rep 6, 32504 Note: not interested in the additive manufacturing part, rather assembling primitive prototypes out of the components to implement. Note: generally use fruits attainable in your environment as substitutes. Side component 1: It’s important to characterise what type of molecules, polymers, etc. are distinctively prevalent for ripeness (for respective fruit). Considerable variation in freshness, say, groups consisting of consumable U were stored (G °C, I% RH) for 0, 2, 4, 6, 8, 10, etc., etc. days. Apply different types of consumables. Note: following such experiments to map the metabloc pathways for ripeneing. Can also include modelling and simulation of biochemical processes throughout. Side component 2: Experiments to conduct alongside side component 1 involving the same fruit speciments with 0, 2, 4, 6, 8, 10, etc., etc. days:-> Montero, T. M. et al (1996). Quality attributes of Strawberry During Ripening. Scientia Horticulturae, volume 65 Issue 4, pages 239 – 250 Ninio R. et al. (2003). Changes in Sugars, Acids, and Volatiles During Ripening of Koubo [Cereus peruvianus (L.) Miller] Fruits. J Agric Food Chem. 29; 51(3): pages 797-801 Anthon GE, LeStrange M, Barrett DM. (2011). Changes in pH, Acids, Sugars and Other Quality Parameters During Extended Vine Holding of Ripe Processing Tomatoes. J Sci Food Agric. 91(7): 1175-81. PART B (staleness) It’s important to characterise what type of molecules, polymers, etc. are distinctively prevalent for staleness (for respective consumable). Considerable variation in “age”, say, groups consisting of consumable X were stored (A °C, B% RH) for 0, 2, 4, 6, 8, 10, etc. etc. days. Apply different types of consumables. Note: generally use fruits attainable in your environment as substitutes. Note: there can be side component 2 like what is done in part A. Note: following such experiments to map the metabolic pathways for staleness. Can also include modelling and simulation of biochemical processes throughout. Wildlife Conservation Models Will be crash immersion OR advance recital of course detailed. Occupancy Modelling Note: will depend on data availability and credibility of such data. Guiding literature for activity --> MacKenzie, D. I. et al (2017). Occupancy Estimation and Modeling: Inferring Patterns and Dynamics of Species Occurrence. Academic Press Outhwaite, C. L., Chandler, R. E., Powney, G. D., & Collen, B., Gregory, R. S. & Isaac, N, J. B. (2018). Prior Specification in Bayesian Occupancy Modelling Improves Analysis of Species Occurrence Data. Ecological Indicators. 93. Pages 333-343 Stochastic Logistic Growth Models A. Review of deterministic standard logistic differential equation Model development and solution(s) Numerical Methods R packages B. Threshold Population Model Model development and solutions Numerical Methods R packages C. Extending (A) and (B) to Predator-Prey Models D. Stochastic logistic differential equation (SLE) Model development. Derivation (solution, expectation, variance) The distribution of SLE (with proof) Simulation by loop design. Investigate for different parameter values Use of R packages For simulation Monte carlo statistics at “final time T”. Mean path and confidence bands for this SDE Maximum and minimum values within confidence bands along with mean path. Analyse and develop: Møller, J. K., Madsen, H. and Carstensen, J. (2011). Parameter Estimation in a Simple Stochastic Differential Equation for Phytoplankton Modelling. Ecological Modelling 222, 1793 – 1799 Heydari, J., Lawless, C., Lydall, D. A., & Wilkinson, D. J. (2014). Fast Bayesian Parameter Estimation for Stochastic Logistic Growth Models. Bio Systems, 122, 55–72. NOTE: there may be other methods from other literature NOTE: will have other ecological interests E. Extending (D) to predator-prey models for ambiances of interest Phylogenetic Comparative Methods in R Revell, L. J. (2011). phytools: an R Package for Phylogenetic Comparative Biology (and other things). Methods in Ecology and Evolution 3(2), pp 217-223 Revell, L. J. and Harmon, L. J. (2022). Phylogenetic Comparative Methods in R, Princeton University Press Note: will pursue organisms of interest (botanic and animalia). US Government and IGO Resources tools for Agriculture MUST have analysis of supporting documentation before software use; followed by logistics, then software/tools implementation. Chosen software/tools sets subject to change. EPA WATERSHEDSS software: https://www.epa.gov/ceam/watershedss US FDA (1998) - Guidance for Industry: Guide to Minimize Microbial Food- Safety Hazards for Fresh Fruits and Vegetables USDA Integrated Farm System Model (IFSM) USDA Science and Technology Conservation Tools Software: https://www.nrcs.usda.gov/wps/portal/nrcs/detailfull/national/ndcsmc/?cid=stelprdb1042198 Other USDA software (huge lists): < https://data.nal.usda.gov/nal-terms/computer-software < https://www.ars.usda.gov/research/software/ Wauchope, R. D. et al (2003). Software for Pest-Management Science: Computer Models and Databases from the United States Department of Agriculture— Agricultural Research Service. Pest Manag Sci 59:691–698 OECD (1999), Environmental Indicators for Agriculture: Vol. 1: Concepts and Framework Vol. 2: Issues and Design -- "The York Workshop", OECD Publishing, Paris OECD (2001), Environmental Indicators for Agriculture: Vol. 3: Methods and Results. OECD Publishing, Paris 16. FSMA Final Rule on Produce Safety (country counterpart to): https://www.fda.gov/food/food-safety-modernization-act-fsma/fsma-final-rule-produce-safety NOTE: concerning field activities and labs for microbiology and botany the following text may serve well in backdrop: Millard, S. P. (2013). EnvStats: An R Package for Environmental Statistics, Springer

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COMPUTER SCIENCE

# COMPUTER SCIENCE Concerns the most up to date standardization via https://www.iso.org/home.html https://isocpp.org C++20 is the one of the latest installment standardization It may be in the best interest of Computer Science students that the General Education Appeasement courses be fulfilled during the “summer” and “winter” sessions. Advance standing upon matriculation would be greatly appreciated. For strong economy, self reliance, sustainability and progression the following three fields under Computer Science are crucial: Software Engineering Computational Science Networks & Security $$A. Computer Science major with Software Engineering concentration Curriculum: --Writing requirements Scientific Writing I & II --Mathematics requirements minimum Calculus for Science & Engineering I-III, Ordinary Differential Equations, Numerical Analysis, Probability & Statistics B --Science requirements minimum General Physics I & II --Computer Science requirements minimum 1. Fundamentals & Procedural Programming with C 2. C++ Programming I 3. C++ Programming II 4. Discrete Structures NOTE: course should not be summed by, “excrement tastes like ice cream, so ice cream tastes like excrement”. 5. Data Structures (C++ Programming II prerequisite) 6. Analysis of Algorithms (Discrete Structures, Numerical Analysis and Data Structures prerequisites) 7. Data Programming with Mathematica 8. Programming Language Concepts (Data Structures prerequisite) 9. Software Design (Data Structures prerequisite) Tools of usage and programming must be secured, geared to only those of interest. Developments must be secured against usurping by fellow students, etc. (permanent log dating, etc.) 10. Advanced Software Design (Software Design, Programming Language Concepts prerequisites) 11. Software Estimation and Metrics (Probability & Statistics B, Data Programming with Mathematica, Software Design prerequisites) 12. GUI Programming & Graphics (Data Structures prerequisite) 13. Computer Systems (Data Structures prerequisite) 14. UNIX/Linux Fundamentals (Data Structures prerequisite) 15. Operating Systems (Computer Systems) 16. Malware Reverse Engineering (Computer Systems, UNIX/Linux Fundamentals, Operating Systems prerequisites) 17. Theoretical Computer Science (Analysis of Algorithms prerequisite) 18. Compiler Construction (Programming Language Concepts, Theoretical Computer Science prerequisites) 19. Introduction to Databases (Computer Systems, Analysis of Algorithms prerequisites) $$B. Computer Science major with Computational Science concentration Curriculum: Writing requirements-- Scientific Writing I & II Science requirements-- General Physics I & II Mathematics requirements-- Calculus for Science & Engineering I-III, Ordinary Differential Equations, Numerical Analysis, Partial Differential Equations, Probability & Statistics B, Mathematical Statistics Computer Science requirements-- 1. Fundamentals & Procedural Programming with C 2. Discrete Structures NOTE: Course should not be summed by, “excrement tastes like ice cream, so ice cream tastes like excrement” 3. C++ Programming I 4. C++ Programming II (C++ Programming I prerequisite) 5. Data Structures (C++ Programming II prerequisite) 6. Data Programming with Mathematica 7. Programming Language Concepts (Data Structures prerequisite) 8. UNIX/Linux Fundamentals (Data Structures prerequisite) 9. Analysis of Algorithms (Discrete Structures, Numerical Analysis and Data Structures prerequisites) 10. Computer Systems (Data Structures prerequisites) 11. Parallel Computing I (Computer Systems, Data Structures, Numerical Analysis, PDE prerequisites) 12. Parallel Computing II (Parallel Computing I prerequisite) 13. Parallel Computing III (Parallel Computing II and Probability & Statistics B prerequisites) 14. Operating Systems (Computer Systems) 15. Theoretical Computer Science (Analysis of Algorithms prerequisite) 16. Machine Learning (Numerical Analysis, Data Programming with Mathematica, Analysis of Algorithms, Probability & Statistics B, Mathematical Statistics prerequisites) 17. Computer Science Modelling & Simulation $$C. Computer Science major with Networks & Security concentration This concentration will likely have two more courses than the other concentrations, however, there is no comparison since this concentration has high disparity to the other concentrations in skill and professionalism. The end rewards overwhelm the “unfairness” of two additional courses. Curriculum: Writing requirements-- Scientific Writing I & II Science requirements-- General Physics I & II Mathematics requirements-- Calculus for Science & Engineering I-III, Ordinary Differential Equations, Numerical Analysis, Probability & Statistics B Computer Science requirements-- 1. Fundamentals & Procedural Programming with C 2. Discrete Structures NOTE: Course should not be summed by, “excrement tastes like ice cream, so ice cream tastes like excrement” 3. C++ Programming I 4. C++ Programming II (C++ Programming I prerequisite) 5. Data Structures (C++ Programming II prerequisite) 6. Data Programming with Mathematica 7. Programming Language Concepts (Data Structures prerequisite) 8. UNIX/Linux Fundamentals (Data Structures prerequisite) 9. Computer Systems (Data Structures prerequisites) 10. Analysis of Algorithms (Discrete Structures, Numerical Analysis and Data Structures prerequisites) 11. Computer Networks with C++ (Computer Systems prerequisite) 12. Advance Computer Networks with C++ (Computer Networks prerequisite) 13. Principles of Network Security (Discrete Structures, Analysis of Algorithms, Advance Computer Networks with C++ prerequisites) 14. Penetration Testing & Ethical Hacking (Principles of Network Security prerequisite) 15. Operating Systems (Computer Systems) 16. Network Programming (UNIX/Linux Fundamentals and Operating Systems prerequisites) 17. Data Compression (Discrete Structures, Data Structures, UNIX/Linux Fundamentals, Numerical Analysis, Probability & Statistics B as prerequisites) 18. Applied Cryptography (Discrete Structures, Probability & Statistics B, Analysis of Algorithms as prerequisites ) 19. Data Center Networking (Programming Language Concepts, Computer Systems, Operating Systems, Advanced Computer Networks, Network Programming prerequisites) 20. Introduction to Databases (Computer Systems, Analysis of Algorithms prerequisites) 21. Database Security (Introduction to Databases prerequisite) Some course descriptions: Discrete Structures NOTE: this is not a mathematics course. Courses is not administered by the mathematics department. Texts for mathematical proofs are forbidden for use with this course. Being a proofs aficionado doesn’t make one a professional programmer. Mathematicians are appreciated for their contributions to human progression, but they are not integrated computer scientists. Mathematicians who take the role of viruses or immunodeficiencies or “restorers” of the status quo are no different to the idea of demons and devils recognised in civilisations. NOTE: course should not be summed by, “excrement tastes like ice cream, so ice cream tastes like excrement.” Course Texts --> A “Discrete Structures for Computer Scientists with Applications” textbook Daniel P. Friedman & Matthias Felleisen, The Little Schemer, MIT Press COURSE TOPICS --> Intro to logic Predicate logic Proofs; set theory Functions Sequences; induction Induction and Recursion Structural Induction Algorithmics: tail recursion, halting problem Relations Transitive closure, equivalence Integers, division Number Theory Number theory and cryptography Intro graph theory HOMEWORK --> There will be homework exercises for each course topic QUIZZES --> Quizzes will mirror homework LABS SCHEDULE --> Lab: Intro to scheme Lab: Boolean functions in scheme Lab: lists in Scheme Lab: predicates on lists Lab: relations as lists in Scheme Lab: recursion on lists Lab: recursive construction of lists Lab: tail recursion Lab: Relation operations on list representation Lab: role-based access control Lab: play with modulo and primes Lab: number theoretic algorithms Lab: various topics Lab: various topics Co-requisite or Prerequisite: Calculus for Science & Engineering I Fundamentals & Procedural Programming with C The goal of the course is to familiarize students with programming in a “high-level language” (C language) while studying the main constructs of C. Students will learn to translate algorithms into correct programs as well as to debug, document and maintain the code. Each weekly assignment covers some aspect of the standard material from instruction. You are expected to complete the evaluation questions assigned. The class “lectures” will primarily focus on helping you with any difficulties you may have with the weekly assignments. The lectures are complemented by lab sessions. The sections of this course differ in the time of their lab sessions. A lab session is conducted by a lab instructor. Lab attendance and participation is required. Lab sessions are an integral part of the course and lab assignments constitute a significant part of the course grade. The lab policies are stated on the lab website and are to be followed for the success in the lab. There are 4 exams. All exams are closed book, open notes, and must be individual work. It is expected that you take each exam at the scheduled time, unless you make prior arrangements with me, or have a documented illness (in which case I expect you to contact me as soon as possible). You will be tested on the material we covered in class. The textbook or the slides alone may not be sufficient for adequate preparation for the exams. Weekly Assignments & bug fixing log 3-4 Quizzes Lab Assignments 3 Exams Programming Assignments will be graded using the following system --> Appearance 15% Logic 30% Efficiency 15% Syntax 30% Documentation 10% Assignments --> Assignments will stem from various texts/literature Quizzes --> For quizzes it’s important to understand what you’re trying to do. You will be required to develop conceptual structures/planning before providing C language builds. There may be vice versa cases as well. There may be cases where you must identify errors and specify corrections. Labs --> Labs will have both recitation and projects development. Expect conceptual guidance and “pointers” from instructor, but nothing more. Concerning the projects, to have constructiveness, will incorporate applications for: Strings Random number generator Service Algorithms (choose out of the following with 1 and 2 being mandatory) 1. Designing a programming solution to the problem; Developing a C library: design of a programming solution based on “customer” requirements; development of an appropriate C library; identifying the data structures that can be used in providing a robust and maintainable solution to the given problem; using the design to implement the code; including detailed comments that explain each function and help in future maintenance of the script. 2. Test application: building a test application for the prior assignment 1 scenario, and performing a unit test 3. Simple calculator 4. Student record management system 5. Calendar 6. Mini project phone book 7. Unit Converter 8. Mini voting system (if deemed manageable by instructor) 9. Tic-tac-toe game (if deemed manageable by instructor) 10. Matrix calculator (if deemed manageable by instructor) 11. Library management system (if deemed manageable by instructor) 12. Electricity bill calculator (if deemed manageable by instructor) 13. Movie ticket booking system (if deemed manageable by instructor) Physics (2-3 projects mandatory) Embedded Systems (2-3 projects mandatory) In-class Algorithm Exercises --> During certain lecture periods there will be dedication to algorithm exercises. Additionally, at times I may call on students to orchestrate conceptual constructions along with development of language builds. If you (individually speaking) get it done quite well, then extra credit will count to following quiz IF you are shaky on such following quiz. A five percent boost is all you are going to get. Another student possibly correcting the called upon student with proper etiquette and respect is also considered. Exams --> Exams will reflect assignments, quizzes and labs in latter stages. Course Outline --> --Computing. The fundamentals of how computers work, what program code is, and how to get setup for the rest of the course. --Introduction to Linux and Using the vi editor --Introduction to C Programming Variables, Expressions and Assignments Preprocessor - #include and #define --Use of functions - printf and scanf. Flow of Control – Creating Functions. Arrays, Strings and Pointers --Lexical Elements, Operators and the C System --Fundamental Data Types --Flow of Control --Functions --Arrays and Pointers --Bitwise Operators and Enumeration Types --The Preprocessor --Structures and Unions --Structures and List Processing --Input and Output C++ Programming I This course will be the introduction to object-oriented programming. However, you are not just going to throw away your procedural programmng knowledge and skills. Being aspiring (computer) scientists you will be treated as such and nothing less. Hence, course will begin to build up your exposure to object-oriented programming, along with the expectation that you can flank such decently with your C knowledge and skills. NOTE: don’t fear excessively, you have a following semester to become better and learn more. The Object-Oriented Environment --> --Understand object-oriented programming and advanced C++ concepts Be able to explain the difference between object-oriented programming and procedural programming. Be able to program using more advanced C++ features such as composition of objects, operator overloads, dynamic memory allocation, inheritance and polymorphism, file I/O, exception handling, etc. Be able to build C++ classes using appropriate encapsulation and design principles. --Improve your problem-solving skills Be able to apply object oriented or non-object-oriented techniques to solve bigger computing problems. --Programming Assignments will be graded using the following system --> Appearance 15% Logic 30% Efficiency 15% Syntax 30% Documentation 10% --Weekly Assignments & Bug Fixing Log --> Assignments will stem from various texts/literature --Quizzes --> For quizzes it’s important to understand what you’re trying to do. You will be required to develop conceptual structures/planning before providing C/C++ language builds (procedural vs object-oriented). There may be vice versa cases as well (procedural vs object-oriented). There may be cases where you must identify errors and specify corrections. Ultimate goal: to make you a good programmer --> Programming skill is not something one processes naturally It takes practice to develop the skill. To become a good programmer, you have to write a certain amount of code, make the code work, and fix a certain number of bugs. Watching other people making your code work is not going to help your program skills and is a missed opportunity. No pain, no gain Tentative 8-10 lab programming projects Features and Expectations: -Some projects concern problem solving -Being accomplished in both procedural and object-oriented environments. Chosen projects done in prerequisite and mentioned projects not done in prerequisite will have both the procedural and object-oriented environments. New projects as well. -The projects are designed for you to do on your own. You are the only one who is responsible for your own code. - Asking for help on your code is a missed opportunity and should only be used as a last resort. If you need to ask anyone to look at your code, ask the TA or myself in person. Asking your friends to look at your code is a form of cheating - Programs with any compiling error will receive a 0 grade. For an experienced programmer, software design and coding takes about 50% of the development process. The other 50% is in debugging, testing, and making the software work. If your code has compiling errors, you did not spend enough time on the project. - 6 lifelines for each person after the first project. The lifelines can be used for the TA or myself to identify bugs (compiler or run-time) in your code. Any question that can be answered without directly looking at your program do not count as a lifeline. If you are able to isolate the problem in one or a few lines of code, you can hand-write the code segment and ask questions without being counted as the lifeline. You can only use your lifelines in person. You should NOT email your code to anyone for bug fixing. Unused lifelines will be converted to extra points for the course at the end of the semester. Grade Constitution: Weekly Assignments & Bug Fixing Log Quizzes Labs Projects 3 Exams Object Oriented Programming Topics --> Note: there will be comparative or disparity structure between procedural and object-oriented. - Week 1: Structures and Classes - Week 2: Constructors and other tools - Week 3: Operator overloading, friends and references - Week 4: Arrays and classes - Week 5: Pointers and dynamic classes - Week 6: String classes - Week 7: Recursion - Week 8: Inheritance - Week 9: Polymorphism, virtual function - Week 10: Templates - Week 12 - 16 Review Sessions & Final Prerequisite: Fundamentals & Procedural Programming with C C++ Programming II Often, for “whatever social, cultural and environmental reasons”, really not much is digested nor retained from a first course in object-oriented programming. This is a second obligation course, to diffuse confusion, tension, academic belittling, character assassination, resentment, grudges, etc., etc. Towards true character building, reinforcing or patching up foundations, confidence, integrity, maturity, etc. YES, both procedural and object oriented. NOTE: more advance projects to be expected. Prerequisite: C++ Programming I Data Structures Upon successful completion of this course you will be able to design and implement Abstract Data Types using C++ to write computer programs that use classic data structures and algorithms. -You are expected to do your own work. This means you are not to work together. If there is evidence to suggest that you have shared work with someone else and/or you cannot thoroughly explain your code, you can receive a negative penalty up to the worth of the assignment. Multiple offenses may be cause to be dropped from the course. -Homework usually consists of programming problems. Programming problems are due at midnight of the due date, written assignments are due at the beginning of class of the due date. Late homework is not accepted. -There will be labs and lab assignments -There will be weekly programming projects. You will also be given instructions as to the precise names for all directories and files. If you fail to follow those directions, you will automatically lose 1/3 a letter grade for that assignment. Projects will be graded on organization, correctness, and level of professional quality. Projects are midnight of the due date. -Mini-tests that will evaluate and reinforce your understanding of recent concepts. Some prior encountered may come back to haunt (likely augmented/amended) -There will be two cumulative mid-terms and a final examination. THERE WILL BE NO MAKE-UPS. These examinations can require you to write code. Prerequisite: C++ Programming II Compiler Construction Introduction to the principles, techniques and tools of modern compiler construction. Topics include lexical analysis, parsing, and semantic analysis, translation, code generation, and run time organisation. Other topics to be discussed are abstract syntax, type checking, and register allocation. Students will design and implement a working compiler in this course. The only meaningful way to learn about compilers is to build them. We will spend a lot of time both inside and outside of class doing just that, so be sure to come to class ready to do some hands-on compiler construction. There will be lectures for sure, and some additional homework assignments, quizzes and tests, but the main focus will always be on the practical application of all that we explore to enable the construction of a working compiler. By the end of the course, students should be able to: Know the base concepts to build an entire compiler, including front-end, middle-end and back-end design. Develop a full compiler from a procedural programming language (such as C) AND object-oriented language (such as C++) down to ASM code generation (MIPS or alternatives). Be autonomous in finding algorithms and tools to assist with the development of a compiler. The main assignment for this class is to build a full compiler from C/C++ to MIPS (or alternatives). It is split into 5 sub-assignments, each of which graded independently: Parsing and type checking Translation from C/C++ AST to a lower-level intermediate representation Register allocation Translation to MIPS (or alternatives) Analysing and transforming GPU programs. NOTE: there may be issue of students plagiarizing among each other and with external sources, hence, concerning MIPS (or alternatives) there will be variations in assignments among students. Namely, they don’t just let anybody into Lockheed Martin, Northrop Grumman, IBM and so forth. Assessment --> 30% Homework assignments, quizzes. 50% Lab Development Programming 20% Final programming project (report and demonstrations) Prerequisites: Programming Language Concepts, Theoretical Computer Science Computer Systems Course serves to assist students in becoming a better programmer by teaching the basic concepts underlying all computer systems. Course serves to have students learn what really happens when your programs run, so that when things go awry (being common-place) you will have the intellectual tools to solve the problem. Why comprehend computer systems if you do all of your programming in high level languages? In most of computer science, we’re pushed to make abstractions and stay within their frameworks. Yet, any abstraction ignores effects that can become critical. Greater detail is needed for optimizing program performance, for working within the finite memory and word size constraints of computers, and for systems-level programming. Commonplace Text: Bryant, R. E. & O’Hallaron, D. R. (2003). Computer Systems: A Programmer’s Perspective, Prentice Hall Reference book on the C programming language: Kernighan, B. W. & Ritchie, D. M. (1988). The C Programming Language, Prentice Hall Participation and assessment in the course will involve five forms of activity: 1. Attending the lectures 2. Preparing for and participating in the recitations. 3. Problem Sets 4. Laboratory assignments 5. Reading the text. 6. Exams LABS: Data Lab Bomb Lab Attack Lab Cache Lab Malloc Lab Malloc Lab TSH Lab Proxy Lab Proxy Lab COURSE OUTLINE: Overview Bits, Bytes, and Integers Floating Point Machine Programmer (4 sessions) Overview Control Data Advanced Programme Optimisation Memory Hierarchy Cache Memories Cache Performance Linking Exceptional Control Flow (2 sessions) Dynamic Storage Allocation (2 sessions) System-Level I/O Virtual Memory P6/Linux Memory System Internetworking Network Programming Web Services Concurrency Synchronization (2 sessions) Prerequisite: Data Structures GUI Programming & Graphics Course serves towards actual development and implementation of GUIs for various applications (office based, general public use and scientific areas). Students will be responsible for actual development for “kindergarten GUIs”. Hence, you will not be limited to writing sketching boxes and flow charts on drawing boards and transparent glass as hype. Prerequisites are prerequisites. A tangible, practical and fluid course outline will be given that serves your best interest: engineering something meaningful, as in, “kindergarten GUIs” development, construction, implementation and debugging. Conceptual/Analytical design and segmented programming (in a chosen environment with whatever development tools) will be crucial processes on multiple occasions. As well, often, students will be asked to profile particular GUIs in public use and to engineer similar forms (will be basic level). Class Participation 4 - 5 Quizzes Major Project Pitch Presentation Major Peer Evaluation Major Project Portfolio (site accessible) Major Project Prototype Self-Assessment Quizzes will concern characterisation, classifying and code patches (analysis, editing, correcting and extending) Concerning peer evaluation, project portfolio and project prototype, site of use must be secured, geared to only those of interest. Developments must be secured against usurping by fellow students, etc. (permanent log dating, etc.) Prerequisite: Data Structures Software Design There is a level of programming maturity beyond introductory programming that comes from building larger systems and understanding how to specify them precisely, manage their complexity, and verify that they work as expected. After completing this course successfully students should be able to: -Successfully build medium-scale software projects in principled ways. -Understand the role of specifications and abstractions and how to verify that an implementation is correct, including effective testing and verification strategies and use of formal reasoning. -Analyse a software development problem and be able to design effective program structures to solve it, including appropriate modularity, separation of abstraction and implementation concerns, use of standard design patterns to solve recurring design problems, and use of standard libraries. -Use modern programming languages effectively, including understanding type systems, objects and classes, modularity, notions of identity and equality, and proper use of exceptions and assertions. -Gain experience with contemporary software tools, including integrated development environments, test frameworks, debuggers, version control, and documentation processing tools. Software Ambiance --> To gain experience we will use C++ and associate tools like an Integrated Development Environment (IDE) Unit Testing Framework Documentation Generator Subversion, Etc. Late Policy --> Deadlines will be given with each assignment. These deadlines are strict. It is exceedingly unlikely that skipping class or being late to class because of homework is in your interest. For the entire quarter, you may have four "late days". You are strongly advised to save them for emergencies. You may not use more than two for the same assignment. On group projects you may only use late days if all members of the group have them available, and all members of the group will be charged for each late day used. They must be used in 24-hour (integer) chunks. Programming projects will include specific requirements for notifying the course staff if you intend to use late days and you must follow instructions to receive them. This policy may not be the same as in your other classes. You are responsible for understanding it if you choose to submit late work. Texts: An advance C++ text. The Pragmatic Programmer by Andrew Hunt and David Thomas, Addison-Wesley, 2000. Assessment --> 55% - Homework assignments, approximately weekly 15% - Midterm exam 25% - Final exam 5% - Reading quizzes We expect to cover the following, with an emphasis on specification and design. The order these are listed is only very rough as we will revisit some topics iteratively: -Reasoning about statements, loops, functions, and data types: pre- and post-conditions, invariants, and specifications. -Testing: coverage, black- and white-box testing, test-first development, regression testing, testing framework -Debugging and assertions -More advanced C++ language issues: generics, exceptions, equality, hashing, subclasses, overloading, and overloading -More advanced tools: IDE and version control -Code Clarity: comments and documentation generator -Program Design: modularity, coupling, cohesion, and design patterns -User interfaces and event-driven programming Prerequisite: Data Structures Advanced Software Design Often, for “whatever social, cultural and environmental reasons”, really not much is digested nor retained from a first course. This is a second chance course, to diffuse confusion, tension, academic belittling, character assassination, resentment, grudges, etc., etc. Towards true character building, reinforcing or patching up foundations, confidence, integrity, maturity, etc. Prerequisite: Software Design Software Estimation and Metrics Course introduces the role of metrics and quantitative models in software development. Product metrics, process metrics, measurement models and techniques for empirical validation. Measurement and analysis: implementation of a metrics program. Measuring software size, complexity, and functionality at different stages of software development. Use of measures to predict effort and schedule required for software projects. Measures of software quality. Analyzing defect data to predict software reliability. Performance measures. Management applications for metrics. Tools that support metrics collection, analysis, summary, and presentation. Course Objectives Upon successful completion of the course students will be able to 1. Understand the guiding principles and practices for using software metrics to manage software engineering teams and projects. 2. Apply software metrics in specific software engineering environments. 3. Understand the importance of planning, documenting, and implementing a software metrics program. 4. Understand the common problems encountered in software metrics and measurement and how to avoid them in specific projects. 5. Analyze the tradeoffs when selecting quantitative measurement techniques, practices, or tools, and understand how these choices may affect the quality, cost and customer acceptance of software metrics. 6. Discuss current research trends in software metrics Primary Text --> Fenton, N. and Bieman, J. (2014). Software Metrics: A Rigorous and Practical Approach. CRC Press Supporting Text --> Laird, L. M. and Brennan, M. C. (2006). Software Measurement and Estimation: A Practical Approach, Wiley-IEEE Computer Society Pr Exams --> The exams may be “take home” exams or “in class” exams. They may be open book or closed book, but, in any case, they must be individual efforts. Discussing the questions on the exam with an individual, other than the instructor, is not permitted. Projects/Homework --> Individual assignments and projects will also be given (some projects may be group projects). Discussion and collaboration with other class members on individual assignments is permitted, and even encouraged, to the extent that said collaboration is a fair and equitable exchange of ideas. That is, one individual should not be doing all the work and sharing it with others. It is permissible to ask other students for help, but it is not permissible to copy the results of others. If several students collectively solve a problem, each should write up the results in his or her own words. Assessment --> Homework 15% Projects 30% Midterm Exam 20% Final Exam 35% Course Outline --> 1. Measurement: What is it? a. Why is it important? b. Measurement in everyday life c. Measurement in software engineering 2. Fundamentals of Measurement Theory a. Measurement: What Is It and Why Do It? (Chapter 1, pp. 1-24) b. The Basics of Measurement (Chapter 2, pp. 25-51) 3. Measurement Scales and Scale Types (Chapter 3, pp. 51-86) a. Types of Measurement Scales b. Meaningfulness in Measurement 4. Measuring Software Quality and User Satisfaction a. Software Quality Control b. Software Defect Removal c. Test-Case Coverage d. Defect Prevention e. Customer-Reported Defects f. User Satisfaction g. Surveys and interviews h. Responsiveness to customer problems i. Defect tracking 5. Software Engineering Measurement (Chapter 3, pp. 87-99) a. Product metrics b. Process metrics c. Resource metrics d. Determining what to measure e. Measuring internal product attributes f. Measuring external product attributes g. Resource measurement 6. Goal-Question-Metric Paradigm (GQM) (Chapter 3, pp. 100-132) a. Determining What to Measure b. Applying the Framework c. Software Measurement Validation 7. Quality Tools in Software Development a. Checklist b. Pareto diagram c. Histogram d. Scatter diagram e. Run chart f. Control chart g. Cause-and-effect diagram 8. Defect Removal Effectiveness 9. Software Models a. The Rayleigh Model b. The Exponential Model c. Reliability growth models d. Quality management models 10. Complexity Metrics and Models a. Halstead’s Software Science b. Cyclomatic Complexity 11. Object-Oriented Metrics 12. Conducting Quality Assessments a. In-process quality assessments b. Software project assessments 13. Using Metrics for Software Process Improvement 14. Developing a Metrics Program 15. Course Review Prerequisites: Probability & Statistics B, Data Programming with Mathematica, Software Design Programming Language Concepts Study of programming language design. The investigation and comparison of different programming language paradigms. This course will cover fundamental concepts of the majority of the thousands of programming languages: techniques for syntax and semantic analysis of programming languages and the major constructs and concepts of procedure, functional and logic languages. It aims to provide not only a unified view of (many) programming languages, but also the foundation which makes it easier for students to grasp/evaluate new languages and enables better programming (modelling) skills. This course in no way concerns “rotting out” the built up C++ skills of students from prerequisites, else instructors and administrators should be run out of town. Key Topics --> 1. Brief history of the programming languages and tradeoffs in language design 2. Formal syntax a. Regular expression and tokens b. Context free grammar and parsing 3. Semantics 4. Procedural paradigm 5. Logic programming paradigm 6. Functional programming paradigm Methods of Assessment of Learning Outcomes --> The expected learning outcomes for the course will be assessed through two non-comprehensive exams, a comprehensive final exam, homework and programming assignments, and (possibly) pop quizzes. Homework Policy --> Homework problems will be given during the semester. Homework will be graded solely on whether it’s attempted (check) or not (zero). Students should view homework as a means of identifying weaknesses in their understanding of a subject. This will hopefully lead to questions in class. Programming assignment policy --> Late work will only be accepted within 24 hours of the due date and will be graded on a 90% basis. Deadlines will not be extended due to system failures or disk crashes. Please always back up work. Code must be properly commented and submission must contain proper instructions on how the code it to be run. Test Policy --> All tests will count towards the final grade; i.e. no exam grades will be "dropped". Only students that miss an exam due to a university-approved absence are eligible to take the makeup exam. After the exams are returned to the class, if there are any questions concerning the grading of the exam, the student must return the test along with a written explanation of their concern to the instructor by the beginning of the class period after the exams are returned. Homework/Quizzes 10% Programming assignments 20% Exam1 20% Exam2 20% Final 30% Textbook: “Programming Language Pragmatics” (3rd Edition) by M. Scott, Published by Morgan Kaufmann Software: Petite Chez Scheme (Free download from www.scheme.com) Clingo (Free download from potassco.sourceforge.net) Course Topics (to span at least 15 weeks) --> Introduction to course Brief overview of different paradigms Compilation versus Interpretation Overview of how a compiler works Formal Syntax - tokens, regular expressions and parsing Formal Syntax - Context-Free Grammars, BNF Syntax Analysis Syntax Analysis - automatic encoding Overview of Syntax of “While” Language Denotational Semantics Adding semantics to syntax analysis code Compiler Optimisations Answer Set Programming Overview of a Functional Language (Scheme) Scheme Imperative Languages and changes Object Oriented Languages Prerequisite: Data Structures Malware Reverse Engineering Course covers approaches for detecting the presence of vulnerabilities in binary software, the analysis of malicious software, and explores recent research and unsolved problems in software protection and forensics. This course will cover: Static Analysis, Dynamic Analysis, Binary Program Analysis Principles, Binary Software Security, Software Forensics and Cyber Attack Response. Students will be required to study published research papers from the top-tier academic venues in computer security and cyber forensics. Course Duration --> 3 sessions per week, 2 hours per session for at least 18 weeks; such doesn’t account for lab hours Course Texts --> Sikorski, M. and Honig, A. Practical Malware Analysis: The Hands-On Guide to Dissecting Malicious Software Ligh, M. H. et al. The Art of Memory Forensics: Detecting Malware and Threats in Windows, Linux, and Mac Memory. Wiley, 2014 Ligh, M. et al. Malware Analyst’s Cookbook and DVD Resources --> CISA and NSA repositories and literature IBM, CISCO,, etc., etc., etc. repositories GHIDRA documentation and literature IDA documentation and literature Documentation and literature for other mentioned tools/software Review Computer Systems texts from prerequisite Tools & Software --> VMWare Workstation (or whatever choice) Netlab GHIDRA IDA NSA code ( https://code.nsa.gov ) OllyDBG WinDbg Binary Ninja Wireshark X-Force Course Assessment --> Attendance and Conduct (based on incentives that can possibly overwhelm other elements of course assessment) Quizzes Practical Exercises Labs Final examination Labs --> NOTE: labs will much more than the following in count addressing course topics. Some areas (mentioned and not mentioned below) can take multiple lab days to complete C/C++ Code Constructs Intro to GHIDRA or IDA (or whatever) Static Malware Reverse Engineering Basic Def Use GHIDRA Plugin or IDA (or whatever) Data Dependence GHIDRA Plugin or IDA (or whatever) Dynamic Control Dependence Course Outline --> Basic Static Analysis Netlab Intro Basic Dynamic Analysis x86 Crash Course (multiple sessions) IDA (or whatever) Binary Ninja (or whatever) C/C++ Code Constructs (multiple sessions) Analysing Malicious Windows Programs (multiple sessions) Debugging and OllyDBG or whatever (multiple sessions) Malware Behaviour (multiple sessions) Covert Malware Launching Data Encoding Malware Focused Network Signatures Practical I Debriefing Malware Classification Anti-Disassembly Anti-Debugging Anti-Virtual-Machine Techniques Packers and Unpacking Shellcode Analysis C++ Analysis Catch-up Kernel Debugging Memory Forensics I Practical 2 Debriefing Memory Forensics II PDF Documents (multiple sessions) Malicious Office Documents (multiple sessions Catch-up Practical 3 Debriefing Exam Review Prerequisites: Computer Systems, UNIX/Linux Fundamentals, Operating Systems Analysis of Algorithms Example Texts: “Algorithms” by Dasgupta, Papadimitriou & Vazirani, McGraw Hill, 2008 The following book may also be used as reference: “Introduction to Algorithms” by Cormen, Leiserson, Rivest & Stein, McGraw Hill - 2nd edition There will be three exams: two midterms and one final. The first midterm will cover the material of the first third of the course, and the second midterm will cover the second third of the course. The final exam will cover material from the entire class. Check the tentative schedule on the webpage for more information. All exams will be in-class on a date arranged and announced ahead of time in class. There will be 5 to 6 sets of homework problems. You will be informed in advance when an assignment is due. A tentative schedule will be available on the website after the first week of lectures. The homework sets consist of practice questions which are intended to assist students in mastering the course content. Many sets will also include analysis and production of the general algorithmic structure, error recognition. Code reduction problems. There will also be programming efforts. Homework should be completed by teams of students - three at most. No additional credit will be given for students that complete a homework individually. Problems not involving programming must be typed. Homework 35 points Exam 1 45 points Exam 2 45 points Exam 3 60 points Course Outline --> 1. MATHEMATICAL TOOLS: Review of mathematical background, concepts of algorithm design, complexity, asymptotics, induction, and randomization. Fibonacci numbers. Euclidean gcd algorithms. Universal hashing. 2. DIVIDE & CONQUER: Fast integer multiplication; recurrences; the master theorem; mergesort; randomized median and selection algorithms; quicksort; fast matrix multiplication. 3. SORTING: Lower bounds for comparison-based sorting; binsort and radix sort. 4. DYNAMIC PROGRAMMING: Paradigm of SPs in DAGs; longest increasing subsequence; approximate string matching; integer and (0,1) knapsack problems; chain matrix multiplication; single-pair reliable SPs, all-pairs SPs; independent sets. 5. GRAPH SEARCH: Graph classes and representations; depth first search in undirected and directed graphs; topological search; strongly connected components. Breadth first search and layered DAGs. 6. SHORTEST PATHS (SPs) IN DIGRAPHS: Single-source SPs for nonnegative edge weights; priority queues and Dijkstra; SPs in DAGs; single-source SPs for general edge weights. Maximum adjacency search. 7. GREEDY ALGORITHMS: Spanning trees and cuts, analysis of union-find and path compression; MST algorithms; randomized algorithm for global minimum cuts; approximate set cover. 8. NETWORK FLOWS: Max flow min cut theorem and integrality; fast algorithms; disjoint (s,t)- dipaths; maximum bipartite matching & minimum vertex cover. Global minimum cuts. 9. ELEMENTS OF NP-COMPLETENESS & PROBLEM REDUCTIONS 10. NP-HARD PROBLEMS. SEARCH & SELECTED APPROXIMATION ALGORITHMS Prerequisites: Discrete Structures, Numerical Analysis, Data Structures II Parallel Computing I NOTE: for computer scientists with expertise in parallel computing your value increases when your work and skills are practical, tangible and fluid with the fields of physics, chemistry, planetary sciences and biology. Competence and time with programming, else nothing can be done. It doesn’t matter how smart mathematicians believe they are; if they don’t have your skills and talent, they pretty much create “dark ages” by rent seeking with toxic and impeding “required” courses in mathematics; to them somehow real analysis, abstract algebra and number theory are essential. Course duration will be longer than conventional courses. Acclimation with frameworks or commerce such as ACM TOPC, OpenMP, CUDA, OpenCL and the MapReduce structure. Libraries also of interest and independent to priors, such as ParaMonte and Cpp-Taskflow. For each module and/or topic various there will be numerous programming activities and programming homework. Note: there will be a lab room designated for this course for various tasks. Note: there’s no intention of teaching Computer Systems, Numerical Analysis, ODE and PDE because such courses are prerequisites, and keeping such integrity is a major step in the direction of competency and professionalism. Such knowledge and skills need to pre-exist towards fully integrating into first tier technology & computation and establishing time constructiveness. You will be held accountable with all prerequisites any given day, because in the real world things aren’t customarily straightforward and “kool-aid”. Note: in this especially, note taking isn’t enough. You will be required to demonstrate the lecturing; will tie up loose ends for lack of comprehension. Note taking or vlog (without privacy infringement) along with development. Note: for all algorithms and numerical methods encountered there will be pursuit of running “parts” on different computers or processors with verification, and compare timing to standard single processor/computer usage. Formulas for predicting and measuring performance and scalability (stand and parallel). For each computing or processing task there will be a run time formula, and as well, there will be developed run time formulas for parallelized computing or parallelized processing tasks; standard and parallelized formulas should be compared. Students can be given such questions on exam and quizzes. It’s also sensible to compare execution run times with those run time formulas (standard and parallel). As well, on exams and quizzes students will be given algorithms for various methods along with kernels. Students may be asked to interpret what goes on. Students may be asked to write C++ code (and possibly Mathematica analogies as well). In other words, course is not limited to given outline. Literature Resources (apart from the first, order isn’t significant): ACM Karypis, Kumar, Grama, et al. Introduction to Parallel Computing, Addison – Wesley Pacheco, P. (2011). An Introduction to Parallel Programming. Morgan Kaufmann Schmidt, B. et al (2017). Parallel programming: Concepts and Practice. Morgan Kaufmann Trobec, R. et al. (2018). Introduction to Parallel computing: From algorithms to Programming on State-of-the-Art Platforms (Undergraduate Topics in Computer Science). Springer Solihin, Y. (2016). Fundamentals of Parallel Multicore architecture. Chapman and Hall/CRC Kale, V. (2019). Parallel Computing Architectures and APIs: IoT Big Data Stream Processing. CRC Press Kirk, D. B. and Hwu, W. W. (2016). Programming Massively Parallel Computers: A Hands-on Approach. Morgan Kaufmann Course Outline --> NOTE: for the given modules it’s necessary that active development involving computer usage as a necessity, else to the student it will all seem like just the flapping gums or horse @$%&, or some @55hole mathematician prancing about a chalk board. 1. Overview of Parallel Computing. Parallel computing concepts, essentials of parallel computer architectures and hardware, and standard programming models for parallel computers. Account setup, hands-on introduction to large-scale system environments for development and execution of parallel applications. 2. Shared Memory Parallel Programming with OpenMP. OpenMP directives, syntax, and operation; parallelize serial codes with OpenMP; control and synchronization; performance issues, scalability, and new features of OpenMP. 3. Distributed Memory Programming with the Message Passing Interface (MPI) library. MPI communication operations and data structures, syntax and features; parallelizing serial codes with MPI, performance issues, future of MPI. 4. Hybrid Computing and Advanced OpenMP. Combining MPI and OpenMP algorithms (hybrid computing) in the same code, and determining an optimal number of MPI process and OpenMP threads. Using new features in OpenMP to direct SIMD (Simultaneous Instruction, Multiple Data) execution, thread affinity, and explicit tasking, allowing user control for vectorization, efficient thread position on cores, and irregular computing (task parallel computing with dependences). Performance Analysis 5. Primitive computational science pursuits Parallel Methods Linear Systems (no manual matrix algebra perversion) Parallel Methods for ODEs Parallel Methods for PDEs NOTE: course will not tolerate any impedance with excessive trivial manual matrix implementation. The machines applied are there to do the trivial boxes dirty work. NOTE: for each computing or processing task or project/lab there will be development run time formula, and as well, there will be run time formulas for parallelized computing /processing tasks; standard and parallelized formulas should be compared. Students can be given such questions on exam and quizzes. It’s also sensible to compare execution run times with the run time formulas (standard and parallel). For each project, written description of amendments in a word processor must accompany programming; programming will have commentary as well. Questions from projects can arise on exams (with variations). NOTE: Professors/Instructors are obligated to alter problem choice for each due project assignment, to persuade against plagiarism, charlatan culture, etc. Course will be augmented by group projects sessions with CUDA, OpenMP, OpenMPI, OpenCL and 0ther libraries mentioned --> I. https://web.engr.oregonstate.edu/~mjb/cs575/projects.html Simple OpenMP experiment OpenMP: Numerical integration/quadrature (various types) For coherency in the numerical integration project to be designed manually in Mathematica and compared to project to be developed in link (C++), and as well compared to NIntgerate[f, {x, xmin, xmax}]; estimations and execution times to be compared. Can NIntgerate[f, {x, xmin, xmax}] be parallelized or is it alrally? OpenMp: Monte Carlo Simulation Similar development to prior Functional Decomposition Vectorized Array Multiplication CUDA Monte Carlo Simulation OpenCL: Array Multiplication and reduction OpenCL/OpenGL Particle system Autocorrelation using OpenMP, SIMD, and OpenCL or CUDA Parallel methods for PDE Use of manual FDM/FEM development towards computation. Begin with non-parallelized manual development (solutions and observation of execution times) both in Mathematica and C++. Then, to develop parallelized counterpart to compare with prior (estimations and execution times) both in Mathematica and C++, alongside Mathematica’s solver packages (NDSolve). Parallel Computing in Optimisation Newton’s method, Gradient Descent (also with treatment of linear systems), Momentum Method, Differential Evolution Parallel Dynamic Programming Parallel Algorithms with sequences and strings Parallel Algorithms with trees and graphs II. Shared Memory implementation. Investigation of OpenMP scheduling. Static versus dynamic; small versus large chunk size. Can be extension of (2) and/or having purpose that’s highly applicable to scientific operations. Comparative analysis for estimations and execution times between developed project and design in Mathematica if constructive and practical. III. Distributed memory implementation with various systems and architectures; pursuing complex hardware schemes. IV. False Sharing V. Simulating Compressible Flow on a Distributed Memory Machine Batten P., Tutty O., Reeve J. (1992) Simulating Compressible Flow on a Distributed Memory Machine. In: Devreese J.T., Van Camp P.E. (eds) Scientific Computing on Supercomputers III. Springer VI. Parallel Mining of Maximal Frequent Itemsets from Databases S. M. Chung and Congnan Luo, "Parallel mining of Maximal Frequent Itemsets from Databases," Proceedings. 15th IEEE International Conference on Tools with Artificial Intelligence, Sacramento, CA, USA, 2003, pp. 134-139. VII. Hybrid Computing and Advanced OpenMP Combining MPI and OpenMP algorithms (hybrid computing) in the same code, and determining an optimal number of MPI process and OpenMP threads. Using new features in OpenMP to direct SIMD (Simultaneous Instruction, Multiple Data) execution, thread affinity, and explicit tasking, allowing user control for vectorization, efficient thread position on cores, and irregular computing (task parallel computing with dependences). Performance Analysis Lab/Field Experiment --> Introduction to the use of Raspberry pi or Arduino multicore (or whatever competitor multicore options) and cluster setups (constituted by many multicore processors). Includes synopsis of architecture, logistics, memory programming/allocation, routines, performance modelling, run time modeling. Analysis of execution times by identification of appropriate controls. For dual core, multicore, stacks in function (involving Arduino, Raspberry Pi, etc., etc.), there will also be procedure towards querying and introspection for verification of competent parallel activity. Prerequisites: Data Structures II, Computer Systems, ODE, Numerical Analysis, PDE, Probability & Statistics

Parallel Computing II NOTE: for computer scientists with expertise in parallel computing your value increases when your work and skills are practical, tangible and fluid with the fields of physics, chemistry, planetary sciences and biology. Competence and time with programming, else nothing can be done. It doesn’t matter how smart mathematicians believe they are; if they don’t have your skills and talent, they pretty much create “dark ages” by rent seeking with toxic and impeding “required” courses in mathematics; to them somehow real analysis, abstract algebra, mathematical proofs, group theory, and number theory are essential for this course. Course duration will be longer than conventional courses. Acclimation with frameworks or commerce such as ACM TOPC, OpenMP, OpenMPI, CUDA, OpenCL and the MapReduce structure. Libraries also of interest and independent to priors, such as ParaMonte and Cpp-Taskflow. In similar means as Parallel Computing I, this course doesn’t concern any prerequisite matriculation passage towards Financial Engineering. I’m not betting on you remembering anything with sustainability based on one course prior. This course serves as treatment for the primitive building of algorithms towards high powered or super computation, and data management. Such modules concern having an arsenal of models and computational and programming skills to be relevant with real world problems, applicable to parallel computation. Note: for all algorithms and numerical methods encountered there will be pursuit of running “parts” on different computers or processors with verification, and compare timing to standard single processor/computer usage. Formulas for predicting and measuring performance and scalability (stand and parallel) For each computing or processing task there will be a run time formula, and as well, there will be developed run time formulas for parallelized computing or parallelized processing tasks; standard and parallelized formulas should be compared. Students can be given such questions on exam and quizzes. It’s also sensible to compare execution run times with those run time formulas (standard and parallel). As well, on exams and quizzes students will be given algorithms for various methods along with kernels. Students may be asked to interpret what goes on. Students may be asked to write C++ code (and possibly Mathematica analogies as well). In other words, course is not limited to given outline --This course is an advanced treatment of Parallel Computing I, towards retention, competency and professionalism. There will be some repetitive instruction from Parallel Computing I in some cases, but will be highly accelerated (architecture, sharing, distribution, hybrid, procedures, flow, confirmation, computational performance and run time formula with confirmation). For each module and/or topic there will be numerous programming activities and programming homework. --Reinforcing at the least quota of group projects sessions and field/labs experiment as in Parallel Computing I. However will also introduce ourselves to the Finite Volume Method to be compared with Finite Element Method. --Recital of “supercomputer” development with Arduino or Raspberry Pi (or whatever) --Will then develop a more commercial “supercomputer” with standard hardware. Note: each stack level must be multi-core. A picture idea: https://www.wikihow.com/Build-a-Supercomputer --GPU Architecture --Parallel Computing for GPU: Strengths of the GPU to see whether it’s worth the effort. Some algorithms are more easily ported to a GPU architecture than others (elaborate and engage examples). It is important to understand the strengths of the GPU to see whether it is worth the effort. Conditions. Comparing with CPUs. NOTE: throughout the course algorithms/instructions for tasks can be developed. Will concern the following environments: OpenMP Wolfram SystemModeler/Modelica Microsoft robotics developer studio TensorFlow Along with some fruitful and sustainable applications for course --> Parallel computing with numerical weather and ocean forecasting models like WRF, POM, ROMS and RCAOM. Exploration and examination of the logistics, development, and computational time required for the highly complex numerical simulations of weather and ocean models with multi core processors and variable RAM/processor speeds. What standard machines are practical? Model time step, grid resolution, number of cells in the domain, system architecture, and finally number of vertical levels and their resolutions. Gropp, W. D. and Smith, E. D. (1990). Computational Fluid Dynamics on Parallel Processors. Computers & Fluids. Volume 18, Issue 3, pages 289 – 304 Lee C.S.G. (1991). Sensor-Based Robots: Algorithms and Architectures. NATO ASI Series (Series F: Computer and Systems Sciences), vol 66. Springer, Berlin, Heidelberg. Focus on: Neural Networks, Parallel Algorithms and Control Architectures (pages 143 – 282) D. I. Jones and P. M. Entwistle, "Parallel Computation of an Algorithm in Robotic Control," 1988 International Conference on Control - CONTROL 88., Oxford, UK, 1988, pp. 438 - 443. S. Jia, X. Yin and X. Li, "Mobile Robot Parallel PF-SLAM based on OpenMP," 2012 IEEE International Conference on Robotics and Biomimetics (ROBIO), Guangzhou, 2012, pp. 508-513 P. T. M. Saito, D. F. Wolf, B. A. Mendonça, K. R. L. J. C. Branco and R. J. Sabatine, "A Parallel Approach for Mobile Robotic Self-Localization," 2009 Fourth International Conference on Computer Sciences and Convergence Information Technology, Seoul, 2009, pp. 762-767 Kasahara H. (1991) Parallel Processing of Robot Control and Simulation. In: Tzafestas S.G. (eds) Microprocessors in Robotic and Manufacturing Systems. Microprocessor-Based Systems Engineering, vol 6. Springer, Dordrecht Duncan S.H., Gordon P.L., Zaluska E.J., Edwards S.I. (1994) Parallel Processing in High Integrity Aircraft Engine Control. In: Gentzsch W., Harms U. (eds) High-Performance Computing and Networking. HPCN-Europe 1994. Lecture Notes in Computer Science, vol 796. Springer, Berlin, Heidelberg Y. Kanehagi, D. Umeda, A. Hayashi, K. Kimura and H. Kasahara, "Parallelization of Automotive Engine Control Software on Embedded Multi-core Processor using OSCAR Compiler," 2013 IEEE COOL Chips XVI, Yokohama, 2013, pp. 1-3. Note: various examples applications can arise on exams and/or quizzes where students must develop or complete or correct algorithms. Prerequisites: Parallel Computing I

Parallel Computing III (syllabus description) NOTE: for computer scientists with expertise in parallel computing your value increases when your work and skills are practical, tangible and fluid with the fields of physics, chemistry, planetary sciences and biology. Competence and time with programming, else nothing can be done. It doesn’t matter how smart mathematicians believe they are; if they don’t have your skills and talent, they pretty much create “dark ages” by rent seeking with toxic and impeding “required” courses in mathematics; to them somehow real analysis, abstract algebra and number theory are essential. Course duration will be longer than conventional courses. Acclimation with frameworks or commerce such as ACM TOPC, OpenMP, OpenMPI, CUDA, OpenCL and the MapReduce structure. Libraries also of interest and independent to priors, such as ParaMonte and Cpp-Taskflow. In similar means as Parallel Computing I, this course doesn’t concern any prerequisite matriculation passage towards Financial Engineering. This course serves as treatment for the primitive building of algorithms towards high powered or super computation, and data management. Such modules concern having an arsenal of models and computational skills to be relevant with real world problems, applicable to parallel computation. This course like Parallel Computing II concerns algorithms for computation, however, catering towards probabilistic alternatives to deterministic algorithms. Logistics and integration will be similar to Parallel Computing II, however, monte carlo building will be emphasized wherever and whenever practical, then compared to deterministic computation. For each module and/or topic various programming activities, programming homework and/or programming projects implemented. NOTE: for all algorithms and numerical methods encountered there will be pursuit of running “parts” on different computers or processors with verification, and compare timing to standard single processor/computer usage. Formulas for predicting and measuring performance and scalability (stand and parallel) For each computing or processing task there will be a run time formula, and as well, there will be developed run time formulas for parallelized computing or parallelized processing tasks; standard and parallelized formulas should be compared. Students can be given such questions on exam and quizzes. It’s also sensible to compare execution run times with those run time formulas (standard and parallel). NOTE: verification of shared memory, distributed memory and (false sharing, or lacking of) is mandatory. As well, on exams and quizzes students will be given algorithms for various monte carlo and kernels. Students may be asked to interpret what goes on. Students may be asked to write C++ code (and possibly Mathematica analogies as well). In other words, course is not limited to given outline. Reinforcing at the least quota of group activities sessions as in Parallel Computing II, however, suiting topics of syllabus. NOTE: on exams, apart from mathematical comprehension and computational theory, students will often be provided applications problems with conceptual groundwork or designs where students must build parallel deterministic and stochastic algorithms to meet desired goals. There may also be trick questions with algorithms (what they really are and/or if they make sense at all, etc.). Syllabus: 1. Monte Carlo method as any process that consumes random numbers Involves programming activities from theory --Each calculation as a numerical experiment --Sources of Errors must be controllable/isolatable --Reproducibility --High dimensionality is favourable, breaks the “curse of dimensionality" --Appropriate where high accuracy is not necessary --Algorithms are Naturally Parallel (empirical verification) 2. Stochastic generation There will be analytical development and actual algorithm building and implementation --Simulating random variables of experiments --Random number generation URNG --> features and general framework NRNG --> features, transformations to a stream of iid U[0,1] random variables, and framework Why much emphasis between URNG and NRNG? Desirable properties of random number generators: Statistical uniformity and unpredictability Period Length Efficiency Theoretical Support Repeatability, portability, jumping ahead, ease of implementation Why much emphasis on RNG? --Reviewing simulation of random experiments and the Inversion method --Acceptance rejection method and ratio-of--uniforms 3. Review of the features of numerical integration/quadrature --Main idea --Advantage: good convergence rate --Not useful for high dimensions - curse of dimensionality 4. Monte Carlo and Quasi Monte Carlo Integration There will be analytical development and actual algorithm building and implementation --MC: properties such as use of URVs, SLLN, CLT (in regards to error bound) --QMC: instead of r.v. will use deterministic variates that fill [0, 1]^d evenly --Comparison between QMC and MC points generation in [0, 1]^2 --Comparing convergence rates between QMC and M for dimensionality --Bounds on the QMC error --The consensus in the literature seems to be: Use numerical integration for small d Quasi-MC useful for medium d Use Monte Carlo integration for large d --Hit-or-Miss Monte Carlo (HMMC) --Crude (or Mean-value) Monte Carlo (CMC) --Comparison between Hit-or-Miss approach and Crude Monte Carlo by analysis of unbiasedness and chosen variance reduction methods. --After such sequential activities, students must determine whether HMMC and CMC are parallel, explain why, and what can be done to verify such; if any isn’t parallel, students must make them into such and exhibit how. ---Hastings-Metropolis (HM) and Importance Sampling for (single and multivariate) integration problems NOTE: matrices with erroneous or incompetent probabilities in a box is way off point with numerical integration for our purposes. Algorithm comprehension and development. You are not here to write fancy notations and perverted gunk; if I ask you to do something computationally with HM, I expect it punctually. Additionally, other methods besides HM will be assignment based, where intentions and analytical algorithm description will be given; students will be responsible for comprehension and programming development. ---Borcherds, P. (2000). Importance Sampling: An Illustrative Introduction. European Journal of Physics, 21(5), 405–411 How can one make such practical with coding development? ---In other cases, such as when you want to evaluate E(X) where you can’t even generate from the distribution of X, importance sampling is necessary. The final, and most crucial, situation where importance sampling is useful is when you want to generate from a density you only know up to a multiplicative constant. Afterwards, pursue computational development. Importance Sampling for variance reduction in multivariate integrals. Will importance sampling be highly helpful with multivariate integral estimation post-HM concerning variance reduction, or are other methods prior better? 5. Comparing Integration Algorithms --The operation NIntgerate[f, {x, xmin, xmax}] --The deterministic manually developed computation via quadrature choices in C++ language --The deterministic manually developed Mathematica computation --The manually developed monte carlo computation (C++) --The manually developed Mathematica monte carlo computation --NIntegrate[f, {x, a, b}, Method--> “MonteCarlo”] --Monte Carlo algorithms are eminently parallelizable, in particular when various parts can be run independently. This allows the parts to be run on different computers and/or processors, therefore significantly reducing the computation time --> For each of the prior 6 tasks pursue means hypothesize run time formula models and compare with the run time data. As well, to pursue means of determining whether each of the 6 tasks run parts of computation on different computers or processors with the verification. If any isn’t parallelized based on data, pursue means of making them parallelized with evidence. NOTE: there may be trials with various integrands. NOTE: may ask for multivariate extensions as well. 6. Probabilistic treatment of PDE All algorithms will be developed in both C++ and Mathematica There will be actual algorithm building and implementation --Elliptic PDE as BVP (identify specific applications) A. The Weiner measure, Gaussian based. Sample paths are brownian motion. Weiner integral representation as an expectation being the solution to the Laplace equation (with Dirichlet problem); proof by exhibiting that such a solution is a function on the boundary, and has the mean value property. Interpretation through Brownian motion. Parallel? How so? Make it to be if not. Interest in identifying the analytical formulas for computation power and execution times when comparing plain non-parallelized numerical methods techniques, parallelized numerical techniques and “parallelized” numerical techniques. Interest in identifying the measures of computation power and execution times when comparing plain numerical methods techniques, parallelized numerical techniques and “parallelized” numerical techniques. B. Can extend Wiener Integrals to vast class of IBVPs through the connection between elliptic operators, SDEs, and the Feynman-Kac Formula. Computational implementation of stochastic algorithm. Compare with non-paralellized methods, parallelized counterparts, namely both deterministic and stochastic (estimation and execution time). --Parabolic PDE as BVP (identify specific applications with special boundary conditions). Analogous treatment to elliptic (A-B) in prior. --Mastrangelo V., Gassilloud D., Heidrich D., Simon F. (1991) Stochastic Modelisation and Parallel Computing. In: Heidrich D., Grossetie J.C. (eds) Computing with T.Node Parallel Architecture. Eurocourses: Computer and Information Science, vol 3. Springer, Dordrecht. --Walk on Spheres (WOS) and Green’s Function First Passage (GFFP) Algorithms Analogous treatment to elliptic (A-B) in prior. --Hyperbolic problems model distortion free information propagation which is fundamentally nonrandom (hence, will not be given monte carlo treatment). --Reaction-Diffusion and Advection-Diffusion (treatment in the same manner as with elliptic and parabolic PDE). Can such be treated with WOS and GFFP? If so, develop parallelized forms. --Random Vortex Method for Navier Stokes Equations (compare only with finite difference or finite element methods) Chien-Cheng Chang (1988). Random Vortex methods for the Navier-Stokes equations, Journal of Computational Physics, Volume 76, Issue 2, Pages 281-300 Stephen Roberts (1985). Accuracy of the Random Vortex Method for a Problem with Non-Smooth Initial Conditions, Journal of Computational Physics, Volume 58, Issue 1, Pages 29-43 Oppenheim, A. (2008). Random Vortex Method. In: Dynamics of Combustion Systems. Springer, Berlin, Heidelberg. 7. Parallel Algorithms for Large-Scale Stochastic Programming There will be analytical development and actual algorithm building and implementation Vladimirou H., Zenios S.A. (1997) Parallel Algorithms for Large-Scale Stochastic Programming. In: Migdalas A., Pardalos P.M., Storøy S. (eds) Parallel Computing in Optimization. Applied Optimization, vol 7. Springer, Boston, MA. 8. Stochastic Approximation Algorithms There will be analytical development and actual algorithm building and implementation H. J. Kushner & G Yin (1987). Stochastic Approximation Algorithms for Parallel and Distributed Processing, Stochastics, 22:3-4, 219-250 9. From Deterministic to Stochastic Gradient Descent There will be analytical development and actual algorithm building and implementation --Deterministic --Stochastic Gradient Qian, X., et al (2019). SGD with Arbitrary Sampling: General Analysis and Improved Rates. ICML Gower, R. et al (2019). SGD: General Analysis and Improved Rates, arXiv:1901. 09401v3 Zhang, Tong (2004). "Solving Large Scale Linear Prediction Problems Using Stochastic Gradient Descent Algorithms". Proceedings of the 21st International Conference on Machine Learning (ICML'04): 116. E.A. Johnson, C. Proppe, B.F. Spencer, L.A. Bergman, G.S. Székely, G.I. Schuëller, Parallel Processing in Computational Stochastic Dynamics, Probabilistic Engineering Mechanics, Volume 18, Issue 1, 2003, Pages 37-60 10. Further Stochastic Optimisation There will be analytical development and actual algorithm building and implementation O. V. Abramov and Y. V. Katueva, "Application of Parallel Computing Techniques for Stochastic Optimization Problems," 2004 5th Asian Control Conference (IEEE Cat. No.04EX904), Melbourne, Victoria, Australia, 2004, pp. 435-441 Vol.1. 11. Computational Stochastic Dynamics There will be analytical development and actual algorithm building and implementation E.A. Johnson, C. Proppe, B.F. Spencer, L.A. Bergman, G.S. Székely, G.I. Schuëller, Parallel Processing in Computational Stochastic Dynamics, Probabilistic Engineering Mechanics, Volume 18, Issue 1, 2003, Pages 37-60 12. Field Applications There will be analytical development and actual algorithm building and implementation The following journal articles examples are recognised with monte carlo employment, but students must recognised if any parallelization is applied, and means to do such if not the case. Algorithms/instructions may not be given explicitly in journal articles, hence such may need to be developed; it may be best to develop single processing monte carlo, then to proceed with parallelization, say from primitive establishment gaining certainty with where and how parallelization can be employed. -Physical Sciences and Engineering: Dongarra, J., Madsen, K. and Wasniewski, J. (1995). Applied Parallel Computing Computations in Physics, Chemistry and Engineering Science. Second International Workshop , PARA’ 95 Lyngby, Denmark, August 21 – 24 , 1995 Proceedings -Environmental Models: Jasper A. Vrugt et al. Application of Parallel Computing to Stochastic Parameter Estimation in Environmental Models, Computers & Geosciences, Volume 32, Issue 8, 2006, Pages 1139-1155 -Groundwater: Leyva-Suarez, E., Herrera, G., S., de la Cruz, L., M. 2015, A Parallel Computing Strategy for Monte Carlo Simulation Using Groundwater Models, Geofisica Internacional, (54-3) 245-254 Dong Y, Li G, Xu H. Distributed Parallel Computing in Stochastic Modelling of Groundwater Systems. Ground Water. 2013 Mar;51(2):293-7 -Engineering: Batteh, J., Tiller, M. and Goodman, A. Monte Carlo Simulations for Evaluating Engine NVH Robustness. 4th International Modelica Conference, March 7-8, 2005, Hamburg University of Technology, Hamburg-Harburg, Germany Batteh, John & Tiller, Michael. (2005). Analytic Evaluation of Engine NVH Robustness Due to Manufacturing Variations. 429-437. ASME 2005 Internal Combustion Engine Division Spring Technical Conference Robinette, D. and Wehrwein, D., "Automatic Transmission Gear Ratio Optimization and Monte Carlo Simulation of Fuel Consumption with Parasitic Loss Uncertainty," SAE Int. J. Commer. Veh. 8(1):45-62, 2015 13. Parallel Monte Carlo for GPU There will be analytical development and actual algorithm building and implementation Develop stochastic counterparts to GPU development in prerequisite. There may be correction/completion questions on exams and/or quizzes. Some applications guides --> Schram, R. D. (2013). Reaction-Diffusion Monte Carlo Model Simulations on the GPU. Journal of Computational Physics, volume 241, pages 95 - 103 Jia, X., Ziegenhein, P., & Jiang, S. B. (2014). GPU-based high-performance computing for radiation therapy. Physics in medicine and biology, 59(4), R151 – R182 Liang, Y., Xing, X., & Li, Y. (2017). A GPU-based large-scale Monte Carlo simulation method for systems with long-range interactions. Journal of Computational Physics, 338, 252. Hamilton, S., Slattery, S., & Evans, T. (2018). Multigroup Monte Carlo on GPUs: Comparison of history- and event-based algorithms. Annals of Nuclear Energy, 113(C), 506 - 518. Prerequisites: Parallel Computing II, Probability & Statistics B Data Compression (syllabus description): Open to EE (Networks) majors as well. Course is an elective based on petition from students who are appropriately qualified with prerequisites. Students are expected to comprehend existing C/C++ programs and modify the code for various goals. The students may also be required to write small programs from scratch. Provided sample code comes with “makefiles” for compilation under a Unix environment. Either familiarity with basic Unix commends or the ability to covert the codes to a windows project is required. multimedia compression - with an emphasis on compressing and transmitting multimedia objects over the Web. Lossless compression methods include statistical coding (e.g., Huffman, Shannon-Fano, facsimile, arithmetic, MNP5/7) and dictionary coding (e.g., LZW). Lossy compression schemes include scalar, vector, differential, subband and transform methods for images and video (e.g., JPEG, wavelets, MPEG, H.261), and for speech and audio encoding (e.g., PCM, DPCM, ADPCM, GSM, MP3, MP4, compact discs). Course will be applications intensive and projects intensive. -Additionally there will be homework tasks (15%) -Projects (20%) To be pursued will have multiple exercises varying in difficulty and formats. Note: included in projects will make use of data, data sets when appropriate and optimally practical. A respective student can be given unique data task towards a respect project. Data can be the standard of a respective ambiance, universal standard, industry based, scientific, etc., etc. Students will not use compression software unless designated to do so --> Project 1: Using Data Compression Software Project 2: Lossless Compression I (Huffman Coder, LZW Coder, LZSS Coder) Project 3: Lossless Compression II (QM Coder) and Vector Quantization Project 4: Run Length Encoding/Decoding Project 5: Burrows Wheeler Project 6: Image and Video Compression Project 7: Lossy Differential (Delta) Encoding/Decoding Project 8: Comparing coding and algorithms with data compression software on chosen media. Students will be assigned different types of files and media of various sizes. They will independently pursue the most efficient coding and algorithms towards applying to such files and media. Then to independently identify different data compression software towards applying to such files and media along with use of different data compression software. Compare performance and quality from developed coding and algorithms with data compression software. -Advance Group Projects (25%) NOTE: will not necessarily follow the given order. The prior 8 basic projects may be too trivial to apply robust and versatile compression with real world technologies, systems and demand. Tangible and abrasive immersion is inevitable. Group projects will be given at times where enough enough lecture material is treated. Classification of the types of compressions and algorithms will be emphasized. Will make use of different data sets of data for each project. 1. Aubert, P., Vuillaume, T., Maurin, G. et al. Polynomial Data Compression for Large-Scale Physics Experiments. Comput Softw Big Sci 2, 6 (2018). 2. Qin Jiancheng, Lu Yiqin, Zhong Yu, "Block-Split Array Coding Algorithm for Long-Stream Data Compression", Journal of Sensors, vol. 2020, Article ID 5726527, 22 pages, 2020. Note: for whatever security concerns, if software “ComZip” isn’t desired, substitute with other 3. M. C. Sorkun and C. Özbey, "Compression Experiments on Term-Document Index," 2017 International Conference on Computer Science and Engineering (UBMK), Antalya, 2017, pp. 435-439 4. Damme, P., Habich, D., Hildebrandt, J., & Lehner, W. (2017). Lightweight Data Compression Algorithms: An Experimental Survey (Experiments and Analyses). EDBT. 5. Heo, Gwang & Kim, Chunggil & Jeon, Seunggon & Jeon, Joon. (2018). An Experimental Study of a Data Compression Technology-Based Intelligent Data Acquisition (IDAQ) System for Structural Health Monitoring of a Long-Span Bridge. Applied Sciences. 8. 361 6. Buchsbaum, A. L. et al (2000). Engineering the Compression of Massive Tables: An Experimental Approach. Proc. 11th ACM-SIAM Symp. on Discrete Algorithms, San Francisco, CA 7. Lonardi, S., Szpankowski, W. and Ward, M. D. Error Resilient LZ’77 Data Compression: Algorithms, Analysis, and Experiments. IEEE Transactions on Information Theory, Volume 53, Number 5, May 2007, pp 1799 – 1813 8. Damme, P., Habich, D., Hildebrandt, J. and Lehner, W. Lightweight Data Compression Algorithms: An Experimental Survey. Experiments and Analyses. Open Proceedings, Series ISSN: 2367-2005. pp 72 – 83 Midterm Exam (20%) Final Exam (20%) Texts: must provide thorough and clear treatment of the detailed topics with emphasis on real and practical applications towards hands on activities. Course will make use of data sets, and how to conjure data sets (most practical and industries based). Course will make use of some data compression software, but will not be incarcerated to them; concerns mainly the extent of use and practicality. Programming will be priority over conventional software towards proper foundation, dexterity and growth. Course is based on the C/C++ environment, however, the ability to compare and contrast with development in premier computational environments is highly constructive, and means to evaluate the level of worth in your labour. The following text is NOT the official book for this course, rather, means of compare/contrast for your level of labour: Salomon, D. A Guide to Data Compression Methods. Springer. Such a text text above may be applying a Mathematica version that’s much more older, however, structure overall should be parallel, or in most cases exact. Course Outline --> I. Introduction ( 1/2 day or 1 day) II. Information Theory of the (English) Language III. Conditional Entropy and Markov Chains Will we actually use Markov Chains in data compression algorithmic structures? IV. Probability Coding (at least 9 sessions) Prefix Codes (and relationship to Entropy) Huffmann Codes Arithmetic Coding V. Applications of Probability Coding (3-5 sessions) Run-length Coding Move-To-Front Coding Residual Coding Context Coding (JBIG, PPM) VI. Dictionary Techniques and LZW Algorithms (at least 3 sessions) VII. Burrows Wheeler Algorithm (1 session) VIII. Lossy Compression Techniques (6-8 sessions) Scalar Quantization and vector Quantization Transform Coding (robust and practical) rough outline such as https://web.stanford.edu/class/ee398a/handouts/lectures/07-TransformCoding.pdf but must include use of Fourier, Bessel, etc. Note: matrices are primarily to be computed via computational tool such as Mathematica. IX. Case Studies (3-5 sessions): JPEG and MPEG. Will include past coding and algorithms, compression steps, quantization tables, luminance planes, zig-zag scanning of blocks, MPEG frames and encoding, etc. MPEG in Direct Broad Satellites, Cable Television, Media Vaults, Real Time Encoding. X. Other Lossy Transform Codes (3-5 sessions) Wavelength Compression Fractal Compression Model-Based Compression XI. Differential Encoding (at least 2 sessions) XII. Subband coding, Haar Transform (at least 2 sessions) XIII. Future and Innovation (time permitting). Concerns progression or advancement in standardization. Potential future standards and revolutions. Prerequisites: Discrete Structures, Data Structures II, UNIX/Linux Fundamentals, Numerical Analysis, Probability & Statistics B, Confidence with Browsers.

Computer Networks Computer network architectures and their application to industry needs. Major topics include vocabulary, hardware, design concepts, current issues, trends, hardware, multi-user operating systems, network protocols, local and wide area networks, intranet and internet communications, analog and digital data transmissions. Textbooks: Internetworking with TCP/IP Volume 1: Principles, Protocols, and Architecture, Fifth Edition, Douglas Comer, 2006, Pearson Prentice Hall. Software of interest for Computer Networks -->: SGAMToolbox, RAMI 4.0 Toolbox https://code.nsa.gov Network Simulators --> Marionnet network simulator REAL network simulator OMNeT++ with INET framework ns-3 NOTE: software mentioned are not replacement for development of programming skills. Course Objectives --> After successful completion of this course, students will be able to: Use advanced networking to plan and deploy internetworks. Provide an understanding of sub-networks Work with the Internetworking concepts: Implement and manage the functions of the Internet protocol suite: TCP/IP Develop IP address based sub-networking Implement IP Routing and Routing Protocols Debug transport level services Manipulate and troubleshoot application services: E-mail, FTP, Rlogin etc. Gain hands-on experience with network hardware Routers (emphasis) Switches Gain an understanding of the widely used Unix servers across the Internet Troubleshoot end to end connectivity problems Diagnose packets, frames and segments traversing a network. Gain hands-on experience with real-world Cisco routers and switches Describe the various Cisco IOS software features Implement Basic IOS Configuration Describe Remote Management Develop and implement network designs Course Grade constitution --> Labs Exam 1 Exam 2 Final Exam Topics --> -Networks and Inter-networks -The OSI Model -Physical Layer (along with 2 lab hours) -Data Link Layer (along with 2 lab hours) -Transport Layer and Session Layer (along with 2 lab hours) -Presentation and Application Layer (along with 2 lab hours) -Network Layer (along with 4 lab hours) -IP Addressing and Sub-netting: IPv4, DHCP,IPv6 (along with 4 lab hours) -Wide Area Network Design -Data Path Determination (along with 2 lab hours) -Basic Router Operations and Configuration (along with 4 lab hours) -IP Routing: RIP, OSPF, BGP (along with 6 lab hours) -Network Security: NAT, Proxy Servers, Firewalls (along with 2 lab hours) Laboratory Projects --> Students create a small local area network and perform packet analysis on data packets at the data-link, network, and transport layers. A second project requires capture and analysis of data packets in the application layer and social implications “sniffing” are examined. Students also create a three node wide-area network and implement data routing using interior routing protocols (static, distance-vector, shortest path first) and exterior routing protocols (BGP). A second aspect of this project is the implementation of NAT and Access-Control Lists (including extended and “secure”). The three node network is expanded to encompass 12 modes and issued of remote management and cooperation among “foreign” domains is examined. Social and Ethical Issues --> The topics discussed in the Application Layer in the OSI model include data (packet) capture and analysis. The ethical implications of capturing data packets in the application layer are discussed and examined. The social and ethical implications of Denial of Service (DOS) attacks and defences and intrusion detection are discussed in the Network Security topics. Students are given an essay question on the midterm and responses are graded. Three hours of class time is spent on this topic. Theoretical Content --> Theoretical content includes: Introduction to computer networks, their hardware and software. [1 week] Connection oriented and connectionless services. [0.5 week] Circuit switching and packet switching. [0.5 week] OSI and TCP/IP reference models. [3.5 weeks] Discussion of physical, data-link layers of the OSI Model Discussion of network layer of the OSI Model Discussion of the transport, and session layers of the OSI Model Discussion of the presentation and application layer of the OSI Model. Transmission media and multiplexing. [1 week] Data link layer protocols: multiple access protocols and LANs using CSMA/CD [1 week] IEEE standards 802.2, 802.3, 802.4, 802.5, 802.6. [0.5 week] Network layer [4 weeks] LAN and WAN design issues. IP Address allocation and subnetting/supernetting issues Routing Algorithms: Distance Vector, Shortest Path First, link state, hierarchical, broadcast, and multicast routing Problem Analysis --> In assignments and exams, students are presented with network data problems requiring them to analyse the success or failure of arp cache generation, ip address subnetting, tcpdump analysis, name service resolution problems, classful routing problems (RIPv1), spf algorithm implementation issues, access control via NAT and access-lists, and network design problems. Solution Design --> This course requires students to implement a three node wide-are network using (a) static routing, (b) dynamic routing with distance-vector algorithms, (c) dynamic routing using shortest path first algorithms (Dijkstra), and (c) access to networks using Network Address Translation access-lists. problems. Prerequisite: Computer Systems Advanced Computer Networks NOTE: Course at times will encounter Unix and Linux environments There will be three quizzes (conducted in class), together accounting for 10% of the total grade. Quizzes will be closed notes and closed book. However, one handwritten A4 sheet will be permitted. Calculators will not be required. Examinations (at least three) will be closed notes and closed book. You will be allowed to bring in an A4-sized handwritten sheet. No calculators will be required. Programming assignments will form a significant component of the course, and will help you apply the classroom concepts in practice. There will be three programming assignments (PA 1-3), each accounting for at least 10% of your grade. The programming assignments must be coded and submitted in groups of two. Evaluation will consist of a code + report submission on the due date, and a written "viva" (in the form of a written test based on the assignment). Any copying of code (without disclosure) will result in an F grade. Like prerequisite course there will be similar but more advanced lab activities, but not as many. Textbooks: TBA Software of interest for Computer Networks -->: SGAMToolbox, RAMI 4.0 Toolbox https://code.nsa.gov Network Simulators --> Marionnet network simulator REAL network simulator OMNeT++ with INET framework ns-3 NOTE: software mentioned are not replacement for development of programming skills. Topics --> Internet architecture and performance modelling Applications: architectures and examples Transport protocols, TCP mechanics, congestion control, resource allocation Internet routing, routing algorithms, BGP, advanced routing concepts, router architectures Link layer: switching, multiple access, MPLS Advanced topics: network virtualization, software defined networking Prerequisite: Computer Networks Principles of Network Security Course introduces the principles of computer security. Information is an important strategic and operational corporate asset. Today computers and computer networks are increasingly being used for storing and retrieving information. Some of information may be of a sensitive nature. Consequently, they need to have adequate security measures that can safeguard sensitive information. In this course, we will begin by investigating some of the security measures that can be employed to safeguard information. For the most part we will look into the theory that goes into designing these measures rather than studying security tools and techniques. This is because there are too many of those tools out there and they are changing frequently. The course examines how system designs, network protocols, and software engineering practices can result in vulnerabilities. The course explores how to better design and implement future systems in order to mitigate vulnerabilities. In addition, the course explores how to detect and mitigate vulnerabilities in existing systems. Understanding security requires understanding system concepts such as memory and network access models, stacks, and buffers. Students are expected to have broad understanding of different aspects of how computer systems work. It is strongly recommended that the student have a working knowledge in computer networks. The student should also feel comfortable with algorithmic concepts and modular arithmetic. If they do not, they are strongly encouraged to refresh their skills in these areas. NOTE: experimentation involving programming exercises in C/C++ and scripting languages is one of the activities of the course. Students should be ready with these skills. NOTE: implementations and analysis following in abundance are expected. By the end of the course, students should be able to: -Understand the fundamental principles of access control models and techniques, authentication and secure system design -Have a strong understanding of different cryptographic protocols and techniques and be able to use them -Apply methods for authentication, access control, intrusion detection and prevention -Identify and mitigate software security vulnerabilities in existing systems. Following is tentative schedule for this class. Note that as the term progresses we are most likely to digress from this schedule quite a bit. However, dates for term paper/project and exams are fixed and will not change. Two recommended references are --> Charles P. Pfleeger, "Security in Computing", Prentice Hall. William Stallings, "Cryptography and Network Security: Principles and Practice.", Prentice-Hall. Simulator --> CyberCIEGE Applied throughout course development Environment Tools --> Virtual Machine Software: Install VirtualBox (version 4.2.6 or newer). This is a free software. Ubuntu 16.04 Virtual Machine Image. All the Linux labs use this image. Will have a user manual. Resources --> NIST National Vulnerability Database CISA – US-CERT https://code.nsa.gov COURSE LABS --> Environmental Variable and Set-UID Lab Buffer Overflow Vulnerable Lab Race Condition Vulnerability Lab Web Basics CSRF Attack Lab SQL Injection Lab Cross-Site Scripting Attack Lab Linux Firewall Lab DNS Pharming Attack Lab Attacks on TCP/IP Protocols Android Repackaging Attack Lab Android Rooting Lab COURSE TOPICS --> Week 1 - Introduction, security concepts, threats, risk modeling and security services Week 2 - Access control models: Discretionary and mandatory access control Week 3 - Access control models: Covert channels and Chinese Wall Week 4 - Access control models: Clark-Wilson, RBAC, ABAC Week 5 - Introduction to cryptography Week 6 - Secret key cryptosystems Week 7 - Key escrow Week 8 - Modular Arithmetic and Public key cryptosystems Week 8 - Public key cryptosystems Week 9 - Diffie-Hellman, RSA, El-Gammal Week 10 - Pairing based cryptosystems, IBE and attribute-based encryption Week 10 - Message digests, Merkle hashes, digital signatures Week 11 - Identification and authentication, Passwords, Biometrics Week 11 - One-time passwords and challenge response schemes, Kerberos Week 12 - Kerberos, SSL, SSH Week 13 - Wireless Security Week 14- Privacy Prerequisites: Discrete Structures, Analysis of Algorithms, Advance Computer Networks with C++ Applied Cryptography Why learn cryptography? Our concerns are privacy and security with communication, data and databases. Where do you find functions for cryptography? Do you or can you build your own? What really matters when it comes to such areas? What will be useful when it comes to implementing tasks with an actual computers, networks, data and so forth? Honestly, you may have all the mathematics chalkboard finesse and jungle rot advantage, but if you can’t programme or code your value isn’t much; the often “mechanical engineer versus the mechanic dilemma”. Prerequisites are prerequisites. Course Assessment --> Homework Quizzes Labs Additional Implementation Assignments Midterm Final Project Extra Credit (may or may not be given) Texts in Unison --> Stallings, W. (2016). Cryptography and Network Security: Principles and Practice. Pearson Schneier, B. (2015). Applied Cryptography: Protocols, Algorithms and Source Code in C Wong, D. (2021). Real-World Cryptography. Manning Menezes, Oorschot, & Vanstone. (1997). The Handbook of Applied Cryptography. CRC Press Resource and Tools --> National Institute of Standards and Technology publications YouTube Videos Tools --> Mathematica Environment and Wolfram Documentation or Help Centre Botan Mhash NaCl Crypto++ OpenSSL Homework --> Component A: stereotypical assignments from texts with some of lecturer’s imagination. Component B: small programming assignments -> Manipulating bits Visual cryptography Cryptoanalysis DES AES Primes Randomness tests Quizzes --> Based on lecturing and homework. Policy on using notes will vary from one quiz to the next. Labs --> Labs will have multiple features Fast review of recent lecturing Some mathematical modelling classification and recognition of applied operations (with some specification) Mathematical structuring of psuedo/procedural code Recognizing pseudo code and describe operations Building pseudo/procedural code based on descriptions Going from C to C++. Will have implementation Disparities between C/C++ libraries use and open source software implementation. Will have implementation Implementing Ciphers and Encryptions List and discuss cryptographic vulnerabilities including key management, randomness, and speed Generate symmetric keys and asymmetric key pairs Create an unsecured communications channel between two computers Create communications channel between computers Communicate securely through an unsecured communications channel Database Security & Cryptography Tasks with actual, networks, data and databases Cryptography tasks for network, data and databases Hardening tasks upon networks, data and databases Additional Implementation Assignments (likely being part of labs when appropriate) --> (A) Conventional exercises with robustness Students will be responsible for writing code for elementary or common ciphers, where code exhibiting operation on “units” with related cipher text; assignments will specify various operations to be completed. Cipher Examples: substitution, transposition, square (being only three); students also design and code counter to retrieve original info or data, and gaining acquaintances with popular or public ciphers. (B) Cryptanalysis (frequency analysis, Index of coincidence, Kasiski examination) Concerns methods for applying or taking advantage of such; also, to stress actual activities with algorithms, code, towards data, files, etc. Gaining acquaintances with popular or public cryptanalysis ciphers, methods, etc. (C) Steganography (digital). Concerns methods for applying or taking advantage of such; also, to stress actual activities with algorithms, code, towards data, files, etc. However, additional software tools and applications may be needed in some cases. Gaining acquaintances with popular or public steganography ciphers, methods, etc: Concealing messages within the lowest bits of noisy images or sound files or video files. Concealing data within encrypted data or within random data. The message to conceal is encrypted, then used to overwrite part of a much larger block of encrypted data or a block of random data (an unbreakable cipher like the one-time pad generates ciphertexts that look perfectly random without the private key). Mimic functions Pictures embedded in video material (optionally played at slower or faster speed). Injecting imperceptible delays to packets sent over the network from the keyboard; delays in keypresses in some applications (Telnet or remote desktop software) can mean a delay in packets, and the delays in the packets can be used to encode data. Content-Aware steganography hides information in the semantics a human user assigns to a datagram. These systems offer security against a nonhuman adversary/warden. (D) Hash functions development; students also design and code counter to retrieve original info or data, and gaining acquaintances with popular or public hash functions. (E) Encryption/decryption programmes for various files and passwords. It’s crucial that students use test files, etc. that are not important (say, constructed “crash dummies”). Creating encryption/decryption programmes in C++. File encrypting and decrypting programme. For file encrypting and decrypting programme such will developed by students, with only heuristics assistance from professor. Will make use of XOR, RSA, and importing (making use of) AES, Serpent, Blowfish and DES. Directed towards different strings, files, pictures, music, video and other types. Students will be tasked with applying multiple algorithms/ciphers for each assigned data (string, file, picture, music, video, etc.). One example format: (i) Import modules “Import <os, random, sys, etc. , etc.>” Particularly of AES, Serpent, Blowfish and DES concerns there will be import/download of modules or ciphers. Import of a hash, say of 256 (like SHA256) (ii) Creating the encryption part Defining encrypt function (takes a key, and file name). Variables such as chunksize, etc., etc., etc. Such is where the encryption takes place. If choice is AES encryption one will have to encrypt in 64 bits or whatever); other mandatory exercises to be of Serpent, Blowfish and DES). One has to create an initialization vector (IV) that’s for the encryption process, and to get the file size to do away with the things in the file that are not needed during encryption. (iii) Decryption part In need of the IV stored in the file to add to the decryptor object to decrypt stuff…so the truncate makes sure it gets the exact file. (iii) The Main programme This part just asks the user for the password, whether he or she wants to encrypt or decrypt and does the work. Likely to exist a function that does a traverse of all the files in the current directory and stores it in an array which will be the files that have been encrypted. Take caution against double encryptions, and not encrypting the encryption programme. The password will be converted to SHA256 (or whatever) because it will have a total of 16 characters and AES (or whatever) needs the number of characters of the key to be equivalent to 16 (or whatever). Same for decryption except not wanting to decrypt all the files; preference in decrypting one file at a time. Put files in the root directory of your drive and run them. WARNING: If you try and decrypt the file with a wrong password you will forever lose access to the file. So, you might as well just delete it...just wack. (iv) Can one create programming where file encrypts when leaving computer or when computer (device) is not recognised? Exams --> Exams will apply various things from Lecturers, Homework, Quizzes, Labs, and Additional Implementation Assignments. Exams will have a written component and a component for computer/network usage. Instructions for exams will be given via repository secured specifically for course ID. Exams will be in-class. Expect exams to be different among students. Students will be spaced out in rooms. Students are allowed to use limited amount of notes. COURSE OUTLINE: Wk 1-3: Overview of Cryptography (HAC Ch 1) Introduction to various cryptographic concepts Attacks Security models Wk 4-5: Block Ciphers (HAC Ch 7) Classical ciphers and their cryptanalysis Modes of operations DES Example guides for Wk 4-5 -Dworkin, M. (2001). Recommendation for Block Cipher Modes of Operation: Methods & Techniques. NIST Special Publication 800-38A -Dworkin, M. (2005). Recommendation for Block Cipher Modes of Operation: The CMAC Mode for Authentication. NIST Special Publication 800-38B -Dworkin, M. (2007). Recommendation for Block Cipher Modes of Operation: The CCM Mode for Authentication and Confidentiality. NIST Special Publication 800-38C -Dworkin, M. (2007). Recommendation for Block Cipher Modes of Operation: Galois/Counter Mode (GCM) and GMAC. NIST Special Publication 800-38D -Dworkin, M. (2010). Recommendation for Block Cipher Modes of Operation: Three Variants of Ciphertext Stealing for CBC Mode. Addendum to NIST Special Publication 800-38A -Dworkin, M. (2010). Recommendation for Block Cipher Modes of Operation: The XTS-AES Mode for Confidentiality on Storage Devices. Addendum to NIST Special Publication 800-38E -Dworkin, M. (2012). Recommendation for Block Cipher Modes of Operation: Methods for Key Wrapping. NIST Special Publication 800-38F -Dworkin, M. (2016). Recommendation for Block Cipher Modes of Operation: Methods for Format-Preserving Encryption. NIST Special Publication 800-38G Wk 6-7: AES Math background for AES (HAC Ch 2). Math for Rijndael xtime() multiplication in GF(2^8) multiplicative inverse in GF(2^8) multiplication of polynomials with coefficients in GF(2^8) Components and structure of Rijndael SubBytes() and InvSubBytes() ShiftRows() and InvShiftRows() MixColumns() and InvMixColumns() AddRoundKey() Key Expansion Equivalent Inverse Cipher Example guides for Wk 6-7: -NIST (2001). Federal Information Processing Standards Publication 197, Announcing the ADVANCED ENCRYPTION STANDARD (AES) -Dworkin, M. J. et al. (2001). Advanced Encryption Standards. Federal Inf. Process. Stds. (NIST FIPS) - 197 -Mouha, N. (2021). Review of the Advanced Encryption Standard. NISTIR 8319 Gueron, S. (2010). White Paper: Intel Advanced Encryption Standard (AES) New Instructions Set. INTEL Creel AES Encryption (Part 1 – 4 ) on YouTube Wk 8: Public-key Parameters (HAC Ch 4) Legendre and Jacobi symbols Primality tests (Fermat’ s test, Miller-Rabin test, AKS test) Generating probable prime numbers Generating provable prime numbers Note: NIST can provide additional about Wk 8 topics information (site search of Google search with topic and NIST included). Wk 9: Public Key Cryptography Number-theoretic Reference Problems (HAC Ch 3) Integer factorization RSA problem Diffie-Hellman problem Square root modulo n problem Discrete logarithm problem Public-key Encryption (HAC Ch 8) Chinese remainder theorem and residue number system RSA public-key encryption Diffie-Hellman key exchange ElGamal public-key encryption Rabin public-key encryption Note: NIST can provide additional about Wk 9 topics information (site search of Google search with topic and NIST included). Wk 10: Pseudorandom Generators and Stream Ciphers Pseudorandom Bits and Sequences (HAC Ch 5) Normal and Chi-square distributions Five basic statistical tests for randomness Cryptographically secure pseudorandom bit generators Stream Ciphers (HAC Ch 6) LFSR (Linear Feedback Shift Register) Non-linear FSR Stream ciphers based on LFSR RC4 Note: NIST can provide additional sources about Wk 10 topics information (Google search with topic and NIST included). Wk 11: Hash Functions and Digital Signatures Hash Functions and Data Integrity (HAC Ch 9) MAC (message authentication code) MDC (modification detection code) OWHF (one-way hash function) CRHF (collision resistant hash function) Yuval’ s birthday attack Breaking of hash functions Digital Signatures (HAC Ch 11) RSA signature scheme Fiat-Shamir signature scheme ElGamal signature scheme One-time signature schemes Note: NIST can provide additional about Wk 11 topics information (site search of Google search with topic and NIST included). A few examples: Chang, D. , Dworkin, M. , Hong, S. , Kelsey, J. and Nandi, M. (2012), A Keyed Sponge Construction with Pseudorandomness in the Standard Model, N/A, Washington, DC, US -Dworkin, M. J., Feldman, L. and Witte, G. A. (2015). Additional Secure Hash Algorithm Standards Offer New Opportunities for Data Protection. ITL Bulletin -Dworkin, M. J. (2015). SHA-3 Standard: Permutation-Based Hash and Extendable-Output Functions. Federal Inf. Process. Stds. (NIST FIPS) - 202 -Dworkin, M. J. and Perlner, R. A. (2015). Analysis of VAES3 (FF2). Cryptology ePrint Archive -Cooper, D. et al (2020). Recommendation for Stateful Hash-Based Signature Schemes. Special Publication (NIST SP) - 800-208 Wk 12: Authentication & Key Management (HAC Ch 10, 12, 13) Note: NIST.gov can provide additional about Wk 12 topics information (site search of Google search with topic and NIST included). Wk 13-15: Cryptographic Protocols Basic cryptographic protocols (AC Ch 3) Intermediate cryptographic protocols (AC Ch 4) Advanced cryptographic protocols (AC Ch 5) Esoteric cryptographic protocols (AC Ch 6) Prerequisites: Discrete Structures, Probability & Statistics B, Analysis of Algorithms Data Programming with Mathematica: Course serves towards advance syntax for development and manipulation. Hence, this course may be difficult or repulsive to students not acquainted with Mathematica. Beneficial towards Quantitative/Computational Finance, Computer Science, Physics, Chemistry and Geophysics majors. Students may gain the most out this course when assigned projects with step assignments, then to investigate how their interests can apply to such, leading to mini projects of interest. One shouldn’t necessarily believe that instruction serves as highest potential with use of functions and development. Functions in the Wolfram Mathematica language are highly versatile in many applications and with other functions. Most individuals will not have an affinity for such, so interests and reading texts involving the use of Mathematica will amplify one’s imagination with the many uses. One should also realise that there are hundreds to thousands of functions in Mathematica catering for various purposes. One should start with their interests, develop, reinforce, then challenge themselves with new ideas. This course will have no environment that allows or encourages majority trends and intimidation. The only culture that should arise is what an individual pursues to accomplish. This course serves as no means to promote or elevate any polarizing social expectations with any type of group that is a majority in course. Students in life should not be hoodwinked by con artists conveying coding expertise in everything; again, there are thousands of functions in the Wolfram Language. Don’t subjugate oneself to gaudy or extravagant fodder shows from others. The foundation of this course serves to be the most constructive and economic towards retention, versatility and practicality. NOTE: it may be inevitable that you encounter things in advance without intent; such is natural due to demands with “data structures”, goals and related interests. NOTE: will be open exams. It’s not a competition about who can first assemble their guns and shoot the other in the head. You are your own best friend, and also your worse enemy. You don’t have to care about how Mathematica markets its product if you help yourself rather than being toxic or ring worm. Course grade constitution: I. Assigned tasks constituted by step assignments 25% Such will be activities where students research the wolfram language and acquire programming remedies. Often instructor will provide abstracts and conceptual framework for a task, where you must figure out programming to implement whatever. II. There will be exams based on the conventional constructive practical syntax stemming from lectured subjects, and resembling past assigned tasks. There may be problems where students will have to complete or correct code or determine whether code does what is conveyed about it. Students may be asked to extend code as well. Students will also be given a conceptual model, task or computation to design. Students can make use of Mathematica in exams for meaningfulness. There will be 4 - 5 exams for 40%. NOTE: will be open exams. It’s not a competition about who can first assemble their guns and shoot the other in the head. III. Mini interest projects (in Mathematica notebook) that apply given course instruction (and possibly with other past instruction). Students can incorporate past instruction and independent development in projects if feasible and practical. To have substance and meaningfulness students will inevitably also incorporate some things from Mathematica not lectured in course, however most development must be based on declared lecturing. Students can incorporate their mathematical and science level skills to serve themselves. For projects of interest students will develop logistical blocks and routines to accompany build and demonstration of their projects. Must have PDF copy print out as well. 3 individual projects 15% IV. Major final project. For projects of interest students will develop logistical blocks and routines to accompany build and demonstration of their projects. Must have PDF copy print out as well. Project will be individual 20%. Course is an environment of learning and encouragement rather than failure by imposing attempted conformity with interests. Note: due to the pursuits of interests, naturally, students to independently acquaint themselves with functions not encountered in instruction and assigned tasks. For one particular subject comparing multiple texts is an excellent means towards acquiring progression. When comparing texts, it may take up to ten times or more for you to realise that a particular method or orchestration in some text (staring at you) may be the most engaging to build on. Plan things out with conceptual development before jumping into a self-made “Jumanji”. Additionally, one must be able to apply structuring to various applications of interest. How does the structuring come into play from one circumstance to another? Learning and retention are not “one-stop” implementations. Challenge yourself with contrary development circumstances or with further interests. Course will be longer than usual courses. One shouldn’t necessarily believe that instruction serves as highest potential with use of functions. Functions in the Wolfram Mathematica language are highly versatile in many applications and with other functions. Most individuals will not have an affinity for such, so interests and reading texts involving the use of Mathematica will amplify one’s imagination with the many uses. One should also realise that there are hundreds to thousands of functions in Mathematica catering for various purposes. One should start with their interests, develop, reinforce, then challenge themselves with new ideas. Texts of consideration: -The Mathematica Book, by Stephen Wolfram -The Mathematica Guidebook for Programming, by Michael Trott -Mathematica: A Problem-Centred Approach, by Roozbeh Hazrat -Mathematica in Action, by Stan Wagon -Essentials of Mathematica by Nino Boccara -Mathematica Cookbook, by Sal Mangano NOTE: for each Mathematica function it’s quite important that you comprehend the scope of all parameter options. As well, you must know how make choice of method of interest. Read the damn documentation center sources well. NOTE: the Wolfram Data Repository will be accessible throughout. Other data sources can be applied as well to be self-reliant and versatile. NOTE: students should practice drawing up the logistics for computational schemes, rather than diving blindly into large tasks or projects; your logistics is your business, namely, will be doing actual programming. Don’t mess yourselves and the future students of this course; your antics can carry over to the future. Your lecturer, etc. should belong in this course, not because of some social excrement show, thug rent seeking and nonsense social toxicity. Course layout --> 1. Basic features of Mathematica notebook Brief survey of capabilities Interacting with the front end Basic concepts and first look at some important functions Documentation Constructs (enforced throughout course) -- > https://reference.wolfram.com/language/tutorial/DocumentationConstructs.html “Insert New Cell”, Palettes, features in “Help”, and Notebook Modification History. Note: other features of Mathematica are left to students’ interests; everything can’t be taught. 2. Calculus Operations & Plotting (single and multivariate) Note: rewiew analytical development before Mathematica development Point evaluation and function evaluation on sets polynomials, exponentials, logarithmic, trigonometric, abstract functions Include “list” or array generation Include developing scatter plots Basic plotting syntax and embellishments (includes plot styles) What’s the difference to scatter plots prior? Review equation for a line determination based on two points; includes identification of axes intercepts Interpolation (Mathematica logistics and implementation only) Axis labelling & curve labelling Plot types and embellishments (with prior) Manipulate function Plotting Data and Mixing several kinds of plots into a single graph Will make use of ListPlot, Show, GraphicsColumn and GraphicsGrid functions. Note: for some functions scaling may be an issue concerning display of characteristic features. As well, prior topics to be infused when practical. Calculus operations of functions Intersection points Root finding Differentiation Integration Note: in progression often such features and tools complement each other towards advance details. 3. Synthetic Data Consider the case where your profession may be in the field of marketing/revenue management, actuarial science, etc. where there isn’t luxury or access to data of interest. What can you do? Generating simulated data sets in order to explore modeling techniques or better understand data generating processes. The user defines the distributions of individual variables, specifies relationships between covariates and outcomes, and generates data based on these specifications. The final data sets can represent randomized control trials, repeated measure designs, cluster randomized trials, or naturally observed data processes. Other complexities that can be added include survival data, correlated data, factorial study designs, step wedge designs, and missing data processes. Adding data to an existing data table. Aside from generating new data sets (as in prior) from scratch, it’s often necessary to generate the data in multiple stages so that we would need to add data as we go along. For example we may have multi-level data with clusters that contain collections of individual observations. The data generation might begin with defining and generating cluster-level variables, followed by the definition and generation of the individual-level data; the individual-level data set would be adding to the cluster-level data set. 4. Import & manipulate data (.xls, .xlsx, .csv, .accd, .mde). APIs and API keys. 5. Database Usage (subject to 4) Cleaning/Wrangling Projects Methods for missing data (to pursue) Kang H. (2013). The Prevention and Handling of the Missing Data. Korean J Anesthesiol. 64(5): 402-6. Treating missing data in Mathematica Summary statistics generation 6. Creating data frames from prior data or prior data frames (subject to modules 3-5) 8. Data Frames Making a Grid of Output Data: Wolfram Documentation Center Make A Grid of Output Data Summary statistics generation Note: sets with high volume of raw data will need more ingenuity with labelling; it’s sensible to know the set’s length before pursuing such. Practical Operations on your data frames 9. Structured Data in Science and Engineering from Mathematica Operations with ElementData, ChemicalData, ParticleData, ParticleTable, ProteinData, FinancialData, etc, etc, etc. In the Wolfram language there’s also geophysical data, say “Earth sciences: Data & Computation”. Advance data acquisition and manipulation example: ETF=FinancialData[#, “Return”, {{2008, 2}, {2013, 2}, “Month”}] [[All, 2]] &/@ {“EWA”, “EWC”, “EWG”, “EWJ”, “EWU”, “SPY”, “EWS”} Note: in the example above the specified parameters (excluding the operators are unique to FinancialData. This ETF array defined can be operated on or manipulated in many more advanced ways. Case Study (just surveying mostly): Malacarne, R. L., Canonical Correlation Analysis, The Mathematica Journal, Volume 16, Jun 23 2014, 22 pages Data structured in above article is dependent on the FinancialData function. However, one can pursue similar array structuring with other data functions, files and external sources. Structuring data (frames) from the mentioned prior specific functions 10. Data Analysis Review For descriptive statistics Mangano’s text, Chapter 12, pages 455 - 504 (has good summary data forms). Will treat some of the topics, but with real data rather than synthetic data from RandomReal and RandomSample. Modules (3) through (8) may or may not come back to haunt. 11. Basic Regression immersion All will be highly strategic rather than a comprehensive environment. Mathematica tools for regression. Justifying variables for models. Choosing between OLS, WLS and GLS choice. Summary statistics and interpretation. 12. Basic Time Series immersion All will be highly strategic rather than a comprehensive environment. Mathematica tools for salient characteristics/decompositions. Model process for time series: selection, estimation, validation and diagnostics. Summary statistics. Forecasting and error. 13. Introductory Machine Learning Wolfram Documentation Center Machine Learning Note: cleaning, wrangling and data description will come back to haunt. For any chosen respective Mathematica ML function one should have a firm understanding what it does, its strengths and limitations. Programming Data Sets (for training, testing, validation); must be relativity large towards performance credibility. Data of consideration will be real data from various applications involving real systems, natural phenomena, processes, etc. If data of meteorology and oceanography are to to be applied, to be annual or seasonal in range and nothing shorter since atmospheric and oceanographic behaviours are highly dynamic in the short term concerning fluid dynamics and thermodynamics where oceanographic and atmospheric behaviours are often “coupled” or influence each each other. Means of improving accuracy. Assumption of no cognition bias in ML; it’s the programmer/researcher who is at fault involving what’s in their minds and possible neglect, augmented by whatever is being put out there. Will be restricted to the following areas: Wolfram Data Repository Supervised Learning Multivariate Regression review: variables choice, OLS/WLS, summary statistics interpretation. Validation. 2 other versatile and robust types Unsupervised learning Clustering Association Dimensionality Reduction 14. Hiding your code (applicable to prior and future instruction) Prerequisites: Ordinary Differential Equations, Numerical Analysis, Probability & Statistics B Machine Learning Course Description: Machine Learning (ML) is the study of how to build “computer systems” that learn from experience. This course on ML will explain how to build systems that learn and adapt using real-world applications, with practical immersion; will also implement such systems. NOTE: course serves to introduce only the basic types of machine learning for a decent foundation. This is a CS course, and not a course in the Data Engineering programme. Course will have a more “cypher, adapt and implement” mode concerning mandatory use of R, Mathematica and C++. NOTE: course will procure 18 weeks, with three sessions per week, and with 2 hours per session “to chew properly and digest”; labs sessions days to be unique to prior. NOTE: on numerous occasions in course there may be algorithms built on prior algorithms or concepts encountered and developed. In many cases, introspecting, querying data and data wrangling towards interests likely will be unavoidable (manually and/or function usage, and issues with missing data); includes knowledge of APIs and API keys. Naturally, skills from Probability & Statistics and Mathematical Statistics courses (being part of prerequisites) will prove invaluable. Such includes cleaning, wrangling and the mess. Example data sources of interest for this course are Kaggle, Google Earth-Engine, Public Administration databases, IGOs, financial data sources, FDIC, central banks, NOAA, geophysics data sources (geology, meteorology, oceanography), astronomy data sources, political science, etc., etc., etc., etc. NOTE: as well, in the Mathematica environment there is the Wolfram Data Repository available; not necessarily confined to it however. NOTE: this course isn’t dedicated to images (recognition, authentication and classification). If you have quarrel with such, find another course elsewhere. What decent person dedicates Machine Learning solely to images? Humans can be the worst pestilence and destroyers when it comes to education, greater than another Bubonic plague itself; they usually make things worse through one as well. Course is directed to students who want to be versatile, pleasant, and not pegged targets. NOTE: if for the case of meteorology and oceanography pursuits, data sets will only be annual or seasonal in range and nothing shorter since atmospheric and oceanographic behaviours are highly dynamic in the short term concerning fluid dynamics, thermodynamics, heat transfer, etc. where oceanographic and atmospheric behaviours are generally coupled. Tools from OpenAI and TensorFlow may prove highly useful if one understands what they can (or want to do) with them, as the dilemma; GitHub repository also has such dilemma. Resources such as OpenAI, OpenCV, TensorFlow, Shogun, SHARK Library, MLPACK Library, OpenNN, Mathematica Repositories and GitHub repositories are there for one to expand their thinking and the possibilities. NOTE: identify C/C++ machine learning libraries for use with course. NOTE: there are also many data repositories for the natural sciences, energy, robotics, etc., etc., etc. The human experience is, to generally learn by experience with applications. Hence, an environment of toxic mathematical frolic and vanity will be frowned upon. One has every right to despise or loathe professors in a mathematical proofs course and group theory course (which have nothing do with this course), because to prove something meaningful you have to know something or do something meaningful in everyday life, rather than intellectual idolatry, perversion, hindrance, bamboozle, terror tactics and parasitic survival. Course will also incorporate industry applications from the ACM, IEEE and other engineering, physical sciences, computation, economics articles and other published papers. Otherwise, this course will be quite meaningless concerning using ML for anything. Concerning the to be mentioned topic areas in machine learning with concepts, comprehension, fluidity, tangibility, practicality and algorithm development, there are some development and analysis concerns likely to arise on multiple occasions, such as: Quality and structure of data Fake or falsified data Model or Algorithm selection Data sets splitting (training, testing, validation) Data leakage Overfitting Underfitting Hyperparameter tuning Pruning Cross validation ROC & AUC One must clearly or definitively understand the role of causal inference when applied (if it’s relevant), in the sense that machine learning has no level of cognition, rather it carries out its role based on “what’s out there” due to its design, and nothing more; causal inference really comes down to special interests that’s often social, political or economic in nature. NOTE: again, this is not plainly a mathematics or statistics course because one is dealing with algorithms for the real world. Fluid, tangible and practical development towards real known innovation is a top priority; prerequisites of this course is to deter a swamp of mathematical frolic impedance or course being mathematically hijacked towards nothing. Students MUST ACCEPT that skills from Probability & Statistics and Mathematical Statistics will be primitive tools that will naturally apply in this course. All prerequisites declared below concern students not getting butchered nor being useless in this course. Course is project-oriented, with emphasis placed on writing programming implementations of learning algorithms applied to real-world problems, along with short reports describing results. NOTE: on numerous occasions in course there may be algorithms built on prior algorithms or concepts encountered and developed. NOTE: course isn’t just about bluntly completing assignments and procedures from modules, rather, also how topics in the modules integrate towards meaningful and economic function. Hence, past modules will come back to haunt, in the sense that what was learnt prior will be useful and essential in the future for useful things. NOTE: one will also be doing much reading on C/C++, Mathematica and R outside of class. NOTE: commentary is expected throughout the C/C++, R and Mathematica programming. Course Assessment DEVELOPMENT ASSIGNMENTS (chosen from the 15 modules) AT LEAST 5-8 MAJOR PROJECTS AT LEAST 1-2 HANDS-ON EXAMS EXAMS WILL CONCERN THE FOLLOWING: (1) to apply knowledge of computing and practical mathematics to machine learning problems, models and algorithms (2) to analyse a problem, identify appropriate methods, logistical scheme development, and identify the computing requirements appropriate for its solution (3) to design, implement, and evaluate an algorithm to meet desired needs (4) to apply mathematical foundations towards algorithms in a practical, tangible and fluid way that demonstrates comprehension of the trade-offs among ML tools choices. (5) One doesn’t expect a student to memorize every algorithm, rather the ability to determine what it does, how to profile it, how data should be structured, etc. There may be trick questions --> Information told isn’t perfectly accurate Purpose and structure of data Algorithm may be rubbish Information told about algorithm isn’t perfectly accurate Some problems for particular topics require development of “flowchart abstraction” before expressing code structure for particular applications. (6) R and Mathematica structures can be given where students must develop particular counterparts in the C/C++ language; vice versa. Elements from (5) may also apply. (7) Based on some development assignments and major projects done, the instructor to conjure questions, having analytical, computational and statistical questions. NOTE: on exams students will be allowed to have 5-10 loose-leaf sized sheets; a sheet implies use of both sides. I don’t expect you to remember every little detail because I assume no one has an affinity nor innate ability at the undergraduate level. ML is consistently presented in a manner that’s not tangible towards one’s personal independence. Often, machine learning commercial products are peddled to an audience with vague sophistication, but also as a necessity for the audience. This course aims to do away with the intimidation and subjugation. This course serves as a computer science course to develop practical, competent and applicable programming. Course will not be incarcerated by any mischievous, impeding, overbearing mathematical culture. Course isn’t geared to dive into a non-constructive mathematical swamp. Accompanying any useful, practical, tangible and fluid mathematical structure will be concise practical, tangible and fluid programming development, relevant to practical applications of machine learning, such as data mining, complex relationships, variables, parameter estimations, forecasting, applied sciences, engineering, economics, political science, etc. Hence, in many aspects this course will have investigative and experimental tones, which are arguably the best ways to really become relevant with ML. R and Mathematica will shadow C/C++ development throughout course for coherency and certainty. Summary statistics in R and Mathematica will prove invaluable. A crucial reason for R and Mathematica to complement a C/C++ building environment is that coherency, manoeuvrability and versatility are economic for building professionalism, time optimisation and job security. As well, as a computer science course, such gives students exposure to different language styles. Prerequisites for this course serve as assurance of students’ maturity and self-reliance; faking your way out of this course will essentially be similar to the “A Bridge Too Far” movie, say, no matter what star celebrities are part of it, one result is expected; barely making it back, but with tails between legs. This course is introductory towards “being about something” after it, which will be taken into consideration with course grade (naturally or de facto). At this level with prerequisites, you are not learning C/C++, rather you are using it naturally to “get through things”. As well, syntax with R and Mathematica should not be daunting tasks. For R tools the following source to serve well --> Tidyverse Tidymodels https://cran.r-project.org/web/views/MachineLearning.html Such list from above source may not have all packages in R. Examples --> caretEnsemble, crossval, EnsembleBase, EnsemblePCReg, forecastML, FuncNN, XGBoost, mlbench, neuralnet, pROC, Rfast Concerning such packages link and the succeeding mentioned packages there may be vignettes. GitHub repository also provides guides in R and for general environments. Programming for splitting data into training, testing and validation sets, etc. Will treat issues with database structure, formats, inspecting character of constituents, data analysis, etc. Will compare with R and Mathematica development. Compare to development with caret package, and as well with practical Mathematica functions. A small idea of what is expected for cross validation with R (but not necessarily the only way) --> Venturini, S. (2016). Cross-Validation for Predictive Analytics Using R. Milano R. Yet again, style in R to vary with packages applied. For the Wolfram Language, Mathematica is self-contained with its guides and tools in a “pampered sense” with Wolfram Documentation Centre. Apart from intelligence and listings in Mathematica’s Documentation Center with functions of ML there’s also applied guides examples (just naming a few) --> https://reference.wolfram.com/language/guide/MachineLearning.html https://www.wolfram.com/wolfram-u/catalog/machine-learning/ https://reference.wolfram.com/language/guide/ClusterAnalysis.html https://reference.wolfram.com/language/guide/NeuralNetworks.html https://www.wolfram.com/language/12/neural-network-framework/?product=language Project assignments will be handed out in class and posted on the course web site, along with the due dates. All projects will be introduced and discussed during class time. Projects will involve a combination of programming and/or writing up your results in (in short report form applying mathematical pallette). You must use C/C++ programming language (via Linux environment) in your projects, accompanied by R and Mathematica counterparts. As part of the project materials you turn in, you will be required to submit instructions for how to compile and run your code, along with all files needed to successfully run your code; Mathematica notebook printout in PDF containing developed Wolfram language comparative programming, whereas for RStudio such will make use of rmarkdown towards pdf form. Ice Breaking articles: IBM – Unsupervised Learning: https://www.ibm.com/cloud/learn/unsupervised-learning IBM – Supervised Learning: https://www.ibm.com/cloud/learn/supervised-learning Almaliki, Z. A. (2019). Do You Know How to Choose the Right Machine Learning Algorithm among 7 Different Types? Toward Data Science The above three articles however are only conceptual and have no influence on the declared obligations and prerequisites for this course. NOTE: course will be applications sensible, relevant, tangible, practical and fluid, else there’s really no point to any huge investment in ML. NOTE: literature provided are subject to change. Modules and Topics that WILL BE COVERED: 1.Data sources, APIs/API keys 2.Data preparation/preprocessing. Data Wrangling 3.Exploratory Data Analysis Note: for this module will restrict to R and Mathematica. For R there’s the R package CADStat. For Mathematica read up with Wolfram Documentation Centre. Histograms, Boxplots, Cumulative Distribution Functions, Q-Q plots, Scatter Plots 4.Detecting fabricated data Note: for this module will restrict to R and Mathematica. Hartgerink C, Wicherts J, van Assen M (2016) The Value of Statistical Tools to Detect Data Fabrication. Research Ideas and Outcomes 2: e8860. Al-Marzouki, S., Evans, S., Marshall, T., & Roberts, I. (2005). Are These Data Real? Statistical Methods for the Detection of Data Fabrication in Clinical Trials. BMJ, 331(7511), 267–143. Yamamoto, K., & Lennon, M. L. (2018). Understanding and Detecting Data Fabrication in Large-Scale Assessments. Quality Assurance in Education, 26(2), 196–212. Benford-Newcomb, Zipf 5.Clustering (concept, methods & modelling, algorithms, hands-on applications) Will restrict to applications implementation for demographics, census and biological data analysis since such data will be easy to acquire 6. Feature Selection Note: a feature is the same as a predictor variable; a target is equivalent to a response variable. First, for datasets chosen will develop correlation matrices. Then heatmaps. Second, will explore a method for feature feature selection. Will identify the concept, followed by (practical, tangible and fluid) analytical structure of the method. Then implementation logistics. Then implementation in the R environment. Will make use of datasets with considerable amounts of features. The Caret R package is just one means of accomplishing such. Univariate feature selection method (will be hands-on) 7. Regression There will be no delving into beginner development due to constraints on time. Review your notes from prerequisites. Multilinear Regression (MR) Heinze, G., Wallisch, C., & Dunkler, D. (2018). Variable selection - A review and recommendations for the practicing statistician. Biometrical journal. Biometrische Zeitschrift, 60(3), 431–449 Dong, J., Rudin, C. Exploring the Cloud of Variable Importance for the Set of All Good Models. Nat Mach Intell 2, 810–824 (2020) Feature Selection review (univariate method) Choosing between OLS, WLS and GLS Then to make use of F-test, Vuong’s test, AIC and BIC, Hannan-Quinn Apart from training, testing and so forth will also use summary statistics Forecasting & Error Feature Importance (regression method) Compare importance results to univariate feature selection method Response variable distribution & conditional expectation For multilinear models to develop the probability distributions for a respective explanatory variable (or multiple) with the response variable, w.r.t. data range. Evaluating Conditional probabilities and conditional expectation. Marginal Effects Applications & differentiation from multiple coefficient of determination Casual Inference and omitted variables Quantile Regression (QR) Scatter Plots Scatterplots are a useful first step in any analysis because they help visualize relationships and identify possible issues (e.g., outliers) that can influence subsequent statistical analyses, or need of regression beyond simple OLS, say, quantile regression (or generalized nonlinear models). Note: concerns for the number of variable pairs. Practical and fluid analysis towards computational logistics; includes variable selection. Then implementation. Comparing with least squares types prior modelling, estimation and validation, forecasting and error Applications in economics (GDP, employment, trade models) quantreg package with manual and vignettes Response variable distribution & conditional expectation For multilinear models to develop the probability distributions for a respective explanatory variable (or multiple) with the response variable, w.r.t. data range. Evaluating Conditional probabilities and conditional expectation. All such is for compare/contrast with OLS/WLS/GLS multilinear models Marginal Effects compared to OLS/WLS/SLS models Coefficient of determination and other summary statistics in quantile regression models compared to OLS/WLS/GLS models Causal inference and omitted variables Ando, T., & Tsay, R. S. (2011). Quantile regression models with factor-augmented predictors and information criterion. The Econometrics Journal, 14(1), 1–24. Implications of feature importance and feature selection for multiple regression and quantile regression (hands-on) Stochastic Frontier Analysis (concept, modelling and logistics) Applications implementation for agriculture and other industries 8.Linear Classifier (generative models versus discriminative models) Logistic Regression Motives Model Structure and Computational Structure Evidence for variables Model fitting Parameters pursuit Summary Statistics analysis Calculating Probabilities/Predicted Probabilities Marginal Effects Multiple logistic regression (extend all prior) Applications implementation in political science, labour economics, astronomy, etc. Feature Importance (logistic method) Compare importance results to: Multilinear regression feature importance Univariate feature selection method Support Vector Machine Fluid analysis towards computational logistics, then implementation Scoring Will try to have comparative implementation development to logistic regression (and means of analyses for disparities) Recursive feature elimination method (will be hands-on) Estimator choices to be logistic and SVM within RFE Then compare to: Univariate selection method Multiple regression feature importance Logistic regression feature importance 9.Decision Trees (past modules will come back to haunt) Note: this is one topic in ML where often lip service and con artists thrive. Well, for our purposes there is the goal of high clarity, strong logistics and practical implementation. NOTE: for applications of Decision trees students must develop definitive schemes with data being immersible with structure. Sequential development of code patches subjugating data. Possible guides: Almuallim, H., Kaneda, S. and Akiba, Y. (2002). Chapter 3: Development and Applications of Decision Trees. Expert Systems, Vol. 1, pages 53 – 77: https://booksite.elsevier.com/9780124438804/leondes_expert_vol1_ch3.pdf Song, Y. Y., & Lu, Y. (2015). Decision Tree Methods: Applications for Classification and Prediction. Shanghai Archives of Psychiatry, 27(2), 130–135 Note: if data manipulation is taken on, then one can possibly compare to module 4 techniques J. Hu, J. Deng and M. Sui, A New Approach for Decision Tree Based on Principal Component Analysis, 2009 International Conference on Computational Intelligence and Software Engineering, Wuhan, pp. 1-4 Decision Trees Feature Importance (hands-on) CART Regression and CART Classification types Then compare such prior two to: Univariate selection method Recursive selection method Multiple regression feature importance Logistic regression feature importance 10.Artificial Neural Networks (theory, tangible/practical structuring, logistics, applications implementation). With applications will like to make use of “flowchart abstraction” development before any possible engagement with code design and implementation. Perceptron Single layer Multi-layer Recurrent Neural network Feedforward Neural Network (and backpropagation) NOTE: establishing role of gradient descent with weights in crucial NOTE: cross validation is mandatory with any pursuit. NOTE: often the R environment AND Mathematica will be used for constructive purposes with exposure and skills building with various assignments. Furthermore, some ideas with C++ development --> A. David Miller- Neural Net in C++ tutorial – Vimeo < https://vimeo.com/19569529 > B. Devlogs – YouTube Will only be concerned with videos related to Neural Networks with C++. Establishing a constructive sequential order with videos is a concern < https://www.youtube.com/channel/UCg9rw36CJztvSEjmei0hSPQ/videos > C. Deep Learning with C++ Peter Goldsborough – Meeting C++ 2017 – YouTube: << https://www.youtube.com/watch?v=8GoYXWOq55A >> D. Issues with overfitting and prevention/mitigation E. Will be applications intensive with real raw data. F. Geophysics to implement Uwamahoro, J., Habarulema, J.B. Empirical Modelling of the Storm Time Geomagnetic Indices: A Comparison Between the Local K and Global Kp Indices. Earth Planet Sp 66, 95 (2014) G. Spectroscopy to implement Ch. Affolter, J.T. Clerc (1993). Prediction of Infrared Spectra from Chemical Structures of Organic Compounds using Neural networks. Chemometrics and Intelligent Laboratory Systems, Volume 21, Issues 2–3, Pages 151-157. Hopefully there’s no need to be well versed in chemistry. Students are also expected to design and develop ANN use with demonstration in class accompanying report. 11.Ensemble Learning Past modules will come back to haunt Will focus mainly on Random Forest (due to familiarity with underlying estimators), and a bit of exposure to Boosts. Will have development for such two types. Random Forest Feature Importance (hands-on) Then compare to: Univariate selection method Recursive selection method (logit estimator vs SVM estimator) Decision Tree feature importance (both types) Multiple regression feature importance Logistic regression feature importance Prerequisites: Numerical Analysis, Data Structures, Probability & Statistics B, Mathematical Statistics, Data Programming with Mathematica. Course will make use of C/C++, R language and Mathematica in a Linux environment. Network Programming Computer networks have become embedded in our everyday lives, enabling applications such as the multi-players online games, electronic commerce and trading, video streaming and conferencing, peer-to-peer file sharing and computations, social networking, Cloud Computing, Internet-of-Things, and of course, text messages and cell phone calls. The course presents the building blocks of a network and how these blocks fit together. The course emphasizes the design and implementation of network software that transforms raw hardware into a richly functional communication system. Real networks (such as the Internet, Ethernet, Wi-Fi) will be used as examples to reinforce the concepts and demonstrate various protocols and architectures. The course also covers notions of network management and modern networking, such as Software-Defined Networks and Data Centre networking Learning Outcomes: 1. Students will be able to describe detailed features of fundamental computer network protocols and networked applications. 2. Students will be able to describe basic features of modern computer network architectures. 3. Students will be able to design, implement, and test core functionalities within classical network protocols and networked applications. 4. Students will be able to perform basic experiments with network analyser tools Skills for Labs --> 1. Solid programming skills in a high-level language (such as C++) are required. If the instructor provides a skeleton of code in some language (e.g., Python or Java) as part of an assignment, you will be expected to incorporate your code in C++ language environment to implement specific networking functions. In this case, the code is mostly straightforward and does not need knowledge of advanced features of the language. 2. A rudimentary understanding of algorithms and their mathematical foundations is required. 3. A rudimentary understanding of computer architecture and operating systems is required. Students are expected to already have the background to read and understand code, write and debug reasonably large (1000-line) programs, run few basic Linux commands, and learn new syntax and apply it without much difficulty. Students are also expected to learn new tools/programs and run them to test and analyse network protocols. Projects --> Projects will concern hands-on IoT development, smart-home development, hands-on Bluetooth development and office requirement development. There will be detailed analysis for hardware, software and designed networks to be integrated. Will be followed by hands-on activities. Students should not expect to be pampered with source codes just to insert and run. The more primitive you are in skills, the more control you have for the future. All your C++ experience and skills will be put to use. There will be 5 - 6 projects. Example texts: Computer Networking, A Top-Down Approach, by Kurose & Ross Software of interest for Computer Networks -->: SGAMToolbox, RAMI 4.0 Toolbox https://code.nsa.gov Network simulators --> Marionnet network simulator REAL network simulator OMNeT++ with INET framework Course Assessment: 5-6 Quizzes 35% Labs 35% Projects 30% Lecture Outline: 1. Overview: introduction to communications connectivity --Links and nodes --LANs and WANs --Internets --Multiplexing --End-to-end channels --Standards, protocols and architectures (OSI, TCP/IP) 2. Applications --Application Programming Interface (sockets) --Client-server, Email (SMTP, POP, IMAP) --Web (HTTP, HTTPS, cookies, caches) --DNS, P2P (file sharing, Skype) 3. Transport services and protocols --UDP and TCP --Basics of reliable communication (stop-and-wait, go-back-n, selective-repeat) --Flow control (sliding window) --End-to-end challenges (TCP reliability and flow control) --Connection management and adaptive retransmission --Congestion control: AIMD, slow start, fast retransmit and recovery, fairness 4. Network Layer: Data Plane --IPv4 and IPv6 --Packet Scheduling --Datagram fragmentation and reassembly --Network Address Translation (NAT) --Generalized Forwarding and Software-Defined Networks (SDN) --The OpenFlow Protocol 5. Network Layer: Control Plane --Packets vs. virtual circuits --Distance-vector routing (loops) --Link-state routing --Border Gateway Protocol (BGP) --Network Management (ICMP, SNMP, CMIP) 6. The Link Layer and LANs --Point-to-point links --LANs: encoding, framing, error detection (parity, CRC) --MAC protocols (Ethernet CSMA/CD) --Internetworking (spanning-tree switches, forwarding) --Link virtualization --Data Centre Networking 7. Network Security --Intro to asymmetric and symmetric cryptography --Transport Layer Security (TLS) protocol --IPSec protocol --Firewalls and Intrusion Detection Systems Prerequisites: UNIX/Linux Fundamentals, Advance Computer Networks Penetration Testing & Ethical Hacking Principles and techniques associated with the cybersecurity practice known as penetration testing or ethical hacking. The course covers planning, reconnaissance, scanning, exploitation, post-exploitation, and result reporting. The student discovers how system vulnerabilities can be exploited and learns to avoid such problems. For security purposes one may construct a very small local area network and wifi that applies only to designated computers and other devices. There’s generally no activity leaving such designated computers and devices. Will be a hands-on engaging environment. Students will encounter various circumstances, develop results and implement; students will log their planning and strategies in process. Notes taking and “drawing boards” likely will also be very important. Will also observe and implement current IEEE and ISC2 standards regardless of what is expressed beneath; some subject areas may require amendments to treat modern technologies and practices. Students and constituents should generally not have their highly cherished devices be subjugated to experimentation, etc. Assessment --> Participation 10% Lab exercises 30% Group projects 20% Midterm 20% Final examination 20% Text example (but may not commit to it) --> Hacking Exposed 7: Network Security Secrets and Solutions, Stuart McClure, Joel Scambray, George Kurtz Simulator --> CyberCIEGE Applied throughout course development Necessary Computer Networks Tools --> SGAMToolbox, RAMI 4.0 Toolbox Prerequisite Course Tools --> Virtual Machine Software: Install VirtualBox (version 4.2.6 or newer). This is a free software. Ubuntu 16.04 Virtual Machine Image. All the Linux labs use this image. Will have a user manual. Necessary Monitoring Tools --> Kali Linux nmap Wireshark https://code.nsa.gov Other tools (https://www.csoonline.com/article/2943524/11-penetration-testing-tools-the-pros-use.html) Resources --> NIST National Vulnerability Database CISA – US-CERT NOTE: course will be interactive in order to be constructive and competent with anything taught. There will be labs with reports in an environment integrated to the world wide web, but doesn’t commerce with any other network systems of any institution or campus. NOTE: based on prerequisite course students should be able to describe or profile in detail components and features relevant to many or most vulnerability, penetration or hacking issues. Such implies that students should be able to recommend the appropriate procedures with implementation. Such may be incorporated in labs and exams. NOTE: behaviour or actions that compromises the privacy and security of others can warrant indefinite failure in course, and other consequences involving school’s administration and legal authorities. Behaviour or actions that compromises the privacy and security of other networks not related to course can warrant indefinite failure in course, and other consequences involving school’s administration and legal authorities. NOTE: there may be advance walkthroughs with simulator throughout course that connects with topics. There will much effort to relate prerequisite course topics to current course topics. Labs from prerequisite course topics may be revisited to relate to current course topics. A gauge of possible subject areas: -Software installation, Pre-engagement, scoping -Ethical requirements and legal issues -Penetration test report structure and components -Reconnaissance -DNS, web reconnaissance -TCP, UDP, connections -Scanning using nmap -File transfer protocol: ftp, http, https, telnet -SSL and TLS encryption -NetBIOS and NFS -Encryption essentials -Windows passwords, hashes -Rainbow tables, Linux passwords, hashes with salt -Searching Linux and Windows file systems -Metasploit exploitation framework -Use of netcat and pivoting -VOIP -Wireless networks and encryption -Lock picking, master keys, and oracle hacks -Cryptography weaknesses -Http, https, javascript, and command injection -Databases, SQL, SQL injection -Browser proxies and non-rendered content, cross-site scripting -Cross-site scripting and cross-site request forgery -Web authentication and session management -Mobile device security issues -Mobile devices and student presentations -Student presentations Prerequisite: Principles of Network Security Data Center Networking Course explores technologies, techniques, and designs for cloud data centre networking, incorporating real production networks at cloud providers like Google, Microsoft, Dell, Nvidia, Cisco, Amazon, etc, etc. Topics include multipath topologies and routing, load balancing, network virtualization, fault-tolerance, performance isolation, network acceleration (e.g. RDMA), in-network computing, explicit congestion control, and protocol independent programmable networking hardware. Ultimately, the goal is to foster an understanding of the many different aspects of data centre networking in a way that is both comprehensive and current. To establish how the cloud became relevant, hardware history and the economics will be treated. Will also have emphasis on security development for both cloud and hardware aspects. NOTE: based on prerequisites successfully completed I expect students to be mature enough to realise that they’re the stakeholders in development. I will not give quizzes or tests in this course. Students will be as good as how serious and dedicated they are to the course; know your priorities. Faking, coning or “thugging” your way out of this course will lead to both short term and long term disasters; the world is bigger than both and is constantly evolving without you. It’s a field about being immersed, functional and very able, neither an environment for socio-political rabble/appeasement nor provocative polarization. Again, the stakeholders and priorities. NOTE: course can lead to certificate acquisition. Literature--> There will be multiple documentation from the following resources (but not limited to them) ACM SIGCOMM NSDI OSDI NOTE: such sources above also provide strong tutorials for pursued tasks. As well, GitHub may prove invaluable. Assignments --> Assignments will involve highly analytical schemes, designs and extensive programming with implementation. Students often will have to become acquainted with unconventional languages, being the nature of the field. Hands on experience with P4 Writing new test cases for existing P4 examples Writing a new P4 programme for (Axon or whatever) routing Writing a new P4 programme for Ethernet-in-Ethernet routing Learning and Benchmarking RDMA CloudLab or whatever Benchmarking RDMA Intro to NFV and Virtual Switching CloudLab environment NFV Benchmarking NOTE: assignments will have much variation abilities to deter the development of a destructive culture towards copy-and-paste, grift and entitlement. Hardware Development & Network Lab Project --> Phase 1: Building a Server with “Old” Hard Drives, Motherboards, CPUs -Understanding the difference between Network attached storage (NAS), DAS and SAN. -Arrangement possibilities: logical, redundant storage containers or RAID (Redundant Array of Independent Disks) or clustering -Access to files using network file sharing protocols -PATA and SATA concerns and understanding MTBF -Network architecture -Network file sharing protocols to understand, conference on and implement: NFS, SMB/CIFB, NCP, HTTP & HTTPS, rsync, FTP & SFTP, UPnP. -Open source server implementations (Linux/Unix) -Will like to establish relation between drives speed, speed of network card and number of clients -Must identify security vulnerabilities and resolutions towards pending server construction -Outstanding interests and concerns: test bed for server activities, redundancy and other arrangement possibilities, performance, data security, and separate bot drive-separate data drive contemplation. Note: microcontrollers and a cooling system are basic hardware to be incorporated with the “old” hard drives, motherboards, CPUs, etc. Phase 2: Extending phase 1 to multiple server constructs integrated Phase 3: Single-rack data center (and possibly up to 3 racks) Concerning phase 1 and 2 we are interested in meaningful and practical applications that serve long term interests. Key hardware components to concern phase 3: routers, switches, firewalls, storage systems, servers, and application-delivery controllers. Expected, phase 3 will take much longer time than phases 1 and 2 due to lecturing pace, networking designing with hardware (includes cooling mechanisms), software, routing, protocols, security, power requirements, etc. etc, etc., etc. Note: keeping note or logs will be very important in all phases for recollection, review and backtracking. Being chintzy in character, for all phases expect to receive hardware donations or resorting to salvaging efforts. Cloud Data Center Development Lab Project --> Activity concerns why cloud networking is a strong market (related hardware costs, space, and staff reduction). Will develop a data center in the cloud. Security development will be one of the major priorities. Before development of the cloud data center with a proprietary vendor we will build intelligence with investigation from use of the following software (one or two): MDCSim BigHouse DCNSim Greencloud OMNeT++ with INET framework Term Project (not limited to the following examples) --> BlueFlame RDMA Benchmark NAPI for RDMA P4 Rate-limiting and sketches Multi-tenant RCP Virtual switch in P4 NOTE: assignments will have much variation abilities to deter a destructive culture development of copy-and-paste, grift and entitlement. Projects will not simply be a “stroll in the park”. Course Assessment --> Assignments 20% Hardware Development & Network Lab Projects 30% Cloud Data Center Development Project 30% Term Project 20% Course Topics --> Multipath Topologies and Routing Virtual Networking Data Center Load Balancing Fault-Tolerance Performance Isolation Network acceleration and In-Network Computing Atomic Multicast and Network Accelerated Consensus Explicit Congestion Control and Packet Scheduling Protocol Independent Programmable Networking Hardware Network Function Virtualization Prerequisites: Programming Language Concepts, Computer Systems, Operating Systems, Advanced Computer Networks, Network Programming Introduction to Databases In this course students are introduced to the concepts and characteristics of relational database systems. The organisation of data within relational databases including normalisation and integrity constraints are explained as well as the concepts related to relational design. The focus of the course is Structure Query Language (SQL), the language of relational database systems. Through hands-on experience both in class and off campus, SQL is practiced, concepts are reinforced and students gain proficiency in using SQL to code and maintain data in relational tables. In addition, students gain proficiency in manipulating relational data using an industry-standard relational database system. Upon successful completion of the course, the student should be able to: Understand the role of a database in an IS, and the relationships databases have with other parts of the IS. Understand the organization of the data in the RDB, the concepts of the table structure, the primary and the foreign keys. Create tables according to a given design, including choosing data types for columns and declaring the column and the table constraints (primary key, foreign key, NOT NULL, CHECK). Populate tables with data and manipulate the data (create, update, delete and retrieve). Program data retrieval queries, including: 1. Select data from one table for various retrieval conditions. 2. Select data from several tables with the help of joins or subqueries, and for various retrieval conditions. 3. Perform aggregate calculations on data from one or several tables. 4. Populate tables with data from other applications and export data to other applications (including spreadsheets). One of the most critical phases of this course is the beginning. Say, what is the most constructive, nurturing and sustainable way to begin? The four letter word “3 – 21 – 14 – 20” and the seven letter word “1 – 19 – 19 – 8 – 15 – 12 – 5” should neither be a tone nor undercurrent, nor approach, nor means of lecturing. Preferential treatment towards any particular student is a monstrous taboo; leads to “scum of the universe” in places where they don’t belong. All constituents of this course should know their priorities, be respectful, considerate and constructively harmonic towards the end goal, subject to quality, integrity and civility all throughout course. Course Text --> Pratt, Philip J. and Mary Z. Last. (2009). A Guide to SQL, 9th edition. Boston: Cengage Learning Software of interest are --> PostgreSQL (preference) Microsoft Access SQLite AsterixDB MariaDB MapReduce (must be included out of the choices) Integrating Tools --> Microsoft Office USB storage device for class assignments and projects. Course Assessment --> 15% Development of Snippet Tasks Will be taking advantage of academic data and general campus data. If data involves students, students swill only identified by student ID 30% – Participation & Four Major Assignments Will be taking advantage of academic data and general campus data. If data involves students, students will only be identified by student ID 40% – 4-5 Exams 15% – Exploratory Tasks with Gov’t Databases via API keys US Census databases US Bureau of Economic Analysis databases US Bureau of Labour Statistics COURSE TOPICS --> Introduction to database concepts Relational databases Creating Tables (2 weeks) Updating Data SQL. Single Table Queries (2 weeks) Simple Queries Sorting Using Functions Grouping (2 weeks) Multiple Table Queries (3 weeks) Querying Multiple Tables Comparing joins, IN and EXISTS Database Administration SQL Functions and Procedures Prerequisites: Computer Systems, Analysis of Algorithms Database Security Study of principles and practices of implementing computer database security in modern businesses and industries, including database security principles, database auditing, security implementation and database reliability. NOTE: much more emphasis on multi-model database management systems Learning Objectives --> -Demonstrate understanding of current database technology and typical database products. -Demonstrate understanding of security architecture in modern computer systems in a typical enterprise. -Formulate a working definition of database security and administration. -Identify contemporary practices of operating system security. -Demonstrate the knowledge and skills for administration of user, profiles, password policies, privileges and roles. -Manage database security on application level. -Conduct database auditing for security and reliability. -Implement typical security projects on enterprise systems. Literature --> A text in Database Security and Auditing Software (using both) --> Open-Source: PostgreSQL Proprietary: Oracle (OR OTHER) NOTE: much more emphasis on multi-model database management systems NOTE: students will create their own (Oracle) database, including tablespaces, user accounts, views, indexes, and other objects necessary to support an application. They will use this database for the duration of the class and complete a number of exercises using this database. There will be PostgreSQL open source counterpart to mirror all proprietary activities. Course Assessment --> Attendance & Participation Tasks from prerequisite Class Contribution, Exercises and Solutions for current course Database Lab security Projects & Reports Midterm Final Project Course Outline --> Introduction: Security issues faced by enterprises Installing a typical database product Security architecture Operating system security principles Administration of users Profiles, password policies, privileges and roles Database application security models Encryptions and Antimalware Database auditing models Application data auditing Practices of database auditing Prerequisite: Introduction to Databases Computer Science Modelling & Simulation Fundamentals and techniques for designing and using simulation, modelling, and optimization algorithms with applications in system performance modelling, business infrastructure modelling, distributed & parallel computing, social sciences, natural sciences. An introduction to advanced complex systems models. Learning objectives for the course include giving students the knowledge and skills to (1) formulate application domain problems suitable for solution using M&S (2) create efficient simulation software in a high-level programming language, (3) use this software to address application domain problems (4) demonstrate skills in working in interdisciplinary teams. M&S projects often involve teams. This course focuses on creating simulation models using general-purpose programming languages. Introduce computer simulation technologies and techniques, providing the foundations for the student to understand computer simulation needs, and to implement and test a variety of simulation and data analysis libraries and programs. This course focuses on what is needed to build simulation software environments, and not just building simulations using pre-existing packages. They will cover the following: 1.Basic Model Forms 2.Basic Simulation Approaches 3.Handling Stepped and Event-based Time in Simulations 4.Discrete versus Continuous Modelling 5.Numerical Techniques 6.Sources and Propagation of Error Breakouts: Participation (Punctuality, Presence and Discussions): (10%) Assignments (15%) Quizzes (15%) Projects 30% 3 Tests: 10% each (30% for all) Course Texts Birta, L.G. and Arbez, G. (2013). Modelling and Simulation: Exploring Dynamical System Behaviour, Springer – Verlag, London Fujimoto, R. M. (2000). Parallel and Distributed Simulation Systems, Wiley, 320 pages Sayama, H. (2015). Introduction to the Modelling and Analysis of Complex systems, Open SUNY Textbooks, 496 pages Course Resources --> Winter Simulation Conference Communications of the ACM Journal of the ACM ACM Transactions on Modelling and Computer Simulation Assignments --> Assignments will reinforce lecture concepts and demonstrate application of programming and critical thinking skills. Collaboration is encouraged, but you must give credit where credit is due. All assignments must be done independently and written (typed) in your own words. Students will also be asked to develop assignments in both C++ and Mathematica. Quizzes -->: Daily quizzes may be used to reinforce concepts, check student comprehension, and initiate discussion. Examinations --> There will three examinations. Projects --> Students will be asked to develop projects in both C++ and Mathematica. All files in submitted project folders are subject to inspection by the instructor. Projects folders are to be submitted electronically. The subject of folders and files must be your last name with first name initial followed by the project subject, course with section, term and year (e.g. "Doe- Project 1- CS ABCD 000- Fall- 20XX"). Course Topics --> Simulation Basics Handling Stepped and Event-based Time in Simulations Discrete versus Continuous Modelling Numerical Techniques Sources and Propagation of Error Dynamical, Finite State, and Complex Model Simulations Graph or Network Transitions Based Simulations Actor Based Simulations Mesh Based Simulations Hybrid Simulations Converting to Parallel and Distributed Simulations Partitioning the Data Partitioning the Algorithms Handling Inter-partition Dependencies Probability and Statistics for Simulations and Analysis Introduction to Queues and Random Noise Random Variates Generation Sensitivity Analysis Simulations Results Analysis and Viewing Tools Display Forms: Tables, Graphs, and Multidimensional Visualization Terminals, X and MS Windows, and Web Interfaces Validation of Model Results Prerequisites: Fundamentals & Procedural Programming with C++; C++ Programming I & II; Numerical Analysis; Discrete Structures; Data Structures; Analysis of Algorithms; Probability & Statistics; Data Programming with Mathematica; Mathematical Statistics PROJECTS OF CONCERN FOR COMPUTER SCIENCE (in “Winter” or “Summer” semesters”) beginning with at least upper sophomore level. Note: Department permission is required where all students must meet a minimum background requirement in mathematics. The department approval requirements for concentration $$A are different from $$B and $$C for obvious reasons; optimal contribution is key. If consensus for project registration exceeds a certain limit, then to have multiple package projects considered. As well, for a package project there’s the possibility of subgroups responsible for certain components. Students are welcomed to repeat projects in the future. There will be a secure database archive for all participants and supervision constituents for respective activity in chronology. Activities will be field classified. FOR ACTIVITIES IN THE “SUMMER” AND WINTER” SESSIONS ALL PARTICIPATING STUDENTS, ASSISTING/ADVISING INSTRUCTORS AND PROFESSORS MUST BE OFFICIALLY RECOGNISED; REQUIRES BOTH CIVILIAN ID AND STUDENT/FACULTY ID FOR CONFIRMATION OF INDIVIDUAL. THERE WILL ALSO BE USE OF IDENTIFICATIONS FOR ACTIVITIES FOR RESPECTIVE SESSION. SECURITY AND NON-PARTICIPATING ADMINISTRATION WILL ONLY IDENTIFY RESPECTIVE ACTIVITY BY IDENTIFICATION CODE. SECURITY AND NON-PARTICIPATING ADMINISTRATION MUST NEVER KNOW WHAT ACTIVITIES IDENTIFICATION CODES IDENTIFY: < Alpha, Alpha, Alpha, Alpha > - < # # # # # > - < session > - < yyyy > Such computer science activities will also warrant criminal background check (CBC) in order to participate. Severely threshold may vary depending on administration. Administrators will provide dated letters of confirmation of thorough CBC to student affairs and other appropriate administration. Such also may include screening that’s parallel to customs & immigration processing where certain levels of criminal history warrants rejection. Email and physical letters with data. Such CBC protocol will not explicitly identify any particular titles or descriptions of any activity, rather, will only convey code as above. It may be the case some activities can be grouped and given a major title together; however, detailed descriptions will be required. Activities repeated can be added to transcripts upon successful completion. Repeated activities later on can be given a designation such as Advance “Name” I, Advance “Name” II. As well, particular repeated activities serve to towards developing true comprehension, competency and professionalism. Capabilities of activity will neither be influenced by local cultural ignorance and stigmas nor by ambiances not of concern to bridge programme. Activity does not encourage intrusive entities due to repulsive cultural habits concerning Trinidad, CC, Africa, Black America and Latin America. Any media developed is not geared to pop culture and minority trends or stereotypes. Activities will be field classified. Particular projects of interest being stationary: A. Computational Software Packages and API development Expected is comprehensive and competent development. In other words would go from analysis, to drawing boxes, to logistics, to builds and tests, to prototypes. Part 1 --> Concerning open source software where enthusiasts can contribute packages primarily towards scientific computation and data (access & manipulation). To decide upon what areas of computation are preference: Geometrical vector spaces & bases with Generalised Gram-Schmidt Function plotting with plot styles Calculus Interpolation Numerical integration/Quadrature Numerical solutions of ODE, PDE Risch’s Algorithm, Risch–Norman algorithm Orthonormal Functions & Polynomials Linear Optimization Nonlinear Optimisation Fourier Approximations Fast Fourier Transformations Spectral Analysis Computational Probability Computational Statistics (includes MLE, MoM, Goodness of fit methods) Regression Analysis Time Series Stochastic Differential Equations Some topics will depend on others. Procedures and functions developed out of the 17 areas generally should be integrable with each other with computations and code functions. Multivariable circumstances must also be considered. Will also institute algorithms for Computer Algebra. Consider parallelization after successful development. Remote access memory usage, power consumption, heat generation will be other elements for evaluation. Open source tools examples of consideration are RStudio and Julia (to avoid encountering legal issues). Namely, design C/C++ packages (thorough programming and testing for speed and robustness with use), then to create an interface package towards platforms such as RStudio or Julia with parallelization. The R environment has devtools to develop packages of interest. To compare with other developed packages of the same purpose (testing for speed and robustness with use). Developed functions should be directly passable to plotting or autonomous plotting without need for organising output data (when relevant). Package likely to be published with author(s) recognition and institution, and contributed to the RStudio or Julia community. Manual(s) must be developed. Rights of intellectual property. Other appropriate departments may assist, where such departments and its participating individuals to be acknowledged. CONCERN: emulator development with GUI Part 2 --> Interest in graphing calculator emulators. Software that is downloadable, say independent of any servers, etc. Concerns a systematic probe of software. --Processing specifications of hardware used by software. Such involves a detailed analysis for of all hardware in function --Interface with PC or Laptop hardware Includes whether emulator computation/processing is more efficient than physical tool. Includes whether emulator energy usage and thermal activity is more efficient. --Computational or Numerical Algorithms used and programmed --The involved GUI programming --System integration codes Part 3 --> After part 2, will pursue software development that extends emulator to preferences and incorporates parallelization in computation towards PC or Laptop. Students can as well have such development (with parallelization) with multicore controller boards (one or multiple in function). Note: initially one will try starting off with the emulator of a basic calculator; graphing calculator activity is mandatory. Issues with energy usage, thermal activity, moisture, electrical interference, etc. CASIO engineering watches (NOT TO SMASH APART) also are of interest. Part 4 (TBA) --> In the future students may develop a prototype computational language. B. Graphical User Interfaces & Touch User Interfaces Expected is comprehensive and competent development. Relating and integrating software computation with interactivity software. In other words would go from analysis, to drawing boxes, to logistics, to builds and tests, to prototypes. Applications for such are very very board. However, ability, practicality and time frame are vital. Areas for interactivity and visual dynamics Bioinformatics Meteorology Oceanography Digital drawing and painting GIS Vendor app Office Common Use Etc., etc., etc. C. IT Inventory Management Resource Custodians must manage and regularly review installed software, and install only software packages required for business purposes. Attackers use and deploy malicious software to gain unauthorized access to systems and sensitive data. When software on a device is not required for business purposes, it unnecessarily introduces potential vulnerabilities and thereby increases the likelihood of compromise. Management Resource Custodians should utilize a process to maintain inventories of installed software packages for all covered devices. Inventories should include, at a minimum, detailed information about the installed software, including the version number and patch level. Resource Custodians should create a list of authorized software for each device type. Authorized software should include only software necessary to meet business needs. Optionally, file integrity checking software could be used to validate with additional assurance that software has not been modified. Inventory should be updated continuously to reflect the latest changes in installed applications. Where continuous updates cannot be reasonably implemented, inventory must be updated at least monthly using an automated process to allow for review and approval of changes per recommendations below. The inventory process should detect and alert the Resource Custodian about unauthorized software packages discovered on a device. Review A process exists for the Resource Custodian to periodically review the list of newly installed or updated software packages at least monthly and reconcile that list against the authorized list of software packages. Approval A process exists for Resource Custodian to approve new or updated software based on business needs. The business need must be construed narrowly such that software must be installed only where necessary for the business purpose or purposes for which the covered data is required. Any unauthorized software must be removed, added to the authorized software list, or approved as an exception. All decisions must be documented. Software Inventory Tools Listed below is a sample list of software tools that may help to gather software inventory data on individual covered devices: Secunia PSI (Microsoft Windows) Apple System Profiler (Mac OS X) cfg2html (*nix) Package management software (RPM, APT, pkg_*, etc.) Where a large number of covered devices require software inventory, data custodians should also explore the centrally managed software inventory solutions. Examples of centrally managed software inventory solution include: Tivoli Endpoint Manager(Microsoft Windows, Mac OS X, and Linux) Casper(Mac OS X devices) Apple Remote Desktop (Mac OS X devices) Spicework (Microsoft Windows, Mac OS X, and Linux devices) Note: hardware counterpart to software inventory management HHS Policy for IT System Inventory: < Management: www.hhs.gov/web/governance/digital-strategy/it-policy-archive/hhs-ocio-policy-for-management-of-the-enterprise-it-system-inventory.html > Note: NIST Special Publication 800-53 Revision 5 (or updated revision) D. Reverse Engineering and Malicious Software Analysis Use of OllyDb, and/or other tools. Such a project demands a network that’s “off the grid”, namely, there’s neither physical integration nor E-M interactions with any other institution operations networks. This project will allow students to analyse code sections towards understanding of the objectives; possibly for students to create their own authentic versions and compare in run types. To develop an understanding of a collection of malicious software with the goal of deducing the hidden intent in each piece of code. The student will collaborate with professionals using reverse engineering tools and techniques to identify software as malicious or not, analyse the subtleties and techniques of each malicious sample, and to gain an understanding of the behavioural aspects of the sample. Students to develop improved tools and techniques for automated and manual analysis. A successful student will gain both breadth and depth of understanding in the latest techniques for analysis and authorship of malicious software. Note: certain electrical engineering students maybe interested. E. VPN Architecture and Development Study of VPN architecture towards construction of an actual VPN network with hardware and networks. To then be compared with Open VPN, SoftEther VPN, (economic) commercial VPN, etc. Seek administration permission to participate. 1. Components rchitecture 2. Conceptual procedures and Logistics 3. Labs -Simulator for VPN CyberCIEGE -http://www.sis.pitt.edu/jjoshi/courses/IS2621/Lab2.pdf -https://booksite.elsevier.com/9780123850591/Lab_Manual/Lab_13.pdf 4. Configuring and Testing the VPN Client 5. VPN-Based penetration testing 6. When you have a VPN active, why do manga sites prohibit access? How do they know? 7. Make sense of the following https://www.darkoperator.com/blog/2017/2/5/home-lab-vpn 8. How can your system be relevant/practical with clouds or cluseters or databases? 9. Security and encryption dilemmas F. Building a Server with “Old” Hard Drives, Motherboards, CPUs (1) History and purpose of Network-attached Storage (NAS) (2) Understanding the difference between NAS (pursued), DAS and SAN (3) Arrangement possibilities: logical, redundant storage containers or RAID (#) (4) Knowledge of the most abundant and frequent errors and failures with NAS, and the technical solutions. (5) PATA and SATA concerns and understanding MTBF (6) Network architecture (7) Network file sharing protocols to understand, conference on and implement: NFS, SMB/CIFB, NCP, HTTP & HTTPS, rsync, FTP & SFTP, UPnP. (8) Open source server implementations (Linux/Unix, Ubuntu) (9) Keep in mind that concerns and interests revolve around UNIX/Linux or Ubuntu (10) Will like to establish relation between drives speed, speed of network card and number of clients (11) Throughout the 10 steps students must identify security vulnerabilities and resolutions towards pending server construction. Development Phase 1: The 8-CORe Raspberry Pi Killer: ODROID XU4Q with CloudShell2 Case – assembly - YOUTUBE Here there’s no necessary requirement of implementing such an ODROID model, rather one that’s comparable. Subjects (1) through (11) to be considerably relevant. Outstanding interests and concerns: test bed for server activities, redundancy and other arrangement possibilities, performance, data security, and separate bot drive-separate data drive contemplation. Development Phase 2: Extensive development of NAS (How To Build a Server: Getting Started - YouTube) Subjects (1) through (11) to be considerably relevant. Rack and/or desktop casing Outstanding interests and concerns: test bed for server activities, redundancy and other arrangement possibilities, performance, data security & encryption, and separate bot drive-separate data drive contemplation. More exhibitions of feasibility: Given link below may be observed as not financially feasible. An intensive recycling programme instituted where found components are comparable or better would serve well. Cooler system must be integrated (cooler tubes and brushless 3omm to 92mm fans). https://www.instructables.com/id/How-to-Build-a-Dedicated-Web-Server/ More explicit demonstrations (from danscourses YouTube website): How to build a server Computer: Part 1 Installing the motherboard – YouTube How to build a server Computer: Part 2 Installing the power supply – YouTube How to build a server Computer: Part 3 Installing the drives – YouTube How to build a server Computer: Part 4 Installing the CPUs – YouTube How to build a server Computer: Part 5 Installing the CPU Cooling Units How to build a server Computer: Part 6 Installing the RAM memory How to build a server Computer: Part 7 connecting power, reset switches, and HDs. Development Phase 3: If an economical commercial NAS is acquirable, then analysis of specs, constitution, arrangement and performance compared to built NAS (both phase 1 and 2). Development of a sustainable resource: If all goes well, such NAS can be implemented with operations, projects and research towards Applied Mathematics, Natural Sciences, Applied Sciences, Engineering, Business, Economics, Political Science and Public Administration. An intensive recycling initiative with “old” hard drives is crucial. SAN-NAS hybrid: Extension of (1) through (11) and phases (2) and (3) to provide all capabilities of a hybrid structure. FURTHER ADVANCEMENT --> --Extending prirdevelopments to multiple server constructs integrated --Single-rack data center (and possibly up to 3 racks) NOTE: we are interested in meaningful and practical applications for racks that serve long term interests. Key hardware components to concern phase 3: routers, switches, firewalls, storage systems, servers, and application-delivery controllers. Networking designing with hardware (includes cooling mechanisms), software, routing, protocols, security, power requirements, etc. etc, etc., etc. Note: keeping note or logs will be very important in all phases for recollection, review and backtracking. Being chintzy in character, for all phases expect to receive hardware donations or resorting to salvaging efforts. Cloud Data Center Development Lab Project --> Activity concerns why cloud networking is a strong market (related hardware costs, space, and staff reduction). Will develop a data center in the cloud. Security development will be one of the major priorities. Before development of the cloud data center with a proprietary vendor we will build intelligence with investigation from use of the following software (one or two): MDCSim BigHouse DCNSim Greencloud OMNeT++ with INET framework Term Project (not limited to the following examples) --> BlueFlame RDMA Benchmark NAPI for RDMA P4 Rate-limiting and sketches Multi-tenant RCP Virtual switch in P4 NOTE: assignments will have much variation abilities to deter a destructive culture development of copy-and-paste, grift and entitlement. Projects will not simply be a “stroll in the park”. G. Database Activities Places for strong skills development in database management systems (DBMS) can be quite exclusive for whatever socioeconomic reasons. Will identify various databases with data available to the public that the common individual takes for granted or shun as gaudy fodder. Knowledge and skills gained with public data can translate to development with any private database in future careers. Instructors should be able to assist with brainstorming, development, logistics, construction and possible data analysis. NOTE: In this activity you will only be as good as how serious and dedicated you are. Critical topics with need and practical and hands-on engagement --> -APIs and data -Introspecting and querying -Data structure and data quality -Developed databases in proprietary software versus DBMS Difference, commonalities and possible integration for practical purpose -Constructing multipurpose long term DBMS based on API feeds with parameters of interest with introspection and querying abilities? -Database Administration/Management -Transfers to Excel, Access and PDF (or Google Sheets format) -Transferring to the R environment and use. Use of Sparklyr -Transferring to the Mathematica environment and use. Applications --> -Identifying types of Metadata and uses -Organisational design structure and other aspects of HR -Demography -National, sovereign, international governance agencies & NGOs How are such databases relevant and useful to your DBMS? Analytics of consideration that may become meaningful --> -Data Analysis Database Management Systems and interfaces of interest are --> Primary: PostgreSQL (then integrability with R + Sparklyr, Mathematica) Secondary: AsterixDB, SQLite, MariaDB Development towards decision making in business, various industries, governance; keeping in mind that data is always expanding and evolving. As “big data” activity progresses parameters will become more specific and abundant. Categorical data must be sensible towards conclusions. Serves well for business and actuarial constituents. In public administration many will assume that big data tools are monstrously expensive, however, such mentioned above platforms are integrable with massive data, granted that appropriate projects or uses are chosen, necessarily with the following stipulations: Appropriate administrative protocols Constituents with proper security clearance, verified training & skills Responsible and constructive use Security measures are in place with updating Antimalware tools with constant updating Firewalls Secured & encrypted LANs (constantly changing security passwords, etc) Secured & hidden WiFi (constantly changing security passwords, etc) Devices are password secured; idle states to resubmitt security passwords Multifactor authentication Security access for altering documentation Disaster Recovery & Backups DR and backups exist independently concerning intrusions or attacks Immunity to systematic black swans DRs & Backups have scheduled updating if not manually by individual Will then pursue blockchain immersion and compare advantages and disadvantages to RDBMS At designated times of the activity students to give live demonstrations concerning topics and projects of interest. PART B Blockchain development analogy to all prior; implies comparative assessment with RDBMS throughout development H. Cybersecurity Foundation PART A 1. Out of software mentioned students can develop models to represent facilities and the operating networks for analysis. There must be ability to identify possible vulnerabilities and lack of modernization. Such elements include: Firewalls & applications permissions Network settings (LAN and Wifi) Access protocols Bandwidth selections (in versus out, etc.) Malware, antivirus, spyware Network encryptions Document encryptions & tracking, blockchain VPNs Then, concerning all such details students will be given varying drills with real networks where they are responsible for treating all such; can include security protocols for faxes, phones, and printers. Security performance versus affordability versus networks speeds is an infamous “realm of existence”. 2. Framework for Improving Critical Infrastructure Cyber Security-- Will have a general view then comparative view of cyber security standards among foreign and international firms, namely, NIST, ISO, IEC, IEEE and ITU. Note: for each organisation or agency standards are subject to change. 3. To develop understanding of what social policies are to be in place to not draw reckless attention to networks and data despite the application of “security hardening”. For business and public administration, structure and policies for public exposure and network abuse in facilities may have various levels of complexity in regard to optimal function, competition, transaction costs, etc. Yet, maintaining equality and respect for all “team members” with appropriate level(s) of security clearance for network in question. Open to constituents of other academic fields. PART B It’s imperative that students successfully complete part A. Such manual or direct skills developed prior will be highly influential towards fully understanding the operations of NAC. Network Access Control (NAC) A solution that uses a set of protocols to define and implement a policy that describes how to secure access to network nodes by devices when they initially attempt to access the network. NAC might integrate the automatic remediation process (fixing non-compliant nodes before allowing access) into the network systems, allowing the network infrastructure such as routers, switches and firewalls to work together with back office servers and end user computing equipment to ensure the information system is operating securely before interoperability is allowed. A basic form of NAC is the 802.1x standard, however, there may be more modern versions. NAC aims to do exactly what the name implies—control access to a network with policies, including pre-admission endpoint security policy checks and post-admission controls over where users and devices can go on a network and what they can do. Goals of NAC Because NAC represents an emerging category of security products its definition is both evolving and controversial. The overarching goals of the concept can be distilled as:· Mitigation of zero-day attacks Authorization, Authentication and Accounting of network connections. Encryption of traffic to the wireless and wired network using protocols for 802.1X such as EAP-TLS, EAP-PEAP or EAP-MSCHAP Role-based controls of user, device, application or security posture post authentication. Automation with other tools to define network role based on other information such as known vulnerabilities, jailbreak status etc. The main benefit of NAC solutions is to prevent end-stations that lack antivirus, patches, or host intrusion prevention software from accessing the network and placing other computers at risk of cross-contamination of computer worms Policy enforcement NAC solutions allow network operators to define policies, such as the types of computers or roles of users allowed to access areas of the network, and enforce them in switches, routers, and network middleboxes. Identity and access managemento Where conventional IP networks enforce access policies in terms of IP addresses. NAC environments attempt to do so based on authenticated user identities, at least for user end-stations such as laptops and desktop computers. Some conventional NACs (but TNC may be most educating towards self-sufficiency): Microsoft - Network access Protection Cisco - Network Administration Control Trusted Network Connect There must be ability to update a NAC to modern circumstances and definitions. Other possible interest in activity (time permitting) may include: IF-MAP Trusted Computing organisation I. Topology, Taxonomy and Operations in Cyber Security Open to EE students. Grids of consideration: LAN, WAN, Wifi Would like experimental grids to carry out experiments. NOTE: designed grids must have no communications to any other network outside of activity. PHASE 1: Development of a Cyber Attack Simulator for Network Modelling and Cyber Security Analysis 1. Background Computer Networks Devices Details Network Packets Exploits Development of Intrusion Dtetection Systems 2. Literature Review Modelling & Classification of Cyber Attacks Simulation of Computer Networks Information Fusion Techniques Applied to the Cyber Domain Object-Orientated Simulation Modelling Surveying different types of Cyber Attack simulators 3. Simulation Model Structure Modelling Intentions and model overview Java (or whatever background) Package Structure Simulation Package Network Package Attack Package Visual Package 4. Network Methodology Network Architecture Machines Connectivity Sensors Virtual Terrain 5. Attack Simulation Methodology Modelling Traffic Available Actions Attack Scenario Attacks Event Handling Scenario Results Exporting Attack Scenarios 6. Evaluation of Simulation Model Verification of Network Model Verification of Attack Simulation Validation of Attacks and Alerts Model Capabilities Model Limitations Applications 7. Conclusions and Future Work PHASE 2: Valeur, F. et al. A Comprehensive Approach to Intrusion Detection Alert Correlation. IEEE TRransactions on Depndable and Secure Computing, Vol. 1, No. 3, July-September 2004 Note: integrating more modern along with predecessors may be possible. PHASE 3: Cyber Attack Tools Consideration of comparing open source tools with proprietary Such a project demands a network that’s “off the grid”, namely, there’s neither physical integration nor WiF interactions with any other institution operations networks. Such a project requires a decent background in Computer Networks (prerequisites of this background will be crucial). Real and explicit engagement activities. --Signature based malware detection methods (PC and Linux) --Malware Detection by Static Analysis; useless when a malware is encrypted or packed --Malware Detection by Dynamic Analysis --Shijoa, P., V., A. Salimb, A., Integrated Static and Dynamic Analysis for Malware Detection, Procedia Computer Science 46 ( 2015 ) 804 – 811 --Metamorphic Malware (anatomy and their tenacity, say, they mutate their code in each generation by employing code obfuscation techniques to thwart detection) --Choudhary, S., P., Vidyarthi, M., D., A Simple Method for Detection of Metamorphic Malware Using Dynamic Analysis and Text Mining, Procedia Computer Science 54 (2015 ) 265 – 270 --Mahawer, D., K., and Nagaraju, A., Metamorphic Malware Detection Using Base Malware Identification Approach, Security Comm. Networks 2014; 7: 1719–1733 --Comparing developed structures and methods with open source and (economical) commercial malware detection --How to integrate into LAN/WAN and Mobile Networks and reducing false alarms. PHASE 4: Means to implement --> Cheng, Y. , Deng, J. , Li, J. , DeLoach, S. , Singhal, A. and Ou, X. (2014), Metrics of Security, Cyber Defense and Situational Awareness, Springer, Dusseldorf J. Malware Reverse Engineering Note: advance development and extensions of tasks from course. K. Developing an Operating System (TBA) Will be mainly towards open source applications. Expected is comprehensive and competent development. In other words would go from analysis, to drawing boxes, to logistics, to builds and tests, to prototypes. L. Machine Learning towards various vehicles Activity isn’t necessarily dependent on the Machine Learning course. Concerns usage out of the following: <Linux>; <Shogun> ; <TensorFlow + RLLib: C++> ; <Microsoft AirSim>; <ROS software> Such isn’t to replace Feedback Control or Automatic Control. Such concerns designed controllers and embedded systems with machine learning & AI. There must be determination on how integrable this activity will be with ME students of Systems Control and Computer Engineering students. Interest in determining the integration (or lack there of) between designed controllers, embedded systems and AI from Machine Learning. Will try to pursue development between Machine learning/AI, Embedded Systems and Designed controllers, say conceptual development, logistics, programming, testing, integration, etc. Open to ME Systems Control and Computer Engineering constituents. M. Mobile Application Development Further details will be explain for this activity N. Service Provision Software Development There are numerous software applied in public sectors and in the private sector to service customers or for other commerce developments, shipping, eliminating mail-in services, etc., etc. Will study various types and build emulating prototypes based on interests. Expected is comprehensive and competent development. In other words would go from analysis, to drawing boxes, to logistics, to builds and tests, to prototypes. Note: not interested in highly personal data; serves only academic development. O. Applied Algorithms This activity has neither influence nor dependency on the Analysis of Algorithms course, however the course that is Data Structures II as a prerequisite will be mandatory. Concerning the customary topics found in a algorithms course will try to situate them to relevant, realistic and practical applications to the best of ability. Such is a means to “buy into what one is selling” for sustainable foundation, confidence, and a progressive mindset with algorithms and one’s future. Expected is comprehensive and competent development. In other words would go from analysis, to drawing boxes, to logistics, to builds and tests, to prototypes. Examples are “Spell Checker” and Grammar Correction similar to that of Microsoft Word. Another example may be dynamic web pages and identifying corrections to be made. One can work on old application software that aren’t maintained any longer and so forth. Another example, “Highlight-copy-paste” where word processor or environment recognises text with recognition of theme fonts, letter sizes, colour, italic, bold, etc, etc.. Not necessarily aiming for development of a word processor, however, if feasible then that’s okay. “Highlight-search web” is another possibility. There are various algorithms many take for granted that are “essential” to daily function. Students should also be able to develop applications or whatever concerning their interests, rather than just blatant plagiarism/exact replications. NOTE: applications range is extremely broad. P. Audio and Video Content Authentication Will make use of media confirmed to be tampered with or falsified, where one will make use of various forensic skills and applying algorithms; compared to “confirmed” untampered media. Apart from customary skills, understanding algorithms before applying them exhibits competency and responsibility. As well, knowing how to integrate and implement algorithms is also crucial. Such operations serve to applicably reinforce and vindicate what is learnt, and to determine to extend of the usefulness of such skills and algorithms. Without interaction all is fodder, and one subjugates themselves to relevance of others. NOTE: the given guides are limited concerning audio treatment, and likely such guides may not be the most robust, modern or internationally accepted. Furthermore, one must comprehend the extent of usefulness with blockchain concerning encryptions, tracking and preserving authenticity of media. Will also have concerns for AI, particular algorithms and common skills to treat “deep fake” videos which likely will be out of the range of such given guides --> Ho, A. (2015). Forensic Authentication of Digital Audio and Video Files. In Handbook of Digital Forensics of Multimedia Data and Devices (pp. 133-181). Chichester, UK: John Wiley & Sons. Upadhyay, S. and Singh, S. K. Video Authentication- An Overview. International Journal of Computer Science & Engineering Survey (IJCSES) Vol.2, No.4, November 2011 Richao, C., Gaobo, Y. and Ningbo, Z. Detection of object-based manipulation by the statistical features of object contour. Forensic Science International 236 (2014) 164–169 Yu, L. et al. Exposing frame deletion by detecting abrupt changes in video streams. Neurocomputing 205 (2016) 84 – 91 Song, J. et al. Integrity verification of the ordered data structures in manipulated video content. Digital Investigation 18 (2016) 1 – 7 Singh, R. D. and Aggarwhal, N. Detection of upscale-crop and splicing for digital video authentication. Digital Investigation 21 (2017) 31 - 52 Singh, R.D., Aggarwal, N. Video content authentication techniques: a comprehensive survey. Multimedia Systems 24, 211–240 (2018) Q. Intelligence and Innovation Initiative for Decision-Making with Transmission Vectors Article of interest: Siraj, A. S. et al. (2018). Spatiotemporal Incidence of Zika and Associated Environmental Drivers for the 2015-2016 Epidemic in Colombia. Scientific Data, 5, 180073. Abstract of journal article: Despite a long history of mosquito-borne virus epidemics in the Americas, the impact of the Zika virus (ZIKV) epidemic of 2015–2016 was unexpected. The need for scientifically informed decision-making is driving research to understand the emergence and spread of ZIKV. To support that research, we assembled a data set of key covariates for modelling ZIKV transmission dynamics in Colombia, where ZIKV transmission was widespread and the government made incidence data publicly available. On a weekly basis between January 1, 2014 and October 1, 2016 at three administrative levels, we collated spatiotemporal Zika incidence data, nine environmental variables, and demographic data into a single downloadable database. These new datasets and those we identified, processed, and assembled at comparable spatial and temporal resolutions will save future researchers considerable time and effort in performing these data processing steps, enabling them to focus instead on extracting epidemiological insights from this important data set. Similar approaches could prove useful for filling data gaps to enable epidemiological analyses of future disease emergence events. Interest with ambiances of concern: Applying the assumption that a Zika vector is not encouraged in the ambiances of interest, instead such a journal article can be used to model disease vectors or infection vectors or infestation vectors in the ambiances of interest. Many other viruses (though likely not as formidable as ZIKA) are known to spread through mosquito activity, and there’s the constant threat of another mealybug infestation. The given journal will be analysed and used as a blueprint to build a data analysis solution to model a decision-making process for contagion or infestations of interest. However, students will be engaged in identifying economical means and open source tools as substitutes for the various products and proprietary tools applied in the journal article. Direct development of data acquisition tools like always will be required; test of such with trials will also be likely to establish credibility. Of consequence, some phases of development with be in the field (exposed to the elements). For the case of mealy bugs, such may or may not be more complicated since one must identify transmission resulting from human activity (negligence, ignorance, etc.). Mathematica and RStudio can be incorporated with other alternative tools and sources as substitutes. The system developed likely will be integrated to an alarming system for computer and mobile devices. Activity is open to public administration constituents, operational research constituents, industrial engineering constituents, meteorology constituents, geology constituents and biology constituents. R. Diseases Surveillance System Sources of Interest --> 1A. Haghiri, H., Rabiei, R., Hosseini, A., Moghaddasi, H., & Asadi, F. (2019). Notifiable Diseases Surveillance System with a Data Architecture Approach: a Systematic Review. Acta Informatica Medica: AIM: journal of the Society for Medical Informatics of Bosnia & Herzegovina: casopis Drustva za medicinsku informatiku BiH, 27(4), 268–277. 2A. JHU Applied Physics Laboratory – Inside ESSENCE: Providing early detection of epidemics – YouTube << https://www.youtube.com/watch?v=4AGPYmXcnZQ >> 2B. JHU Applied Physics Laboratory – EESENCE Early Notification of Epidemics – YouTube << https://www.youtube.com/watch?v=uxP6bGUhZ1c >> Based on 1 and 2 will like to develop a prototype disease surveillance system. However, concerning the first source one would like to determine whether there are alternatives to the “data architecture approach”, and whether they are more predominant or popular. Nevertheless, the approach conveyed in the given journal article appears to be quite feasible to develop concerning APIs, algorithm instructions and what not. Source (2) provides socially informative ideas but really isn’t much. Is ESSENCE based on the “data architecture approach”? It may also be the case that data constructed from sources may not be exactly to preference, hence one may have to write “data structure” instructions to acquire preference. How does one know they’re getting the right type of they want? First attempt at developing such a system may not go far into successful development as one would like, However, your level of progress will be a stepping stone to be better and advance further. As well, such activity “forces” one to do research and become knowledgeable or accessible to things never imagined before. It’s best that one keeps record of development in stages so they can backtrack and remain fresh with their own labour. Some of the links in the following sites may be helpful with ideas: << https://www.cdc.gov/csels/dhis/ >> << https://wonder.cdc.gov >> Consider as well the “Topics” and “A – Z Index” links in the latter. S. Cluster Development with Parallel Computing ---Will begin with common microcontrollers. Architecture, logistics, routines, performance modelling, run time modeling. Towards meaningful applied tasks. Will first immerse with multicore capabilities of microcontrollers with meaningful applied tasks. ---Following, multicore microcontrollers will constitute a cluster. Architecture, logistics, routines, performance modelling, run time modeling. Towards meaninigful applied tasks. ---Will then pursue cluster development with real conventional systems, multi-core mother boards in clusters. Architecture, logistics, routines, performance modelling, run time modeling. Towards meaningful applied tasks ---Parallel Computing For Neural Networks (when ready) http://meseec.ce.rit.edu/756-projects/spring2013/1-4.pdf NOTE: there will be actual lab operations to perform meaningful applications. References: [1] Kwabena Boahen. Neuromorphic microchips. Scientific American, 292(5):56–63, 2005. [2] Nordström, T. and B. Svensson, “Using and designing massively parallel computers for artificial neural networks,” Journal of Parallel and Distributed Computing, vol. 14, no. 3, pp. 260-285, 1992. [3] Thulasiram, R.K.; Rahman, R.M.; Thulasiraman, P., "Neural network training algorithms on parallel architectures for finance applications," Parallel Processing Workshops, 2003. Proceedings. 2003 International Conference on , vol., no., pp.236,243, 6-9 Oct. 2003 [4] Seiffert, Udo. "Artificial neural networks on massively parallel computer hardware." Neurocomputing 57 (2004): 135-150. [5] Srinivasan, N.; Vaidehi, V., "Cluster computing for neural network based anomaly detection," Networks, 2005. Jointly held with the 2005 IEEE 7th Malaysia International Conference on Communication., 2005 13th IEEE International Conference on , vol.1, no., pp.5 pp.,, 0-0 0 [6] A. Margaris, E. Kotsialos, and M. Roumeliotis, “Simulating Parallel Neural Networks In Distributed Computing Systems,” 2nd International Conference “From Scientific Computing to Computational Engineering”, pp. 5–8, 2006.

T. Data Processing Will have extensive development with the Apache framework. Will develop constructive and practical integration of the Apache tools, but first we must definitively decide what can we do with all that stuff that’s highly useful and economic with potentially long-term meaningfulness. Really real projects. We’re not just going to draw all sorts of concept charts/boxes, utter all sorts of taboo vocabulary and call that innovation. We want really real projects: Conceptual development Hardware tree Networks Apache logistics Routines, etc., etc. Building the system, implementation and processing Apache --> Hadhoop Spark Kafka Mesos Beam Flink Sparklyr --> What can really please a crowd is strong data analytics with fancy visuals. Sparklyr can provide just that. Other tools of interest --> Rocks Cluster Distribution ProActive Microsoft Machine Learning Server Configuring local and R packages repository for offline IOP R4ML” (associated to IBM® Open Platform with Apache Spark and Apache Hadoop), and analysing big data with RM4L. U. Air Traffic Flow Management Open to Operations Management, Electrical Engineering and Computer Science constituents. Available tools of interest : 1. Opensky Network (https://opensky-network.org) for access to databases and live feeds One will like to make use of the real time data and history resource in a manner being subjugated to introspection and queries into computational environments, GIS and GUI environments. 2. Flightradar24 One will like to make use of the real time data and history resource in a manner being subjugated to introspection and queries into computational environments, GIS and GUI environments. 3. Kaggle 4. FlightAware (flightaware.com) One can also build modules for tracking: https://flightaware.com/adsb/piaware/ 5. NASA Software SMS/ SDSS STBO Data Fuser MFSim – Multi-fidelity Simulation Airspace Concepts Evaluation System (ACES) Phase 1-- Will be well immersed in active operations out of the mentioned five tools applied to air traffic control. What can you do? Phase 2-- Sridhar, B., Grabbe, S. R., and Mukherjee, A., Modelling and Optimization in Traffic Flow Management, Proceedings of the IEEE, Vol. 96, No. 12, December 2008 The focus of this paper is to analyse, and well establish the logistics towards optimisation in TFM. Can the mentioned tools facilitate some level of a TFM system with consideration of economic hardware? What is needed, and how to integrate all to develop a functioning system? Practical and tangible things will be done with such mentioned tools relevant to the article. Phase 3-- Shridhar, B. et al. Modeling and Simulation of the Impact of Air Traffic Operations on the Environment. American Institute of Aeronautics and Astronautics: https://aviationsystems.arc.nasa.gov/publications/2011/mst11_sridhar.pdf Future ATM Concepts Evaluation Tool (FACET) may not be available to all for use (or may be defunct). We are not concerned with acquiring the original FACET, rather, to comprehend FACET towards analysis, technologies, engineering and logistics to be applied. We are in pursuit of developing a generic active system in operation. The given articles provide useful information concerning the structure and uses of FACET. Based on such following articles one can possibly acquire various hardware, network technologies, software (includes operational algorithms, packages and GUIs) with the ability to incorporate various data for a respective ambiance or international, with weather influences. “Air traffic control centre”, and establish the network technologies (hardware, software, data sources, communication and flow of organised data). Will then revisit phase 2. Article in phase 2 may only be an optimisation pursuit without concern for natural environmental factors and fuel consumption. Possible recommended flight paths acquired in phase may be considerably incompatible with what is accomplished in this phase. PART A (Aircraft Information) Type, Speed, Altitude, Mass Data’s structure and form must be useful for pursuit PART B (development of SAGE) Supporting literature and data -Kim, B., Feming, G. et al (2005). System for Assessing Aviation’s Global Emissions (SAGE), Version 1.5, Technical Manual. Federal Aviation Administration: https://www.faa.gov/about/office_org/headquarters_offices/apl/research/models/sage/media/FAA-EE-2005-01_SAGE-Technical-Manual.pdf -Malwitz, A., Kim, B. et al (2005). System for assessing Aviation’s Global Emissions (SAGE), Version 1.5, Validation Assessment, Model Assumptions and Uncertainties. Federal Aviation Administration: https://www.faa.gov/about/office_org/headquarters_offices/apl/research/models/sage/media/FAA-EE-2005-03_SAGE-Validation.pdf -One can use SAGE inventory Data from the following source to confirm accuracy of programming development: https://www.faa.gov/about/office_org/headquarters_offices/apl/research/models/sage/ Note: for phases 2 and 3 any structure programming can be C++ or Mathematica. V. Developing Generic Models and Simulators Likely some similar features to activity (U) Expected is comprehensive and competent development. In other words would go from analysis, to drawing boxes, to logistics, to builds and tests, to prototypes. Means to compare with incumbent tool, or proprietary tools or open source tools that are premier. PART A (Environment Protection) Developing US EPA models and simulators with GUIs in generic fashion Ecological Models Environmental Models Risk/Hazard Models Note: will require the (published) associated academic literature for comprehension, analyses, developing logistics and pursuit of programming builds. Will also like to develop dynamical parameters/inputs. PART B (Climate Change) Integrated Assessment Models (IAM). Similar to part A. Check Oceanography & Meteorology post PART C (Astrophysics) Astrophysics Thermochemical Equilibrium Codes Blecic, J. and Bowman, M. O. (2016). TEA: A Code Calculating Thermochemical Equilibrium Abundances. The Astrophysical Journal Supplement Series, 225:4 (14pp) PART D (Aerospace/Mechanical Engineering) and Aerospace/Mechanical Engineering Combustion Codes Codes and system to develop: The ICT-Thermodynamic code Colvin, A., Gierczak, C., Siegl, W., & Butler, J. (1997). A Software Program for Carrying Out Multi-Purpose Exhaust Composition Calculations. SAE Transactions, 106, 252-260. Note: may need to extend to include NO and NO2 Will also like to develop dynamical parameters/inputs. NOTE: GEOPHYSICS, CFD, STRUCTURAL ANALYSIS INTERESTS ARE ALSO WELCOMED W. N-Body Simulations (check Physics post)

X. Maps, direction and schedules Expected is comprehensive and competent development. In other words would go from analysis, to drawing boxes, to logistics, to builds and tests, to prototypes. Part A Public Transportation arrival times notification Observe various public metro bus transportation schedules where each route is unique and with unique schedule. One will like to develop an arrival indicator application. Knowing all stops is vital. GPS development will be required in regard to each stop or station. What networking/communications hardware and software will be required to create a competent system? One may use common vehicles instead (even bicycles) to test a prototype system. Particular notifications at each terminal/stop/station: Time to Arrival (hr : min) green Recent Departure (hr : min) red Next Arrival (hr : min) yellow/amber Note “Time to arrival” computations and “Next arrival” computations may be much more technical than perceived. Part B The well renowned Google Maps application. Will like to investigate the GPS and algorithms for directions by: Mass transit Public transportation Pedestrian Cycling Taxi Depending on ambiance, concerning public transportation there can possible be different combinations (involving, different buses, trains, and possibly ferries). Application is also capable of directions for intercontinental travel, among provinces and so forth. In addition, means to incorporate part A. Algorithms may be more technical than initial perception concerning schedules, tracking and types of optimisation. Activity open to EE majors, Operations Management/Operational Research and Computer Science constituents. Y. Separation of Sounds in Audio Comparative Analysis of chosen methods. Methods expressed are just examples, hence not confined to them. Will implement them and compare/contrast by various means/standards. Not only interested in separation of vocals. -Z. Rafii and B. Pardo, "A Simple Music/Voice Separation Method Based on the Extraction of the Repeating Musical sStructure," 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2011, pages 221-224 -Types of Neural Networks Techniques -Mavaddati, S. (2020). A Novel Singing Voice Separation Method Based on a Learnable Decomposition Technique. Circuits, Systems, and Signal Processing, Volume 39, Issue 7, Pages 3652 - 3681 -Various other types of methods out there Z. Decentralized and Centralized Multi-Robot Motion Planning (incomplete) --ORCA, a state-of-the-art decentralized approach Article: COMING SOON --GLAS: Global-to-Local Safe Autonomy Synthesis for Multi-Robot Motion Planning with End-to-End Learning Rivière, B., Hönig, W., Yue, Y. and Chung, S. (2020). GLAS: Global-to-Local Safe Autonomy Synthesis for Multi-Robot Motion Planning With End-to-End Learning. IEEE Robotics and Automation Letters, vol. 5, no. 3, pp. 4249-4256 One of the major challenges with becoming more user friendly is the ability to apply practicaly, fluidly and competently with vehicles that buzz around the place. Z1.Machine Learning with Embedded Systems Analysis, logistics and hands-on development for ML with microcontrollers and embedded systems. Literature guides of interest: J. Lee, M. Stanley, A. Spanias and C. Tepedelenlioglu, "Integrating Machine Learning in Embedded Sensor Systems for Internet-of-Things Applications," 2016 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), Limassol, 2016, pp. 290-294. AI on Microcontrollers uTensor brings Deep-Learning to MCUs – YouTube: https://www.youtube.com/watch?v=PBzbs4HoqHs Why Machine Learning on Microcontrollers? – Neil Tan – The Things Conference 2019 – YouTube: https://www.youtube.com/watch?v=ccTsOa6GXJs Haigh, K. Z. et al (2015). Machine Learning for Embedded Systems: A Case Study. Raytheon BBN Technologies, BBN Report – 8571: http://www.cs.cmu.edu/afs/cs/usr/khaigh/www/papers/2015-HaighTechReport-Embedded.pdf Embedded Processing with Texas Instruments --> TIDEP – 01004: Machine Learning Inference for Embedded Applications Reference Design: https://www.ti.com/tool/TIDEP-01004 Machine Learning on FPGAs: Neural Networks – YouTube --> https://www.youtube.com/watch?v=3iCifD8gZ0Q Note: concerning microcontrollers with ML, other firms such as STMicroelectronics, Adafruit, etc., etc., etc. are prevalent. List of other activities open to Computer Science students-- Aerospace Engineering: D, H, K, P, T, U, W Mechanical Engineering: A, C, E, F, M, N, P, T, AA6 Industrial Engineering: A, C, D, H, K, N, P NOTE: for engineering activities check engineering post. Physics: N-body simulations will also be of great interest. Physics: assistance to Physics constituents in Foundations in Particle Physics with Geant4 simulations will also be of great interest. Plasma Propulsion as well. NOTE: for physics activities check physics post. SOFTWARE & TOOLS (to complement courses and activities) Software of interest for Computer Networks -->: -- SGAMToolbox, RAMI 4.0 Toolbox -- https://code.nsa.gov -- OllyDbg, WinDbg -- GNU debugger --Netlab --VMWare Workstation (or whatever choice) --GHIDRA --IDA --Binary Ninja Network simulators --> -- Marionnet network simulator -- REAL network simulator -- OMNeT++ with INET framework OS Security studies and Network Probing --> -- https://code.nsa.gov -- Wireshark -- Nmap -- Kali Linux -- nmap -- Wireshark -- Node Zero -- Parrrot Security OS -- Network Security toolkit -- BlackArch Linux -- BlackBox -- OpenVAS -- https://medium.com/oniverse/best-linux-os-for-hackers-and-network-security-professionals-82e3c24f84d0 For assembly language acquisition --> -- Interactive Disassembler (IDA) -- ns-3 Network Simulator

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Economics, Political Science, Public Administration, Business

ECONOMICS The economics curriculum provides a foundation for real world adaptability. The programme functions as economics being self-sustainable. Ability is more important than being a con artist with curves/lines and synthetic problems. Yes, you do have options. Ambiance, the world, knowledge, skills and accountability. Economics curriculum: --Communication --> Scientific Writing I & II --Mandatory Courses --> Enterprise Data Analysis I & II (check GFIN); International Financial Statement Analysis I & II (check FIN); Corporate Finance (check FIN); Calculus for Business & Economics I-III; Probability & Statistics B; Mathematical Statistics --Core Courses --> Microeconomics I-II; Introduction to Macroeconomics; Intermediate Macroeconomics; Money & Banking; Macroeconomic Accounting Statistics; Economics of Regulation; Econometrics; Economic Time Series; Public Finance; Sustainability Measures; Empirical International Trade --Mandatory Investment & Instruments Courses --> Theory of Interest for Finance (check COMPUT FIN); Investment & Portfolios in Corporate Finance (check FIN). There are concentration track options for Economics majors. A choice is mandatory. Must choose one of the following tracks: --Option Track 1 --> Microeconomics III; Industrial Organisation; Computational Studies of Mergers & Acquisitions; International Commerce (check FIN); Corporate Valuation (check FIN); Financial Accounting (check FIN) --Option Track 2 --> Microeconomics III; Industrial Organisation; Computational Studies of Mergers & Acquisitions; Optimisation (check Actuarial post); R Analysis (check Actuarial post); Agricultural & Economic Sustainability --Option Track 3 --> Microeconomics III; Industrial Organisation; Computational Studies of Mergers & Acquisitions, Programme Evaluation I & II (check PA), Computational Labour Economics. Note: for Programme Evaluation I & II, economics majors will require Mathematical Statistics or Econometrics course as substitute for Quantitative Analysis in Political Studies I; also must complete Enterprise Data Analysis I & II; Upper Level Standing. --Option Track 4 --> Microeconomics III; Industrial Organisation; Computational Studies of Mergers & Acquisitions; Programme Evaluation I & II (check PA); Agricultural & Economic Sustainability Note: for Programme Evaluation I & II, economics majors will require Mathematical Statistics or Econometrics course as substitute for Quantitative Analysis in Political Studies I; also must complete Enterprise Data Analysis I & II; Upper Level Standing. --Option Track 5 --> International Macroeconomics; Advanced Macroeconomics; Fiscal Administration (check PA); Monetary Theory & Policy; Research Methods in Monetary Policy; Regional Economics NOTE: for Probability & Statistics B, Mathematical Statistics, students should check the actuarial post. Further description of some courses below: Microeconomics I Comprehension of basic modelling and economic interpretation with demand and supply, and to learn major microeconomic concepts, including utility, scarcity, elasticity, efficiency, output and costs, and externalities. By analysing markets and studying the decision-making process by consumers and producers, students will be able to comprehend and differentiate the market types—perfect competition, monopoly, monopolistic completion and oligopoly. Typical Text: TBA Mathematical tone --> You are expected to have at least concurrent registration and perpetual progression with Calculus II until term’s end. Labs and Assignments --> Developing concepts and models in R from interpreted statements and data can be a strong indicator of a student’s capability, competence and seriousness about economics with professionalism. I can’t just assume such special development to be properly treated in the Calculus I-III sequence because calculus is the priority in such courses (and whatever ideologies or tribal structure or rent seeking for relevance). Hence, students will get their hands dirty with some basic computational modelling, coding and visualization development of some economic concepts and models in R. Students must draw conclusions based on their findings for all such topics. A. Calculus with R run-through --Geometry: plots, values at points, zeros, intersects, tangents, curve fitting --Differentiation: average rate of change, instantaneous rates of change, derivative values, critical points, relative extrema, concavity, absolute extrema --Integration: antiderivatives, area, economics applications, etc., etc. B. Elementary economics data analysis --Immersion with databases Basics of acquiring data sets from various sources Kaggle, Amazon AWS, USDA, agricultural marketing resource centres, FDA, Census, BLS, other gov’t databases, UNCTADstat, UN FAO, OECD, Capital Markets, etc., etc., etc. Quandl R package Data Cleaning basics Comprehension of measures of central tendency, variance, standard deviation. Generating summary statistics and interpretation The R packages, Stats, Tidyverse and Tidymodels Statistical plotting (scatter plots, box plots, histograms). Pearson Correlation. GGally package. Correlation heat maps with specication of correlation type. Regression models with summary statistics interpretation and forecasting Data structure for time series. Salient characteristics identification and exhibition; models with summary statistics interpretation. Forecasting. C. Of the following text concern will be chapters 1-5: Dayal V. (2015). An Introduction to R for Quantitative Economics, SpringerBriefs in Economics. Springer It’s also possible to generate all such with naturally installed R packages, to compare and contrast with prior D. Ideal con Kool-Aid problem sets are not good enough. Sustainability goals: based on development from (A) through (C), students will apply real data sets for determination of market models or characteristics. It’s important to have understanding of data structure and skills in data manipulation towards developing demand and supply models. If you can’t develop things from the raw or primitively then you don’t understand it. Concerns the following areas: agricultural, commodities, service industry, retail industry, etc., etc. Students must visually develop properties, system constraints, etc. Expected will be commentary among coding and to have axes labelling. Students will also be given statements to verify or debunk. Necessary topics of concern for development with use of R and RStudio: -Data Modelling (developed with real raw data) Supply and Demand (curve fitting and/or regression) Elasticity (curve fitting and/or regression) Market models (prior two topics and surplus/deficit will re-emerge): Pure Competition Pure Monopoly Monopolistic Competition Oligopoly Quizzes --> Complete your assignments, so you don’t have to worry about what you will encounter on quizzes. Don’t expect all questions to be multiple choice. Exams --> Students will have to pick a date and time convenient for them to take the final exam on or before the due date. The final exam will be a reflection of covered course material, assignments, quizzes and labs to evaluate students’ understanding of key concepts. Will have R usage as well. Open notes for R. Grading --> Assignments 15% Labs 25% Quizzes 20% Final 40% Course Outline --> Week 1 -- Introduction. What is Economics? The Economic problem Week 2 -- Demand and Supply Week 3 -- Demand and Supply Demand and Supply, Elasticity Assignment 1 Due and Quiz 1 Week 4 -- Elasticity Week 5 -- Efficiency and Equity Week 6 -- Utility and Demand Week 7 -- Possibilities, Preferences, and Choices Assignment 2 Due and Quiz 2 Week 8 -- Reviewing Loose ends Week 9 -- Output and Costs Week 10 -- Perfect Competition Week 11 -- Monopoly Week 12 -- Monopolistic Competition Assignment 3 Due and Quiz 3 Week 13 -- Oligopoly Week 14 -- Public Choices and Public Goods Week 15 -- Externalities and Environment Assignment 4 Due and Quiz 4 Week 16 -- Introduction to factors of Production, Economic Inequality Final Exam Prerequisites: Calculus I

Microeconomics II We will look into consumer and firm maximization problems, and the General and Partial equilibrium models, imperfect competition models and some game theory fundamentals at the end of the quarter. Most of the topics will include theoretical derivations as well as real life applications. Fundamental Comprehension --> Ability to use microeconomic terminology Highest-valued alternative foregone is the opportunity cost of what is chosen How individuals and firms make themselves as well off as possible in a world of scarcity How prices inform the decisions about which goods and services to produce, how to produce them, and who gets them How government policies affect the allocation of resources in a market economy How market structure influences the allocation of resources Applications --> Microeconomic principles and diagrams to understand and explain economic events and other social phenomena Calculus to solve optimization problems Use economic reasoning to explain the strategic choices of individuals or organizations Critique the economic content of articles or presentations Appreciate the usefulness of economic reasoning in personal decision making Typical Text --> Intermediate Microeconomics, by Hal Varian Accompanying Texts --> Intermediate Microeconomics with Calculus, Hal Varian Microeconomics, Jeffrey Perloff Problem Sets --> Will have the same tone and manner as in prerequisite, but at a more advanced and accelerated level based on course texts Labs --> ---Generally, will have advanced repetition of (B) and (D) lab activities done in prerequisite (more intensified and much faster relevant to course topics). ---Based on prerequisites, thus leading to the assumption that students are capable with series expansions and basic ODEs, will begin converting some ODEs into difference equations in R. Package dde can accompany analytical modelling; else, and most likely build manually for the long haul. The following gives an idea of what’s to be expected as a beginner: Dayal, V. (2020). Difference Equations. In: Quantitative Economics with R, Springer, Singapore. Fulford, G., Forrester, P., & Jones, A. (1997). Linear Difference Equations in Finance and Economics. In: Modelling with Differential and Difference Equations (Australian Mathematical Society Lecture Series, pp. 126-145), Cambridge: Cambridge University Press https://mjo.osborne.economics.utoronto.ca/index.php/tutorial/index/1/fod/t The following topics will be treated w.r.t. difference equations (simulation and conditions development, recognised parameters estimates versus regression development estimates approach): Logistic growth model and predator-prey models Dynamics of Market Price (linear and nonlinear entities) A market equilibrium model with price dynamics; dynamic stability and ensuring such Determining Dynamic Market Equilibrium Price Function Using Second Order Linear Differential Equations (applying difference equation rather) Todorova, T. (2012). The Economic Dynamics of Inflation and Unemployment. Theoretical Economics Letters. Vol.2 No.2, Paper ID 19278 Exchange rate overshooting model by Dornbusch (and alternatives) ---Externalities field cases Note: will focus on financial quantitative development towards retention and sustainability, NOT conceptual curves. Cost-Benefit Analysis Overview Benefits (monetised and non-monetised impacts) Costs (monetised and non-monetised impacts) Benefits and Cost estimation guides/manuals (monetised and non-monetised impacts) Social discount rate methodology Logistics and active implementation Externalities Positive Negative Adhikari, S.R. (2016). Methods of Measuring Externalities. In: Economics of Urban Externalities. SpringerBriefs in Economics. Springer, Singapore Quizzes --> We will have 5-6 quizzes. Quizzes will have limited typical questions from prerequisites mixed in with this course level problems. At the end of the term, we will drop your lowest grade and take the remaining 5 into account. Don’t expect all questions to be multiple choice. Exams --> It will focus on the material covered in class, but in a manner not requiring you to cram with the latest instruction. Will have R usage. Open notes for R. Don’t expect all questions to be multiple choice. Course Pace --> Generally it will take 10 weeks to complete course, however, an additional 3 – 5 weeks can be applied concerning reinforcement and competency Grade --> Problem Sets (10%) Labs (25%) Quizzes (20%) Midterm (20%) Final (25%) Course Outline --> WEEK 1 -- Chapter 1: The Market Chapter 2: Budget Constraint Chapter 3: Preferences WEEK 2 -- Chapter 4: Utility Chapter 5: Choice Quiz 1 WEEK 3 -- Chapter 6: Demand WEEK 4 -- Chapter 32: Exchange Quiz 2 WEEK 5 -- Chapter 19: Technology Chapter 20: Profit Maximization Quiz 3 WEEK 6 -- Midterm Exam Chapter 21: Cost Minimization WEEK 7 -- Chapter 22: Cost Curves Chapter 23: Firm Supply WEEK 8 -- Chapter 24: Industry Supply Chapter 25: Monopoly Chapter 26: Monopoly Behaviour Quiz 4 WEEK 9 -- Chapter 28: Oligopoly Quiz 5 WEEK 10 -- Chapter 29: Game Theory Chapter 14: Game Applications Quiz 6 Prerequisites: Calculus II; Microeconomics I Microeconomics III Course has a “duality” approach, namely, lectures make the “fundamentalist” and “snobbish” gauntlet; labs give traction and will be your money maker in the future. Theory and substance aren’t necessarily cut from the same cloth. Homework Problem Sets --> Students will have a week to complete the problem sets. R Labs --> NOTE: some things you will learn on the fly; you can’t expect everything to fall perfectly in place. A. Advance fast immersion into real world pricing of commodities Joutz, F. L. et al (2000). Retail Food Price Forecasting at ERS: The Process, Methodology, and Performance from 1984 to 1997. Economics Research Service, USDA. Technical Bulletin No. 1885 For such above literature with analysis then determine computational logistics towards replication. Will then advance to other markets with inclusion of other commodities incorporating more modern data: Wheat, Rice, Sugar, Corn, Soybean, Cocoa, Coffee Includes equilibrium determination, utility, etc. B. Hedonic modelling and estimation Experience from prerequisites labs means you’re good enough to hang in there with regression development. Various applications. D. Identification and validation of utility/production functions: Basic utility and production functions (must include Cobbs-Douglas, CES). The following text may not treat all types of interests but our intention is to have transparency and practicality concerning the following areas: bundles, general markets, production, efficiency, labour economics, etc. Coto-Millán, P. (2003). Utility and Production: Theory and Applications. Springer Physica, Heidelberg Calibrating Cobb-Douglas and CES (utility and production) Overview, logistics and code development Difference between calibrating & estimating for Cobb-Douglas and Constant Elasticity of Substitution? Can the following be implemented in a computational environment such as R? Afriat, S. N. (1967). The Construction of Utility Functions from Expenditure Data. International Economic Review, 8(1), 67–77 Note: data sources and data subject to change. Pursue for various industries for different environments (regions or countries) Note: compare to method of determining optimal production based on marginal cost (with calculus, etc.) Note: try to extend from Cobbs-Douglas to CES function and compare to marginal cost approach Biddle, J.E. (2011). The Introduction of the Cobb-Douglas Regression and its Adoption by Agricultural Economists. History of Political Economy, 43, pages 235-257. Note: try to extend all prior from Cobbs-Douglas to the CES function Introduction R microeconomic tools (limited exposure) micEcon, micEconAids, micEconCES, micEconSNQP Econometric estimation of Cobb-Douglas and CES functions (with above packages and direct econometric skills) compared to development with standard R tools/packages. E. Data Envelopment Analysis (firms, markets, industries, agriculture) Modelling and analysis with field applications R Packages of Interest for DEA rDEA, deaR, Benchmarking Special case treatment after other interests: Sengupta, J., Sahoo, B. (2006). Cost Efficiency in Models of Data Envelopment Analysis. In: Efficiency Models in Data Envelopment Analysis, Palgrave Macmillan, London. F. Stochastic Frontier Analysis (firms, markets, industries, agriculture) Modelling and analysis with field applications R Packages of Interest for SFA frontier, npsf, sfa, ssfa, semsfa, Benchmarking Special case treatment after other interests: SFA for cost efficiency (hospitals, community colleges, banking industry, agriculture) Advantages and disadvantages between DEA and SFA. NOTE: can Cobb-Douglas and CES functions be applied to SFA and DEA? G. Statistical Analysis in Partial Equilibrium Descriptive statistics. Skew and kurtosis. Correlation measure (Pearson, Spearman and Kendall). Correlation heatmaps for three or more variables. Econometric development of supply and demand analysis (including elasticities). Times series methods for comparative assessments. Speculation on behaviours and tools for verification. H. General Equilibrium Models Based on prerequisites, thus leading to the assumption that students are capable with ODEs and difference equations. PART 1 - will begin pursuing contemporary general equilibrium models; idea, constituents and their properties in unification. PART 2 - DSGE Modelling and Simulation Components Role of production and utility functions Junior, C. J. C. and Garcia-Cintado, A. C. (2018). Teaching DSGE Models to Undergraduates. Economica A 19, 424 – 444 How capable or practical will the R package dde be? Logistics Investigation. To make use of DYNARE + OccBin Toolkit after analysis Use of DynareR as well Estimations and scenarios Harrison, G.W. et al (2000). Using Dynamic General Equilibrium Models for Policy Analysis. Elsevier PART 3. CGE Modelling and Simulation (with GAMS): Components Role of production and utility functions Devarajan, S. and Go, D. S. (1998). The Simplest Dynamic General Equilibrium Model of an Open Economy. Journal of Policy Modelling 20(6): pages 677 – 714 Zhang, X. (2013). A Simple Structure for CGE models. GTAP Purdue The following texts provide guidance for programming and simulation: Hosoe, N., Gasawa, K., & Hashimoto, H. (2010). Textbook of Computable General Equilibrium Modeling: Programming and Simulations, Palgrave Macmillan Limited. Chang, G. H. (2022). Theory and Programming of Computable General Equilibrium (CGE) Models: A Textbook for Beginners. World Scientific. After analysis and computational skills development will develop for concerns of interest Dixon, P. B. and Jorgenson, D. W. (2013). Handbook of Computable General Equilibrium Modelling SET, Volumes 1A and 1B. Elsevier I. Advance development of Externalities field cases lab from prerequisite course. Exams --> There will be two midterm exams and a cumulative final exam. Limited amounts of notes for use. I encourage students to use a calculator and a ruler in the exams. All exams will include R usage. Prerequisite course labs will also be thrown at you. Course Grade Constitution --> Homework 20% R Labs 35% 2 Midterm exams (15% each) Final exam (15%) Resonating Texts --> Varian H., Microeconomic Analysis, New York and London, Norton Mas-Colell A., Whinston M. D., & Green J. R., Microeconomic Theory, Oxford Kreps D., 1990, A Course in Microeconomic Theory, Princeton Course Outline --> Analytical Logistics for Primitive Data Analysis in Microeconomics To be precursor to labs A to C Preferences and Utility Labs A to C must be completed before module is introduced To be precursor to lab D Utility Maximization and Choice Income and Substitution Effects Demand Relationship Among Goods Production Functions Cost Functions Profit Maximization General Equilibrium and Welfare To be precursor to lab H Markets Competitive Markets Imperfect Competition Asymmetric Information Wolak, F. A. (1994). An Econometric Analysis of the Asymmetric Information, Regulator-Utility Interaction. Annales Deconomie et de Statistique - No 34 Monopoly Externalities and Public Goods To be precursor to lab H Prerequisites: Calculus III; Microeconomics II.

Introduction to Macroeconomics Course prerequisite is a bit more advance than the norm. However, the goal of this course is to capture substance with meaningful quantitative and computational skills. Yes, you are here to acquire long term value, not just drawing intersecting lines and calling it macroeconomics. Note: I will not ask you to remember every equation on the fly. Mathematical tone --> You are expected to have at least concurrent registration and perpetual progression with Calculus II until term’s end. Labs and Assignments --> For each assignment set you will be advised on what pace you must keep up with, assuming strong comprehension and growing competence. As well, some questions will not be multiple choice. Have the maturity to review what you are uncertain about; ask questions. I can’t just assume such special development to be properly treated in the Calculus for Business and Economics I-III course sequence because calculus is the priority in such courses (and whatever ideologies or tribal motives). Hence, class will get their hands dirty with some basic maths and visualization of some economic concepts and models with R. Will get an early introduction the package R packages Tidyverse, Tidymodels, Quandl, data files and data from Kaggle, Fed, IMF, OECD, Bureau of stats, etc., etc. Labs will be based on the following areas: Quizzes --> We will have 5 quizzes. They will take no more than 30 minutes, and will be held at the beginning of class on chosen dates. At the end of the quarter, we will drop your lowest grade and take the remaining 5 into account. Don’t expect all questions to be multiple choice. Labs --> A. Elementary economics data analysis --Immersion with databases Basics of acquiring data sets from various sources Kaggle, Amazon AWS, USDA, agricultural marketing resource centres, FDA, Census, BLS, other gov’t databases, UNCTADstat, UN FAO, OECD, Capital Markets, etc., etc., etc. Quandl R package Data Cleaning basics Comprehension of measures of central tendency, variance, standard deviation. Generating summary statistics and interpretation The R packages, Stats, Tidyverse and Tidymodels Statistical plotting (scatter plots, box plots, histograms). Regression with summary statistics interpretation and forecasting Data structure for time series. Salient characteristics identification, primitive models with summary statistics interpretation. Forecasting B. Of the following text concern will be chapters 1-5: Dayal V. (2015). An Introduction to R for Quantitative Economics, SpringerBriefs in Economics. Springer It’s also possible to generate all such with naturally installed R packages, to compare and contrast with prior C. Scott. W. Hegerty: https://github.com/hegerty/ECON343/ D. Time Series analysis: summary statistics; salient characteristics tools in R; recognising volatility and shocks; correlations Consumption Investment Gov’t Expenditure Inflation Employment Nominal GDP versus real GDP Exports as share of GDP Debt to GDP Currency pairs Comparing different assets (prices with rates, percentage change) Comparing different assets alongside NEER and REER E. Estimation (open or closed economy) Estimation of Consumption Function Model (and forecasting) Estimation of Investment Function Model (and forecasting) Modelling and forecasting expenditure F. Short Run Closed Economy Models: 1. Review of elementary macroeconomic models: Algebraic development for IS curve and LM curve towards IS-LM. Followed by Numerics concerning economic scenarios. Algebraic treatment for AD and AS towards AD-AS. Followed by numerics concerning economic scenarios. Algebraic treatment for AD and IA towards AD-IA. Followed by numerics concerning economic scenarios. 2. R development for macroeconomic models We Think Therefore We R. (2012). Revisiting Basic Macroeconomics: Illustrations with R. R Bloggers: https://www.r-bloggers.com/revisiting-basic-macroeconomics-illustrations-with-r Will reinforce more development with IS-LM towards economic fluctuations and policy. Followed by R development for IA, then R development for AD-IA concerning economic fluctuations and policy, and then R development for AD-AS concerning market influences and policy. G. Chand, S. 11 Main Causes of Growth of Public Expenditures – Explained! Your Article Library: https://www.yourarticlelibrary.com/economics/11-main-causes-of-growth-of-public-expenditures-explained/26304 For such alleged causes determine whether there are overlaps? Then pursue empirical analysis and exploratory data analysis for verification. H. Short Run Open Economy Mundell-Fleming Algebraic development. Followed by numerics concerning economic scenarios. Extend G2 with Mundell-Fleming I. Dayal V. (2015). The Solow Growth Model. In: An Introduction to R for Quantitative Economics. SpringerBriefs in Economics. Springer Additional pursuits: Making Solow Growth model meaningful with data. Extensions of Solow and making meaningful to data Quizzes --> Complete your assignments, so you don’t have to worry about what you will encounter on quizzes. Don’t expect all questions to be multiple choice. Poor performances on quizzes and track record with assignments can be taken as a strong argument against you. Exams --> Administered in a manner not requiring you to cram with the latest instruction. Don’t expect all questions to be multiple choice. The final exam will be a reflection of covered course material, assignments, quizzes and labs to evaluate students’ understanding of key concepts. Will have R usage as well. Grade --> Assignments (15%) Quizzes (10%) Labs (30%) 3 Exams (45%) Course Outline --> This course introduces the key macroeconomic variables and explain how they are defined and measured to interpret macroeconomic data properly. Course discusses how macroeconomic variables influence market agents at various levels and public activities. Establishing a foundation for the analysis of the mechanisms that drive macroeconomic variables. Identify the various sectors of the economy in function, and possible interdependencies driven by different processes or pursuits, towards a holistic view. You will be able to systematically assess the national and international economic environment. Note: a module doesn’t necessarily imply 1 week, namely, some modules wil be completed faster than others. STRUCTURING MACROECONOMICS (Module 1-6) -- -Module 1: Supply & Demand. Elasticity -Module 2: National Income Accounting: Concepts & Definitions for a Closed Economy Closed Economy definition Stock/Flow Distinction What Counts as Output Concepts: Market value; Final goods and services; Within a period of time; Factors of production located within that country Why Income Equals Output What Happens to Income Taxes, Consumption, Saving Who buys Goods Consumption, Government Purchases, Investment (Business Fixed Investment, Inventory Investment, Residential Fixed Investment) -Module 3: Putting the Categories Together Simple Economy: all income is spent on goods and services The Simple Economy plus Government The Simple Economy plus Government and Investment The Basic Closed Economy Framework; Fiscal Surpluses and Deficits -Module 4: The Income-Expenditure Model Macroeconomic Equilibrium Aggregate Supply and Aggregate Demand The Consumption Function Aggregate Expenditure and Equilibrium (with numerical examples and changes) Perspective: Does the IE model acknowledge inflation? -Module 5: Economic Activity Consumption function and the saving function; compare current income hypothesis with the permanent income hypothesis; predict the effect that temporary versus permanent changes in income will have on consumption; factors that can cause the consumption function to shift. Concerns Determining gov’t spending and reasons for such Determining the aggregate level of desired consumption Nominal interest rate and real interest rate Economic scenarios involving prior elements in economic activity. Practice problems -Module 6: Key Macroeconomic Indicators and Their Measurement Meaning of macroeconomic indicators like GDP (Nominal GDP, Real GDP, GDP deflator, base year), the unemployment rate, and inflation. How are they measured? How should the figures for such variables be interpreted? SHORT-RUN CLOSED ECONOMY (Module 7-9) -- -Module 7: Elementary Shift Models Keynesian model versus Classical Models Investment Saving (IS) and Liquidity Preference Money Supply (LM) IS and LM derivations, solutions and numerics IS-LM (algebraic, numerical, geometric) Analysing various economic activity scenarios (including the presence of inflation) Aggregate Supply (AS) and Aggregate Demand (AD) AD and AS derivations, solutions and numerics AD-AS (algebraic, numerical, geometric) Analysing various economic activity scenarios (including the presence of inflation) Modeling or investigating price level & output relationship -Module 8: Modelling and Measuring Inflation Review of measurement of economy’s production of goods and services What causes Inflation? Retail Price Index (RPI). Consumer Price Index (RPI). Inflation measurement with CPI and RPI. Naive forecast and regression forecast (to be implemented) Economic Fluctuations: AD-IA (algebraic, solutions, numerical, geometrical) Analysing various economic activity scenarios -Module 9: Monetary Policy and Fiscal Policy Fiscal: concerns, automatic stabilizers, systematic framework, liquidity traps, respective tools and guidance concerning state of economy. Monetary: concerns, systematic framework, policies, respective tools and guidance concerning state of economy. Use of AD-AS and AD-IA for analysing monetary and fiscal treatment; fluctuations, shocks, policies and rules; most rules are dynamic so conceptual idea of structure to be synthesized in an algebraic and numerical treatment with AD-AS and AD-IA. LONG-RUN CLOSED ECONOMY -- -Module 10: Long Run Economic Growth in Closed Economy Solow Growth Model (with and without government) Long-term economic analysis Extensions of Solow (counterpart to prior) OPEN ECONOMY -- -Module 10: Open Economy (extending modules 2-3 development) From Closed to Open Imports and Exports Foreign Savings and Foreign Investment The Rest of the World and Balance of Payments -Module 11: Assembling the Picture Trade Deficit: Structure and Formulas Trade Surplus: Structure and Formulas Algebra: Definitions and Fundamental Balances < https://faculty.washington.edu/danby/bls324/macro/bop/2-2new.htm > -Module 12: The Open-Economy Income-Expenditure Model [ https://faculty.washington.edu/danby/bls324/macro/bop/2_3.html ] Numerical Case Studies Algebra for Equilibrium and the Multiplier: https://faculty.washington.edu/danby/bls324/macro/bop/algebra.html More Numerics with Equilibrium -Module 13: Money Market How do central banks influence the money market and the interest rate? What factors drive the supply and demand for money? SHORT RUN OPEN ECONOMY -- -Module 14: Nominal exchange rate, interest rate, and output Reasons for foreign exchange Forces on the currency exchange rate Asset-backed currency vs. Fiat currency: pros and cons Why does the foreign exchange market function as OTC? Spot Rate and Forward Exchange Rate How do the spot and forward exchange rates interact with the expected rates of future dates? Nominal Exchange Rate and Real Exchange Rate How do central banks influence the exchange rate? Modelling and dynamics pursuits: The interest rate determines the cost of capital, the opportunity cost of using money, and the exchange rate. Mundell-Fleming model (MFM) < en.wikipedia.org/wiki/Mundell–Fleming model > Can the MFM elaborate strongly on the following questions? How does the exchange rate interact with domestic and foreign prices to determine the competitiveness of an economy’s producers? How does the exchange rate affect the trade balance and foreign payments of an economy? Polices and rules via the MFM (algebraic and numeric) LONG RUN OPEN ECONOMY -- Module 15: Modelling Daniel, B. C. (1977). Inflation and Unemployment in Open Economies. International Finance Discussion Papers. No.114. Federal Reserve Open Economy Solow Model and Extensions Can the same conclusions be drawn from both Solow type models and the development of Daniel (1977)? Prerequisites: Calculus I Money & Banking Tools --> Sovereign ambiance analogy to the following < https://www.fdic.gov/bank/ > R Packages: FinCal, jrvFinance, tvm, YieldCurve, BondValuation Note: use of such R packages must succeed analytical development Problem sets --> Problem sets will be distributed for each topic and will be discussed in class the following week. These are not assessed, but will serve their purpose. Assessment --> 5 – 6 Quizzes 30% Lowest to be drop and average taken of the rest to serve Research Lab Activities (in groups) 20% Midterm 25% Noncumulative final examination 25% Labs --> LAB1: Financial analysis of financial institutions Will make use of financial statements from SEC filings or SEC Edgar. Will be assigned various banks in groups to develop analysis; crash immersion for assessing capital adequacy, reserves, credit, liquidity, etc. Observation and analysis based on: https://www.fdic.gov/bank/ LAB2: Interest models and properties Structure: principal with and without coupon Discrete and continuous compounding TVM/future value, present value, and net present value Pricing/valuation of bonds Nominal interest rate, real interest rate Internal Rate of Return Accrued Interest, Effective Interest rate, APR, APY Duration types & Immunization types Interpolate a yield curve by regression analysis (bond market direction and speculation on where the economy might be going). LAB3: IPOs. Dividend Discount Models, DCF, and comparables. Developing regression models for stocks; beta and VaR for stocks; basic time series analysis for stocks. CAPM and multi-factor models for asset expectations and risk premiums (case for both bonds and stocks). LAB4: Fiscal indicators Identification and implementation of fiscal indicators Analysis of IMF’s semi-annually published Fiscal Monitor. LAB5: Inflation and Predicting Inflation Consumer Price Index: Comprehension of structure Building baskets with specified assets and computation Avdiu, K. and Unger, S. (2022). Predicting Inflation—A Holistic Approach. J. Risk Financial Manag., 15, 151 Is gold a good leading indicator of inflation? LAB6: Recital of economic models: IS-LM, AD-AS and AD-IA Analytical derivations, solutions, numerics, and geometrical interpretations: IS, AD, AS, etc. Relevance and construction: IS-LM, AD-AS & AD-IA. Shifts, deducing or investigating rules, policies from such models and tools (empirical cases) Course Outline --> 1. Money and the Financial System 2. Treasury Purpose Tools in economic policy Agencies of the Treasury Functions 3. Value of Money Pigou, A. C. (1917). The Value of Money. The Quarterly Journal of Economics, 32(1), 38–65. What is this article saying? Is such article relevant with real markets? 4. Financial Institutions Why and when did banks become a fixture in society? How do banks acquire or generate capital to establish themselves as financial institutions? Governance and regulation for banks to operate Management of Financial Institutions Capital, Liquidity, Credit Quality, and Deposit Insurance Banking policies for good mixture of liquidity, credit and capital Basel measures and recommendations Use of financial statements and requirements measures Why do banks borrow from each other? Federal funds rate and Interbank rate: differentiate between them. Regulation by central banks Economic Analysis versus performance of banks 5. Fixed Income Investments Time Value of Money (TVM) and Rate of Return (RoR) Structure: principal with and without coupon Compounding (discrete and continuous) Future Value, Present Value, Net Present Value Accrued Interest Government Securities General Instruments Sources for credit measure Auctions and Valuation CDs, Corporate bonds, loans, mortgages, etc., etc. General Instruments Sources for credit measure Vendors for such and their regulation Regulation Valuation Influences on interest rates Ross, S. (2021). How Does Money Supply Affect Interest Rates? Investopedia Lioudis, N. K. (2021). Who Determines Interest Rates? Investopedia Heakal, R. and Boyle, M. J. (2021). Forces that Cause Changes in Interest Rates. Investopedia Beers, B. (2021). Negative Interest Rate Definition. Investopedia Interest risk, duration types and immunization Trustworthiness of credit ratings: households & firms, and gov’t Credit: households and firms Relative health of the markets and economy as a whole Yield Curve (quality and maturities) Expectations of market participants about future changes in interest rates and their assessment of monetary policy conditions De facto measure of liquidity: bid ask spread Interest adjustment based on perceived risk with market agents CAPM and multi-factor models Does lender competition stabilize interest rates that results in caps beneath the measure of CAPM and multi-factor models? 6. Equity Market IPOs: Dividend Discount Models (DDMs), DCF, Comparables Regulation Influences on stock prices Beta, standard deviation and VaR CAPM and Multi-factor Models Relation between treasury yield rates and stocks 7. Central Bank Structure Preliminaries: Central Banks and the Federal Reserve System Why is a federal funds rate needed? What will such influence? Theories of Monetary Policy Transmission of monetary policy Goals, monetary policy, transmission channels, effects Policy Rules Tools of Monetary Policy and relation to rules Conduct of monetary policy How rules and transmission channels affect markets Interpretation of monetary policy and rule(s) and applied tools Rudimentary models: AD-AS and AD-IA Algebraic and numeric focused 8. Differentiation between central banks and treasuries Powers and responsibilities in regulation and economic policy Coexistence and complimentary tools in monetary economy 9. Fiscal Governance Taxes for goods and services Automatic Stabilizers and redistribution/funding for public services Public Budget and Budget Constraint Budget Deficit: consequences and counters Fiscal Indicators Recessions & Liquidity Traps Picking up where monetary policy reaches its limits Relevance of AD-AS, AD-IA to fiscal policy (algebraic, numerical) Coordinating Monetary Policy with Fiscal policy via AD-AS and AD-IA? Algebraic and numeric focused 9. Basic Money Dynamic(s) Money Supply (short run and long run) Determinants of Money Supply The Equation of Exchange and its use in economic analysis Will investigate various behaviors and scenarios Inflation Review monetary policy concerning money supply Wikipedia - Money Multiplier (applicable for assignment case scenarios with banks) 10. Currency & Policy Economic reasoning for currency exchange From Bretton Woods to fiat to current, why? Foreign Exchange Fixed and floating Economic arguments and validation for rates types Models and requirements/conditions for good welfare The Foreign Exchange Market. Why permitted to function in such manner? Value of money from the value of treasury notes Means of analysing (active immersion) Value of money from foreign exchange reserves Means of analysing (active immersion) Exchange rate measure vs treasuries vs foreign exchange reserves Comparative analysis for possible disparities (active immersion) Which best reflects inflation? Mundell–Fleming model (IS-LM-BoP) Algebraic and numeric focused Shifts, policies, rules and tools Prerequisite: Introduction to Macroeconomics, Calculus II Intermediate Macroeconomics This course is aimed to keep a pace of practical progression from prerequisite. Namely, continual advancement in developing practical macroeconomic models involving real world dynamic. One has to move forward rather than being sabotaged or hoodwinked with “interesting intersecting lines”. You can’t permit yourself to be subjugated by toxic scams over and over. Concerning the bigger picture, the algebraic and calculus structure directive is much more constructive long term versus watching intersecting lines; not possible to develop strongly with the latter. The expression, “have respect for your kidneys” is metaphorical here. While such pursuit still may not reflect the real economy as it is, they provide better economic insights for us. As you will also find out in the coming weeks, there is no one specific model that explains all facets of the economy concerning monetary management. Thus, I will introduce different economic models for you to use and compare. Homework 20% --> Reacquaintance with Intro Macro problems. For the growth models and the Multiplier-Accelerator model, David Romer’s “Advance Macroeconomics” text will apply ONLY FOR SUCH. For modules (8) to (10) in course outline there will be classical problems for static versions of IS-LM, AD-AS and AD-IA concerning shifts, policy and rules before dynamic development in an algebraic and numeric manner. Extending to problems with dynamic IS-LM and dynamic AD-AS. R LABS 20% --> --Advance fast repetition of labs (A) to (F) from Introduction to Macroeconomics course labs with possible augmentations. -Based on prerequisites, thus leading to the assumption that students are capable with series expansions and basic ODEs, will begin converting some ODEs into difference equations in R. Package dde can accompany analytical modelling; else, and most likely build manually in R for the long haul. The following gives an of what’s to be expected as a beginner: Dayal, V. (2020). Difference Equations. In: Quantitative Economics with R, Springer, Singapore. Fulford, G., Forrester, P., & Jones, A. (1997). Linear Difference Equations in Finance and Economics. In: Modelling with Differential and Difference Equations (Australian Mathematical Society Lecture Series, pp. 126-145). Cambridge: Cambridge University Press https://mjo.osborne.economics.utoronto.ca/index.php/tutorial/index/1/fod/t Developing difference equations and investigate dynamics and various conditions. Then, recognised parameter estimates compared to econometric parameter methods, and drawing conclusions (with holistic economic rationale): Solow-Swan Mankiw – Romer – Weil Ramsey – Cass – Koopmans Model Overlapping Generations Model Then compare manual computational construction and package dde use with Dynare + OccBin Toolkit and Dynare R development Multiplier-Accelerator model Exchange rate overshooting model by Dornbusch (and alternatives) --Yield Curve Modelling (development and contrast) Review of use Interpolation of the yield curve: making connection to your calculus skills. Data elements will be 3-4 at most. Interpolation in R 10+ data elements with R Nelson Siegel model Diebold Li Model (published version): Diebold, Francis X. and Canlin Li. (2006). Forecasting the Term Structure of Government Bond Yields, Journal of Econometrics, v130, 337-364 Nelson–Siegel–Svensson Schumann, E. Fitting the Nelson–Siegel–Svensson Model with Differential Evolution. Cran R Spline Method Fisher-Nychka-Zervos (Spline) --Analysis of Business Cycles Spotting Recessions Measuring and Dating the Business Cycle in R --Simulating Dynamic IS-LM, and DAD-DAS Shifts, policies and rules 4 Exams 60% Will include problems from prerequisites macro course Will concern lectures and homework in this course COURSE OUTLINE --> LONG TERM MODELS AND TOOLS -- 1. Growth Models in the Long Run. What can they tell you? Strengths and weaknesses comparatively. How useful are they? Key topics to investigate: savings and investment (short run vs. long run); population growth; investment; saving; aggregate production; consumption; full employment; returns to scale; expressing concepts in per capita terms; capital deepening and capital widening; long-run steady state; real interest and real wage; population growth variance; saving rate variance; dynamic scoring. Note: calibrations methodology with economy and so forth expected. Note: determine order yielding the most tangible, fluid, constructive and sustainable delivery Exogenous growth model Mankiw – Romer – Weil Ramsey – Cass – Koopmans Overlapping Generations (OLG) Multiplier-Accelerator 2. Growth Models Investigation Klenow, P. & Rodríguez-Clare, A. (1997). The Neoclassical Revival in Growth Economics: Has It Gone Too Far? NBER Chapters, in: NBER Macroeconomics Annual 1997, Vol 12, pages 73 – 114, NBER Research, Inc. Question: how to develop the following article relevant with modern data? Baumol, W. J. (1986). Productivity Growth, Convergence, and Welfare: What the Long-Run Data Show. The American Economic Review. 76 (5): pages 1072–1085. Note: extend with more modern data. 3. Overview of DYNARE + OccBin Toolkit and Dynare R towards OLG. 4. Yield curve and applying estimating methods 5. Analysis of business cycles: finding any relationship between household debt and impending economic downturn (augment with more modern data) Mian, A. R., Sufi, A. and Verner, E. (2015). Household Debt and Business Cycles Worldwide (NBER Working Paper 21581 Developing economies (demonstrations for countries with medium grade credit ratings) 6. Spotting Recessions The following literature to be guides for development in R Chappelow, J. & Barnier, B. (2020). Guide to Economic Recession, Investopedia The Economist – How To Spot a Recession: Economists have a new method for predicting big downturns Pickert, R. Tips for Spotting a U. S. Recession Before it Come Official. Bloomberg Are tools from (4) consistent with the identified methods of spotting recessions? 7. Measuring and Dating the Business Cycle in R Achuthan, L. (2020). Business Cycle. Investopedia From the above article to develop data analysis for measuring and dating business cycles. Then for different countries and to determine whether phases are consistent with each other. SHORT TERM DYNAMIC MODELS -- 8. Dynamic IS-LM Review of static IS and LM (algebraic, numerical) towards IS-LM Derivation (algebraic,) numerical, solutions and graphical Extending priors to IS-LM (algebraic, numerical and means of use) For shifts will try to match with causes based on economic data; policies and rules. Extending the IS-LM model to the dynamic case; solutions, calibrations, simulations, shifts policies and rules. Possible additional interest (to computationally replicate): De Cesare, L., & Sportelli, M. (2005). A Dynamic IS-LM Model with Delayed Taxation revenues. Chaos, Solitons and Fractals, 25(1), 233–244. Wang, X. H., & Yang, B. Z. (2012). Yield Curve Inversion and the Incidence of Recession: A Dynamic IS-LM Model with Term Structure of Interest Rates. International Advances in Economic Research, 18(2), 177–185. 9. Dynamic AD-AS (algebraic, numerical, graphical) Review of static AD and AS Derivation (algebraic), solutions, numerical and graphical simulations then followed by AD-AS development (algebraic/c, numerical and means of use) Extending priors to DAD-DAS (and means of use) For dynamics based on simulation will try to match with economic conditions; policies and rules. Build on the following towards empirical cases studies concerning solution, policies, rules decisions (and critique): --https://warwick.ac.uk/study/summer-with-warwick/warwick-summer-school/courses/macroeconomics/09._das-dad_-_handout.pdf --https://personal.utdallas.edu/~d.sul/Macro/chap14.pdf 10. Dynamic AD-IA? Review of static AD and IA Derivation (algebraic), solutions, numerical and graphical simulations then followed by AD-IA development (algebraic/c, numerical and means of use) Extending priors to dynamic version (and means of use)? For dynamics based on simulation will try to match with economic conditions; policies and rules. LONG-TERM OPEN ECONOMY MODELS -- 11. Daniel, B. C. (1977). Inflation and Unemployment in Open Economies. International Finance Discussion Papers. No.114. Federal Reserve 12. Open Economy Solow Model (OESM) Assessing International Capital Mobility Empirically The Feldstein-Horioka Puzzle The Lucas Paradox Open Economy Solow Model: Capital Mobility The Basic Model Empirical Issues 12. Can the following be extended to open economy? Empirical Investigation? Mankiw – Romer – Weil Ramsey – Cass – Koopmans 13. Can the same conclusions be brawn from (1), (12) and (13)? SHORT TERM DYNAMIC OPEN ECONOMY MODELS? Advance Review of the Mundell-Fleming Model Dynamic IS-LM-X Model Wang, P. (2017). A Dynamic IS-LM-X Model of Exchange Rate Adjustments and Movements. International Economics (Paris), 149, 74–86. Wang, P. (2020). The Dynamic IS-LM-X Model of Exchange Rate Movements. In: The Economics of Foreign Exchange and Global Finance. Springer Texts in Business and Economics. Springer, Berlin, Heidelberg Are all conclusions for economic scenarios, policies and rules with Mundell-Flemming consistent with the dynamic IS-LM-X Model? MONETARY TRANSMISSION MECHANISM -- Role of the Central Bank, Transmission Mechanism, and Conduct of Monetary Policy. Will observe/analyse the structure. Will then identify rule(s) and tools for intended effects and channels. INTRODUCTION TO MONETARY POLICY RULES -- For the following rules how does one arrive to such specific formulas? Pursue a transition that emphasizes similarities to increasing unique attributes. Are the rules of exact form for all countries? Taylor rule Balanced-approach rule ELB-adjusted rule Inertial rule First-Difference rule Outcome-Based rule Nominal income targeting rule The references in the following may prove beneficial: https://www.federalreserve.gov/monetarypolicy/policy-rules-and-how-policymakers-use-them.htm Prerequisites: Introduction to Macroeconomics, Calculus II Macroeconomic Accounts Statistics Basic concepts, and principles and skills required to compile and disseminate macroeconomic and financial statistics. Note: all considered political scales (national, provincial and municipal) are assumed to be open economy. Note: I will not ask you to remember every equation. ESSENTIAL TOPICS (to resonate continuously throughout course) --> Differentiate institutional units and sectors Apply the concept of residence Record stocks and flows in an integrated manner Apply appropriate accounting rules Classify financial instruments Summarize IMF’s Data Standards Initiatives Requirements & Recommendation Evaluate macroeconomic inter-linkages. National Accounts Main elements with construction for each Circular Flow of Economic Identity Key identity: Production = Income = Expenditure National Income and Product Accounts Measuring GDP Income Approach Expenditure Approach Production Approach Income and Saving Private Disposable Income Private Saving Net Government (Public) Income Government (Public) Saving National Saving Uses of National Saving Assessment of Taxes Fiscal Indicators (more than one) Measuring Capital Flows Claessens, S. and Naude, D. (1993). Recent Estimates of Capital Flight, World Bank WPS 1186 National Accounts for Economic Assessment Assessing Economic Welfare Assessing Transitioning Economy Assessing Inflation Current Account Benchmark How is the Intro Macroeconomics course relevant macroeconomic accounts statistics? Note: concerns how algebraic models and numerical inputs apply to observe dynamics STRUCTURAL GUIDE --> System of National Accounts 2008 < https://unstats.un.org/unsd/nationalaccount/docs/SNA2008.pdf AUGMENTATIVE LITERATURE --> NOTE: the following two literature only serves to expand upon the given essential tasks and structural guide with “waterdown” exercises, but don’t expect all course exercises to always be that superficial. National Accounts: A Practical Introduction. United Nations 2003. Studies in Methods Series F, No.85 Lequiller, F. and D. Blades (2014), Understanding National Accounts: Second Edition, OECD Publishing, Paris Eurostat Manuals and Guidelines – Essential SNA: Building the Basics, European Union NATIONAL ACCOUNTS PUBLICATIONS --> < https://unstats.un.org/unsd/nationalaccount/pubsDB.asp < https://unstats.un.org/unsd/nationalaccount/impUNSD.asp < https://www.unsiap.or.jp/tot/index.html RESOURCES--> IMF data repositories UN Stats data repositories Bank for International Settlements Gov’t data repositories COURSE LABS (with Excel and R use) --> Developing course data skills towards quantities on interest. Logistics and development of elements in National Accounts. NOTE: done on multiple occasions with course progression. Advance treatment of selected problems from prerequisite macroeconomics course relevant to this course when appropriate. Purpose is to observe how real macroeconomic statistics development and dynamics influence models. Given at designated periods Advance recital of chosen labs from prerequisite macroeconomics course. Given at designated periods Analysis of National Accounts Publications QUIZZES --> Prerequisite topics and questions from Intro Macro course Concepts and multiple choice (based on structural guide) Manipulation of economics equations for various perspectives (with data inputs) Analysis of data found in National Accounts Publications Analysis of financial statements & data statements towards reasoning and computation (straightforward questions and indirect reasoning) EXAMS --> Exams will have two components Will reflect quizzes Open environment: will be asked to retrieve and provide assessment of the data (city, provincial, national) and computational guidance. GROUPS TERM PROJECT --> Gathering economic activity data to tabulate statistics based on SNA 2008, but only at city or provincial level. Done in a quarterly manner but will account for four to six years. A. Will not rely on summarized data, rather, use of highly primitive data to tests your development skills. How primitive? In course progression you will be emulating all figures and tables from the structural guide, where they will be applied for development for the term project; develop logistics among all such towards your computations. You will be making extensive data searches within the public sector, public finance, households (all types), private sector, NPOs and NGOs, Assets, Liabilities, etc., etc. All major financial statements will be developed during the collective process. Proper citations and reference will make or break you as well. Proper procedure and mechanics will have much weight just as quantitative accuracy. As well to compute quarterly for four years: GDP, GDP per capita, real GDP, GNI, savings, assets and liabilities, debt and its variation. Real GDP growth rate. Public sector debt and its dynamic. B. All given essential topics will be relevant in your term project. C. To be given a grade I must observe that you are actually intimate with the whole process (also including citations), rather than being a con artist with public data summaries. D. How does GDP forecasting based on system of “National” Accounts compare to regression method involving determined predictor variables (thus applying heavy data)? E. How does inflation assessment based on system of “National” Accounts compare to econometric methods (thus applying heavy data)? Prerequisites: Enterprise Data Analysis I & II, International Financial Statements Analysis I & II, Intermediate Macroeconomics International Macroeconomics Aside for concerns a country’s output, inflation, interest rates, exchange rates, & trade balance, course also considers the international linkages arising from capital & trade flows. Additionally, the course examines the effects of macroeconomic events on the international business environment. Labs (done in a manner that’s harmonic to course progression development) --> 1.Economic Statistics (due date to be given) A. GDP forecasting (regression and time series) B. Gross National Income (GNI) World Bank Atlas method (develop and compare with organised data): https://datahelpdesk.worldbank.org/knowledgebase/articles/378832-the-world-bank-atlas-method-detailed-methodology C. Determining the Trade balance Intimate process via SNA guides Where do you get the primitive data to compute? Logistics and implementation 3-4 examples to be done rather than just accepting the given numbers D. Which factors can Influence a Country’s Balance of Trade? Investopedia Means to validate the statements E. Global PMI Analysis F. Inflation and Employment Inflation Forecasting Avdiu, K. and Unger, S. (2022). Predicting Inflation—A Holistic Approach. J. Risk Financial Manag., 15, 151 Is gold a good leading indicator for inflation? G. Employment Forecasting 2. National Accounts (2-3 countries) Identifying economic welfare Assessment of economic policy Inflation assessment Can the following tools apply? Beneish, Dechow F, Modified Jones, Altman Z, and Merton default model 3. DSGE for exchange rate tradeoffs. To develop and simulate for various conditions: Devereux, M. (2000). A Simple Dynamic General Equilibrium Model of the Tradeoff Between Fixed & Floating Exchange Rates. London, Centre for Economic Policy Research DYNARE + OccBin Toolkit after analysis; DynareR Floating Currency Pairs Forecasting 4.Tools to Predict Economic Recessions Will apply the identified tools to past business cycles to determine predictive power (with some statistical indicators applied); future predictions as well. Yield Curve PMI Composite Index of Leading Indicators Global PMI OECD Composite Leading Indicator < https://www.oecd.org/sdd/leading-indicators/41629509.pdf > The TED spread ---Concept. Instructor must exhibit to students how to competently read and analyse market data observed: ---Credit risk and default risk observation ---Trade construction methodology ---Perturbation values, observation of hedge ratios (with any formula) ---Liquidity-related factors Note: for such above there are likely analogies to such for a respective ambiance of interest to create a “foreign TED spread”. Else, construct them. Also, with the replacement of LIBOR apply appropriate substitution. Assignments --> TBD: a combination of “status quo” problems COMBINED WITH assignment tasks mentioned in MANDATORY DEVELOPMENT. Exams --> Exams will reflect assignments Course Grade Constitution --> 5 or 7 Assignments Sets 35% 3 Exams 45% Labs 20% Course Literature --> TBA: must match mandatory development with level of topics MANDATORY DEVELOPMENT --> NOTE: selected topics from texts will be chosen to accommodate (not dictate upon) the following listed mandatory topics: 1.COMPREHENSION OF A MONETARY ECONOMY AND CONCERNS 2.CONCERNING EQUILIBRIUM WHAT IS THE ROLE OF THE TREASURY IN A MONETARY ECONOMY COMPARED TO CENTRAL BANK POLICY? 3.THE MONEY SUPPLY PROCESS: Assisting literature for development Krugman & Wells 2009, Chapter 14: Money, Banking, and the Federal Reserve System: Reserves, Bank Deposits, and the Money Multiplier, pp.393-396. In: Macroeconomics. Macmillan. Mankiw 2008, Part IV: Money and Prices in the Long Run: The Money Multiplier, pp. 347 – 349. In: Principles of Macroeconomics. Cengage Learning Mankiw 2002, Chapter 18: Money Supply and Money Demand: A Model of the Money Supply, pp. 486 – 487. In: Macroeconomics. MacMillan Wikipedia - Money Multiplier (applicable for assignment case scenarios with banks) Determinants of Money Supply (exogenous and endogenous perspectives) The minimum cash reserve ratio The level of bank reserves The desire of the people to hold currency relative to deposits Latter two determinants together are called the monetary base or the high- powered money. High-Powered money and the money multiplier Other Factors: money supply is a function not only of the high-powered money determined by the monetary authorities, but of interest rates, income and other factors. The latter factors change the proportion of money balances that the public holds as cash. Changes in business activity can change the behaviour of banks and the public and thus affect the money supply. Hence the money supply is not only an exogenous controllable item but also an endogenously determined item. High-Powered money and the money multiplier (formulae) Equation of exchange Measures of money supply M1, M2, M3, M4, Money Zero Maturity (MZM) Definition Derivation of the money multipliers Velocity for measures The Money Market Model. How is it relevant to IS-LM, AD-AS and AD-IA? Have algebraic and numerical emphasis mostly before consideration of any use of curves (as possible assignments) Gorton, D. (2021). How Does Money Supply Affect Inflation? Investopedia Many statements to validate, as well, empirical exercises to validate Relation between Monetary intervention and money supply. IS-LM, AD-AS and AD-IA? Have algebraic and numerical emphasis mostly before consideration of any use of curves (as possible assignments) 4.REASONS OR AGENDAS FOR INTERNATIONAL TRADE General Agreement on Tariffs and Trade (GATT) What assets, products and services are applicable? Purpose of the WTO and its influence. Differentiation between WTO, UNCTAD and UNCITRAL. Non-Tariff Measures and the IBT Agreement. 5.EXCHANGE RATES Why does the currency exchange market exist? Why must/does it exist as an over-the-counter (OTC) marketplace? Economic arguments and validation for rates types Fixed and floating (fiscal and monetary management) Requirements or conditions for good welfare Value of money from the value of treasury notes Means of analysing (active immersion assignments) Value of money from foreign exchange reserves Means of analysing (active immersion assignments) Exchange rate vs treasuries vs foreign exchange reserves vs PPP Comparative analysis for possible disparities (active immersion assignments). Which best reflects inflation? (active immersion assignments) IMF: Classification of Exchange Rate Arrangements and Monetary Policy Frameworks < https://www.imf.org/external/np/mfd/er/2004/eng/0604.htm > Influence of money supply on currency exchange Theoretical models Statistical relationship between money supply, GDP, inflation, unemployment and exchange rate (via time series correlation measures, scatter plots) Overvalue and Undervalue (active immersion assignments) Nominal Exchange Rate and Real Exchange Rate Real Effective Exchange Rate 6.MUNDELL-FLEMING MODEL (extending the IS-LM) Development (algebraic, numerical, solutions and graphical) Boughton, J. M. (2002). On the Origins of the Fleming – Mundell Model, International Monetary Fund. IMF Working Paper. WP/02/107 Gandolfo, G. (2016). The Mundell-Fleming Model. In: International Finance and Open-Economy Macroeconomics. Springer Texts in Business and Economics. Springer, Berlin, Heidelberg. Fleming, J. Marcus (1962). IMF Staff Papers. 9: 369–379. Mundell, Robert A. (1963). Canadian Journal of Economics and Political Science. 29 (4): 475–485. Deductions or guidelines for shifts, policies & rules (case assignments) Try to analyse, make sense of the following, then pursue replication, followed by countries of interest with more modern data Obstfeld, M. (2001). International Macroeconomics: Beyond the Mundell-Fleming Model. IMF Staff Papers Vol. 47, Special Issue 7.OVERSHOOTING MODEL Dornbusch, R. (1976). "Expectations and Exchange Rate Dynamics". Journal of Political Economy. 84 (6): 1161–1176. Frenkel, J. A., & Rodriguez, C. A. (1982). Exchange Rate Dynamics and the Overshooting Hypothesis (La dynamique des taux de change et l’hypothèse du surajustement) (La dinámica de los tipos de cambio y la hipótesis del ajuste excesivo). Staff Papers (International Monetary Fund), 29(1), 1–30. Rogoff, K. (2002). Dornbusch ’s Overshooting Model After Twenty-Five Years. IMF Working Paper, WP/02/39 What is relation or disparity between Dornbusch’s model and the Mundell-Fleming model? 8.DYNAMIC SHORT TERM OPEN ECONOMY MODELS Dynamic IS-LM-X Model (review) Wang, P. (2017). A Dynamic IS-LM-X Model of Exchange Rate Adjustments and Movements. International Economics (Paris), 149, 74–86. Wang, P. (2020). The Dynamic IS-LM-X Model of Exchange Rate Movements. In: The Economics of Foreign Exchange and Global Finance. Springer Texts in Business and Economics. Springer, Berlin, Heidelberg Are all conclusions for economic scenarios, policies and rules with the dynamic IS-LM-X Model consistent with the Mundell-Flemming and/or the Overshooting Model? (active investigation assignments for students) 9.FINANCIAL TRANSACTIONS Heakal, R. (2021). What is the Bank for International Settlements? Investopedia Scott, G. (2021). International Swaps and Derivatives Association (ISDA), Investopedia Chen, J. (2020). ISDA Master Agreement. Investopedia Balance of Payments For each type of account to identify respective uniqueness and what vital analysis stem from them; to have case examples from past periods Balance Sheet Current Account Capital Account Relationship between Current Account and Capital Account Errors and omissions Measuring Capital Flows (active investigation assignments for students) Claessens, S. and Naude, D. (1993). Recent Estimates of Capital Flight, World Bank WPS 1186 10.CURRENT ACCOUNT ANALYSIS Cases of (persistent) current account deficits: factors and evidence. Do deficits mean the economy is weak? What to worry about? What not to worry about? Does a surplus automatically mean that the economy is strong? How to reduce the current account deficit? Influence of current account deficit on terms of trade. Effect of devaluation on terms of trade. Current Account Benchmarks: Ca’ Zorzi, M., Chudik, A. and Dieppe, A. (2009). Current Account Benchmarks for Central and Eastern Europe. A Desperate Search? European Central Bank Working Paper Series No. 995 Coutinho, L., Turrini, A. and Zeugner, S. (2018). Methodologies for the Assessment of Current Account Benchmarks. EU Discussion Paper 086 (some implementable assignments) 11.NATIONAL INCOME The National Income Identity. Disparity between GNP and GDP National Income Identity in terms of the Current Account Income Determination in the Open Economy GDP and Real GDP: the misconceptions 12. MONETARY POLICY & EXCHANGE RATE Gianviti, F. (2014). Relationship Between Monetary Policy and Exchange Rate Policy. In L. Satragno (Author) & T. Cottier, R. Lastra, & C. Tietje (Eds.), The Rule of Law in Monetary Affairs: World Trade Forum (pp. 545-569). Cambridge: Cambridge University Press. Kolasa, M., et al (2022). Monetary Policy and Exchange Rate Dynamics in a Behavioral Open Economy Model. IMF Working Paper, WP/22/112 IMF - Classification of Exchange Rate Arrangements and Monetary Policy Frameworks: https://www.imf.org/external/np/mfd/er/2004/eng/0604.htm 13.FISCAL INTERVENTION: What are its goals in a monetary economy? Money supply and the consolidated government budget constraint What makes fiscal policy work well with monetary policy? Masson, P. & Blundell-Wignall, A. (1985). Fiscal Policy and The Exchange Rate in the Big Seven: Transmission of U.S. Government Spending Shocks, European Economic Review, Elsevier, vol. 28(1-2), pages 11-42. Note: appropriate parameter values to be pursued. Fiscal Indicators (to implement assignments) 14.DEBT SUSTAINABILITY Concept Debt Sustainability Indicators Interpreting Models Implementing with financial data IMF: Debt Sustainability Analysis Low-Income Countries Interactive Guide on Debt Sustainability Framework for Low- Income Countries: www.imf.org/en/publications/dsa Identifying models for tables and validation with figures; independently develop future projections as well. 15. DEBT TO GDP (some of the literature requires data updating for development assignments) Caner, Mehmet; Grennes, Thomas; Koehler-Geib, Fritzi, 2010, Finding The Tipping Point -- When Sovereign Debt Turns Bad,” Policy Research Working Paper Series 5391, The World Bank Pescatori, A., Sandri, D. and Simon, J. (2014). Debt and Growth: Is There a Magic Threshold? IMF Working Paper WP/14/34 Hennerich, H. (2020). Debt-to-GDP Ratio: How High Is Too High? It Depends, Federal Reserve Bank of St. Louis 16.BALANCE OF PAYMENTS CRISES Krugman, P. (1979). A Model of Balance-of-Payments Crises. Journal of Money, Credit and Banking, Vol. 11, No. 3, pp. 311-325 Calvo, G. A. (2000). Balance-of-Payments Crises in Emerging Markets: Large Capital Inflows and Sovereign Governments. In: Currency Crises. University of Chicago Press, p. 71 - 97 Pattillo, C. A. et al (2000). Anticipating Balance of Payment Crises: The Role of Early Warning Systems. IMF Occasional Papers (there may be some implementable tasks as assignments) Coutinho, L., Turrini, A. and Zeugner, S. (2018). Methodologies for the Assessment of Current Account Benchmarks. European Economy, Discussion Paper 086 (some implementable assignments) Evidence of capital flight (active investigation assignments for students) 17.CURRENCY CRISIS Radcliffe, B. (2021). What is a Currency Crises? Investopedia Krugman, P. R. et al (1999). Currency Crises. In: International Capital Flows. University of Chicago Press, p. 421 - 466 Krugman, Paul (2014). "Currency Regimes, Capital Flows, and Crises". IMF Economic Review. 62 (4): 470–493. Predicting Currency Crisis (requires implementation assignments) Berg, A. and Pattillo, (1998). Are Currency Crises Predictable? A Test. IMF WP/98/154 Berg, A. and Pattillo, C. (1999). Predicting Currency Crises: The Indicators Approach and an Alternative, Journal of International Money and Finance, Volume 18, Issue 4, Pages 561-586 Peltonen, T. A. (2006). Are Emerging Market Currency Crises Predictable? A Test. ECB Working Paper Series NO. 571 Inoue, A., & Rossi, B. (2008). Monitoring and Forecasting Currency Crises. Journal of Money, Credit and Banking, 40(2/3), 523–534. Xu, L., Kinkyo, T., & Hamori, S. (2018). Predicting Currency Crises: A Novel Approach Combining Random Forests and Wavelet Transform. Journal of Risk and Financial Management, 11(4), 86. MDPI AG Probit model Vlaar, P. J. G. Early Warning Systems for Currency Crises. Bank of International Settlements 18.QUALITATIVE VIEW OF ECONOMIES OECD System of Composite Leading Indicators How to interpret Assignments: will empirically investigate its accuracy in prediction for various past periods Global PMI (counterpart to priors) 19.ELEMENTS OF FINANCIAL CRISIS Stylized facts of Credit Booms and Sudden Stops Mendoza, E. G. and Terrones, M. E. (2012). An Anatomy of Credit Booms and Their Demise. NBER Working Paper 18379 Arena, M. et al (2015). Credit Booms and Macroeconomic Dynamics: Stylized Facts and Lessons for Low-Income Countries. IMF Working Paper WP/15/11 Borrowing Constraints and Fisherian Amplification Bianchi, J. and Mendoza, E. G. (2020). A Fisherian Approach to Financial Crises: Lessons from the Sudden Stops Literature. NBER Working Paper No. 26915. Note: there can be simulation development to follow. 20.MACROPRUDENTIAL INDICATORS & INSTRUMENTS PART A (requires implementation assignments) Evans, O. et al. (2000). Macroprudential Indicators of Financial System Soundness, IMF Occasional Paper 00/192 Hilbers, P., Krueger, R., Moretti, M. (2000). New Tools for Assessing Financial System Soundness, Finance and Development 37(3) PART B (concepts and logistics only) Lim, C. et al (2011). Macroprudential Policy: What Instruments and How to Use Them? Lessons from Country Experiences. IMF Working Papers 238 Capital Instruments Balla, E. and McKenna, A. (2009). Dynamic Provisioning: A Countercyclical Tool for Loan Loss Reserves. Economic Quarterly—Volume 95, Number 4—Pages 383–418 Leverage Ratios Restrictions on profit distribution 21.SPECIAL DRAWING RIGHTS Kenton, W. (2002). Special Drawing Rights (SDRs). Investopedia Arauz, A. and Cashman, K. (2021). November Data Shows More Countries Are Using Special Drawing Rights; Over 30 Countries Have Actively Used Most of Their New SDRs. CEPR Cashman, K., Arauz, A. and Merling, L. (2022). Special Drawing Rights: The Right Tool to Use to Respond to the Pandemic and Other Challenges. CEPR From the latter two articles there is obligation to have follow ups on data and updates on use by countries for speculation or confirmed objectives. 22. BASEL ACCORDS History and observation of the tangible/practical significant measures for each reform 23. Global Supply Chain Pressures, International Trade, and Inflation di Giovanni, J. et al (2022). Global Supply Chain Pressures, International Trade, and Inflation. Federal Reserve Bank of New York Staff Reports, No. 1024 Focus on section 3 and after Going from Baqaee and Farhi (2022) to Cakmaklı et al. (2021) Analysis, then logistics and practicality for the R environment 24. Montiel, P. J. (2002). "11 The Long-Run Equilibrium Real Exchange Rate: Theory and Measurement". In Macroeconomic Management. USA: International Monetary Fund. (requires implementation assignments) Prerequisites: Microeconomics II, Intermediate Macroeconomics, Macroeconomic Accounts Statistics Advanced Macroeconomics A course with such notorious title often ends up as being one of confusion and discouragement with seeming “rancid mathematical fodder cascade”. The aim of this course is to graduate from simpler economic models to immersion into DSGE and CGE. However, skills with simpler economic models is something that should not be thrown away. Grading --> Problem Sets 20% Labs with Excel, R, Dynare and GAMS 35% 3 Exams 45% Main Topics --> 1. Behrman, J. and Hanson, J. A. (1979). The Use of Econometric Models in Developing Countries. In: Short-Term Macroeconomic Policy in Latin America, NBER 2. Overlapping Generations Models and its relevance to fiscal policy 3. Advance review of monetary policy rules from Intermediate Macroeconomics. Observing how economic data encourages their implementation. 4. Development of Dynamic Stochastic General Equilibrium (DSGE) Identification & characteristics of constituent models & properties Compare and contrast with the following concerning economic behaviour, dynamics, policy and rules: Dynamic IS-LM, Dynamic AD-AS (being DAD-DAS and NOT DAD-SAS). Will try development of case studies. 5. Applications of DSGE models (active development) 6. Development of Computable General Equilibrium (GGE) Identification & characteristics of constituent models & properties Compare and contrast with the following concerning economic behaviour, dynamics, policy and rules: Dynamic IS-LM, DAD-DAS and Dynamic IS-LM-X 7. Applications of CGE (active development) Economic Assessment Trade Tradeoff Between Fixed & Floating Exchange Rates Natural Disasters Environmental regulations and policies Problem Sets --> A. Review Algebraic and numerical concerning the constituents for structure, properties and conditions. IS, LM, IS-LM AD, AS and AD-AS Algebraic, calculus and calibrations applied for dynamic models concerning the constituents for structure, properties and conditions. Followed by simulations: Dynamic IS-LM DAD-DAS A Dynamic IS-LM-X Overlapping Generations Model Applications in growth and fiscal policy B. DSGE Notion and applications Constituents for structure Properties and conditions of such constituents Calibrations and estimations C. CGE Notion and applications Constituents for structure Properties and conditions of such constituents Calibrations and estimations Labs with Excel, R, Dynare, DynareR and GAMS --> 1. Chosen lab topics from prerequisites 2. National Accounting (3-4) Assist for lab: https://unstats.un.org/unsd/nationalaccount/pubsDB.asp Assess current standard of living or the distribution of income within a population Assess effects of various economic policies Inflation determination 3. For the adjective econometric in Behrman, J. and Hanson, J. A. (1979), will investigate how such comes in. Practice runs as well. 4. Transitional Dynamics in Growth Models Macroeconomic Fast review of growth models and analysis key topics from prerequisite. Relevance of transitional dynamics in growth models to various economic terms, quantities and parameters of interest Methods, conditions and interpretations: analytical immersion Simulations in R 5. Overlapping Generations Models applied to fiscal policy To make use of DYNARE + OccBin Toolkit after analysis. DynareR can also be applied. 6. Model analysis and dynamics with simulations (like will be in good flow with course outline: Hartley, J. (Ed.), Hoover, K. (Ed.), Salyer, K. (Ed.). (1998). Real Business Cycles. London: Routledge. Concerns Chapter 2, Chapter 3, Chapter 7 and other chapters (from such text). Will make use of both past eras and modern times. 7. Advance review of Policy Rules For the following rules how does one arrive to such specific formulas? Pursue a transition that emphasizes similarities to increasing unique attributes. Are the rules of exact form for all countries? Compare rules and their results based on applying appropriate data Taylor rule Balanced-approach rule ELB-adjusted rule Inertial rule First-Difference rule Outcome-Based rule Nominal income targeting rule The references in the following may prove beneficial: https://www.federalreserve.gov/monetarypolicy/policy-rules-and-how-policymakers-use-them.htm 8. Monetary Transmission Mechanism Will observe/analyse the structure. Will then identify monetary rule(s) and tools for intended effects and channels. How do rules and tools influence the mechanism? 9. Role of Cobb-Douglas and CES in macroeconomics. Difference between Calibration and Estimation of Cobb-Douglas and CES (utility and production)? Overview, logistics and code development 10. Simulation with General Equilibrium: General Equilibrium R packages (CGE, GE) Note: acronym above for package doesn’t mean speifically Computable General Equilibrium. Analyse given reference literature to comprehend package structure. Then analyse reference manual. Apply to ambiances of interest 11. Dynamic Stochastic General Equilibrium (DSGE) Junior, C. J. C. and Garcia-Cintado, A. C. (2018). Teaching DSGE Models to Undergraduates. Economica A 19, 424 – 444 To make use of DYNARE + OccBin Toolkit after analysis. DynareR can also be applied Note: interests will go much further than article with development and simulation; sustainability with applications Calibrations/conditions. Estimation of open economy DSGE model, etc. Harrison, G.W. et al (2000). Using Dynamic General Equilibrium Models for Policy Analysis. Elsevier Devereux, M. (2000). A Simple Dynamic General Equilibrium Model of the Trade-Off Between Fixed & Floating Exchange Rates. London, Centre for Economic Policy Research. Attempts to apply conditions and circumstances for displays Case studies: from implementation of policies to withdrawal Estimations and forecasting 12. Computable General Equilibrium Will need some strong sessions for immersion with the GAMS environment before proceeding. Devarajan, S. and Go, D. S. (1998). The Simplest Dynamic General Equilibrium Model of an Open Economy. Journal of Policy Modelling 20(6): pages 677 – 714 Will have more advance models to treat common applications. Some resources: Burfisher, M. E. (2011). Introduction to Computable General Equilibrium Models, (2011). Cambridge University Press. Dixon, P. B. and Jorgenson, D. W. Eds. (2013). Handbook of Computable General Equilibrium Modelling SET, Volumes 1A and 1B. Elsevier Perali, F. and Scandizzo, P. (2018). The New Generation of Computable General Equilibrium Models: Modelling the Economy. Cham: Springer The following texts provide guidance for programming and simulation: Hosoe, N., Gasawa, K., & Hashimoto, H. (2010). Textbook of Computable General Equilibrium Modeling: Programming and Simulations, Palgrave Macmillan Limited. Chang, G. H. (2022). Theory and Programming of Computable General Equilibrium (CGE) Models: A Textbook for Beginners. World Scientific. --Note: after analysis will implement with use of data for wherever concerning interests; calibrations, estimations and forecasting 13. Comparing DAD-DAS and Dynamic IS-LM-X to DSGE and CGE concerning dynamics, forecasting, policies, rules and critique Prereqs: Macroeconomic Accounts Statistics, Intermediate Macroeconomics. Co-requisite: Probability & Statistics B Economics of Regulation Course will introduce role of government in markets where competitive equilibria is “good” or “fail.” Course will emphasize the importance of market structure and industrial performance, including the strategic interaction of firms. We will examine the behaviour of individual markets in some detail, focusing on cost analysis, the determinants of market demand, investment behaviour, market power, and the implications of government regulatory behavior. Reference Textbook --> Viscusi, W. K, Vernon, J. M. & Harrington, J. E. (2000). Economics of Regulation & Antitrust, MIT Press Resources (for group term report for assigned regulation) --> OECD (2009), Regulatory Impact Analysis: A Tool for Policy Coherence, OECD Reviews of Regulatory Reform, OECD Publishing, Paris OECD (2014), OECD Framework for Regulatory Policy Evaluation, OECD Publishing, Paris Emissions Trading in Practice, Second Edition: A Handbook on Design and Implementation. World Bank Group 2021 Course Grade Constitution --> Problem Sets Empirical Modelling Simulation Games Tasks Midterm Exam 1 Midterm Exam 2 Final Exam Group Term Report for Assigned Regulation Empirical Modelling --> Note: empirical modelling done according to flow of course. A. Will choose various markets from different regions of the globe to measure market competition and monopoly power. The following literature (all of them) will be applied to current data: OECD (2021), Methodologies to Measure Market Competition, OECD Competition Committee Issues Paper OECD (2022), Data Screening Tools in Competition Investigations, OECD Competition Policy Roundtable Background Note Pindyck, R. S. (1985). The Measurement of Monopoly Power in Dynamic Markets. The Journal of Law & Economics, 28(1), 193–222. (1984). Sloan School of Management Working Paper No. 1540-84: https://core.ac.uk/download/pdf/4379734.pdf For cases will pursue means to classify out of he following w.r.t. circumstances for consumers; measurement of consumer surplus and producer surplus. Competitive Monopolistic Competition Monopsony Oligopoly Oligopsony Are your findings harmonic with OECD’s set of indicators of product market regulation (PMR)? Why or why not? B. Methods of measuring externalities (to implement) Adhikari, S.R. (2016). Methods of Measuring Externalities. In: Economics of Urban Externalities. SpringerBriefs in Economics. Springer, Singapore. Simulation Guides/Tools --> Note: for any simulation game a group corresponds to a player. Notes and data recorded during games to prove quite essential. After each game students will be asked to generate a written summary based on questions developed by instructor to be rated. Questions will be relevant to the many topics in lectures. Simulations/Games done according to flow of course. White, F. (1994). Cooperative Learning through Simulation of Regulated Markets. Review of Agricultural Economics, 16(1), 83-91. University of California Berkeley, The Competitive Strategy Game (Severin Borenstein) Gambit (open-source collection of tools for doing computation in game theory) Externalities: Thomas P. Andrews (2002) The Paper River Revisited: A Common Property Externality Exercise, The Journal of Economic Education, 33:4, pages 327 - 332 Freeway Game: http://www.thefreewaygame.com An Experimental Pedagogy for Sustainability Ethics: The Externalities Games: < https://serc.carleton.edu/introgeo/games/examples/62222.html > Regulatory Impact & Decision Making: Musshoff, O. & Hirschauer, N. (2014) Using Business Simulation Games in Regulatory Impact Analysis – The Case of Policies Aimed at Reducing Nitrogen Leaching, Applied Economics, 46:25, 3049-3060 Ayadi H, et al (2014). SimPhy: A Simulation Game to Lessen the Impact of Phytosanitaries on Health and the Environment--the Case of Merja Zerga in Morocco. Environ Sci Pollut Res Int. 21(7): 4950-63 M. Buchholz, M., Holst, G. & Musshoff, O. (2016). Irrigation Water Policy Analysis using a Business Simulation Game. Water Resources Research, 52(10), pp. 7980-7998 Carbon Market Simulator – Vivid Economics Course Outline --> 1. The Role of Government Introduction to the course. The making of a regulation. Possible instrument choices. Why one instrument over another? Social Cost Benefit Analysis. Consequences of regulation. 2. Markets Types of markets: competitive, monopoly, monopsony, oligopoly, oligopsony, and monopolistic competition. Measurement of consumer surplus and producer surplus. The competitive market and economic efficiency. Monopolies and dead weight loss. Excluding (highly) competitive markets, can dead weight loss exist in other mentioned types of markets? If so, Are they as severe as the monopolistic case? Gains and losses from government intervention: price controls, price supports, taxes, subsidies, tariffs, import quotas. Oligopoly and collusion. Cournot-Nash equilibrium. Bertrand. competition. More on efficiency, relative to the perfectly competitive market model. 3. The Dominant Firm and Strategic Competition The dominant firm and the competitive fringe. Limit pricing and methods for deterring entry. 4. Introduction to Economic Regulation. Motivation behind economic regulation potential instruments for regulation. Goals of regulation. Historic background Stigler, G. J. (1971). The Theory of Economic Regulation. The Bell Journal of Economics and Management Science, 2(1), 3–21. 5. Public Enterprise The origins of public ownership as a way to regulate economic activity. Public vs Private ownership. Does the threat of nationalization/municipalization discipline private firms? 6. Regulating Natural Monopolies Electric Power, Natural Gas & Water Service Examples. Theory of natural monopoly. TASK: for recognised monopolies there will be effort to confirm or establish all such. One, example using electric power. Pricing strategies, rate structure, peak load pricing. Consequences: Averch-Johnson effect. Average Cost Pricing Rule Hayes, A. (2022). Average Cost Pricing Rule. Investopedia Kwoka, J. E. (2006). The Role of Competition in Natural Monopoly: Costs, Public Ownership, and Regulation. Review of Industrial Organization, 29(1/2), pages 127–147 TASK: after analysis there’s much interest in development counterparts for ambiances of interest. 7. Franchise Bidding Examples. Using franchise bidding as an alternative to regulation in the case of a natural monopoly. Issues with franchise bidding. Zupan, Mark A. (1989). The Efficacy of Franchise Bidding Schemes in the Case of Cable Television: Some Systematic Evidence. The Journal of Law & Economics 32, no. 2: 401–56 Identifying resolutions for issue identified in prior article 8. Dynamic Issues in Natural Monopoly Regulation What should a regulator do when an industry transforms over time due to exogenous changes that can either (1) change the optimal price or (2) change the industry from a natural monopoly into “something else”? Telecommunication Example. The regulation of wireless telephony. The importance of common standards. Lessons from Europe. Spectrum Auctions. 9. Transportation Regulation Surface Freight (Railroads and Trucks) 10. Effects of Regulation Joskow, P. L. and Rose, N. L. (1989). The Effects of Economic Regulation. In: R. Schmalensee & R. Willig (ed.), Handbook of Industrial Organisation, Edition 1, volume 2, chapter 25, pages 1449-1506, Elsevier. TASK: much emphasis on applying section 4, “Methodologies for Measuring the Effects of Regulation” to real cases based on above literature. Chambers, D., Collins, C.A. & Krause, A. (2019). How Do Federal Regulations Affect Consumer Prices? An Analysis of the Regressive Effects of Regulation. Public Choice 180, 57–90 TASK: in analysis of above literature it’s crucial to verify a causal relation between gov’t regulations and consumer prices. Pursue with ambiances if interest to draw conclusions. Yandle, B. (1989). Bootleggers and Baptists in the Market for Regulation. In: Shogren, J.F. (eds) The Political Economy of Government Regulation. Topics in Regulatory Economics and Policy Series, vol 4. Springer. 11. Regulations and programmes targeted for elimination In any ambiance there are often may regulations or acts targeted for elimination; however, policy impact can go beyond welfare loss. What methods are there to determine whether regulation is “doing what it was meant to do”, alongside non-monetised impacts? Impact evaluation overview: < https://en.wikipedia.org/wiki/Impact_evaluation >. Hence will have intimate logistics for impact evaluation with chosen case studies. 12. Externalities Cost-Benefit Approach: Harvey, J. (1994). Externalities and Cost-Benefit Analysis. In: Economics Revision Guide. Palgrave, London. Empirical development for positive and negative cases TASK: for above will not just shove stats and crossing/parallel lines to your face, rather you will build real CBA examples from the ground up with intelligence and real raw data; no lines or curves will be given to you nor will be necessarily desired. You will speculate on possible externalities from monetised and non-monetised analyses; identifying costs and benefits from the potential agents or elements. Note: for the monetised case make use of cost estimation guides for development; likewise for benefit. Note: non-monetised cost and benefit estimation guides also exist. To really comprehend one must know how to build. AGAIN: policy impact can go beyond welfare loss. What methods are there to determine whether regulation is “doing what it was meant to do”, alongside non-monetised impacts? Impact evaluation overview: < https://en.wikipedia.org/wiki/Impact_evaluation >. Hence may have logistics for chosen case studies. Ross, S. (2021). How is a Market failure Corrected? Investopedia “Market failures can be corrected through government intervention, such as new laws or taxes, tariffs, subsidies, and trade restrictions.” Concerning the latter four interventions, how are such modelled or how are the quantities derived? Fritsche, U.R. (1994). Modelling Externalities: Cost-Effectiveness of Reducing Environmental Impacts. In: de Almeida, A.T., Rosenfeld, A.H., Roturier, J., Norgard, J. (eds) Integrated Electricity Resource Planning. NATO ASI Series, vol 261. Springer, Dordrecht. TASKS: can we make the literature of Fritsche practical for ambiance of concern? Attempt with development logistics and data sources. Property rights and common property resources. 13. The Value of Life Why do we need to put an economic value on life? The calculation of the value of life and how it is used in economic analysis. Adjustment of VSL for Inflation and Real Income Growth? Albrecht, Gary R. (1992). Issues Affecting the Calculated Value of Life, Journal of Forensic Economics, vol. 5, no. 2, pp. 97–104 TASK: method in above article may be adopted. Will like active pursuits with such. Incorporate inflation and real income growth if not incorporated. Disability-adjusted life year (DALY) Concept and role in health economics regulation Calculation Quality-adjusted life years (QALYs) Concept and role in health economics regulation Calculation Supporting Articles: Prieto L, Sacristán JA. (2003). Problems and Solutions in Calculating Quality-Adjusted Life Years (QALYs). Health Qual Life Outcomes.1:80. Sassi, F. (2006). Calculating QALYs, Comparing QALY and DALY Calculations, Health Policy and Planning, Volume 21, Issue 5, Pages 402–408 TASK: (1) to compute DALY and QUALY for ambiance of interest; (2) above prior two articles for active pursuits Analytical and Quantitative structure of Cost-Effectiveness Analysis 14. Environmental Regulation Background of regulation in the [chosen ambiance]. Price versus quantity restrictions. Command and control versus market-based incentive programs. Markets for clean air Idea and basics of auctions The example of markets for SO2 permits and how they operate. Assisting literature: EPA-How Do Emissions Trading Programmes Work? Limit on Pollution Emissions: https://www.epa.gov/emissions-trading-resources/how-do-emissions-trading-programs-work EPA-Frequent Questions about the Acid Rain Program Allowance Auction: https://www.epa.gov/airmarkets/frequent-questions-about-acid-rain-program-allowance-auction#where_do_allowances_come_from TASK: the following two articles to analyse, then pursue development with more modern data and compare with years treated in the articles Joskow, P. L., Schmalensee, R., & Bailey, E. M. (1998). The Market for Sulfur Dioxide Emissions. The American Economic Review, 88(4), 669–685. Hitaj, C. & Stocking, A. Market Efficiency and the U.S. Market for Sulfur Dioxide Allowances. Congressional Budget Office, WP 2014-01 Electricity Tariff Design Concept Model Freier, J. And von Loess, V. (2022). Dynamic Electricity Tariffs: Designing Reasonable Pricing Schemes for Private Households. Energy Economics 112, 106146 15. The Regulation of Workplace Safety Regulatory approaches to safety evaluation and enforcement. Assessment of the benefits of health and safety legislation TASK: the following article to be analysed, then pursuit of development for ambiance and industry of interest: Thiede I. & Thiede M. (2015). Quantifying the Costs and Benefits of Occupational Health and Safety Interventions at a Bangladesh Shipbuilding Company. Int J Occup Environ Health. 21(2):127-36 16. Copyright Watt, R. (2009). An Empirical Analysis of the Economics of Copyright: How Valid are the Results of Studies in Developed Countries for Developing Countries? In: The Economics of Intellectual Property - Suggestions for Further Research in Developing Countries and Countries with Economies in Transition. World Intellectual Property Organisation What are the costs and benefits of tougher enforcement of record companies’ property rights? Prerequisites: Microeconomics II, Calculus for Business & Economics III

Industrial Organisation Industrial Organisation is concerned with the study of imperfect competition (i.e., functioning of markets with few competitors). The existence of a small number of competitors generates situations of strategic interactions among the market participants. The course will explore a wide range of possible market structures and the competitive and cooperative strategies employed by profit maximizing firms when there are few firms, entry barriers, differentiated products, and/or imperfect information. Textbook of Interest --> Pepall, L., Richards, D. & Norman, G. Industrial Organization: Contemporary Theory and Empirical Applications, Wiley Assisting Text --> Choi, P., Dunaway, E. and Munoz-Garcia, F. (2021). Industrial Organisation – Practice Exercises with Answer Keys. Springer Cham Assessment --> Class Participation 5-6 Problem Sets Labs 3 Examinations Labs --> NOTE: labs concern data analysis and simulations/games. Labs will align with course topics. SIMULATIONS: for the simulations/games a player will consist of a certain number of students in a group. Notes and data recorded during games to prove quite essential. After each game students will be asked to generate a written summary based on questions developed by instructor to be rated. Questions will be relevant to the many topics in lectures. Scheduled simulations/games activities from the following: < https://economics-games.com < https://www.moblab.com/moblab-industrial-organization-courses DATA ANALYSIS: for data analysis focus is development rather than imposed mediocrity cap from condescending upper-level knuckle heads, sentient viruses and con artists. -Advance repetition of chosen labs from Economics of Regulation course. -Demand Estimation-- A. Data Description The credibility and success of empirical work will hinge on the data that is leveraged. Depending on the industry and the application, data may be plentiful or sparse; it is always preferable to rely on richer data (when available and accessible at reasonable cost (both time and financial)) to inform our estimates than to implicitly assume them through structure or assumptions. That said, research is all about navigating these tradeoffs (and being explicit and honest about them). To anchor discussion, the data that we should have in mind when discussing demand estimation tends to look as follows: • The unit of observation will be quantity of product purchased (say 12 oz Bump Belly beer) together with a price for a given time period (say a week) at a location (Store, ZIP, MSA, state, country...). • You will generally need to take a stance on the relevant market and set of products within a consumer’s choice set; in addition, there typically is an outside good (e.g., non-purchase) that you will need to control for (either with data or via assumptions). • Today, there is now a large amount of consumer-level purchase data collected by marketing firms (for instance the ERIM panel used by Ackerberg RAND 1997 to look at the effects of TV ads on yogurt purchases). Yey, the vast majority of demand data is aggregated at some level. As we will discuss, less-aggregated data tends to allow us to estimate more detailed (ambitious) models. • Note that you often have a lot of information: you can get many characteristics of the good (Alcohol by volume, calories, etc.) from the manufacturer or industry publications or packaging since you know the brand. The location means we can merge the demand observation with census data to get information on consumer characteristics. The date means we can look at see what the spot prices of likely inputs were at the time (say gas, electricity etc.). • Typical data sources: industry organizations, marketing and survey firms (e.g. AC Nielson), proprietary data from manufacturer, marketing departments have some scanner data online (e.g. Chicago GSB). • The survey of consumer expenditures also has some information on person-level consumption on product groups like cars or soft-drinks. • More often than not, data will require some ingenuity, luck, and a lot of elbow grease to obtain. Theory can help fill in some holes, but at the end of the day, good data (and variation!) is necessary for a convincing paper. • Data files or data pursuits via introspection and wrangling; would be a lab in itself. Investigative development is important to comprehend a credible process. B. Guiding text for manual R development: Berry, S. T. & Hale, P. A. (2021). Chapter 1 – Foundations of Demand Estimation. In: Handbook of Industrial Organisation, 4(1), pages 1 – 62 C. Development with the R package BLPestimatoR; given package comes with a vignette. This package will be applied despite whatever results from (B). Compare with any findings from (B). COURSE TOPICS --> 1- Introduction • Introduction to Industrial Organization: PRN Chapter 1. • Review of Basic Microeconomic Theory: – Technology and Costs. PRN Chapter 4.1 (excluding 4.1.3). – Competition versus Monopoly. PRN Chapter 2 (excluding 2.3 and 2.4). 2- Market Structure and Market Power • Concentration Measures and Evidence. PRN Chapter 3. • Cost and Non-Cost Determinants of Market Structure. PRN Chapter 4 (excluding 4.1.1, 4.1.2, and 4.6). 3- Monopoly Pricing Schemes • Durable Goods. PRN Chapters 2.3.3, and 2.3.4. • Third degree price discrimination. PRN Chapter 5 (excluding 5.6). • First degree price discrimination. PRN Chapter 6 (excluding 6.1.2, and 6.4). • Second degree price discrimination. PRN Chapter 6(excluding 6.1.2, and 6.4). • Tie-in sales and bundling. PRN Chapter 8 (excluding 8.1.1, 8.1.2, 8.1.3, and 8.5). 4- Product Variety and Quality Under Monopoly • Product Variety. PRN Chapters 7.1, 7.2 and 7.3. • Product Quality. PRN Chapter 7.5.1. 5- Basic Oligopoly Models • Game Theory: Static Games. PRN Chapters 9.1-9.3 or Gibbons Chapter 1 (pp 1-12). • Static Competition: – Homogeneous Goods: PRN Chapters 9.4-9.5 and 10.1. or Gibbons Chapter 1.2.A. – Differentiated Goods: PRN 10.2-10.3, or Gibbons Chapter 1.2.B. • Game Theory: Dynamic Games. PRN Chapter 11 (excluding 11.5), or Gibbons Chapters 2.1, 2.2 and 2.3 (skip the complex applications). 6- Anticompetitive Behavior and Antitrust Policy • Entry Deterrence. PRN Chapters 12 (excluding 12.2.2, 12.3.1, and 12.5), 13.2.2 and 13.3.2. • Predatory Conduct. PRN Chapter 13 (excluding 13.3.1, 13.3.3, and 13.6). • Price Fixing, Repeated Interaction, and Antitrust Policy. PRN Chapter 14 (excluding 14.4.1 and 14.5) and Appendix to Chapter 1. 7- Mergers • Horizontal Mergers. PRN Chapter 15 (excluding 15.5.2, and 15.7). • Vertical and Conglomerate Mergers. PRN Chapter 16 (excluding 16.3, 16.4, 16.6, and 16.7). 8- Non-Price Competition • Advertising. PRN Chapter 19 (excluding 19.5 and 19.6). 6 • Innovation (Research and Development). PRN Chapter 20 (excluding 20.3, 20.5, and 20.6) Prerequisites: Microeconomics III, Mathematical Statistics. Co-requisite or Prerequisite: Economics of Regulation Computational Studies of Mergers & Acquisitions Course serves to introduce students to practical methods and tools for the investigation of markets and industries welfare. Course structure progression serves to able students to administer case studies and possible future scenarios intimately. Complacency, effort and devotion are keys to success in this course. COMPONENTS OF COURSE: (A) Empirical Investigations (with R environment). The following are “stand-by articles” to be related to obligations in (B) if deemed constructive. Sectors or industries are subject to change in the interest of (B) and more modern data availability; also possibly serving as extra credit. Sumner. (1981). Measurement of Monopoly Behavior: An Application to the Cigarette Industry. The Journal of Political Economy, 89(5), 1010–1019. Goldberg. K, (1995). Product Differentiation and Oligopoly in International Markets: The Case of the U.S. Automobile Industry. Econometrica, 63(4), pages 891–951. Mullin, W. & Genesove, D. (1998). Testing Static Oligopoly Models: Conduct and Cost in the Sugar Industry, 1890-1914. The Rand Journal of Economics, 29(2), 355–377 Nevo, A. (2011). Empirical Models of Consumer Behaviour, Annual Reviews, Volume 3, pp 51 – 75 Valletti, T., and Zenger, H. (2021). Mergers with Differentiated Products: Where Do We Stand? Rev Ind Organ 58, 179–212 (B) Immersive Computational Participation (with R environment) (B1) Market Power: Concentration Ratio, Herfindahl-Hirschman Index and Lerner index Baker, J. B. & Bresnahan, T. F. (1988). Estimating the Residual Demand Curve Facing a Single Firm, International Journal of Industrial Organisation, 6(3), pp 283-300 Bresnahan, T. F. (1989). Chapter 17 – Empirical Studies of Industries with Market Power. In: Handbook of Industrial Organisation, Volume 2, pages 1011 – 1057 Nevo, Aviv. 2001. “Measuring Market Power in the Ready-to-Eat Cereal Industry.” Econometrica, 69(2): 307–42 Note: consider other industries today besides cereal Market Definition (to pursue): < https://www.ee-mc.com/tools/market-definition.html > (B2) Demand Estimation Development: Review and advance recital of labs (A) and (B) from IO course. BLPestimatoR R package immersion and its motivation Berry, S., Levinsohn, J., & Pakes, A. (1995). Automobile Prices in Market Equilibrium. Econometrica, 63(4), 841–890. Note: consider other industries today besides automobiles Nevo, Aviv. 2000. “A Practitioner’s Guide to Estimation of Random-Coefficients Logit Models of Demand.” Journal of Economics and Management Strategy, 9(4): 513–48 Gandhi, A. & Nevo, A. (2021). Chapter 2 – Empirical Models of Demand and Supply in Differentiated Products. In: Handbook of Industrial Organisation, 4(1), pages 63 – 139 (B3) Merger Simulation Models Oliver Budzinski & Isabel Ruhmer, (2010), Merger Simulation in Competition Policy: A Survey, Journal of Competition Law and Economics, 6(2): pages 277-319. < https://www.ee-mc.com/tools/merger-simulation-models.html > Further literature (optional): Epstein, Roy J., and Daniel L. Rubinfeld. (2002). Merger Simulation: A Simplified Approach with New Applications. Antitrust Law Journal 69, no. 3: 883–919. Wen-Jen Tsay & Wei-Min Hu (2022) Merger Simulation based on Survey–Generated Diversion Ratios, European Competition Journal, 18:2, 249-264 (B4) Merger Simulation via designated R package antitrust Package also come with a vignette for antitrust R package: https://cran.r-project.org/web/packages/antitrust/vignettes/Reference.html (B5) Merger Guidelines Note: stages B1 to B4 serve as “walkthrough” to apply guidelines. Premerger & Acquisition Guidelines Project (2-3 mergers or acquisitions) Horizontal merger guidelines: Department of Justice & Federal Trade Commission Merger Guidelines (check website or use search engine). Also, apply also its commentary document) Supporting literature Wang, X. and Vistnes, D. (2013). Economic Tools for Evaluating Competitive Harm in Horizontal Mergers. Thomson Reuters Vertical mergers literature: Wong, E. K. (2018). Antitrust Analysis of Vertical Mergers: Recent Developments and Economic Teachings. ABA Antitrust Source Additional literature: Walker, J. (2020). Economic Analysis in Merger Investigations. 2020 OECD Global Forum on Competition Discussion Paper (B6) Evaluating the Performance of Merger Simulation (C) Collusion literature to emulate for interests: Bolotova, Y., Connor, J. & Miller, D. (2008). International Journal of Industrial Organization. 26. 1290-1307. Bonnet, C. & Bouamra-Mechemache, Z. (2019). Empirical Methodology for the Evaluation of Collusive Behaviour in Vertically-Related Markets: An Application to the "Yogurt Cartel" in France. International Review on Law & Economics, 61, 105872 (D) Cartel Detection https://www.ee-mc.com/tools/cartel-detection/cartel-screening.html (E) Damage Calculation https://www.ee-mc.com/tools/damage-calculation.html (F) Antitrust Cases & Future Scenarios (F1) Analysing antitrust cases (2-3). Acquire the legal documentation. Will make use of acquired intelligence, skills and tools stemming from (A) through (E). Do cases outcomes agree with your analyses? (F2) Predicting Mergers and Acquisitions Note: various other industries may be pursued. Training and testing of models expected. Adelaja, A.O., Nayga, R.M., & Farooq, Z. (1999), Predicting M&A in the Food Industry. Agribusiness, 15(1), 1-23. R. Moriarty, H. Ly, E. Lan and S. K. McIntosh, "Deal or No Deal: Predicting Mergers and Acquisitions at Scale," 2019 IEEE International Conference on Big Data (Big Data), 2019, pp. 5552-5558 Prerequisites: Microeconomics III, Industrial Organisation, Mathematical Statistics

Public Finance The branch of economics that assesses the government revenue and government expenditure of the public authorities, and the adjustment of one or the other to achieve desirable effects and avoid undesirable ones. Course is just as important as monetary policy courses, hence prerequisites given are necessities, forcing upper level standing for recognition of the importance of practical skills in public finance; sound footing for good reacquaintance with advance pursuits. NOTE: an 18 weeks course, with 2 hours per session and 3 sessions per week; labs hours are unique to session hours. Course Literature --> NOTE: there will be no standard text for this course. Topics and literature given to be applied. Tools for labs and written paper --> R + RStudio Microsoft Office Assessment --> Groups Labs (highly quantitative substance) 60% --> Note: for labs instructor traverses thoroughly the ideas, purposes and logistics for implementation; implementation is the responsibility of student groups. The given labs to be done in the most constructive order THAT CONNECTS WELL WITH THE MANDATORY COURSE TOPICS: Tasks mentioned in mandatory course topics 20% Group Written Term Paper 20% --> Groups will complete a term paper (15 to 20 pages) on a fiscal policy of their choice. A policy must be selected by no more than one group (on a first come basis). You will document your fiscal policy in a way that uses the theories, skills and tools from course topics and labs. The assignment guide will give more refined details. Due 1 week after final lab. GROUP LABS --> 1. National Accounting Assists for this lab: SNA 2008 https://unstats.un.org/unsd/nationalaccount/pubsDB.asp Insight into how an economy is performing Determine the effect of various economic policies Guidance regarding inflation policy and can be especially useful in the transitioning economies of developing nations Statistics for production levels identifying shifting labour forces Using aggregate National Accounts data to estimate future tax revenues for main taxes. Methods (as in plural) for measuring the size of gov’t Note: may not exclusively depend on national accounts. 2. Public Revenue profile for 4-12 years compared to various dynamics (employment, household income, household taxes and business taxes) via exploratory data analysis development in R. Note: time series is also applicable. 3. Density plots for income distribution and apply log transformation... Income density plots for a society with inequality at the bottom and a society with inequality at the top. Development of income thresholds: Low income: income that is less than 60% of the median Middle income: income between 60% and 200% of the median High income: income that is greater than 200% of the median To really understand the difference between the two societies, we need to look at the income distributions using a logarithmic transformation. Under a (”one-to-one”) log transformation: {1, 10, 100, 1000} --> {0, 1, 2, & 3}; such compresses the distribution, allowing to better see both the left and right tails. Seeing these tails is important because that’s where the inequality lives. Using a log transformation, replot our income density curves. Evolution of income distribution for chosen amount of years Estimating elasticities of taxable income for various income brackets for a chosen economy and years with a common method. 4. Elements in a Budget Analysis Balaguer-Coll M.T. (2018) Budget Analysis. In: Farazmand A. (eds) Global Encyclopedia of Public Administration, Public Policy, and Governance. Springer, Cham. PP 401 - 409 Analysis of public record DD/MM/YYYY Include entitlement versus discretionary profiling Analysis of Public Expenditure at “end cycle” compared to prior Include applying the mentioned budget indicators in above literature with real data. 5. Forecasting (quantitative and qualitative techniques) Literature options for development: International Monetary Fund. (1985). " Chapter 9 WORKSHOP 7 Revenue Forecasting". In Financial Policy Workshops. USA: International Monetary Fund GFOA: Financial Forecasting in the Budget Preparation Process Williams, D. and Calabrese, T. (2019). The Palgrave Handbook of Government Budget Forecasting. Palgrave Macmillan Model for baseline budget projections. Will implement some elements 6. Empirical tools for taxes Will choose topics from the following texts to implement Sorensen, P. B. (2022). Measuring the Tax Burden on Capital and Labour. MIT Press Li, H. and Pomerleau, K. Measuring Marginal Effective Tax Rates on Capital Income. Fiscal Fact No. 687, 2020 Li, H. (2017). “Measuring Marginal Tax Rate on Capital Assets. Tax Foundation. Overview of the Tax Foundation’s Tax and Growth Model”. Tax Foundation 7. To analyse and develop towards fiscal policy concerns: Auerbach, A. J. and Kotlikoff, L. J. (1983). National Savings, Economic Welfare, and the Structure of Taxation." Behavioral Simulation Methods in Tax Policy Analysis, edited by Martin Feldstein. Chicago: University of Chicago Press, (1983), pp. 459-498. Note: NBER version exists Try to use such to project respective policy or scenario for a past period; set prior conditions/parameters/values towards the simulations, and observe accuracy. Note: not concerned with periods of economic shocks. 8. Dynamic Scoring (to implement/simulate for various conditions) Coherent concept Scope of structure and modelling. Possible differentiation from (7) Logistics towards implementation The following gives a more rounded idea: Mankiw, N. G. and Weinzierl, M. (2004). Dynamic Scoring: A Back-of-the-Envelope Guide. NBER Working Paper 11000 Lynch, M. S. and Gravelle, J. G. (2021). Dynamic Scoring in the Congressional Budget Process. CRS Report R46233 9. Applying NBER’s TAXSIM (R package for TAXSIM: usincometaxes) or EUROMOD (must find or develop one’s own data or hypothetical data). May need to have comparative/contrasting understanding to (7) and (8); Notion, structure, modelling, comprehending inputs and outputs Make data adjustments to concern ambiance of interest Logistics for implementation, then actual implementation 10. Auerbach, A. J., & Kotlikoff, L. J. (1987). Evaluating Fiscal Policy with a Dynamic Simulation Model. The American Economic Review, 77(2), 49–55 Try to use such to project respective policy or scenario for a past period; set prior conditions/parameters/values towards the simulations, and observe accuracy. Note: not concerned with periods of economic shocks. Will implement for future concerns as well. 11.Tax Incentives EITC Cost Williams, E., Waxman, S. and Legendre, E. (2020). How Much Would a State Earned Income Tax Credit Cost in Fiscal Year 2021? Centre on Budget and Policy Priorities Interest in above article is applying: -Data Sources (substitute country data of interest) -Three Steps to Estimating the Cost of a State EITC Note: there are benefits (monetised & non-monetised) to consider for the respective EITC Cost-Benefit Analysis (CBA) Chen, D. (2015). The Framework for Assessing Tax Incentives: A Cost – Benefit Analysis Approach. UN Paper for Workshop on Tax Incentives and Base Protection New York, 23-24 April 2015 Kronfol, H. and Victor Steenbergen, V. (2020). Evaluating the Costs and Benefits of Corporate Tax Incentives: Methodological Approaches and Policy Considerations. The World Bank Group 12. Cost-Benefit Analysis for public projects for investments From provincial or city agendas will identify some proposed projects or investments and apply Cost-Benefit Analysis. There are guides to build your CBA rather than accepting “phantom numbers”. Monetised impacts. Make use of cost estimation guides for development; likewise for benefit. Non-monetised impacts case analyses There exists guides Discounting development Gollier, C. (2002). Discounting an Uncertain Future. Journal of Public Economics, Vol. 85 Issue 2, pp. 149 – 166 Weitzman, Martin, L. 2001. Gamma Discounting. American Economic Review, 91 (1): 260-271. Freeman, M. C. and Groom, B. (2016). How Certain are We about the Certainty-Equivalent Long Term Social Discount Rate? Journal of Environmental Economics and Management, Vol 79, pp. 152 – 168 RIMS -II, IMPLAN, Chmura, LM3 or REMI may factor in Campbell, H., & Brown, R. (2003). Benefit-Cost Analysis: Financial and Economic Appraisal using Spreadsheets (pp. 194-220). Cambridge: Cambridge University Press 13. Externalities How to identify externalities in the real world Measuring Externalities (to be implemented) Cost of Damages and Cost of Control Adhikari S.R. (2016) Methods of Measuring Externalities. In: Economics of Urban Externalities. SpringerBriefs in Economics 14. Fiscal Measures (with gov’t data) PART A Benz, U. and Fetzer, S. (2006). Indicators for Measuring Fiscal Sustainability: A Comparison of the OECD Method and Generational Accounting, FinanzArchiv/ Public Finance Analysis, Vol. 62, No. 3, pp. 367-391 (25 pages). PART B Fiscal Health Analysis for chosen public services, public goods, etc. Scale choices (provincial or city or borough). Assisting guides for pursuits: Suarez V., Lesneski C. and Denison, D. (2011). Making the Case for using Financial Indicators in Local Public Health Agencies. Am J Public Health 101(3), pages 419-25. McDonald, B. D. (2018). Local Governance and the Issue of Fiscal Health, State and Local Government Review, 50(1), 46–55. Framework & measures, computational logistics, implementation NOTE: augment with Beneish, Dechow F, Modified Jones and Altman Z PART C Fiscal Consolidation with General Equilibrium Treatment (pursuit development for ambiance of interest) Wouters, R. (2014). Fiscal Consolidation in General Equilibrium Models, Bank of International Settlements Hurnik, J. (2004). Fiscal Consolidation in General Equilibrium Framework – the Case of the Czech Republic. Prague Economic Papers. vol. 2004(2), pages 142-158. 15. Public Pension Projections Economic Policy Committee and Directorate-General for Economic and Financial Affairs. (2007). Pension Schemes and Projection Models in EU-25 Member States. European Economy Occasional Papers, No.35 The goal is to develop projections for future years. The process for projects will involve comprehension of the schemes, models and relevant data towards projections. Compare with projections of the governments. Then, to determine which scheme and model best projects a public pension in your ambiance. MANDATORY COURSE TOPICS --> 1.Introduction 2.The Public Sector 3.The Idea of Redistribution 4.National Income Accounting 5.Public Goods 6.Public Provision of Private Goods 7.Social Insurance and Redistribution 8.Bourguignon, F., Spadaro, A. Microsimulation as a Tool for Evaluating Redistribution Policies. J Econ Inequal 4, 77–106 (2006). 9.Size of Gov’t & Efficiency PART A In-class comparative development with the following (with ambiances of interest): Berry, W. D., & Lowery, D. (1984). The Journal of Politics, 46(4), 1193–1206. Garand, J. (1989). Social Science Quarterly 70(2); 487 Ferris, J. S., & West, E. G. (1996). Southern Economic Journal, 62(3), pages 537–553 Armey Curve and BARS Curve PART B In-class comparative development with the following (with ambiances of interest): Cepal (2015). Methods of Measuring the Economy, Efficiency and Public Expenditure, Annex 7 Diamond, J. (1990). "9 Measuring Efficiency in Government: Techniques and Experience". In Government Financial Management. USA: International Monetary Fund. 10.The institutions and theory of taxation (incidence, inefficiencies, optimisation) 11. Automatic Stabilizers Taxation in Society Tax Multiplier Issue of varying MPS among different households (and possibly businesses) Taxation & Labour Supply What macroeconomic models can explain the taxation and labour supply relationship? Followed by analysis of data to vindicate models. Tax burden on savings versus tax burden on consumption Automatic Stabilizers Design of income tax instruments (households, businesses, sales tax) concerning economic shocks, recessions and expansion. Transfers (unemployment, food funds assistance, Medicare, child credits, other credits, subsidies, etc., etc.). Do all transfers have built in mechanisms for inflation? Identify the quantitative elements. Means to show how government taxation and spending change automatically when real GDP changes (either direction) in the short run with the AD-AS model; analytic modelling/algebraic structure and numerics are the concern, NOT curve shifts. Augment with DAD-DAS modelling and simulation. Supporting literature for development for automatic stabilizers (adjust to ambiance and settings): Eilbott. (1966). The Effectiveness of Automatic Stabilizers. The American Economic Review, 56(3), 450–465. Chalmers, & Fischel, W. A. (1967). An Analysis of Automatic Stabilizers in a Small Econometric Model. National Tax Journal, 20(4), 432 Follete, G. and Lutz, B. (2010). Fiscal Policy in the United States: Automatic Stabilizers, Discretionary Fiscal Policy Actions, and the Economy. Federal Reserve Board Mattesini, F. & Rossi, L. (2012). Monetary Policy and Automatic Stabilizers: The Role of Progressive Taxation. Journal of Money, Credit and Banking, 44(5), 825–862. Russek, F. and Kowalewski, K. (2015). How CBO Estimates Automatic Stabilizers. Congressional Budget Office, Working Paper 2015-07 Maravalle, A. and Rawdanowicz, L. (2020). How Effective are Automatic Fiscal Stabilizers in the OCED Countries? OECD Economics Working Papers No. 1635 12.Dynamic Scoring 13.Treasury Budget Investopedia Team (2021). U.S. Treasury Budget. Investopedia Above article has many statements to clarify, and mandatory verification by use of economic models (with real market data) and statistical methods. Such monthly report is observed as a useful indicator of the government's current financing needs, which influences market interest rates. Concerning bonds, notes and bills, how is the “debt portfolio” constructed to meet the budget or deal with deficits concerning maturities? Should be related to deficit, and revenue expectations/forecasting. Is cash flow matching linear programming (or asset-liability LP) practical? If so, is it the best method? For a deficit, the report details the mix of long, medium, and short maturity debt used to finance it. Miller, P. J. (1983). Higher Deficit Policies Lead to Higher Inflation. Federal Reserve Bank of Minneapolis. Quarterly Review, Winter Is the title of the article relevant in more modern times? Would correlation be enough to prove or disprove such? Proceed regardless of answer, along with alternative possible robust methods of determination. Different ambiances may be considered as well. Catao, L. & Terrones, M. E. (2003). Fiscal Deficits and Inflation. IMF Working Paper WP/03/65 (concerns priors) 14.Public Expenditure Management Entitlement Spending and Discretionary Spending. Implicit Obligation examples (Medicare costs, retirement benefits, social welfare). Is it unique to entitlement spending? Chand, S. 11 Main Causes of Growth of Public Expenditures – Explained! Your Article Library: https://www.yourarticlelibrary.com/economics/11-main-causes-of-growth-of-public-expenditures-explained/26304 For such alleged causes determine whether there are overlaps? Then pursue empirical analysis and exploratory data analysis for verification. Borcherding, T. E. (1985). The Causes of Government Expenditure Growth: A Survey of the U. S. Evidence. Journal of Public Economics 28(3), 359 – 382 Does above journal article capture all causes in Chand’s article? Budget Analysis Balaguer-Coll M.T. (2018) Budget Analysis. In: Farazmand A. (eds) Global Encyclopedia of Public Administration, Public Policy, and Governance, Springer, Cham. PP 401 - 409 Public Deficit. Laws enacted for failure to meet deficit target. Potter, B. H. and Diamond, J. (1999). Guidelines for Public Expenditure Management. International Monetary Fund Note: establish provincial/city counterparts to prior [with identification of the balanced budget requirement law(s), ex-post BBR and ex-ante BBR]. Design and Conduct of Public Expenditure Reviews 15.Budget Forecasting Williams, D. and Calabrese, T. (2019). The Palgrave Handbook of Government Budget Forecasting. Palgrave Macmillan Focus on identifying a robust framework and model. Then fluid and practical quantitative elements involved. 16. Public Debt Probasco, J. (2021). The National Debt Explained. Investopedia. Evolution of debt modelled on prior debt, interest paid on prior debt and prior deficit. Can such be used for highly accurate forecasts? Validate or discredit, along with other forecasting alternatives. Blanchard, O. (2017). Chapter 22 – Fiscal Policy: A Summing Up. In: Macroeconomics. Pearson. Cole, Harold L., (2019). Chapter 16 - Modelling Government Debt and Inflation, In: Finance and Financial Intermediation: A Modern Treatment of Money, Credit, and Banking, Oxford Academic Intemporal Budget Constraint (BC): relating present discounted value (PDV) of gov’ts obligations to the PDV of its revenues. Some of the elements to consider PDV of remaining tax payments of existing generations PDV of tax payments of future generations PDV of all future gov’t consumption Inflation Current gov’t debt What models best represent or analyse w.r.t. such above elements? Will be implemented and tested. Fiscal Indicators and Fiscal Health Analysis Tools applied to avoid breach of debt ceiling Orrnert, A. (2019). Options for Managing a Sudden Rise in Public Debt. K4D Will have case studies for countries of interest with use of gov’t repositories. Particularly for Fiscal consolidation the following may be good development with inclusion of modern data, but countries outside of OECD may be an issue: Molnár, Margit (2012). Fiscal Consolidation: What Factors Determine the Success of Consolidation Efforts? OECD Journal: Economic Studies, Vol. 2012/1. 17.Fiscal Policy Purpose Liquidity Trap (LT) Features Relevance of AD-AS and DAD-DAS with economic standing and fiscal resolutions. Analytic modelling/algebraic structure, numerics and simulation scenarios are the concern, NOT curve shifts. 18. Effect of Gov’t on Economy Ganti, A. and Estevez, E. (2021). Fiscal Multiplier. Investopedia Fiscal Multiplier. How to credibly verify that FM is the clear cause? Issue of varying MPC among different households; MPC also depends on the form in which fiscal stimulus is received. For contractionary policies is such multiplier meaningful for evaluation? Will the Multiplier Effect (ME) always be a correct measure of the Crowding-Out Effect (COE)? What macroeconomic models can explain the COE? Fiscal deficit, can in theory, boost a sluggish economy by giving more money to people who can then buy and invest more. Long-term deficits, however, can be detrimental for economic growth and stability. OLG model or Auerbach-Kotlikoff model type? For the following literature, after analysis to make use of the identified models with chosen settings to evaluate: Gale, W. G. and Samwick, A. (2014). Effect of Income Tax Changes on Economic Growth. Brookings Institute. What type of countries prevail with running public deficits for long periods? What differentiates countries with favourable outcome to those with unfortunate outcome? Pursue model for such two questions. 19.Cost-Benefit Analysis (CBA) Must be well rounded and highly logistical to serve computational pursuits Recognition of stakeholders Costs and Benefits Monetised elements Non-monetised elements Discounting (active development) Gollier, C. (2002). Discounting an Uncertain Future. Journal of Public Economics, Vol. 85 Issue 2, pp. 149 – 166 Weitzman, Martin, L. 2001. Gamma Discounting. American Economic Review, 91(1): 260-271. Freeman, M. C. and Groom, B. (2016). How Certain are We about the Certainty-Equivalent Long Term Social Discount Rate? Journal of Environmental Economics and Management, Vol 79, pp. 152 – 168 Tools such RIMS II, IMPLAN, Chmura, LM3 may factor into CBA. 20. Market Efficiency, Externalities & Resolutions 21. Public Transactions (public fees and fines) A. Finance and Revenue Management in Public Transportation Financial modelling via financial statements for chosen service Revenue Management or transportation engineering have unavoidable linkages to public finance. Our interest, attempts to identify and analyse a current robust or flexible premier pricing model. The following literature may be emulated towards environment of interest (but not limited to such method): Skinner, D., Waksman, R. & Wang, G. H. (1983). Empirical Modelling & Forecasting of Monthly Transit Revenue for Financial Planning: A Case Study of SCR TD in Los Angeles. Transportation Research Board, Issue # 936. B. Department of Transportation case study Will pursue quantitative arguments (models) for current pricing for different services. Highlighting the claimed causes for hikes or price model change(s), how to validate? What data and models are conventionally applied to justify charge increases? What data and models are conventionally applied for operations cuts/increases with transportation services in particular? C. Revenue from fines can be lucrative. Examples: fines from securities exchange commission or trade commission, transportation, and the many other common infractions penalised by other agencies at various gov’t levels. Models for such pricing/fines. Concerning such fines, does the Cost of Damages method, or Cost of Control method, or those of Adhikari S.R. (2016) for measuring externalities translate well? How do fines contribute to society? Identify the redistribution transmissions. 22. Tax Evasion Richupan, S. (1984). Measuring Tax Evasion: An introduction to Measurement Techniques, Finance & Development, 0021(004), A011 Note: will explore two methods that are practical in terms of data acquisition ease and time constraints. Prerequisites: Microeconomics II, Macroeconomics II, Econometrics, Economic Time Series Econometrics Course will be centered on the R environment with RStudio, with heavy usage of data from various sources for meaningfulness with modelling and forecasting. Course grade will be constituted by homework, exams, group projects and individual projects. Students must hone their skills in programming and computation that best serves them towards highly successful completion of course. An intention of this course is not to get cascaded and lost/drowned with (economic and statistical) theory despite prerequisites. Course is about applied econometrics. NOTE: course will require 18 weeks with at least 2 hours per session. NOTE: data and computational assignments given to students follow only analytical setup by instructor. Note: this is NOT a frolic theory course where things are done just for the hell of it. You have real goals. Note: it will be quite rare for me to give you “kool-aid” summary statistics; the majority of the times you will be responsible for such development in assignments, projects and exams. NOTE: for competency and relevancy course to encounter applications where structuring and modelling from lectures will serve to introduce such following applications. Applications not necessarily to be introduced in the following sequential order, and WILL be applied multiple times for different topics) -- *Cross sectional data *Panel data *Latent variables (empirical models, observables, unobservables) *Endogeneous Variables versus Exogeneous Variables *Model with Transformed Endogeneous Variables *Forecasting and Measurement Error (prevalent throughout course) *Demand and Supply Curves *Price Elasticity of Demand/Supply *Hedonic modelling and estimation *Consumer Growth *Cobb-Douglas and CES *Stochastic Frontier Analysis *Currency Exchange *Balance of Trade *Gravity Model Estimation (Trade) *Real Effective Exchange Rate *Gross Domestic Product The 9 variables interest are gov’t spending, consumer spending, investment, trade balance, employment, interest rates, inflation, industrial production & manufacturing, sentiment indicators. *Labour Economics applications (logistic models and censored count data.) Prototypical Status-Quo Lecturing Textbooks --> Wooldridge, Jeffrey M. Introductory Econometrics: A Modern Approach, Mason, OH: Thomson/South-Western Goldberger, Arthur S. A Course in Econometrics. Cambridge, MA: Harvard University Press R texts (for homework, projects and exams) --> Gentleman, R., Hornik, K., and Parmigiani, G., Use R!, Springer Kleiber C., Zeileis A. (2008). Applied Econometrics with R. Springer-Verlag Sheather, S. J., A Modern Approach to Regression with R, Springer Multiple texts likely will be applied to acquire practical DEVELOPMENT of models with data and R usage; often for personal footing and progress multiple texts are often used. Consult with CRAN if all fails. Note: apart from problems found in textbooks and R sources there will be great initiative to make use of data relevant to the listed above applications. Make use of the above applications topics at times most appropriate towards the given structure outline (may be applied multiple times). Some mentioned applications can be represented by both linear and multi-linear models. Note: course will have multiple R packages conventionally applied to regression. Students must become decent with data acquisition, data wrangling, summary statistics generation and various plots (includes residuals). There will be homework and test problems with natural raw data, given summary statistics for students to verify and/or interpret, etc. In ALL FUTURE projects and assignments students must justify their variables in models with appropriate methods. Will ALSO include the use of training sets, test sets and cross-validation (R packages tidyverse, tidymodels and caret to serve well for first two and feature importance/selection). NOTE: emphasis on Training/Test sets and Validation (caret and others) NOTE: all projects will be constituted by the R environment with rmarkdown and conversion to pdf documents. Having commentary throughout project, accompanied by written analysis in a word processor (with use of mathematical palette throughout). Some projects may be assigned topics while others to be exploratory. NOTE: for most subjects in this course, cases and problems will not be able to be done by hand, so don’t get intimidated or hoodwinked by professors or instructors who spend most of their time writing rigid things on a board. NOTE: for bivariate models, data to be applied will be small sets (around 25-50 elements at least and at most). NOTE: exams with modules 5 and beyond, the professor will draw some questions with high volume data sets heavily to ACTIVELY apply, hence, students must become well versed in computational skills with R and will be allowed to use their notes. “Watching someone sail a boat is completely different to being on a boat and sailing it in various types of weather.” Besides developing regression models with analysis of parameters students must also be able to interpret summary statistics. Analytical descriptions on paper will also be required. NOTE: projects will increase in difficulty as more topics are treated. Students will also be required to develop a final project. Professor will have a preliminary synopsis of projects to be turned in. NOTE: final major regression project must treat the following: multilinear, Quantile & Logistic. NOTE: emphasis on Training/Test sets and Cross-Validation Grade constitution --> Bivariate Models (exam + homework) 10% Multiple regression 55% Homework 0.1 Projects 0.5 Exams 0.4 Final major regression project 35% Course will have procured time for lab sessions where professor will only provide analytic modelling guidance. Apart from R packages and R sources conveyed in the “Goody Bag” post the following information can help one in further reducing manual building of models (if one is fast with schemes to be constructive): https://cran.r-project.org/web/views/Econometrics.html COURSE OUTLINE --> 1. INTRODUCTION --Types of Economic Data, Data Access and Reliability A. Data sources, APIs (National Accounts, IMF, OECD, BIS, World Bank, central banks, Eurostat, EUROPA, UN structures and agencies, census, balance of payments, gov’t statistics, etc., etc.). Database introspection, queries with R (using either URL sites, APIs, DBI, dplyr, dbplyr, odbc or R packages). B. Handouts: use of text files, script files, csv files, excel files, addresses, etc. towards R. C. Handouts for data frames: dim(), head(), str(), glimpse() N/A identification. Extraction, or mean input or median input. Dong, Y. and Peng, CY.J. (2013). Principled Missing Data Methods for Researchers. SpringerPlus 2, 222 filter(), select (), mutate(), order(), join(), scan(), rename() $ operation in R when needed 2. FAST REVIEW OF PREREQUISITE STATISITCS WITH R Probability distributions and their properties Summary Statistics generation Statistical Sampling and uses Intelligence gathering from Box plots, skew, kurtosis, density plots, P-P, Q-Q Comprehending critical values for real raw data sets (untampered data) Goodness-of-fit tests for distributions Statistical methods for fraud detection with R 3. GLANCE AT ECONOMETRIC MODELS & THE RELEVANT DATA TYPES lance at econometric models, data types -The Idea of Econometrics -TAKE HEED: AFTER MODULE 4, it’s important to determine whether weighted least squares or general least squares is more appropriate than OLS. 4. BIVARIATE REGRESSION BASICS -Comprehending the variables (what they measure) -Graphical analysis (scatter plot, box plot and density plot) -Correlation -Simple linear regression: finding the means of variables, SDs of variables and correlation coefficient towards obtaining the regression coefficient and intercept. -Ordinary Least Squares (OLS) and the assumptions -Coefficient of determination -Interpretation of summary statistics via OLS -Residuals versus fitted values (RvF), and goodness of fit -Heteroscedasticity in bivariate models? RvF: case with CAPM -Variability in errors; distribution of errors with large sample size -Advance interpretation of summary statistics -Train, Test, Validation -A common mistake people make when describing the relationship between two quantitative variables is that they confuse association and causation. Case: fire damage and number of firefighters sent --> the seriousness of the fire Brian L. Joiner (1981) Lurking Variables: Some Examples, The American Statistician, 35:4, 227 – 233 5. FEATURE SELECTION Note: a feature is the same as a predictor variable; a target is equivalent to a response variable. First, for datasets chosen will develop correlation matrices. Then heatmaps. Second, will explore a feature selection method. Will identify the concepts, followed by (practical, tangible and fluid) analytical structure of the method. Then implementation logistics. Then implementation in the R environment. Will make use of datasets with considerable amounts of features. The Caret R package is just one means of accomplishing such. Univariate feature selection method (will be hands-on) Note: will be emphasized in all modules following. 6. MULTIPLE REGRESSION (MR) NOTE: must independently recognise whether weighted least squares or generalised least squared is better suited than OLS. Mandatory crucial topics are listed --> -Evidence for variables Heinze, G., Wallisch, C., & Dunkler, D. (2018). Variable selection - A Review and Recommendations for the Practicing Statistician. Biometrical Journal. Biometrische Zeitschrift, 60(3), 431–449. -Feature Selection review from (5) compared to prior -Role of Ordinary Least squares (OLS) in multiple regression -olsrr: Tools for Building OLS Regression Models; compare to Heinze et al -WLS and/or GLS in multiple regression -Distribution of the OLS/WLS/GLS estimator Get to the point (WLS and GLS treatment also expected): https://www.econometrics-with-r.org/4-5-tsdotoe.html https://www.econometrics-with-r.org/6-5-the-distribution-of-the-ols-estimators-in-multiple-regression.html -Heteroscedasticity in multiple regression and R tools for such -Role of AIC, BIC, Vuong and HQC Ludden, T.M., Beal, S.L. & Sheiner, L.B. Comparison of the Akaike Information Criterion, the Schwarz criterion & the F test as guides to model selection, Journal of Pharmacokinetics and Biopharmaceutics (1994) 22: 431. Pho, K., et al (2019). Comparison among Akaike Information Criterion, Bayesian Information Criterion & Vuong's test in Model Selection: A Case Study of Violated Speed Regulation in Taiwan. Journal of Advanced Engineering & Computation, 3(1), 293-303. Hannan–Quinn Information Criterion (HQC) contrast -The multiple coefficient of determination -Interpretation of summary statistics via OLS/WLS/GLS for MR estimator in multiple regression. -Train, Test, Validation -Wage variations Prospect variables to validate: education, work experience, unionization, industry, occupation, region, and demographics) Coefficients via OLS/WLS/GLS Model Validation Wage distribution, conditional probabilities and conditional expectations (for various predictor variables, one at a time or in bulk) w.r.t. data. -Marginal Effects Idea and analytical description of effects Use of R package margins Applications -Multiple Regression applications in Economics -Differences-in-differences Concept and logistics R tools 7. MULTIPLE REGRESSION (continued) Heteroscedasticity, consequences of Log transformations to adjust for heteroscedastic disturbances and possible limitations or setbacks OLS summary statistics versus Log transformation with OLS, versus WLS summary statistics versus GLS. Serial correlation in time series, consequences of Quasi-differencing; common-factor- restriction; Durbin-Watson test for serial correlation and Breusch-Watson statistic. 8. MULTICOLINEARITY: Detection, consequences and remedies -Correlation matrix for predictor variables. What can you learn? -Distinguish between structural multicollinearity and data-based multicollinearity. -Understand variance inflation factors and how to use them to help detect multicollinearity. -Ways of reducing data-based multicollinearity: Collecting additional data under conditions Different experimental or observational conditions Correlation Heatmaps -Feature Importance regression method Then compare to univariate feature selection method 9. DUMMY VARIABLES 10. INSTRUMENTAL VARIABLES (IV), MEASURMENT ERROR, REGRESSION-DISCONTINUITY DESIGNS -Instrumental Variables Holland, S. (2020). Supply, Demand and the Instrumental Variable. Towards data Science Angrist, J.; Krueger, A. (2001). "Instrumental Variables and the Search for Identification: From Supply and Demand to Natural Experiments". Journal of Economic Perspectives. 15 (4): 69–85. Bound, J., Jaeger, D. A. and Baker, R. M. (1995). "Problems with Instrumental Variables Estimation when the Correlation between the Instruments and the Endogenous Explanatory Variable is Weak". Journal of the American Statistical Association. 90 (430): 443. -Measurement error Wald, A. “The Fitting of Straight Lines if Both Variables are Subject to Error.” Annals of Mathematical Statistics 11:3 (1940): 284–300. Note: there can be other applications. -Regression-Discontinuity designs --> Imbens G., Lemieux T. Regression Discontinuity Designs: A Guide to Practice, Journal of Econometrics. 2008; 142 (2): 615 - 635 McCrary (2008). "Manipulation of the Running Variable in the Regression Discontinuity Design: A Density Test". Journal of Econometrics. 142 (2), pages 698 – 714 Lee, D. S. and Lemieux, T. Regression Discontinuity Designs in Economics, Journal of Economic Literature 48 (June 2010): 281 – 355 11. QUANTILE REGRESSION Quantile Regression (quantreg package with manual and vignettes) Scatter Plots are a useful first step in any analysis because they help visualize relationships and identify possible issues (e.g., outliers) that can influence subsequent statistical analyses, or need of regression beyond simple OLS, say, quantile regression (or generalized nonlinear models). Waldmann, E. (2018). Quantile Regression: A Short Story on How and Why. Statistical Modelling, 18(3–4), 203–218. Davino, C., Furno, M., & Vistocco, D. (2014). Quantile regression: Theory and Applications. Wiley Das, K., Krzywinski, M. & Altman, N. (2019). Quantile Regression. Nat Methods 16, 451–452 Comparing with OLS/WLS/GLS (summary statistics and performance). Applications of interest: Growth equations Fitzenberger, B., Koenker, R. and Machado, J. A. F. (2002), Economic Applications of Quantile Regression. Physica-Verlag Heidelberg 12. LOCAL REGRESSION Notion of local regression, model structures and components. Logistics, implementation and summary statistics (compared to OLS and quantile) LOESS (locally estimated scatterplot smoothing) LOWESS (locally weighted scatterplot smoothing) Multivariate development as well. Is the trend (positive or negative) in scatter plots absolute OLS versus Quantile versus LOESS/LOWESS versus Spline Observing trend and summary statistics Implications for multivariate models and forecasting 13. LOGISTIC REGRESSION Note: will focus on labour economics applications, censored count data and political economy Motives Model Structure and Computational Structure Evidence for variables Model fitting pursuit Summary Statistics analysis Calculating Probabilities/Predicted Probabilities Marginal Effects Feature Importance logistic regression method Then compare with Univariate feature selection method Linear regression feature importance method Multiple logistic regression (extend all prior) Prereqs: Mathematical Statistics (check Actuarial post), Macroeconomics II, Microeconomics II.

Economic Time Series Without the use of raw data and an enforced computational environment this course will not be meaningful. I can’t just give you chalkboard written models and condensed “Kool-Aid” summary data then expect you to really understand what’s really there. This course doesn’t have much time to spend on statistical theory. NOTE: course will require around 18 weeks with at least 2 hours per session. Two status quo texts conventionally applied --> Enders, Walter. 2015. Applied Econometric Time Series, Wiley Kleiber, C. & Zeileis, A. 2008. Applied Econometrics with R (use R!), Springer R guides for homework, take-home assignments, projects --> Farnsworth, G. 2008, Econometrics in R. CRAN R Project Time Series Analysis with Applications in R, by Jonathan Cryer and Kung-Sik Chan, Springer Time Series Analysis and its Applications with R Examples, by R. H. Shumway and D. S. Stoffer. Introductory Time Series with R, by P. S. P. Cowpertwait and A. V. Metcalfe Supportive general texts likely to be referred to in course --> Hayashi, F. 2000. Econometrics. Princeton University Press Hamilton, J. D. 1994. Time Series Analysis. Princeton University Press Juselius, K. 2007. The Cointegrated VAR Model: Methodology and Applications. Oxford Press. L¨utkepohl, H. 2005. New Introduction to Multiple Time Series Analysis, Springer. Assessment --> --Homework (analytical and R skills) --5 take-home assignments. The assignments will be handed out in class and will be due in about 7-10 days; they will involve solving end-of-chapter problems, data analysis, and data computation exercises with time series. If I’m giving you at least 1 week…then that says something about what I expect. Take home assignments may not be exact replicas of lecturing and literature applied. --Projects will be based on lecturing and literature (texts AND assigned journal articles; data likely will be augmented). Projects will come when instructor deems class is exposed to enough material. Prerequisites will haunt you. Journal articles listed in course topics concern active computational development in lecturing. --Final exam done in a room with disabled WIFI, disabled LAN with an environment that rejects hot-spots. You will use your computers or room computers with R ability. 24 hours prior, say, you will be given various data files with no assignments structure, where you must know how to apply them towards time series pursuits. At exam time questionnaires will be handed out. To complete questions you will rely on your statistics and time series knowledge/skills (analytical and R). Open notes and can make use of past assignments and projects for reference. Final exam will be comprehensive. --The paper will involve either (a) and/or (b): (a) replicating the developments and results of an existing paper, and critically extending it further (ambiance of interest, incorporation of new data, etc.) (b) presenting the results of original research. Typically, the paper will be chosen by the student in consultation with the instructor and should have the following characteristics: (1) the paper must analyse a development question (2) the paper must use substantial time series econometric analysis, preferably multiple large areas covered in this class. CONTENT, MECHANICS, EFFORT, QUALITY. Concerning course outline, for any journal articles applied the mentioned textbooks will be applied first before introducing journal articles, as means to develop needed foundation. Journal articles serve as meaningful and practical applications. Students are expected to read and apply preliminary analysis for chosen journal articles before scheduled lecture. Concerning any applications or applied journal articles, to also critique the models, and use of data from general sources. In other words, one will not just assume observed times series in journal articles are efficient. One needs to definitively develop how economic theory and economic models are reflected by the times series applied; quite crucial with multivariate time series. This course is NOT a playground for reckless and inconsiderate mathematicians and statisticians about their own interests; contrary behaviour requires that you be placed in a corner with 1000 element data sets to figure things out with a slide rule, probability chart, your fingers and a noise modulator…. with your cherished intellect. Some idea with cross validation (but not limited to): Moudiki, T. (2020). Time Series Cross-Validation Using crossval. R-bloggers NOTE: such above example for training/test/validation data is only one means since the R environment fortunately often encourages development towards comfort (with different packages); concern as well for multivariate times series. Applied journal articles concern applications for topics and assignments or projects. NOTE: for each major topic you will have to make sense of what you’re learning in regard to real raw data and R usage. NOTE: in each module summary statistics for time series will be included and analysed. Done emphatically throughout each module. NOTE: MAPE, MSE and MAE treatment expected throughout NOTE: this isn’t a matrix algebra course. You should know what a matrix is independently. Lengths and arrays of data are too big to be wasting other people’s time with perverted trivial manual matrix operations circus shows. NOTE: you are not mastering stereotypical exams with memory, pen/pencils and paper. You master things on your own when you get a good feel for what you’re immersed in. Tools --> Will employ R with RStudio employing various packages. R package use likely to vary in progression MANDATORY FOCUS TOPICS --> 1. DATA SOURCES OF INTEREST, FILE TYPES, APIs. IMPORTING & DATA WRANGLING 2. GRAPHICAL EXAMINATION OF TIME SERIES & DISTRBUTION DETERMINATION 3. CONSTRUCTIONS (2-3 sessions) Deterministic difference equations Lag operators Conditional expectation How are all such prior relevant in modelling data? 4. TYPES OF TIMES SERIES DECOMPOSITION Importance of knowing which components are in your time series Implementation 5. ADVANCE DETECTION OF SALIENT CHARACTEREISTICS OF TIME SERIES (3-4 sessions) NOTE: focus will be concepts and R computation goals. Such are for cross-referencing/validating with module (4) prior. Seasonality Properties, models and tests implementation Stable Seasonal Pattern Forecasting Model Non-parametric Properties, models HAC Non- Parametric Tests of Mean of Differences Friedman’s Non-parametric test Datta, D. D. and Du, W. (2012). Nonparametric HAC Estimation for Time Series Data with Missing Observations. Board of Governors of the Federal Reserve System International Finance Discussion Papers Number 1060 (apply to real world cases) Trend tests Properties, models, tests implementation Deterministic Trend/Seasonal Forecasting Model Buys-Ballot Plots DTDS Cyclicity Properties, models, tests implementation Box-Pierce-Ljung Portmonteau Test Stationarity Properties, models and tests implementations Augmented Dickey-Fuller test (ADF Test) Kwiatkowski-Phillips-Schmidt-Shin test (KPSS test) 6. UNOBSERVABLE COMPONENT FORECASTING MODEL (2-3 sessions) 7. BOX-JENKINGS PROCESS (3-4 sessions) Model Identification Stationarity and Seasonality Detecting Stationarity Seasonality Differencing for Stationarity Seasonal Differencing p and q identification Model Estimation Model Validation Model Diagnostics 8. BOX-JENKINGS FORECASTING MODEL (2-4 sessions) Forecasting for Stationary, Non-Seasonal Time Series Non-Seasonal, Stochastically-Trending Time Series Seasonal, Stochastically-Trending Time Series For all priors use of MAE, MAPE and RMSE is expected 9. EXPONENTIAL SMOOTHING Single, double and triple 10. TRANSFER FUNCTION MODEL (2-3 sessions) Montgomery, Douglas C. & Weatherby, G. (1980). Modelling and Forecasting Time Series Using Transfer Function and Intervention Methods, A I I E Transactions, 12:4, 289-307 Conflicts with Box-Jenkins? Limitations with linearity? 11. STATE SPACE MODELS (SSM) NOTE: will only focus on SSM as an alternative to Box-Jenkins concerning the alleged issue that in "the economic and social fields, real series are never stationary however much differencing is done", from Commandeur & Koopman (2007, §10.4) [ Commandeur, J. J. F.; Koopman, S. J. (2007). Introduction to State Space Time Series Analysis. Oxford University Press] State-Space Formulation Structural Models AR, MA, ARMA and ARIMA models in state-space form Develop the counterpart process for Box-Jenkins Verify the concern of Commandeur & Koopman with real data against B-J How does forecasting and forecasting error compare to B-J? Filtering and Smoothing: The Kalman Filter and EM Algorithm 12. GOVERNMENT SIZE-ECONOMIC GROWTH RELATION WITH TIME SERIES Example literature for development (there are others): Ram, R. (1986). Government Size and Economic Growth: A New Framework and Some Evidence from Cross-Section and Time-Series Data. The American Economic Review, 76(1), 191–203 V. V. Bhanoji Rao. (1989). Government Size and Economic Growth: A New Framework and Some Evidence from Cross-Section and Time-Series Data: Comment. The American Economic Review, 79(1), 272–280 O. Faruk Altunc & Celil Aydin (2013). The Relationship between Optimal Size of Government and Economic Growth: Empirical Evidence from Turkey, Romania & Bulgaria. Procedia - Social & Behavioral Sciences 92, pp 66 – 75 13. VECTOR AUTOREGRESSIVE TIME SERIES MODELS (4-6 sessions) Note: must have means to treat salient characteristics (stationarity, trend, seasonality) in multivariate time series similar to (4) and (5). Model: development, estimation, validation, forecasting and error VARsingnR package (1-2 sessions) Danne, C. (2015). The VARsignR Package. CRAN Danne, Christian (2015). "VARsignR: Estimating VARS Using Sign Restrictions in R., MPRA Paper 68429, University Library of Munich, Germany. State Space Representation of VAR (advantages and disadvantages) VAR: evaluation of the forecasting accuracies of competing forecasting methods (2-3 sessions) VARsignR R package identifies structural shocks in Vector Autoregressions (VARs) using sign restrictions Forecasting the Yield Curve Moench, E. (2005). Forecasting the Yield Curve in a Data-Rich Environment: A No-Arbitrage Factor-Augmented VAR Approach, ECB Working Paper No. 544 14. FEATURE IMPORTANCE AND FEATRURE SELECTION METHODS FOR MULTI-DIMENSION TIME SERIES DATA Note: must comprehend and develop the influence on (13), and also for modules (16) and (17). 15. SHOCKS IN ECONOMY (2-3 sessions) The given journal articles and literature will be analysed. Will determine how well the articles’ development conforms with our methodology process. Then replicate them to best of ability. Then augment with more modern data and sovereignty of interest. May require additional literature. Methods for identifying shocks & estimating impulse responses- constructive analysis, logistics and implementation -- Monetary policy shocks Bachmann, R., Gödl-Hanisch, I. and Sims, E. R. (2021). Identifying Monetary Policy Shocks using the Central Bank’s Information Set. NBER Working Paper 29572 Fiscal shocks Auerbach, A. J. and Gorodnichenko, Y. (2014). Effect of Fiscal Shocks in a Globalised World. 15th Jacques Polk Annual Research Conference, International Monetary Fund Montasser GE, et al (2020). The Time-series Linkages between US Fiscal Policy and Asset Prices. Public Finance Review, 48(3):303-339. Financial Shocks of Natural Disasters Miao, Q., Hou, Y. and Abrigo, M. (2018). Measuring the Financial Shocks of Natural Disasters: A Panel Study of U.S. States. National Tax Journal 71.1: pages 11–44 Benali, N., Mbarek, M.B. & Feki, R. (2019). Natural Disaster, Government Revenues and Expenditures: Evidence from High and Middle-Income Countries, J Knowl Econ 10, 695–710 16. FORECAST EVALUATION OF SMALL NESTED MODEL SETS Concept and structure of nested models Hubrich, K. and West, K. D. (2010). Forecast Evaluation of Small Nested Model Sets. Journal of applied Econometrics 25: 574 – 594 Clark, T. E and McCracken, M. W. (2009). Nested Forecast Model Comparisons: A New Approach to Testing Equal Accuracy. The Federal Reserve Bank of Kansas City, RWP 09 – 11 Granziera, E., Hubrich, K. and Moon, H. R. (2013). A Predictability Test for a Small Number of Nested Models. ECB Working Paper Series, No. 1580 17.MULTIPLE FORECAST COMPARISON & FORMING EFFICIENT “COMBINATION” FORECASTS (4-5 sessions) Tests Morgan-Granger-Newbold (MGN) Harvey, Leybourne and Newbold (HLN) Meese-Rogoff (MR) Diebold-Mariano (DM) Multivariate counterparts for priors (if need be) Combination Forecasting Some Basic Theorems on Diversification of Forecasts (survey only) Nelson Combination Method Granger-Ramanathan Combination Method Combinations with Time-Varying Weights Application literature Clark, T. E and McCracken, M. W. (2007). Combining Forecasts From Nested Models. Finance and Economics Discussion Series, Federal Reserve Board 2007 – 43 How applicable is the following R packages to prior topic(s)? CRAN R.(n.d.). Getting Started with Modeltime Ensemble. CRAN R https://cran.r-project.org/web/packages/modeltime.ensemble/vignettes/getting-started-with-modeltime-ensemble.html Prerequisites: Mathematical Statistics (check Actuarial post), Microeconomics II, Macroeconomics II

Monetary Theory and Policy --An introduction to modern monetary economics for advanced undergraduates. Course presents the core New Keynesian model and recent advances, taking into account financial frictions, and discusses recent research on an intuitive level based on simple static and two-period models, but also prepares readers for an extension to a truly dynamic analysis. Lecturing Text--> Cao, J. and Illing, G. (2019). Money: Theory and Price. Springer Texts in Business and Economics. Springer Assessment --> Problem Sets from lecturing text 5 Quizzes Labs Course Phases --> Part I: Long-run perspective, addressing classical monetary policy issues such as determination of the price level and interaction between monetary and fiscal policy. Part II: Core New Keynesian model, characterising optimal monetary policy to stabilize short-term shocks. Rules vs. discretion and the challenges arising from control errors, imperfect information and robustness issues. Optimal control in the presence of an effective lower bound. Part III: limited to the following Modelling financial frictions Identification of transmission mechanisms of monetary policy via banking and introduces models with incomplete markets. Presenting a tractable model for handling liquidity management and demonstrating that the need to sell assets in crisis amplifies the volatility of the real economy. Relation between monetary policy and financial stability, addressing systemic risk and the role of macro-prudential regulation. Problem Sets --> Questions for AD, AS and AD-AS, DAD-DAS Algebraic, numerical Questions and simulations for DAD-DAS Problems from lecturing text Problems for constituents of DSGE and CGE; properties and conditions of the constituents. Some simulations implemented. Quizzes --> Based on problem sets and lecturing Labs --> Labs will be done in particular bundles with to be determined sequence among labs, having fluid relation, high coherency, tangibility and practicality going from one lab to the next. Considerable amount of various data to apply. Specified labs detailed are a rare opportunity, where you are the beneficiary. 1. Primitives -Review of the derivation and relevance of the IS, LM, AD and AS curves with solutions; construction of AD-AS and IS–LM–FEs. Reviewing circumstances with shifts, policies and rules. -Review of creating DAD-DAS and investigating different scenarios/policies/rules. -Analysis of the following section, then investigate for other countries with different time periods Flaschel, P. (2009). Keynesian DAD-DAS Modeling: Baseline Structure and Estimation. In: The Macrodynamics of Capitalism. Springer, Pages 305-333 Note: this lab is a special case where topics and problems will be done on multiple occasions, unlike the other labs. 2. New Keynesian Models Note: literature for calibration and simulation pursuits -- Dennis, Richard. 2003. “New Keynesian Optimal Policy models: An Empirical Assessment.” FRBSF Working Paper 2003-16 (2005). Monetary Policy in the New Keynesian Model. In: Monetary Policy and the German Unemployment Problem in Macroeconomic Models. Kieler Studien - Kiel Studies, vol 334. Springer, Berlin, Heidelberg. De Vroey, M. (2016). Second-Generation New Keynesian Modeling. In A History of Macroeconomics from Keynes to Lucas and Beyond (pp. 307-336). Cambridge: Cambridge University Press. Alla, Z., Espinoza, R. and Ghosh, A. R. (2017). FX Intervention in the New Keynesian Model. IMF WP/17/207 Sims, E. and Wu, J. C. (2019). The Four Equation New Keynesian Model, FRBSF 3. Tools of Monetary Policy Investopedia Team (2021). Monetary Policy. Investopedia Chen, J. (2021). Foreign Exchange Intervention. Investopedia For each identified tool of monetary policy what rule(s) will be appropriate for control? Will like to verify with case examples based on economic data? 4. DSGE Beginner sources PART A De Grauwe, P., The Scientific Foundation of Dynamic Stochastic General Equilibrium (DSGE) Models, Public Choice (2010) 144: 413–443 Costa Junior, C. J. and Garcia-Cintado, A. C. (2018). Teaching DSGE Models to Undergraduates. EconomiA 19, 424 - 444 DYNARE Heavy immersion Note: interests will go much further than article with development and simulation; sustainability with applications Note: OccBin Toolkit in Dynare may be of interest, however, one must comprehend any limitations or hindrances of a first-order approach implemented in general. DynareR package for R is also possible. Guerrieri, L. & Lacoviello, M. (2014). OccBin: A Toolkit for Solving Dynamic Models with Occasionally Binding Constraints Easily. Finance and Economics Discussion Series. Division of Research & Statistics & Monetary Affairs. Federal Reserve Board Guerrieri, L. & Lacoviello, M. (2015). OccBin: A Toolkit for Solving Dynamic Models with Occasionally Binding Constraints Easily. Journal Monetary Economics, Volume 70, pages 22 – 38 Note: package DynareR to investigate (concerns for OccBin Toolkit) PART B Note: apart from comprehension of models structure there can be comparative analysis with their implementation -- Policy Analysis Using DSGE Models Sbordone, A. et al (2010). Policy Analysis Using DSGE Models: An Introduction, FRBY Economic Policy Review FRBNY DSGE meets Julia <https://github.com/FRBNY-DSGE/DSGE.jl > The given above link provides the DSGE code in the Julia language. However, if one can develop the code in R, then that’s fine as well. PART C FRS/US Model: https://www.federalreserve.gov/econres/us-models-package.htm PART D Bayesian DSGE: RAMSES Adolfson, M. et al (2007a), Journal of International Economics vol.72(2), pages 481-511. Adolfson, M. et al, (2007b), Sveriges Riksbank Economic Review 2, pp 5-39 Adolfson, M. et al (2011). Board of Governors of the Federal Reserve System International Finance Discussion Papers Number 1023 Adolfson, M. et (2014). Monetary Policy Trade-Offs in an Estimated Open-Economy DSGE model. Journal of Economic Dynamics & Control, vol.42, pqges 33-49 PART E Monetary Transmission Channels in DSGE Labus, M. and Labus, M. (2019). Monetary Transmission Channels in DSGE Models: Decomposition of Impulse Response Functions Approach. Comput Econ 53, 27–50 PART F Vector autoregressions (VARs) for testing dynamic stochastic general equilibrium (DSGE) models 5. Computable General Equilibrium development with GAMS To build a practical, tangible and fluid computational foundation. The following are invaluable texts: Burfisher, M. E. (2011). Introduction to Computable General Equilibrium Models. Cambridge University Press. Hosoe, N., Gasawa, K., & Hashimoto, H. (2010). Textbook of Computable General Equilibrium Modeling: Programming and Simulations. Palgrave Macmillan Limited. Dixon, P. B. and Jorgenson, D. W. (2013). Handbook of Computable General Equilibrium Modelling SET, Volumes 1A and 1B. Elsevier Perali, F. and Scandizzo, P. (2018). The New Generation of Computable General Equilibrium Models: Modelling the Economy. Cham: Springer. The following texts provide guidance for programming and simulation: Chang, G. H. (2022). Theory and Programming of Computable General Equilibrium (CGE) Models: A Textbook for Beginners. World Scientific. 6. Monetary Policy Rules The references in the following may prove beneficial: https://www.federalreserve.gov/monetarypolicy/policy-rules-and-how-policymakers-use-them.htm From past economic periods investigate how such rules were implemented. Is DSGE and CGE a simulation means to implement such rules w.r.t. monetary tools? Identify how data, DSGE and CGE lead to choice implementation; retractions as well. Are simple economic models (DAD-DAS) just as formidable? What discretion is considered regardless? For the various monetary tools available to central banks from (7), how do such tools either in expansionary policy or contractionary policy relate to such rules? Legacy: McCallum, B. T. (2000). Alternative Monetary Policy Rules: A Comparison with Historical Settings for the United States, the United Kingdom, & Japan. Federal Reserve Bank of Richmond Note: pursue with more modern data, also with incorporation of candidate rules mentioned in the given federal reserve link. 7. National Accounts (analysis, measures and benchmarks) Balance Sheet, Current, Capital, Financial Assists for lab: SNA 2008 https://unstats.un.org/unsd/nationalaccount/pubsDB.asp Are the following applicable to national accounts? Beneish Model, Altman Z Model, Modified Jones Model, Dechow F Score, Newcomb-Benford Law, Zipf’s Law Logistics for determination of GDP and GNI via national accounts Assessing the effects of various economic policies Income/wealth distribution (compared to Lorenz and Gini) Inflation determination compared to CPI 8. Validating the Fisher Effect 9. Money Supply process Bajpai, L. (2020). How Central Banks Control the Supply of Money. Investopedia Kenton, W. (2021). Reserve Ratio. Investopedia Using financial statements of banks to compute reserve ratio and reserve requirement Velocity of Money Means of money supply control What tools and data are applied for determination of choice of money supply control method? Will acquire the logistics and implement the means. Will try to observe data that exhibits the TRUE response from money supply control methods in the micro level (or in industries), say, consumer spending, loans (particular types), mortgages, securing financing by companies, etc., etc.. At the macro level will try to observe data that exhibits the response from money supply control method, say, influence on interest rates, inflation and unemployment, towards models development. 10. PMIs analysis 11. Modelling, analysing and forecasting the yield curve with the Nelson-Svensson-Siegel model For comparative development: YieldCurve R package Enrico Schumann. Fitting the Nelson–Siegel–Svensson model with Differential Evolution. CRAN R Prerequisites: Microeconomics II, Money & Banking, Advanced Macroeconomics, Mathematical Statistics Co-requisites or Prerequisites: Econometrics, Economic Time Series Research Methods in Monetary Policy Course hours applied will be considerably longer than a conventional term, AND requirement of at least 3 hours per lab session. Guiding Literature --> Much literature will stem from the given articles in the EA outlines, else literature will be provided if not stated. Grading --> -EA labs MONETARY POLICY LABS (EAs) --> Specific EAs will be done after coverage of related course lectures. Will consistently be highly data relevant and computational. Class will be partitioned into groups, where all groups will be held accountable for EAs 1 – 13 towards applied monetary workings (tangible/practical and fluid applications). Focus will be adjustment to assigned nation. Group scoring will be based on qualitative development and quantitative development, say, transparency, practicality, robustness, accuracy. AS WELL, knowledge and skills from prerequisites will serve well. NOTE: EAs to be done in chosen particular bundles, granted that all EAs in a particular bundle to be appropriately sequenced, having decent relation, high coherency, tangibility, practicality and fluidity going from one to the next. EAs are a rare opportunity, where you are the beneficiary. As well, the order with developed bundles will be determined. REMINDER: monetary intervention concern impartial decision marking. There’s no role for socio-political rhetoric, divisiveness and policies. Despite having to deal with the economic effects stemming from the legislative and executive branches, a central bank is an independent agency. HAVE FORESIGHT OF THE OUTCOME WITH A CONTRARY STANCE. REMINDER: stay fresh and sharp with knowledge and skills from prerequisites. Essential Attributes (EA) --> 1. Resources & Tools (acquisition, interpretations and uses) -R environment and common packages. R environment for economic data acquisition (acquisition and wrangling) towards data analysis, modelling, etc. EDA, regresion, time series -Central Bank Commerce Federal Funds Rate Baldwin, J. G. (2021). Impact of Interest Rate Changes by the Federal Reserve. Investopedia Forward Guidance Biege Book and/or Greenbook (or sovereignty analogies) Economic interpretations of such information 2. Assets --Singh, M. (2021). Understanding the Federal Reserve Balance Sheet, Investopedia Concerning the federal reserve “thinning” or “expanding” its balance sheet, what policies, rules, guidelines and tools are applied? Will review numerous past balance sheets and try to situate/apply the policy, rules, guidelines and tools for the decision making. --Analysis of balance sheets over various years --Corporate bonds may be treated differently concerning economic pursuits: A. Buying corporate bonds in an aggressive manner concerning unfavourable economic shocks, etc. What type of monetary tool is this? What empirical economic conditions must arise to apply such tool? Try to situate/apply the policy, rules, guidelines and tools for the decision making. There must be quantitative/computational models or techniques to support the decision making in question. A tapering rule? When to completely withdraw? Assist: Galema, R. and Lugo, S. (2021). When Central Banks Buy Corporate Bonds: Target Selection and Impact of the European Corporate Sector Purchase Programme. Journal of Financial Stability 54 100881 Note: ETFs are relevant as well B. Concerning a central banks’ balance sheets for corporate bonds in assets. Industries, firm valuations and market share (if able). What risk management frame work exists? Do Beneish, Dechow F, Modified Jones, Altman Z and Merton default model apply? Are default correlations and liquidity standard considerations before transactions? C. Is it possible for reserves to invest in corporate bonds and foreign corporate bonds plainly as investments? D. Are Off-Balance Sheet notes applicable to Central Banks? --Foreign notes/currencies (types) Purpose, and influence of levels of such foreign assets on respective exchange rates and domestic treasuries. --Exchange Risk Measurement of exposure and use of VaR Currency baskets to smooth risks (will have development for such) Other tools to mitigate exchange risk --Reserves For ambiances of interest to apply and analyse. Is such literature compatible? International Monetary Fund. (2016). Guidance on the Assessment of Reserve Adequacy and Related Considerations Bar-ilan, A. and Lederman, D. (2007). International Reserves and Monetary Policy. Economic Letters, Volume 97, Issue 2, pp 170 - 188 --Integrity tests and fraud detection on national accounts? Cah Flow Analysis, Benford-Newcomb, Zipf's, Beneish, Dechow F, Modified Jones, Altman Z --Portfolio risk preference from balance sheets at various periods of the business cycle (asset types and weights). Hopefully there’s enough transparency to identify strategies in a “investment portfolio type manner”. Do rebalancing techniques for portfolios in finance apply to central banks? 3. Debt What policies exist that central banks apply to assist in dealing with debt concerns? Johnston, M. (2021). How Central Banks Monetize Government Debt, Investopedia Consideration of practical tools and means of simulation effects based on prior article. Household debt. Is an increase in household debt in relation to a country's (real) GDP in at least the short to medium term a strong predictor of a weakening economy? 4. Forecasting PART A Note: applying time series skills from prerequisites. Must be able to identify the types of time series to apply and the crucial specifications and assumptions that will apply. Survey of Professional Forecasters (SPF); CBO; Cleveland FRS BVAR Identifying and interpreting all variables to forecast Nature and data needed for respective variable Developing models for variables to implement (SPF, CBO, etc., etc.) Some guidance: --Variables, transformations, and files in the survey www.philadelphiafed.org/-/media/frbp/assets/surveys-and-data/survey-of-professional-forecasters/spf-documentation.pdf --Stark, T. (2010). Realistic Evaluation of Real-Time Forecasts in the Survey of Professional Forecasters. Federal Reserve Bank of Philadelphia PART B Serge de Valk, Daiane de Mattos and Pedro Ferreira. Nowcasting: An R Package for Predicting Economic Variables Using Dynamic Factor Models. The R Journal Vol. 11/01, June 2019 Note: pursue other economic variables besides GDP. Then, will take a more intimate approach in developing prediction models for economic variables, to compare with prior. PART C After analysis of the following, to be concerned with development with more modern years. Knotek II, E. S. et al (2016). Federal Funds Rates Based on Seven Simple Monetary Policy Rules, Federal Reserve Bank of Cleveland, Economic Commentary. Number 2016-07 PART D To analyse and develop with ambiances of interest: --Paramanik RN, Kamaiah B. A Structural Vector Autoregression Model for Monetary Policy Analysis in India. Margin: The Journal of Applied Economic Research. 2014;8(4):401-429. --Holtemöller, Oliver, 2002. "Structural Vector Autoregressive Models and Monetary Policy Analysis., SFB 373 Discussion Papers 2002, 7, Humboldt, University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes. --VARsignR R package identifies structural shocks in Vector Autoregressions (VARs) using sign restrictions 5. Inflation PART A -Consumer Price Index (CPI) and its use with federal reserve interest rate policy -Basket Model for CPI, Sources for data and implementation -National accounts method for inflation determination -Avdiu, K. and Unger, S. (2022). Predicting Inflation—A Holistic Approach. J. Risk Financial Manag., 15, 151 -Applying forecasting skills from prerequisites to compare with (4) and prior. PART B Output Gap Purpose and controversies Being an inflation gauge and needed link to unemployment Classical Method Cerra, V. & Saxena, S. C. (2000). Alternative Methods of Estimating Potential Output and the Output Gap: An Application to Sweden, IMF WP/00/59 Pursue means of evaluating consistency or relation between CPI and output gap. PART C (literature for development) Tallman, Ellis W. 1995. “Inflation and Inflation Forecasting: An Introduction.” Federal Reserve Bank of Atlanta Economic Review, pages 13-27. Webb, Roy H. 1995. “Inflation Forecasts from VAR Models.” Journal of Forecasting pp. 267-285. Stockton, David J., and Charles S. Struckmeyer. 1989. “Tests of the Specification and Predictive Accuracy of Nonnested Models of Inflation.” Review of Economics and Statistics pp. 275-283. PART D Kramer, L. (2020). How Do Governments Reduce Inflation? Investopedia. PART E (monitoring, policy & caution) Non-Accelerating Inflation Rate of Unemployment (NAIRU) Murphy, C. B. and Kelly, R. C. (2021). Non-Accelerating Inflation Rate of Unemployment (NAIRU). Investopedia Investigating the Key Takeways from above source NAIRU versus natural rate of employment Guides to assist: Staiger, Douglas, James H. Stock, and Mark W. Watson. 1997. “The NAIRU, Unemployment and Monetary Policy.” Journal of Economic Perspectives (Winter) pp. 33-49. P. McAdam & K. Mc Morrow, (1999). The NAIRU Concept – Measurement Uncertainties, Hysteresis and Economic Policy Rule, European Economy – Economic Papers 2008 -2015, Directorate General Economic and Financial Affairs (DG ECFIN), European Commission Turner, D. et al (2001). Estimating the Structural Rate of Unemployment for the OECD Countries. OECD Economic Studies No. 33, 2001/II Amano M. (2013). The NAIRU, Potential Output, and the Kalman Filter: A Survey and Method of Estimation. In: Money, Capital Formation and Economic Growth. Palgrave Macmillan, London. Victor V. Claar (2006) Is the NAIRU More Useful in Forecasting Inflation than the Natural Rate of Unemployment? Applied Economics, 38:18, 2179-2189 6. DSGE and CGE Models Comprehension of computational models and construction in a transparent, coherent, fluid and tangible manner; spectrum of uses for each. If you don’t treat this now with effort and quality, chances are you will never get back to it. NOTE: make choices, but active implementation is mandatory. PART A: --FRBNY DSGE Model meets Julia < https://github.com/FRBNY-DSGE/DSGE.jl > --FRS/US Model < https://www.federalreserve.gov/econres/us-models-package.htm > --BEQM Model < Harrison, R., Nikolov, K. et al. (2005). Bank of England > < Nikolov, Kalin. (2013). European Central Bank > --ToTEM III < Dorich, J. et al (2013). > < Corrigan, P. et al (2021). > --Vector autoregressions (VARs) for testing dynamic stochastic general equilibrium (DSGE) models Note: Dynare + OccBin Toolkit, and DynareR have meaningful use. PART B (CGE Models with GAMS) Burfisher, M. E. (2011). Introduction to Computable General Equilibrium Models. Cambridge University Press. Dixon, P. B. and Jorgenson, D. W. (2013). Handbook of Computable General Equilibrium Modelling SET, Volumes 1A and 1B. Elsevier Perali, F. and Scandizzo, P. (2018). The New Generation of Computable General Equilibrium Models: Modelling the Economy. Cham: Springer. The following text provides guidance for programming and simulation: Hosoe, N., Gasawa, K., & Hashimoto, H. (2010). Textbook of Computable General Equilibrium Modeling: Programming and Simulations. Palgrave Macmillan Limited. Chang, G. H. (2022). Theory and Programming of Computable General Equilibrium (CGE) Models: A Textbook for Beginners. World Scientific. 7. Monetary Transmission Channels/Mechanisms & Conditions Ireland, P. N. (2005). The Monetary Transmission Mechanism. Federal Reserve Bank of Boston, Working Papers No. 06‐1 Kuttner, K, N. and Mosser, P. C. (2002). The Monetary Transmission Mechanism: Some Answers and Further Questions. FRBNY Economic Policy Review Note: for all such above use of DSGE, or CGE with real data, or Structural VAR, or regression may be necessary to acquire a strong sense of verification of dynamics. --The following literature to be analysed, then pursuit of DSGE development based on it. Dynare + OccBin and DynareR can be useful. Beyer, A. et al (2017). The Transmission Channels of Monetary, Macro- and Microprudential Policies and their Interrelations. European Central Bank Occasional Paper Series – No. 191 Labus, M. and Labus, M. (2019). Monetary Transmission Channels in DSGE Models: Transmission mechanism of monetary policy Decomposition of Impulse Response Functions Approach. Comput Econ 53, 27–50 --Try to link or relate policies, rules, tools and disengagement at different stages via analytical modelling or DSGE or CGE or VAR or regression 8. Policies & Rules in Monetary Policy NOTE: one will like to make sense of policies and rules with the real world involving past and present data, economics dynamics, and monetary tool. Relevance of economic data, regression, time series, DSGE, CGE to all such. PART A - Monetary Policies Walsh, C. E. Using Monetary Policy to Stabilize Economic Activity. Kansas City Fed. pp 245 – 296 Berg, A., Karam, P. and Laxton , D. A Practical Model-Based Approach to Monetary Policy Analysis – Overview. IMF Working Paper WP/06/80 Berg, A., Karam, P. and Laxton , D. Practical Model-Based Approach to Monetary Policy Analysis – A How to Guide. WP/06/81 Adolfson, M. et al (2008a), "Optimal Monetary Policy in an Operational Medium-Sized Model: Technical Appendix," Working Paper PART B - Rules Taylor, J. B. and Williams, J. C. (2010). Chapter 15 – Simple and Robust Rules for Monetary Policy. Pages 829 – 859. In: Handbook of Monetary Economics, Volume 3 Kahn, G. A. Estimated Rules for Monetary Policy. Federal Reserve Bank of Kansas City. Economic Review, Fourth Quarter 2012 Devereux, M. B., Engel, C. and Lombardo, G. (2020). Implementable Rules for International Monetary Policy Coordination. IMF Econ Rev 68, 108 – 162 9. Monetary Tools Quantitative Easing (QE); Quantitative Tightening (QT); Yield Curve Control (YCC); Interest on Reserves (IOR); Overnight Reverse Repurchase Agreement (ONRRP); Foreign Exchange Intervention (FXI); Price Stability & Inflation Targeting; Reserve Requirements Why are QE and YCC considered unconventional monetary policies? For all considered monetary tools, is there is a hierarchy preference, or does choice primarily depend on economic circumstances at hand? PART A (QE) as unconventional monetary policy --Purpose of QE --Historical origins and cause for such prominence and acceptance --What data analysis, rules, tools and models are applied to implement QE policy? --Implementation mechanism of QE Song, Z. and Zhu, H. (2018). Quantitative Easing Auctions of Treasury Bonds, Journal of Financial Economics, 128, 103 – 124 Will like to validate for period in question and other periods. Also applicable to other foreign places where QE is acknowledged, but the internal yield curve model may differ from one to the next. --How is the intensity or effect from QE determined or captured? What data analysis, models, rules and tools are applied to gauge and control QE policy? Demonstrations required. PART B Develop the following papers with relevant ambiance data of your interest, and/or determine consistency with part A development: Kabaca, S. (2016). Quantitative Easing in a Small Open Economy: An International Portfolio Balancing Approach. Bank of Canada Working Paper 2016 - 55 < https://www.bankofcanada.ca/wp-content/uploads/2016/12/swp2016-55.pdf > PART C (QT) Analogy development to QE (for part A) PART D (YCC) Analogy development to QE (for part A) Assist: Pol, E. (2021). The Economic Logic of the Yield-Curve Control Policy, Economic Papers, 41 (1) Are the effects of QE (bonds quantity) more intense than YCC (prices of bonds) short term and long term? PART E (IOR) -Analogy development to the priors -For the case of the Fed raising (or lowering) the fed fund rate by X basis points, what models, rules, techniques and tools are applied to implement? Will have case studies. PART F (ONRRP) Analogy development to the priors PART G (FXI) Analogy development to the priors PART H (Price Stability) Will be highly computational and data driven. How does the reserve arrive at a particular percentage as their inflation target? What is deflation and the possible causes? How does one determine constructiveness and potential hazard? -Bernanke, B. S. (2006). The Benefits of Price Stability. Board of Governors of the Federal Reserve System -Svensson L.E.O. (1999). Price Stability as a Target for Monetary Policy: Defining and Maintaining Price Stability. National Bureau of Economic Research. Working Paper 7276 -Orphanides, A. and Wieland. V. (1998). Price Stability and Monetary Policy Effectiveness when Nominal Interest Rates are Bounded at Zero. Board of Governors of the Federal Reserve System < https://www.federalreserve.gov/pubs/feds/1998/199835/199835pap.pdf > -Svensson L.E.O. (2010). Inflation Targeting. National Bureau of Economic Research. Working Paper 16654 -Doh, T. (2007). What Does the Yield Curve Tell Us About the Federal Reserve’s Implicit Inflation Target? The Federal Reserve Bank of Kansas City RWP 07 – 10 PART I (Reserve Requirements) Analogy to the priors with assisting literature: -Reserve Requirements: Current Use, Motivations and Practical Considerations, OECD 2018 -Federico, P., Vegh C., and Vuletin G. (2014), NBER Working Paper No 20612 -Gray, S. (2011), IMF Working Paper WP/11/36 McKinnon, R. 1973, Money and Capital in Economic Development, The Brookings Institution -Montoro, C. and Moreno, R. (2013), BIS Quarterly Review, March 2011 10. Fiscal Policy Influence --Differentiating fiscal policy from monetary policy Influence on markets and employment When is fiscal policy most effective/practical? Liquidity Trap (LT) Features Resolutions --Using a CGE model to estimate the consequences of an expansive (contractionary) fiscal policy for ambiance --Means to determine when withdrawal is appropriate, and what/when monetary policy should be taken up --Fiscal Multiplier determination (away from ideal assumptions). How is such different from estimating fiscal consequences via CGE? --Using a mix of monetary and fiscal policies towards control on economic phenomena. Assisting literature: Cantore, C. et al (2017). Optimal Fiscal and Monetary Policy, Debt Crisis and Management. International Monetary Fund. Working Paper No. 17/78. Stock number: WPIEA2017078 Empirical studies. Application of the mixture in action. What models, rules, simulations and data support the monetary policy with fiscal policy in place (from engagement to withdrawal)? Data, recognition of detailed actions (central bank and legislature), and literature. Increments in time must not be too broad to neglect dynamic in data and the intricate policies. 11. Labour Market Response to relevant economic variables and fiscal tools. Forecasting and error. 12. Statistical Analysis and Evaluation of Macroeconomic Policies PART A (Overview Literature) Romer, C. D. and Romer, D. H. (1990). New Evidence on the Monetary Transmission Mechanism. Brookings Papers on Economic Activity Kashyap, A., K. and Stein, J. C. (1999 draft). What Do A Million Observations on Banks Say About the Transmission of Monetary Policy? NBER Working Paper Hoover, K. D. and Jordá, O. (2001). Measuring Systematic Monetary Policy, Federal Reserve Bank of St. Louis. Bean, C., Larsen, J. and Nikolov, K. (2002). Financial Frictions and the Monetary Transmission Mechanism: Theory, Evidence and Policy Implications. European Central Bank Working Paper No. 113 Boivin, J. and Giannoni, M. (2002). Assessing Changes in the Monetary Transmission Mechanism: A VAR Approach. FRBNY Economic Policy Review Boivin, J., Kiley, M. T. and Mishkin, F. S. (2010). How Has the Monetary Transmission Mechanism Evolved Over Time? Federal Reserve Board, Finance and Economics Discussion Series (FEDS) Staff Working Papers. Franta, Michal; Horváth, Roman; Rusnák, Marek (2012) : Evaluating Changes in the Monetary Transmission Mechanism in the Czech Republic, IES Working Paper, No. 11/2012, Charles University in Prague, Institute of Economic Studies (IES), Prague Rebei, N. (2017). Evaluating Changes in the Transmission Mechanism of Government Spending Shocks. IMF Working Paper WP/17/49 PART B The given journal articles beneath claim statistical analysis and evaluation techniques of macroeconomic policies. Will also like to include the conventional alternatives as well. Such given articles and alternatives to be analysed, developed in R and compared Rotemberg, Julio, and Michael Woodford. (1997). An Optimization-Based Econometric Framework for the Evaluation of Monetary Policy.” In Ben Bernanke and Julio Rotemberg, eds., NBER Macroeconomics Annual. Cambridge, MA: MIT Press. Liu, Z., Cai, Z., Fang, Y. et al. (2020). Statistical Analysis and Evaluation of Macroeconomic Policies: A Selective Review. Appl. Math. J. Chin. Univ. 35, 57–83 (2020). 13. Asset Price Bubbles & Monetary Policy Include possible consequences Phillips, P. C. B. and Shi, S. (2020). Chapter 2. Real-Time monitoring of asset Markets: Bubbles and Crises. Pages 61 – 80. In: Vinod, H. D. and Rao, c. R. Handbook of Statistics volume 42. Financial, Macro and Micro Econometrics Using R. North Holland. Cowles foundation Discussion Paper No.2152 version: https://cowles.yale.edu/sites/default/files/files/pub/d21/d2152.pdf It’s important that one becomes actively acquainted with R package psymonitor with various data of different times. Analyse and replicate. There’s also possibility of investigation with new data. Then can proceed with other ambiances of interest. R vignettes: Phillips, P. C. B., Shi, S. and Caspi, I. (2018). Real-Time Monitoring of Bubbles: The S&P 500. CRAN R Phillips, P. C. B. (2018). Real-Time Monitoring of Crisis: The European Sovereign Sector. CRAN R Supporting literature: --Phillips, P. C. B., Shi, S. and Yu, J. (2015). Testing for Multiple Bubbles: Historical Episodes of Exuberance and Collapse in the S&P 500. International Economic Review, volume 56, number 4. < http://korora.econ.yale.edu/phillips/pubs/art/p1498.pdf --Phillips, P. C. B., Shi, S. and Yu, J. (2015). Testing for Multiple Bubbles: Limit Theory of Real-Time Detectors. Cowles Foundation Discussion Paper No. 1915, Available at SSRN: https://ssrn.com/abstract=2327633 PART B How well does the Phillips related literature stack up against methods out of the following for various past events? Gurkaynak, R. S. (2005). Econometric Tests of Asset Price Bubbles: Taking Stock. Federal Reserve Board Robert Jarrow (2016). Testing for Asset Price Bubbles: Three New Approaches, Quantitative Finance Letters, 4:1, 4-9 PART C The following two articles are good to analyse. Past bubbles will be treated/modelled with such articles Filardo, A. (2004). Monetary Policy and Asset Price Bubble: Calibrating the Monetary Policy Trade-Offs. BIS Working Papers No.155 Evegenidis, A. and Malliaris, A. G. (2020). To Lean or Not to Lean Against an Asset Price Bubble? Empirical Evidence. Economic Inquiry. Vol. 58(4), 1958 – 1976 Prerequisites --> International Financial Statement Analysis II, Money & Banking, Monetary Theory & Policy, Econometrics, Economic Time Series

Regional Economics The study of regions in economics with the advent of “local” competition for attractive industries, as well as the increasing responsibility of local, state, and national governments for development issues. Will be focused on countries whose provinces/states and municipalities have strong economic independence and accountability: Canada, USA, Australia, U.K., Mexico, etc., etc. This course explores how economic activity is distributed across space and investigates the implications of including spatial aspects in economic analysis. The course is composed of labs components A, B, and C towards term report assessment (D): A. Intimate Tools 1. Development from course text (done on multiple occasions appropriately with course progression). Intelligence development and analysis from course text, accompanied by means of acquiring and screening regional economics data in the process. Active implementation of chosen methods and tools for data analysis (statistical, machine learning, tools and methods found in course text). 2. Must augment with the following when appropriate in course development Secondary data with demography and exploratory data analysis. Hedonic Development Estimating the demand for housing, land, and neighbourhood, characteristics Bid-rent curves for households, offices, and manufacturing, and cities. Hedonic Analysis of Rents and Wages Zabel, J.E. (2008). Using Hedonic Models to Measure Racial Discrimination and Prejudice in the U.S. Housing Market. In: Baranzini, A. et al (eds) Hedonic Methods in Housing Markets. Springer Yinger, J. (2016). Hedonic Estimates of Neighborhood Ethnic Preferences, Public Finance Review, 44(1), 22-51. Measuring local quality of life and productivity Local Multiplier Effect and LM3 measure Tax transfer policy Relationship between Urban Density and Building Energy Consumption; forecasting energy consumption Fiscal Health Analysis development Public Education (primary, secondary, high school, collegiate) Public Goods Government Accounts Following, develop trend analysis for prior 3 Graduation Rate in Public Education High School (followed by trend analysis) Collegiate (followed by trend analysis) Regional economic measures<Input-output; shift-share analysis; LQ; economic base; multiplier effects; economic base; export employment; leakage effects > Note: a unit as in geographical scale can be adjusted Also, recognise the industries that are driving growth/stability in the “market”. Is observation of the trend in such measures annually a good indicator of industries’ direction? Data envelopment analysis and stochastic frontier analysis (meaningful with specified markets, industries or sectors). Analytical structure before computation/simulation. Efficiency in identified markets, industries, markets, sectors, agriculture, etc. R Packages of interest for DEA rDEA, deaR, Benchmarking R Packages of interest for SFA frontier, npsf, sfa, ssfa, semsfa, Benchmarking B. Development with REAT R package Wieland T. (2019). REAT: A Regional Economic Analysis Toolbox for R, REGION, 6(3), R1–R57 https://openjournals.wu-wien.ac.at/region/paper_267/267.html Note: it’s important to comprehend your pursuits concerning the types of modelling and data (structure) required, along with the means to acquire and properly incorporate the data for implementation. C. CGE modelling and implementation (with GAMS): Mark D. Partridge & Dan S. Rickman (2010) Computable General Equilibrium (CGE) Modelling for Regional Economic Development Analysis, Regional Studies, 44:10, 1311-1328 Supporting literature: Burfisher, M. E. (2011). Introduction to Computable General Equilibrium Models, (2011). Cambridge University Press Perali, F. and Scandizzo, P. (2018). The New Generation of Computable General Equilibrium Models: Modelling the Economy. Cham: Springer. The following text provides guidance for programming and simulation; consideration towards the R + RStudio environment: Hosoe, N., Gasawa, K., & Hashimoto, H. (2010). Textbook of Computable General Equilibrium Modelling: Programming & Simulations. London: Palgrave Macmillan Limited Chang, G. H. (2022). Theory and Programming of Computable General Equilibrium (CGE) Models: A Textbook for Beginners. World Scientific. NOTE: elements (A) through (C) serve towards student groups term projects. D. For student groups term projects, a respective student group will choose a region or province for which to write an economic profile and assessment. By collecting data through official sources and applying the tools learnt, the student should be able to develop a profile and assessment worthy of presentation to the respective environments’ government. The study should consist of the following elements --> Title Abstract 1.Introduction 2.Historical backgrounds Trace the ambiances from when founded/settled This should also include cultural influences, political structure, etc. 3.Current economic profile using available secondary data Population, housing (and real estate), income, employment data, and other demographics Comparison to other similar “communities” 4.Assessments based on (A) for lower political boundaries 5.Estimating Exports (assets are not the only type of export, A REMINDER). Assists: Pfister R.L. (1980) The Minimum Requirements Technique of Estimating Exports: A Further Evaluation. In: Pleeter S. (eds) Economic Impact Analysis: Methodology and Applications. Studies in Applied Regional Science, vol 19. Springer, Dordrecht Pratt, R. (1968). An Appraisal of the Minimum-Requirements Technique, Economic Geography, 44(2), 117-124 Annual trend in estimates 6.Economic Structure Analysis Assisting guides: Rita Almeida (2007) Local Economic Structure and Growth, Spatial Economic Analysis, 2:1, 65-90 Sudhir K. Thakur (2011). Fundamental Economic Structure and Structural Change in Regional Economies: A Methodological Approach., Region et development, Region et Development, LEAD, Universite du Sud, - Toulon Var, vol. pp 9 – 38 Nebojša Stojčić, Heri Bezić, Tomislav Galović. (2016). Economic Structure and Regional Economic Performance in Advanced EU Economies. South East European Journal of Economics and Business, Volume 11(1), 54-66 Note: economic shocks and their causes in timelines should be noted for fair assessment; shocks can be observed with R packages of interest. If any recessions, to identify the causes(s), and policies applied towards recovery; complemented by data analysis identifying recession start to current state. Note: likely comparative view with (4) and (5). 7. Assessments based on (B) 8. Assessments based on (C) 9.Policy assessment for regional development Culture of the “community” Policy changes, economic incentives, etc. Comparisons to other similar “communities” 10.Economic Forecasting Review of findings with tools from economic assessment earlier; (4) through (8). Government Budget Analysis (may be critiqued by prior) Conclusion based on all priors 11.Summarization Generalization to other similar “communities”? Lessons that can be learned from this particular ambiance’s history of development and future prospects 12.Compare your unique and non-plagiarizing development to regional economic reports from banks and credit rating agencies 13.References Course Text --> John P. Blair, and Michael, C. Carroll (2008). Local Economic Development: Analysis Practices, and Globalisation, SAGE Publications Tools --> Excel R and various packages in RStudio REAT R package GAMS for CGE Grading --> Intimate Tools REAT R Package Development CGE modelling and implementation (with GAMS) Student Groups Term Projects Course Outline --> PART I Chapters 1-4 PART II Chapters 5-8 PART III Chapters 9-12 Prerequisites: Scientific Writing I & II, Microeconomics II, Advance Macroeconomics, Econometrics, Economic Time Series Sustainability Measures Course explores various measures and indicators for sustainable development at different scales. Case studies, field studies and labs will be used to stimulate learning, provide practical experience and have retention. Note: assume up to 18 weeks for this course. Assessment --> Written and quantitative/computational group assignments 50% Labs/Field Project(s) 50% NECESSARY TOOLS (for all tasks in course) --> R with RStudio Microsoft Office COURSE TOPICS --> 1.Stakeholders Geopolitical Boundaries: provincial, county, city, district A. Economic Accountability. General constituents of the public finance economy (goods and services) and linkages to the private sector for region within the particular boundary of consideration (data acquisition, modelling & dynamic) : Public Sector (note: the public sector can also be segemented) Employment, churn rate, job creation Public Services Public Goods or Community/government programmes Taxation Household taxes Business taxes (classifications) Sales taxes (various) Property taxes Estate and Gift taxes Public Transactions (various fees, tolls, penal codes fines, etc.) Pension Premiums (if gov’t run) Possible also at the provincial scale Gov’t Insurances Possible also at the provincial scale Public Investment Gov’t Auctions Markets Assets Valuations Accrued interest for credit/debt instruments Lotteries & Gambling Liabilities Balances, invoices, debts, Cash flow, debts payoff, invoices/balances payoff forecast Measuring gov’t & efficiency Cepal (2015). Methods of Measuring the Economy, Efficiency and Public Expenditure, Annex 7 Diamond, J. (1990). "9 Measuring Efficiency in Government: Techniques and Experience". In Government Financial Management. USA: International Monetary Fund. Real Estate Income distribution (observance for different periods) Agricultural Economy (if applicable) Tourism Private Sector linkages Employment, churn rate, job creation, payrolls Highfill, T. et al (2020). Measuring the Small Business Economy, BEA Working Paper Series, WP2020-4 Kotz, H. (2022). Measuring Business: Accounting for Companies' Value Creation and Societal Impact. VoxEU CEPR Private investments into region (non-Tourism) B. Even at municipal levels the notion of open economy is practical. From the Macroeconomic Accounts Statistics course concerning accounting what constituent elements are not accounted for with all priors when observing (A)? C. Economic value for goods and services (pursue): Willing to pay Hedonic pricing D. Compare to other regions: Input-output, economic base, shift-share analysis, LQ, export employment, multiplier effects, leakage effects, etc. Identify leading industries based on such prior measures. Include trends in such measures when comparing with other regions. E. Industries, sectors, firms, agriculture production Data Envelopment Analysis Stochastic Frontier Analysis F. Fiscal Health Analysis for public services (to be implemented) Segmentation choices (provincial, city, borough, district) Framework, computational logistics & implementation 2.Project Evaluation Capital Budgeting (framework and computational logistics) Cost-Benefit Analysis (monetised and non-monetised) Overview of process Monetised cost-benefits guides/manuals Non-Monetised Impacts: amenity, aesthetics, environment, ecological, heritage, culture Non-Monetised Benefits Manual: Qualitative and Quantitative Measures, Waka Kotahi NZ Transport Agency 2020 Discounting (NPV, IRR, Risk adjusted gamma) Data, Computational Logistics 3. Public-Private Partnerships (to develop) Grossman, S. A. (2012). The Management and Measurement of Public-Private Partnerships: Toward an Integral and Balanced Approach. Public Performance & Management Review, 35(4), 595–616. Koontz, T. M. & Thomas, C. W. (2012) Measuring the Performance of Public-Private Partnerships, Public Performance & Management Review, 35:4, 769-786 4.The Principal-Agent Problem Principal-Agent Problem in Government Concept and examples Instruments and Mechanisms (subject to costs and benefits) Performance metrics/evaluation and compensation: aligning the interests of both principal and agent. Note: may comprise of both quantitative and qualitive elements. Monitoring and Reporting Systems (types) Auditing & Verification (types) Gov’t oversight/inspection agencies (assumption of neutral agenda) Agents’ equity welfare/standing with project/programme Requires constant review Performance bonds or insurance? 5. Better Business Analysis of the following: Alfaro, L. et al (2021). Doing Business: External Panel Review. Final Report, World Bank Pre-Concept Note Business Enabling Environment (BEE) February 4, 2022, World Bank How to implement the identified measures from prior articles? Pursue such. 6.Healthcare To develop: Alemayehu, B., & Warner, K. E. (2004). The Lifetime Distribution of Health Care Costs. Health Services Research, 39(3), 627–642. Market Deviations: Mwachofi, A. & Al-Assaf, A. F. (2011). Health Care Market Deviations from the Ideal Market. Sultan Qaboos University Med. Journal, 11(3), 328–337. To develop with ambiance of interest: Friesen, C. E., Seliske, P. & Papadopoulos, A. (2016). Using Principal Component Analysis to Identify Priority Neighbourhoods for Health Services Delivery by Ranking Socioeconomic Status. Online Journal of Public Health Informatics, 8(2) Yu, J., Castellani, K., Forysinski, K. et al. (2021). Geospatial Indicators of Exposure, Sensitivity, and Adaptive Capacity to Assess Neighbourhood Variation in Vulnerability to Climate Change-Related Health Hazards. Environmental Health 20, 31 7.Applying the Overlapping Generations Model (OLG) Model overview and applications Dynare + OccBin Toolkit and DynareR can treat 8.National Accounts (NA) Assist for topics: SNA 2008 < https://unstats.un.org/unsd/nationalaccount/pubsDB.asp > Approaches to measure GDP Assess the distribution of income within a population Assess inflation via NA. Is the assessment of inflation equivalent to CPI? Assess effects of various economic policies 9. Statuses in the Measure of Production of Goods and Services GDP vs real GDP GNI vs Real GDP GDP per Capita https://web.northeastern.edu/econpress/2017/01/23/a-critique-of-gdp-per-capita-as-a-measure-of-wellbeing/ Harvie, D., Slater, G., Philp, B., & Wheatley, D. (2009). Economic Well-being and British Regions: The Problem with GDP Per Capita. Review of Social Economy, 67(4), 483–505. Ratio of national debt to GDP Note: apply the intelligence gathered from both literature for assessment. May have to extend such with more modern data. Hennerich, H. Debt-to-GDP Ratio: How High Is Too High? It Depends, Federal Reserve Bank of St. Louis Caner, Mehmet; Grennes, Thomas; Koehler-Geib, Fritzi. (2010), Finding the Tipping Point -- When Sovereign Debt Turns Bad. Policy Research Working Paper no. WPS 5391. World Bank. Real GDP versus the labour market and labour forecasting. 10.Fiscal Indicators (computation development and forecasting) Benz, U. and Fetzer, S. (2006). Indicators for Measuring Fiscal Sustainability: A Comparison of the OECD Method and Generational Accounting, FinanzArchiv / Public Finance Analysis, Vol. 62, No. 3, pp. 367-391 (25 pages). 11.Inequality Measurement and Redistribution (active development) Income density plots for a society with inequality at the bottom and a society with inequality at the top. Development of income thresholds: Low income: income that is less than 60% of the median Middle income: income between 60% and 200% of the median High income: income that is greater than 200% of the median To really understand the difference between the two societies, we need to look at the income distributions using a logarithmic transformation. Under a (”one-to-one”) log transformation: {1, 10, 100, 1000} --> {0, 1, 2, & 3}; such compresses the distribution, allowing to better see both the left and right tails. Seeing these tails is important because that’s where the inequality lives. Using a log transformation, replot our income density curves. Evolution of income distribution for chosen amount of years Redistribution of wealth Vertical Equity (proportional tax and progressive tax) Microsimulation. Will analyse structure of chosen models before implementation R package for TAXSIM: usincometaxes Euromod Jonathan Anomaly, J. (2015). Public Goods and Government Action, Politics, Philosophy & Economics, Vol. 14(2) 109–128 On pages 112 for the 7 given questions to pursue data wise w.r.t. to appropriate models. Cost of Living and Poverty Threshold Income Inequality Measures: De Maio F. G. (2007). Income Inequality Measures. Journal of Epidemiology and Community Health, 61(10), 849–852 King, M. A. (1983). An Index of Inequality: With Applications to Horizontal Equity and Social Mobility. Econometrica, 51(1), 99–115 Alternatives: FGT index, Palma index & Wolfson Polarization index R packages of consideration for contrasts with prior development and public databases: acid, affluenceIndex, dineq, gglorenz, ineq, lorenz, Survgini 12.Human Development Human Index (HDI) & WB’s World Development Indicators Analysis of Models and scrutinizing data integrity 13.Economic modelling of externalities Cost and Benefits: monetised and non-monetised treatment Positive externalities Negative production externalities Negative consumption externalities Measuring externalities (to implement) Cost of Damages and Cost of Control Adhikari S.R. (2016) Methods of Measuring Externalities. In: Economics of Urban Externalities. SpringerBriefs in Economics Corrections for negative externalities (production and consumption, respectively) 14.Environmental Economy Environmental Externalities concept Determining measurement practicality offered by the following articles: Mark, J. H. (1980). A Preference Approach to Measuring the Impact of Environmental Externalities. Land Economics, 56(1), 103–116. Bemow, S., Biewald, B., Marron, D. (1991). Environmental Externalities Measurement: Quantification, Valuation and Monetization. In: Hohmeyer, O. and Ottinger, R.L. (eds) External Environmental Costs of Electric Power. Springer Are methods from module (13) more practical and representative than prior articles? Modelling tools and forecasting in-class development (various environmental interests alongside growth): A. Environmental Economy Measures (to develop) Hedonic Pricing Method Ecosystems Environmental Attributes Travel Cost Method with environmental goods Contingent Valuation Method MAJOR LABS/FIELD PROJECTS --> Note: Instructor should provide ideas on what they’re looking for (in mode of professional administrative development). Note: to be done in groups (with changing constituents). Groups will present their developments. Some labs/field projects will be done in bundles. 1.Census and Demography with R For ambiance in question the databases, APIs, wrangling, etc. Interests of concern: A. Demography The following literature to serve as guides for development in R, where choice of packages and style may vary. The quality-quantity manifold concerning your development will naturally have its critics and proponents. United Nations. Manuals on Estimating Population Yusuf, F., Martins, J. M. and Swanson. D. A. (2014). Methods of Demographic Analysis. Springer Netherlands, 310 pages The Springer Series in Demographic Methods and Population Analysis B. Exploratory Data Analysis: R Packages CADStat and Tidyverse Variable Distributions Histograms Boxplots Cumulative Distribution Functions Q-Q Plots Scatter Plots Scatterplots are a useful first step in any analysis because they help visualize relationships and identify possible issues (e.g., outliers) that can influence subsequent statistical analyses, or need of regression beyond simple OLS, say, quantile regression or generalized nonlinear models. Note: concerns for the amount of variable pairs. Correlation Analysis (Pearson or Spearman?) Heat Maps ggpairs() function Conditional Probability Analysis (CADStat) Clustering (tidverse and tidymodels) Principal Component Analysis 2.Spatial Microsimulation development Note: crime is not the only interests. Note: Instructor should develop goals and computational logistics before R based immersion development; other tools may also apply. FOCUS LITERATURE FOR DEVELOPMENT O’Donoghue, C., Baltagi, B., & Sadka, E. (2014). Handbook of Microsimulation Modelling (Vol. 293). Emerald Publishing Limited Edwards, K. and Tanton, R. (2012). Spatial Microsimulation: A Reference Guide for Users. Springer Netherlands Bourguignon, F., Spadaro, A. Microsimulation as a Tool for Evaluating Redistribution Policies. J Econ Inequal 4, 77–106 (2006). Note: mandatory Harland, K. et al (2012). Creating Realistic Synthetic Populations at Varying Spatial Scales: A Comparative Critique of Population Synthesis Techniques, JASSS. 15(1) 1. TOOLS FOR DEVELOPMENT Packages msm and MicSim may accompany such above texts. Some assists for both packages: Sabine Zinn, 2014. The MicSIM Package of R: An Entry-Level Toolkit for Continuous-Time Microsimulation. International Journal of Microsimulation, International Microsimulation Association, vol. 7(3), pages 3-32. Jackson, C. H. Multi-State Models for Panel Data: The msm Package for R. Journal of Statistical Software, January 2011, Volume 38, Issue 8. Lovelace, R. and Dumont, R. (2016). Spatial Microsimulation with R. Chapman and Hall/CRC Modgen < https://www.statcan.gc.ca/eng/microsimulation/modgen/modgen Assisting test for Modgen: Alain Bélanger, A. and Sabourin, P. (2017). Microsimulation and Population Dynamics, An Introduction to Modgen 12, Volume 43. Springer JAS-mine Alternative tool: http://www.geog.leeds.ac.uk/courses/other/crime/microsimulation/practical1.html 3.Economic Efficiency Modelling Data Envelop Analysis & Stochastic Frontier Analysis Analytical development before computation/simulation. Applications in agriculture, industries, public sectors & environmental efficiency R Packages of Interest for DEA rDEA, deaR, Benchmarking R Packages of Interest for SFA frontier, npsf, sfa, ssfa, semsfa, Benchmarking 4.CBA, SROI & PPP COST – BENEFIT ANALYSIS: Literature Assists: Campbell, H., & Brown, R. (2003). Benefit-Cost Analysis: Financial and Economic Appraisal using Spreadsheets (pp. 194-220). Cambridge: Cambridge University Press Sener Salci & Glenn P. Jenkins, 2016. “Incorporating Risk and Uncertainty in Cost-Benefit Analysis”, Development Discussion Papers 2016-09, JDI Executive Programmes. Various projects such as infrastructure, transportation, service branch operations, etc., etc., etc., but environmental and/or ecological impacts are always connected critical issues. Stakeholders (social, environmental, ecological, economic) Choose a manual or guide or literature that will aid in identifying, quantifying, and evaluating the future costs and benefits of alternative solutions; as well assist in identifying the optimum course of action for decision making purposes. Monetised: Cost and Benefits. Make use of cost estimation guides for development; likewise for benefit. Non-Monetised Impacts analyses: amenity, aesthetics, environment, ecological, heritage, culture Non-Monetised Benefits Manual: Qualitative and Quantitative Measures, Waka Kotahi NZ Transport Agency 2020; cost analogy Discounting (NPV, IRR, risk adjusted gamma) Tools such as RIMS -II, IMPLAN, Chmura, LM3 or REMI may factor in B/C ratio Computational logistics for implementation Keep in mind that longer horizons likely will result in quantitative inaccuracy and various risks SOCIAL RETURN ON INVESTMENT (SROI): Folger, J. (2021). What Factors Go Into Calculating Social Return on Investment (SROI)? Investopedia Will apply to (past) projects and investments. If Analytic Hierarchy Process is used there are some R packages to accommodate. PUBLIC-PRIVATE PARTNERSHIPS Use the literature from course lecture module (3) 5. Environmental Measures A. Life Cycle Assessment (LCA) Note: applying LCA will not be lip service Foundation and Guides: ISO 14000 Series Curran, M. A. (2012). Life Cycle Assessment Handbook: A Guide for Environmentally Stable Products. Wiley Heijungs, R, and Suh. S. (2002). The Computational Structure of Life Cycle Assessment. Springer Netherlands Groen, E.A., Bokkers, E.A.M., Heijungs, R. et al. (2017). Methods for Global Sensitivity Analysis in Life Cycle Assessment. Int J Life Cycle Assess 22, pages 1125–1137 For whatever projects or topics chosen such above literature to be guide in analytical development towards a quantitative structure/model. Then, to apply specialized software: OpenLCA or Brightway2 or SimaPro (Community Edition), ACV-GOST, OpenIO, One Click LCA. Can LCA be used to critique Cost-Benefit Analysis and SROI concerning environmental accountability? B. Economic Input-Output Life-Cycle Assessment (EIO-LCA) Hawkins, T. & Matthews, D. (2009). A Classroom Simulation to Teach Economic Input−Output Life Cycle Assessment. Journal of Industrial Ecology. Volume 13 Issue 4, pages 622 – 637 EIO-LCA < http://www.eiolca.net > < http://www.eiolca.net/cgi-bin/dft/custom.pl > Further literature Assists: Economic Input-Output Life-Cycle Assessment (EIO-LCA) Hendrickson, C. T. et al. "Comparing Two Life Cycle Assessment Approaches: A Process Model vs. Economic Input-Output-Based Assessment," Proceedings of the 1997 IEEE International Symposium on Electronics and the Environment. ISEE-1997, 1997, pp. 176-181 Hendrickson, C.T., Lave, L.B., & Matthews, H.S. (2006). Environmental Life Cycle Assessment of Goods and Services: An Input-Output Approach (1st ed.). Routledge. 6. World Climate Simulation https://www.climateinteractive.org/world-climate-simulation/ Prerequisites: Enterprise Data Analysis II, International Financial Statements Analysis I & II, Microeconomics II, Introduction to Macroeconomics, Macroeconomic Accounts Statistics, Econometrics, Economic Time Series Empirical International Trade THIS IS NOT A THEORY OF INTERNATIONAL TRADE COURSE. Course emphasizes applicable computational tools for goods that are tradable across borders; goods aren’t necessarily physical. Emphasis on applicable computational development also concerns eliminating the stereotype or misconception of impracticality/intangibility. Obligations may seem congested and hectic in this course; I would be screwing you over if I didn’t make it so; goods in trade across borders in is actually a hectic operation. When the dust settles (subject to your dedication), you will have “awakened abilities” for your future. NO GUTS NO GLORY. NOTE: an 18 weeks course. Course will be highly labourious in the R environment; I’m not kidding about that. Prerequisites stated will be invaluable; efficiency and success will depend on them. The effort applied will determine how far you will go. What you have developed will be your “war chest" of computational tools for your future aspirations. Lecturing Texts IN UNISON --> Bacchetta, M. et al. (2012). A Practical Guide to Trade Policy Analysis, World Trade Organisation Yotov, Y. V. et al (2016). An Advanced Guide to Trade Policy Analysis: The Structural Gravity Model (Volume 2), World Trade Organisation Plummer, M. G., Cheong, D. and Hamanaka, S. (2010). Methodology for Impact Assessment of Free Trade Agreements, Asian Development Bank Porto, M. (2020). Using R for Trade Policy Analysis: R Codes for the UNCTAD and WTO Practical. Springer International Publishing Regulations and cooperative frameworks stem from the following --> UNCTAD, WTO, UNCITRAL Further Resources --> https://www.wto.org/english/res_e/reser_e/PracticalGuideFiles.zip https://www.wto.org/english/res_e/reser_e/AdvancedGuideFiles.zip Databases --> UNCTAD, WTO, UNCITRAL, UN Comtrade, OECD, UNFAO, World Bank WITS, World Bank Trade, Production and Protection Database, IMF, CEPII, ITPD-E, Dynamic Gravity Dataset, GTAP, UNSD Grading --> R exercise problems being adjusted and/or augmented (EPAA) Course labs in R and GAMS environment R Development Major Assignments (MA) TBA Group Term Projects (GTP) Literature use: 1.Baccheta, M et al (2012) for (EPAA) and (MA) 2.Yotov, Y. V. et al (2016) for (EPAA) and (MA) 3.Plummer, M. G. et al (2010) for (MA) 4.Porto, M. (2020) for (EPAA) and (MA) 5.Costinot, A. and Rodríguez-Clare, A. (2014). Chapter 4, Trade Theory with Numbers: Quantifying the Consequences of Globalization. In: Handbook of International Economics, Volume 4. Elsevier, pp 197 – 261 (MA) 6.Trade Policy Simulation Models only for GTP UNCTAD Trade Policy Simulation Model Sam Laird and Alexander Yeats UNCTAD-FAO Agricultural Trade Policy Simulation Model (ATPSM) Ralf Peters and David Vanzetti NOTE: for group term projects students must report their developments at designated periods along with consultation with instructor. Students are responsible for R development. COURSE OUTLINE --> Bacchetta et al: Chp 1 – 2 Chp 3 to be augmented by Chp 1 of Yotov et al Chp 4 Chp 5 to be augmented by Chp 2 of Yotov et al Computable General Equilibrium structural development review and use Comparative: limitations of CGE Analysis ang Gravity models Plummer et al: Chp 2 (confined to 2.1) Chp 3 (confined 3.1 – 3.2) Bacchetta et al: Chp 6 COURSE LABS --> Instructor develops the concepts and logistics, then left for students to develop mainly in R. Depending on the lab students will be assigned different ambiances concerning the mentioned goals. Labs will be bunched into groups. 1. Comparative Advantage Review Comparative Advantage Indices Types and respective structure Constructing and testing Kiyota, K. (2011). A Test of the Law of Comparative Advantage, Revisited, Rev World Econ 147, 771 Choi, Nakgyoon, (2011). Empirical Tests of Comparative Advantage: Factor Proportions, Technology, and Geography. KIEP Research Paper No. Working Paper-11-01 Ballance, R. H., Forstner, H., & Murray, T. (1987). Consistency Tests of Alternative Measures of Comparative Advantage. The Review of Economics and Statistics, 69(1), 157–161. 2. Barriers to Trade and Non-Tariff Trade Measures (Overview) Barriers to Trade WTO’s Technical Barriers to Trade (TBT) Agreement UNCTAD - Non-tariff measures (NTMs) 3. Active Comparative Analysis of Partial Equilibrium Models From the text of Bacchetta et al, namely, pp 146 – 171 (and Yotov et al), will be comparing such models and uses to those from the following: Hallren, R. and Riker, D. (2017). An Introduction to Partial Equilibrium Modelling of Trade Policy. USITC Economic Working Paper Series, Working Paper 2017-07-B Khachaturian, T. and Riker, D. (2016). A Multi-Mode Partial Equilibrium Model of Trade in Professional Services. USITC Economic Working Paper Series, Working Paper 2016-11-A. Note: consider services or markets of interest 4. Literature to analyse and simulate for various conditions: Devereux, M. (2000). A Simple Dynamic General Equilibrium Model of the Tradeoff Between Fixed & Floating Exchange Rates. London, Centre for Economic Policy Research. Simulate various conditions/circumstances DYNARE + OccBin Toolkit Package DynareR 5. Real Exchange Rate Structure and Alternatives EUROSTAT-OECD Methodological Manual on Purchasing Power Parities (PPPs), European Union / OECD, 2012 Schmitt-Grohé, S., Uribe, M. and Woodford, M. (2022). Chapter 9, Real Exchange Rate. In: International Macroeconomics: A Modern Approach, Princeton University Press Moosa I.A., Bhatti R.H. (1997) Purchasing Power Parity: Model Specification and Related Econometric Issues. In: International Parity Conditions. Palgrave Macmillan, London. 6. Real Exchange Rate Measures Salto, M. and Turrini, A. (2010). Comparing Alternative Methodologies for Real Exchange Rate Assessment. Economic Papers 427. European Commission Methodologies to develop 7. Time Series for Demand Exports Models Mahmoud, E., Motwani, J., & Rice, G. (1990). Forecasting US Exports: An Illustration using Time Series and Econometric Models. Omega-international Journal of Management Science, 18, 375-382 Senhadji, A. S., & Montenegro, C. E. (1999). Time Series Analysis of Export Demand Equations: A Cross-Country Analysis. IMF Staff Papers, 46(3), pages 259 –273 Imports Models Agbola, F. W. and Damoense, M. Y. (2005), Time‐Series Estimation of Import Demand Functions for Pulses in India, Journal of Economic Studies, Vol. 32, Number 2, pp. 146-157 Keck, A., A. Raubold and A. Truppia (2010), "Forecasting International Trade: A Time Series Approach", OECD Journal: Journal of Business Cycle Measurement and Analysis, vol. 2009/2 8. Determining price elasticities of import demand and export supply Kee, H. L., Nicita, A., & Olarreaga, M. (2008). Import Demand Elasticities and Trade Distortions. The Review of Economics and Statistics, 90(4), 666–682 Imbs, J. and Mejean, I. (2010). Trade Elasticities: A Final Report European for the European Commission. Economic Papers 432 Tokarick, S. (2010). A Method for Calculating Export Supply and Import Demand Elasticities, IMF Working Papers, 2010(180), A001. Fontagné, L. G., Guimbard, H. & Orefice, G. 2019. Product-Level Trade Elasticities: Worth Weighting For. CEPII Working Paper No 2019-17 9. Gravity Models Concept and purpose. Strengths and weaknesses of Gravity Models. NOTE: use of R package “gravity” compared to direct development in R Chaney, T. (2013). The Gravity Equation in International Trade: An Explanation. NBER Working Paper Series, Working Paper 19285 Econometric estimation of gravity equations: Baltagi B.H., Egger P.H., Erhardt K. (2017) The Estimation of Gravity Models in International Trade. In: Matyas L. (eds) The Econometrics of Multi-Dimensional Panels. Advanced Studies in Theoretical and Applied Econometrics, vol 50. Springer, Cham Shepherd, B., Doytchinova, H. and Kravchenko, A. (2019). Gravity Model of International Trade: A User Guide' (R version). Bangkok: United Nations ESCAP 10. Barriers to Trade, Basic Analysis of a Tariffs, and Gravity Model Revisited Barriers to trade and Non-Tariff Measures (review) Basic Analysis of a Tariff Nasreen Nawaz (2019) A Dynamic Model for an Optimal Specific Import Tariff, The International Trade Journal, 33:3, 255-276 How to test? Gravity Model for Barriers Explaining barriers to trade with the Gravity Model Gravity model for tariffs Using the Gravity Model to Estimate the Costs of Protectionism How do firms or countries evade Tariffs? Counter tactics? Case Studies. 11. CGE Trade Modelling (with GAMS) Try to make the following real data relevant as possible: Zhang, X. G. (2006). Armington Elasticities and Terms of Trade Effects in Global CGE Models. Productivity Commission Staff Working Paper. Melbourne Lofgren, H. and Cicowiez, M. (2018). Linking Armington and CET Elasticities of Substitution and Transformation to Price Elasticities of Import Demand and Export Supply: A Note for CGE Practitioners. CEDLAS, Working Papers 0222 Burfisher, M. (2021). Trade in a CGE Model. In: Introduction to Computable General Equilibrium Models. Cambridge University Press. pp. 194-218 Whalley, J. (2012). General Equilibrium Global Trade Models. The Tricontinental Series on Global Economic Issues: volume 1 Helpful CGE literature: Hosoe, N., Gasawa, K., & Hashimoto, H. (2010). Textbook of Computable General Equilibrium Modeling: Programming and Simulations. London: Palgrave Macmillan Limited. Chang, G. H. (2022). Theory and Programming of Computable General Equilibrium (CGE) Models: A Textbook for Beginners. World Scientific. Premier Models (choice of 2-3) Note: the prior literature are for preliminary essential development -- OECD- METRO trade model CEPII MIRAGE - E GTAP models (standard model, Dynamic GTAP, GTEM, MYGTAP) < https://www.gtap.agecon.purdue.edu/default.asp > Worldbank-Linkage CPB Worldscan PEP Standard CGE Models 12. Real Effective Exchange Rate (REER) To analyse models in given literature, then replicate Schmitz, M. et al. (2012). Revisiting the Effective Exchange Rates of the EURO. ECB Occasional Paper Series No. 134 Done for timeline in above literature. Will also consider other regions Followed by implementation with more modern data. Will also consider other regions Discussion paper to develop: Coutinho, L. et al (2021). Methodologies for the Assessment of Real Effective Exchange Rates. European Economy Discussion Paper 149 Working paper to develop and comparative counterpart development to prior: Mayer, T. and Steingress, W. (2019). Estimating the Effect of Exchange Rate Changes on Total Exports. BIS Working Papers No 786 Highlight the key takeaways in the following source and pursue such assessments: Hayes, A. (2020). Real Effective Exchange Rate – REER Definition, Investopedia 13. Balassa-Samuelson Effect (BSE) Model development Measurement Analyse & develop the measures to compare with the database: Couharde, C. et al (2019). Measuring the Balassa-Samuelson- Effect: A Guidance Note on the RPROD Database. CEPII Working Paper, Paris Will there be differences in prices and incomes across countries as a result of differences in productivity? Analyse and replicate, then use of more modern data: MacDonald R. and Ricci, L. A. (2001). PPP and the Balassa-Samuelson Effect: The Role of the Distribution Sector. IMF Working Paper WPIEA0382001 To validate: BSE “explains why using exchange rates vs. purchasing power parity to compare prices and incomes across countries will give different results”, Investopedia. 14. Analysis of the Current Account and benchmarks (implementable) Analysis of the Current Account Ca’ Zorzi, M., Chudik, A. and Dieppe, A. (2009). Current Account Benchmarks for Central and Eastern Europe. A Desperate Search? European Central Bank Working Paper Series No. 995 Coutinho, L., Turrini, A. and Zeugner, S. (2018). Methodologies for the Assessment of Current Account Benchmarks. EU Discussion Paper 086 15. Montiel, P. J. (2002). "11 The Long-Run Equilibrium Real Exchange Rate: Theory and Measurement". In Macroeconomic Management. USA: International Monetary Fund. (requires implementation assignments) Prerequisites: Microeconomics III, (or Advanced Macroeconomics), Econometrics, Economic Time Series. Computational Labour Economics The objective of the course is to immerse students into applicable and practical tools of modelling, computation and econometrics in the field of labour economics. In a manner that provides sustainability for future academic and professional interests. Hence, prerequisites for this course are a bit more advanced than the typical “fodder” or “in one ear, out the next” undergrad course. Grading --> Major Projects 65% Take Home Final Exam 35% Take Home Final Exam --> There is a take-home examination at the end of the term based on lecturing, projects AND ALL prerequisites. MAJOR PROJECTS (requires prerequisites knowledge and skills) --> Note: data sources will depend on ambiance of lecturing; adjust to suit wherever. Will also be incorporating much more modern data. Note: various lab activities will be bundled accordingly and w.r.t. lecturing progress. A. Basic data analysis: databases; wrangling; summary statistics generation; plots; correlation matrices and heatmaps; distributions; regression; time series with possible salient characteristics and model evaluation. Sources of concern: BLS Public Data (possibly with API) CPS Type data NBER databases (or country counterpart, possibly with API) OECD API, etc., etc., etc., etc. Household Panel Surveys (different places and regions) Economic indicators (CPI, EPI, Employment Situation, PPI, Productivity & Costs, Real Earnings, Country Import & Export Prices). Strong applications. B. CPS Data Flinn, C. “Econometric Analysis of CPS-Type Unemployment Data.” J. of Human Resources (1986) 21: 456-484. Analyse, replicate and develop to ambiance of interest. Median Duration of In-Progress Unemployment Spells: Time Series and salient features C. Macroeconomic influences on employment -Okun’s law models “A country’s GDP must grow at about a 4% rate for one year to achieve a 1% reduction in the rate of unemployment”, (Furhmann, Investopedia). Analysing and testing (developed and developing countries at different time periods) with econometrics. -Relationship between fed fund rate and unemployment Sam, K. A. (2014). The Federal Funds Rate and Unemployment Relationship: Does Business Confidence Matter? University of Wisconsin-Stout Journal of Student Research, 13, 112-126. Article to be analysed/critiqued. Followed development of all displays. Then to have analysis/critique of given methodology, succeeded by development. Pursuit of more modern time periods as well. -Conventional economic variables for employment and forecasting. Intelligence and skills from the Econometrics course expected. Validation for the following elements/variables (and possibly others) towards an employment model. Multicollinearity issues may arise. Model identification, estimation, forecasting & error. Some candidate predictor variables of features: Fed Funds Rate Inflation Gov’t Deficit Public Debt Gov’t Size Business payroll taxes and other business tax incentives Purchasing Management Index Industrial Production Index Trade Balance GDP -Analyse, replicate and pursue ambiances of interest: Lafourcade, P. et al (2016). Labour Market Modelling in Light of the Financial Crisis. Occasional Paper Series, No. 175. European Central Bank Note: applicable to other crises w.r.t. ambiances -Fiscal policies and labour (include modern data) Bovaa, E., Kolerus, C. and Tapsoba, S. J. A. (2014). A Fiscal Job? An Analysis of Fiscal Policy and the Labour Market. IMF WP/14/216 Stepanyan, A. and Leigh, L. (2015). Fiscal Policy Implications for Labour Market Outcomes in Middle-Income Countries. IMF WP/15/17 -Tax Burden Will choose topics from the following text to development and implement Sorensen, P. B. (2022). Measuring the Tax Burden on Capital and Labour, MIT Press -The employment elasticity of economic growth Pursue descriptive method development and econometric method development to compare/contrast -Earned Income Tax Credit Purpose and consensus impacts (assuming constructive spending or consumption by households). The recognised low-to-middle income cases can be analysed with EITC calculation. Then to possibly analyse how the extra income aids in essentials (transportation, healthcare, sustenance, utilities, etc., etc., etc.); cost of living measure may or be practical. Williams, E., Waxman, S. and Legendre, E. (2020). How Much Would a State Earned Income Tax Credit Cost in Fiscal Year 2021? Centre on Budget and Policy Priorities Interest in this article is applying the -Data Sources (substitute country data of interest) -Three Steps to Estimating the Cost of a State EITC Note: depending on your country, provinces/states may not have such fiscal policy power. So, adjust accordingly. Does cost outweigh the benefits? Tax simulators such as EUROMOD and NBER TAXSIM can be useful; tools such as RIMS -II, IMPLAN, Chmura, LM3 or general equilibrium and REMI may be relevant to the cost-benefit analysis pursuit. Note: consideration of monetised and non-monetised benefits as well. D. Labour Market Dynamics -Develop the following to simulate for various conditions with pursuit of parameters based on ambiance of interest Demirel, U. D. (2020). Labor Market Effects of Tax Changes in Times of High and Low Unemployment. Congressional Budget Office, Working Paper 2020-05 Also, means to validate simulation developments with empirical economic circumstances. -An interesting task will be development for chosen ambiance with considered time range: Pranvera Elezi et al. (2014). Albania Labour Market Dynamics 2001-2011, INSTAT 2014 -Develop the following with pursuit of parameters Fiaschi, A. and Tealdi, C. (2021). A General Methodology to Measure Labour Market Dynamics. IZA DP No. 14254 -Means to compare prior two tasks E. Labour Market Forecasting Developing the Beveridge Curve Regis Barnichon & Christopher J. Nekarda, 2013. The Ins and Outs of Forecasting Unemployment: Using Labor Force Flows to Forecast the Labor Market. Finance and Economics Discussion 2013 - 19, Board of Governors of the Federal Reserve System (U.S.). https://www.brookings.edu/wp-content/uploads/2012/09/2012b_Barnichon.pdf Analyse, replicate and develop to ambiance of interest. Will compare with relatable model development and forecasting from (C). F. Wages Analysis PART 1 Wage variations Model Development Prospect variables to validate: education, work experience, unionization, industry, occupation, region, demographics, etc. Coefficients via OLS/WLS/GLS/Quantile Model Validation Wage distribution, conditional probabilities and conditional expectations (for various predictor variables, one at a time or in bulk) w.r.t. data. Marginal effects (margins package) PART 2 (Reservation Wage (RW) from the indifference curve) Note: from data will consider different occupations. Various scenarios for X, Y and Z “parameters” based on: Consumption-Leisure plane scaling Determining a realistic utility function. How to accomplish such? Marginal utility of consumption Marginal utility of leisure Marginal rate of substitution X hours of leisure $Y unemployment benefits (with whatever increments) $Z per hour wage offer in the market Believes by searching to find a better offer Variation between RW and Z. PART 3: To have analysis of the following and to situate or make relevant to identify counterparts with part 2: Krueger, A. B. and Mueller, A. I. (2014). A Contribution to the Empirics of Reservation Wages. NBER Working Paper Series, Working Paper 19870 Pursue empirics for whatever region of interest PART 4. (Long-Run Asymmetries) Kölling, A. (2020). Long‐Run Asymmetries in Labor Demand: Estimating Wage Elasticities of Labor Demand Using a Fractional Panel Probit Model, Labour, 34(1), pp. 26-47. Note: try logit as well. PART 5 (Wage Characterisation) Note: determine constructive succession order. Can adjust to ambiance of interest with modern data included Cahuc, P., Postel-Vinay, F., & Robin, J.-M. (2006). Wage Bargaining with On-the-Job Search: Theory and Evidence. Econometrica, 74(2), 323–364. Postel-Vinay, F. and JM Robin. (2002). Wage Dispersion with Worker and Employer Heterogeneity. Econometrica70: 295-350 Moscarini, G. (2005). Job Matching and the Wage Distribution. ”Econometrica 73: 481-516 Hofler, R. A., & Murphy, K. J. (1994). Estimating Reservation Wages of Employed Workers Using a Stochastic Frontier. Southern Economic Journal, 60(4), 961–976. PART 6 (Wage Forecasting) To compare with regression model in (F) for ambiances of interest (if feasible): Koskinen, L., Nummi, T. and Salonen, J. Modelling and Predicting Individual Salaries: A Study of Finland’s Unique Dataset. Finnish Centre for Pensions Working Papers 2005: 2 https://www.julkari.fi/bitstream/handle/10024/129098/ModellingandpredictingindividualsalariesastudyofFinlandsuniquedataset.pdf For the following develop with exclusion of NFIB: Knotek, E. S. (2015). Difficulties Forecasting Wage Growth. Federal Reserve Bank of Cleveland Note: for BVAR one can compare model determination with the BVAR package and the bvartools package in R G. Hedonic Analysis Hedonic Analysis of Rents and Wages H. Economic Cost Index (ECI) James Chen (Investopedia) – Employment Cost Index (ECI) Past data to be applied to verify any high accuracy, and towards future forecasting: Ruser, J. W. (2001). The Employment Cost Index: What Is It? Monthly Labor Review < https://www.bls.gov/opub/mlr/2001/09/art1full.pdf Relationships between Wages, Prices, and Economic Activity One to pursue development/critique of the analytical/time series models; compare model preference with literature models (if such comes up). Data will be used to validate. Knotek, E. S. and Zaman, S. (2014). On the Relationships between Wages, Prices, and Economic Activity. Economic Commentary. Federal Reserve Bank of Cleveland I. Logistic/Probit Regression in Labour Economics Fluid analysis and computational logistics towards implementation. Can adjust to places of interest with data relevance (incorporating modern data) in development. Options: Ciecka, J., & Donley, T. (1996). A Logit Model of Labor Force Participation, Journal of Forensic Economics, 9(3), 261-282. Kiiver, H. and Espelage, F. (2016). The Use of Regression Models in Labour Market Flow Statistics. European Conference on Quality in Official Statistics Ciuhu (Dobre), Ana-Maria & Caragea, Nicoleta & Alexandru, Ciprian, (2017), Modelling the Potential Human Capital on the Labour Market Using Logistic Regression in R. Romanian Statistical Review. 65. 141-152. Strzelecka, A., Kurdyś-Kujawska, A. and Zawadzka, D. (2020). Application of Logistic Regression Models to Assess Household Financial Decisions Regarding Debt. Procedia Computer Science 176, 3418–3427 Kaiser, L. C. (2006). Female Labor Market Transitions in Europe. IZA Discussion Paper No. 2115 The household and employment determinants of poverty for households different time points. J. Censored Count Data Models Merkle, L., & Zimmermann, K. (1992). The Demographics of Labour Turnover: A Comparison of Ordinal Probit and Censored Count Data Models. Recherches économiques De Louvain, 58(3-4), 283-306. Caudill SB and Mixon FG. (1995). Modelling Household Fertility Decisions: Estimation and Testing of Censored Regression Models for Count Data. Empir Econ. 20(2):183-96 K. Migration and Outsourcing Articles from lecture to be developed COURSE MODULES --> A. Primitive Labour Market Modelling (highly restricted time schedule) Will have a transitioning process of going from precalculus models to multivariate calculus models and skills Labour Supply Labour Demand Competitive Equilibrium Can developed models from the prior three be transformed into meaningful econometric models or time series models, or is curve fitting more appropriate? Cairo, I., Fujita, S. and Morales-Jiménez, C. (2019). Elasticities of Labor Supply and Labor Force Participation Flows. Federal Reserve Bank of Philadelphia, Working Paper 19-03. NOTE: acquiring data to model all such (for ambiances of interest) Nazier, H. Estimating Labor Demand Elasticities and Elasticities of Substitution in Egyptian Manufacturing Sector: A Firm-Level Static Analysis. Ind. J. Labour Econ. 62, 549–575 (2019). NOTE: acquiring data to model all such (for ambiances of interest). Interest in other sectors as well. Compensating Differentials versus Efficiency Wages Analyse the given two journal articles and develop comparative analysis. Aim is to apply both methods to sectors or industries to ambiances of interest with relevant data: Arai, M. (1994). Compensating Wage Differentials versus Efficiency Wages: An Empirical Study of Job Autonomy and Wages. Industrial Relations, Volume 32, Issue 2, pages 249 – 262 Fairris, D., & Alston, L. J. (1994). Wages and the Intensity of Labor Effort: Efficiency Wages versus Compensating Payments. Southern Economic Journal, 61(1), 149–160. B. Labour Laws and Workers’ Rights Acts, amendments and minimum wage C. Labour Market Dynamics Search and Matching Model in Labour Economics (concept and structure serving in labour economics) To develop for ambiances of interest: Lubik, T. A. (2009). Estimating a Search and Matching Model of the Aggregate Labour Market. Economic Quarterly—Volume 95, Number 2—Pages 101–120 Robalino, D. A. & Weber, M. (2016). Simulations of Labour Policies in Tunisia with a Structural Job-Search Model. World Bank Lancaster, T. (1979). Econometric Methods for the Duration of Unemployment, Econometrica, 47(4), 939-956. WorkSim (concept): https://www.oecd.org/naec/OECD_2017_WorkSim_Ballot_Kant.pdf Worksim Development Ballot and Kant 2017, OECD Ballot, G., Kant, J. D.and Goudet, O. (2013a). A Multi-Agent Model of the French Labour Market: WorkSim » WEHIA 2013 - 18th Annual Workshop on Economic Science with Heterogeneous Interacting Agents - Reykjavik University, Iceland - June 20-22, 2013. Ballot, G., Kant, J. D. and Goudet, O. (2013b). Modelling Both Sides of the French Labour Market with Adaptive Agents Under Bounded Rationality » The 25th Annual Conference of the EAEPE (European Association for Evolutionary Political Economy), Bobigny – November 2013. Goudet, Kant and Ballot 2017, Comput Econ Determinants of Job Mobility: Ng, T. W. H., Sorensen, K. L., Eby, L. T., & Feldman, D. C. (2007), Determinants of Job Mobility: A Theoretical Integration and Extension. Journal of Occupational and Organizational Psychology, 80, 363–386. Developing logistic regression models (basic, multi, log) D. Household Economics Household Bargaining and Labor Supply Models of Household Formation and Dissolution References for module: Ebert, Udo; Moyes, Patrick (October 2009). "Household Decisions and Equivalence Scales". Journal of Population Economics. 22 (4): 1039–1062 Hopefully we can apply parameters to models Keilman, N., Kuijsten, A. and Vossen, A. (1988). Modelling of Household Formation and Dissolution. Oxford University Press A challenge to class to develop with demography data Fortin, B., & Lacroix, G. (1997). A Test of the Unitary and Collective Models of Household Labour Supply. The Economic Journal, 107(443), 933-955. E. Asymmetric Information in the Labour Market Principal-Agent Problems in the Labour Market Econometric Models of Moral Hazard F. Monosopy in Labour Markets Analyse and pursue validation for wherever Sokolova, A., & Sorensen, T. (2021). Monopsony in Labor Markets: A Meta-Analysis. Industrial & Labor Relations Review, 74(1), 27–55. For the following the highly fruitful task of understanding how to model the determinants of earnings in matched employer-employee data sets and the implications for inequality and the labor share Manning, A. (2019). Monopsony in Labor Markets: A Review. Industrial and Labor Relations Review G. Labour Unions Labour Unions & Collective Bargaining. Legal steps in union formation and recognition Effect of unions in demand-supply models with equilibrium wage in the wage-labour plane. Articles to analyse, replicate and pursue ambiance of interest with modern data included: Card, D. (1996). The Effect of Unions on the Structure of Wages: A Longitudinal Analysis. Econometrica, 64(4), 957–979 Gurtzgen, N. (2016). Estimating the Wage Premium of Collective Wage Contracts: Evidence from Longitudinal Linked Employer-Employee Data, Industrial Relations (Berkeley), 55(2), 294–322 Barth, E., Bryson, A. and Dale-Olsen, H. (2020). Union Density Effects on Productivity and Wages, The Economic Journal, Volume 130, Issue 631, Pages 1898–1936 Investigate empirically with whatever models (may prove tedious) Do unions hamper workers in the long run by driving firms into bankruptcy, or by blocking the new technologies and production methods that lead to economic growth? Do countries with a higher percentage of unionized workers usually have less growth in productivity because of strikes and other disruptions caused by the unions? Why or why not? Decline or growth in union membership? Why? H. Labour Market Policy Evaluation Policies in Labor Economics For the given literature, after analysis identify the tools and techniques required to implement a meaningful evaluation. Will pursue real world evaluations (with incorporation of much modern data for wherever) Robalino, D. A. & Weber, M. (2016). Simulations of Labour Policies in Tunisia with a Structural Job-Search Model. World Bank https://www.gtap.agecon.purdue.edu/resources/download/8131.pdf Pierre, G. (1999). A Framework for Active Labour Market Policy Evaluation, Employment & Training Papers 49 I. Minimum Wage Simulations The given literature can be applied in comparative view. However, after analysis, pursue ambiances of interest, possibly augmented with more modern data Wolff, E., & Nadiri, M. (1981). A Simulation Model of the Effects of an Increase in the Minimum Wage on Employment, Output, and the Price Level. In: Report of the Minimum Wage Study Commission (Vol. 6). U.S. Government Printing Office. Johnson, W. R., & Browning, E. K. (1983). The Distributional and Efficiency Effects of Increasing the Minimum Wage: A Simulation. The American Economic Review, 73(1), 204–211 Flinn, C. J. (2006). Minimum Wage Effects on Labour Market Outcomes under Search, Matching & Endogenous Contact Rates. Econometrica, Vol. 74, No. 4, 1013–1062 MaCurdy, T. (2015). How Effective is the Minimum Wage at Supporting the Poor? Journal of Political Economy Volume 123, Number 2 Lemos, S. (2008). A Survey of the Effects of the Minimum Wage on Prices, SRPN: Social Economics (Topic). J. Costs and Production Human Capital ROI (public sector elements case examples) Development and verification via financial statements, annual reports, etc., Analyse, then develop for whatever region of interests (among cities, or provinces or countries with modern data included) Thomas E. Lambert. (2016). Do Efficiency and Productivity Pay Off for Capital and Labor? A Note Using Data Envelopment Analysis. World Review of Political Economy, 7(4), 474–485. K. Effects of Migration and Outsourcing on Labour & Wages Note: analysis of literature in lecturing, then development in lab PART I: literature for development with possible calibration, measurement or estimation for comparative analysis Bandyopadhyay, S. and Wall, H. J. (2007). Immigration and Outsourcing: A General Equilibrium Analysis, Federal Reserve Bank of St. Louis Working Paper 2005-058 Yomogida, M., & Zhao, L. (2010). Two-Way Outsourcing, International Migration, and Wage Inequality. Southern Economic Journal, 77(1), 161–180. PART II Replicate findings then apply to more modern data Horgos, D. (2009). Labour Market Effects of International Outsourcing: How Measurement Matters. International Review of Economics and Finance 18, pages 611–623 Prerequisites: Microeconomics III, Introduction to Macroeconomics, Econometrics, Economic Time Series Agriculture & Economic Sustainability Course serves to introduce basic agricultural research and incorporation of economic measures and tools. Course will be lab and field based. Each module will be accommodated by labs. Note: an 18 weeks course, 2 lecture sessions per week, 2 hours per session. Note: 3 hours per lab session. Lab sessions serve as logistics for lecture sessions. A lab session will highly likely accommodate multiple lab topics. Tools and skills from prerequisite courses will be invaluable for labs; students will be responsible for computational development and reports. Note: ambiances assigned may vary among students on multiple occasions. As well, identified commodities may be substituted by other commodities, specifically for produce. Conversions Reference (CR) --> Weights, Measures, and Conversion Factors for Agricultural Commodities and Their Products. Economic Research Service in cooperation with the Agricultural Marketing Service, the Agricultural Research Service, and the National Agricultural Statistics Service, U.S. Department of Agriculture. 1992, Agricultural Handbook No. 697 Outline --> 1. Agricultural conversions. CR given will be applied for various (field/lab) exercises. 2. Sustainability Planning A. Cropping Systems Blanco-Canqui, H., Lal, R. (2010). Cropping Systems. In: Principles of Soil Conservation and Management. Springer, Dordrecht. Identify/characterize types in ambiance Yang, T., Siddique, K. H. M., & Liu, K. (2020). Cropping Systems in Agriculture and their Impact on Soil Health-A Review. Global Ecology and Conservation, 23, [e01118] Amsili, J. P. et al (2021). Cropping System and Soil Texture Shape Soil Health Outcomes and Scoring Functions. Soil Security 4, 100012 Make relevant to ambiance data B. Multicriteria Decision Analysis Note: example articles to emulate for ambiances of interest. GRASS GIS with MCDA add-ons to be applicable. Part A ( Land Use) Herzberg, R. et al. (2019). Land, 8(6), 90. MDPI AG. Wotlolan, D.L., Lowry, J.H., Wales, N.A. et al. (2021). Agroforest Syst 95, 1519–1532 (2021). Part B (Water Management) Ravier, C. et al (2015). Land Use Policy , vol. 42 pp 131 – 140 Radmehr, A., Bozorg-Haddad, O. & Loáiciga, H.A. (2022). Sci Rep 12, 8406 (2022). C. Crop Rotation (subjugated by A and B) Overview Crop Rotation Simulation Asseng, S. et al (2014). Simulation Modelling: Applications in Cropping Systems. Encyclopedia of Agriculture and Food Systems. Pages 102 – 112 The most common models used to simulate crop rotations are DSSAT, EPIC, APSIM, CropSyst, STICS, SALUS, and root zone water quality model (RZWQM). Hopefully choices (at least 2) are accessible, fluid and practically implementable. D. Can (A) through (C) be efficiently integrated? 3. Supply and Demand for Commodities A. Estimating demand curves and supply curves with regression B. Estimating elasticities of supply and demand Kennes, W. (1983). European Review of Agricultural Economics, 10(4), pages 357–376 Wohlgenant, M. K. (1985). Western Journal of Agricultural Economics 10(2): 322-329. Helen, D., and L. S. Willett. (1986). Northeastern Journal of Agricultural and Resource Economics, pp. 160-167. Helen, D. and G. Pompelli. (1988). Western Journal of Agriculture Economics. 13: 37-44 Price, D. W., & Mittelhammer, R. C. (1979). Western Journal of Agricultural Economics, 4(1), 69–86. Huang, K. [US Demand for Food: A Complete System of Price and Income Effects.] United States Department Of Agriculture, Economic Research Service, Technical Bulletin 1714 Huang, K. S., and B. Lin. (2000). Estimation of Food Demand and Nutrient Elasticities from Household Survey Data. Food and Rural Economic Division, Economic Research Service, US Department of Agriculture, Technical Bulletin, Number 1887 Brester, G. W., and M. K. Wohlgenant. (1993). Correcting For Measurement Error in Food Demand Estimation. The Review of Economics and Statistics. 75: 352-356 Roberts, M. J., & Schlenker, W. (2013). The American Economic Review, 103(6), 2265–2295. [NBER version exists] Al Rawashdeh, R. (2022). Estimating Short-Run (SR) and Long-Run (LR) Demand Elasticities of Phosphate. Miner Econ (2022). C. Recollection: what conclusions can be conventionally drawn from development of (A) and (B)? 4. Agricultural Household Models: Theory and Applications Note: goal is to have such literature be relatable to data of interest. Singh, I., Squire, L., & Strauss, J. (1986). A Survey of Agricultural Household Models: Recent Findings and Policy Implications. The World Bank Economic Review, 1(1), 149–179 Benjamin, D. (1992). Household Composition, Labor Markets, and Labor Demand: Testing for Separation in Agricultural Household Models, Econometrica, Vol. 60, No. 2, pp. 287-322 Singh, Inderjit; Squire, Lyn; Strauss, John [editors]. Agricultural Household Models: Extensions, Applications, and Policy (English). Washington, D.C. World Bank Group Taylor, J.E. and Adelman, I. (2003). Agricultural Household Models: Genesis, Evolution, and Extensions. Review of Economics of the Household 1, 33–58 5. Farm Size and Productivity Relationship Note: goal is to have literature be relatable to data of interest. 6. Market Analysis in Agriculture PESTEL and SWOT are applicable 7. Soft Commodities Pricing Methods PART A Given literature to analyse, computationally replicate, and augment with more modern data (for countries and commodities of interest). Westcott, P. C. and Linwood A. Hoffman. (1999). Price Determination for Corn and Wheat: The Role of Market Factors and Government Programmes. Market and Trade Economics Division, Economic Research Service, U.S. Department of Agriculture. Technical Bulletin No. 1878 PART B Given literature to analyse, computationally replicate, and augment with more modern data (for countries and commodities of interest). Joutz, F. L. et al (2000). Retail Food Price Forecasting at ERS: The Process, Methodology, and Performance from 1984 to 1997. Economics Research Service, USDA. Technical Bulletin No. 1885 PART C Given literature to analyse, computationally replicate, and augment with more modern data (for countries and commodities of interest). Knittel, C. R. and Pindyck, R. S. (2016). The Simple Economics of Commodity Price Speculation. American Economic Journal: Macroeconomics, 8(2): 85–110 8. Weather Data Exploratory Data Analysis in R for regions of interest Identify reliable data sources. Data size will be extremely huge. Introspection of data. Concerns are periods relevant to agricultural activity and time length of data. Querying with parameters specified. Generate summary statistics R Packages CADStat, Tidyverse, Tidymodels Summary Stastics, Skew, Kurtosis Variable Distributions Histograms Boxplots Cumulative Distribution Functions Q-Q Plots Scatter Plots Scatterplots are a useful first step in any analysis because they help visualize relationships and identify possible issues (e.g., outliers) that can influence subsequent statistical analyses, or need of regression beyond simple OLS, say, quantile regression or generalized nonlinear models. Note: concerns for the number of variable pairs. Correlation Analysis (Pearson or Spearman?) Conditional Probability Analysis In cases in which many different variables interact, multivariate approaches for exploring data may provide greater insights: Variable Clustering Feature Important and Feature Selection methods Note: apart from regression, time series will also be applicable concerning salient characteristics with decompositions. 9. Environmental Safety Flood Inundation Mapping and Simulation. HEC-RAS and HEC-FIA may be serviceable for considered environment; succeeds credible geology assessment with GIS application (say GRASS GIS) and historical data. Food Safety US FDA (2011) - Guidance for Industry: Evaluating the Safety of Flood-affected Food Crops for Human Consumption 10. Risk Assessment Choudhary, Vikas, et al (2016). Agricultural Sector Risk Assessment: Methodological Guidance for Practitioners (English). Agriculture Global Practice Discussion Paper, no. 10 Washington, D.C., World Bank Group. NOTE: prior to be used for profiling chosen environment. Along with (8) and (9), the following may be integrable with prior, or a stand alone pursuit -- AgMIP – https://agmip.org/data-and-tools-updated/ 11. Cash Crops Motivation for cash crop production. Why a balanced agriculture portfolio over cash crops? Causes of disaster with cash crops. 12. Tools of consideration for crop production planning: Mean-Variance Analysis (MVA) Target MOTAD (TMOTAD) Articles following as guides for development. However, will be working with real agriculture data from farmers/producers in environments of interest for development. Tauer, L. W. (1983). Target MOTAD. American Journal of Agricultural Economics, 65(3), 606–610. Curtis, C. E. et al. (1987). A Target MOTAD Approach to Marketing Strategy Selection for Soybeans. North Central Journal of Agricultural Economics, 9(2), 195–206. Watts, M. J., Held, L. J. and Helmers, G. A. (1984). A Comparison of Target MOTAD to MOTAD. Canadian Journal of Agricultural Economics, 32(1), pages 175 -186 Berbel, J. (1990). A Comparison of Target MOTAD Efficient Sets and the Choice of Target. Canadian Journal of Agricultural Economics, 38(1),149 -158 Comparative Assessment: MVA versus TMOTAD Development based on current field data 13. Life Cycle Assessment (LCA) in Agriculture General guide structure: LCA from ISO 14000 series Note: OpenLCA or Brightway2 or SimaPro (community Edition), ACV-GOST, OpenIO, One Click LCA may be serviceable. General: Haas, G., Wetterich, F. & Geier, U. (2000). Life Cycle Assessment Framework in Agriculture on the Farm Level. Int. J. LCA 5, 345 De Rosa, M. (2018). Land Use and Land-use Changes in Life Cycle Assessment: Green Modelling or Black Boxing? Ecological Economics, volume 144, pages 73 – 81 van der Werf, H.M.G., Knudsen, M.T. & Cederberg, C. (2020). Towards Better Representation of Organic Agriculture in Life Cycle Assessment. Nat Sustain 3, pages 419–425 Pesticide Relevant Margni, M. et al. (2002). Life Cycle Impact Assessment of Pesticides on Human Health and Ecosystems. Agriculture, Ecosystems & Environment. 93(1-3). Pages 379-392. Hellweg, S. and Geisler, G. (2013). Life cycle Impact Assessment of Pesticides, Int J LCA 8, 310–312 Xue, X., Hawkins, T.R., Ingwersen, W.W. et al. (2015). Demonstrating an Approach for Including Pesticide use in Life-Cycle Assessment: Estimating Human and Ecosystem Toxicity of Pesticide use in Midwest Corn Farming. Int J Life Cycle Assess 20, 1117–1126 Peña, N. et al. (2018). Freshwater Ecotoxicity Assessment of Pesticide use in Crop Production: Testing the Influence of Modelling Choices. Journal of Cleaner Production. 209. Pages 1332-1341 Note: honourable mention -- Sponsler, D. B. et al (2019). Pesticides and Pollinators: A Socioecological Synthesis. Science of the Total Environment 662, 1012 – 1027 14. Environmental/Habitat Impact PART A (likely inquisition from 13) Van der Werf HMG, Tzilivakis J, Lewis K, Basset-Mens C. (2007), Environmental Impacts of Farm Scenarios According to Five Assessment Methods. Agriculture, Ecosystems & Environment 118(1-4): 327-338 Van der Werf HMG, Petit J. (2002). Evaluation of the Environmental Impact of Agriculture at the Farm Level: A Comparison and Analysis of 12 Indicator-Based Methods. Agriculture, Ecosystems and Environment 93: 131-145 15. Overview of licenses and registrations for particular services and products in agriculture 16. Agriculture Sustainability FAO Sustainable Goals: https://www.fao.org/sustainable-development-goals/indicators/241/en/ Methodology Data Collection & Reporting E-Learning FAO - A Literature Review on Frameworks and Methods for Measuring and Monitoring Sustainable Agriculture. Further Literature: Bockstaller, C., Guichard, L., Keichinger, O. et al. (2009). Comparison of Methods to Assess the Sustainability of Agricultural Systems. A Review. Agron. Sustain. Dev. 29, 223–235 Hayati, D., Ranjbar, Z., Karami, E. (2010). Measuring Agricultural Sustainability, In: Lichtfouse, E. (eds) Biodiversity, Biofuels, Agroforestry and Conservation Agriculture. Sustainable Agriculture Reviews, vol 5. Springer, Dordrecht. 17. Productivity and Efficiency in Agriculture PART A Food and Agriculture Organization of the United Nations (FAO). (2017), Productivity and Efficiency Measurement in Agriculture: Literature Review and Gaps Analysis USDA Documentation and Methods: https://www.ers.usda.gov/data-products/international-agricultural-productivity/documentation-and-methods/ PART B Data Envelopment Analysis and Stochastic Frontier Analysis R Packages of Interest for DEA rDEA, deaR, Benchmarking R Packages of Interest for SFA frontier, npsf, sfa, ssfa, semsfa, Benchmarking 18. Livestock PART A - Livestock Systems Overview PART B - Sustainable Livestock Systems Moran D. and Blair K. J. (2021). Review: Sustainable Livestock Systems: Anticipating Demand-Side Challenges. Animal 15(1), 100288 19. Financial Models & Valuation Developing a Farm Financial Model: https://farms.extension.wisc.edu/articles/developing-a-farm-financial-model/ Farm Valuation Edwards, William M. (2017). How Much Is That Farm Really Worth—A Comparison of Three Land Purchase Decision Tools. Journal of Applied Farm Economics 1(1), Article 2 Jeanneaux, P. et al (2022). Farm Valuation: A Comparison of Methods for French Farms. Agribusiness 38(4), pp 786-809 Ma, S., & Swinton, S. M. (2012). Hedonic Valuation of Farmland Using Sale Prices versus Appraised Values. Land Economics, 88(1), 1–15. Prerequisites: International Financial Statements Analysis II, Microeconomics II, Econometrics, Economic Time Series, R Analysis (check Actuarial post) FOR ACTIVITIES IN THE “SUMMER” AND WINTER” SESSIONS ALL PARTICIPATING STUDENTS, ASSISTING/ADVISING INSTRUCTORS AND PROFESSORS MUST BE OFFICIALLY RECOGNISED; REQUIRES BOTH CIVILIAN ID AND STUDENT/FACULTY ID FOR CONFIRMATION OF INDIVIDUAL. THERE WILL ALSO BE USE OF IDENTIFICATIONS FOR ACTIVITIES FOR RESPECTIVE SESSION. SECURITY AND NON-PARTICIPATING ADMINISTRATION WILL ONLY IDENTIFY RESPECTIVE ACTIVITY BY IDENTIFICATION CODE. SECURITY AND NON-PARTICIPATING ADMINISTRATION MUST NEVER KNOW WHAT ACTIVITIES IDENTIFICATION CODES IDENTIFY: < Alpha, Alpha, Alpha, Alpha > - < # # # # # > - < session > - < yyyy > It may be the case some activities can be grouped and given a major title together; however, detailed descriptions will be required. Activities repeated can be added to transcripts upon successful completion. Repeated activities later on can be given a designation such as Advance “Name” I, Advance “Name” II. As well, particular repeated activities serve to towards developing true comprehension, competency and professionalism. Secured Archives < Note to self >: further investigation of gEcon for R The Economic Scenario Generator activity is open to Economics constituents. CHECK NEAR BOTTOM OF PAGE Macroeconomic Statistics Accounting Advance treatment of structure, methods from course Open to ECON students Measuring Capital Flows Claessens, S. and Naude, D. (1993). Recent Estimates of Capital Flight, World Bank WPS 1186 NOTE: adjust to regions of interest incorporating modern data. Deposit Insurance (CHECK ACTUARIAL POST) Demography Development and Analysis Open to Political Science, Public Administration and Operations Management/Operational Research constituents. Concerns labs 1 and 2 from the Sustainability Measures course. Much more time will be dedicated to acquiring stronger comprehension and competence. Economic Impact Analysis Note: analytical modelling and computational logistics are essential before active implementation with such tools. Find documentation for such. Economic Impact Analysis (all of them to pursue in constructive order): Input-Output Model: RIMS -II, IMPLAN, Chmura, LM3 World Bank Partial Equilibrium Analysis Multi-market Models Reduced-Form Estimation Impact Analysis: Tools linking microeconomic distribution or behavior to macroeconomic frameworks or models From Rutgers University: R/ECON™ I-O: An Economic Impact Model Simulation Models: Computable General Equilibrium, REMI Areas of interest: Communities, Cities and Provinces with projects/development Proposed legislation or regulatory changes Infrastructure Industries/Sectors How sectors of an economy interact Fiscal Policy (expansionary or contractionary) Social Welfare For highly localised cases, an LM3 example: Mitchell, A., & Lemon, M. (2019). Using the LM3 method to evaluate economic impacts of an on-line retailer of local food in an English market town. Local Economy, 34(1), 51–67. --About RIMS II: RIMS II: An Essential Tool for Regional Developers and Planners. Bureau of Economic Analysis, USDOC --Additional intelligence: Pleeter S. (1980) Methodologies of Economic Impact Analysis: An Overview. In: Pleeter S. (eds) Economic Impact Analysis: Methodology and Applications. Studies in Applied Regional Science, vol 19. Springer, Dordrecht. Input-Output Models for Short Term Assessment of Natural Disasters Okuyama, Y., Hewings, G.J.D., Sonis, M. (2004). Measuring Economic Impacts of Disasters: Interregional Input-Output Analysis Using Sequential Interindustry Model. In: Okuyama, Y., Chang, S.E. (eds) Modeling Spatial and Economic Impacts of Disasters. Advances in Spatial Science. Springer, Berlin, Heidelberg. Computable General Equilibrium Models for Short Term and Long Term Assessment of Natural Disasters (with GAMS) PART A (preliminary development guides) Perali, F., & Scandizzo, P. (2018). The New Generation of Computable General Equilibrium Models: Modelling the Economy. Cham: Springer. Hosoe, N., Gasawa, K., & Hashimoto, H. (2010). Textbook of Computable General Equilibrium Modelling: Programming and Simulations. London: Palgrave Macmillan Limited. Chang, G. H. (2022). Theory and Programming of Computable General Equilibrium (CGE) Models: A Textbook for Beginners. World Scientific PART B (CGE short term Natural Disaster models to develop) Yoshio Kajitani & Hirokazu Tatano (2018) Applicability of a Spatial Computable General Equilibrium Model to Assess the Short-term Economic Impact of Natural Disasters, Economic Systems Research, 30:3, 289-312 PART C (common CGE long term Natural Disaster models to develop) Xie, W. et al (2014). Modelling the Economic Costs of Disasters and Recovery: Analysis Using a Dynamic Computable General Equilibrium Model. Nat. Hazards Earth Syst. Sci., 14, 757–772 Verikios, G. Chapter 5: CGE Models of Infectious Diseases: with a Focus on Influenza. In: Bryant, T. (2016). The WSPC Reference In Natural Resources and Environmental Policy in the Era of Global Change. World Scientific Note: other types of diseases as well Dixon, P. et al (2017). Economic Consequences of Terrorism and Natural Disasters: The Computable General Equilibrium Approach. In A. Abbas, M. Tambe, & D. Von Winterfeldt (Eds.), Improving Homeland Security Decisions (pp. 158-192). Cambridge University Press. Integrated Global System Modelling (IGSM) Framework (Check Meteorology & Oceanography post) A collaboration activity between Economics constituents and constituents of Meteorology and Oceanography. Economics constituents will be responsible for development with the following: Human System Model --> Economic Projection and Policy Analysis (EPPA) Meteorology & Oceanography constituents will be responsible for development with the following: Earth System Model --> The MIT Earth System Model (MESM) Integrated Assessment Models (check Meteorology & Oceanography post) Tax Models & Fiscal Policies 1. Capital Tax models A. Corporate Income tax model B. Small Business tax model C. Household tax models 2. Russek, F. and Kowalewski, K. (2015). How CBO Estimates Automatic Stabilizers. Congressional Budget Office, Working Paper 2015-07 3. Empirical tools in public finance Data sources (bureau of labour statistics, census bureau, treasury, bureau of economic analysis, bureau of economic research, CPS data, compustat) and interests 4. Empirical tools for taxes Will choose topics from the following text to implement Sorensen, P. B. (2022). Measuring the Tax Burden on Capital and Labour. MIT Press Li, H. and Pomerleau, K. Measuring Marginal Effective Tax Rates on Capital Income. Fiscal Fact No. 687, 2020 Li, H. (2017). “Measuring Marginal Tax Rate on Capital Assets. Tax Foundation. Overview of the Tax Foundation’s Tax and Growth Model”. Tax Foundation 5. National Savings, Economic Welfare, and the Structure of Taxation (to be implemented for various concerns) Auerbach, A. J. and Kotlikoff, L. J. (1983). National Savings, Economic Welfare, and the Structure of Taxation." Behavioral Simulation Methods in Tax Policy Analysis, edited by Martin Feldstein. Chicago: University of Chicago Press, (1983), pp. 459-498. Note: NBER version exists 6. Tax-benefit Models The following are often open-source tools to pursue research. HOWEVER, a tool is no good if you don’t have strong comprehension of the modelling and logistics applied towards implementation. Will have analysis of 3-5 tools. Australia: APPSIM, STINMOD+ Canada: DYNACAN European Union: EUROMOD (a favourite since it’s flexible with data choice) Finland: TUJA France: TAXXIP Sweden: SWEtaxben Germany: IZAΨMOD, MIKMOD-ESt Ireland: SWITCH USA: NBER TAXSIM (a favourite since it’s flexible with data choice) R package for TAXSIM: usincometaxes Tax Foundation Stephen J. Entin, Huaqun Li, and Kyle Pomerleau, “Overview of the Tax Foundation’s General Equilibrium Model,” Tax Foundation, April 2018 7. Dynamic Scoring (to be implemented) Coherent concept The following gives a more rounded idea: Mankiw, N. G. and Weinzierl, M. (2004). Dynamic Scoring: A Back-of-the-Envelope Guide. NBER Working Paper 11000 Lynch, M. S. and Gravelle, J. G. (2021). Dynamic Scoring in the Congressional Budget Process. CRS Report R46233 Scope of models and logistics towards implementation for various fiscal interests Implementation 8. Using Aggregate National Accounts data, typically relied upon to estimate future tax revenues for main taxes. For the 3-5 chosen tools will have comparative implementations with numerous fiscal numerous. Fiscal Analysis PART A: Fiscal Simulation Auerbach, A. J. and Kotlikoff, L. J. (1987). Dynamic Fiscal Policy, Cambridge University Press Logistics for computation & active implementation for fluid & applicable analysis. Will apply proposed or ongoing fiscal policies, fiscal notes or various economic scenarios. Note: there are various modifications of the Auerback-Kotlikoff Model. Ludwig, Alexander. (2005). Moment Estimation in Auerbach-Kotlikoff Models: How well do they match the data? Mannheim Research Institute for the Economics of Aging, University of Mannheim, MEA discussion paper series 05093 Try to use such to project respective policy or scenario for a past period; set prior conditions/parameters/values towards the simulations, and observe accuracy. Note: not concerned with periods of economic shocks. PART B: Fiscal Multiplier From the following paper, after analysis identify the tools and techniques required to implement a meaningful evaluation. Will pursue real world evaluations (with incorporation of much modern data) Batini, N. et al (2014). Fiscal Multipliers: Size, Determinants, and Use in Macroeconomic Projections. International Monetary Fund PART C: Evaluating Fiscal Policy Auerbach, A. J., & Kotlikoff, L. J. (1987). Evaluating Fiscal Policy with a Dynamic Simulation Model. The American Economic Review, 77(2), 49–55 Try to use such to project respective policy or scenario for a past period; set prior conditions/parameters/values towards the simulations, and observe accuracy. Note: not concerned with periods of economic shocks. PART D: Fiscal Indicators From the following papers, after analysis identify the tools and techniques required to implement a meaningful evaluation. Will pursue real world evaluations (with incorporation of much modern data) Larch, M. and Martins, J. N. (2007). Fiscal Indicators. European Economy – Economy Papers Number 297 Benz, U. and Fetzer, S. (2006). Indicators for Measuring Fiscal Sustainability: A Comparison of the OECD Method and Generational Accounting, FinanzArchiv / Public Finance Analysis, Vol. 62, No. 3, pp. 367-391 (25 pages) PART E: Fiscal Consolidation with General Equilibrium Treatment (pursuit development for ambiance of interest) Wouters, R. (2014). Fiscal Consolidation in General Equilibrium Models, Bank of International Settlements Hurnik, J. (2004). Fiscal Consolidation in General Equilibrium Framework – the Case of the Czech Republic. Prague Economic Papers. vol. 2004(2), pages 142-158. PART F: Fiscal Health Monitoring in the Public Sector Will be applied to sectors such as schools for whatever regional scale. Can also be done for utilities and other public goods or services. Much financial statements/data required. Assisting guides for pursuits for public goods, public services (provincial, municipal and borough levels): Suarez V., Lesneski C. and Denison, D. (2011). Making the Case for using Financial Indicators in Local Public Health Agencies. Am J Public Health 101(3), pages 419-25. McDonald, B. D. (2018). Local Governance and the Issue of Fiscal Health, State and Local Government Review, 50(1), 46–55. PART G: Management in the Public Sector Tasks from the following with public data: Wang, H. (2014). Financial Management in the Public Sector: Tools, Applications, and Cases. Routledge Stochastic Models for long term projections O’Harra, J., Sabelhaus, J. and Michael Simpson, M. (2004). Overview of the Congressional Budget Office Long-Term (CBOLT) Policy Simulation Model. Technical Paper Series Congressional Budget Office Washington, DC, 2004-1 Schwabish, J. A. (2013). Modeling Individual Earnings in CBO’s Long-Term Microsimulation Model. Working Paper 2013-04 Cheng, A. W. (2004). A Stochastic Model of the Long Range Financial Status of the OASDI Programme. Actuarial Study No.117. SSA Pub. No. 11-11555 Try to use such to project respective policy or scenario for a past period; set prior conditions/parameters/values towards the simulations, and observe accuracy. Note: not concerned with periods of economic shocks. Note: open to actuarial students Budget Stress Testing For a province or region of autonomy applying stress testing for various circumstances such as natural disasters, shocks, recessions, etc. Budget Stress Testing (model example): State Budget Stress Testing User Guide: A Collaborative Endeavor of the Kem C. Gardner Policy Institute and the Utah Office of the Legislative Fiscal Analyst: https://gardner.utah.edu/wp-content/uploads/PEW-State-Budget-Stress-Test-User-Guide.pdf Cost Estimates for Bills Goal is to develop estimation of advanced bills or passed bills. Will like to see how our estimates compare to data of the congressional budget office; for cases of high disparity to speculate on possible causes and try to amend to best of ability. The following literature to be development guides: Congressional Budget Office 2018, How CBO Prepares Cost Estimates, Publication 53519 GAO 2020. Cost Estimating and Assessment Guide: Best Practices for Developing and Managing Program Costs. GAO-20-195G Recession prediction development (back testing and future) Literature to assist (for ambiances of interest): Watson, M. W. (1991). Using Econometric Models to Predict Recessions, Federal Reserve Bank of Chicago, Economic Perspectives Stock, J. H. and Watson, M. W. (1993). A Procedure for Predicting Recessions with Leading Indicators: Econometric Issues & Recent Experience. In: Business Cycles, Indicators & Forecasting. University of Chicago Press, pp. 95 – 156 Fornari, F. and Lemke, W. (2010). Prediction Recession Probabilities with Financial Variables over Multiple Horizons. ECB Working Paper Series No. 1255 Liu, W. and Moench, E. (2014). What Predicts U.S. Recessions? Federal Reserve Bank of New York Staff Reports No. 691 Note: will be comparing with the following A. Global PMI B. OECD Composite Leading Indicator < https://www.oecd.org/sdd/leading-indicators/41629509.pdf > C. The TED spread Concept. Instructor must exhibit to students how to competently read and analyse market data observed: ---Credit risk and default risk observation ---Trade construction methodology ---Perturbation values, observation of hedge ratios (with any formula) ---Liquidity-related factors Note: for such above there are likely analogies to such for a respective ambiance of interest to create a “foreign TED spread”. Else, construct them. Also, with the replacement of LIBOR apply appropriate substitution. Measuring the Business Cycle Chronology & identifying Business Cycle Turning Points Articles to be analysed then replication, followed by countries of interest Gehringer, A. and Mayer, T. (2021). Measuring the Business Cycle Chronology with a Novel Business Cycle Indicator for Germany. J Bus Cycle Res 17, 71–89 (2021). Chauvet, M. and Piger, J. M. (2003). Identifying Business Cycle Turning Points in Real Time. Review, Federal Reserve Bank of St. Louis OECD System of Composite Leading Indicators: https://www.oecd.org/sdd/leading-indicators/41629509.pdf The purpose of the above OECD guidance is to develop the indicator based on such description. Models can possibly vary among students. Goal is to compare development with the associated data of OECD database to confirm its consistency. As well, how does such OECD indicators compare to development from the former two articles future wise?

Agricultural Macro Welfare PART A (Input-Output models for Agriculture) Note: goal is to have such literature be relatable to data of interest. Heady, E. O., & Schnittker, J. A. (1957). Application of Input-Output Models to Agriculture. Journal of Farm Economics, 39(3), 745–758. Harris, T. R., Deller, S., Goetz, S. (2014). Linkages of the Agricultural Sector Models and Precautions., In Neal van Alfen (Ed.), Encyclopedia of Agriculture and Food Systems, Vol. 4. (pp. 148-155). Elsevier Inc. PART B (Measurement of Agricultural Protection) Strak, J. (1982). Measurement of Agricultural Protection. Palgrave Macmillan London �� Cahill, Carmel & Legg, Wilfrid. (1990). Estimation of Agricultural Assistance Using Producer and Consumer Subsidy Equivalents: Theory and Practice, OECD Economic Studies 13. William A. Masters (1993) Measuring Protection in Agriculture: The Producer Subsidy Equivalent Revisited, Oxford Agrarian Studies, 21:2, 133-142 Effland, A. (2011). Classifying and Measuring Agricultural Support: Identifying Differences Between the WTO and OECD Systems. Economic Information Bulletin No. (EIB-74) 24 pp PART C (Land Usage Analysis) LANDIS-II: https://www.landis-ii.org Computational Studies of Mergers & Acquisitions ADVANCE SKILLS DEVELOPMENT Successful completion of course is a prerequisite. Health Decision Sciences with R (check Actuarial post) Open to Economics AND Public Administration students CGE for Environmental Impact Interest is GAMS development A. OECD-Environment Modelling Tools ENV-Linkages Model (to develop) Château, J., R. Dellink and E. Lanzi (2014) Château, J., C. Rebolledo and R. Dellink (2011) Dellink, R., et al. (2021) Other pandemics with future effects too B. The MIT Emissions Prediction and Policy Analysis (EPPA) Model (to develop) Paltsev, S. et al (2005): The MIT Emissions Prediction and Policy Analysis (EPPA) Model: Version 4. Joint Program Report Series Report 125 C. Forecasting Environmental Decision Making (to develop) J. Scott Armstrong (1999). Forecasting for Environmental Decision Making. In: V.H. Dale and M.E. English, eds., Tools to Aid Environmental Decision Making, Springer-Verlag, pp. 192-225. ID. US EPA SAGE CGE Model Marten, A., Schreiber, A., and Wolverton, A. 2021. SAGE Model Documentation (2.0.1). U.S. Environmental Protection Agency Implementing US EPA SAGE CGE Model (at least with GAMS) # POLITICAL SCIENCE Curriculum: The Political Science environment concerns cerebral functional growth, ingenuity, adaptation and advancement from acquired knowledge and skills. Political Science is not Economics. Political science is the study of government and diplomacy. A political scientist is mostly observant of political climates and activity. The curriculum is constituted by crucial courses towards knowledge and building skills in the following: 1. Government and Legal Foundations 2. History and Observation 3. Compare and Contrast 4. Critical Thinking 5. Recognised legal contests/suits and rulings where positions are recognised and analysed with outcome 6. Bills in the legislature (major perspectives and outcomes) 7. Economics Integrity 8. Political Commerce 9. Data Analysis Curriculum has no requirement of literature writing, rather, only political writing courses. ----Mandatory courses Enterprise Data Analysis I & II (check FIN); International Financial Statement Analysis I & II (check FIN); Calculus for Business & Econ I & II, Introduction to Computational Statistics for Political Studies ----Core courses 1.Political & Policy Writing << Elementary Writing for Political Science; Advance Writing for Political Science >> 2.Government << Constitutional Law; Legislative Process; Executive Process; Judicial Process; Comparative Politics; Comparative Electoral Systems >> 3.Economics Integrity (check ECON) << Introduction to Macroeconomics, Intermediate Macroeconomics >> 4.Political Commerce << Fiscal Administration (check PA); Public Policy; Public Policy Formulation & Implementation (check PA); Public Policy Analysis; Elements in Political Theory, Political Economy >> 5.International Relations << International Governance >> 6.Political Science Research << Quantitative Analysis in Political Studies I & II; Survey Research; Methods of Political Analysis >> Note: It’s recommended that student have advance placement and/or plan to take general education appeasement courses in the “winter” or “summer” sessions. Course descriptions: Introduction to Computational Statistics for Political Studies: In this course, we will focus on learning various practical statistical techniques and their applications that will assist you in making business decisions. The primary objective of this course is to enable students to perform and understand statistical analysis of data, with the view of being able to critically evaluate statistical reports or findings. Objectives: 1. Explain the concepts of descriptive statistics and use sample statistics to make inferences about population characteristics. 2. Recognise different models of statistical processes such as hypothesis testing through Chi-square, linear and multiple regression, etc. 3. Explain statistical processes and choose which process to use for particular data analysis applications 4. Learn to interpret statistical results as a basis for decision-making 5. Learn to use applicable statistics software 6. Collaborate effectively to use statistical analysis to address business challenges 7. Communicate your interpretation of the results of statistical analysis logically and persuasively in speaking and writing. 8. Course is only for political studies. SO MIND YOUR DAMN BUSINESS. Statistics without solid experience in a computational environment doesn’t mean much. Course will make extensive usage of R involving RStudio with real world data to accommodate theory and analytical modelling. Students will be required to learn how to import and manipulate data extensively. Students will be assigned statistical activities during course towards development of skills and practical maturity. Will make use of real-world data. Course literature will cater for the R environment Course Grade Constitution --> Status Quo Homework 10% R Environment Assignments + R projects in course 30% 3 Exams 60% Will reflect homework (3 zombie questions only) 0.15 Ability to show comprehension and mechanics 0.35 R skills with much more emphasis on the latter 0.5 Limited open notes Course Outline --> -Introduction -Data Acquisition via R Acquiring data from addresses, databases, file types. Generate and manipulate data frames: basic wrangling. -Descriptive statistics will real data -Generating Histograms with real data -Box plot with real data -Probability: Basic Concepts -Random Variables (theory, discrete r.v. and continuous r.v.) Standard topics and random variable generation/simulation Apart from general exercises will also make use of real data -Binomial, exponential and Poisson distributions -Normal Distribution -Sampling Distributions (based on simulation and real raw data) -MLE & MoM -Confidence Intervals (not confined to normal) -Chi-Square distribution The bottom line is to establish the flow of the uses competently with applications involving real raw data. Comprehending categorical data sets and ordinal data sets Organisation of data and sensitivity of categories concerning traits of interest. Test for independence McHugh ML. (2013). The chi-square Test of Independence. Biochem Med (Zagreb). 23(2): 143-9. Using Fisher’s Exact Test as an alternative Test of homogeneity Test of variance Applications of the Chi-Square distribution with confidence intervals -T Distribution Not concerned with zombie problems. If no normality, then T-test is not applicable. Kim T.K. & Park J. H. (2019). More About the Basic Assumptions of T-test: Normality and Sample Size. Korean J Anesthesiol. 72(4): 331-335. Sample size determination Population parameter estimation Confidence intervals -Goodness of Fit Primitives Summary Statistics Skew and Kurtosis Box Plots Density Plots P-P and Q-Q Statistical Tests Definition, Null hypothesis One-sided & two-sided tests of hypothesis Types of test statistics (T and Chi-Square) Comprehending critical values for ideal distributions Significance levels Comparing critical values for real raw data sets Does your data distribution exonerate ideal models? Contemporary Tests: Chi-Square Test Kolmogorov-Smirnov Test Anderson-Darling test Shapiro-Wilk Test -Hypothesis Testing (exploratory Module with R) We are and not concerned with zombie problems. What’s important is how it’s meaningful to you with your future endeavours in PS and PA. Majaski, C. (2021). Hypothesis Testing. Investopedia NOTE: Goodness of Fit module will be crucial -Covariance & Correlation (real massive data immersion). Correlation matrices for 3 or more variables. Heatmaps development. -Mukaka M. M. (2012). Statistics Corner: A Guide to Appropriate Use of Correlation Coefficient in Medical Research. Malawi Medical Journal: The Journal of Medical Association of Malawi, 24(3), 69–71. -Simple Linear Regression -Multiple Linear Regression (AT LEAST 5 sessions) Data structuring with R Multilinear regression structure Variables selection OLS Summary Statistics for Regression -Fraud Detection Methods (to be implemented) Prerequisites: Calculus for Business & Economics I & II Elementary Writing for Political Science Course assumes students are well nurtured in academic essay writing, say, experience in various academic writing styles before matriculating into college. Course is designed to assist in learning research, analytical, writing concepts and skills in the political science field. Course encompasses both objective and persuasive writing. This course will familiarize the student with analytical, research and writing skills in all four areas of the political science major: Regional Politics, Political Theory, International Politics, and Comparative Politics. The course methodology assists the student in learning by presenting all of these skills and concepts in a system that presents basic skills and concepts in short assignments, and then builds on these basic skills and concepts to support their goal towards mastery in longer and more complex assignments. Course concerns the student gaining ability to demonstrate: 1. Clear and accurate understanding of political science writing in all four areas of the major 2. Ability to produce effective written and oral communication in all four areas of the major; including competent citation, clear and careful organization around a competent thesis, professional format, grammatical presentation, analytical accuracy and intellectual depth 3. Mastery of basic and more complex forms of argument in political science, including knowledge of types of political science writing, competent presentation of, and support for, both objective and persuasive analysis in all four areas of the major 4. Effective engagement in the creative processes of intellectual political science writing, research, and analysis, including techniques for brainstorming, collaboration, revising, flexibility in thinking and research and reflecting on feedback, and 5. Competent research skills in all four areas of the major. Specialized tasks (order to follow course outline) --> Traditional, and computer-assisted sources, with basic bibliography citation of 10 sources (3 tasks) Class Exercises detailed throughout Group Oral Presentations Developments & Assignments Objective, Persuasive, Position Research Development Issue/topic, Supporting literature for topic(s) Research phase, thesis, tentative outline, and list of sources Note: “--” segmentation corresponds to a week Course Outline --> --Conventionally-used political science sources and how to cite them 1. Introduction to course and the four substantive areas of the major 2. (“CMS”) and (“APA”) look up and read relevant references. Why the use of citation in political science writing 3. Transitioning to the (CMS) style for documentation, and basic differences among bibliography, footnote, and endnote form 4. Transitioning to (APA) style for documentation 5. Library usage, traditional and computer-assisted sources in political science 6. Proof-reading your citation form, and basics to help you master both accuracy and reuse of citation form. --Basic, objective political analysis, research and writing 1. What Is a Research Paper? Finding the Evidence. 2. What are “objective” or neutral” research, neutral analysis and neutral writing in political science? 3. Taking into account the nature and identity of the “audience” 4. Objective writing style, grammar, vocabulary, format, organisation 5. What is Political Theory? 6. What is Politics? Local, global 7. Use of data to support objective assertions and analysis 8. Dealing with ambiguities or conflicts in or among sources 9. Different types of political science writing that are “objective” in all four areas of the major 10. Critical reading in the political science field. 11. Key concepts in researching political science: i) professional vocabulary; ii) starting efficiently when you know an area; iii) starting efficiently when you don’t know an area; iv) what makes a source “relevant”; v) what makes a relevant source “better” or “best,” and vi) the number of sources you need to support an assertion. 12. Formation of objective, analytical theses in the four categories of the politics major. --Continuation of prior week 1. Where Do I Begin? 2. Formation of a complex, objective, analytical thesis: class exercise 3. Basics of the objective, expository introduction and conclusion 4. outlining: adding sub-issues to the main issue outline: class exercise 5. Adequacy of objective analysis: clarity, relevance of data and concepts, substantive rigor, level of appropriate detail, and responsiveness to question asked. 6. Cite checking as distinguished from citation form 7. Writing organization: topic sentences and paragraph structure 8. Proofreading your work --Expanding and applying objective analysis and writing to address more complex problems in political science 1. What is Comparative Politics? 2. Differences and similarities in objective and persuasive essay writing 3. Organization of essay, quick outlining and “labeling” as organisational techniques, substantive accuracy,” effective timing, appropriate level of detail, your instructor as your audience. Class exercise, “labeling” 4. What is constructive feedback and what is its value for you and others? In-class exercise: learning from reviewing, assessing, and giving Feedback on the work of others (with instructor “rubric” and using article summaries from last week). --Expanding objective research, analysis and writing in political science to more complex problems 1. Improving your use of data to support assertions: class exercise 2. Dealing with ambiguities in sources in objective, analytical writing 3. Flexibility in approach: to footnotes: how long & how detailed should they be 4. Use of external sources and plagiarism: academic honestly, proper attribution of data, quotations, ideas, and paraphrases. Note: out of specialized tasks there are assignments declared that’s appropriate for this module. Determine appropriate time. --Transitioning from objective research, analysis and writing in political science to “position” research, analysis and writing 1. Finding the Evidence: Review relevant parts 2. More complex analytical objective research, analysis and writing 3. Objective research methodologies and techniques vs. persuasive research methodologies and techniques 4. Determining when you have found the “answer” / how many sources does it take? 5. Sufficiency of research: knowing when to stop: objective vs. argumentative research and analysis 6. Review: reliability of data 7. Cite checking and citation form revisited 8. Purpose and form for footnotes within text, revisited 9. Flexibility of approach: relationships among research data, issues, thesis, and outline. --Transitioning to more complex problems in political science that require an argumentative position 1. Developing “position” analysis: format, credibility and ethics 2. The thesis in argumentative writing. 3. Introduction to making an oral presentation: objective vs. argumentative 4. Oral presentations: style, tone, format, professionalism 5. Oral presentations: fielding easy and hard questions 6. Oral presentations: clarity, accuracy, use of supporting data, level of detail 7. The elements of good timing in oral presentations Note: out of specialized tasks there are assignments declared that’s appropriate for this module. Determine appropriate time. --Expanding research, analysis and/or writing into the oral presentation 1. ORAL PRESENTATIONS 2. STUDENTS NOT PRESENTING PLEASE BE PREPARED TO ASK QUESTIONS! Note: out of specialized tasks there are assignments declared that’s appropriate for this module. Determine appropriate time. --Argumentative or advocacy writing in the political science, continued 1. Writing your persuasive paper: “Critical Papers” 2. Making the transition from objective to persuasive/advocacy writing and analysis, con’t. 3. Specific types of political science writing that involve advocacy or persuasive writing 4. Taking into account sources that weaken or contradict your position --The Complex Position or Persuasive Paper 1. Understanding the task, reviewed 2. Research strategies, reviewed 3. Objective analysis as the basis of “position” analysis, reviewed 4. Citation form, end notes, footnotes, bibliography, reviewed 5. Keeping track of sources, reviewed. 6. Types and sufficiency of data, reviewed 7. Effective organization of persuasive analysis, con’t. Note: Begin research on final paper --More complex forms of persuasive or advocacy writing in political science 1. Researching persuasive problems, con’t.: intellectual honesty and examining both positive and negative sources or data. 2. Revisiting how to find and take into account data and sources that support the position argued. 3. Revisiting how to find and take into account data and sources that weaken the position argued 4. Revisiting how to take into account ambiguities in data and sources that contradict the position argued 5. Developing more specific methods for taking into account “negative” sources or data: distinguishing, discounting, acknowledging ambiguity or conflict, or demonstrating weak relevance or, demonstrating irrelevance Note: Continue research on final paper. Tentative outline, tentative thesis and preliminary list of sources for final paper. --Research Time Week (no classes) 1. Turn in outline, thesis, and source list at end of week 2. The complex political science problem: next steps 3. When should you try to use humor? --The final phase of working on the complex argumentative or persuasive problem in political science 1. Text: Review all relevant parts needed 2. Return, review, and discuss final paper outline, thesis, etc. 3. Research strategies revisited 4. Honing the issues, thesis, and analysis for the complex argumentative paper 5. Review of flexibility in approach, position taken, thesis statement, feedback received, and new research data or information found 6. Putting it altogether in the complex, argumentative paper Out of specialized tasks there are assignments declared that’s appropriate for this module. Determine appropriate time. Prerequisite: Introduction to Computational Statistics for Political Studies Advance Writing for Political Science An 18-week writing studio course, with 2 sessions per week. “MEMO”: Political science is generally divided into four main fields: “Environment” politics, comparative politics, international relations, and political theory/philosophy. Increasingly, some political scientists focus exclusively on research methodologies. Regardless of the specific field of interest, all writing in political science strives to be objective in its approach, emphasizing clear and logically presented arguments, even-handed consideration of likely counterarguments, and thorough evaluation of relevant evidence for and against your primary claim. Course Assessment --> Components A, B, C & D COMPONENT A --> Argument essays (2-3) Responses to articles, texts, or events (2) Op-ed pieces (1) For argument essays and responses development from prerequisite will be used extensively for such three components. Namely, such will be used to build your development pathway with logistics; will be collected. Followed by drafts to be submitted. NOTE: the “memo” will be applied extensively as an underlying rubric. COMPONENT B --> The scientific method is a way of discovering general truths about the world we live in. Its primary assumptions are that there is such a thing as objective reality and that it is knowable through a person’s faculty of reason. Its primary mechanism is theory testing. This means that a possible explanation of how the world works is tested against the evidence of the real world. In the social sciences, it is usually either impractical or unethical to use experiments, so there’s heavy reliance on historical data. We test our explanations against the past in the hopes of understanding the present and better predicting the future. What this means in practical terms is that we develop a theory (or thesis) before we have seen the evidence, so that we can test it honestly. COMPONENT C --> Research Design NOTE: the “memo” will be applied extensively as an underlying rubric. You go through the following steps but stop short of collecting and analysing evidence/data: 1.Choosing a Topic 2.Background Reading 3.Choosing a Puzzle Some question about the topic that you think is particularly interesting. Keep in mind that political scientists are interested in relations of cause and effect. This means that, while they consider purely descriptive work to be interesting and useful, they think of it as data, and not political science. Various questions conjured will not be appropriate puzzles. 4.Formulating a Thesis/Theory Your thesis/theory is essentially your general answer to the puzzle. Having done the background reading, you probably have a guess as to […]. In your theory, you state your guess clearly and concisely in terms of variables. The independent variable (I.V.) is the factor you are arguing causes something to happen. The dependent variable (D.V.) is what is caused by (depends on) something. 5.Defining Key Terms (operationalizing) The scientific method requires your work to be very clear so that anyone else could repeat exactly what you did to test your honesty and the reliability of your results. This includes being clear about what complex words mean. Definition simply explains what something is Operationalization explains what something is in terms that can be measured or observed. 6.Formulating Hypotheses if-then statements which take all the possible values of the independent variable as the “if”-side and link the possible values of the dependent variable as the “then”-side. 7.Control Variables – ceteris paribus 8.Collecting Data 9.Analysing Data 10.Concluding, Reasoning, Interests and Possible Expansion COMPONENT D --> Research development pursuit NOTE: the “memo” will be applied extensively as an underlying rubric. Prerequisite: Elementary Writing for Political Science Constitutional Law The purpose of this class is to acquaint you with the legal principles under-girding the federal system of government. You will study the nature and powers of the Parliament, Executive and the Courts. The course will rely highly on the legal case study method as a learning strategy for understanding key principles of Constitutional law. One of the most vital aspects of politics: interpreting and applying the nation's fundamental rules. Case law provides insight into how actual Constitutional controversies are resolved and can have a binding effect on the resolution of subsequent cases, so the case study method helps judges, lawyers, and students understand the law and predict the outcome of future cases. Students are expected to read and think about the assigned material before each class. Likewise, you are expected to contribute to the classroom discussions on both a voluntary and involuntary basis. I will call on you. Your participation may impact your grade at the margins. Exams concern historical knowledge, constitutional knowledge & amendments. Course outline range --> COMPARATIVE (3-4 weeks) Note: at designated periods will introduce the following methods of comparative politics at a moderate level in labs concerning purpose, preparation, logistics and implementation: The Comparative Method Case Studies Qualitative Data Cross-National Quantitative Research NOTE: there will be further topics for labs not mentioned below to accommodate such above methods. Topics: 1.Monarchial forms of government. Republican forms of government. One-party states and military governments. What is your nation’s classification? 2.Will identify dominant theories on the creation of a constitution, with comparative view among different nations through time to support such. 3.Democracy Models 4.Disparities between prime minister and president among democracy models concerning democratic office tenure, powers, limits, organisation with offices and departments 5.Does a parliamentary political system require any impeachment structure? If yes, identify. Are there any sovereign “no” examples. Comparison/Contrast to the provincial levels. 6.Role or influence of constitutions with the existing strength of federalism and legal reservation with provinces/states. 7. Emergence of totalitarian governments and role of the gov’t branches Non-democratic origins Transformation from democracy models 8.Is there a benchmark constitution? AMBIANCE FOCUS (11-12 weeks) Within course the following elements will resonate for the AMBIANCE FOCUS TOPICS IN SECOND PART OF COURSE (not necessarily in given order, and such elements may apply on numerous occasions): -Socio-political conflicts and the constitution -Historical Judicial Reviews -Supreme Court Cases -Historical Acts and Amendments -Judicial ruling on executive policies -Judicial ruling on legislative actions Students may also encounter hypothetical cases from instructor, where students will provide constitutional analysis to the best of their abilities based on acquired knowledge from individual personal readings and course instruction. Some hypothetical cases will be group assignments while others will be done individually. Topics: 1.Founding of the constitution and its evolution (focus on ambiance). Will identify in detail delegates, emissaries, officials, ministries, agencies playing pivotal roles in development of the constitution. Agendas/interests of such entities. 2.Nature of the Constitution 3.Separation of Powers 4.Organisation of the Branches based on constitutional powers of the branches 5.Constitutional supremacy, power of interpretation and early controversies. 6.The action of judicial review and interpretation is a “fear” gauge on whether an established government is truly committed to abide by its structure. True or false. 7.Executive prerogatives and associated checks by other branches of government: foreign policy, emergency, military action and war. Creating executive departments. Executive leader powers with appointments and removals. Removals and policy on the enforcement of law. Executive orders. Suspension of parliament and government shutdowns. 8.Congressional influence on executive leadership of government. Review of a parliamentary/semi-presidential political system versus presidential system. Do executive appointments require parliamentary approval or is such only characteristic of presidential forms of government? For prior question, have comparison/contrast to the provincial and city levels. 9.Congressional Oversight 10.Judicial Branch Federal Review of the constitutional relevance of the judicial body Organisation and the selection process Process for high court hearings and trials Provincial (counterparts to priors) Legal routine or process between provincial and federal 11. Congressional powers and limitations over judicial ruling. 12.Taxing, Spending and Administration of Foreign Aid 13.Legislative influence on the constitution and the judicial body. 14.Removal of judicial constituents (federal and provincial, respectively) International Governance Course concerns the review of some of the major institutions and tools for cooperation among transnational actors, towards negotiating responses to problems or interests that affect more than one state or region. Observation of the limited or demarcated authority to enforce compliance. The modern query of world governance exists in the context of globalization and globalizing regimes of power: politically and economically. Resonating elements in course are history, stability, security, economic welfare and globalization. Course has a government classification option. Course also has social/society classification option. Course also appeases the “History” classification option since it concerns civilisation and “advancement” of the human species from 18th through 21st century. Standard Applied Course Engagement --> Activities and tasks identified in course topics. Additionally, there can be numerous analytical/critical thinking topics/questions and historical events/periods that are tangibly and fluidly relevant to each module. Instructor to provide additional such not mentioned in course outline based on various texts, articles, other forms of literature and acceptable sources not listed. Analytical topics, critical thinking questions and historical events/periods will be unique to questions or concerns expressed in lecture outline. Some of the “Yakety-yak” literature (but not limited to): Coicaud J.-M. & Heiskanen V. (2001). The Legitimacy of International Organisations. United Nations University Press Tallberg, J. and Zürn, M. (2019). The Legitimacy and Legitimation of International Organizations: Introduction and Framework. Rev Int Organ 14(4), pages 581–606 Dellmuth, L., Scholte, J., & Tallberg, J. (2019). Institutional Sources of Legitimacy for International Organisations: Beyond Procedure Versus Performance. Review of International Studies, 45(4), 627-646 Hopefully, such literature will not sabotage your course obligations. NEVERTHELESS, course is primarily geared towards students having meaningful comprehension of IGOs structure and sense of good utility with IGOs, rather than being con artists; all in course outline MUST be treated. UN Literature --> UN Official Documentation System: https://documents.un.org/prod/ods.nsf/home.xsp Websites Navigation (group activity) --> There are multiple tasks throughout the term where student groups must independently navigate websites of agencies, organisations, offices & affiliates to acquire general information, charters, policies, databases, manuals, guides, guidelines, working papers, technical papers, published journals, evaluation tools/software, etc., etc., etc.; questions and research will be based on such elements. Citations and references are mandatory. NOTE: skills from ALL prerequisites will be put to good use. NOTE: will not be the stereotypical charted pursuits. There will be places and sites areas pursued that are typically not ventured. NOTE: will require good effort and independent skills for exploratory pursuits or “treasure hunts”. Entities of interest (EOI): UN major bodies UN family of organisations UN Specialized Agencies (some may not be listed in priors) NATO, OSCE, Interpol, Europol BIS, OECD, WTO (World Trade Organisation), UNCITRAL, UNCTAD Supranational entities and its agencies/ministries/offices/(EU, EC, CC) Sovereign states executive branch (offices and departments) Tasks based on EOI: Frameworks, guides, manuals and logistics. Analysis of diplomacy, polices or treaties or conferences Policies, operations, finance and outcomes for events, periods, etc. Sovereign states executive branch (offices and departments) concerning policies and actions in foreign affairs compared to IGO policies and actions. Discovery and use of tools, software and kits. Data Analysis Exploratory data analysis Econometric modelling with forecasts Things not thought of yet Labs --> 1.UN Agencies, Bodies, Organisations, Funds & Programmes operations: -Students must be competent in acquiring external information (articles, documentation and data) from the authentic and credible sources. Technological skills with sites, addresses, databases APIs. Introspection and queries. -Annual operations reports. Analysis of operations (different periods). -For assigned IGO agencies acquire annual (or quarterly) audited financial statements for the most recent period. Present the results of your analysis in a brief class presentation. You will prepare an accounting written report of approximately 2-3 pages summarizing the accounting classification and the accepted accounting principles treatment for your chosen entity Financial Statements Integrity and Financial Analysis (different periods). Fraud Analysis (different periods). Can fiscal health analysis be done? If so, develop. 2.Measuring Legitimacy: PART A Gilley, B. (2006). The Meaning and Measure of State Legitimacy: Results for 72 Countries. European Journal of Political Research 45: 499 – 525 Analysis Replicate Incorporate more modern data For past 20 - 40 years what is the trend in such measure for chosen countries? Then for countries recognised with high legitimacy based on findings, identify their levels of participation and/or influence in international governance (mainly economics, international security, human rights) with staffing and executive positions. Does state legitimacy correlate well with influence in international governance? PART B WBG Worldwide Governance Indicators: < https://info.worldbank.org/governance/wgi/ > Intension Indicators Methodology Kaufmann, D., Kraay, A. and Mastruzzi, M. (2010). The Worldwide Governance Indicators: Methodology and Analytical Issues, World Bank Policy Research Working Paper No. 5430 Quality and credibility of data (practicality and criticisms) Preliminary personal criticism of indicators. What don’t you understand? Do poorer countries who likely lack corporate commerce, industrialization and self-reliance fall victim to the interest of foreign entities from developed countries? Academic Inquisitions Kaufmann, D., Kraay, A. and Mastruzzi, M. (2007). Worldwide Governance Indicators Project: Answering the Critics. World Bank Policy Research Working Paper No. 4149 Thomas, M. (2009). What Do the Worldwide Governance Indicators Measure? European Journal of Development Research. 22 (1): 31–54 Langbein, L. and Knack, S. (2010). The Worldwide Governance Indicators: Six, One, or None?". Journal of Development Studies. 46(2): 350–370 Other questions Further Resource Malito, D. V., Umbach, G. and Bhuta, N. (2018). The Palgrave Handbook of Indicators in Global Governance. Palgrave Macmillan PART C Analyse and replicate, followed by inclusion of more modern data: Binder, M. and Heupel, M. (2021). The Politics of Legitimation in International Organisations, Journal of Global Security Studies, 6(3), ogaa033 3.The Global Conflict Risk Index (to apply): https://drmkc.jrc.ec.europa.eu/initiatives-services/global-conflict-risk-index#documents/1059/list Note: methodology and other documentation must be analysed before use. 4.Active operations with the following: INFORM RISK INFORM SEVERITY INFORM WARNING Note: for each the methodology and other documentation must be analysed before use. 5.Comparative analysis between (3) and (4): Product SWOT analysis. Compliment to each other? Do any indicators from (2) serve as alternatives? 6.Analysing video of chosen UN Security Council meeting: Reviewing the process for initiating meetings, and acquire summoning literature published by UN Security Council to analyse. Procedures. Priors will be aligned to whatever particular meeting event. Policy, conflicts and proposals. Arguments for policy or proposals by respective sovereignty in council. Outcomes/resolutions: analyse resulting UNSC position from published literature compare to video. Analysis of retaliation or response from subjugated ambiances/nations. Note: instructor can provide critical thinking interests throughout. 7.Policy Evaluation for IGOs' policies, programmes, projects: Programme Theory Impact Evaluation (specified methods) Gertler, P. et al (2016). Impact Evaluation in Practice: Second Practice, World Bank Publications Cost-Benefit Analysis (monetised and non-monetised) Estimation guides exist Quizzes --> Elements in quizzes can apply various components. Knowledge and activities from modules and lectures (including financial analysis), and analytical responses, etc. In general, you may get 3 days advance notice for quizzes. There will be 4-5 quizzes, where the lowest will be dropped. Lack of participation or failure to keep a respectful environment can warrant incorporating pop quizzes. 3 Exams --> Part of exams will involve historical knowledge and common knowledge; will be closed book. Students must disable all electronic devices of communication. Such parts of exams will be timed. Such parts of exams will be carried out before any other parts. Part of exams will involve case scenarios and/or current events. Will concern critical thinking and analytical processing. Students must disable all electronic devices of communication. Part of exams will involve accessing credible sources, annual reports and financial data/accounting data towards accounting analysis to provide assessment; proper citation will compliment such. Students will make use of their communication devices. Formality --> NOTE: wars from imperialism, failure of the League of Nations, World War II, Cold War spills, NATO (and its many activities), nuclear bomb drills, WMDs, Middle East Crises (off and on), epidemics/pandemics, human trafficking, drug trafficking, massacres, genocide, various migrant crises, terrorism, incursions and annexations can’t be identified with one race. NOTE: despite course considering only the 18th to 21st century, on planet Earth, various history, cultures, commerce and religions existed before the 1300s and 1400s. Don’t get hung up with bamboozles, or opportunistic, parasitic, megalomaniac cultural penetration in the latter years following. Attendance and Conduct Policy --> Conduct that’s detrimental to the quality and integrity of the course can lead to students forfeiting 69% of final grade. Conduct that’s detrimental to the safety or social well-being of other students and instructor(s) in course can lead to students forfeiting 69% of final grade, along with legal consequences and exercise of campus security and safety policies. I will not tell you explicitly how lack of attendance and punctuality will affect your grade; certain elements of assessment will be targeted. ASSESSMENT --> Standard Applied Course Engagement Websites Navigation Labs Quizzes (course topics) Exams (course topics) Attendance and Conduct Policy TOPICS IN COURSE PROGRESSION --> ---MODULE 1 Before the League of Nations (18th-19th century) Key themes with specified geographic focus: colonialism, imperialism through militaristic enforcement, international human rights. **Significant international treaties (eastern and western hemisphere). **Enterprises and companies. Was mercantilism the main driver of imperialism, and colonialism? What forms of equity or commissions existed towards the respective sovereign state concerning international endeavours and interests? How did competing sovereignties or even competing firms become knowledgeable of each other’s foreign interests, ventures or exploits? **What were the standing notions of international humanitarian aid and peacekeeping in such two centuries among sovereign states? Was there a typical procedure? What was the best policy? For organisations such as churches, the Salvation Army, International Red Cross etc. being international organisations of service, how were they perceived and treated by sovereign governance in such era(s)? ---MODULE 2: Security and Stability NOTE: for mentioned IGOs, institutions and multilateral governance will have investigation for History, governance structure A. Paris Peace Conference Identifying the history, governance structure. Identifying the interests of the major sovereignties involved and the resulting diplomacy or politics (influence, security interest and economic agendas as well). Associated Treaties. B. League of Nations Establishment and reasons for such Diplomatic Infrastructure Diplomatic Methods & Practices Consensus Building & Essential Steps Was there any structure of policy to facilitate humanitarian and economic development? Reason(s) for its failure (consensus or questionable reasons for such) C. United Nations Founding purpose UN charter and its major subjects Structure of the following: General Assembly, Security Council, Human Rights Council, the Economic & Social Council, Trusteeship Council, the Secretariat, the International Court of Justice. Includes sequencing among the establishments relating to consensus interests and the advancement of sustainability. Vienna Convention on the Law of Treaties Vienna Convention on Diplomatic Relations The UN and Democracy < https://www.un.org/en/global-issues/democracy > < Guidance Note of the Secretary-General on Democracy > Membership process UN Security Council United Nations Security Council Provisional Rules of Procedure Sievers, L., and Daws, S. (2014). The Procedure of the UN Security Council, Oxford Academic Genser, J., & Stagno Ugarte, B. (Eds.). (2014). The United Nations Security Council in the Age of Human Rights. Cambridge University Press. Must all members of the U.N. security council full-fledged constituents of all such agencies? What statutes or policies ensure or permit a sovereign nation to be a member of the U.N. security council? Identify the UN Specialized Agencies and “authorities” vested with each. For such specialized agencies or firms what were the drivers/causes for such establishments? How do they relate to economic and political interests? For chosen specialized agencies: diplomatic infrastructure, policy development, diplomatic methods/practices, consensus building towards essential steps. Can a nation be completely expulsed from the UN? If so, what conditions must reside? Review the differences between the UN and the League of Nations concerning sustainability. D. Functionality & Audits Literature: Regulations and Rules Governing Programme Planning, the Programme Aspects of the Budget, the Monitoring of Implementation and the Methods of Evaluation < https://hr.un.org/content/regulations-and-rules-governing-programme-planning-programme-aspects-budget-monitoring > PART 1 What robust and adaptable methods can be applied to evaluate the functionality of IGO specialized agencies, WBG, EU and OECD? The mentioned “Yakety-yak” literature provided may help. Will have implementation of such methods in lab sessions and draw conclusions. PART 2 How does one validate the annual reports and accounting/finance of the UN institutions, agencies and affiliates w.r.t. to time settings? E. UN’s International Court of Justice Review purpose and history What gives this court power? How is it’s structure and operations different to sovereign courts? Overview the ICJ articles Jurisdiction Legitimate Judicial Candidates Selection Process & Judicial Election process Prosecutor/Claimant and Defence selection by gov’ts How is a ICJ matter created? Procedures for hearings and Cases. ICJ Articles for evidence Further reads (but not limited to such): Devaney J. Fact-Finding and Expert Evidence. In: Espósito C, Parlett K, eds. The Cambridge Companion to the International Court of Justice. Cambridge Companions to Law. Cambridge: Cambridge University Press; 2023:187-207 Devaney JG. A Coherence Framework for Fact-Finding Before the International Court of Justice. Leiden Journal of International Law. 2023;36(4):1073-1094 Noticeable convictions, won suits or acquittals in history Such above two literature (and others) can be used to simulate outcome(s); analysis of simulated outcome(s) versus realised outcome(s). Schulte, C. '1 Methodology', Compliance with Decisions of the International Court of Justice, THE INTERNATIONAL COURTS & TRIBUNALS SERIES (Oxford, 2004; online edn, Oxford Academic, 1 Jan. 2010) Determine consistency with ICJ articles Challenges to ICJ relevance/authority/jurisdiction and consequences. Relationship between UN Security Council and ICJ. F. Rome Statute and the International Criminal Court Review purpose, formal proposal & establishment, and history Analogous development/treatment to all in (E). How is it’s structure and operations different to the ICJ? Possible relation between the ICC and UN’s ICJ. Why is there co-existence between the ICC and ICJ? Who has more authority or influence internationally between the two judicial structures and possible reasons for such? Are ICC operations considered a preliminary development to motivate the ICJ? Analysis of 1-2 particular countries with the following designations : Signatory that has not ratified State party that subsequently withdrew its membership Signatory that subsequently withdrew its signature Non-party, non-signatory Speculation and supporting evidence for the observed above designations. Guantanamo confinement. How so? ICJ or ICC approach? Trump’s administration sanctions Conflict with ICJ statutes (towards Iran) Respective arguments, actions and consequences. Sanctions on ICC judicial elements Respective arguments, actions and consequences. G. UN Treaties Collection Where to locate? Quick run-through General constitutional foundation and delegation process among the nations. Treaties making process (TMP) From the following resource there are many statements where case examples must be pursued: https://archive.unu.edu/unupress/unupbooks/uu25ee/uu25ee09.htm After, will try to map out the development of chosen treaties with TMP, incorporating the theories, principles, literature and laws/regulations that apply to the chosen treaties. H. Supranational treaties towards external countries or regions Possible literature of interest: https://rm.coe.int/168004ad95 (with possible counterparts from other regions as well) I. Security Cooperation NATO and Warsaw Pact Compare/Contrast Spheres of influence Cause(s) for establishment Articles of Agreement Courts & Tribunal Funding Financial Regulations and Financial Rules & Procedures Membership Process Concurrent jurisdiction under the [..] status of forces agreement Jurisdiction of the Receiving State over Forces of the Sending State under the NATO Status of Forces Agreement Case studies for Finland and Sweden before and during/after 2022 Russia-Ukraine conflict. J. Organisation for Security and Cooperation in Europe (OSCE) Flexibility in the Helsinki Final Act as a non-binding status Nonintersecting elements between the Helsinki Final act and the Paris Charter. Despite the organisation’s formal title, observed are participants of North America, Northern Africa, Asia, and Oceania. For such participants not being geopolitically what types of interest make them relevant, and what roles do the play? What are the interests? Between the UN, EU and OSCE whose efforts are more effective historically? Chronology comparison of financial contribution from member states; identify interests related to the financing. Why is the non-binding charter of the OSCE quite effective with financial contributions? K. Modern Diplomacy Structure 1.Decision Theory -- Spector, B. I. Chapter 3. Decision Theory: Diagnosing Strategic Alternatives and Outcome Trade-Offs. pp 73 – 94. In: Zartman, I. W. (Editor). 1994. International Multilateral Negotiation – Approaches to the Management of Complexity. Jossey – Bass, Inc. 2. Negotiation Models -- Druckman D. (2007) Negotiation Models and Applications. In: Avenhaus R. and Zartman I. W. (eds) Diplomacy Games. Springer, Berlin, Heidelberg For the prior two literature (Spector, Druckman) try to apply to 2 or 3 ongoing or past diplomacy/ conflicts. Actors, catalysts, policies, consequences, etc. can stem from legislative actions and executive branch actions from respective countries and/or multilateral policies. Note: data will be invaluable to apply structuring/models, and to make sense of options, positions and probabilities, etc., etc. Identify realised outcomes via state department publishing, legislature record, international gov’t organisations or NGOs, etc., and evaluate outcome(s) based on decision theory and negotiation models; contrast to the other possibilities in regard to likelihood, rationality, favourable or unfavourable positions. Are realised outcomes identified in prior developments? L. Supranationalism (European Union, Eastern Caribbean and Caribbean Community) -Comparative analysis of attractiveness and interests for joining -Comparative counterparts of: Treaties among the regional counterparts. Will have a comparative analysis of the establishment and political structure. -Possible literature of interest: https://rm.coe.int/168004ad95 (with the counterparts from other regions as well) -Copenhagen Criteria. How can the political, economic and legislative requirement elements be validated with credibility? Will also have case studies for nations based on such criteria; from recognition of application to current standing. For economic conditions specifically will identify the specific indicators or measures that must be consistently met. -Explanation for Haiti being allowed CC membership based on sound political and economic rational, indicators and models with credible evidence? -Comparative analysis for conditions to remain in union based on treaties -Comparative analysis of: How legislative representation is appointed How executive positions are appointed -Comparative analysis of general court (history, functions, composition, jurisdiction & powers) Additionally: Judicial Candidates Selection Process & Judicial Election process for the different courts -Court of Justice of the European Union (CJEU) History, composition, jurisdiction & powers Legitimate Judicial Candidates Selection Process & Judicial Election process for the different courts Does the Court of Justice have more relevance/weight than UN’s ICJ or ICC? What differentiates this court from ICJ and ICC with reviews and rulings? -European Court of Human Rights History, functions, composition, powers & jurisdiction Legitimate Judicial Candidates Selection Process & Judicial Election process for the different courts Disparities and weight against UN structures -Eastern Caribbean Supreme Court History, functions, composition, powers & jurisdiction Legitimate Judicial Candidates Selection Process & Judicial Election process for the different courts Conflicts between the ECSC and the Caribbean Court of Justice concerning jurisdiction? -Reviewing the conditions for membership, respectively. Interest in Article 50 of the EU and if possible EC, CC counterparts. -Between the EC and CC concerning trade and other topics identify any conflicts in the past. How were the conflicts resolved? Generally who is at a disadvantage? -Economic foundations and economic tools (EU, EC and CC, respectively). With member countries being both collaborators and competitors among themselves, what framework or policies encourage stability and growth with such dilemma? Does empirical evidence exhibit higher geo-economic development (rate) with supranationalism? Does a WTO court (or UNCITRAL) have more power or influence than the general court in supranationalism concerning trade? Can such UN IGOs judicial entities overrule the general court with credibility? -Concerning, Switzerland, Norway, the U.K., Hungary and Belarus will identify the social, economic and (geo)political issues that are generators of skepticism, conservatism and disengagement against regional membership. How do such issues compare with the social, ecnonmic and political metrics for EU membership? -Regional security policies and programmes Will identify whether policies and statues in such unions lead to more security and human welfare than disjoint existences. Concerning human rights and financial regulation will identify universalities among sovereignties. Will identify implicit competencies (belonging to lower levels of government) and explicit competencies. Has supranationalism encouraged or reduced immigration within the region of concern? For whatever answer, what variables are highly influential? Note that jurisdictional competition may a subject matter that bulks together various variables. Is supranationalism a boon to United Nations for monitoring, management and operations with national/homeland security? M. FATF-GAFI Development and administration FATF Methodology, Guidelines and Risk Indicators The following to be used to profile ambiances of interests: Barker, A. G. (2013). The Risks to Non-Profit Organisations of Abuse for Money Laundering and Terrorists Financing in Serbia, Council of Europe N. UNODC Identifying the causes for its creation and the major framers/developers. UNODC governance structure Legal administration How are its executives selected? UNODC University Module Series -Organised Crime: < https://www.unodc.org/e4j/tertiary/organized-crime.html > Note: choice of modules in the above Will review some UNODC guidelines or manuals for detection of narcotics (and fetanyl) and illegal drugs concerning port authority or homeland security administrations. How are such manuals or guidelines developed? Sources of scientific research and empirical research for such guidelines. Analysis of UNODC Open Data O. Interpol History, legal foundations and statutes, administration, procedure and conditions for membership. Jurisdiction. Protocols What conditions must be met to establish international warrants and operations with Interpol? Comprehension of intervention abilities. What are the linkages between Interpol and the UN concerning global governance? Concerning Interpol identify any residing bureaucratic or constructive relationship involving the UNOCD? Does the lack of corporation with Interpol have any considerable influence on international diplomacy and commerce? How does a country get expelled from Interpol? Case Studies? ---MODULE 3 International Government Organisations (formation and diplomacy) Johnson, T., & Urpelainen, J. (2014). International Bureaucrats and the Formation of Intergovernmental Organizations: Institutional Design Discretion Sweetens the Pot. International Organization, 68(1), 177-209. Barnett, Michael and Finnemore, Martha. "2. International Organizations as Bureaucracies". Rules for the World: International Organizations in Global Politics, Ithaca, NY: Cornell University Press, 2012, pp. 16-44. Cortell, A. P., Peterson, S. (2022). Autonomy and International Organisations. J Int Relat Dev 25, 399–424 Cao, X. (2009). Networks of Intergovernmental Organizations and Convergence in Domestic Economic Policies. International Studies Quarterly, 53(4), 1095–1130. Statistical and ecobometric activities can be emulated for applied data sets and more modern data sets. ---MODULE 4 Economics and Trade NOTE: for the mentioned organisations or institutions will have identification for history and governance structure. This module will be a bit more condensed due to the number of elements, but acquisition and use of financial data will be reinforced. Respective financing and operations (excluding the 1700s and 1800s). Issues of transparency (within and dealing with sovereign states). A. International Trade (1700s and 1800s) Who were the initiators, coordinators and regulators? Mercantilism Period and controlling routes? B. For the (1700s and 1800s) how were records of transactions and balances honoured or deemed legally admissible among foreign nations before modern establishments? C. Free Trade in the 19th century? D. Bank for International Settlements (BIS) Origin, goals, framework, administration & regulations Concerning the European Central Bank (ECB) and Eastern Central Caribbean Bank (ECCB) what are the relationships and rules for such two intergovernmental banks with the BIS? E. Forward thinking Analysis of institutions such as the IMF and WBG being conceived before the end of WWII. F. Free trade and (versus) Domestic Production G. 1948- General Agreement on Tariffs and Trade (GATT) Highlight the drivers and initiators. Role of asset backed currencies and fiat currencies post-GATT. H. IMF and the World Bank International Monetary Fund: -> James M. Boughton, The IMF and the Force of History: Ten Events and Ten Ideas That Have Shaped the Institution. IMF Working Paper WP 04/75. Primary functions Prerequisites to be relevant to the organisation. Process of immersion and integration into this global system. Articles of Agreement of the International Monetary Fund Analytical discussions and possible participant conflicts in history is possible What are the models and metrics for determining loans or transactions to particular countries? Compare with a PESTEL format for such. World Bank: -> Catalysts or influences for the creation of the World Bank Primary functions Prerequisites to be relevant to the organisation. Process of immersion and integration into this global system. Administration Articles of agreement Analytical discussions and possible participant conflicts in history is possible. What are the models/metrics for determining loans or transactions to particular countries? Compare with a PESTEL format for such. International Monetary Fund. (2020). IMF and the World Bank: https://www.imf.org/en/About/Factsheets/Sheets/2016/07/27/15/31/IMF-World-Bank Driscoll, D. D. (1996). The IMF and the World Bank, How do They Differ? International Monetary Fund I. OECD Further: von Lampe, M., K. Deconinck and V. Bastien (2016), Trade-Related International Regulatory Co-operation: A Theoretical Framework, OECD Trade Policy Papers, No. 195, OECD Publishing, Paris, OECD (2017), International Regulatory Co-operation and Trade: Understanding the Trade Costs of Regulatory Divergence and the Remedies, OECD Publishing, Paris, J. World Trade Organisation (WTO) and Balance of Trade 1. Review of GATT Prerequisites to be relevant to the organisation. Process of immersion and integration 2. Design of administrations to support charters, various missions and objectives. Recognition/analysis of agendas and related operations. 3. Judicial court/structure in the WTO Functions, composition, powers & jurisdiction 4. What are the major subtleties between the general structure of the WTO and trade structures of the EU, NAFTA, Eastern Caribbean and the African Union? 5. Policies and initiatives towards crypto currencies with DeFi concerning laws/rules. 6. What prior foundation existed as the predecessor to the WTO? Compare its structure to what was developed via (1) through (4). The Technical Barriers to Trade (TBT) Agreement K. Special Drawing Rights Kenton, W. (2002). Special Drawing Rights (SDRs). Investopedia Laws and Articles for SDRs Process to access SRDs L. World Intellectual Property Organisation (WIPO) Prerequisites to be relevant to the organisation. Process of immersion and integration into this global system. For a country such as Guyana and others identify the causes for lack of progression with intellectual property towards firms or enterprises (corporate, entertainment, humanities, etc.). What are the economic, commerce and political effects for lack of intellectual property development? Is poor FDI highly correlated with such? Are the results same for macroeconomic and development measures? M. World Trade IGOs UNCITRAL, UNCTAD & WTO Differentiating in terms of functions, service, global governance and abilities. What is the constructive flow of operations and governance among such three? N. Recall the Caribbean Community structure and Eastern Caribbean structure What distinguishes the CC from the EC concerning economics? Open Market notion (purely economic definition) Identify advantages and disadvantages of EC against the CC Can judicial rulings of the EC concerning economics and trade be much more regarded than judicial rulings of the CC? If any existing trade agreements between external nations and the CC block, how does EC interests work? Can there be both CC and EC trade agreements with any same outside sovereignty? Are free trade agreements or open market agreements ever in conflict with WTO, UNCITRAL & UNCTAD statutes or foundations concerning the EC and CC existence? ---MODULE 5 NGOs & NPOs Resonance Korey, W. (1999). Human Rights NGOs: The Power of Persuasion. Ethics & International Affairs, 13, 151-174. Spiro, Peter J. (2008). NGOs and Human Rights: Channels of Power. Research Handbook on Human Rights, Edward Elgar, 2009, Temple University Legal Studies Research Paper No. 2009-6 What are the major elements for credible human rights development, growth and sustainability? Are such three highly correlated? Why or why not? The following two articles concern: Analysis -> Replication -> Incorporate more modern data -> Pursue analysis for other NGOs Henry, L.A., Sundstrom, L.M., Winston, C. et al. NGO Participation in Global Governance Institutions: International and Domestic Drivers of Engagement. Int Groups Adv 8, 291–332 (2019) Allard, G. and Martinez, C. A. (2008). The Influence of Government Policy and NGOs on Capturing Private Investment. Global Forum on International Investment 27 – 28 March 2008. OECD. ---MODULE 6 Technology and Advancement NOTE: for the mentioned organisations & associations will have identification for history and governance structure A. United Nations Standards Coordinating Committee (UNSCC) B. International Organization for Standardization (ISO) How did this organisation become relevant? Governance. Prerequisites to be relevant to the organisation. If one assumes weighted voting for particular “delegates” in such organisation, how can such be validated? Who is relevant to advance agendas and interests? Concerning elements representation for a single country, how does one evaluate the credibility and integrity of such an individual? For a respective country with questionable social and political levels/standings, how does the ISO evaluate or legitimize the credibility of meaningful presence? Conflicts or contradictions with the UNSCC? C. ECMA International (counterpart to B) D. Information Technology Agreement (ITA) and Basic Telecommunications Agreement (BTA) Relevance or interpretation or policy with the following Economic cooperation International banking Synchronization or coordination with FATFA International security Travel and Customs E. International Telecommunication Union (ITU) Under the auspices of UNESCO, IFIP is recognised by the United Nations. Position or policy on net neutrality. Position or policy on monopolistic and oligopolistic media conglomerates/enterprises internationally. F. International Federation for Information Processing (IFIP) Under the auspices of UNESCO, IFIP is recognised by the United Nations G. IETF & IANA H. ISACA How did this organisation become relevant and dominant? What relationships or policies reside with the UN structure? I. Establish a bureaucratic scheme, commerce or constructive relation between (A) - (I) ---MODULE 7 International Media Communications The International Press Telecommunications Council (IPTC) and International Press Institute (IPI) History, governance structure Prerequisites to be relevant to such organisations. Process of integration. What relationships or policies are there with the UN foundations? Polices on intellectual property rights. Policies on intellectual property rights Information Interchange Model (IIM) What levels/types of technologies and policies/guidelines are incorporated to maintain authenticity in (meta)data and recognition of proper sources concerning issues of plagiarism, false claims of ownership, intellectual property, fraudulent media, etc.? Is the IIM a system officially recognised by many/most countries concerning their reputation, national security or interests, whether for intelligence pursuits or censoring? Is the IIM often in conflict with gov’t policy? Role of the WTO in international media communications Role of the WIPO in international media communications What types of conventional commerce are there between the IPI and IPTC? For international mergers or takeovers involving telecommunications giants, apart from respective national regulatory influence what roles do the IOTC, IPI, WTO and WIPO have? Do such institutions have policies against oligopoly structures or attempts against distributed market share in relation to corporate headquarters residencies and political affiliations of the administration in question? Issues of reduction in media pluralism and independent views. With foreign sovereignty having their limitations or strong interests, how is the conveyance of media orchestrated with credibility? How is there authenticity and integrity? Methods in foreign policy and law by a sovereign state that assure authentic and credible media. Concerning geo-political/human crisis how is authentication of such events established with the international community and international governance? ---MODULE 8 Aviation and Air Transportation A. International Civil Aviation Organisation (ICAO) History, governance structure Airspace sovereignty (civil and military operations) Prerequisites to be relevant to the organisation. Process of immersion and integration into this global system. How does a sovereign state acquire air travel commerce with international firms? Concerning international air traffic, how does a respective sovereign state determine whether incoming foreign air traffic meet safety, security and energy standards sans being a constant business impedance? How does the ICAO determine whether a port or sovereignty maintains upkeep with international standards? How does an airport become certified nationally and internationally? How does an airport acquire air transportation services? What is the consensus amount of regulations for air travel and security agreed upon by recognised sovereign states related to post-9/11? How was this done? Case of International air disasters: foreign airlines in international air space versus foreign airline in sovereign airspace. For the case of foreign airspace and international airspace (both developed nations and third world), how is credibility of investigations determined? B. International Air Transport Association (IATA) History, governance structure Relevance to airspace sovereignty Prerequisites to be relevant to the organisation. Process of immersion and integration into this global system. For policies and agreements generated through the IATA, will such have considerable influence on the relevance or decision making of the ICAO? Are their emissaries operating for both the ICAO and IATA? Cartel history of the IATA, and current regulation against cartel standing. Concerning price fixing, are there any recognised historical cartel actions among airlines carried out apart from the IATA? Cite price fixing evidence if so. Is there cultural or formal lobbying between the IATA and ICAO? Possible case of entities of IATA with official ties within the ICAO and vice versa. Does the WTO have relevance in aviation and air transportation policy and standards? Consider major the international airlines concerning market share operations in the continents of North America, South America, Europe, Asia and Australia. Can entities of such firms be formally recognised as having major roles in the IATA, ICAO and WTO? C. Production and commerce in the Aerospace industry Statement to prove or disprove: there are many countries with the ability to produce commercial aircraft, however, often its commonly circulated that air transportation permission into foreign territories is extremely correlated in the same direction with the aircraft components incorporated. Support with statistics and 5C Analysis development. Airbus, Boeing, Bombardier, Lockheed Martin, etc., etc. Thales Group, Northrop Grumman Corporation & other avionics specialists Jet engine companies Keep in mind there’s nearly 200 countries today, so how are countries without aerospace engineering prowess convinced with new products in short time and safety standards? Is it constructive to limit change in market share in the aerospace industry concerning intellectual property, accountability, quality and labour stability? Apart from incidents and media what intelligence allowed for the suspension of Boeing’s 737 Dreamliner? Are inquiries, probe, hearings, etc. more extensive than elsewhere than in the United States? Is it a challenge to prosecute or apply embargoes on Boeing due to an oligopoly with exclusive industry services for aircraft and the components manufacturing “cartel”? Is the commercial aerospace industry the only realm where an oligopoly can thrive on international governance? What are the causes or catalysts for the creation and thriving of oligopolies in international governance? D. Aircraft Engine Environmental Analysis ICAO Aircraft Engine Emissions Databank Will try to collect data sets for the last 20-25 years. The aim with such data sets is to develop a model that confirms some level of environmental initiative. Consideration of how variables and/or parameters relate to emissions performance as aircraft engine development advances. How are performance/emissions data reporting by firms authenticated as credible? Between aerospace engineering firms, airlines, environment agencies of gov’ts, and aviation agencies of gov’ts, who has the biggest muscle? Determining benchmarks in emissions standards: nations compared to IGOs. ICAO Models and Databases (to investigate): https://www.icao.int/environmental-protection/pages/modelling-and-databases.aspx ICAO Environmental Tools (to investigate): https://www.icao.int/environmental-protection/Pages/Tools.aspx ---MODULE 9 Environment Initiatives Models (EIMs) A. What are they? How do EIMs become accepted by international bodies? B. Economic Input-Output Life Cycle Assessment 1.Analysis of method; guides and logistics before implementation 2.Building a customized model: http://www.eiolca.net/cgi-bin/dft/custom.pl C. Integrated Assessment Models (IAM) Vaidyanathan, G. (2012). Core Concept: Integrated Assessment Climate Policy Models have Proven Useful, with Caveats. PNAS Vol. 118 No. 9 e2101899118 Comparative Analysis with IAMs Note: will have some actual implementation and analysis of findings comparatively -- 1.Exploring the DICE model: logistics and Excel use 2.Framework for Uncertainty, Negotiation and Distribution (FUND) Analyse and acquire source code 3.Global Change Analysis Model (GCAM) Source: < http://www.globalchange.umd.edu/gcam/ > 4.REgional Model of Investment and Development (REMIND) Source: https://www.pik-potsdam.de/en/institute/departments/transformation-pathways/models/remind D. Identification of economic incentives for cooperation (countries and firms) E. Which nations are typically respected or take on leadership roles with environmental “policing” or enforcement? Why? What makes them legitimate leaders? ---MODULE 10 Marine Regulation A. International Maritime Organisation (IMO) United Nations Convention on the Law of the Sea (UNCLOS) International Tribunal for the Law of the Sea (ITLOS) International Seabed Authority (ISA) International Convention for the Prevention of Pollution from Ships (MARPOL) Will identify various significant conflicts throughout history that lead to the following four entities: UNCLOS, ITLOS, ISA and MARPOL Annex I-VI Administrative structure and judicial selection process and for UNCLOS, ITLOS, and ISA, respectively. What is operating relationship between such three? B. COLREGS, SOLAS 1974 + ISPS For particular articles in COLREGS will like to determine causes for its development. What are the disparities between COLREG and rules of your ambiance? Is there an acceptable limit for disparities between ambiance rules and COLREGS? For particular articles in SOLAS 1974 + ISPS will like to determine stimuli that lead to their development. Relation between naval architecture codes and SOLAS 1974 + ISPS ---MODULE 11 Territorial Principle (TP) How was TP established with/in the UN? TP versus state legitimacy. What/who can be trusted? Monitoring due process? Articles to build further discussions: Cormier, M. & Vagias, M. (2015). The Territorial Jurisdiction of the International Criminal Court, Journal of International Criminal Justice, 13(4), pp 895–896 Review ICJ counterpart as well. Maillart, JB. (2019). The Limits of Subjective Territorial Jurisdiction in the Context of Cybercrime. ERA Forum 19, 375–390 ---MODULE 12 Determinants for the Preference in Upholding Specific IGO Regulations – ask ChatGPT (or other AI) Identify 7-8 key factors Model for determinants influencing IGO regulation preference Econometric model(s) development for prior and validation? ---MODULE 13 Sanctions 1.UN’s Charter addressing sanctions 2.Process (multilateral, UN) Agendas and claims Legislation/Litigation process Means of credible evidence and validation to pursue 3.Conditions for UN to oppose external multilateral sanctions 4.Sanctions and the administrative channels for gov’ts Diplomatic Executive Economic 5.Analysis of chosen sanctions based on literature from state department, executive office, parliament, treasuries (OFAC, HM Treasury, etc. etc.), EU, UN, use of trusted media, etc. Will choose 3-4 past or current sanctions for analysis (targets and outcomes). Earlier structuring (1 through 4) will be used towards: A. Setting, conflict/plot B. Targets, intended effects, outcomes Analyse effects upon targets, general “market agents” & sovereignty 1. Diplomatic: resulting effects and responsive/counteracting tools with effects; may take much effort 2. Economic: observed effects (which may take much effort) Basic time series analysis with means to identify shocks and degradation: banks (equity, capital, credit/default risk), stock markets, major sources of income, gov’t securities (ratings, liquidity), exchange rate with benchmark currencies, foreign reserve dynamic, monetary policies/applied tools, fiscal policy, trade balance, FDI. Some advance structuring/development literature to further expand upon (A) and (B) (adjust to ambiances of study): Doxey, M. (1972). International Sanctions: A Framework for Analysis with Special Reference to the UN and Southern Africa. International Organization, 26(3), 527–550. Crawford, N.C., Klotz, A. (1999). How Sanctions Work: A Framework for Analysis. In: Crawford, N.C., Klotz, A. (eds) How Sanctions Work. International Political Economy Series. Palgrave Macmillan, London Haider Ali Khan, & Oscar Plaza. (1986). Measuring and Analysing the Economic Effects of Trade Sanctions against South Africa: A New Approach. Africa Today, 33(2/3), 47–58. Allen., S. H. (2008). The Domestic Political Costs of Economic Sanctions, The Journal of Conflict Resolution, 52(6), 916–944. 6. Global impact of economic sanctions (based on significant conflicts) Basic time series analysis with means to identify shocks and degradation: commodities (raw, hard, soft); energy; food prices; gov’t securities liquidity in advanced economies; stock markets in advanced economies; benchmark currencies compared to remaining G20 members, etc., etc. 7.Meissner, K. (2022). How to Sanction International Wrongdoing? The Design of EU Restrictive Measures. Rev Int Organ. Analyse, use of QCA and SetMethods R packages Prerequisites: at least upper sophomore level, respective writing sequence, International Financial Statements I & II, Introduction to Computational Statistics for Political Studies (or Mathematical Statistics) Legislative Process This course will examine the origin of the legislative branch ambiance government and the unique role it plays in representing all of the people of the country. Its history reveals the development of country and how the Parliament has adjusted, modified and changed internally and independently---all within the constitutional constraints designed by the Constitution’s authors. Parliament is often comprised of two similar yet each uniquely different legislative bodies. We will examine the differences and the role each legislative body plays to develop and refine public policies resulting in statutory law. We will examine the budget process which influences and controls all emerging public policies. We will scrutinize the role of parliamentary oversight of the executive branch and the role of the judiciary in our constitutional form of government. In examining how parliament really works, we shall explore common public criticisms as well as discuss ways in which parliaments’ effort could be improved. Lastly, we will look into the important role civic participation plays in demanding improved performance of this complex and diverse branch of government. NOTE: aside from national/federal legislature will also include treatment of provincial level and city level legislatures in comparative manner with the national or federal level for all topics. Activities for assessment (some not necessarily in specific order and/or may be done on multiple occasions) --> --Review constitution concerning legislative branch powers and checks by the other branches --We shall read texts, and official provincial and federal law/bill libraries and repositories --Analyse specific legislative proposals --Apply our insights in practical exercises that require reading, thoughtful analysis, writing and representation of a particular vested interest. --Bill Analysis Memorandum Methodology --Evaluation of 2-3 Bill Analysis. Accompanied by identification and profiling of legitimate stakeholders. Programme Theory. Non-monetised impacts. --Case Studies: Welfare of bills. Review past/current bills (federal, provincial, municipal) in the legislative process (pass and fail) with analyses to give course substance in progression --Impact Evaluation (design) for a passed bill 2-4 years following Gertler, P. et al (2016). Impact Evaluation in Practice: Second Practice, World Bank Publications --Case Studies: Judicial review/ruling of bills and parliamentary response --Take 3-5 quizzes throughout course (facts, T/F, and analytical short responses) --Political ideology and organisation in the legislature (based on module) Group assignments for provincial and municipal levels, however, all groups will be accountable for the federal level. --Take 2-3 examinations --Write a Legislative Bill Analysis Memorandum in lieu of a Final Examination. Documentation & Tools (crucial to undercurrent activities) --> Parliamentary repositories and databases Bill Analyses Cost Estimation data Bill Tracker Voting record or databases Lecturing Outline --> NOTE: aside from national/federal legislature will also include treatment of provincial level and city level legislatures in comparative manner with the national or federal level for all topics. --Overview of the National Constitution --Constitutional structure for a legislature (federal, provincial, municipal comparatively). Framers and establishment. --Parliamentary structure, representation, service (time and term limits), elections process. Sessions and Cycles Federal, provincial and municipal --Parliamentary demographics (federal, provincial and municipal). Parliament and Law-making. --Political ideology and organisation in the legislature PART A: Liberal, Moderate and Conservative. How to definitively distinguish one from the other? Will be based on the social, political and economic realms. PART B: will choose district, city, provincial and national levels of legislature, accessing voting record versus ideology campaigns to model and analyse, comparing with public political characterisation, and the demography of the voters that support(ed) respective representation or candidate. PART C: database of individuals and individuals who have made contributions to federally registered political committees. Some exploratory data analysis and clustering will be applied. PART D: MONIMATE (scaling method) Poole, Keith T.; Rosenthal, Howard (1985). A Spatial Analysis for Legislative Role Call Analysis. American journal of Political Science, 29(2): 357–384. Extend to W-NOMINATE and DW-NOMINATE as well. R environment will be applied PART F: for one’s ambiance will apply similar structures as the following: < https://www.govtrack.us/about/analysis#overview R environment will be applied PART G: Bipartisan Index The Lugar Center-McCourt School Bipartisan Index: https://www.thelugarcenter.org/ourwork-Bipartisan-Index.html PART H: analysis of development and function of committees in the legislature. Regulations for committees. PART I: Does a legislature serve best when its bipartisan dominated? --Lower House structure, representation, and selection process. Lower House Rules Committee Resolutions and Reports. --Scheduling Lower House Legislation & House Floor Procedures --Upper House structure, representation, and selection process. Upper House Rules Committee Resolutions and Reports --Scheduling Upper House Legislation & Upper House Floor Procedures --Differentiating powers of each house along with identification of constitutional framework for such. Power Resolving Lower House/Upper House Differences & Legislative Oversight. Dynamic Process. Some history. --Lobbying Regulations Ambiance analogy to: https://www.everycrsreport.com/reports/RL31126.html --Preliminary legislative action and role of committees in agenda setting (for both upper and lower houses) --Bill Process (federal, provincial, municipal comparatively): life or death in in the legislature; executive veto and the possibility of legislative overrule. Case Studies. --Organising and Drafting Legislation --Tools or systems used to track legislation. Hands-on activities --Bill Analysis Memorandum Methodology --Case studies: legislative process and judicial review/ruling, and parliamentary response. --Budget Office serving parliament (federal, provincial, municipal) Responsibilities with nonpartisan policy. Survey of duties and literature development from databases/repositories/archives, say, common knowledge, procedures, technical terms, working papers, technical papers, research, etc. --Parliamentary Budget Process (with inclusion of the role of budget office) --Comparative observation of federal, provincial and local legislatures: structure, procedures, some history and demographics (of a chosen few); budgeting processes also included. --National congress having significant power and responsibility to respond to Supreme Court decisions. On statutory matters, there is no question that Congress may negate a Supreme Court interpretation by enacting new legislation. Structure/power towards T&T presidential decisions. --National Parliamentary grounds. Library and Databases immersion. --Tobago House of Assembly Library and Databases immersion --Finish Legislative Bill Analysis Memorandum. Legislative Bill Analysis Memorandum Due Prerequisites: Constitutional Law Executive Process Outline--> COMPARATIVE: --Constitutional framework for the executive structure Democracy Models of democracy with the executive branch Powers, limitations and service Constitution Identification of powers and checks by the legislative & judicial branches Organsiation of the Executive Branch Crowned monarchy and constitutional monarchy; counterparts to prior Executive structure and welfare in communism North Korea, China, Cuba, Vietnam. --Selection process of the executive leadership among democratic models Structure and process AMBIANCE BASED: Note: questions for outline to be answered throughout progression What is the bureaucracy? What tools does the bureaucracy have for implementing federal programs? How does the President exert control over the bureaucracy? What resources are available to President? What are different structural arrangements available? Is the bureaucracy responsible to the Executive Branch or to the Legislative Branch? How does Congress exercise oversight? Is Congressional oversight part of the solution or part of the problem? What actions can the President take unilaterally? What is the basis for such actions? What are some of the constraints on using such authority? What can Congress do to counteract presidential unilateral actions? Do Presidents act because Congress has not? How are the foreign policy roles of Congress and the President balanced? What issues arise with the bureaucracy? How does the president balance role of commander in chief and chief diplomat? What is the role of the executive branch in the federal budget? What mechanisms does the Executive Branch use to improve budget performance? COURSE OUTLINE: --Role and influence in a system of checks and balances --Selection process of the executive leadership. Influence of demography and ideology. Service (time and term limits). --Organisation of the executive branch, and how it is affected by the executive leader’s management style or agendas: 1. Executive Office Structure 2. Executive Branch Organisation 3. Transmissions and/or function between (1) and (2) 4. Group Assignment: observe a respective executive leader’s nominations or confirmations for cabinet positions, departments, ministries, commissions, agencies, etc. What are the backgrounds of such nominees (education, occupation history, ideals/rhetoric, sociopolitical record)? Administering a competent background investigation concerning prior question? Sources and references are expected. Do candidates identify well with the consensus executive policy or ideology? 5. Group Assignment: for the executive administration in question choose a programme or policy to apply the following elements of programme evaluation: A. Identifying specific changes in policy (both general and budgetary impact) B. Identification of the various stakeholders, executive channels to provincial administrations. C. Programme Theory D. Legal challenges, possible judicial reviews and rulings (if relevant) E. Process Evaluation RAND Corporation - Evaluate Outcomes of the Programme: https://www.rand.org/pubs/tools/TL114/manual/step8.html F. Impact evaluation (selected methods): Gertler, P. et al (2016). Impact Evaluation in Practice: Second Practice, World Bank Publications. NOTE: from Gertler to choose 1 or 2 methods that are feasible. NOTE: systematic black swans, fiscal management, global economy and geopolitics may influence without executive policy/programme at fault. Much emphasis on citations and references for assignment throughout. Can also be done for respective province municipality. 2 out of the following areas -- Agriculture Energy Environment Treasury Trade Executive orders with taxation Economy policy Socioeconomic Development/Social Welfare Health & Human Services Justice (attorney general’s guidelines towards states/provinces) National Security Immigration Government size --Organisation of the executive branch for respective province or city, and how it is affected by the executive leader’s management style or agendas. Note: similar analysis to most of prior module, but omission of irrelevant elements regarding provincial level and city level. --Social Scientific Dimensions A. Drawing the line between the conservative and the liberal. Establish. B. Consistent realised outstanding ideals. Political History: Prior legislative and/or executive political record background of individual in question; track record on policies from priors via executive and legislative databases. C. Psychological dimensions of executive leader service, including executive leader character types Group Assignment: for chosen executive leaderships draw conclusions based on application of (A) to (D). Note: (A) to (D) may also be done for respective province and city. --Executive engagements with the legal process 1. Executive relations with Congress, and the factors that shape presidential success in Congress. 2. Lobbying the executive branch Executive Agency (or office) Lobbying Lobbying restrictions/disclosure acts 3. Attempted policies and the response of congress considering political makeup. 4. The influence of congressional elections results on success of executive policies; lower house and upper house, respectively. Are congressional elections results a strong gauge on feasibility of executive policies? 5. For democracies consider the executive leader’s relations with bureaucrats, and why they often resist the executive leader’s preferences 6. The mutual influences of the executive leader and the judicial branch on each other. --System of Balance and Checks review Structure and case studies with the executive role highly illuminated in terms of abilities, influence and restrictions. --Judicial reviews and rulings on executive orders Notable articles of the constitution for such and how prior executive actions stimulate reviews or judicial rulings. Process and cases in history. --The executive leader’s relationship with the press. Comparing America’s press engagement and etiquette with other countries. --Public opinion toward the president, its trends, sources and consequences Approval ratings and polls: structure of polls, ratings and credibility. Welfare of polls and ratings. --The concept of executive (leader) opportunity, and how it influences a leader’s performance in office. --Federal Budget Executive Budget Request (EBR): structure and analysis Group Assignment: Part A: comparative assessment of EBR with counterproposals of major factions in the legislature. Pat B: comparative assessment between predecessor and successor (or executive having “opposite political ideology” prior) Course Assessment --> 1. Attendance and Participation 2. Quizzes (T/F + Executive Orders/Policy vs Judicial Review/Rulings + short responses) 3. Midterm (T/F + Executive Orders/Policy vs Judicial Review/Rulings + short responses) 4. Group Assignments 5. Final Exam (T/F + Executive Orders/Policy vs Judicial Review/Rulings + short responses) Prerequisites: Constitutional Law, Introduction to Computational Statistics for Political Studies Judicial Process To comprehend what the law actually is in practice, and to understand how it evolves over time, it’s necessary to understand how judges decide cases. The purpose of this course is to survey the social scientific literature on how judges make decisions. Topics include theories of decision making; judicial selection; constraints under which judges operate; the agenda and litigation process; collegial courts; intercourt relations; the separation of powers; and, the public. Course materials will be drawn from chosen text, judicial record AND original published studies. NOTE: THERE WILL BE historical review of court cases incorporated at various times. Will also identify historical judicial hearings and their fates due to the courts. Elements for course assessment --> 1. Lack of participation will make things much more difficult for you; making yourselves easier targets with the instructor’s creativity. 2. At four times during the term you will be required to write a 1-2 page reaction memorandum. These memoranda must be solely your work. On the first day of class you will receive, by lot, the sessions for which you are responsible for circulating a discussion memorandum. The memos will form the basis for class discussion. You should plan to read them before the seminar meets. Lack of effort or lack of memo submission on time, and lack of memo reading will make things much more difficult for you; making yourselves easier targets with the instructor’s creativity. 3. Essay: each student will write a 15-page essay over the course of the semester. The topic of the essay can be chosen by the student, but requires approval of the instructor. There are three types of essays students can choose to write: – Critical Literature Review. Critically review a literature related to judicial decision making. Contain a clear thesis, a discussion of what we know (and, perhaps, what we do not know), and the implications of what we know to legal practice. These essays might, also, contain a discussion of the normative implications of a particular literature. – Case Analyses. An analysis of a set of cases, typically in a single area of law or constitution, through the lens of one or more literature related to judicial decision making. Carefully select cases that provide analytical leverage for the thesis of the essay. Includes notable articles of the constitution or law (provincial or national), and how prior cases possibly influence reviews or rulings in question. – Original Empirical Research. Some original research conducted by the student. Written as research notes, that situate the research question within a literature, posit a clear research design, and—using existing or original data—conduct suitable statistical analysis. Submit by given date a 1-2 paragraph description of the essay one plans to undertake. I will, then, meet with each student on two decided days to provide feedback and guidance. On or before a following given date, each student is responsible for submitting, in hard copy, a full outline of their essay, including citations to cases and/or the literature that will be referenced. I will provide written feedback on these outlines and meet with students as needed; after deadline penalty can vary drastically or minimally. Final essays are due on date noted. Essays must have designated particular format, and converted to pdf file before submitting. Footnotes, endnotes, tables, figures, and a bibliography do not count toward the page limit. 4. Judicial Intelligence Students are expected to be knowledgeable on judicial structure, operations, processes, placement (local, provincial and federal). All such will be present in quizzes and exams. 5. Students are expected to be knowledgeable about particular amount of “landmark cases” and decisions: supreme, collegiate, appellate, trial, civil and opinion writing for the ambiance in question. There will be quizzes and exams incorporating all such. Concerning court cases: –For given excerpts students must identify the court case –True or False questions –Giving historical summaries –For general circumstances or dilemmas students to reference appropriate court case; there can possibly be multiple references as long they’re considerably “in the ball park” and relevant to current exercises of law. Process for cases to be heard by supreme courts (federal and provincial). Will include analysis of attempts (both failing to the reach the supreme court and those successful for case). Filling in critical statements, points and features. All such will be present in quizzes and exams. 6. Development of chosen measures from module 7 7. Simulations: plea bargain; civil case development and procedures Students are expected to be well prepared with legal knowledge and logistics. Good representation and performance are crucial for legal success. References and law repositories will be provided that are relevant. There will be those of professional legal background as guidance and evaluators. For each simulation there will be a process walkthrough without exhibiting much details of respective strategies and tactics before actual simulation. 8. All topics are applicable to quizzes and exams Assessment --> Participation Quizzes Memorandums 2 Simulations 2-3 Exams Essay Topic Outline --> 1. Separation of Powers. Foundations and Sources of Law 2. The Judicial Branch Identity development Causes of Judicial Review Problem of Judicial Review The Role and Identity of the Judge 3. Provincial and Federal Court Systems Structure of Provincial and Federal Court Systems Organisational Meetings, Agendas and Procedures. The network of committees 4. Provincial and Federal Court Selection of Judges Role and influence of executive body and legislature makeup on selection and confirmation. 5. Constitutional powers and limits (checks) on the Court Systems Federal Provincial Coexistence between provincial supreme courts and the federal supreme court: reviews and rulings in regard to executive branch policy (federal and provincial) and/or legislative branch policy (federal and provincial). SIMULATION: the process for both provincial supreme court and federal supreme court with whatever hypothetical sociopolitical issue. Students must be well prepared to properly and competently orchestrate the transitioning or involvement procedure. Cases between provincial and federal. Followed by case studies. 6. Law and Constraint 7. Ideology May rely heavily on journal articles Gaining the concepts of common measures: A. Segal-Cover Score B. Judicial Common Space C. Campaign Contributions Methodology Adam Bonica, Michael J. Woodruff, A Common-Space Measure of State Supreme Court Ideology, The Journal of Law, Economics, and Organization, Volume 31, Issue 3, August 2015, Pages 472–498, D. Party-Adjusted Surrogate Judge Ideology (PAJID) scores developed by Brace, Langer, and Hall (2000), which are focused on ideology for justices on state supreme courts. E. Martin-Quinn Score Note: excluding (E) some measures may be implementable w.r.t. limited time available. 8. Judicial Conduct Bangalore Principles of Impartiality and Integrity, and progressive efforts for measures Code of Conduct for Judges (Federal, Provincial, Municipal, respectively) Commission for Judicial Conduct (Federal, Provincial, Municipal, respectively) Establishment and Authorities Procedures involving role of commission intervention and action Case studies for judges under inquisition and outcomes 9. Intra-Court Bargaining and Opinion Writing Case studies in opinion writing (concerns and comparative arguments). Make use of Court Opinion Writing Databases. 10. Race, Gender, and Other Ascriptive Characteristics 11. Collegial Courts 12. Criminal Procedure and Trials 13. Assessing the Theory and Practice of Criminal Sentencing 14. Plea Bargain Simulation 15. Data Analysis for Criminal Offences Statistics for levels of punishment w.r.t. type of criminal offence Deterrence Hypothesis Probe models development, replicate or amend. Then pursue ambiance or region of interest with more modern data (determine best model). Followed by marginal effects versus forecasting. Taylor, J. B. (1978). Econometric Models of Criminal Behaviour: A Review. In: Heinke, J. M. Economic models of Criminal Behaviour. North-Holland Publishing Brier, S. S., & Fienberg, S. E. (1980). Recent Econometric Modeling of Crime and Punishment: Support for the Deterrence Hypothesis? Evaluation Review, 4(2), 147–191. Simester, D. I. and Brodie, R. J. Forecasting Criminal Sentencing Decision, International Journal of Forecasting 9 (1993) 49-60 North-Holland Schildberg-Hörisch, H. and Strassmair, C. (2012). An Experimental Test of the Deterrence Hypothesis, The Journal of Law, Economics, and Organization, Volume 28, Issue 3, Pages 447–459. Issues of disproportionality with race and wealth 16. Civil Court Civil Trials and Procedures SIMULATION: with tools and resources. Development process of a civil case, from filing to trial. 17. Existence of retention elections in local governance 18. Appellate Divisions Civil cases, criminal cases, provincial supreme court, federal supreme court, Surrogate’s Court, Family Court, and Court of Claims. Prerequisite: Constitutional Law, Introduction to Computational Statistics for Political Studies Comparative Electoral Systems Representative democracy concerns a set of rules to determine who wins elections and gets to govern. The rules in consideration can drastically vary in regard to how votes are cast, counted, and translated into seats, and differences in the rules can produce significantly different political outcomes, both directly (due to the way in which votes are counted) and indirectly (due to incentives that affect the behaviour of political actors, such as voters and political parties). The electoral system is identified as the set of rules that structure the process of voting and election. This course will survey and analyse electoral systems from around the world to explore how electoral rules can affect voters, politicians, parties, policymaking, and representation. --Know and understand the basic mechanical differences between electoral systems. --Use electoral results to obtain key measures of analysis, such as the effective number of parties and level of (dis)proportionality (being just one of many). --Compare and contrast the electoral systems used by different countries, and evaluate how observed differences in the politics of those countries may be related to the electoral systems. --Recognise the possibilities and limitations of electoral system design and reform. Typical Texts (in unison): The Politics of Electoral Systems (PES). 2008. Eds. Michael Gallagher and Paul Mitchell. Oxford University Press Electoral System Design: The New International IDEA Handbook (IDEA), 2008. Eds. Andrew Reynolds, Ben Reilly, and Andrew Ellis Reference: Colomer, J. M. (2004). The Handbook of Electoral System Choice. Palgrave Macmillan UK PES contains country-specific chapters, which are usually divided into the following sections: (1) Historical background of the country’s political system (2) Origins of the current electoral system (3) The electoral system as it stands today (4) Political consequences of the electoral system (5) The politics of electoral reform When thinking about the origins of electoral systems and debates about their reform, it's important to remember that they are usually adopted by the very actors–– politicians and parties––who will be most affected. Ask yourself: who stood to benefit from the adoption of certain rules, and who were the major players in these deliberations? Pay attention to the critical electoral variables in Section 3. When you are done reading, you should be able to answer the following types of questions: - What is the ballot’s structure (does it allow for intraparty competition)? - How many votes does each voter get and are they cast at the party or candidate level? - When the election is over, to what level do votes “pool” (can votes for one candidate help another)? - How many seats are allocated in each district? By what rule or formula? Section 4 will help you think about the theoretically relevant consequences of these rules for important dimensions of the political system: - How do political parties or candidates interact with their (potential) supporters? - What types of campaigning activities do candidates or parties pursue? - What types of candidates are attractive to parties, and to voters? - How cohesive are party members in terms of legislative voting? - What kinds of parliamentary activities are important to legislators? - What is the process of government formation (e.g., coalitions, cabinet post distribution)? - How stable (long-lived) are governments? ELECTIONS IN HISTORY --> Will treat past elections where the electoral college vote was contested, or with resonating controversy. Roles and actions of the following branches in sequence: Executive Legislature Judicial The various perspectives, rulings and/or resolutions, progression. ELECTION ANALYSIS PAPER --> Imagine you are a country expert who has been asked to write a post-election analysis for the State Department, an NGO, or the news media. You will choose a specific election in some country, -Explain the electoral system -Describe the parties or candidates that contested the election -Discuss the outcome, focusing in particular on how the electoral system helped shape the results, and applying the key measures of analysis (e.g., indices of fragmentation, disproportionality and others) you have learned from the course. You may choose any election in any democracy after 2005 (the last year covered in PES, the main textbook), except for an election that is included in the readings or already extensively covered. The election case you choose must be approved by whatever assigned date. You must consult (and cite) a minimum of four sources, including at least one academic source––meaning a peer reviewed journal article or a book published by a major press. You may also make use of web-based sources, such as newspapers, specialized blogs, or data archives. In addition, it would be helpful to consult primary sources (e.g., government, NGO, or international organization publications about electoral systems or elections). Since the point of the election analysis is to advance an argument that helps the reader understand what was significant––in your considered judgment––about the election and the electoral system, your paper should have a clear thesis statement and your argument should be carefully developed with supporting evidence. Topics may include such questions as: --How did the electoral system shape the conduct of the campaign and/or the outcome of the election? --How might the results (i.e., the distribution of seats) have been different under a different electoral system? --Was there any coordination failure among parties or candidates? Why, and how did this affect the results? --Was some party or minority group advantaged or disadvantaged by the electoral system? --Would a reform of the electoral system help resolve some perceived problem related to the current electoral system? Students with more advanced statistical skills are welcome to analyse the raw election data, if such data are available, but this is not required. If you need help narrowing your topic, or finding information or data for the election you’ve chosen, please consult me. As you read about each country case, you should focus on getting the basics of the rules correct, and then thinking about how those rules help to determine which behaviours make the most sense for politicians and parties to pursue. The above types of questions may also help to motivate your response papers and class discussion. QUIZZES --> Quizzes will arise every 2 – 3 weeks. Pop quizzes can arise when participation and discussions are poor. ELECTIONS INTEGRITY (concerns week 14-15) --> Case Studies: vindicating findings or consensus view of past elections. Tools to assist with pursuits -- BBC – Vote Rigging: How to Spot the Tell-Tale Signs Wikipedia – Election Fraud Alvarez, R. M., Hall, T. E., & Hyde, S. D. (2008). Election Fraud: Detecting and Deterring Electoral Manipulation. Brookings Institution Press. Hicken, A. and Mebane, W. R. (2017). A Guide to Election Forensics. USAID, Research and Innovation Working Paper series Rozenas, A. (2017). Detecting Election Fraud from Irregularities in Vote-Share Distributions. Political Analysis, 25(1), 41-56. ASSESSMENT --> Discussion//participation Quizzes Elections Integrity Election analysis paper and presentation Topic Outline --> WEEK 1. Introduction and Orientation to the Topic WEEK 2. Interparty Effects I: Duverger’s Law WEEK 3. Interparty Effects II: Party System Fragmentation & Gov't Stability WEEK 4. Intraparty Effects I: Candidate Selection and Candidate Characteristics WEEK 5. Intraparty Effects II: Candidate and Legislator Behaviour WEEK 6. Single-Member District Systems WEEK 7. Proportional Representation I: Closed-List Systems WEEK 8. Proportional Representation II: Open and Flexible-List Systems WEEK 9. Ranked-Choice Ballots: Alternative Vote Systems and STV Systems WEEK 10. Electoral System Reform WEEK 11. Mixed-Member Systems WEEK 12. Japan: from Signal Non-Transferable Vote to a Mixed System WEEK 13. Electoral System Effects in New Democracies WEEK 14 – 15. Election Fraud Detection Prerequisites: Introduction to Computational Statistics for Political Studies, Upper Level Standing. Co-requisite: Comparative Politics Comparative Politics We study politics in a comparative context, not just to find out about other countries, but to broaden and deepen our understanding of important and general political processes. We do this by making systematic comparisons among political systems that are similar in many respects, but nonetheless differ in important ways. This allows us to analyse the effect of these differences in a careful and rigorous way, enriching our understanding of how politics works. Exams --> 3-4 typical exams to be administered Analysis Labs --> The Comparative Method Case Studies Qualitative Data Cross-National Quantitative Research There will labs procured for each method prior. A method will be assigned to a designated topics bundle. Following, groups are assigned countries sets for each method. Reports accompany labs. There may be labs where methods can be done comparatively later on chosen topics. Major Topics --> -Social contracts, constitutions & delivering expectations -How do prior existing environments (social, political, economic) shape the nature of a constitution and its separation of powers? -Democratization throughout history -Democracy Models -Government branches with checks and balances -Executive government structure, appointee process, power and limitations -Means of federal and/or provincial judicial appointments and confirmation -Federalism models -Comparative: federalism, unitary, confederations Disparities in constitutions; power distribution; judicial authority; regional economics, culture -Conservatism versus Liberalism. Foundations and characteristics -Tendencies for bipartisan politics -Political Instability (social, economic, political) -Non-democratic systems -Authoritarian rule (creation & causes, structure, preferences, economic welfare) -Proper size of government -Globalisation -Protectionism Prerequisites: Introduction to Computational Statistics for Political Studies, Upper Level Standing. Co-requisite: Comparative Electoral Systems

Public Policy Course Provides and Overview of the field of public policy, exploring its theories, processes, and applications in contemporary society. Students to examine the role of gov’t, stakeholders, and institutions in shaping public policy; as well as the impact of policy decisions on various societal issues. through case studies and real-world examples, students will develop analytical skills to comprehend, evaluate, and critique public policies. We will place the ideas from the readings into the context of past and present-day current events in politics. A step forward to becoming more politically critical, informed, and engaged citizens. OBJECTIVES --> -Comprehend the concepts of public policy and its significance in government. -Analyse the role of gov’t, interest groups , and other stakeholders in the policy-making process. -Examine and apply different models and theories of policy analysis and implementation. -Explore the impact of public policies on social, economic, an environmental issues. Develop critical thinking and analytical skills to evaluate and propose solutions to policy challenges. Feature Analysis --> At different times in the course for past and current (events and policies) groups of around 5 constituents will develop feature analysis Underlying Concepts: Why Focus on Public Policy; Determining legitimate stakeholders; Stakeholder Analysis; Types of Policies; Agenda Setting; Policy Preferences; Path Dependence; Policy Feedback; Power and Preferences. Underlying Challenges: Polarization and Policy Making; Provisionality & Non-Legislative Policymaking; Rights & Policy; Inequality & Representation; Visibility; The Policy State in a Constitutional System NOTE: some elements out of “Underlying Concepts” will need to be addressed. Models and Theory of Policy Making --> Applying models and theories of policy-making to model and analyse past or present policies: Rational Comprehensive model Incrementalism Advocacy coalition Framework Punctuated Equilibrium theory At different times in the course for past and current (events and policies) groups of around 5 constituents will develop models for past or present policies. NOTE: inevitably such 4 priors will need to be combined to gain insights and policy shaping. Policy Tools and Instruments --> At different times in the course for past and current (events and policies) groups of around 5 constituents will develop for past or present policies. For different types of policies (social, economic and environmental) students will identify policy tools and instruments within a programme theory framework. Literature --> Dunn, w. N. (2017). Public Policy Analysis: An Introduction. Routledge Bardach, E., & Patashnik, E. M. (2015). A practical guide for policy analysis: The eightfold path to more effective problem-solving. CQ Press. Additional assigned texts and journal articles Resources --> Gov’t record archives: Executive record. Documentation/literature/data from various elements of the branch. Municipal, provincial, national. Public Administrations: record, documentation/literature/data from various elements of the public sector or public administration. Municipal, provincial, national. Legislative action: bills & amendments. Bill cost estimation. Fiscal policy. Judicial record. Municipal, provincial, national. ASSESSMENT --> Class participation and engagement Feature Analysis Models and Theories of Policy-Making Policy Tools and Instruments COURSE TOPICS --> Introduction to Public Policy The Policy Making Process Policy Analysis and Evaluation Policy Implementation and Public Administration Models and Theories of Policy-Making Policy Tools and Instruments Social Policy Economic Policy Environmental Policy International and Global Policy issues Policy Evaluation Tools and Methods (overview) Transparency, coherency and practicality Prerequisites: Enterprise Data Analysis I & II, Introduction to Computational Statistics for Political Studies, Constitutional Law, Elementary Writing for Political Science, Advanced Writing for Political Science (for PA will be Public Administration Writing I & II instead of latter two) Public Policy Analysis This course provides an introduction to the issues and methods of public policy analysis. This course provides students with a “tool kit” of practical methods for analysing public policy issues. It develops a policy research and modelling skillset in considering complex, real-world issues involving multiple actors with diverse interests, information uncertainty, institutional complexity, and ethical controversy. Required Texts --> Munger, M. (2000). Analysing Policy: Choices, Conflicts, & Practices. W. W. Norton & Co. Wheelan, C. (2011). Introduction to Public Policy. W. W. Norton & Co. R Exercises Text --> Monogan, J. E. (2015). Political Analysis Using R. Springer International Publishing Literature for Term Projects (both will be applied) --> Patton, Sawicki, & Clark (2012). Basic Methods of Policy Analysis and Planning. Routledge Gertler, P. et al (2016). Impact Evaluation in Practice: Second Practice, World Bank Publications Resources --> Almanac of policy issues/agendas provides background information, archived documents, and links to major national public policy issues, organized the public policy of the sovereignty into the nine categories. Congression data (bills, bill estimator/estimation, etc.) Executive record, literature, data, etc. Public Sector administrations (record, literature, data, databases) Judicial Review/Record (if relevant) Tools --> R + RStudio Excel NOTE: prerequisite development and skills can come back to haunt. NOTE: students often may be asked to provide the following synopsis as a precursor for policy analysis: Conflict or plot Motives Policy Elements (issues, agendas, stakeholders, agencies) Policy Tools and Instruments Programme Theory Intended outcomes and incentives R Environment --> -Political Analysis with R (Monogan) Activities -R Exercises (to augment Monogan activities) --> 1.Using microdata to estimate the size of a population impacted by a policy or program. 2.Estimating the per-unit impact of a policy change or programme implementation. 3.Understanding the demographics of impacted populations, including demonstrating which populations are disproportionately impacted. 4.Accounting for uncertainty with sensitivity analysis Method Labs --> Applied hands-on set of assignments to reinforce methods introduced in the readings and lecture. These assignments will include spreadsheet-based tools and R programming to develop skills of analysis for public policy. Students are encouraged to bring their laptops to class to follow along with the instructor when demonstrations are provided, and/or take detailed notes that will help them. NOTE: from prerequisite will have advance recital of labs to be precursors to methods labs of this course. Specific designated lab(s) from prerequisite will be chosen that connects well to the method lab to be done. Prerequisite labs should only apply data that precedes the respective policy’s implemented date. Grading --> Methods Labs #1 – 8 40% R Environment 25% Political Analysis with R (Monogan) Activities R Exercises Term Projects 35% WEEK 1 Welcome & Syllabus (Weelan Chap 1) Introduction to Policy Analysis, Context & Overview (Munger Chap 1 pp. 3-29) WEEK 2 Policy Writing I (Dunn, W. (2012). Public Policy Analysis. Boston: Pearson. Chapter 8: Developing Policy Arguments. pp. 338-374) Policy Writing II & Methods Lab 1: Policy Writing Musso, J., Biller, R., & Myrtle, R. (2000). Tradecraft: Professional Writing as Problem Solving. Journal of Policy Analysis and Management, 19 (4) 635-646 WEEK 3 – 4 Market Failure I (Munger Chapter 3) Market Failure II (Munger Chapter 4, Wheelan Chapter 3 (3.1--3.4) Market Failure III. (Wheelan Chapter 4) Statistical Evidence for Policy Analysis (Wheelan Chapter 10, Wheelan Chapter 9 pp. 304-308) WEEK 5 Statistical Evidence for Policy Analysis (Wheelan Chapter 10, Wheelan Chapter 9 pp. 304-308) Methods Lab 2: Statistical Evidence for Policy Analysis WEEK 6 Practical Criteria: Politics (Wheelan Chapter 6, pp. 177-207) McConnell, A. (2010). Policy Success, Policy Failure and Grey Areas In-Between. Journal of Public Policy, 30(3), 345-362 WEEK 7 Practical Criteria: Designing Policy Alternatives [May, P. (1981). Hints for Crafting Alternative Policies. Policy Analysis, 7 (29): 27 – 44] Evaluative Criteria & Equity (Wheelan Chapter 5, pp. 139-170) WEEK 8 Methods Lab 3: Practical & Evaluative Criteria Forecasting for Policy Analysis Patton, Sawicki, & Clark (2012). Basic Methods of Policy Analysis and Planning. Chapter 7. Evaluating Alternative Policies: Forecasting Methods, pp. 244 - 257. Routledge WEEK 9 Midterm Review Midterm Exam WEEK 10 Methods Lab 4: Forecasting for Policy Analysis Discounting I: Risk (Munger Chapter 9, pp. 139-170) WEEK 11 Methods Lab 5: Risk Analysis (Munger Chapter 9, pp. 139-170) Discounting II: Time (Munger Chapter 10, pp. 322-347) WEEK 12 Discounting II: Time (Munger Chapter 10, pp. 322-347) Cost-Benefit Analysis I (Munger Chapter 11, pp. 352-378) WEEK 13 Cost-Benefit Analysis II (Munger Chapter 11, pp. 352-378) Augmented with: Monetised costs and benefits Non-monetised impacts analyses: amenity, aesthetics, environment, ecological, heritage, culture Non-Monetised Benefits Manual: Qualitative and Quantitative Measures, Waka Kotahi NZ Transport Agency 2020; costs analogy Tools like RIMS-II, IMPLAN, Chmura, LM3 or REMI may factor in. Campbell, H. and Brown, R. (2003). Benefit-Cost Analysis: Financial and Economic Appraisal Using Spreadsheets, Cambridge University Press, pp (194-220). Social Return on Investment WEEK 14 Methods Lab 6: Cost-Benefit Analysis WEEK 15 - 18 Applying/Developing policy implementation indicators Methods Lab 7: Policy Evaluation Tools Externalities Methods Lab 8: Externalities Adhikari, S.R. (2016). Methods of Measuring Externalities. In: Economics of Urban Externalities. SpringerBriefs in Economics. Springer Tying up loose ends Prerequisite: Public Policy Formulation & Implementation (check PA) Elements in Political Theory This course introduces you to political theory by tracing the history of the philosophical debate over the proper relation among (1) freedom, (2) citizenship and (3) economics. Note: course has both government appeasement option, social/society option and history appeasement option. Learning Objectives --> 1. To learn about the nature of political theory and the ways political theoretical thinking can enhance our capacities for critical reflection and democratic citizenship. 2. To understand how the concepts of freedom and citizenship have had multiple and sometimes conflicting meanings in the history of Western political thought. 3. To understand how the meanings of freedom and citizenship have varied in response to changing understandings of economics. 4. To strengthen our argumentative writing and command of English prose through careful practice. Note: written responses will have considerable role in course evaluation. There will also be a term paper. Literature --> Notable works in political thought, treatise, theses, journal articles, constitutions, judicial record (reviews and rulings), etc., etc., etc. Quizzes --> Will have quizzes on common knowledge, history, authors and their works, government, and a few court cases. Analysis Labs --> The Comparative Method Case Studies Qualitative Data Cross-National Quantitative Research There will labs procured for each method prior. A method will be assigned to a designated mandatory intellect concerns. Following, groups are assigned countries/regions sets for each method. Reports accompany labs. There may be labs where methods can be done comparatively later on chosen topics. Mandatory Intellect Concerns --> -Divine Right: rise, sustainability and fall -Feudalism: origins, socio-political structure, socio-economic structure, means of sustainability, challenges, decline -Emergence of capitalism in post feudal era Walery, S. (2006). Capitalism and Market in the Renaissance. L'Économie politique, 30, 87-112. Reinert, S. A. and Fredona, R. (2017). Merchants and the Origins of Capitalism, Harvard Business School Working Paper 18-021 What foundations gave merchants the will and security to practice price variability to all levels of society? How was such preserved? -Colonization and subjugation of native habitants or sovereign states Emergence and causes. Evolving socio-political and socoieconomic structure -Age of Enlightenment Origins. What major social reforms or conditions enabled such movements? Can anyone be a scholar in such era? Major ideas and interests. Challenge to the rule of nobility? Suppression attempts on ideas. Motives for rebellions Major Outcomes: Haitian Revolution, American Revolution and the French Revolution. Sociopolitical and socioeconomic change. Analysis of failures and successes between authority and constituents. -Liberties versus civil rights/equality -Emergence and sustainability of Abolitionism -Social Contract Sustainability & progression Identifying causes of failures -Forms of government Based on selection of governance; liberties versus civil rights/equality -Origins and Appeal of Democracy -Democracy Models Analysis on preference or establishment of types among different countries. Analysis of the branches of gov’t w.r.t. democracy model Liberties versus civil rights/equality -Is the influence of judicial branch stronger in direct democracy compared to other democratic models? -Social Institutions and influence in politics -Alliances: common values, class, wealth and interest groups in the makeup. Defining the notions of liberal and conservative? What makes a moderate What creates alliances among the societal spectrum? What destroys them? -Federalism Causes of strong federalism. Balancing interests and powers Reasons for variances: Switzerland, United States and other forms. -Democratic Sustainability -What is the true role of media in society? Is corporate media more trustworthy than state run media? -Socialism and its disparities with Communism -Political Economy: Socialism vs Capitalism Prerequisites: upper level standing, department permission Quantitative Analysis in Political Studies I This course provides an introduction to statistical methods for the political sciences (and Public Administration), with applications likely to be used in your research. To be able to apply methods to political science problems. This is not a “chalkboard/sharpie-board, pen and paper course”. NOTE: FOR YOUR OWN WELL BEING MIND YOUR DAMN BUSINESS AND DON’T GO STICKING YOUR NOSE ELSEWHERE. THIS IS NOT A MATHEMATICS DEPARTMENT COURSE. Upon successful completion of this course, participants will have acquired an understanding of: · Acquiring data from addresses, databases, file types, APIs. Introspection and queries (databases, APIs and file types) · how quantitative methods can contribute to study social and political phenomena, make inferences about relationships, and test theories · differences between experimental and observational data and implications for interpreting quantitative analyses · how to describe quantitative data · how to make inferences and test hypotheses using quantitative data · how to identify, assess, and interpret relationships among variables · the logic and assumptions of linear regression modelling · diagnostics of linear regression models · common problems in fitting linear regression models to empirical data · criteria for building and choosing models for empirical data · limitations of quantitative approaches to social science Participants will acquire practical skills in: · using software for data management, analysis, and creating presentable summaries of findings · documenting a workflow from beginning to end · building on a core set of skills to learn new tools and commands in other, subsequent courses NOTE: course will demand 18 weeks Materials --> Kabacoff, R. Quick-R. Available at statmethods.net. This website offers well-explained computer code to complete most, if not all, of the data analysis tasks we work on in this course. James E. Monogan III. 2015. Political Analysis Using R. Springer. Fox, J. and Weisberg, S. (2011). An R Companion to Applied Regression, Second Edition. Sage, Thousand Oaks. Field, A., Miles, J., and Field, Z. (2012). Discovering Statistics Using R, SAGE Publications, Thousand Oaks. Texts, notes, assignments, projects from prerequisite as review reference NOTE: students are welcomed to incorporate other R texts, such as those from Springer and CRC press. Articles --> Course will also make use of some PS/PA journal articles as a means for analysis and to build R computational environments IN THE INTEREST OF POLITICAL SCIENCE AND (PUBLIC ADMINISTRATION). Computing --> We will rely heavily on R and RStudio. Reproducible Computing --> All work you do as a social scientist, particularly any data analysis you use to reach conclusions, needs to be reproducible. To this end, our course puts special emphasis on techniques and tools that help you create reproducible research. Using scripts and data analysis notebooks are some of these tools. research, I recommend the following print books (not being course texts): Stodden, V., Leisch, F., and Peng, R. D. (2014). Implementing Reproducible Research. Chapman and Hall/CRC, Boca Raton, FL Gandrud, C. (2013). Reproducible Research with R and RStudio. Chapman and Hall/CRC, Boca Raton, FL Weekly assignments (20%) --> For assignments involving work in R, you have to submit these assignments as RMarkdown data analysis notebooks, along with analytical description using mathematical pallette in a word processor. Will be composed of both prerequisite assignments and current course assignments in each set. Two Take Home Midterms (30%) --> Also expect use of the R with RMarkdown, then converted to PDF format. Replication Project (25%) --> Replicating (or more precisely, reproducing) other scholars’ work is a key element of the scientific process. To engage with quantitative social scientific studies, you will replicate (reproduce) a study of your choice or from a list of suggestions using the methods you are learning in our course. This assignment will also give you some insight on how to conduct your own data analysis. By week 4, you need to identify a scholarly article from a PS/PA journal that uses quantitative methods (including multiple linear regression) and for which replication data is publicly available. After you send me the article, you will complete the following steps and turn in your final replication project by the beginning of class on week 12: 1. Retrieve the (replication) data for the article 2. Write an outline of your replication plan (template provided) 3. Write a replication script 4. Conduct the replication analysis of the main model in the article 5. Complete a replication memo, summarizing your findings (template provided) Research plan (20%) --> To facilitate your use of the methods learned in this course, you will compose a research plan that will help you write a publishable paper. This research plan is also similar to the type of document you would submit to pre-register a study at a journal. Your document needs to contain a summary of your research question, preliminary answer(s), research design, and a data analysis plan. You will submit this document (no more than 7 single-spaced pages) to me on designated due date. I will then send the document to a randomly assigned colleague for review. Topic Outline: 1.DATA ACQUISITION --> Acquiring data from addresses, databases, file types, APIs. Making data frames: introspection and queries. Basic data modelling review Research design. Questions and models. Experimental vs observational data. Using your computer as a scientific workstation Software skills: · Install R and RStudio · Install and load packages in R · Open, edit, and save an R script file · Begin a project in RStudio · Acquiring data from addresses, databases, file types, APIs. Making data frames: introspection, structuring and wrangling · Basic data modelling · Open and compile a template for an RMarkdown data analysis notebook in R · Converting to PDF · In-class Assignments concerning intro to R 2.DESCRIPTIVE STATISTICS Software skills: · Accessing a dataset in Excel/Open Office/Google Docs/csv · Dataset from an external source (APIs, governenment agencies, IGOs, Kaggle, etc. etc.) · Making data frames: introspecting datasets (based on prior two), and queries on dataset into R. Data Wrangling. · Summarize variables and datasets · Statistical methods for fraud detection · Create a well-designed, editable document with descriptive statistics and graphs. Will also treat more general data sources and formats towards R. 3.PROBABLITY & DISTRIBUTIONS Review of Probability Axioms Simulating random variables with data Review of ideal distributions and their properties Evaluate ideal probabilities (various interval types) Software skills: · Plot a distribution with histograms, density plots for ideal distributions · Plot a distribution with histograms, density plots with real data · Plots with both histograms and densities in display · PP plots for real data · QQ Plots for real data . MLE and MoM for real data · Sample data from a distribution (general) · Plot cumulative distributions · Document and organize code 4.INFERENCE & HYPOTHESS TESTING Software Skills · Reinforcement of descriptive statistics generation upon data (both real raw data and simulated) · Skew and Kurtosis · Box Plot · Histograms · Density Plots · P-P and Q-Q · Methods of finding point estimates MLE, MoM, Method of Least Squares · Calculate and plot confidence around a mean. If not normal, then what? · Comprehending critical values for real raw data sets · Advance repetition of Goodness-of-Fit module from prerequisite · Hypothesis Testing in R When we get to hypothesis testing we are and not concerned with zombie problems. What’s important is how it’s meaningful to you with your endeavours in PS and PA. Majaski, C. (2021). Hypothesis Testing. Investopedia NOTE: all prior modules (1-3) will be reinforced before applying hypothesis testing. NOTE: topics with means and variances are strictly for the following topics: comparative analysis, policy evaluation, quality assurance, and predictive modelling. Will apply real world data with such topics...NO EXCEPTIONS...NO EXCUSES....RAW LIKE SUSHI. Note: mean and variances are not appropriate for Impact Evaluation; calm your backsides down. 5. ASSOCIATION BETWEEN VARIABLES Software skills: · Correlation types types. Correlation matrices and heat maps. · Chi-Square for categorical variables and ordinal variables (association among variables, contingency tables development, homogeneity, variances) · Fisher Exact Test as alternative to prior concerning association. 6.BIVARIATE REGRESSION Software skills: · Refresher of data acquisition from wherever and management · Refresher of summary statistics development · Create a scatterplot of two variables with a line of best fit · Calculate the correlation coefficient of two variables · Estimate a linear regression model with one predictor · Create a residual plot · Summary statistics of regression modelling · Summarize and present regression results in a well-designed document 7.DATA MANAGEMENT Software skills: . Making data frames involving various data types (and probing data) · Import datasets from different sources into R (and probing data) · Clean a dataset for data analysis: making data frames from raw data sets or prior data frames. · Descriptive statistics again · Statistical methods for fraud detection · Merge datasets with a common identifier · Collapse a dataset 8.MULTIPLE REGRESSION Software skills: · Selecting Variables · Estimate a regression model with multiple predictors . Summary statistics interpretation · Heteroskedasticity · Present regression results graphically · Calculate standardized regression coefficients · Summary Statistics review · Forecasting & Error · Training & test sets · “Holding a value constant” and marginal effect 9.DEALING WITH UNUSUAL & INFLUENTIAL DATA Software skills: · Diagnose outliers. What you call an outlier, why is it an outlier? · Assess outliers, leverage, and influence in one combined plot · Hat-values · Studentized residuals · Cook’s D statistic · Create added-variable plots · Missing Data (To implement) Kang H. (2013). The Prevention and Handling of the Missing Data. Korean J Anesthesiol. 64(5): 402-6 Dong, Y., Peng, CY.J. (2013). Principled Missing Data Methods for Researchers. SpringerPlus 2, 222 NOTE: if any regression technique is to be applied data probing must be involved to avoid the often-naive assumption of OLS/WLS/GLS. 10.DIAGNOSING & DEALING WITH VILATIONS OF OLS ASSUMPTIONS, INCLUDING ENDOGENEITY Software skills: · Conduct numerical and graphical checks for violations of the OLS assumptions · Create component-plus-residual plots · Transform variables · Calculate variance inflation factors · Calculate “robust” standard errors for a regression model 11.MODERATNG RELATIONSHIPS: INTERACTION TERMS (module 10 will resonate) Terms to know (terms not necessarily expressed in desired learning order): Dummy variable, dichotomous, polytomous, interaction term, constitutive terms, principle of marginality, centring variables, marginal effects Software skills: · Estimate linear regressions with interaction terms · Present and interpret interaction terms numerically and graphically · Create marginal effects plots for interactions (margins package) 12.MODEL FIT, MODEL CHECKING, FUNCTIONAL FORMS, VARIABLE SELECTION (modules 10 & 11 will resonate) NOTE: relevance of module 8 is required. Software skills: · Adjusted R 2 · Variance Inflation Factor · Simulate predicted data from a developed regression model · Compare simulated and observed data · Assess model fit with numerical and graphical methods · Transform variables · Marginal effect (margins package) 13.GENERALISED LINEAR MODELS Response variables: Categorical and Dichotomous Linear probability model, Probability of the response (π), Linear predictor Transformations (logit or probit). Unobserved/latent variable formulation exp(Xβ)/1+exp(Xβ), Maximum likelihood estimation, Deviance, Log-likelihood Separation/separability. Ordered logit and probit, Multinomial logit. Software skills: · Note: applications concern political science, political economy and social datasets . Test for independence among categorical variables (Chi-Square test and Fisher Exact test upon your developed contingency tables) · Use of stats{glm function}, glmnet, GLMcat packages · Estimate generalized linear models using maximum likelihood . Summary statistics glm models · Present estimates using predicted outcomes (probabilities) · Diagnose problems with generalized linear models · Marginal effect (margins package) Prerequisite: Introduction to Computational Statistics for Political Studies Quantitative Analysis in Political Studies II This course extends what you did in previous courses by focusing more on nonlinear model forms: "generalized linear models," or "maximum likelihood models." In this course we’re highly concerned with how to adapt the standard linear model that you know so that a broader class of outcome variables can be accommodated. These include: counts, dichotomous outcomes, bounded variables, and more. There is a some theoretical basis for the models that we will use. Also, the bulk of the learning in the course will take place outside of the classroom by reading, practicing using statistical software, replicating the work of others, and doing problem sets. Keep in mind that the skills attained in this course are those that the discipline of political science expects of any self-declared data-oriented researcher. Use of the statistical environment R in conjunction with RStudio. NOTE: some weekly lectures will involve code analysis and building. Grading --> Problem sets (40%) Real world tasks (35%) Use of political data [polls, elections, policy, legislative, executive, executive administration (offices, departments, agencies, bureaus), IGOs, etc., etc.] to characterise and for model development (ambiance, foreign and international), and forecasting. Use of economic data from gov’t (offices, departments, agencies, bureaus) and IGOs to characterise and for model development, and forecasting. Assigned journal articles for replication and inclusion of modern data An exam on MLE theory and basic models (25%) Problems Sets --> A. Problem sets will include software skills, projects tasks and assignments done in prerequisite to stay fresh. B. Course problem sets will be a combination of analytical and software computational assignments based on lecturing. Real world tasks and replication assignments --> For assigned published works to analyse, obtain the data, and critique/compare with other models and the results. Articles to use available datasets (COW, national election studies, GSS, Kaggle, gov’t, IGOs, etc.), but some authors are forthcoming about distributing their data if asked. If it’s necessary to take on the task of cleaning and structuring raw data, they will receive extra credit (up to a 10% boost). References --> Faraway. Extending the Linear Model with R: Generalized Linear, Mixed Effects and Nonparametric Regression Models. Chapman & Hall/CRC Faraway. Linear Models with R. Chapman & Hall/CRC Monogan, J. E. (2015). Political Analysis Using R. Springer Materials, texts assignments and projects from prerequisite Topic Outline --> WEEK 1. Uncertainty, Inference, and Hypothesis Testing Misconceptions of the loss function: rhetoric of significance tests Insignificance of null hypothesis significance testing Problem Set # 1 WEEK 2. The Likelihood Model of Inference Binomial PMF likelihood grid search Model syntax summary Problem set # 2 WEEK 3. Models for Dichotomous Outcomes Homework: Prereq refresher exercise set Faraway, Chapter 2, Exercises 1-7. For Exercise 2.2, download the wbca.txt data from Faraway, Chapter 2, Exercises 1-7. For Exercise 2.2, download the wbca.txt data from http://www.maths.bath.ac.uk/~jjf23/ELM/. Also for Exercise 2.2, do not use the step function in part (b), use your own intuition) Find a datasets with a dichotomous outcomes that you are interested in. Run an appropriate glm model in R and submit the output with a paragraph defending the variables and model fit. WEEK 4. Models for Count Outcomes Homework: Prereq refresher exercise set Faraway Chapter 3, Exercises 1-7 WEEK 5. Models for Contingency Tables Homework: Prereq refresher exercise set Faraway, Chapter 4, Exercises 1-7 WEEK 6. Models For Ordered and Unordered Categorical Data Homework: Prereq refresher exercise set 1. Faraway Chapter 5, Exercises 1-6. 2.Consider a proportional odds model using the logit link function with only one explanatory variable in addition to the constant. Express the odds ratio (i.e. not-logged) for a one-unit change in the explanatory variable. What does this simplify to? WEEK 7. EXAMINATION (analytical and computational mixture) WEEK 8. How to Handle Missing Data in Models. The EM Algorithm and Multiple Imputation Problem Set WEEK 9. The GLM Theory and the Exponential Family Form Homework: Prereq refresher exercise set Faraway Chapter 6, Exercises 1-5 WEEK 10. Other GLMs, Quasi-Likelihood Estimation Homework: Prereq refresher exercise set Faraway Chapter 7, Exercises 1-7 LAST INSTRUCTION WEEK. Random Effects. Homework: Prereq refresher exercise set Faraway Chapter 8, Exercises 1-9. WEEK 11. Finishing and turning in replications. WEEK 12. Discussion of replications. Prerequisite: Quantitative Analysis in Political Studies I Political Economy Politics posits a large role for economics in determining political outcomes, and economics suggests a central role for policy in the workings of markets. Political economy attempts to make these connections explicit, by treating economic and political outcomes as interdependent and endogenous. Insights and lacuna that arise in using economic methodology, including formal models and regression analysis, to analyse political phenomena and interactions between the economic and political systems. Course makes use of 16 - 18 weeks, 3 days per week, 2 hours per day. First two days are dedicated to the lecturing text, for analysis and debates. Third day in each week is dedicated to given journal articles for analysis and development; students are responsible for R development, but instructor can give logistical advise. Lecturing text --> Stilwell, Frank, (2011). Political Economy: The Contest of Economic Ideas, Oxford University Press Expected in environment--> Inherent empirical challenges that arise in attempting to assign causality or interconnectedness among economic and political variables. Moderate Debate. Software --> For the empirical exercises you’ll be working with data. You will use R to work with data. Packages of one’s choice to be used. Inquisitions on models expected. Succession: make data/computational adjustments concerning ambiances of interest and time frames throughout. Class Participation (10%) --> A big part of the course is talking about what you read. You’ll should read the stuff for that meeting carefully and think about them in depth before coming to class. In-Class Quizzes (25%) --> Quizzes concern development from the lecturing text. The quizzes will be graded on a 0-1-2 basis, and I will drop your lowest two grades. Empirical Research Group Term Project (35%) --> Parker, D. and Kirkpatrick, C. (2012). Measuring Regulatory Performance: The Economic Impact of Regulatory Policy - A Literature Review of Quantitative Evidence. OECD Expert Paper No. 3 -When using a word processor use of mathematical pallette is also expected. -Word processor document must also be converted to pdf document. -All priors will be complimented by development in the R environment. Proper headings, structure, etc. R development must have sensible commentary with computational development. Models critique expected. Also must be converted to pdf document via rmarkdown. Data sources and database lists will be provided, where hints on structuring troublesome data to be encountered may be provided. PART A - the above expert paper will be used to investigate the impact of a regulatory policy via Causal Chain Analysis development for assigned policy in ambiance. Computable General Equilibrium use to be omitted since course is primarily geared towards political science students. PART B - for section three of the expert paper groups, will be assigned comparative assessment among 2-3 highlighted literature out of the many. Objective of each paper, methodology, logistics, replication and so forth. Note: the WBG Doing Business Index has been discontinued, but hopefully the index and data are archived. PART C - Impact Evaluation Designs Gertler, P. et al (2016). Impact Evaluation in Practice: Second Practice, World Bank Publications Groups will apply the same regulatory policy from part A, but with chosen method(s) from Gertler, P. et al 2016, then compare to findings from part A. Empirical Exercises (30%) --> Empirical exercises will be based on all given journal articles. Expected will be development in R where computational development is complimented by commentary. Via Rmarkdown to convert development into pdf files. It may be inevitable that data sets include modern data as well, thus changing analysis and conclusions. Hence, to first develop with data range used by articles, then extending with more modern data. You will work in small groups (3 or 4) and hand in a single common development. 1.Economic effects of Constitutions Mueller, D.C. (2007). Torsten Persson and Guido Tabellini, The Economic Effects of Constitutions. Constit Polit Econ 18, 63–68 Persson, Torsten & Tabellini, Guido. (2004). The Economic Effect of Constitutions. MIT Press, 306 pages 2.Human Development Baum, M., & Lake, D. (2003). The Political Economy of Growth: Democracy and Human Capital. American Journal of Political Science, 47(2), 333-347 Allan Drazen (2008). Is There a Different Political Economy for Developing Countries? Issues, Perspectives, and Methodology, Journal of African Economies, Volume 17, Issue suppl_1, Pages 18–71 Ullah, S. Azim, P. and Asghar, N. (2014). Political Economy of Human Development: An Empirical Investigation for Asian Countries. Pakistan Economic and Social Review, 52(1), 75-97 3.Measuring Social and Political Requirements for System Stability in Latin America Duff, E. & McCamant, J. (1968). Measuring Social and Political Requirements for System Stability in Latin America. The American Political Science Review, 62(4), 1125-1143. 4.Democratization Jay Ulfelder & Michael Lustik (2007) Modelling Transitions To and From Democracy, Democratization, 14:3, 351-387 Teorell, J. (2010). Determinants of Democratization: Explaining Regime Change in the World, 1972–2006. Cambridge: Cambridge University Press Thomas Mustillo (2017) Party Nationalization Following Democratization: Modelling Change in Turbulent Times, Democratization, 24:6, 929-950 5.Political Preferences -Formation of political preferences -Measurement of political preferences Epstein, L., & Mershon, C. (1996). Measuring Political Preferences. American Journal of Political Science, 40(1), 261-294. 6.Rent Seeking -From public commodity to favouring the financially stable Causes and resolutions with negative externalities mitigation -From lobbying to subsidies, grants and tariff protection -Limiting competition or creating barriers to entry -Economic rents sans added productivity or capital at risk -Occupational Licensing Journal Articles Spindler, Z. A (1990). A Rent-Seeking Perspective on Privatization. North American Review of Economics and Finance, Volume 1, Issue 1, Pages 87-103 Pecorino, P. (1992). Rent Seeking and Growth: The Case of Growth through Human Capital Accumulation. The Canadian Journal of Economics, 25(4), pages 944-956 Pedersen, K.R. (1997). The Political Economy of Distribution in Developing Countries: A Rent-Seeking Approach. Public Choice 91, 351–373. Khwaja, Asim, and Atif Mian. 2011. “Rent Seeking and Corruption in Financial Markets”. Annual Review of Economics 3 (1): 579-600 Sections 3 and 4 serve well towards research and model building 7.Elections and Government Spending Comparative analysis to draw conclusions: Dewan, T. and Shepsle, k. A. (2011). Political Economy Models of Elections. Annual Review of Political Science 2011 14:1, 311-330 Adi Brender, Allan Drazen (2013). Elections, Leaders, and the Composition of Government Spending, Journal of Public Economics Volume 97, pp 18-31 Drazen, A. and Eslava, M., Electoral Manipulation via Voter-Friendly Spending: Theory and Evidence. Journal of Development Economics 92 (2010) 39–52 8.Size of Government and Economy -What are the significant qualities for identifying economic strength? Students will pursue hypotheses and try to acquire consistent data to model and test. -Various methods for measuring the size of government -For the following articles, analyse, model critique, then replicate/confirm or compare with model preference with results and forecasting. Then for other ambiances where data with modern extension is accessible. Altunc, O. F. and Aydin, C. (2013). The Relationship Between Optimal Size of Government and Economic Growth: Empirical Evidence from Turkey, Romania and Bulgaria, Procedia - Social and Behavioral Sciences 92, 66 – 75 Cetin, M. (2017). Does Government Size Affect Economic Growth in Developing Countries? Evidence from Non-Stationary Panel Data, Euro. Journal of Economic Studies, 6(2) 9.Determinants of Institutional Quality Borner, S. et al. (2004), Institutional Efficiency and Its Determinants: The Role of Political Factors in Economic Growth. OECD José Antonio Alonso, Carlos Garcimartin & Virmantas Kvedaras (2020), Determinants of Institutional Quality: An Empirical Exploration, Journal of Economic Policy Reform, 23:2, 229-247 10.The Design and Use of Political Economy Indicators Banaian, K. & Roberts, B. (Eds.). The Design and Use of Political Economy Indicators: Challenges of Definition, Aggregation, and Application, Palgrave. Are conclusions drawn from political economy indicators parallel to conclusions drawn from WB Development Indicators? 11.Regional Integration Applications A. Matthews, A. (2003). Regional Integration and Food Security in Developing Countries. Food and Agriculture Organization of the United Nations B. Articles to analyse, and then make use of ambiance data of interest with possible inclusion or more modern data (CC, EC, EU) Genna, G. M. & Hiroi, T. (2004). Power Preponderance & Domestic Politics: Explaining Regional Economic Integration in Latin America & the Caribbean, 1960-1997. International Interactions. 30(2):143-164 Feils, D.J., Rahman, M. The Impact of Regional Integration on Insider and Outsider FDI. Manag Int Rev 51, 41–63 (2011) 12.Regulatory Competition Regional choices and data can be adjusted Malone, T., Koumpias, A. M., & Bylund, P. L. (2019). Entrepreneurial Response to Interstate Regulatory Competition: Evidence from a Behavioural Discrete Choice Experiment. Journal of Regulatory Economics, 55(2), 172–192. Zheng, D., Shi, M., & Pang, R. (2021). Agglomeration Economies and Environmental Regulatory Competition: Evidence from China, Journal of Cleaner Production, Volume 280, Part 2, 124506 Mazol, A. (2021). Jurisdictional Competition for FDI in Developing and Developed Countries. Free Policy Network Brief Series 13. Despotism One may also have their competing models to validate and test alongside those given in the articles (modern data inclusion expected): Cheibub, J.A., Gandhi, J. & Vreeland, J.R. Democracy and Dictatorship Revisited. Public Choice 143, 67–101 (2010). Haggard, Stephan; Kaufman, Robert R. (August 2012). "Inequality and Regime Change: Democratic Transitions and the Stability of Democratic Rule". American Political Science Review. 106 (3): 495 – 516 Ristei, Mihaiela; Centellas, Miguel (2013). The Democracy Cluster Classification Index. Political Analysis. 21 (3): 334–349. Prerequisites: Intermediate Macroeconomics, Quantitative Analysis in Political Science I Survey Research Course Literature (IN UNISON) --> Singleton, R. A. & Straits, B. C. (2017). Approaches to Social Research. New York: Oxford University Press Lumley, T. (2010). Complex Surveys: A Guide to Analysis Using R, Wiley Tools and Resources --> R + RStudio Microsoft Office 365 United States Office of Management and Budget (OMB) Standards & Guidelines for Statistical Surveys - https://www.samhsa.gov/data/sites/default/files/standards_stat_surveys.pdf Code of sound and ethical practice in the conduct of public opinion and survey research, and promoting the informed and appropriate use of research results. Assessment --> Quizzes Written Responses/Analyses R Labs Statistical Tools for Survey Research (highly demanding and data subject to change) Survey Strategies Survey Critique Questionnaire Design Writing a questionnaire for a benchmark survey Proposed experiment & semester-long project in which students are expected to develop, pilot test, analyze and evaluate their own survey instruments Prerequisites: Advance Writing for Political Science; Quantitative Analysis in Political Studies I & II; Senior Standing Methods of Political Analysis Course will focus on three related issues: 1) how authors in political science and in related fields convince their readers of the validity of their theories; 2) how the reader can distinguish between convincing and unconvincing research; 3) how one can design their own research to be as convincing as possible. In this course, students should develop a taste for criticism: that is, not believing things written only because they have been published, but in evaluating the evidence presented; in being skeptical, yet fair. This last skill will be most appreciated when you begin to design your own research projects in this course and in later years. Applied Texts --> King, Gary, Robert O. Keohane, and Sidney Verba. 1994. Designing Social Inquiry: Scientific Inference in Qualitative Research. Princeton: Princeton University Press. Frankfort-Nachmias, Chava and David Nachmias. 1999. Research Methods in the Social Sciences, Sixth Edition. New York: St. Martin’s. NOTE: other literature will apply throughout When relevant, all literature should be read with three questions in mind, questions to which we will return constantly in class, and which should be the topics of your papers: 1) What is the author’s argument or theory, and how does it compare to alternative theories that might be proposed or have been proposed by others? 2) What evidence does the author provide, and how convincing is it? and 3) How could the research be improved? Also of particular interest will be the question of alternative theories: has the author of a given theory not only convinced you that her theory makes good sense, but also that rival explanations have been eliminated? Short Papers --> There will be a series of short papers throughout the term, assigned in such a way that several students will have assignments each week on a rotating basis. Each week’s discussion, therefore, will benefit from a number of students who have been assigned to write papers on particular topics. These short papers should not be summaries of the readings. Rather, they should take issue with the author(s) on some particular question, discuss what potential problems arise from what the author(s) did, and propose an improvement. You should not spend time on generalities, but should go quickly into the particulars. After stating the general problem, spend some time discussing the particular mistake or unforeseen implication of what the author did, then discuss how to make improvements. Also discuss how this change might be related to any possible changes in the substantive conclusions of the article. In class discussion, you may be asked to summarize the reading and to begin the discussion on problems and improvements. Term Paper --> There is a term paper, due on the last day of class, with a preliminary draft due approximately one month before. This paper will be a large version of the short papers. In it, you need to: 1) choose a limited area of research that interests you; 2) identify some empirical studies that have been done on that topic, using contrasting methodological approaches; 3) evaluate these studies and their methodologies, discussing the strong and weak points of each approach, and linking these to the theory being tested; and 4) propose a theory, a research design, and a set of measurements that would be the best possible way to answer your question. You should go into detail on the proposed theory, the research design, measurements, availability of evidence, and any other important points. The topic may be anything from political science that interests you (you may want to choose a topic that interests you enough to follow up on, for example in your other statistics, methods, or substantive courses this or next semester). The literature review does not have to be all-inclusive; rather the important point is that it include examples of different approaches (case study, longitudinal design, cross-sectional comparison, experimental study, for example), so that you can discuss the strong and weak points of each approach. Your discussion of the literature should show what problems have plagued researchers in the past, and your proposal obviously should do away with those problems. You should be able to do this in about 25 pages or so. Assessment --> 40% Total combined for short papers 40% Term paper 20% Class participation Course Outline --> PART ONE: Introduction and Review 1. The Scientific Approach. The importance of being wrong; the nature of scientific explanation; the nature of evidence; what is convincing to a scientist; how evidence accumulates; what is “proof.” We will return to some of the philosophical questions of this approach during the last week of the term. For now, the focus will be on developing a shared vocabulary and an understanding of the process. Note how these ideas apply to quantitative and to qualitative research projects. Nachmias, Ch. 1-4. KKV Ch. 1-3. Stinchcombe, Arthur L. 1968. Constructing Social Theories. Chicago: University of Chicago Press, 1968. Ch. 2: The Logic Of Scientific Inference Pp. 15-56. 2. Review of statistical concepts and terminology Topics to review include: measures of central tendency and of dispersion; Z-scores; bivariate measures of association. We will go into some detail about Proportional Reduction in Error, a concept that comes up again and again during the term. We will return constantly to questions of covariance throughout the term, so you need a good understanding of both the underlying statistics and the conceptual ideas behind them. Finally, we will discuss some basics of sampling vocabulary including the concept of “statistical significance.” Obviously, all this material cannot be covered in a single discussion, so emphasis here will be on creating a list of things you should already know or pick up during the term. Nachmias, Ch. 15, 16, and skim ch. 17. King, Gary. 1989. Unifying Political Methodology. New York: Cambridge University Press. Chapter 1: Introduction. PART TWO: Research Design Questions 1. Experiments and Quasi-experimental designs. This week focuses on designing a research project so that covariance, time-order, and spuriousness can be controlled or demonstrated. Time-series, cross-sectional designs, experimental designs, and a wide variety of other techniques are described. Note especially the numerous generic threats to validity that Campbell and Stanley lay out. KKV explain how these relate to qualitative as well as to quantitative designs. Nachmias makes it easier to understand. Nachmias, Ch. 5, 6. KKV Ch. 4-6. Campbell, Donald T. and Julian C. Stanley. 1963. Experimental and Quasi-Experimental Designs for Research. Chicago: Rand McNally. 2. Quasi-experiments and other examples from the literature. Consider the strength of these designs, and discuss whether the authors could have reached similar conclusions if they had chosen different designs. Will incorporate various journal articles as applications 3. Game Theoretical Approaches. Gates and Humes provide an overview and some detailed examples of the uses of game theory in political science Gates, Scott and Brian D. Humes. 1997. Games, Information, and Politics: Applying Game Theoretic Models to Political Science. Ann Arbor: University of Michigan Press. PART THREE: Measurement Issues 1. Measurement terminology; tests for reliability and validity; basics of designing good measures that tap the concepts they are supposed to tap; how to recognize measures that do not measure what they say they measure; systematic versus random measurement error and their consequences; building indices combining multiple measures into a single scale. Nachmias, Ch. 7, 11, 12, 18, skim ch. 9 2. Sampling; Survey design. Many measurement issues are here, specific to surveys this week, but also apparent in other types of research. Also sampling procedures and the importance of sampling error as opposed to other types of error in most work that involves sampling, such as surveys. Note the differences and similarities between mass surveys, elite surveys, and mail questionnaires, and pay attention to how one creates a sampling frame and ensures a high response rate. Nachmias, Ch. 8, 10 Will also apply chosen journal articles 3. Cross-Level Inferences, Ecological Analysis; summary and review of material covered so far. Robinson, W. S. 1950. Ecological Correlations and the Behavior of Individuals. American Sociological Review 15: 351-7. Naroll, Raoul. 1973. Galton’s Problem. In: A Handbook of Methods in Cultural Anthropology. New York: Columbia University Press, pp. 974-89. Achen, Christopher H. and W. Phillips Shively. 1995. Cross-Level Inference. Chicago: University of Chicago Press. Chapter 1: Cross-Level Inference. King, Gary. 1997. A Solution to the Ecological Inference Problem. (Princeton: Princeton University Press), chapter 1, “Qualitative Overview.” PART FOUR: Evaluating Prominent Research Projects In this section of the course you will apply the various critical skills you’ve acquired to evaluating a series of prominent and influential works in the literature. Your papers and class discussion will focus on exactly what the authors did, how they designed their project, how they measured relevant variables, how they considered rival hypotheses as well as their own, how they gathered their data, and all other elements of the research project. In addition to pointing out the consequences of the choices that scholars made, in each paper you should suggest alternative ways to design a research project on the same topic and discuss the relative merits of the various approaches. 1. Experiments in political science Will apply chosen articles and literature PART FIVE: Paradigms, Approaches, and Professional Controversies 1. Kuhn’s theory of the nature of scientific progress; some current disputes in the discipline. Kuhn, Thomas S. 1970. The Structure of Scientific Revolutions. Chicago: University of Chicago Press. Ch. 1,2,6,7,9. Almond Gabriel A. and Stephen J. Genco. 1977. Clouds, Clocks, and the Study of Politics. World Politics 29 (4): 489-522 Prerequisites: Comparative Politics; Constitutional Law; Advance Writing for Political Science; Quantitative Analysis in Political Studies I & II; Senior Standing FOR ACTIVITIES IN THE “SUMMER” AND WINTER” SESSIONS ALL PARTICIPATING STUDENTS, ASSISTING/ADVISING INSTRUCTORS AND PROFESSORS MUST BE OFFICIALLY RECOGNISED; REQUIRES BOTH CIVILIAN ID AND STUDENT/FACULTY ID FOR CONFIRMATION OF INDIVIDUAL. THERE WILL ALSO BE USE OF IDENTIFICATIONS FOR ACTIVITIES FOR RESPECTIVE SESSION. SECURITY AND NON-PARTICIPATING ADMINISTRATION WILL ONLY IDENTIFY RESPECTIVE ACTIVITY BY IDENTIFICATION CODE. SECURITY AND NON-PARTICIPATING ADMINISTRATION MUST NEVER KNOW WHAT ACTIVITIES IDENTIFICATION CODES IDENTIFY: < Alpha, Alpha, Alpha, Alpha > - < # # # # # > - < session > - < yyyy > Such activities will also warrant criminal background check (CBC) in order to participate. Severely threshold may vary depending on administration. Administrators will provide dated letters of confirmation of thorough CBC to student affairs and other appropriate administration. Such also may include screening that’s parallel to customs & immigration processing where certain levels of criminal history warrants rejection. Email and physical letters with data. Such CBC protocol will not explicitly identify any particular titles or descriptions of any activity, rather, will only convey code as above. Activities repeated can be added to transcripts upon successful completion. Repeated activities later on can be given a designation such as Advance “Name” I, Advance “Name” II. As well, particular repeated activities serve to towards developing true comprehension, competency and professionalism. Activities will be field classified. Secured Archives. It may be the case some activities can be grouped and given a major title together; however, detailed descriptions will be required. Policy Analysis Open to PS and PA students Advance treatment of the skills and tools from the following courses: Phase 1- Public Policy Formulation & Implementation (check PA) Phase 2- Public Policy Analysis (check PS) Observation and analysis of politics venues Activity serves both Political science and Public Administration students. Note: open to both PS and PA students Analysis of resonating political ideologies, conjectures, hypotheses and legality based on conflict, law and rulings with governance. To attend/observe negotiations, conferencing, public hearings, town hall meetings, political debates, executive branch public correspondences, congressional public correspondences, judicial committee hearings and so forth. Concerns local, national and international events. For certain venues above one must understand that they may neither be able to attend nor observe directly such venues. Rather, acquisition of intelligence: data, literature, media. Pre stages and post stages intelligence. Nevertheless, attending venues will still be pursued granted that scheduling and travel logistics are pleasant and economical. For public administration constituents such commerce allows for a direct observation and assessment of the projection of tones and policy of various political and public administrative elements. Note: activity is in no way partisan sponsored nor influenced. FIELD POSSIBILITIES: A. Political calendar, updates on contested seats, nominations (legislative, executive and judicial) B. Diplomatic polices or executive orders or policies in function with government constituents or representatives. Consider various levels in bureaucracy C. Political current events D. Security/emergency management and decision making E. Bills introduced or ratified F. Public Advocacy entities G. International diplomacy concerning protocols, agreements, etc. Key subjects will be identified with the relevant gov’t agencies, commissions, etc. ASSUMPTIONS Preparatory Prepare questioning and possible themes to encounter Atmosphere As well, arising themes from respective conflict and/or parley. Significant entities in dialogues/conveyances may need to be cited. Arising questions based on dialogue and tones. All questions should be preserved whether answered or not. Note taking or recording Developments must be preserved, archived. Such serves towards recollection, future investigations, cross referencing, etc. Legal grounds: analysis of credibility/validity of major forces concerning respective interests. Professional literature, government resources and data will naturally apply. ELEMENTS EXPECTED THROUGHOUT: 1. Fact checking 2. Use of data when required (includes data validation/accuracy) 3. Comprehension and legal justification of arguments/positions 4. Cost benefit analysis, impact evaluation and environmental impacts Case of competing ideas/proposals Case of implemented policies 5. Bureaucratic Record, Literature, Tools and Data (when relevant) Constitutional, legislative, executive (leadership, offices, branches), judicial, IGOs Municipal, Provincial, Autonomy, National, etc. 6. Citations and references --Phases of commerce engagement SUBJUGATED BY “ASSUMPTIONS” and "ELEMENTS EXPECTED THROUGHOUT” (1) First phase Conflicts and settings. Students must identify the conflict timeline, agents and LEGITIMATE stakeholders. Agencies and stakeholders relations Relevance and self-interests, respectively; possible instruments to deter moral hazard (2) Second phase I. Setting The policy or position(s) or stance(s) of a respective sovereignty or unique governance or entity/agent or among the different legitimate stakeholders must be analysed; followed by programme theory (if practical). Students must establish all the considerable historical factors and stimuli leading to the issues at hand. Students must identify the possible (or observed) social, economic and political ramifications (for policy, position, stance or choice); there may be counterfactuals for each ramification. II. Decision Theory Spector, B. I. Chapter 3. Decision Theory: Diagnosing Strategic Alternatives and Outcome Trade-Offs. pp 73 – 94. In: Zartman, I. W. (Editor). 1994. International Multilateral Negotiation – Approaches to the Management of Complexity. Jossey – Bass, Inc. III. Negotiation Models Druckman D. (2007) Negotiation Models and Applications. In: Avenhaus R. and Zartman I. W. (eds) Diplomacy Games. Springer, Berlin, Heidelberg IV. The prior two literature to be applied Note: data will be invaluable to apply structuring/models, and to make sense of options, positions and probabilities. Components for such tasks are: V. Unanswered questions (self-generated or acquired) (3) Third Phase Clean-up or further necessities or interests. There may be counter-policies or counter resolutions that exist; may follow the same total process from beginning to end. Political Environment PART A Quality in Public Opinion Research Will frame constructive and field applicable questions based on current welfare. Will have some field test activity that will not be compromised by pre-exposure of pursuits. Objectives of the research --> Design the survey instrument to the identified objectives Design your sample to reach the right audience to meet your objectives Train your interviewers to collect data in a manner that reduces error Monitor data as it is being collected to find any inconsistencies and to make ensure your data is representative of the area you are surveying. PART B (subjugated by part A) The goal is to extract the logistical and operational essentials out of Chapters 2 – 5 rather than heavy devotion to the text: Russell G. Brooker and Todd Schaefer (2005), Public Opinion in the 21st: Let the People Speak? Cengage Learning Determining strength of methods with respect to geographical scale or political boundary and cost PART C The following article can serve as a strong structure towards field research concerning ideological scaling. Recognising that the range in political ideologies often can be represented geo-spatially, it may be logical to segment survey field into provincial or district or city boundaries. It’s important that students know how to determine what is a good sample and how well geo-spatially distributed their surveys are Everett J. A. (2013). The 12 Item Social and Economic Conservatism Scale (SECS). PloS one, 8 (12), e82131 Note: the following literature can be applied to expand on activity implemented from above literature to analyse possible data fabrication by (outside) data collectors, or whether responses in environments are rigged to convey false narratives. Hernandez I, Ristow T, Hauenstein M. (2021). Curbing Curbstoning: Distributional Methods to Detect Survey Data Fabrication by Third-Parties. Psychol Methods. 2021 Aug 26. PART D Then for a respective province or district or city, students must identify the congressional and executive representations. Extensive voting record related/connected to the 12-14 items from part C. Are the conclusions from part C consistent with elected officials’ records AND rhetoric (commerce)? PART E Additionally, for each region or spatial field pursue measures such as average income, median income, upper income brackets and lower income brackets. Ethnicity, etc., etc. Other demography. Analysis PART F Do conclusions or findings among (A) to (E) “add up” with each other? PART G Analyse and replicate with other interest groups: Finger, Leslie. K. (2018). Interest Group Influence and the Two Faces of Power. American Politics Research, volume 47 (4), pages 852–886. PART H Analyse the following, then adjust to region or sovereignty of interest. Pursue the research development. What is the third overarching research question? Lorenzo De Sio & Romain Lachat (2020) Making Sense of Party Strategy Innovation: Challenge to Ideology and Conflict-Mobilisation as Dimensions of Party Competition, West European Politics, 43:3, 688-719 Criteria Budget Planning Note: open to PS and PA --Delphi Method --Simalto can be applied to predicting which of the alternative combinations of optional service benefits provided by a local authority, state or national government in their annual budget would meet with the ‘maximum’ approval of a target population. --PESTEL & SWOT (with templates) --Develop Analytical Hierarch Process (AHP) R packages exist for AHP Feasibility Studies Research Open to PS, PA, RM, ECON, FIN and OM/AOR students Behrens, W., & Hawranek, P. (1991). Manual for the Preparation of Industrial Feasibility Studies. United Nations Industrial Development Organization Brockhouse, J. W. and Wadsworth, J. J. (2016). Vital Steps: A Cooperative Feasibilty Study Guide. USDA, Rural Development Service Report 58 Feasibility Study Guide (Western Australia): https://www.dlgsc.wa.gov.au/department/publications/publication/feasibility-study-guide Quantitative Analysis for Elections Note: this activity can be of great service to Political Science and Public Administration students. Past and possibly current empirical data and observation of accuracy in prediction for past elections. Adjust to ambiance of interest (i). Identifying Likely Voters Murray, G. R., Riley, C. and Scime, A., Pre-Election Polling: Identifying Likely Voters Using Iterative Expert Data Mining, Public Opinion Quarterly, Vol. 73, No. 1, Spring 2009, pp. 159–171 (ii). Targeting Voters Rusch, T., Lee, I., Hornik, K., Jank, W., & Zeileis, A. (2013). Influencing Elections with Statistics: Targeting Voters with Logistic Regression Trees. The Annals of Applied Statistics, 7(3), 1612–1639. (iii). Election Forecasting Abramowitz, A. I. (2008). It's about time: Forecasting the 2008 Presidential Election with the Time-for-Change Model, International Journal of Forecasting 24, 209–217. Campbell, J. E., (1996). Polls and Votes: The Trial-Heat Presidential Election Forecasting Model, Certainty, and Political Campaigns." American Politics Quarterly 24, 4: 408-34 Berg, Nelson, and Rietz. (2008). Prediction Market Accuracy in the Long Run. International Journal of Forecasting 24, 2 (2008): 285-300. Web. Bayesian Rigdon, S. E. et al (2009). A Bayesian Prediction Model for the U.S. Presidential Election. American Politics Research Volume 37 Number 4, pages 700-724 Rigdon, S. E. et al (2010). An Analysis of Daily Predictions for the 2008 United States Presidential Election. CS-BIGS 4(1): 1-8 (iv). Election Irregularities and Vote Rigging Klimek, P., Yegorov, Y., Hanel, R., & Thurner, S. (2012). Statistical Detection of Systematic Election Irregularities. Proceedings of the National Academy of Sciences of the United States of America, 109(41), 16469–16473. Jiménez, R., & Hidalgo, M. (2014). Forensic Analysis of Venezuelan Elections During the Chávez presidency. PloS one, 9(6), e100884. Jimenez, R., Hidalgo, M., & Klimek, P. (2017). Testing for Voter Rigging in Small Polling Stations. Science Advances, 3(6), e1602363. doi:10.1126/sciadv.1602363 Klimek, P., Jiménez, R., Hidalgo, M., Hinteregger, A., & Thurner, S. (2018). Forensic Analysis of Turkish Elections in 2017-2018. PloS one, 13(10), e0204975. Newcomb-Benford Law and Zipf’s Law Political Redistricting Note: open to both PS and PA students Lines that determine congressional, state legislature, and local government districts are redrawn based on census data for every specified number of years. It's a highly influential process because it tremendously affects who can and will be elected to represent citizens on the local, state, and federal levels. Yearly, the geographic distribution of people changes. Hence, it’s often necessary to redraw districts to accommodate such changes. The redistricting process becomes more tedious because governments must balance competing considerations when redrawing boundary lines each decade. Congressional and provincial legislature districts must have equal population to comply with the judicial system “one man, one vote” rulings. Since the process is based on who lives where, it’s an intrinsically geographic one that requires the integration of many factors. Will pursue development of unprecedented access to the redistricting process. This capability can provide complete government transparency. The effects of boundary changes on associated populations can be tested interactively and worked on collaboratively. To develop reliable current-year estimates and five-year projected population figures, so entities don’t have to wait until the census authority delivers demographic data to provinces. Concerns data to better understand the trends and factors at work in a region, assess redistricting scenarios, and build consensus. Once district boundaries are finalized, the demographic data used for this process remains valuable and can be used to improve election management. 1. Identify the agendas, proper causes and interests involved in political redistricting. Exposure to mechanisms for political redistricting. 2. Skills of introspecting and querying data of interest, where such data concerns development in data analysis and geospatial analysis. 3. The following can be applied to multiple phases of activity: https://gerrymander.princeton.edu/redistricting-report-card-methodology Namely, for both development and analysis of past cases. 4. Methods, exhibitions and simulations (in R) Global Spatial Autocorrelation Local Spatial Autocorrelation Voronoi diagrams of equitable weighting and distribution K-means clustering The following journal article can be computationally developed towards measurement of compactness of political districting plans (and also compared with compactness measures in 3): Fryer, R., & Holden, R. (2011). Measuring the Compactness of Political Districting Plans. Journal of Law and Economics, 54(3), 493-535; likely there may be alternative/comparable journal articles. Then, one can apply the R package called “redist”. The package allows for the implementation of various constraints in the redistricting process such as geographic compactness and population parity requirements. The package implements methods that are described in the following article: Fifield, Higgins, Imai and Tarr (2016). “A New Automated Redistricting Simulator Using Markov Chain Monte Carlo”. Working paper available: https://imai.fas.harvard.edu/research/files/redist.pdf 5. Use of Geographical Information Systems (GIS) in political redistricting Crespin, M. H. (2005). Using Geographic Information Systems to Measure District Change, 2000–2002. Political Analysis, 13(3), 253–260 6. Chen, J., & Cottrell, D. (2016). Evaluating Partisan Gains from Congressional Gerrymandering: Using Computer Simulations to Estimate the Effect of Gerrymandering in the U.S. House. Electoral Studies, 44(C), 329-340. Political Campaigning O'Day, B. (2003). Political Campaign Planning Manual: A Step by Step Guide to Winning Elections. National Democratic Institute Goal is to situate upcoming or ongoing political competition on calendar. Taking an approach without identifying favouritism or preference to candidates. Namely, you as a political scientist. Will be heavily data oriented, also with some expected use of GIS; some “marketing” skills will be applied to develop “political campaigning products” or “sound marketing” for respective combatants based on “segmentation issues” that aren’t overwhelmingly toxic to strong mass support. Your development can be used to critique political campaigns and/or impartial augmentations/corrections can be applied with updates. Situate appropriately: major disparities and competing issues among candidates and support; resonating and developing. Fact checking, intelligence, emotional manoeuvrability and ideological mapping are concerns as well. Campaign Mobilisation Given journal articles can serve as separate research guides. However, the ambiance of interest and the associated data will be the substitute. Quite old data may not available, but overall, to make comparative assessments among the different campaign seasons. R + RStudio environment Holbrook, T. M. and McClurg, S. D. The Mobilization of Core Supporters: Campaigns, Turnout, and Electoral Composition in United States Presidential Elections. American Journal of Political Science, Vol. 49, No. 4, October 2005, Pp. 689-703 Middleton, J. A. and Green, D. P. (2008). Do Community-Based Voter Mobilization Campaigns Work Even in Battleground States? Evaluating the Effectiveness of MoveOn’s 2004 Outreach Campaign. Quarterly Journal of Political Science, 3: 63–82 Probit and Logit Models in Political Science Probit and logit models with fluidity and tangibility, and proper usage with data; data may need probing, structuring, cleaning, etc. Adjust to ambiances of interest. Will make use of the R + RStudio environment. --Francis, J., & Payne, C. (1977). The Use of the Logistic Model In Political Science: British Elections, 1964-1970. Political Methodology, 4(3), 233-270. --Alvarez, R. M. and Nagler, J. (1998). When Politics and Models Collide: Estimating Models of Multiparty Elections. American Journal of Political Science, Vol. 42, No. 1, pp. 55-96 --Miwa, Hirofumi. (2016). Partial Observability Probit Models and Its Extension in Political Science: Modelling Voters' Ideology. The Japanese Journal of Behaviourmetrics. Volume 43 Issue 2, 113-128. --Chen, J., & Cottrell, D. (2016). Evaluating Partisan Gains from Congressional Gerrymandering: Using Computer Simulations to Estimate the Effect of Gerrymandering in the U.S. House. Electoral Studies, 44(C), 329-340. --Bailey, Michael, and Chang, Kelly H. 2001. “Comparing Presidents, Senators, and Justices: Interinstitutional Preference Estimation.” Journal of Law, Economics, & Organization 17:477–506. Note: other articles of interest as well. Statistical Analysis of the Legislature & Bill Journey Open to PS and PA Note: will be done at the federal level, provincial level and city level. Note: preference is development in the R environment when computation and simulation are required. PART A 3-4 bills may be pursued 1. Review of the bill process 2. Tools or systems used to track legislation. Hands-on activities. 3. Reviewing Bill Analysis. 4. Programme Theory 5. Further analyses for bill(s) in question: -Any bill needs a major supporter in each house of Congress. Gaining the attention of the relevant committee (member(s) or chairperson) -Easing the concerns of outside groups. Possible bill(s) amendments -Allies in the federal bureaucracy -Cost estimation data. Means to pay for bill(s) -Non-monetised impacts on stakeholders from bill(s) -Gauging the proportion of the house(s) with adamant opposition PART B Note: will be done at the federal level, provincial level and city level. -NOMINATE (scaling method) Poole, Keith T.; Rosenthal, Howard (1985). A Spatial Analysis for Legislative Role Call. Analysis. American journal of Political Science, 29(2): 357–384. -Extend to W-NOMINATE and DW-NOMINATE as well. -For one’s ambiance will apply similar structures as the following: https://www.govtrack.us/about/analysis#overview -Moore tools: Jackman, S. (2001). Multidimensional Analysis of Roll Call Data via Bayesian Simulation: Identification, Estimation, Inference, and Model Checking. Political Analysis, 9(3), 227-241 Clinton, J., Jackman, S., & River, D. (2004). The Statistical Analysis of Roll Call Data. American Political Science Review, 98(2), 355-370. Shor, B., Berry, C., & McCarty, N. (2010). A Bridge to Somewhere: Mapping State and Congressional Ideology on a Cross-institutional Common Space. Legislative Studies Quarterly, 35(3), 417–448 -Bipartisan Index (pursue development) The Lugar Center-McCourt School Bipartisan Index: https://www.thelugarcenter.org/ourwork-Bipartisan-Index.html Political Instability Note: open to both PS and PA students Will make use of the given articles comparatively towards analysis and measures of political instability. Will also incorporate modern data. Duff, E. & McCamant, J. (1968). Measuring Social and Political Requirements for System Stability in Latin America. The American Political Science Review, 62(4), 1125-1143 Linehan, W. (1976). Models For the Measurement of Political Instability, Political Methodology, 3(4), 441-486. Ari Aisen and Francisco Jose Veiga (2011). How Does Political Instability Affect Economic Growth? IMF Working Paper WP/11/12 Advocacy Lab Open to PS and PA students Immersion into theory and practice of the concepts and tools of advocacy and will work with those in the field to apply our learning. We will team with different/multiple advocacy organisations, NGOs, NPOs, etc. to advocate for a range of supportive measures and actions to help address a number of issues. Advocacy campaign can vary for each year. Gain hands-on experience in taking on a social justice issue towards change. The following may be applicable for relatable elements Public Engagement Guide. Newfoundland & Labrador, Office of Public Engagement: https://www.gov.nl.ca/pep/files/Public-Engagement-Guide.pdf NOTE: much responsibilities and tasks with data and writing. Establishing as a credible sources of information and/or ethically linking to credible sources for information. Goals & Outcomes in a chosen sequential manner that’s constructive and sustainable; otherwise some things may reverberate on multiple occasions --> 1. Detailed analysis and structuring of issues recognised. Programme Theory for measures and actions for issues recognised. 2. Analysis of the structure and possible effects of measures and actions Identify key stakeholders and interest groups for measures and actions. Identify the range of possible outcomes for stakeholders and interest groups. Policy impact assessment. Monetised costs and benefits. Non-monetised impacts. 3. Apply analytical methods to understand the dimensions of power and decision-making at the community, state, and national levels; market makeup 4. Consider how changes in civic engagement and voluntary associations impact community organizing and grassroots mobilization. Determine how to identify and engage community members and organizations that will get involved in an advocacy campaign and how to support their participation in decision-making processes and coalition building. 5. Position one’s own public service interests within a larger public service landscape. Principal-Agency dilemma (personal, stakeholders and other elements). 6. Develop strategies to enhance social and economic justice within organizational and political systems especially as they affect specific demographics, as well as strategies to address social class 7. Identify professional values and ethical positions within, as well as between systems, which may appear to be incompatible with political roles and strategies and develop skills to bridge these incompatibilities to affect change 8. Generate policy alternatives and differentiate among them, including assessing their feasibility and consequences 9. Identify and utilize methods and skills, which develop and sustain interorganizational networks 10. Demonstrate advocacy skills, such as testifying, lobbying, and providing staff support for public interest, constituency and/or grassroots community groups; Identify institutional and community practices that disempower, and develop strategies to challenge them 11. Demonstrate how to share empowerment theory and practice with constituencies who are unfamiliar or inclined to oppose such 12. Issues with intellectual property: credits, development rights, literature development, operations management. Media. Public administration record archives. 13. Continue the development, sustainability and credibility of the professional use-of-self. Linkages between public sector and private sector Open to PS and PA. Will have field studies. Note: Cost-Benefit Analysis and SROI to also be incorporated. Model Articles: Grossman, S. A. (2012). The Management and Measurement of Public-Private Partnerships: Toward an Integral and Balanced Approach. Public Performance & Management Review, 35(4), 595–616. Koontz, Tom & Thomas, Craig. (2012). Measuring the Performance of Public-Private Partnerships: A Systematic Method for Distinguishing Outputs from Outcomes. Public Performance & Management Review. 35(4). 769-786. Judicial Educational Activities Ambiance counterparts to the following: 1.The Supreme Court for Educators -> https://www.thirteen.org/wnet/supremecourt/educators/lp4b.html Note: at least 3-5 cases should be considered to develop skills and competence. 2.United States Courts Education Activities -> https://www.uscourts.gov/about-federal-courts/educational-resources/educational-activities NOTE: trial court pursuits and civil litigation pursuits are also possible as well. Judicial ideology measures For ambiance of interest will pursue research and development for federal supreme and lower courts with the following: Segal-Cover Score Judicial Common Space Martin-Quinn Score Note: the R environment will be employed when times arise for advance computation and simulation. Helpful literature: Segal–Cover score Segal, Jeffrey A.; Cover, Albert D. (June 1989). "Ideological Values and the Votes of U.S. Supreme Court Justices". The American Political Science Review. 83 (2): 557–565 Segal, Jeffrey A.; Epstein, Lee; Cameron, Charles M.; Spaeth, Harold J. (August 1995). "Ideological Values and the Votes of U.S. Supreme Court Justices Revisited". The Journal of Politics. 57 (03): 812–82 Judicial Common Space (JCS): Lee Epstein, Andrew D. Martin, Jeffrey A. Segal, Chad Westerland, The Judicial Common Space, The Journal of Law, Economics, and Organization, Volume 23, Issue 2, June 2007, Pages 303–32 Martin-Quinn score: Martin, Andrew D.; Quinn, Kevin M. (2002). Dynamic Ideal Point Estimation via Markov Chain Monte Carlo for the U.S. Supreme Court, 1953-1999. Political Analysis. 10 (2): 134–153 Spruk, Rok; Kovac, Mitja (2019). Replicating and Extending Martin-Quinn Scores. International Review of Law and Economics. 60: 105861 Health Decision Sciences with R activity (check Actuarial post) Open to Economics AND Public Administration students Advance Impact Evaluation Practice Gertler, P. et al (2016). Impact Evaluation in Practice: Second Practice, World Bank Publications Note: much field studies. Open to PS and PA students.

# PUBLIC ADMINISTRATION The degree is called Public Administration, not Urban Planning. Note: a Public Administration degree is not, and will never, be a substitute for an Economics degree. Note: It’s recommended that students have advance placement and/or plan to take general education appeasement courses in the “winter” or “summer” sessions. Mandatory Curriculum makeup: 1. Integrating tools-- Enterprise Data Analysis I & II (check FIN); International Financial Statements Analysis I & II (check FIN); Calculus for Business & Economics I & II, Introduction to Computational Statistics for Political Studies (check PS) 2. Economics Accountability-- Introduction to Macroeconomics, Intermediate Macroeconomics 3. Governance (all three listed in PS)-- Constitutional Law, Executive Process, Comparative PA, Public Policy 4. PA Writing Mandatory-- Public Administration Writing I-II 5. PA Professional Development Mandatory (all listed courses) PA Management Public Personnel Administration; Public Project Management; Public Policy Formulation & Implementation; Non-Profit & Public Organisations Management PA Finance Financial Management for Non-Profit Organisations; Fiscal Administration; Government Accounting Quantitative Analysis-- Quantitative Analysis in Political Studies I (check PS); Research Methods in Public Administration Research & Response-- Crisis Management; Research in Crisis & Crisis Mitigation; Programme Evaluation I-II Course descriptions-- Comparative PA The purpose of this course is to provide students with an overview of the basic concepts used to compare public administration across national governments. Comparative public administration aims to understand the different ways in which agents of governance operate to achieve goals and deliver services and their effectiveness in doing so. As an academic study, comparative administration contributes to social knowledge by testing ideas about and concepts for comparing government organisation and operation. It may provide ways to comparatively assess the extent to which public entities are producing desirable changes and benefits. Goals throughout course: -- Review the history and development of comparative public administration as a study and movement in public administration. -- Present the key concepts for thinking about administrative systems and their backgrounds and similarities and differences in the modern nation state and global economy. -- Lay out the challenges and idiosyncrasies of national administration and development in the modern context. -- Become acquainted with the culture, political economy, and administrative systems and problems in particular national systems. Resources --> Journals (public policy, public administration, political economy, foreign policy) Literature, manuals, guides, archives, databases, toolkits, software from government agencies, IGOs, OECD, etc., etc. Development and Sustainability Indicators/Indices: political, economic, social Assignments & Requirements --> Attendance & Participation Current Events Labs & Development Assistance Article Extract Group Analysis of Responding Actors Term Project Group Article Extract --> Turn in components: -Qualitative research (interview, focus group, or archival data analysis, answering questions about how from the participants’ perspective regarding important issues/policies in comparative public administration). -Quantitative research on article (statistical analysis, hypotheses testing, using survey, experimental, existing datasets to test relationships between independent variables and dependent variables in comparative public policy, public administration or civil society) -Attempt at linking prior two Group Analysis of Responding Actors Term Project --> Critically and systematically analyse two responding actors’ responses to systematic crises or shocks, e.g. pandemics, natural disasters, hacking and ransom attacks, terrorist attacks, foreign policy. Components: -Intelligence on systematic crises or shocks -Models for damages, effects and costs. Cost estimation. -Response Actors Background Responding actors could be public, inter-organizational partnerships, and networks. Describe their goals/purposes, sizes, age, governance structures, and policy domains. Why are the two responding actors comparable? If the shocks are not the same, why are they comparable? -The Network Response Present actors’ responses to a systemic shock/crisis, possibly including cross-policy, cross-function, and cross-sector collaboration. Cite at least 3 quality sources to support your summary of responses. -Policy Analysis and Learning/Change -Governance Successes and Failures Analyse the successes and failures of responses of government and nongovernment actors. To what extent the year Y responses reflect policy/governance learning from X earlier responses (if relevant); including policy adjustment, reversal, and change? Please specify the indicators of successes and failures. Model or structure of indicators with logistics. Findings from the applied indicators. Cite at least 3 quality sources to support your assessment. Note: may or may not need to exhibit the offsetting of the second component; some things are not recoverable. -Policy Options Not Taken and Why What other policy options were debated but ended up not adopted? Why were they not taken up by the actors? Cite at least 3 quality sources to support your discussion of policy options. Lessons Learned What are the lessons we can learn from the failures and successes of the country’s responses or region? How likely are they become part of the policy agenda of peer actors in the same or foreign countries? any weaknesses, limitations, or risks? Labs & Development Assistance --> Will be focused to towards development of your Group Response Actors Term Project. Prereqs: Introduction to Computational Statistics for Political Studies (check PS) Public Personnel Administration Overview of the context in which public personnel management is administered, with exploration of core functions and activities. Case studies and exercises will be applied to spotlight the tensions, responsibilities, and tasks of personnel management. NOTE: satisfies social/society requirement Grading --> Quizzes (determined topics) Students are required to submit 2 comments or questions illustrating comprehension of the assigned material each week. Students can choose to submit 2 questions, 2 comments, or one of each. Commentaries are not summaries. Questions or comments may or may not be addressed during course. Group Projects Payroll simulation framework, logistics & implementation Work Force Planning Term Project Payroll simulation framework, logistics & implementation --> Student groups will be assigned 2 ministries of public administration (system wide or branches) to simulate payrolls for the staff spectrum. Some research will be required. Emphasis on framework or model, logistics and implementation with a tool. Note: student groups are required to have active demonstrations with modelling and development during presentation; each member will have a turn. Work Force Planning Term Project --> Groups will be assigned an element of the public sector to apply the following guide to workforce planning: < https://hr.nih.gov/workforce/workforce-planning/getting-started > < https://hr.nih.gov/workforce/workforce-planning > Data gathering and development Outline --> --Introduction to Public Personnel Management --Core Values of the Civil/Public Service Civil/Public Service Merit Systems and their preservation; identifying comparable legislative amendments for different ambiances; civil/public service versus merit system Spoils system and its legal limit; identify court case(s) about political parties versus entities concerning the spoils system. --Law of Public Personnel Management Identification of constitution structure and crucial modern reforms Observation of any possible legal variances (or politics) sub-nationally --Fostering Inclusiveness and Confronting Discrimination Are there discrepancies between a merit system and equal opportunity? Despite neglecting disallowing declaration of race and sex, what parts of the recruiting process are likely to create discriminatory practices? Role of diversity among recruitment personnel, and at what level of government intervention does such diversification become considerably active. Desired credentials versus auditioning or trial runs; cost effectiveness versus assurance. --Labour Relations Labour enforcement protocols. Who makes higher enforcement a higher interest, employees or administration? Initiators or stimuli for negotiation of labour rights and entitlement. Rights and limitations of unions. Is it often more of a provincial or a national issue? What circumstances lead to a national issue? When is a strike illegal? Collective bargaining. Are there statistical or data observations that hint of possible future labour disputes? Group Project: Collective Bargaining Agreements & Pension Planning (provincial, national and foreign) A. Labor Unions Means to be legally recognised as labour union. Rules and regulations for administration, operations and promotion systems. Collective Bargaining Agreements Agreement archives in securities exchange or department of labour Observation of major CBAs to recognise typical model structure, major correlations and disparities Analysing the presence or influence of unions in the public sector today. Identify major unions (assigned industries and sectors) Employee membership trend Market share trend B. Workforce Reduction What criteria should be used in selecting employees for a workforce reduction? Pursue case studies based on the elements out of the following towards public sector entities -> SHRM Foundation’s Effective Practice Guidelines Series – Employee Downsizing and its Alternatives – Strategies for Long-Term Success: https://www.shrm.org/hr-today/trends-and-forecasting/special-reports-and-expert-views/documents/employment-downsizing.pdf C. Empirical Studies of Workforce Reduction To pursue matching workforce reduction strategies implemented in the public sector with the following articles. Will be highly data oriented: Cameron, K. S., Freeman, S. J., & Mishra, A. K. (1993). Downsizing and Redesigning Organisations. In G. P. Huber and W H. Glick (Editors), Organisational Change and Redesign. Oxford: Oxford University Press Freeman, S. J., & Cameron, K. S. (1993). Organizational Downsizing: A Convergence and Reorientation Framework. Organization Science, 4, 10-29 Freeman, S. J. (1999). The Gestalt of Organizational Downsizing: Downsizing Strategies as Packages of Change. Human Relations 52, 1505–1541 --Pension Planning For assigned occupations (and unions) to profile instruments’ in pension plans’ characteristics with premiums. What model(s) determine pension income? Income subjugated by earnings after taxes, benefits dues and pension premiums. What is best for you based on lifestyle? How does preference in pension deposit size influence taxes? --Public Pensions Role of retirement boards, means of establishment, structure and roles in the structure. Internal versus external management. Coggburn, J. D. & Reddick, C. G. (2007) Public Pension Management: Issues and Trends, International Journal of Public Administration, 30:10, 995-1020 Funding structure. Rule and models for employer contribution rate. Increasing contribution rates and the potential relief mechanism. Review of annuity benefit model in relation to rules and models for employer contribution rate. Investment management model Survey of public pension funds in the market and means of determining performance. Gov’ts outsourcing pensions to the private sector Objectives. Does the employer need consent from employee or union? Differentiating the risks between public pensions and privatized pensions. --Tax Benefits Structures and instruments. Validating formulas for various scenarios. --Vacation and Leave Days Models and Tables in various industries of public sector/service Comparative assessment among different countries --Other Benefits Healthcare Insurance Tuition Reimbursement Model --Recruiting and Testing Guidelines for developing selection criteria How is selection criteria validated? How is testing validated? What foundations make such testing credible? Measures of training and experience Selection interview Group Project: Recruiting and Testing: Employment demography. Identify the major tools applied in recruitment and testing for assigned public administration areas. What skills, backgrounds and education do such tools encourage concerning screening? What indicators are there to determine the skills, backgrounds and education required to improve efficiency and quality? Trends in sectors (will be technical measures to research and model). Equal employment opportunity regulations and limitations based on type labour(s). Initiatives for inclusiveness. Note: project will resonate around above course topics. --University of Cambridge -Human Resources – Principles of Job Design: https://www.hr.admin.cam.ac.uk/pay-benefits/grading%20-%20faq/grading/principles-job-design Group Project: Job Design Investigation For a prior design in the public sector, apply prior source to investigate and draw conclusion(s) --Compensation. Rubrics and law (provincial and national) --Strategic Workforce Planning Accountability agencies (national and provincial). Highlighting the principles. Succession planning and management Influence of changing directors Human Capital Benchmark reports Reduction-in-force factors and conducting Technology integration as an animal Workforce planning model (subject to prior topics). May have case studies. What factors are related to bad impressions of the public sector? What sectors of public administration weigh heavily on classification on a country’s development standing? Group Project: Personnel Optimisation Modelling and Personnel Scheduling Technology A. Basic encounter in personnel optimisation/scheduling. Students will be assigned 2 public sector facilities/sites. They will research operations obligations, leading to profiling or segmentation w.r.t. to skills, budgets, demand, etc., etc. Such done without consideration of actual realised staff body. Will develop optimisation models and implement in R. Compare with observed actual realised staffing. B. Will have some immersion into personnel scheduling software. There will not be heavy treatment of scheduling models, but some ideas/foundations will float before software use. May be compared to findings from (A). Group Project: IT Modernization Plan (city, provincial or national ministries) Information technology is vital to the way an administration serves the public. Applying technology effectively and creatively over the years to better serve the changing needs of the people. A. Selection Process Steps 1.Discern the various elements and questions related to workplace technology 2.Create a strategy for technology planning 3.Decide on technology plans and how to choose technology. Note: must include 5C Analysis implementation for companies and products. Develop trend observation if possible. Note: must include financial analysis for all companies and products, plus applying Beneish, Dechow F and Altman Z. Note: cybersecurity scheme subjugating/constraining priors Note: for the steps the following literature provides guidance for different industries with technology integration -> *Campise, J. A. (1972). Choosing a Computer System for Project Management. Project Management Quarterly, 3(4), 13–16. *Quinn, S. D. et al (2018). National Checklist Program for IT Products – Guidelines for Checklist Users and Developers. NIST Special Publication 800-70 Revision 4 *Information Technology Investment Management: A Framework for Assessing and Improving Process Maturity. GAO March 2004 Version 1.1 GAO-04-394G *National Centre for Education Statistics – Forum Unified Education Technology Suite: https://nces.ed.gov/pubs2005/tech_suite/index.asp *Health & Human Service ECLKC: https://eclkc.ohs.acf.hhs.gov/organizational-leadership/article/whats-involved-technology-planning *Bhangoo, T. (2020). How To Select The Right Technology Solution: Five Strategies For Leaders. Forbes Note: groups to be given sets of technologies products concerning a particular sector of non-profits or public administration, to gather intelligence and analyses towards choice selection. B. Highlight the following: Modernization Plan, Business Domains, Technical Domains, Modernization Cost-Benefits-Avoidance, Executing Modernization Plan. C. Empirical Findings: Major investments over a particular designated period, and means to prudently derive the greatest value possible from such technology investments. Identification of disruption to legacy systems, business processes and, ultimately, to the way of labour Labour skills dynamic resulting from modernization Evidence of systems enhancing productivity and yielding numerous efficiencies to the way administration functions. Growing challenges of modernization Were environmental initiatives a major concern for modernization? Does data verify environment effectives? --Measuring the Performance of Human Resources Management Systems Tools and strategies Problems and prospects HR metrics Group Project: Implementation of HR metrics A. For different occupations or industries in the public sector will pursue implementation of the metrics with trend recognition. Choice of metrics will be AUGMENTED BY the following: Human Capital ROI Will be acquiring various financial statements from both the private sector and public set for determination. Note: as well, historical performance is important to observe Gender Balance of Employment Gender Balance of Management Employee Turnover Rate, employee churn rate Payrolls Retirement Rate measures B. To develop for ambiance of concern: Somani, Ravi. (2021). Public-Sector Productivity (Part 1): Why Is It Important and How Can We Measure It? Washington, D.C. World Bank Group From OECD: Lehtoranta, O. and Niemi, M. (1997). Measuring Public Sector Productivity in Finland, Economic Statistics, Statistics Finland, STD/NA(97)15 C. Some public sector elements can be in competition with private sector elements. Interests -- Salary Competitiveness Ratio Employee Benefits Retention Retirement Rate --Employee Performance Appraisal Rounded guide to employee appraisal Boundaries on conversations with employees --Discipline Guidelines from merit systems Incidents and review of employees in workspace of concern (confidentially) Review of merit systems and legal actions. Prerequisite: International Financial Statements Analysis II, Upper Level Standing, Department Permission Public Administration Writing I Good public writing involves many stages: good memos and grant proposals do not just “happen” overnight. Competent reports or engaging press releases do not constitute everything you know about their central subject. They are the product of much thought, research and frequently much revision. The good news is that, like any technique, it is one that can be learned through practice and useful feedback. Course also has special emphasis on developing self-evaluation techniques for you to draw from and use professionally long after. This course focuses on discussing, developing and practicing the techniques and understanding required to produce good public writing of different kinds. Skills to benefit students who intend to engage in all areas of the policy professions, public administration, the non-profit sector, the political media, or work in governmental institutions. The course guides you through the process of writing several types of professional public communications including memos, policy briefs, initial grant proposals, white papers and press releases. We will cover the criteria to look for and emulate in a good public document, learn how to assess the needs and interests of diverse audiences and how to present relevant information to them in the most effective way. The course also explores the impact of the law and electronic communications on public communications. Students will be expected to distinguish good work from bad both in their own writing and in the published works used to construct them. Not a liberal arts course; will focus on operational and systematic issues occurring in actual Public Administration. To write about Public Policy one must have experience in it. It’s assumed that students are experienced with writing basic essays from high school, else they would not be here. NOTE: course may extend to 18 weeks. Typical Text: Swain, J. W. & Swain, K. D. (2014). Effective Writing in the Public Sector, Routledge, 222 pages Resources --> Various literature, guidelines, manual, data, etc., etc. from various elements of the public sector, executive administrations and IGOs. Outside Assignments --> Assignments done outside of class. For any outside assignment to be done in groups, each constituent of a group must develop their own literature to be submitted with consensus assignment; individuality will be checked and will have weight on determination of contribution to group and overall effort by group. NOTE: references or citations implied whenever warranted. Assessment --> Discussions/Forums In-class assignments Outside assignments Some outside assignments will have more weight than others. Audience Analyses (based on credible sources) to be mandatory precursor development before actual outside assignments, concerning: Report Writing, Press Releases, Newsletters, Media Alerts Course Outline --> --Introduction to Public Writing Reading/Assignments --Fact checking and sources Reading/Assignment Outside Assignments: groups will be assigned documents, social media, websites, and other literature concerning statements or assertions or claimed data without idea of sources and references. Students will be responsible for critiquing, and to generate counter responses or provide proper structure (framework, model, design, etc.) with citations or references. --Persuasive Writing and Clarity Reading/Assignments --Planning your Public Communications Reading/Assignments --Policy Briefs Reading/Assignments Outside Assignment: drafting Policy Briefs --Memos Outside Assignment: Memos development --Proposals Reading/Assignments Outside Assignment: write a grant proposal --Emails and Letters Reading/Assignments Outside Assignments: Correspondence and Notification --Report Writing Reading/Assignments Outside Assignments: Report Writing --Justifications. Budget Justifications Readings/Assignments Outside Assignments: Budget Justifications --Press Releases, Newsletters Readings/Assignments Outside Assignment: Draft a Press release (or Newsletter) --Creating Media Alerts Press release versus media alert Readings/Assignment Outside Assignment: construct a Media Alert Prerequisite: Comparative PA Public Administration Writing II Expect harsher critique and grading. NOTE: course may extend to 18 weeks Possible Project: 3 week press kit development and conveyance Prerequisite: Public Administration Writing I Public Project Management Project management concepts and principles, and to engage students with the intricacies and challenge of managing public or private projects with tight schedules and limited resources. Students will also apply relevant tools and techniques and by making extensive use of case studies and simulation exercises to assimilate that knowledge. Students should be able to apply with a reasonable level of confidence the following tools and techniques of effective project management: Objective setting and project design Planning, scheduling, and budgeting Progress control and monitoring Risk assessment and management Project Management KPIs Class sessions will typically consist of lectures, class discussions, case study analysis, and in-class problem solving Course Literature --> Gray, Clifford F. and Erik W. Larson. 2018. Project Management: The Managerial Process. McGraw-Hill Irwin Publishers Assisting Literature --> Edwards, P., Vaz-Serra, P. & Edwards, M. (2019). Managing Project Risk, Wiley A Guide to the Project Management Body of Knowledge (PMBOK Guide) Mandatory Tools --> Microsoft Office 365 Microsoft Project (or SAP Enterprise Portfolio & Project Management) Resources --> Microsoft tutorials/lab manuals on Microsoft Project Microsoft learning: https://docs.microsoft.com/en-us/learn/browse/ YouTube videos Features --> 1. Case study assignments. Can be done in groups but should be submitted individually in the form of a memo. Guidelines for submitting memos will be provided. Will also incorporate PESTEL and SWOT tasks when appropriate. 2. Take-home assignments involve analysing a large case study and submitting recommendations using a memo format and solving several problems and exercises. May be done in groups. Will also incorporate PESTEL and SWOT tasks when appropriate. 3. Labs will take on development of concepts, structuring, logistics and implementation with project management software. -Structured on operations of the institution, or coordinated participation in the public sector, being low risk with data privacy. Note: choice of operations guaranteed to be completed within 15 - 18 weeks. Guidelines for the groups will be distributed in class. -Students should develop logistical and pivoting notes -via Microsoft Project, or other chosen tool. Heavy use of documentation and manuals for tools is expected alongside. YouTube videos exist as well. Also, instruction in labs will be recorded for students’ convenience. -Labs will be at least 3 hours involving concepts, tasks development and practice; likely to extend with obligative development outside of lab time as well. -Students will be expected to provide written synopsis/summaries of their development and provide tool development progress at chosen stages. 4. Practicum sessions for Microsoft Project --> Development in labs will play a pivotal role towards major developments with substance and practicality. 5. Midterm Exam and Final Exam will have multiple components: -Comprehension and intelligence with lecturing and labs (concepts, development, management, etc., etc.). As well, practice problems may come back to haunt. -Case studies may appear -Developed logistical and pivoting lab notes will be vital for the midterm exam and final exam. On both exams there will also be development tasks with Microsoft Project based on given data, parameters, etc., etc. Assessment --> Class Participation & Homework Practice Sets Case Studies + 2 Take Home Assignments Labs Practicum sessions for Microsoft Excel and Microsoft Project Mid-term Exam Final Exam Group Presentations PART I -- WEEK 1. Understanding Project Management Chapters 1 and 10 Youker, R. (1989). Managing the Project Cycle for Time, Cost, and Quality: Lessons from World Bank Experience. Project Management. Vol. 7, no. 1. WEEK 2. Organisation Strategy and Project Selection Chapter 2 EXCEL Practicum WEEK 3. Organisation Structure and Culture; International Projects Chapters 3 and 15 Project Management Institute. A Guide to the Project Management Body of Knowledge. Chapter 2 (Project Life Cycle and Organization). Youker, R. (1977).Organisational Alternatives for Project Managers. Project Management Quarterly. Vol. VIII, no.1 PESTEL Development (external literature and sources for development) Case Studies for chosen environments WEEK 4. Managing Project Teams Chapter 11 Kerzner, H. Project Management: A Systems Approach to Planning, Scheduling and Controlling. 8th Edition. John Wiley & Sons. 2003, chapter 7 (Conflicts) Verma, V. K. (1996). Human Resource Skills for the Project Manager. The Human Aspects of Project Management. Vol. 2. Project Management Institute. Chapter 3 (Understanding Conflict) PART II -- WEEK 5. Defining the Project Chapter 4 Crosby, B. L. (1991). Stakeholder Analysis: A Vital Tool for Strategic Managers. Technical Notes. A publication of USAID’s Implementing Policy Change Project. Grimble, Robin. (1998). Stakeholder Methodologies in Natural Resource Management: Best Practice Guidelines. Natural Resource Institute. The University of Greenwich WEEK 6. Developing a Project Plan Chapter 6 WEEK 7. Developing a Project Plan (continued) Microsoft Project Practicum # 1 WEEK 8. Estimating Project Times and Costs Chapter 5 WEEK 9. Midterm WEEK 10. Managing Risk Chapter 7 WEEK 11. Scheduling Resources and Costs Chapter 8 Microsoft Project Practicum # 2 WEEK 12. Scheduling Resources and Costs (continued) Chapter 8 WEEK 13. Progress and Performance Measurement and Evaluation Chapter 13 Microsoft Project Practicum #3 WEEK 14. Progress & Performance Measurement & Evaluation (continued) Chapter 13 SWOT in Project Management (external literature and sources for development) Project Management KPIs WEEK 15 -18. Integrity/Clean-Up to Presentation Prerequisites: Enterprise Data Analysis I & II, Upper Level Standing Non-Profit & Public Organisations Management Overview of the management skills required by leaders of non-profit organizations and will discuss the purpose or mission of the organisation and its place in society. Management theory and practice tell us that to successfully fulfil its mission an organisation should engage in a process of planning and organising its resources to implement a plan. The course will also include a discussion of how to develop financial resources through fundraising and earned income ventures. We will also explore marketing and communication techniques, financial management, and the role of the governing board in the non-profit organization. Assisting Literature --> Wolf, T. (2012). Managing a Non-profit Organisation. New York: Free Press. Heyman, D.R. (2011). Non-profit Management 101: A Complete Practical Guide for Leaders and Professionals. San Francisco: Jossey-Bass NOTE: many or most cases course will apply other literature and sources. Operations Data --> --Listings & Filings: Securities Exchange Commission, Gov’t Revenue Admin --Financial Statements: Balance Sheet (Statement of Financial Position), Income Statement (Statement of Activities), Statement of Functional Expenses, Non-Profit Financial Statement of Cash Flows, Internal Revenue Filings --Annual Reports International Data & Tools --> UN Data (UNODC & UNSD) Open-Source Resources --> Indices of Social Development: https://isd.iss.nl/data-access/ OCHA Tools: https://www.unocha.org/ocha-digital-services OCHA Programme Cycle: https://www.humanitarianresponse.info/programme-cycle/space/page/assessments-overview Course Assessment --> Assisting Literature Exercises 20% Group Assignments 50% In-Class Obligations 30% --Week 1 What is non-profit management? Overview of the Non-Profit Sector --Week 2 Law and Governance Mandatory government registries and taxation status for NGOs/NPOs The role of the governing board. Review and analyse the legal aspects of board governance, by laws, conflicts of interest, and fiduciary responsibilities. Comparative Legal Framework for NPOs/NGOs concerning different countries or provinces: Starting an NPO/NGO Process Will be responsible for written development relevant to process Determination of tax-exempt status (provincial and federal) Forms of taxation exemption based on classification types Financial reporting procedure with exemptions filing Requirements/rules for foreign NPOs/NGOs Foreign Funding of domestic and foreign NPOs/NGOs Examination of Board Members of three NPOs and analyse the strengths and weaknesses of these members as to their role on the Board and what resources they bring to their Board. Due date(s) will be given. --Week 3 - 5 Environmental Stability Scanning, Human Capital, and Strategic Planning A. Demography (national, provincial, municipal) Gov’t census and labour statistics UN Agencies B. Harsh Data (UNODC & UNSD) C. Indices of Social Development: https://isd.iss.nl/data-access/ D. How do you acquire data for cultural factors? Material Culture, Cultural Preferences, Languages, Education, Religion, Ethics & Values, Social Organisation E. Human Capital *Flood, J. P. (2005). Managing Volunteers: Developing and Implementing an Effective Programme. Proceedings of the 2005 Northeastern Recreation Research Symposium GTR-NE-341 *U.S. Department of Health and Human Services. (2005). Successful Strategies for Recruiting, Training, and Utilizing Volunteers. DHHS Publication No. (SMA) 05–4005 *Screening tools example: https://www.nycservice.org/pages/pages/172 *Organisational Design: https://www.aihr.com/blog/organizational-design/ *4 frames -- structures, symbols, people, & power (Bolman & Deal 2008) *Nikolova, M. (2014) Principals and Agents: An Investigation of Executive Compensation in Human Service Nonprofits. Voluntas 25, 679–706 (2014) F. Strategic Planning Process (preliminary scanning for a NPO project) Most or all Prior (A through E) may factor in Programme Theory: < https://www.jmu.edu/assessment/sass/ac-step-two.shtml > Steps in a Local Strategic Planning Process: www.fordham.edu/info/26620/steps_in_a_local_strategic_planning_process Groups will be assigned a project based on (A) through (F). Due date will be given. --Week 6 Needs Assessment Groups will be assigned nonprofit programme planning. Consideration of a new programme, where through a needs assessment to determine whether the program is necessary. Due date will be given. --Week 7 - 9 Risk Data and Risk Identification Tools for NGOs/NPOs The given methodologies, sources and tools concern development of a fluid, tangible and competent scheme for credible analysis in good timing. A. Profiling with IGOs Data UNODC and UNSD Measures and indicators for political stability and security B. Concerning the mentioned sources what can you do? Groups will have exploratory project(s). Concerns both the International Data & Tools (given above) and Open-Source Resources (given above). Due date(s) will be given. C. Risk Assessment Development Tools Relevance to various types of non-profits and their welfare 1.The Global Conflict Risk Index (in-class development) https://drmkc.jrc.ec.europa.eu/initiatives-services/global-conflict-risk-index#documents/1059/list Note: the methodology and other documentation must be analysed before use. 2.INFORM (analysis & in-class implementation) INFORM Index for Risk Management INFORM Severity Risk INFORM Warning Note: for each the methodology and other documentation must be analysed before use. 3.Environmental Emergencies Centre (analysis & in-class implementation) The Flash Environmental Assessment Tool (FEAT) Rapid Environmental Assessment Tool (REAT) Note: for each the methodology and other documentation must be analysed before use. Comparative assessment between (1), (2) and (3) (in-class implementation): Product SWOT analysis AND compliment (augment) to each other for various environments based on analysis and implementation. D. Financial Integrity PART A (general knowledge or ambiance counterpart): Office of the Comptroller of Currency - Bank Secrecy Act/Anti-Money Laundering: Joint Fact Sheet on Charities and Nonprofit Organizations PART B (in-class development) The following literature can be expanded to treat general non-profits. With respect to sector/service of the NPO considered, apply such literature as a model or inquiry for the various conditions, administrations and issues pertaining to the ambiance: Barker, A. G. (2013). The Risks to Non-Profit Organisations of Abuse for Money Laundering and Terrorists Financing in Serbia, Council of Europe E. Develop the following literature with environment data of interest: Ferwerda, J., Kleemans, E.R. Estimating Money Laundering Risks: An Application to Business Sectors in the Netherlands. Eur J Crim Policy Res 25, 45–62 (2019). Can possibly be altered to NPOs following --Week 10 Marketing and Communications Part A Group Assignment: Choose 5 non-profits of your choice. Visit their websites and analyse their marketing content. Review the content from a “diversity” perspective. That is, does the marketing of the organisation reflect the diversity of society? How to make credible/relevant conclusions? Count diversity in the images used (gender, race, age, etc.) Count diversity in the with social media used by the organisation Is the board membership diverse? Assumes such is accessible followed by extensive background checks. Are the materials shared “broad” in terms of meeting interests for a range of groups or, are the materials narrowly targeted to a single demographic? Services portfolio analysis. Multiple annual reports or statements of activities to identify geographical and cultural exposure. Income Revenue Analysis and Cash Flow Analysis Compute the following for respective non-profit: Total Available Market (TAM) The Serviceable Available Market (SAM) The Serviceable Obtainable Market (SOM) Drawing conclusions Due date(s) will be given Part B Group Assignment: For 2-3 assigned NPOs/NGOs identify and apply segmentation models subject to part A. Note: beneficiary and donor, respectively. Due date(s) will be given. Part C Group Assignment: Observation of the Brand IDEA Framework for 2-3 NPOS. Literature assist: Laidler-Kylander, Nathalie, and Julia Shepard Stenzel. (2013). PART 3 – Putting the Brand Idea into Action. In: The Brand IDEA – Managing Nonprofit Brands with Integrity, Democracy and Affinity. Wiley Class Discussion - Intellectual Property development process and initiatives for sustainability and growth Due date(s) will be given --Week 11 NPOs Supply Chains (In-class implementation) PART A Will try to empirically model NPOs w.r.t. sector. Elements to incorporate in supply chains: legitimacy, mission and directives, sources of income, markets, means of penetration, communication channels, distribution channels, transactions costs, fund accounting, value creation PART B Supply Chains are “naturally” prone to disruption for various reasons. Reasons tend to reside in the economic-political-social “manifold”. For each element to identify conventional sources of disruption. Identify methods and tools that are robust and practical for risk indication. - Knowledge and skills in capital markets and economics often are relevant - Knowledge and skills from week 7 - 10 may be invaluable. - Note: world development indicators and world bank indicators may be too lagging and broad sighted, but still respected - May not be captured by any of the priors, since causes may be highly microeconomic or being operational risk/hazard Such methods and tools to be applied to the chosen NPOs in part A for particular operations. PART C Cost-Benefit Analysis (CBA) for charity projects (2-3 Cases for CBA) Framework and logistics Settings based on Part A and part B is a good start Monetised: Costs and Benefits Non-monetised impacts: Cost and Benefits Discounting Findings PART D Managing project risk overview. Will try to construct a fast logistical model for cases based on the following text due to time constraints: Edwards, P., Vaz-Serra, P. and Edwards, M. (2019). Managing Project Risk. Wiley --Week 12 Fiscal Management and Accounting Lecturing Assist: Towle, J. A. (1992). Fiscal Management for Non-Governmental Organisations: A Practical, “How To” Manual to Assist Environmental NGOs in the Eastern Caribbean. Island Resources Foundation Group Assignment: student groups will be assigned 3-4 NPOs/NGOs where they must acquire the essential financial statements for 5 – 6 years. Financial statements (with adjustments) towards -- Financial Ratios: Fundraising Ratio Programme Expense Ratio Operating Reserve Ratio Quick Ratio or Current Ratio Viability Ratio Programme Efficiency Ratio Operations Reliance Ratio Trend in each prior ratio Financial Integrity: Cash Flow Analysis Beneish model Dechow F model Modified Jones Altman Z-score Are valuation methods for corporate firms towards M&A directly applicable to NPOs in M&A? Due date(s) will be given --Week 13 - 14 Strategic Management Resource Advantage Theory treatment: Topaloglu, O., McDonald, R. E., & Hunt, S. D. (2018). The Theoretical Foundations of Nonprofit Competition: A Resource-Advantage Theory Approach. Journal of Nonprofit & Public Sector Marketing, 30(3), 229 – 250. Group Assignment: Following analysis of Topaloglu et al (2018) literature, groups will be assigned 3-4 competing NPOs/NGOs where they are to develop competitive strategy structured on resource-advantage theory, and based on data, resources and tools mentioned, given or applied in course; crucially as well, intelligence and skills from prior weeks also to be invaluable. Due date(s) will be given. PESTEL and SWOT (with templates): Assisting literature: Understanding your External and Internal Context for Better Planning and Decision-Making (UNICEF) -> https://sites.unicef.org/knowledge-exchange/index_83128.html Group Assignment (Due date(s) will be given): PESTLE analysis and SWOT Analysis for 3-4 NPOs/NGOs How does the R-A theory study compare/contrast with PESTEL/SWOT? --Week 15 Financial Resources Membership dues, private donations, sale of goods & services, gov’t funding, grants from other non-profits, loans Grants Learning Search for Grants That Fit Your Nonprofit Organization. Where and how? Ambiance counterpart to: https://www.grants.gov/learn-grants.html Issue of historical preservation (operations legacy, contributors, intellectual property) --Week 16 - 17 Technology Integration 1. Discern the various elements and questions related to workplace technology 2. Create a strategy for technology planning 3. Decide on technology plans and how to choose technology. Note: must include SWOT among the companies and products/portfolio Note: must include 5C Analysis implementation for companies with products. Develop trend observation as well. Note: must include financial analysis for companies with products, plus Beneish, Dechow F, Modified Jones, Altman Z (all with trend). 4. Technology Transition Planning (examples): https://orta.research.noaa.gov/plans/ https://www.tswg.gov/TechnologyTransition.html 5. Cybersecurity scheme subjugating/constraining priors For steps 1 - 4 the following literature provides guidance for different industries with technology integration -> *Campise, J. A. (1972). Choosing a Computer System for Project Management. Project Management Quarterly, 3(4), 13–16. *Quinn, S. D. et al (2018). National Checklist Programme for IT Products – Guidelines for Checklist Users and Developers. NIST Special Publication 800-70 Revision 4 *Information Technology Investment Management: A Framework for Assessing and Improving Process Maturity. GAO March 2004 Version 1.1 GAO-04-394G *National Centre for Education Statistics – Forum Unified Education Technology Suite: https://nces.ed.gov/pubs2005/tech_suite/index.asp *Health & Human Service ECLKC: https://eclkc.ohs.acf.hhs.gov/organizational-leadership/article/whats-involved-technology-planning *Bhangoo, T. (2020). How to Select the Right Technology Solution: Five Strategies for Leaders. Forbes Note: groups to be given sets of technologies products concerning a particular sector of non-profits, to gather intelligence and analyses towards choice selection. --Week 18 Performance Measures. Stakeholder Engagement PM Resources: Chartered Professional Accountants of Canada – Performance Measurement for Non-Profit Organisations (NPOs) USAID - The Performance Management Toolkit A Guide to Developing and Implementing Performance Management Plans Features of a Stakeholder Engagement (toolkit) with robust methodologies Prerequisites: Enterprise Data Analysis I & II, International Financial Statement Analysis I & II. Corequisite: Introduction to Computational Statistics for Political Studies Financial Management for Non-Profit Organisations By the end of this course, students will be able to: Understand techniques for financial planning, decision-making, and working capital management in non-profit organizations Employ cost allocation techniques to non-profit organizations. The following learning outcome is addressed in this course: Students will demonstrate knowledge of financial management for non-profit organizations. Flanking Texts --> Weikart, Lynne, Greg Chen, and Ed Sermier. 2012. Budgeting and Financial Management for Nonprofit Organizations. Thousand Oaks, CA: CQ Press Zietlow, John, Jo Hankin, and Alan Seidner. 2007. Financial Management for Nonprofit Organizations: Policies and Practices. John Wiley & Sons, Inc. FASB Guidelines --> FASB Not-for-Profits Financial Reporting Standards Grant Management Guideline --> National Endowment for The Arts Office of Inspector General - Financial Management Guide for Non-Profit Organisations, September 2008 Note: grant awards lower than $500K individually may require audits in other industries. NOTE: COURSE LEVEL WILL REFLECT PREREQUISITES Tools --> Microsoft Office 365 Microsoft Dynamics R + RStudio SEC and IR databases Balance Sheet (Statement of financial position); Income Statement (Statement of Activities); Statement of Functional Expenses; Non-Profit Financial Statement of Cash Flows; Internal Revenue Filings Many NPOs and Public Administrations will be applied as case examples with their data. Course Assessment (based on the given 9 elements) --> 1. Assignments based on lecturing texts and FASB guidelines 2. Questionnaires and Structuring Assignments Tax accounting and a right to gross expenditures Conditions for exemptions on profit tax Value added tax Local tax 3. NGO/NPO summaries 4. Labs 5. Assigned tasks from: Wang, H. (2014). Financial Management in the Public Sector: Tools, Applications, and Cases. Routledge Tasks to include real data from actual public sectors or campus programmes (since data is easily accessible) 6. Specified Team Assignments in modules 7. Develop financial statements for assigned local NPO or campus institution NPO programme term assignment 8. Forecasting and Operating Budget Group Term Assignment 9. Obligation of 3 Exams Essential Labs --> -Summarize the differences between financial accounting and managerial accounting. Tools and techniques that differentiate and what they reveal. -Acquisition of financial statements from SEC and other gov’t realms. Read and interpret/analyse non-profit financial statements. Horizontal analysis, Vertical Analysis, and developing ratios. -Capital Budgeting Time Value of Money Understand the concept of the time value of money and apply it to various types of financial decisions (e.g. creating sinking funds). Making use of spreadsheet skills for priors. Cash Budgeting Organizing spreadsheets into modules for different parts of a company and linking results; using a one-variable input table for sensitivity analysis to evaluate alternate operating tactics. Multi-variable input extension. Understanding the role of a cash budget in a company’s marketing, production, and financial operations; examining the impacts of changing conditions on cash flows: forecasting the short-term borrowing a CFO must plan for. Spreadsheet skills: creating spreadsheets that evaluate the financial payments from various types of capital investments; using one- and multi-variable input tables to analyze the sensitivity of financial payoffs to changes in conditions. Evaluate financial payoffs from different types of capital investments, such as investing in new facilities, replacing equipment; determining whether to lease or buy equipment. -Analysis and development of the following: Baber, William & Roberts, Andrea & Visvanathan, Gnanakumar. (2001), Charitable Organizations' Strategies and Program-Spending Ratios. Accounting Horizons 15(4): 329-343. Possible implementation with chosen organisations. Identifying trend over various years with quarterly/semi-annual/annual benchmarks -Utilize budgeting and financial planning methodologies -Social Return on Investment (SROI) Cooney, K. and Lynch-Cerullo, K. (2014). Measuring the Social Returns of Nonprofits and Social Enterprises: The Promise and Perils of the SROI, Nonprofit Policy Forum, 5(2), pp. 367-393 Will make use of gov’t projects/investments/programmes because data will be highly accessible and transparent. 2-3 cases to be done. Exams --> Exams will assess development based on weekly readings, and (1) to (4) of course assessment. Expect use of Microsoft Office tools and R as well. Develop financial statements for assigned local NPO Term Assignment --> Work with assigned (local) NPO groups to develop financial statements Forecasting and Operating Budget Group Term Assignment --> Note: students will use of intelligence and skills from their obligations PART A -- For a campus institution or programme estimate/forecast revenues & expenses based on Y size period history. Then compare to an actual established budget following. Apply variance analysis and control management. PART B -- For a campus institution or programme students to engage in walkthrough logistics and development of cost-benefit analysis for budgeting or project; means of identifying rational alternatives towards CBA. PART C -- Prepare an operating budget for chosen campus institution or programme. You will retrieve relevant sets of financial data, given a X-year history of the Statement of Financial Position and Statement of Activities. In addition to the financial history, you will be given a set of budget assumptions to guide you in the preparation of the budget, as well as a budget workbook. You are to prepare a balanced operating budget as directed by the trustees. In addition to submitting the budget workbook with the balanced operating budget, you must prepare a written budget justification memo addressed to the board of trustees explaining the decisions you made in balancing the budget. The budget justification memo must address each line (revenue and expenses) on the operating budget. There will also be presentations. Note: lecturing, intelligence, skills from assignments and labs will be invaluable. PART D -- Financial modelling for nonprofits. Groups to develop a financial model for a nonprofit or programme of the campus. Key essentials for financial model: What elements involved in building a financial model for common corporate firms are relevant to nonprofits? What non-monetized concerns or sensitivities apply to nonprofits concerning a financial model development? Course Outline --> INTRODUCTION TO FINANCIAL MANAGEMENT IN NON-PROFIT ORGANISATIONS 1. Articulate the context of financial management in non-profit organizations 2. Articulate the primary financial objective for a non-profit organization 3. Provide a rationale for liquidity management 4. Identify the basic financial statements for a non-profit organization, and associated laws with Securities Exchange commission and Internal Revenue 5. Differentiate between a commercial organization and a non-profit organization 6. Articulate non-profit accounting concepts and terminology related to non-profit organisations UNDERSTAND NON-PROFIT FINANCIAL STATEMENTS 1. Interpret non-profit financial statements 2. Articulate cash versus accrual accounting 3. Articulate how organizational effectiveness is reflected by financial data 4. Differentiate non-profit financial statements from commercial statements 5. Interpret the statements of financial position, activities and cash flow and toe role of notes to the statements. 6. Interpret financial statements by classification 7. Make funding decisions based on analysis of financial statements for non-profit organizations MANAGING STRUCTURE, ETHICS & ACCOUNTABILITY & ACCOUNTING FOR JOINT COSTS 1. Build a structure for a non-profit organization that incorporates all of the elements including board structure as well as the management structure 2. Create an accountable organizational structure 3. Articulate how the financial management function fits into the overall organization structure 4. Develop methods to monitor accountability 5. Allocate joint costs in a non-profit organization MANAGING LIABILITIES/SARBANES – OXLEY (or ambiance counterpart) FOR NON-PROFITS 1. Make decisions on how to finance a non-profit organization 2. Articulate an overview debt and how it can be utilized. 3. Develop a plan for debt management. 4. Develop a debt policy 5. Match financial sources to strategic objective 6. Develop a plan on how to manage banking relationships 7. Articulate how the titles of Sarbanes Oxley (or ambiance counterpart) can help non-profit organizational efficiency and transparency Teams to be formed to apply such prior skills to 3 or 4 NPOs assigned FUNDING MODELS Foster, W. L., Kim, P. and Christiansen, B. (2009). Ten Nonprofit Funding Models, Stanford Social Innovation Review Forbes Non-Profit Council. (2021). 10 Ways Nonprofits Can Develop A Self-Funding Model. Forbes Teams to be formed to apply chosen methods from latter article based on given settings. Be sensitive to the costs and benefits. ASSETS 1. Investment of the nonprofit organization’s assets. 2. Fiduciary structure and policy 3. Complexities and the contributing factors to these include: risk and mitigation (market volatility, liquidity, credit, interest), investment styles, manager selection challenges, and alternative investments choices. 4. Survey investment objectives and policies for both short-term and long-term investments. 5. Means of appraisal or valuation of the specific assets at time T. 6. Risk identification, risk measurement and risk mitigation for specific assets. FINANCIAL PLANNING, OPERATING AND CASH BUDGETS 1. Articulate the overall budgeting function in a non-profit organization 2. Role of Financial Statements (FS), Operations Reports (OR) and data history from FS and OR 3. Develop a process for creating a budget 4. PESTLE AND SWOT analysis in a budget plan 5. Utilize variance analysis and create a management control tool 6. Respond to budgeting difficulties and utilize various budgeting tools to improve performance 7. Articulate the use of program budgeting, flexible budgeting and rolling budgets. Teams to be formed to apply such prior skills to various programmes of the institution. CAPITAL STRUCTURE OF NPOs 1. Static Trade-Off Theory vs Pecking Order Theory 2. Non-Profit Capital Structure & Endowments 3. Contrasting Literature The methodologies and data sets applied are of great interest. Analyse the respective empirical research, then replicate. Then augment with more modern data. Note: hopefully data sets are easily accessible, else there’s usually alternative respected data sets to apply. Calabrese, T. D. (2011). Testing Competing Capital Structure Theories of Nonprofit Organizations. Public Financial Publications Garcia-Rodriguez, I., Romero-Merino, M. E., & Santamaria-Mariscal, M. (2022). Capital Structure and Debt Maturity in Nonprofit Organizations. Nonprofit and Voluntary Sector Quarterly. FUND ACCOUNTING Unrestricted Funds, Restricted Funds. Recognition of self-balancing set of accounts with its own revenues and other additions, expenditures and other deductions, assets, liabilities, and fund balance. Reporting. Teams to be formed to apply such prior skills to various programmes of the institution. AUDITING IN NON-PROFTS 1. A clean audit opinion merely states the financial statements accurately reflect the organisation’s true financial structure –good or bad. 2. Auditing Types Internal Audits Audits performed under the Generally Accepted Auditing Standard Agreed Upon Procedure (AUP) 3. Audit by law? 4. Why a nonprofit may conduct an audit even when law doesn’t require it. 5. Intelligence on External Audit Preparation: https://rmas.fad.harvard.edu/pages/preparing-external-audit 6. Internal Audit Checklist (Cash) and logistics 7.Integrity For common potential cash fraud schemes identify the risks and indicators, along with complimenting auditing procedures Vertical Analysis and Horizontal Analysis with financial statements. Teams will audit departments or programmes in the institution and elsewhere based on identified schemes, checklists, analyses, models, laws and scores prior. Done also for municipal and provincial statements/data. 8. Concerning 2-3 NPOs with gov’t grants record of at least $X identify the audits required by government regulation for grant expenditure 9. Case for NOT conducting an independent audit Audit expense for small non-profits Audit cost-grant differential Observation of charge rates subject to revenue More affordable alternatives Review Compilation Differentiation: Review vs Compilation vs Audit Will preparation be the same for Reviews and Compilations? 10. Additional ways to demonstrate financial transparency Teams will be assigned various programmes of the institution to determine how well financial transparency has been established sans use of external audits. Can the observations be validated? Compare to operations based on (5) to (7). 11. Board of directors Cost-Benefit Analysis for External Audits INTEGRITY IN INVENTORY 1. Integrity audit preparation and inventory audit logistics 2. Inventory Metrics 3. Linking inventory to financial statements 4. Wells, J. T. (2001). Journal of Accountancy. Teams to be formed to apply such prior skills to institutions or 3 or 4 NPOs assigned. FINANCIAL HEALTH 1. Focus on managing the balance sheet. Every dollar of assets on the balance sheet must be financed with either a dollar of debt or a dollar of equity (net assets). Will discuss the positive and negative aspects of using debt in the nonprofit organization’s capital structure. 2. Through financial statements adjustments and other skills apply the following: Ratio Analysis Fundraising ratio Programme Expense ratio Operating Reserve ratio Quick ratio, Current ratio Viability ratio Programme Efficiency ratio Operations Reliance ratio Data Integrity and Health (DIH) Cash Flow Analysis Beneish model Dechow F Modified Jones Altman Z-score Note: for DIH substitute with NPO counterpart ratios when needed. 3. Identify liquidity management methods/strategies. 4. Klotz, C. (2020). Nonprofit Liquidity: Better Financial Storytelling under ASU 2016-14. The CPA Journal 5. Prepare internal financial reports that are used for management and governance decision making. 6. Understand the finances of the nonprofit with particular emphasis on analysis of the fiscal information and congruence with the 990 report (or ambiance counterpart) and its actual work. Be able to comment on the long-term trends and financial stability of the organization. Teams to be formed to apply such prior skills to 3 or 4 NPOs assigned FINANCIAL SUSTAINABILITY 1. Pursue a practical explanatory model of financial sustainability for non-profits 2. How does such model critique particular NPOs? Will pursue case examples. Prerequisites: Enterprise Data Analysis I & II, International Financial Statement Analysis I & II. Corequisite: Introduction to Computational Statistics for Political Studies. Public Policy Formulation and Implementation An introduction to the key stages through which public problems are recognized, channeled into the political process, and policies to address them formulated and implemented. Critical reflection on the manner in which political practices, institutions, and stakeholders influence the framing of issues, the alternatives that enter debate, and the evolution of public policies over time, and their ultimate impacts on society. Guide text --> Jodi Sandfort and Stephanie Moulton. (2015). Effective Implementation in Practice: Integrating Public Policy and Management. Jossey-Bass. 416 pages Note: make use of appendices as well Tools --> PolicyMaker software < https://michaelrreich.com/policymaker-software/ > Resources --> Executive record/literature (offices, departments, agencies, bureaus, etc.) Almanac of Policy Issues/Agendas: Culture & Society Economic affairs Education Health & Social Welfare Criminal Justice Environment Foreign Affairs National Security Documentation/literature/data from various elements of the public sector or public administrations Gov’t Bureaus or Agencies (data, statistics, literature) IGOs (data, statistics, literature) Congressional record (bills, bill estimator/estimation) Constitutional record Judicial review & record (when relevant) Course Assessment --> Resonating elements and skills in (all) assignments Policy Questions Labs Literature Synthesis Papers Constitutional and Policy Issues Policy Content Evaluation Team Research Project & Presentations Resonating elements and skills in all assignments --> MANDATORY when applicable: The background of the policy issue chosen for studies Stakeholders (Principals spectrum and Agents spectrum involved) Relevance and self-interests, for respective entity Policy tools and instruments Applying models and theories of public policy Programme Theory. Theory of change with policy < https://www.jmu.edu/assessment/sass/ac-step-two.shtml > The pre-implementation impact assessments Possible instruments to deter moral hazard Stakeholders (Principals spectrum and Agents spectrum involved) Cost-Benefit analysis (OFTEN) Monetised: costs and benefits Non-monetised Impacts: amenity, aesthetics, environment, ecological, heritage, culture Non-Monetised Benefits Manual: Qualitative and Quantitative Measures, Waka Kotahi NZ Transport Agency 2020 (OFTEN); costs analogy included Discounting Campbell, H., & Brown, R. (2003). Benefit-Cost Analysis: Financial and Economic Appraisal using Spreadsheets (pp. 194-220). Cambridge Univ. Press. Actual perceived consequences Recommendations Proper citations and references Literature Synthesis Papers --> Each student is required to write three (3) short literature papers synthesizing the approaches and leading issues identified in the readings for the weeks designated. The papers are to include references (when relevant). There are several ways the formulation and implementation of public policy is approached in the field and illustrated in the class through various issues and themes, from an historical development of the ambiance political institutions, issues of values and ethics, organisation capacity, stakeholder engagement, causal theory, mandate design, etc. Must demonstrate your grasp of the assigned readings and how they relate to your understanding of the formulation and implementation process. Policy Questions Labs (1-2 policies per lab) --> Hinrichs-Krapels, S. et al (2020). Palgrave Communications 6:101 (H-K) Note: lab elements will be stretched out appropriately to course obligations 1.Issue Identification and Definition: https://www.gov.nl.ca/pep/issue-identification-and-definition/ 2.Issue Identification (H-K) Additional questions: Is there a need of new policy on respective topic/issue? What credible empirical evidence (social, economic, environmental) conveys such? What are the causes(s) and how to verify? Do any current policy contribute to the problem? 3.Developing options based on the findings along with respective policy network identification and means of enforcement, respectively. Theory of change, respectively. 4.(Multinomial) Logistic Regression to estimate and predict perceptions. 5.Policy Feasibility Analysis (implementing the steps) 6.Policy Formulation (H-K) What is the best available evidence to use in formulating respective policy? What are the options in implementing respective policy? 7.Policy Implementation (H-K) What are the barriers/facilitators of implementing this policy? What is the best way to implement respective policy to allow for evaluation? Evaluate the costs and benefits of implementing. 8.Policy Evaluation (H-K) How should respective policy be evaluated? Constitutional and Policy Issues --> Entities may challenge the efficacy of policies based on constitutional amendments/components to argue a series of unintended consequences that may undermine policy and polarize groups against one another. Case studies characterising policy and intent, institutions and stakeholders, provocation entities vs advocacy entities, analysing intent vs counterfactuals (logically and legality), empirical standing. Judicial review and ruling. Team Research Project & Presentations (3-5 teams) --> The deliverables: -Mid-term presentation focused on a statement of the ‘problem’ being addressed and approach to research The “problem” being addressed (evidence and interests) The policy adopted to address the problem The theory of change underlying the policy The researchable questions the team wants to answer The methodology that will be employed to answer research questions Identification of responsibilities of the individual team members -Toward the end of the term, a presentation on research findings, suggestions for improving the implementation process, and the team’s view of the ideal (best imaginable) way for society to address the problem Brief restatement of the problem (evidence and interests) and policy Scholarly research on the policy Research questions and findings Strengths and limitations of the teams research and findings Assessment of the effectiveness of the policy’s implementation Recommendations for improving implementation References and any appendices -Policy Memo to gov’t executive head (3-5 pages) Applies acquired intelligence and skills from course, including the key dimensions of your implementation strategy; cautions or qualifications to include. Prerequisites: Public Policy (check PS) Fiscal Administration Introduction to the basics of budgeting in government. Budgeting represents an essential part of any government because it is through budgeting that elected politicians and appointed officials set their goals for the government, as well as developing the resources to meet those goals. NOTE: most topics will emphasize much observation and analysis of public data. Optional Text --> Mikesell, Fiscal Administration, Tenth Edition (2018), Wadsworth Note: there are data sources to accompany text for real world settings and data. Supporting Literature (mandatory) --> Country analogy to -- Congressional Budget Office: Budget Concepts and Processes: https://www.cbo.gov/topics/budget/budget-concepts-and-process Cornia, G., Nelson, R., & Wilko, A. (2004). Fiscal Planning, Budgeting, and Rebudgeting Using Revenue Semaphores. Public Administration Review, 64(2), 164-179. Potter, B. H. and Diamond, J. Guidelines for Public Expenditure Management. International Monetary Fund Fiscal Transparency Handbook. International Monetary Fund 2018 Resources --> Government/Public Administration financial repositories/archives/databases of various geopolitical scales. NOTE: most lecture topics will emphasize much observation and analysis of public data. Tools --> Microsoft Office 365 R + RStudio Quizzes --> Closed book and closed notes. Concerns vocabulary, concepts and knowledge. Exams --> -Part of exams will resemble quizzes. Closed book and closed notes. -Part of exams will concern active acquisition of public data where students will perform tasks and provide elaboration/analysis. Example of data sources (for various years): Executive Leadership’s OMB, CBO, Treasury, Budget Analysis, Fiscal Financial Statements, National Accounts. Open notes. -Part of exams concern applying methods and tools introduced in course and from supporting literature; given when lectured prior. Open notes. -Exams may have variations among students. Fiscal Health Analysis Reports --> Student groups will develop a fiscal health report for assigned 1.Public Service or public administration (in boroughs or district) 2.City or municipality (will also include Altman Z-score) 3.Province (will also include Altman Z-score) Public service Example: for schools in a particular province providing a set of financial indicators for each school district that may be used by various levels of government and citizens to evaluate the financial health of the province’s school districts. Idea example: https://www.cde.state.co.us/cdefinance/fiscalhealthanalysisjuly2014 Note: students are expected to cite data sources, literature and proper guidance for models, computations and displays. Note: to accompany, methods and tools of determining quality programmes and productivity. Course Grade Constitution --> Quizzes Exams Projects Analysis of gov’t financial statements with ratios development Taxation – Evaluation Criteria module Forecasting module Fiscal Sustainability module Wang, H. (2014). Routledge Fiscal Health Analysis Assisting guides for pursuits for public goods, public services (provincial, municipal and borough levels): Suarez V., Lesneski C. and Denison, D. (2011). Making the Case for using Financial Indicators in Local Public Health Agencies. Am J Public Health 101(3), pages 419-25. McDonald, B. D. (2018). Local Governance and the Issue of Fiscal Health. State and Local Government Review, 50(1), 46–55. Augment with Beneish, Dechow F, Modified Jones & Altman Z Groups will be assigned specific tasks for various public sectors, public agencies, etc. Public-Private Partnership Case Studies Grossman, S. A. (2012) Koontz, Tom & Thomas, Craig. (2012). Course Outline --> 1.Principles of Public Finance 2.Income Taxes and Property Taxes What are the models? 3.User Fees and Taxes on Goods and Services What are the models? 4.Taxation – Evaluation Criteria Objective: to develop taxes and a tax system that serve the broad needs of society in an efficient, fair and impartial way. Ideal taxation criteria: economic efficiency, economic competitiveness, administrative simplicity, adequacy, and equity/fairness. Task: what tools or methods exist to evaluate for the earlier given 5 criteria? How are they implemented? Verifying/implementing such tools or methods for chosen provinces. Diverse public opinion: citizen or resident views taxes differently based on the taxes they pay and the benefits they receive. Consequently, selecting taxes and designing a tax system for state and “local” revenues is a process of trade-off and compromise. Task: demography development for income/taxing segmentation concerning assigned region of interest. Outstanding public goods, services and utility to be identified for trade-off development. Task: development of articles with modern data Plumley, A. H. (1996). The Determinants of Tax Income Compliance: Estimating the Impacts of Tax Policy, Enforcement, and IRS Responsiveness. Internal Revenue Service. Publication 1916 (Rev. 11-96) Catalog Number 22555A Gemmell, N., & Hasseldine, J. (2014). Taxpayers’ Behavioural Responses and Measures of Tax Compliance “Gaps”: A Critique and a New Measure. Fiscal Studies, 35(3), 275–296. 5.Tax Expenditures and Distribution among households 6.Automatic Stabilizers What explicit models or formulas create the offsets? Evidence of their function. 7.Forecasting Literature of interest: Simalto: can be applied to predicting which of the alternative combinations of optional service benefits provided by a local authority, state or national government in their annual budget would meet with the ‘maximum’ approval of a target population. International Monetary Fund. (1985). " Chapter 9 WORKSHOP 7 Revenue Forecasting". In Financial Policy Workshops. USA: International Monetary Fund GFOA. Financial Forecasting in the Budget Preparation Process, Government Finance Officers Association Williams, D. and Calabrese, T. (2019). The Palgrave Handbook of Government Budget Forecasting. Palgrave Macmillan 8.Budget Concepts (constructing the flow of things) Budget Baseline and Budget Options Budget Authority, Obligations, and Outlays Authorization Acts and Appropriation Acts Discretionary Spending & Mandatory Spending Implicit Obligation examples (medicare costs, retirement benefits, social welfare). Is it unique to entitlement spending? Interest on the debt Rescissions and Reappropriations Cash Accounting, Accrual Accounting, and Fair-Value Accounting Revenues, Offsetting Collections, and Offsetting Receipts Deficit and Debt On-Budget and Off-Budget Cost Estimates, Dynamic Analysis, and Scorekeeping Calendar Year and Federal Fiscal Year 9.The Budget Process Note: will be subjugated by the Budget Concepts module prior Federal agencies create budget requests and submit them to the Executive Leadership’s Office of Management & Budget (OMB). OMB and the Executive Budget Process Followed by analysis of literature: Government Leader’s Budget Request Congressional Budget Office (CBO) Maintaining the Baseline Estimating cost and revenue Scoring revenue and spending bills Economic Projections Long term financial status Legislative Budget Process Budget Approval Discretionary, Mandatory, Interest on Debt Budget Execution Laws enacted for failure to meet deficit target. Complimentary Text: Potter, B. H. and Diamond, J. (1999). Guidelines for Public Expenditure Management. International Monetary Fund Fiscal Consolidation 10.Fiscal Federalism 11.Cost Accounting & Auditing Methods/Tools 12.The Deficit, Debt and Debt Ceiling 13.Fiscal Sustainability Examining the size of long-term fiscal imbalances Burrnside, Craig. 2005. Fiscal Sustainability in Theory and Practice: A Handbook. Washington, DC: World Bank From prior text I may ask students to apply tools to countries or provinces in more modern times. 14.Will pursue some implementations from the following based on real data from the public sector. Wang, H. (2014). Financial Management in the Public Sector: Tools, Applications, and Cases. Routledge 15.Public-Private Partnerships Implement cases studies based on: Grossman, S. A. (2012). The Management and Measurement of Public-Private Partnership: Toward an Integral and Balanced Approach. Public Performance & Management Review, 35(4), pages 595–616 Koontz, Tom & Thomas, Craig. (2012). Measuring the Performance of Public-Private Partnerships: A Systematic Method for Distinguishing Outputs from Outcomes. Public Performance & Management Review. 35(4). 769-786. 16.State and Local Governments GFOA. Best Practices: Financial Forecasting in the Budget Preparation Process Best Practice: A Framework for Improved State and Local Government Budgeting, NACSLB, 1998 17.A Manual on the Design and Conduct of Public Expenditure Reviews in Caribbean Countries. Cepal, United Nations 2017 Prerequisites for PA & PS: Enterprise Data Analysis I & II, International Financial Statements Analysis I & II, Quantitative Analysis in Political Studies I Prerequisites for FIN & ECON: Enterprise Data Analysis I & II, International Financial Statements Analysis I & II, Introduction to Computational Statistics for Political Studies, Junior Standing. Government Accounting This course is designed to cover financial reporting, managerial, auditing and information systems issues in governmental entities. Students will apply dual-track accounting to help develop skills at analyzing transactions in a governmental entity and follow their effect on the financial statements. The course is presented in two parts. Part 1 covers state and local government. Part 2 focuses on accountability for public funds. Course Text --> Reck, J., Lowensohn, S. & Wilson, E. (2013). Accounting for Governmental and Nonprofit Entities. New York, NY: McGrawHill Irwin. Accounting Resources (or ambiance compart) --> Financial Accounting Standards Board (FASB) Governmental Accounting Standards Board (GASB) Federal Accounting Standards Advisory Board Resources --> Government/Public Administration financial repositories/archives/databases of various geopolitical scales. NOTE: most lecture topics will emphasize much observation and analysis of public data. Tools --> Microsoft Office 365 Microsoft Dynamics R + RStudio Assessment --> Assignments Weekly or Bi-Weekly Quizzes Midterm Examination Financial Statement Analysis (4-5) City Of Smithville Project Economic Development Project Analysis & Presentation Final Examination Financial Statement Analysis (on multiple ocassions) --> Using a government’s comprehensive annual financial report, budget document, and other relevant reports, students will analyse the financial statements with traditional financial analysis tools as described throughout the course. Assigned gov’ts to vary among students. City Of “Smithville” Project --> The well known comprehensive project for students. However, I personally don’t like “sealed off proprietary environments” when education for public service is relevant. Plagiarizing other past students’ labour, or copying other students are concerns. Goal is to make project highly relevant with real data. Namely, becoming highly acclimated with government accounting practice by use of actual data from a municipality or province to administer such a project. Hence, groups will be assigned unique environments Economic Development Project Analysis & Presentation --> Small working groups will be assigned during class. Students will be asked to take on the role of a municipal CFO and evaluate a proposal for an economic development project. Using a detailed case study real project, groups will analyse the benefits and costs of the proposal and produce a recommendation. Course Obligations --> 1.Introduction to Accounting and Financial Reporting 2.Principles of Accounting and Financial Reporting 3.Governmental Operating Statement Accounts 4.Accounting for Governmental Operating Activities 5.Accounting for Capital Assets and Capital Projects 6.Accounting for General Long-term Liabilities and Debt Service 7.Accounting for Business-type Activities of State and Local Governments 8.Accounting for Fiduciary Activities – Agency and Trust Funds 9.Financial Reporting of State and Local Governments 10.Analysis of Governmental Financial Performance 11.GAO Financial Audit Manual (for local or provincial level): https://www.gao.gov/financial_audit_manual It’s quite important that students also comprehend what documents and data apply (where and how) when the logistics are treated; applying what’s what, where to find, and process/method for assimilation. 12.Budgeting and Performance Management Prerequisites for PA & PS: Enterprise Data Analysis I & II, International Financial Statements Analysis I & II, Introduction to Computational Statistics for Political Studies, Junior Standing. Crisis Management Means to develop workable plans for natural and industrial type disasters and emergencies. Principles and techniques preparing for various types of disasters, loss prevention measures, and preservation of organisation resources are discussed. Case study approach is used to develop and refine the desired application and critical skills. Evolving process with decision making and crisis management; cooperation, consistency and transparency are other key factors to establish. Student learning outcomes: 1. Critically review emergency disasters, both major and minor, detailing the preparations, response, and recovery. 2. Apply selected plans to actual sites to evaluate their strength and weaknesses as mechanisms for strategy “real world” sites. 3. Develop a comprehensive emergency plan for a specific type of emergency. 4. Complete exercises and projects to enhance their knowledge of comprehensive emergency management. Course Text --> Phillips, B., Neal, D. & Webb, Gary (2012), Introduction to Emergency Management, CRC Press. Augmentative Literature and Tools --> 1.Risk Management Guide for information Technology Systems Stonebumer, G., Goguen, A. and Feringa, A. (2002). Risk Management Guide for information Technology Systems: Recommendations of the National Institute of Standards and technology. Special Publication 800 – 30 Note: this literature is archived for historical purposes, but it’s much more tangible with academic and field exercises than its successor(s). This specified version above to be used to assess multiple environments. 2.United States Environmental Protection Agency Human Health Risk Assessment Tools (and Databases) Ecological Risk Assessment Tools (and Databases) Note: choice of tools for lesson planning/activities/projects will require dedicated search, proper comprehension, and proper tool acclimation. 3.WHO: Manual for Investigating Suspected Outbreaks of Illnesses of Possible Chemical Etiology Guidance for Investigation and Control Logistics. For certain features will like to identify what types of administrations, data, tools and skills will be required to make such features accessible or tangible or quantifiable or qualitatively credible. 4.FEMA Benefit-Cost Analysis: https://www.fema.gov/grants/tools/benefit-cost-analysis 5.Predicting and Assessing the Impact of Hurricanes with GIS. To develop with a GIS of choice Taramelli, A. et al. (2008). Estimating Hurricane Hazards Using a GIS system, Nat. Hazards Earth Syst. Sci., 8, 839–854 Meng, X. et al. A Simple GIS-Based Model for Urban Rainstorm Inundation Simulation. Sustainability, 2019, 11, 2830 6.HEC-FIA Immersion 7.Human Casualties in Earthquakes Spence, R., So, E., & Scawthorn, C. (2011). Human Casualties in Earthquakes Progress in Modelling and Mitigation. Springer Netherlands Chosen chapters that are highly tangible and quantitative will be used as frameworks for projects. Will require environment data, infrastructure data, etc., etc. Apply to different natural disasters and confirm whether developments are consistent with official reports for specific beginning to “horizon”, respectively. 8.Modelling Excess Deaths Rivera R. & Rolke W. (2019). Modelling Excess Deaths After a Natural Disaster with Application to Hurricane Maria. Stat Med. 38(23):4545-4554. Replicate. Apply to other natural disasters and confirm whether developments are consistent with official reports for specific beginning to “horizon”. 9. FEMA Substantial Damage Estimator Tool: https://www.fema.gov/emergency-managers/risk-management/building-science/substantial-damage-estimator-tool Assessment --> I. Exercises, Case Studies and Projects 70% Based on course text AND given augmentative literature and tools II. Exams 30% There will be 2-3 exams based on lectures, assigned readings and applied sources. Students are to develop intelligence notes based on their belief what is critical knowledge from the readings towards use on exams; students will be informed on subject areas that may be encountered. Personal intelligence as well is warranted. Course Topics --> Emergency Preparedness Principles Regulatory Influences Interior Ministry Occupational Safety and Health Administration National Response Plan, National Response Centre Critical Infrastructure Protection Emergency Management Planning Vulnerability Assessments Plan Development and Implementation Chemical Emergencies Biological Emergencies Public Transportation Terrorism Natural Disasters Recovery Efforts Economic Impact Mitigation Prerequisites: Introduction to Computational Statistics for Political Studies (or Mathematical Statistics), Upper Junior level Research in Crisis and Crisis Mitigation Course employs students’ analytical, technology and empirical skills towards emergencies and crisis research. Obligations will be done in groups. Note: course has the social/society appeasement option. Some activities to be bundled into different projects based on connections and fluidity. NOTE: texts, literature, notes, assignments and projects from prerequisite can be useful to this course. External professional sources and data will have considerable amount of relevancy in respective project development; also includes legal referencing at times. Mathematical and data analysis skills will prove quite advantageous and provide much more quality. NOTE: instructor will provide walk-throughs for each project. Students will participate in changing groups. Term activities for all groups ---> (1) Information Technology & Security: PART A Shen et al, Managing Coordination in Emergency Response Systems with Information Technologies, IT for Emergency Response System Coordination, Proceedings of the Tenth Americas Conference on Information Systems, New York, New York, August 2004 https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.120.372&rep=rep1&type=pdf Environment evaluation. Then will choose without bias at least three past emergencies or crisis as walk-throughs. Such will incorporate fitting in agencies/authorities appropriately involving IT system networks towards the progression or diffusion of knowledge and coordination PART B Stonebumer, G., Goguen, A. and Feringa, A. (2002). Risk Management Guide for information Technology Systems: Recommendations of the National Institute of Standards and technology. Special Publication 800 – 30 Note: literature is archived for historical purposes, but it’s much more tangible with academic and field exercises than its successors. Will be used to assess multiple environments. (2) Networking and coordination in public health: PART A -- Advance repetition of investigating suspected outbreaks from prerequisite PART B -- The following can be a guide for administrative development in public health emergencies: U.S. Department of Health and Human Services Centers for Disease Control and Prevention. (2018). Public Health Emergency Preparedness & Response https://www.cdc.gov/cpr/readiness/00_docs/CDC_PreparednesResponseCapabilities_October2018_Final_508.pdf Resources are only as good as the efficiency of networking and coordination response. Restricting to the following sections --- Capability 3: Emergency Operations Coordination pp 34–41 Capability 6: Information Sharing pp 62–67 For tasks described in the two sections acquire the size of government towards preparedness and response; level(s) of administration and interactions relevant or appropriate for such two sections, with the respective support or operations they must provide. (3) Epidemics and Pandemics NOTE: some elements of (2) may or may not serve well with fluidity and tangibility. Interests or pursuits will not be based solely on Zika, so amend for other pathogens of interest. There may times where students will have development for past and future international “crises”. Analysis will incorporate professional literature and sources of supporting data. Some assists towards questions or concerns: World Health Organisation (2018), Managing Epidemics World Health Organisation (2016-2017), Zika Strategic Response Plan Saker, L. et al. (2004). Globalization and Infectious Diseases: A Review of the Linkages. Special Topics in Social, Economic and Behavioural (SEB) Research, World Health Organization. TDR/STR/SEN/ST/04.2 -For viral case considered identify the unique process of the biological infiltration, transmission, symptoms, level transmission difficulty, tenacity/mutation prowess. What environmental and weather parameters will support high possibility of accumulation? What ecological or habitat friendly resolutions are in place? Identifying migration pathways to optimise transmission. -Identify the public administration sector(s) with the systematic coordination protocol(s) for responsible identification of contagion threats, containment and resolution. What are the detailed protocols ranging from identification, detection, migration prohibition, containment and treatment? -How reliable is intelligence from contagion countries towards preparation and identification of transmission intensity with carriers subject to time frame? What international system exists that administrates or coordinates communication and data for identification of uncontrolled pathogen transmission? How does one determine a foreign epidemic threat to be a considerable threat? Identify what infection thresholds/rates and inability of treatment of contagion/antigen to initiate an epidemic/pandemic alert. -Observe the following two videos. Interest after concerns identifying the means of developing such a system, or recognition of such system network currently in operation. Inside ESSENCE: Providing early detection of epidemics – YouTube ESSENCE: Early Notification of Epidemics – YouTube For ESSENCE identification of technologies integrated. Logistics for network design and communication -Implementing the R package R0, where elaboration of functions and parameters will be pursued before implementation. -Projects to develop with R and GIS (contagion, ambiances and timelines subject to change): Sorichetta, A., Bird, T., Ruktanonchai, N. et al. Mapping Internal Connectivity through Human Migration in Malaria Endemic Countries. Sci Data 3, 160066 (2016). Rahman, M.R., Islam, A.H.M.H. & Islam, M.N. Geospatial Modelling on the Spread and Dynamics of 154 Day Outbreak of the Novel Coronavirus (COVID-19) Pandemic in Bangladesh Towards Vulnerability Zoning and Management Approaches. Model. Earth Syst. Environ. (2020). Coccia M. (2020). Factors Determining the Diffusion of COVID-19 and Suggested Strategy to Prevent Future Accelerated Viral Infectivity Similar to COVID. The Science of the Total Environment, 729, 138474. -Smoothing epidemic/pandemic data Often observed in time series data is high volatility within very small time intervals. Then will pursue computational development for smoothing of various data; not restricted to SARS/MERS. For smoothing what are the pros and cons upon raw time series? -Are transmission cases (rate) always explanatory for mortality (rates)? Elaborate on such. -Identification of legal structure for registry and containment of pathogen carriers in the interest of public safety, but also preserves rights to best of ability. Concerning individuals testing positive for whatever pathogen epidemic/pandemics, what legal policies are in place concerning proper identification, patient tracking, contact tracing and containment? How can the enforcement of residential quarantining or visitor quarantining be made possible? Penal code for quarantining and carriers. How is modern contact tracing developed and authenticated? -Are clinics or walk-ins less likely to be communicative/cooperative with official health epidemic emergency systems/networks due to the type of service characteristics? Are laboratories for testing (blood work, stool, saliva, urine, etc.) legally obligated to communicate troublesome findings to health emergencies public administration in advance before communication to medical site of origin with doctors? Communications systems requirements, regulations and protocols for testing facilities in the national response framework -For the case where no vaccination treatment is systematically/globally accessible (due to whatever priorities of countries, or if vaccines are still in development), what are the best resolutions? -The following can be developed towards ambiances of interest Grima, S. et al (2020). A Country Pandemic Risk Exposure Measurement Model, Risk Management and Healthcare Policy. Risk Management and Healthcare Policy, 13, 2067–2077. Recall the USA’s great challenge to mitigate the COVID 19 spread, compared to countries that are deemed economically and/or politically inferior. How are countries of lesser standing better performers in mitigation concerning country pandemic risk exposure measurement? -Crucial society deliverables and preservation of competent functionality. May need to identify or construct contingences/protocols for statutory sustainability against system pressures Law Enforcement Laws that can’t be suspended (criminal, financial, environmental protection, labour, etc.) and arguments for such Laws that can be suspended and arguments for such Policy on mortgages and other loans Mitigating sustenance price shocks Policy on Landlords and tenants Social welfare fiscal policy Subject to budget and fiscal intervention National Medical/Health directives Medical billing policies Public Transportation Service Commuter regulations and employee guidelines Traveler Restrictions and Checkpoints (land, aquatic, air) Freight Transport -DEA literature to analyse and develop for ambiance: Nepomuceno, T., Silva, W., Nepomuceno, K., & Barros, I. (2020). A DEA-Based Complexity of Needs Approach for Hospital Beds Evacuation during the COVID-19 Outbreak. Journal of Healthcare Engineering, 2020, 8857553. Ibrahim, M. D., Binofai, F., & MM Alshamsi, R. (2020). Pandemic Response Management Framework based on Efficiency of COVID-19 Control and Treatment. Future Virology, 10.2217/fvl-2020-0368. Means of perpetually updating data that’s authentic (official). What are the most forefront information systems in operation for epidemics/pandemics with data assimilation assistance and networking? -Analyse and develop the following article: Ivanov, D. (2020). Predicting the Impacts of Epidemic Outbreaks on Global Supply Chains: A Simulation-Based Analysis on the Coronavirus Outbreak (COVID-19/SARS-CoV-2) Case. Transportation Research. Part E, Logistics and Transportation Review, 136, 101922–101922. Can also be augmented for analysis with other epidemics/pandemics -The following two sources can be used in comparative analysis fashion to develop a premature sustenance supply-demand model that doesn’t economically hinder vendors and customers during crisis --> Wernau, J. (2020). How China Kept its Supermarkets Stocked as Coronavirus Ravaged. The Wall Street Journal Peltz, J. F. and Dean, S. (2020). Sales are Up at Supermarkets. But that Brings New Problems for the Grocery Industry. Los Angeles Times -Economics in vaccine production The following literature can be applied for sovereignty perspective assessments and practical expectations: Focus on Chapters 3, 4, 6 and 7 in: Institute of Medicine and National Research Council. 1985. Vaccine Supply and Innovation. Washington, DC: The National Academies Press. Crucial variables in vaccine development (not necessarily all listed): firms’ human capital, production capability, cost of vaccine development, market potential, competitors. For sovereignty with efficient recognition and management in pandemics (SERMP), what do such five variables imply for SERMP? -Approval process for vaccine use Where can you find testing data that serves no agenda? Rubrics for evaluation. Analysing the data Approval stages and bureaucratic process with gov’t department and agencies Case studies of America’s FDA stance versus CDC recommendations of vaccine distribution for use. Apart from desperation, how are nations convinced with vaccine credibility and safety? -For countries that produce vaccines with commitment to GAVI or GIVS or COVAX or CEPI, what are they obligated to concerning pricing and distribution towards countries with less resources? World Health Organisation. (2021). Covid -19 Vaccination Financing & Budgeting Q&A (can be extended as a general pathogen topic): https://www.who.int/news/item/27-04-2021-covid-19-vaccination-financing-and-budgeting-q-a Acquire the budget and budget analysis of gov’t. Comparative analysis between pre-pandemic (or pre-epidemic) and pressures/stresses during pandemic (epidemic). What components or areas were most hindered by allocations? Can AHP or PROMETHEE support the decision making? Identify the major sources of gov’t revenue towards treasury with forecasting for 4-10 years in the future for such elements. How has the pandemic (epidemic) influence such forecasting? Can poorer countries avoid a vaccine bidding war? For the long term sensibility, will assume that no other foreign gov’t will buy vaccines for your ambiance. Also, with the assumption that pricing is strongly driven by demand, supply shocks and pharmaceutical competition, regardless of any international governance intervention. Cost of Vaccine Coverage (ideal currency with scale) versus Cost of Vaccine Coverage expressed as percentage of IMF Country Quota (assuming $x per person/100% of population; log scaled). Concerns data acquisition and geometrical representation. Also, ranking countries by World Development Indicators where do they reside in such cost plane? -Quantitative data research based on the following: Standaert, B., & Rappuoli, R. (2017). 2. How is the Economic Assessment of Vaccines Performed Today? Journal of Market Access & Health Policy, 5(1), 1335163 Does vaccine efficacy ever have influence on price in either elevated pandemic phase or with inventory needs for resurgence measures? -For pathogens such as Zika, Ebola, SARS and MERS, apart from recognising transmissions processes, what long term effective policies and programmes concerning migration, agriculture and hygiene can be instituted? (4) There may be analogy to (3) concerning livestock and pestilence for a embargo framework (transmission profile, surveillance and mitigation). Relevant public administration sectors, the associated policies and procedures will apply. Possibility of pathogen animal-to-animal or animal-to-human transmissions with effects. Effect of profound resolutions on natural constituents of habitats. (5) Simulating a Mass Vaccination Clinic A. This simulation will be conditional, namely, one will have to schedule and coordinate participation concerning such public administration simulations: Aaby, Kay & Cook, Tyson & Herrmann, Jeffrey & Jordan, Carol & Wood, Kathy. (2005). Title: Simulating a Mass Vaccination Clinic Running Title: Simulating a Mass Vaccination Clinic. 1-19. https://isr.umd.edu/Labs/CIM/projects/clinic/hcms.pdf What parameters or variables will be warped or have much change in dynamic for a grand epidemic or pandemic? B. Analyse the following, possibly replicate and amend to contagion of interest wherever Beeler M.F., Aleman D.M., Carter M.W. (2016) A Simulation Case Study to Improve Staffing Decisions at Mass Immunization Clinics for Pandemic Influenza. In: Mustafee N. (eds) Operational Research for Emergency Planning in Healthcare: Volume 1. The OR Essentials series. Palgrave Macmillan, London. C. with respect to a budget can the restocking of vaccines for low epidemic/pandemic risk and conventional medicine be sacrificed or reduced for higher level risk pathogens in transmission? Inventory facility allocation modelling subject to budget constraints and expirations. D. Rough Inventory Approaches Yarmand, H. et al. Optimal Two-Phase Vaccine Allocation to Geographically Different Regions Under Uncertainty. European Journal of Operational Research 233 (2014) 208- 219 E. For respective epidemic/pandemic the threat level can dictate who in society are priority. Means of identification of those most vulnerable. Hence, consumption rate can vary depending on the priority populous, infection intensity, willingness, and vaccine shelf-life expectancy. A respective vaccine may be riskier for particular age groups than others, where alternatives may be scarce and/or more reliable to the general populous. As well, mutation monitoring. Will it be Analytical Hierarchy Process (or AHN), or use of other decision analysis methods subjugating model from (D)? F. Contrary to prior there’s the business cycle and global competition where long terms effects from epidemic/pandemic may be underestimated. Prioritization for vaccination in the populous may need to be much more strategic. Apart from the most vulnerable, there’s education welfare, state of labour, production towards the economy. Then compare development from (E) with development from (F). Does (F) indirectly encompass (E)? Furthermore, if there’s any transition based on labour force priorities and/or demography, are vaccine manufacturers towards GAVI or GIVS or COVAX or CEPI capable of raising prices based on a country’s epidemic/pandemic profile or dependency? (6) GIS for emergency management PART A Predicting and Assessing the Impact of Hurricanes with GIS. To develop with a GIS of choice. Projects from prerequisite course will be repeated. Plus: Seenu, P.Z., Venkata Rathnam, E. & Jayakumar, K.V. (2020). Visualization of Urban Flood Inundation using SWMM and 4D GIS. Spat. Inf. Res. 28, 459–467 PART B HEC-FIA Immersion PART C Analyse the following article, replicate, then apply to your ambiance Shaman, J. et al (2002). Using a Dynamic Hydrology Model to Predict Mosquito Abundances in Flood and Swamp Water. Emerging Infectious Diseases. 8(1) (7). Coastal Adaptation to Sea level Rise Tool (COAST) & Urban Flooding Action plan mainly towards economic resolve and quality of living with coastal adaptation. Concerns regions of high infrastructure, residential areas and so forth near coast lines. Storm surge effect will be considered, being occurrences within each year compared to long term sea rise due to climatology studies. Modelling and forecasting with regression and time series will be applied based on data gathering. Frequency changes for certain measures each year may also be of interest. Possible Concerns: Meteorological and oceanography data Storm surge modelling and prediction R + RStudio (with chosen packages) KML/KNM applications (there are other formats) GIS (includes Google Earth/Maps) Some USGS and HEC software if applicable to ambiances of interest All such will likely be incorporated towards construction of COAST system which can be updated without much manually drastic amendments with each component. General steps in process to be implemented: i. Engage Stakeholders to Select Different Scenarios for Sea Level Rise and Storm Surge. ii. PESTEL approach for assessment of coastal zone weather hazards and management iii. Provide a Vulnerability Assessment with Cumulative Expected Damage Estimates Over Time for a “No Action” Scenario of Sea Level Rise and Storm Surge. iv. Select Candidate Adaptation Actions to Protect from Sea Level Rise and Storm Surge, Staged Over Time, and Estimate the Costs of Each Action v. Perform a Cost Benefit Analysis of Adaptation Strategies FEMA Benefit-Cost Analysis: https://www.fema.gov/grants/tools/benefit-cost-analysis vi. Ecological impact assessment: apply a highly regarded framework that leads to credible quantitative results. vii. Concerns for future public planning with infrastructure, business and residential development in areas of interest. Can predict future damage estimates, economic stress, quality of living, etc. with COAST. Category 5 storms are the benchmark. viii. Implement the Strategies: Move the Needle off of Zero. (8). FEMA Substantial Damage Estimator Tool: https://www.fema.gov/emergency-managers/risk-management/building-science/substantial-damage-estimator-tool (9). Homeland Security -Financial Action Task Force (FATF): a G7 inter-governmental body I. FATF Recommendations II. Trade-Based Money laundering: Risk Indicators III. Virtual assets Red Flag Indicators of Money Laundering & Terrorist -International Transactions Monitoring Monitoring foreign investments in ambiance that are not voluntarily submitted. Relevant laws and agencies. How to monitor with no loose ends? Monitoring investments by national firms in foreign countries that are not voluntarily submitted. Relevant laws and agencies. How to monitor with no loose ends? -Analyse and develop the following articles to suit environment of interest with modern data included: Money Laundering Risks Ferwerda, J., Kleemans, E.R. Estimating Money Laundering Risks: An Application to Business Sectors in the Netherlands. Eur J Crim Policy Res 25, 45–62 (2019). -Political Instability (to analyse and develop with modern data included) Duff, E. & McCamant, J. (1968). Measuring Social and Political Requirements for System Stability in Latin America. The American Political Science Review, 62(4), 1125-1143. Linehan, W. (1976). Models For the Measurement of Political Instability, Political Methodology, 3(4), 441-486. -Instability Monitoring The Global Conflict Risk Index: https://drmkc.jrc.ec.europa.eu/Innovation/Global-Conflict-Risk-Index-GCRI#documents/1059/list Note: analysis of methodology and other literature for GCRI before implementation Hands-on development with the following: INFORM Risk INFORM Security INFORM Warning Note: analysis of methodology and other literature for INFORM tools before implementation. Comparative assessment between INFORM and GCRI. Product SWOT? -Labeling & Sentiment Lee J. and Nerghes, A. Refugee or Migrant Crisis? Labels, Perceived Agency, and Sentiment polarity in Online Discussions. Social Media + Society Jul – Sep 2018: 1 – 22 -Refugee Patterns (to develop) Suleimenova, D., Bell, D. & Groen, D. (2017). A Generalised Simulation Development Approach for Predicting Refugee Destinations. Sci Rep 7, 13377 Will not restrict case studies to Europe, rather, will also investigate South American caravans, Venezuela migrant crisis, past African crisis, Myanmar and possibly others. Compare simulations with actual evolutions. Note: there may times where students will have development for an ongoing or future international/foreign crisis. -Policy and Planning for the following: Intervention by the public assisting migrants/refugees Opportunistic trafficking operations Radical xenophobic vigilantes Methods of determining security risks with possible opportunistic extremists’ infiltration; relevant regions and migration modes. -General Refugees accommodation --> Note: there may times where students will have development for an ongoing or future international/foreign crisis. Students should also reference appropriate agencies of an international body such as the UN concerning roles with ongoing activity; have as well the perspective of the foreign gov’t agencies to build analyses or policies concerning based on both UN agencies policy and foreign gov’t agencies. Some earlier features in this module 8 may be highly useful. Things to develop: A. Migration Monitoring Features for development Analysis of refugee ethnicity Profiling the dynamics of regions of affliction & the expansion Note: various earlier activities to prove beneficial Populations to be displaced GIS and Geography Analysis Regional Economics profiling and supply chains disruption Disruptions that are social and economic Crisis Expansion severity. Note: Instability Monitoring earlier may help. Determination of migration routes Note: some earlier activities to prove beneficial Modes of transportation (origins, arrival sites, destinations) Further GIS implementation (detailed development of terrains, infiltration pathways, infrastructure/traffic modes) Security checkpoints based on terrains, migration routes and destinations Are refugees subject to the set immigration quota? Initial public policy (may evolve) B. Needs Assessment UNHCR Needs Assessment Handbook Overview; features comprehension; pursuit of logistical structure for competence; for certain features will like to identify what types of data, tools and skills will be required to make such features accessible or tangible or quantifiable or qualitatively credible. Note: earlier activities in this module 9 can trickle in. C. Availability of Resources & Personnel. Note: earlier activities in this module 9 can trickle in. Security & Containment Identification, Processing and Registration How does one assess the credibility of foreign warrants and how to acquire strong counsel regarding legal status and well-being? D. How is a refugee cap determined? E. NPOs/NGOs incorporation Licenses/registration/permits/authorization Administrative tree and organisation Policies, protocols and communication between NPOs/NGOs & gov’t agencies Observation of NPOs/NGOs guidelines/policies Supply Chain Observation Inspections and monitoring by gov’t agencies Acceptable image/reputation and stress reduction for gov’t NPO/NGO evaluation models with crucial data collection F. How will NPO/NGOs incorporation affect consumption of public resources, finance & personnel use? G. Life cycle of operations. How must acquired data be modelled to effectively recognise possible prodigality (for resources, finance, staff sizing) w/o NPOs/NGOs? H. Keeping track of refugee whereabouts (with legal boundaries) I. What are the short term & long-term goals/benefits for partaking in refugee accommodation? Economically Foreign Policy Prerequisite: Crisis Management Research Methods in Public Administration An introduction to the application of social science research methods to problems in public management and policy. Topics include research design, measurement, data collection techniques, and research ethics. Operations in this course: 1) Identifying which research designs and data collection strategies are the most appropriate for planning and evaluating public policy, programme, and management interventions. 2) Problems Sets A. Problem sets will include software skills, projects tasks and assignments done in prerequisite (Quantitative Analysis in Political Science I) to stay fresh. B. Course problem sets will be a combination of analytical and computational assignments based on lecturing 3) Gaining increased sophistication as a research "consumer" who understands the strengths and limitations of research studies 4) Given the technical nature of this course, attendance at every class meeting is especially important. Each class builds on material learned in previous class sessions and will often cover some important material not covered in the assigned readings. As an added incentive, the instructor reserves the right to give quizzes in the beginning of class (no late or make-up quizzes will be allowed). 5) Students (in groups of 2 or 3) will be asked to prepare a research design to answer a question posed to them. The format of these assignments will be very similar to the questions asked on the midterm exam. The research proposal assignment is an opportunity for students to integrate all essential components of research methods in an area of interest to them. The students will work in small groups (2-3 students) to identify a research question of interest to public administration and design a research study to answer this question. The assignment has two parts: 1) initial research proposal memo 2) 10 minute oral research proposal presentation Proposal Memo. Students will be required to submit a memo written to convince the reader that the research is both important and feasible. In the proposal memo, the following questions must be addressed: -What is your research question? -Why do you want to undertake it? Who will care and why? -What do you think may be happening and how would this study help you know? (identify the variables, relationships of interest and hypotheses) -What audience(s) do you hope to influence? -What type of research design might you use to test your hypothesis and why? Research Proposal Presentation. Each student group will be required to give a formal presentation of their research proposal. Prior to the final presentation, students must hand in a report and draft PowerPoint presentation for instructor review and feedback. The proposal presentation should discuss the following elements: 1. Statement of the problem Research objective/question Significance of the problem 2. Outline of the theoretical framework or model Justify and conceptualize the variables that you select Identify independent and dependent variable(s) Introduce testable hypotheses 3. Research design Study design and how it helps rule out alternative explanations Identify study subjects (sample)/units of analysis Describe sampling procedure Data collection methods (measures/instruments; operationalization) 4. Management Plan The time table Budget 5. Anticipated strengths, weaknesses and benefits. 6. Ethical considerations Course Grade Constitution --> Attendance & Participation Take Home Quizzes Experimental & Quasi Design Assignments Midterm Exam Research Proposal Memo Research Proposal Presentation Final Examination Course Textbook --> O’Sullivan, E., Rassel, G. R. & Berner, M. (2008). Research Methods for Public Administrators. New York: Longman Publishers. Assisting Literature --> United States Office of Management and Budget (OMB) Standards & Guidelines for Statistical Surveys - https://www.samhsa.gov/data/sites/default/files/standards_stat_surveys.pdf NOTE: textbook chapters will be accompanied by chosen journal articles catering for specific topics. Tools for activities: R and Excel Course Outline --> --Introduction: Research Use & Process --Introduction to Research and the importance of Theory --Measurement & Data Management --Research Design: Experiments --Research Design: Quasi-Experiments --Research Design: Cross-Sectional --Research Design Continued --Surveys Sampling & Administration --Survey Measurement --Survey Design Exercise --Research Ethics --Research Ethics continued & Reporting Research Results Prerequisites: Enterprise Data Analysis II; Quantitative Analysis in Political Studies I, Upper Level Standing. The later the better (but not too late).

Programme Evaluation I Students gain practical experience through a series of exercises involving the design of methods, development of indicators, computational tools, and development of an evaluation plan to measure impact. Course introduces students to the following 5 elements: 1.Needs Assessment 2.Programme Theory < https://www.jmu.edu/assessment/sass/ac-step-two.shtml > 3.Feasibility Study (FS) Note: for FS when it comes to the economic evaluation and financial analysis stages must be able to competently develop the following -- Cost-Benefit Analysis Monetised impacts: costs and benefits Non-monetised impacts: costs and benefits Discounting, computation, etc. Cash Flow Projections Financial Sustainability 4. Social Return on Investment (SROI) 5.Impact Evaluation OECD – Outline of Principles of Impact Evaluation [ https://www.oecd.org/dac/evaluation/dcdndep/37671602.pdf ] Gertler, P. J. et al (2016). Impact Evaluation in Practice. World Bank Group, and Inter-American Development Bank Critical Learning and Skills Outcomes --> ASPECT A. Intelligence and development in programme evaluation for the 5 mentioned elements: Purpose Framework Modelling w.r.t. project/programme in question Levels of measurement: population-based vs. program-based pertaining to such Develop objectives and indicators. Inputs and Outputs (qualitative and quantitative) Sources of data. Competence and efficiency with data assimilation for indicators, inputs and outputs Benchmarks Other Essentials ASPECT B. Write an evaluation plan for each element Towards various public administrations/departments, NPOs, etc. Course Literature and Tools --> Wholey, Josheph S., Hatry, H. P., and K.E. Newcomer. 2004. Handbook of Practical Evaluation, 2nd, Edition. Jossey-Bass. Rossi, Lipsey, and Freeman. Evaluation: A Systematic Approach. 7th edition. Sage Publications, 2004. Langbein, L. (2012). Public Programme Evaluation: A Statistical Guide, Routledge, 264 pages Social Return on Investment (SROI) Literature --> Folger, J. (2021) What Factors Go Into Calculating Social Return on Investment (SROI)? Investopedia UNDP literature (and others) Impact Evaluation Literature --> Gertler, P. J., Martinez, S. et al (2016). Impact Evaluation in Practice, World Bank Group, and Inter-American Development Bank Feasibility Study Literature --> Make use of gov’t, IGO and academic texts. There will be some highly quantitative/computational elements implemented. Literature and tools for Cost-Benefit Analysis --> -Use of credible CBA manuals/guides (mandatory) -Campbell, H., & Brown, R. (2003). Benefit-Cost Analysis: Financial and Economic Appraisal using Spreadsheets (pp. 194-220). Cambridge: Cambridge University Press Groups Term Evaluation Plan --> Student groups in the class will prepare the evaluation plans to fulfill the requirements for this class. Each evaluation plan will contain five parts, where a particular part represents a separate assignment. The topics to cover in each section are as follows: -Defining the problem/issue/project, stakeholders, and describing the intervention -Development Process and Logistics -Levels of Measurement. Inputs and Outputs -Sources of data and credibility -Competence and efficiency with data assimilation for indicators -Modern assimilation and execution -Baselines, Benchmarks and Analysis Note: groups will have the option to select either a domestic programme, or a federal programme, or an international program for this paper. Note: there may or may not be considerable distance in time between course and prerequisites. Students are encouraged to review their Statistics, Econometrics and R skills. Prerequisites: Enterprise Data Analysis II; International Financial Statements Analysis I & II; Quantitative Analysis in Political Studies I, Upper Level Standing. The later the better (but not too late). Programme Evaluation II --Student groups will be orchestrating field projects with various public/governance sectors. Prerequisite: Programme Evaluation I NOTE: FOR VARIOUS BUSINESS COURSES RESOURCES SUCH AS Kaggle AND UPENN WRDS databases WITH CRSP/Compustat Merged Database (CCM) can be invaluable. SERIOUSLY --Getting Started with Wharton Research Data Services – YouTube --http://business-school.exeter.ac.uk/documents/resources/databases/wrds/user_guide.pdf --https://www.wiso.uni-hamburg.de/en/bibliothek/recherche/datenbanken/unternehmensdaten/wrds-getting-started-uhh.pdf REVENUE MANAGEMENT Revenue Management resides under the Business institution. Revenue Management curriculum: --Mandatory Courses --> Calculus for Business & Economics I-III, Optimisation, Probability & Statistics B, Mathematical Statistics --Core Courses (constituted by the following 5 different components): 1.General Business Structure << Business Communication & Writing I & II, Enterprise Data Analysis I & II (check FIN), International Financial Statement Analysis I & II (check FIN), Corporate Finance (check FIN) >> 2.Economics << Microeconomics I >> 3.Marketing Basics << Marketing Management I & II; Marketing Research & Analytics; Pricing Strategies; Customer Relationship Management >> 4.Commerce Skills << International Commerce (check FIN), Strategic Business Analysis & Modelling (check FIN) >> 5.Professional Necessities << R Analysis (check ACTUAR post); Operations Management I (Check OM); Logistics & Inventory (Check OM); Service Operations Management; Revenue Management I-II >> FOR THE FOLLOWING COURSES CHECK IN ACTUARIAL POST: Optimisation, Probability & Statistics, Mathematical Statistics NOTE: example data sources that may serve well for various courses -- https://aws.amazon.com/data-exchange/ https://www.kaggle.com/datasets/jackdaoud/marketing-data https://www.kaggle.com/datasets/demodatauk/digital-marketing-eventlevel-sample https://catalog.data.gov/dataset?tags=marketing https://oru.libguides.com/datasets/business https://libguides.mit.edu/c.php?g=385111&p=3452342 Marketing Management I Marketing is much more than advertising alone; even the most skillful marketer cannot make customers buy things that they don't want. Rather, marketing involves: (1) identifying customer needs, (2) satisfying these needs with the right product and/or service, (3) assuring availability to customers through the best distribution channels, (4) using promotional activities in ways that motivate purchase as effectively as possible, and (5) choosing a suitable price to boost the firm’s profitability while also maintaining customer satisfaction. These decisions – product, distribution, promotion, and price – comprise the marketing mix. Together with a rigorous analysis of the customers, competitors, and the overall business environment, they are the key activities of marketing management. Goal is to find the right marketing mix to avoid the economic consequences. You will learn how to make sound decisions pertaining to: 1. Segmentation, Targeting, and Positioning. How to assess market potential, understand and analyze customer behavior, and focus resources on specific customer segments and against specific competitors. 2. Go to Market Strategy. How to understand the role of distributors, retailers, and other intermediaries in delivering products, services and information to customers. 3. Branding. How to develop, measure, and capitalize on brand equity. 4. Pricing. How to set prices that capitalize on value to customer and capture value for the firm. 5. Marketing Communications. How to develop an effective mix of communication efforts. NOTE: course will be 16-18 weeks in duration Course Text --> Strategic Marketing Management: The Framework – 10th edition by Alexander Optional Supplement --> The Shopping Revolution, Updated and Expanded: How Retailers Succeed in an Era of Endless Disruption Accelerated by COVID-19 by Barbara Kahn Applied Resources --> Statistics based on databases from US Census, US BEA, US BLS via API Statistical Abstract (of country), Country Census Business Builder Regional levels as well Economic Indicators (consumer confidence, PMIs, inflation, labour statistics, income statistics, money supply) Pew Research Centre databases Living Facts Google Trends Tools --> Sawtooth Software or alternative UPENN Pivot or Perish Assessment --> Case Studies Assignments/Projects Simulation & Presentation 2 Exams COURSE OUTLINE --> 1.What is Marketing? (Textbook: Chapters 1 & 2) 2.Textbook Ch. 6, Ch 14-16 3. Hands-on investigating of the use of the Applied Resources for research with presentation. Will be a bit challenging 4.Segmentation, Targeting, Positioning (Textbook: Chapters 3-5) 5. STP Case Studies Guide to compliment text knowledge (supported by Applied Resources): Salesforce - Step UP Marketing Strategy with STP (Segmentation, Targeting, Positioning): A Comprehensive Guide -> www.salesforce.com/in/blog/2022/03/segmentation-targeting-positioning-model.html 6.Customer Decision Making / Journey 7.Indeed Editorial Team. (2021). The 5 Stages of the Consumer Decision Making Process. Indeed Students in groups will be given example cases on how consumers identify their needs and make purchasing decisions. Students will identify how respective consumer is to be categorized in terms of STP with market measures applied for respective consumer 8.Consumer Decision Mapping and Redesign Lab 9.Customer Lifetime Value 10.Sharapa, M. (2019). 5 Simple Ways to Calculate Customer Lifetime Value, Medium Will work with retailers (or whosoever) to pursue to such measures 11.Branding Strategy (Textbook: Chapter 9) 12.Branding Strategy Case Studies 13.Brand Measurement 14.Whitler, Kimberly A. (2021). 9 Brand Measurement Methods. Positioning for Advantage: Techniques and Strategies to Grow Brand Value, New York Chichester, West Sussex: Columbia University Press, pp. 179-202. Field Case Studies 15.Pricing Strategy (Textbook: Chapter 10) 16.Sawtooth/Conjoint Lab (via Sawtooth Software or alternative) 17.Product Life Cycle 18.Product Life Cycle Case Studies 19.Go-to-Market Strategy (Textbook: Chapter 13) Distribution Channnel modelling and analysis for chosen firms in various industries; include risk analyses 20.Pivot of Perish Simulation: Introduction & Preparation 21.Simulation Debrief 22.Marketing Communications (Textbook: Chapter 12) Prerequisites: Enterprise Data Analysis I & II; Must fulfill the Business writing sequence; Microeconomics I & II Marketing Management II Issues related to the marketing process, major trends and forces that are changing the marketing landscape, marketing information, building and managing brands, marketing strategy and roles of ethics in marketing. Course Texts --> Iacobucci, Dawn, “MM 4”, 4th edition, Cengage Markstrat Participant Handbook, Stratx Personal Refresher Text --> Strategic Marketing Management: The Framework – 10th edition by Alexander Applied Resources --> Statistics based on databases from US Census, US BEA, US BLS via API Statistical Abstract (of country), Country Census Business Builder Regional levels as well Economic Indicators (consumer confidence, PMIs, inflation, labour statistics, income statistics, money supply) Pew Research Centre databases Living Facts Google Trends Tools --> Sawtooth Software or alternative UPENN Pivot or Perish StratX Simulations web.stratxsimulations.com/programs-in-the-classroom-the-workplace StratX Simulation --> Likely to be a full-term project. Team Marketing Term Project (integrated marketing programme) --> A. Identify an existing product/brand issue being faced by a company. Completely analyse the brand/product, focusing your analysis on marketing concepts and issues covered in this class which you feel are important in explaining the issues involved and the differences between the brand/product you have chosen and its competitors. Clearly outline your assumptions and thought processes. B. Suggest actions and strategies (on each issue), which you feel would enable the product/brand to improve its market position. Clearly outline your assumptions and thinking. At minimum, your report must include AT LEAST: A title page identifying the members of the marketing team, product/brand and/or company name. Executive Summary Overview of the company’s mission Value proposition PESTEL and SWOT Description of the issue being faced that your plan will address Marketing strategy (segmentation target mkts, positioning, marketing mix strategies, marketing communications) Competition Band Measurement Methods Brand/product analysis Distribution Recommendation (including but not limited to; marketing strategy, target markets and segments, 4p’s and 4c’s, integrated marketing communications). Assessment --> Advance recital of case studies, assignments and projects from prerequisite Basic Simulation (Pivot or Perish) StratX Simulation 2 Exams 2 progression development for team marketing project Team Marketing Project COURSE LAYOUT --> NOTE: from prerequisite the course topics, activities, assignments, projects and case studies to be recited in an advance manner to be well suited precursors to related modules of this course; firms and ambiances subject to change. -Consumer behavior & Marketing Management -Strategies for segmentation, targeting & positioning -Measuring & Managing successful marketing strategies for products and services -The strategic role of brands -Measuring and managing strong brands -New Product & product decisions- Measuring key success factors -Distribution strategies -Pricing strategies -Communication strategies -Social media & marketing strategies Prerequisite: Marketing Management I Pricing Strategies This course gives students the means to approach pricing problems and to develop a pricing strategy and corresponding tactics that can maximize shareholder value. While each industry is unique in some ways, there are enough commonalities in pricing problems across industries to develop a set of rich insights applicable to a broad audience. The learning objectives of this course are simple. At the end of this course you should be able to: 1. Help a company raise its effective price. 2. Leverage your organisation’s unique insights and qualitative knowledge to develop and implement a strategic pricing plan. Each class is designed to further build a student’s pricing toolbox and provide insights into the theory and practice of effective pricing. Course will use a mix of lectures AND case discussions. The purpose of this course is to equip students with a process to make informed, strategic pricing decisions. Typical Text --> Nagle, Thomas T., and Georg Müller. (2017). The Strategy and Tactics of Pricing: A guide to Growing More Profitably. Routledge Resources --> Statistics based on databases from US Census, US BEA, US BLS via API Statistical Abstract (of country), Country Census Business Builder Regional levels as well Economic Indicators (consumer confidence, PMIs, inflation, labour statistics, income statistics, money supply) Pew Research Centre databases Living Facts Google Trends Price Monitoring Tools R packages (along with possible inclusion of arules and arulesViz ) MAJOR COMPONENTS OF COURSE 80% Contribution to Discussion & Collaboration Estimation of Value to Customer Price Structure Pricing Research Methods Necessary Footing Labs Making Pricing Decisions with Limited Information Integrating Pricing Knowledge TESTING 20% 3 Quizzes 0.6 Final Exam 0.4 Collaboration --> Pricing decisions are often made in management teams. Team members should raise thoughtful points, respectfully challenge assumptions, and work to build consensus regarding the beliefs about the market and how to use these beliefs in the pricing strategy. Team members must come to meetings prepared to make informed contributions to the process. Hence, students will be evaluated on their contribution to discussion. Quality of comments will be weighted more heavily than the quantity of comments. Coming to class prepared by having read the required readings will be useful in generating insightful contributions to discussion. I call upon the students to do their part in welcoming their peers’ points of view. Estimation of Value to Customer --> When launching a new product, a manager cannot use historical sales data to guide the pricing decision. However, a manager can use knowledge of the customer’s value drivers and the knowledge of the product’s attributes to inform the pricing decision in an Economic Value Estimation. Will have Economic Value Estimation assignments on Individual B2B or B2C Company. Price Structure --> Determines the method by which total transaction prices are determined. Price structures are a strategic means to price-segment the market. http://faculty.fortlewis.edu/walker_d/econ_325_-_pricing_structures.htm Expect case studies and directed circumstances to be given. Pricing Research Methods --> Managers can use survey techniques to predict response to pricing decisions. Student teams will design, implement, and analyse the results of monadic pricing studies and a conjoint studies. You will have an exciting opportunity to get real market feedback and see how well this feedback aligns with your pricing research findings. Necessary Footing Labs --> A. Primitive Empirics -5C Analysis in Marketing -Industry analysis with Data Envelopment Analysis, Stochastic Frontier Analysis -The well-known equation for a product or service Retail Price = Cost + Markup So, what influences the markup? Costs can be direct, indirect and variable. How to incorporate them strongly in a quantitative manner? Willingness based on economy. A general model representation of markup: Markup = f(price of substitutes, specials, season, input costs) Will try to synthesize explicit models for various services or products based on market data and other crucial data. Influence of competition on markup. B. Primitive Pricing 1. Geographical pricing with consideration of quality of life elements, economy, and the distribution channels among competitors 2. Hedonic modelling and estimation 3. Data Envelopment Analysis Flelder, S. (1995). The Use of Data Envelopment Analysis for the Detection of Price Above the Competitive Level. Empirica 22, 103–113. Wang, B., Anderson, T. R. & Zehr, W. (2016). Competitive Pricing Using Data Envelopment Analysis — Pricing for Oscilloscopes, IJITM vol. 13(01), 1650006. Hopefully applicable to other products and services as well C. Further Pricing Practices (determine constructive order) Competitive, Penetration, Cost-plus, Skimming, High-low, Premium, Psychological, Bundle, Dynamic For the given above practices the concerns are: (1) Pros and cons (2) Gathering intelligence on firms and ambiance will also be important, and what phases are such firms in (3) Logistics for implementation based on 1 and 2 (4) Empirical validation of the practices (5) Economic statistics and business statistics may be applied for possible stimuli identification There will be multiple sessions with supporting modelling and quantitative literature as guides. Strong candidate pricing practices applied comparatively for chosen markets or circumstances; such concerns real data not being way out of the ballpark with the pricing practices in question leading to “defeating bewilderment”. Multiple products and services to apply. Price monitoring tools may also be useful. D. Dynamic Pricing in Sports (to develop in ambiance of interest) Cain, B., Saporoschetz, N. & Ginting, T. (2020). A Dynamic Pricing Model for Professional Sports Teams. Journal of Purdue Undergraduate Research: Volume 10 Huang, Z. et al. (2021). Dynamic Pricing for Sports Tickets. In: Stahlbock, R. et al. (eds) Advances in Data Science and Information Engineering. Transactions on Computational Science and Computational Intelligence. Springer, Cham Making Pricing Decisions with Limited Information --> It is common to feel under-informed when making pricing decisions. It is important to be able to use limited information effectively and determine what information can and should be collected to make better informed decisions. Integrating Pricing Knowledge --> The pricing problems that managers face doesn’t always look like problems they have seen solved before. The key to solving complex problems is applying the appropriate frameworks. Students will practice determining which frameworks to apply to two complex situations. Phases of course --> 1. Overview 2. Value Creation 3. Price Structure 4. Value Communication 5. Pricing Policy 6. Price Level 7. Competitive Dynamics Topic Schedule --> WEEK 1 Introduction to Strategic Pricing WEEK 2 Strategic Pricing Exercises Economic Value Estimation (EVE) WEEK 3 Price Response Estimation: Conjoint Analysis B2B/B2C Discussion & Price Elasticity Pricing Practicum Idea Presentations Due B2B/B2C EVE Individual Assignment due in last class of the week WEEK 4 Pricing Panel Price Structure: Price Metrics WEEK 5 Price Structure: Price-Offer Configuration Price Structure: Behavioural Pricing WEEK 6 Review and Catchup WEEK 7 Price and Value Communication Pricing Policy WEEK 8 Pricing New Products Answer Dash Presentations WEEK 9 Managing Competitive Dynamics WEEK 10 Live Case Exercise Life-Cycle Pricing WEEK 11 When and How to Fight a Price War WEEK 12 - 13 Managing Price inflation. Given literature can be investigated based on observation of sectors, industries, and price monitoring tools with historical data. May be tedious to identify strongly any “contradictions” to prior foundations or modules: Donovan, M. (2008). How Marketers Can Manage Price Inflation. Harvard Business Review Johnson, E. and Gaputis, D. (2020 – 2021). Effective Pricing Strategies During Inflation for Consumer Companies. Deloitte WEEK 14 - 15 Catchup & Review FINAL EXAM Prerequisites: Enterprise Data Analysis II, Microeconomics II, Marketing Management II, Mathematical Statistics Customer Relationship Management This course examines customer relationship management (CRM) and its application in marketing, sales, and service. Effective CRM strategies help companies align business process with customer centric strategies using people, technology, and knowledge. Companies strive to use CRM to optimize the identification, acquisition, growth, and retention of desired customers to gain competitive advantage and maximize profit. Emphasis is given on both conceptual knowledge and hands-on learning using a leading CRM software. CRM discussions and assignments will address relationship marketing with both organizational customers (B2B) and consumers/households (B2C). Although organizations continue to invest heavily in CRM, CRM implementations experience a high failure rate. Why? The pitfalls as well as the benefits of CRM strategy and implementation are addressed in the course. After successfully completing this course, a student should: 1) Understand the fundamentals of CRM 2) Recognize the basic technological infrastructure and organizations involved in current and emerging CRM practices. COURSE TEXT & LAB HANDOUTS --> Principles of Customer Relationship Management by Baran, Galka, Strunk, Southwestern (CENGAGE Learning), 2008 Lab Handouts will be provided during or before lab sessions. ADDITIONAL RESOURCE TEXTS --> Kumar and Reinartz (2012). Customer Relationship Management: Concept, Strategy, & Tools, Springer Buttle, F. (2009). Customer Relationship Management, Elsevier Ltd. CASE MATERIALS --> All cases can be purchased directly from Harvard Business Review website or chosen alternative sources such as MIT, etc., etc., etc. TOOLS --> Microsoft Office 365 R environment Amazon tools RESOURCES--> Statistics based on databases from US Census, US BEA, US BLS via API Statistical Abstract (of country), Country Census Business Builder Regional levels as well Economic Indicators (consumer confidence, PMIs, inflation, labour statistics, income statistics, money supply) Pew Research Centre databases Living Facts Google Trends LABS --> 1.Segmentation Methods Note: hopefully census data, bureau of economic analysis data, labour statistics data, Amazon data sets, Kaggle Google Trends, Google Analytics, Pew Research Centre databases, Living Facts, etc. are data rich, well structured, applicable and easily integrable to develop practical and robust segmentation. PART A To recall 4-5 types of traditional segmentation to be identified and developed. Much introspection and querying for development. Recalling STP Case Studies from Marketing Management I & II can help. For each type of segmentation, use of professionally recognised guidelines or manuals are expected. PART B (R Immersion) Chapman, C., Feit, E.M. (2019). Segmentation: Clustering and Classification. In: R For Marketing Research and Analytics. Use R!. Springer, Cham. Dolnicar, S., Grun, B. and Leisch, F. (2018). Market Segmentation Analysis: Understanding It, Doing It, and Making It Useful. Springer 2.Association Rules: Chapman, C. & Feit, E. M. (2015). Association Rules for Market Basket Analysis. In: R for Marketing Research and Analytics. Use R!, Springer R Packages arules and arulesViz applied 3.RFM Analysis PART A Comprehension and logistics R packgage rfm Reference manual Vignettes (customer level data, transaction level data) Interested in applying data of choice PART B Segmentation with RFM Procedure and logistics Actual implementation in R, then if able comparative analysis with development from (1). 4.Customer Lifetime Value PART A Inquisition upon article: OWOX (2019). 5 Simple Ways to Calculate Customer Lifetime Value, Medium If article is found solid, will work with retailers (or whosoever) to pursue to such measures PART B Use of R package CLVTools Package reference manual Vignettes for R package Will work with data from retailers (or whosoever/whatsoever) PART C Comparative analysis of measures from OWOX with CLVTools R package 5.OLS Regression and Logistic Regression (LR) for CRM interests Customer Segmentation (OLS and LR) Customer Lifetime value (OLS) Churn Prediction (LR) Cross-Selling and Upselling (OLS and LR) Demand Forecasting (OLS and LR) PROJECTS --> --CRM PROJECT 1: Market Measures Robust and dexterous methods to compute the following (will be done for assigned ambiances). At least two methods for each to compare: Total Available Market Serviceable Available Market Serviceable Obtainable Market 5C Analysis implementation for chosen firms (active comprehensive development): CFI Team. (2022). 5C Analysis. Corporate Finance Institute --CRM PROJECT 2: Data Envelopment Analysis Application Brown, J. R., & Ragsdale, C. T. (2002). The Competitive Market Efficiency of Hotel Brands: An Application of Data Envelopment Analysis. Journal of Hospitality & Tourism Research, 26(4), 332–360. Note: to also implement for various sectors/industries with regions and time frames of interest. --CRM PROJECT 3: Customer Value Metrics (to implement) Google Analytics May rely heavily on Amazon tools and willing participation by firms --CRM PROJECT 4: Developing a model of customer relationship management and business intelligence systems for catalogue and online retailers. --CRM PROJECT 5: Confirmatory Factor Analysis & Structural Equation Modeling Chapman, C., Feit, E.M. (2015). Confirmatory Factor Analysis and Structural Equation Modeling. In: R for Marketing Research and Analytics. Use R!, Springer, Cham. A. Confirmatory Factor Analysis Comprehension Logistics R Implementation runs B. Structural Equation Modelling Comprehension Other References: Baumgartner, H. and Homburg, C.(1996). Applications of Structural Equation Modelling in Marketing and Consumer Research: A Review, International Journal of Research in Marketing 13(2), pp 139-161 Chin, W. W., Peterson, R. A., & Brown, S. P. (2008). Structural Equation Modeling in Marketing: Some Practical Reminders. Journal of Marketing Theory and Practice, 16(4), 287–298. Logistics R Implementation runs Some loose R guides: https://bookdown.org/bean_jerry/using_r_for_social_work_research/structural-equation-modeling.html https://quantdev.ssri.psu.edu/tutorials/structural-equation-modeling-r-using-lavaan https://stats.oarc.ucla.edu/r/seminars/rsem/ ASSESSMENT --> Presence + Behaviour + Assignments Quizzes (4-6) Case Analyses) CRM Projects 1-6 Midterm Final COURSE TOPICS AND CONTENTS --> --Module I – CRM Theory & Development This module is designed to provide introduction to Customer Relationship Management, History and Development of CRM, and Relationship Marketing. This module also explores the issues related to Organizational structure and CRM. --Module II – Data, Information & Technology This module introduces students to the CRM Technology and Data Platforms, Database and Data Management, and the role of Business Intelligence (BI) in CRM. Types of CRM software systems and associated logistics. --Module III – CRM: Impact on Sales & Marketing Strategy This module is dedicated for exploration of the impact of Customer Relationship management on Sales & Marketing Strategy. --Module IV – CRM Evaluation In the CRM Evaluation module, several categories of measurement of CRM effectiveness including CRM’s impact on company efficiency, effectiveness, and employee behaviour are discussed --Module V – Privacy, Ethics and Future of CRM CRM strategy relies heavily on the efficient and accurate capture and use of customer information. Therefore, organizations have a responsibility to meet or exceed their customer’s expectations to privacy. This module highlights consumer privacy concerns and what organizations can do in support of privacy and ethical compliance. Prerequisites: Enterprise Data Analysis II, Microeconomics II, Marketing Management II, Mathematical Statistics Service Operations Management Depending on your ambiance the service industry accounts can reach 75% of the employment and around 60% of all personal consumption. This course will explore the service industries (e.g., transportation, retailing, restaurants, education, etc.) with a view toward developing models that allow planners to reduce costs and enhance customer service. Topics to be covered include facility location planning for services (e.g., ambulances, fire stations, repair facilities, cell phone facilities), resource allocation problems, inventory management issues in the service sector, workforce planning and scheduling, yield and demand management, queueing analysis and design of service systems, call centre management, and vehicle routing in the service industries. Typical text: Daskin, M. S. (2010), Service Science, Wiley Supporting Text --> Chang, C. M. (2010), Service Systems Management and Engineering: Creating Strategic Differentiation & Operational Excellence, Wiley The course also has a secondary objective of introducing students to the non-textbook literature. Some of the course will be based on case studies that were documented in Interfaces, a journal published by INFORMS, the Institute for Operations Research and the Management Sciences (or other). This journal is designed to be accessible to a broad range of readers. Students will be exposed to a number of papers in the literature spanning a variety of problems in the service sector and a number of different industries. Students will learn to read such papers critically. Subject areas will concern various industries, supply chain concerns, revenue management, workforce, auctions, districting, etc.: Technology Requirement --> 1.R Packages Optmisation R packages (for integer, mixed, etc.) Inventory (if relevant to level of topics) SCperf, Inventorymodel, inventorize Multi-objective Programming and Goal Programming, 90C29: caRamel, GPareto, mco, emoa, rmoo Queuing r packages queueing, queuecomputer Data Envelopment Analysis rDEA, deaR, Benchmarking Vehicle Routing optrees, igraph, netgen 2.Excel 3.Word Processor Course Grading --> Homework Assignments (approximately one per week) 30% Standard Exercises Assignments with modelling, computation/simulation activities For R usage there must be commentary throughout development Written summary of one paper and computational analysis 10% Will be asked to elaborate on settings and modelling Analysis of variables and parameters Making relevant to R and/or Excel environments Model a real business or service with such; try incorporating prior Exam 1 15% Exam 2 15% Final Exam 30% Course Outline --> -GREETINGS Introduction, course overview, importance of services in economy -LOCATION MODELS & COVERING MODELS Taxonomy of location models and continuous location model Set covering model Maximum covering model Median and fixed charge location models -MULTI-OBJECTIVE MODELS Multi-objective optimisation Multi-objective location models -INVENTORY ISSUES Deterministic inventory issues in services Stochastic inventory issues in services -RESOURCE ALLOCATION Resource allocation issues in services -WORKFORCE SCHEDULING Short term workforce scheduling -QUEUEING THEORY Queueing theory – basic principles Kendall’s notation, Memoryless property of the exponential, CK equations Fundamentals of Markovian Steady State Equation, (M/M/1 and M/M/s) Finite population, finite queue, M/G/1 and time dependent queueing Linking performance to scheduling Priority queueing -DATA ENVELOPMENT ANALYSIS (DEA) Overview and applications Practice development assignments with DEA -DEA APPLIED TO QUEUES Safdar, K. A., Emrouznejad, A. & Dey, P. K. (2016). Assessing the Queuing Process Using Data Envelopment Analysis: An Application in Health Centres. J Med Syst 40, 32 Al-Refaie, A. et al (2014). Applying Simulation and DEA to Improve Performance of Emergency Department in a Jordanian Hospital. Simulation Modellin & Practice Theory 41, 59–72 Can such DEA application to queues be practical for other service industries? Pursue tangible and practical development -CALL CENTRE DESIGNS Course literature treatment Garnet, O., Mandelbaum, A. & Reiman, M. (2002). Designing a Call Center with Impatient Customers. Manufacturing & Service Operations Management, vol. 4(3), pages 208-227. Jagerman, David & Melamed, B. (2003). Models and Approximations for Call Center Design. Methodology And Computing In Applied Probability. 5. 159-181 -WORKFORCE SCHEDULING Long term work force scheduling Long term work force scheduling and the newsvendor problem -VEHICLE ROUTING Vehicle routing – arch routing Vehicle routing – node routing Prereqs: Enterprise Data Analysis II, Optimisation, Probability & Statistics B Marketing Research & Analytics Course Text --> Iacobucci, D. & Churchill, G. A. (2019). Marketing Research: Methodological Foundations. CreateSpace Independent Publishing Platform NOTE: prerequisites assume much competence and self worth. This is not a course of memorization talent. R Literature --> Chapman, C. and McDonnell Feit, E. (2019). R For Marketing Research and Analytics. Springer, Cham. Dolnicar, S., Grun, B. and Leisch, F. (2018). Market Segmentation Analysis: Understanding It, Doing It, and Making It Useful. Springer Paez, A. and Boisjoly, G. (2022). Discrete Choice Analysis with R. Springer ChoiceModelR package R Ambiance Skills Throughout Term --> Note: appropriate order will be determined, and some topics done on multiple occasions and sometimes in bundles despite given order: Secondary Data vs. Primary Data Descriptive/Summary Statistics (include interpretation of skew & kurtosis) Histograms and Scatter plots Correlation Purpose and Types R packages (GGally, DataExplorer, correlation) Chi-Square Test and Fisher Test of Independence (practical, logistical, and get it done) ANOVA (practical, logistical, and get it done) Sample Size determination Sampling Techniques OLS Multiple Regression Variables selection, summary statistics, forecasting & error Marginal effects Applications in Marketing Analytics Logistic Regression Variables selection, summary statistics, forecasting & error Multinomial, nested, mixed Applications in Marketing Analytics Ordinal Regression Development, Variables selection, model evaluation Applications in Marketing Analytics Marketing Mix Modelling (MMM) Regression (fast review, linear and non-linear effects) Time Series (salient characteristics, model determination, summary statistics) Sales Components (base and incremental) Elements measured in MMM Cluster Analysis & Segmentation Association Rules (arules and arulesViz R packages) Causal Designs and Experiments NOTE: R literature chosen to match topics chosen from course text. Course Assessment based on 5 components (everything not necessarily in specified order) --> 1.R Ambiance Skills Throughout Term 2.Primitive Research Assignments: A) Qualitative Research Assignment/Focus group Develop a focus group plan to test a concept highlighted in the designated business case that is related to advertising for a product. Each student needs to follow the guidelines given in Chapter 4 of the textbook. The plan should be developed so that a research manager could readily follow it during implementation and understand the limitations of the results from the focus group. Therefore, it should highlight all limitations, assumptions as well as constraints. B) Quantitative Research Assignment Develop hypotheses For the first part of the assignment, each student will review related literature (from sources such as academic journal articles, business articles, and online articles) and develop a hypothesis for the effect of price and advertising on sales revenue. Note: other variables are likely. Test hypotheses using Regression Topic, motivation, target and features types Data sources identification and assimilation via R to analyse the data and test your hypothesis Describe the data analyses you have conducted Highlight important results of the data analysis State whether your hypothesis was supported or not, and if the hypothesis was not supported, why? Highlight implications of the results Provide managerial recommendations 3.Advance Marketing Research Tools Assignments A) Cluster Analysis, Classification and Multidimensional Scaling B) Conjoint Analysis (in-class assignment) 4.Marketing Research Term Project Working in teams, students will conduct research to address a current business problem affecting a specific company. A) Select a manufacturing, service, or governmental organization that they believe would benefit from new data-driven insights, and describe a specific marketing problem it is facing. B) Identify what information is needed to resolve the problem. C) Formulate related research questions. D) Review literature and develop hypotheses. E) Conduct research to answer research questions. F) Write a report. Must follow the format described in the “Chapter 19 Research Report” of the I&C book 5. Final Exam: Analytical Questions Prerequisites: Marketing Management II, Mathematical Statistics

Revenue Management I This course focuses on the demand without attempting to manage the supply. But it does take the amount, location, condition, or vintage of the supplies into account. Demand must be understood first to be managed. This understanding comes partly from statistical forecasting but more importantly from the identification of the demand drivers. These drivers are specific to industries, but some are common and easily obtainable such as general macroeconomic indicators, demographic data, housing inventories, and temperatures. Unlike these demand drivers, prices can be managed over time, customer classes, locations. A good portion of the course is dedicated to determining good prices depending on inventory, capacity, input costs, and previous prices. In this process, both analytical arguments and methods are presented and their appropriateness in various practical contexts are discussed. Most applications are recent and made possible by the advances in technology, information systems, and data mining. Prerequisites will be crucial to course development. Typical Text --> Pricing & Revenue Optimization. Robert L. Phillips Resource --> Various RM journals Technology Requirement --> Price repository/database w.r.t. quantity or unit, etc., etc. Price Monitoring Tool R environment may incorporate arules and arulesViz R optimisation and inventory packages will be relevant R package RM2 to be useful Other packages related to skills from prerequisites or maturation Excel Homework & Assignments --> You can discuss homework and assignments with others but must write up by yourself with the full understanding of what you write. During quizzes, any printed or hand-written hard-copy material (book/note) can be used but no device with cellular (mobile, wireless) communication capability is allowed even if that capability is disabled. Pricing Strategies --> Advance recital of pricing strategies labs form Pricing Strategies course. Implementation studies to complement or contrast modules 1-5 & 12. Group Projects in R --> With use of R students are expected to have commentary during throughout the computation or simulation development accompanying typed in a word processor. Price response function Demand functions and price optimisation Price response estimation Overbooking Project Real data: critical fractile methods versus monte carlo methods. The RM2 R package to follow. Assessment --> Class attendance and contribution to discussion Homework and Assignments Group Projects Pricing Strategies 4 Quizzes Course Modules: 1-6 Demand Management; 7-12 Revenue Management --> 1. Introduction to pricing and revenue optimization 2. Demand functions and price optimisation: Price-Response function Competition Note: the following to be incorporated (and critiqued) for analysis discussion, however, one may have to analytically build up structure for any advance functions applied Fonseca, Y. (2017). Price Optimisation: How to find the Price that Maximizes your Profit. R Bloggers Fonseca, Y. (2018). Different Demand Functions and Optimal Price Estimation in R. R Bloggers 3. Demand Drivers 4. Price-Response Estimation (industries specific) Note: there must be active development in the R environment based on course text and retrieved data. As well, the following guide may or may not be useful: Jerenz, A. (2008). Survival Analysis: Estimation of the Price-Response Function. In: Revenue Management and Survival Analysis in the Automobile Industry. Gabler. 5. Price Differentiation: Volume discounts; Arbitrage and Cannibalization; Consumer welfare 6. Constrained Supply: Opportunity Cost; Segmentation; Pricing 7. Revenue Management 8. Capacity Allocation 9. Network Management 10. Overbooking 11. Markdown Pricing 12. Customized Pricing: List Prices vs. Customized Prices; Responses to Competitor Bids Prerequisites: Enterprise Data Analysis II, Optimisation, Mathematical Statistics, R Analysis, Pricing Strategies Revenue Management II Advance treatment and reinforcement course for revenue management. Assessment --> Class Participation Assignments (done individually) Prerequisite Projects Recital All will be done. Being precursors appropriately in sync or situated with current course group projects Group Projects (data driven) Inventory Models Demand Forecasting (build on prior project) Competitive Factors Discrete Choice models (build on prior projects) Overbooking & Booking Limits Unconstraining Methods in RM Pricing Performance Measures Finance (use of financial statements) for EBITDA, EVA, NOPLAT, Operating Cash Flow, FCF Final Exam In-class open book/notes, R use Course Text --> Pricing and Revenue Optimization by Robert L. Phillips Resources --> RM related journals Technology Requirement --> Price repository/database w.r.t. quantity or unit, etc., etc. Price Monitoring Tool R environment (what was said in prerequisite) Excel Course Topics --> 1.Demand Drivers 2. Inventory Models of RM Stochastic Inventory Management and the Newsvendor Model [or (r, Q)] R packages of interest: SCperf, Inventorymodel, inventorize, tsutils Inventory Analysis (modelling, construction and R) ABC - XYZ Analysis Note: student groups will be assigned 2-3 firms or services to work with; hospitals, pharmacies, hospitality, vehicle rental services, commodities (soft, raw, hard), textiles, manufacturing, retail, public services, etc. Single Resource Revenue Management, and expected marginal value to control sales 3.Demand Forecasting and Data Analysis (lecturing to structure project) Based on: https://en.wikipedia.org/wiki/Demand_forecasting Unconstraining for unobservable no-purchases--concept and the EM technique and exponential smoothing models 4.Competitive Factors (lecturing to structure project) PESTEL, SWOT and 5C Analysis development 5.Discrete Choice Models Paez, A. and Boisjoly, G. (2022). Discrete Choice Analysis with R. Springer. Ben-Akiva, M., et al. (1997). Modelling Methods for Discrete Choice Analysis, Marketing Letters, 8(3), 273–286. Ortelli, N. et al (2021). Assisted Specification of Discrete Choice Models, Journal of Choice Modelling 39, 100285l Kim, C., Cho, S. and Im, J. (20ZZ). RMM: An R Package for Customer Choice-Based Revenue Management Models for Sales Transaction Data. The R Journal Vol. XX/YY, AAAA Note: preference with data of interest may be a concern. ChoiceModelR package 6.RM Process management (organizational issues) 7.Overbooking Critical Fractile Methods Monte Carlo Methods Include prerequisite project recital 8.Booking Limits EMSR-b and Bid-Price Models (RM2 R package to follow) 9.Unconstraining Methods in RM Guo, P., Xiao, B. and Li, J. (2012). Unconstraining Methods in Revenue Management Systems: Research Overview and Prospects. Advances in Operations Research, Volume 2012, Article ID 270910, 23 pages 10.Pricing Microeconomic and marketing theories on consumer- behaviour & pricing Product design, bundling and demand segmentation Dynamic Pricing Policies Yuan, Etienne. (2020). How I Built a Dynamic Pricing Model. Towards Data Science Katsov, I. (2019). A Guide to Dynamic Pricing Algorithms. Grid Dynamics Will take on industry specific examples for development 11.Price-Response Estimation (include prerequisite project recital) Survival Analysis (active development in R): Not confined to car industry development, but: Estimation of the Price-Response Function. In: Revenue Management and 12.Pricing Policies in Action Markdown Policies and Liquidation Pricing with supply constraints Customized pricing and e-commerce 13. Network RM (focus on airlines and air cargo) Network revenue management, control mechanisms Linear Programming Approach to Revenue Management Augmenting literature: An, J., Mikhaylov, A.Y., & Jung, S. (2021). A Linear Programming Approach for Robust Network Revenue Management in the Airline Industry, Journal of Air Transport Management, 91, 101979. Clough, M., Jacobs, T. & Gel, E. (2014). A Choice-Based Mixed Integer Programming Formulation for Network Revenue Management. J Revenue Pricing Management 13, 366–387 (2014) Kunnumkal, S., Talluri, K., & Topaloglu, H. (2012). A Randomized Linear Programming Method for Network Revenue Management with Product-Specific No-Shows. Transportation Science, 46(1), 90–108. Applying Network RM to different industries (airlines and air cargo) Footing (developing competent logistics): from modelus 1 - 13 -- in regards to development for Network RM what will be practically applicable or meaningful or integrable? A goal is to have problems where the amount of variables and parameters are manageable concerning intimacy in analysis and modelling, and manageable with CPU/GPU limits concerning R use when called upon. 14.Revenue Management Models and Methods. How to classify RM problems and appropriate means to solve them. The following article may or may not be encompassing: Talluri, K. T. et al (2009). Revenue Management: Models and Methods, Proceedings of the 2009 Winter Simulation Conference, WSC 2009 Solving Revenue Management Problems Goal is to have problems where the amount of variables and parameters are manageable concerning intimacy in analysis and modelling, and manageable with CPU/GPU limits concerning R use when called upon. 15.Performance Measurement (analyse & implement for ambiances of interest) Applications: to hotels and restaurants, vehicle rentals, public transportation, hospitals or other public services) ADR, RevPAR, RevPOR, GOPPAR, TRevPAR, NRevPAR, ARPA ProPASH and ProPASM González, A. B. R., Wilby, M. R., Díaz, J. J. V. et al (2021). Utilization Rate of the fleet: A Novel Performance Metric for a Novel Shared Mobility, Transportation 16.Finance: EBITDA, EVA, NOPLAT, Operating Cash Flow, FCF Prerequisite: Revenue Management I REVENUE MANAGEMENT ACTIVITY FOR “SUMMER” AND “WINTER” SESSIONS It may be the case some activities can be grouped and given a major title together; however, detailed descriptions will be required. Activities repeated can be added to transcripts upon successful completion. Repeated activities later on can be given a designation such as Advance “Name” I, Advance “Name” II. As well, particular repeated activities serve to towards developing true comprehension, competency and professionalism. Activities will be field classified. Particular projects of interest being stationary: DETERMINING CUSTOMERS’ PREFERENCES Basic Resonating R literature (but not the focus): Chapman, C. and McDonnell Feit, E. (2019). R For Marketing Research and Analytics. Springer, Cham. Dolnicar, S., Grun, B. and Leisch, F. (2018). Market Segmentation Analysis: Understanding It, Doing It, and Making It Useful. Springer Based on assumed limitations with resources we may be restricted to the following three methods with large samples (assuming that compensation towards participants is economically reasonable): 1.Surveys and Focus Groups 2.Conjoint Analysis R package conjoint may suffice 3.Discrete Choice Models Paez, A. and Boisjoly, G. (2022). Discrete Choice Analysis with R. Springer ChoiceModelR package Ben-Akiva, M., et al. (1997). Modelling Methods for Discrete Choice Analysis, Marketing Letters, 8(3), 273–286. Ortelli, N. et al (2021). Assisted Specification of Discrete Choice Models, Journal of Choice Modelling 39, 100285l Kim, C., Cho, S. and Im, J. (20ZZ). RMM: An R Package for Customer Choice-Based Revenue Management Models for Sales Transaction Data. The R Journal Vol. XX/YY, AAAA Wierenga, B. (Editor). (2008). Handbook of Marketing Decision Models (Vol. 121). Springer NOTE: for the 3 areas prior prior -- A. Intension B. Pros and cons C. Comprehensive, professional and robust frameworks, logistics and implementation. Seek out applicable R packages as well. D. Comparative analysis of results. CUSTOMER LIFETIME VALUE (CHECK ACTUARIAL POST) CUSTOMER VALUE TOOLS AND METRICS PART A 5C Analysis implementation for chosen firms (active development) CFI Tea. (2022). 5C Analysis. Corporate Finance Institute Note: much effort in identifying robust and dexterous methods to compute TAM, SAM, SOM that will be involved in the 5C analysis when they are encountered. PESTEL/SWOT will also be taken seriously. PART B Segmentation in R (standard and RFM based) Logistic Regression activities PART C Developing a model of customer relationship management and business intelligence systems for catalogue and online retailers (or whatever). PART D Association Rules Packages arules and arulesViz applications (may be influenced by part B & C) PART E Customer Value Metrics Google Trends Google Analytics Can R be integrated? PART G Development based on the following text in the R environment Kumar, V. and Petersen, J. A. (2012). Statistical Methods in Customer Relationship Management, Wiley RISK MANAGMENT FOR RM OPERATIONS (COMING SOON) .... HOSPITALITY R language will be applied extensively. The following packages may be momentarily highly useful: arules arulesViz There will be other R packages to apply. PHASE 1 (Intelligence and development): <The essential components of Revenue Management --Motivation to travel --The main elements of the function of Revenue Management --Comprehend Revenue Management terms and definitions --Comprehending your customers’ pathways to booking or reservations --How customers shop for accommodation --Learn what drives customers search and selection process --Learn what influences their choices during their search (including travel agents) <Market Segmentation --Defining segmentation --Why hotels segment their markets --How to define each segment e.g. Corporate, Events, Wholesale, Retail etc --Is a channel the same as a segment? --How to use this segmentation to gain insights and improve bottom line results --Understand different consumer behaviours in difference channel --Understand the different terms and strategies around using Segments vs Channels vs personalised offer. NOTE: inevitably one should always expect to have expensive platforms made available for use. Nevertheless, the R language is powerful towards market segmentation. The following are ideas (our interests will be different) --> Yiu, R. (2019). Market Segmentation with R (PCA and K-Means Clustering) – Part 1. Towards Data Science Jimmyxu (2018). Segmentation Analysis. Rpubs by RStudio Pawar, R. S. (2019). Customer Segmentation: A Practical Introduction in R. Towards Data Science Coffey, K. K0means Clustering for Customer Segmentation: A Practical Example http://www.kimberlycoffey.com/blog/2016/8/k-means-clustering-for-customer-segmentation Igras, K. and Appsilon Data Science. Customer Segmentation for R Users. KDnuggets DATAFLAIR TEAM (2019). Data Science Project – Customer Segmentation using Machine Learning in R. Data Flair https://data-flair.training/blogs/r-data-science-project-customer-segmentation/ NOTE: one must clearly distinguish between market segmentation and customer segmentation. Will like to pursue market segmentation and customer segmentation activities with data to become tangibly familiar and competent at least. <The Hospitality Industry --What are the fundamental principles of economics and their role in Hotel Revenue Management? --How do Revenue Directors monitor and measure their competitor marketplace? --How do Hotel Managers identify true competitor properties? --How do you read competitor reports and use other data to derive strategic insights, and use the data to make better decisions? Distribution --Definition of Distribution within the Accommodation sector --Definition of accommodation Inventory and how it is managed --Types of distribution channels --Factors of the Cost of Sale --Steps to implementing a successful Distribution Strategy --Important role of technology in a Distribution Strategy --Definition of Rate Parity and its role in Distribution <Forecasting --What are the different types of forecasts? --What are the objectives for each of the types of forecasts? --What information do I need to put a forecast together? --How do I find this information? --What questions should I ask when putting together a forecast? --How often should I be adjusting the forecasts? --What are the steps that I need to follow to put the forecast together? --What is the difference between unconstrained and constrained demand? --What are the elements of an accurate forecast? <Revenue Strategy --To understand the components of a good revenue strategy --Different revenue strategies explained --Pricing Strategy --Exercises in how to use the Revenue Strategy to manage day-to-day tactics --Inventory Control- how inventory can impact sales. If forecasting constraint, monitor to ensure controls do not have too big an impact and adjusting strategy where necessary and why revenue managers might withhold inventory. <Hotels Room Pricing --How to price your different room types --Different types of pricing explained – what and why: BAR, Rack, Group, Corporate, Tactical vs Strategic pricing, Mobile only pricing – why? Wholesalers, Static vs Dynamic rates, Corporate & Event, Opaque Pricing, Length of Stay Pricing, Loyalty clubs and Closed User Group rates. Additionally, what technologies and software can be applied for optimal modelling and analysis of pricing methodologies w.r.t. time invested? --Packages/ promotions/ Discounting – Discounting –what additional volume required if I discount my price? Is a lower price generating new demand? --Understanding the impact on discounting -How to calculate Occupancy needed to offset discounts --Understanding the influences on pricing including decoy and anchor pricing --Lead time and its impact on pricing --Displacement Analysis --Contracts --Technology available to monitor and manage pricing PHASE 2 (market dynamics): Crucial terms concepts, constructs, industry and quantity terms of interest: Market segmentation Customer segmentation Customer equity (value equity, brand equity, retention equity) -> Variable price product package types -> Customer Lifetime Value(s) CLVTools R package with vignettes Market Effectiveness Distribution channelling is essential to develop pricing (packages) Pricing of packages varies to take advantage of opportunities. With market segmentation comes conditions such as seasonal activities, weather, emerging events and other things; additionally, price variance due to competition customarily occurs within such time intervals. Whatever events, season or circumstance one wants to capitalise on distribution channels must be practical with the time constraints. The following articles (may not be premier) are to be subjugated to predictive analytics logistics. Immersion activities are necessary. One must know what prior developments or phases that determine a pricing strategy and allocation: Bitran, G., and Caldentey, R., An Overview of Pricing Models for Revenue Management, Manufacturing & Service Operations Management 2003 INFORMS Vol. 5, No. 3, Summer 2003, pp. 203–229 Masruroh, N. A., and Putri, E. C., Pricing Model Development for Hotel Industries Using Game Theory Approach Considering Seasonal Factor and Uncertain Demand, Proceedings of the 2012 IEEE ICMIT One must know how forecasting is related to the above predictive analysis model. The following articles are guides to be subjugated to the predictive analytics manner above. Computation immersion activities are necessary: Pereira, L. N., An Introduction to Helpful Forecasting Methods for Hotel Revenue Management, International Journal of Hospitality Management 58 (2016) 13–23. Rajopadhye, M., Forecasting Uncertain Hotel Room Demand, Information Sciences 132 (2001) 1 - 11 Nakano, M., Saga, R., & Tsuji, H. (2005). Hotel Room Allocation for Sales Channel by Dynamic Programming. 2005 IEEE Conference on Emerging Technologies and Factory Automation, 1, 6 pp.-1100. PHASE 3 (data logistics and immersion): Wil be highly dependent on phase 2. First skill --> Identifying the types of data of interest. Logistics for such data based on phase 1 and phase 2. In the R environment to introspect and query data on hospitality for regions of interest with competing agents. Some of the elements: Customers Segmentation Data (products, pricing, transactions, etc., etc., etc.) Pricing models Reservation system Forecasting Optimisation Second skill --> In the R environment students must be able to develop a revenue management system based on first skill prior. PRICING STRATEGIES Will be advance recital of models, tools, techniques from course. AIRLINE INDUSTRY Note: open to Operations Management/Operational Research The following two literature concern operations planning or development for airlines in the real world --> -Traffic Forecasting and Economic Planning Workshop, International Civil Aviation Organization, FEPW (Cairo)-WP/5 2010: https://www.icao.int/MID/Documents/2010/fepw/docs/fepw_wp05.pdf -ICAO Forecasting Manual Concerns with development --> Comprehensive understanding of the development process, and the choosing the best models to be implemented. Models will range from deterministic to stochastic. Will like to develop validation through case studies of airlines to critique application of real airline/airport data. Data sources examples --> ICAO Economic Development (https://www.icao.int/sustainability/Pages/Statistics.aspx) UK Civil Aviation Authority (Airline Data) https://data.gov.uk/search?filters%5Bpublisher%5D=Civil+Aviation+Authority UBC Transportation Industry: Air (https://guides.library.ubc.ca/transportation_air/stats ) FAA Data & Research Bureau of Transportation Statistics OAG, MIT Global Airline Industry Programme (Airline Data Project) Kaggle R environment --> R with R studio and packages of interests will provide the idealistic environment for pursuits; use of the typical deterministic optimisation packages, and as well, having stochastic and statistical prowess R Packages specifically for Multi-objective programming, Goal programming, and 90C29 (if needed): caRamel, GPareto, mco, emoa, rmoo Note: activity may not explicitly treat segmentation with customers with routes and forecasts; likely leading to more technical sensitivities. SERVQUAL, weighted SERVQUAL, SERVPERF and weighted SERVPERF in the field NOTE: also open to Public Administration students concerning public services and private sector services to the public. 1. SERVQUAL Parasuraman, A, Ziethaml, V. & Berry, L.L. (1985), "SERVQUAL: A Multiple- Item Scale for Measuring Consumer Perceptions of Service Quality' Journal of Retailing, Vo. 62, no. 1, pp 12-40 Parasuraman, A., Berry, L.L. and Zeithaml, V.A., (1991) “Refinement and Reassessment of the SERVQUAL scale,” Journal of Retailing, Vol. 67, no. 4, pp 57-67 2. Find Weighted SERVQUAL literature 3. SERVPERF Cronin Jr, J. J., & Taylor, S. A. (1994). SERVPERF versus SERQUAL: Reconciling Performance-Based and Perceptions-Minus-Expectations Measurement of Service Quality. The Journal of Marketing, 125-131. Jain, S. K., & Gupta, G. (2004). Measuring Service Quality: SERVQUAL vs. SERVPERF Scales, Vikalpa, 29(2), 25-37. 4. Find Weighted SERVPERF literature for pursuits MERMI and possible alternatives PART A -Performance Measurement (analyse & implement for ambiances of interest) Operations (some applicable to hotels and restaurants, vehicle rentals) Intensions of the model; pros and cons; model analysis; logistics; implementation; comparative analysis. Note: some models may be extension of others so develop constructively. ADR, RevPAR, RevPOR, GOPPAR, TRevPAR, NRevPAR, ARPA ProPASH and ProPASM González, A.B.R., Wilby, M.R., Díaz, J.J.V. et al. Utilization Rate of the Fleet: a Novel Performance Metric for a Novel Shared Mobility. Transportation (2021). PART B Analyse the given journal articles, determine the logistics, sources to acquire data and means to incorporate such data to replicate such evaluations. Other (or prior) evaluation metrics to develop and compare with MERMI. Assisting literature for MERMI: Talón-Ballestero, P., González-Serrano, L. & Figueroa-Domecq, C. (2014). A Model for Evaluating Revenue Management Implementation (MERMI) in the Hotel Industry. Journal of Revenue and Pricing Management. Aug 2014, volume 13, issue 4, pp 309–321 Rodriguez- Algeciras, A. & Talón-Ballestero, P., (2017). An Empirical Analysis of the Effectiveness of Hotel Revenue Management in Five-Star Hotels in Barcelona, Spain. Journal of Hospitality and Tourism Management 32, 24-34 ONLINE RETAIL ANALYTICS DEVELOPMENT Ferreira, k., Lee, B. H. A. and Simchi-Levi, D. (2016). Analytics for an Online Retailer: Demand Forecasting & Price Optimisation. Manufacturing & Service Operations Management, 18(1) The R environment and accessible databases will be applied towards interests. Note: open to Operations Management/Operational Research FINANCE Finance degree endeavors reside under Business. --Core Courses (constituted by the following 4 different components): 1. Communication << Business Communication & Writing I & II, Enterprise Data Analysis I & II, International Financial Statement Analysis I & II, Corporate Finance >> 2. Financial Commerce << Corporate Valuation, Venture Capital, Mergers & Acquisitions, International Commerce >> 3. Investment & Derivatives << Theory of Interest for Finance (check COMPUT FIN); Investment & Portfolios in Corporate Finance; Options & Futures for Business Management >> 4. Capital Markets << Asset Management >> --Mandatory Courses: Calculus for Business & Economics I-III, Introduction to Macroeconomics (check ECON), Money & Banking (check ECON), Probability & Statistics, Mathematical Statistics, Personal Finance (check Actuarial) --Special Required Electives Tracks: Option 1: Financial Accounting, Corporate Auditing, Investment Banking, Corporate Risk Management Option 2: Financial Accounting, R Analysis (Actuarial post), Commercial Bank Management, Bank Risk Management Option 3: Optimisation (Actuarial post), R Analysis (Actuarial post), Applied Decision Analysis (check OM), Corporate Risk Management Option 4: Financial Accounting, Strategic Business Analysis & Modelling, Corporate Risk Management, R Analysis.

NOTE: for Probability & Statistics, Mathematical Statistics check Actuarial post. NOTE: for some finance courses sources such as the following may prove useful: https://www.sec.gov/oiea/Article/edgarguide.html In general know how to use SEC Edgar (other foreign counterpart) when needed. Not necessarily all data to be found there Specific course descriptions below: Enterprise Data Analysis I Learning the key functions of Microsoft Excel. You will learn how to use it for general business activities such as problem solving, presentations, as well as general personal use. It's assumed each student possesses computer skills. Enterprise tools and techniques using modern data analysis tools. Introduction into basic and advanced functions in order to build a strong foundation for performing mathematical and analytical functions and analysis. Review of spreadsheet fundamentals, formulas, graphing, data slicing with pivot tables, and dashboard development. Managing and analysing enterprise data with spreadsheets. This course will involve individual spreadsheet work as well as multiple team projects demonstrating data organization, management, presentation, and analytical techniques. At the completion of this course students will be able to: Import, format, and validate data from multiple sources. Perform excel functionality to format and manipulate data. Evaluate personal and business problems and determine the best course of action. Understand how to format data and perform advanced formula functionality Evaluate problems and determine the best course of action Present data findings in a visual format for easy comprehension Course Grade Constitution --> Attendance & Participation Homework Assignments Labs 2 Data Analysis Projects Midterm Exam Final Exam Textbooks & Tutorials: TBA Tools to be used throughout course --> Excel YouTube Microsoft learning: https://docs.microsoft.com/en-us/learn/browse/ Course Outline --> Overview, navigation, Excel basics and cell referencing Importing and Validation of Data Formatting and Math Functions Lookup and Business Math Functions Charting and Pivot Tables Visualizing Data Data Analysis Project 1 Advanced Formatting and Functions Pivot functionality, charting, graphing Problem Solving Functions Financial Functions Data Analytics Process Data Analysis Project 2 Co-requisite (for BUS, ECN, PS, PA, ACTUAR and COMPFIN majors only): International Financial Statement Analysis I Enterprise Data Analysis II Course is roughly 2 hours per lecture. Course meets in a computer lab regularly, and/or students will make use of their personal computers in room. Objective --> Customarily progression in Excel rides on specifically what projects one is trying to accomplish; fiddling blindly in Excel isn’t really productive at all. MS Access is used for working with large datasets. Texts: TBA Tools to be used throughout course --> MS Excel MS Access YouTube Microsoft learning: https://docs.microsoft.com/en-us/learn/browse/ Course Grade Constitution --> Homework Prerequisite Refreshers: assignments encountered in prerequisite given at various times to stay fresh. Scheduled Evaluations: three in-class computer-based evaluations. Based on a combination of prerequisite skills and content covered in all course activities (readings from the text, outside reading materials, discussion questions, lab activities, and course case studies). NOTE: gov’t data with Excel and Access may be substitutes for other data that may be deemed sensitive. Treasury, Economics, Labour, Census, NIH, FDA, USDA, Municipal, SEC, FTC, IGOs, etc., etc. 7 Projects: Course will emphasize applications. Your skills and self-sufficiency will be put to the test. Some projects will have same due dats. Quantitative Grading formula --> Attendance Homework Prerequisite Refreshers 3 Scheduled Evaluations 7 Projects Course Outcomes (Mandatory) --> · Construct, modify, and print a professionally designed and formatted spreadsheet. · Create and manipulate various types of charts and enhance charts with drawing tools. · Create and use basic formulas and functions. · Create and use complex and advanced formulas and functions from each category of functions provided by Excel. · Create macros, customize toolbars, and create command buttons · Utilize XML for data exchange · Using named ranges, create a database and perform the following: sort, filter, advance filter, and extract. · Analyze lists and databases using database functions · Create Pivot tables, use Solver, Scenario, and Goal Seek for data analysis. · Using Excel and OLE, share data with other applications. · Using various Excel tools, perform what if analysis and projections on business data. · Create 3D worksheets, 3D workbooks, and 3D formulas. · Validate and control data entry. · Perform trend analysis. · Perform Web Queries · Perform SQL Queries · Explore and utilize the various tools provided by Excel for use in a business environment. Projects --> PROJECT 1: HR PERSONNEL IN HR, INVENTORY & SUPPLY Techniques Applied --> Spreadsheet Constructions Basic tools/techniques/skills that are applicable and practical with HR pursuits, inventory and supply chain. PROJECT 2: APPLICATIONS IN CORPORATE FINANCE & INVESTMENTS Case 1: Investment Portfolio Analysis Techniques Applied --> Advanced formulae Charting & Presentations Grouping data Scenarios/What-if Analysis Data Tables/Break Even Analysis Case 2: Loan Analysis Techniques Applied --> Advanced Formulae Functions Goal Seek Case 3: Depreciation Schedule Analysis Techniques Applied --> Functions What-if analysis Change tracking and collaboration Goal seek PROJECT 3: PROJECT MANAGEMENT Case 1: Gantt charts Project goal(s) Project structure Parameters and constraints Assigned personnel Macros PROJECT 4: APPLICATIONS IN HUMAN RESOURCES Case 1: Employee and Payroll Decision Making Techniques Applied --> Working with large datasets Lookup Tables Filtering Multiple worksheets linking Advanced formulas and macros Charting and presentations PROJECT 5: LINKING MULTIPLE SPREADSHEETS & DATASETS WITH MS ACCESS Case 1: Import, Link and Integrate Spreadsheets into Tables Techniques Applied --> The need for more powerful databases Relational database concept Excel vs. a relational database Table creation & table field properties Importing spreadsheets Table relationships Import, Link and Integrate Spreadsheets into Tables PROJECT 6: DATABASES, XBRL, XML Relevance of Excel with DBMS: introspection, queries and analysis Involves .csv. .xlsx, .accdb Government (departments, agencies, bureaus, administration), international government organisations, etc., etc. Making .accdb files Understanding parameters with XBRL for financial data requests and organising data XML integrability/extraction (forwards and backwards) PROJECT 7: INTRODUCTORY EXPLORATORY DATA ANALYSIS (External Sources, Excel and Access) Techniques Applied --> Introspection, Queries and Recognition of Data Sizes Developing Correlation Matrices (bivariate and higher) Extracting Variables Followed by conditions of interest Summary Statistics for variables Distribution of each variable Univariate distribution between two variables; various pairs Scatter Plots among variable pairs. Regression among variable pairs (with summary statistics) Basic Time Series analysis (optional) Prerequisite: Enterprise Data Analysis I Co-requisite (for BUS, ECN, PS, PA, ACTUAR and COMPFIN majors only): International Financial Statement Analysis II International Financial Statements Analysis I Course examines the accounting process, transaction analysis, asset and equity accounting, financial statement preparation and analysis, and related topics. A study of analysing, classifying, and recording business transactions in both manual and computerized environment. Complete the accounting cycle, prepare financial statements. Course Literature --> Textbook TBA Mandatory Resource Guides: GAAP or IFRS or ambiance preference Tools --> Microsoft Office 365 Microsoft Dynamics Management Reporter Microsoft learning: https://docs.microsoft.com/en-us/learn/browse/ Course will make use of financial statements of private companies, NGOs and public administration to be practical and to gain real exposure. NOTE: students will learn how to access proper official data. Assessment --> Assignments & Analysis Sets Quizzes General Labs XBRL Student Project 3 Exams Overview of Assessment --> Each module will be accompanied by Assignments & Analysis Sets. Lab(s) will take on multiple modules. Each lab will have analytical activities, computational exercises and development with Microsoft tools. Quizzes will reflect Assignments & Analysis Sets, and some elements of labs (analytical activities and computational exercises) XBRL Project concerns proper application of data for active commerce and regulations. TOPICS --> Accounting Process Financial Statements (Types, Structure, Formulas, Procedures & Logistics) Chosen, Assets and Liabilities (classifications, valuation, earnings and taxes) Time Value of Money Construction of Financial Statements (with assets and liabilities) Evaluation of Financial Statements (of the major types) Adjusting Entries Financial Statements Process for Developing (9 - 12) Measures Profitability Efficiency Liquidity Debt structure and risk Information, decision making, and financial markets Co-requisite (for BUS, ECN, PS, PA, ACTUAR and COMPFIN majors only): Enterprise Data Analysis I International Financial Statements Analysis II Advance treatment for topics from prerequisite and introduction to advance analysis. Course Literature --> Textbook TBA Mandatory Resource Guides: GAAP or IFRS or ambiance preference Tools --> Microsoft Office 365 Microsoft Dynamics Management Reporter Microsoft learning: https://docs.microsoft.com/en-us/learn/browse/ Course will make use of financial statements of private companies, NGOs and public administration to be practical and to gain real exposure. NOTE: students will learn how to access proper official data. Assessment --> Assignments & Analysis Sets Quizzes General Labs XBRL Student Project 3 Exams Overview of Assessment --> Each module will be accompanied by Assignments & Analysis Sets. Lab(s) will take on multiple modules. Each lab will have analytical activities, computational exercises and development with Microsoft tools. Quizzes will reflect Assignments & Analysis Sets, and some elements of labs (analytical activities and computational exercises) XBRL Project concerns proper application of data for active commerce and regulations ADVANCE IMPLIED TOPICS/TASKS -- Accounting Process Financial Statements (Types, Structure, Formulas, Procedures) Chosen, Assets and Liabilities (classifications, valuation, earnings, taxes) Time Value of Money Construction of Financial Statements (with assets and liabilities) Adjusting Entries Evaluation (of the 3 major types) of Financial Statements Adjusting accounts or financial statements towards measures (profit, efficiency, liquidity, debt). About 9-12 measures in total. MANDATORY TOPICS/TASKS (3 weeks)-- Horizontal Analysis (HA) Vertical Analysis (VA) Trend Analysis Prerequisite: International Financial Statements Analysis I Co-requisite (for BUS, ECN, PS, PA, ACTUAR and COMPFIN majors only): Enterprise Data Analysis II Corporate Finance This course presents the foundations of finance with an emphasis on applications vital for corporate managers. NOTE: course will be immersive applications intensive and wide range for each module. NOTE: computing in this course is needed. I will not provide summarized data towards formulas and models for you. In this course it’s critical that students build integrity and self-reliance; be prepared to pursue data from various sources independently, because in the real world such is required to be deemed competent. Computational Skills --> Alongside manual computation, all modules will also have emphasis on much use of spreadsheets and/or R with computation. Realistic finance highly goes beyond the pen and paper. Alongside analytical and manual tasks, R and Microsoft software use will arise often. Financial Statements Analyses --> Your accounting skills will be tested without restraint, based on Balance Sheets, Income Statements, Cash Flow Statements. Tasks often may not be direct, say, ingenuity skills. For various assigned firms students are responsible for applying horizontal analysis, vertical analysis. Developing ratio analysis based on the 3 major financial statements; adjusting accounts for financial statements for ratios analysis. Concerns: liquidity, debt, profitability, efficiency, and market value. Applications --> The given applications in the syllabus will be hands-on, requiring students to gather data from appropriate sources. Instructor provides interpretation of concepts and the logistics, then students must follow through. Cases --> Cases will be available on technology platform used. Students can make groups of up to 4 constituents for cases. Cases will serve to challenge students with course topics. Note: all topics in course outline will be treated. Note: a single case can/will incorporate multiple topics to test your knowledge and understanding. Note: for each case prior applications can show up any time when required. Exams --> The 2-3 exams are open-book and you are free to bring a calculator to the exam (recommended). As well, exams will also make use of a computer lab or personal computers. You should know for a particular question whether computer usage makes sense or not. Exams will reflect computational skills, financial statements analyses, applications, and cases (all different to those encountered). Also expect to gather data, say, gathering financial statements and markets data on your own for tasks. Some tasks will require the mentioned tools. For questions on instruments, if R packages are used, such must be complemented with manual development. Tools --> Real financial statements (balance sheets, income statements & cash flow statements) from SEC or whatever Capital Markets data Microsoft Office 365 Microsoft Management Reporter Microsoft learning: https://docs.microsoft.com/en-us/learn/browse/ R Packages: FinCal, jrvFinance, tvm, YieldCurve, BondValuation NOTE: course will be applications intensive and wide range for each module. Namely, applications for module topics will be treated in a manner where logistics and tools are meaningful and practical to be put to work involving the quantitative aspects. Textbook of consideration --> Corporate Finance, Berk & DeMarzo, Pearson - Prentice Hall Assessment --> Assignments: computational skills, financial statements analyses Applications Cases 2-3 Exams Outline --> 1.Salutations and expectations. Technology tools applied for materials 2.Time Value of Money Chapter sections 3.1, 4.1 – 4.3, 4.5 – 4.8, 4Appendix, 5.8 Applications: Valuing zero-coupon bonds; Valuing coupons; Valuing and structuring annuities and perpetuities; Savings, Retirement planning 3.Interest Rates Chapter sections 5.1 – 5.3, 5.5 Applications: Bonds, Savings vehicles, Mortgage financing and refinancing decisions 4.Discounting Cash flow (DCF) Analysis Chapter sections 2, 3.1, 3.3, 7.1, 8.1 – 8.4 Applications: Strategic Decision-Making, Capital Budgeting, Financial Statement Analysis, Strategic Decision Making with Resource Constraints Case 1 5. Return on Investment Chapter section 7.2, 7.4 Applications: Amortizing Loans, Personal Finance (auto loans, leases, mortgages), Financial Negotiating Strategies Case 2 6. IPO Model & Prospectus Initial Public Offering Model: structured process firms follow to become a publicly traded company. Murphy, C. B. (2022). What is a Prospectus? Example, Uses, and How to Read It. Investopedia Applications: groups will be assigned 2-3 firms for prospectus analysis 7. Fixed Income Securities Chapter sections 3.4, 3.5, 6.1 – 6.5, 6Appendix, 30.4 Applications: Valuing and investing in treasury securities, Managing a bond portfolio Case 3 8. Listings & Valuing Stocks Hayes, A. (2021). Listings Requirements. Investopedia Comparative view of requirements for NYSE, NASDAQ, LSE, TSX, BSE, and arguments for listing preferences Stock valuation methods: DDM, DCF, AEVM, Comparables Analysis Concepts, logistics and implementation Chapter sections 9.1 – 9.4 augmented by priors Fernando, J. (2022). Earnings per Share: What does it Mean and How to Calculate It. Investopedia Applications: EPS types, Mergers and Acquisitions, Corporate defenses Case 4 9. Non-Publicly Traded Appraisals Investopedia Articles Liberto, D. (2021). Appraisal Method of Depreciation Bloomenthal, A. (2021). Appraisal Approach: Definition, How Process Works, and Example Best Online Auction Websites Based on intelligence and skills acquired from priors will choose items under various categories among different auction websites, observing auctions and bids. Note: alternatives to website data is the Kaggle repository and others. Bids (and possibly timing of bids) will be needed. Then students will apply appreciation methods. Namely, Appraisal Method of Depreciation versus Accounting Depreciation from Liberto; real estate methods from Bloomenthal. How do overall bids and winning bids compare to your valuations and initial average retail price? What can be speculated? Note: other useful “blogs” -> Liberto, D. (2022). Straight Line Basis. Investopedia Slater, S. (2017). How Do Appraisers Determine Depreciation? Linkedin Kimatu, E. (2021). Depreciation Methods: 4 Types with Formulas and Examples, Indeed Collectables Why do collectables grow in value? What models determine valuation and how to apply? Can one apply both depreciation appraisal and collector appraisal? If so, observe deviations. 10. Capital Gains and Capital Losses Chen, J. (2021). Capital Gains: Definition, Rules, Taxes, and Asset Types, Investopedia For Capital Assets and Financial Assets with real market data will determine CG or CL with tax rules of ambiance considered. Moskowitz, D. (2022). How Collectibles Are Taxed. Investopedia 11. Risk and the Cost of Capital Chapter sections 10.1 – 10.8 Applications: Portfolio management Case 5 12. CAPM Chapter sections 11.7 and 11.8, 12.1 – 12.6 Applications: CAPM stock valuation (versus comparables, DDM, DCF, AEVM), Portfolio management, Capital budgeting Case 6 13. Corporate Capital Structure Chapter section 14.1 – 14.5, 15.1 – 15. 5, 16.1 – 16.4 Applications: Industry Capital Structure, Optimal Capital structure, Refinancing, Share Repurchase Programmes Case 7 14. Introduction to Advance Uses of Financial Statements Building a Three Statement Model Building pro forma statements: assumptions and development Applications: implementation practice for both prior topics 15. Corporate Annual Report (CAR) & Quarterly Corporate Earnings (QCE) CAR - Sources for official data. How to efficiently read a CAR QCE - Tuovila, A. (2022). Guide to Company Earnings. Investopedia Applications: Implementation practice for CAR and QCE 16. PESTLE Analysis and SWOT Analysis Framework and logistics for implementation Applications: implementation practice Prerequisite: International Financial Statement Analysis II Financial Accounting Course Objectives --> (1) understand how a company’s operating and financing transactions create corporate wealth and risk. (2) develop an intuitive feel for when and how financial reports communicate the prospective and final outcomes of transactions. Reference Textbooks --> Hamlen, S. S. (2019). Advanced Accounting, Cambridge Business Publishers Reference Textbooks (for technology immersion) --> Hanlon, M., et al. (2019). Financial Accounting, Cambridge Business Publishers Stickney, Clyde P., and Roman L. Weil. (2003). Financial Accounting: An Introduction to Concepts, Methods, and Uses. Thomson South-Western Note: prerequisites are prerequisites. Required Resources --> 1. The U.S. SEC's HTTPS file system allows comprehensive access to the SEC's EDGAR filings by corporations, funds, and individuals; disseminated to the public through the EDGAR dissemination Service. Dissemination stream also populates the EDGAR public database on sec.gov, which can be researched through a variety of EDGAR public searches. One may be interested in possible APIs, introspection and queries. Other foreign ambiances likely will have all such abilities. 2. Official financial accounting standards of respective ambiance; IFRS and/or possible interest in comparative study to treat course topics. Required Tools --> Office 365 Microsoft Dynamics Microsoft learning: https://docs.microsoft.com/en-us/learn/browse/ Course Grade Constitution --> Assignments Labs Quizzes (based on prerequisites and current course) 3 Exams (will reflect quizzes and open notes) Groups Term Project: A + B GROUPS TERM PROJECT PART A --> Student groups will be given a (large) portfolio of assets, liabilities and transactions at one given date and time to develop the three major financial statements for a future date and time. Students will apply all their knowledge and skills from focus course topics and prerequisites. Then to implement the following upon the to be developed financial statements: Vertical Analysis and Horizontal Analysis Adjusting accounts/statements towards at least 6-9 ratios Profit, efficiency, liquidity and debt Computing the following measures: EBITDA, NIAT, ATOI, NOPAT NOPLAT, Operating Cash Flow, EVA GROUPS TERM PROJECT PART B --> Pro forma financials development and reporting. Groups will be assigned 2 companies/firms to develop pro forma financials based on acquired financial data and given outline of features and expectations. FOCUS COURSE TOPICS (TOWARDS IFRS STANDARDS) --> Profile/characterisation of organisation Law and regulation for corporate/business accounting, financial reporting, securities exchange and trade. The Accounting Process & Balance Sheet Financial Accounting and Firm Value Rapid topics Cash and Cash Equivalents Payables Receivables Bond valuation Fixed and floating (interest on both purchase price and coupon) Discrete compounding and continuous compounding Accrued interest, Effective Interest Rate, APR, APY Issuing and Investing in Debt Securities Equity valuation models Equity returns Issuing and Investing in Equity Securities Valuing liabilities Long-term and short-term liabilities. Maturity matching AND alternatives Securitizations & VIE Stock-Based Compensation Earnings per Share Derivatives Forwards Price or premiums Options Premiums, are composed of the sum of its intrinsic and time value; expiration date or exercised time Foreign currency translation, foreign currency transactions Currency Swaps: structure, gains and losses Hedonic Pricing for properties or rents Intangible Assets Calculating Intangible Value Methods Relief from Royalty Method (RRM) Multiperiod Excess Earnings Method (MPEEM) With and Without Method (WWM) Real Option Pricing Replacement Cost Method Less Obsolescence Collectively: Kenton, W. (2021). Calculated Intangible Value (CIV), Investopedia Accounting Changes & Error Corrections Earnings and Income Taxes Subject to most of the prior focus topics Off-Balance Sheet financing Reporting Requirements Firm Valuation Liquidations Partnerships Corporations Mergers and Acquisitions Post Acquisition Consolidation Constructing financial statements: balance sheet, income statement, cash flow statement Prerequisites: International Financial Statement Analysis II Corporate Auditing This course is designed to provide an introduction to auditing. The objectives include principles and practices used by internal auditors (and public accountants) in examining financial statements and supporting data. Special emphasis is given to assets and liabilities. This course is a study of techniques available for gathering, summarizing, analysing and interpreting the data presented in financial statements and procedures used in verifying the fairness of the information. Also emphasizes ethical and legal aspects and considerations. Course Literature --> Louwers, T. et al (2021). Auditing & Assurance Services. McGraw Hill Supporting Texts --> Messier Jr, W., Steven Glover, S. and Douglas Prawitt, D. (2019). Auditing & Assurance Services: A Systematic Approach. McGraw Hill Arens, A. A. et al (2019). Auditing and Assurance Services, Pearson Assessment --> -Assignments -Quizzes -Exams -Labs -Will apply the auditing process upon the institution’s financial data...likely being the only resource allowed to do such, because firms don’t want to be done-in by amateurs. Groups assigned different college programmes or public services -Financial Statements Integrity Groups Assignment Based on module 6. Each group assigned 3-5 firms to apply ALL the measures and models from the three articles; assigned programmes of the university or college as well. Course Outline --> MODULE 1: Coverage Audit Process: Start to Finish Reports on audited financial statements Reading Auditing and Assurance Services / RISK Management Fraud and Audit Risk Professional Standards Appendix: Legal Liability Appendix: Professional Ethics MODULE 2: Engagement Planning Management Fraud and Audit Risk Risk Assessment: Internal Control Evaluation Audit Plan Cash Internal Controls Questionnaires MODULE 3: Acquisition and Expenditure Cycle Production Cycle Revenue and Collection Finance and Investment International Controls Questionnaire MODULE 4: Sampling Attributes Variables Review: Audit Evidence; Audit of Cash MODULE 5: Completing the Audit Reports on Audited F/S Other Public Accounting Services Internal, Governmental, and Fraud Audits Auditing in a Computerized Environment MODULE 6: Regulations for off-balance-sheets activities, and requirement of making notes, and providing detailed disclosures in quantitative and qualitative statements SPVs and Partnerships Financial Statements Integrity Bloomenthal, A. (2021). Detecting Financial Statement Fraud. Investopedia How to Detect and Prevent Financial Statement Fraud, Association for Fraud Examiners. VI. General Techniques for Financial statement Analysis. Association of Certified Fraud Examiners Padgaonkar, D. (2021). How to Detect Fraud in Your Company’s Financial Statements. Forbes Case studies: (1) Logistics and implementation of analyses, models, laws and scores upon financial statements from the prior three literature. (2) Will analyse various past legal cases via financial data from SEC, firm repository, affidavits, tax filings, court documents and rulings. Will apply various analyses, financial ratios, laws, scores and models from the prior three literature. Prerequisites: Financial Accounting Corporate Valuation Course will meet for AT LEAST 2 hours per session for 2 days per week. This course covers business valuation, and equity valuation. While the course is designed first and foremost to be very practical, the tools and methods covered in this course are presented in the framework of generally accepted financial theory. Overall, in course one doesn’t expect students to remember every technical detail by hand concerning mechanics and computation, hence, formulas will be naturally given on quizzes, exams and cases and projects; understanding what you’re doing, and competently completing real world tasks with real external data is what’s essential. Additionally, there will be investigation into how well sensitivity analysis can apply to valuation methods. Tools and resources that will apply in this course --> General financial statements Balance Sheets Income Statements Cash Flow Statements SEC Data UPENN WRDS databases + CRSP/Compustat Merged Database (CCM) Crunchbase Course Grade Constitution --> Homework will be advance reinforcement of assignments (computational skills, financial statements analyses) and applications done in the corporate finance course. Financial Statements Analysis Quizzes Valuation Cases (8-10) based on all modules Small Business Valuation Group Project BreakUp Value (2) Valuation vs Performance Ratios vs Industry Perception (2) Course Literature --> TBA Classroom Policies --> I encourage the class to self-regulate and determine its own standards regarding classroom policies, and contemplate the possible consequences for violating them. Variables of interest: Attending class and punctuality (self-explanatory) Use of laptops. There are abundant cases where learning is enhanced by the use of laptops. Else, figure out what will lead to catastrophe. Turning in your assignments on due dates Conduct (behaviour, plagiarism, sabotage) COURSE TOPICS: --Will have review of the different financial statements and recognise the purposes they serve in valuation. Financial statements: balance sheets, income statements, cash flow, etc. will strongly resonate. Hence, students must exhibit ability to determine necessary data from fetched financial statements. --Following, a broad overview and discussion of valuation techniques. There are a number of different ways to try and determine the value of a company, and it's almost always good practice to use more than one valuation method. --Small Business Valuation Income Based Approach EBITDA Seller’s Discretionary Earnings: SDE Multiple -> SDE Comparative analysis of advantages and disadvantages of income based approaches EBITDA, Operating Cash Flow, NOPLAT, EVA Can any of the above latter 3 be a strong substitute for EBITDA or SDE? Asset Based Approach Book Value Adjusted Net Asset Method Excess Earnings Valuation Calculating Intangible Value Methods Relief from Royalty Method (RRM) Multiperiod Excess Earnings Method (MPEEM) With and Without Method (WWM) Replacement Cost Method Less Obsolescence Collectively: Kenton, W. (2021). Calculated Intangible Value (CIV), Investopedia Market-based approach—checking what comparable companies sold for Discounted Cash Flow Analysis (likely NOPLAT based also of interest) Implied Topics Our discount rate discussion involves determining the firm’s cost of capital – both debt and equity capital – and the effect of leverage (debt) on the firm’s cost of equity and the firm’s overall cost of capital. Will also treat the use of CAPM and multi-factor models as alternatives. Case of cost of equity as discount rate. Following our discount rate discussion, we cover valuation effects of a firm’s capital structure. Adjusted Present Value versus DCF Note: Small Business Valuation Group Project. Groups assigned two small business to develop analysis based on various prior topics. --Corporate Valuation What valuation methods applied to treat small business prior will be relevant to high value corporate firms? Additional Essentials: Earnings Multiplier Abnormal Earnings Valuation Model P/E FCF to Equity --Control premiums and liquidity discounts --IPOs & Prospectus Initial Public Offering Model Structured process firms follow to become a publicly traded company. Prospectus (tasks oriented) Murphy, C. B. (2022). What is a Prospectus? Example, Uses, and How to Read It. Investopedia IPO Valuation Model (novice tasks oriented) --Stock Valuation Methods (SVMs) Review: DDM, DCF, AEVM, Comparables Analysis How many of the above SVMs can be used to compare to IPOs issued? Pursue future valuation. --LBO and M&A contexts; earnings accretion and dilution in M&A transactions. --Valuing Financial Institutions --Shares Buy Back Claire Boyte-White (Investopedia) – When Does it Benefit a Company to Buy Back Outstanding Shares? What is the influence on EBITDA, NIAT, NOPAT, NOPLAT, Operating Cash Flow, EVA and P/E? --Breakup Value Chen, J. (2021). Breakup Value: What it Means, How it Works. Investopedia Relative Valuation Intrinsic Valuation - DCF model Market Capitalization Times Revenue Method Case studies for breakups with use of non-condensed financial data towards the valuation methods mentioned. Hargrave, M. (2020)Sum-of-the Parts valuation (SOTP) Meaning, Formula, Example. Investopedia DCF Valuation Asset-Based Valuation & Multiples Valuation using revenue Operating Profit or Profit Margins Case studies for breakups with use of non-condensed financial data towards the valuation methods mentioned. --Financial Ratios and Industry Perception. Measurable performance and industry perception as tangible attractions. Financial Ratios Means of adjusting financial statments Basic Financial Metrics Young, J. (2022). Metrics. Investopedia Recall: EBITDA, NOPLAT, Operating Cash Flow, EVA and P/E Trend Analysis PESTLE and SWOT Review of framework and logistics Robust and trustworthy templates to apply Prerequisites: Enterprise Data Analysis I & II, International Financial Statements I & II, Corporate Finance Co-requisite: Venture Capital Venture Capital This course focuses on the venture capital cycle and typical venture-backed start-up companies. Covers the typical venture fund structure and related VC objectives and investment strategies, intellectual property, and common organizational issues encountered in the formation of start-ups. It covers matters relating to initial capitalization and early-stage equity incentive and compensation arrangements, valuation methodologies, challenges of fundraising, due diligence, financing strategies, and harvesting. Students critically examine investment terms found in term sheets and the dynamics of negotiations between the owners and the venture capitalist. The course provides the intellectual framework used in the VC process, valuation in venture capital settings, creating term sheets, the process of due diligence and deal structuring. Other learning objectives include building an understanding of harvesting through IPO, divestitures or M&A and strategic sales. The final objective of this course covers the important contractual issues and documents in venture capital deals. Basic transactions documents (BUT not limited to): term sheets; letters of intent; confidentiality agreements; investment contracts/rights agreements; stock purchase agreements; Amended and Restated Certificates of Incorporation; merger agreements and other documents required for M&A transactions; asset purchase agreements; convertible Notes; crowdfunding filings with SEC. AS WELL, will also engage the significance of public notary and the generally accepted entities towards VC. Note: course satisfies the social/society appeasement. Course Assessment --> Class Participation Homework & Quizzes VC Valuation Methods Case Analyses via SEC, VC databases, etc., etc., etc. Mid-term Exam (in-class) Financial Model for VC Post Assessment VC Metrics on market VCs Final Exam Main Texts (expensive) --> Wong, L. H. (2005). Venture Capital Fund Management: A Comprehensive Approach to Investment Practices & the Entire Operations of a VC Firm, Aspatore Book/West DeWolf, D. I., Glaser, J. D. and Roth, E. M. (2021). Venture Capital: Forms & Analysis. Law Journal Press Additional Literature --> Ross, S. (2020). How is Venture Capital Regulated by Government? Investopedia Doherty, V. P. and Smith, M. E. (1981). Ponzi Schemes and Laundering – How Illicit Funds are Acquired & Concealed. FBI Law Enforcement Bulletin Volume: 50 Issue: 11, Pages: 5-11 Stancill, J. M. (1986). How Much Money Does Your New Venture Need? Harvard Business Review Fried, V. & Hisrich, R. (1994). Toward a Model of Venture Capital Investment Decision Making. Financial Management, 23(3), 28-37 Applied Sources/Tools --> Securities Exchange Commission VC databases UPENN WRDS+CRSP+CCM; Pitchbook; Capital IQ; Crunchbase Quizzes & Exams --> VC is one of the most social areas in finance hence on quizzes and exams expect to encounter main topics, the theatre (acts and scenes development), venture debt, valuation and convertible loans. Case Analysis --> Note: concerning case analyses with data, for some firms depending on point in course a respective case will concern particular topics and means of development for such. Example Case study to be segmented: Distributed Denial of Service (DDoS) PART A -- Industry Product and associated technologies, tools, etc. etc. Desired outcomes of services General characterisation of strategies Extent of capabilities/resources Market Landscape (empirical and measurables) Trend, sustainability, and long-term prospects (likely extending prior) Who can and will pay? The Companies For respective company identify unique specifics of product(s) that will provide qualitative value PART B -- Due Diligence preliminaries Firm’s legal standing (licenses, permits, etc. etc.) Raised capital & verification Beta trials and possible referrals. Intellectual property? Availability of first-generation product? Have roughly similar per-box pricing model and ROI argument PART C -- Due diligence second phase Organisational structure Business model/sales strategy Reviews from industry experts, surveys, etc. Patents of products possibility? Development of financial model for revenue projections & scenarios VC valuation methods compared to given value Compare with existing alternative services/solutions: Marketing Winners & Losers, mergers Service and industry effectiveness of alternative solutions Finance & Sustainability Testimonies with previous round VCs: DD and commitment PART D -- In the end, a decision between: More conservative technology with a slight lead in BD and R&D versus More ambitious technology with less visibility, but a better deal Contemplating both investments Financial Model for VC --> Assigned groups for proposed startups or assigned VCs. Understanding the business will greatly help in development (expected). Concern here mainly is strong development for competency, transparency and accuracy: 1. Economy/Industry/market/ 2. Business Model and Business Case 3. PESTEL, SWOT, 5C Analysis 4. Pro Forma financials development 5. Pre-money valuation: based on 1-4 + lecturing --> VC valuation methods 6. Review and possible amendments for (1)-(5) 7. Expected results based on (1)-(6) How to Read Venture Capital Fund Metrics. The 9 Key Venture Capital Metrics: Explained [2023]. (n.d.). https://dialllog.co/venture-capital-vc-metrics Note: exclude last three in article. ROA, ROE, ROIC NPV SROI 8. Build a financial model Some elements of (1) through (8) may be relevant Post Assessment VC Metrics on market VCs --> Groups assigned 2-3 VCs from data A to date B via financial statements Augmented with determination of liquidity, debt and efficiency ratios. Main Topics --> 1) Defining investment strategy 2) Fund raising process 3) Fund size and portfolio construction 4) Limited Partners Agreement/terms of investment 5) Sourcing investment opportunities 6) Conducting due diligence 7) Venture debt 8) Collateral by convertible loans and other investment types 9) Valuation methods 7) Structuring investment transactions 11) Value creation and evaluation 12) Exit strategies 13) Board culture, composition and orientation 14) Documentation. AUGMENTATIONS (MUST incorporate into course progression when appropriate) --> Investopedia – Private Equity vs. Venture Capital: What’s the Difference? Ben McClure (Investopedia) – How Investment Capitalist Make Choices? How are VC valuation methods different to general corporate valuation methods? Ben McClure (Investopedia) – Valuing Startup Ventures Hudson, M. (2015). The Art of Valuing a Startup. Forbes VC Valuation Methods Scorecard Valuation Methodology First Chicago Method Venture Capital Valuation Method Dave Berkus Method Risk Factor Summation Method The 14 Main Topics along with the Main Texts, Additional Literature, Applied Sources/Tools, and Augmentations will govern the following mandatory “VC Theatre Process” (of various acts and scenes) throughout the course --> TYPES OF VCs: – Angel investors Often with a tech industry background, in position to judge high-risk investments Usually a small investment (< $1M) in a very early-stage company (demo, 2-3 employees) MOTIVATION: – Interest in technology and industry – Dramatic return on investment via exit or liquidity event Initial Public Offering (IPO) of company Subsequent financing rounds – Financial VCs Most common type of VC An investment firm, capital raised from institutions and individuals Often organized as formal VC funds, with limits on size, lifetime and exits Sometimes organised as a holding company Fund compensation: carried interest Holding company compensation: IPO Fund sizes: ~$25M to 10’s of billions MOTIVATION: – Purely financial: maximize return on investment – IPOs, Mergers and Acquisitions (M&A) – Strategic VCs Typically, a (small) division of a large technology company Examples: Intel, Cisco, Siemens, AT&T Corporate funding for strategic investment Help companies whose success may spur revenue growth of VC corporation Not exclusively or primarily concerned with return on investment May provide investees with valuable connections and partnerships Typically take a “back seat” role in funding Funding Process: Single Process – Company and interested VCs find each other – Company makes its pitch to multiple VCs: – Business plan, executive summary, financial projections with assumptions, competitive analysis – Interested VCs engage in due diligence – Technology, market, competitive, business development – Legal and Accounting (structure, permits, licenses, and finance) – A lead investor is identified, rest are follow-on – The following are negotiated – Venture Debt (circumstances) – Company valuation – Size of round – Lead investor share of round – Terms of investment – Process repeats several times, builds on previous rounds DUE DILIGENCE (DD): – Tools – Tech or industry background (in-house rare among financials) – Review Legal and Accounting (updates) – Industry and analyst reports (e.g., Gartner) – Reference calls (e.g., beta’s) and clients – Patents: outline based on Park, H., Yoon, J. & Kim, K. (2012). Identifying Patent Infringement Using SAO Based Semantic Technological Similarities, Scientometrics, Springer, vol. 90(2), pages 515-52 – Visits to company – Gut instinct – Hurdles – Lack of company history – Lack of market history – Lack of market? – Company hyperbole – Inflated projections – Changing economy – Use of PESTEL/SWOT Analysis? 5C Analysis? – Legally Binding and Legally Admissible documentation/tools/resources throughout the VC process TERMS OF INVESTMENT: – Initially laid out in a term sheet (not binding!) – Typically comes after a fair amount of DD – Venture debt (circumstances) – Valuation + investment --> VC equity (share) – Collateral by convertible loans (circumstances) – Other important elements – Board seats and reserved matters – Drag-along and tag-along rights – Liquidation and dividend preferences – Non-competition – Full and weighted ratchet – Moral: these days, VCs extract a huge amount of control over their portfolio companies. BASICS OF VALUATION: – Pre-money valuation V: agreed value of company prior to this round’s investment (I) – Public Notary for VCs To highlight role at different stages with essential documentation throughout VC process – Post-money valuation V’ = V + I – VC equity in company: I/V’ = I/(V+I), not I/V – Example: $5M invested on $10M pre-money gives VC 1/3 of the shares, not being ½ – Partners in a venture vs. outright purchase – I and V are items of negotiation – Generally company wants large V, VC small V, but there are many subtleties… – This round’s V will have an impact on future rounds – Possible elements of valuation: – Multiple of revenue or earnings – Projected percentage of market share BOARDS SEATS & RESERVED MATTERS: –Corporate Boards – Not involved in day-to-day operations – Hold extreme control in major corporate events (sale, mergers, acquisitions, IPOs, bankruptcy) –Lead VC in each round takes seat(s) –Reserved matters (veto or approval) – Any sale, acquisition, merger, liquidation – Budget approval – Executive removal/appointment – Strategic or business plan changes –During difficult times, companies are often controlled by their VCs OTHER TYPICAL VCs RIGHTS: –Right of first refusal on sale of shares –Tag-along rights: follow founder sale on pro rata basis –Drag-along rights: force sale of company –Liquidation preference: multiple of investment –No-compete conditions on founders –Anti-dilution protection – Recompute VC shares based on subsequent “down round” – Weighted ratchet: use average (weighted) share price so far – Full ratchet: use down round share price – Example Founders 10 shares, VC 10 shares at $1 per share Founder issues 1 additional share at $0.10 per share Weighted ratchet: avg. price 10.10/11, VC now owns ~10.89 shares (21.89 total) Full ratchet: VC now owns 10/0.10 = 100 shares (out of 111) –Matters in bridge rounds and other dire circumstances –Right to participate in subsequent rounds (usually follow-on) –Later VC rights often supersede earlier WHY MULTIPLE ROUNDS & VCs: –Multiple rounds –Many points of valuation – Company: money gets cheaper if successful – VCs: allows specialization in stage/risk – Single round wasteful of capital –Multiple VCs –Company: Amortization of control! –VCs Share risk Share DD –Both: different VC strengths (financial vs. strategic) SO WHAT DO VCS LOOK FOR?: –Committed, experienced management –Defensible technology –Growth market (not consultancy) –Venture Capital Metrics –Significant revenues –Realistic sales and marketing plan (VARs and OEMs vs. direct sales force) Corequisite or Prerequisite: Corporate Valuation Mergers & Acquisitions This course covers the broad field of mergers, acquisitions, and divestitures. Students will apply learnt content to real mergers and acquisitions and have the opportunity to present to the class their findings and conclusions. Specific course objectives include: To provide the student a framework for analyzing transactions including understanding strategic rationale, valuation methodologies, deal structures, bidding strategies, and the need for a value proposition. Course Texts --> M&A: A Practical Guide to Doing the Deal, Jeff Hooke, John Wiley & Sons, Applied Mergers & Acquisitions, Robert F. Bruner, John Wiley & Sons Ideas in Layman terms: Adam Hayes (Investopedia) – Mergers and Acquisitions – M&A Elvis Picardo (Investopedia) – How M&A Can Affect a Company Legal Framework Literature --> Pantazi T. (2012) The Legal Framework for Mergers and Acquisitions in the European Union and the United States. In: Bitzenis A., Vlachos V.A., Papadimitriou P. (eds) Mergers and Acquisitions as the Pillar of Foreign Direct Investment. Palgrave Macmillan Tools --> Microsoft Office R + RStudio Required resources --> SEC EDGAR and Databases Financial Statements from SEC domain Balance sheets Income statements Cash flow statements UPENN WRDS databases + CRSP + CCM Capital IQ, Pitchbook, Crunchbase (or alternatives) Tear Sheet sources Yahoo Finance or Google Finance World Wide Web provides a wealth of resources useful for evaluating M&A’s. Procedural Matters --> Student assignments include: A. Being prepared to discuss questions and/or problems that will be posted to “Blackboard” throughout the semester. They do not have to be turned in and will be posted at least 1 week before discussion date. Solutions will not be posted. Discussion questions may also show up in exams. B. Completing assigned cases analyses Completing a midterm and final exam. NOTE: expect to apply all knowledge, skills and tools from prerequisites and this course. C. A team project which will be turned in, and graded, and in addition, will be presented to the class on the dates designated. These team projects are: Analysis of a large M&A transaction. Study of causes and effects of a recent large merger or acquisition. The requirements for each of these team projects are set forth in a later part of this syllabus. Teams of six (6) are to be formed during the first week of class. The group is to email me the members of their team before date dd/mm/yyyy. Any students needing help to get into a team should email me before then. Grading --> Class Participation Quizzes Group Case Assignments Midterm Exam Team Project Report Submissions Final Exam Final Draft of Team Project Report & Presentation Exams --> Notes: students will be permitted to use limited amount of notes for midterm exam and final exam. One component of the final exam will be using the web and data sources for case analyses; all other components of the final exam must be submitted in before proceeding with final exam case analyses. Team Project: – Merger & Acquisition Study; Causes and Effects of a Recent Merger or Acquisition --> The objective of this study is to analyse a recent merger/acquisition announcement to identify the causes and effects of the particular merger/acquisition move. Your group is to choose a merger or acquisition announcement from a given list. Note: in the future team projects, some of these deals may be still pending, or busted-up by third parties, or canceled; expectations for some components to require projections development or “post-mortem” skills incorporated. As well, in some cases, the buyer is a publicly traded company, while in others the buyer is a private firm or a private equity fund. Your group will prepare a paper on the merger or acquisition selected and present your findings to the class. The instructor will inform you of your assigned acquisition or merger by designated date. ESSENTIALS FOR TEAM PROJECT: Project Report Submissions --> Required to submit 3-4 project progression material throughout the term. Includes the following: For each party before the M&A or LBO Financial statements analysis Horizontal analysis and vertical analysis Financial ratios (liquidity, profit, efficiency, debt) and trends 3-statements development, NOPAT, NOPLAT. DCF versus alternative valuations (besides comparables) PESTEL/SWOT development, 5C Analysis Proforma financials Revenue forecasting and Expenditure forecasting Merger structure Intangible value (IV) identification. Is it relevant to a M&A or LBO? Dumont, M. (2021). How Accretion/Dilution Analysis Affects Mergers and Acquisitions, Investopedia M&A model or LBO model development involving synergies Synergies M&A/LBO post valuation M&A/LBO PESTEL/SWOT development EPS (types and quality) after M&A/LBO Proforma financials after M&A or LBO Revenue and expenditure forecasting for the synergies-M&A/LBO model Realised SROI with the M&A or LBO (if relevant) ADDITIONAL EXPECTED INPUTS: -Your term paper should also have the following A-L “theatre”: A. ECONOMIC SETTING OF BUYER’S INDUSTRY 1.Important characteristics of the industry 2.Challenges faced by the industry over the 5 years prior to the transaction. 3.Industry trends, if applicable, prior to the transaction. 4.Outlook for the industry over next 5-10 years as of time of transaction. B. BUSINESS ECONOMICS REASONS FOR THE TRANSACTION 1.Reasons stated in SEC filings, annual report, and the deal announcement. 2.Reasons stated in financial press. C. STRATEGY D. TERMS OF THE TRANSACTION E. INITIAL REACTION TO DEAL (stock market reaction, security analysts, financial press) F. VALUE CREATION G. DEAL HISTORY/BIDDERS/COUNTER-OFFERS/LEGAL BATTLE H. COMPARISON TO OTHER ACQUISITIONS OF BUYER I. IMPACT OF ACQUISITION ON CONSTITUENTS 1.Initial impact of deal on constituents’ financial statements (e.g., changes in debt/capital ratio; EPS accretion or dilution, and other things). 2.Initial changes after the transaction due to acquisition (e.g., layoffs, divestitures, changes in constituents’ management). J. IMPACT OF ACQUISITION ON INDUSTRY STRUCTURE 1.Was the buyer’s or merger’s announcement preceded by other large acquisitions in the same industry? 2.If your answer to 1 above is yes, what influence do you think the prior acquisitions had on the decision for the buyer to announce this deal? 3.Was the constituents’ announcement followed by other large (over $1 billion) mergers or acquisitions in the same industry? List these mergers or acquisitions and whether you believe they were motivated or a result of the M/A under study. 4.Do you believe the merger or acquisition under study will cause more mergers or acquisitions in the buyer’s or merger’s industry? Why? 5.What impact do you believe the merger or acquisition under study will have on market share? On competitive advantage? On growth? On profitability? K. POST-MERGER PERFORMANCE (FROM CLOSING TO NOW) 1.Measure the performance of the buyer or merger and the selected 2-3 key competitors by: (1) Total return to shareholders over past 5 years. (2) Return on equity over this time frame. (3) Compare (1) and (2) above to benchmarks for the industry Total return Return on equity 2.How did the economy and industry perform subsequent to the subject merger or acquisition? Reasons 3.How did the buyer or merger perform subsequent to the acquisition? Include impact on firm’s financial health, organization structure, market position and reputation. Reasons. 4.With the benefit of hindsight, did the Buyer make mistakes with its major strategies and investment trusts (both internal and external)? L. CONCLUSIONS 1.Which of the companies studied (Buyer and 2-3 key competitors) seemed to have followed the best strategy and execution? 2.Does one company appear to be consistently better than the others? 3.What is the source of its superiority? 4.If you were the CEO (of the buyer or merger), would you have done anything differently? Explain. 5.Do you think the Buyer will create value on this acquisition? Why or why not? CLASS PARTICIPATION --> Students will be asked to elaborate on processes, concerns, and yield solutions to the questions and problems assigned. COURSE TOPICS & ASSIGNMENTS --> 1.M&A activity and M&A as a component of corporate strategy 2.The M&A Process: How companies execute M&A? Find a target? 3.Merger Proxy Statement & Acquisition Search 4.PESTEL + SWOT, 5C Analysis (constituents before M&A or LBO) 5.Risks in M&A Integration risk Overpayment Culture Clash 6.Building 3-statement models concerning M&A/LBOs 7.Historical financial analysis of target. Projections for target. M&A valuation: role of NOPLAT. DCF approach versus alternative valuation methods (besides comparables). Case Assignment 1: Projections for “Target” firms NOPLAT, DCF (versus alternative methods not being comparables) Critique of firm “X” valuation 8.Valuation: Comparables Active pursuit of comparables with valuation 9.Valuing High Levered Deals 10.Valuing Liquidity & Control 11.M&A and LBO Financial Structures 12.Designing a deal to achieve buyer (i) EPS and (ii) balance sheet objectives. EPS calculations for combined firm Segal, T. (2022). The 5 Types of Earnings per Share. Investopedia Wayman, R. (2019). How to Evaluate the Quality of EPS. Investopedia Value (money losing firm) Specified case examples Case Assignment 2: Valuing liquidity Financial structure logistics for assigned M&As and LBOs 13.M&A Transaction Process: Seller viewpoint. How an M&A transaction proceeds, the players, the government regulations, the documents, etc. 14.Legal Structures, Tax Issues, Post-Merger Integration Case Assignment 3: Quality of EPS EPS types calculations 15.PESTEL + SWOT, 5C Analysis after M&A or LBO 16.Hostile Takeovers Takeover & Defences Case Assignment 4 Hostile takeovers Post M&A or Post LBO: PESTEL + SWOT, 5C Analysis Defences (unsuccessful takeovers) Prerequisite: Corporate Valuation

Investments & Portfolios in Corporate Finance This course is highly quantitative and relies heavily on data. The R language (with packages) will be highly emphasized due to its vast computational power and outstanding treatment of high-volume compacted data. R Packages may vary among students or groups. This not a matrix algebra course. In profession no one sits down and manually computes matrices because they have better things to do; they are in a business and profession. Not about what a mathematician thinks is “elegant”. Quantitative Finance is a business, not a luxury. Homework --> Expect use of R and Excel to accompany your write-ups providing enough details so that it's possible to understand how you arrived at solutions or resolutions. Commentary expected throughout R development. If you just state the (re)solution, you will lose most points. Exams --> Some tasks will be similar homework, while other tasks will demand exploratory and analysis skills, and “engineering”. R Projects --> Instructor will provide goals and logistics. However, students will make use of R skills and R packages of their choice to complete projects. First: based on module 1 Second: Modules 2 - 5 Third: based on modules 6 - 7 Fourth: Based on modules 1 - 8 Fifth: based on modules 9 - 11 (subject to modules 1 - 8) For each project, accompanying the R development, expected will be analytical writeups in a word processor with high emphasis of mathematical palette use. Excel to serve with financial statements. Writeups concern objectives, motivations, development process with explanations, and results with reasoning. R Packages of interest --> BondValuation, credule, CreditMetrics, cvar, fAssets, fImport, FinCal, FinCovRegularization, fPortfolio, GCPM, jrvFinance, pdfetch, pa, PerformanceAnalytics, PortfolioAnalytics, Quandl, quantmod, RQuantLib, SWIM, tvm Note: such packages serve to accompany analytical development for strong consistency and relevance; not a substitute. Course Evaluation --> Homework 10% 5 R projects 30% Midterm I 20% Midterm II 20% Final Exam 20% Literature Guides --> Ang, C. S. (2015). Analysing Financial Data and Implementing Financial Models Using R. Springer International Publishing. Pfaff, B. (2013). Financial Risk Modelling & Portfolio Optimization with R, Wiley Scherer, B. and Douglas Martin, R. (2005). Introduction to Modern Portfolio Optimization With NUOPT and S-PLUS. Springer NOTE: reading is fundamental. You can’t develop if you don’t read; lectures aren’t enough. Comfort in R is key. NOTE: modern data is essential for many/most things in this course, including projects. COURSE TOPICS --> 1. Assessment Tools Real assets versus financial assets Relation between gov’t bond yields and stocks Historical rates of returns for stocks, currencies and bonds (computational modelling) Economic indicators: Unemployment Inflation (leading) Yield Curve YieldCurve R package Enrico Schumann. Fitting the Nelson–Siegel–Svensson model with Differential Evolution. CRAN R Janpu Hou. (2017). The Yield Curve – Example of Correlation. RPubs PMI analysis Survey of Professional Forecasters & Biege book Industries PESTEL, SWOT and 5C analysis OECD System of Composite Leading Indicators Global PMI Observation of Gov’t Budget Analysis Influence on Sectors and Industries Fed funds rate anticipation based on assumed monetary policy rule via data Fiscal Policy & Fiscal Indicators TED spread (and counterparts for other developed countries) 2. Fixed Income (portfolio determinants) Bond markets and interest rates A. Simple face value with interest (discrete and continuous compounding) B. Interest on both face value and coupon (discrete and continuous compounding) Valuation for both (A) and (B) Accrued interest for both (A) and (B) Listed credit ratings and default probability (gov’t and corporate) S&P, Moody’s, Fitch, CariCris Health by financial ratios (corporate) Profitability ratios, liquidity ratios, efficiency ratios, coverage ratios Historical performance in PR, LR, ER, CR (if applicable) Financial Statements Integrity Beneish, Dechow, Altman Z Score, Modified Jones Default probability determination via equity (corporate) from Merton and KMV VaR and CVaR for bonds Review elements from module 1 and their influence on bonds (gov’t and corporate) Multi-factor models and PCA for interest assessment Lioudis, N. (2022). Top 4 Strategies for Managing a Bond Portfolio. Investopedia Treynor ratio and Sortino ratio for bonds Default Correlation Merton Approach (or KMV) Multi-Factor models Approach 3. Stocks (portfolio determinants) Valuation (DDM, DCF, AEDM, CAPM) Compare methods (relevance or practicality) Implementation Stock Metrics Ratios (P/E, PEG, P/B, D/E, Price-to-Sales) FCF, Payout, ROE, beta benchmarking, portfolio beta Health by financial ratios Profitability ratios, liquidity, efficiency ratios, coverage ratios Historical performance in PR, LR, ER, CR (if applicable) Financial Statements Integrity Beneish, Dechow, Altman Z, Zeta Analysis, Modified Jones Review elements from module 1 and their influence on stocks Markets and volatility Standard deviation VaR and CVaR for stocks Based on realised volatility and implied volatility, respectively Treynor ratio and Sortino ratio for stocks Review elements from module 1 and their influence on stocks 4. Currencies What drives currency markets? Variables of influence (chosen elements from module 1) May need more open economy assessment tools Measuring currency exposure Predicting currency crisis Berg, A. and Pattillo, C. (1999). Predicting currency crises: The Indicators Approach and an Alternative, Journal of International Money and Finance, Volume 18, Issue 4, Pages 561-586 Probit model Vlaar, P. J. G. Early Warning Systems for Currency Crises. Bank of International Settlements 5. Inflation Market research Is inflation more a concern for stocks or gov’t bonds or corporate bonds? Historical survey of high surges or high receding in inflation. Means to forecast. 6. Weak Asset Allocation (stocks and bonds) Note: assumption is that intelligence and skills from all prior modules and topics have been developed/established. Beta, portfolio beta, benchmarking beta Mean-Variance analysis 7. CAPM versus Multi-factor Models (stocks and bonds) Capital Asset Pricing Model Uses and structure Computational logistics and implementation (direct development versus packages) Residuals versus fitted values (RvF) Heteroscedasticity in bivariate models? RvF: case with CAPM How do multi-factor models differ from CAPM? Zivot. E. (2015). Financial Risk Models in R: Factor Models for Asset Returns and Interest Rate Models. Scottish Financial Risk Academy https://faculty.washington.edu/ezivot/research/factorModelTutorial_handout.pdf Enkhjin. (2019). Port0502. RPubs by Rstudio Regenstein, J. (2018). Many Factor Models. R Views by RStudio Direct development versus R packages Observing disparities: CAPM versus multi-factor models 8. Practical Asset Allocation Note: importantly we’re assuming modules 1 through 7 were competently applied prior Modern portfolio theory & post-modern portfolio theory Benchmarking your portfolio Building a portfolio with multi-factor models Measuring diversification within each asset class How much diversification is too much? Magic weights? Principal Component Analysis Applications PCA to calculate VaR? Portfolio Construction Using Principle Component Analysis (general model and hands-on construction) Lei, D. (2019). Black–Litterman Asset Allocation Model Based on Principal Component Analysis (PCA) Under Uncertainty. Cluster Comput 22, 4299–4306 Preference being S&P500, Russell 200, STOXX Europe 600, TXS Composite, or chosen set of stocks Will try for stocks and bonds, respectively, then mixture of both, then with currencies and commodities integrated with stocks and bonds Is PCA better than mean-variance analysis (MPT) and multi-factor models for selection and optimisation? Note: for the allocation methods it’s important to comprehend how past intelligence and skills from modules 1 through 7 are embedded (PCA, muliti-factor and mean-variance) Strategic Asset Allocation (SAA) Chen, J. (2020). Strategic Asset Allocation. Investopedia Policy objectives and policy constraints Weights development/consensus findings. How was consensus model developed? Empirical evidence to support weights for SAA Insured Asset Allocation (INSAA) Comparative development to SAA prior Will the use of index funds, sectors funds and ETFs within portfolio lead to more active management in insured asset allocation? Integrated Asset Allocation (INTAA) Comparative development to SAA and INSAA Transaction costs concerns: SAA versus INSAA versus INTAA 9. Allocation Dynamic Part A: students will be given numerous baskets of assets (stocks, bonds, currencies, commodities). They will determine the type of asset allocation in play. Which portfolio selection and optimisation method are relatable. To apply risk assessment in regard to economic standing. Part B: students will choose based on modules (1) - (5) various assets (stocks, bonds, currencies, commodities). They will be asked to apply SAA based on an imaginary supplied fixed capital; valuation of assets is crucial towards weights. Will apply all prior portfolio selection and optimsation methods. PART C: students will be given a highly volatile portfolio of assets stocks, bonds, currencies, commodities) to emphasize actual IAA practice. 10. Portfolio Rebalancing Pinkasovitch, A. (2021). Types of Rebalancing Strategies. Investopedia Smart beta rebalancing Methods will be intimately applied to portfolios of various assets; identification of risks to mitigate included with verification, and valuation of assets is crucial towards rebalancing. Note: will be subject to modules 7-9 11. Performance Preliminary measures Alpha, K-ratio, Standard Deviation, Ratios (Sortino, ROMAD, Treynor) Up-Market Capture Ratio, Down-Market Capture Ratio Performance Attribution Brinson model Regression approach Brinson as Regression 12. Behavioural Finance (optional) Market efficiency and anomalies Individual investors and behavioural biases Principal-agent dilemma and incentives Prerequisite: Enterprise Data Analysis II, Financial Statement Analysis I & II, Corporate Finance, Probability & Statistics B, Mathematical Statistics. Options & Futures for Business Management (R environment): This derivatives course is specifically tailored only to students of business degree pursuits. Course Literature: TBA Labs --> Note: computation/simulation development will follow manual analytical development for all labs. Note: some labs will have multiple sessions that may not be sequential. A. R Labs outcomes: --Data acquisition and making data frames; time series (analysis); summary statistics; analysis of market data; fitting distributions to data --Financial Indicators (investigation of functions and their parameters) --Financial Visualization (investigation of functions and their parameters) --Students will acquaint themselves with computational assignments for options and options strategies involving the “pmax” function in R involving both puts and calls, longs and shorts, and more complex options strategies towards plotting/simulation of geometries. All prior will treat both piecewise models and continuously compounded models. B. For each security or derivative encountered will learn to access and interpret market data, and the relevance of such data to our models and costs based on bid/ask requests. C. Picking Strike Prices D. Computational development of hedge ratio types in R E. Options strategies in R subject to shares AND bid/ask requests F. Primitive builds of binomial tree and Black Scholes Merton in R versus R packages and other monte carlo European options American options G. Becoming acquainted with particular packages in R for valuation/pricing of derivatives compared to theory. Concerns assets and derivatives (forwards, European Options, American Options). Packages of interest: derivmkts, fAssets, fExoticOptions, fImport, fOptions, jrvFinance, LSMRealOptions, Quandl, ragtop, RQuantLib H. Historical Volatility and Implied Volatility Models and data applied. Comparing both. Major Projects (MPs) --> Based on modules: 1, 2, 3, 8 Exams --> 4 exams with limited notes for use; concerns understanding what you’re doing. Grading Weights--> HW 15% Labs 25% MJs 20% 4 Exams 40% Course Outline --> 1.Asset types and Markets. What drives financial markets? Commodities Balasubramaniam, K. (2020). Who sets the Price of Commodities? – Investopedia Why are there different markers for oil? Which benchmark/marker concerns you, say delivery/procurement versus taking advantage of market dynamics without possessing the asset? Currencies Floating Rate vs. Fixed Rate: What’s the Difference? – Investopedia The Foreign Exchange Spot Market Banton, C. and Scott, G. (2019). Investopedia How are International Exchange Rates Set? Segal, T. (2021). Using Currency Relations to your Advantage. Investopedia Stocks Definition and structure Means of creation and recognition with commissions Market with exchanges, platforms & transaction process It’s imperative that students are exposed to the logistics and computational development for mentioned methods from the following given links, comparing with each other and recognised market value. Some methods may concern “present” valuation while others concern “future” valuation. Chen, J. (2020). Dividend Discount Model (DDM) – Investopedia Kenton, W. (2020). Abnornal Earnings Valuation Model – Investopedia Capital Asset Pricing Model (CAPM) for stock valuation Joseph Nguyen (Investopedia) – How to Choose the Best Stock- Valuation Method Stock metrics and means of determination For various stocks compare market value to the given prior valuation methods, and to stock metrics. Are such compare/contrasts adequate enough to determine overvalued or undervalued stock? Acquiring and re-adjusting financial statements towards: liquidity ratios, coverage ratios, profitability ratios and efficiency ratios; historical behaviour. 2. Future outlook on currencies and stocks (quantitative AND judgmental methods) Leading economic indicators: Money supply, PMIs, yield curve Leading and Lagging Inflation Survey of Professional Forecasters Biege Book Monetary Policy Rules, Tools Economic data to predict implementation of such Economic data to predict retraction of such Gov’t Budget Analysis Fiscal Indicators and Fiscal Policy Geopolitics PESTEL, SWOT analysis: serves as planning beyond the luxury of day trading How will incoming information/perturbators (future outlook module) prior influence your PESTEL and SWOT? Will be tangible with template usage for PESTEL and SWOT. Results generally “complement critique” stock valuation (present and future), metrics and financial ratios. 3. Systematic Measures & Behaviour Beta coefficient, variance and standard deviation. Which is more practical? Beta versus VaR and CVaR for systematic risk Ahmed, S., Bu, Z., & Tsvetanov, D. (2019). Best of the Best: A Comparison of Factor Models. Journal of Financial and Quantitative Analysis, 54(4), 1713-1758 What advantages do factor models have over CAPM Portfolio construction with factor models Market relationship between risk free bonds yields rates and stock indices Data Analysis for S&P/TSX Composite Index (with Canada gov’t bonds), S&P 500 (with treasuries), Russell 2000 (with U.K. gov’t bonds), STOXX Europe 600 (risk free European bonds). 4. Arbitrage Lioudis, N. K. (2019). What is Arbitrage? - Investopedia Will treat practical problems concerning arbitrage. Is arbitrage a driving force in markets? Folger, J. (2019). Arbitrage versus Speculation: What’s the Difference? - Investopedia 5. Forwards for currencies Foreign exchange forwards (introduction, purpose and vendors) FX Spot–Forward Arbitrage (what are you looking for?) FX Forward Price Quotes and Forward Points (how are they useful?) Timing (establish relevance) Payoff models for currency forwards (developed from the prior subjects) Call (long and short) Put (long and short) Range forward contracts with payoff models 5. Introduction to Forwards for Stocks Definition, vendors, practical uses or goals Piecewise linear models and generating plots of put and calls (also with long and short, respectively). Continuously compounded models of put and calls, and generating plots (also with longs and shorts). Put-Call Parity 6. Introduction to Options Differentiation from forwards European and American Options Call and put options; long and short; option terminology; margins; CBOE products (or whatever ambiance). Continuously compounded models of put and calls, and generating plots (also with longs and shorts). Picardo, E. (2020). Options Basics: How to Pick the Right Strike Price – Investopedia Kenton, W. (2018). What is Moneyness? Investopedia Simon, H. (2020). What is Option Moneyness? Investopedia How is Picardo’s article relevant to the prior two articles? Put-Call Parity with European Options and not with American Options Foreign exchange Options (subject to all priors) 7. Options Strategies Hedging with Options. Is hedging for making money? Mirzayev, E. (2019). Options Strategies: A Guide for Beginners. Investopedia Based on modules (1), (2) and Picardo, for asset types and specific stocks will ask students to create options strategies for a six months window; may also require students to re-evaluate or revise their strategies based on new information. Includes range forward contracts. Seth, S. (2021). Using Options Data to Predict Stock Market Direction, Investopedia 8. Profit Potential of Options and Performance Evaluation Farley, A. (2020). Measure Profit Potential with Options Risk Graphs. Investopedia For the above literature included with applied shares and how they influence derivatives portfolios. For performance evaluation, intention will concern both arbitrary sets of options chosen with applied shares, AND index options. Bookstaber, R., & Clarke, R. (1984). Option Portfolio Strategies: Measurement and Evaluation. The Journal of Business, 57(4), 469-492. Sets of options with applied shares, and index options Can one draw the same conclusions when comparing Farley to Bookstaber & Clarke? 9. The Binomial-Tree and Risk Neutral Pricing Replicating-portfolio; risk neutral/adjusted probabilities 10. Derivative Pricing in the Binomial-Tree Model Dynamic replication; delta-hedging; self-financing portfolios; calibrating the binomial model; pricing calls and puts. 11. The Black-Scholes-Merton Model Understanding, deriving and using. Case of BSM-model for non-dividend paying stocks Review binomial tree to BSM, then (geometric) Brownian motion as a generalisation of the binomial tree. BSM and its relation to lognormal. The Black-Scholes-Merton Model and its Greeks. What do they measure? How do they apply? Greeks constructing the Black-Scholes PDE. 12. Delta-Hedging and Option Returns Delta-hedging; convexity vs time decay; hedging error vs transaction costs; value-at-risk; leverage; Portfolio Insurance. 13. Limitations and Extensions of The Black-Scholes-Merton Model Options on dividend paying stocks, equity indices, currencies, commodities, forwards and futures; negative skewness; fat tails; smile; smirk. 14. Implied Volatility Models Notion. Models. Comparing historical volatility to implied volatility. Why? Prerequisites: Corporate Finance, Mathematical Statistics Investment Banking Course learning outcomes: (i) financial statement spreading and analysis; (ii) valuation (using comparables, precedent transactions, and discounted cash flow analysis) of public and private companies in both minority interest and controlling interest situations; (iii) construction and sensitivity of integrated cash flow models (financial statement projections); (iv) construction and analysis of leveraged buyout models; (v) construction and analysis of M&A (accretion/dilution) models. Classroom discussions will be a blend of lecture and case studies, with case studies involving a hands-on modeling approach by all students. Homework and projects will provide additional real-world context and practice for in-class discussions and case studies. A. PREREQUISITES ARE PREREQUISITES (needed) B. STUDENT LEARNING OUTCOMES: Identify different ways to value a company, and describe the key differences between them. Calculate the value of a company, forecast its success or failure, and determine its stock price or sale price. Gain a working knowledge of and ability to construct integrated cash flow models (projections), including revolver modeling. Describe the various ways an individual or a company raises money from investors. Identify the advantages and disadvantages of leveraged buy-outs. Gain a working knowledge of and ability to construct leveraged buyout models, including sources/uses of cash, proforma balance sheet, returns modeling, and PIK debt with warrants. Analyse how a company can go from $0 to $1 Billion in value without ever making a profit. Gain a working knowledge of and ability to construct accretion/dilution (M&A) models, both in shortcut and long form, and including synergies and CHOOSE functionality. C. TYPICAL TEXTBOOKS --> Text for advanced review of financial statement analysis Prerequisites texts and literature Investment Banking: Valuation, Leveraged Buyouts, and Mergers & Acquisitions, by Joshua Rosenbaum and Joshua Pearl D. COURSE TOOLS --> Financial statements (balance sheets, income statements, cash flow) Templates (only for consistency) Data via UPENN WRDS + CRSP+ CCM, etc., concerning observation of real data profiles, designated assignments, study cases and projects. Securities and Exchange commissions filings and structure Crunchbase, Pitchbook, Capital IQ SEC Data Microsoft Office Microsoft Dynamics Microsoft learning: https://docs.microsoft.com/en-us/learn/browse/ E. COURSE GRADE CONSTITUTION --> Class Participation Homework Assignments Quizzes Case Analyses Group Projects F. GROUP PROJECTS (all required) --> Ratio Analysis (profit, efficiency, liquidity, debt) Cash Flow Analysis Integrity Beneish, Dechow F, Modified Jones, Altman Z model Corporate Valuation methods and comparables Development of the 3-statement model and analysis Pro Forma Financials development Forecasting Annual Revenues Financial Statements Seasonal Revenues Dumont, M. (2021). How Accretion/Dilution Analysis Affects Mergers and Acquisitions, Investopedia PESTEL + SWOT (for each before M&A/LBO and after M&A/LBO) 5C Analysis development (for each before M&A/LBO and after M&A/LBO) LBO model development and M&A development Adjusted Present Value method vs Cash Flow to Equity G. MANDATORY MAIN TOPICS --> Investment Banking Activities Financial Statement Analysis Application of Valuation Mechanics and Techniques NOPAT, NOPLAT Financial Modelling & Comprehensive Valuation Analysis M&A LBOs Deal Mechanics Corporate Restructuring Corporate Defence Credit & Finance Legal, Ethical & Governance Issues in Investment Banking Settings H. ESSENTIAL DEVELOPMENT FOR MANDATORY TOPICS --> INTRODUCTION, INDUSTRY OVERVIEW, FINANCIAL STATEMENTS OVERVIEW AND ANALYSIS (Topic 1) a. Brief Industry Overview – Bulge Bracket vs. Boutique Investment Banks, PE Firms, Hedge Funds b. Review of Financial Statements – Balance Sheet, Income Statement, Statement of Cash Flows c. SEC Filings Overview or other ambiance Process Analysis of S1 documents d. Review of sample 10-K– Business Overview, MD&A section, Financial Statements, and Notes e. Overview of Non-Recurring Adjustments f. Examples of Non-Recurring Adjustments g. Deriving Historic Ratios and Trends h. Example of “Spreading” Financials i. Homework (Individual) - Spread the financial statements for Heinz (or whatever) VALUATION (Topic 2) a. Overview of the three Generally Accepted Valuation Methodologies Discounted Cash Flow Analysis (DCF) Trading Multiples Precedent Transactions b. Overview of Valuation Template c. Spreading Comps – Example d. Precedent Transactions Analysis - Example e. Discounted Cash Flow Analysis - Example f. Homework (Group, due in parts): 1. Comps Spreading Exercise 2. Trading Multiples Exercise 3. Precedent Transactions Exercise 4. DCF Exercise and alternatives INTEGRATED CASH FLOW MODEL- PROJECTIONS (Topic 3) a. Uses for a Financial Model b. Tips for Setting up a Financial Model c. Creating Five Year Projections for Income Statement, Balance Sheet and Cash Flow d. Debt and Interest Schedule e. Integration of Projected Income Statement, Balance Sheet and Cash Flow f. Revolver Modeling g. Running Sensitivities h. Homework (Individual) – Construct integrated cash flow model (projections) BREAKUPS (Topic 4) Chen J. (2021). Breakup Value: What It Means, How It Works. Investopedia Note: all valuation methods observed in prior will be developed and compared for various firms. Hargrave, M. (2020). Sum-of-the-Parts Valuation (SOTP) Meaning, Formula, Example. Investopedia Note: all valuation methods observed in prior will be developed and compared for various firms. What are the key factors to consider when negotiating break-up fees in an IB deal? LEVERAGED BUYOUT (LBO) MODELING (Topic 5) a. Private Equity Industry Overview – Fund Structure, Returns, Waterfall Models b. Uses for An LBO Model on Sell-side and Buy-side c. Review of Deal Structure and LBO Model Example Introduction to LBOs Creation of a Sources and Uses Worksheet Discussion of Typical Financing Sources for LBO Purchase Price Calculations and Considerations Capital Structure Options / Reviews Proforma Financials development Goodwill Calculation Integration of Income Statement, Balance Sheet, Cash Flow Debt and Interest Schedule Revolver and Mandatory / Option Debt Prepayment and Impact on Returns Returns Analysis – IRR on Debt, Hybrid Instruments and Equity Investments d. Returns Analyses e. Homework (Group) – Construct LBO Model MERGERS & ACQUISITIONS MODELING, M&A SALE PROCESS (Topic 6) a. Uses for a Merger Model b. PESTEL + SWOT (for each before M&A and after M&A) c. 5C Analysis development (for each before M&A and after M&A) d. How to construct a Merger Model e. Calculation of Equity Value and Purchase Price f. Explanation of Consideration Used in Purchase (Stock, Cash, Assumed Debt) g. Discussion of Multiples Paid h. Post-Merger Control Issues i. Synergies and Pretax Synergies Required to Breakeven j. Revenue and EBITDA Contribution; tasks (NIAT, ATOI, NOPAT, NOPLAT, Operating Cash Flow, EVA) k. Proforma Financial development l. EPS Dilution/Accretion for Acquirer m. Sensitivities n. M&A Sale Process – a brief overview (time permitting) o. Pitching - a brief overview (time permitting) p. Homework (Individual) – Construct Shortcut M&A Accretion/Dilution Model Prerequisites: Corporate Valuation, Mergers & Acquisitions, Senior Standing.

Asset Management In this course one’s skills or talent are generally developed by personal investment in developing models and strategies. Towards group projects assigned, professors/instructors to provide objectives, mechanisms and logistics for research or tasks. Professors/instructors to provide process guidance and review of progressing projects. Computational developments to be supported by reports with the official participants of the respective project. NOTE: review R packages from your prerequisites. People tend to heavily underestimate what they have. Caution: plan, so logistics and implementations are tangible, fluid and cost/time effective. Attendance 15% --> Note: poor or destructive behaviour can warrant an amplification of 69% forfeited from final course grade. Data & computational group project assignments 85% --> Data & computational project assignments follow conceptual and model setup by instructor. It’s likely inevitable that, financial statements, Quandl, UPENN WRDS with various datasets and the CRSP/Compustat Merged Database (CCM) will be used along with other data sources and tools. Some of the topics in course outline will be the assignments. Each numeric module warrants a heavy project. Course Outline --> 1. Foreign Exchange Features: ---Linking the Money Market to the Foreign Exchange Market ---Exchange Rate Overshooting & Volatility ---Relation between forward exchange rate & current spot exchange rate 2. Industry methods of forecasting currency exchange rates and instruments ---Levich, R. M. (1998). Chapter 6. Determination of Spot Exchange Rates. In: International Financial Markets – Prices & Policies. Irwin/McGraw-Hill ---Econometric models: Cheung, Y. et al. (2017). Exchange Rate Prediction Redux: New Models, New Data, New Currencies. ECB Working Paper 2018 Note: replicative econometric research needs to be done. Verify with applied data, then investigate for more modern data. ---Strength of economic growth Yoichi Tsuchiya, 2012. " Is the Purchasing Manager’s Index Useful for Assessing Economy’s strength? A Directional Analysis. Economics Bulletin, AcessEcon, vol. 32 (2), pages 1302 - 1311 (likely applicable towards other ambiances) Note: as well, black swans, political contagion and geopolitical perturbations are difficult to quantify. ---Does strength of economy findings (from PMI index) always correlate well with results stemming from models chosen out of Cheung et al (2017) ECB Working Paper Series? ---Fixed exchange rates and pegged exchange rates Investopedia – Floating Rate vs. Fixed Exchange Rate: What’s the Difference Richard Lee – Investopedia. Pegged Exchange Rates: The Pros & Cons Caroline Banton (Investopedia). How are International Exchange rates Sets ---Questioning the reverence for currency pegs project Apart from the trade being a common reason for currency pegs, develop empirical research towards determining whether respective policy served well or not. Particular interest towards temporary pegs, say, observation pre-peg, peg period and post peg. Apart from needing to hold large reserves of counterpart currency (observe evolution), incorporate economic statistics/data that will serve well in research, accompanied by A. Purchasing of gov't bonds versus selloffs B. Current Account Deficit/Surplus C. National Depth to GDP ratio -Hennerich, H. Debt-to-GDP Ratio: How High Is Too High? It Depends, Federal Reserve Bank of St. Louis -Caner, Mehmet; Grennes, Thomas; Koehler-Geib, Fritzi. (2010). "Finding the Tipping Point -- When Sovereign Debt Turns Bad". Policy Research working paper; no. WPS 5391. World Bank. Note: may have to extend with more modern data -How to model with intelligence gathered from (i) and (ii) D. Money Supply E. Observe whether nation that created peg is actually disciplined with holding of large reserves of counterpart currency. If not, how fast are reserves burnt and why so? Can a reserve holding threshold or quantity be determined towards the peg? F. Possible trade tensions with other countries Trade balance among countries in trade conflict Project for students --> Students (likely in groups) will be given different pegs to the US dollar and the Euro, to develop highly sensitive forecast models (2 - 3) for the case of a floating rate (which incorporates market and economic data for chosen periods) within the peg life period, to compare with fixed rate and determine the level of convergence or divergence to such fixed rate over time. Note: in the pre-peg phase real currency market data will be applied to train/test forecast model(s), but also models can be supplied evolving economic data throughout peg phase. ---Currency Exposure PART A: What commodities and other assets are highly correlated (+ and -) with currencies? Events of interest: phases in the business cycle, and shocks. Strategies. PART B: known means of determining currency exposure (develop) Hekman, C. R. (1983). Measuring Foreign Exchange Exposure: A Practical Theory and Its Application. Financial Analysts Journal, 39 Adler, M., & Dumas, B. (1984). Exposure to Currency Risk: Definition and Measurement. Financial Management, 13(2), 41-50. Lane, P., & Shambaugh, J. (2010). Financial Exchange Rates and International Currency Exposures. The American Economic Review, 100(1), 518-540. PART C: for the following journal article below will like to incorporate more modern data and treat other industries as well (for industries segmentation purposes) Khoo, A. Estimation of Foreign Currency Exposure: An Application to Mining Companies in Australia. Journal of International Money and Finance. Volume 13, Issue, June 1994, Pages 342 – 363 ---Value-at-Risk Estimation of foreign exchange risk The following guides serves well towards development of VaR : Papaioannou, M. (2006). Exchange Rate Risk Measurement and Management: Issues and Approaches for Firms. International Monetary Fund WP/06/255 Bredin, Don & Hyde, Stuart. (2002). Forex Risk: Measurement and Evaluation using Value-at-Risk. Research Technical Papers 6/RT/02, Central Bank Ireland Swami, O. S., Pandey, S. K. and Pancholy, P. (2016). Value-at-Risk Estimation of foreign Exchange Rate Risk in India. Asia-Pacific Journal of Management Research and Innovation. 12(1): 1 – 10 ---Range forwards (long and short) ---Currency Crisis Radcliffe, B. (2019). What is a Currency Crisis? Investopedia Identify models and techniques applied in the following literature. Can expect much data analysis, possible sensitivity analysis and econometric/time series tools incorporated. Past events investigation. Modern data as well. Investigations will be highly data driven in computational environment. Kaminsky, G., Lizondo, S. and Reinhart, C. M. (1997). Leading Indicators of Currency Crises. Policy Research Working Paper 1852, The World Bank Berg, A. and Pattillo, C. (1999). Predicting Currency Crises: The indicators approach and an alternative, Journal of International Money and Finance, Volume 18, Issue 4, Pages 561-586 Probit model Vlaar, P. J. G. Early Warning Systems for Currency Crises. Bank of International Settlements 3. Global Currencies ---Benchmark currencies (CHF, EUR, GBP, JPY and USD). Identifying trends in the following: Evidence of global liquidity BIS global liquidity indicators: methodology https://www.bis.org/statistics/gli/gli_methodology.pdf Government budget deficit Other Fiscal Indicators Gov’t Credit Balance of Trade Debt to GDP Inflation You may also rank currencies with PCA ---Currencies of high potential as candidates or substitutes (CAN, AUS, SGD) for benchmark currencies; use the trends in the above and observe how each prospect currency stacks up with the benchmark currencies. With the same timeline apply PPP with the benchmark currencies; goods chosen must be essentials that are monetized. You may also rank candidates among the premiers in PCA. ---For different regions will make use of empirical and computational tools/skills to decide which currency can be a benchmark currency for the respective region. ---Speculate on a respective prospect currency whether the sovereign authority prefers a low value with the benchmark currencies in the interest of trade, etc., and its value with (chosen) emerging markets or developing countries. How is inflation treated? Note: case of Japan’s currency is an interesting one being a benchmark currency. ---Currency baskets Uses of currency baskets: Ganti, A. (2021). Currency Basket. Investopedia The U.S. Dollar Index (USDX), Special Drawing Rights (SDR). ---Building a currency basket Development assist: Edison, H. J. and Vardal, E. (1985). Optimal Currency Basket in a World of Generalized Floating an Application to the Nordic Countries. International Finance Discussion Papers (IFDP). No.266 Edison, H. J. and Vårdal, E. (1990). Optimal Currency Baskets for Small, Developed Economies. The Scandinavian Journal of Economics, 92(4), pages 559–571 Han, H. (2000). Choice of Currency Basket Weights and Its Implications on Trade Balance, International Review of Economics and Finance 9, 323–350 Daniels, J. P., Toumanoff, P. G., and von der Ruhr, M. (2001). Optimal Currency Basket Pegs for Developing and Emerging Economies, Journal of Economic Integration 16(1); 128-145 Jyh-Dean Hwang (2015). On the Correct Model Specification for Estimating the Structure of a Currency Basket, Applied Economics Letters, 22:10, 783-787 Projects of interest: Build a currency basket model for USDX. Does it conform to the given US Dollar Index formula? Regardless, confirm the accuracy over various years by comparing alongside historical valuation data. Except for a given formula to compare with, what was done for for the USDX will also be done for the SDR. Note: historical data SDR valuation data for contrast can be found on IMF website. Modelling and Forecasting of USDX volatility with ARIMA, GARCH and ARIMA-GARCH models. AIC, AICC, BIC, HQIC for model selection; followed by forecasting and error. Build a currency basket of the EC, CC, Latina America, Africa and Asian regions A basket of currencies may be used by monetary authorities to set the value of their currency. Compare wih actual realised policy. For exposure to different countries use of a currency basket to smooth risk. Better than currency options or range forwards? 4. Holding Cash. Inflation, Government Bonds and Commodities A. Two sound foundational guides (replication and extension with new data) –> Nason, R. S. and Patel, P. C. (2016). Is Cash king? Market Performance and Cash During a Recession. Journal of Business Research 69, 4242–4248 You, J., Lin, L. and Huang, J. (2020). When is Cash King? International Evidence on the Value of Cash Across the Business Cycle. Rev Quant Finan Acc 54, 1101–1131 B. In addition, with recession periods it may be sensible to compare yields from risk free assets and commodities (specifically gold) and draw conclusions. C. Inflation --> (i). Consumer Price Index (CPI) Relevance to the investor Basket model, sources for data and forecasting skills (ii) Meyer, B. H. and Pasaogullari, M. (2010). Simple Ways to Forecast Inflation: What Works Best? Federal Reserve Bank of Cleveland Economic Commentary, Number 2010-17 (iii). Research Federal Reserve Bank of St. Louis. (2019). Is Gold a Good Hedge Against Inflation? The FRED Blog Note: students are expected to have skills to independently generate their own geometrical exhibitions. Augment with modern data. Distribution fitting will also be appreciated. Bloomenthal, A. (2020). The Better Inflation Hedge: Gold or Treasuries? Investopedia Alexander P. Attié and Shaun K. Roache. (2009). Inflation Hedging for Long-Term Investors. IMF Working Paper WP/09/90 Ambiances and modern data D. Commodities in Hedging portfolios Banton, C. (2020). Commodities: The Portfolio Hedge. Investopedia What models are practical towards weight in portfolio? 5. Gov’t bonds and the economy Choe, S. and Veiga, A. (2021). EXPLAINER: Why Rising Rates are Unsettling Wall Street. AP News Duguid, K. (2021). Explainer: What Rising Bond Yields Mean for Markets, Reuters A. The given literature to be analysed B. Development of data analysis for modelling dynamic Different economic periods for different years C. What does your developed (Svennson) yield curve show? Such different economic periods for the different years D. Choose at least five other ambiances (developed and developing) for (A) through (C) E. Is the effect of rising bond rates always reflected on individual stocks? 6. Economic Indicators that help predict market trends -Unemployment -Inflation (leading and lagging) -Economic data towards prediction of monetary rules implementation -Yield Curve YieldCurve R package Enrico Schumann. Fitting the Nelson–Siegel–Svensson model with Differential Evolution. CRAN R Janpu Hou. (2017). The Yield Curve – Example of Correlation. RPubs -Money Supply -PMIs Investopedia - Purchasing Manager’s Index (PMI) Picardo, E. (2019). The Importance of the Purchasing Manager’s Index - Investopedia -“Beige Book” -Observation of Gov’t Budget Analysis for expenditure and cuts Sectors and Industries relevance -Monetary policy rules with data for possible future central bank action -Fiscal Indicators -Fiscal Policy -Is an increase in household debt in relation to a country's (real) GDP in at least the short to medium term a strong predictor of a weakening economy? -OECD System of Composite Leading Indicators -Global PMI For development: Vermeulen, P. (2012). Quantifying the Qualitative Responses of the Output Purchasing Managers Index in the US and the Euro Area. European Central Bank. Working Paper Series No 1417. “ The survey based monthly US ISM production index and Eurozone manufacturing PMI output index provide early information on industrial output growth before the release of the official industrial production index” (Vermeulen 2012). Will try to compare the consistency between such indices and the computational methodology found in the following article with time periods of interest (and compare to) --> Joseph, A., Larrain, M. and Turner, C. Forecasting Purchasing Managers’ Index with Compressed Interest Rates and Past Values. Procedia Computer Science 6 (2011) 213–218 -TED Spread (counterpart for developed counties) 7. Advanced stock analysis ---Initial Public Offering (IPO) Model to implement ---Case of a new IPO (analysis of S1 documentation) ---Meaning of given shares ---Speed reading SEC filings ---Value of common stock Ahmed, S., Bu, Z., & Tsvetanov, D. (2019). Best of the Best: A Comparison of Factor Models. Journal of Financial and Quantitative Analysis, 54(4), 1713-1758 Chen, J. and Scott, G. (2020). Dividend Discount Model (DDM). Investopedia Chen, J. (2021). Multistage Dividend Discount Model, Investopedia Joseph Nguyen (Investopedia) – How to Choose the Best Stock Valuation Method Kenton, W. (2020). Abnormal Earnings Valuation Model (AEVM). Investopedia Capital Asset Pricing Model (CAPM) or Multi-Factor models It’s imperative that students are exposed to the relevance, logistics and computational development for mentioned methods from the prior three given literature, comparing with each other and recognised market value. NOTE: there are methods for prices “today” and those to predict “future” prices. For various stocks compare market value to present valuation, future valuation with stock metrics. Are assets overvalued or undervalued? ---Market relationship between risk free bonds yields rates and stock indices Data Analysis for S&P/TSX Composite Index (with Canada gov’t bonds), S&P 500 (with treasuries), Russell 2000 (with U.K. gov’t bonds), STOXX Europe 600 (with risk free assets in Europe). ---Defensive stocks Chen, J. (2020). Defensive Stock. Investopedia With market data how can we vindicate the adjective “defensive” or “non-cyclical”? Note: defensive stocks don’t necessarily imply optimal gains. Note: a student project will be to analyse how volatile defensive stocks are against poor PMI releases and downturn yield curve. Will choose multiple successive years and monthly (or whatever) reports. ---Develop the following for various firms in regions of interest: Mohammed Issah & Samuel Antwi | David McMillan (Reviewing Editor) (2017) Role of Macroeconomic Variables on firms’ Performance: Evidence from the UK, Cogent Economics & Finance, 5:1 ---Creating a rubric chart involving the following nine a. Economic Indicators Predict Market Trends (review module 6) b. PESTEL & SWOT Analysis c. Pinkasovitch, A. (2019). Analysing Stocks with Porter’s Five Forces, Investopedia d. Investopedia (2018). The 4 Basic Elements of Stock Value e. Chosen stock valuation methods from earlier f. Stock Metrics Ratios (P/E, PEG, P/B, D/E, Price-to-Sales) EBITDA, NIAT, ATOI, NOPAT, NOPLAT, Operating Cash Flow, EVA FCF, Payout, ROE, ROA, beta benchmarking, portfolio beta g. Ratios and trend (Liquidity, Coverage, Profitability, Efficiency): h. Beneish Model, Modified Jones Model, Dechow F Score, Altman Z Model i. Off-balance sheet concerns ---Market Sector Indices: One can find or develop market capitalization weighted index for a respect sector (will identify the modelling and logistics) to compare with high-volume indices. Consider an index for each sector. Sector indices will be compared among each other and with high-volume indices. Summarizing the performance of stocks grouped by specific market sectors; allows investors to benchmark the performance of a particular stock market sector or industry. Comparing the performances of particular stock to its associated market sector (in conjunction with prior rubric analysis towards particular stock considered). 8. Asset investment risk measures (equity, debt and mixture of such two). Primary goal is to develop quantitative/computational models applicable to assets in markets and portfolios; meaningful “risk valuation”. As well, students must understand what they’re trying to measure. In general, cause of personal choices in equity and securities depends on firm (or individual). The mentioned risk measures generally have no rationale from economics, rather they are overall statistical towards performance. Methodologies for choices in equity are treated in other modules of the course. ---Securities exchange and trade commissions filings/registrations (investment types and operations) ---Special Purpose Vehicle/Entity (SPV/SPE): purpose and tactics ---Beta (measure of systematic risk) of a security or portfolio in comparison to the market as a whole. ---VaR, Expected Shortfall monte carlo (computational) and Stressed Expected Shortfall (computational). ---There are very case sensitive portfolio constitutions to consider. An elementary case could be a portfolio consisting solely of N different stocks (assuming diversification in different industries); a more general case, a portfolio consisting of unique stocks securities and stocks with different maturities. Skills in manipulation of arrays by computational tools are necessary. ---Jensen Index ---K-ratio ---Sortino Ratio ---Treynor Ratio ---Return Over Maximum Drawn Down (RoMaD) 9. Expense ratio and index fund development ---Actively Managed Funds Note: catering for different types of asset allocation Modules (6), (7) and (8) to be undercurrent. Comparative development: mean-variance, multi-factor models, PCA Market efficiency, Risks, Empirical performance and Transaction costs ---Index fund development A. Economy assessment & assessment of industries. Modules (6), (7) and (8) to be undercurrent B. Sampling from the index in accordance with its overall makeup and construction for different sectors; use some discretion as to how many you want to include in each sector class. Comparative development: mean-variance, multi-factor models, PCA Seldom case of increasing or decreasing the number of stocks (or shares of stock) you hold in each sector. C. Weighted average market capitalization D. Establish your benchmark(s) E. Individual trade costs & investment capital. Create yours or not? Linear Programming may just be only one means of “basketing”, but that MUST be subjugated to all prior. A project will be developing your own index funds. In groups students will develop at least three index funds, each from a different sovereign environment. Must also demonstrate how to track and evaluate. 10. Liquidity in Investment Funds The following papers can serve as guides towards logistics and means towards developing a tangible computational toolkit for liquidity; measuring it and stress testing. Professor will orchestrate analysis and conceptual groundwork of computational structure. Students are to develop computational code toolkit and apply real market instruments. May also be applicable to ETFs. ---Measuring Liquidity Profile of Mutual Funds Hussain, A. (2022). Mutual Fund Liquidity Ratio. Investopedia Aramonte, S., Scotti, C. and Zer, I. (2019). Measuring the Liquidity Profile of Mutual Funds. Finance and Economics Discussion Series Divisions of Research & Statistics and Monetary Affairs Federal Reserve Board, Washington, D.C. US Federal Reserve Students may be given questions based on established data concerning constituents of respective fund where they must compute liquidity. Students may be asked to develop a mutual fund constituted by a broad range of securities, stocks, cash, derivatives, etc., that suffices a liquidity measure threshold, having other systematic risks in mind. ---Measuring Mutual Fund Risk Banton, C. (2020). 5 Ways to Measure Mutual Fund Risk. Investopedia PURSUE ---Performance measures for Mutual Funds Jensen, Standard Deviation, Sharpe, Sortino, Treynor Compare a fund’s performance against its benchmark index Up-Market Capture Ratio, Down-Market Capture Ratio Performance relative to risk taken Performance Attribution 11. Liquidity stress testing for Investment Funds Note: will be project based and not only based on bonds --> Arora, R. et al. Bond Funds and Fixed-Income Market Liquidity: A Stress-Testing Approach. Technical Report No. 115, Bank of Canada 2019 Bouveret, A. (2017). Liquidity Stress Tests for Investment Funds: A Practical Guide. IMF Working Paper No. 17/226 12. Fund Analysis and Building Project: The R environment will be available and recommended to be put to much use for the following projects. ---Student groups will be given "funds” with stocks, bonds (gov’t and corp) and currencies where each group is given a different make up, but same number of stocks, bonds and currencies. Student groups will investigate particular stocks, bonds and currencies. NOTE: constituents of “funds” will be assessed by tool/skills acquired from prerequisites, and (critically) prior modules. You will also compose your process in writing with spread involving mathematical palette to accompany. Determination of which constituents and recommendation of researched assets for possible replacement to constitute an aggressive portfolio, defensive portfolio, income portfolio, speculative portfolio, hybrid portfolio, respectively. ---A fund manager with 200 stocks (or bonds, notes, bills) in portfolio. To analyse these securities quantitatively a manager will require a co-relational matrix of the size 200 by 200, which makes the problem very complex. However, PCA can extract 10 Principal Components which best represent the variance in the securities best, reducing the complexity of problem while still explaining the movement of all 200 stocks (or bonds, notes, bills). Kaiser rule? ---Making use of the R Packages ESG A. Logistical scheme for economic scenario generator concerning stocks, bonds (gov’t and corp), currencies, commodities and derivatives. B. Apply the package to the considered assets and derivatives ---More Portfolio Rebalancing Will be given various (high volatility) assets types in a portfolio (stocks, bonds, notes, bills, currencies) at given past date leading to a future date, to apply methods 13. Market (in)efficiency & elementary derivatives Generally concerns stocks, currencies and commodities as assets of consideration. Derivatives are neither means of stock analysis as in past modules, however, such modules can influence one’s mindset for transactions with long term options derivatives. ---Concept of arbitrage and no-arbitrage ---Conditions for surplus/deficit or market correction: The following subjects are not well treated which lead to market participants in false positions or comforts. Treat the following notions in the most logical/constructive sequential manner --> Margin Debt Marginal Call Liquidation Level Federal Call Liquidation Margin Will have active market case studies to comprehend how they are situated and resolutions to accompany. Vasquez, J. and Pakiam, R. Gold Prices Plunge by Most Intraday since June 2013, Bloomberg Bloomberg, Gold Joins the Virus Sell-Off With Biggest Slide Since 2013 ---Making sense of Hedge Funds in the Commodities Market For a hedge fund with ventures in commodities what are the “common strategies” applied concerning speculation or hedging, or even towards taxes reduction? An example: Wallace. J. (2020). Hedge funds that Cashed in When Oil Prices Cratered. The Wall Street Journal. <https://www.wsj.com/articles/hedge-funds-that-cashed-in-when-oil-prices-cratered-11585145260 >. Consider as well the bullish counterpart (or also tax reduction opportunities). Then, consider the following article: Scanlan, D. (2020). How One Hedge Fund Made Money Amid Singapore Hub Meltdown. Bloomberg. Does the finance or economics add up? What particular economic circumstance or scenario would make stock piles high in demand towards a profit? What are the unique principles in this latter strategy compared to “common strategies”? ---O’hara, N. (2020). How to use Index futures. Investopedia ---Applications of minimum variance hedge ---European Options ---Relating shares to options strategies ---European currency options (structure & basic strategies) ---Range forwards contracts with options (long and short) ---Pricing/Valuation of European stock options and currency options 14. Elementary volatility measures for options (primarily for stock as the asset): ---Historical volatility ---Indices of future volatility that provide a measure of market risk and investors' sentiments. ---An essential role of implied volatility: bull & bear markets. However, for options on stock, currencies and commodities each unique asset has unique volatility to consider. Particular past modules for stock analysis and currencies analysis must be well understood for strategy and planning with assets; company A does not necessarily equate to company B with market. ---Comparison between Implied and Historical volatility for the determination of overvalued and undervalued options; such comparison conclusion is never a substitute for stock analysis. 15. Measuring the market’s risk A. Wanting to know the daily VaR and CVaR of the market at a 99.9% confidence level (S&P 500, Russell 200, TSX Composite, STOXX Europe 600). B. Measuring the market’s risk expectations for an extreme event, often called a “tail event” or a “black swan,” which is a drop of at least three standard deviations. For integrity and professionalism, one must understand some level of modelling (distributions, fat tails, etc.) in a setting with implied volatility. Means to calculate the cost of protecting against such a drop, providing important insight into investors’ expectations. It’s features: (i) Using instantaneous implied volatility to calculate standard deviation of returns (will be actually done). (ii) Responding to current market conditions rather than relying on historical data. (iii) Extending to a portfolio of stocks. Pursue w.r.t. implied volatility Note: if there’s analogy for commodities then so be it. Will also like prior developed measure to be compared to the following journal article concerning past extreme events. Do they complement each other well? Samer, A. A. (2010). Stock Return Dynamics Around U.S. Stock Market Crises & Inverted Smiles. Journal of New Business Ideas & Trends. Volume 8, Issue 2 16. Attitudes of market participants Your individual culture may seem to be that of a “bozo” when it comes to financial markets. One must definitively identify practical stimuli for market behaviour. A. Some articles for analysis: Imbert, F. and Huang, E. (2020). Stocks Rise to Start the Week as Amazon and Apple lead Tech Higher, Gold Hits Record. CNBC Why is gold rising when stocks are soaring? Krugman, P. Stocks are Soaring. So is Misery. The New York Times Is the market behaviour of S&P 500, Russell 2000, Dow Jones and Nasdaq parallel to other ambiances (STOXX, TSX, etc.)? What are the drivers (Pied Piper) of such stock behaviour? Reasoning. B. Articles and development in (A) will be applied as the setting for the following: The degree to which funds are flowing in and out of various fixed income mutual funds and ETFs can also help gauge sentiment, particularly towards means of caution. 17. Market Efficiency (ME) & Asset Price Bubbles (APB) PART A (ME) Godfrey, K. R. L. (2017). Towards a Model-Free Measure of Market Efficiency Pacific – Basin Finance Journal, volume 44, pages 97 – 112 Tran, Vu. & Leirvik, T. (2019). A Simple but Powerful Measure of Market Efficiency. Finance Research Letters, Elsevier, 29(C), pages 141 – 151 PART B (APB) Note: when dealing with stocks will not focus only on the S&P 500 but also other indices such as the Russell 2000. Other developed countries as well, and also STOXX Europe 600 Phillips, P. C. B. and Shi, S. (2020). Chapter 2. Real-Time monitoring of asset Markets: Bubbles and Crises. Pages 61 – 80. In: Vinod, H. D. and Rao, C. R. Handbook of Statistics volume 42. Financial, Macro and Micro Econometrics Using R. North Holland. Cowles foundation Discussion Paper No.2152 version: https://cowles.yale.edu/sites/default/files/files/pub/d21/d2152.pdf It’s important that one becomes actively acquainted with R package psymonitor with various data of different times. Analyse and replicate. Then investigation with new data. Then can proceed with other ambiances of interest. R vignettes: Phillips, P. C. B., Shi, S. and Caspi, I. (2018). Real-Time Monitoring of Bubbles: The S&P 500. CRAN R Phillips, P. C. B. (2018). Real-Time Monitoring of Crisis: The European Sovereign Sector. CRAN R How well does it stack up against methods out of the following? Gurkaynak, R. S. (2005). Econometric Tests of Asset Price Bubbles: Taking Stock. Federal Reserve Board Robert Jarrow (2016). Testing for Asset Price Bubbles: Three New Approaches, Quantitative Finance Letters, 4:1, 4-9 Prerequisites: Macroeconomics I; International Financial Statement Analysis I & II; Corporate Finance; Investment & Portfolios in Corporate Finance; Mathematical Statistics. International Commerce This is a course where “structuring levels of certainty” and finance are drivers of commerce. Prerequisites will be pivotal with keeping pace, being competent and constructive. Course will involve high amounts data, and quantitative/’computational development. Market entry group presentations are pursued after modules involving market entry, corruption in markets, and barriers to market entry are treated. Written reports must accompany presentations. The presentation aspect will also carry over to participation weight. Remembering everything for a test in this subject is ultimately superficial. Data and circumstances in environments are always changing. The greatest importance is to have independent skills in data gathering, and good navigation. What you know and do comes from what you’ve gathered and reasoned. Exams will be done in groups with open literature and open notes, with use of technology/data tools. Parts of exams will include profiling, research and analysis for ambiance(s) of interest. References and citations are required. Other components will concern various types of risks, pricing, valuation, measures, etc. Such exams will also serve as structure towards the required final project. Groups should review the evaluations of their exams and make the necessary amendments. Groups will be assigned foreign markets and develop the proposal/project with updated data (when needed) and so forth. Grade constitution: Participation Quizzes will also reflect common knowledge (academic maturity), accounting and corporate finance, and analysis development. Quizzes in total will reflect some modules. Market Entry Group Presentations Exams (3-4) Final Project Applicable Resources --> Securities Exchange Commission Federal Trade Commission (or sovereign counterpart) FDIC data (or sovereign counterpart) IGOs (UNSD, IMF data, OECD Observer, OECD data, OECD Main Indicators, World Bank Indicators, IABS, WTO, UNCTAD profiles, UNCTAD FDI and UN Comtrade Databases WIPO, UN’s FAO) NIST Cybersecurity Framework (or other) Compustat +WRDS, Crunchbase Trade Online: https://ised-isde.canada.ca/site/trade-data-online/en Barron’s Online, Reuters, Bloomberg, Yahoo Finance Kaggle Necessary Computation tool: R + RStudio, MS Office, Google Sheets, where instructor will assume without reservation that prerequisites are AT LEAST met. Socioeconomic “noise” to accompany course outline (in appropriate manner) --> 1. Explain why understanding cultural differences are crucial for global business. 2. Identify factors that should be considered when firms participate in foreign direct investment (FDI) and what are the benefits and costs to host and home countries. 3. Identify ways a firm can acquire and neutralize location advantages. 4. Identify strategic responses firms can take to deal with foreign exchange movements or foreign inflation. 5.Describe different international strategies for entering foreign markets. 6.Describe the relationship between multinational strategy and structure. FINAL GROUP PROJECT (for a currently functioning firm wherever). COURSE OUTLINE --> --Globalisation & Business Today --Global Culture. Differences in culture. Ethics and Social responsibility --The Economic, Legal and Political Environment. Political economy. Security. --Foreign Direct Investment 1. Horizontal, vertical, and conglomerate are the types of FDIs A. Advantages (with types seeking) B. Risks C. Which is the most defensive against economic downturn (regional and global)? D. Forms of FDI incentives 2. Company’s growth strategy and governing laws A. Characteristic regulations that are influential on productivity and profit. B. Comparing countries. What industries in FDI dominate? Concerns analysis of evolution (35-40 years) with consideration of business cycles between host and investor countries. Developing Countries (25-30) Developed Countries (all) Equity types and levels, retail, services, logistics, manufacturing 3. Intelligence Resources: Harrison, A and A Rodriguez-Clare (2010), “Trade, Foreign Investment, and Industrial Policy for Developing Countries”, Handbook of Development Economics, Vol. 5: 4039-4214. Antalóczy, K., Sass, M. and Szanyi, M. (2011). Policies for Attracting Foreign Direct Investment and Enhancing its Spillovers to Indigenous Firms: The Case of Hungary. In: Multinational Corporations and Local Firms in Emerging Economies. Amsterdam University Press Moran, T H (2014), “Foreign Investment and Supply Chains in Emerging Markets: Recurring Problems and Demonstrated Solutions”, Washington, DC: Peterson Institute for International Economics. Working Paper 14 - 1. 4. Will also be interactive with OECD FDI data (there’s 15-16 indicators) Understanding the indicators. Identify the data sources/channels and logistics towards computational model or statistic (possibly can verify data). PCA development. --Environmental Scanning 1. Capital Account in international macroeconomics (analysis of data) Importing or exporting capital? Identifying historical trend Attractiveness to investors. Identifying historical trend Financial account versus capital account 2. Current Account Analysis and Benchmarks 3. Debt to GDP Hennerich, H. Debt-to-GDP Ratio: How High Is Too High? It Depends, Federal Reserve Bank of St. Louis Methodologies for prediction of balance of payment crisis (to be implemented) 4. Indicators OECD Observer, OECD data, OECD Main Indicators World Bank Indicators Trade Online: https://ised-isde.canada.ca/site/trade-data-online/en UNCTAD profiles, UNCTAD FDI and UN Comtrade Databases 5. Corruption monitoring in market Identification and analysis of corruption indicators A. For the measures of corruption measure to comparatively investigate the model, components, means of data acquisition (structuring and regularity), logistics Index of Public Integrity WEF Global Competitive index World Bank Governance Indicators 6. Regional Economics Will also be “borrowing” some evaluation and computational tools from regional economics to directly implement for quantitative results with regional, provincial and/or municipal levels for compare-contrast Input-Output, LQ, Economic Base, Shift-Share Analysis Multiplier Effects, Export Employment, Leakage Effects What industries are driving growth/stability in the market based on priors? Is observation of the trend in such measures annually a good indicator of industries’ direction? Efficiency in Industries/Sectors (current period, successive periods analysis for trend as well). Stochastic Frontier Analysis. Data Envelopment Analysis. Fiscal Behaviour (national, provincial, municipal) Fiscal Analysis Fiscal indicators 7. Socio-Cultural Scanning (national, provincial, municipal) Demography Gov’t census and labour statistics UN Agencies Indices of Social Development: https://isd.iss.nl/data-access/ How do you acquire data for cultural factors? Material Culture, Cultural Preferences, Languages, Education, Religion, Ethics & Values, Social Organisation 8. Market measures Barnett, W. (1988). Four Steps to Forecast Total Market Demand. Harvard Business Review Pursue active implementation of such four steps for assigned ambiances; pursue alternative methods to contrast with. Methods to compute the following (will be done for assigned ambiances) : Serviceable Available Market (SAM) Serviceable Obtainable Market (SOM) 9. Tax Transfer Policy (national, provincial, municipal) 10. PESTEL and SWOT Analysis Source guide (to develop): SWOT and PESTEL: Understanding your External and Internal Context for Better Planning and Decision-Making. UNICEF https://sites.unicef.org/knowledge-exchange/index_83128.html Note: will be comprehensively and thoroughly applied with data and the necessarily templates What or who is the benchmark in the market? What differentiates “them” from the rest? Ranking method? --Foreign Market Competition Measurement & Barriers to Foreign Market Entry Types of barriers and how to identify empirically: Primary Antitrust Ancillary Will choose various markets from different regions of the globe to measure market competition and monopoly power. The following literature (all of them) will be applied to current data: OECD (2021), Methodologies to Measure Market Competition, OECD Competition Committee Issues Paper OECD (2022), Data Screening Tools in Competition Investigations, OECD Competition Policy Roundtable Background Note --Regulation and contracts in international commerce: UNCITRAL, WTO, ITC model contracts (types), International Chamber of Commerce (ICC) --Operations, Banking, Financial Regulations: A. Corporate governance issues in international management. Stakeholders. Responsibilities of directors, managers. Protectionism. B. Federal Deposit Insurance structure: FDIC policies - comparative analysis among chosen different sovereignty. The given source serves as a strong resource for research << https://www.fdic.gov/bank/ >> How do other sovereignty compare with such data development? Try finding the data (and pursue analysis of interest such as financial health, etc.). C. Legal currency exchange intermediaries: Means of proper identification Statutory requirements for operations disparities among chosen ambiances D. Financial Reporting: IFRS vs chosen ambiance standards E. Sanctions and Risk Indicators: FATF-GAFI To develop: Ferwerda, J., Kleemans, E.R. Estimating Money Laundering Risks: An Application to Business Sectors in the Netherlands. Eur J Crim Policy Res 25, 45–62 (2019). Databases (active run through) - OFAC, HM Treasury, EU, UN, WBG Not always identical with sanctions among each other. F. Regulation towards firms (to implement) OECD international Standard Cost Manual: https://www.oecd.org/regreform/regulatory-policy/34227698.pdf --Financial risks on assets and instruments 1. Interest rate risk (investor perspective) Means of identification Duration types to measure interest rate risk Bond Immunization methods Must have the ability to comprehend a situation and model/apply three out of the following: cash flow matching, duration matching, convexity matching, FRAs and swaps. 2. Credit Risk (investor and firm perspective) Means of identification (credit ratings) Historical trend in coverage ratios, liquidity ratios and solvency ratios Beneish, Dechow, Modified Jones, Altman Z Using equity to estimate default probabilities (Merton’s model or KMV model) For a higher level of perceived credit risk, investors and lenders usually demand a higher rate of interest for their capital. Is CAPM good enough, or use of multi-factor models, or other method? 3. Foreign Exchange Risk (firm perspective) Determining currency exposure (highly quantitative/computational) Value-at-Risk Estimation of foreign exchange risk Hedging with European currency options Range forwards contracts (different strategies) Predicting currency crisis 4. Inflation Risk (firm perspective) CPI, WPI, PPI Percent inflation rate formula (PIRF) Change in dollar value based on PIRF Forecasting must be developed: Meyer, B. H. and Pasaogullari, M. (2010). Simple Ways to Forecast Inflation: What Works Best? Federal Reserve Bank of Cleveland Economic Commentary, Number 2010-17 Resolution: build an inflation premium into the interest rate or required rate of return demanded for an investment based on expected inflation. Can CAPM or multi-factor models or other account for inflation apart from market risk and return? --Organisational structure formalities Efficient usage of firm’s manpower and resources towards optimal production. Organisation chart design of “functions” concerns firm towards X years from now. The boxes and their linkages (functions, professional skills & education, technology, communication and interactions/coexistence) with possibly of “sub-boxes”. Personnel optimisation via linear programming concerning scale of intended operations and efficiency. --The Distribution Channel One particular business may have options in distribution channels, depending on operations scale, segmentation, innovative technology, environmental sustainability, etc., etc. --Experience Curve Effects Concept, model validation with data (in different ambiances) and related causes for effect; compare to Porter’s model and (PESTEL to SWOT) --Tax Regulations and Corporate Dues (if relevant) How are financial statements submitted related to tax reporting documentation? Can charged taxation on companies be verified via their financial statements? Seth, S. (2022). Transfer Pricing. Investopedia --Cooking the Books The given are some basic additional guides to assist with financial analysis --> Wayman, R. (2019). 8 Ways Companies Cook the Books – Investopedia Adkins, T. (2019). Financial Statement Manipulation – Investopedia Kuepper, J. (2020). Spotting Creative Accounting on the Balance Sheet – Investopedia Bloomenthal, A. (2021). Detecting Financial Statement Fraud. Investopedia Will analyse various past cases via financial data from SEC/Comptroller, firm repository, tax filings, affidavits and court rulings. From above literature will try to identify/apply the various types of method or /models. Examples (but not limited to): Hin Leong: Cheong, S., Cang, A. and Koh, J. (2020). Hin Leong Failed to Declare 800 Million Losses. Bloomberg Olympus: Layne, N. and Reynolds, I. (2011). Olympus Admits Hid Losses for Decades, Reuters Soble, J. (2011). Olympus Used Takeover Fees to Hide Losses, Financial Times --Off-balance sheet concerns Regulations for off-balance-sheets activities, and requirement of making note, and providing detailed disclosures in quantitative and qualitative statements. How attractive is the market of consideration? SPVs and Partnerships --Insurance 1. Insurance for international business 2. Rate Making Methods (will try to apply) Internal Rate of Return Method (IRRM) Feldblum, S. (1992). CASACT Vaughn, T. R. Misapplication of Internal Rate of Return Models in Property/Liability Insurance Ratemaking. CASACT Generalised Linear Models Concerned with logistics and implementation. Then computational contrast to IRRM. 3. Claims Valuation and Calculation --Export Finance & Export Credit Insurance Comprehension Instruments and operations --Cybersecurity/Intel planning & strategy formalities Standards for Cybersecurity (consider a renowned framework) Corporate espionage What is valuable? What elements and operations contribute highly to revenue in your business? --Capital Budgeting Subject may not be highly transparent and tangible until finance structure and accounting for respective business is analysed. 1. Grasping capital requirements. Analysis of other firm(s) of desired scale viewed as your benchmark is one possibility, or based on branches elsewhere subject to market/inflation correction. A. Expected costs accounting (hopefully no overlaps) Hedonic pricing for lease properties or rents Organisational finance Development & production costs Distribution channels (complicated by segmentation?) Cybersecurity/Intel planning Insurance Export Finance & Export Credit Insurance Taxes Pricing and Dues pricing B. Credbility Assessment: Horizontal analysis, vertical analysis, ratio analyses (with trend for each), and measures (Beneish, Dechow F, Modified Jones, Altman Z-score). C. Proforma and forecasting 2. Framework, model and essential features of Capital Budgeting Then quantify based on (1), followed by Risk Analysis with Scenarios & Monte Carlo (Excel and R). 3. Investor accessibility Note: investors can be broad depending on maturity of company Equity investments Debt investments 4. Methods for choosing the discount rate WACC Adjusted Present Value CAPM and multi-factor models (for risk premium) Chen, J (2019). Target return. Investopedia Majaski, C. (2020). Cost of Capital vs. Discount Rate: What’s the Difference? Investopedia Gorton, D. (2020). A Quick guide to the Risk Adjusted Discount Rate, Investopedia. 5. Forecasting methods to predict future outlook Active development Multilinear regression, moving average and general time series upon financial statements Gov’t budget analysis and fiscal policy OECD System of Composite Leading Indicators PMI’s TED Spread (or ambiance counterpart) PESTEL + SWOT Pro Forma + Financial Statements Forecasting 6. Finding the Optimal Capital Structure Hayes, A. and Kindness, D. (2020). Optimal Capital Structure. Investopedia Aswath Damodaran. Finding the Right Financing Mix: The Capital Structure Decision. Stern school of Business: http://people.stern.nyu.edu/adamodar/pdfiles/cf2E/capstru.pdf Note: 1 through 5 will have influence on optimal mix. Activities to develop in R and/or Excel (but to be adjusted for course applications). To encompass all capital and expenditure in capital budgeting. Account for the additional subtleties from prior modules for a capital budget pursued: Clark, V., Reed, M. and Stephan, J. Using Monte Carlo Simulation for a Capital Budgeting Project. Management Accounting Quarterly 20 Fall 2010, Volume 12, Number 1 --Business Assessment (with possible comparables or not) Profitability EBITDA, NIAT, ATOI, NOPAT, NOPLAT, Operating Cash Flow, EVA Efficiency Efficiency Ratio, ICR, DCL Coverage Ratios Liquidity Ratios Integrity Beneish Model, Dechow F Score, Modified Jones, Altman Z Default Probability of Default (via equity by Merton’s model) Chow, J. T. S., 2015. “Stress Testing Corporate Balance Sheets in Emerging Market Economies”, IMF Working Paper, WP/15/216. Adjusted Present Value (APV) CAPM vs multi-factor models vs APV for expected return Sound payment record to the vendors, banks and suppliers Attributes of reputation: innovation; people management; use of corporate assets; social responsibility; quality of management; long-term investment value; quality of products/services; green initiatives PESTEL and SWOT --Production/Cost Efficiency Measures Note: some of the following measures will apply depending on type of business. Yet, for all will try to have active implementation. Historical performance is also important to observe. Treat by determined best order and relevance: Linking inventory to financial statements LOB Efficiency Measure Inventory Turnover Ratio Asset Turnover Ratio Cash Conversion Cycle Accounts Payable Turnover Ratio Accounts Receivable Turnover Ratio Wells, J. T. (2001). Journal of Accountancy Data Envelopment Analysis Stochastic Frontier Analysis --Economic Indicators (of environment) Macro Indicators Analysis Gov’t Budget Analysis, Fiscal Policy, Fiscal Indicators SNA Current Account evaluation and benchmark Ambiance PMI OECD System of Composite Leading Indicators Global PMI Monetary policy rules with data for possible future central bank action and consequences Chow, J. T. S., 2015. “Stress Testing Corporate Balance Sheets in Emerging Market Economies”, IMF Working Paper, WP/15/216. Reassessment based on Environmental Scanning module Prerequisites --> Writing Sequence; Enterprise Data Analysis II; International Financial Statement Analysis II; Corporate Finance; Mathematical Statistics

Strategic Business Analysis and Modelling Course gives a strategic Business analysis and modelling techniques used to assess and enhance organisational performance or development. Course Objectives -Comprehend the fundamentals of strategic analysis and modelling. -Applying 5C Analysis to assess internal and external business factors. -Explore different business models and their applications. -Examine value creation, delivery, and capture within organisations. Apply strategic modelling techniques to real-world business scenarios. The major subjects of this course are: --Business Model --Revenue Model -- 5C Analysis --Value Model --Feasibility Study Course Assessment: Assignments and Quizzes (will extend beyond the midterm) Financial Analysis (given on various occasions all term) Adjusting financial statements and developing (9) ratios Profit, liquidity, debt. Develop trend as well for each. NOPLAT, EVA. Develop trend for both as well for each. Beneish, Modified Jones, Dechow F Score, Altman Z Develop trend as well for each. Midterm (will reflect assignments and quizzes) Team Assignments (1 for each module) Group Project (encompasses most or all modules) Course Tools: Microsoft Office (or Google Counterparts) R + RStudio Scientific Calculator Financial Statements of firms Financial, Industry and Market data tools/resources Course Outline: Introduction to Strategic Business Analysis Overview of strategic management Importance of strategic analysis and modelling Key concepts and frameworks 5C Analysis Company Analysis: internal assessment of strengths and weaknesses. Sustainable competitive advantage. VRIO (Variable Rare Imitable Organised) model. Collaborators Analysis: company’s supply change. Agendas and incentives. Customer Analysis: The Total Available Market (TAM). The Serviceable Available Market (SAM). The Serviceable Obtainable Market (SOM). Note: such prior three involves much quantitative modelling, and computation. Competitor Analysis: Industry Classification Systems. Examining market share within an industry (CR 4 and alternatives). Issue with classifications systems – a firm may operate across multiple industries, or it may serve a niche market that differs from the traditional industry definition. Context Analysis: use of PESTEL. Business Models Definition and importance of business models Types of business models Value Proposition Comprehending the concept and its components Developing a compelling value proposition Value proposition canvas exercise Value Creation and Delivery Value chain analysis Processes and activities for value creation Distribution channels and logistics for value delivery. Value Capture Revenue models and pricing strategies Monetization methods Maximizing value capture Strategic Modelling Techniques Scenario Planning SWOT Analysis Decision Trees Monte Carlo Simulation Feasibility Study Project Description Market Analysis Prior modules will reemerge. Augmented by industry trends, customer needs, and potential target markets. Technical Feasibility Economic Feasibility Costs, revenue, cash flow projections, ROI, and other financial metrics Legal and Regulatory Feasibility Operational Feasibility Scheduling and Timeline Resource Requirements Risk Analysis Prerequisites: Enterprise Data Analysis I & II, International Financial Statements Analysis II, Corporate Finance, Mathematical Statistics. Commercial Bank Management Literature Material --> Van Greuning, Hennie; Brajovic Bratanovic, Sonja. (2020). Analyzing Banking Risk (4th Edition): A Framework for Assessing Corporate Governance and Risk Management. © Washington, DC: World Bank. Berlinger, E. (2015). Mastering R for Quantitative Finance. Packt Publishing. Supporting Resources --> Tripp, J., & Calvert, M. (2007). A Practical Approach to Teaching Commercial Bank Management: Experiential Learning and More. Journal of Financial Education, 33, 63-73 Hester, D. (1991). Instructional Simulation of a Commercial Banking System, The Journal of Economic Education, 22(2), 111-143 Mandatory Tools --> Scientific Calculator Excel R and RStudio RStudio + R packages --> fimport, Quandl, quantmod BondValuation, FinCal, jrvFinance fPortfolio, fAssets, fOptions, LSMRealOptions CreditMetrics, GCPM, pa, Performance Analytics, PortfolioAnalytics, cvar, LDPD Essential Resources --> Securities Exchange Commissions Statutory Data & EDGAR Banks’ financial statements Banks’ reports Sovereign ambiance analogy to the following https://www.fdic.gov/bank/ BIS Capital markets databases (include UPENN WRDS) Kaggle NOTICE FOR COURSE: Financial statements will be applied extensively, else, there’s really nothing. Computational activity for measurements and analysis can go beyond lecture text, making use of skills from prerequisites listed. To be highly practical and real world competent one must become well versed in actual “portfolio” make-ups. Course will make use of the listed “Tools” and “Essential "Resources” for analysis, assignments and projects. Presence will be in lectures, assignments, quizzes, exams, labs and projects. Grade Constitution --> Homework Labs 2-3 Exams (based on lectures + homework + labs + open notes + R + Excel + scientific calculator) Projects HOMEWORK --> --Metrics For numerous assigned banks at designated periods to manually develop the following via financial data: A. Profitability (Net Interest Margin) B. Capital Adequacy (Total Capital Ratio, Tier 1 Ratio) C. Asset Quality (Asset Quality Ratio, Loans Quality Ratio) D. Liquidity Ratios for banks E. Volatility of Funding and Concentration of Deposits F. Efficiency (Efficiency Ratio, Interest Coverage Ratio, Operating Leverage, Degree of Combined Leverage, Maturity Mismatch) G. CET1 Ratio H. Loan-to-Value Ratio. Loan Loss Reserve Ratio. PCL Ratio. I. Cash Flow Analysis --Concerning the text of Van Greuning & Bratanovic there will be assignments for banks with their data based on measures, displayed diagrams, charts, tables and simulations in the text. Note: such assignments to be based on assigned reading. Concerns chapters 3-10. LABS --> --Individual Debt Instruments Modified Duration Exponential Duration Livingston, M. and Zhou, L. (2005) Exponential Duration: A More Accurate Estimation of Interest Rate Risk, Journal of Financial Research, 28, 343–61 Discrete Duration Bajo, E., Barbi, M. and Hillier, D. (2013). Interest Rate Risk Estimation: A New Duration-Based Approach. Applied Economics, 45 (19) 2697 - 2704 Convexity Analysis based on prior durations (compare amongst) --Interest Rate Risk Measurement (holistic) Gap Analysis Economic Value of Equity Net Interest Income --Credit Risk (based on lectures) --Currencies Exercise problems review: Weithers, T. (2013). Foreign Exchange: A Practical Guide to the FX Markets. Wiley (chapters 4 & 5) Measuring Exposure (based on lectures) Value-at-Risk estimation of foreign exchange risk (based on lectures) --FX Instruments (based on lectures) --Valuation of European Currency Option (put and call) PROJECTS --> --Collective analysis of asset allocation strategies of banks for different periods A. For assigned sample set of banks, based on financial statements for assets of respective bank to determine allocation strategy. B. Compare prior to observed indicators with practical time periods (OECD Composite Leading Indicators, TED Spread, Global PMI, Gov’t Fiscal Indicators, Yield Curve, Mutual Funds Liquidity) --Berlinger, E. (2015). Mastering R for Quantitative Finance. Packt Publishing, pages 290 - 316 Chapters 2, 4, 11-13. Note: for assets with distributions applied, based on new real data to also applying alternatives alongside normal distribution, such as Lognormal, Variance Gamma, and Meixner. --Banker Credit Analysis (based on lecture module) --Pursuit based on establishment from lecturing: Ferwerda, J. and Kleemans, E. R. (2019). Estimating Money Laundering Risks: An Application to Business Sectors in the Netherlands. Eur J Crim Policy Res 25, 45–62 COURSE OUTLINE --> --Overview of the financial services sector 1.Introduction to banking and financial services management. 2.Legalities --Administration(s) for licensing, registry, supervision of banks Starting a bank Establishing a domestic branch Establishing a foreign branch --Quantitative legal requirements for a financial institution --Governing Bodies and Supervisory Bodies for banks --Key Aspects of a Bank Transactions System --Bank Transactions System (engineering overview) Framework (Technology Stack, Security Frameworks, Transactions Framework) -> Model (Data Model, Transaction Model, User Model) -> Design (User Interface, Backend Design, Scalability, Security Design, Security Design, Transaction Workflow) --Reserve Requirements (literature and data TBA) 1. Reserve requirements. Calculation of reserve balance requirements. Finding the required reserves, excess reserves, and the maximum amount by which demand deposits could expand, based on a required reserve ratio, with a system having $X in deposits and $Y in reserves. Reserve Maintenance Manuals, and questions. 2. Deposit Insurance: origins and structure. How is the maximum federal deposit insurance determined? Is it the same for all banks? Why or why not? How is FDI related to banks’ reserve requirements, assets and liabilities? --Influence of the fed funds rate on banks --Balance Sheet Structure (chapter 4 of Van Greuning ) Constituents. What is a healthy composition? --Income Statement structure (chapter 5 of Van Greuning ) Drawing conclusions for specified periods --Risk Identification (overview) Analysing financial institutions in terms of risk identification --Capital Adequacy (chapter 6 of Van Greuning) Must develop lecturing to highlight major points. Some sections can be exploited towards data analysis, simulation and computational activities. --Liquidity (literature and data TBA) Structure of funding Cash Flow Analysis --FDIC (or ambiance counterpart): obtaining data about banks, their competitors and industry statistics in order to perform comparisons/contrasts. --Basic Securities (literature and data TBA). 1. Review of Equity IPO & shares development Stock valuation (DDM, DCF, AEVM, CAPM, multi-factor models) Stock metrics Health by ratios and trend (profitability, coverage, liquidity, solvency) PESTEL and SWOT 2. Review of Fixed Instruments Discrete & continuous compounding (cash flow, NPV & FV) Zeros (discrete and continuous compounding) Bonds with coupon interest and the principal at maturity (BCPMs) Valuation IRR, effective interest rate, APR, APY Zeros and BCPMs Duration & Convexity (for interest rate risk) Zeros and BCPMs Health by ratios and trend (profitability, coverage, liquidity, solvency) Credit Rating data. Relation between perceived risk(s) and interest setting (multi-factor models implementation). PESTEL and SWOT also applicable Market relation between “treasuries” yields, treasury price & stocks 3. Advance practice of multi-factor models and PCA for portfolio selection & optimisation (stocks, bonds and currencies included) 4. Apply methods used to measure (systematic) risk for bonds and stocks Beta, portfolio beta and benchmarking. What are you measuring? VaR, CVaR, Stressed VaR. What are you measuring? 5. Performance Measures (active implementation) Standard deviation R-squared Alpha Sharpe ratio, Sortino ratio, Treynor ratio K-ratio Up-Market Capture Ratio, Down-Market Capture Ratio Performance Attribution 6. Rebalancing Portfolios (Assets of banks) --Index Options (will focus on equity) Structure. Basic strategies with models. Picking strike prices for strategies. What amount of capital or shares must be determined? Bid and ask issues in markets. Reminder: everything doesn’t require hedging unless significant risk is possible in the near future; you hedge wrong, you loose more. Banks apply options strategies for gains as well. --Credit Risk (literature and data TBA) A. Credit ratings data B. Probability of default data C. Ratios (coverage ratios, liquidity ratios, and solvency ratios); observation of trend for each chosen ratio. D. Altman Z (practical exercises) E. Using Equity Prices to Estimate Default Probabilities - Merton Note: will have practical exercises, & treatment for general bonds (besides zero bonds) as well Merton. R. C. (1974). On the Pricing of Corporate Debt: The Risk Structure of Interest Rates. Journal of Finance, 29: 449 – 70 Hull, J. C. and Basu, S. Using Equity Prices to Estimate Default Probabilities. In: Options, Futures and Other Derivatives. Pearson. 2016, pages 582 – 584 Will be directly immersed with determining a company’s assets and liabilities as inputs. Compare Merton’s method development to default probability listings. Note: extend Merton model to KMV model and compute; compare also to default probability listings. F. Expected Loss (class body computational pursuit) Factors for computation: Probability of Default (PD) Exposure at Default calculation (EAD) Loss Given Default calculation (LGD) Expected Loss being time dependent Cash flows from repayment over time Loans are typically backed up by pledged collateral whose value changes differently over time vs. the outstanding loan value Sometimes both the probability of default and the loss given default can rise. Flores, J. A. E., Basualdo, T. L. and Sordo, A. R. Q. (2010). Regulatory Use of System-Wide Estimations of PD, LGD and EAD. Financial Stability Institute 2010. Bank for International Settlements Further tool for LGD: Tong, E., Mues, C. and Thomas, L. (2013) A Zero-Adjusted Gamma Model for Mortgage Loan Loss Given Default. International Journal of Forecasting, 29, 548-562. G. What if: expected loss of credit asset if PD and LGD are correlated. --Currencies (literature and data TBA) Why do banks participate in the foreign exchange market? Regulations for banks as a currency exchange service. Weithers, T. (2013). Foreign Exchange: A Practical Guide to the FX Markets. Wiley (chapters 4 & 5) For the following journal article there should be means to implement such practically to really understand how it functions. Is it practical or highly compatible with modern day banking? Bell, P., & Hamidi-Noori, A. (1984). Foreign Currency Inventory Management in a Branch Bank. The Journal of the Operational Research Society, 35(6), pages 513-525. Practical methods of currency exchange rates forecasting Measuring currency exposure: Hekman, C. R. (1983). Measuring Foreign Exchange Exposure: A Practical Theory and Its Application. Financial Analysts Journal, 39(5), 59–65. Value-at-Risk Estimation of foreign exchange risk: Papaioannou, M. (2006). Exchange Rate Risk Measurement and Management: Issues and Approaches for Firms. International Monetary Fund WP/06/255 Bredin, Don & Hyde, Stuart. (2002). Forex Risk: Measurement and Evaluation using Value-at-Risk. Research Technical Papers 6/RT/02, Central Bank Ireland Swami, O. S., Pandey, S. K. and Pancholy, P. (2106). Value-at-Risk Estimation of Foreign Exchange Rate Risk in India. Asia-Pacific Journal of Management Research and Innovation. 12(1): 1 – 10 FX Instruments: Concerns ONLY recognition and resolution procedures with the stereotypical problems thrown Foreign Exchange Forwards Types of Currency Swaps Cross-Currency Swaps Currency Options Structure(s) Valuation of European Currency Option Range Forward Contracts (long and short) Note: everything doesn’t require hedging unless significant risk is possible in the near future. Banks apply options strategies for gains as well. Issues with bids and asks for considered strategy. Currency transaction reporting --Banks and Borrowed Funds Commercial banks borrowing from the federal reserve. Why? What risk is the federal reserve taking on? Interbank lending. How do banks analyse each other with interbank lending risk? Is “too big to fail” a driving rationale? --Asset Liability Management (literature and data TBA) The following sources are solid guides towards anything hands-on and practical: Banton, C. & Boyle, M. J. (2020). Asset/Liability Management. Investopedia Gup, B. (2011). Asset/Liability Management. In: Banking and Financial Institutions (pp. 75-93). John Wiley & Sons Greuning, Hennie & Bratanovic, Sofija-Sonja. (2020). Asset-Liability Management. In: Analysing Banking Risk (Fourth Edition): A Framework for Assessing Corporate Governance and Risk Management (pp.281-295). World Bank eLibrary --Interest Rate Risk Premium (IRRP) for Credit Assets (literature and data TBA) Will like intimate treatment with acquirable data for tangible determination for IRRP. 1. Determination of risk-premium Component A: background screening (enterprise legality and legal/penal track record, business model, revenue mode, PESTEL/SWOT) Component B: data elements for analysis (proof of income, financial statements, off-balance sheet activities notes, credit risk via logistic model vs credit bureaus data) Component C: macro elements (economic outlook, gov’t fiscal policy, gov’t budget analysis, gov’t fiscal indicators, fed funds rate anticipation based on economic data, TED spread). Component D: Multi-factor models or PCA for IRRP? Component E: consideration of loan competitors --Loan loss provision: Albert, G. (2021). Loan Loss Provision. Investopedia How is it developed? --Banker Credit Analysis Student groups will be given different ideal loan/lending policies, along with strong data for proper processing. Based on known procedures students will be asked to make decisions on loan approvals. Process, data and tools applied for decision making: 1.Information Collection (will be more extensive than expected) 2.Information Analysis 3.Business models and revenue models development 4.Financial Statements Integrity Horizontal Analysis, Vertical Analysis, Beneish Model, Modified Jones Model, Dechow F Score, Altman Z Model 5.Methods of proving or determining income: Specific item, net worth, expenditures, bank deposits, cash and percentage markup methods Can be done for multiple periods if relevant Free Cash Flow Can be done for multiple periods if relevant 6.Financial Ratios & Trends in the financial ratios (if relevant) Liquidity, coverage, profitability, efficiency 7.Credit Risk (data subject to change) Credit Data (credit firms and rating firms) Probability of default via equity (Merton model and KMV model) Credit Risk Modelling using Logistic Regression 8.Creditworthiness, and Default Risk Premium or IRRP (from earlier) 9.Review: Business model and Revenue Model. PESTEL + SWOT 10.Credit Security (collateral) 11.Loan-to-Value Ratio 12.Decision Making --Management of sources of funds including deposits, borrowed funds, fee income, and other means of capital (literature TBA) --Understand why a balance must be achieved among liquidity, risk assumption, and profitability --Anti-Money Laundering Bank Secrecy Act (BSA): https://www.occ.treas.gov/topics/supervision-and-examination/bsa/index-bsa.html Note: identify ambiance counterpart --Transaction activity monitoring (literature and data TBA) Currency Transaction Report (CFT) & Suspicious Activity Report (SAT): Use and formats Tools to detect suspicious activity Structure for compliance Sanctions framework National IGOs (UN and EU) Enforcement Networks & Agencies National IGOs (UN and EU) Analysis, logistics and implementation towards places of interest augmented with modern data: Ferwerda, J. and Kleemans, E.R. Estimating Money Laundering Risks: An Application to Business Sectors in the Netherlands. Eur J Crim Policy Res 25, 45–62 (2019). Prerequisites: Corporate Finance, Theory of Interest for Finance (check COMPUT FIN), Money & Banking, Mathematical Statistics, Investments & Portfolios in Corporate Finance, A course in financial derivatives.

Bank Risk Management Risk management is the rational development and execution of a plan or strategy to deal with potential losses. Structure and regulation are important phases in risk management; however, data intelligence/skills and computational skills are essential to apply any tangible and practical risk management. Data from different sources/ambiances will often be required. NOTE: course has a logistics and computation approach, rather than a landslide of finesse faux and the mainstream hoodwink expertise. Tools --> All mandatory tools and essential resources (software, data sources, resources) from prerequisite WILL APPLY. NOTE: course will make emphasis on high data usage to build practicality with directives, demonstrate constructiveness and competence. NOTE: for R packages people tend to heavily underestimate what’s in front of them: BondValuation, credule, cvar, CreditMetrics, ESG, fAssets, fImport, FinCal, fOptions, fPortfolio, GCPM, jrvFinance, LSMRealOptions, LDPD, NMOF, optiRum, pa, PerformanceAnalytics, PortfolioAnalytics, psymonitor, Quandl, quantmod, Standardized Approach for Counterparty Credit Risk - (SACCR), SWIM DiffusionRimp, DiffusionRgqd, DiffusionRjgqd, Langevin, sde, Sim.DiffProc, stochvol, yuima Other packages from derivatives courses Plan well, so logistics and implementations are tangible, fluid and cost/time effective. NOTE: financial statements, gov’t data, financial data of capital markets (debt securities, equity, currencies, commodities, derivatives) and repositories will be applied extensively, else, there’s really nothing. Course hours and duration --> Requires 6 hours per week for 18 weeks Course evaluation constituents --> Problem sets (based on prerequisites) 20% Problems, Tasks and Labs from both prerequisites Chapter 22 & 24 Hull text Course Labs 40% Projects Case Studies 40% VaR and Credit Risk references --> Hull, J. C. (2017). Options, Futures and Other Derivatives. Pearson. The chapters of interest in Hull’s text: ONLY chapter 22, 24.6 and 24.9. Concerns only computational field tasks for VaR, credit risk and the relatable practice “Kool-Aid” problems for such chapters/sections. Guiding Literature for Projects --> A. Economic Scenario Generator: Wilkie, A.D. (1986) A Stochastic Investment Model for Actuarial Use, Transactions of the Faculty of Actuaries, 39, 341–403. Wilkie, A.D. (1995) More on a Stochastic Asset Model for Actuarial Use. British Actuarial Journal, 1(5), 777–964 Huber, P. (1997) A Review of Wilkie’s Stochastic Asset Model. British Actuarial Journal, 3(1), 181–210. Bégin, J.-F. (2019) Economic Scenario Generator and Parameter uncertainty: A Bayesian approach. ASTIN Bulletin, 49(2), 335–372. Pedersen. H. et al (2016). Economic Scenario Generators: A Practical Guide. Society of Actuaries Conning (2020), “A User’s Guide to Economic Scenario Generation in Property/Casualty Insurance.” Casualty Actuarial Society, CAS Research Papers. Applying developed skills from R Analysis course and the ESG R package. B. Stress Testing Literature: Montesi, G. & Papiro, G. (2018). Bank Stress Testing: A Stochastic Simulation Framework to Assess Banks’ Financial Fragility. Risk, 6, 82, 54 pages Bellini, T. (2016). Stress Testing and Risk Integration in Banks: A Statistical Framework and Practical Software Guide (in Matlab and R). Elsevier Ltd. Academic Press (Note: any Matlab code can be replicated in R) C. Climate Stress Testing UNEP FI’s Comprehensive Good Practice Guide to Climate Stress Testing. A detailed user guide for financial institutions looking to understand climate stress testing and develop plans for effectively executing them. It has been created to assist the financial sector in its climate stress testing journey and should be adapted to meet the needs of a given firm. Jung, H., Engle, R. and Berner, R. (2021). Climate Stress Testing. Federal Reserve Bank of New York, Staff Reports No. 977 PROJECTS --> Projects case studies for students. Involves strong development in a word processor, R and Excel. Sessions will be vital, so know your priorities. PROJECT 1: Economic Assessment Report (with 3 session guidance) Elements for project development -- Unemployment Inflation (leading) Yield Curve YieldCurve R package Enrico Schumann. Fitting the Nelson–Siegel–Svensson model with Differential Evolution. CRAN R Janpu Hou. (2017). The Yield Curve – Example of Correlation. RPubs Purchasing Manager’s Index (PMI) For development: Vermeulen, P. (2012). Quantifying the Qualitative Responses of the Output Purchasing Managers Index in the US and the Euro Area. European Central Bank. Working Paper Series No 1417. “ The survey based monthly US ISM production index and Eurozone manufacturing PMI output index provide early information on industrial output growth before the release of the official industrial production index” (Vermeulen 2012). Will try to compare the consistency between such indices and the computational methodology found in the following article with time periods of interest (and compare to): Joseph, A., Larrain, M. and Turner, C. Forecasting Purchasing Managers’ Index with Compressed Interest Rates and Past Values. Procedia Computer Science 6 (2011) 213–218 Beige Book Observation of Gov’t Budget Analysis for expenditure and cuts Sectors and Industries relevance Fiscal Indicators & Fiscal Policy Monetary policy rules with economic data for possible future central bank action. Is an increase in household debt in relation to a country's (real) GDP in at least the short to medium term a strong predictor of a weakening economy? OECD System of Composite Leading Indicators Global PMI TED Spread (consider counterparts for other developed countries) PROJECT 2: Economic Scenario Generator (ESG) Overview Sessions (3 sessions) Project Components: A. Portfolio selection and optimisation development (having stocks, currencies, gov’t bonds, corporate bonds, loans) based on mean-variance, multifactor models, and Principal Component Analysis. B. US Federal Reserve - Monetary Policy Principles and Practice: https://www.federalreserve.gov/monetarypolicy/policy-rules-and-how-policymakers-use-them.htm Identifying economic conditions for their implementation. Anticipating Central Bank policy based on economic data. C. Choice of economic scenarios (systematic, monetary, fiscal, mixture) and policy being highly influential on assets and liabilities D. Structuring analysis for ESG based on guiding literature Intimate analysis of computational structure (IA) Logistics for ESG ESG R package logistics (pack) E. Comparative analysis upon portfolios: IA vs pack Note: some mentioned SDEs R packages may also be invaluable. F. Reacquaintance with portfolio rebalancing types versus hedging on (massive assets) PROJECT 3: Stress Testing (ST) Overview Sessions (3 sessions) Project Components: A. Assigned banks’ balance sheets; elements being toxic or junk is irrelevant. Ratio analysis (with trend), Beneish, Dechow, Modified Jones, Altman Z, and use of probability of default (Merton’s model) B. Structuring analysis for ST from chosen stress testing literature Analysis and logistics of chosen approaches C. Implementation and analysis for (B) PROJECT 4: Climate Stress Testing (CST) Overview Sessions (3 sessions) Project Components: A. May apply the same assets and liabilities from prior project B. Structuring analysis for CST from chosen stress testing literature Logistics of chosen approaches Implementation and analysis COURSE LABS --> Note: labs will take up the majority of time of the course. Labs target specific risks in the role of fund managers who also operate in financial institutions. Some labs may be bundled to maintain fluidity and tangibility. List of labs: --Review of balance sheets & other financial statements. It’s essential to capture the role of financial statements in bank risk management. Concerns are purpose and interpretation of data; skills likely will show up in other labs and some projects. --Financial Statements Integrity Basic Horizontal Analysis and Vertical Analysis Restructuring financial statements for ratio analysis (liquidity, profitability, debt) where around 9 to apply. Observation of trend with each ratio. Beneish Model, Dechow F Score, Modified Jones Model, Altman Z Model --Review of Systematic Risk Measurements Note: one needs to definitively comprehend the risk measures what they represent, and how not to misuse them. Value at Risk (historical, model-building) For chapter 22 of Hull students must have the ability to implement all methods or approaches in this chapter in R (whether manual builds or use of packages). Problem sets in the chapter are generally “lip service” requirements. For the following must have the ability to implement in R (whether manual builds or use of packages) Beta and portfolio beta CVaR (individual and portfolio) Stressed VaR (individual and portfolio) Systematic risk for stocks with implied volatility Measuring the market’s expectations for an extreme event, often called a “tail event” or a “black swan,” being a drop of at least three standard deviations. Modelling (distributions, fat-tailed, etc.) in a setting with implied volatility. Means to calculate cost of protecting against a drop: (i) Using instantaneous implied volatility to calculate standard deviation of returns (will be actually done). (ii) Responding to current market conditions instead on historical data. (iii) Extending to a portfolio of stocks. Pursue w.r.t. implied volatility Reminder: hedging with options serves to neutralize risk when risk is logically identified; banks apply options strategies for gains as well. --Bonds Standing Financial Statements Integrity (review from earlier module) concerning firms’ financial health. Public Ratings versus Default probabilities by equity (Merton’s model and KMV model): review and development from prerequisite course. Default Correlation Development: A. Merton Model Approach Erlenmaier, U. and Gersbach, H. (2014). Default Correlations in the Merton Model, Review of Finance, 18(5), Pages 1775–1809 B. First-Passage-Time Models Approach Zhou, C. An Analysis of Default Correlations & Multiple Defaults. Rev. Financ. Stud. 2001, 14, 555–576. Valužis, M. On the Probabilities of Correlated Defaults: A First Passage Time Approach. Nonlinear Anal. Model. Control 2008, 13, 117–133. Metzler, A. On the First Passage Problem for Correlated Brownian Motion, Stat. Probab. Lett. 2010, 80, 277–284 Li, W. Probability of Default & Default Correlations. J. Risk Financial Manag. 2016, 9, 7 C. Multi-Factor Models Approach PESTEL + SWOT (with robust templates) Beta Type Measures Aslanidis, N., Christiansen, C. and Cipollini, A. (2019), Predicting Bond Betas using Macro-Finance Variables, Finance Research Letters, Volume 29, Pages 193-19 Pilotte, E., & Sterbenz, F. (2006). Sharpe and Treynor Ratios on Treasury Bonds. The Journal of Business, 79(1), 149-180. --Liquidity Risk Measurement: Gabbi, Giampaolo. (2004). Measuring Liquidity Risk in a Banking Management Framework. Managerial Finance. 30. 44-58. Banks E. (2014). Measuring Liquidity Risk. In: Liquidity Risk. Global Financial Markets Series. Palgrave Macmillan, London Jobst, A. A. (2014). Measuring Systemic Risk-Adjusted Liquidity (SRL) - A Model Approach. Journal of Banking & Finance, 45, 270. Note: there’s the IMF Working Paper version for the above Pathi, R. (2017). Measuring Liquidity Risk in a Banking Management Framework. EAPJFRM Volume 8 Issue 2 Stress Testing: Liquidity Coverage Ratio Jan Willem van den End. (2008). Liquidity Stress – Tester: A Model for Stress Testing Banks’ Liquidity Risks. DNB Working Papers 175, Netherlands Central Bank, Research Department Arora, R. et al. (2019). Bond Funds and Fixed-Income Market Liquidity: A Stress-Testing Approach. Technical Report No. 115, Bank of Canada Cont, R., Kotlicki, A. & Valderrama, L. (2020). Liquidity at Risk: Joint-Stress Testing of Solvency and Liquidity. Journal of Banking & Finance 118, 105871 --Interest Rate Risk Quantifying Interest Rate Risk Gap Analysis Economic Value of Equity Net Interest Income Abdymomunov, A. and Gerlach, J. Stress Testing Interest Rate Risk Exposure, Journal of Banking & Finance 49 (2014) 287–301; interested in Svensson extension as well. Multifactor models applied to interest rate Principal Component Analysis applied to interest rate Managing Interest Rate Risk Interest Rate Risk Management using Duration Gap Methodology Principal Component-Based Fixed Income Immunization Hedging: interest rate swaps, forward rate agreements (FRAs). Reminder: hedging serves to neutralize risk when risk is logically identified; not make money. --Credit Risk Review crediting ratings Interest in 24.6 and 24.9 of Hull; consider only related problem sets. Note: for all computation or monte carlo tools in such two chapter sections students should have the ability to implement them in R. Coverage Ratios, Liquidity Ratios, Solvency Ratios Trend observation as well Altman Z Score review and implementation Advance review and implementation of determining probability of default by equity via Merton’s model and KMV model from prerequisite course. Note: compare to credit agencies ratings. Recital of Expected Loss from prerequisite course Modelling and stress testing for credit risk: Drehmann, M., Sorensen, S. and Stringa, M. The Integrated Impact of Credit and Interest Rate Risk on Banks: A Dynamic Framework and Stress Testing Application. Journal of Banking & Finance, 34 (2010) 713 – 729 Chan-Lau, J. (2003). Anticipating Credit Events using Credit Default Swaps, with An application to Sovereign Debt Crises. IMF Working Paper, WP/03/106 --Inflation Risk Forecasting must be developed: Meyer, B. H. and Pasaogullari, M. (2010), Simple Ways to Forecast Inflation: What Works Best? Federal Reserve Bank of Cleveland Economic Commentary, Number 2010-17 Interest premiums required to offset forecasted inflation for future investment assets and liabilities to incur. What models or tools can be implemented? Fed Policy Rule Monetary Policy Principles and Practice - Policy Rules and How Policymakers Use Them: https://www.federalreserve.gov/monetarypolicy/policy-rules-and-how-policymakers-use-them.htm What economic data is relevant and the criteria required? Means to analyse how such policy (or rules) drives markets --Currency Exposure & Risk Measuring Currency Exposure (review prerequisite and implement) Value-at-Risk estimation of currency exchange risk (review prerequisite and implement) NOTE: may need (or be asked) to adjust to an implied volatility setting similar to what was done with stocks earlier. Range forward contracts development (upturn and downturn) --Capital Adequacy Measures Total Capital Ratio, Tier 1 Ratio Capital adequacy ratio, also known as capital-to-risk weighted assets ratio (CRAR). --Standardized Approach for Counterparty Credit Risk (SACCR) Basel Committee on Banking Supervision. (2014). The Standardized Approach for Measuring Counterparty Credit Risk Exposures. Bank for International Settlements: https://www.bis.org/publ/bcbs279.pdf Use of SACCR R package Prerequisite: Commercial Bank Management, R Analysis

Corporate Risk Management Course will make use of computation and simulation tools. Specific Learning Outcomes: -Identify and explain various interpretations of risk -For each interpretation of risk, understand and be able to calculate various measures of risk -Calculate and interpret characteristics of probability distributions -Conduct and interpret Monte Carlo simulations -Understand the condition under which diversifiable risk does and does not affect firm value -Evaluate circumstances under which risk reduction will increase firm value -Interpreting types of Value-At-Risk (VaR), calculation in simple settings, & know the faults -Understand the factors that determine the price of insurance in a competitive market -Construct simulation models to price insurance contracts -Understand contractual provisions in commercial insurance contracts -Understand the types of derivative contracts and how they can be used to reduce risk -ISO IEC 31010:2019 Risk Management — Risk Assessment Techniques Assessment --> Lab Assignments Will incorporate R and Excel 9 Assignments Groups Projects Required tools --> R with RStudio and packages Excel and @RISK software ISO 31010 - Risk Management Techniques Course to make use of various data and financial sources. Course will also make use of balance sheets, income statements, cash flows statements, etc. Journal articles of interest to be introduced at designated times with topics. Course Computational Outline --> A. INTRODUCTION TO CORPORATE RISK MANGEMENT 1.What is risk? 2.The risk management process 3.Objectives of corporate risk management 4.Potential behaviour biases that can impact risk management decisions 5. Decision making with less-than-perfect information B. PROBABILITY DISTRIBUTIONS AND USE OF R FOR EDA 1.Characteristics of Probability Distributions 2.Covariance and Correlation Includes forms of correlation and appropriate usage Mukaka M. M. (2012). Statistics Corner: A Guide to Appropriate Use of Correlation Coefficient in Medical Research. Malawi Medical Journal: The Journal of Medical Association of Malawi, 24(3), 69–71. 3.Sums of Random Variables 4.Analysing Sums of Random Variables 5.The Normal Distribution (ND) Assumptions for ND 6. EDA & Goodness of Fit Summary Statistics Correlation heat maps. Applying the ggpairs() function Box Plot Chi-Square test, Kolmogorov–Smirnov test, Anderson-Darling, Shapiro-Wilk test GROUP PROJECT: first assigned groups projects will be based on (A) - (B) C. REACQUAINTANCE MODELLING, SIMULATION WITH R 1.Historical Simulation 2. Monte Carlo Simulation (towards uncertainty in formulas/models) Basic Modelling Concepts Inputs: constants versus random variables Assigning probability densities to random variables Simulations in RStudio and Excel 3.Expenditure Probabilistic Risk Estimate Eu, Z. (2020). Building a Probabilistic Risk Estimate Using Monte Carlo Simulations. Medium, Analytics Vidhya Such article above can use used to frame expenditure operations for other business types. Will have both Excel and R pursuits. 4.Value at Risk Historical simulation Variance-covariance Monte Carlo Note: applications to be hands-on computational for all three priors. For the methods that aren’t monte carlo, concerns and practical resolutions for when data isn’t normal. 5.Conditional Value at Risk (with computational applications) with assumption of non-normality. 6.Stressed Value at Risk (with computational applications) with assumption of non-normality. 7.Niclas, A., Jankensgård, H. and Oxelheim, L. (2005). Exposure-Based Cash-Flow-at-Risk: An Alternative to VaR for Industrial Companies. Journal of Applied Corporate Finance 17, no. 3 (2005): 76-86. Note: compare to VaR methods GROUP PROJECT: second assigned groups projects will be based on (C) D. WHEN DOES RISK INCREASE VALUE? Effect of expected losses on expected cash flows Effect of variability of cash flows on the cost of capital Effect of variability of cash flows on expected cash flows How Taxes can influence risk management decision GROUP PROJECT: third assigned groups projects will be based on (D). E. INVESTMENT DECISIONS 1.Gov’t registries and legal standing 2.Securities exchange, commerce, trade commission: operational standing 3.The three-statement model 4.Horizontal Analysis & Vertical Analysis for financial statements 5.Financial Ratios (data driven tasks via financial statements) Coverage Ratios, Liquidity Ratios, Solvency Ratios, Profitability Ratios, and Efficiency Ratios. Finding trend in ratios. 6.Tools and techniques to identify possible financial statements fraud: Beneish Model, Modified Jones Model, Dechow F Score, Altman Z Model 7.Off-Balance Sheet notes 8.Special Purpose Vehicle/Entity (SPV/SPE) Purpose, tactics and deception 9.Capital Budgeting framework and essential features 10.Discount Rate Cost of equity WACC Adjusted Present Value (APV) Risk Adjusted Value (CAPM and multi-factor models). 11.Clark, V., Reed, M. and Stephan, J. (2010). Using Monte Carlo Simulation for a Capital Budgeting Project. Management Accounting Quarterly, Volume 12, Number 1 12.Eu, Z. (2020). Building a Probabilistic Risk Estimate Using Monte Carlo Simulations. Medium Analytics Vidhya Topics will vary 13.Platon, V. and Constantinescu, A. Monte Carlo Method in Risk Analysis for Investment Projects. Procedia Economics and Finance 15 (2014) 393 – 400 Almeida, Heitor, and Thomas Phillippon. "Estimating the Risk-Adjusted Costs of Financial Distress." Journal of Applied Corporate Finance 20, no. 4 (2008): pages 105-109. 14.Penalized Present Value. How does such compare with (11) and (12) 15.Confidence Capital required to be at least 95% sure of having enough for a project (possibly with other ongoing projects). Amount in reserves needed to be at least 95% sure of covering the risks in business? GROUP PROJECT: fourth assigned groups projects will be based on (E). F. COST-BENEFIT ANALYSIS (highly quantitative) 1.Framework analysis and logistics for monetised aspects There are professional guides for planning and development 2.Project-based development (logistics and will be highly quantitative) Means to competently account for costs and benefits Critical values like discount rate Cost of equity, WACC, APV, CAPM, multi-factor models Tools such as RIMS -II, IMPLAN, Chmura, LM3 or REMI may factor in 3. Campbell, H., & Brown, R. (2003). Benefit-Cost Analysis: Financial and Economic Appraisal using Spreadsheets (pp. 194-220). Cambridge: Cambridge University Press 4.Inflationary Environment Velez-Pareja, Ignacio, (1999). Project Evaluation in an Inflationary Environment, Cuadernos de Administracion, Vol. 14, No. 23, pp. 107-130 Velez-Pareja, Ignacio and Tham, Joseph, (2002). Valuation in an Inflationary Environment 5.Sener Salci & Glenn P. Jenkins, 2016. “Incorporating Risk and Uncertainty in Cost-Benefit Analysis”, Development Discussion Papers 2016-09, JDI Executive Programmes. GROUP PROJECT: fifth assigned groups projects will be based on (F). G. REDUCING RISK WITH INSURANCE 1.Purpose of insurance 2.Insurance Rate Making (to be implemented) The following journal article to be analysed, then will investigate the feasibility and practicality. Namely, making the formulas, measures and parameters meaningful from data or computation. We want competent and fluid applicability Williams, C. A. (1954). An Analysis of Current Experience and Retrospective Rating Plans. The Journal of Finance Vol. 9, No. 4, pp. 377-411 (35 pages) Internal Rate of Return Method Feldblum, S. (1992). CASACT Vaughn, T. R. Misapplication of Internal Rate of Return Models in Property/Liability Insurance Ratemaking. CASACT Generalised Linear Models Tober, S. (2020). Basics of Insurance Pricing: With a Quick Intro to GLM Models. Towards Data Science Ohlsson, E. and Johansson, B. (2010). Non-Life Insurance Pricing with Generalised Linear Models. Springer 3.Contractual provisions (deductibles, limits, exclusions) 4.Claims Valuation/Calculation 5.Estimating Claims Settlement with Generalised Linear Models GROUP PROJECT: sixth assigned groups projects will be based on (G). H. CURRENCY RISK 1.For the following journal articles will like to incorporate more modern data and treat other industries as well: Hekman, C. R. (1983). Measuring Foreign Exchange Exposure: A Practical Theory and Its Application. Financial Analysts Journal, 39 Khoo, A. Estimation of Foreign Currency Exposure: An Application to Mining Companies in Australia. Journal of International Money and Finance. Vol 13, Issue, June 1994, Pages 342 – 363 2.For the following literature will focus on development of VaR for multiple currencies in portfolio: Papaioannou, M. (2006). Exchange Rate Risk Measurement and Management: Issues & Approaches for Firms. IMF Working Paper WP/06/255 3.Currency Swaps (definitions and scenarios) Cross-currency coupon swap Cross-currency basis swap 4.Derivatives case examples (strategies, models & pricing) Minimum variance hedge ratio (data oriented and computational) Forwards (purpose, strategies and applied structuring) Constructing payoff models for strategies How does capital at stake apply to prior? Options (purpose, strategies and applied structuring) Constructing payoff models for strategies How does capital at stake apply to prior? Range forward contracts. As well, how does capital at stake apply? GROUP PROJECT: seventh assigned groups projects will be based on (H). I. WEATHER RISK INSTRUMENTS Note: will emphasize realistic and practical applications, modelling and operations. Literature for realistic and tangible engagement. Weather Index Insurance. For such articles there will be labs to develop and compare with data for chosen environments: Taib, C. M. I. C. T. and Benth, F. E. (2012). Pricing of Temperature Index Insurance. Review of Development Finance. Volume 2, Issue 1, pages 22 – 31 Shirsath, P. et al. (2019). Designing Weather Index Insurance of Crops for the Increased Satisfaction of Farmers, Industry and the Government. Climate Risk Management, Volume 25, 100189 Andrea Martínez Salgueiro, (2019). Weather Index-Based Insurance as a Meteorological Risk Management Alternative in Viticulture. Wine Economics and Policy, Volume 8, Issue 2, Pages 114-126 Boyd, M. et al. (2020). The Design of Weather Index Insurance Using Principal Component Regression and Partial Least Squares Regression: The Case of Forage Crops, North American Actuarial Journal, 24:3, 355-369 GROUP PROJECT: eighth assigned groups projects will be based on (I). J. ISO IEC 31010:2019 RISK MANAGEMENT— Risk Assessment Techniques GROUP PROJECT: assigned RAT topics. Prerequisites: Enterprise Data Analysis I & II, International Financial Statements Analysis I & II, Corporate Finance, Probability & Statistics B, Mathematical Statistics OPERATIONS MANAGEMENT/APPLIED OPERATIONAL RESEARCH Operation Management endeavors reside under the Business institution. OM/OR curriculum: --Mandatory Courses Calculus for Business & Economics I-III; Optimisation (check Actuarial post); Probability & Statistics B (check Actuarial post); Mathematical Statistics (check Actuarial post) --Core Courses (constituted by the following 5 components): 1. Tools << Business Communication & Writing I & II; Enterprise Data Analysis I & II (check FIN); International Financial Statement Analysis I & II (check FIN); Corporate Finance (check FIN) >> 2. Economic Integrity << Microeconomics I & II >> 3. Necessities << Network Optimisation; R Analysis (check Actuarial post); Operations Management I & II; Applied Decision Analysis >> 4. Professional Skills Requirements << International Commerce (check FIN); Logistics & Inventory; Supply Chain Modelling & Analysis; Operations Planning & Scheduling >> 5. There are electives to choose from (MUST CHOOSE 3 or 4): Service Operations Management (check RM) Engineering Cost & Production Economics course (check ENGR under IE section) Investments & Portfolios in Corporate Finance (check FIN) Options & Futures for Business Management (check FIN) Asset Management (check FIN) Corporate Risk Management (check FIN) Agriculture and Economic Sustainability (check ECON) Public Project Management (check PA) Transportation Modelling (check CIVE) Crisis Management (check PA) Research in Crisis & Crisis Mitigation (check PA) Programme Evaluation I & II (check PA) Note: the Quantitative Analysis in Political Studies I prerequisite to be replaced by either Mathematical Statistics or R Analysis. FOR THE FOLLOWING COURSES CHECK IN ACTUARIAL POST: Optimisation, Probability & Statistics, Mathematical Statistics Course Descriptions --> Network Optimisation Will assume a solid background in linear programming and R skills. Network flow problems are a subclass of linear programming problems, with applications in a wide range of areas. In this course, we will survey algorithms and applications of network flow problems. Focus topics will be: MAXIMUM FLOWS SHORTEST PATHS MINIMUM COST FLOWS MINIMUM SPANNING TREES Course Intensions --> 1. Knowledge of the key network optimization problems, and state-of-the-art algorithms for solving them. 2. Algorithmic thinking skills: – obtaining intuition for the development of algorithms. – finding an algorithm’s “weaknesses” or proving they do not exist: ∗ proving correctness ∗ running time analysis 3. Recognise applications of network flows and to demonstrate equivalence of problems. Typical Text --> Ravindra K. Ahuja, Thomas L. Magnanti and James B. Orlin, Network Flows: Theory, Algorithms, and Applications, Prentice Hall Topic Outline --> We will cover (parts of) Chapters 1-10, 12, 13, and 19. Modelling and construction of algorithms before computational environment is vital in order to comprehend what you’re really doing with packages and functions. It may also be possible to employ different packages for different pursuits with different topics --> Primitive Resources: -- http://rpubs.com/alexgeor/CPLEX1 >> -- Concerning optimal trees in weighted graphs one can make use of the R package “optrees” The R package “igraph” also has value: https://henrywang.nl/maximum-flow-problem-with-r/#more-21 -- netgen R package Homework --> Homework assignments in the beginning in a limited fashion to reacquaint one with standard linear optimisation modelling complemented by use of R to solve them. Towards network optimisation there will be standard problem sets, for modelling, and along with optimisation with R in order to best serve your interests. Exams will concern the following abilities: (1) to apply knowledge of mathematical modelling skills and recognition of models and algorithms (2) Algorithm design/structuring. Correctness and running time analysis. (3) Ability to actually implement R operations and use of packages for solution finding. Will be encountered often for consistency. (4) In some cases one doesn’t expect a student to memorize every algorithm, rather the ability to determine what it does, how to classify it, how data should be structured, etc. There may be trick questions: Information told about algorithm isn’t perfectly accurate Algorithm may be rubbish First Exam --> Will be in-class, open notes and R applicable. Questions will reflect homework. Second Exam --> Will be take home to make use of notes and R. In addition, questions observed to be consistently wrong or error prone in resolutions by students (homework and exam 1) will show up. Will also incorporate the latter topics in both depth and magnitude. Final Exam --> Will be similar to second exam, but will be comprehensive and in-class to encompass all of the term. Students will be randomly given different exam sheets. So, you have a networking problem to take up your time. Assessment --> Homework 25% Exam 1 20% Exam 2 20% Final Exam 35% Prerequisite: Optimisation Operations Management I 1.Process Analysis: to evaluate the performance of business processes, and how to identify opportunities for improvement. 2.Inventory Management: to recognise the different types of inventory in a supply chain and the reasons for its accumulation, and tools for deciding how much inventory a business should hold under different circumstances. 3.Quality Control: to measure and control the quality of the output of a business process. 4.Exposure to the more advanced topics of Queueing (measure and reduce waiting times), Revenue Management (manage prices and product availability), and Supply Chain Coordination (establish mutually beneficial relationships among partners in a supply chain). A few notes on grading components --> Student groups: projects and presentations are group assignments. Students should form groups of five members each by the end of the first week of class, and each group should email its composition as soon as it is formed. NOTE: projects will be based on Process Analysis and Quality Management NOTE: homework will emphatically encourage the use of R, Excel and other software alongside analytical development based on Queuing, Inventory Management, Supply Chain. Exams --> Exams will concern the only the following three areas: Queuing, Inventory Management, Supply Chain. Will allowed limited notes during exams. Course will not be much without a quantitative/computational environment. With much effort to consistently apply Excel and R usage; will apply to homework as well. For the R environment in assignments throughout there must be commentary along with development. Typical text: VARIOUS LITERATURE Tools --> R packages + RStudio Excel Microsoft Project Grade Assessment --> Homework 20% Projects + Presentations 20% Exam I 20% Exam II 20% Exam III (Final) 20% WEEK 1 – 5 Tools of concern: Microsoft Project Introduction Processes Analysis: Processes Flow Diagrams, Capacity, Flow Rate Processes Analysis: Gantt Charts, Cycle Time Processes Analysis: Utilization, Line Balancing Processes Analysis: Pipeline Inventory, Little’s law Processes Analysis: Setup Times, Batching WEEK 6 – 9 Student Presentations I Review: Review of exponential and Poisson Queuing: Waiting & Arrival Models Queuing: Staffing, Pooling, Lost Demand Note: R Packages of interest (applied when appropriate) --> queueing queuecomputer Ebert, A., Wu, P., Mengersen, K., & Ruggeri, F. (2017). Computationally Efficient Simulation of Queues: The R Package queuecomputer. arXiv Note: observe packages manuals for full possibilities WEEK 10 – 12 Note: R Packages of interest (applied when appropriate) --> SCperf Inventorymodel inventorize tsutils Topics in such weeks: Inventory Management: Economic Order Quantity Inventory Management: Economic Production Quantity Inventory Management: Newsvendor Salazar, R. Newsvendor Inventory Problem with R. Medium Analytics Vidhya Multi-period Base Stock Policy (R,Q) Policy Salazar, R. ABC Inventory Analysis with R: Effective Inventory Planning and Managing. Medium XYZ Analysis For the R packages, aside from treating “ideal problems” catering for the above topics, will also analyse how such packages can treat the following: Yarmand, H. et al. Optimal Two-Phase Vaccine Allocation to Geographically Different Regions Under Uncertainty. European Journal of Operational Research 233 (2014) 208- 219 WEEK 13 – 15 Supply Chain Management I Supply Chain Management II Note: R Packages of interest (applied when appropriate) --> cplexAPI, CVXR, lpSolve, lpSolveAPI, NlcOptim, nloptr WEEK 16 – 17 Quality Management: I Quality Management: II Quality Management: Lean Operations WEEK 18 Student Presentations II Prerequisites: Enterprise Data Analysis I & II, Optimisation, Probability & Statistics B Operations Management II Note: packages and tools from prerequisite will reverberate throughout course. Grading --> Prerequisite refresher tasks R projects 3 Exams Prerequisite refresher tasks --> Students will be given problem sets, projects, and assignments with R usage & other software. R projects --> Concerns process analysis, data envelopment analysis, and stochastic frontier analysis Exams --> Exams will be based on personnel scheduling, queuing, and perishable inventory. Students are allowed access to R and Excel. COURSE OUTLINE --> 1. Personnel Scheduling Note: R Packages and software of interest for this module (applied when appropriate after modelling development): cplexAPI, CVXR, lpSolve, lpSolveAPI, NlcOptim, nloptr, Rglpk Excel Brucker, P., Qu, R., and Burke, E., Personnel Scheduling: Models and Complexity, European Journal of Operational Research 210 (2011) 467–473 The above article to serve as a categorization guide: (i) permanence centred planning (ii) fluctuation centred planning (iii) mobility centred planning (iv) project centred planning Emphasis on determining what type of scheduling should apply to cases considered. Other particular examples: Kassa, B., A., and Tizazu, A., E., Personnel Scheduling Using Integer Programming Model-A application at Avanti Blue-Nine Hotels, SpringerPlus, 2013; 2: 333 Becker, T., Steenweg, P., M., and Mareike, P., and Werners, B., Cyclic Shift Scheduling with On-Call Duties for Emergency Medical Services, Health Care Management Science, Springer Nature 2018 Semra Ağralı, S., Taskin, Z., C., and Tamer Ünal, A., T., Employee Scheduling in Service Industries with Flexible Employee Availability and Demand, Omega 66 (2017) 159–169 2. Advance Recital of Queuing & Activities --Waiting Models, Staffing, Pooling, Lost Demand --Additional structure where simulations will also be pursued in R: Ingolfsson, A. Haque, M. A. and Umnikov, A. (2002). Accounting for Time Varying Queuing Effects in Workforce Scheduling. European Journal of Operational Research, volume 139 , issue 3, pages 585 – 597 Defraeye M., Van Nieuwenhuyse I. (2015). Personnel Scheduling in Queues with Time-varying Arrival Rates: Applications of Simulation-Optimization. In: Dellino G., Meloni C. (eds) Uncertainty Management in Simulation-Optimization of Complex Systems. Operations Research/Computer Science Interfaces Series, vol 59. Springer, Boston, MA 3. Advance Recital of Processes Analysis and Activities 4. Inventory Advance Recital & Activities (from Operations Management I) 5. Perishable Inventory Text Examples: Nahmias, S. (2011). Perishable Inventory Systems. Springer Gor, R. (2011). Management of Perishable Inventory: A Mathematical Modelling Approach: Study of Optimal Ordering Policies for Time Varying Decay Rate of Inventory Under Different Payment Conditions. LAP LAMBERT Academic Publishing Note: don’t want topic to turn into Sir Arthur Conan Doyle’s “Lost World”. R Packages of interest (if still applicable to topic) --> SCperf Inventorymodel inventorize tsutils 6. Data Envelop Analysis (DEA) Note: many parts will be applications focused, data oriented and will be projects based. Concerns efficiency in firms, industries, markets, sectors, agriculture R Packages of Interest for DEA: rDEA, deaR, Benchmarking --Concepts, structure, applications --Lotfi, F.H. et al (2020). Data Envelopment Analysis with R. Springer --Ranking --Narasimhan, R., Talluri, S. and Mendez, D. (2001). Supplier Evaluation and Rationalization via Data Envelopment Analysis: An Empirical Examination. Journal of Supply Chain Management, Volume 37 Issue 2. Pages 28 – 37 --Evaluate performance of chosen industries --Chance-Constrained Data Envelopment Analysis Land, K. C., C. A. Knox Lovell, & Thore, S. (1993). Chance-Constrained Data Envelopment Analysis. Managerial and Decision Economics, 14(6), pages 541–554. Note: to extend to other applications 7. Applied Multivariate Regression --Applied review from Mathematical Statistics course 8. Stochastic Frontier Analysis (SFA) Note: will be applications focused, data oriented and will be projects based. Concerns efficiency in industries, markets, sectors, agriculture R Packages of Interest for SFA: frontier, npsf, sfa, ssfa, semsfa, Benchmarking --To be competent or formidable in the R computational environment one must understand what they’re computing. --Further analytic structuring (if required): Aigner, D.J.; Lovell, C.A.K.; Schmidt, P. (1977) Formulation and Estimation of Stochastic Frontier Production Functions. Journal of Econometrics, 6: 21 – 37. Literature R guides assist: Guo, X. et al (2018). Specification Testing of Production in a Stochastic Frontier Model. Sustainability, 2018, 10 (9), 3082 Ferrara, Giancarlo. (2020). Chapter 9, Stochastic Frontier Models Using R, pages 299 – 326. In: Vino, H. D. and Rao, C. R. Handbook of Statistics (vol 42). Financial, Macro and Micro Econometrics Using R. North Holland Elisa Fusco & Francesco Vidoli (2015). Spatial Stochastic Frontier Models: Instructions For Use. CRAN R Robin C. Sickles & Wonho Song & Valentin Zelenyuk, 2020. Econometric Analysis of Productivity: Theory and Implementation in R. Pages 267 – 297. In: Vino, H. D. and Rao, C. R. Handbook of Statistics (volume 42). Financial, Macro and Micro Econometrics Using R. North Holland R structure: https://sites.google.com/site/productivityinr/ 9. SFA versus DEA Advantages and disadvantages Prerequisites: Operations Management I, Mathematical Statistics Logistics & Inventory Role of logistics and inventory management: warehousing, transportation, facility location, forecasting, inventory management and assortment planning. -Concepts, techniques, methods and applications of logistics and inventory management strategic planning. -Quantitative/computational environment. With much effort to consistently apply Excel and R usage; will apply to homework, quizzes and exams; must always accompany analytical development. For the R environment in assignments throughout there must be commentary along development. Homework --> Concerns learning and skills reinforcement. Quizzes --> There are 3 in-class quizzes during the class period. These are closed-book, but students are permitted to bring sheet of notes. Exams --> There are 3 exams throughout course. They are closed-book, but students are permitted to bring 2 – 3 sheets of notes. Field Studies Projects (FSPs) --> Groups will be responsible for analysis and modelling with logistics and supply chain systems assigned to them. There will be numerous visits. There will be much data gathering towards modelling, computation and simulation pursuits, based on knowledge and skills from course. Each group will be responsible for 5 phases. Note: for sites to have sign off log sheets with description of encounters. Project guides to be provided. Students are expected to competently apply a GIS, R with packages, and possibly Excel. FSPs: Based on Week 2-6 Based on Week 7-8 Based on Week 9-10 Based on Week 11-13 Based on Week 14 Technology requirement --> R environment Excel GIS Word Processor R packages of interest: cplexAPI, CVXR, lpSolve, lpSolveAPI, NlcOptim, nloptr, Rglpk optrees, igraph SCperf, Inventorymodel, inventorize, tsutils Course Texts --> Ronald H. Ballou. Business Logistics/Supply Chain Management, 5th Edition. Pearson Prentice Hall 2004 Chopra, Sunil and Peter Meindl. 2016. Supply Chain Management: Strategy, Planning, and Operation, 6th Edition. Pearson Prentice Hall. Course Grading --> Homework 3 Quizzes 3 Exams Field Studies Projects Course outline --> WEEK 1 Introduction and course overview WEEK 2 – 3 Warehousing and Storage Management WEEK 4 Cross-docking and Transit Point WEEK 5 – 6 Transportation and Routing WEEK 7 – 8 Third-party Logistics Facility Location and Network Design WEEK 9 – 10 Capacity Location and Logistical Design Demand Forecasting WEEK 11 – 13 (ultimate goal is to extend to applications of interest) Inventory Advance Recital (from Operations Management I) ABC - XYZ Analysis Thieuleux, E. (2022, August 17). ABC XYZ Analysis in Inventory Management: Example in Excel. AbcSupplyChain Sap. (2016, June 17). ABC/XYZ Analysis. SAP Help Portal WEEK 14 Aggregate Inventory Control and Risk Pooling WEEK 15 Assortment Management Prerequisite: Operations Management I Applied Decision Analysis: This course concerns the use of analytical and computational skills in practical decision making. Course will be highly project oriented. For most or many succeeding modules expect to build on prior modules. Homework --> For each module there will be assigned homework concerning standard problems. Also, be prepared to use Excel and R extensively. Projects --> There will be 5 – 9 projects (individual and/or group) for each module to pursue. Projects will often incorporate high usage of the R environment and Excel. Exams --> For each exam you are permitted to bring 5-6 loose leafs of notes; exams go beyond memorization, and you can’t remember everything off hand.. You are making big decisions, rather than being the brat or scum or scourge of the year. All exams will require use of R and Excel. You will also still be required to state analysis, developments and modelling as preliminaries to R and Excel use. Concerning probability/statistics I don’t like to give ideal or counterfeit data from textbooks; you will have to personally fetch and investigate raw data. Tools --> R with packages Assume use of your conventional probability and statistics R skills Assume use of R packages for optimisation (linear, integer, mixed, quadratic, etc., etc.) Analytic Hierarchy Process: ahp, Prize, ahpsurvey Multi-objective programming and Goal programming, 90C29: caRamel, GPareto, mco, emoa, rmoo Quantitative Multicriteria Decision Aiding Process MCDA R package PROMETHEE PROMETHEE R package Marginal Effects: margins Options LSMRealOptions Qualitative Multicriteria Decision < http://www-ai.ijs.si/MarkoBohanec/dexi.html > Microsoft Office 365 Excel usage when constructive Word Processor Sources --> Aside from given texts and articles there are many texts and journal articles to build on, to acquire a strong foundation with substance and applicability. For a student recognition from analysis will be crucial for success. Grading --> HW 10% Projects 45% 3 Open Notes Exams 45% NOTE: on exams you will encounter applications questions focused on comprehension, proper usage, logistics and implementation. Course Modules/Topics --> 1. Multiperiod Planning Models Applications of interest: Production/inventory planning Human resource staffing Capacity expansion/plant location problems Investment problems Schrage, L. (2018). A Guide to Optimization-Based Multiperiod Planning, INFORMS TutORials in Operations Research () 50-63 Hansmann, F. and Hess, S. W. (1960). A Linear Programming Approach to Production and Employment Scheduling. Management Science 1(1) 46-51 Tadeusz Sawik (2019). Two-Period vs. Multi-Period Model for Supply Chain Disruption Management, International Journal of Production Research, 57:14 2. Analytic Hierarchy Process Some resources if needed: Saaty, T.L. (1980). The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation. McGraw-Hill Lawrence Bodin, L. and Gass, S. I. (2014). Exercises for Teaching the Analytic Hierarchy Process. INFORMS Transactions on Education 4(2), pp 1–13 Note: disregard MBA mention since prerequisites are met; immersive development is more productive than academic titles. Vargas, R. V. (2010). Using the Analytic Hierarchy Process (AHP) to Select and Prioritize Projects in a Portfolio. Paper presented at PMI® Global Congress 2010—North America, Washington, DC. Newtown Square, PA: Project Management Institute 3. Preference Ranking Organization Method for Enrichment of Evaluations (PROMETHEE) Brans, J. P., & Vincke, P. (1985). Management science, 31(6), 647-656. Brans, J. P., & Mareschal, B. (2005). PROMETHEE methods. In Multiple Criteria Decision Analysis: State of the Art Surveys (pp. 163-186). Springer Applications for PROMETHEE: TBD 4. Qualitative Multicriteria Decision After overview and logistics will develop quantitative versus qualitative case studies (AHP and PROMETHEE). 5. Stochastic and Statistics Tools Review axioms of probability distributions Simulating random variables (or frequency distributions) and interpretation Structuring & analysis of basic real world events Computational development/representation of real world events events The Normal Distribution Arguments for its emergence and practicality Limpert, E. & Stahel, W. A. (2011). Problems with Using the Normal Distribution and Ways to Improve Quality and Efficiency of Data Analysis. PloS one, 6(7), e21403. Dealing with missing data Simulating data when real data is elusive Sample size determination EDA & Goodness of fit (advanced development) Data Summary Statistics (max, min, mean, median, standard deviation, skew, kurtosis) Box Plot Q-Q plot Correlation heat maps. Applying the ggpairs() function Comprehending critical values for ideal distributions (not only normal) Comprehending critical values for real raw data sets Does your data distribution exonerate ideal models for critical values? Chi-Square test, Kolmogorov–Smirnov test, Shapiro-Wilk test, Anderson-Darling test Maximum Likelihood Estimators and Method of Moments Confidence Intervals (not confined to normal distribution) Correlation (development and large data sets) Assumptions for Pearson Correlation & computational means of verification Extend following beyond the field of medicine: Mukaka M. M. (2012). Statistics Corner: A Guide to Appropriate Use of Correlation Coefficient in Medical Research. Malawi Medical Journal: The Journal of Medical Association of Malawi, 24(3), 69–71. Test Statistics We are not concerned with zombie textbook problems. What’s important is how it’s meaningful to you with your future endeavours in OM/AOR. NOTE: all topics in the EDA and Goodness of-fit module will be crucial. No normality means no T-test and F-test NOTE: will be restricted to the following -- Test for independence McHugh ML. (2013). The Chi-square Test of Independence, Biochem Med (Zagreb). 23(2): 143-9. Using Fisher’s Exact Test as an alternative Test of variance Significance of the correlation coefficient. What if not Pearson? Interpreting summary statistics for multivariate regression models Sample size determination 6. Feature Selection (will be hands-on and comparative) Note: a feature is the same as a predictor variable; a target is equivalent to a response variable. First, for datasets chosen will develop correlation matrices. Then heatmaps. Second, will explore a method for feature selection. Will identify the concept, followed by (practical, tangible and fluid) analytical structure. Then implementation logistics. Then implementation in the R environment. Will make use of datasets with considerable amounts of features. Univariate Feature Selection Recursive Feature Selection Boruta FSelectorRccp Note: compare results among all. As well, examination of correlation heat map (via either Pearson or spearman or Kendall) to observe any possible multicollinearity. 7. Multivariate Regression Advance review from Mathematical Statistics Summary statistics of data Review of knowledge and R skills for multivariate from Mathematical Statistics Augmented by the following: Scatter plots and influence on choice of regression model Quantile Regression (to develop logistics, and applications development in R) Motives; model structure and computational structure; summary statistics; contrast to OLS counterpart via summary statistics. Is the trend (positive or negative) in scatter plots absolute OLS versus Quantile versus LOESS/LOWESS versus Spline Observing trend and summary statistics Implications for multivariate models and forecasting Feature selection review Forecasting & Error Response variable distribution & conditional expectation For multilinear models to develop the probability distributions for a respective explanatory variable (or with multiple variables) with the response variable, w.r.t. data range. Evaluating Conditional probabilities and conditional expectation. Marginal Effects 8. Multivariate Logit Regression (to develop logistics, and applications development in R) Motives; model structure and computational structure; evidence for variables; summary statistics analysis; calculating probabilities/predicted probabilities; marginal effects Feature importance logistic regression method 9. Agricultural Planning Optimisation (real data relevant) Target MOTAD. Articles following as guides for development. However, will be working with real agriculture data from farmers/producers in environments of interest for development. Structural guides: Tauer, L. W. (1983). Target MOTAD. American Journal of Agricultural Economics, 65(3), 606–610. Watts, M. J., Held, L. J. and Helmers, G. A. (1984). A Comparison of Target MOTAD to MOTAD. Canadian Journal of Agricultural Economics, 32(1), pages 175 -186. Curtis, C. E. et al. (1987). A Target MOTAD Approach to Marketing Strategy Selection for Soybeans. North Central Journal of Agricultural Economics, 9(2), 195–206. Berbel, J. (1990). A Comparison of Target MOTAD Efficient Sets and the Choice of Target. Canadian Journal of Agricultural Economics, Volume 38 Issue 1, pp 149. 10. Monte Carlo Applications Note: must compose analysis and modelling prior to R and Excel usage. Monte Carlo for uncertainty in models/formulas Applying to models in finance, portfolios, operations management, revenue management, etc. Concerns actual computation with R and Excel, yet you will still be required to compose analysis and modelling prior. 11. Cost-Benefit Analysis (monetised and non-monetised aspects) Framework analysis and logistics CBA manuals exist for various fields Project-based development Note: sensitive values like determining rate of return (cost of equity, WACC, APV, CAPM, multi-factor models). There are guides/manuals to build your CBA rather than accepting “phantom numbers”. Tools such as RIMS -II, IMPLAN, Chmura, LM3 or REMI may also apply Excel Implementation: Campbell, H., & Brown, R. (2003). Benefit-Cost Analysis: Financial and Economic Appraisal using Spreadsheets (pp. 194-220). Cambridge: Cambridge University Press Augmentation: Sener Salci & Glenn P. Jenkins, 2016. “Incorporating Risk and Uncertainty in Cost-Benefit Analysis”, Development Discussion Papers 2016-09, JDI Executive Programmes. Prereqs: Enterprise Data analysis II, Optimisation, Probability & Statistics B, Mathematical Statistics, Senior Standing Supply Chain Modelling & Analysis An introduction to supply chain logistics systems, including: The components of logistics systems, such as supplies, storage, materials handling, production, inventory, orders, and transportation systems The interactions between these components Models and techniques for the analysis of logistics systems and the development of information and decision support systems. Objectives --> Develop familiarity with supply chain logistics concepts Understand the issues in logistics system design and operation Develop the ability to formulate quantitative decision models for logistics system design and management. Typical Text --> Goetschalckx, Marc, Supply Chain Engineering, 2011 Supporting Text --> Ghiani, G., Laporte, G., & Musmanno, R. (2004). Introduction to Logistics Systems Planning and Control, Wiley Field Literature (optional) --> Determination of the applied techniques and tools throughout, along with accessibility of one’s data resources for their ambiance to emulate: Silva, S. et al (2018). Optimisation of Supply Chain of Targeted Public Distribution System in Dhenkanal, Odisha. World Food Programme Georgiadis GP, Georgiadis MC. (2021). Optimal Planning of the COVID-19 Vaccine Supply Chain. Vaccine, 9(37): 5302-5312. Shabani, K., Outwater, M. and Murray, D. (2018). Behavioral/Agent-Based Supply Chain Modelling Research Synthesis and Guide. U.S. Department of Transportation Required Tools --> R + RStudio environment (various packages used in prerequisites) Excel Microsoft Dynamics 365 Supply Chain Management GIS Kaggle data, gov’t data and others Grades will be assigned as follows --> Homework: 10% Quizzes: 10% 5-6 Projects 30% Exam 1: 15% Exam 2: 15% Final exam: 20% Homework --> Once a week. Start working on each homework early, to have time to ask (and understand) questions before the homework is due. Projects Expectations--> --Generally all modules will be relevant throughout --It may be challenging to acquire real and practical data, but such will be acquired for use. Generating synthetic data may or may not be applied. --Expect to apply all knowledge and skills from prerequisites without restrictions. A succeeding project may or may not depend on prior project(s). --Will have relevance to applications from both texts concerning modelling, and case examples, with software use (both R and Microsoft) towards data analysis, system development, computation, extrapolation, forecasting, etc., etc. --In some cases also incorporating GIS/mapping software for routing & networks, distance & time for travel. Supply chain networks intelligence from course applied in both R and Microsoft, accompanied by written analysis; establishing such with relevancy to course topics. Course Topics Covered --> 1. Supply chain management The coordination of supply chain activities involving multiple participants in the supply chain. – Supply chain game – Bullwhip effect – Vendor managed inventory 2. Data and Forecasting Introduction to methods for data collection, data management, and forecasting future uncertain data. – Data collection technology – Database design for supply chain management – Extrapolation forecasting – Multivariate forecasting via regression – Time Series extrapolation and forecasting Methods 3. Vendor/Supplier Selection --Data Envelopment Analysis (DEA) Chosen literature to apply with R packages --Principal Component Analysis (PCA) Overview the objective and uses of PCA PCA with R activities The following articles are to be analysed, followed by pursuit of environments and industries of interest based in R (where GIS displays can be incorporated as well): Petroni, A. and Braglia, M. (2000). Vendor Selection Using Principal Component Analysis. Journal of Supply Chain Management, Vol36 Issue 1, Pages 63 – 69 Wang, J., Swartz, C. L. E., Corbett, B. & Huang, K. (2020). Supply Chain Monitoring Using Principal Component Analysis. Ind. Eng. Chem. Res, 59, 27, 12487 - 12503 --DEA versus PCA (strengths and weaknesses) hands-on 4. Freight transportation modes Overview of motor freight, sea cargo, railroad, air cargo, and package express transport providers. 5. Transportation mode and route selection The transportation market: transportation costs, freight rates, contracts, spot market. How do shippers decide which modes/carriers to use for moving freight? How do shippers and carriers both decide on paths? – Transportation costs and rates – Models for mode/carrier selection – Minimum-cost path models 6. Fleet Management Cerny, J. (1997). Fleet Management – Selected Optimisation Problems. IFAC Proceeding Volumes 30(8), pages 593 – 596 7. Truckload Trucking Models for managing a freight transport fleet serving origin-destination direct shipments. – Time-space networks – Assignment problems for scheduling 8. LTL Trucking and Vehicle Routing Introduction to routing and scheduling problems for a local consolidation terminal. – Traveling salesman problem – Robert, R. and Toth, P. (2012). Models and Algorithms for the Asymmetric Traveling Salesman Problem: An Experimental Comparison. EURO J Transp Logist, 1:113–133. Note: instances and benchmarks may need updating. – Bin packing problem – Vehicle routing problem 9. Consolidation Transportation How does a shipper or a consolidation carrier decide how to structure a terminal network, and then move freight through the terminal network? – Role of consolidation – Network design – Minimum-cost network flow models – Facility location models 10. Pricing and Revenue Management Introduction to pricing of transportation services for profit maximization. 11. Supply Chain Risk Management – Risk Sharing Contracts – Risk Pooling: Centralization, Postponement, Omni Channel – Risk Hedging 12. Supply Chain Modelling for Perishables (Time Permitting) Orjuela-Castro, J.A., Orejuela-Cabrera, J.P. & Adarme-Jaimes, (2022). W. Multi-Objective Model for Perishable Food Logistics Networks Design Considering Availability and Access. OPSEARCH 59, 1244–1270 Prerequisites: Enterprise Data Analysis II, Optimisation, Network Optimisation, Mathematical Statistics Operations Planning & Scheduling Analytical methods and tools for inventory control and production planning and control. We will study forecasting methods, inventory models, deterministic and probabilistic production planning and scheduling methods, and shop floor control techniques. You will be assigned problem sets, that will include both analytical and computational problems. There will be a full term project where you will work in groups. Groups will be working with firms and/or public sector elements towards implementation of the analytical models and the Technology Requirements given. For the full term project an outline will be provided involving proper sequence of course topics and tools. There will be 2 midterm exams and a final exam, all open book, open notes. Typical texts --> Factory Physics by W.J. Hopp and M.L. Spearman Production and Operations Analysis by S. Nahmias Operations Engineering and Management; Concepts, Analytics and principles for Improvement, by Seyed M.R. Iravani Technology Requirements --> R environment Excel Microsoft Project Microsoft Dynamics 365 Supply Chain Management Grading --> Problem Sets 15% Full Term Project 30% Midterm Exam 1 15% Midterm Exam 2 15% Final Exam 25% Course Outline --> Introduction to production planning and scheduling Capacity management and control Forecasting Detecting stationarity and trend Moving Average Exponential smoothing and Holt-Winters Method Tracking signals, Trigg-Leach method Aggregate production planning Common strategies Linear Programming (LP) approach Scheduling production and workforce in manufacturing systems Deterministic Schedilung Stochastic Scheduling Production Scheduling Resource Constrained Scheduling Variability in production and inventory systems Deterministic inventory models EOQ Discount models EPQ Models with constraints on budget and space Stochastic inventory models Newsboy problem Continuous review models (R,Q) policy, Periodic Review Systems (s,S) policy ABC, XYZ, ABC-XYZ Inventory Lean Operations (JIT, CONWIP, Kanban, TQM, TPM, etc.) Risk pooling strategies Prerequisites: Operations Management II List of engineering “summer” and “winter” activities open to Operational Research (Operations Management) students --> Industrial Engineering (check engineering post): A, B, D, E, F, H, I, J, K, M, N, P NOTE: other activities can be developed to cater for interests “SUMMER” & “WINTER” ACTIVITIES Activities repeated can be added to transcripts upon successful completion. Repeated activities later on can be given a designation such as Advance “Name” I, Advance “Name” II, etc. Fraud Detection....CHECK ACTUARIAL POST Open to all students Financial Modelling Basics Ratio Analysis via financial statements skills Cash Flow Analysis Beneish, Dechow F, Modified Jones, Altman Z, Probability of Default (via equity) and the KMV extension of prior Corporate Valuation methods Development of the 3-statement model Pro Forma Financials development Forecasting Annual Revenue Regression models, error patterns, downside risk, forecast accuracy. Financial Statements Based on forecasts of revenues, using Excel’s Scenario Manager to do sensitivity analysis. Seasonal Revenues Creating seasonally-adjusted forecasting models by joining seasonal adjustments to an annual trend line or a moving average trend line; using error feedback to correct a model so that the average error is zero; using period values to update annual forecasts and revise the model. PESTEL + SWOT 5C Analysis development WACC Analysis vs Adjusted Present Value method vs Cash Flow to Equity Active market research and trade modelling Open to all students A. Basic Data Gathering Acquiring financial statements (balance sheet, income, cash flow). In the RStudio environment acquiring financial data for market assets: intraday, closing price, comprehension of dynamics. B. Fundamental Analysis Will be assigned at least 15-20 stocks. Creating “dashboard fill-ins for firms in columns” based on the following features is good preparation: Speed reading SEC filings Financial statements (GAAP or non-GAAP) Coverage ratios, liquidity ratios, profitability ratios, efficiency ratios Include historical performance Beneish, Dechow, Modified Jones, Altman z Economic forecasts Current Account Benchmarks Fed Policy, Budget Analysis, Fiscal Policy, Fiscal Indicators PESTEL and SWOT Stock Valuation (present and future) Stock Metrics P/E, PEG, P/B, D/E, Price-to-Sales FCF, Payout, ROE, Beta Beta coefficients and market risk-reward measures C. Use of quantmod and QuandlR package, and/or other packages. D. Technical Analysis Basics of Technical Analysis – Investopedia (subsections 1 through 12). As well, Investopedia provides information on various TA indicators. Some clear ideas of trading strategies-- Introduction to Technical Analysis Price Patterns - Investopedia How to Build a Trading Indicator - Investopedia 7 Technical Indicators to Build a Trading Toolkit - Investopedia Based on such Investopedia sources to immerse into R activities, namely, Technical analysis in R. Example ideas: Technical Analysis Using R – YouTube Using R in real time financial market trading – YouTube Packages often of use F for TA: quantmod, fTrading, TTR. Commercial trading simulation tools at disposal: Investopedia Stock Simulator, CME Group simulators, Ninja Trader, London Stock Exchange Virtual Portfolio, London Stock Exchange Trading Simulator, TMX Capital Markets Learning Centre < https://www.tmx-edu.com >, FACTSim, Virtual Stock Exchange The fundamental analysis versus Technical Analysis development. E. Transactions Records Interested in transactions logs for analysis of activities Blotters Haynes, A. (2022). Blotter. Investopedia F. Transaction thresholds (appropriate order) Marginal Call, Margin Debt, Liquidation Level, Liquidation Margin, Federal Call Quantitative Analysis Note: open to all. Probability & Statistics background Note: interested in a portfolio having stocks, bonds and currencies. The given guides may not necessarily be in appropriate order, hence a robust and versatile framework to implement will be developed based on such guides. There must be analytical development in progression to make sense of the R development. -Introduction to Finance with R – Ronald Hochreiter – YouTube -Codebliss --> Quantitative Finance with R Part 1: Intro and Data - YouTube Quantitative Finance with R Part 2: Portfolio Analysis - YouTube Quantitative Finance with R Part 3: Portfolio Optimization - YouTube -Principal Component Analysis --> Hefin Rhys: Principal Component Analysis in R – YouTube Martin Geissmann: Principal Component Analysis in R for Portfolio- Diversification – YouTube Other YouTube videos exist -QuantCourse --> Portfolio & Single Stock VAR and CVAR in R – YouTube -Autochartist --> Using R in real time financial trading – YouTube Value, Growth & Sustainability with Tech (CHECK ACTUARIAL POST) Open to all students Life Cycle Costing (CHECK CIVIL ENGINEERING POST) Open to all students Economic Scenario Generator Note: for Finance and Economics majors Activity concerns identifying the purpose of an economic scenario generator and developing fluid and tangible logistics towards accomplishing goals. Literature guides --> Wilkie, A.D. (1986) A Stochastic Investment Model for Actuarial use. Transactions of the Faculty of Actuaries, 39, 341–403. Wilkie, A.D. (1995) More on a Stochastic Asset Model for Actuarial Use. British Actuarial Journal, 1(5), 777–964 Huber, P. (1997) A Review of Wilkie’s Stochastic Asset Model. British Actuarial Journal, 3(1), 181–210. Bégin, J.-F. (2019) Economic Scenario Generator and Parameter uncertainty: A Bayesian approach. ASTIN Bulletin, 49(2), 335–372. Pedersen. H. et al (2016). Economic Scenario Generators: A Practical Guide. Society of Actuaries: Conning (2020). A User’s Guide to Economic Scenario Generation in Property/Casualty Insurance. Casualty Actuarial Society, CAS Research Papers PART A Development of multiple portfolios, each constituted by stocks, corporate bonds, gov’t (domestic and foreign), currencies and commodities based on mean-variance, factor models and PCA, respectively, in the R environment. Each portfolio to have 20-25 elements to be realistic. PART B --From the given literature, analysis followed by logistics for R implementation. Identifying what types of R programming and R packages will be needed throughout development. Pursue development --Followed by immersion into R package ESG Regulation towards firms (to implement) Open to all (specifically business and economics students) OECD international Standard Cost Manual: https://www.oecd.org/regreform/regulatory-policy/34227698.pdf NOTE: will be applied extensively for various firms nationally and internationally. Public Project Management Advance repetition of methodologies, tools, logistics and software from course in PA. Much emphasis on Microsoft Project use. Will collaborate with elements of the public sector. Work Force Planning Geared mainly towards PA students. Groups will be assigned to various elements of the public sector to apply the following guide to workforce planning (intimately and comprehensively): < https://hr.nih.gov/workforce/workforce-planning/getting-started > < https://hr.nih.gov/workforce/workforce-planning > Data gathering will be crucial for development ISO 31010 – Risk Assessment Techniques (RAT) For various industries in the private sector and elements of the public sector will pursue chosen RAT topics comprehensively. For any quantitative or computational tools/techniques applications, they will not be restrained. Note: open to all.

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CIVIL ENGINEERING

# CIVIL ENGINEERING NOTE: Civil Engineering endeavor will have a core requirement unique to any other engineering field. Programme primarily concerns those who are highly talented in non-performing Creative Arts, Upholstery, Woodwork, Masonry, etc., where opportunities in such skills are greatly limited. To provide professional opportunities beyond trade labour; such individuals to also have history demonstrating high levels of mathematics or physics. Additionally, programme demands students of great self-discipline, patience and tolerance for volatile business and operational development. NOTE: It may be in the best interest of Civil Engineering students that the General Education Appeasement courses be fulfilled during the “summer” and “winter” sessions. NOTE: this academic endeavor is dependent on “summer” and “winter” activities to be considered valuable. Pretty much, you don’t have a choice concerning your best interest. Writing requirements --> Engineering Design I & II (Writing appeasement) History requirement --> Historical Architecture and Civil Engineering There will be two types of literature, namely, Art History and Civil Engineering History. Concerns accomplishments and institutions from: B.C.- A.D. (Africa, Asia, Middle East) Middle Ages Tudor architecture Renaissance Circa Louis XIV Colonial Victorian Modern To incorporate historical architecture and civil engineering of buildings and structures out of the following: Reservoirs and Aqueducts Forts Churches Schools and Colleges Bridges Hospitals Town Halls, Assemblies, Parliament Public Buildings Sports Arenas Sea Ports Airports Train Bridges and Train Tunnels Channel tunnel, The Øresund bridge, Chesapeake Bay Bridge-Tunnel Eiffel Tower Lady Liberty Statue of “Jesus” (Brazil) In the Caribbean and other places from colonial to present (destroyed and present). Will also include buildings constructed within solid rock and methods applied to accomplish such. May include subways and catacombs (ot made of human remains). Concerning a respective structure to some degree treated will be purpose, historical circumstances, social welfare, societal progression, etc., etc. Course carries the history satisfaction option and the humanities satisfaction option. Mathematics requirements --> Calculus for Science & Engineering I-III Ordinary Differential Equations Numerical Analysis Probability & Statistics B Mathematical Statistics Science requirements --> General Physics I & II Vibrations & Waves Fluid Mechanics General Engineering requirements --> Statics (check ME) Mechanics of Materials (check ME) Mechanics of Materials Lab (check ME) Engineering Thermodynamics (check ME) Civil Engineering requirements --> Structural Analysis, Advanced Structural Analysis, Cement Structures, Civil Engineering Materials Lab, Advance Cement Structures, Steel Structures, Advanced Steel Structures, Applied Hydraulics, Geographic Information Systems for Civil Engineering, Hydraulic Engineering Design, Geotechnical Engineering, Highway Engineering, Transportation Modelling, Land Surveying, Building Information Modeling for Capital Projects, Project Controls I & II

Course descriptions: Structural Analysis Structural analysis/design process, structural forms, and basic structural elements. Analysis of statically determinate structures including beams, trusses, frames, and composite structures, shear and moment diagrams, influence lines, and moving loads. Methods to compute deflections including double integration, moment area, and virtual work. Methods of analysis for statically indeterminate structures including consistent deformation, slope deflection and moment distribution. Use of structural analysis programs. Typical Course Text: Fundamentals of Structural Analysis, by Leet, Uang, & Gilbert, McGraw-Hill Tools --> SCIA Engineer Autodesk Revit RFEM Sap 2000 It’s imperative that there are lab sessions towards immersion and practical professional usage of structural software for civil engineering practices and analysis of crucial, critical, technical subjects. Homework --> A number of relevant homework problems, grouped into one or more problem sets will be assigned on the class website or given in class at the end of lecture. Some problems will challenge you with prerequisite tasks. Assignments will be collected in class at the beginning of a lecture in hard copy. Homework are suggested to be in a standard format. This includes: (a) statement of the problem (with drawn sketch and a CAD sketch) (b) statement of the problem (with developed structure n a CAD sketch) (c) quantities with given values (d) quantities to be found (e) solution of the problem. Assigned will be typed unless there’s necessity cases for work to be done in pencil. Students to accumulate points from the following --> Assignments 20% Lab 15% Midterm Exam 25% Term-Project & Presentation 15% Final Exam 25% Course Outline --> Week 1. Introduction , Structural Elements Week 2. Design Loads Week 3. Reactions, Free Body Diagrams Week 4. Trusses Week 5. Trusses Week 6. Beams and Frames Week 7. Shear, Moment Diagrams and deflection curves Week 8. Shear, Moment Diagrams and deflection curves Week 9. Cables Week 10. Influence Lines Week 11. Midterm Week 12. Influence Lines Week 13. Deflection of Beams and Frames Week 14. Analysis of Indeterminate Structures Week 15. Project Presentation Week 16. Final Exam Prerequisites: Mechanics of Materials, Mechanics of Materials Lab Co-requisite or Prerequisite: Calculus III, General Physics I. It’s imperative that you are keeping up with your math and physics courses (particularly General Physics I, ODE and Numerical Analysis) concerning the succeeding course. Civil Engineering Materials Lab Introduction to the concepts, techniques, and devices applied to measure engineering properties of materials. There is an emphasis on measurement of load-deformation characteristics and failure modes of both natural and fabricated materials. Weekly experiments include data collection, data analysis, and interpretation and presentation of results. Laboratory Sessions Scheduled for two hours on X day but this will change after the first lecture. Perform laboratory assignments in small (3 to 5 person) groups. Will meet in various rooms depending on experiment. We will send you email when the lab material is available. Read the material before the laboratory and be prepared to do the work Objectives Make measurements of behaviour of various materials used in CE Provide physical observations to complement concepts learned prior Introduce experimental procedures and common measurement equipment. Exposure to a variety of established material testing techniques. Conduct of the Course Each of the ten assignments will be done in small groups. Data will be made available electronically after each lab. Each person will use the data and prepare an individual report. The report will be due about one week after the lab session. The report will be graded based on clarity, data interpretation, and presentation. Operations in course: 30 minute group (X day and Z day) session for overview 90 minute subgroup session to make measurements Take all the data at the end of your session Data posted at end of each session or end of week Analysis and reports Requirements Attend lectures (short description of experiments). Ten laboratory assignments (90%) Participation, preparation, subjective evaluation, etc. (10%) There may be quizzes based on standards and procedures Reference Materials Each lab assignment will include specific reading assignments. Book of ASTM Standards (post 2000) or ambiance standards Lab Experiments Data Acquisition and Instruments Tension I - Elastic Behaviour Tension II - Failure of Common Materials Direct Shear - Frictional Behaviour Concrete I - Early Age Properties Compression - Directionality Concrete II - Compression and Indirect Tension Soil Classification Consolidation Test (Partial Experiment) Tension III - Heat Treatment Measurable Outcomes (Assessment Methods; Laboratory Reports, Quizzes). You should be able to: Calibrate electronic sensors Operate a data acquisition system Operate various types of testing machines Configure a testing machine to measure tension or compression behaviour Compute engineering values (e.g., stress or strain) from laboratory measures Analyse a stress versus strain curve for modulus, yield and strength Identify modes of failure Describe the frictional behaviour of soils Classify soils according to the USCS (or whatever) system Proportion a concrete mix to meet specific design requirements Describe the directional strength variation of an anisotropic material Evaluate the time rate of deformation of fine grained soils Specify the necessary heat treating to obtain the desired steel properties Write a technical laboratory report Prerequisites: Structural Analysis Advanced Structural Analysis Mathematica and SCIA Engineer (or Autodesk Revit and RFEM as software alternatives) It’s imperative that there are lab sessions towards immersion and practical professional usage of structural software for civil engineering practices and analysis of crucial, critical, technical subjects. Prototypical Textbook: Kassimali, Aslam. (2012). Matrix Structural Analysis. 2nd Edition, Cengage Learning Mathematical Tools --> Mathematica Structural analysis Tools --> SCIA Engineer Autodesk Revit RFEM Sap 2000 It’s imperative that there are lab sessions towards immersion and practical professional usage of structural software for civil engineering practices and analysis of crucial, critical, technical subjects. Assignments 20% Major Structural Lab Projects 15% Midterm Exam 25% Term-Project & Presentation 15% Final Exam 25% Assignments and Major Structural Lab Projects All tasks must have an analytical computational component accompany development in a computational environment and CAD. This is not a manual matrix algebra course. You are aspiring civil engineers engineers, not practitioners of flattery and ideology. It’s quite important that you understand the difference between a civil engineer and a mathematician before you take this course, because patience and time on indulgence will not be tolerated. If you have to apply inverse or transpose or adjoint[adjoint[adjoint]] or Eigen or whatever, we are only concerned with when it comes up with modelling...then how to do away with the time consuming pig pen chase. Course Outline: I. Introduction, Definitions and Concepts Analysis Techniques Types of Frames Structures Structure Idealisation Fundamental Analysis Relationships Review of Select Classical Methods Moment Area Slope Deflection Momentum Distribution Method II. Matrix Operations Note: course will not get carried away with matrix theory, rather it will serve as a primitive tool towards something much greater than it (where meaningful use of time is just part of the reason). However, students much know modelling set ups. Most matrix operations will make use of Mathematica. III. The Flexibility Method Indeterminancy Formulation of the Basic Equations Application to Plane Trusses IV. Formation of the Global Analysis Equations for Plane Trusses Coordinate Systems Degrees of Freedom Member Stiffness and Local Coordinates Coordinate Transformations Member Stiffness and Global Coordinates Assembly of Structure Stiffness -->Direct Stiffness and Code Number Methods Analysis Procedure Application within Computer Programs V. Formation of the Global Analysis Equations for Beams Member Stiffness: Local and Global Coordinates Assembly of Structure Stiffness Analysis Procedure VI. Formation of the Global Analysis Equations for Plane Frames Member Stiffness: Local Coordinates Coordinate Transformations Member Stiffness: Global Coordinates Assembly of Structure Stiffness Analysis Procedure VII. Other Topics and Structures Member Releases “Secondary Effects” – Support Displacement, Temperature Change, Member Misfit Nonlinear Behaviour and Analysis Shear effects (Timoshenko Beam Theory) VIII. Rayleigh-Ritz Method IX. The Finite Element Method (as time permits) Departure from classical Rayleigh Ritz Method leads to FEM Trial functions are defined for sub-domains Generally, the use of values of space variable at the nodes as unknowns Basic Concepts, Relationships Plane Stress Element Matrix Condensation Connections and Joints Symmetry and Antisymmetry Prerequisites: Structural Analysis, General Physics I, ODE, Numerical Analysis, Calculus III. Steel Structures An introductory course in the design of steel structures. The objectives of this course are: To learn the behavior and design of structural steel components, for example, members and connections in two-dimensional (2D) truss and frame structures. To gain an educational and comprehensive experience in the desin of steel structures. In this course design concepts, the basics of structural loading, load combination, design of steel structural members, and the use of current design specifications will be discussed. This course will also make you familiar with steel design aids/tools that are commonly used by practicing structural engineers. Course will not be confined to ASCE metric, AISC manual and ACI code, rather a comparative view of guidelines between the previously mentioned and that of the Japanese, USA and ambiance of concern. Texts: to be announced Steel Design Methods: ASD and LRFD Specification texts Steel Construction Manuals International Building Code (at least 2018) NOTE: a specific level of competence in skills from prerequisite is expected. It’s imperative that there are lab sessions towards practical and professional usage of structural software for civil engineering practices and analysis of crucial, critical, technical subjects. General Tools: SCIA Engineer SCIA-Concrete Section SAP 2000 Midas Civil Autodesk Revit RFEM as software alternatives Seismic Tools: OpenSees STKO (Scientific ToolKit for OpenSees) Build-X GID + OpenSees Grading: Homeworks 15% Quizzes 10% Lab Assignments 25% Midterm Exam 20% Final Exam 30% Lab Activities Role --> A. The goal of the lab portion of this course is to reinforce and progress with engineering analysis and design software. Students will learn how to build a model of an office building using this software including assigning loads to the structure, analysing the structure, and controlling the capacity of members. Students have to complete a series of hand calculations on a number of members in order to check the calculations done by respective software. B. Lab activities with emphasize the influence of steel design methods, specifications, manuals and building codes. Lab Activities --> 1- Typical Building Structural Systems 2- Introduction to the Design Project 3- Loads and Load Factors 4- Modeling the Geometry and Assigning Member Sections 5- Assigning Loads and Load Cases 6- Performing Analysis and Obtaining Analysis Results 7- Generating Design Sheets for Selected Elements 8- Hand Calculations to Check the Results 9. Earthquake Analysis The lab activities will be synchronized with the lectures. The time for each lab module will be announced in advance. Please make sure you bring your laptop to class on these days. At the end of each lab, students need to complete and sign a log sheet. ONLY the forms that are submitted at the end of the lab sessions will be accepted. A final report describing the process of modeling and design, selected outputs and hand calculations should be submitted. The written report is due before the week of final exams. Each student must submit an individual report. The required content of the report will be discussed later. Weights for lab grading --> Tutorial Model 0.15 Log Sheets 0.25 Final Report 0.3 Completeness and Correctness of Structure Model 0.30 Course Outline --> 1. Introduction 2. Steel Material and Mechanical Properties of Steel 3. Structural Shapes and Calculation of Section Properties 4. Design Philosophies and Limit States in Steel Structure Design (ASD and LRFD Methods) 5. Design of Members Subjected to Tensile Forces a. Yielding Limit State b. Effective Net Area and Rupture Limit State c. Block Shear Failure 6. Design of Members Subjected to Compressive Forces (Column Elements) a. Buckling and Euler Theory b. Slenderness Ratio and Design for Stability c. Axial Compressive Capacity d. Local Buckling 7. Design of Members Subjected to Bending (Beam Elements) a. Plastic Section Modulus and Plastic Moment b. Lateral Torsional Buckling (LTB) c. Beams with Non-Compact Sections 8. Design of Members Subjected to Combined Effects of Axial Forces and Bending Moments (Beam Column Elements) a. Interaction of Bending and Axial Forces b. Interaction Relationship c. Design for Stability and Moment Magnification Factors 9. Connections (bolted and welded) a. Basics of Bolted Connections b. Bolts Subjected to Tension c. Bolts Subjected to Shear and Tension Analogy of (a) through (c) for welded connections Prerequisite: General Physics I, Calculus III, ODE, Advance Structural Analysis. Advance Steel Structures This course examines advanced designs of structural steel buildings including consideration of torsion, lateral-torsional buckling, local buckling, plate girder design, connection design, framing systems for seismic design, nonlinear frame behavior, and principles of stability per the Effective Length, First-Order Analysis and Direct Analysis Method This course examines advanced design concepts for structural steel applicable to various types of steel structures; the primary code source applies to building design, which is supplemented by a strong theoretical background in steel behaviour applicable to bridges and non-typical structures. Upon completion of this class, students will be able to do the following: apply the unified code philosophy of ASD/LRFD to steel building design; describe the inelastic design philosophy; recognise sources of stability behaviour including geometric, material, and 2nd order effects; design steel members and frames based on code of standard practice for conditions such as torsion, slender elements, buckling, and combined stresses; design for frame stability using ELM, FM, or DM methods; recognize when the Seismic Provisions apply to building frames; categorize moment and braced frames as Special, Intermediate, or Ordinary per the Seismic Provisions; you will recognise the role of modern computer analysis in the job of a structural engineer and understand the steps necessary to perform an essential Quality Assurance peer review. Course Objectives --> --Differentiate between three design approaches: ASD, LRFD, and Inelastic Design. --Explain the unique purpose of code documents related to structural steel design including Steel Construction Manuals Specification for Structural Steel Buildings ANSI/ASTM 303 (and other ambiances) COSP Minimum Design Loads & Associated Criteria for Buildings & Other Structures --Describe the mechanics of steel as it relates to elastic and inelastic behaviour, flexural buckling, torsional buckling, flexural-torsional buckling, lateral torsional buckling, and local buckling. --Understand the probabilistic foundation of LRFD as a mean’s of designing economical and reliable structures, and how the code changed to a unified design philosophy for ASD/LRFD. --Design steel members per Specification Chapters B-H & J, including torsional, flexural-torsional, local and lateral-torsional buckling design considerations. --Describe the sources of nonlinear behaviour in members and frames, including the sources of material and geometric nonlinear effects. --Apply nonlinear effects in a steel analysis model. --Design steel frames so as to be structurally stable using the following methods: Effective Length First-Order Analysis Direct Analysis --Recognise the role of modern computer analysis in the job of a structural engineer and understand the steps necessary to perform an essential Quality Assurance peer review. Analyse open and closed steel members for torsion loading. --Design of I-shaped, doubly symmetric plate girders. --Distinguish between the three types of connection design options as described in the COSP. --Calculate the design strength of bolt, weld, and connecting element limit states. --Determine for beam-to-column shear and moment connections the applicable limit states. --Design simple and moment resisting connections using bolts and welds. --Explain how seismic risk is quantified by the International Building Code by using a Maximum Considered Earthquake ground motion (MCER) --Explain seismic building performance to owners & communities to manage expectations and provide options. --Understand how ductility and fuse members are used as the basis of steel seismic design per the code “Seismic Provisions for Steel Buildings”. --Describe the seismic design behaviour of moment and braced frames such as Special, Intermediate, and Ordinary per “Seismic Provisions for Steel Buildings”. Prerequisite Texts: May be different to prerequisite to treat specified objects and topics. Hold on to the following type texts from prerequisite for reference Steel Design Methods: ASD and LRFD Specification texts Steel Construction Manuals International Building Code (at least 2018) Necessary type texts: -Steel Construction Manuals -Specification for Structural Steel Buildings -ANSI/ASTM 303 (and other ambiances) -COSP -Minimum Design Loads & Associated Criteria for Buildings & Other Structures General Tools: MASTAN 2 SCIA Engineer SCIA-Concrete Section SAP 2000 Midas Civil Autodesk Revit RFEM as software alternatives Seismic Tools: OpenSees STKO (Scientific ToolKit for OpenSees) Build-X GID + OpenSees Homework --> 1. Will consist of problems from prerequisite as a refresher 2. Will have standard problems at the level of this course 3. You may be tasked to competently complete extensions of advance cases of some lab assignments from prerequisite in shorter time spans to keep you on your toes Quizzes --> 1. Will consist of problems from prerequisite as a refresher 2. Will have standard problems at the level of this course Lab Assignments --> Labs will come to treat each subject. Weights for lab grading --> Tutorial Model 0.15 Log Sheets 0.25 Final Report 0.3 Completeness and Correctness of Structure Model 0.30 There will still be emphasis holistic construction,but will emphasis the technicalities of the course. Grading --> Homeworks 15% Quizzes 10% Lab Assignments 25% Midterm Exam 20% Final Exam 30% Course Outline --> Introduction to Advanced Steel Design Member Stability: Part 1 Member Stability: Part 2 Frame Stability: Part 1 Frame Stability: Part 2 Frame Stability: Part 3 Fundamentals of Torsion Theory Design for Combined Stresses Plate Girders in Bending Plate Girders in Shear Shear and Moment Connection Design Steel Systems for Seismic Design NOTE: don’t take such course outline lightly because of the way it looks. Prerequisite: Steel Structures Cement Structures https://ocw.mit.edu/courses/civil-and-environmental-engineering/1-054-mechanics-and-design-of-concrete-structures-spring-2004/syllabus/ Prerequisite: Civil Engineering Materials Lab, Advance Structural Analysis Advanced Cement Structures This course will cover the basic prestressed concrete design. Principles of prestressing, constituent material, loading and allowable stresses, working and ultimate stress analysis and design, shear and torsion, deflections, prestress losses, continuous beams, composite beams, and compression members. Typical text: Naaman, A. E. “Prestressed Concrete Analysis and Design – Fundamental,” 2nd edition, Techno Press, 2004. Supplementary text: PCI Design Handbook, Sixth Edition, 2004 Nawy, Edward G. “Prestressed concrete : a fundamental approach”. Prentice Hall, c2010 Tools --> SCIA Concrete Section MIDAs Civil Grading: Homework 15% Quizzes 10% 2 Exams 40% Final 20% Project 15% Steps for achieving a high grade --> Don’t memorize procedures – there are too many Learn theory behind solution methods Do homework – exercise the brain Study for tests Ask questions when you don’t understand something Course Outline --> Chapter 1. Principles of Prestressing Introduction History of Prestressed Concrete Classification and Types of Prestressed Concrete Structures Pre-stressed Concrete Analysis Prestressed Concrete Design Prestressed Concrete versus Reinforced Concrete Chapter 2. Constituent Materials and Code Provisions Reinforcing Steel Prestressing Steel Concrete Chapter 3. The Philosophy of Design Strength Reduction Factors Overload Factors Chapter 4. Flexure: Working Stress Analysis and Design Loading Stages Useful Section Properties and Notations Sign Conventions Flexural Analysis - Mathematical Basis Use of Stress-Inequality Conditions for the Design of Section Properties Limiting the Eccentricity along the Span Some Preliminary Design Hints Cracking Moment Chapter 5. Flexure: Ultimate Strength Analysis and Design Load-Deflection Response Flexural Types of Failure Analysis of the Section at Ultimate Concept of Reinforcement Index Limiting Values of the Reinforcement Index Satisfying Ultimate Strength Requirements Design for Ultimate Strength Indeterminate Structures and Composite Elements - Ultimate Strength Chapter 6. Design for Shear and Torsion Introduction Reinforced Versus Prestressed Concrete – Shear Diagonal Tension in Uncracked Sections Shear Stresses in Uncracked Sections Shear Cracking Behaviour Shear Reinforcement after Cracking Design for Shear Torsion Torsional Stresses Post-Cracking Torsional Resistance Design for Pure Torsion Combined Shear and Torsion Chapter 7. Deflections Background Information Short-Term Deflections Long-Term Deflections (Simplified Method) Long-Term Deflections (Incremental Time-Step Method) Deflection Limitations Deflection Control Chapter 10. Continuous Beams and Indeterminate Structures Background Information Secondary Moments and Zero-Load C Line Linear Transformation Properties of Concordant Tendons Equivalent Loads Working Stress Analysis and Design Ultimate Strength Analysis Chapter 13. Analysis and Design of Compression Members Types of Compression Members and Advantages Behaviour of Columns Analysis of Short Columns Slender Columns ACI Code and Other Design Considerations Chapter 8. Prestress Losses Total Losses in Pretensioned Members Total Losses in Post-Tensioned Members Methods for Estimating Prestress Losses Elastic Shortening Relaxation Shrinkage Creep Friction Anchorage Set Prerequisites: Cement Structures Applied Hydraulics Lectures: 2 days per week, 2 hours per day Labs: 1 day per week, 2 hours per day Recommended Textbook: Open-Channel Flow by M. H. Chaudhry, Springer Tools --> EPANET and/or WDNetXL Note: such tools usage will not be restricted to topics where they are specifically stated. Tools will be applied on many occasions throughout course and labs. Grading --> Two Exams 40% Homework (Roughly one every week) 20% Labs: Modelling, Design(s), Computations & Hands-on activities 30% Punctual arrival In-class quizzes and participation 10% Course Objectives --> Setup equations to analyse small piping systems that include branches, parallel pipes, loops and/or reservoirs. Students will learn how to apply the fundamental concepts of Energy, Momentum and Continuity will be discussed in solving practical design problems. Many problems encountered will be mirrored by practical understanding of energy and energy losses, namely, head and head loss that drive the flow of water, with various methods of estimating head loss and applied with computations to select pipe sizes, and analyse the performance of simple compound systems will be covered. Energy, momentum and continuity modelling can be introduced alongside various topics before formal engagement at designated schedule in course schedule. Nonlinear relationship between head loss and flow. Determine flow distribution in simple networks using the Hardy Cross Method. Applying the Newton-Raphson method (and possibly more advance methods). Employing EPAnet and/or WDNetXL, analyse and design small piping networks for flow, pressure distribution and pump requirements. SystemModeler to be used alongside EPAnet and/or WDNetXL. Develop lumped operating characteristics for series and parallel pumps. Identify the basic elements of your network design that are specifically controlled by federal, state and/or local regulations or codes Design pump placement to prevent cavitation. Design open-channel systems based on uniform flow analysis. Design open-channel transitions using energy concepts. Design a sequence of uniform channels to satisfy a client’s stated objectives; the channels differ in bottom slope or width and may incorporate transitions produced by rapid changes in bottom elevation or width. Explain the importance of professional licensure in the context of responsibility for your design. Write technical memos that report the results of design/ analysis and employ appendices to provide sufficient information to check and confirm the results. Recognise the importance of professional and ethical responsibilities. Labs with software (SystemModeler, EPAnet and/or WDNetXL and others) for modelling design(s) and simulations to accompany hands-on activities. LABS --> NOTE: labs will be implemented at appropriate times in course. Concerning labs with hands-on activities (in a manner with the most coherent, tangible, fluid and sustainable sequencing among each other and with lectures). FEATURES: A. Pump chart/pump curves and performance will be incorporated in other labs and hands-on activities when constructive B. NPSH, NPSHA and NPSHR will be incorporated in other labs and hands-on activities when constructive) C. In built models different experiments will make use out of components such as mechanical lever and/or solenoid valves (with control), pressure control valves, pumps, meters, (digital) sensors & gauges towards geometrical representation of data. Surge suppressors, hydraulic ram, hydraulic jump chamber towards calculations. D. Experiments concerning pumps in parallel and series. Will be compared with different types of software (SystemModeler/Modelica, EPAnet and/or WDNetXL). E. Experiments concerning energy losses in pipes, energy losses in bends, laminar flow visualization. Will be compared with different types of software (SystemModeler/Modelica, EPAnet and/or WDNetXL). F. Onsite analysis of various industrial systems compared to software models. Requires assistance from Utilities providers. G. Centrifugal pumps. Will begin with characteristic features and mathematical modelling for such based on physics. Efficiency modelling and efficiency curves. Will then acquire ideal characteristics (curves and so forth) with different types of software. Then, use of Centrifugal pumps (WASA assistance) with data acquisition characteristics, analysis and efficiency modelling. H. Hydraulic jump chamber. Conservation equations and verifying equations of fluid flow: https://luk.staff.ugm.ac.id/ochannel/loncatair/labjump.html Kim, Y. et al (2015). Hydraulic Jump and Energy Dissipation with Sluice Gate. Water, 7, 5115 - 5133. I. Water hammer. All models built concern data retrieval as means compare among such built models. Development of rules on how quickly valves can be opened or closed. Exhibiting phenomena by by built pipeline model. To observe the phenomenon of water hammer in a long copper piping system, and to quantify wave speed, potential surge, line pack, and attenuation. Then design and build models to avoid such water hammer condition. Note: a built model with mechanical valve turned off slowly also a means of water hammer avoidance (must demonstrate along with other methods). Wave celerity determination and factors that determine celerity. Note: use of surge suppressors in comparative built models; will compare data curves of built models with designs to treat water hammer without surge suppressors, versus built models with designs to treat water hammer with surge suppressors, versus elementary built models that don’t consider water hammer. J. Hydraulic ram pump. Model and design hydraulic ram pumps. 1. Guides for modelling and experimentation: Hussin, N. S. M . et al. Design and Analysis of Hydraulic Ram Water Pumping System. IOP Conf. Series: Journal of Physics: Conf. Series 908 (2017) 012052 2. Will also pursue replication of simulation curves from the following: Najm, H. N., Azoury, P. H., & Piasecki, M. (1999). Hydraulic Ram Analysis: A New Look at an Old Problem. Proceedings of the Institution of Mechanical Engineers, Part A: Journal of Power and Energy, 213(2), pages 127–141 Carvalho, Mario & Diniz, Alberto & Neves, Fernando. (2011). Numerical Model for a Hydraulic Ram Pump. 5. 733-746. To be develop simulations in Wolfram SystemModeler or Modelica to compare Interested in characteristic curves for forces on various valves, pressure at various valves, pressure from source, pressure at destination, water rate accumulation at destination, etc. etc. Modelling the influence of gravity may be required depending on setup. 3. Will like a field trip to WASA to observe a hydraulic ram pump (if any is present). Observe the various parameters being monitored with corresponding time varying curves; data and printouts appreciated, to compare with priors. 4. Will build one or two hydraulic ram pumps in function and operate them for constructive means of data gathering and analysis. However, will additionally have pressure sensors at different points, say at different valves, at incline point on decline, and at destination. Will also determine work required to reach destination. To as well the influence of gravity on rate rates at different points. Will also pursue determination of the rate of volume delivered. Determination of the volumetric efficiency, namely, the ratio of the volume water delivered to the target versus volume of water flowing through the waste pipe; this is equivalent to the ratio of the target height to the reservoir height. Reference: Asvapoositkul, W. et al. Determination of Hydraulic Ram Pump Performance: Experimental Results. Advances in Civil Engineering Volume 2019, Article ID 9702183, 11 pages Course Lecturing Schedule --> Applied Hydrostatics Overview of the fundamental concepts of energy, momentum and continuity for application Piping Problems: Manning’s Equation Energy in Open Channels: Uniform flow analysis Hydraulic Jump; Critical Flow Alternate forms for energy losses; EPANET and/or WDNetXL Simple Pipe Systems – ad hoc solutions Simple Pipe Systems – EPANET and/or WDNetXL solutions Pipe Network Analysis (1 week) Pipe System Design: problem definition & constraints Pipe System Design Turbomachinery: Radial flow pumps Pipe System Design with Pumps NPSH and Cavitation Energy Concepts: Application of Energy Equation Application of Energy Equation Use of Energy Equation in Transitions (Design) Momentum Concepts Nonuniform Gradually Varied Flow Controls & Profile Synthesis Profile Computations Gradually Varied Flow Design (2 weeks) Profile Computations: standard step method Prerequisites: ODE, Numerical Analysis, Calculus III Co-requisite: Geographic Information Systems for Civil Engineers Geographic Information Systems for Civil Engineers: The field of Geographic Information Systems, GIS, is concerned with the description, analysis, and management of geographic information. This course offers an introduction to methods of managing and processing geographic information. Emphasis will be placed on the nature of geographic information, data models and structures for geographic information, geographic data input, data manipulation and data storage, spatial analytic and modelling techniques, and error analysis. The course is made of two components: lectures and labs. In the lectures, the conceptual elements of the above topics will be discussed. The labs are designed in such a way that students will gain first-hand experience in data input, data management, data analyses, and result presentation in a geographical information system. Concerning Civil Engineering the use of GIS will be focused on developmental environments, various infrastructure, commute network analysis and urban development.. Appeases the technology requirement. Upper level standing at least recommended. The basic objectives of this course for students are: 1. To understand the basic structures, concepts, and theories of GIS 2. To gain a hand-on experience with a variety of GIS operations Typical Texts: Longley P.A., M.F. Goodchild, D.J. Maguire, D.W. Rhind, 2011.Geographic Information Systems and Science. John Wiley and Sons Chang, K.T., 2012. Introduction to Geographic Information Systems (Sixth Edition). McGraw Hill, New York de Smith, M., Goodchild, M., Longley, P., 2013. Geospatial Analysis: A Comprehensive Guide (www.spatialanalysisonline.com) Tools --> GIS of your choosing; students will be debriefed on operational requirements Mathematica Google Earth Google Maps Resources: https://www.google.com/earth/outreach/learn/ support.google.com/maps/answer/144349 There are highly established freeware GIS tools for use. Premier such available are SAGA GIS, ILWIS, MapWindow GIS, uDig, GRASS GIS and others; check Goody bag post. Note: GRASS GIS to be preference. Major priorities are sustainable skills in logistics, data management, accessibility & integration of data sets for project development and exhibition. Project(s) to have considerable life cycles with future use. Additionally, Wolfram Mathematica tools, Google Earth and Google Maps can possibly coexist or be a substitute in such a instruction environment, primarily for rapid data visualisation. Course is concerned with the ability to develop meaningful professional data analysis and visualisation of sustainable value to whatever specified target audience. Unique talent development among such tools are encouraged, under the condition that the interests or demand of the target audience is appeased, of high quality. Some highly capable students will be able to develop projects with various systems, while for others finding an environment that suites them is key (highly dependent on what they comprehend and the effort they give). Mathematica has the computational prowess among the rest, but isn’t visually savvy or accommodating as the rest. For those with high preference for Mathematica the following search topics in Wolfram Documentation and topics from Wolfram Blog will prove quite fruitful Earth Sciences: Data and Computation Geographic Data & Entities Geospatial Formats Geodesy Cloud Execution Metadata Create Instant APIs https://community.wolfram.com/content?curTag=geographic%20information%20system It’s recommended that those who choose such Mathematica path are those who have successfully completed the Data Programming with Mathematica course to a high degree, or of their own business have deployed Mathematica successfully with various projects. It takes a bit of skill with methods emanating from the above Mathematica (search) topics; not the favouritism propaganda you have acquired. Class Presentation --> Students need to review a journal article (or multiple articles) and give a presentation in the class. The article or articles can relate to GIS concepts, theories, or applications. An article in your discipline is preferred for you to review, for the reason that it would help you to think how to apply GIS in your work in the future. To present your reviewed article, you need to prepare five to eight slides in the format of PowerPoint, which would take approximately five to six minutes to present. In your slides, one of them would be how GIS is helpful in the article. You will have to give a small demonstration of some partial development for your project that substantially relates to your goals with whatever choice of tool employed. Followed by some substantial development (already done) with a GIS or other tool, or combination. You will have two or three minutes to answer the questions raised by the audience. Grading --> Lab Exercises 30% Exam I 25% Exam II 25% Civil Engineering Relevant GIS Term Project 20% Labs --> There are two components for labs: 1. Having GRASS GIS as preference concerns standard developments with course progression. 2. Extracurricular activities with Addons for GRASS GIS. Primarily, there must be strong development for a specific topic in (1) in order to commence with a respective Addons activity -- https://grass.osgeo.org/grass82/manuals/addons// Multicriteria decision decision analysis must be one topic for Addons extracurricular activities. An example: Massei, G., et al (2014). Decision Support Systems for Environmental Management: A Case Study on Wastewater from Agriculture, Journal of Environmental Management, Volume 146, Pages 491-504 However, PROMETHEE is not our only interest, and multiple MCDA addons will be pursued. Course Outline --> WEEK 1 Course Overview GIS Overview The Nature of Geographic Information WEEK 2 Data Representation Measuring Systems: Location – Coordinate Systems Data Representation Measuring Systems: Location – Coordinate Systems (Continue) WEEK 3 Data Representation Measuring Systems: Location – Coordinate Transformation Data Representation Measuring Systems: Topology Measuring Systems: Attributes WEEK 4 Data Representation Spatial Data Models: Introduction to spatial data models Spatial Data Models: Raster data models Data Representation Spatial Data Models: Relational Data Models Spatial Data Models: Vector Data Models (I) WEEK 5 Data Representation Spatial Data Models: Vector Data Models (II) Data Representation Spatial Data Models: TIN Summary of Spatial Data Models: Raster, Vector, TIN WEEK 6 Data Representation Linking attribute data with spatial data Recent Development of Data models WEEK 7 GIS Database Creation and Maintenance (I) Data Input & Editing GIS Database Creation and Maintenance (II) DBMS and its use in GIS WEEK 8 Review for Exam 1 Exam 1 WEEK 9 GIS Database Creation and Maintenance (III) Metadata / Database creation Guidelines / NSDI Data Analysis Measurement & Connectivity WEEK 10 Data Analysis Interpolation WEEK 11 Data Analysis Digital Terrain Analysis Data Analysis: Statistical Operations & Point Pattern Analysis WEEK 12 Data Analysis Classification Data Analysis GIS-based Modelling and Spatial Overlay (I) WEEK 13 Data Analysis GIS-based Modelling and Spatial Overlay (II) Data Analysis Summary Uncertainty WEEK 14 Geo-representation, Geo-presentation, and GeoVisualization GIS Applications WEEK 15 Student Presentations Student Presentations WEEK 16 Review for Exam Exam II Prerequisite: Maturity, Junior Standing. Co-requisite: Applied Hydraulics Hydraulics Engineering Design This course is designed to present these Academic/Learning Goals -Principles and methods of hydraulic engineering design -Use of computer models to support hydraulic engineering design -Development of a hydraulic engineering design project Proficiency with computers and familiarity with Excel is expected. There will be some computer assignments using HEC and other computer programs, and GIS usage as well. Typical Text: Walski, T. et al. (2013). Computer Applications in Hydraulic Engineering. Bentley Institute Press. 420 Pages Such text is quite expensive, namely, process can approach $275. Elsewhere, around $6 (but I’m not going to tell you where). Will try to get around that. Additionally, there’s no commitment to any Bentley software in this course. Tools --> -GIS (GRASS GIS with addons; MCDA will be one of many activities) -EPANET, WDNetXL -HEC-RAS, iRIC -HEC-HMS, SWMM (from the EPA) -PRMS (Precipitation Runoff Modeling System), SWAT (http://swat.tamu.edu/) -MODSIM + CSUDP -MODFOW, MT3DMS -USDA NRCS (can be substitutes): SITES, WinDAM C, DrainMod, EFH 2, EFT, ND-Drain, Structural Design, Win TR-20, Win TR-55 Lecture Learning --> Lectures supplemented with outside reading and homework Labs --> Labs will concern applying theory and study towards use of different software for various software. Such skills development can possibly be used to develop a major team design project. Major Design Project --> There will be a major design project carried out within a project team for which an oral and written report will be presented at the end of the semester. Carried out in collaboration with a group of 3 or 4 students. Mandatory use of skills developed in labs should be exhibited in reports and oral presentations. Your design projects should not be confined to exact replication of lab activities. Exams --> There will be 3 in-class exams. Will have three 75 minute in-class examinations. The civil engineering concerns many obligations and optimal usage of time; hence each examination will permit you to use 2 loose leaf review sheets. Missed examinations may be made up only if the reason for missing was illness or some other emergency. There will be no Final Exam. Grading: Homework 15% Labs 35% 3 Exams 30% Major Team Design Project 20% Weekly Topics --> 1. Basic Hydraulics (EPANET/WDNetXL) 2. Basic Hydrology: Rainfall (HEC-HMS) 3. Basic Hydrology: Runoff (HEC-HMS) 4. Curb Gutter and Inlet Design (will make use of chosen software from list) 5. Storm Sewer Design (will make use of chosen software from list) 6. Culvert Design Culvert (will make use of chosen software from list) 7. Using GIS in Hydraulic Design ArcGIS (Or alternative) 8. Project Status, etc. etc. 9. Recap or review, etc. ,etc. 10. Water Surface Profiles (Channels) (HEC-RAS) 11. Water Surface Profiles (Bridges) (HEC-RAS) 12. Detention Pond Design (HEC-HMS) 13. Detention Pond Design for WQ 14. Project Status, etc., etc. 15. Design Studio 16. Design Presentations Prerequisite: Applied Hydraulics Geotechnical Engineering This course is concerns engineering problems in which the material is soil AND rock (soil/rock mechanics, geotechnical engineering). Technically speaking, soil mechanics consists of the study of soil properties and soil behaviour, whereas foundation engineering is the design of foundations on soils and rock. In this course, we will focus on understanding some of the basic principles of soil properties with some applications to earth structures. The principles given in this course are also applicable to rock mechanics. This course will run unusually longer than typical course during a term. Up to an additional 3 weeks will be required. I am interested in having you develop an appreciation for the significance of natural material (soil and rock) in civil engineering applications. Course will: 1. Introduce you to the discipline of geotechnical engineering and be your steppingstone into this area. 2. Help you recognize problems you will encounter in your engineering practice that are related to geotechnical engineering. At that point, if geotechnical engineering is not your specialty, STOP and seek assistance from a geotechnical engineer. 3. Help you answer some questions that might be asked on your Professional Engineer (PE) exam. Typical Texts: Foundation Engineering Handbook, edited by Hsai-Yang Fang, Van Nostrand Principles of Foundation Engineering, B.M. Das, PWS-Kent, Necessary Resources --> Geological Profiles for areas of interest International Atomic Energy Agency (2022). Methodologies for Seismic Soil–Structure Interaction Analysis in the Design and Assessment of Nuclear Installations, TECDOC Series, IAEA, Vienna Note: highly serviceable regardless of preference to nuclear installations Article references --> Sousa, Luís & Chapman, & Miranda, Tiago. (2010). Deep Rock Foundations of Skyscrapers. Soils and Rocks. 33. Poulos, H.G. Tall Building Foundations: Design Methods and Applications. Innov. Infrastruct. Solut. 1, 10 (2016) Tools --> This may be one of the courses where software will be costly, and may be unavoidable. 1. A simple straightforward Geotechnical Software package by the name of GEOPRO 5.0 (by DataSurge, Bradford, MA). In most cases this software will be used for verification/check of hand calculations only. The software is up and running in the PC lab. You need to go in and select the specific application as the general icon is not active. This package is capable of carrying out a variety of analyses including those that are highly relevant to this course: a. Stress distribution – Vertical stress below surface & lateral stress due to surcharge. b. Settlement Analyses - consolidation, immediate settlement, time rate settlement c. Foundation Design - bearing capacity d. Retaining Structures - earth pressures, cantilever sheet pile wall (clay and sand), anchored sheet pile wall 2. LimitState geo version 3.0 by Limitstate Ltd 3. DEEPXCAV 2011, Deep Excavation Engineering Programme 4. PLAXIS – Geotechnical Finite Element Program Concerning such software confirming the correct models and formula by comparing with software results would be appreciated. Nevertheless, in luck, there may be some leeway for certain topics with reduced cost, namely: Optum (https://optumce.com/academic/) ZSoil (https://www.zsoil.com) SPECFEM 3D Geotech (will need a mesher) ADONIS Code Aster DUNE (https://www.dune-project.org) MOOSE (Multiphysics Object Oriented Simulation Environment) Cast3m (http://www-cast3m.cea.fr) ANSYS OpenFoam Such software will serve well towards FEM/FEA and other things (WHICH WILL BE DONE), but they are not as topic specific as those expensive products. Note: some software and texts from prior civil engineering course may come back to prove useful. Weekly Case Studies --> About once a week a student team will be assigned to present a current construction case study highlighting the geotechnical aspects of a project. The team will have to select the project from “Engineering News Record (ENR)”, Civil Engineering, Tunnels and Tunnelling, etc. or an ongoing construction project in the area. Geological profiling is mandatory to confirm that methods applied in project of study are consistent with ground strata, say, possible sedimentation, geomorphology, igneous or metamorphic profile, possibly hydrology, etc. Use of a GIS to augment geological profile can be interesting if desired. Presentation to include 10 – 15 slides summarizing the geological profile and geotechnical aspects of the project and how they relate to materials presented in course. All slides shall be numbered. An addition 5 – 7 slides will be allowed for geological profiling; figures and tables will not be considered in the limit of slides. The presentation will be allotted 10 – 15 minutes for presentation and 5 minutes for discussion. The presentation must at least include the following elements: Introduction Geological Profile Key Geotechnical Elements/Issues Plan View & Cross-Section showing Soil/Rockbed Layers Summary of Geotechnical Properties Summary of Challenges and Lessons Learned Wil have a 4 – 8 page report summarizing the case study is to be submitted at the time of presentation. The report shall have no more than ½ page of references. Figures and tables to be present in both report and the presentation. I will not consider figures and tables as part of the 8 – page maximum count. The team may consult with the instructor prior to making a presentation. The report and presentation should be of the highest professional quality. A group usually consists of 6-7 students. The report (pdf format) and presentation (power point) must be posted electronically on appropriate network by 12 am before the presentation is delivered (late submittal will receive a grade of zero). Labs --> COMPONENT A. Familiarization with the ASTM Standard Methods of soil analysis commonly used by the Geotechnical Engineering community (experiments and studies will be done in a constructive and economic/resources saving order, hence not necessarily as listed) Water content determination Specific gravity Grain size distribution Atterberg limits Liquid limit by cone penetration Standard Proctor test Permeability test Hydraulic Conductivity Consolidation test Rotary pressure sounding Direct Shear test or Share Vane test Dilatancy Load test (static, dynamic, statnamic) R-value COMPONENT B. Rock Strata Some may be lab-based, while others will require field activities. The following provides a general idea of what’s to be expected for labs: U.S. Army Corps of Engineers (1994). Rock Foundations. Engineer Manual 1110-1-2908 https://www.publications.usace.army.mil/Portals/76/Publications/EngineerManuals/EM_1110-1-2908.pdf COMPONENT C. Cemented Sand Collins, B. D. and Sitar, N. Geotechnical Properties of Cemented Sands in Steep slopes. Journal of Geotechnical and Geoenvironmental Engineering. Volume 135 Issue 10, October 2009 Vranna, A. and Tika, T. Undrained Monotonic and Cyclic Response of Weakly Cemented Sand. Journal of Geotechnical and Geoenvironmental Engineering. Volume 146 Issue 5, May 2020 Note: activities in components B and C are not successors to component A; scheduling of activities will mix among A, B and C. Collective Projects --> Collective projects concern analytical development leading to computer programmes. Will be a total class effort assisting each other with development. Aspects will be reviewed in course, where class will make use of external time for development. The following computer programmes can be pursued where analysis and logistics will be provided towards developmen tby student groups: 1. Simulation of shallow foundation load test 2. Static capacity of shallow foundations 3. Sheet pile wall analysis (cantilever and/or anchored) 4. Interpretation of a shallow foundation load test 5. Beam on elastic foundations 6. Shallow foundation settlement analysis (immediate and/or time dependent) 7. Scoops3D implementation Reid, M. E., Christia, S. B., Brien and D. L. and Henderson, S. T. (2015). Scoops3D—Software to Analyze Three-Dimensional Slope Stability Throughout a Digital Landscape. U.S. Geological Survey, Series 14-A1 First will geologically profile regions of various elevation characteristics, along with soil and bedrck profile. Note: if weather influences are consderable, then hopefully such can be integrated. 8. OpenSHA implementation Supporting literature found at: https://opensha.org 9. International Atomic Energy Agency (2022). Methodologies for Seismic Soil–Structure Interaction Analysis in the Design and Assessment of Nuclear Installations, TECDOC Series, IAEA, Vienna (will generalise to habitats and surroundings of interest) Accompanying programme must be analytical development report in pdf. I also expect you to make use of mathematical pellets in your writings. To have at least proper heading, authors, participants, table of contents, abstract, list of figures, introduction, introduction, body sections with figures and tables, conclusion, references. Class to should be mature enough to be functional, competent and innovative. Attempts to hustle or rip-off or plagiarize any pre-existing programmes will result in brutal consequences; cheating, plagiarism and so forth can leading to exercising of the most severe academic and institution consequences. 10. The following tools can be used for intellegence on sesimic map codes, and to compare with government guidelines for assurance: ASCE 7: https://asce7hazardtool.online ATC Hazards by location: https://hazards.atcouncil.org OSHPD Seismic Design Maps: https://seismicmaps.org Exams --> The exams are not a mere repetition of the homework. You will be asked to apply material you have learned through class discussions, reading the textbook and the case history of the week. You should come fully prepared for each exam and quiz. The completion of the exams and quizzes will require writing implements, a calculator, and drawing tools such as a bow compass, protractor, and graded straight edge. Students may not pick up the assignments of their friends, as this violates University regulations on privacy. Quizzes --> Each week there will be a quiz. Quizzes will not follow a sequential build with problems or questions in likeness to course development; difficulty of problems or question will be given in a random manner. The quizzes are open book with a duration of 5-15 min. They will consist of multiple-choice questions regarding topics from recent lectures and assigned reading material. The lowest 4 quizzes scores will not be considered. Please read the assigned reading materials and ask questions if you don’t understand concepts to prepare for the quizzes. This is to accommodate up to 4 missed quizzes for any number of and so forth. There will be no makeup of these quizzes. Solutions will be promptly posted at the end of a given class session. Midterms --> There will be two 80-minute long midterm exams during the semester. The exams are open book and closed note. Final exam --> There will be a 3-hour long final exam. The final exam is also open book and closed note. In the exams you will be asked both qualitative and quantitative questions. Grading Homework and Computer Exercises 25% Labs 25% Case Study & Collective Project 15% Quizzes and Exams 35% Course Outline --> Week 1. Foundation perspective, classification and types Week 2-3. Site Exploration Methods of site investigations Soil boring and sampling Determination of soil properties from site tests Geophysical exploration Laboratory test and geotechnical report Week 4-5. Bearing Capacity of Shallow Foundations Failure patterns of shallow foundations. Terzaghi's bearing capacity equation for shallow foundations General Capacity equation and water table effect Bearing capacity of eccentrically loaded foundations Bearing capacity for footings on layered soil Bearing capacity from SPT and CPT Week 6. Settlement of shallow foundations Immediate for flexible and rigid footings Immediate settlement by Schmertmann method Immediate settlement of eccentrically loaded foundations Consolidation settlement Differential settlement. Week 7-8. Design of Spread footings Square footings Rectangular footings Week 9. Design of Rectangular Combined footing Week 10. Design of Mat Foundations Bearing capacity of mat foundation Differential settlement of mats Structural design of mat foundations Conventional rigid method Week 11-15. Pile Foundations Steel, concrete, timber and composite piles Estimating pile length Load transfer mechanism Equations for estimating pile capacity Laterally loaded piles Immediate settlement under piles Pile groups: efficiency, load bearing, elastic settlement, and consolidation settlement Design of pile caps: Circulage method Week 16 Geosynthetic Reinforcements --> -Geotechnik (Editor) and Johnson< A (Translator). (2001). Recommendations for Design and Analysis of Earth Structures Using Geosynthetic Reinforcements -EBGEO. Ernst & Sohn. 338 pages -Han J., Chen J., Hong Z. (2008) Geosynthetic Reinforcement for Riverside Slope Stability of Levees Due to Rapid Drawdown. In: Liu H., Deng A., Chu J. (eds) Geotechnical Engineering for Disaster Mitigation and Rehabilitation. Springer, Berlin, Heidelberg Week 17 Liquefaction of soil and sand (find strong resources) Sewers to float upward Catastrophes with high rise buildings Broken roads Uplifted manholes Will also have a DIY liquefaction demonstration May also go to the beach and create quicksand Flowside --> Wanatowski D., Chu J., Lo R.S.C. (2008) Types of Flowslide Failures and Possible Failure Mechanisms. In: Liu H., Deng A., Chu J. (eds) Geotechnical Engineering for Disaster Mitigation and Rehabilitation. Springer, Berlin, Heidelberg Resolutions for Liquefaction and Flowside Week 18-19 Used to resolve loose ends, or labs and finishing collective project. Prerequisites: Numerical analysis, Civil Engineering Materials Lab. Students are expected to have successfully completed a first course in Steel structures, and a first course in Cement Structures. Highway Engineering Explores the planning, design, construction, and characteristics of highways and city streets, including layout, traffic requirements, safety and control, drainage, sub-grade structure, base courses, and surface pavements. Problems to be solved include geometric design, traffic volume, channelization, and hydrology. Lab projects involve roadway designing. Typical Text: Highway Engineering by Oglebsy. Wiley & Sons NOTE: course will approach will not concern any freshmen, sophomore and junior maturity. Hence, other textbooks and sources will likely accommodate above text. Reference Texts and Sources: 1. Highway Engineering Handbook, K. Woods, McGraw Hill, 1st Edition 2. Traffic Engineers Handbook, H. Evans 3. Highway Engineering, Ritter & Paquette, Ronald Press 4. Route Surveying, C. F. Meyer, International Textbook Company 5. Data Book for Civil Engineers, E. E. Seelye, J. Wiley & Sons 6. Open Channel Hydraulics, V. T. Chow, McGraw Hill 7. A Policy of Geometric Design of Highways and Streets, American Association of State Highway and Transportation Officials (AASHTO) 1984)…or appropriate standards for whatever ambiance 8. Principles of Pavement Design, E. Yoder, J. Wiley & Sons 9. Standard Specifications for Road and Bridge Construction, NJ State Department of Transportation (1989) 10. Standard Specifications for Highway Bridges, 10th Edition, American Association of State Highway and Transportation Officials (T6310.A6)…or appropriate standards for whatever ambiance NOTE: the given references can serve well towards lectures, labs and independent projects. Objectives: Demonstrate highway terminology Structural codes, construction codes and specifications. Demonstrate the design requirements for roads and highways Demonstrate the construction and inspection requirements of roads Demonstrate safety, traffic analyses and vehicle abilities in the design of roads Demonstrate drainage design for roads. Demonstrate the relationship between surveying, and highway design and layout Laboratory --> Laboratories will be used for lab design projects. Slides and films will be used for stimulating discussion of highway. Two major lab projects will be undertaken 1. Parking Lot Layout of property lines, fencing, curb, aprons, ingress, and egress, parking stalls, details of curb, pavement, etc. Students may be expected to produce this drawing using particular software and drafting computer techniques. 2. Highway Design The reconstruction and redesign of a major traffic artery requiring calculations for width of roadway, intersections, drainage, pavement, alignment and quantity estimates. A set of drawings will be prepared. Students may be expected to produce drawings using different types of software and computer drafting techniques. A written report on each project will be required. Independent Projects--> There will extensive structural analysis and construction development for the following highway features: Intersections Flyovers Interchanges Projects will involve extensive intelligence and skills from Advance Structural Analysis, Advance Steel Structures, and advance Cement Structures. Students will choose existing examples across the world today (for such three features). Students will scout data for dimensional parameters (some critical features will be much more technical than others), design features and components of construction. One of the first things to be implemented will use of a GIS (GRASS GIS) for data in topography, coordinates ranges and possible setting with respect to rural or urban areas. Google Earth features and Google Maps features can also augment project. Relation to routes are also expected. Based on their data retrieval students will develop such highway features from bottom based on experience and competence from the prerequisites of this course; will be harshly graded for lack of detail, mechanics, coherency, analyses and computation from such prerequisites. However, I will not necessarily be harsh with asphalt professional and pavement design because such two constructions are new to you. Projects will have two components, namely a research report and presentation. References are required in reports and presentations. Exams --> 2 Tests and a Final Examination will be given. Objective questions (closed book) and analytical problems (open book) are given. Each test is approximately 2 hours in duration. Grading --> Homework, class participation and interest, and attendance 10% Laboratory Projects, including written report and oral presentation 20% Independent projects 20% 2 Tests 30% Final Examination 20% Course Outline --> UNIT I (3 Weeks): INTRODUCTION; TERMINOLOGY; HIGHWAY PLANNING AND ECONOMY; PARKING 1. List and describe the major areas of study and analysis for highway development. 2. List and describe the different types of governmental highway systems, and give real examples of each. 3. Discuss the Interstate Highway system. 4. List and describe the highway types. 5. List and describe several highway organizations and associations. 6. List and describe the various classes of data that must be complied in highway planning. 7. List and describe the costs to be included in highway economy studies. 8. Compute motor vehicle operating costs to the highway user. 9. Describe the requirements for a small shopping centre parking lot as to space dimensions and angles, driveway widths and turning radii. May also include super malls, campuses, high rise housing, etc. UNIT II (3 Weeks): DRIVER, VEHICLE AND ROAD CHARACTERISTICS; HIGHWAY DESIGN 1. Define “perception time” and “reaction time,” and give recommended design values. 2. List and differentiate between the four methods of estimating future traffic volumes 3. Applying the methods of estimating future traffic volumes. 4. Define and calculate service volumes of highways considering the effects of sight distance, obstructions, grades, land widths and commercial vehicles. 5. Using the “benefit cost ratio” method, determine if it is economically feasible to construct a particular highway alignment. 6. List the factors that reduce highway capacity. 7. Compute safe stopping and passing distances for level roadways and for vertical curves in crest or sag. 8. Compute super-elevation requirements for horizontal curves considering design speed, friction and radius in the calculations. Describe the meaning of “runout” as it applies to super-elevation of horizontal curves. 9. Compute stations and elevations along horizontal and vertical curves. 10. Sketch typical cross sections and profiles of highways. 11. List the values of typical lane widths, grades and design speeds. 12. Determine the minimum vertical curve length to provide safe stopping sight distance and safe passing sight distance. 13. Determine the appropriate speed degree of curvature and/or radius for horizontal curves UNIT III (1 Week): TRAFFIC ENGINEERING 1. Describe various channelizing devices. 2. List and describe the general types of intersections at grade and grade separated, and list the advantages and disadvantages of each. 3. Draw a space-time diagram between two intersections given the traffic signal cycles. 4. Calculate the ideal distance between the intersections given the space-time diagram and the roadway design speed. 5. Calculate the ideal speed between two intersections given the distance and traffic signal cycles. 6. State the advantages and disadvantages of traffic signals. 7. Define traffic actuated and fixed time signals. 8. Describe the general contents of the “Manual of Uniform Traffic Control Devices.” 9. List and describe the various types of traffic control UNIT IV (3 Weeks): HIGHWAY DRAINAGE 1. Compute the water runoff from a drainage area, given the storm frequency, character and slope of ground surface using available charts and graphs and the “rational formula”: i.e. (Q = Aci). 2. Explain the meaning of each parameter in the “rational formula.” 3. Design a circular pipe, trapezoidal culvert and rectangular culvert to efficiently carry a particular water flow, under free flow conditions, using available charts and graphs and the Manning Formula. 4. Analyse a given storm drain system for various flow parameters, such as velocity and flow using the Manning Formula. 5. Set-up in tabular form the necessary chart for completely analysing or designing a simple storm drain system. 6. List and describe various drainage structures such as manholes, inlets, end-walls and headwalls. 7. Classify sub-critical and supercritical flow. UNIT V (2 Weeks): HIGHWAY SUB-GRADES, BASE COURSES, AND SURFACE COURSES 1. Sketch a cross section of a roadway including a description of “surface courses,” “base course,” “sub-base” and “sub-grade.” 2. List and describe the soil characteristics which influence the quality of sub-grades under highway pavements. 3. Describe the different types of base courses. 4. Describe the correct procedures for constructing base courses. 5. Contrast and compare rigid and flexible pavements. 6. List and/or define the methods for the design of flexible pavements. 7. Design a flexible base pavement using the AASHO Method or whatever international counterpart). 8. Compare and contrast “elastic,” “consolidation” and “plastic” deformations as they apply to loadings of flexible pavements. UNIT VI (2 ½ Weeks): BITUMINOUS MATERIALS AND PRODUCTION PROCESSES 1. Explain the procedure for manufacture of “asphalt cements” and “rapid curing,” “slow curing,” “medium curing” and emulsified asphalt binders. 2. Compare and contrast the uses of the various materials listed in number (1). 3. List and define the various methods for testing the stability of bituminous concrete mixtures. 4. Explain the correct construction procedure for the spreading and compacting of bituminous concrete base and surface courses. 5. Explain the various steps in the preparation of bituminous concrete mixtures in a “batch type” plant. 6. Define the various types of surface treatments used to restore existing bituminous concrete and stone roads. 7. List the items that an inspector should look for at the site of bituminous concrete construction. Prerequisites: Advance Structural Analysis, Advance Steel Structures, Advance Cement Structures Co-requisite: Transportation Modelling Transportation Modelling Engineers in the transportation field and urban planners require skills used in transportation planning to effectively understand the transportation system and urban form. Effective transportation planning requires the understanding of existing techniques and a thorough understanding of their limitations. Text of consideration: Modelling Transport, Ortúzar and Willumsen, 4th Ed. References: Urban Transportation Planning, Meyer and Miller, 2nd Edition Metropolitan Travel Forecasting, Transportation Research Board, Special Report 288 Literature to possibly assist with computational development: Skinner, D., Waksman, R. and Wang, G. H. (1983). Empirical Modelling and Forecasting of Monthly Transit Revenue for Financial Planning: A Case Study of SCRTD in Los Angeles. Transportation Research Record Issue # 936 Tsekeris, T. and Tsekeris, C. (2011). Demand Forecasting in Transport: Overview and Modelling Advances, Economic Research – Ekonmska Istrazivanja, 24: 1, 82 – 94 Transportation Revenue Forecast Model: Methodology Overview, Oregon Department of Transportation. December 2015 Economics and Financial Analysis García-Ferrer, A., Bujosa, M., de Juan, A., & Poncela, P. (2006). Demand Forecast and Elasticities Estimation of Public Transport. Journal of Transport Economics and Policy, 40(1), 45–67. General Visual and Computation tools: GIS (GRASS GIS with addons) Mathematica R + Rstudio Transportation modelling software --> One may be ready to call out TransCAD as the feature software. The significant advantage of TransCAD is its GIS that’s applicable to virtually any infrastructure network across the globe. There are open source alternatives, however, they may or may not directly supply such GIS capability, but are just as good as TransCAD with everything else. Examples of such are MITSIMLab Multi-Agent Transport System Toolkit (MATSim) Simulation of Urban Mobility (SUMO) Has the ability to Import road networks from common network formats such as OpenStreetMap, VISUM, VISSIM, NavTeq, MATsim and OpenDRIVE The following software cater specifically for mesoscopic modelling: Mezzo-Mesoscopic Traffic simulator, DTALite: A queue-based mesoscopic traffic simulator for fast model evaluation and calibration As well, the following software has a strong reputation: TRANSYT-7F NOTE: if software to be applied are not financial costly, take advantage of the time outside course to practice, for development of competency and confidence. Course Goals: 1. Develop transportation system planning concepts 2. Introduce students to the use of [chosen software] 3. Improve transportation planning and modelling skills 4. Create an understanding of the planning process 5. Identify practical applications for the planning process 6. Improve writing and presentation skills NOTE: the following may be problematic or not treated due to time constraints Bicycle and Pedestrian Planning Transit Planning Freight Demand models Homework --> The homework should be submitted on the day that it is due. I need the homework turned in by this date so that I can return the solutions to you within a week. If you are unable to attend class, please submit your homework via e-mail. If the homework is not submitted the maximum score will degrade in the following manner with each deduction associated with class meetings. Labs --> The class will have eight [chosen software] labs in place of a lecture. These labs will teach the basics for [chosen software] use and its application to the project. Additional office hours for the lab will also be scheduled. Exams --> Mid-term and Final (open and closed book). The exams will last one and a half hours, and the final will be two and a half hours. While each test will focus on a specific section, any of the course objectives that have been covered to that point may be addressed. All of the problem solving will be open book while other portions of the test will be closed book. Projects/Presentations --> For the project, a student group (2-3 students) will develop a transportation-planning model for assigned ambiance using [chosen software]. The modelling process and the subsequent recommendations for the future conditions must be presented. Details on the project will be distributed during the first two labs. The findings from project [with chosen software] will be presented at the end of the course in a 12-15 minute presentation. The [chosen software] presentation should focus on the original solution proposed by your group. The presentations will be graded on content, clarity, and timeliness. Skills will be acquired from labs; however, settings, conditions and place(s) of interest will be different. Project Grading Criteria: Organization 0.15 Clarity 0.15 Content 0.3 Solution Originality 0.1 Difficulty 0.1 Content 0.2 Grading: Homework 10% Mid-Term 20% Final 35% [Chosen software] Project and Presentation 35% Course Outline --> WEEK 1. CHAPTER 1 Introduction, Review Supply and Demand Why do we need Transportation Planning? And the Planning Process WEEK 2. CHAPTER 3 Sampling, Modelling and Data Collection Data Collection and Networks Assignment due: Sampling and Data Analysis WEEK 3. Primitive Modelling Link flow theory: modelling of traffic flow on an individual link. Fundamentals of traffic flow: variables of interest, basic flow-speed-density relationship ("fundamental equation"), models of traffic flow (e.g., Greenshields, Greenberg, May). Introduction to microscopic car-following models: linear car-following models, asymptotic and local stability, steady-state behaviour, nonlinear car-following models, steady-state behaviour. Introduction to mesoscopic modelling Introduction to macroscopic fluid-flow models: continuity equation, recovering Greenberg's model, propagation of disturbances (density waves), shock waves. WEEK 4. Introductory Labs Lab 1: Introduction to [chosen software] Lab 2: continuation of [chosen software] WEEK 5. CHAPTER 4 Trip Generation: General and Regression Trip Generation: Cross-Classification Assignment due: Sampling Design WEEK 6 Lab 3: Trip Generation Chapter 5 – Trip Distribution: Growth Factor WEEK 7. CHAPTER 5 Trip Distribution: Gravity Trip Distribution: Calibration and Issues Assignment due: Trip Generation WEEK 8 Lab 4: Trip Distribution Catching Up/Review/Modal Split Assignment due: Trip Distribution WEEK 9. CHAPTER 6 Modal Split Midterm WEEK 10. CHAPTER 7 Discrete Choice Models: Multinomial Logit Lab5: Mode Choice WEEK 11. CHAPTER 10 Assignment: Basics Assignment: Basics Assignment due: Mode Choice WEEK 12. CHAPTER 10 & 11 Assignment: Beyond AON Equilibrium methods: Equilibrium assignment WEEK 13 Lab 6: Traffic Assignment Validation and Forecasting Assignment due: Basic Assignment WEEK 14. LABS Lab 7: Putting it all together Lab 8: Analysing Problems and Solutions WEEK 15. CHAPTER 13 Activity Based Models Activity Based Models Assignment due: Equilibrium Assignment WEEK 16 Software Project Due Presentations Presentations Prerequisites: Calculus III, Optimisation, Probability & Statistics, Mathematical Statistics Land Surveying Course Objective --> To provide an introduction to land surveying measurements and calculations for natural resource managers and landscape designers for the purpose of carrying out basic mapping projects and simple construction layouts. One may intuitively think of a GIS, however, ranges for measures and mapping may be too small for a GIS to pay detailed attention too. In small ranges there may elevation sensitivities taken likely with a general GIS concerning infrastructure and construction projects. Areas of interest may be highly specific in perimeter and various obstacles. The hardest part about this course will be acquiring theodolites and total stations. Typical Text: Surveying Fundamentals and Practices, by Jerry Nathanson, Michael T. Lanzafama, Philip Kissam, Prentice Hall Tools: Scientific Calculator Good Trigonometry Set with a 360° protractor Determined stationery Jump Drive (relative) Smartphone/Smartpad Thorough GPS GIS (GRASS GIS with addons) Photography Field spot markers (and something to drive them down) Necessary tools from the institution: Theodolite(s) Total Stations Course components Theoretical and analytical development Extensive Field activities Schedule for field activities may be extended depending on weather. Course requires students to travel considerable distances to have access to various environments, habitats, etc. Always have hiking shoes and durable wear (not Prada, Chanel, Gucci, Dior, Jimmy choo, Jordans, Yeezy, Nike, white or off white pants, white shoes and so forth). All times excellent hygiene practice is expected involving interactions with each other and with tools in the field. Hydration sustenance is expected. Environmentally acceptable bodily pesticide. Refrain from littering. Refrain from loitering onto property you are not given permission to be on. Having smartphones with long battery life with robust networks will be much appreciated. You are neither allowed to be playing music, nor watching videos, nor use of headphones with audio and video upon reaching surveying sites. Activities in field activities (not necessarily in given particular order): identifying locations, TIN models, contours, TOPO maps, boundary surveys and more). Such activities may require additional specific software. Students who are absent a specific amount of times for fields activities are easily in jeopardy of failing course. A respective missed field activity warrants a score of 0 for associated field report. Some amount of times in lectures will be procured towards prepping for field activities. Prepping will part of your field activity grade weight. Will recognise a professional manner of generating reports from field activities. Replacement policy --> The Replacement Rule may be used one time and is defined as follows: A missed exam or the lowest score on either Exam 1 or Exam 2 may be replaced with the average score of any two other exams—i.e., either Exam 1 or Exam 2 and the Final Exam. However, before applying the rule to the lowest score on Exam 1 or Exam 2, you must achieve a grade of at least 69% on the Final Exam. The replace rule cannot be used to replace the Final Exam score. Grading: Assignments 15% Constructive field participation 15% Field Reports 20% 2 Exams (@ 15% each) 30% Final Exam 20% Course Outline --> Introduction (1 WEEK) - 1. Types of surveying measurement errors and three different categorical sources for these errors. 2. Properties of random errors and explain how random errors propagate or how they influence the end results of measured or calculated quantities. 3. Describe the meaning of accuracy, precision, and resolution. Levelling (3 WEEKS)- 1. Levelling - Explain the theory of differential levelling by utilizing two equations and a labelled profile view showing a level, a levelling rod, the ground surface, the elevation datum, and other required variables. 2. Conduct levelling operations by using a level to acquire back sights, foresights, intermediate foresights, and perform calculations to determine elevations and make the checks to verify and quantify the results. 3. Calculate differences in elevation using back sights, foresights, elevations, and slope distances and slope angles. 4. Describe the concept of stationing as used to define the location of points along a linear feature such as along a centre line for profile levelling. 5. Perform a simple level loop adjustment Distance Measurements (1 WEEK) - 1. Calculate horizontal distance given slope distance and slope angle. 2. Describe how precision is expressed for distance measurements. 3. Explain these methods for expressing slope gradient: slope angle, percent slope, and the top scale. 4. List four units used in distance measurement and convert from one unit to the other. Angle and Directions (2 WEEKS) - 1. Operate a total station to obtain angles-to-the right, vertical angles, slope distances, horizontal distances, and vertical distances. 2. Given the bearing of one side of a traverse and any combination of interior angles, exterior angles, deflection angles or angles-to-the-right at the vertexes of a traverse, calculate the bearings and/or azimuths of all other sides of the traverse; or, given the bearings or azimuths of all sides of a traverse, calculate any of the above mentioned angles at each vertex. 3. Explain the difference between a zenith angle and an angle of elevation or an angle of depression. Traverse Calculations (3 WEEKS) - 1. Describe two traversing methods and three types of traverses. 2. Perform traverse calculations for angle adjustment, bearing or azimuth, latitude, departure, linear error of closure, relative error of closure, compass-rule corrections, and coordinates. 3. Calculate the direction and distance between two points when the coordinates of the two points are known. 4. Calculate the area of a closed traverse. Topographic Mapping (3 WEEKS) - 1. Describe four field methods for collecting topographic and planimetric data. Describe the office procedures for creating a topographic map. 2. Describe how intermediate and index contours are selected. 3. Describe the characteristics of index contours as shown on a map. 4. Create a topographic map showing the minimum required map labels and elements using profile and cross-section data. 5. Create a topographic map showing the minimum required map labels and elements using data from the controlling point method of data collection. Construction Surveying 2 – 3 WEEKS) - 1. Explain how baselines and batter boards are used during the construction layout for constructed facilities or landscape designs. 2. Explain how to set a grade stake or a grade elevation from a temporary benchmark (TMB). 3. Perform calculations for slope stake positions in cut and fill situations. 4. Calculate earthwork volumes. Prerequisite: Senior Standing Building Information Modeling for Capital Projects This course focuses on the skills and information needed to effectively use an existing Building Information Model (BIM) in plan execution for a building construction project. This is a project-based course where students gain knowledge on the implementation of BIM concepts throughout the lifecycle of a building, from planning and design, to construction and operations. NOTE: this course requires a significant investment of time and outside work. Finish it on time. By taking this class, you will be able to: (1) Define BIM (2) Describe workflow in using BIM in the building lifecycle (3) Perform model-based cost estimating (4) Perform 4D/5D simulations (5) Apply BIM to reduce error and change orders in capital projects (6) Evaluate and communicate your ideas related to the use of BIM in the building life cycle Tool --> For this particular course Autodesk Bim 360 along with Autodesk Revit may be the most appropriate. Software will be in labs, and also means to download on your laptops or home computers. References--> Eastman, C.; Teicholz, P.; Sacks, R.; Liston, K. (2008) BIM Handbook: A Guide to Building Information Modeling for Owners, Managers, Designers, Engineers and Contractors. New York: Wiley. 504 pp. Hardin, B., & McCool, D. (2015). BIM and construction management: proven tools, methods, and workflows. John Wiley & Sons Issa, R. R., & Olbina, S. (Eds.). (2015). Building Information Modeling: Applications and Practices. American Society of Civil Engineers Kymmell, W. (2007). Building Information Modeling: Planning and Managing Construction Projects with 4D CAD and Simulations (McGraw-Hill Construction Series). McGraw Hill Professional. Homework assignments --> (i). Assignments will include handouts or notifications through communication platform to be completed. (ii). Much or assignments will be software development activities. Based on lectures and labs. Often it will be cause of altering and augmenting topics and activities in lectures and labs. Quizzes --> Quizzes are closed book, closed note evaluation. Quizzes will cover part of the class material (subjects will be announced in class), assigned readings and guest lectures. Quizzes may include problems, definition/matching, multiple choice, and short answer questions as appropriate to the material covered. Software Development Lab --> Labs will play a crucial role in development. Without strong emphasis and dedication in lab, virtually will be lost. There will be at least 13 labs with software development throughout the course. BIM building Project --> Students will work on a semester-long BIM project to apply skills to develop a BIM model; this will be based on assignments and labs ithroughout the course, and a final report/presentation. Grading --> Homework Assignments 30% (individual weights vary) Software Development Lab 25% Quizzes 15% (individual weights vary) BIM building project 30% Topics --> (1) Overview of the course & organization; Introduction to Building Information Modelling (2) Model-based Cost Estimating (3) Construction Scheduling and 4D Simulation (4) Energy Modelling (5) Design Coordination (6) Conflicts/Interference Checking Prerequisite: Upper Junior Standing Project Controls I Course introduces major concepts of project controls in an integrated fashion, with particular emphasis on cost and time controls. Major topic areas include network scheduling, methods of cost control, and schedule and resource management, as well as special topics such as forensics and the impact of contracts on controls. Course provides a holistic view of major ideas in project controls. Fundamentals of planning, scheduling, and cost management on projects. Topics include network scheduling, activity and resource management, cost loading and cost control, and computer tools used for project controls, such as schedule simulation and three-dimensional and four-dimensional CAD. Specific learning objectives include --> 1. Ability to calculate network schedules and make use of project scheduling software. 2. Understand problems with resource constraints and apply basic techniques of resource levelling to scheduling. 3. Understand and apply methods of schedule compression 4. Understand sources of uncertainty and risk in schedules and apply methods to quantify schedule risk 5. Understand and apply the basic methods of forecasting for cost and schedule. 6. Ability to apply work breakdown structures and cost load a schedule as well as perform earned value calculations. 7. Understand broad concepts of project controls as related to phases of the project and project organization. Typical Text: Forrest Clark & A.B. Lorenzoni, Applied Cost Engineering, CRC Press Supporting Resources: CII RR244-11 - Global Project Controls and Management Systems. 2012 Jimmie Hinze, Construction Planning & Scheduling, Pearson/Prentice Hall Lab Tools Auotdesk BIM 360 (or alternative) Participation --> Attending class is not equal to class participation – participation means asking and answering questions, sharing experiences, etc. Note also that mini-project assessments will be considered when evaluating participation grades. Homework --> Homework consists of traditional problem sets as well as short written questions relating to the course materials and reading. Homework assignments should be completed individually, but I encourage study groups for discussion. Length of homework assignments will vary, and weighting of homework grades will vary with length and difficulty. Labs --> Concerns intelligence and skills to develop towards all projects in course. Homework will augment the theoretical analytical aspects towards skills. Labs include project management and 3D/4D/5D tools. Midterm --> Midterm is closed book, closed note exams. Calculators are allowed provided you haven’t programmed them with notes. Mini Projects --> Student mini projects are meant to allow exploration of a project controls technique in some depth. The mini project consists of identification and project approval with the instructor and a short-written summary of the technique, reference sources, and an original sample problem/illustration. These mini projects will be first assessed by a classmate and then both the assessment and revised project will be submitted for a grade. Major Project --> The class project is also designed to allow small groups to explore aspects of project controls through the design and implementation of a control system. The project can contain selection of novel control measures, describe an integrated system of controls for certain phases of the project, and/or experiment with novel visualizations. Discussion around the project is planned in the first days of class. Based on interest and background of the students, we will better define the project in the initial class days. Grading: Class Participation 10% (instructor’s discretion) Homework 20% Labs 15% Student mini project 15% Midterm 20% Class Project 20% Course Outline --> WK 1 - Intro to Project Controls; Definitions and 13 trends WK 2 - Estimating - overview Basics of network scheduling: activity calcs, float and critical path; computer scheduling WK 3 - Cost Loading and control, Earned Value; Work breakdown structures, work packaging for control; computer scheduling WK 4 - QUIZ – Schedule basics Control During Conceptual Design Engineering WK 5 - Control During Detailed Engineering 3D/4D Schedule visualization WK 6 - Control During Construction WK 7 - Owner view of project controls WK 8 - Schedule & Resource Management: schedule compression, resource levelling and planning Student MiniProjects – First Submission WK 9 - Risk Modelling & Predictive Controls: PERT, simulation Student Mini Projects – Classmate Assessment Due WK 10 - Trending and Forecasting; managing risk & contingency WK 11 - 12 Forensics Student Mini Projects – Final Submission WK 13 - Change Management WK 14 - Midterm WK 15 - Project presentations Project write-up due Prerequisite: Building Information Modeling for Capital Projects Project Controls II Integrity, competency and professionalism are basic goals. Our aim is fit course schedule with actual projects administered by either WASA, Works, Infrastructure, TSTT, T&TEC, etc. There will be a gudeline for competent implementation of project controls. Your intelligence and skills from prerequisite will be essential for development. All tools from prerequisite will be applied. Additionally, expect other things like stationery, smartpad, smartphone (carefully handled), hard hat, work boots, etc. to be relevant. Prerequisite: Project Controls I Civil Engineering students may or may not have interest to complete specific activity labours found in the Geology curriculum. Furthermore, Civil Engineering activities listed beneath, if repeated can be added to transcripts upon successful completion. Many or most activities can be done before and after exposure to any courses of the subject in degree pursuit. Repeated activities later on can be given a designation such as Advance “Name” I, Advance “Name” II. As well, particular repeated activities serve to towards developing true comprehension, competency and professionalism. CONSTITUENTS ON NOTICE: Activities concerns results that can be acknowledged by the professional engineering society. Capabilities of activity will neither be influenced by local cultural ignorance and stigmas nor by ambiances not of concern to bridge programme. Activity does not encourage intrusive entities due to repulsive cultural habits concerning Trinidad, CC, Africa, Black America and Latin America. Any media developed is not geared to pop culture and minority trends or stereotypes. FOR ACTIVITIES IN THE “SUMMER” AND WINTER” SESSIONS ALL PARTICIPATING STUDENTS, ASSISTING/ADVISING INSTRUCTORS AND PROFESSORS MUST BE OFFICIALLY RECOGNISED; REQUIRES BOTH CIVILIAN ID AND STUDENT/FACULTY ID FOR CONFIRMATION OF INDIVIDUAL. THERE WILL ALSO BE USE OF IDENTIFICATIONS FOR ACTIVITIES FOR RESPECTIVE SESSION. SECURITY AND NON-PARTICIPATING ADMINISTRATION WILL ONLY IDENTIFY RESPECTIVE ACTIVITY BY IDENTIFICATION CODE. SECURITY AND NON-PARTICIPATING ADMINISTRATION MUST NEVER KNOW WHAT ACTIVITIES IDENTIFICATION CODES IDENTIFY: < Alpha, Alpha, Alpha, Alpha > - < # # # # # > - < session > - < yyyy > Such civil engineering activities will also warrant criminal background check (CBC) in order to participate. Severely threshold may vary depending on administration. Administrators will provide dated letters of confirmation of thorough CBC to student affairs and other appropriate administration. Such also may include screening that’s parallel to customs & immigration processing where certain levels of criminal history warrants rejection. Email and physical letters with data. Such CBC protocol will not explicitly identify any particular titles or descriptions of any activity, rather, will only convey code as above. It may be the case some activities can be grouped and given a major title together; however, detailed descriptions will be required. Activities will be field classified. Particular projects of interest being stationary: 1. Leonardo da Vinci bridge Will construct various scales from popsicle sticks or eco-friendly substitute to scales at least 9 feet in length. Essentially will determine the physics and engineering for such bridges. Statics likely will have vital role. CAD models with structural analysis and stability can be incorporated. Will identify strengths and weakness of the bridge. Effects of shear, compression, lateral perturbations and torsion. Will then observe Leonardo da Vinci bridges in service to the public and the augmentations applied to make such constructions serviceable to the public. 2. Additional, rudimentary structural skills requirement (repeatable): I. Micro-scale bridge competence Will make use of primitive materials such as wood, bamboo, aluminium, etc. to construct bridge types different to (1). Will predict the load capacity, durability, etc. based on material knowledge and structural Analysis; will then test such and determine whether bridge performance exceeds or falls short of predicted limitations with loads applied, pursuing possible causes. II. Steel scaled down model of a bridge (20-25 feet) carrying 1-1 ½ tons of weight. Design from principles learnt in class; various frames to be analysed concerning economics with materials and time, and forecasted structural integrity properties, aesthetics. CADs and structuring integrity software to apply; must figure out the means to visually and computationally situate the respective material (of particular geometry, weight and mass distribution) in question upon frame. Must fabricate the bridge itself. After planning building must constructed within a designated time. Performance is measured on weight, structural efficiency and aesthetics. Notice: for a respective bridge frame the students must convey the means of attachments, say screws and bolts, welding, etc. Students will be introduced to different loads of various geometries and centre of masses; will concern different materials. Students must determine if such materials are appropriate to be situated on constructed bridge; if not favourable to then choose an appropriate frame design dependent on material cost and estimated timing for construction. Will then test such and determine whether bridge performance exceeds or falls short of predicted limitations with loads applied, pursuing possible causes. To also compare with other possible frame candidates with economics confirmed (materials and time). Latter bridges designed in CAD need not be built. III. Structural analysis for connectors Structural analysis for welding, bolts and screws, connector plates, hinges. Concerning popular structures that require welding, bolts and screws students must determine the structural integrity at such regions. What methods are to be applied for determination of such? 3. Truss Bridges Computational and Design Investigation (repeatable): I. Truss Bridge types--- Pratt, Parker, K-truss, Howe, Camelback, Warren, Fink, Double Intersect Pratt, Warren with Verticals, Bowstring, Baltimore, Double Intersection Warren, Waddell “A” Truss, Pennsylvania, Lattice, McCallum, Suspension and so forth. Students will use knowledge and skills acquired from classes, CADs and structural integrity software to determine structural integrity of the unique structural components for each style of truss structure, and result from integration in total. Concerning economics, choose situation land gaps or river banks to bridge for a width scale, height scale and length scale of such gap, then confirm costs and likely time for completion. II. Analogy to (I) for suspension bridges III. Analogy to (I) for ridged frame bridges IV. Rigid frame bridges versus truss bridges versus cable suspension bridges. V. There may may be “microscale” constructions, however, developing highly economic field investigations may be challenging, 4. Fluid and Thermal Analysis in Civil Engineering (repeatable) Open to Industrial Engineering constituents I. Primitive Environmental Thermodynamics (i). Will extensively acquire knowledge about architecture/civil engineering design towards function for natural Air-conditioning for buildings or sites in Asia, Ancient Egypt and the Middle Ages. Built micro-climates in the Middle East. (ii). Zeer pot fridge or Pot in Pot fridge Definition and construction can be found from many sources. After construction of such (at least three), temperature sensors that can store readings chronologically will be placed inside each. Each fridge will be placed at completely different locations known to experience considerably high temperatures. As well a temperature sensor to be placed outside and separate of each respective fridge with the same recording ability. Each test trial may be a duration of daylight for three days. Preference be that days not concern precipitation and cloudy skies. Will collect data and geometrically represent temperature readings with respect to time. There will be an issue about size (chamber depth and/or volume) being a factor; find experimental resolution if economic. Then, after studying the materials used to make such refrigerators concerning their makeup and thermal properties, propose substitute materials one believes that will provide drastically better results; build and repeat experimentation with concern about whether size (chamber depth and/or volume) will factor in. (iii). Identify any modern structure that make use of similar refrigeration innovation like ii); may not be water involved but more modern advanced materials. Try constructing microscale modules to replicate experiments like in (ii) and compare results. (iv). Fridge without electricity -YouTube Study then build (or reassemble). Temperature sensors that can store readings chronologically will be placed inside. Each test trial may be a duration of daylight for three days. II. Air flow in ducts and pipes There will be different on-site observations. Critical components for control: Pipes, Ducts, In-line ducts fans, Register grills, In-line duct mufflers, Plug-in thermostats, HVAC controls; to understand how such seven features can constitute a simple system. For ducts and pipes there will be on site observations of: Material types, Various geometrical designs, Fitting and Connecting methods, Various suspension methods. As well, thermal insulation methods when applied. Instructor will assign various buildings with ventilation and thermal requirements. Students will use software to develop model and simulation that sufficiently meets the requirements of respective building. Establish of cost based on various materials applied and scale of project. Software such as Autodesk Revit (MEP) or other for air in ducts and pipes to apply considerably. III. Fluids Mechanics Properties of Fluids; Viscosity; Laminar & Turbulent Fluid Flow; Boundary Layer; Continuity, Momentum and Energy equations for Fluid Flows. A master equation for fluids (gases and liquids). Numerical schemes, OpenFoam and Cart3d use. IV. Air flow over and along buildings and structures Concerning the following journal articles investigate the modelling deelopment, computational software or codes mentioned towards the CFD process. Will try to apply skills acquired from (III) to implement such. Baskaran, A., and and Kashef, A., Investigation of Air Flow Around Buildings Using Computational Fluid Dynamics Techniques, Engineering Structures, Vol. 18, No. 11, pp. 861-875, 1996. The following journal article may or may not be of assistance: Tominaga, Y., Flow Around a High-Rise Building Using Steady and Unsteady RANS CFD: Effect of Large-Scale Fluctuations on the Velocity Statistics, J. Wind Eng. Ind. Aerodyn. 142 (2015) 93–103 The following journal article to be analysed and experimentally tested with building of choice: Yau, Y., H., and Lian, Y., C., A Computational Fluid Dynamics Study of the Effects of Buoyancy on Air Flow Surrounding a Building, Building Serv. Eng. Res. Technol. 2016, Vol. 37(3) 257–271 Assuming no wind tunnel is required, analyse and replicate journal article to acquire findings and compare to article: Du, Y., Mak, C., M., and Tang, B., Effects of Building Height and Porosity on Pedestrian Level Wind Comfort in a High-Density Urban Built Environment, BUILD SIMUL (2018) 11: 1215–1228 V. Demonstrating the Laws of Thermodynamics through Experiments VI. Contemporary Thermodynamics for Buildings and Infrastructure (i) Overview of Heat transfer (conduction, convection and radiation) applying to buildings. (ii) Fundamental laws of thermodynamics (with practical relevance) (iii) Thermal resistance and thermal capacitance. Will experimentally verify with thermal sensors or thermometers and timer. The tedious task will be designing “isolated” systems when needed. (iv) Refrigeration cycles. Will become acquainted with different refrigeration cycles and their practicality in buildings, structures, etc. Will identify real buildings, constructions, etc. then to: Develop refrigeration cycle model Followed by experimental valIdation via board controllers, sensors, DAQ, etc. implement particular refrigeration cycle schemes. OvervIew of buildIng codes for cycles and environmental sustainability Codes for energy efficIency and empirIcal validation VII. Thermal Conductivity of Isotropic, Anisotropic & Non-isotropic Materials Must have the ability to differentiate isotropic media from anisotropic/non-isotropic media. Such concerns common materials applied in civil engineering (i) Wood (ii) Steel beams (includes influence on malleability and ductility) Steels cables (includes influence on malleability and ductility) (iii) Aluminum (includes influence on malleability and ductility) (iv) Copper (v) Concrete (vi) Reinforced concrete Kim, Jung J et al. (2014). Extracting Concrete Thermal Characteristics from Temperature Time History of RC Column Exposed to Standard Fire.” The Scientific World Journal 242806. (vii) Glass (viii) Poly (methyl methacrylate) (ix) PVC (x) Fire proofing sprays Will like to know what materials can be overall characterised by the Heat Equation. Analytical description and solution(s) for each material with geometry, material properties, appropriate initial and boundary conditions will be required; compared to lab/field findings. Will also pursue analytical modelling and solutions for anisotropic/non-isotropic materials concernIng conductivity w.r.t. geometry, material properties, appropriate initial and boundary conditions; compared to lab/field findings. Concerning the given journal articles various investigations can be developed. Investigation of concern for listed materials above -- A. Fourier Law. Why does Fourier’s law account for both isotropic and anisotropic/non-isotropic media? Overall boundary geometries are quadrilateral planar, circular planar, cuboid, cylindrical, tube pipes (linear and circular), discs, hollow spheres, solid spheres. B. Modeling and derivation of the Heat equation with practical initial conditions and practical boundary conditions. C. Modelling and derivation of model(s) for anisotropic/non-isotropic media with practical initial conditions and practical boundary conditions. Some assists for experimentatIon: Su, S.,Chen, J. and Zhang, C. (2011). Study on Performance of Anisotropic Materials of Thermal Conductivity. The Open Civil Engineering Journal, 5, 168-172 Ulrich Gross, Gerald Barth, Rhena Wulf, Le Thanh Son Tran. Thermal Conductivity of Non-isotropic Materials Measured by Various Methods. High Temperatures - High Pressures, 2001, volume 33, pages 141 – 150. 15 ECTP Proceedings pages 805 - 814 To identify whether analytical analysis and field/lab experimentation are consistent with intended use of respective material. --Infrared Imaging for a time frame with chose time intervals. --Temperature sensing with infrared sensing that’s time continuous Concerns use applying respective material to high heat source for observation and chronological data gathering for conduction rate and temperature dynamics for respective material. May or may not involve multiple trials for respective material. Determine whether heat conduct rate data conforms well to theoretical conduction rate model(s). Material will then be isolated quickly from high temperature heat source to an environment of constant room temperature to observe cooling down procedure via infrared imaging with chronological data gathering for cooling rate and temperature dynamics for respective material. May or may not involve multiple trials for respective material. Determine whether heat dissipation rate data conforms well to theoretical dissipation rate model(s). As well, respective material will have initial setting of residing in a ambiance of “room temperature” then exposed to freezing temperatures; also involves observation of cooling down procedure via infrared imaging with chronological data gathering for cooling rate and temperature dynamics for respective material. May or may not involve multiple trials for respective material. --Will also be concerned with material integrity due to temperatures and climate. This part doesn’t need to be experimental. Relevant properties of expansion, contraction, malleability, ductility, cracking, weathering, etc. --Weathering due to thermal stress, frost weathering, biological effects (moss, lichens, other microorganism growth with moisture), oxidation. This part doesn’t need to be experimental. --How does temperature influence FEA for concrete beams, steel beams and steel cables? Keep in mind that characteristics for particular material must be incorporated. Consider typical heat transfer models for such materials and their geometries upon FEA (solar variations for tropic to hot arid ambiances). There may be cold climate treatment. Moisture may also have influence on the heat transfer model in question (hot places or cold places). Interest here towards tensile strength, stress, strain, and the flexibility for large distance scales. VIII. Thermal Modelling of Chosen Building Buildings account for approximately 40% of world energy use with around 21% of greenhouse gases. Greenhouse in metric tons vary from one environment to the next. Intelligent Buildings must seek to: Reduce heating, cooling and lighting loads through climate responsive design and conservation practices Employ renewable energy sources (daylighting, passive solar heating, photovoltaics, geothermal, and groundwater cooling) Specify efficient HVAC and lighting systems that consider part-load conditions and utility interface requirements Optimize building performance by employing energy modelling programs and optimize system control strategies Monitor project performance Energy codes provide minimum building requirements that are cost-effective in saving energy. Students must identify what types of machine and systems will appease the controller function, with consideration of cost-effectiveness with such machinery and systems in the short and long run. Identify a modern building that’s common use to apply as a test-bed for advanced energy management in campus buildings and systems. Test-bed facility involves design, implementation and evaluation of a sensor network prototype Sensors Include: Temperature Humidity Light Light Intensity Air pressure Mobility patterns of humans inside building (may not be practical) New measurements can help improve and design control Energy Management and Control Systems (EMCS) In order to investigate how new technologies can help improve energy usage in modern high activity buildings, a scalable thermal model of the building needs to be created, verified and validated. Scalability is important when analysing control systems for large buildings. Relevant to hybrid control system models. Objectives Create a scalable model (Modelica or SystemModeler) of building thermodynamics Model chosen building Validate model using reference data of chosen building Heat Transfer Topics Conduction Convection Radiation Heat Storage How much energy is required to increase the temperature by a specified amount. Proportional to the mass of the object Thermal Circuits Representation of thermal transfer Thermal circuit is a representation of the resistance to heat flow as though it were a resistor Heat storage elements can be represented as capacitors Temperature can be represented as potential Network nodal analysis, the following must be satisfied at each node Model must have a term that represents heat added to the node by means other than surface convection. If internal heat is present, the added heats are known Resistance for conduction Resistance for convection Considered approach Developing control systems and test system-level performance. Possibly creating custom component models using the SystemModeler and/or with Modelica, which enables text-based authoring of physical modelling components, domains, and libraries. Modelling systems spanning mechanical, electrical, hydraulic and other physical domains and physical networks. An issue may be building model data for validation Verifying the model against other platforms Analytical Model Since building is a complex system, a complete theoretical approach is impractical. Assumptions Air is the zone is fully mixed. Temperature distribution is uniform and the dynamics can be expressed in a lump capacity model Effect of each wall is the same Ground and roof have no effect on the zone temperature The density of the air is assumed to be constant and is not influenced by changing the temperature and humidity ratio of the zone Description of Model State variables Zone temperature and wall temperatures People, lights and extreme weather conditions are uncontrolled inputs Input variables Air flow rate for each zone constituents for equations in Model Variables Temperature Heat flow Humidity (may not be directly applicable) Air pressure (may not be directlly applicable); see how it relates to assumption of constant air density Intensity (for light) Luminosity (for light) Parameters Specific Heat Density Mass Heat transfer coefficient of the material Conduction coefficient Length of conductor Area Note: other heat gains can be set to zero Room model will be in the form of a circuit Involving SystemModeler and/or with Modelica for rooms(much use of PIDs) Top level phase on SystemModeler and/or with Modelica Controller(s), dynamics, scopes Thermal model level Room level Wall level and Control block Model: PDEs Mathematica Model: Results PDE vs. SystemModeler and/or with Modelica As well to determine order of error (may be due to numerical integration errors or other things) Model Results: Scalability PID N-room model Set point is around 25 degrees Celsius. Compute time increases, but model is easily scalable on SystemModeler and/or with Modelica. If wall properties are similar, SystemModeler/Modelica model is easily scalable as well. Control pursuit PID Model for room uses the desired temperature errors as input. Very easy to implement on SystemModeler/Modelica. Other advance control techniques (LQR, CLQR, MPC) require state space representation. If nonlinear properties arise then PID may have trouble. As well, scalability can be a problem and state-space representation is not easily implementable. No direct state-space extension from circuit analysis For the N-room model system define the state space Non-linear system can be linearized about a nominal trajectory for implementation of LQR or CLQR. The constraint is the input since the amount of airflow should be… The matrices A, R1, R2 and B are defined by the dynamics of the system. R1 and R2 are necessary to represent the non-linearity in the model. Linearization is straight forward. Selection of nominal trajectory is not. Future work should focus on providing the correct system dynamics to the controller. Pursue Experimental development for chosen building The mentioned sensors will placed securely at many points in chosen building (Temperature, Humidity, Light, Light Intensity, Air Pressure) Concerning the building’s internal, sensors generally should not be directly placed under light sources, airducts, air conditioning, etc. All data to be collected must be calibrated to run exactly with same timing. Readings will be “continuous in time” Sensors must be uniquely identifiable in system with location labelling Will involve much use of microcontrollers Will need high amounts of storage. A cluster with microcontrollers may be prove quite constructive Telemetry may or may not serve well Power source for system must be perpetually reliable (back-up power source if viewed essential) Components in system must be voltage compatible If any sensors and components are to be external to building development appropriate precipitation and moisture insulation System must not be easily reachable to be tampered with or compromised (people, dogs, cats, rats/rodents, insect clogging, reptiles, etc.) Compare data experimental data to simulation There may be questions, such as determining the power consumption needed (per month, annual, etc.) based on simulated model; compared to average real cost acquired by building. As well, there may be competing models to compare with long with the acquired real data from “field experiment”. Two examples: Bastida, H. et al. Thermal Dynamic Modelling and Temperature Controller Design for a House. Energy Procedia 158 (2019) 2800 – 2805 F. Belić, Ž. Hocenski and D. Slišković, "Thermal Modelling of Buildings with RC method and Parameter Estimation," 2016 International Conference on Smart Systems and Technologies (SST), Osijek, 2016, pp. 19-25 And yes, what else can you do with acquired data from “field experiment concerning machine learning? Will ML methods be closely comparable to simulations? Participation requirement for this activity requires: Calculus III ODE General Physics I NOTE: there are different types of thermal systems for buildings which will vary from one building to another. Two examples: HVAC Radiant Cooling + ventilation An example RC model --> He, L. et al. Simplified Building Thermal Model Used for Optimal Control of Radiant cooling System. Mathematical Problems in Engineering Volume 2016, Article ID 2976731, 15 pages 5. Revolutionary Air Conditioner (repeatable) Analysis of given video Revolutionary Air Conditioner – YouTube < https://www.youtube.com/watch?v=R_g4nT4a28U > PART A Thermodynamics inquisition (includes refrigeration cycles) PART B If recognised as feasible proceed with scenarios for the improvements suggested in video, or by one’s own research, then new thermodynamics inquisition applied. PART C Also PWM or MPPT development for the case of solar power integration. PART D Planning and construction of system Components in modelling followed by transfer functions and simulation Systemmodeler/Modelica, DWSIM , COCO Possibly CAD development with Manifolds and tubes, etc. Includes competence with identifying the mechanical and electrical components to fit to scale Comprehending the electrical tools to be applied (oscilloscopes, multimeters, power electronics, fans, etc., etc.) that are efficient and competent. Construction of system and testing Economics to be applied (compared to natural use of plain air conditioner) Cost-Benefit Analysis Life Cycle Assessment Energy Audit Note: personal satisfaction of system to all be considered 6. Solar Powered Air Conditioner (REPEATABLE) Solar Powered Air Conditioner - YouTube < https://www.youtube.com/watch?v=7w4rg3UcsgI&t=1044s > PART A Thermodynamics inquisition (includes refrigeration cycles) PART B If recognised as feasible proceed with scenarios for the improvements suggested in video, or by one’s own research, then new thermodynamics inquisition applied. PART C Also PWM or MPPT development for solar power integration. PART D Planning and construction of system Components in modelling followed by transfer functions and simulation Systemmodeler/Modelica, DWSIM , COCO Possibly CAD development with Manifolds and tubes, etc. Includes competence with identifying the mechanical and electrical components to fit to scale Comprehending the electrical tools to be applied (oscilloscopes, multimeters, power electronics, fans, etc., etc.) that are efficient and competent. Construction of system and testing Economics to be applied (compared to natural use of plain air conditioner) Cost-Benefit Analysis Life Cycle Assessment Energy Audit Note: personal satisfaction of system to all be considered 7. Vibrational Field Investigation (repeatable): The given journal articles to serve as guides, however, choice of ambiances with relevant data to be taken into account-- (i) Memory, T., J., Thambiratnam, D., P., and Brameld, G., H., Free Vibration Analysis of Bridges, Engineering Structures, Vol. 17, No. pp. 705-713, 1995 (ii) Wodzinowski, R., Sennah, K., and Afefy, H., M., Free Vibration Analysis of Horizontally Curved Composite Concrete-Steel I-Girder Bridges, Journal of Constructional Steel Research 140 (2018) 47-61 (iii) Goremikins, V. et al, Simplified Method of Determination of Natural-Vibration Frequencies of Prestressed Suspension Bridge, Procedia Engineering 57 (2013) 343 – 352 (iv) Nagayama, T., et al, Bridge Natural Frequency Estimation by Extracting the Common Vibration Component From the Responses of Two Vehicles, 6th International Conference on Advances in Experimental Structural Engineering, 11th International Workshop on Advanced Smart Materials and Smart Structures Technology, August 1-2, 2015, University of Illinois, Urbana-Champaign, United States (v) Geng, Y., Ranzi, G., Wang, Y., and Wang, Y., Out-of-Plane Creep Buckling Analysis on Slender Concrete-Filled Steel Tubular Arches, Journal of Constructional Steel Research 140 (2018) 164-190 8. Reinforced Concrete Field Investigation (repeatable): --Vasko, M. et al, The Damage Analysis of the Reinforced Concrete Beam and the Prestressed Reinforced Concrete Beam, MATEC Web of Conferences 157, 02055 (2018) --Espana, R., M. et al, Evolutionary Strategies as Applied to Shear Strain Effects in Reinforced Concrete Beams, Applied Soft Computing 57 (2017) 164–176 --Bhogayata, A., C., and Arora, N., K., Fresh and Strength Properties of Concrete Reinforced with Metalized Plastic Waste Fibers, Construction and Building Materials 146 (2017) 455–463 9. Connection Analysis Field Investigation (repeatable): --Lee, J., Goldsworthy, H., M, and Gad, E., F., Blind Bolted T-stub Connections to Unfilled Hollow Section Columns in Low Rise Structures, Journal of Constructional Steel Research 66 (2010) 981–992 --Brandonisio, G., De Luca, and A., Mele, E., Shear Strength of Panel Zone in Beam-to-Column Connections, Journal of Constructional Steel Research 71 (2012) 129–142 --Tizani, W. et al, Rotational Stiffness of a Blind-Bolted Connection to Concrete-Filled Tubes Using Modified Hollo-Bolt, Journal of Constructional Steel Research 80 (2013) 317–331 10. Reinforced Concrete Field Investigation (repeatable): Note: students, assistants, etc. may need to construct specified concretes if such a case comes. --Rumsey, N., Russell, J., and Tarhini, K., Innovative Approach to Teaching Undergraduate Reinforced Concrete Design, 40th ASEE/IEEE Frontiers in Education Conference, October 27 - 30, 2010, Washington, DC. Arezoumandi, M., et al, An experimental Study on Shear Strength of Reinforced Concrete Beams with 100% Recycled Concrete Aggregate, Construction and Building Materials 53 (2014) 612–620. Following such, also be will reinforced concrete different types, namely, materials used for reinforced concrete where results will be compared; weight differences can also be taken into consideration. Note: students, assistants, etc. may need to construct specified concretes if such a case comes. Adjrad, A., et al, Prediction of the Rupture of Circular Sections of Reinforced Concrete and Fiber Reinforced Concrete, International Journal of Concrete Structures and Materials Vol.10, No.3, pp.373–381, September 2016. Apply various international codes. Note: students, assistants, etc. may need to construct specified concretes if such a case comes. --Pang, Y., and Li, L., Seismic Collapse Assessment of Bridge Piers Constructed with Steel Fibers Reinforced Concrete, PLOS ONE, July 10, 2018. Note: given data in journal article can be substituted with more modern data of similar sample size, or extended with modern data. 11. Foundation Engineering (repeatable) Concerns proper analysis, assessment, and treatment for various foundations (soil, rock soil, rock, sand, etc.). Identifying protocols, procedures, tools and stationary applied to a respective ground (being unique in relation to composition, layers, associated weather and climate). Also, of interest will be foundations on cliffs, banks, and weather effects on foundation. Pursuing observation of various field-sites in the beginning, progressing and completed stages; coming to terms with what type and size of building(s) to be constructed. Concerns of procedures to be applied when unusual intense or extreme weather takes place (on both sides of the spectrum); may be one day or multiple days for such amplified weather. Consideration for bridge foundations as well (with respect to type). Masonry planning and operations. Includes determination of optimal procurement for tasks/phases. Must detail methods applied in processes to avoid disproportions and common human errors. Measurements, scaling, use of box levels (or maybe even lasers if economic), cement, bricks, rebar, beams, construction string. Students towards their personal research to develop engineering report for design and evaluation for structural integrity pursued, versus acquired data in construction. 12. Concrete Structures Repair (repeatable) Activity will make emphasis to have field operations and experimentation Phase 1 Note: the following guides may provide a vibe that may or may not restrict quantitative and computational activities in (i) and (ii). However, such a situation will not happen: U.S. Department of the Interior Bureau of Reclamation. Reclamation-Managing Water in the West: Guide to Concrete Repair. August 2015. T. J. Wipf, F. W. Klaiber, E. J. Raker. (2004) Effective Structural Concrete Repair, Volume 3 of 3, Evaluation of Repair Materials for Use in Patching Damaged Concrete; TR-428, March 2004. Iowa Department of Transportation. These guides will be subjugated to the layout of (i) and (ii). If they don’t suffice in total, sources will be identified that do such. Note: calculation models throughout (i) and (ii) will be identified. (i) The first step in a successful repair project involves damage assessment and arriving at a proper diagnosis (includes causes). All too often, by the time concrete shows obvious signs of distress, and the owner wants it fixed, it may be too late, and replacement may be more effective. There must be determination of when concrete should be repaired and when it is best replaced. Modern damage assessment methods and then with identification and repair of various kinds of concrete problems. (ii) Effective yet economical methods of repairing concrete structures. It addresses the most common challenges of concrete rehabilitation, including crack repair, corrosion of reinforcement, patching, column deterioration, using strengthening methods in lieu of repair, choosing the most appropriate repair materials, and many more. Despite much advice available on the topic, many concrete repairs fail prematurely, sometimes within a few years. Explaining where the common pitfalls of concrete repairs lie and how to avoid them. There can be various cases studies throughout. Phase 2 The latter guide (Wipf et al) contains experimental descriptions that may carry over to phase 2. The given journal articles convey strong experiments for testing repaired concrete structures. In terms of economic feasibility experiments pursued might be scaled down versions of original experiments. Hence, one must determine if the results from scaled down experiments are consistent with results in articles. --Hasholt, M. T. and Jensen, O. M. Chloride Migration in Concrete with superabsorbent polymers. Cement & Concrete Composites 55 (2015) 290–297 --Hongqiang, C. et al. Influence of Anion Types on the Electrodeposition Healing Effect of Concrete Cracks. Journal of Wuhan University of Technology-Mater. Sci. Ed. Dec.2012, 1154 - 1159 --Hongqiang, C. et al. Use of Electrochemical Method for Repair of Concrete Cracks. Construction and Building Materials 73 (2014) 58–66 --J.S. Ryou, J. S. and Otsuki, N. Experimental study on Repair of concrete Structural Members by Electrochemical Method. Scripta Materialia 52 (2005) 1123–1127. X-ray diffraction might not be feasible. --Pattnaik, R. R. and Rangaraju, P. R. Investigation on Flexure Test of Composite Beam of Repair Materials and Substrate Concrete for Durable Repair. J. Inst. Eng. India Ser. A (October–December 2014) 95(4):203–209 --Pelà, L., Aprile, A. and Beneditti, A. Experimental Study of Retrofit solutions for Damaged Concrete Bridge Slabs. Composites: Part B 43 (2012) 2471–2479. --Yang, Y. et al. Repair of RC Bridge Columns with Interlocking Spirals & Fractured Longitudinal Bars – An Experimental Study. Construction and Building Materials 78 (2015) 405–420 --Chellapandian, M. and Prakash, S. S. Rapid Repair of Severely damaged Reinforced Concrete Columns Under Combined Axial Compression and Flexure: An experimental study. Construction and Building Materials 173 (2018) 368–380 13. Surveying (repeatable) Example manuals: https://www.dot.state.mn.us/surveying/pdf/sm-manual-2007.pdf http://www.dot.ca.gov/landsurveys/surveys-manual.html Concerns competent surveying with instruments (hopefully) for various terrains, such seashore estates, ports, capitals, roadways with rapid variations in attitude, conservation estates, rural terrain, mountainous terrain, basic roadways, construction site, etc. Such manuals and their international counterparts are to be understood and applied competently for a respective environment mentioned. Students are obligated to practice with multiple environments within a given period. Includes professional data acquisition, storage, management and modelling; at times will incorporate usage of GIS. High concern for surveying the after effects of natural disasters such as flooding, land slides, mud slides, storms, earthquakes. Note: open to geology students. 14. Highway Engineering (repeatable) Key concerns: I. Planning and development Traffic research Financing Environmental Impact Assessment Highway Safety II. Design Geometric Design (with various design considerations) Materials Flexible Pavement Design Rigid Pavement Design Flexible Pavement Overlay Design Rigid Pavement Overlay Design Drainage System Design III. Construction, maintenance and management Highway construction (with technical and commercial elements) Reviewing the geotechnical specifications of the project towards information is about ambiance conditions, required equipment, material excavation, dewatering requirements, shoring requirements, water quantities for compaction and dust control, etc. Subbase course construction Base course construction Surface course construction Hot-mix asphalt layers PCC Highway Maintenance Repair of functional pavement defects Extend the functional and structural service life of the pavement Maintain road safety and signage Keep road reserve in acceptable condition Activity throughout will likely to make high usage of GIS (GRASS GIS); Google Maps may provide insight and assistance, but will not be the primary tool. Financing groundwork, forecasts, cost accounting and final cost expense will be extensively treated for subject areas listed above. There will likely technical and intricate concerns with materials, detail, elements. Paths and access for critical areas such as highways, airports, “town”, residential areas, esplanade, mountainous places (with abundant curvature), etc. Pursue from public record various data and blueprints for various highway engineering projects to analyse. If scheduling logistics and site access are accomplished, to observe critical phases of active construction projects; data may or may not be readily accessible for such, however, based on specific designation of active construction project(s) and scale, students may be able forecast completion date expectation and projects costs based on topics above, where minimal formal public relations data is required. Some idea of labour force towards payroll, labour scheduling and progress should also factor in. Ability to forecast time frames for completion. Recognise major causes for setbacks, running expenses, etc. (excluding maintenance). 15. Advanced High-Performance Materials for Highway construction (incomplete) 16. Seismic Codes (repeatable) PART A To develop some structures via CAD (beams, slabs, other building structure components) to investigate structural properties via FEA and vibrational analysis. Part B Analysis and experimentation: Soong, T.T. & Costantinou, M.C. (1994). Passive and Active Structural Vibration Control in Civil Engineering. CISM International Centre for Mechanical Sciences (Courses and Lectures), vol 345. Springer, Vienna Note: from the above journal article there’s interest in actual implementing of some methods and tools, whether microscal representations or with actual specimens. Ansal, Atilla, Ilki, Alper, & Fardis, Michael N. (2014). Seismic Evaluation and Rehabilitation of Structures (2014 ed., Vol. 26, Geotechnical, Geological and Earthquake Engineering). Cham: Springer International Publishing. From the above text interest ranges from chapter 6 – 27. Note: Will try to replicate crucial experimentation that are economic with resources available. Such chosen experiments will be compared to relevant international seismic building codes. Fajfar, P. (2018). Analysis in Seismic Provisions for Buildings: Past, Present and Future. Bulletin of Earthquake Engineering, 16(7), 2567-2608. Note: from the above journal article there’s interest in actual implementing of some nonlinear methods, probabilistic analysis, the PRA method, and tolerable probability of failure for designs, proposed structures and current standing structures. PART C Slocum, R. K. et al (2018). Response Spectrum Devices for Active Learning in Earthquake Engineering Education. HardwareX, volume 4, e00032 Abstract --> “Structural and geotechnical engineers regularly use response spectra to assess the response of civil infrastructure to earthquakes; however, the underlying concepts of response spectra are often difficult for civil engineering students to grasp. Hardware specifications for two low cost response spectrum devices (RSDs) facilitate an inductive approach for teaching response spectrum concepts to students. The RSDs, which consist of wooden masses, compression springs, and accelerometers, can be excited manually or on a portable shake table to show the effects of mass and stiffness on the dynamic response of structures subjected to earthquake ground motion. Auxiliary Python scripts record real time accelerometer data, enabling students to compare the observed RSD response to numerical computations.” Will pursue dvlopment of experments from such journal article? Much analysis of data acquired. PART D 1. International Atomic Energy Agency (2022). Methodologies for Seismic Soil–Structure Interaction Analysis in the Design and Assessment of Nuclear Installations, TECDOC Series, IAEA, Vienna (will generalise to habitats and surroundings of interest) 2. Scoops3D implementation Reid, M. E., Christia, S. B., Brien and D. L. and Henderson, S. T. (2015). Scoops3D—Software to Analyze Three-Dimensional Slope Stability Throughout a Digital Landscape. U.S. Geological Survey, Series 14-A1 First will geologically profile regions of various elevation characteristics, along with soil and bedrck profile. Note: if weather influences are consderable, then hopefully such can be integrated. 3. OpenSHA implementation Supporting literature found at: https://opensha.org PART E The following tools can be used for intellegence on sesimic map codes, and to compare with government guidelines for assurance: ASCE 7: https://asce7hazardtool.online ATC Hazards by location: https://hazards.atcouncil.org OSHPD Seismic Design Maps: https://seismicmaps.org PART F Note: not interested in bamboozles and screwjobs with models and equations due to purely mathematical toxic personalities. If a calamity (future or occurred) was considered, what will you do with all that stuff? How will you apply all that stuff? Apart from a stochastic and statistical background, schemes and logistics are important. We need to develop such. Certain things will not be as straightforward when applying to the field (concerning parameters and quantities), but you are in this activity to resolve all those things. Note: the following literature (likely in need of amending or augmentations) may be of interest. Developing an operational framework to readly implement when needed may be a challenge. Coordinated logisitcs is important to be useful: Araya, R. & Der Kiureghian, A. (1988). Seismic Hazard Analysis: Improved Models, Uncertainties and Sensitivities. Report to the National Science Foundation. Report No. UCB/EERC-90/11 Recommendations for Probabilistic Seismic Hazard Analysis: Guidance on Uncertainty and Use of Experts. Lawrence Livermore National Laboratory. NUREG/CR-6372 UCRL-ID- 122160 Vol. 1 17. Numerical Simulation of Early Age Cracking of Reinforced Concrete Bridge Decks (repeatable) The following article serves as a good guide for simulation and experimentation. Ishida, T., Pen, K., Tanaka, Y., Kashimura, K. and Iwaki, I. Numerical Simulation of Early Age Cracking of Reinforced Concrete Bridge Decks with a Full-3D Multiscale and Multi-Chemo-Physical Integrated Analysis. Appl. Sci. 2018, 8, 394. 18. Vibrational Analysis for Crack Detection in Composite Beams The are various articles providing analytical methods for crack detection. Choose 3 – 4 methods to pursue experimental investigation comparing the given methods. Methods considered should not further amplify the damage of the composite beam. One example to consider: Stephen R. Borneman, Seyed M. Hashemi, "Vibration-Based, Nondestructive Methodology for Detecting Multiple Cracks in Bending-Torsion Coupled Laminated Composite Beams", Shock and Vibration, vol. 2018, Article ID 9628141, 10 pages, 2018 NOTE: will like to compare vibrational methods with optical and thermal methods. For thermal, preferably infrared imaging at “rational” temperartures. 19. Amplifying Rainwater Acquisition (repeatable) The ability to harvest rain water in tropical environments is terribly unappreciated. Particularly, having water collecting structures that can benefit many in a specific district, province, etc. Consider pervious concrete or the famous Topmix Permeable; will make selections out of highly economic choices. Pervious concrete is made using large aggregates with little to no fine aggregates. Concrete paste then coats the aggregates and allows water to pass through the concrete slab. It’s observed as practical for sustainable construction and is one out of many environmental low impact development techniques applied to protect water quality. Preliminary: 1. Investigate interaction of pervious concrete types with water (chemistry) Short term and long term 2. Investigate interaction of pervious concrete types with soils types, bedrock types, igneous rocks and metamorphic rocks (chemistry) Short term and long term 3. Investigate bodily intake of pervious concrete particles 4. For any necessary purification techniques what are the by-products from samples of water undergoing pervious concrete transmission (includes sedimentary stone/rock particles). Resolutions if any unfavourable by-products 5. Chemical longevity of pervious concrete 6. Weathering studies (include thermal dynamic) 7. Hydrology profiling. NOT TO TAMPER WITH RAINFORESTS AND PLACES OF HIGH VEGETATION. Evidence of consistent rainfall w.r.t to climate change dynamics, or prediction for places with increased rainfall due to climate change dynamic. 8. It’s essential that rainfall gathered/channelled has no damaging consequences on habitat/ecosystem. 9. Engineering concentration channels towards dams will take some ingenuity. Mechanisms to determine excess load and redirection in a manner than doesn’t create hazards (erosion, mudslides, avalanches. Rather redistribution that assists ecosystems in a manner that will not create breeding grounds for mosquitoes. A. Microscale development stage: Will target areas of usual high rainfall during rainy and dry seasons, but with poor water utility service. Will choose a very small areas for construction. Following cement permeation to have concentrated flow towards a contained structure of sediments in the following order: Large gravel --> fine gravel --> coarse sand --> fine sand --> activated charcoal --> fine sand. Will likely pursue comparative analysis of water content between running water before entry into porous cement versus water after permeation through sediment filtration. Filtration layers should be replaceable and properly disposed of. Will construct multiple filtering channels. Each station with numerous trials for a particular mixture, and analyse the results [water with dissolved soil, soap/detergent water, construction wastewater, sludge, water with oil]. Such mixtures are “extreme” cases of possible contamination concerning possible following water treatment. The “product” will be collected for each trial of a respective station. Will analyse the “product” water composition and proportion of pollutants total to water (via density or weight methods) compared to mixture before entry into filtering system. Such incorporates also observation of whether porous material becomes clogged for particular solutions; limited test trials may not be adequate, but applying granulate analysis of porous concrete, viscous properties of solution, adhesiveness from cohesive forces, etc. Can a rate of clogging be determined for each solution? Such likely is necessary for lower sediment layers, where clogging rate for each layer may be unique; changing times to correspond to layer with smallest time. NOTE: clogging rates for pervious cement and sediment layers will be different for each station. If porous cement is to be cleaned concerning deposits build up, “gunk” and microbial “pool”, what can be used to not compromise the structural integrity and not chemically contaminate its filtering efficiency. Determination when porous cement must be changed in the distant future concerning structural integrity and irreversible contamination. Will also like to determine the tensile strength and shear strength of porous concrete. Will like to determine the weathering resistance of porous concrete. B. Design towards high acquisition of water consistently with rainfall towards concentrated directional flow with piping will be a challenge. There may be multiple designs that could work well. How does one make construction appear pleasant to environment in question short term and possibly long term? Then, for a target site with reputation of having consistent tremendous runoff during rainfall, design a large sale porous cement structure with concentrated flow and designed filtration, where aesthetics are considered to blend structure well with environment of consideration. THIS ABOVE ACTIVITY HAS NOTHING TO DO WITH DRAINING RIVERS, STREAMS AND WETLANDS. ACTIVITY NEITHER CONCERNS REDIRECTING RIVERS NOR STREAMS. ACTIVITY CONCERNS ACCESSING HIGH QUANTITY RUNOFFS UNIQUE TO STREAMS AND RIVERS. C. Forecasting & Economics Forecasting amount of water acquisition for each season. Cost-Benefit Analysis (include scheduled maintenance and replacement) Life Cycle Assessment (include scheduled maintenance and replacement) 20. Geotechnical foams (repeatable) Note: apart from analysis and intelligence there will be field activities or micro-environment activities when appropriate. For analysis and temperature seek out professional sources such as journal articles, chemistry texts, manuals, etc. Chemistry and physics will be enforced in terms of modelling and computation. Such will include chemical characteristics profile. Students should be able to determine labour ability for volume foam to be applied for respective foam concerning the volume that is to be occupied; realistically volumes in field will be quite generic, however, to compute for less general volumes shows knowledge. --Will identify different types and the various critical uses --Chemical description --Chemical reaction and physics that lead to a respective foam having reaction strength against foundations, trenches, etc. In other words, how you go from chemical reactions to Newton’s 2nd Law where sum is greater than weight of massive chunk or whatever. --Identifying the economic effectiveness compared to other alternatives --Environmental impact, possible toxicity to land life forms, aquatic life forms, and behaviour when exposed to flame --Lifespan of effectiveness with respect to the elements, extreme cold temperatures and extreme heat temperatures (conduction, convection) --Determination of possible substances that can abruptly degrade or alter ideal properties (essentially for each type). 21. Structural Health Monitoring (repeatable) Note: a full strong general idea can be found at Wikipedia. Structural health monitoring (SHM) is the operation of applying a damage detection and characterisation plan for engineering structures such as buildings and bridge. Damage being variations to the material and/or geometric properties of a structural system, including changes to the boundary conditions and system connectivity, which negatively affect the system's performance. The SHM process involves the observation of a system over time using periodically sampled response measurements from an array of sensors (often inertial accelerometers), the extraction of damage-sensitive features from these measurements, and the statistical analysis of these features to determine the current state of system health. For long term SHM, the output of this process is periodically updated information regarding the ability of the structure to perform its intended function in light of the inevitable aging and degradation resulting from operational environments. After extreme events, such as earthquakes or blast loading, SHM is used for rapid condition screening and aims to provide, in near real time, reliable information regarding the integrity of the structure. Infrastructure inspection, such as road network and bridges, plays a key role in public safety in regard to both long-term damage accumulation and post extreme event scenarios. As part of the rapid developments in data-driven technologies that are transforming many fields in engineering and science, machine learning and computer vision techniques are increasingly capable of reliably diagnosing and classifying patterns in image data, which has clear applications in inspection contexts. A. Statistical Pattern Recognition Farrar, C. R., Doebling, S. W. and Nix. D. A. (2001). Vibration-Based Structural Damage Identification. Philosophical Transactions of the Royal Society A. 359 (1778), pp 131 – 149 Hoon, S. et al. (2004). A Review of Strutural Health Monitoring Literature: 1996 – 2001. Los Alamos, NM: Los Alamos National Laboratories. B. Stages of increasing difficulty that require the knowledge of previous stages, namely: Detecting the existence of the damage on the structure Locating the damage Identifying the types of damage Quantifying the severity of the damage It’s necessary to employ signal processing and statistical classification to convert sensor data on the infrastructural health status into damage info for assessment. The data acquisition portion of the SHM process involves selecting the excitation methods, the sensor types, number and locations, and the data acquisition/storage/transmittal hardware. Again, this process will be application specific. Economic considerations will play a major role in making these decisions. The intervals at which data should be collected is another consideration that must be addressed. Since data can be measured under varying conditions, the ability to normalize the data becomes very important to the damage identification process. As it applies to SHM, data normalization is the process of separating changes in sensor reading caused by damage from those caused by varying operational and environmental conditions. One of the most common procedures is to normalize the measured responses by the measured inputs. When environmental or operational variability is an issue, the need can arise to normalize the data in some temporal fashion to facilitate the comparison of data measured at similar times of an environmental or operational cycle. Sources of variability in the data acquisition process and with the system being monitored need to be identified and minimized to the extent possible. In general, not all sources of variability can be eliminated. Therefore, it is necessary to make the appropriate measurements such that these sources can be statistically quantified. Variability can arise from changing environmental and test conditions, changes in the data reduction process, and unit-to-unit inconsistencies. Data cleansing is the process of selectively choosing data to pass on to or reject from the feature selection process. The data cleansing process is usually based on knowledge gained by individuals directly involved with the data acquisition. As an example, an inspection of the test setup may reveal that a sensor was loosely mounted and, hence, based on the judgment of the individuals performing the measurement, this set of data or the data from that particular sensor may be selectively deleted from the feature selection process. Signal processing techniques such as filtering and re-sampling can also be thought of as data cleansing procedures. Finally, the data acquisition, normalization, and cleansing portion of SHM process should not be static. Insight gained from the feature selection process and the statistical model development process will provide information regarding changes that can improve the data acquisition process. The area of the SHM process that receives the most attention in the technical literature is the identification of data features that allows one to distinguish between the undamaged and damaged structure. Inherent in this feature selection process is the condensation of the data. The best features for damage identification are, again, application specific. One of the most common feature extraction methods is based on correlating measured system response quantities, such a vibration amplitude or frequency, with the first-hand observations of the degrading system. Another method of developing features for damage identification is to apply engineered flaws, similar to ones expected in actual operating conditions, to systems and develop an initial understanding of the parameters that are sensitive to the expected damage. The flawed system can also be used to validate that the diagnostic measurements are sensitive enough to distinguish between features identified from the undamaged and damaged system. The use of analytical tools such as experimentally validated finite element models can be a great asset in this process. In many cases the analytical tools are used to perform numerical experiments where the flaws are introduced through computer simulation. Damage accumulation testing, during which significant structural components of the system under study are degraded by subjecting them to realistic loading conditions, can also be used to identify appropriate features. This process may involve induced-damage testing, fatigue testing, corrosion growth, or temperature cycling to accumulate certain types of damage in an accelerated fashion. Insight into the appropriate features can be gained from several types of analytical and experimental studies as described above and is usually the result of information obtained from some combination of these studies. The operational implementation and diagnostic measurement technologies needed to perform SHM produce more data than traditional uses of structural dynamics information. A condensation of the data is advantageous and necessary when comparisons of many feature sets obtained over the lifetime of the structure are envisioned. Also, because data will be acquired from a structure over an extended period of time and in an operational environment, robust data reduction techniques must be developed to retain feature sensitivity to the structural changes of interest in the presence of environmental and operational variability. To further aid in the extraction and recording of quality data needed to perform SHM, the statistical significance of the features should be characterized and used in the condensation process. The portion of the SHM process that has received the least attention in the technical literature is the development of statistical models for discrimination between features from the undamaged and damaged structures. Statistical model development is concerned with the implementation of the algorithms that operate on the extracted features to quantify the damage state of the structure. The algorithms used in statistical model development usually fall into three categories. When data are available from both the undamaged and damaged structure, the statistical pattern recognition algorithms fall into the general classification referred to as supervised learning. Group classification and regression analysis are categories of supervised learning algorithms. Unsupervised learning refers to algorithms that are applied to data not containing examples from the damaged structure. Outlier or novelty detection is the primary class of algorithms applied in unsupervised learning applications. All of the algorithms analyse statistical distributions of the measured or derived features to enhance the damage identification process. Fundamental axioms or principles Worden, Keith; Charles R. Farrar; Graeme Manson; Gyuhae Park (2007). The Fundamental Axioms of Structural Health Monitoring. Philosophical Transactions of the Royal Society A. 463 (2082): 1639–1664. SHM Systems Structure Sensors Thermal Imaging Fiber Optics Data acquisition systems Data Transfer and Storage Mechanism Data Management Data Interpretation and Diagnosis System Identification Structural Model Update Structural Condition Assessment Prediction of Remain Life Service Sensing Guides --> -Tennyson, Roderic (October 2005). "Monitoring Bridge Structures Using Long Gage-Length Fiber Optic Sensors". Caltrans Bridge Research Conference 2005. -Davoudi, Rouzbeh; Miller, Greg; Kutz, Nathan (2018). "Data-driven vision-based inspection for reinforced concrete beams and slabs: Quantitative damage and load estimation". Automation in Construction. 96: 292–309. -Davoudi, Rouzbeh; Miller, Greg; Kutz, Nathan (2018). "Structural load estimation using machine vision and surface crack patterns for shear-critical RC beams and slabs". Computing in Civil Engineering. 32 (4): 04018024 -Raghavan, A. and Cesnik, C. E., Review of guided-wave structural health monitoring," Shock and Vibration Digest, vol. 39, no. 2, pp. 91-114, 2007 -Carden, E; Fanning P (2004). "Vibration based condition monitoring: a review". Structural Health Monitoring. 3 (4): 355–377 -Montalvao, D., Maia, N. M. M., and Ribeiro, A. M. R., \A review of vibration- based structural health monitoring with special emphasis on composite materials," Shock and Vibration Digest, vol. 38, no. 4, pp. 295-326, 2006. -Fan, W. and Qiao, P. Z., Vibration-based damage identification methods: A review and comparative study," Structural Health Monitoring, vol. 10, no. 1, pp. 83-111, 2010. -Dixit, A. and Hodges, D. H., A general damage theory: Solution of nth-order equations using unified framework," Mechanics Research Communications, vol. 38, no. 7, pp. 486-493, 2011. -Dixit, A. and Hanagud, S., Damage localization by isolating the part of the response due to the damage only," Journal of Applied Mechanics, vol. 80, Number 1, p. 011015, 2012 Failure Modes --> Gunes, O. Chapter 5. Failure Modes in Structural Applications of Fiber- Reinforced Polymer (FRP) Composites and their Prevention. Developments in Fiber- Reinforced Polymer (FRP) Composites for Civil Engineering. Woodhead Publishing Series in Civil and Structural Engineering, 2013, Pages 115 - 147 Above guide may not treat all civil structures, hence, one may need to acquire the failure modes for respective civil structure in question. Data Analysis --> Zonta, D. Chapter 2, Reduction and Fusion for Assessing and Monitoring Civil Infrastructures. Sensor Technologies for Civil Infrastructures. Applications in Structural Health Monitoring. Volume 2 in Woodhead Publishing Series in Electronic and Optical Materials, 2014, Pages 33 - 66 NOTE: corrosion analysis may also be done. Assumptions for practicality --> Micro to meso scale constructions at chosen sites. Likely 2-3 “identical” prototypes for a particular civil structure. One sample structure (out of the 2 or 3) to be the control, where the others will be intentionally damaged (but not severely) in different ways. Then will apply perturbations (constructive rocking, stamping, ground shaking, etc. etc.). Sensors, fiber optics, thermal imaging, DAQs, data ttransfer & storage, and other tools will be generic and integrated to microcontrollers and/or old laptops. Activity can be recognised as making use of different levels of time series, filtering, time orienting, machine learning algorithms, Principal component analysis, and what not. Tools such as R and Mathematica will treat such very well. Generally, for Bridges --> Health monitoring of large bridges can be performed by simultaneous measurement of loads on the bridge and effects of these loads. It typically includes monitoring of: Wind and weather Traffic Pre-stressing and stay cables Deck Pylons Ground Provided with this knowledge, the engineer can: Estimate the loads and their effects Estimate the state of fatigue or other limit state Forecast the probable evolution of the bridge's health However, due to scale, some aspects can’t be done. NOTE: will also pursue micro/meso scale building structural foundations Some further ideas: Structural Health Monitoring - YouTube ( https://www.youtube.com/watch?v=oO7E2G2WfL4&feature=youtu.be ) BridgeMonitor – structural Health Monitoring system – YouTube ( https://www.youtube.com/watch?v=nE7AxPzOst8 ) NOTE: the following are may be of interest as well to analyse and experimentally develop --> Heo, Gwang & Kim, Chunggil & Jeon, Seunggon & Jeon, Joon. (2018). An Experimental Study of a Data Compression Technology-Based Intelligent Data Acquisition (IDAQ) System for Structural Health Monitoring of a Long- 22. Construction Reporting (repeatable) Hopefully active field sites will be available during times. Observe the progress of a home or place of accommodation in construction: from foundation to structural development to “structural encapsulation”. Site can possibly be corporate or government controlled. --Speculate on building design concerning ground environment, terrain and the arguable perpetual influence of weather (common and extreme). Perspectives: status quo, profession counsel and personal opinion (be honest). --For each phase students are to analyse or to identify the critical aspects of civil engineering; includes materials, tools and processes involved. Students to also definitively identify the essential roles of carpentry and masonry involved. --There will be a finance and cost accounting aspect as well concerning, resources, materials, tools, water usage construction costs, electricity usage construction cost, technologies, manpower, WASA integration (water and sewage), wiring (electrician labour and power estimate to run building) and T&TEC integration, telecommunication account and wiring (TSTT or whatever). One will naturally have pre-established theory about housing construction finance (capital and debt). One will also have a pre-established model for cost accounting to be compared alongside the progressing construction; there may be perturbations for various reasons. Students will be expected to give expected final cost. There may be much more technical finance and accounting formulas or tools than expected. All will be professional. --Quality of construction assessment throughout development is crucial, but may be provocative. Photos and recording may not be optional. --Students should also have a time of completion forecast, and to record data of any possible hindrances (weather, operational hazards, competency, labour effort, labour force, finance). Forecasts should be updated. Activity will be much more technical and academic than expected. All will be professional. NOTE: multiple spreadsheet development throughout likely to accompany research writing structure. NOTE: hopefully students’ efforts will neither antagonize, nor agitate, nor unethically expose anyone. 23. Reservoir studies, Modelling and Control (may be augmented in the future) I. Major themes of this activity: History and Types (including variations in cisterns) Uses Operation Safety Environmental Impact II. Naturally there will be field trips. Then to have civil engineering studies and analyses of various types of reservoirs (all constructed and excavated areas). The Hillsborough Reservoir of Tobago to be one of the introductory case studies. There will be “classical” types and “modern” types. Methods of reservoir constructing will be pursued in detail; such includes sedimentation preferences or whatever else is possible. Will go into detail the types of flow control mechanisms and actuation structures for levying water flow and depths. Emergency water release mechanisms. Some reservoirs may be highly divergent to others concerning the amount and levels of technologies employed. Will include various hydraulic engineering design principles. The 2 following sources may prove useful --> Hydrologic Engineering Requirements for Reservoirs. Engineering Design. US Army Corps of Engineers. EM 1110-2-1420. 24 Sep 2018 https://www.publications.usace.army.mil/Portals/76/Users/182/86/2486/EM_1110-2-1420.pdf Willey, R. G. (1982). River and Reservoir Systems Water Quality Modelling Capability. US Army Corps of Engineers. TP-83 https://www.hec.usace.army.mil/publications/TechnicalPapers/TP-83.pdf Following such there are USDA NRCS software that can be used for dam development: SITES WinDAM C DrainMod EFH 2 EFT ND-Drain Structural Design Win TR-20 Win TR-55 As well, HEC-RAS, iRIC HEC-HMS, SWMM (from the EPA) It may be constructive acquire dcumentation for such software to analyse before use of software. How compatible are such two prior Army Corps literature with the software documentation? Following, to be implementation of the software for environments considered. Will then apply structural analysis, steel structures and concrete structures implemented for designs considered. This means use of softaware for steel structures and cement structures. III. FEM/FEA for dam or reservoir failure Strong characterisation, geophysical and boundary modelling/description of the reservoir are crucial. What features of the reservoir can be identified with possible failure(s) due to natural mechanical phenomena with water, barrier composition, etc, etc.? Operation systems/control failure is a unique subject. Followed by different reservoir types from various ambiance and proceed. The following idea examples are “static” which is a good start, but will like to extend to dynamical simulations: --Nguyen, L. Guide for Analysis of Concrete Dam Structures using Finite Element Methods. DSO-2018-09. U.S. Department of the Interior Bureau of Reclamation https://www.usbr.gov/ssle/damsafety/TechDev/DSOTechDev/DSO-2018-09.pdf --FEMA. Selecting Analytic Tools for Concrete Dams Address Key Events Along Potential Failure Mode Paths. Federal Emergency Management Agency. July 2014 https://www.fema.gov/media-library-data/1423072356123-801ff39d781345289daa842256a31a4d/FEMAP-1016.pdf --Chonghui, F. et al. Analysis on Dam-Break Case of Concrete Arch Dam and Forecast of Failure Scope Based on Point Safety Factor. 2012 International Conference on Modern Hydraulic Engineering. Procedia Engineering 28 (2012) 617 – 625 --Athani, S. S. et al. Seepage and Stability Analyses of Earth Dam Using Finite Element Method. International Conference on Water Resource, coastal and Ocean Engineering (ICWRCOE). Aquatic Procedia 4 (2015) 876 – 883 --Alonso, E. E. and Pinyol, N. M. Numerical Analysis of Rapid Drawdown: Application in Real cases. Water Science and Engineering. Volume 9, Issue 3. July 2016, Pages 175-182 --Bulatov, G., Ibraeva, Y. and Tarasevskii, P. Computing Values of Crack Characteristics in Earth Dam. 15th International scientific conference “Underground Urbanisation as a Prerequisite for Sustainable Development”. Procedia Engineering 165 (2016) 1611 – 1618 --Vandenberge, D.R. Total stress rapid drawdown analysis of the Pilarcitos Dam failure using the finite element method. Front. Struct. Civ. Eng. 8, 115–123 (2014). software tools of interest --> Optum (https://optumce.com/academic/) ZSoil (https://www.zsoil.com) SPECFEM 3D Geotech (will need a mesher) ADONIS DUNE (https://www.dune-project.org) MOOSE (Multiphysics Object Oriented Simulation Environment) Cast3m (http://www-cast3m.cea.fr) ANSYS Code Aster OpenFoam IV. Seismic Loads Review of vibration modelling in continuous media Analytical development with towards comprehension of seismic codes and provisions relevant to reservoirs/dams (may be unique for each type). OpenSees software (may be robust enough) V. The following is a decent article for large scale complex hydrology environments. Article to be analysed. To also be competent with the technological logistics for the development and evaluation of models. A major accomplishment would be studies for hydrological systems of differences ambiances. Data access and retrieval may or may not be relativity tedious. Lin, P. et al. Development and Evaluation of a Physically-Based Lake Level Model for Water Resource Management: A case Study for Lake Buchanan, Texas. Journal of Hydrology: Regional studies 4 (2015) 661 – 674 Activity will require various tools to successfully complete. Tools likely to be useful: Mathematica GIS (GRASS GIS with addons) Google Maps, Google Earth EPANET or WDNetXL Hydrology (RHESSys) USDA NRCS software HEC-HMS HEC-RAS iRIC PRMS (Precipitation Runoff Modelling System) SWAT(http://swat.tamu.edu/) MODSIM + CSUDP https://www.hec.usace.army.mil/software MODFLOW (+ Gridgen) + MT3DMS The following models will serve to compete or augment model applied in the article of Lin (2015) et al, prior. For the case of augmentation, students must have ingenuity to identify and implement relevance. MIKE SHE model (Systeme Hydrologique European) HBV model (Hydrologiska Byrans Vattenavdelning model) TOPMODEL VIC model (Variable Infiltration Capacity model) SWAT model (Soil and Water Assessment Tool) VI. Data Retreival Schemes and Logistics. Data structures and calculus to involve the following elements --> 1. Seasonal Precipitation character 2. Water source(s) other than precipitation in relevant Inflow record/flux 3. Microclimate influence Atmospheric Temperature data Humidity data Barometric data Precipitation data 4. Ecological influence Local Area Succeeding areas (in a polar coordinates sense) Preceding areas/sources (if relevant concerning natural water flow) Wildlife/species count pre-development and post development Environmental water system flow evolution (if relevant concerning natural water flow). Satellite photos to accompany for pre-development and post development (depending on type of reservoir) 5. Hydrology data of reservoir (long term record) Service demand profile Includes the variation through time Volumes Depths Water regulation activities Water temperature (near surface and beneath) Ph levels Oxygen levels 6. Cleaning or filtration procedures (with ecological impact) 7. Maintenance operations VII. The following is a good starter to develop. Then to consider other ambiances Fan, F. M. et al. Verification of Inflow into Hydropower Reservoirs using Ensemble Forecasts of the TIGGE Database for Large Scale Basins in Brazil. Journal of Hydrology: Regional Studies 4 (2015) 196 227 24. Analysis, Replication of Traffic Modelling, Simulation & Computation For the algorithms observed the type of language used or understood (Wolfram, R, C, C++) isn’t of any concern, unless quantitative simulations are needed to be observed with actual models. Interest directed towards constituents of of Computer Science, Industrial Engineering, Civil Engineering. Activity is open to Operations Management/Operation Research via special invite. (1) Field data collection and analysis PART A Will pursue at least two methods in the field for traffic data determination with pursuit of necessary associated parameters for traffic flows, rates, distribution, patterns, etc. Such field activities serve to educate students on the technologies they take for granted with highway migration. Some guides: --Al-Sobky, A. A. and Mousa, R. M., Traffic Density Determination and its Applications Using Smartphone, Alexandria Engineering Journal (2016) 55, 513–523 --Leduc, Guillaume. (2008). Road Traffic Data: Collection Methods and Applications, JRC European Commission, Working Papers on Energy, Transport and Climate Change --Yatskiv, I. et al, An Overview of Different Methods Available to Observe Traffic Flows Using New Technologies, European Commission, Eurostat CROS NTTS 2013 Programme Session 8P, Poster Session on Spatial and Mobility Statistics. --Soliño, A., Lara Galera, A., & Colín, F. (2017). Measuring uncertainty of traffic volume on motorway concessions: A time-series analysis. Transportation Research Procedia, 27(C), 3-10. General Guides --> --Ferrara, A., Sacone, S., & Siri, S. (2018). Freeway Traffic Modelling and Control (Advances in Industrial Control). Cham: Springer International Publishing. --Zambrano-Martinez, J. L., Calafate, C. T., Soler, D., Cano, J. C., & Manzoni, P. (2018). Modelling and Characterization of Traffic Flows in Urban Environments. Sensors (Basel, Switzerland), 18(7), 2020. One must consider what periods of interest should be pursued. For a respective traffic region one can pursue the case for a typical hour between some period daily of a typical weekday, however such will require very technical trials. Such can be specific towards morning commutes, or even commutes (both concerned heavily around education, labour and public administration activity purposes). The same goes for a weekend day. There may be interest for special events and associated traffic regions. PART B Example of development data accessible to the public: https://data.cityofnewyork.us/Transportation/Real-Time-Traffic-Speed-Data/qkm5-nuaq Can use model development to critique development in part A. If you don’t want to directly run to such types of websites every time, where additionally you are interested specific types of data, what can you do? APIs and API keys are crucial. Such will include data manipulation towards data analysis. How can you structure your data to be of relevance to traffic models; can serve well towards microscopic and mesoscopic traffic models for interest at hand. LIKELY TO BE USED LATER ON. (2) Fundamentals of Microscopic Traffic Flow --> Link flow theory: modeling of traffic flow on an individual link. Fundamentals of traffic flow: --variables of interest, basic flow-speed-density relationship ("fundamental equation") --Introduction to microscopic car-following models: linear car-following models, asymptotic and local stability, steady-state behavior, nonlinear car-following models, steady-state behavior. --Nagel-Schreckenberg & traffic jams, or cellular automation. Understanding of a flow diagram of a microscopic model, and possible associated “pseudo code” development and simulation. Then, calibration, say, quantifying model parameters using real-world data. --Additional Microscopic guides: <Song, D., Tharmarasa, R., Zhou, G., Florea, M., Duclos-Hindie, N., & Kirubarajan, T. (2019). Multi-Vehicle Tracking Using Microscopic Traffic Models. IEEE Transactions on Intelligent Transportation Systems, 20(1), 149-161> < Treiber, M., Kesting, A., & Helbing, D. (2006). Delays, inaccuracies and anticipation in microscopic traffic models. Physica A: Statistical Mechanics and Its Applications, 360(1), 71-88> <A. Paz, V. Molano, E. Martinez, C. Gaviria, and C. Arteaga: Calibration of Traffic Flow Models Using a Memetic Algorithm, Transportation Research Part C, 55 (2015) 432–443> <M. Yu and W. Fan, Calibration of Microscopic Traffic Simulation Models Using Metaheuristic Algorithms, International Journal of Transportation Science and Technology, 6 (2017) 63–77> (3) Microscopic Traffic Flow Tools --> MITSIMLab Multi-Agent Transport System Toolkit (MATSim) Simulation of Urban Mobility (SUMO) Has the ability to Import road networks from common network formats such as OpenStreetMap, VISUM, VISSIM, NavTeq, MATsim and OpenDRIVE One must consider what periods of interest should be pursued. Means to determine consistency between analytical development prior and such tools. (4) Fundamentals of Mesoscopic Traffic Flow --> -- variables of interest -- Functions of the manner f(t, x, V) as a probability density function, expressing the probability of observing a vehicle at a particular time, at a specified position, traversing with a particular velocity. Methods similar to statistical mechanics for computing functions in likeness of the Boltzmann equation. -- Additional Mesoscopic guides: Note: Mezzo - Mesoscopic Traffic simulator https://www.ctr.kth.se/research/current-projects/mezzo-mesoscopic-traffic-simulator-1.726113 <Burghout, W., Koutsopoulos, H., & Andreasson, I. (2006). A discrete-event mesoscopic traffic simulation model for hybrid traffic simulation. 2006 IEEE Intelligent Transportation Systems Conference, 1102-1107> <Wang, Y. and He, Z. Mesoscopic Modelling and Analysis of Traffic Flow Based on Stationary Observations. Procedia Computer Science 151 (2019) 800 – 807> <Gangi, M. et al. Network Traffic Control Based on a Mesoscopic Dynamic Flow Model. Transportation Research Part C 66 (2016) 3 – 26> <S. Yu, Y. Xu, S. Mabu, M. K. Mainali, K. Shimada, and K. Hirasawa: Q Value-Based Dynamic Programming with Boltzmann Distribution in Large Scale Road Network, SICE Journal of Control, Measurement, and System Integration, Vol. 4, No. 2, pp. 129–136, March 2011> <E. Ben-Naim and P.L. Krapivsky: Steady-State Properties of Traffic Flows, J. Phys. A: Math. Gen. 31 (1998) 8073–8080. Printed in the UK> (5) Mesoscopic Traffic Flow Tools --> The following software cater specifically for mesoscopic modelling. Means to determine consistency between analytical development prior and such tools: Mezzo-Mesoscopic Traffic simulator DTALite: A queue-based mesoscopic traffic simulator for fast model evaluation and calibration Xuesong Zhou & Jeffrey Taylor | Filippo Pratico (Reviewing Editor) (2014) DTALite: A queue-based mesoscopic traffic simulator for fast model evaluation and calibration, Cogent Engineering, 1:1 (6) As well, the following software has a strong reputation: TRANSYT-7F Determine scale of applicability (7) Fundamentals of Macroscopic Traffic Flow - Macroscopic models: being parallel to fluid dynamics and PDE, which balance laws for specific gross quantities of concern, say, the density of vehicles, or their mean velocity. Mathematical models of traffic flow includes both ODE and PDE. Additional guides-- <G. Brettia, R. Natalinib, and B. Piccoli: Numerical algorithms for simulations of a traffic model on road networks, Journal of Computational and Applied Mathematics, 210 (2007) 71 – 77> <A. Spiliopoulou, I. Papamichail, M. Papageorgiou, I. Tyrinopoulos, and J. Chrysoulakis: Macroscopic Traffic Flow Model Calibration Using Different Optimization Algorithms, Transportation Research Procedia, 6 (2015) 144 – 157> <Khan, Z.H. & Gulliver, T. A Macroscopic Traffic Model for Traffic Flow Harmonization. European Transport Research Review. (2018) 10: 30> To then simulate developed macroscopic model based on such articles involving real data and compare with developed simulated microscopic model results from software. NOTE: unless one is very well seasoned and competent in traffic flow modelling the following topics likely will be counter-productive in regards to developing a foundational of endurance and clarity. Will not treat such subjects will high detail concerning this activity. Will mostly let the software tools guide use: Traffic signal control Route Guidance and Traffic Assignment in Networks The mathematical intellect may be too impeding, viscous, intangible or have the “cuffed to cannon ball and chain in water effect” concerning feedback/automatic control, embedded systems and programming logic controllers, which concerns of technical fields of engineering. Operational Research, Systems Control and Computer Science constituents can possibly tackle such two subjects independently.

25.Transportation Planning: Methodology and Techniques (repeatable) Open to Industrial Engineering constituents as well. Concerns transportation planning and provides the student with an understanding of transportation planning models, including travel demand models of trip generation, trip distribution, mode choice, and traffic assignment. Instruction in econometric model estimation methods and use of behavioural models in service design, marketing and prediction. Practical problems are assigned to provide familiarity with models used and experience in data handling and estimation. The reason for this activity not being a course is due to the fact that many ambiances are not in a rapid infrastructure growth age like China for various years. Else, other ambiances are not that big and dynamic to have transportation planning be highly focused on. Activity will have some demands with development of statistics skills; not for the sake of flattery, but towards meaningful use with computational environment tools. Activity will require for you to have at least successfully completed the Probability & Statistics course in your curriculum. Formalities --> A. Activity will not indulge you with any matrix algebra finesse because matrix algebra is just a tool you use when you stumble across grotesque linear systems. Justice from the universe and its wisdom, systems encountered will be too big to be manually focusing on flattery with diagonalizations, inverse, adjoint[adjoint[adjoint]] and so forth. If you can solve a 2 by 2 system represented by a box of numbers, well, that’s good enough in terms of understanding what you’re trying to do. The import thing with systems of equations is understanding how they practically come about as models without excessively stressing fantasy assumptions against non-linearity; a computational tool can do the rest. Some will not be satisfied unless you have encountered 3 by 3 systems, but at the end of the day, it’s just a time-consuming flattery. Optimisation is optimisation; we don’t dedicate our lives exclusively to pig pen matrix algebra. B. Assumption of solid statistics background As far as civil engineering goes practical statistical estimation cases may be quite elusive and idealistic, but they do exist. For our purposes statistical methods will be highly applied to serve engagement with a computational environment with real data. Much theory will be omitted; people have gotten their spotlight for centuries to highlight theory. In this activity we have civil engineering goals to accomplish. One should expect that normal distribution may be highly trivial or idealistic, due to the fact that traffic is highly subject to black swans such as traffic jams, evacuations and so forth. Additionally, such black swan data can be result of “getting to know your new highway”, rush hours, major venue events, government lotteries, cash crunches, and possibly other things. Hence, realistic data will have much skew, kurtsosis, and in some ases very small variance. No one is waiting patiently for the CLT to show up weeks and months later. Will begin with building competent computational skills in the following in a highly advanced and fast paced manner (due to assumption of statistics background) concerning traffic data--> Data acquisitions (querying, called parameters, sources, APIs, etc.) Basic Data Modelling Curve fitting (deterministic) Descriptive statistics from data sets Data distributions MLE for high volume data sets (know the right distribution type) Advance Data Manipulation Missing data and possible resolutions Making data frames and common activities with data frames Determining data distributions P-P, Q-Q, goodness of-fit Determining parameters of distributions Hypothesis tests assuming non-normal distributions being prevalent Analysis of variance. What for? Practicality over obnoxious flattery? Regression Correlation and bivariate models Multivariate structure Evidence for variables by data OLS assumption on non-OLS F-test, Vuong, AIC and BIC for choosing models Summary statistics for determination of good or bad models Training sets, test sets, etc. Time series may prove invaluable at times Such above data skills development in no way completes the activity; such skills as plainly precursors to the real traffic planning pursuits. NOTE: software mentioned in activity 24 may or may not be required to acquire idealistic traffic flow dynamic parameters; deterministic structure data often precedes a stochastic or statistical analysis for a strong overall analysis. Hopefully software in activity 24 are GIS relevant (else TransCAD, which may not treat micro, meso and macro in all). Outline --> Overview Travel Demand Theory (strong development) Urban Transportation Model System (strong development) Estimating Methods (highly extensive) Data Collection issues Trip Generation (highly extensive) Trip Distribution (highly extensive) Model split (strong development) Traffic Assignment and Direct Demand Models (strong development) Civil engineering texts to structure on (CRITICALLY, don’t assume lack of importance due to descending order) --> Ben-Akiva and Lerman, Discrete Choice Analysis Domenich and McFadden, Urban Travel Demand Oi and Shuldiner, An Analysis of Urban Travel Demand Ortuzar and Willumsen, Modelling Transport Tasks: 1. Demand-Supply Equilibration & Urban Transportation Modeling System (UTMS) 2. R and Mathematica Familiarization and Data Exploration Distribution 3. Estimation of Trip Generation Models: Basic Issues Distribution 4. Estimation of Trip Generation Models: Advanced Models Distribution 5. Trip Distribution Models Distribution 6. Estimation of Mode Split Models Distribution 7. Public transportation optimisation -Interval rate versus empirical methods of actual observation from trials -Will make use of some microscopic and mesoscopic traffic simulation software (with particular infrastructure of interest wherever); compare with prior. -Demand Revenue Management Concerns hypothetical and real systems. This likely will include thinking beyond brute mathematics to develop economic practicality; prior tasks will highly influence. Will make use of mentioned texts earlier. One should compare development and conclusions with the current system in place wherever. NOTE: task 7 will be based on prior tasks 1 – 6. As well, areas in task 7 may be sequential. Time Series and model selection with training sets, test sets, and cross validation may or may not also arise. Likely there will also be a re-evaluation process through time. C. Project Management -Framework for Public-Privacy Partnerships (PPP) -Organisational structure (PPP) -Elements Shareholders C-level executives Analysts Contractors and labour force auditing Integrity, Quality and safety gov’t agencies throughout process -Choice among project management styles. Factor to consider: Scale Timing Elements (prior) with scheduling Capital flow audits or liquidity audits -Costs and Operations Smith A.J. (1995). Estimating, Tendering and Bidding for Construction, Macmillan Building and Surveying Series. Palgrave, London Savas, B. and Al-Jibouri, S. (2016). Efficacy of Estimation Methods in Forecasting Building Projects’ Costs. Journal of Construction Engineering and Management, Volume 142, Issue 11 -Principal-Agent Problem: misplaced incentives encouraging strategic manipulation -For earlier hypothetical projects or real systems developed from B7 will try to analyse how such influences the structure of the acting elements and costs estimation. D. Consider the following real world projects (subject to change) Bang Na Expressway, Thailand Montreal REM Crossrail, U.K. Will gather respective government planning, operations and contracts data, and quantitative data. Two major concerns are: Revenue forecasts (rate of return in 2 year increments) Changing costs Will consider the knowledge acquired and skills developed prior, with possible need of additional knowledge and skills for determination of such two concerns. The latter concerns means to derive the published figures at the respective periods. NOTE: may be more technical than what one believes for both concerns. NOTE: may often have to apply various metropolis elsewhere to acquire broad and robust activity. 26. Water Distribution Network’s Modelling & Calibration. Sensor Placement for Leak Location in Water Distribution Networks Using Genetic Algorithms Open to constituents of Civil Engineering, Mechanical Engineering, Operational Research (Operations Management) and Computer Science. (i) Acquaintance and modelling with EPANET2 and WDNetXL; may require use of a GIS and Google Maps later on. (ii) Modeling and calibration of a small and poorly documented (portion of the) water distribution network (WDN) that shows pressure problems. Field campaigns are conducted to reduce the inaccuracies found in the inventory’s drawings and to aid building a first WDN model. A trial and error procedure was then used to produce successive refinements for the desirable WDN’s model fit. The following article to serve as guide: --Alves, Z., Muranho, J., Albuquerque, T., and Ferreira, A., Water Distribution Network’s Modelling and Calibration. A Case Study Based on Scarce Inventory Data, Procedia Engineering 70 ( 2014 ) 31 – 40. (iii) Applying Data Assimilation (DA) methods to a Water Distribution System Model to improve the real time estimation of water demand, and hydraulic system states. A time series model is used to forecast water demands which are used to drive the hydraulic model to predict the future system state. Both water demands and water demand model parameters are corrected via DA methods to update the system state. The results indicate that DA methods improved offline hydraulic modelling predictions. Of the DA methods, the Ensemble Kalman Filter outperformed the Kalman Filter in term of updating demands and water demand model parameters. Incorporates EPANET2 (or WDNetXL) usage; may require use of a GIS (GRASS GIS) and Google Maps. Data request from WASA or corresponding utility service may be needed. Develop such to the best of ability with ambiances of choice --> --Okeya, I. et al. Online modelling of water distribution system using data assimilation. Procedia Engineering 70 ( 2014 ) 1261 – 1270 (iv) Acquaintance with the RELOPT model Incorporates EPANET2 (or WDNetXL) usage; may require use of a GIS and Google Maps. Data request from WASA or corresponding utility service may be needed. After acquaintance with EPANET2 to analyse and comprehend the RELOPT model based on Journal article: --Mohamed Abdel Moneim (August 1st 2011). Modelling Reliability Based Optimization Design for Water Distribution Networks, Scientific and Engineering Applications Using MATLAB, Emilson Pereira Leite, IntechOpen < not content with MATLAB use as the only option >. Reliability-based optimization design prime directive for a water distribution network using modelling technique of Mathematica programming language. ill like to focus on ambiances of interestGoals: Acquainting optimum least-cost design for water distribution networks using new efficient and time consumed method. Define risk components for water distribution networks. Define the most critical components of water distribution networks that affect the level of serviceability under different cases of operation (i.e. define level of service under risk). Analysis, evaluation and treating reliability for water distribution networks. Define the reliability of water distribution network over a given period of time. Define the optimum solution of water distribution network that achieve the optimum lease-cost design and certain accepted reliability in one time (reliability-based optimization). Develop stand-alone reliability-based optimization model comprising all the above-mentioned objectives. Getting the reliability-based optimization design for water distribution networks requires searching among several available population set of solutions. RELOPT model consists of the following components: Hydraulic solver EPANET2: consists of the dynamic libraries that are required to be called by Mathematica program for hydraulic analysis. Pre-estimation model (AGM): this sub-model provides the lower and upper bounds that are required for OPTWNET to start optimization search process. Optimization model (OPTWNET): defines the optimum solution using LAGA. LAGA automatic search engine module. Reliability model (RELWNET): this model is connected with three sub-models <minimum cut-sets model; Generic Expectation Function model; reliability calculation model>. The model passes the final calculated reliability to the main model RELOPT. (v) Optimisation and Reliability Assessment of Water Distribution Networks Data request from WASA or corresponding utility service may be required, and and may require use of a GIS and Google Maps--- --M. Abunada, Trifunović, N., Kennedy, M., and Babel, M., Optimization and Reliability Assessment of Water Distribution Networks Incorporating Demand Balancing Tanks, Procedia Engineering 70 ( 2014 ) 4 – 13 --Djebedjian B., Reliability-Based Water Network Optimization for Steady State Flow and Water Hammer. ASME. International Pipeline Conference, Volume 3: Materials and Joining; Pipeline Automation and Measurement; Risk and Reliability, Parts A and B (): 727-737. Note: Acquiring NORAT (Networks Optimization and Reliability Assessment Tool) towards integration with EPANET 2 may or may not prove difficult. Nevertheless, there are alternatives which require more direct procedures integrating algorithms, CAD, EPANET 2, etc. (vi) Sensor placements to detect leakage: After after analysis of the following journal articles, to apply to local and chosen ambiances. Concerns water pressure readings at nodes and other places of interests for particular date(s) corresponding to leakage. To comprehend and implement algorithms towards predictions for actual source of leakage(s). by use of pressure history data in grid of interest where scheme will be applied and compared to past maintenance schedules at sites. Numerous genetic algorithms will be employed and compared. For robustness, will employ the different schemes from each article and compare results. Data request from WASA or corresponding utility service and may require use of a GIS and Google Maps along with EAPNET2 or WDNetXL for use in pursuit --> --Steffelbauer, D., Neumayer, M., Gunther, M., and Fuchs-Hanusch, D., Sensor Placement and Leakage Localization Considering Demand Uncertainties, Procedia Engineering 89 ( 2014 ) 1160 – 1167 --Casillas, M., V. et al, Optimal Sensor Placement for Leak Location in Water Distribution Networks Using Genetic Algorithms, Sensors 2013, 13, 14984-15005 --Puleo, V., Freni, G., and La Loggia, G., Pressure Sensors Positioning for Leakages Detection Under Uncertain Demands, EPiC Series in Engineering, Volume 3, 2018, Pages 1713-1717 Note: there will likely be issues if there are multiple sources of leaks. For such a circumstance one must cleverly segment grid involving knowledge of models, formulas, etc.). (vi) Consider the following: -- Al-Ani, D., and S. Habibi, S., Optimal Operation of Water Pumping Stations, Water and Society II, WIT Transactions on Ecology and The Environment, Vol 178 To adjust to ambiance(s) of interest. Based on ambiance(s) to apply methodology of the given journal article and compare with the active authentic pumping settings operations of ambiance(s). Then will try to compare genetic algorithms with differential evolution applied in article to observe results. Incorporates EPANET2 or WDNetXL usage; may require use of a GIS and Google Map. Data request from WASA or corresponding utility service. 27. Piping Design and Systems in the Energy Sector (repeatable) Open to Mechanical Engineering and Industrial Engineering constituents. Concerns fossil fuels and fossil gases i. Properties of gases and liquids from fluid mechanics and applied hydraulics (to include expansion, compression) ii. Chemical Characteristics 1.Chemical formulas for different hydrocarbon gas mixtures AND oil 2.Respective Density (different temperatures and atmospheric pressures) 3.Respective Auto-ignition Temperature 4.Respective Combustion Temperature 5.Respective Combustion Model 6.Respective Burn Rate Behaviour (at different atmospheric pressures) 7.Human intake Epidermis contact Inhalation Oral intake Eye contact Eco-friendly cleaners (biological and environment) 8. Hazard diamond 9.For the products from processing or refinement will also be responsible for similar data to 1 through 7. Respective Exhaust Products (from ignition/combustion) Raw mixtures (natural gas and oil) Refined or processed products iii. Drilling rigs and extraction systems Drilling Characteristic components and CAD displays of critical components System Designs Applied Power Systems Methods of deployment & foundation stability in respective environment Operation Procedures and regulations Components and systems for extraction, pumping and transfer Characteristic components and CAD displays of critical components System Designs Applied Power Systems Methods of deployment and foundation stability in respective environment Operation procedures and operation regulations Operations parameters Regulated chemical dispersants and their chemical characteristics Regulation on chemical dispersants Operation procedures and operation regulations iv. Environments Discovered reserves Geological/Geotechnical/Oceanography profiles for networks/transport Habitat and sensitivities Rock and Soil Seismology profiling and seismic history Possible weather influences on operations Environmental protocols (Geo, Marine and Weather) Ecological concerns and contamination mitigation methods Economy (Markets and Demand) v. A quite difficult or rough phase in energy infrastructure is its systematic and operational planning. What research must be done to develop planning and logistics? vi. Consider storage, processing plant(s) and supply chain networks to be developed. Will consider hypothetical regions of development, mining, processing, refining, service distribution and so forth. Will choose actual places on the map, but such places will not necessarily have observed systems in place. Raw storage --> refining/distilling --> storage/reserves --> supply For a warm up develop the following: Liquid Fluid Flow Process design Review of laws in fluid mechanics Modelling behaviour w.r.t. fluid properties and geometries Patrascioiu, C. (2011). Chapter 3. Fluid Flow Control. In: Papantonis, D. Centrifugal Pumps. IntechOpen (account for gases as well) Replicate findings and exhibitions from given above chapter, or improve upon Modelling, control/controllers and simulation (simple to complex systems) with the following elements Natural fluid viscosity (may not be relevant to gases) Pumps (centrifugal, volumetric), control valves, “hydraulic resistance”, “transducers (flow, differential pressure), gauges Will then extend the process design to include phase changes (liquid to gas or gas to liquid), hence extension with evaporators, condensers and air pumps/air compressors (going from modelling to simulation like prior for such three incorporated into the system as well). Next, to develop systematic flow diagrams for the oil refinery and natural gas processing. Primitive development of process design by use of the following WITH most of (ii) in mind: --STANJAN --COCO (+ ChemSep), DWSIM (+ ChemSep), ESMO simulator, and Wolfram SystemModeler. NOTE: modelling fluid behaviours (liquid and gas), modelling components, controllers and developing simulations are expected. Then, even further, for the “sophisticated development” the following software to be of assistance Autodesk Plant Design Suite Autocad Plant 3D Even at the processing to product(s) operation there are channel networks that also require reliability development and sensing features with data processing. EPANET can be a worthy tool for monitoring, but for the case of natural gas further sensing is required to detect possible leakage into the atmosphere. Supply chain ports to be incorporated in design. vii. Oil/natural gas products storage and plant layouts must be developed: Literature Guides for piping design and networks --> --Adewumi, M (2020). Phase Relations in Reservoir Engineering. LibreTexts NOTE: develop consistency between above and most of (ii). --Barker, G. B. The Engineer’s Guide to Plant Layout and Piping Design for the Oil and Gas Industries. Gulf Professional Publishing, 473 pages --Moran, S. (2017). Process Plant Layout. Butterworth-Heinemann, 756 pages --Facilities Planning (third edition), J. A. Tompkins, J. A. White, Y. A. Bozer, J. M. A. Tanchoco, John Wiley & Sons, 2003. 2) --Facility Layout and Location: An Analytical Approach, R. L. Francis, L. F. McGinnis, J. A. White, Prentice Hall, 1992 --Zhao, P. et al. The Design of Oil Well Production Engineering Analysis System. The Open Mechanical Engineering Journal, 2015, 9, 437 - 442 viii. Supply chain optimisation The aim of this study is to design and optimize an integrated natural gas supply chain (NGSC) formulated as a mixed integer linear programming (MILP) model or Network Optimisation model. Optimisation framework for natural gas/oil supply chain. Gas/oil storage process in the supply chain. The integrated strategic and tactical planning of gas supply chain is performed. Location-allocation and capacity of facilities and pipeline routes are considered. The proposed model to be applied to a real world case study based on information derived from Ambiance’s NGSC. Significant effect of parameters of operating costs and demand volume. The following literature can be applied to incorporate more realistic attributes. --Cimellaro, G. P. et al. (2015). Resilience-Based Design of Natural Gas Distribution Networks. Journal of Infrastructure Systems, volume 21, Issue 1 --T.C. Pharris and R.L. Kolpa. (2007). Overview of the Design, Construction, and Operation of Interstate Liquid Petroleum Pipelines. Argonne National Laboratory. --S. M. Folga. (2207). Natural Gas Pipeline Technology Overview. Argonne National Laboratory. ANL/EVS/TM/08-5 https://publications.anl.gov/anlpubs/2008/02/61034.pdf --T. M. El-Shiekh (2013) The Optimal Design of Natural Gas Transmission Pipelines, Energy Sources, Part B: Economics, Planning & Policy, 8:1, 7-13 Infrastructure tools to apply --> R packages (optrees, igraph) GASCalc 5.0 Autodesk Plant Design Suite Autocad Plant 3D GIS (GRASS GIS with addons) EPANET + EPANET Toolkit (hopefully critical adjustments for oil and natural gas can be made) Regulation/control Pressure readings Temperature readings (somehow will incorporate) Leakage detection for gas (consider when in the real world) Distribution of detectors likely based on reliability modelling GPS/telemetry development It’s not about a “blip” at one moment in time Designing a monitoring scheme incorporating robust data analysis Requires at least two sensors at one point Maintenance/upgrade cycles NOTE: chemical process design should logically come before plant designs, infrastructure and networking. NOTE: concerning auto-ignition and auto-combustion temperatures, such hazardous points can be achieved much easier on small scales than large scales. An somewhat analogy, drying your laundry on a clothesline in the sun, namely, you don’t need a heat wave to dry them. Applies to plants and networks. NOTE: some of the following terms, measures and data structures should necessarily arise: Distributed pressure sensing Distributed temperature sensing Distributed leakage detection (for natural gas) High Pressure Distribution System Low Pressure Distribution System Maximum Allowable Operating Pressure Season set point pressures Operating pressure regulations Over pressure Protection Regulator stations Gate Station or Point of Delivery Farm Tap or Field Regulator Abnormal Operating Conditions (around 8 types) Mains and Services Valve Sectionalizing Relief Valves Remotely Operated Valves Heating Seasonal Load Non-heating Seasonal Load Location Class Specified Minimum Yield Strength (SMYS) Heating Degree Day Summary of Stations and Local Production Gas Supply Points Summary of System Design by Operating Pressure Customer Management Module Load Data Regulator Station Analysis Regulator Operational Database Weather and Regulator station databases Area Isolation Module Vendor Equipment Sizing Software Hardening the System Against Natural Disasters Data and computational tools --> Google Earth Engine Kaggle Energy administration data/databases ADIOS (Automated Data Inquiry for Oil Spills) Generalised Environmental Modelling System for Surface Waters (http://gemss.com/gemss.html) Hopefully environmental geometries and settings can be adjusted Mathematica Excel NOTE: geological topography weather patterns can have drastic effect on components and network optimisation. Seismic activity concerns, soil and rocks mechanics are other issues as well. Such also implies that taking advantage of the gravitation potential isn’t always an option. ix. Transmission and Distribution System Reliability Analysis Maintain Adequate System Pressures (MASP) Maximum Allowable Operating Pressure (MAOP) Over Pressure Protection (OPP) Monitoring and Controlling System Pressures and Flows System Looping Redundancy Station Reliability Integrity Management Odorization System Constraint Analysis x. Real Networks Will analyse various real networks and determine any features, operation systems and components taken for granted or overlooked. Distribution networks of various provinces, cities, towns, etc. If we can’t acquire the actual distribution networks, we will develop it based on general idea, expectation, demand and mapping by a GIS, then subjugating EPANET and other software to such. xi. Reliability Assessment of Oil/Natural Gas Distribution Networks Goes beyond reliability at stations. Yet, will have similar parameters for lines like in prior (ix). EPANET can be applicable in the same manner it’s used for water networks to some degree. You will have pressure sensing at various points to access data. Temperature sensors will be needed as well for both oil and gas. For natural gas, additionally, special sensing to detect leakage into the environment is a necessity. Linear optimisation and genetic algorithms to apply for network optimisation. Often stochastic skills and tools will be applied for reliability. Reliability concerns the following Networks between mining and refining Supply Chain networks xii. Multiperiod Optimisation fr field production Will situate the following journal articles to environmnts of interest. GIS, Mathematical and R to be available. Awasthi, U., Marmier, R. & Grossmann, I.E. Multiperiod optimization model for oilfield production planning: bicriterion optimization and two-stage stochastic programming model. Optim Eng 20, 1227–1248 (2019). xiii. Energy Substitutes in Planning Due to environmental statues, mandates, social preferences and so forth alternative energy sources are becoming quite premier. --Consider proposed or well planned out alternative energy projects to be implemented. This includes sites and supply networks, capacity, etc. --It may also be the case that media such as wind, solar and nuclear energy may not be prevalent perpetually; storage facilities are realistic. --It may the case that progressive administrations would like to cap their fossil fuel/gas fossil emissions, hence switching to various energy sources at various times with higher capacity. --Natural gas with turbine engineering/technologies are quite prevalent in the creation of power supply. --Consider government grants to residencies and businesses with solar power usage xiv. Sensing, predictive maintenance tools and implementation Analysis of the various technologies implemented in practice Develop of sensing and predictive maintenance lab projects for such. WILL NOT BE USING ACTUAL FOSSIL FUELS/FOSSIL GASES. NOT CONTENT WITH USING SERVICE WATER FOR THIS PARTICULAR ACTIVITY. NEITHER RIVERS NOR LAKES, NOR ESTUARIES. Used cooking oil in contained environments Old car oil, etc. in contained environments Seawater with only one direction (not back into sea) Develop wind tunnels and vents leading into pipe networks imbue flowing air with rotten eggs smell or something Possibly also in use with other sensing are particle sensors Pipes, valves, pumps, gauges and storage will be relatively smaller than real networks. xiv. Life Cycle Assessment for plants and supply networks Life Cycle Analysis (LCA) ISO 14000 Series Data sources used in LCAs are typically large databases Will identify databases and means towards assimilation Introspection, querying, etc., etc Software: OpenLCA 28. Industrial Hydraulic Systems (repeatable) Systems of interest are those that play crucial roles in water service (industrial residential and metropolitan) Mandatory pursuits --> For hydraulic power units and complex hydraulic systems will incorporate heavy Analysis Modelling Hydraulic circuits Control and Simulation Energy accounting and life Cycle Assessment Will incorporate heavy assists from WASA concerning facilities, equipment, systems, and grids. Tools to apply --> GIS (GRASS GIS with addons) EPANET and/or WDNetXL Modelica libraries PRELIMINARY SKILLS TO REINFORCE BEFORE PURSUITS--> 1. Setup equations to analyse small piping systems that include branches, parallel pipes, loops and/or reservoirs. 2. Students will learn how to apply the fundamental concepts of Energy, Momentum and Continuity will be discussed in solving practical design problems. Many problems encountered will be mirrored by practical understanding of energy and energy losses, namely, head and head loss that drive the flow of water, with various methods of estimating head loss and applied with computations to select pipe sizes, and analyse the performance of simple compound systems will be covered. Energy, momentum and continuity modelling can be introduced alongside various topics before formal engagement at designated schedule in course schedule. 3. Nonlinear relationship between head loss and flow. Determine flow distribution in simple networks using the Hardy Cross Method. Applying the Newton-Raphson method (and possibly more advance methods). 4. Employing EPAnet and/or WDNetXL, analyse and design small piping networks for flow, pressure distribution and pump requirements. SystemModeler/Modelica to be used alongside EPAnet and/or WDNetXL. 5. Develop lumped operating characteristics for series and parallel pumps. 6. Identify the basic elements of your network design that are specifically controlled by federal, state and/or local regulations or codes. 7. Design pump placement to prevent cavitation. 8. Design open-channel systems based on uniform flow analysis. 9. Design open-channel transitions using energy concepts. 10. Design a sequence of uniform channels to satisfy a client’s stated objectives; the channels differ in bottom slope or width and may incorporate transitions produced by rapid changes in bottom elevation or width. 11. Explain the importance of professional licensure in the context of responsibility for your design. 12. Write technical memos that report the results of design/ analysis and employ appendices to provide sufficient information to check and confirm the results. 13. Recognize the importance of professional and ethical responsibilities. 14. Labs with software (SystemModeler/Modelica, EPAnet and/or WDNetXL) for modelling design(s) and simulations to accompany hands-on activities. Labs will be implemented at appropriate times in course. 29. Reinforcement of Activities from Hydraulics Engineering Design course 30. Calculate impervious surfaces from spectral imagery (repeatable) Ground surfaces that are impenetrable to water can cause serious environmental problems, including flooding and contaminated runoff. Because impervious surfaces are such a danger, many governments, like the City of Louisville, Kentucky, charge landowners with high amounts of impervious surfaces on their properties. To calculate fees, the you'll segment and classify aerial imagery by land use to calculate the area of impervious surfaces per land parcel. https://learn.arcgis.com/en/projects/calculate-impervious-surfaces-from-spectral-imagery/ NOTE: may pursue development with the mentioned software....OR MAKE USE OF GIS OF YOUR CHOICE. 31. Comparison of Regression Tools for Regional Electric Load Forecasting (repeatable) N. J. Johannesen, M. Kolhe and M. Goodwin, "Comparison of Regression Tools for Regional Electric Load Forecasting," 2018 3rd International Conference on Smart and Sustainable Technologies (SpliTech), Split, Croatia, 2018, pp. 1-6. Comparative analysis of the various regressions tools when implemented with use of whatever data that’s available. NOTE: may incorporate Ensemble Learning as well. 32. Life Cycle Costing PART A (LCC) Consider a project in development phase or past where competitive alternatives are determined to be equally “feasible”. Activity concerns LCC development. Note: analytical modelling is a necessity before software use, because you must thoroughly understand what you’re doing. Likely, multiple projects will be pursued. The following serve as strong guides for pursuit of LCC --> Life Cycle Costing ISO 15686-5:2017 Kneifel, J. and Webb, D. (2020). Life Cycle Costing for the Federal Energy Management Programme. NIST Handbook 135 Software: https://www.nist.gov/services-resources/software/building-life-cycle-cost-programs Note: will not only consider BLCC (texts give other areas in LCC) Further Assists: --https://www.gsa.gov/node/81412 --Dhillon, B. S. (2009). Life Cycle Costing for Engineers. CRC Press --Energy Price Indices and Discount Factors for Life Cycle Cost Analysis, National Institute of Standards and Technology, Gaithersburg, MD Example applied case for imagination--> http://www.eng.auburn.edu/research/centers/ncat/files/aaptp/Report.Final.06-06.pdf Note: the development analysis and software mentioned earlier possibly can be use to validate Auburn’s final report. Note: current proposed or developing projects in ambiance will also be assessed. PART B (Bidding) Will pursuit LCC evaluation for (bid) contracts with utilities such as TSTT, T&TEC, WASA, Works, etc. subject to part B. NOTE: analysis and evaluation likely will be very comprehensive and quantitatively technical. For past, present or future bid contracts, first, comprehensive and highly quantitative LCC will be orchestrated towards findings. Then by such LCC will investigate which bid contracts are favourable; history in procurement, quality service and punctuality of competing firms will be considered. 33. Analysis of PET Bricks The inability in providing sustainable solutions towards resource efficiency through product-life extension, redistribution, remanufacturing, recycling, as well as re-engineering of wastes to maintain economic, society, and ecological balance, are the challenges facing the environment in the last decades. However, revolutionary 'green' types of bricks and construction materials could be made from recycled PVC and other synthetic materials. Consideration of PET and possibly other materials to recycle to produce bricks. Construction bricks made from Polyethylene Terephthalate (PET) and other plastics A. Materials exhibit myriad properties, whether the following will involve both intelligence from databases and lab/field experiments comparing tradition masonry bricks with PET bricks: --Mechanical properties(types of loadings, stress analysis, strain analysis, stress – strain analysis, factor safety, failure theories (Maximum Shear Stress Theory, Maximum Normal Stress Theory, Maximum Strain Energy Theory, Maximum Distortion Energy Theory), fracture mechanics, fracture toughness) --Chemical properties --Electrical properties --Thermal properties --Electromagnetic perturbation analysis (various wavelengths) B. Will develop Finite Element Analysis for such bricks integrated in a housing unit to investigate various “punishments” or investigate tolerances and failure analysis. Compared to conventional masonry bricks. C. Health hazards --Cement dust exposure with use of bricks --PET (manufacturing, high temperatures, other hazards) --Comparative greenhouse gas emissions D. Economics and Sustainability (PET versus conventional masonry) --Material longevity and integrity for extreme weather (on both sides of the spectrum) --Thermal insulation practicality (winter and summer) --Cost to make one brick (conventional versus PET) Does mass production tell a different tale? --Product speed (with quality) --Carbon footprint and greenhouse gas emissions --Life Cycle Assessment for production versus standard bricks OpenLCA applicable --Life Cycle Costing OpenLCA applicable --Cost Benefit Analysis E. Structural properties to investigate for PET bricks --Integration with structural members (if cases ever arise) --Means of integrating PET bricks together versus conventional includes time costs --Bearing capacity concerning soil --Resilient modulus of the subgrades F. Developing a sustainable non-industrial plant for PET, also being subject to prior phases. Includes LCA.

34. Repetition of Geotechnical Engineering activities from course Prerequisite: Geotechnical Engineering course 35. Aerodynamics of Buildings Apart from goals, parameters and constraints applied towards design and construction of buildings, there’s also need for aerodynamic investigation or analysis to acquire pleasant environments and safety. The following literature can provide such: General Knowledge (GK) -- Cermak, J. E. (1976). Aerodynamics of Buildings. Annual Review of Fluid Mechanics 8:1, 75-106 Lawson. (2001). Building Aerodynamics. Imperial College Press Mooneghi, M. A. & Kargarmoakhar, R. (2016). Aerodynamic Mitigation and Shape Optimisation of Buildings: Review. Journal of Building Engineering, Vol. 6 pages 225 – 235 Wind Loads (WL) -- Government building code for wind loads Melbourne W.H. (1988) Definition of Wind Pressure on Tall Buildings. In: Beedle L.S. (eds) Second Century of the Skyscraper. Springer, Boston, MA. Pressure Integration Technique for Predicting Wind-Induced Response in High-Rise Buildings Aly, A. M. (2013). Pressure Integration Technique for Predicting Wind-Induced Response in High-Rise Buildings. Alexandria Engineering Journal 52, 717 – 731 Konstantinov, A. and Ratnayake, M. L. (2018). Calculation of PVC Windows for Wind Loads in High-Rise Buildings. E3S Web of Conferences 33, 02025 The following tools can be used to compare with manual determinaton of wind loads for assurance: ASCE 7: https://asce7hazardtool.online ATC Hazards by location: https://hazards.atcouncil.org Simulation and Experimentation -- Analysis/comprehension of the factors and building components influential to pleasant environments and safety based on GK and WL Analysis of various tools and techniques for aerodynamic analysis General building geometry with CFD applied for aerodynamic investigation Detailed design of buildings subject to CFD for aerodymanics Implies the inclusion of windows, vents, etc., etc. Also with various unconventional configurations A building’s aerodynamics influence on background environment Influence on shorter buildings (case scenarios for different heights) Influence on street level Aerodynamics of a block of high rise buildings Flow among the high rise buildings Influence on shorter buildings (case scenarios for different heights) Influence on street level Analysis and replication of observed experimentation in the following literature: Aly, A.M., Thomas, M. & Gol-Zaroudi, H. (2021). Experimental investigation of the aerodynamics of a large industrial building with parapet. Advances in. Aerodynamics. 3, 26 Hui, Y. et al (2013). Pressure and Flow Field Investigation of Interference Effects on External Pressures Between High-Rise Buildings. Journal of Wind Engineering and Industrial Aerodynamics 115, 150 -161 36. Risk Management and Risk-Based Cost Estimation Guidelines: Nevada Department of Transportation. (2021). Risk Management and Risk-Based Cost Estimation Guidelines: https://www.dot.nv.gov/home/showpublisheddocument/4518/637637657516400000 Collaboration with DOT, Works, WASA, etc., etc. Guidelines applied to pending or ongoing infrastructure projects. Will be highly quantitative. Alongside given guidelines above “traditional” methods can be developed and implemented for compare and contrast. Hopefully projects’ time lines aren’t beyond the time window students have, else, only forecasted development can be accomplished; variances and post assessments are highly desired in general.

For all activities there will be a secure database archive for all participants and supervision constituents for respective activity in chronology. Activities will be field classified. There are MANDATORY activities to be done by Civil Engineering students under Geology; check such section. Other “summer” and “winter” activities open to Civil Engineering-- Aerospace Engineering: H Mechanical Engineering: Q, R, T, W, X For such activities check posts related to them.

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ENGINEERING

# ENGINEERING ----The engineering programme concerns competence and professionalism in technical engineering skills. Such programmes are structured for smooth transition into graduate programmes in engineering, concerning efficient usage of time spent on degree. ----For the Modelling & Simulation Lab course An 18 weeks course to acquire smoothness, sustainability and retention. One must choose appropriately when the course is taken concerning the thorough (and intense) usage of Wolfram SystemModeler, Modelica AND other software for advanced and professional activities. All students relevant to this course must have minimum prerequisites, Feedback Control, and Practical Programming in C for Engineering II (or C++ II counterpart). Additionally, upon proper enrolment in course, students in AE and ME should be well on their way past Systems Modelling I & II; for EE and COMPE students they should be well past Circuit Analysis i & II, Solid State Devices I. NOTE: Electrical Engineering and Computer Engineering students will share unique course sections. Aerospace engineering students will have their own cross section. Mechanical Engineering students will have their own course section. This Modelling & Simulations Lab course concerns advance treatment of various general integrated engineering or process systems with SystemModeler and whatever else to apply. Course strives to have students be competent, fluid and comfortable with development, computation and simulation after physics and mathematical modelling development. Course is NOT about any mathematics department, nor in any way caters for a mathematics major. Idea of SystemModeler --> www.wolfram.com/system-modeler/ www.wolfram.com/wolfram-u/catalog/product-training/system-modeler/ Course grade is constituted by individual quizzes, individual exams (minimum of 3) and group projects. For group projects: (i). Each project concerns at least three SystemModeler/Modelica demonstrations, namely, one demonstration will be picked by instructor, the others being students’ choice. (ii). Projects will involve development of systems and their control in engineering; data processing, etc., etc. Students to research the systems concerning the constituents, integration, control, performance, etc. Included will be written description of respective system and its components, with appropriate physics, engineering and mathematics models. Students must also submit computation and/or CAD tool/system modelling documentation of developed project before demonstration begins. (iii). Students groups will conduct live active demonstrations developing the system in question; each member of a group likely to take turn in development. Mathematica likely will also be involved with SystemModeler/Modelica. (iv). There will be additional group projects WITH OTHER SOFTWARE mentioned in course. To be reasonable with technical and intricate subjects there will be at least 4 exams to complete. Individual exams concern: 1. Physics subjugating mathematical modelling 2. Systems Mechanical Thermal-Mechanical Electrical Electromechanical 3. Circuitry models (not all will be electrical) 4. System Models and Control Transfer functions, state-space (where by nature generally nonlinear systems are present, but will encounter linearity only if practical), feedback/automatic control and frequency domain. Included, for some tasks, given will be controllers for quite “elementary systems”, where students must deduce the physics and system models based on system parameters that would lead to such controllers; can be T or F questions, or trick questions, or controller design. 5. Tuning controllers 6. Modelica language & Modelica libraries/packages. Constructing system models with components 7. Bode graphs. Target responses and actual responses. 8. System integration procedures and activities with Mathematica SystemModel/Modelica 9. Operation and procedures for other software incorporated in course. 10. Single board computer interface with control/interactivity Mainly towards EE, CE and ME students Without skills in system construction and modelling one is setting themselves up for extreme self-embarrassment and lack of ability to design and develop advance systems to be integrated. NOTE: without physics controller designs make no practical sense. (I) EE Students Concerning class sections focused towards EE, activities and lecturing will go beyond Circuit Analysis II, into nonlinear circuits. Will deal with the use of diodes in circuits. Will encounter various popular nonlinear circuits and practical applications. May encounter ANSYS use with electromagnetics and semiconductors. 1. Basic Circuitry -Components in series and components in parallel -Series-parallel combination -Kirchoff and RLC -Kirchoff: series and combination -Ideal behaviour versus real behaviour of components with Kirchoff -Techniques for DC circuits augmented with phasors for AC circuits -AC power systems of different phases. -Treatment of polyphase AC circuit quantities as phasors towards balanced circuits being simplified; unbalanced circuits being treated as an algebraic combination of symmetrical components (reduces labour needed in electrical calculations of voltage drop, power flow, and short-circuit currents). -Transformers Ideal transformer modelling Non ideal transformers Effect of frequency Energy losses -Ideal Equivalent circuits Concepts and rules towards construction Must be able to develop real circuits before representation by ideal circuits (may be given ECs to develop real counterpart or vice versa) 2. DC motors, AC motors and universal motors Anatomy of such three types of motors. Electromagnetics of motors (all three types) Circuitry and behaviour of current/volatage (AC, DC, universal) 3. Ansys Motor-CAD applications for DC, AC and universal motors Analysis of motor design and resulting properties. Reconciling developments from (2) with findings from software activities 4. Modelling and High-Performance Control of Electric Machines System model characterisation Transfer functions Controller design and implementation for motors (DC, AC, universal) Anatomy of actuators Modelling, transfer functions, controller design and implementation for actuators Choice topics and tasks out of the following texts that’s relatable to simulators: Modelling and High-Performance Control of Electric Machines. IEEE Series on Power Engineering. Mohamed E. El-Hawary, Series Editor Vukosavic S.N. (2013) Modelling Electrical Machines. In: Electrical Machines. Power Electronics and Power Systems. Springer Example case for motors: a thorough synopsis that’s extendable to virtually any simulator brand --> Hardware and Software Co Design for Motor Control Application < https://www.youtube.com/watch?v=dE38QBQR8Tw > However, treatment will be towards more domesticated motors that are cheap or reusable; consideration for DC, AC and universal. 5. Will deal with circuits that make up the given electrical components and the meaningful uses/applications, where the most tedious part may be keeping things tangible and highly applied sans being a “washout”. Not all listed may be done. Modelling to be accompanied by simulations to verify circuit characteristics: Transistors NPN and PNP structure & behaviour Circuit design Amplifiers Op-amp integrators Op-amp differentiators Oscillators (for various geometric outputs and the relevance of such) Voltage regulators (quite broad and with specifications) Inverters Converters Voltage to frequency converters Frequency regulators Pulse generators 6. Will investigate how such 11 features constitute standard electronic/electromagnetic devices: electromagnetic frequency variability, antennas, receivers, amplitude modulations, frequency modulations, EMI filters, etc. Will develop virtual constructs and simulate as well. Are controlrs relevant to such? If so, to develop them, and investigate directly how they apply in built simulations. 7. Thermoelectric effects with semiconductors (modelling and simulation) Will also have cooling simulation projects versus lab experiment observation 8. Electromagnetics --Overvew of electromagnteic theory and analytical solutions for practical fields. --Computational electromagnetics Relevance to antenna performance, electromagnetic compatibility, radar cross section and electromagnetic wave propagation when not in free space. Survey and of implementation of chosen DE solvers Validaton of electromagnetic simulation, namely, to comprehend and be accountable for the validity domain of its simulation. The measure is, "how far from the reality are the results?" Answering this question involves three steps: comparison between simulation results and analytical formulation, cross-comparison between codes, and comparison of simulation results with measurement. Light scattering code development Electromagnetics FEA with software (DC, AC and universal motors) Firstly, will consider various applications settings and prematurely identify the possible analytical EM modelling that’s appropriate with whatever needed conditions, and corresponding solutions. Then, followed by electromagnetics FEA and compare with the premature analytical development. How consistent are the analytical treatment to the electromagnetics FEA representing realistic systems? Electromagnetics FEA with software (transformers) Özüpak, Y., Mamiş, M.S. (2020). Analysis of Electromagnetic and Loss Effects of Sub-harmonics on Transformers by Finite Element Method. Sādhanā 45, 226 Extend to different types of transformers Note: treatment for noise is also expected Electromagnetics FEA with software (circuit boards) 9. Microcontrollers can apply heavily to projects in physics, engineering and so forth. The ability to scope microcontroller properties and observe performance are vital. As well, means to acquire data of interest that’s structured/coupled in a time varying manner. https://www.wolfram.com/language/12/microcontroller-kit/ How to model microcontroller performance from features (a few examples out of many) --> Live CEOing (116): Microcontroller Support in Wolfram Language Live CEOing (130): MicrocontrollerKit Design in Wolfram Language Live CEOing (142): MicrocontrollerKit Design in Wolfram Language Will be given conventional dynamical systems (mechanical, electrical, electromechanical, environmental monitoring, MIMO, etc.) where students are required to develop system models, transfer functions and controllers. Students will apply the virtual support from Mathematica to support their analytical development for confirmation. Means of data acquistion and analyss. 10. More applications of microcontrollers --Continuation of (9). Wolfram software and others have virtual modules with for Raspberry Pi and other microcontrollers for “elementary” skills building. Such virtual tools with various programming and system set-ups will be applied to simulate projects before actual orchestration or physical projects. Data and characteristics will be compared to physical projects. Examples (but not limited to such) Automatic Phase Change over from 3 phase electricity system Bi directional Rotation of an induction motor with a remote control device Design & implement controllers into microcontrollers for DC/AC/Universal Motor. Differential Protection of Transformer Using 8051 Microcontroller Single Phasing Preventer using Microcontroller Temperature Control Lab 11. Function of 555 timer IC and derivatives concerning timer, delay, pulse generation, and oscillator applications. What is so relevant and great about a timer IC? IC designs and modelling Simulation Control Applications integration 12. Analysis of micrcontroller ICs in “simultaneous” function. For chosen projects involving microcontroller boards will analyse how the various ICs function (or coordinate or relate). Prior module development may influence much. (II) ME Students 1. Logistical overview of common elementary dynamical systems Newtonian methodology (very limited) Modelling and simulation Bicycle, tricycle, motorcycle, motor-tricycle, monowheel 2. Fluid and Thermal systems Liquid Fluid Flow Review of laws in fluid mechanics Modelling behaviour w.r.t. fluid properties and geometries Patrascioiu, C. (2011). Chapter 3. Fluid Flow Control. In: Papantonis, D. Centrifugal Pumps. IntechOpen Replicate findings and exhibitions from given above chapter More literature expected for more general concerns Simple to very complex systems Modelling Natural fluid resistance Control valves, hydraulic resistors, pumps (centrifugal, volumetric) Transducers (flow, differential pressure) Transfer functions Controllers Simulation and verification Thermal Control Overview of heat transfer modelling Conventional systems and modelling for essential components Transfer functions Controller Design for temperature control of heat exchangers Thermal mass flow controllers Condenser Controllers Simulation and verification 3. Modelling common terrestrial and marine vehicle dynamics --Modelling of standard four wheel land vehicle --Chen, K., Pei, X., Ma, G., Guo, X., Longitudinal/Lateral Stability Analysis of Vehicle Motion in the Nonlinear Region, Mathematical Problems in Engineering, Volume 2016, Article ID 3419108, 15 pages --Recognition of transfer functions and controllers for prior. --Simulating longitudinal and lateral vehicle dynamics. Vehicle blocks introduced to be used for various applications and requirements. Building vehicle dynamics models using inputs (steering, longitudinal velocity, external forces, etc., etc., etc) to calculate motion. --Ibrahim, R., A. and Grace, I., M., Modelling of Ship Roll Dynamics and its Coupling with Heave and Pitch, Mathematical Problems in Engineering, Volume 2010, Article ID 934714, 32 pages --Recognition of transfer functions and controllers for prior --Simulate ship roll dynamics and its coupling with heave and pitch. Vehicle blocks introduced to be used for various applications and requirements. Building vehicle dynamics models using inputs to calculate motion. 4. Internal combustion engines Review of the long run process Conventional constituents Review of thermodynamic cycles for ICEs Otto Cycle and Diesel Cycle Analysis of Wolfram Demonstrations Project: Otto Cycle https://demonstrations.wolfram.com/OttoCycle/ Analysis of code and replication Develop the Diesel Cycle counterpart Develop the Brayton Cycle counterpart Does the addition of turbochargers transform such prior cycles into the Brayton Cycle? From the following literature will focus on chapter IV Organization and Use of Computer Program ZMOTTO: Zeleznik, F. J. and McBride, B. J. (1985). Modelling the Internal Combustion Engine. NASA Reference Publication 1094 --> https://ntrs.nasa.gov/api/citations/19850011423/downloads/19850011423.pdf ZMOTTO will be analysed. Necessarily, first encounter to be Chapter IV, then will identify and incorporate the necessary equations from prior chapters in a tangible, fluid and practical manner; must know what goes where and why. For sequencing of equations, I may ask you to develop controllers to synchronize equations based on the ICB process. As well, may not ask you to develop all of the code, rather development of patches in Mathematica or C instead of FORTRAN that integrates one phase to the next; you may be required to determine what quantitative models and parameters are relevant. Engine simulation simulation with Modelica libraries and OpenWam Overview of the purpose of lookup tables Identify essential formulas required to construct engine look up tables There will also be activities with software for look up tables 5. Gasoline powertrain Roberts, N. and Dempsey, M. Detailed Powertrain Dynamics Modelling in Dymola – Modelica. 7th IFAC Symposium on Advances in Automotive Control. The International Federation of Automatic Control. September 4-7, 2013. Tokyo, Japan. Note: not particularly content with Dymola environment. Note: will be developed 6. Engine Control Unit L. S. Mendonça, D. D. Luceiro, M. E. S. Martins and F. E. Bisogno, "Development of an Engine Control Unit: Implementation of the Architecture of Tasks," 2017 IEEE International Conference on Industrial Technology (ICIT), 2017, pp. 1142-1146 Note: may try to implement algorithms analysed 7. Electric vehicle powertain Followed by the three guides towards development of modelling and control --> Jian Zhou, Xiangming Shen & Dong Liu, "Modeling and Simulation for Electric Vehicle Powertrain controls," 2014 IEEE Conference and Expo Transportation Electrification Asia-Pacific (ITEC Asia-Pacific), Beijing, 2014, pp. 1-4 S. George, R. V. Chacko and A. Mathew, "Off-line and Real-time Simulation Modelling of Electric Vehicle Power Train," 2014 Annual International Conference on Emerging Research Areas: Magnetics, Machines and Drives (AICERA/iCMMD), Kottayam, 2014, pp. 1-8. Note: will be developed 8. Vehicle Steering Systems Note: apart from any analytical modelling will also make use of System Modeler/Modelica to develop the systems with the technical components. Abhiteja, P. et al Design, Simulation of Steering System for a Go Kart Vehicle. AIP Conference Proceedings��, Volume 2200, Issue 1 020009 (2019) Li, L., Wu, W., Chen, J., Shi, J. et al., "Modeling and Simulation Research on the Electric Power Steering System for a Passenger Car," SAE Technical Paper 2016-01-0464, 2016 E. Iyasere, J. Black, M. Kinstle, B. Post, J. Wagner and D. Dawson, "A Real Time Re-Configurable Steering Simulator for System Design Studies," 2007 American Control Conference, New York, NY, 2007, pp. 2289-2295 9. Brake system Dynamic Modelling of automotive braking systems Simulation and Control of braking system Hydraulic and Electric 10. Terrestrial vehicle (car, exploration rovers, motorcycle, marine, etc, etc.) simulation and control with systems models. Create a library for vehicle modelling, which can be used to study driving dynamics during different driving conditions. NOTE: consideration of electric vehicles as well Create Custom Libraries Illustrate the Model Diagram Integrate Custom Equations Evaluate Control Scenarios Wolfram SystemModeler and Modelica packages are well suited to take on such a challenge. Inevitably at least hundreds of equations may be in play (“embedded”). Matrix algebra is not control; CAS will be put to use rather than things being lost in translation, or being sabotaged towards nothing. NOTE: the physics/engineering models must remain prevalent to be consistent with what you’re doing throughout. NOTE: at different phases students will be asked to develop generic analytical controllers to compare with software deductions. 11. Structural Analysis FEM and FEA for structural analysis/dynamic behaviour. Consideration of various structures with visual simulations development. Ansys and Nastran/Patran software immersion into structural analysis. 12. DC motor, AC motors and universal motors. Anatomy of such three types of motors. Electromagnetics of motors (all such types) Circuitry and behaviour of current/volage (AC, DC, universal). 13. Modelling and High-Performance Control of Electric Machines Choice topics and tasks out of the following text that’s relatable to simulators Modelling and High-Performance Control of Electric Machines. IEEE Series on Power Engineering. Mohamed E. El-Hawary, Series Editor System Modelling Transfer functions Controller design and implementation for motors (DC, AC, universal) Treatment of actuators constituted by motors Controller design and implementation for actuators Example case for motors: a thorough synopsis that’s extendable to virtually any simulator brand --> Hardware and Software Co Design for Motor Control Application https://www.youtube.com/watch?v=dE38QBQR8Tw However, treatment will be towards more domesticated motors that are cheap or reusable; consideration for DC, AC and universal. 14. Microcontrollers and projects in physics and engineering The ability to scope microcontroller properties and observe performance are vital. As well, means to acquire data of interest that’s structured/coupled in a time varying manner. https://www.wolfram.com/language/12/microcontroller-kit/ How to model microcontroller performance from features (a few examples out of many) --> Live CEOing (116): Microcontroller Support in Wolfram Language Live CEOing (130): MicrocontrollerKit Design in Wolfram Language Live CEOing (142): MicrocontrollerKit Design in Wolfram Language Will be given conventional dynamical systems (mechanical, electrical, electromechanical, environmental monitoring, MIMO, etc.) where students are required to develop system models, transfer functions and controllers. Students will apply the virtual support from Mathematica to support their analytical development for confirmation. Means of data acquisition and analysis. 15. Robotic design, mechanics, dynamics control and simulations Robotic anatomy (types) Robotic arms actuation (various types and sophistication) Motors & Drivetrain models Physics (mechanics) and system equations must be developed initially Transfer functions Controllers design and implementation for arms Controllers design and implementation for mobile robots Examples--> -WolframSystemModeler - Physics - Arduino Robot Arm -There will be more complicated controllers towards other types of robot arms -Wolfram Language Microcontroller Kit: Line Following Zumo Robot -There will be more complicated controllers towards other types of vehicles complicated controllers towards other types of vehicles) 16. More applications of microcontrollers --Continuation of (13). Wolfram software and others have virtual modules with for Raspberry Pi and other microcontrollers for “elementary” skills building. Such virtual tools with various programming and system set-ups will be applied to simulate projects before actual orchestration or physical projects. Data and characteristics will be compared to physical projects. Examples (but not limited to such) Automatic phase change over from 3 phase electricity system Bi directional rotation of an induction motor with a remote control device Design & implement controllers into microcontrollers DC, AC, Universal Motor Robotic arm control with microcontrollers All developed, built and programmed from scratch Temperature control lab (III) AE Students 1. Components of flight Mechanics of flight Aerofoils Overview of aerodynamics and lift. From Bernoulli to Euler to Navier-Stokes How are aerofoil designs related to Navier-Stokes modelling? Simulating aerodynamics and lift Aerofoils and it application to different locations on aircraft (wings, flaps, rudders, fins and elevators). 2. Determining acceleration and distance needed for aircraft takeoff 3. Aircraft geometric designs & specifications for aerodynamic performance: DATCOM, XFLR5, Athena Vortex Lattice (AVL), XFOIL 4. Deriving dynamic pressure from conservation of fluid momentum. Developing a module to simulate dynamic pressure on aircraft at various speeds and altitudes. 5. Propeller designs, propeller aerodynamic analysis & performance. Simulation. 6. Review of thermodynamc cycles for ICEs for props Otto Cycle and Diesel Cycle Analysis of Wolfram Demonstrations Project: Otto Cycle https://demonstrations.wolfram.com/OttoCycle/ Analysis of code and replication Develop the Brayton Cycle counterpart 6. Jet Engines --Types of jet engines (advantages, disadvantages and conditions for operation) Recall the Wolfram Demonstrations Project: Otto Cycle in module (5). Amend the code to acquire the Brayton Cycle (T-s and P-V). --Thermochemical Codes Koch, Ernst-Christian & Weiser, Volker & Webb, Rutger. (2009). Review on Thermochemical Codes. Conference: 36th International Pyrotechnics Seminar At: Rotterdam The ICT-Thermodynamic code can also serve well towards combustion engines. For demonstration of ICT-Thermodynamic code in action what must be developed? Pursue. --Performances of Jet Engines i. Energy Balance for Thermodynamic Analyzation ii. Performance measures via NASA’s WATE software or pyCycle software; accompanied by identification and elaborations of the various formulas for the observed simulated performance --Modelling jet engines to acquire transfer functions, controllers --Jet Engine Control Unit M. Dub, J. Bajer, and M. Stepanek, "Electronic Starting Control Unit for Small Jet Engine," International Conference on Military Technologies (ICMT) 2015, Brno, Czech Republic, 2015, pp. 1-4, Csank, J., May, R. D., J. S. and Guo, T. (2010). Control Design for a Generic Commercial Aircraft Engine. NASA/TM—2010-216811 & AIAA–2010–6629 L. Gou, Z. Liu, A. Liang, L. Wang, and Z. Zhou, "Design of Simulation Platform for Control System in Aircraft Engine," 2018 37th Chinese Control Conference (CCC), Wuhan, China, 2018, pp. 8671-8676 7. Aircraft dynamics Aircraft actuation for direction and manoeuvres (pitch, roll and yaw, combinations) Actuation components (with modelling, transfer functions, controllers and simulation) Hydraulic power & flap subsystem (include hierarchical model) Linear actuator and flap subsystem (include hierarchical model) Also for rudders, fins, elevators as well if not redundant tasks 8. Aircraft Landing gear dynamics: modelling transfer functions, controllers development and simulation 9. Flight Modelling, Control and Simulation Flight mechanics: identifying the general equations rather than monstrousity boxes or arrays for excrement shows). Matrix algebra is not control and simulation; CAS will be put to use rather than things being lost in translation, or being sabotaged towards nothing. Note: it’s highly unlikely you will ever operate on matrices by hand (don’t have the time for that, nobody does that). This is a engineering course, not some mathematician’s ideological rent seeking course. If I were to give you bluntly a bunch of boxes with weird stuff inside out of nowhere, what would you do with it? No professional sits down and does manual matrix algebra because they have better things to do. The physics/engineering models must remain prevalent to be consistent with what you’re doing throughout. --The following may or may not be useful/practical towards pursuits: Peters, M. and Konyak, M. A. (2012). The Engineering Analysis and Design of the Aircraft Dynamics Model For the FAA Target Generation Facility. Federal Aviation Authority 99162-01 -> https://docplayer.net/5135879-The-engineering-analysis-and-design-of-the-aircraft-dynamics-model-for-the-faa-target-generation-facility.html Dussart, G. et al. (2018). Flight Dynamic Modelling and Simulation of Large Flexible Aircraft, Flight Physics - Models, Techniques and Technologies, Konstantin Volkov, IntechOpen NOTE: at different phases students will be asked to develop generic analytical controllers to compare with software. --Modelling, Control and Simulation for helicopters, bicopters and quadcopters Simulation in software (prop, turbine, helicopter, bi-copter, quad-copter). NOTE: at different phases students will be asked to develop generic analytical controllers to compare with software deductions. -To create a library for aircraft modelling, which can be used to study flight dynamics during different flight conditions Create Custom Libraries Illustrate the Model Diagram Integrate Custom Equations Evaluate Control Scenarios Wolfram SystemModeler and Modelica packages are well suited to take such a challenge. Students to be tasked with amendments for different aircraft. Inevitably at least hundreds of equations may be in play (“embedded”). --Use of FlightGear Simulator (open source) to have practical observation of aircraft manoeuvres with system/target responses; compared to the SystemModeler/Modelica development prior. --Determination of the following for different aircraft: Minimum distance and acceleration needed for take-off Rate of ascent w.r.t. prior two parameters Greatest altitude Maximum cruising speed at best performance altitude Maximum distance of travel Time of longest flight 10. Structural analysis for aircraft --Overview of numerical methods applied --Applying Nastran/Patran or ANSYS (upon structural members, other body parts and skin) 11. Rocket flight modelling & simulation --Theoretical rocket flight modelling (single and multistage) --Velocity model incorporating drag coefficients, aerodynamic coefficients, aerodynamic forces and motion ( single and multistage) --ROCETS from NASA software and OpenRocket Simulator development to be compared to prior theoretical rocket flight modelling (single and multistage). --Transfer functions and rocket flight control --Developing a model for maximum dynamic pressure based on consideration of atmospheric density being dependent on altitude and a rocket velocity model; implcations on mechanical, aerodynamics/compressible flow and thermal sensitivities applying to rocket design and structural modal analysis (that doesn’t contribute much to rocket weight). --Concerning maximum dynamic pressure, why are hybrid and liquid propellant rockets more advantageous or favourable than solid propellant rockets? 12. Solid Rocket Propellants and Motors Premature analytical modelling: i. The ICT-Thermodynamic code applied to rocket propellants ii. A Computer Program for the Prediction of Solid Propellant Rocket Motor Performance. Volume I - III Complimenting software for priors: NASA CEA software BurnSim GUIPEP + PROPEP STANJAN --Combustion & Adiabatic Flame Temperature (AFT) -- Will walk through the logistics, then pursue computational examples for various propellants. Basic guides: https://www.nakka-rocketry.net/th_comb.html https://www.nakka-rocketry.net/th_appx.html STANJAN for AFT --Solid propellant grains and burn laws. To determine under what conditions a respective law is relevant: Saint-Robert's Law (or Vieille’s Law) Muraour’s Law Piobert’s Law --Chamber Pressure: https://www.nakka-rocketry.net/th_pres.html From the first source prior the rate of change of chamber pressure model, namely equation 10 or 13, to verifying it’s solution to be equation 14 with consideration of various gases (specific heat ratio). Furthermore, there’s the following dilemma of two-phase flow: https://www.nakka-rocketry.net/th_2phf.html Hence, means to amend equation 14 from first source to be pursued. ---Nozzle Theory: https://www.nakka-rocketry.net/th_nozz.html Note: will treat various propellants concerning questions where data for propellant is required. Physics and mathematical modelling for gas/vapor dynamics with convergence-divergent rocket nozzle (cone or bell). Will also involve Mach modelling and direct calculation of the average local mach number in converging–diverging nozzles. There can be numerical simulations as well. --Deriving thrust model based on rocket motor design and propellant grain --> https://www.nakka-rocketry.net/th_thrst.html Note: formula must also reflect geometrical parameters of the rocket motor. Note: will treat various propellants concerning questions where data for propellant is required. --Identifying a model for specific impulse based on thrust model development earlier (i.e. reflects both rocket motor geometrical parameters and ratios of specific heat with the issue of two-phase flow). Then, onward to total impulse. 13. M El-Naggar et al 2020 Experimental Investigation of Star Grains in Dual Thrust Solid Propellant Motors. IOP Conference Series: Materials Science and Engineering 973 012001 The primary goals are developing Figure 19, Figure 20, and making sense of Figure 30 14. Students to be given instruction to develop rocket profiles for chosen solid propellant rockets with software: < NASA CEA software, BurnSim, GUIPEP + PROPEP, STANJAN > < OpenRocket Simulator, ROCETS from NASA software catalogue > Analytical profiling to flank software activity: Rocket motor structure (with convergent-divergent specifications) Physical design (static stability, aerodynamics) Drag Force Lift Force (and lift to drag ratio) Dynamic Pressure Ballistic Coefficient Critical Angle of Attack Centre of Pressure Turning moment and pitch moment Force coefiiencts and and Aerodynamic coefficients Cp - Cg state Motor performance with respect to propellant characteristics and rocket motor size Rocket trajectory, maximum speed, maximum acceleration, maximum altitude, range ----For “winter” and “summer” sessions concerning at least upper sophomores, there are activities of technical development skills; weekly schedule be four to five days per week for at least three to five hours each day, with consistent analysis and field experimentation/lab environment tone. Enginering students are expected to participate consistently towards interests. For the case of the “summer” session likely 12 weeks will be available. “Winter” sessions will be more sensitive for operations due to stronger time constraints. Students are permitted to participate immediately upon confirmation of appropriate amount of credits for upper sophomore standing. Such activities concern hands-on experience in the development and creation of engineering systems that conventionally influence everyday dynamic. Such activities are also a means to initiate “light bulbs” or awaken hidden potential in students that are not present during normal academic semesters. Students to participate in at least two activities at a time. In future activities students are permitted to repeat a project. In reality, activities will likely be the most nurturing and rewarding experiences students will ever have in life. Building competency and professionalism by repetition is needed before graduate school. A whole activity is characterised by an alphabetic order. There will be a SECURE & PERMANENT database archive for all participants and supervision constituents for respective activity in chronology (with data). Activities repeated can be added to transcripts upon successful completion. Repeated activities later on can be given a designation such as Advance “Name” I, Advance “Name” II. As well, particular repeated activities serve to towards developing true comprehension, competency and professionalism. CONSTITUENTS ON NOTICE: Activities concerns results that can be acknowledged by the professional engineering society. Capabilities of activity will neither be influenced by local cultural ignorance and stigmas, nor by ambiances not of concern to bridge programme. ACTIVITIES ARE NOT DEMONSTRATIONS TOWARDS STUDENTS, BUT RATHER ENVIRONMENTS FOR STUDENTS TO DEVELOP ENGINEERING AND TANGIBLE SKILLS. REPETITION IN SUCH BUILDS STRUCTURE, CHARACTER AND PURPOSE. ANY ATTEMPTED REGRESSION OR REDUCTION IS SABOTAGE, AND OFTEN CONNECTED WITH PARASITISM, AGITATING EXPOSURE, EXPLOITATION, AND CONTAGION INTENSIFICATION OF ALL SUCH UPON ELSEWHERE. ADDITIONAL NOTICE: some activities may apply particular tools more extensively than others, however, such does not necessary mean that one is a prerequisite for each other. Participation in activity depends on engineering administration & coordination with collaborations with other departments when appropriate. ALL PARTICIPATING STUDENTS, ASSISTING/ADVISING INSTRUCTORS AND PROFESSORS MUST BE OFFICIALLY RECOGNISED; REQUIRES BOTH CIVILIAN ID AND STUDENT/FACULTY ID FOR CONFIRMATION OF INDIVIDUAL. THERE WILL ALSO BE USE OF IDENTIFICATIONS FOR ACTIVITIES FOR RESPECTIVE SESSION. SECURITY AND NON-PARTICIPATING ADMINISTRATION WILL ONLY IDENTIFY RESPECTIVE ACTIVITY BY IDENTIFICATION CODE. SECURITY AND NON-PARTICIPATING ADMINISTRATION MUST NEVER KNOW WHAT ACTIVITIES IDENTIFICATION CODES IDENTIFY: < Alpha, Alpha, Alpha, Alpha > - < # # # # # > - < session > - < yyyy > Engineering activities will also warrant criminal background check (CBC) in order to participate. Severely threshold may vary depending on administration. Administrators will provide dated letters of confirmation of thorough CBC to student affairs and other appropriate administration. Such also may include screening that’s parallel to customs & immigration processing where certain levels of criminal history warrants rejection. Email and physical letters with data. Such CBC protocol will not explicitly identify any particular titles or descriptions of any activity, rather, will only convey code as above. Activities with data will be securely archived. Note: certain activities in one field of engineering will garner great interest or will be crucial to other fields of engineering. Activities will have designation on whether constituents in other fields of engineering can participate. It may be the case some activities can be grouped and given a major title together; however, detailed descriptions will be required. NOTE: senior engineering thesis is a structured document and presentation based on development from research. Hence, you will be delivering a thesis, rather than necessarily having current hands-on research at current time. Activities done will be a treasure trove for pursuing your “engineering thesis”; augmented by skills from courses. “Engineering Thesis” will not be a course, but a presentation. AEROSPACE ENGINEERING (some activities will also cater towards ME) A. Primitive aircraft analysis and testing ability This activity will be a very intense process for students in their academic career. However, completing all such phases, at least competently, in the designated “summer” or “winter” session time, things will become much easier following such. Such activity demands repetition in the following “summer” and “winter” sessions to become well rooted in the culture of aerospace engineering. Anything less is degenerate and contagion. Phase 1--- I. General flight, directional and stabilization https://www.grc.nasa.gov/www/k-12/airplane/airplane.html Of great importance (often taken for granted) identify the definitive role(s) of each component. II. Airfoils (Aerofoils) <http://hyperphysics.phy-astr.gsu.edu/hbase/Fluids/airfoil.html> <http://web.mit.edu/2.972/www/reports/airfoil/airfoil.html> III. Recognising Euler equations in airflow and means of solution IV. Airfoil evolution and conditions on Euler equations for respective airfoil (subsonic, transonic, supersonic, hypersonic examples). Navier-Stokes equations as generalisation of the Euler equations; what brings one to the other. Provide numerical solving synopsis catering specifically for airfoils. Besides sub, trans, super and hyper cases, often considered is the condition of the attack angle. Some journal articles assists: --Verhoff, A. (2006). Analytical Solution of the Euler Equations for Airfoil Flow at Subsonic and Transonic Conditions. ICAS-Secretariat - 25th Congress of the International Council of the Aeronautical Sciences 2006. 2. In such above article the expressed form of Euler equations is quite technical. Not solely focused on mathematical folly; one has real objectives. --Simak, J., Solution of 2D Euler Equations and Application to Airfoil Design, WDS'06 Proceedings of Contributed Papers, Part I, 47–52, 2006. --Lomtev, I. and Karniadakis, G., A Discontinuous Galerkin Method for the Navier-Stokes Equations, Int. J. Numer. Meth. Fluids 29: 587–603 (1999) --Leoviriyakit, K., Kim, S. and Jameson, A., Aero-Structural Wing Planform Optimisation Using the Navier-Stokes Equations, 10th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, 30 Aug - 1 Sep 2004 --Jameson, A. and Martinelli, L. and Pierce, N. A., Optimum Aerodynamic Design Using the Navier–Stokes Equations, Theoret. Comput. Fluid Dynamics (1998) 10: 213–237 V. Acknowledging the Coanda effect Consider the physics of the following and amend or reconcile with elementary discussion from earlier: Anderson, D. F. and Eberhardt, S. (2001). The Newtonian Description of Lift of a Wing. FERMILAB-Pub-01/036-E March 2001 Consider the following journal article concerning the Coanda effect where one will specifically cater for airfoil geometries (and possibly with flaps), resulting in unique modelling, and making use of CFD simulation: Dumitrache, A., Frunzulica, F. and Ionescu, T.C. (2012). Mathematical Modelling and Numerical Investigations on the Coanda Effect, Nonlinearity, Bifurcation and Chaos - Theory and Applications, Jan Awrejcewicz and Peter Hagedorn, IntechOpen, DOI: 10.5772/50403 Is the Coanda effect unique to prior physics and modelling of flight, thus providing lift augmentation, or is it something that’s not identified properly in modelling with the Euler equation or RANS throughout (IV)? VI. Observing the behaviour of various airfoils Wolfram Demonstrations Project-- Potential flow over a NACA Four-Digit Airfoil Potential Flow over an Airfoil Specified by Numerical Data File Note: source code is available for such demonstrations. Such demonstrations are unique in the sense that you can actually observe the programming structure instead of using a developed platform where user is ignorant of its construction. For the first two demonstrations, the source directory (if any) applied may be disabled off and on, so compensate. Developed platforms such as DATCOM, XFLR5, Athena Vortex Lattice (AVL), XFOIL, OpenVSP VSPAERO, Open VOGEL, AVL are excellent companions. Additionally, pursue access of various airfoil databases and how to integrate into the latter of the two Wolfram demonstrations. VII. Lifting-Line Theory VIII. Vortex Lattice Method This is not matrix algebra folly so computational tools will be applied towards meaningful and constructive objectives. Phase 2--- DIY Wind Tunnels. Wind tunnels can be constructed hardly without any expense. First case: Homemade Wind Tunnel – YouTube Wind Tunnel Science Project - YouTube Else, one can simply employ relevant parts of an HVAC duct with its large blades, where running channel becomes highly convergent with flux concentrating cylindrical pipes (PVC, acrylic or aluminium), feeding to attached transparent station; likely motor change for high thrust. Expected, students must determine fluid pressure and/or flux and/or air velocity for various regions, entries/exits. Constructed module will be extended: (1) There will be different airfoil designs made to test. Each airfoil will be made of the same material, having virtually the same cross-sectional length and same lateral length. (2) Second, height of chamber will be scaled in terms of centimetres or inches. With such there can be measurable observations of lift w.r.t. thrust or gust produced by motor with propeller. A small and cheap proximity sensor suspended above in station towards measurement of heights subject to controlled generated lift is superior. (3) Upon switching on and speed controller onto motor with propeller, one should know the corresponding thrust or stream magnitude produced for each speed change. Might be able to add in sensors for proper confirmation or consistency. (4) Will apply coloured dust particles that are neither health hazards not flammable. Make homemade Holi powder or something. Such will be used to observe potential flow or stream lines in ambiance; flux magnitude change observations as well. Compare differences among the different types of airfoils with respect to air flux magnitude. (5) May compare results with the latter of Wolfram Demonstrations in phase 1. Second case: Development and construction of a wind tunnel where the attack angle for a respective airfoil can be altered via turning beam shaft fixed through airfoil. Bean shaft extends outside through wind tunnel in a manner where turning shaft beam aligns with an angle measures (be creative) where axes correctly align without any issues of axes dislocation. Along with angle of attack variations, case generators (3) and (4) will be applied. One can compare results with the latter of Wolfram Demonstrations in phase 1. Phase 3--- Development of Planform modelling and design The following excerpt text can be used for elementary intelligence and computational development skills --> Gudmundsson Snorri. (2014). The Anatomy of the Wing. In General Aviation Aircraft Design - Applied Methods and Procedures (pp. 299 - 399). Elsevier. Succeeding analysis of the following journal articles, one should determine whether its structure is still considered modern. Also, if possible, pursuit of computational code development that’s constructive and sustainable. Furthermore, one will necessarily like to extend optimisation to transonic and supersonic settings (if article is still credible in more modern times) --> Wakayama, S. and Kroo, I. Sunbsonic Wing Planform Design Using Multidisciplinary Optimisation. Journal of Aircraft. Volume 32 , No. 4, July – August 1995. For common characteristic parameters or measures will like to compare prior developments with numbers/models/designs generated in the following software based on specified settings ---> DATCOM, XFLR5, Athena Vortex Lattice (AVL), XFOIL, OpenVSP VSPAERO, Open VOGEL, AVL Phase 4--- I. Flapped airfoils. Review the definitive role of flaps integrated to wings and the cross sectional airfoils. Recognise different types of flaps associated with different wings and the particular air foil designs. Some flaps associated to particular wing types have made significant impact on the performance of aircraft; will mainly identify such with some significant primitive designs in aerospace engineering history. II. Identify the crucial orientations of flaps: Best efficiency – for climbing, cruising descent Increased wing area – for take-off and initial climb Maximum lift and high drag – approach to landing Maximum drag and reduced lift – for braking on a runway III. Concerned with influence on lift coefficient, drag coefficient, pressure coefficient, and momentum coefficient. Pursuit of a tangible and “fluidly” developed mathematical structure on real knowledge of aerodynamic principles. Analysis assists: Gudmundsson Snorri. (2014). The Anatomy of Lift Enhancement. In General Aviation Aircraft Design - Applied Methods and Procedures (pp. 401- 458). Elsevier. Shehata, H. et al. Aerodynamic Analysis of Flapped Airfoil at High Angles of Attack, 2018 AIAA Aerospace Sciences Meeting, AIAA SciTech Forum, (AIAA 2018-0037) Obeid, S., Jha, R. and Ahmadi, G., RANS Simulations of Aerodynamic Performance of NACA 0015 Flapped Airfoil, Fluids 2017, 2, 2 Ockfen, A. E. and Matveev, K. I, Aerodynamic Characteristics of NACA 4412 Airfoil Section with Flap in Extreme Ground Effect, Inter J Nav Archit Oc Engng (2009) 1: 1-12 ; will treat other airfoil models as well. Leishman, J. G., Unsteady Lift of a Flapped Airfoil by Indicial Concepts, Journal of Aircraft, March, Vol. 31, No. 2 : pp. 288-297 Nagarajan Hariharan and J. G. Leishman. "Unsteady Aerodynamics of a Flapped Airfoil in Subsonic Flow by Indicial Concepts", Journal of Aircraft, Vol. 33, No. 5 (1996), pp. 855-868 Note: specified airfoils and flaps detailed in journal articles may be changed to suit. IV. Flapped wing modules for lab experimentation: Will develop at least three or four different flapped wing module designs. Developing such modules overall isn’t sophisticated. Consider the article from Shehata et al, mentioned above, and the following journal article, Su, Y. Y. and Lee, T., Unsteady Airfoil with a Harmonically Deflected Trailing-Edge Flap, Journal of Fluids and Structures 27 (2011) 1411–1424. Such two articles provide basic experimental constructions. Note: find a cheap DAQ system if one is to be applied. Apply the same “Holi powder” concoction as well w.r.t. so similar speed controller adjustments as before. V. Consider pursuit of establishing interactive and practical optimisation and mechanism design of a flap of interest. Concerns the improvement of the take-off and landing aerodynamic performance of aircraft. Using a numerical simulation method for the case of the considered type of aerofoil, the multi-objective optimization of the overlap, gap, deflection angle, and bending angle of the flap under take-off and landing configurations to be studied. Compared with the traditional flap at a take-off angle of 8 degrees, target goals: 1. Increasing lift coefficient by a considerable higher percentage 2. Increasing lift-to-drag ratio by a considerable higher percentage Under landing configuration, 3. Considerable improvement in the lift coefficient at a stall angle of attack about 13%. Under cruise state, 4. Considerable improvement in the lift-to-drag ratio over a wide range of lift coefficients, and the maximum increment is about 30%. Hints: ‘‘Smart High-Lift Devices for Next Generation Wings (SADE)” concept, the Variable Camber Continuous Trailing Edge Flap (VCCTEF) by NASA. CFD optimization platform architecture: -Optimisation parameters -> Overlap, Gap, Deflection Angle, Bending Angle -Computational Tool Numerical Simulation Programme -> Airfoil: Computational Tool Modelling Programme -Gridgen mesh generation script programme -> Generate script programme glyph -Aerodynamic Analysis Software -> CFD calculation software: Fluent (or CFX) Note: take a hint with OpenFoam A certain type of general aviation aircraft must be chosen to verify the 2D results. Main parameters of this aircraft: -Fuselage width -Fuselage length -Span length -Chord length of wing root -Chord length of wing tip -Wing reference area -Aspect ratio -Ratio of chord length of wing root to chord length of wing tip -1/4 chord sweep angle -Twist angle -Dihedral angle -Incidence angle Article guide: Lu, W., Tian, Y. and Liu, P. (2017). Aerodynamic Optimisation and Mechanism Design of Flexible Variable Camber Trailing-Edge Flap. Chinese Journal of Aeronautics, Volume 30 Issue 3 , pages 988 – 1003 Note: one will not be incarcerated exclusive usage of MATLAB. Phase 5--- Actuation (with modelling, transfer functions, controllers) Hydraulic power & flap subsystem (include hierarchical model) Linear actuator and flap subsystem (include hierarchical model) Tasks also for rudders/fins/elevators Landing gear systems Phase 6--- (i). One major competence and professionalism hurdle in aerospace engineering is to exhibit the ability of flight solely on aerodynamics. Gliders with actuation, say, variation control in pitch, roll and yaw, leading to all possible flight dynamics. Actuation will be remote controlled. There will be no engines for thrust. For this to be successful all prior aerodynamic development must be applied towards optimal or efficient aerodynamic geometry that's sturdy, together with choice of aircraft design and collective foundation structuring. Prototype gliders to be made first will have no RC actuation on wings, rudders and stabilizer parts, but very small crafts just to confirm aerodynamic ability. Then, will build large gliders with RC actuation for variations in pitch, roll, yaw leading to all possible flight dynamics. To Assume that FlightGear Simulator (open source) has glider models (with your choice model), will acquire characterising curves (data) from aircraft behaviour. The following software (hopefully having gliders) can provide dimensional parameters for craft parts towards the most aerodynamic design (: DATCOM, XFLR5, Athena Vortex Lattice (AVL), XFOIL, OpenVSP VSPAERO, Open VOGEL, AVL Multiple test models may be developed for high response in aerodynamics, Materials should be obviously light, sturdy, and flexible as well. Test models must incorporate the following the components: A small GPS tracking system Altimeter sensing Acceleration sensing Speed sensing Gyroscopic sensing All possibly with synchronized to store “time instantaneous” data. All such likely to be managed by programmable boards. Additionally, very light key chain camera for recording too. With incorporation of prior features, to have thorough observation of the flight optimisation system weights estimation method guide, students are to determine what chapters are relevant to a glider: Wells, D. P. and McCullers, L. A. (2017). The Flight Optimization System Weights Estimation Method. NASA/TM–2017–219627/Volume I https://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/20170005851.pdf It’s important to design and test actuator systems that will produce aircraft dynamics from basic components (motors, actuators, etc.). Scale and weight of wings, flaps, rudders, etc., etc. should be incorporated towards designing optimal actuation systems to be applied. As well, to be thorough, will try to develop controller analysis for each type of actuation design for glider. Can controller development be compatible with data from FlightGear Simulator? On meteorological calendar favourable weather (arid with high non-turbulent wind) at chosen high altitudes/plateaus to be manually launched, or alternatively launching by a sling shot method. NOTE: for light but highly sturdy structure one of many possible options can be the following: How to make a composite – BLACK wing – YouTube < https://www.youtube.com/watch?v=MMAhDYsUf2g > Reminder, weight distribution constituted by structure, internal systems and external systems should be configured efficiently in terms of consensus aeronautics design, sans hindering the aerodynamics and stability for excellent flight control. Calibration of Control Surface - YouTube: https://www.youtube.com/watch?v=1jwgnYzj7F4 Calibration of Control Surfaces (Experiment) - YouTube: https://www.youtube.com/watch?v=zOjj4S7LH-I To have a long successful flight gravity assist is crucial. The launch mechanical energy for glider will deteriorate over time, however taking advantage of the conversion between gravitational potential energy and kinetic energy is the goal; feasible distances, altitudes, speeds, yaw, roll and pitch will be subject to such conversion. Such includes: dynamic soaring, slope soaring, slope gliding. One must establish the fluid mechanics, aerodynamics, drag depending on craft geometry and mechanical energy evolution (KE < ---> GPE) for optimal craft performance, where flight paths will necessarily apply all such, namely, feasible distances, altitudes, speeds, yaw, roll and pitch will be subject to all such. NOTE: flight path reconstruction Teixeira, B. O., Tôrres, L. A., Iscold, P., & Aguirre, L. A. (2011). Flight Path Reconstruction – A Comparison of Nonlinear Kalman Filter and Smoother Algorithms. Aerospace Science and Technology, 15(1), 60-71. May be able to compare with FlightGear Simulator and NASA’s NewSTEP is a (matlab-based) iterative extended Kalman filter/smoother designed for solving trajectory reconstruction problems for flight test experiments. NOTE: will then extend to incorporation of propulsion with strong electric prop(s) and power source. Control and performance will be compared to glider control and performance based on responses (data) and sensing data. Weight distribution constituted by structure, internal systems and external systems should be configured efficiently in terms of consensus aeronautics design, sans hindering the aerodynamics for excellent flight and control. Flight path reconstruction as well. (ii). Applying propulsion and geometry for aerodynamics towards flight with unconventional frames. Replicate and operate the IKEA flying chair or IKEA chair plane (check out such on YouTube). (iii). Another major competence and professionalism hurdle in aerospace engineering concerns identifying some of the most basic but conventional airplane designs and applying elementary propulsion. There will be at least two designs to test. The material to be used mostly will be cardboard or foam board with light beams. Geometries to be drawn and cut out towards construction of mobile and aerodynamic aircrafts. There must be ingenuity with frame design. Flight theory, aerodynamics with geometry and weight configuration in the interest of aeronautics. Determination of the minimal requirement for ground motion and air thrust; propulsion system must be determined that yields highly effective results. From elementary kinematics acquire the formula to calculate the distance needed to reach a specified speed with a given acceleration. However, the acceleration model stems from mechanics that can ensure aircraft lift; this acceleration model must be established first then substituted into that distance formula. Useful analysis < http://www.dept.aoe.vt.edu/~lutze/AOE3104/takeoff&landing.pdf > Wells, D. P. and McCullers, L. A. (2017). The Flight Optimization System Weights Estimation Method. NASA/TM–2017–219627/Volume I Stability and manoeuvrability will be put to test in different wind conditions for flights, preferably with no precipitation. Aircrafts will be remote controlled having propeller thrust sources. Some structural assists --> Confidence building: < https://www.youtube.com/watch?v=qJZoqGHAIDE > < https://www.youtube.com/watch?v=PbyVGfB1oCg > < https://www.youtube.com/watch?v=karr67ZYho4 > More analytic: < https://www.youtube.com/watch?v=h_RzXO5u3M0 > Students should also challenge themselves in developing other aerofoil designs to provide higher performance or different aerodynamic sensitivity. Making use of similar software as in prior link, the number of formers inside of the wing and how they are arranged would influence the chord curvature, where length parameters can be found. Students can scale down different aerofoil designs and observing what dimensions will suffice relevant to the number and arrangement of formers applied to resemble such aerofoil models. Servos attachment vague idea: < https://www.youtube.com/watch?v=LrOqNI__3NQ < https://www.youtube.com/watch?v=O7hq9evCcLQ More advanced prototypes (however to pursue means to acquire different aerofoil designs for such type of aircraft): < https://www.youtube.com/watch?v=dpzGJ7387qA < https://www.youtube.com/watch?v=K4EO5_E8euQ Another advanced prototype (but preference is foam board and for code to be written in platform other than Excel and Matlab): < https://www.youtube.com/watch?v=aSD69jdi2CE Calibration of Control Surface - YouTube: https://www.youtube.com/watch?v=1jwgnYzj7F4 Calibration of Control Surfaces (Experment) - YouTube: https://www.youtube.com/watch?v=zOjj4S7LH-I Phase 7--- Microscale construction of modern aircraft for flight exhibitions. Such activity serves to rigorously introduce students to the anatomy of aircraft vessels towards structural integrity, aerodynamic configurations, control and stability. Technical terminologies will be reinforced throughout design process and construction of vessels for flight. There will be no bought commercial airplane building kits for assembly. Assist 1: www.fzt.haw-hamburg.de/pers/Scholz/HOOU/ Assist 2: www.fzt.haw-hamburg.de/pers/Scholz/ewade/2016/Paper_F_Nicolosi.pdf Further assists: Wells, D. P. and McCullers, L. A. (2017). The Flight Optimization System Weights Estimation Method. NASA/TM–2017–219627/Volume I Raymer, D. (2018 6th ed.). Aircraft Design: A Conceptual Approach. AIAA Snorri Gudmundsson. (2013). General Aviation Aircraft Design. Butterworth-Heinemann Such assists may or may not be inclusive of all modern aircraft models. For the above assist 1 link some files will be quite beneficial while others will be impractical for scale considered. Both assists will be thoroughly analysed (except for the irrelevant subjects pertaining to finance and revenue management). There may be technical mathematical models but use of the mentioned tools such as DATCOM, XFLR5, Athena Vortex Lattice (AVL), XFOIL, OpenVSP VSPAERO, Open VOGEL, AVL can resolve such difficulty, and provide dimensional parameters for craft parts. There will be considerable immersion into the mentioned software tools. Such tools will also be used to develop performance predictions for vessel. There will be demand for accuracy and efficiency with critical components responsible for aerodynamics, control, stability, motion and flight. Don’t concern oneself with lavish details such as windows, windscreens, vessel body job and logos. Concerning propulsion, one will pursue components that would best provide behaviour or performance similar to real vessel one emulates; vessel must not be prone to behaviour uncharacteristic of the real vessel in low winds. Incorporated into vessels will be altimeter, accelerometers for speed and acceleration, gyroscope sensor and magnetometer. Key chain camera applied as well. Such sensors to be synchronized with each other concerning time towards data storage. Will have a very light black box that records actions by operator, actions (both active and neutral) synchronized with all sensing data. Such to be created with programmable boards. Will have designated flight plan. Data will be compared or incorporated to predictions stemming from mentioned software tools. Will employ models where balsa wood, pine wood, fiber glass, or carbon fiber (or wood frame + carbon fiber surface) serve well towards the structure, shape, aerodynamics, and the containment of power sources, sensing and control. There will be at least two unique aircraft types to model, build and have flight demonstrations to critique geometric construction, theory from physics, aerodynamic design, and components for aircraft control. Vessels will be RC with operator having control over the following: Flaps (for change in lift and drag) Ailerons (for change in roll motion) Rudders (for change in yaw motion) Elevators (to change in pitch) Retractable landing gear systems Calibration of Control Surface - YouTube: https://www.youtube.com/watch?v=1jwgnYzj7F4 Calibration of Control Surfaces (Experment) - YouTube: https://www.youtube.com/watch?v=zOjj4S7LH-I There will also be aircraft with stationary suspension landing gears. Develop a flight plan coordinated drill for respective aircraft with specific course involving altitudes, speeds, one-direction rectilinear motion, two dimensional manoeuvres and three-dimensional manoeuvres. Data retrieved can be compared to flight modelling and software tools [ DATCOM, XFLR5, Athena Vortex Lattice (AVL), XFOIL, OpenVSP VSPAERO, Open VOGEL, AVL] concerning development of a flight simulator. Determine theoretical top flight speed. Flight envelope, level flight performance and doghouse plot; will like to confirm such three in test flight trials. NOTE: flight path reconstruction Teixeira, B. O., Tôrres, L. A., Iscold, P., & Aguirre, L. A. (2011). Flight Path Reconstruction – A Comparison of Nonlinear Kalman Filter and Smoother Algorithms. Aerospace Science and Technology, 15(1), 60-71. May be able to compare with FlightGear Simulator and NASA’s NewSTEP is a (matlab-based) iterative extended Kalman filter/smoother designed for solving trajectory reconstruction problems for flight test experiments. B. Design, Structural Analysis, and Ground Mobility for Modern Airplanes Phase 1-- Visits to maintenance hangars and/or aircraft graveyards to observe in detail the structural constitution of aircrafts. Such opportunities are for proper insights into real aircrafts beyond the ignorant traveler. Students should take advantage of the opportunity to compare what was accomplished in activity (A) to what is observed. Some major goals: --Observation of the structural design of various types of fuselages/airframes --Observation of various types of landing gears --Methods for the proper attachment of engines to wings or at other positions will be thoroughly investigated. --Methods for the proper attachment of aircraft surfaces. A source that may assist with the verbiage and other additional technical details: home.iitk.ac.in/~mohite/Basic_construction.pdf Phase 2-- Structural design and assembly will be highly comprehensive compared to the YouTube structural design in Activity A-phase 2, since real passenger or carrier jets don’t have vertebra. For different chosen aircraft will identify all components needed to assemble the body, respectively. The detailed task: imagine that you are the crew responsible for assembling the respective aircraft’s body. Areofoil designs, wing designs, structural members, components for placements, bolting, fastening, screwing together, etc. Includes placement and securing features for jet engines. Of consequence, before integration each component to be designed in detail with high accuracy in CAD; some to be duplicated while others to vary in size scales. Then structural analysis (SA) for each. Then all to be integrated to together in CAD, followed by structural analysis of the body wholly; may have to zoom in to observe SA at different levels. Catia is one renown CAD for detail and integration. With Patran/Nastran and Ansys to have structural analysis/FEA done, and possibly vibration analysis. Phase 3-- Specifications with tools such as DATCOM, XFLR5, Athena Vortex Lattice (AVL), XFOIL, OpenVSP VSPAERO, Open VOGEL, AVL. Followed by aircraft development in CAD. Phase 4-- For developed models in phase 2 (with wings and other vital structural components) will try to subjugate geometrical design accurately to phase 3. Phase 5-- Concerning the arrangement and assembly of engines onto wings or other locations, the methods must be understood well regarding weights of engines, and the stress/strain applied to wings or other placements at full power. Methods for the proper attachment of engines to wings will be thoroughly revisited. Additionally and crucially, concerning the the position of engine installment on the aircraft, there must be comprehensive analysis of how such locations affect the respective aircraft’s manoeuvrability, control and stability. There are various aircraft models where engines aren’t located on the wings of the aircraft. How is systems control modelling different for aircrafts with engines not located on wings? Phase 6-- Landing gear development 1. Identify the components of the landing gear of modern aircraft and configuration of actuators for “cabin” storage. 2. Modelling, transfer functions and control 3. Make use of SystemModeler/Modelica towards integrating all components into control simulation. Includes automatic control, system-level design, etc.. 4. Will develop landing gear modules (for the three locations) bigger than what was applied in Activity A-phase. Expected, components will not be exact as a landing gear system for a true passenger craft. Students will plan the development with consideration of aircraft and loads to operate with. Will make use of conventional components of robotics/mechatronics to develop. Components to consider --> motors, motor controls, actuators, hydraulics/pneumatics, shock absorbance, Oleo struts, links, power source, etc. Prototype(s) to function in the same role as a true landing gear. Would like a control model applied to such. Simulate before building. Must have competent controlled folding ability. Must have competent controlled turn ability. In general, one should understand the tire specifications required to support respective location. Data from respective constructed landing gear in operation should be highly similar to data from simulations. C. Flight Control Directed towards AE, ME (system control) Flight Mechanics Modelling --> transfer functions --> controllers --> simulation NOTE: will have a generic approach, but students will make the amendments when aircraft models are considered. Different aircraft models can lead to different complexities. NOTE: one must not blindly assume that there’s no non-linearity as a means to flood in sabotaging mathematical frolic with equations in boxes; general forms must be understood with proper means to treat them, in order to be relevant in the AE industry. Regardless, for linear systems of equations, no one has time to watch you solve them manually with finesse towards missing the whole point of doing all such; how you get to the stupid boxes is what’s important. Then, comes what to do with the grotesque boxes; you’re not a slave processor, understanding that modern aircraft are too highly complex to be devoted to playing around in “quadrilateral” pig pens. Apart from analysis/comprehension of the conventional governing models will also consider the possible non-linear generalisations. In the real the world different aircraft models will lead to different aerodynamic and manoeuvrability performances. Then, such simulation activity will be followed by use of FlightGear simulator (open source) to demonstrate such; compare FlightGear simulator data results to data or model characteristics in SystemModeler/Modelica. Namely, for each aircraft model chosen flight stability & control modelling developed must be relatable to manoeuvres data observation(characteristic curves and target responses, etc., etc); print out, take photographs or whatever to compare results. D. Creating micro jet engines integrated with sensor devices & engine control For aerospace engineering constituents, activities (A), (B) and (C) must be successfully completed to pursue this activity; activity pursuit will be dependent on aerospace engineering constituents. Activity will also incorporate constituents from mechanical engineering, computer engineering and computer science. Introductions: 1. Jet Engine, How it works ? - YouTube 2. How it’s Made - Model RC Turbines - YouTube 3. From the construction of the Turbo Jet engine to the flight – just one step - YouTube < https://www.youtube.com/watch?v=dYFYZ-g7fzA&t=4s > (I). Centrifugal jet engine. Compressors concern the feeding of air into and around the turbines and combustion; majority of air cools engine, while a low portion concerns combustion to hastily accelerate the gas into the turbine. Turbine uses some of the energy from the gas to spin up quite fast. For centrifugal jet engine, unlike axial compressor in front a centrifugal compressor is used. Constitution: (multiple) turbine fans, compressor, pressure shaft, turbines, combustors. Engine(s) will always be built from scratch and operated . Centrifugal compressor and axial turbine. Such engines will be integrated into mini crafts for flight. Such is a right of passage or establishment of competency concerning elementary jet engines. (II). Constructive preparation for such: 1. Jet Engines Components of a jet engine and respective function Overall Process Types of jet engines (advantages, disadvantages and conditions for operation) Brayton Cycle with Jet engine components (T-s and P-V) Performances of jet Engines i. Gas Turbine Schematic, Notation and Station Numbering (https://web.mit.edu/16.unified/www/FALL/thermodynamics/notes/node85.html) ii. Energy Balance for Thermodynamic Analyzation. How is relevant to (i)?. Does it provide better assessment than (i)? iii. Between (i) and (ii) which is more practical? 2. Compressor-Impeller Design, Turbine Design, Nozzle Design To develop design competence, one must first consider the type of aircraft model of interest. Then consideration of the scale of such aircraft. Such will give focus to identifying jet engine(s) specifications (dimensions and thrust/power range) for best performance with aircraft. Note: much emphasis with (1). 3. Assisting literature for analytical treatment towards modelling and design The Gas Turbine Handbook, by the National Energy Technology Laboratory, United States Department of Engineering (focus is mainly towards aerospace engineering) Wessley, G. J. J. Design and Modelling of a Micro Turbojet Engine for UAV Propulsion. International Journal of Engineering and Advanced Technology (IJEAT). Volume 8, Issue – 3S, February 2019 Note: for our purposes (1) and (2) must be relevant, and our scale will be a tad larger. 4. STANJAN can be applied to various sensitive issues such as equilibrium combustion, by-products and other things at appropriate times. Fuel and by-products may not be exactly as what is described in the given articles and our micro jet engines of pursuit may or may not be categorized as turbo jet engines. - Godin, Th., Harvey, S., and Stouffs, P. "Chemically Reactive Flow of Hot Combustion Gases in an Aircraft Turbo-Jet Engine." Proceedings of the ASME 1997 International Gas Turbine and Aeroengine Congress and Exhibition. Volume 2: Coal, Biomass and Alternative Fuels; Combustion and Fuels; Oil and Gas Applications; Cycle Innovations. Orlando, Florida, USA. June 2–5, 1997. V002T06A039. ASME. 5. Compressors Design The following text provides a sound treatment of compressor design and optimisation. One example topic of interest (out of many) would be “Simple Blade Design”: Meinhard T. Schobeiri, M. T. (2012). Turbomachinery flow Physics and Dynamic Performance. Springer-Verlag Berlin Heidelberg Other sources: - Xu, C., and Amano, R., S., Design and Optimization of Turbo Compressors, WIT Transactions on State of the Art in Science and Engineering, Vol 42, pages 305-348 - Chen, N., X., Zhang, H., W., and Huang, W., G., Aerodynamic Sweeping Study and Design for Transonic Compressor Rotor Blades, Journal of Thermal Science Vol.19, No.4 (2010) 295−299 - Vlahostergios, Z., Performance Assessment of Reynolds Stress & Eddy Viscosity Models on a Transitional DCA Compressor Blade, Aerospace 2018, 5 (4), 102 If one is to make use of compressor components from turbo machinery, our scale of interest should be equivalent to a truck’s turbocharger components (compressor-impellor and turbine size). As well, they must be able to confirm the geometrical, aerodynamic analysis and compressor efficiency. Much emphasis is placed on compressor design and optimisation because combustion efficiency is related to highly pressurized or condensed air resulting from compressor operation. Our compressor development should reflect our desired engine scale to make any sense for our pursuits. If one’s desire is to have compressor components machined, following analysis based on prior sources, they can make use of CAESES or Catia of ANSYS to conjure their prototype design leading to CNC machining orders or task operation. AGAIN, our scale of interest should be equivalent to a truck’s turbocharger components (compressor-impellor and turbine size). 6. Combustor Design Design and optimisation involving use of ANSYS – FLUENT or other alternative. Flame stability and emissions idea using premixed combustion model Parente, J, Mori, G, Anisimov, VV, & Croce, G. "Micro Gas Turbine Combustion Chamber Design and CFD Analysis." Proceedings of the ASME Turbo Expo 2004: Power for Land, Sea, and Air. Volume 1: Turbo Expo 2004. Vienna, Austria. June 14–17, 2004. pp. 787-796. ASME. Combustor development should reflect our desired engine scale to make any sense for our pursuits. 7. Turbine(s) design Turbojet Engine, Impeller Design, Turbine Design, Nozzle Design It’s expected that turbine performance will be significantly influenced by (3) through (6). Thrust output range should reflect performance of jet engine components’ behaviour. Includes aerodynamic and CFD analysis as well. Turbine(s) development should reflect our desired engine scale to make any sense for our pursuits. 8. Weight Analysis of Turbine Engines (WATE) or pyCycle software from NASA catalogue Before immersion with NASA WATE or pyCycle the following journal article attempts to provide a holistic view. The calculation features of the main elements of the engine blading section, namely, a centrifugal compressor, a reverse-flow combustor, and a radial-axial turbine are considered. The design of the inlet and output duct, rotor bearings, and lubrication system is described. Such article may be able to explain outcomes based on inputs applied to NASA WATE or pyCycle. Sychenkov, V.A., Limanskii, A.S., Yousef, W.M. et al. Micro Gas Turbine Engine for Unmanned Aerial Vehicles. Russ. Aeronaut. 62, 651–660 (2019). Concerning compressors, for what is observed with compressor analysis from prior article, can it accommodated or be harmonious with compressor design/optimisation articles observed in (5)? Additionally, NASA WATE or pyCycle can be compared with development such as the following (but will construct compressor jet engine with determination on the compressor profile and the number of turbines): Axial Turbine Engine Simulation in SolidWorks – YouTube Aero-Mechanical Simulation of Turbomachinery Blading – YouTube NOTE: the ICT-Thermodnamic code accompanied by development from (4) can be compared to NASA WATE or pyClycle, or serve possibly as substitute. (III). Phase (II) will be applied to develop compressor engine models to the caliber of designs pursued. Design components with specification of materials required for desired thermal function and fluid dynamics towards optimal performance. By such one should acquire optimal quantities and parameters, and varying models/control functions for engine dynamics and thermal behaviour. For the case of using compressors from turbochargers, one must question whether the compressor will be operating outside of original design conditions. The ability to read a compressor performance map is crucial . For the case of a pursued milled compressor of specified size, detailed parameters must be set towards acquiring a gauge on performance range. Incorporating ANYSYS CFX (or alternative) can prove highly productive. However, one must first have the ability to read compressor performance maps. Some assists: -Perez, R. X., How to Read a Centrifugal Compressor Performance Map, In: Operator’s Guide to Process Compressors, Scrivener Publishing, 2019 John Wiley & Sons, Inc., pages 83 – 89 -McMullen, R. and Pino, Y., Conditioning Turbocharger Compressor Map Data for Use in Engine Performance Simulation, SAE Int. J. Engines 11(4): 491 – 507, 2018 -Tsoutsanis, E. et al, A component map tuning method for performance prediction and diagnostics of gas turbine compressors, Applied Energy 135 (2014) 572–585 -Li, X. et al, A component map adaptation method for compressor modelling and diagnosis, Advances in Mechanical Engineering 2018, Vol. 10(3) 1–13 -Kang, D. W. and Kim T. S., Model-based performance diagnostics of heavy-duty gas turbines using compressor map adaptation, Applied Energy 212 (2018) 1345–1359 Emphasizing system analysis with NASA WATE or pyCycle and compressor performance with ANSYS CFX. For the case of ANSYS: ANSYS CFX: Performance Mapping - YouTube An end result is the ability to predict what conditions inhibit compressor stall. Structural analysis also warranted. The modelling in the 2 following articles may be able to explain computations observed in NASA WATE or pyCycle software for scale considered. Just don’t assume that such articles will supersede all prior articles, analysis and development. It’s your duty to determine that such following articles are harmonic with others prior whenever needed: L. Fozo, R. Andoga and R. Kovacs, "Thermo-dynamic cycle computation of a micro turbojet engine," 2016 IEEE 17th International Symposium on Computational Intelligence and Informatics (CINTI), Budapest, 2016, pp. 000075-000080 J. Gao and Y. Huang, "Modeling and Simulation of an Aero Turbojet Engine with GasTurb," 2011 International Conference on Intelligence Science and Information Engineering, Wuhan, 2011, pp. 295-298 Reiterating, mostly likely components available will be larger than what is observed in commercial scale products, which is welcomed because we’re about engineering, not legitimizing market share for any product. (IV). One then pursues design and engineering development. There will be two jet engine model types: -MUST establish a trim relationship between the inducer and exducer of turbine and compressor wheel (an area ratio) that’s highly efficient concerning scale of interest <https://www.grc.nasa.gov/WWW/K-12/airplane/ctmatch.html>. Again, relevance of compressor mapping. There must also be proper system analysis and structural integrity study for gears, bearings and seals involved w.r.t. to optimal power, torques and rpms. Failure analysis for shafts, bearings, seals. Will demand analysis and development from (II) and (III) with identification of the proper formulas that apply; thorough analysis concerning the performance range of the compressor and the optimal turbine model in configuration. To also include the following: NASA – Compressor Turbine Matching < https://www.grc.nasa.gov/www/k-12/airplane/ctmatch.html >. Will include study for the design of compressor(s) and turbine(s) by applying (II) and (III) with identification of the proper formulas that apply for scale of interest. Hence, necessarily, engines will be built instead and operated. - Hopefully “engine starters” such as Sullivan Hi-Tork or Hobbico TorqMaster are adequate enough generate high enough rotation (concerning our scale of interest). Naturally as well, there are tools of mechanics that can serve well to generate high rpms (concerning our scale of interest). Also, if it’s the case, an engine starter can be made, say, acquiring the right motor size to apply enough rpm upon the compressor fixture. The biggest challenge will be finding the right extensions to securely and efficiently apply the angular velocities needed; connector should not rip up the compressor’s “nose” during operation. A car battery withproper voltage requirements should be adequate. (V). Fuel choice It’s important to have a proper method for determining which type of fuel will be applied. This treatment will highly influence phase (X) later on. Objective: contributes to yielding strong propulsion Concerns: excessively high consumption in short time span. Exhaust products. Emissions rate of exhaust products. (VI). Sensing for determination of temperatures, rpm, torque, thrust, fuel intake, CFM velocity to accommodate proper construction of compressor engines. Such direct sensor readings likely to be synchronized in time; for each time count will be associated sensor readings. Such will be accompanied by computations for bypass ratios, thermal transfer rates (with respect to materials used), power under certain conditions, exhaust pollution output. Case of unbalanced elimination with rotors, turbines and compressors; means to locate the region(s) of unbalance and methods of elimination. Infrared imaging for viewing of the engine and thrust space continuously in time; detecting infrared energy and converting it into electronic signals, then to be processed to produce thermal images. Also to acquire temperature measurements through such infrared imaging over time. Pursue a configuration where infrared imaging and infrared temperature measurements are made for a determined interval of seconds (could be each second); data for arrangement, modelling and comparative analysis with software models and consensus professional data; to be done for the rocket motor environment as well. All recordings and data (by direct sensing methods and infrared techniques) should be stored, dated, labelled, etc. (VII). Theoretical analysis of compressors at supersonic speeds (if relevant, but should be known regardless). When compressor blades reach the speed of sound it creates an intense shockwave. Shockwaves possess highly compressed and uncompressed waves which travel in series in the form of turbulence. Since the turbine blades are not very large the shockwaves impede on the compressors ability to force in more air. As a result the fuel efficiency is severely impacted. Observe how modern jet engines are built to resolve such the issue. (VIII). Modelling jet engines to acquire transfer functions (MIMO or whatever), then controllers. (IX). Engine Control Management (ECU) Initially built compressor engines described above (with determined amount of compressor stages) to be stepping stones towards more professional development. Advance prototypes to be built reinforcing (I) through (VIII) to accommodate ECU interests. In general ECU’s are relatively cheap, however, it’s use is to be amended to operate the idealistic micro jet engine considered with use of a programmable board (if needed) and what not; there are programmable boards with digital displays well suited for such. How would such a system be developed and integrated with the jet engine? Logistics and design, simulation tests, then implement and operate. In general, for a particular engine there may be unique properties to measure based on components of the engine. Inputs come from the engine, while outputs that go out to injectors and ignition that’s on the engine. For inputs that come into the ECU one can choose a wide range of things for data logging and advance tuning operations. Ideally sensors for the engine to run: air temperature coolant temperature (likely not relevant for our purposes) throttle position manifold pressure engine speed Look-up tables configured in the ECU. An example, say, fuel and ignition set up by tuner; sending signals out to fuel injectors for fuel regulation for desired target air to fuel ratio—towards making the most power. Look-up is 3-D in the management system, say 16-32 load points for rpm range, etc. Other interest may be exhaust gas temperatures and pressures. With an ECU there’s efficient use of resources and limiting on pollution with testing. In this case RC engine size scale may need to be a bit bigger than initial to actually make such operations practical. The ECU has the responsibility of managing the engine to ensure proper operation. It can control the engine through its outputs to the fuel pump, ignition and start up motor. Decisions are based on data taken from its sensors. By listening to external commands the ECU can be told to perform operations like starting up, shutting down or setting the throttle. One decision that the ECU needs to make is how much fuel to add to the combustion chamber during acceleration. This decision has implications in the performance of the engine, but must be limited by the compressor’s surge line. You cannot simply add a large amount of fuel into the combustion chambers quickly. It causes violent vibrations that can damage the engine. By measuring the engine’s speed and pressure, the fuel flow is carefully managed by the ECU. There is a specific procedure that the ECU follows in order to get the engine from a stopped position into a state where a user can throttle the engine. Once the ECU receives a control message to start up it follows instructions similar to these: Turn on the start-up motor Measure turbine speed until the turbine reaches x RPM Start fuel flow Start the ignitor Check temperature sensor for an increase in temperature (indicating ignition) Stop the ignitor Stop start up “engine” (if practical) Increase fuel flow until the turbine reaches y RPM (about 8 times x) Enter the running state Designing an Electronic Control Unit (ECU) is only a genesis. The features in ECUs, such as Powertrain Control Units (if relevant to jet engines and this scale), are quickly becoming more complex and offering more features. In highly professional cases (likely not here) thousands of variables (likely not here) are present for the engineer to modify during the in-vehicle calibration phase, and fine tuning them is as complicated as it is critical. Calibration tools importantly impact the efficiency and effectiveness of the ECU development process. These tools are typically comprised of software to perform the adjustment of the variables and an ECU hardware interface to provide the connection of the software to the controller. One must be able to measure and time-align relationships of inputs and outputs and make real-time modifications. Once these steps are complete the user has control and can throttle the engine as needed. As the ECU is running it constantly performs critical tasks that prevent the engine from reaching a dangerous state. This arises from the fact that the mechanical components of the engine are rated for certain limits. For example, the turbine may only handle temperatures of 800°C and speeds of 115,000 RPM, over which the engine can see a drastically reduced lifespan or fail completely. If any of these conditions are exceeded the ECU must detect it, take over control and recover the engine to a safe state. Since we are designing a custom engine there is some extra functionality that we want to build into our system. A terminal that communicates with the ECU during run-time is critical. The idea is that we will be able to control the engine, monitor performance and set variables for tuning the engine. The ECU sending back log messages lets us graph, analyse and record the conditions inside the engine; tweaks parameters that affect engine performance using data gathered in previous runs. A good ECU requires redundancy of all components, including sensors and electric power supply. To have dual channels, namely, all parts of the system are independently duplicated. Modelica libraries for jet engines are acquirable. Hopefully, microjet engine operational scales are possible where one can acquire (ideal) characteristics of interest. Interest in identifying PID control for jet engine as well, concerning comprehension of what’s going on. The challenge will be making such simulation and control meaningful to applied hardware. Furthermore, the following literature provides some idea, but, our interest is towards our microjet engines: L. S. Mendonça, D. D. Luceiro, M. E. S. Martins and F. E. Bisogno, "Development of an Engine Control Unit: Implementation of the Architecture of Tasks," 2017 IEEE International Conference on Industrial Technology (ICIT), Toronto, ON, 2017, pp. 1142-1146. B. Jeeva, S. Awate, J. Rajesh, A. Chowdhury and S. Sheshadri, "Development of Custom-Made Engine Control Unit for a Research Engine," 2014 2nd International Conference on Emerging Technology Trends in Electronics, Communication and Networking, Surat, 2014, pp. 1-6. Validating programme patches and testing in simulation are essential. Will like the C or C++ environment. Other notable literature: M. Dub, J. Bajer, and M. Stepanek, "Electronic Starting Control Unit for Small Jet Engine," International Conference on Military Technologies (ICMT) 2015, Brno, Czech Republic, 2015, pp. 1-4, Csank, J., May, R. D., J. S. and Guo, T. (2010). Control Design for a Generic Commercial Aircraft Engine. NASA/TM—2010-216811 & AIAA–2010–6629 L. Gou, Z. Liu, A. Liang, L. Wang, and Z. Zhou, "Design of Simulation Platform for Control System in Aircraft Engine," 2018 37th Chinese Control Conference (CCC), Wuhan, China, 2018, pp. 8671-8676. Parallelization may be inevitable (but will not depend on course experience, rather for experience purposes, yet any background in such is appreciated). Some assist (but our concern is for microjet engines): -Thompson, H. A. & Fleming, P. (1991). Parallel Implementations of Gas Turbine Simulations Using Transputers. Proceedings of The Institution of Mechanical Engineers Part I- Journal of Systems and Control Engineering - PROC INST MECH ENG I-J SYST C. 205. 199-206. -Thompson, H. A. (1992). Parallel Processing for Jet Engine Control. Advances in Industrial Control. Springer-Verlag, London -Duncan S.H., Gordon P.L., Zaluska E.J., Edwards S.I. (1994) Parallel Processing in High Integrity Aircraft Engine Control. In: Gentzsch W., Harms U. (eds) High-Performance Computing and Networking. HPCN-Europe 1994. Lecture Notes in Computer Science, vol 796. Springer, Berlin, Heidelberg The following three loose sources may be a distraction or beneficial --> https://cboard.cprogramming.com/c-programming/145514-small-engine-ecu-efi-moped-using-audrino-uno.html https://learn.sparkfun.com/tutorials/getting-started-with-obd-ii/all https://rusefi.com NOTE: instantaneous duration infrared imaging and instantaneous duration infrared temperature data will accompany ECU activity. To then observe commercial passenger jet engines to recognise any embedded or integrated system that has similar function as such. Full Authority Digital Engine Control (FADEC) 1. Concerns understanding its purpose (with emphasis on the adjective “full authority”) 2. To understand the general component features of FADEC 3. Will trace all physical integration/links with engine in question. Such requires up close observation of a real jet engine (not necessarily physical contact). If field observation is not possible CATIA models may provide such. Observing the network sophistication with components and various sensing operations. 4. Innovation or advancements today: implementations of FADEC functions on a system-on-a-chip (SOC) to improve performance and reduce the size, weight, and thermal footprint of FADEC systems on traditional turbine engines. (X). Following the ECU optimisation, after time has passed where engines have cooled down the respective engine will be operated again and subjected to chronological infrared imaging to observe and acquire temperature dynamic through time. Infrared imaging for viewing of the engine and thrust space continuously in time; detecting infrared energy and converting it into electronic signals, then to be processed to produce a thermal image and perform temperature calculations. Pursue a configuration where temperature calculations are made for a determined interval of seconds (could be each second); data for arrangement, modelling and comparative analysis with software models and consensus professional data. Recordings and data should be storable in initial state, dated, labelled, etc. Such to be compared with ECU data. Furthermore --> Arreola – Zamora, M. Fluid Flow Analysis of a Micro Turbine Jet Engine. NASA https://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/20150022385.pdf (XI). Pollution Emissions The following synopsis is an alteration of Eloy R. Lozano , Walter W. Melvin Jr. & Seymour Ochheiser (1968) Air Pollution Emissions From Jet Engines, Journal of the Air Pollution Control Association, 18: 6, 392-394 A means to accommodate micro jet engines. Will find highly economic analytical methods as substitute. Pollution emissions from developed jet engine types to be determined. Possible pollutants to be recognised include nitrogen oxides, aldehydes, carbon monoxide, hydrocarbons, and odours. To have a method for determining the magnitude of pollution emissions due to commercial jet aircraft operation by using basic emission factors. -Engine Specification and Performance Data Table (Average Values) Engine Type Fuel type Power Setting (Taxi, Take-off, Climb, Cruise, Approach) Fuel Flow lb/hr Fuel/ Air Ratio Exhaust Gas Temperature Pressure in Hg Intake Air Temperature Concerning such table development one will (concerning power setting) have to conjure theoretical models approach for such engine (likely considering that engine functions in pair at least). As well based on theoretical aircraft models and acquired engine data one needs to determine times for power setting types. Summing forces leading to Newton’s second law is quite vague; same goes for determining acceleration and distance requirements for take-offs. The aerodynamic design, average amount of required actuation, subject to weight, propulsion capability and loads will influence Newton’s law and the two latter mentioned parameters (in a kinematic sense). This is why analytical modelling and simulations are crucial; only a few crafts can be built at a time, and we’re trying to conserve resources and reduce pollution to best of ability. -Estimated Time of Departure and Landing Table Basically, from theory to determine timing within power settings -Develop jet engine exhaust sampling system -Methods of Analysis Pollutant Type Sampling Apparatus Analytical Method Sampling efficiency is crucial. As well, samples to not be taken during acceleration or deceleration modes because large variations in exhaust composition were observed during these periods. -Pollution Emissions from Jet Aircraft Table (power setting and engine type & pollutant type) -Estimated Pollution Emissions from Jet Aircraft Operations Table (discriminating pollutant type) (XII). NOTE: accumulated dust on blades can greatly deteriorate jet engine performance. (XIII). Review of theoretical analysis of compressors at supersonic speeds from above. For supersonic speeds determine whether built jet engines would reach such. Possibly ECU is programmed to reduce jet engine max to avoid fuel deficiency and so forth. If so to observe and analyse ECU operations via “black box” data records. Compressor Stall --> Mikhailov, A., Mikhailova, A., Akhmetov, Y., & Akhmedzyanov, D. (2017). Simulation of Gas Turbine Engines Considering the Rotating Stall in a Compressor. Procedia Engineering, 176, 207-217 NOTE: compressor stall is virtually eliminated by the ECU/FADEC. Comprehend how such is done. (XIV). Aircraft turbine blades cooling Consider and aircraft traveling around an altitude of 40,000 feet above sea level. Determine what the air temperature should be based on the following: https://www.grc.nasa.gov/www/k-12/rocket/atmos.html Is the result consistence with other sources or toolbox applications? An aircraft’s turbine blades function near the combustion chamber become quite hot. A coolant is required to oppose turbine blade failure. Will the air at such an altitude resolve this issue? Related to the prior question, consider the relation between cold air and pressure for circulation. Related to pressure for air circulation what is the ideal temperature preferred to function optimally? The following guides can serve well for detailed turbine cooling analysis: https://www1.grc.nasa.gov/historic-facilities/special-projects-laboratory/materials-research/ https://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/19680009718.pdf Han, J., & Dutta, S. (2001). Recent developments in turbine blade internal cooling. Annals of the New York Academy of Sciences, 934, 162-78. Han, J. (2004). Recent Studies in Turbine Blade Cooling. International Journal of Rotating Machinery, 10(6), 443-457. Rolls-Royce (2015). The Jet Engine. Rolls Royce Technical Publications; John Wiley & Sons (XV). Analyse the following: Acceleration of an Airplane by a Turbojet Engine -YouTube https://www.youtube.com/watch?v=7XlR_g1f-i0 Consider different models and sizes of turbojet engine aircraft. Based on a list of values for the described parameters as in link can a chart be developed for determination of needed distance and acceleration for a respective airplane to accomplish takeoff? Model and develop code towards a display of some sort with means to vary parameter values. Determination of the following for different aircraft: Minimum distance and acceleration needed for take-off Rate of ascent w.r.t. prior two parameters Greatest altitude Maximum cruising speed at best performance altitude Maximum distance of travel Time of longest flight (XVI). Compare and Contrast with Real Passenger Jet Engines Turbofan jet engines (greater efficiency) Jet engines with axial-centrifugal compressor combinations Air Starters System components of passenger scale jet engines Physiology Sensing, control and regulation Such mentions above reveal that this activity in total is “kindergarten” learning in aerospace engineering; opposition to it can be viewed as disheartening or socioeconomic impedance. (XVII). Ultimately, systems developed concerns configuration into an aerodynamic body towards actual flight with designed course and manoeuvre. Will empahise much Aerodynamics, Aircraft Design and Structural Analysis: Wells, D. P. and McCullers, L. A. (2017). The Flight Optimization System Weights Estimation Method. NASA/TM–2017–219627/Volume I Raymer, D. (2018 6th ed.). Aircraft Design: A Conceptual Approach. AIAA Gudmundsson Snorri. (2014). General Aviation Aircraft Design - Applied Methods and Procedures. Elsevier/Butterworth-Heinemann Structural analysis likely will be comprehensive Weight distribution determination of integrated systems for optimal aircraft performance Propulsion Integrated ECU Sensors (altimeter, acceleromter, gyro, etc. ) with time synchronization Data collecting module(s) from sensors Control Electric power sources for prior 4 Fule tanks (with CoM/CoG variance issue) Based on engines developed and aircraft design, determination of the following (theory versus data collection): Minimum distance and acceleration needed for take-off Rate of ascent w.r.t. prior two parameters Greatest altitude Maximum cruising speed at best performance altitude Maximum distance of travel Time of longest flight Flight Envelope and Doghouse Plot Incorporated into vessels will be altimeter, accelerometers for speed and acceleration, gyroscope sensor and magnetometer. Such sensors to be synchronized with each other concerning time towards data storage; for each time count will be associated sensor readings. Develop a flight plan coordinated drill for respective aircraft with specific course involving altitudes, speeds, manoeuvres; multiple trials. Will have a very light black box that records actions by operator (both active and neutral) and ECU actions, synchronized with all sensing data. Such to be created with programmable boards. Data retrieved can be associated to (C). Note: craft can be controlled by an old laptop, or old Wii control stick, etc., etc. Determine theoretical top flight speed. Development of flight envelope, level flight performance and doghouse plot; with compare all such three with flight trials. NOTE: flight path reconstruction Teixeira, B. O., Tôrres, L. A., Iscold, P., & Aguirre, L. A. (2011). Flight Path Reconstruction – A Comparison of Nonlinear Kalman Filter and Smoother Algorithms. Aerospace Science and Technology, 15(1), 60-71. May be able to compare with FlightGear Simulator and NASA’s NewSTEP is a (matlab-based) iterative extended Kalman filter/smoother designed for solving trajectory reconstruction problems for flight test experiments. (XVIII). Performance Deterioration Modeling in Aircraft Gas Turbine Engines This phase subject is critical in the professional AE field. One major issue is that there may not be a consensus method to model and predict such deterioration. NOTE: the given articles below are just a few pursuits for treatment; other example methodologies can involve (multivariate) time series. Nevertheless, the engine models of interest may be different and more intricate than what’s observed in such articles, hence, one must make the appropriate amendments for such. Well, one can choose three to four different engine models and determine how consistent the methods are with each other; such comparative process may be the method of assurance in the AE industry, where one develops safety thresholds based on comparative findings. --Zaita, A. V., Buley, G., and Karlsons, G. (April 1, 1998). "Performance Deterioration Modeling in Aircraft Gas Turbine Engines." ASME. J. Eng. Gas Turbines Power. April 1998; 120(2): 344–349. --Yoon, J. E. et al. Analysis of performance deterioration of a micro gas turbine and the use of neural network for predicting deteriorated component characteristics. Journal of Mechanical Science and Technology 22 (2008) 2516 - 2525 --Gholamhossein, Maryam & Vatani, Ameneh & Daroogheh, Najmeh & Khorasani, K. (2012). Prediction of the Jet Engine Performance Deterioration. ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE). 1. 10.1115/IMECE2012-87936. --Koh, W. C. et al. A Computational Study to Investigate the Effect of Altitude on Deteriorated Engine Performance. IOP Conf. Series: Materials Science and Engineering 370 (2018) 012001 NOTE: all prior jet engines built will not serve to reduce any phase in this activity in the future. Competence, elegance and precision will likely increase season after season. Activity will lead to a secured inventory of jet engines of various sizes for use in various aircraft. All jet engines built will be registered into a secure and confidential inventory database. Data and development from prior seasons will require security access; clearance will concern what interests, motives or objectives constituents are recognised to have. Data and developments concern no other academic institution outside and external. Orders with machining if be the case warrants highest of privacy and security. Typically, each jet engine will be assigned a confidential ID. Such ID will be used to: -Identify jet engine -Engine class Dimensions Ideal performance parameters Operational requirements -Date of completion and confirmation of functionality -Life expectancy starting from date of completion and confirmation of functionality -Operational activities Each activity with respective operating time Technical data for particular operation at medium to elevated states with respective timing -Dated inspection reports E. Helicopter System Modelling & Control 1. Rotorcraft mechanics 2. Ren, B., et al, Modelling, Control and Coordination of Helicopter Systems, Springer, 2012 Such is an extensive text towards comprehensive dynamical modelling and control of helicopter systems. Includes recognising the crucial governing equations for general motion, rotor mechanisms, and rotator blades dynamics. NOTE: overall, will be analogous to activity (C) concerning data and characteristics from Systemodeler/Modelica compared to data acquired from FlightGear Simulator; based on flight plans and coordinated manoeuvres. Additional sources that may prove quite useful: Pan, L., and Renliang, C., A Mathematical Model for Helicopter Comprehensive Analysis, Chinese Journal of Aeronautics 23(2010) 320-326. Gavrilets V. (2015) Dynamic Model for a Miniature Aerobatic Helicopter. In: Valavanis K., Vachtsevanos G. (eds) Handbook of Unmanned Aerial Vehicles. Springer, Dordrecht Mettler, B., Tischler, M. and Takeo, K. (2002). System Identification Modelling of a Small-Scale Unmanned RotorCraft Helicopter. Journal of the American Helicopter Society, Volume 47, Number 1, 1 January 2002, pp. 50-63(14) S. Panza and M. Lovera, "Rotor State Feedback in Helicopter Flight Control: Robustness and fault tolerance," 2014 IEEE Conference on Control Applications (CCA), Juan Les Antibes, 2014, pp. 451-456. Ji, H., Chen, R., & Li, P. (2018). Rotor-state Feedback Control Design to Improve Helicopter Turbulence Alleviation in Hover. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 232(1), 156–168. Butt, S. S. and Aschemann, H. Multi-Variable Integral Sliding Mode Control of a Two Degrees of Freedom Helicopter. IFAC-PapersOnLine 48 – 1 (2015) 82 – 807 F. Helicopter Engineering Activity (E) is a prerequisite. This project will also incorporate constituents from mechanical engineering, computer engineering and computer science. (i). Will pursue RC fuel helicopter engines. Will have comparative analysis between such RC engines and commercial passenger scale helicopter engines. Goal is to develop a drive train (main and rudder) integratedwith engine, integrated ECU, fuel source integrated, actuators, sensors (gyro, accelermeter, altimeter, etc.), camera, power source (for actuators, flight stability/control system, sensors, ECU, fuel input based with ECU, flight/stability, camera, etc.). Batteries and electrical systems should not be expoesed to high heat and moisture (condensation or precipitation). It’s important to understand the geometries and orientations for all such components in order to design a chassis that’s strong and light; centre of mass or centre of gravity is a concern; keep in mind CoM or Cog will change with fuel consumption. As well, chassis should not be easily vulnerable to high heat exposure. Note: one is expected to have developed multiple spare chassis. The two engine models of concern: Four- stroke engine (bought or salvaged from other equipment) Turbine powered (bought) Will determine whether a stroke engine is practical or feasible for passenger scale. (ii). Helicopter rotor constitution in CAD and/or field observations. After making decision on the components that will be chosen for helicopter rotor assembly, structural analysis would be greatly appreciated further giving idea on the levels of stress and strain that will apply, subject to rpm, torque, etc.; also keeping in mind that drastic weight is disadvantageous --> Shafts, axles, gears, bearings, static mast, spherical bearing droop stop ring, droop stop retainer, pitch change links, rotating swash plates, non-rotating swash plates, lateral links, scissors assembly, torque links, main rotor dampener, strap pack, hub, de-rotational unit, pitch housing. etc. applied will be represented by basic commercial parts; concerns for the optimal parts not leading to rapid mechanical breakdown. Also concerns optimal support for weight and strain of rotor blade fixtures together with rotor (and blade radius of concern). Note: one is expected to have multiple spare parts of the listed above. A pursuit is an optimal “transmission” system w.r.t. to that’s satisfactory in sturdiness, while also be light. Thorough machine design with scaling for high performance. Isolated engines considered have known performance parameters, but when integrated to the “transmission” system the power, torque and rpm at “full throttle” must not fall below a certain percentage; otherwise “transmission” system will be labelled nothing more than an impedance. Planning will incorporate CAD development, materials analysis, etc.. Failure analysis for rotor components is also possible. (iii). Assumption is, activity (E) was at least competently developed for flight stability and control. Motors with actuators should be appropriate for the various desired actuations. Power/lifetime analysis of power systems should be determined concerning all the necessary responsibilities for flight chosen missions and manoeuvring. (iv). Test bench for powertrain + ECU + drive train +other components (v). Design and construction of helicopter blades The cross section aerofoil design of the rotor blades are generally harmonious to geometry descriptions recognised in DATCOM, XFLR5 (low Reynolds numbers), Athena Vortex Lattice (AVL), XFOIL and other detailed software, but lateral geometrical design and composition to be accounted for. Making of rotor blades to suit specified loads, lift demands, speed, etc. while retaining integrity and desired flexibility can be quite technical. Depending on size of aircraft rotor blades made of wood likely will not suffice due to the mechanics and dynamics of rotor blades in function. Construction is often seclusive or not mainstream. An extensive lab case example --> Mainz. H. et al (2005). ABC Rotor Blades: Design Manufacturing and Testing. 31TH EUROPEAN ROTORCRAFT FORUM FLORENCE, ITALY – SEPTEMBER 13-15, 2005 PAPER 118: https://www.cedrat-technologies.com/fileadmin/user_upload/CTEC/Publications/Publications/2010/04/ERF-31_2005_DLR-ONERA_ABC-ROTOR-BLADES-DESIGN.pdf Keep mind how the blade will be fitted and connected. From all such one can predict the operational extremes of the rotor blades. CFD analysis with Ansys can be applied as well. Note: incorporation of carbon fiber encapsulating foam and UD spar “glass” can be greatly rewarding. The alternative: Fiberglass Rotor Blade Layup time-lapse - YouTube --> (https://www.youtube.com/watch?v=D5yzFrMb2d4 ) Homebuilt Carbon Rotor Blades – YouTube --> (https://www.youtube.com/watch?v=IW8WZkWZgqI ) two critical concerns --> First, one should be able to simulate how rotor blade will perform at various speeds. Determination of lift for various speeds. Second, being very crucial, the structural behaviour of the rotor blades at various speeds. Third, how will pitching at various speeds influence structural integrity. A literature that may prove helpful with logistical development (there can be software substitutes): Ngoc Anh Vu, et al (2016). A Fully Automated Framework for Helicopter Rotor Blades Design and Analysis Including Aerodynamics, Structure, and Manufacturing. Chinese Journal of Aeronautics, 29(6), pages 1602 – 1617 Must have competent means of confirming structural integrity and flexibility with choice(s) for rotor blade composition w.r.t. aerodynamic design for helicopter use; performance must be met with scale in consideration. Note: must develop multiple rotor blade sets. (vi). Primitive testing (will likely be done in a safety room operated outside of it). Will like to first test the ECU controlled powertrain + drivetrain. Data of interest: rpm, torque, fuel rate, instantaneous infrared data (imaging and temperature, respectively). Will then like to integrate rotor blades into test bench. Data of interest: rpm, torque, fuel rate, instantaneous infrared data (imaging and temperature, respectively, and thrust from main and rudder (tricky one). (vii). Site for yesting/calibrating pitch and roll motions with the main rotor and tail rotor; data acquisition concerning control analysis for servos, actuators (involving pitch links, roll links, control rods and so forth) where dynamic can be analysed towards establishment of smooth and efficient mechanical control, say, feedback/autmatic control and/or parameter settings. The pitch and roll is developed to be adjusted by steps of 1/10 of degree and memorized or standardized in “tables” as any other configuration parameters. The rotor speed is servo controlled within a few rpm's. For each measurements a hundred of samples are picked up and averaged. The complete bench/envirnment to insure good reliability in the measurements which are made either on ground effect (IGE) or out of ground effect (OGE) using solid legs to rise up the body. (viii). Determine theoretical top flight speed, level flight performance, and level flight envelop. Determine theoretical time of maximum flight for fuel capacity with fuel type. (ix). Exhibition (multiple times) of lift, fixed position off ground, and motions that are uniquely finesse to a helicopter. Such sensors to be synchronized with each other concerning data acquisition. Develop a flight plan with scripted coordinated drills. Note: craft can be controlled by an old laptop, or old Wii control stick, etc., etc. NOTE: flight path reconstruction Teixeira, B. O., Tôrres, L. A., Iscold, P., & Aguirre, L. A. (2011). Flight Path Reconstruction – A Comparison of Nonlinear Kalman Filter and Smoother Algorithms. Aerospace Science and Technology, 15(1), 60-71. May be able to compare with FlightGear Simulator and NASA’s NewSTEP is a (matlab-based) iterative extended Kalman filter/smoother designed for solving trajectory reconstruction problems for flight test experiments. G. Electric Analogy to (F) Structural components overall to be almost exact, however, one must identify the analogy to the ECU, appropriate power supply, speed controller and voltage requirements for each specific electrical constituent. Of consequence, craft’s weight and weight distribution likely to be quite different. Best operated in a temperate climate on the cooler end (but not drastic cold). Major issue with electric rotor crafts at the passenger scale are power supply, battery management, flight control (in various atmospheric environments), equipment insulation from the elements, and flight longevity, all mostly subject to passenger loads. Such should also be investigated. H. Rocket Science & Engineering NOTE: one must never mistake this activity to be a hobbyist club that restricts academic and engineering labour, nor will it ever converge to a hobbyist club that restricts academic and engineering labour. Activity has a policy of not giving handouts. Namely, every following description as is will be done intimately. Nothing will be pre-developed for any future operations with this activity. You are being engineers, not hustle coders. Such also implies that I don’t care for sex or gender (or whatever) cameos. It’s about you not creating bad publicity and embarrassing development errors with general projects. You being at least foundationally competent at various levels towards your future; you don’t ever invite/incorporate/nurture con artists, saboteurs and parasites. All data from this activity will be securely archived. Constituents on notice: this activity concerns rocket performances that can be acknowledged by the professional engineering society, professional physics society and professional chemistry society. Physics and chemistry constituents are welcomed. Open to ME, IE, EE, COMPE and CIVE, constituents. (i). Principles and physics of rockets with mathematical rigor Ganji, D., D., et al. Propulsion and Launching Analysis of Variable-Mass Rockets by Analytical Methods, Propulsion and Power Research 2013; 2(3): 225–233 (ii). Building solid propellant rockets with safe conventional constituents Solid propellant rockets are often considered the beginning of professional conventional rocket science and engineering. Respective chemistry will be analysed towards harmony with physics. There will be determination of rocket design and composition that’s most advantageous towards thrust and specific impulse, say, parameters such as rocket motor classification, propellant, propellant grains, vessel weight, mass configuration, rocket stability, structural integrity, aerodynamics, etc.. NOTE: from this point on concerning parameters, conditions and models all students must be able to identify, organise and know when to use them in the most competent and fluid manner. For whatever cultural reasons, there are entities who aim to be mischievous, to confuse, be a hindrance and be destructive because they have nothing better to do…and they get paid for it when in reality they contribute nothing practical and constructive. With such parameters, conditions and models, something like “biological pathway” must be developed that’s fluid to students towards competency and professionalism, however, such is not a means to pursue being a con artist like many theoretical mathematicians. All data and sources provided in activity must be understood concerning what and when to apply. A condensed idea of rocket construction --> NASA High Powered Video Series Counterpart Documents: https://www.nasa.gov/sites/default/files/atoms/files/sl_video_instruction_book.pdf Primitive mechanics & aerodynamics features --> -Sizing of engine motor to determine body dimensions L class rocket motor for launches -Canard fins design & tail fins design (meaningful aerodynamic effects) Critical angle of attack for all such -Modelling & Analysis (will be serious) Lift Force, Drag Force, Dynamic Pressure, Ballistic Coefficient, Critical Angle of Attack, Centre of Pressure Static Stability (centre of gravity, centre of pressure) Stable Cp must reside below the Cg. Lift and drag forces maintain their directions but the direction of the torque created by the forces is reversed. To increase stability of rocket (if needed) add weight to nose, or increase the area of the fins. Identifying Axial Force and Normal Force Lift force and drag force in terms of such forces Turning moment dependent on normal force Defining pitch moment Dynamic Stability (damping ratio, homogeneous response, step response) Finite Element Analysis: mode shapes Drag Coefficient and Aerodynamic coefficients Drag (friction force coefficient, body drag, base drag, total drag) Aerodynamic coefficients – dynamic and control derivatives Computational fluid dynamics Again: Cp must reside below the Cg Dynamic stability of (all) fins --> Flutter boundary equation: NACA Technical Paper 4197 (may need amending). Determining flutter velocity and instances. The geometrical parameters in such equation require formulas; yet air pressure (and speed of sound) to be highly variable due to drastic change in altitude and temperature in a short period. Flutter velocity changes with altitude, hence, to accurately predict flutter speed, the altitude at which maximum velocity is achieved must be known. The following source may be a further assist with flutter velocity and divergence velocity. Software acquisition may be a problem concerning vendor’s preference in customer, but its foundation can be confirmed, and alternative software or simulations based on modelling can be done --> http://www.aerorocket.com/finsim.html (if based on NACA Technical Paper 4197 may require amending) -Flight Dynamics 6DoF Mathematical Model Rotation Kinematics and Rotational Matrix Aerodynamic forces and motion Summary of the 6-DoF Equations of Motion Note: matrices are just tools where in general CAS are applied to do away with such time consuming monstrosities. What’s important is that you understand what goes in a matrix, rather than playing in a Mathematician’s pig pen. Maximum Dynamic Pressure Modelling for rockets Determination -Will then have pre-analysis of rocket dynamics performance with software: OpenRocket Simulator ROCETS from NASA software catalogue Then critically, comes crucial mechanical engineering development requiring detailed geometrical development. Software mentioned at the end of this activity description will provide the intricate parameters; also, one must be responsible by comprehending the associated formulas. Data to develop geometries in CAD, followed by structural analysis, design and construction logistics (compatible with primitive mechanics and aerodynamics features prior) --> Propulsion System Design and Mounting Features Structure Team Determining Structural Loads Structural Component Design Determining shift of Cg due to propellant burn off Prediction for the Cp regime of flight (to always reside beneath Cg) Stability of margin model Manufacturing and Assembly For the structure team, structural loads, and structural components design, to be developed in a manner where the resulting weight distribution neither considerably creates change in pitch w,r.t. to rocket’s axis of symmetry during ascent, nor influence yaw changes during ascent. . For internal systems and apogee parachute deployment system all such should be securely situated in a manner where the resulting weight distribution neither considerably creates change in pitch w,r.t. to rocket’s axis of symmetry during ascent, nor influence yaw changes during ascent. Larger scale rockets (at least L class motors) must be built for launches to accommodate height readings, velocity readings, acceleration readings, gyro sensing (concerning roll, pitch and yaw concerning), apogee sensing-parachute actuation, and strong professional performances. Development of apogee sensing for parachute deployment (likely involves magnetometer). There are two common options for rocket recovery system (RRS): Piston ejection system Richard Nakka – Parachute Recovery System (https://www.nakka-rocketry.net/parasys.html) System design and development for RRS may be more technical than expected. It must well planned out and designed to scale. For parachute with chords choice should be those that can handle the jerk or strain applied following parachute ejection and descent. Based on curved surface area of parachutes in function one should determine highest amounts of air resistance (with reduced weight of rocket); hence, also the highest tension chords will face. RRS should be tested multiple times with two phases: Actuation ejection or kinetic deployment Apogee sensing & computing to trigger actuation ejection or kinetic deploy Instruction for RRS shouldn’t be in conflict with other sensing and processing obligations. All mentioned sensing must be chronologically synchronised with each other. System should also be able to time log parachute deployment related to apogee determination. All sensing for chronological data storage can be extracted, arranged, curve fitted, etc. Sensors, processing and storage to be internally stationed where they are not susceptible to impact damage and drastic heat. Parallel processing if need be. Sensing Apogee-parachute actuation Altitude Acceleration Velocity Gyroscope (concerning roll, pitch and yaw concerning stability) Data from gyroscope sensing to indicate whether rocket has competent trajectory performance overall when compared to ideal model. Cameras Downward view with wide range Lateral view For acquired data form sensing one can compare with simulation models to acquire a gauge on the values of parameters, coefficients, etc applied to rocket; will vary among the different propellants. Note: there may be system(s) that account for multiple types of sensing in one module, BUT, if such a module doesn’t function then it’s all bad for sensing and data. Sensing configuration to be encapsulated (likely in cylindrical fashion) that’s not susceptible to dislodging by jerk motions due to inertia, impact damage, heat, etc. Note: old smartphone boards have various sensors that can be practical in the sense that the configurations are optimised with minimal weight. Some insight: How to See and Use Mobile Phone Sensors Data - YouTube: https://www.youtube.com/watch?v=o8yJxDOFCXo However, one wants to minimize weight and synchronize with other data in time towards data storage. Smartphone board directly may be preference, possibly integrated with microcontrollers (if warranted). In addition to taking advantage of the GPS, one can probably include taking advantage of any remaining cellular network system, say, seeing the phone as registered could use radio triangulation from nearby towers to determine its location, but with less accuracy; a cheap “pay-as-you-go” network is possible. Preferably one will like a smartphone will all such sensors to take full advantage of the app. The barometer means of altitude determination with smartphone sensors has high accuracy concerning “cabin pressure”, but reference points are required. Apart from the data structured on time counts into storage, consider as well if the time coordinated data can be transmitted through the “pay-as-you-go” network to ground reception. Thus, team can have an advance view of real rocket data geometrically compared to theoretical model with the known parameters. Standard time associated data should also be possible. Such innovation with smartphones to be a secondary/backup independent system in rocket specifically tailored towards rocket data types mentioned. Also there must be means to activate sensing and cameras in rocket, in conjunction with synchronized data storing activation, all such upon “continuity check” success confirmation by circuit system. Wireless signalling is an optimal candidate to activate all such; upon launch circuit “continuity check” success confirmation. One may develop “automation” where activation directly follows launch circuit “continuity check” confirmation. Will be first virtually constructed and simulated towards acquiring detailed behaviour and characteristics of such extended circuit. Then onwards to constructing and testing wireless activation. A functioning system (from smartphone and from “professional sensors”) will give “data feedback” to operator. Confidential wireless security code likely required to activate; must be a secured network post activation. This is an engineering activity, rather than ignorant bliss and subjugation to retail expenses. The limit and mandatory pursuit for solid propellant rocket launches will be rockets with L class motors. For rocket launchpad design and development, the following source is a solid idea, but construction will likely not be as lavish (generic cost-effective recording cameras rather than GoPro, say, video camera key chains tapped on can work if not exposed to much high temperatures) --> https://www.rocketryphotography.com Much development design in a CAD constituted with efficient mechanisms, hence optimal elimination of any impedance and misaligned or perturbed launches. Structural analysis if warranted. Structure must be foundationally stable in most environments. As well, structure must be reusable and portable without much burden. For rocket igniter design and development a launch controller should be designed to: 1. Avoid accidental ignition, particularly when a person is wiring the igniter at the launch pad. 2. Indicate whether the igniter is properly connected (called a “continuity check”). 3. Efficiently deliver battery energy to igniter, avoiding launch failure, and maximizing battery life. Will then proceed with designing a basic rocket launcher circuit and simulate such to observe its character. Then, proceeding with development of a rocket launcher circuit board similar to the following: https://www.robotroom.com/Rocket-Ignition-System-1.html One shouldn’t be intimidated by the looks of such ignition system, namely, circuit analysis, virtual construction and simulation will simplify things towards competency and professionalism for detailed behaviour. A general structure --> https://arduining.com/2012/03/01/rocket-launch-controller-simulated/ An Arduino (or other) module can eliminate excessive circuit features. However, igniter should provide the appropriate surge characteristics to ignite L class rocket motors with consideration of type of propellant; amend Arduino (or whatever) programming, circuit components and power source to operate such. Hence, operational capability and power source should be comparable to that of “Robot Room” page 1 through 5. Then, onward to constructing such, testing behaviour and characteristics compared to simulation. This is an engineering activity, rather than ignorant bliss and excessive subjugation to commercial retail brands expenses. Alongside research (chemistry, physics and modelling), software GUIPEP + PROPEP, BurnSim and CEA from NASA will be used for propellant predictions. Such will also have determination on the type of materials the rocket nozzles will be made of; likely there will be different types made. Understanding a software’s foundation is important, which is why research (physics, chemistry and modelling) are essential. NOTE: NH4ClO4 will be the only type of oxidizer applied for solid propellant rockets. Concerns ordering in advance from sources that provide quality product. Activity will apply NH4ClO4 in developed propellants when ready for burn rate tests, test stations and rocket launches. NH4ClO4 will not be accessible outside of “summer” & “winter” terms unless authorized senior project is recognised. Like NH4ClO4, same for nano Al whether serving as as additive or fuel. NOTE: for each propellant constituent one must know the characteristics. Main concerns are -- Containment, storage protocols and “shelf life” Deterioration or weakening causes Auto-ignition temperature Combustion temperature Boiling point (if relevant) Melting point (if relevant) Chemical safety and Biohazards NOTE: there will likely be need to confirm the authenticity, purity and characteristics of propellant constituents. Before rocket launches will pursue rocket motor test stations with the following propellants (each to also be applied to rocket launches): (1) C6H14O6 + NH4ClO4 + additive NH4ClO4 MEANS NH4ClO4. For such C6H14O6 based propellant, additive to be nano-sized Al. This propellant will actually be the most dangerous to develop out of all propellants pursued. The dry compression method WILL NOT be pursued, because there's a significant chance for self-ignition while mixing (and during compression). The preferred method of preparing this particular propellant is dry heating. The sugar and oxidizer to be individually ground or milled to particle size of interest (if respective grain size from orders aren’t satisfactory), then tumbled to ensure uniform mixing; one must be careful with ground sugar itself, not to mention, the oxidizer. We want quality with this fuel, thus, knowing the melting point of C6H14O6 will be essential; not going overboard with high temperatures that can lead to combustion hazards with oxidizer. With heating the fuel/binder melts and coats the grains of the oxidizer indiscriminately. Before melting, determining how the nano Al is to be incorporated, say, during melting process, or at some lower temperature in the viscous melt form? Avoid creating auto-ignition hot-spots with improperly distributed mix on heating apparatus; heat transfer should also be spatially uniform in distribution from heating apparatus. I don’t favour the alternative dissolving-and-heating method because one isn’t certain that the (distilled) water will be completely evaporated; rocket science would be diminished concerning model performances. We are trying to get the most out of C6H14O6, by using such oxidizer and additive. Yet, for rocket science and engineering one can’t be stuck on C6H14O6 type solid propellants, say, C6H14O6 types still lack efficiency based on specific impulse; a rocket motor’s potential goes unfulfilled. One must have experience with at least one type of “real” APCP. NOTE: due to the preferred process of dry heating, individual slugs of solid propellant of equal length are contained within the motor (casing); lengths summed should result in a total length that’s optimal for rocket motor’s whole length when they are placed in. This type of propellant will be the only case where multiple slugs are required due to preparation. (2) ALICE propellant Nano Al will serve as a fuel. --Pourpoint, T.L. et al, Feasibility Study and Demonstration of an Aluminium and Ice Solid Propellant, International Journal of Aerospace Engineering, Volume 2012 Article ID 874076, 11 pages --Risha, G. A. et al. Combustion of Frozen Nanoaluminum and Water Mixtures. Journal of Propulsion and Power, Vol. 30, No. 1, January–February 2014 (3) nano Al + 100% Silicone Rubber Caulk (contains no water) + NH4ClO4 This will be our “real” APCP propellant. Concerning propellant (3), nano Al will serve as a fuel alongside the binder rather than being an additive. Note: the compound known as polydimethylsiloxane (PDMS) is found in common rubber sealant products. One may observe different siloxane compounds, however, poly is emphasized in the given beneath journal article. Nevertheless, GE and other corporations provide domesticated products with such. SILICONE TO BE USED MUST HAVE NO WATER IN CONSTITUTION. The AP/AL/silicone propellant cures pretty fast to a “rubbery” grain. Can the viscosity of the silicone be reduced at elevated temperatures not equal nor above combustion and auto-ignition? Would such temperature ranges be substantially below auto-ignition and combustion temperatures for NH4ClO4 and nano Al? There are PDMS with different molecular weights. Does lower molecular weight imply lower viscosity? Does lower molecular weight imply better performance? Issue with structural integrity of propellant grain. --Eisele, S., Gerber, P. and Menke, K. (2002). Fast Burning Rocket Propellants Based on Silicone Binders - New Aspects of an Old System. Propellants, Explosive and Pyrotechnics, Volume 27, Issue 3. Pages 161 – 167. To develop this propellant one must first solely ground the NH4ClO4 into smaller size particles. Then incorporate the nano Al with such oxidizer. Mixing/turning should be done relatively slow in a containment that neither generates high friction nor high heat in mixing/turning containment. Then to integrate the resulting Al - NH4ClO4 homogeneous mixture with the silicone. A homogeneous mixture with all three propellant constituents is pursued; crucial for stable rocket performance. Further intelligence --> --WeiQiang Pang et al.(2019). Chapter 7. Performance of Composite Solid Propellant Containing Nanosized Particles. In: Nanomaterials in rocket propulsion systems. Elsevier, Amsterdam, Netherlands. Pages 263 – 298 --Greatrix, D. (2015). Numerical Evaluation of the Use of Aluminium Particles for Enhancing Solid Rocket Motor Combustion Stability. Energies 8, 1195 - 1215 Students must determine the ratio for constituents by mass yielding optimal performance based. For each propellant will determine the various possible products. In solid propellant rockets structural integrity with performance is of great importance concerning the rigors of the rocket’s combustion chamber, inertia and the acceleration range throughout ascension. One may take a premature peak at rocket software data concerning the rocket motor class of interest (L class for the rocket launches as mandatory) to have an idea of what values these three measures will have; will influence moulding/casting qualities. For all given propellants students should research the best techniques to acquire quality grains. For a respective solid rocket propellant the characteristics of a constituent can’t be assumed to suffice the other constituents in mix. For all propellants will determine the best ratios for optimal performance and compare with predictions from GUIPEP + PROPEP, NASA CEA and BurnSim. Will then have test stations experimentation and rocket launches. A MUST --> all propellants developed must have homogeneous mixture. For a respective chemical reaction students must be able to explain the reactiveness, energies, temperatures, etc. NOTE: identical test rocket motors must be made, say, a quantity where each propellant will be fairly tested (with trials), etc. Overall, the essential characteristics of respective solid propellant (1 through 5) to be made aware of: --process method --curing time --storage environment & shelf life --density --melting point --boiling point --auto-ignition temperature --combustion temperature/adiabatic flame temperature --mass fraction of condensed-phase products --exhaust products --effective molecular weight of exhaust products --burn rate behaviour --characteristic exhaust velocity (predicted via software versus measured) --instantaneous exit/exhaust temperatures --specific impulse (predicted analytically vs software vs findings from tests) --burn rate at 1 atm --burn rate at 1000 psia Rocket motors for launch concern L class rocket motors. Will pursue heights, accelerations and velocities that vindicate the time, research and labour applied in activity. Propellant combustion: What is described in the following link will be pursued analytically through introduced chemistry and physics, then compared with analysis from tools such as GUIPEP + PROPEP, NASA CEA and BurnSim --> https://www.nakka-rocketry.net/th_comb.html https://www.nakka-rocketry.net/th_appx.html Note: geometry of propellant needed (for BATES and star). Calculation of Adiabatic Flame Temperature (AFT) concerns propellants (1) through (3). Students must understand the analytical modelling and computation of AFT with any rocket propellant in order to comprehend what they are applying into software. The burn rate of the propellant will determine which of the two geometrical grain types will be used towards excellent performance for rocket motors. Again, professional software for parameters provided below. The burning surface of a rocket propellant grain recedes in a direction perpendicular to this burning surface. The rate of regression, typically measured in inches per second (or mm per second), is termed burning rate (or burn rate). This rate can differ significantly for different propellants, or for one particular propellant, depending on various operating conditions as well as formulation. Knowing quantitatively the burning rate of a propellant, and how it changes under various conditions, is of fundamental importance in the successful design of a solid rocket motor: https://www.nakka-rocketry.net/burnrate.html The prior link doesn’t imply activity will only concern sugar types and sorbitol propellants; will treat the mentioned others earlier. Such a treatment in prior link can be extended to treat the other methods towards burn characteristics of interest. The burn rate of the propellant will determine which of the two geometrical grain types will be used towards excellent performance for rocket motors (between BATES/tubular grain and star grain). The following article provides idea of a generic Crawford burner (or strand burner), rather than gaudy proprietary equipment --> Aziz, A., Mamat, R. and Wan Ali, W. K. Development of strand burner for solid propellant burning rate studies. WIOP Conf. Series: Materials Science and Engineering 50 (2013) 012048 As well, the following the provides various methods for the determination of the burning rates of solid propellants: Gupta, G. et al. Various Methods for the Determination of the Burning Rates of Solid Propellants. Central European Journal of Energetic Materials, 2015, 12(3), 593-620 Richard Nakka’s Strand Burner for Burn Rate Measurements --> https://www.nakka-rocketry.net/staburn.html Nakka’s strand burner illustration may be more feasible/tangible than the journal articles, but principles in general should coincide with each other. One can compare experimental burn rate findings with known results for propellant composition ratios. Design of propellant grain-- The core of the grain can have a variety of cross-sections. The core shape has a considerable influence on the shape of the thrust-time profile. For respective cross-section data, research the thrust versus time curve from professionally recognised resources. Examples: BATES, tabular, rod & tube, double anchor, star, multi fin, dual composition, wagon-wheel, etc. Thrust being proportional to burning area (instantaneous burning area). A rough idea of modelling can be found on Richard Nakka’s website --> Solid rocket motor theory-propellant grain Grain area calculations Solid propellant burn rate A neutral burn may be desirable because it often provides greater efficiency in delivery of total impulse, as a nozzle operates most efficiently at a constant chamber pressure; clearly distinguish between progressive burn and neutral burn. In some cases a BATES grain is preferred. Exposure to and understanding of the physics and mathematical modelling are necessities towards being a professional. Rough summary (elementary examples): https://www.nakka-rocketry.net/th_grain.html Interested in BATES/tubular grain and star grain. However, for neutral burn with star grain, MANDATORY, the propellant grain mass and length be the same as the BATES counterpart; the star’s area (not the burning area) MUST NOT result in reduction of either two such parameters. The thrust (and chamber pressure) that a rocket creates is proportional to the instantaneous burning area. One’s pursuit concerning the star grain is the area under the thrust-time curve (acquired via integral calculus) being approximately equivalent or greater than that of the BATES/tubular grain for the same time duration for same grain mass and same grain length. The following may be of interest to verify: Mod – 01 Lec – 25 Burning Surface Area of Solid Propellant Grains – YouTube https://www.youtube.com/watch?v=00mvx4IjD5M Nozzle development: --Modelling for thermal-compressible flow for optimal thrust with convergent-divergent nozzles. It may prove annoying to find compact and concise modelling, however, such needs to be comprehended for use. Includes half angles of 30 degree convergent and 12 degree divergent with explanation for such parameters being optimal. Supporting complimentary texts: Greatrix, D., R., Rocket Nozzle Flow. Powered Flight: The Engineering of Aerospace Propulsion, Springer, pages 303-315 Greatrix, D., R., Solid Propellant Rocket Motors. Powered Flight: The Engineering of Aerospace Propulsion, Springer, pages 323-378 Sutton, George P., and Oscar Biblarz. “Rocket Propulsion Elements”, John Wiley & Sons, Incorporated, 2016. Xu, J., and Zhao, C., Two-Dimensional Numerical Simulations of Shock Waves in Micro Convergent–Divergent Nozzles, International Journal of Heat and Mass Transfer 50 (2007) 2434–2438 Majdalani, J., and Maicke, B., A., Direct Calculation of the Average Local Mach Number in Converging–Diverging Nozzles, Aerospace Science and Technology 24 (2013) 111–115 Professional nozzle design and construction (a must). Apart from critical dimension parameters and angles one must determine what shape of nozzle (conical nozzle, bell, optimum contour nozzle, annular nozzle) is best suited for the respective rocket motor class towards best performance. Nozzle design in CAD, then transferred to Patran/Nastran for structural analysis, and ANSYS or Cart3d or OpenFOAM for CFD analysis; assistance can be found from professional software below. Nozzles to be made from metal and/or graphite will be pursued. Richard Nakka’s Experimental Rocketry - Machining of Rocket Nozzles. However, ignore reaming usage and concern oneself with the angular ability of more modern lathes like in the following two YouTube videos (exact title)--> How do you make a rocket nozzle? - YouTube Making a Graphite Rocket Nozzle - YouTube For identical scale rockets compare between metal nozzles and graphite nozzles for weight concerns, motor integration methods, rocket motor weight, nozzle performance heat limits; some propellants may warrant graphite as material for nozzle, while aluminium or other metal will suffice for other propellants. Note: design and construction of powerful rocket motors with stability and structural integrity are priorities. Again, professional software for parameters provided below. Again, the burning surface of a rocket propellant grain recedes in a direction perpendicular to this burning surface. The rate of regression, typically measured in inches per second (or mm per second), is termed burning rate (or burn rate). This rate can differ significantly for different propellants, or for one particular propellant, depending on various operating conditions as well as formulation. Knowing quantitatively the burning rate of a propellant, and how it changes under various conditions, is of fundamental importance in the successful design of a solid rocket motor. All manual prediction of rocket performance by thrust and pressure formulas to precede use of NASA CEA, GUIPEP + PROPEP, BurnSim, ROCETS from NASA software catalog and OpenRocket Simulator. Note: everything doesn’t require hedging unless significant risk is possible in the near future. Software beneath to aid in rocket motor parameters. Note: For rockets ignition will never be manually done understanding that an igniter is to be constructed to rocket motors. Motor casing designs (accounting for nozzle integration) based on software recommendation and designed in CAD, then onwards to Pastran/Natran with structural analysis. One of the principal priorities is to determine the optimal blast radius in the likelihood of malfunction, etc. Safety is a top priority. Critical interests --> -- https://www.nakka-rocketry.net/th_nozz.html -- https://www.nakka-rocketry.net/th_pres.html -- https://www.nakka-rocketry.net/th_2phf.html Predicting rocket performance by thrust and pressure formulas. Such concerns the following data: --Fuel type and mass quantity --Atmospheric pressure --Atmospheric temperature --Burnt rate coefficient --Pressure exponent --Fuel density --Length of grain --Grain burning area --Nozzle throat area --Nozzle exist area -Specific heat ratio and/or two-phase flow Determine maximum, and final steady-state chamber pressure for a (unrestricted) grain of particular propellant with specified dimensions; compare with NASA CEA, GUIPEP + PROPEP and BurnSim. The above parameters will be used among formulas for characteristic exhaust velocity (c-star), pressure, thrust coefficient, and thrust; there will be assumptions for gamma (isentropic exponent), ratio of universal gas constant to effective molecular weight, a non-calorically perfect gas, an isentropic nozzle, an expected chamber temperature, perfectly expanded nozzle, and the expected fuel regression rate. If not convinced with Nakkka’s Two-Phase Flow development concerning the isentropic exponent and ratio of specific heats, pay attention to pages 7 – 8 in the following source: NASA-Thermodynamic and Transport Combustion Properties of Hydrocarbons with Air, by Sanford Gordon Such along with the following journal article: Marić, Galović, & Šmuc. (2005). Calculation of Natural Gas Isentropic Exponent. Flow Measurement and Instrumentation, 16(1), 13-20 The products to be of gas and condense composites, hence, accounting for the two types of moles may be of consideration. One may also have to take into consideration two isentropic exponent formulas due to flow velocity at different areas. This possible subtlety to concern which of the isentropic exponents will be appropriately applied Low velocity flow -> chamber pressure and c-star High velocity flow -> exhaust velocity, thrust, thrust coefficient and other nozzle flow parameters. Compare manual computation findings to that of the given software. For those curious, they can analyse the following archived documents --> D. E. Coats et al A Computer Programme for the Prediction of Solid Propellant Rocket Motor Performance. Volume I-III: https://apps.dtic.mil/dtic/tr/fulltext/u2/a015140.pdf https://apps.dtic.mil/dtic/tr/fulltext/u2/a022880.pdf Coats, D.E., Levine, J., Nickerson, G., Tyson, T.J., Cohen, N., Harry, D., & Price, C. (1975). A Computer Program for the Prediction of Solid Propellant Rocket Motor Performance. Volume 3. Then, refresh with concepts such as the following: https://www.nakka-rocketry.net/th_thrst.html Then, onwards to construction of rocket test stations --> Pursuit of time continuous curves for pressure, thrust, vibration and temperature. There will be multiple trials. With testing of stationed rocket motors it would be great to actually acquire real data for thrust; force (thrust) readings continuously over time, to compare with the projected thrust curve from different software used concerning the chosen core cross-section design(s) experimented with for the propellant grain (done for all propellant-oxidizer configuration contestants). There will be also be a pressure-time curve. The following source to serve as conceptual guides towards building a (static) test stand for the purpose of testing actual rocket motors rather than simple grains made. Reason being, burn out of grain will not describe the actual character of rocket thrust. Rocket motors with actual nozzles will be tested. Cylindrical shaft for rocket motor placement should completely hold rocket motor where rocket motor should be level and steady where thrust vector to generally be directed parallel to cylindrical shaft holding. Gravitational influence leading to weight should be extracted. FOR STATIC TESTS AND LAUNCHES L CLASS ROCKET MOTORS WILL BE USED. Test station(s) development and construction to require a bit of ingenuity Structure of the static test station to be designed in CAD then transferred to Pastran/Natran and Ansys for structural analysis. Keep in mind one is pursuing altitudes and performance to validate the worth of this activity. The challenge will be development of a rocket test stand design for an L class rocket motor. Two of the most basic designs examples https://aeroconsystems.com/cart/images/custom/steele_2.jpg https://aeroconsystems.com/cart/images/custom/doud_2.jpg For the former, acquiring data that is “simultaneous” w.r.t. time is the challenge. For the latter, a load cell and load cell amplifier will be required, where rocket motor fits and is secured in the vertical casing (similar to an actual rocket). The 10 aspects for rocket motor test stands: 1. Thrust curve and pressure curve to be compared to predictions. Regardless of choice of static test station, thrust data curve and pressure curve will be compared alongside prediction thrust curve from different software detailed below; such will be done for all participating contestant fuel-oxidizer configurations as a means of observation of certainty or consistency. A robust amount of “real” thrust values with associated respective timing can possibly be oriented with ideal curves from software provided beneath; will be based heavily on design accuracy of constructed motor and propellant (constitution and ratio, characteristics, grain design). 2. The total impulse will be the integral of the thrust over the duration of the rocket motor when active. 3. The delivered specific impulse of the propellant is the total impulse divided by the propellant’s mass --> https://www.nakka-rocketry.net/impcalc.html 4. Both forms of impulse also will be compared to predictions from different software detail below; such will be done for all participating contestant fuel-oxidizer configurations as a sly means of observation of certainty or consistency. 5. With static test station vibration sensing w.r.t. time also to apply. 6. One goal is to have comparative view of vibration activity, thrust activity, pressure activity and temperature activity; each quantity to have its own axes, but axes for quantities synchronized in time scale and duration. 7. Will also incorporate from motor testing the burn rate determination by analysis using the pressure-time curve obtained from motor testing: https://www.nakka-rocketry.net/ptburn.html Note: students should know safety protocols for storage of propellant grains, delay grains, etc.; concerns environment and capable security measures. Burn rate modelling --> Overall models/methods applied will be compared to findings from (7) Determination of whether a respective burn rate found via modelling w.r.t to length of grain fits well to the duration of associated motor test. Will compare with burn rate determination from the pressure-time curve obtained from motor testing (7). Hence, there will be three means of burn rate determination to be compared. the burn rate coefficient and pressure exponent however will be acquired values from known professional sources. The following articles can be applied for data analysis with motor stand experimentation data: -Shekhar, K. Mathematical Formulation and Validation of Muraour’s Linear Burning Rate Law for Solid Rocket Propellants. Central European Journal of Energetic Materials, 2012, 9(4), 353-364 -NASA - Solid Rocket Motor Performance Analysis and Prediction. NASA-SP-8039 (focus pp 46 – 51): https://ntrs.nasa.gov/api/citations/19720011135/downloads/19720011135.pdf -Fry, R. S. Propellant Subscale Burning Rate Analysis Methods for U. S. and Selected NATO Facilities. Chemical Propulsion Information Agency, CPTR 75 JANUARY 2002. Chemical Propulsion Information Agency, CPTR 75 JANUARY 2002: https://pdfs.semanticscholar.org/99a2/3536d72c7095668ed41847e155a1490c24ce.pdf 8. There will be pursuit of measurements for particle exhaust velocities. The following sources can serve well towards incorporating such: -Balakumar, B. J. and Adrian, R. J., Particle-Image Velocimetry in the Exhaust of Small Solid Rocket Motors, American Physical Society, Division of Fluid Dynamics 55th Annual Meeting, abstract id. KN.006, 2002 -Balakumar, B. J. and Adrian, R. J., Particle-Image Velocimetry Measurement in the Exhaust of a Solid Rocket Motor, Experiments in Fluids 36 (2004) 166 – 175 -Pagliaroli, T. et al. (2015). Velocity Measurement of Particles Ejected from a Small-Size Solid Rocket Motor. Journal of Propulsion and Power. Volume 31. No 6.1-8.10.2514/1.B35490. For any possible use of a DAQ system in such mentioned sources, likely such can be substituted with programmable boards and sensors. 9. Infrared imaging for viewing of the thrust tail geometry continuously in time; detecting infrared energy and converting it into electronic signals, then to be processed to produce chronological thermal images, and associated continuous infrared temperature measurements data to be compared to data from conventional temperature sensors. Pursue a configuration where infrared imaging and infrared temperature measurements are made for a determined interval of seconds (could be each second or tenth of a second); data for arrangement, modelling and comparative analysis with software models and consensus professional data. Infrared imaging and infrared temperature data gathering should also be done on the rocket motor body to observe whether propellant and propellant grains are well behaved within. All types of recordings and data (by direct sensing methods and infrared techniques) should be stored, dated, labelled, etc. 10. Adiabatic flame temperature analytic determination compared to rocket motor test sensing data. REMINDER: Static motor tests will data will be compared with NASA CEA, GUIPEP + PROPEP and BurnSim, and analytical model predictions. Building of rockets --> It’ may be best that one set aside rocket motors that have not been used in test stations with the various propellant mixtures. Competent, professional-like design of rocket bodies must be established towards building that holds all critical components (rocket motors with propellants, sensing-visual with microcontroller and power source, parachute, etc., etc. mentioned earlier) in a sturdy manner not prone to damage by impact, inertia, heat or combustion activity; configured in a manner for weight distribution or centre of mass being desirable. Concerning containment or casing for sensing and power source such must be quite light but sturdy against inertial events and the possibility of hard impact; containment should not interfere with sensing abilities. Power source may supply a specific voltage, hence regulators and/or converters may or may not be necessary towards microcontrollers, sensing (and possibly) visual. Internal and external physical parameters of rocket body design must be professionally established. Body must be relatively light and impact damage resistant regardless of parachute. There will be multiple trials. Useful software will be provided below. A beginner goal is to CHALLENGE 1,151 (lbf x sec) of total impulse without reservation, hence the appropriate rocket motor class for launches will be the L-class rocket motor as a constituent to efficient structural design of rocket, with rocket being efficiently aerodynamic, along with well developed internal systems that’s well secured (virtually no inertial difference between internal systems and rocket body). Furthermore will like to pursue the theoretical limits of the L-class with launches as a means of certainty. Rockets for launch will have the ideal dimensions for L class rocket motor, however, will be glad to exceed 1,151 (lbf x sec) of total impulse. One must determine maximum dynamic pressure for rocket based on predicted performance for the L class rocket motor, type of propellant, rocket design; software may provide such. Airframes for rockets for solid propellant rockets: Mostly carbon fiber or fiberglass (required intermediate level material) Students should be able to determine the following trek parameters based on “kinematics” and compare to predicted results from software mentioned: Peak Altitude Burnout Altitude Maximum Velocity Time to Apogee Range What maximum percentage of escape velocity does one anticipate based on preliminary computations (manually and by software)? Will be compared to gathered rocket trek data. Students should also develop Launch Reports and Flight Summary that will be securely archived; includes photos, ground observer(s) videos, on-board video, flight data sensing (all types). Data acquired will also be expressed alongside theoretical predicted results (from software). NOTE: all of the given propellants should easily exceed Mach 1.41 at burnout. Software and codes that are extremely beneficial for rockets in activity --> (1) The ICT-Thermodynamic code H. Bathelt, and F. Volk. The ICT-Thermodynamic code (ICT-Code). Proceedings 27th Int. Annual Conference of ICT, June 25 – 28, 1996, P 92 F. Volk. and H. Bathelt. Application of the Virial Equation of States in calculating Interior Ballistic Quantities. Propellants Explos. 1, 7 – 14 (1976) Kelzenberg, S. et al. (2014). New version of the ICT-thermodynamic Code. Fraunhofer Publica Fraunhofer-Institut für Chemische Technologie -ICT-, Pfinztal: Energetic Materials. Particles, Processing, Applications: 45th International Annual Conference of ICT, June 24 - 27, 2014, Karlsruhe, Germany. Pfinztal: Fraunhofer ICT, 2014, pp. 95.1-95.9 (2) Thermochemical performance software: -- NASA CEA, GUIPEP + PROPEP, BurnSim; STANJAN, DWSIM (+ ChemSep) or COCO (+ ChemSep) may prove quite useful alongside the prior mentioned software above for hybrid propellants. (3) Components and flight performance: --OpenRocket Simulator --RASAero --ROCETS from NASA software catalog In this case both software will likely complement each other. (4) Aerodynamic Analysis software: --Cart3d (from NASA software catalog) --RASAero --OpenFoam --ANSYS (5) Structural Analysis software: Patran/Nastran or ANSYS Note: throughout most or all phases of this activity motor sensing tools are based on economic ingenuity. View all mentioned operations as analogous to learning programming or coding with generic tools available. The absolute advantage with being economic is that ingenuity and independence are spawned and nurtured. All types of recordings and data should be storable in initial state, dated, labelled, etc. NOTE: solid propellant rockets generally serve as first stage or boosters in launches. Hence, activities with at least hybrid rocket propellants are crucial (in another activity mentioned further beneath); will restrict to hybrid rocket propellants since they are very safe, economic and accessible to civilians, inlike liquid propellants being highly expensive concerning oxidizers, fuel, turbopumps and regulatory/legal problems. NOTE: static motor tests and rocket launches will be far from any marine/aquatic environments and high vegetation environments. I. Developing rocket payload separation mechanisms This activity will be more advanced than any separation mechanisms applied in activity (R), but isn’t necessarily dependent on activity (R). For rocket separation mechanisms will pursue detailed geometric viewing of the components and integration into a unit. CATIA, ANSYS, Patran/Nastran will be made available. Such will be followed by proposing methods to construct the technical components, including (but not limited to) CNC milling, CNC drilling, CNC turing, lathes, etc. This will also be focus towards actuation mechanisms involved (actuators, pyro, etc.). For considered scale to be engineered there must be determination for the range of operations (various essential parameters) and practical payloads. It’s essential to have analysis and comprehension of applied system control and circuitry involved. The ability to develop such mechanisms (multiple prototypes) will be a huge accomplishment. There must be ability to test such mechanisms as well. NASA Flight Separation Mechanisms- Space Vehicle Design Criteria --> [ https://ntrs.nasa.gov/citations/19710019510 ] Types of separation mechanisms: --Ball Lock Separation Mechanism --Clamp-Band Joint Considering Pyroshock of Satellite Separation --Clamp Bands Separation Systems --Resources --> Planetary systems Corporation Acquire the documentation for each product from the following site: https://www.planetarysystemscorp.com/products/ 1. User Manuals 2. Operating Procedure 3. Requesting the CAD models 4. Paper & Presentations [ https://www.planetarysystemscorp.com/papers-and-presentations/ ] The alternative: EUROCKOT Chapter 4 Spacecraft Interfaces [ http://www.eurockot.com/wp-content/uploads/2012/10/Ch4UsersGuidess5Rev0.pdf ] NOTE: we can’t be involved in market share with such established companies. This activity is for educational purposes towards demonstration of ability in astronautics mechanical engineering. A complimentary article of possible interest: Li, J., Yan, S. and Tan, X. (2014). Dynamic-Envelope Analysis of Clamp-Band Joint Considering Pyroshock of Satellite Separation, Journal of Spacecraft and Rockets, Volume 51, Number 5 NOTE: modern washing machine locking systems may be up to par with the necessary requirements. May be a good reference for hands-on investigation and analysis of mechanisms with actuation control; actual analysis of components and circuitry for the electrical triggering. Crucially, whether such a system will applicable to environmental conditions considered. Will require gods skills in CAD development (and/or laser imaging) towards mechanical structure integration ingenuity J. Field trips observation Maintenance, assembly/disassembly of prop engines, commercial jet engines and helicopter engines (with drive train and powertrain). Likely two repetitive trips for each type of engine; prop engines, jet engines and helicopter counterpart respectively. Honestly, in modern times this will prove somewhat difficult. K. Quadcopter Development Open to Computer Science and Mechanical Engineering constituents. Phase 1 -->> Moderate development stages: -Frame design with structural analysis to house power source, propulsion integratin, communications sensing-control, camera, wiring. Weight of frame material from choice of material to be used. -Quadcopter system modelling -Choice of motors with performance specifications -Choice of propellers -Power source specifications required -Determination of lift or thrust for a single motor with propeller, and implications on parameters from prior stages concerning the four motor-propeller configuration. -Determining components for communications sensing-control based on prior system modelling, control, simulation and other stages. -Data storage where all sensing quantities collected are time-synchronised. -Determination of power source required, and voltage requirements for particular constituents of the communications sensing-control scheme. Test to see if all such equipment work. -Weight of frame with power source, integrated propulsion system, communications-sensing, processing, memory, camera, wiring. Mass distribution or CoG or CoM should be sensible for flight stability and manoeuvres. -Expected resulting minimal lift thrust. -Determination of power source’s life span for ideal flight (sensing, processing, motors, camera, etc. Detrmine distance of no return based n powerconsumption of qudcopter. Determine altitude limitations. Determining maximum speed (likely subject to atmospheric conditions). Determine level flight performance and level flight envelop. Note: likely back-up components will be required. Phase 2 -->> Proceed with analysis of the following and scale to parameters established in phase 1. Some assisting guides example: Naidoo, Y., Stopforth, R., and Bright, G., Quad-Rotor Unmanned Aerial Vehicle Helicopter Modelling & Control, Int J Adv Robotic Sy, 2011, Vol. 8, No. 4, 139-149 Note: spoon feeding development stunts authenticity, foundation and ingenuity, which is why phase 1 and this phase is required. Students tenured in activity should not be allowed to ruin the development endeavour of new students to activity by premature exposure. Further assists: Lozano, R. (2010). Unmanned Aerial Vehicles: Embedded Control. Somerset: John Wiley & Sons, Incorporated. He, Z., & Zhao, L. (2014). A Simple Attitude Control of Quadrotor Helicopter based on Ziegler-Nichols Rules for Runing PD Parameters. The Scientific World Journal, 2014, 280180. Xuan-Mung, N. and Hong, S. Improved Attitude Control Algorithm for Quadcopter Unmanned Aerial Vehicles. Applied Sciences. 2019, 9, 2122 One must then should also consider the programming that accompanies all control. Carrillo, L. at al (2013). Quad Rotorcraft Control : Vision-Based Hovering and Navigation. London: Springer. Phase 3 --> There are threemain types of stability of great concern: -Hovering (with comprehensive modelling) -Forward and backward motion (with comprehensive modelling) -Sliding mode. -“Directional derivative” motion (combination of latter two) NOTE: control doesn’t have much value if one doesn’t have the programming to apply with embedded systems and microcontrollers and so forth. Hence, will employ a simulator that can build the C code (SystemModeler or Modelica or Simulink). The simulink perspective logistics can be observed from the following: MATLAB – Brian Douglas: Drone simulation and Control (Part 1 – Part 5) – YouTube https://www.youtube.com/watch?v=hGcGPUqB67Q&list=PLPNM6NzYyzYqMYNc5e4_xip-yEu1jiVrr . Phase 4 -->> How does one test code for flight simulatin where qualitative data is spatial motion? Phase 5 --> Flight plan testing craft at different speeds in conjunction with demonstrating pitch, roll and yaw motions....followed by necessary manoeuvres; response and stability should be observed. On board there will be gyroscopic sensing (pitch, yaw, roll), pressure sensing, altitude sensing and speed sensing; all such data must be time synchronized when directly collected and stored during flight for later flight evaluation analysis; may also be possible for analysis of flight commands concerning controllers, responses, voltage, etc., etc. Phase 6 -->> Consider bicopter models such as the MV-22 Osprey paying particular attention to axial actuation. Consider designing a bicopter where pitch, roll and yaw motions are the result of motors with coordinated rotation speeds, and use of servos on arm extensions that are light and strong holding the motors. Some modelling and control assistance guides: Jianmin Su, Chengyue Su, Sheng Xu, and Xiaoxing Yang, “A Multibody Model of Tilt-Rotor Aircraft Based on Kane’s Method,” International Journal of Aerospace Engineering, vol. 2019, Article ID 9396352, 10 pages, 2019. Haixu, L., Xiangju,Q. and Weijun, W. Multi-body Motion Modeling and Simulation for Tilt Rotor Aircraft. Chinese Journal of Aeronautics 23(2010) 415-422 Miller, M. and J. Narkiewicz, 2006. Tiltrotor modelling for simulation in various Flight conditions. J. Theor. Applied Mech., 44: 881-906. Qi, Wang & Wenhai, Wu. (2014). Modelling and Analysis of Tiltrotor Aircraft for Flight Control Design. Information Technology Journal. 13. 885-894. Phase 6 --> Analogy to phases 1 through 5. Note: for larger scale bi-copters the motors, servos, power source, frame materials and other crucial components may or may not be drastically different. Actuation design likely to require more sophisticated components with weight and strength in mind. Pursue such competently. L. Propeller Propulsion # Part 1 -Forces acting on a propeller: Thrust bending Centrifugal Centrifugal and aerodynamic twisting Torque bending Vibratory Pursue Newton’s second law versus Euler modelling versus Navier-Stokes approach; may not be pretty results. # Part 2 -Conventional aerofoils and geometric designs applied to aircraft propellers for high performance Will compare different propeller designs and performance with respect to material, weight and design -- Blade Element Theory Momentum Theory Blade Element Momentum Theory (BEMT) Some assistance: Rwigema, M. K., Propeller Blade Element Momentum Theory with Vortex Wake Deflection, 27th International Congress of the Aeronautical Sciences, 2010. Determining highly regarded models for propeller thrust that’s highly dependent on propeller specifications and atmospheric conditions. - CFD Analysis: Then, compare/contrast out of ANYS (CFX and Fluent), SolidWorks, Cart3d, OpenProp or OpenFOAM for propeller aerodynamic behaviour, thrust behaviour and streamline magnitudes. How well do findings compare with the prior 3 theories? Between BEMT and CFD which provides the most meaningful data? How well do BEMT and CFD compliment each other? # Part 3 Economy from Computation: Sforza, P. M. (2017). Chapter 10. Propellers. Pages 487-524. In: Theory of Aerospace Propulsion. Butterworth - Heinemann Which type of propeller can be dubbed stratospheric worthy? Liu, X. and He, W., Performance Calculation and Design of Stratospheric Propeller, IEEE Access, Volume 5, June 26, 2017 # Part 4 Electrical Aircraft Propulsion System Doupe, A. J. Electrical Aircraft Propulsion System. DOE CREATT Program, June 8, 2012 California Polytechnic State University, Aerospace Engineering Department San Luis Obispo, CA https://digitalcommons.calpoly.edu/cgi/viewcontent.cgi?article=1079&context=aerosp There may be components not economically feasible, hence, one must pursue economic substitutions if such be the case. System will also incorporate a motor control unit. Thrust data w.r.t. to rpm plotting will be also be included. A speed controller towards voltage variation is also pursued, Thrust data w.r.t. to voltage is also pursued. Make use of propellers that are feasible for such a test station. Note: air density and pressure above sea level may be assumed. # Part 5 Then, consider motors of the following scale in possession (hypothetically), where the major issue is insulation from humidity, precipitation, lightning, E-M interference. Giant Brushless homemade Motors of Unreal Power – YouTube < https://www.youtube.com/watch?v=ioWJClmSPgQ > Pursuit will be design of light but sturdy (weather) insulation enclosure with shaft, bearings, etc. (if needed). Weight distribution in function should not be considerable hindrance/impedance on performance; comparable or equivalent to what was observed in video. NOTE: try to acquire the exhibited data in the video. To model and simulate the characteristics, properties and behaviour we will develop with the following software Design and physics/engineering characteristics (scale and performance) Advanced Electromagnetics Group – SPEED ANSYS (Maxwell, Motor-CAD) Control and simulation SystemModeler Hopefully models, scale, properties and characteristics are transferrable to a mechanical CAD where mechanical integration design can be done. FEA as well if warranted (accounting for materials’ properties) Develop analogy to PAD. Yet, one must have a good idea of the performance of a single motor to determine the minimal amount for 190 lbs passenger with aircraft # Part 6 --Piston engine prop (PEP) Analogy to part 4 Concerning PEP it’s just a matter of designing and implementing an optimal transmission or drivetrain towards the prop from the piston engine. One must know the specs of the type of piston engine considered and that power dissipates when applied to the shaft concerning mass element along the length of shaft and prop/fixture weight. Expected, all weight will have considerable influence on acceleration from thrust Also, ECUs will be relevant. --Propulsion and aircraft design (PAD) Concerns a developed light single passenger aircraft, powerred by two. 5.5 hp lawnmower motors with structural design, weight profiling (aircraft components & distribution) and aerodynamic features to take full advantage of the powertrain applied. What propeller design will serve optimal? Maximum weight support may be a 190 lb passenger (with weight from necessities accounted for). Consider the necessary power source needed to have flight at least above all heights of vegetation and conventional residencies. How is all such feasible? Determine: �� Minimum distance & speed/acceleration needed to have lift; Resulting rate of climb based on prior Greatest altitude achievable Maximum cruising speed Time of longest possible flight Will also extend to three and four engines. M. Weather balloon Meteorological Measurements, Observation and Recovery This activity generally resides under Meteorological and Oceanographic administration. AE students are invited to participate. Check such section for more details. AE students will have the additional tasks of: (1) air compression efficiency variation w.r.t. increasing altitude (2) Determination jet engine turbine(s) efficiency variation w.r.t. increasing altitude (3) Efficiency for various types of rocket nozzles as rockets traverse into higher altitudes. N. Aeroelastic Analysis of Aircraft Wings and Flutter Note: This activity highly depends on sound knowledge and skills acquired from activity (A). PART 1 (i) Will begin with an overview of aeroelastic behaviour for wings +flaps with the cross sectional aerooils. To highlight the roles of aerodynamic force, inertial force and elastic force, with the resulting heave, pitch and oscillating behaviours. Will highlight historical or potential hazards from stall and flutter behaviours. (ii) Develop the free-body diagram Will pursue accurate interpretation of each parameter, and the (linear, angular) displacements, and torques associated to them. Leading to the nonlinear aeroelastic behaviour model (iii) Developing particular wind tunnel rig experiments With wind tunnel active one pursues “small” amplitude stall flutter oscillations. Will pursue setting the conditions (special conditions or ranges) to induce to flutter activity. This may be an experiment for purely visual purposes: www.ltas-aea.ulg.ac.be/cms/uploads/stallflutter.html Other necessary type of flutter test rig: www.dlr.de/ae/en/DesktopDefault.aspx/tabid-9731/16698_read-40639/gallery-1/gallery_read-Image.21.24429/ An oscilloscope can also be incorporated to observe the motion of the wing in terms of waves in the above setup. Another setup as well: www.ltas-aea.ulg.ac.be/cms/uploads/stallCFDTFE.html A more complicated setup yielding multiple types of data: De Marqui Junior, C. et al (2007), Design of an Experimental Flutter Mount System, Journal of the Brazilian Society of Mechanical Sciences and Engineering, Vol. 29 No. 3 Note: for robustness one should consider two or three different types of aerofoils for the varius types of flutter rig experimentation. (iv) Numerically simulate the dynamic stall and stall flutter of a 2D NACA0012 wing (and others). Simulations to be carried out by solving the URANS (Unsteady Reynolds Averaged Navier Stokes) equations in parallel with the structural equations of motion. The aerodynamic calculations can be performed using OpenFOAM or Mathematica or other. Simulation results to be compared to experimental data from a rectangular wing (or other) with end-plates undergoing stall flutter oscillations. Note: for the equations of motion, there are different formulas, namely some scholars somehow incorporate dimensionless parameters. However, this isn’t a mathematical “ride off a cliff” activity. Pursue means that best works to accomplish objective(s) with the necessary robustness wherever or whenever desired. (v) The following two journal article assists provide details towards aeroelastic prediction for aircraft applications. However, develop credible and sturdy interpretations for the settings and modelling. If computational logistics and setups can’t be transparent and developed towards simulations and outputs, then all is futile: --Henshaw, M. J. de C. et al, Non-Linear Aeroelastic Prediction for Aircraft Applications, Progress in Aerospace Sciences 43 (2007) 65–137 --Kim, T., Flutter Prediction Methodology Dased on Dynamic Eigen Decomposition and Frequency-Domain Stability, Journal of Fluids and Structures 86 (2019) 354–367 Note: for such two articles the objective is neither suppression with matrix algebra nor matrix theory. One has real pursuits in life, so apply computational tools for support; no one decent and civilised prays for dystopia. One example of extravagant field experimentation for flutter prediction: Pak, Chan-Gi, Unsteady Aerodynamic Model Tuning for Precise Flutter Prediction. NASA Dryden Flight Research Center Edwards, CA, United States https://ntrs.nasa.gov/citations/20110014455 https://ntrs.nasa.gov/api/citations/20110014455/downloads/20110014455.pdf Overall articles of Kim and Henshaw should find common ground with this NASA field experimentation. (vi) Consider the following journal article. Analyse and pursue development of experimentation to confirm or disprove: Peretz, O. and Gat, A. D., Forced Vibrations as a Mechanism to Suppress Flutter— An Aeroelastic Kapitza’s Pendulum, Journal of Fluids and Structures 85 (2019) 138–148 Regardless of outcome, is such mechanism applied to aircraft in operations today, or possibly in testing stage? Identify tools or mechanisms used on aircrafts today to resolve stall flutter phenomena. (vii) Some transonic analysis (time permitting): --Bendiksen, O. O., Nonlinear Mode Interactions and Period-Tripling Flutter in Transonic Flow, Journal of Fluids and Structures 19 (2004) 591–606 Note: stall flutter treatment also applies to vertical stabilizers with rudders, and horizontal stabilizers with elevators. PART 2 (i). Continuous flutter and divergent flutter (amplitude increase). Model characterisation for flutter w.r.t. to aircraft size/design, aircraft material and speed will be crucial. Speed limitation threshold based on Airspeed ratio of energies (at such and beyond) Airplaine design dive speed (Vd) and never exceed speed (Vne). Determining flutter speed and the instances of flutter NACA Technical Paper 4197. Does one require use of a more accurate term for torsional modulus? We will analyse the material property included in such equation, concerning Shear Modulus, being the representation of the amount of deformation associated with a particular amount of force. Basically, the higher the shear modulus the more force it can handle. Can one assume that materials are isotropic? If not, what must be treated? For the following parameters in the flutter boundary equation one must identify their equations Thickness of the wing Root chord (c) Aspect Ratio (AR) Taper Ratio (l) Air pressure (temperature and pressure variations) Speed of sound Flutter velocity changes with altitude; therefore, to accurately predict flutter speed the altitude at which maximum velocity is achieved must be known. (ii). The influence of counterbalance weights to suppress flutter. Investigation of the use of counterbalance weights to the movable surfaces to damp such oscillations (ailerons, elevator, and rudder surfaces structure components to suppress flutter). Presence and “retracting” of counterbalance weights. Can counterbalance weights completely treat flutter regardless of whatever operational speeds and manoeuvres? Some assists that may be useful to interests of concern: --Njuguna, J., Flutter Prediction, Suppression and Control in Aircraft Composite Wings as a Design Prerequisite: A survey --Zhang, F. and Soffker, D., Active Flutter Suppression of a Nonlinear Aeroelastic System Using PI-Observer, Motion & Vibration Control, Springer 2009, pages 367 - 376 --Ghiringhelli, G. L. et al, Active Flutter Suppression Techniques in Aircraft Wings, Control and Dynamical Systems, Volume 52, 1992, pages 57 – 115 --De Marqui, C., Belo, E. M., & Marques, F. D. (2005). A flutter suppression active controller. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 219(1), 19–33. --Theis, J., Pfifre, H. and Seiler, P., Robust Control Design for Active Flutter Suppression, AIAA 2016 --Ibrahim, I. A. and Castravete, S. C., Flutter Suppression of a Plate-like Wing via Parametric Excitation, Nonlinear Dyn (2006) 46: 387 – 426 --Lanjun Li, Shouyi Yu, N. Kawai and H. Matsushita, "Active Flutter Suppression Control Using Piezo-Ceramic Actuators," 2006 6th World Congress on Intelligent Control and Automation, Dalian, 2006, pp. 6323-6326. --Tsushima, N. and Su, W., Flutter Suppression for Highly Flexible Wings using Passive and Active Piezoelectric Effects, Aerospace Science and Technology 65 (2017) 78–89 O. TBA P. Control Stabilization of Rockets Open to Mechanical Engineering & Computer Science constituents To proceed with activity, activity (H) must be at least competently carried out. NOTE: NH4ClO4 will be the only type of oxidizer applied for solid propellant rockets. Concerns ordering in advance from sources that provide quality product. Activity will apply NH4ClO4 in developed propellants when ready for burn rate tests, test stations and rocket launches. NH4ClO4 will not be accessible outside of “summer” & “winter” terms unless authorized senior project is recognised. Like NH4ClO4, same for nano Al whether serving as as additive or fuel. Rockets spin about their longitudinal axis due to an imperfect realization. Despite gyroscopic behaviour commonly desired as a means to increase the unlikeness of the rocket trajectory being perturbed, why is roll stabilization sometimes preferred? Designing, developing and testing an automatic control system to eliminate roll angle variation in rockets. Will then simulate system. The system of consideration applied uses 2-4 control canard fins mainly for aerodynamic control, moved by a flight computer equipped with a 3DOF gyroscope, an accelerometer, atmospheric pressure sensor, etc. etc. Likely to incorporate the C programming language for instruction(s). Includes microcontroller(s), gyroscope sensor(s), 4 servos, shaft connectors, shafts. Code will employ at least two Kalman filters towards computation of optimal estimation of the state-space from sensor data. Note: roll stability control must not block visual. Various sensors for velocity, acceleration, apogee, etc. with synchronised chronological data storage. Data from gyroscope sensing (also time synchronized with the other sensor data types) will be analysed to judge the efficiency of the developed roll stabilization control. GPS, cellular network, etc. Towards designing the controller and predicting the dynamic behaviour of the rocket in whole, application of Mathematica/SystemModeler or Modelica for a 6 degree of freedom mathematical model and towards simulation, etc. All aerodynamic parameters can be estimated from past real test flight data or by some other means such as software provided, DATCOM, etc, etc. Prototype system build and tests before real integration into rocket Some assists: -Chen, Yong-chao & Gao, Xin-bao & Gao, Min & Lv, Hui-miao. (2016). Aerodynamic Characteristic of a Canard Guided Rocket. International Journal of Modeling, Simulation, and Scientific Computing. 08. -Barret, C. Design of Flight Control Augmentors and Resulting Flight Stability and Control Analysis. AIAA 35th Aerospace Sciences Meeting and Exhibit, 06 January 1997 – 09 January 1997 -Xie, K., Liu, Y. & Xin, J. Controlled Canard Configuration Study for a Solid Rocket Motor Based Unmanned Air Vehicle. J Mech Sci Technol (2009) 23: pp 3271 - 3280. -Kan Xie and Yu Liu, "An Experimental Study of Controlled Canard for a Solid Rocket Motor Based Unmanned Air Vehicle," 2010 3rd International Symposium on Systems and Control in Aeronautics and Astronautics, Harbin, 2010, pp. 732-737. -Chen, Yong-chao & Gao, Xin-bao & Gao, Min. (2017). Numerical Simulation on Rolling Characteristics of Canard-controlled Rockets with a Free-Spinning Tail. International Journal of Modeling, Simulation, and Scientific Computing. Volume 8. No. 2, 1750061 It’s imperative that students encounter conceptual development before programming development, testing and integration. Again, to proceed with activity, activity (H) must be at least competently carried out. There will be rocket launches with automated canards controlled by developed “embedded system”. NOTE: static motor tests and rocket launches will be far from any marine/aquatic environments and high vegetation environments. Q. Vortex ring state for rotorcraft i. Vuichard Recovery Technique - How to escape a Vortex Ring State – YouTube ii. General immersion guides: --Toropov, M. Y. and Stepanov, S. Y., Modelling of Helicopter Flight Imitation in the Vortex Ring State, Russ. Aeronaut.(2016) 59: 517 - 522 --NASA - Model for Vortex Ring State Influence on Rotorcraft Flight Dynamics https://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/20060024029.pdf --Basset, P. et al, Prediction of the Vortex Ring State Boundary of a Helicopter in Descending Flight by Simulation, Journal of the American Helicopter Society, Volume 53, Number 2, 1 April 2008, pp. 139-151 (13) --Vortex Ring State Protection Flight Control Law, by B. Dang-Vu https://hal-onera.archives-ouvertes.fr/hal-01061133/document iii. Experimentation guide: Westbrook-Netherton, O. and Toomer, C. (2014) An investigation into predicting vortex ring state in rotary aircraft. In: RAeS Advanced Aero Concepts, Design and Operations, University of Bristol, Bristol, UK, 22-24 July 2014. London: Royal Aeronautical Society Available from: http://eprints.uwe.ac.uk/26800 R. 3 stage combustible rocket Activity (H) must be competently completed into order to proceed with this activity. This activity doesn’t overall depend on activity (I). PHASE 1 Elementary staging (to begin with 2-stage rockets then to 3-stage): < https://www.apogeerockets.com/education/downloads/Newsletter99.pdf > PHASE 2 (MANDATORY) NOTE: NH4ClO4 will be the only type of oxidizer applied for solid propellant rockets. Concerns ordering in advance from sources that provide quality product. Activity will apply NH4ClO4 in developed propellants when ready for burn rate tests, test stations and rocket launches. NH4ClO4 will not be accessible outside of “summer” & “winter” terms unless authorized senior project is recognised. Like NH4ClO4, same for nano Al whether serving as as additive or fuel. Mandatory advancing to HDRMs or SNRMs. Hold Down and Release Mechanisms (HDRM) or Separation Nut Release Mechanisms (SNRM). Will be an extension of (iii) and (iv) from activity (H) for solid propellant rockets. One of the principal priorities is to determine the optimal blast radius in the likelihood of malfunction, etc. All sensing, visual, data storage from (iii) in activity (H) will be integrated. Such area in rocket engineering is one of the most intricate and publicly elusive subjects. The ability to implement and competently operate with multistage rockets are characteristics of any premier or developed educational and engineering environment or foundation. Concerned with electronic staging timer or pre-programmed flight computer sending some charge after an acceleration event. Trial staging rockets concern the provided propellants from (iii) in activity (H). A comprehensive or thorough description for the most efficient mechanisms to integrate into vessel can be found in the document “Flight Separation Mechanisms” from NASA (https://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/19710019510.pdf ); stressing awareness and understanding of the guidelines and models for separation mechanisms that’s sufficient to simulate accurately all significant motions of the separating bodies. One must clearly understand or determine the operational range (high and low) and extremes (high and low) of integrated mechanisms for the vessel in question. Software mentioned beneath can provide great insight. If there is any physical testing to be done, such testing must be the most relevant and practical to vessel of concern and mission environments of the vessel. Control configuration for rocket sections with mechanisms must be determined, and separation mechanisms are assumed to be reusable in the future; tracking software provided below. GPS would be nice as well for each stage. Based on such sensing one can compare data with simulation models to provide an idea of what parameters, coefficients, etc. have great influence. To be fitted with three cameras to observe rocket body segregations. Chassis launch stations are obvious. To properly house intricate actuators with other technical devices involved in HDRMs or SNRMs good space within air frames is required. Hence, at least N class rocket motors are preferable for multistage activity concerning incorporation of the technical internal mechanisms. Such N rocket motor class preference concerns accommodating well all mechanisms. The cross-sectional radii of all airframe stages may be much greater than all nozzle divergence radii. CAD design for multi-stage separation will be a technical feet. HDRM process logistics-- For any possibility of multistage rockets with HDRMs the crossection radius of rocket body must be considerably big to orient at least two HDRMs devices away from the position of the nozzle. Consider two to four HDRMs in cardinal positions to each other where neither is close to the centre where nozzle will be oriented. Stage connects will have bulk plates designed in a manner where the majority of matter distribution resides mostly around where the placement holes/rods are to be for the HDRM connects. There should be placement design for nozzle confinement, and for parachute ejection of lower stage. Bulk plates to be made of light metal but sturdy enough to withstand the punishment of structural rocketry mechanics. Use of two to four HDRMs may be required, all having equal distance between nozzle and each. TiNi Micro Latch is an example of HDRMs (but desired model of interest may concern more height with connection). It’s very likely that nozzles in upper stages will not extrude for convenience. Air fittings-Quick Separation Couplings (AFQSC) as possible alternative to TiNi Micro Latch --> One isn’t concerned with applied fluid pressure, rather taking advantage of the mechanism for holding and separation. Likely for AFQSC industrial grade will be choice that provides superb locking. Rather than fluid lines one must develop strong but light (machined) tube rods attached through the bulk plates to secure the fittings and couplers, respectively, concerning lower stage and upper stage. The tips of the top of the tube rods to be machined to provide a screw-in orientation for couplers and fittings. The tube rods holding the couplers and fittings should provide long enough extension to connect in a manner where upper stage and lower stage align without leaving space between. Concerning the “air” fittings-couplers connection one must determine the limit of maximum force these connections can take regardless of such concern seemingly superfluous due to lower thrust and the resulting inertia upon higher rocket stages. The fittings and couplers to be industrial grade with good rating(s) for performance assurance. There may be at least three to four sets in unison function required to develop an HDRM mechanism with such. One has to develop the means of actuation upon couplers to separate from fittings. The actuation to be applied must have excellent “grip” on couplings to actuate. A primitive example idea would be using linear actuators or linear servos that employ “grippers” which attach orthogonally to the translation rods of the linear actuators/linear servos. The orthorgonal end end of the “grippers” will be what firmly grips the pull-down on the couplers. The following gives an imaginative idea on what is meant by “grippers, however, to have an entrance that fits the rods of the linear actuator efficiently without tendency to separate, become crooked or crack under stress/strain. As well, “gripping part” must efficiently fit the coupler (rather what is observed); without separation, getting crooked or cracking. Namely, a metallic “KS coupler”. Most of the length of the vertical translation rods must reside within upper stage body. Position control and speed control are crucial with the linear actuators/linear servos; must be controlled by micrcontrollers rather than manual turning switches. All linear actuators/linear servos must function simultaneously. It’s very important that such contraptions within the airframes are oriented in a manner that perfectly distributes the weight w.r.t. the axis of symmetry of the airframes. There must be extensive trials for synchronized releases. Determining separation timing for each set possibly by use of lasers if feasible. Features of sensing & control for a non-payload stage algorithm --> 1. Each stage to have active acceleration sensing. Developed theoretical acceleration model for rocket concerning a respective stage with HDRM assembly. Acceleration sensor gets readings (beyond “assembly site speeds”) when “armed”. Based on predicted performance of rocket stage there should be a acceleration-time profile. Acceleration sensing with processing to determine when rocket motor has outdone its use in relation to theoretical acceleration-time model. A 3-second advance buffer would be nice. Note: acceleration is superior to velocity; velocity is superior to position due to natural environmental forces altering the direction of rocket, resulting in rocket not having a continuously orthogonal flight path w.r.t. ground. As well altitude isn’t equivalent to distance from launch site because natural environmental forces alter direction of rocket, resulting in rocket not continuously traversing orthogonally w.r.t. ground reference point. Overall, each rocket performance isn’t exact as the other for various “subtle” reasons. All such may or may not directly be parallel with the notion of differentiability being stronger than continuity in calculus; well acceleration is easily connected to Newton’s 2nd law. 2. Concerning detach-and-separation, for actuation in upper stage, possibly sensors can detect full contractions. With the law of inertia applying to all stages not much force is required to generate a good perturbation separation. Decoupling action uses force, being contrary to operating inertia, but will that be enough? Does “conservation” of linear momentum for a portioning body solve that problem? Additionally, lack of compression upon upper stage due to burn out from lower stage, drag will become quite influential on lower stage leading to additional natural separation. If drag is crucial for separation, then in this case velocity will be more influential than acceleration, playing the crucial role in separation, namely, max-drag available should correspond to Vmax. Reaching the highest acceleration doesn’t mean rocket has reached Vmax. So, a condition on velocity is needed where the upward force from coupler detachment (however minute) with drag as counter direction needs to be enough to overcome remaining weight of lower stage. Thus, velocity sensing isn’t only for data collection. Then, upper stage will then have ignition. 3. Lower stage may or may not have a LED/IR proximity sensor control system that’s continuously active. Such will be used to determine adequate distance from upper stage to release parachute, regardless of lower stage reaching apogee or not. To test HDRM one needs a “ acceleration sensing and computing simulation interface” for HDRM. Will run multiple velocity-acceleration simulation models profiles with designed HDRM. The real sensors with computing systems to be integrated in to 3-stage rockets for lunch should be at least on par with consistently successful artificial tests. One must design a HDRM test station for such. Such 3-phase process for multistage also serves towards evaluation of rocket motors, quality of propellant and propellant grain; recover each rocket stage and examine the rocket motors and contents. Note: first time students are encouraged to develop their own programming creativity and amendments before exposure to anything developed in the past. Each stage will have an installed camera, velocity sensing, acceleration sensing, altimeter sensing, gyroscope sensing and vibration sensing. GPS would be nice as well for each stage. Only the payload stage will have additionally apogee sensing for parachute ejection. In payload station apogee sensing and control towards parachute deployment naturally computes apogee regardless of what the other stages do. The challenge will be activating all sensing & control, and visuals for all stages. The following journal articles serve towards development of theoretical system modelling of multistage rocket motion concerning rotations among the pitch, roll and yaw axes for creating an ideal model, despite such adjectives with axes not directly mentioned in the articles; identify angles that coincide with such throughout. Data from gyroscope sensing to be compared to ideal model to determine whether rocket has competent performance overall when compared: Pontani, M., and Teofilatto, P., Simple Method for Performance Evaluation of Multistage Rockets, Acta Astronautica 94 (2014) 434–445 Chelaru, T., and Barbu, C., Mathematical Model for Sounding Rockets, Using Attitude and Rotation Angles, International Journal of Applied Mathematics and Informatics, Issue 2, Volume 3, 2009 Jeyakumar, D., Biswas, K. K., and Rao, B. N. (2005). Stage Separation Dynamic Analysis of Upper Stage of a Multistage Launch Vehicle using Retro Rockets, Mathematical and Computer Modelling 41, 849 - 866 Note: will not be bogged down by matrix algebra for any of the given journal articles; computational tools will be applied towards proper use of time. Additionally, compare gyroscope sensing versus theoretical ideal model with trajectory software mentioned below. System-level testing for the 3-phase algorithm with hardware can be applied based on modelling from such three journals. One can develop simulations that provide different scenarios for the HDRM programming to take in and carry out its role. Note: students should know safety protocols for storage of propellants, motor rocket system, etc.; concerns environment and capable security measures. All types of recordings and data should be storable in initial state, dated, labelled, etc. Software & code extremely beneficial to multistage rockets --> (1) The ICT-Thermodynamic code H. Bathelt, and F. Volk. The ICT-Thermodynamic code (ICT-Code). Proceedings 27th Int. Annual Conference of ICT, June 25 – 28, 1996, P 92 F. Volk. and H. Bathelt. Application of the Virial Equation of States in calculating Interior Ballistic Quantities. Propellants Explos. 1, 7 – 14 (1976) Kelzenberg, S. et al. (2014). New version of the ICT-thermodynamic Code. Fraunhofer Publica Fraunhofer-Institut für Chemische Technologie -ICT-, Pfinztal: Energetic Materials. Particles, Processing, Applications: 45th International Annual Conference of ICT, June 24 - 27, 2014, Karlsruhe, Germany. Pfinztal: Fraunhofer ICT, 2014, pp. 95.1-95.9 (2) Thermochemical performance software: --CEA from NASA software catalog, GUIPEP + PROPEP, BurnSim; STANJAN, DWSIM (+ ChemSep) or COCO (+ ChemSep) may prove quite useful alongside the prior mentioned software above for hybrid propellants. (3) Components and flight performance: --OpenRocket Simulator --RASAero --ROCETS from NASA software catalog In this case both software will likely complement each other. (4) Aerodynamic Analysis software: --RASAero --Cart3d (from NASA software catalog) --OpenFoam --ANSYS (5) Structural Analysis software: Patran/Nastran or ANSYS NOTE: static motor tests and rocket launches will be far from any marine/aquatic environments and high vegeytation environments. NOTE: a scheme involving modern washing machine locking systems may be possible with the necessary requirements. May be a good reference for hands-on investigation and analysis of mechanisms with actuation control; actual analysis of components and circuitry for the electrical triggering. Will require gods skills in CAD development towards mechanical structure design for integration ingenuity S. Hybrid propellant rocket motors AND progression to flight Activity (H) must be competently completed into order to proceed with this activity. NOTE: for use of nano Al such concerns ordering in advance from sources that provide quality product. Activity will only apply nano Al when test stations and rocket launches (and possibly burn rate investigations) are ready to be implemented. Nano Al will not be accessible outside of “summer” and “winter” terms unless authorized senior project is recognised. MANDATORY hybrid propellants of concern: 1. GOX + Paraffin + nano Al 2. GOX + nano Al + Silicone Rubber Caulk (contains no water) NOTE: there will likely be need to confirm the authenticity and purity of propellant constituents. Students must determine the ratio for constituents yielding optimal performance combined with acceptable casting qualities for grain; chemistry and physics must be established compared to software data. For convenience will restrict to BATES grains for all propellants. For the case of paraffin there are some “Goldilocks” substances with anywhere from 25 to 50 carbon atoms per molecule, which are robust enough structurally. The kind of paraffin wax considered is sometimes called sculptor’s wax or hurricane wax. It’s surprisingly strong, say, means to break it up and extract it from spent fuel cartridges. Knowledge and applicability of the following for proper modelling and control of a hybrid propellant rocket motor (mandatory): 1. Propellant Characteristics 2. Chemical Reactions Similar data structure to solid fuel propellants. However, one must comprehend that propellant combustion and adiabatic flame temperature involve characteristics of an oxidizer gas AND the characteristics of the fuel grain; would be a bit more technical than activity (H). Followed by burn rate towards design of grain. 3. Physics and mathematical modelling for zones Un-combusted oxidizer flow Combustion Convection Fuel-rich outflow How can such physics and modelling identify the pressure dynamic throughout the combustion chamber? For fuel in process, situating liquid melt: the droplets, then as reacting droplets to vaporized fuel. Treatment for dO/dF all the way to Mach speeds with vapor from fuel chamber to convergent-divergent nozzle. 4. Efficient configuration of oxidizer chamber towards fuel grain chamber concerning the critical components: feeds, solenoid control valves, injector, ignitor(s), preheater grains, various types of sensors, etc. For professionalism one may be required to develop structural components and injector in CAD with detail; for structural analysis with components in unison the results should be ratings that surpass expected optimal chamber pressures and temperatures. One should also know the specifications of each component and limits. 5. Solenoid control valve circuit and its control 6. The most challenging part may be design and integration of the ignitor(s) 7. Process Dynamics & Control dO/dF will be dependent on oxidizer flow from channel. Maybe of great interest is to understand how the solenoid control valves applied up to the injectors (test stand and in rocket) will perform, say, the actual flow rate into chambers. Naturally, one should be interested in whether oxidizer inflow rate should be higher than burn rate. Additionally, should oxidizer inflow duration be configured to exceed lifetime of grain regression? What gives the optimal result based on both prior questions? Technical concerns --> Chamber Pressure Hard start issue Higher chamber pressure implies more thrust (generally) Self pressurization of oxidizer Determination of chamber pressure for unhindered oxidizer flow, hence stable combustion Realistically will have changing chamber pressure, so prior is more complicated Recalling some crucial structural components Injector (I) Nozzle inlet (Ni) Nozzle throat (Nt) Nozzle exit (Ne) Thermodynamic Properties Specific heat (p = const.) for I, Ni, Nt, Ne Specific heat (V = const.) for I, Ni, Nt, Ne Gas constant for I, Ni, Nt, Ne Molecular weight for I, Ni, Nt, Ne Isentropic exponent for I, Ni, Nt, Ne Density for I, Ni, Nt, Ne Sonic velocity for I, Ni, Nt, Ne Velocity for Nt, Ne Mach velocity for Nt, Ne Area ratio for I, Ni, Nt, Ne Mass flux for Nt, Ne Mixture Ratio Optimal mixture ratio Keep this ratio in mind when selecting valves for the oxidizer injection Ratio will shift throughout the burn Incorporate Chamber Pressure into the Oxidizer flow rate model Model the mass flow rate into the post combustion chamber Model the total mass lost by the rocket NOTE: we are not aiming for ratios that yield results indistinguishable from solid propellant rockets (Isp, velocity and altitude). A contrary stance identifies inadequate application of the effort from development. Concerning ignition design and integration with economic feasibility and simplicity, will follow the path of Spiegl (link later on) involving an ignitor and pre-heater: “The ignitors and pre-heaters are simplified solid rocket fuel grains designed to provide significant heat and flame in order to a) open the UC valves b) light the hybrid rocket motor An elementary idea rundown construction of a hybrid propellantrocket can be observed in the following link (but NOT interested in N2O and PVC fuel confined to a heavy aluminium body for rocket, rather carbon fiber): <http://www.spiegl.org/rocket02/solusn/> Development and machining of the oxidizer injector is crucial: --Pedreira, S. M. et al, Performance Analysis of Injectors for a Hybrid Propulsion System, Journal of the Brazilian Society of Mechanical Sciences and Engineering (2019) 41: 47 --Bouziane, M. et al, Performance Comparison of Oxidizer Injectors in a 1-kN Paraffin-Fueled Hybrid Rocket Motor, Aerospace Science and Technology 89 (2019) 392 – 406 For any concerns with low regression rate, it will be dealt with by the following two MANDATORY attributes: 1. Nano Al will be part of the propellant grain as a fuel in both propellant types; in propellant 1 paraffin is also a fuel, while in propellant 2 Silicone rubber caulk (no water) will be both fuel and binder. 2. Will have swirl injectors machined to suit rocket. For test station, obviously there will be a feed system where GOX is integrated but oxidizer distribution operates when triggered; rocket motors install in a manner that integrates with oxidizer feeds. Code and software that’s extremely beneficial for rockets--> (1) The ICT-Thermodynamic code H. Bathelt, and F. Volk. The ICT-Thermodynamic Code (ICT-Code). Proceedings 27th Int. Annual Conference of ICT, June 25 – 28, 1996, P 92 F. Volk. and H. Bathelt. Application of the Virial Equation of States in calculating Interior Ballistic Quantities. Propellants Explos. 1, 7 – 14 (1976) Kelzenberg, S. et al. (2014). New version of the ICT-thermodynamic Code. Fraunhofer Publica. Energetic Materials. Particles, Processing, Applications: 45th International Annual Conference of ICT, June 24 - 27, 2014, Karlsruhe, Germany. Pfinztal: Fraunhofer ICT, 2014, pp. 95.1-95.9 (2) Thermochemical performance software: --CEA from NASA software catalog, GUIPEP + PROPEP; STANJAN, DWSIM (+ ChemSep) or COCO (+ ChemSep) may prove quite useful alongside the prior mentioned software above for hybrid propellants. (3) Components and flight performance: --OpenRocket Simulator --RASAero --ROCETS from NASA software catalog In this case both software will likely complement each other. (4) Aerodynamic Analysis software: --RASAero --Cart3d (from NASA software catalog) --OpenFoam --ANSYS (5) Structural Analysis software: Patran/Nastran or ANSYS For gaseous tanks they will be pressured to a degree where work applied consistently puts all of oxidizer to use towards a high specific impulse. Some hybrid rocket behaviour guides --> (i). Chiaverini, M. J. (2000). Fundamentals of Hybrid Rocket Combustion and Propulsion. American Institute of Aeronautics and Astronautics. (ii). Genevieve, B., et al, A Computational Tool for Predicting Hybrid Rocket Motor Performance, R & D Journal of the South African Institution of Mechanical Engineering 2017, 33, 56 - 65 (iii). Chelaru, T., and Mingireanu, F., Hybrid Rocket Engine, Theoretical Model and Experiment, Acta Astronautica 68 (2011) 1891–1902 (iv). Thomas, J. C., Stahl, J. M., Morrow, G. R. and Peterson, E. L., Design of a Lab-Scale Hybrid Rocket Test Stand, 52nd AIAA/SAE/ASEE Joint Propulsion Conference 2016 Paraffin fuel guides --> (i). Petrarolo, A., Kobald, M., and Schlechtriem, S., Understanding Kelvin–Helmholtz Instability in Paraffin‑Based Hybrid Rocket Fuels, Experiments in Fluids (2018) 59: 62 (ii). Piscitelli, F., et al, Characterization and Manufacturing of a Paraffin Wax as Fuel for Hybrid Rockets, Propulsion and Power Research 2018;7(3): 218–230 (iii). Saccone, G. et al. Manufacturing Processes of Paraffin Grains as Fuel for Hybrid Rocket Engines. 51st AIAA/ASME/SAE/ASEE Joint Propulsion Conference, 27-29th July, 2015, Orlando, Florida (iv). Veale, K. et al. (2018). The Structural Properties of Paraffin Wax Based Hybrid Rocket Fuels with Aluminium Particles. Acta Astronautica volume 151 pages 864 – 873 (v). Pal, Y., and Kumar, V., R., Thermal Decomposition study of Paraffin Based Hybrid Rocket Fuel Containing Aluminium and Boron Additives, Thermochimica Acta 655 (2017) 63 – 75 (vi). Y. Pal & V. Ravi Kumar, "Regression Rate Studies of Hybrid Rocket Fuel on a Lab Scale Rocket Motor," 2015 International Conference on Robotics, Automation, Control & Embedded Systems (RACE), Chennai, 2015, pp. 1- 5. NOTE: for any process of moulding/casting fuel grains with paraffin + nano Al involving high temperatures, paraffin should not reach temperatures responsible for transition into vapour phase, and aluminium particles should not be exposed to near ignition/combustion temperatures. GOX + nano Al + Silicone Rubber Caulk (contains no water) --> Such will be developed similar to what was encountered in activity (H), however, in this case NH4ClO4 will be excluded from composition of grain; GOX to be the sole oxidizer. Expected to perform at least as good as the well known propellant that is GOX + HTPB + nano Al. HTPB is expensive and the casting/exhaust by-products from HTPB are highly toxic. For hybrid propellant rockets predicting rocket motor performance may be more tedious than what was encountered for solid rocket propellants. Test station sensing towards thrust curve accumulation, chamber pressure and temperature readings of interest that are collectible. Additionally, for oxidizer supply tanks and other critical points in test station module, to have pressure sensing; such related to mass flow rates. Generally, except for oxidizer supply tanks all sensing to be digital where values can be acquired and geometrically conveyed in a time oriented manner. Such crucial data concerns comparing with rocket performance prediction from manual calculations and prediction software. Following continuity check and activation of sensors, in system design there must be means to activate solenoid control valve directly before ignition. Namely, there can be a scheme that delays ignition for a few seconds following initiation of solenoid control valve. Based on pressure settings of oxidizer chamber, feeds and assumed pressure in motor chamber before combustion one can determine the time it takes to reach nozzle throat or igniter (which ever is appropriate). Time continuous pressure sensing, time continuous thrust sensing, time continuous infrared imaging, time continuous infrared temperature sensing, exhaust velocity determination, time continuous vibration sensing, will be applied to hybrid rocket motors in static test stations. Will try to compare pressure chamber build up model to pressure sensing data. Comparing thrust curves among the different hybrid propellant-oxidizer configurations and the predictions; such also would be greatly appreciated with pressure data, assuming pressure curve prediction by software is possible towards comparing with data. With static test station vibration sensing w.r.t. time also to apply. Another goal is to have comparative view of vibration activity, thrust activity, pressure activity and temperature activity; each physical measure category to have its own axes, but axes for quantities will be vertically sequential in display and synchronized in time scale and duration. As well, economy advantage must be determined by comparing data from solid propellant activity and experimentation from static test station with hybrid fuel configurations. Such concerns the weight and complexity of the hybrid rocket motor system compared to the solid rocket motor system in regard to thrust, specific impulse and average impulse. There will be multiple trials. Likely, multiple configurations for hybrid rocket motor system towards optimal weight configuration and system efficiency if observed and deemed practical. Microcontrollers to be responsible for ignitors, valves control control, sensors, and visual operations in fashion of parallel computing (stack or multi-core) or independent boards; power source to operate all such prior being essential, and may need voltage adjustments for a respective operation. Based on the different voltage adjustments for different operations one should prematurely simulate the lifespan of the power source with the expectation that is exceeds greatly rocket trek from beginning to end. Note: this description of the complexity range for control but isn’t necessarily optimal concerning economics of functionality and weight (in regard to mass and weight distribution). Note: students should know safety protocols for storage of propellants, motor rocket system, etc.; concerns environment and capable security measures. For rocket launches tanks must be fitted or stabilized to frames within. Generally GOX tanks are thick and heavy, thus, developing one’s own gas chambers for rockets to launch. CAD development will be useful with design to integrate with other components and dimensions of preference are determined. Then tanks are machined. Emphasis on gas being highly compressed in gas chambers. With such lighter containment there’s possibility of having more concentration is small volume compared to small molar measure that takes up high volume; giving certainty that fuel grain usage is not squandered, and rocket uses full altitude potential. The O/F ratio with consideration that GOX must be highly pressurized. For hybrid propellant rocket launches, M and N class rocket motors are required due to higher accessibility for larger scales involving technologies and engineering. Additionally, the weight of constituents in hybrid systems to considerably add up more than solid rocket propellant systems; it may be a greater challenge to maintain Cg above Cp. As well, orientation of structural components and internal systems, etc. to be properly distributed symmetrically w.r.t. the roll axis. As well, structural integrity and flutter resolution for aerodynamic fins. However, like solid propellant rockets launched in activity (H) all integrated sensing (primary, secondary and also apogee for parachute) and visuals to be applied. Concerning containment or casing for sensing and power source such must be quite light but sturdy against inertial events and the possibility of hard impact; containment should not interfere with sensing abilities. NOTE: There also may be need for temperature and pressure digital monitoring sensors that can send data to operator for decision on proceeding with continuity check launch; such two sensors will be active before continuity check that activates all other sensors (primary and secondary). Following continuity check and activation of sensors, in system design there must be means to activate solenoid control valve directly before ignition. Namely, there can be a scheme that delays ignition for a few seconds following initiation of solenoid control valve. Based on pressure settings of oxidizer chamber, feeds and assumed pressure in motor chamber before combustion one can determine the time it takes to reach nozzle throat or igniter (which ever is appropriate). NOTE: Maximum dynamic pressure likely will have greater influence with hybrid propellant rockets than with solid propellant rockets. Development and operations with hybrid propellant rockets IS A NECESSITY because not all rocket motors are boosters, and general spacecraft need to control their burn. Success with hybrid propellant rockets exhibits high competence, integrability and ability to advance. All types of recordings and data should be stored in initial state, dated, labelled, etc. NOTE: static motor tests AND rocket launches will be far from any marine/aquatic environments and high vegetation environments. If you don’t launch any then you really can’t say you’ve worked with hybrid rockets. T. Flybys and Gravity Assists Open to ME, EE, COMPE, CS and physics constituents I. Some review of orbital mechanics. Will highlight essential topics: -Newton’s Laws and Kepler’s Laws -Second order differential equation of motion for two orbiting bodies -Conic polar trajectory equation deduced from prior -Conic sections equations in polar form -Conic sections orbits based on energy analysis and eccentricity -Delta v -Hohmann transfer -Bi-elliptic transfer -Patched conic approximation -Universal variables < Herrick, S. (1965). Universal Variables, Astronomical Journal, Vol. 70, p. 309 >. The universal variable formulation (works well with the variation of parameters technique). Quote: “In a two-body simulation, orbital elements [the satellite's initial position vector and velocity vector at a given epoch t = 0] are sufficient to compute the satellite's position and velocity at any time in the future, using the universal variable formulation; radar sites or professional sources can provide the position and velocity vectors at the epoch of observation, t = 0, for satellites and most of the planets. Conversely, at any moment in the satellite's orbit, we can measure its position and velocity, and then use the universal variable approach to determine what its initial position and velocity would have been at the epoch”, Wikipedia. Will like to verify this by comparing universal variable formulation with given initial data to updating data from professional databases. -Keplerian elements There are 8 elements that you need to define an orbit. Identify them. Determining the orbital elements from the position vector and velocity; radar sites or professional sources can provide the position and velocity vectors at the epoch of observation, t = 0, for satellites and most of the planets. Determining the position vector and velocity vector from the orbital elements. Compare orbit finding with use of these 8 elements to universal variable formulation, and also to updating data from professional databases. -Perturbations The following are some effects which make real orbits differ from the simple models based on a spherical earth: 1. Equatorial bulges cause precession of the node and the perigee; might be treated by manipulating the gravitational potential with applying motion of inertia and McCullough’s formula with Legendre polynomials (zonal harmonics). 2. Tesseral harmonics of the gravity field introduce additional perturbations Cook, G. E., (1963). Perturbations of the Satellite Orbits by Tesseral Harmonics in the Earth’s Gravitational Potential. Planetary & Space Science, Vol 11 Issue 7, pp 797 – 815 Kozai, Y., Tesseral Harmonics of the Gravitational Potential of the Earth as Derived from Satellite Motions, The Astronomical Journal volume 66 Number 7, September 1961 3. Lunar and solar gravity perturbations alter the orbits G. E. Cook (1962). Luni-Solar Perturbations of the Orbit of an Earth Satellite, Geophysical Journal International, Volume 6, Issue 3, Pages 271–291 Roy, A. E. (1969). Luni-Solar Perturbations of an Earth Satellite. Astrophysics and Space Science, Volume 4, Issue 4, pp. 375-386 Colombo C (2019) Long-Term Evolution of Highly-Elliptical Orbits: Luni-Solar Perturbation Effects for Stability and Re-entry. Front. Astron. Space Sci. 6:34. Kozai, Y. A New Method to Compute Lunisolar Perturbations in Satellite Motions, NASA – Research in Space Science, SAO Report N0. 349 Davis, D. C., Patterson, C. and Howell, K. (2007). Solar Gravity Perturbations to facilitate Long-Term Orbits: Application to Cassini, Paper AAS 07-275 4. Atmospheric drag reduces semi-major axis unless make-up thrust is used Prieto, D. M., Graziano, B. P. Roberts, P. C. E. Spacecraft Drag Modelling. Progress in Aerospace Sciences Volume 64, January 2014, Pages 56-65. For a respective planet or satellite an appropriate atmospheric density model must be determined. 5 . With all prior perturbations (1) through (4) the position vector and velocity vector vary with time. The technique to compute the effect of perturbations becomes one of finding expressions, either exact or approximate, for such time varying functions. Most of them can be handled on short timescales (perhaps less than a few thousand orbits) by perturbation theory because they are small relative to the corresponding two-body effects. Compare orbit predicting with perturbation theory to updating data from professional databases and see if predictions are better than prior methods. -Parabolic time of flight -Hyperbolic time of flight II. Goal is utilize a gravity assist from Planet A and determine a minimum two impulse mission to Planet B. Begin by looking for a solution on a specified date and time, with the Julian date corresponding to such. Modelling must be comprehended to pursue any code development. Modelling and development of code with input parameters; comprehension and proper use of formulas must be established before code development. ODE propagation method and Lambert’s problem. Goals: 1. Develop Gravity Assist Maneuver Code 2. Test Code Against Known Solutions 3. Begin Analysis for Arrival at “Near Earth Object” (NEO) Code Logistics: 1. Obtain Ephemeris data for Earth, planet A and planet B from NASA’s Horizons database. 2. Find Lambert Solution from Earth to planet A 3. Find Lambert Solution from planet A to planet B 4. Find the change in velocity needed at the gravity assist to patch both Lambert solutions together. Data sources and tools of possible interest: 1. At ESA all satellite operations are managed by the European Space Operation Centre (ESOC). This is also the authority providing the trajectory data to all the scientific groups working within the space missions. Data Distribution System (DDS) 2. SPICE https://naif.jpl.nasa.gov/naif/ 3. Orbit Visualization Tool (OVT) http://ovt.irfu.se 4. NASA’s Horizons Database 5. SPace ENVironment Information System (SPENVIS) To estimate the amount of radiation from the Van Allen radiation belts. Different models to be incorporated. Determine the total expected radiation dose for concerns about possible risk of damaging the electronics. Radiation belt models AP-8 and AE-8, To estimate the total radiation dose (energy deposited in the target), we used the SPENVIS implementation of the SHIELD DOSE-2 model (v 2.10) developed by NIST << Seltzer, S. M. (1994) Updated Calculations for Routine Space-Shielding Radiation Dose Estimates: SHIELD DOSE-2, NIST Interagency/Internal Report (NISTIR) >>. The modelling can be refined using SPENVIS’ “Sectoring analysis for more complex geometries” and ”Multi-Layered Shielding Simulation (Mulassis)”. Additionally, to determine what level of shielding is required to protect passengers (from beginning to end). There might also be need of requirement coordinate transformation routines (GEI, GEA, GSE, GEO, etc., etc.). An additional coordinate system of concern is the craft internal system (CIS) whose centre is the craft itself, with special conditions for the “x” and “y” axes. It would be nice if programme can introspect and/or query data from the following sources. Concerning data sources and tools (1 – 4) there are the following executions: --Read the craft trajectory and attitude data files provided by ESOC (or whatever) --Read the planetary trajectory data files provided by NASA JPL Horizon System --Fit the different data to match in time --Perform coordinate transformations (will see) --Calculate time and index for closest approach --Visualize trajectory and attitude of craft during flybys in a simple way (optional) --Calculate when probes are in wake and when they are sunlit (optional) The main program file calls external routines for reading and treating the data as well as for visualizing the results. The idea has been to make the program useful for future flybys and the structure is made so that it should be easy to add new routines, such as new coordinate transformation functions, and to easily change the input data as it is constantly being updated. When the main programme (calling other programmes) goes through the following procedure: --Choice for the user to select what event should be considered, i.e either one of the four planetary flybys or the whole mission --Reading of the ”raw” data from text files for the current event [“….”] ROUTINES FOR TRAJECTORY DATA --Interpolation of the craft trajectory and attitude data to match the constant time steps for the planetary trajectory --calculating things like the time for closest approach and the Julian day numbers for the data --Performing coordinate transformations --Presenting the trajectories (and other data) in a number of different plots Visualization often plays a high role in mission confidence. When running the visualization program the user can chose between a number of plot types and options. They are: --trajectory plots in the GSE coordinate system with the planet and Moon motion included, a three dimensional plot as well as two dimensional projections --same trajectory plots as above but with small coloured vectors indicating the spacecraft’s x (red), y (green) and z (blue) axes at certain points in time, preferably every hour --a plot in the geographical system for the Earth flybys, showing craft’s path on a world map and its position at the closest approach --a plot over the Sun’s motion (and the motion of the velocity vector) in the CIS system, translated to the probes respectively --an option to save the craft box model image file described above for a chosen probe --an option to calculate the expected eclipse/wake data from the saved image file and store it in variables --plots showing the illumination and plasma exposure for each probe --a plot over the whole craft mission in a heliocentric coordinate system, divided up into sub-plots covering the interesting time periods --an option to set the time span that should apply on the plot data, making it possible to ”zoom in” interesting time periods --an option to store the trajectory and attitude (or whatever) data in a text file with tab separated columns --an option to store the eclipse/wake data in a file, to be used for comparison with measured data Parameter categorizations (may be excessive or not): DEPARTURE Departure object name Departure date (Julian Date) Departure date (mm/dd/yyyy hh: mm: ss) Departure energy (Kgm^2/s^2) FLYBY Flyby object name Flyby date (Julian Day) Flyby date (mm/dd/yyyy hh: mm: ss) Radius_per (km) Delta total (deg) Angle from dot product (rad) Altitude of flyby (Km) Aiming radius (Km) Minimum altitude flyby (Km) V infinity in vector (Km/s) V infinity out vector (Km/s) Magnitude of velocity change at perigee dv_per OBJECTIVE FUNCTION (Kgm^2/s^2) ARRIVAL Arrival object name Arrival date (Julian Date) Arrival date (mm/dd/yyyy hh: mm: ss) TIME OF FLIGHT tof (days) tof (s) TRAJECTORY Ellipse of type Number of complete revolutions around the Sun Change in the true anomaly (deg) Prograde trajectory ORBITAL ELEMENTS Period (years) Period (s) Angular momentum (Kgm/s^2) Semi-major axis (Km) Semi-major axis (AU) Eccentricity Inclination (deg) Right ascension (deg) Argument of perihelion (deg) True anomaly at departure (deg) True anomaly at arrival (deg) Mean anomaly at departure (deg) Mean anomaly at arrival (deg) Eccentric anomaly at departure (deg) Eccentric anomaly at arrival (deg) STATE VECTORS Position vector at departure (Km) Velocity vector at departure (Km) Velocity vector at arrival (Km) III. Extend developed code with parallel computation if possible IV. Case of using gravity assist for asteroid intercept flight plans V. Multi-gravity Assist development (if able) VI. For celestial studies safety parameters for flybys are required. For a general astronomical body there are crucial concerns: --Preferred minimal orbit based on celestial body’s gravity and possible atmospheric data --Multiple adjustment boosts or maneuvers concerning orbits of interest or escape: Federal Aviation Admnistration, Maneuvering in Space 4.1.5, In: Advance Aerospace Medicine On-line Section III – Space Operations – Basic Concepts of Manned Spacecraft Design --> https://www.faa.gov/about/office_org/headquarters_offices/avs/offices/aam/cami/library/online_libraries/aerospace_medicine/tutorial/media/III.4.1.5_Maneuvering_in_Space.pdf Such crucial concerns are likely related to the effects mentioned in the perturbations treatment. However, one must account for the unique data of the planet or celestial body in question. As well, for bodies such as the sun, radiation exposure is a concern for craft electronics (and possibly passengers). Electromagnetic interference. There’s also concern for violent unpredictable solar (star) weather and solar (star) radiation pressure. Note: the following may or may not be used to compare with results --> https://software.nasa.gov/software/GSC-16720-1 https://code.nasa.gov There may be other useful software from the NASA software catalogue. U. Missions and Manoeuvring (COMING SOON) V. Rocket nozzle erosion for solid propellant and hybrid propellant rockets Activities (H) and (S) both must be done competently to proceed with this activity. Possibly, it’s inevitable that rocket nozzle (throat) erosion may overcome due to continual rocket motors usage. Note: along with rocket nozzles from activities (H) and (S), data from activities (H), (S) and possibly activity (R) as well may prove quite essential. This activity concerns analysis modelling, numerical analysis, simulation development for nozzle (throat) erosion, its minimization for both solid propellant rocket motors and hybrid propellant rocket motors, and imaging of such rocket nozzles if possible. Will also apply whatever practical and tangible reliability engineering to subject. Our interest will be rocket motors from past usage, hence, molybdenum inserts will generally not be considered. However, will pursue determination on whether the erosion causing three distinct processes recognised in the journal articles still apply, and the conditions needed for each process to occur; includes phases and products for each process. Perhaps, imaging of rocket nozzles if possible will be inevitable, rather than absolute dependence on simulations. Nevertheless, it will also be constructive to learn about molybdenum inserts, carbon-carbon/graphite nozzles and other types from the journal articles. 1. Solid Propellant treatment --> --De Morton, M. E. (1977). Erosion in Rocket Motor Nozzles. Wear, Volume 41, Issue 2 pages 223 – 231 --Zhang, J., Jackson, T. L., Buckmaster, J. and Najjar, F. (2001). Erosion in Solid-Propellant Rocket Motor Nozzles with Unsteady Nonuniform Inlet Conditions. Journal of Propulsion and Power Volume 27, No. 3. May – June 2011 --Evans, B. et al (2006). Evaluation of Nozzle Erosion Characteristics Utilizing a Rocket Motor Simulator. In Collection of Technical Papers - AIAA/ASME/SAE/ASEE 42nd Joint Propulsion Conference (Vol. 11, pp. 8850-8862) --Evans, B. et al. Nozzle Throat Erosion Characterisation Study Using a Solid-Propellant Rocket Motor Simulator. 43rd AIAA/ASME/SAE/ASEE Joint Propulsion Conference & Exhibit, 8 – 11 July 2007, Cincinnati, Ohio. 2. Hybrid Propellant treatment --> --Kamps, L. et al. Method for Determining Nozzle-Throat-Erosion History in Hybrid Rockets. Journal of Propulsion and Power, 33(6), 1369 – 1377 --Bianchi, D. and Nasuti, F. Numerical Analysis of Nozzle Material Thermochemical Erosion in Hybrid Rocket Engines. 48th AIAA/ASME/SAE/ASEE Joint Propulsion Conference & Exhibit, 30 July 1st – 1st August 2012, Atlanta, Georgia --Hui. T. et al. Numerical and Experimental Study of the Thermochemical Erosion of a Graphite Nozzle in a Hybrid Rocket Motor with a Star Grain. Acta Astronautica 155 (2019) 10 – 22 3. Role of metal additives as nozzle erosion reducers? W. Primitive development of autonomous landing aircrafts This activity is at the most primitive level. Flight simulators can be highly parallel to real aircrafts. One will determine whether programming in such simulators are practical with real aircraft actions. If so, then one is to develop automatic control and integrate with such programming towards autonomous landing of an aircraft. To begin, flight modelling/dynamics must be well understood towards development of automatic control. It’s crucial that competent control for all actuators are well established and developed. Ground steering laws and moments (if such two are necessary) incorporated into flight dynamics by addition of a process which calculates forces and moments acting on the vehicle due to interaction between the wheels and runway surface. Some journal article guides that may serve well for development: -- Lee C.S.G. (1991). Sensor-Based Robots: Algorithms and Architectures. NATO ASI Series (Series F: Computer and Systems Sciences), vol 66. Springer, Berlin, Heidelberg. Focus on: Neural Networks, Parallel Algorithms and Control Architectures (pages 143 – 282) --S. Singh and R. Padhi, "Automatic path planning and control design for autonomous landing of UAVs using dynamic inversion," 2009 American Control Conference, St. Louis, MO, USA, 2009, pp. 2409-2414 --De Bruin, A. and Jones, T. Accurate Autonomous Landing of a Fixed Wing Unmanned Aircraft under Crosswind Conditions. IFAC-PapersOnLine 49-17 (2016) 170–175 --Tripathi, A. K. and Padhi, R. Autonomous Landing for UAVs using T-MPSP Guidance and Dynamic Inversion Autopilot. IFAC-PapersOnLine 49 – 1 (2016) 018 - 023 --Wolkow, Stephan, Angermann, Maik, Dekiert, Andreas, Bestmann, Ulf, "Model-based Threshold and Centerline Detection for Aircraft Positioning during Landing Approach," Proceedings of the ION 2019 Pacific PNT Meeting, Honolulu, Hawaii, April 2019, pp. 767-776. This latter journal article specializes in runway recognition, which may be specific. Namely, our pursuit is arbitrary site landings. Sensing and data collection spectrum --> Altitude sensing Ascent/Descent rate sensing Distance sensing Speed sensing (and possibly its instantaneous rate of change) Gyro sensing (pitch, roll, yaw and possibly their derivatives) Telemetry (or whatever) There must be means to acquire data form all sensing; all must be synchronized. Review flight modelling, transfer functions and control chosen aircraft models Fight simulator programming module --> FLIGHTGEAR FLIGHT SIMULATOR (open source) with C/C++ Elementary actuation tests --> Flight simulator-Arduino-servos interface: validate all aircraft actuation for respective aircraft model with flight, stabilization and landing approach. Following, additional rules and conditions may be necessary for programming amendments, subject to journal articles and sensors’ data for response concerning autonomous landings; commands/instructions will be applied to simulator when landing process is initiated. If parallel processing is practical to speed up processing, then so be it. System must be able to control the following variables: Altitude, altitude rate, speed, gyro (pitch, roll, yaw) Programme in trial runs with different approaches (position, speeds and altitudes, combination). For aircrafts models considered, there will be theoretical responses versus measured responses (in flight). As well, flight data will be collected. Process --> Aircraft models, physical architecture (aircraft model specifications) Flight stability modelling and control of chosen aircrafts FLIGHTGEAR FLIGHT SIMULATOR trial runs Acquiring data for flight stability and control Landing trials acquiring the data gyro data, configuration(s), variables and responses Various types of sensors and actuators testing Characterising sensors and actuators performance Flight Simulator interfacing with actuators for trial runs Likely simulator will have various environmental conditions Acquiring data for flight stability and control Landing trials acquiring the data Means of analysing synchronization performance Is automatic control valid? Optimisation? Determining how sensing and actuators interface (hardware wise and programming wise) What instructions are required to perform autonomous landing capability? Means of robust testing for communication and efficiency between sensing and actuation rules Aircraft models construction and installment of autonomous landing system Development of frequency air traffic control site. Such site will serve EM wave homing that conveys landing specifications with data for landing “strip”. To test will whatever telemetry or communications system. Manual control test runs ensuring that vehicles operate smoothly in flight (acquire data) Implementing autonomous landing trials (acquire data) Will build intermediate-large size RC aircrafts (larger than usual). NOTE: approaches for landing must have speed limit to reduce impact damage. Naturally, aircraft will be remote controlled for take-off and whatever types of flight courses planned. However, aircraft must autonomously complete landings. Will have trials for various speeds and altitude approaches (logically different combinations). NOTE: flight path reconstruction Teixeira, B. O., Tôrres, L. A., Iscold, P., & Aguirre, L. A. (2011). Flight Path Reconstruction – A Comparison of Nonlinear Kalman Filter and Smoother Algorithms. Aerospace Science and Technology, 15(1), 60-71. May be able to compare with FlightGear Simulator and NASA’s NewSTEP is a (matlab-based) iterative extended Kalman filter/smoother designed for solving trajectory reconstruction problems for flight test experiments. Open to computer science constituents and mechanical engineering constituents. NOTE: also interested in multi-rotor micro UAVs X. H2O2 Propulsion NOTE: for use of H2O2 and Kerosene such concerns ordering in advance from sources that provide quality product. Activity will only apply H2O2 and Kerosene when test stations and rocket launches (and possibly burn rate investigations) are ready to be implemented. H2O2 and Kerosene will not be accessible outside of “summer” and “winter” terms unless authorized senior project is recognised. 70% concentrated H2O2 is the minimum, but that's crummy for standard research purposes. Proper storage and environment. Don’t aim for 70%, rather pursue higher concentration to avoid any margin of error with concentration potency; 85% to 90% at least to be pursued. Establish safety protocols when administering H2O2 with 70% or higher concentration, catalysts exposure to H2O2 when not desired; likewise for Kerosene. NOTE: there will likely be need to confirm the authenticity and purity of propellant constituents (oxider, fuel and catalysts). PART A (Prelude) Assist with catalysts --> Morlan, P. W. et al (1999). Catalyst Development of Hydrogen Peroxide Rocket Engines. American Institute of Aeronautics and Astronautics 99 – 2740. 35th Joint Propulsion Conference and Exhibit, 20 June 1999 – 24 June 1999 - Acceptable purity of hydrogen peroxide is what percentage. Why? Chemistry to validate. - A task will concern given compounds to determine whether they are good or poor catalysts or non-reactive with hydrgen peroxide PART B (Monopropellant) Cervone, A. et al (2006). Development of Hydrogen Peroxide Monopropellant Rockets. 42nd AIAA/ASME/SAE/ASEE Joint Propulsion conference & Exhibit: https://www.esa.int/gsp/ACT/doc/PRO/ACT-RPR-PRO-JPC2006-HP%20Rockets%202006-5239.pdf Jung, S. et al (2021). Scaling of Catalyst Bed for Hydrogen Peroxide Monopropellant Thrusters using Catalytic Decomposition Modelling. Acta Astronautica 187, pp 167 – 180 Goal is to develop a test station PART C (H2O2 - Kerosene Propulsion) Tacussis, V. et al. Designing and Building a Hydrogen Peroxide-Kerosene Rocket Engine. American Institute of Aeronautics and Astronautics. 52nd AIAA/SAE/ASEE Joint Propulsion Conference July 25-27, 2016 From the abstract, “Project Spartan Spear was composed of seven aerospace engineering undergraduate students at San Jose State University that chose to design, build and test a liquid bipropellant rocket engine….” However, one should take advantage of the opportunity for repetition and reinforcement. Is part A’s Isp more efficient than part B’s? Software that’s extremely beneficial for rockets –> (1) Thermochemical performance software: –CEA from NASA software catalogue, GUIPEP + PROPEP; STANJAN, DWSIM (+ ChemSep) or COCO (+ ChemSep) or SystemModeler may prove quite useful alongside the prior mentioned software above for hybrid propellants. (2) Components: –OpenRocket Simulator –ROCETS from NASA software catalogue In this case both software will likely complement each other. (3) Aerodynamic Analysis software: –Cart3d (from NASA software catalogue) –OpenFoam –ANSYS (4) Structural Analysis software: Patran/Nastran or ANSYS For gaseous tanks they will be pressured to a degree where work applied consistently puts all of oxidizer to use towards a high specific impulse. Y. Monitoring and Predictive Maintenance for Aircraft Activity A, B, C and D are prerequisites for this activity. Concerning aircraft for various purposes the cost of failure is much higher than its apparent cost. Conventionally, many or most companies deal with this problem by being pessimistic and through accurate maintenance programs replace fallible components before failures. Despite regular maintenance as preference over failures, often the maintenance is carried out before it’s “needed”. Therefore, it’s not an optimal solution from a cost perspective, yet, risking it all during crucial operations generally will not seem logical. Predictive maintenance avoids maximizing the use of resources. Predictive maintenance will detect the anomalies and failure patterns and provide early warnings. PART A (comprehension) Often capturing dynamic profiles of systems off the assembly line for aircraft is a decent strategy. It’s imperative that a competent and practical model-based design of predictive maintenance be designed. How will the sensing and data processing features be integrated? Analysis should be in line with the expected performance or behaviour of the project when designed. A particular aircraft design and the associated operational demands often will lead to behavioural characteristics that are highly unique. Pursue intelligence on monitoring and predictive maintenance for aircraft. PART B (planning and development) NOTE: much success will depend on part A -For structural monitoring students will need to design an aircraft in detail where geometry can be subjugated to both structural analysis and dynamic simulation with FEM/FEA. Other characteristics may be vibration profiles and so forth (likely other things). To also identify the different types of sensing applied to various parts of aircraft structure. To be accompanied by identifying structural codes requirements. -Students can also develop microscale representations of structural parts constituted by carbon fire, composites, etc., supported internally by light frame with aerofoil cross sections, etc. Within such microscale representations are various types of sensors towards acquiring data from various tests. Structural analysis and dynamic simulations with FEM/FEA can be compared with acquired data. Such means that the microscale representations must well developed in CAD, accounting for material properties similar to the physical constructions that will be tested in lab. -Aircraft body actuators for manoeuvres and stabilization may be a bit tricky to develop, but not out of league. Motors and actuators can be directly simulated to identify ideal performance/behaviour; then in function with ailerons and so forth (via SystemModeler/Modelica). Data from instituted motors and actuators into built ailerons, etc, can be acquired. Compare and contrast. -Propulsions systems also make use of sensors embedded to gather various data. Propulsion systems monitoring may be quite complex. For prop engines, such will be fairly easy to develop since the major challenge is acquiring RC combustion engines with shaft and prop integrated. Will still require use of an ECU, where a cheap conventional combustion engine ECU may suffice. The ECU only concerns regulation towards performance; such is not the same as predictive maintenance. Another way of looking at it, if your engine is crummy, the ECU can only do so much before the craft falls out of the sky. 1. For a prop engine active observation and analysis are highly feasible, because attaching a shaft with a well fixed propeller to well made proprietary “small” combustion engines is no big deal. We would like to profile this engine for ideal performance. Our engine scale may be an issue with Ansys, SystemModeler, Modelica and OpenWam. If so, will have to run a (relatively) new engine with an ECU and collect data to be used as the control case. A. Data used by the ECU in continuous function will also be acquired without interfering with the ongoing ECU data processing and continuous operation. B. Additionally, one must first identify what types of other sensing will be needed for monitoring. Some possible elements may be Vibration analysis (to detect cracks/fractures, inadequacy) Unbalance detection (possible degradation) Detects whether out of “equilibrium” from initial state; not concerned with applying further body reduction Acoustics Transfer functions (input-output) versus system data Infrared analysis concerns continuous imaging and continuous temperature data acquisition, respectively. Note: the following text may assist with the vibration analysis implementation Mironov A., Doronkin P., Mironovs D. (2019) Research and Practical Application of Vibration Transfer Functions in Diagnostics of Jet Engine. In: Kabashkin I., Yatskiv (Jackiva) I., Prentkovskis O. (eds) Reliability and Statistics in Transportation and Communication. RelStat 2018. Lecture Notes in Networks and Systems, vol 68. Springer, Cham. To have a crummy engine from consensus, versus a well functioning one from consensus. Mechanics/dynamics/control characteristics and/or machine learning. After all such, one is to design the analysing predictive maintenance models to compare with respective data. 2. For a turbo jet engine, we’re actually going to just extend activity (D). Again, the ECU only concerns regulation towards performance; such is not the same as predictive maintenance. Another way of looking at it, if your engine is crummy, the ECU can only do so much before the aircraft falls out of the sky. A challenge will be identifying data that’s characteristic of a good engine during start-up and under optimisation by an ECU. Hence, one must go on acquired data from activity (D) for such, and also compared with simulations from Modelica libraries. A. Data used by the ECU in continuous function will also be acquired without interfering with the ongoing ECU data processing and continuous operation. B. Additionally, one must first identify what types of other sensing will be needed for monitoring. Some possible examples may be Vibration analysis (to detect cracks or fractures) Unbalance detection (possible degradation) Detects whether out of “equilibrium” from initial state; not concerned with applying further body reduction Acoustics Transfer functions (input-output) versus system data Infrared analysis concerns continuous imaging and continuous temperature data acquisition, respectively. Note: the following text may assist with the vibration analysis implementation Mironov A., Doronkin P., Mironovs D. (2019) Research and Practical Application of Vibration Transfer Functions in Diagnostics of Jet Engine. In: Kabashkin I., Yatskiv (Jackiva) I., Prentkovskis O. (eds) Reliability and Statistics in Transportation and Communication. RelStat 2018. Lecture Notes in Networks and Systems, vol 68. Springer, Cham. To have a crummy engine from consensus, versus a well functioning one from consensus. Mechanics/dynamics/control characteristics and/or machine learning. After all such, one is to design the analysing predictive maintenance models to compare with respective data. Note: for real passenger jets, recall the many complicated systems and networks residing on jet engines. Well, this activity is a “stripped down or simplified” version of such; obviously not all systems for real jet engines are treated here. In the real world, applied modern systems may augment “onboard data collection” with telemetry use (telemetry not required in activity, but one can scheme it up as a bonus in this activity). Note: in the real world continuous oral structural inspection on blades, turbines and compressors also apply. In the real world continuous dust inspection on blades, turbines and compressors also apply. Note: there are parallels to rocket pre-launch checks and launch stages with NASA, ESA, SpaceX, etc. Z. Structural Health Monitoring of Rocket Engines (INCOMPLETE) Qing XP, Chan H-L, Beard SJ, Kumar A. An Active Diagnostic System for Structural Health Monitoring of Rocket Engines. Journal of Intelligent Material Systems and Structures. 2006;17(7):619-628. Qing, Xinlin & Wu, Zhanjun & Beard, Shawn & Chang, fu-kuo. (2008). Advanced active health monitoring system of liquid rocket engines. Proceedings of SPIE - The International Society for Optical Engineering. 7375 MECHANICAL ENGINEERING (some activities will also cater towards AE, EE, IE, CS and CIVE) A. Analysis and calibration process of chosen combustion engines. Comparison to passenger scale models. Electric Analogy. Arduino/Raspberry Pi or other integration always welcomed. 1. Review: How Car Engine Works – YouTube Diesel Engine, How it Works? YouTube The Differences Between Petrol and Diesel Engines - YouTube 2. Review of Otto cycle 3. One can reference the following for modelling treatment: --Zeleznik, F. J. and McBride, B. J., Modelling the Internal Combustion Engine, NASA Reference Publication 1094, March 1985 Note: don’t become intimidated by the cascade of equations given early. Rather, first analyse/identify a typical engine’s makeup and how each component functions and contributes in the system process. Then, jump to chapters succeeding the cascade of equations that model the algorithmic process with the dynamical system. Not interested with intimate analysis of the function algorithms, however, based on this strategy taken one can situate equations appropriately. 4. Will have strong immersion into tools such as OpenWam 5. Active assembly/disassembly of old engines. Will identify the characteristic components for the ICE. Such likely concerns different types that are/were conventionally representative of the commercial and industrial industry; RC, motorcycle, chainsaw (or lawnmower), car engine and backhoe. Comparative analysis of design concerning necessary systems components with respect to scale and desired outputs, etc. For characteristic components will recall the relevant associated models for such from (3). 6. Simulation of an ICE (engine model may vary) Review with OpenWam tasks 7. For a RC internal combustion engine, for provided parameters from manufacturers, to develop ingenuity schemes towards confirmation of such, and towards calibration; sensory for torque, rpm, exhaust count, fuel intake, heat analysis, etc. Then, infrared analysis where temperature can be interpreted over time for specific regions of the engine. All such prior to be used towards applications of formulas characteristic of IC analysis (not limited to horsepower, manifold vacuum, vacuum gauge, AFR); some may even require Newton’s method, interpolation or least squares. Calibrations may be needed to match manufacturer statistics or to attain optimal function. May or may not repeat such for larger scale engines. 8. Control for ICE for control analysis: --Cook, J. A. and Powell, B. K., Modelling of an Internal Combustion Engine for Control Analysis, IEEE Control Systems Magazine, vol. 8, no. 4, pp. 20-26, Aug. 1988. --Guzzella, L., & Onder, Christopher H. (2010). Introduction to modeling and Control of Internal Combustion Engine Systems (2nd ed.). Berlin: Springer. Note: the latter is quite comprehensive, hence focus on specific interest for during time. As well, diesel engines often don’t require spark plugs in dynamics, so be careful. Transfer functions development. 9. Will identify the components/devices applied to the engine for control/regulation under different conditions. 10. Engine Control Management (ECU) Use of a programmable module board towards an ECU for engines. In general ECU’s are relatively cheap, however, it’s use is to be amended to operate an idealistic small engine with use of a programmable board (if needed) and what not; there are programmable boards with digital displays well suited for such. How would such a system be developed and integrated with the engine? Logistics and design, then implement and operate. In general, for a particular engine there may be unique properties to measure based on components of the engine. Inputs come into from the engine, while outputs that go out to injectors and ignition that’s on the engine. Inputs that come into the ECU one can choose a wide range of things for data logging and advance tuning operations. Ideally (may not fully apply to engine) sensors for the engine to run: air temperature coolant temperature throttle position manifold pressure engine speed In highly professional cases (likely not here) thousands of variables are present for the engineer to modify during the in-vehicle calibration phase, and fine tuning them is as complicated as it is critical. Calibration tools importantly impact the efficiency and effectiveness of the ECU development process. These tools are typically comprised of PC-based software to perform the adjustment of the variables and an ECU hardware interface to provide the connection of the software to the controller. One must be able to measure and time-align relationships of inputs and outputs and make real-time modifications. System level verification of developed ECU before integration and operation with RC engine. Look-up tables configured in the ECU. An example, say, fuel and ignition set up by tuner; sending signals out to fuel injectors for fuel regulation for desired target air to fuel ratio—towards making the most power. Look-up is 3-D in the management system, say 16-32 load points for rpm range, etc. Other interest may be exhaust gas temperatures and pressures. With an ECU there’s efficient use of resources and limiting on pollution with testing. In this case RC engine size scale may need to be a bit bigger than initial to actually make such operations practical. System level verification of developed ECU before integration and operation with RC engine. Infrared imaging for viewing of the engine continuously in time; detecting infrared energy and converting it into electronic signals, then to be processed to produce thermal imaging and perform temperature calculations (means of collection and storage). Pursue a configuration where temperature calculations are made for a determined interval of seconds (could be each second); data for arrangement, modelling and comparative analysis with software models and consensus professional data. Recordings and data should be storable in initial state, dated, labelled, etc. Such to be compared with ECU data. Helpful assists: L. S. Mendonça, D. D. Luceiro, M. E. S. Martins and F. E. Bisogno, "Development of an Engine Control Unit: Implementation of the Architecture of Tasks," 2017 IEEE International Conference on Industrial Technology (ICIT), Toronto, ON, 2017, pp. 1142-1146. B. Jeeva, S. Awate, J. Rajesh, A. Chowdhury and S. Sheshadri, "Development of Custom-Made Engine Control Unit for a Research Engine," 2014 2nd International Conference on Emerging Technology Trends in Electronics, Communication and Networking, Surat, 2014, pp. 1-6. Validating programme patches and testing in simulation are essential. Will like the C or C++ environment. Additional assist: Y. Kanehagi, D. Umeda, A. Hayashi, K. Kimura and H. Kasahara, "Parallelization of Automotive Engine Control Software on Embedded Multi-Core Processor using OSCAR Compiler," 2013 IEEE COOL Chips XVI, Yokohama, 2013, pp. 1-3. Note: will not be subjugated to proprietary compilers. The next level will be implementing on larger scale engines (relatively old, sans need of carburettor and distributor). Note: visual dynamometers may be active with ECU for both RC scale and passenger scale. A dynamometer is not an ECU. 11. Will be interested in conjuring the following maps with operating points: Power versus rpm maps Power versus torque maps Torque versus AFR Power versus AFR <rpm, torque> versus AFR Pressure versus volume (concerning pistons) Pressure versus crank angle Brake specific Fuel Consumption (BSFX) map Local equivalence ratio versus temperature 12. A software programme to be written in envronment of choice permitting the convenient calculation of volume percents of CO, CO₂, O₂, H₂, and H₂O from fuel composition (H/C and O/C ratios), the water content (dew point) of the combustion air, and a chosen stoichiometry (air/fuel ratio). The program considers the Water Gas Shift reaction and the production of hydrogen under fuel rich conditions. Programme should valid for both standard gasolines and oxygenated blends. Vehicle emissions data will be collected to compare with values calculated by the programme with actual experimentally determined values from vehicle exhaust. To verify good agreement (or not) for measurements made at a series of air/fuel ratios ranging from lambda of 0.85-1.2. Note: may have to account for nitrous oxide as well. Note: firm product emissions data for an RC engine may be more difficult to acquire than a “standard” passenger scale engine; will not be deterred however. Colvin, A., Gierczak, C., Siegl, W., & Butler, J. (1997). A Software Program for Carrying Out Multi-Purpose Exhaust Composition Calculations. SAE Transactions, 106, 252-260. Note: there may be other exhausts constititents such as Nitrous Oxide 12. Interested in Operating Maps (theory versus experimental data) < > Emissions map in gm/hr < > Emissions versus speed and load < > Emissions (gm/bhphr) versus F/A Ratio < > Emissions (gm/hr) versus F/A Ratio < > Emissions (gm/bhphr) versus F/A Ratio and engine speed Horsepower versus F/A Ratio Horsepower versus F/A Ratio and Engine Speed Horsepower versus Fuel Rate (at 2000 rpm) <> Emissions versus Horsepower (at 2000 rpm) Note: < CO, CO₂, O₂, H₂, and H₂O, NO, NO2 > towards < > , namely, each having unique representation; all emissions count data can be captured simultaneously, and it’s just a matter of mapping different spaces. Note: will not be running engines for an hour; scale up or down units of interest. Note: assumptions will be ideal atmosphere composition, pressure, humidity and temperature. B. Transmissions Development of transmissions based on needs and design parameters. Consideration of multiple transmissions models. Determining performance limitations based on engine power supply capability. Concerns both manual and automatic (5 to 6 speed). 1. Identify the crucial components of transmissions. Manual Transmission, How it Works? – YouTube Clutch, How does it work? – YouTube Automatic vs Manual Transmission – YouTube 2. How to make 5 speed Gearbox +R from plywood – YouTube Such above can also be made out of cardboard. There are Lego modules that be constructed but may not be economically feasible. Based on power applied from source, concerning the constituents students must be able to deduce the system equations involving torque and rpm, respectively, such to initiated gear. For each constituent will try to find a possible relation between torque and rpm, subject to initiated gear. Nevertheless, a luxurious pursuit of torque and speed measurements throughout for particular components subject to speed change would be nice if able; a means to validate deduced theoretical equations. DIY how clutch works from plywood – YouTube Again, there are Lego modules that can be constructed but may not be economically feasible. Based on power applied from source, concerning the constituents students to deduce the system equations involving torque and rpm, respectively, such to initiated gear. For each constituent will try to find a possible relation between torque and rpm, subject to initiated gear. Nevertheless, a luxurious pursuit of torque and speed measurements throughout for particular components subject to speed change would be nice if able; a means to validate deduced theoretical equations. 3. Design and dimensioning of all machine elements, such as gears, bearings, seals, tooth systems, shifting elements, shafts, housings. Determination of appropriate materials each part should be made out of concerning resistivity to wear and tear, heat conduction, heat transfer, etc. Models with CAD towards structural analysis with Patran/Nastran or ANSYS, and identify whether (colour) elevated regions are synonymous with customary breakdowns or dysfunction. A pursuit is an optimal “transmission” system w.r.t. to weight that’s sturdy towards the engine, hence, thorough machine design with scaling for high performance. Isolated engines considered have known performance parameters, but when integrated to the “transmission” system the power, torque and rpm at “full throttle” must not fall below a certain percentage; otherwise “transmission” system will be labelled nothing more than an impedance. System designed will also be simulated. Failure analysis for gears, shafts, bearings, etc. etc. Reliability or life expectancy data can as well be pursued based on structured data compared towards the probabilistic and statistical modelling. 4. Primitive modelling and control for cars Zanasi, R. et al (2001). Dynamic Modelling and Control of a Car Transmission System. 2001 IEEE/ASME International Conference on Advanced Intelligent Mechatronics. Proceedings (Cat. No.01TH8556), 1, 416-421 vol.1. Zhou Meilan, Wang Xudong, & Zhou Yongqin. (2006). Modelling and Simulation of Continuously Variable Transmission for Passenger Car. 2006 International Forum on Strategic Technology, 100-103. Zhai, H., Zhu, C., Song, C., Liu, H., Li, G., & Ma, F. (2015). Dynamic Modelling and Analysis for Transmission System of High-Power wind Turbine Gearbox. Journal of Mechanical Science and Technology, 29(10), 4073-4082. Singh, G, Sharma, M, & Singh, A. (2018). Novel Automated Manual Transmission Gear-Shift Map Modelling Based on Throttle Position. International Journal of Automotive and Mechanical Engineering, 15(1), 5053-5073. 5. Based on acquired knowledge from prior journal articles will pursue extension to 5-speed (or 6 speed) synchromesh gearbox inside a manual transmission vehicle. As well, illustrate the modelling of vibration and noise in a 5-speed (or 6 speed) synchromesh gearbox inside a manual transmission vehicle. A transient multibody dynamics analysis computes the gearbox vibrations for the specified engine speed and external load. The normal acceleration of the gearbox housing is converted to the frequency domain, which is to be included as a source of noise. An acoustics analysis is then performed in order to compute the sound pressure levels in the near, far, and exterior fields. Field experimentation counterpart for comparison would be greatly welcomed. 6. Automatic transmission treatment counterpart to (5). As well: Zhang, N. et al, Modelling of Dynamic Characteristics of an Automatic Transmission during Shift Changes, Proc Instn Mech Engrs Vol 216 Part I: J Systems and Control Engineering, 2002, pages 331 – 341 7. Consider the following journal article: Pate, P.D. and Patel, J. M., An Experimental Investigation of Power Losses in Manual Transmission Gear Box, International Journal of Applied Research in Mechanical Engineering (IJARME) ISSN: 2231 – 5950, Volume 2, Issue 1, 2012 http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.457.2932&rep=rep1&type=pdf To analyse and develop similar experiment. Will also try to pursue experimentation of multiple transmissions, but for different scales and sizes. Are there more modern means to test such interests? If economically feasible, succeed the primitive experiments with such. 8. Case of integration with other drivetrain components and powertrain elements. 9. The following journals are to be analysed, then pursuit of experimentation with vehicles over appropriate ranges. A driving cycle test will be dependent on ambiance of consideration: --Zhao, X. et al, Optimizing Gear Shifting Strategy for Off-Road Vehicle with Dynamic Programming, Hindawi Publishing Corporation Mathematical Problems in Engineering, Volume 2014, Article ID 642949, 9 pages --Ngo, V. D., Hofman, T., Steinbuch, M., & Serrarens, A. (2014). Gear shift map design methodology for automotive transmissions. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, 228(1), 50–72. --D. V. Ngo, T. Hofman, M. Steinbuch, A. Serrarens and L. Merkx, "Improvement of fuel economy in Power-Shift Automated Manual Transmission through shift strategy optimization - an experimental study," 2010 IEEE Vehicle Power and Propulsion Conference, Lille, 2010, pp. 1-5. 10. Find electric vehicle analogy to (8 - 9); electric vehicles may be a challenge to come by depending on ambiance. Two examples: --Li, H. et al, Three-Parameter Shift Schedule of Automatic Mechanical Transmission for Electric Bus, Energy Procedia 145 (2018) 504 – 509 --Hsieh, L. and Tang, H., The Innovative Design of Automatic Transmissions for Electric Motorcycles, Transactions of the Canadian Society for Mechanical Engineering, Vol. 37, No. 3, 2013 Such two above articles concern mainly an electric bus and a electric motorcycle. There must be determination on whether a 3-parameter case is overall representative of other types of electric vehicles. 11. Duel clutch transmission (or other) to optimise for fuel economy by modifying the (gear) shifting schedule with a parameter sweep via parallel computing. Generate all parameter sets wishing to test and distribute those simulations to the multicore (first serially then parallel). Whether given link below has parallel computing or not such is highly welcomed to reduce hours of processing; there can be up to 20 parameters to consider--> https://www.wolfram.com/system-modeler/examples/automotive-transportation/driveline-drive-cycle-analysis.html The following journal articles may serve well in the future: --Nezhadali, V. and Eriksson, L., A Framework for Modelling and Optimal Control of Automatic Transmission Systems, IFAC-PapersOnLine 48-15 (2015) 285 – 291 --Guo, W. et al, Dynamic Analysis and Control of the Clutch Filling Process in Clutch-to-Clutch Transmissions, Hindawi Publishing Corporation Mathematical Problems in Engineering Volume 2014, Article ID 293637, 14 pages --Shin, C. et al, A dry clutch control algorithm for AMT systems in a parallel hybrid electric bus, World Electric Vehicle Journal Vol. 5, May 6 – 9, 2012 --He, H. et al, Dynamic Coordinated Shifting Control of Automated Mechanical Transmissions without a Clutch in a Plug-In Hybrid Electric Vehicle, Energies 2012, 5, 3094 – 3109 C. Robot Actuation & Control Familiarization with arbitrary primitive robots, whether planar and/or spatial. Robot assembly is constituted by common features such as actuators, motors, microcontrollers, power source, arms, pivots, etc. Concerns for the configurations and function of encoders, etc. as well The many things individuals take for granted or stereotypes they incur themselves are the influences for sustaining or growing ignorance, retention of high costs, and dependency on likely problematic entities with grip on resources and networking due to the mentioned two influences. This activity serves to reduce such influences and be a purely non-toxic, engaging and sustainable. 1. Observe the following link. Understanding primitive development is the means to reduce limitations in pursuits: www.theremino.com/wp-content/uploads/2012/10/ArmMauro4.jpg Likely, pursuits will be/become more advance than observed. Necessarily, one aim is to develop the body components in a CAD, then machining such components (metal or synthetic, or combination) to the desired specifications. Such described actuation and control will also be incorporated in the most educating, interactive and nurturing means as possible towards advance future projects. 2. Students will incorporate intensive mechanics and kinematics modelling. Use the appropriate mobility equations (planar or spatial) to calculate the number of degrees-of-freedom for each of the following robots is just elementary but will be treated with high concern in terms of physics and the resulting mathematical modelling. Sketch the kinematic diagrams and attach the coordinate frames. Derive the Denavit-Hartenberg Parameters. Determine the joint limits – report in a clear table, using deg units (mm for the prismatic joint if relevant). Sketch the approximate translational workspace of this robot. NOTE: consideration of robotic kinematics and dynamics relating to CoG and CoM w.r.t. to chosen designs concerning the components to be applied (from body components, connectors, knots-and-bolts [or whatever], motors-actutators, power, etc.) 3. Will develop control/controllers for actuation and responses. Follwed by SystemModeler/Modelica usage. Consider the possibility of variation in motion speed of dynamics with respect to energy and voltage applied. As well, robots will be simulated to capture system response in the form of graphs. Target responses. Describe the reachable workspaces of each. 4. Determination on various materials respective robot body (carbon fiber, acrylic, metal, other polymer, etc.). Such having crucial role on weight, weight distribution, structural integrity, stress on motors, etc. Identify all crucial joints to be part of the respective primitive robot; include joint variable names for each. Measure all important dimensions for the designated primitive robots (units: m and deg/rad). 5. One must determine efficient means of power towards quality actuation and control based on (2), (3) and (4). Identify the ideal robot power source, actuators, transmissions, etc., etc. What sensors are to be used (if relevant)? Identification of electromechanical components generating the dynamics, with forces and torques applied. Consideration of DC single phase or three-phase; motor starters, reduced voltage starters, adjustable speed drives, motor controllers, intelligent controllers. AC motor counterpart with the needed means for regulation of voltage, etc. Possible scheme and development for converting AC supply towards DC actuation throughout robot. Possible scheme and development for converting DC supply towards AC actuation throughout robot. 6. What is the “OS or programming environment”? Conceptual development of code before employing instruction languages. Code testing before use on physical module (code applied to simulator based on system-level approach or whatever). If done in C or C++ environment, then to relate to Mathematica language or vice versa. The following may or may not be of assistance (but rather in C/C++): https://ocw.mit.edu/courses/mechanical-engineering/2-007-design-and-manufacturing-i-spring-2009/lecture-notes/MIT2_007s09_lec14.pdf Generally, servos will not be type observed in above link. Note: some time will be devoted to motor programming such as running specific motor types on PBASIC, C, C++; as well speed control for motors. 7. Performing various task(s) for a specific repeated number of times. System responses and target responses will be compared with really operational data and modelling from developed respective robot. The predicted reachable workspaces will be compared to the range of actual developed robots. Such to provide validation or correction of data hypothesized. Base on all such whatever calibration or “smoothing” needed will be pursued. 8. Following, there will be decision on two or three types of robotic modules to develop. There is concern as well for building a 5 DOF robot arm with five servo (motors). Consider at least robot module choices that make use of PLCs. All prior steps described in general will apply, however, one now concerns themselves with PLC programming to such “system engineering” and actuation. One aims to apply C programming. D. Mechatronic Systems Development (i) Analysis of the following: Jaksic, N. I. (2012, June), A Mechatronics Experiment: Introduction to Linear Motors Paper presented at 2012 ASEE Annual Conference & Exposition, San Antonio, Texas. Then proceed with experimental investigation. As, well, to complement, virtual components can probably be found in SystemModeler to simulate based on set parameters; to be compare to experimental setups. (ii) Analysis of the following: Grimheden, M. and Hanson, M., Modular approach to Experimental Learning and Fast Prototype Design of Mechatronic Systems, INTERNATIONAL CONFERENCE ON ENGINEERING DESIGN ICED 03 STOCKHOLM, AUGUST 19-21, 2003 Then proceed with experimental investigation. As, well, to complement, virtual components can probably be found in SystemModeler to simulate based on set parameters; to be compared to experimental setups. (iii) Analyses and development of the following: www.ee.unlv.edu/~b1morris/ee292/docs/kit.pdf Compare the process and results to what was accomplished in (ii). As, well, to complement, virtual components can probably be found in SystemModeler to simulate based on set parameters; to be compared to experimental setups. (iv) Analyses and development of the following: Tutunji, T., A., and Saleem, A. (2015), A Methodology for the Identification and Control of Electromechanical Actuators, Methods X 2 (2015), 219-231. Pursue alternative methodologies and develop to compare with prior. E. Brainstorming, construction and control towards development of mobile robots This activity focuses on the development of mobile robots. Note: A construction CAD will be available, also SolidWorks, ANSYS, Nastran, Patran, SystemModeler/Modelica will be available. # Rigid Constituency 1. What will project do? Propose function character design, drive train structure design with respective chassis/frame design, steering system, etc. Identify any possible arm or extension dynamics with the crucial components necessary for such. Control for gravitational configurations is crucial; torques and moment of inertia. 2. Motors, motor controllers, servos, voltage control, limit switches, wheels, shafts, bearings, steering, actuators. Sensors such as optical sensors, gyroscopes, etc. Radio modem (some modules can be quite economic with a simple timer ic 555). Processing and control modules. Fans (if needed). Telemetry. Power sources. Note: with frame and detailed constituents, have motors that provide efficient speeds against loads applied Pneumatics (only if relevant) with compressors, air tanks, cylinders, pressure sensors, valves; determination of PSI storage in cylinders. 3. There will be automatic control and simulation. As well, programmable commands will be conceptually developed before programming and testing; students must have at least one year of officially recognised programming background in C/C++. Instructor/professor must prohibit students from observing sanctioned professional code of choice likely to be used as much as possible. System level design with verification via SystemModeler. Mechatronics background may be quite helpful as well. F. Gyro Stabilization Open to physics students (i) Review of mechanics and dynamics of a gyroscope (acquire models) . (ii) Guide: Making a Home Machine Shop Gyroscope -YouTube Before construction, for professionalism, to be developed in CAD. Determine the significance of material types towards gyroscope. Determine the rotational inertia for each circular component and rods. Melting and casting not required but succeeding construction (or reassembly) required. (iii) Observe in video the rotation of the ring succeeding the motor induced rotation of the disc. Develop a model for the rate of rotational velocity from the effects of conservation of angular momentum, torque, etc., related to initial rotating disc. (iv) Based on rotation of disc and rotation of ring develop a model for respective axis precession (equatorial and polar) w.r.t. centre of mass/centre of gravity. (v) For the motor applied to the gyroscope is there a designated time for stationary amount of rpms to be applied, and why if so? (vi) Can a gyroscopic sensor be applied without considerably hindering the prototypical behaviour of the gyroscope? If so, apply and acquire data towards exhibition of variations through time continuously for the duration. Sensor should be able to account for rotations with pitch, roll and yaw. Compare with prior models developed. Multiple trials. (vii) Can a critical condition (or conditions) for “instability” be acquired, say, when equatorial plane tilt-plunges to surface? If so, what parameters must be met for such, and w.r.t. time if possible. (viii) Rotational dynamics of the Rattleback; such must explain why there’s reinforcement to a favoured direction of rotation. Is any Coriolis phenomena equivalent to what is observed with water or other (low viscosity) liquids? Will attempt to design the rattleback in CAD, as well pursue functions or numerical models that well describe the geometry in Mathematica. Concerns developments from Mathematica into a 3D printable format; will investigate how such designs perform versus prototypical rattlebacks. There will be different 3D prints based on functions or numerical models used and CAD. (ix) Primitive Gyrocar Observe the 5 series videos from Okki Moeljadi on YouTube: Gyrocar # 1 through Gyrocar # 5 Including the following video: Control moment gyro test – YouTube For the physics in work (based on Newton's laws and Lagrangian methodology) develop the mathematical modelling to express such systems. Then develop the feedback/automatic control for such even for the case with external interference. Such apparatuses will then be built and operated with gyroscope sensing and associated data accumulation w.r.t. time for later observation. Roll dynamics be plotted w.r.t to time. It may be possible to have both data accumulation towards storage and active gyroscopic data observation. Article that may prove useful: Stephen C. Spry and Anouck R. Girard (2008) Gyroscopic stabilisation of unstable vehicles: Configurations, Dynamics, and Control, Vehicle System Dynamics, International Journal of Vehicle Mechanics and Mobility, Volume 46 Issue sup 1 pages 247- 260 (x) Pursue developing the following: Gryczan, M.(2010). “Gyrocar”. Make Volume 23 ( https://cdn.makezine.com/make/2010/10/WP113Gyrocar.pdf ) Expected would be explanation and mdelling of the physics taking place, feedback/automatic control (if relevant) and embedded system development. (xi) Cubic stabilization Apart from the body geometry for stabilization, constitution: Reaction wheels Brushless DC motors Sensors (inertial and other specific types) Microcontrollers Non-linear controller Appropriate embedded algorithms Note: developing a control moment gyro may be easier Such apparatus will include gyroscope sensing and associated data accumulation w.r.t. time for later observation. Pitch-roll-yaw dynamics will be plotted w.r.t to time. Relevant feedback control or automatic control. Apart from the feedback/automatic control one must comprehend the C/C++ programming instructions. Conceptual development and flow diagrams before writing and implementing programming instruction with developed feedback/automatic control. Interest in rotational balancing, balancing on edge or tip and mobility. Testing stability (rotational balancing, balancing on edge or tip if relevant, and mobility). Possibly, determination of minimal external force (torque) that can undermine stability. Possibly, questionable magnitude of force of arbitrary direction to undermine stability. Possibly, (if feasible) residing on vibrating surface subjected to various frequencies (nodes) both sinusoidal and chaotic, with varying in amplitudes; includes spontaneous drastic stop of driven oscillator, and spontaneous drastic rise of driven oscillator. (xii) Other essential goals (a must): 1.Two-wheel motion inverted self balancing balancing robot Apart from the feedback/automatic control one must comprehend the C/C++ programming instructions. Conceptual development and flow diagrams before writing and implementing programming instruction with developed feedback/automatic control. Possible assistance: Yufeng Zhuang, Zeyan Hu, & Yi Yao. (2014). Two-wheeled self-balancing robot dynamic model and controller design. Proceeding of the 11th World Congress on Intelligent Control and Automation, 1935–1939. Tayefi, M., & Geng, Z. (2018). Self-Balancing Controlled Lagrangian and Geometric Control of Unmanned Mobile Robots. Journal of Intelligent & Robotic Systems, 90(1), 253–265. Will have telemetry operations. 2.Ball on plate PID controller with Arduino or Raspberry Pi or other Apart from the feedback/automatic control one must comprehend the C/C++ programming instructions. Conceptual development and flow diagrams before writing and implementing programming instruction with developed feedback/automatic control. Main components of the constitution: 2 digital servo motors Arduino Due or other Touchscreen glass with its sensory integration, and 5-wire resisitive A PID controller with touchscreen driver TV remote driver with Arduino Nano (or other) IR sensor TV remote control is used to give commands (e.g. circle, square, etc.). 2x aluminium servo arm 3x servo rod Extra thin plate arm to reduce twisting Makrolon Will have telemetry module 3.Self-Balancing Unicycle Robot Assisiting guides: Nguyen, P., Nguyen, T., & Ngo, T. (2021). Balancing Control for Single-Wheel unicycle Robot using the Sliding mode controller. IOP Conference Series. Materials Science and Engineering, 1109(1), 012020 Zeyan Hu, Lei Guo, Shimin Wei, & Qizheng Liao. (2014). Design of LQR and PID controllers for the self balancing unicycle robot. 2014 IEEE International Conference on Information and Automation (ICIA), 972–977. Will have telemetry operations. (xiii) Analysis --Turnwald, A. and Liu, S., A Nonlinear Bike Model for Purposes of Controller and Observer Design, IFAC PapersOnLine 51-2 (2018) 391–396 --P. Y. Lam, "Gyroscopic stabilization of a Kid-Size Bicycle," 2011 IEEE 5th International Conference on Cybernetics and Intelligent Systems (CIS), Qingdao, 2011, pp. 247-252. --Yetkin, H. et al, Gyroscopic Stabilization of an Unmanned Bicycle, IEEE 2014 American Control Conference (ACC) June 4-6, 2014. Portland, Oregon, USA --Keo, L. et al, Stabilization of an Unmanned Bicycle with Flywheel Balance, 8th IFAC Symposium on Nonlinear Control Systems University of Bologna, Italy, September 1-3, 2010 G. Advance Modern Vehicle Chassis/Frames (Aerospace, Terrestrial and Naval) Open to aerospace engineering constituents as well. Structural design fundamentals leading up to vehicle body dynamic surface area design. ANALYSIS AND FIELD INVESTIGATION will be based on primitive models and their modern counterparts found into today’s modern vehicles. Catia use likely will be highly advantageous. There will be times where one moves between Catia, Patran + Nastran and Ansys. Catia sometimes yields some of the most intricate detail in vehicle make up of interest. Technical terms for a respective component and purpose(s) they serve Possible symmetries Structural analysis Applied materials Weight & weight distribution Crumple zones and impact absorption 1. As preliminary, chassis/frame design and structural members (if relevant) to be developed in CAD, then to be applied towards such six parameters. Note: in terms of the mentioned six parameters there will be comparative analysis for the structure elements considered, namely, primitive design forms of configured cylindrical poles and rods, versus those models that are quite modern https://www.environmentalengineering.org.uk/wp-content/uploads//media/Different-steel-grades-used-in-Volvo-XC60-body-structure.jpg Despite such given link, will also observe difference vehicle types concerning the six parameters (such as SUVs, All terrain, light and large aircrafts, naval, etc.). Consider what placement, suspending and fixing practices are necessary to incorporate engine orientation (combustion and electric), drivetrain orientation, transmission (if relevant), wheels with suspension, systems control, fuel configuration, passenger orientation, payload orientation. Incorporation of all such features with chassis/frame towards structural analysis would be a huge feet professionally. Concerning crumple zones and impact absorption will identify the forces applied for various collision scenarios, with consideration of the influence of the vehicle components housed in respective frame. Special software may be needed for such simulations, and will identify what specific materials types are required at certain areas of the frame. 2. Will have field observation and interactive investigation of actual aerospace and terrestrial vehicles (including the placement, suspending and fixing practices). 3. Bolting, fastening, welding techniques for body mounting (exterior surface geometry); body mounting on chassis, say, primitive types (rods, poles, etc.) and modern types (modern cars). 4. Bolting, fastening, locking techniques for interior design. Applies to aircraft as well. Such will also be field observation and interactive investigation. 5. Dynamic behaviour with FEM. Visual simulations development H. Modern Brake Design and Testing (i) Modelling “classical” brake systems using hydraulic and pneumatic components-- Initially, for the hydraulic and pneumatic systems will manually develop the system modelling (physics, ODEs, possible transient response, Laplace transform modelling, state space representation, etc.). Some components: Cylinders, direction control valves, fluid properties, types of pumps, sensors, etc. rotary actuators, etc., etc. Will model PID control, flow rate of fluid, pressure variation of cylinder, etc, etc.. (ii) Will develop simulations for a “classical” brake system and acquire target responses along with actual responses. System response in form of graphs. Including means to exhibit braking distance would be appreciated (if possible) to compare with basic physics models. (iii) Brakes are often described according to several characteristics (at least 10) --For characteristics that can be tied to quantitative modelling trying to confirm whether the associated models confirm that simulations are too ideal; characteristics are likely related. --Detailed design of braking systems can possibly be acquired through CATIA and probably Ansys. Will additionally try pursuing constructive investigation on most of such characteristics by use of CATIA and Ansys by involving interaction with models available (if possible). (iv) Will experiment with real system and have and actual responses concerning temperature, by analysis and replication of experimentation as described: --Dalimus, Z., Braking System and Brake Temperature Response Repeated Cycle, Mechatronics, Electrical Power, and Vehicular Technology 05 (2014) 123-128 Mathematica/SystemModeler substitution for Matlab/Simulink (v) Proceed with analysis of the following journal article: --Feldmanis, J., Mathematical Modelling of Brake Friction Lining Heat and Wear. Engineering for Rural Development, 7, Jelgava (Latvia), 29-30 May 2008, 2008, Issue 7, pp.236-241 How can one reconcile modelling in journal article of (iv) with the latter journal article? Such recent journal article can serve as a decent guide for experimentation. Preferably replicated, but system setup doesn’t have to be exact. Determine at what temperatures do conventional brake pads loose desired performance. (vi) Modelling electromagnetic brake systems Ming Qian and P. Kachroo, "Modeling and control of electromagnetic brakes for enhanced braking capabilities for automated highway systems," Proceedings of Conference on Intelligent Transportation Systems, Boston, MA, USA, 1997, pp. 391-396. Manually develop the system modelling (physics, ODEs, possible transient response, Laplace transform modelling, state space representation, etc.). Will model PID control, etc. (vii) Will develop simulations for a electromagnetic brake system and acquire target responses along with actual responses. System response in form of graphs. Including means to exhibit braking distance would be appreciated (if possible) to compare with basic physics models. Followed by modelling treatment of regenerative modules with accompanying experimentation concerning charging. (viii) Magnetorheological fluid disc brake --Ubaidillah et al., "Simulation and experimental studies on braking response of inertial load using magnetorheological brake," 2014 International Conference on Electrical Engineering and Computer Science (ICEECS), Kuta, 2014, pp. 353-358. Ansys is good to work with, but preference is not to be subjugated by Matlab. Journal article also provides a decent guide for experimentation to acquire data. As well, pursue means of acquiring such curves by the numerical methods considered, and as well those stemming from experimentation being compared to theoretical findings (if possible). --Attia, E. M. et al, Theoretical and Experimental Study of Magnetorheological Fluid Disc Brake, Alexandria Engineering Journal (2017) 56, 189–200 Journal article also provides a decent guide for experimentation to acquire data. As well, pursue means of acquiring such curves by the numerical methods considered, and as well those stemming from experimentation being compared to theoretical findings (if possible). In what ways are the former and latter journal articles harmonious and disjoint? Verify such. (ix) Eddy brakes I. Suspension analysis, testing and rail vehicles NOTE: there may be nonlinear properties, so extend to such if need be. Examples for assistance --> Ozcan, D., Sonmez, U. and Guvenc, L. (2013). Optimisation of the Nonlinear Suspension Characteristics of a Light Commercial Vehicle. Hindawi Publishing Corporation. International Journal of Vehicular Technology, Volume 2013, Article ID 562424, 16 pages Mohite, A., & Mitra, A. (2018). Development of Linear and Non-linear Vehicle Suspension Model. Materials Today: Proceedings, 5(2), 4317-4326. (i). Identify the essential components of vehicle modern suspension. Pursue derivation for the spring constant of a helical spring. Apart from the number of coils, wire diameter, and diameter of the coil, identify methods of determining the shear modulus. Identify various types of suspensions. Compare “heavy” vehicles to “light” vehicles, and observe what types of suspensions are applied respectively? (ii). Dependent suspensions. Differentiate between interconnected suspensions and semi-active/active suspensions. Suspension configurations for two-wheel drive, four-wheel drive and all-wheel drive in regard to beam axles and independent suspensions. (iii). Evaluation of wheel performance on soil: Hegazy, S., and Sandu, C., Experimental Investigation of Vehicle Mobility Using a Novel Wheel Mobility Number, Journal of Terramechanics 50 (2013) 303–310 Access to a single wheel tester and ability to carry out described experimentation would be great. (iv). ANSYS suspension analysis with different amounts of force applied. Must determine safety limit for suspension in question. (v). Mechanics of an active suspension control arm. Structural analysis and fatigue analysis for a suspension control arm. Treat different designs. (vi). Simulating Vehicle Suspension with a Simplified Quarter-Car Model The simplified quarter-car suspension model is basically a mass-spring-damper system with the car serving as the mass, the suspension coil as the spring, and the shock absorber as the damper. 1. The mathematics of the system are based on the differential equation of the spring-damper suspension. Solve the differential equation with appropriate initial conditions. Apply Laplace transform to yield a transfer function. 2. Quarter model simulation PART A Simulate via numerical methods with interactive ability to adjust suspension parameters and road condition parameters (road bump height and bump frequency). Use of Manipulate function in Mathematica http://demonstrations.wolfram.com/SimulatingVehicleSuspensionWithASimplifiedQuarterCarModel/ Understanding the physics and mathematics rather than plain code copying are crucial in the long run, else one will be a schmuck and appear highly incompetent. PART B Then apply TransferFunctionModel, OutputResponse and StateResponse functions to calculate the car movement with interactive ability to adjust suspension parameters and road condition parameters (road bump height and bump frequency). The developed simulation demonstrations allow one to investigate the effect of different suspension parameters and road conditions on the vertical motion of the car. PART C https://www.wolfram.com/language/12/microcontroller-kit/hil-simulation-of-a-quarter-car-suspension-model.html?product=language (vii). Quarter-Car Suspension Model with Double Spring Extend (iv) to such. Masses (m1 m2) Stiffness (k1 k2) Damping (c1 c2) Input type single bump or sinusoidal option height duration frequency (viii). Quarter-car models are ideal because roads are generally not laterally uniform like speed bumps at airports, etc. Is it possible to extend (vi) or (vii) to full-car? If so, implement. Analyse the following articles and pursue means to acquire the curves, time series, simulations, etc: --Pazooki, A., Rakheja S., and Cao, D.., Modelling and Validation of Off-Road Vehicle Ride Dynamics, Mechanical Systems and Signal Processing 28 (2012) 679–695 --Senatore, C., and Sandu, C., Torque Distribution Influence on Tractive Efficiency and Mobility of Off-Road Wheeled Vehicles, Journal of Terramechanics 48 (2011) 372–383 --Sharma, S. K., et al, Numerical Studies Using Full Car Model for Combined Primary and Cabin Suspension, Procedia Technology 23 ( 2016 ) 171 – 178. Note: SystemModeler or Modelica to replace Simulink. (ix). An example of development process: Passenger vehicle Suspension Design and Analysis in Maple – YouTube However, preference to be a Modelica language or environment to develop such. (x). Pursue facility resources for suspension testing. Each corner of the vehicle is tested for rebound, and yield a respective curve and corresponding rating. As well, possibly, if feasible there there’s also lateral variation testing. Various vehicle models to be studied, if feasible. Bearing no ill will to anyone, will try to find curves from testing yielding “firm”, “hard”, “very hard”, “soft”, “very soft”; will need axes and scaling print outs of such (or storable) to compare with simulations developed in (vi) and (vii). Will make various interactive parameter adjustments to observe what parameter values yield the curves from the suspension testing. PART D (Train Bogie) 1. Will be incorporating Mathematica, SystemModeler/Modelica after coherent and sustainable analysis. Some literature guides: Knothe, K. and Stichel, S. (2017). Rail Vehicle Dynamics, Springer, Cham Iwnicki, S. et al (2019). Handbook f Railway Vehicle Dynamics. CRC Press Jawahar, P. M. and Gupta, K. N. (1990). Mathematical Modelling for Lateral Dynamic simulation of a Railway vehicle with Conventional & Unconventional Wheelset. Math Comput. Modelling, Vol. 14, pp. 989-994. Garg, V. K. and Dukkipati, R. V. (1984). Dynamics of Railway Vehicle Systems. Elsevier C.P. Keizer (1987) Introduction to the Dynamics of Rail Vehicles, Vehicle System Dynamics, 16:sup1, 37-74 B. Ballew, B. J. Chan & C. Sandu (2011) Multibody Dynamics Modelling of the Freight Train Bogie System, Vehicle System Dynamics, 49:4, 501-526 2. To analyse and develop: Shrestha, S., Spiryagin, M. and Wu, Q. (2020). Real-Time Multibody Modelling and Simulation of a Scaled Bogie Test Rig. Rail. Eng. Science 28(2):146–159 J. Modelling and development of excavation vehicles and cranes PART A To become confident will start with design and development of “elementary school level” Hydraulic crane projects https://sites.google.com/bvsd.org/mccloud-2018-19/78-design-tech/student-choice-projects/engineering-and-architecture-projects/hydraulic-crane https://www.instructables.com/id/CARDBOARD-Robotic-Hydraulic-Arm/ PART B The given journal article provides a general idea of the microscale crane project to be pursued. Additionally, the structural loads of a construction crane (for all critical components) and operational capacity must be pursued prematurely via CAD and structural analysis software. Rubio-Ávila, J. J., Alcántara-Ramírez, R., Jaimes-Ponce, and Siller-Alcalá, I I. (2007). Design, Construction, and Control of a Novel Tower Crane. International Journal of Mathematics and Computers in Simulation. Issue 2, Volume 1 https://pdfs.semanticscholar.org/6741/8ea19da18309f65c4e70d1552fdbd8fbd01a.pdf PART C Then, to be concern with modern cranes constituted by truss members and jib sections. Will not be actually built, but will be modelled and analysed. Structural loads of for truss members, various jibs, pendants/rods, trolley, cables, etc. Findings must be consistent with the chosen industrial model for operational capacity PART D (excavator observation and analysis) 1. Field activity observing and analysing components and control of excavators 2. Component Definitions and Labelling Conventions 3. Governing statics (for the different configurations) 4. Modelling centre of gravity in different configurations 5. CAD and Structural Analysis with Ansys or Patran/Nastran. Complimented by the types of materials used for certain components concerning strength, durability, weight, oxidation, etc. 6. Cylinder Space to Joint Space Transformation 7. Forward Displacement Analysis 8. Reverse Displacement Analysis 9. Joint Space to Cylinder Space Transformation 10. Actuator Force to Joint Torque Transformation 11. Lagrangian Dynamics --Patel B. P. and Prajapati, J. M. Dynamics of Mini Hydraulic Backhoe Excavator: A Lagrange-Euler (L-E) Approach. International Journal of Mechanical, Aerospace, Industrial, Mechatronic and Manufacturing Engineering. Volume 8, Number 1, 2014 Will take on a Mathematica/SystemModeler environment. Will manually develop simulation and compare to SystemModeler module for backhoes/excavators. 12. Bucket Trajectory Simulation Patel B. P. and Prajapati, J. M. Evaluation of Bucket Capacity, Digging Force Calculations and Static Force Analysis of Mini Hydraulic Backhoe Excavator. Machine Design, Vol.4 (2012) No.1, ISSN 1821-1259 pp. 59 – 66 In such succession, from such journal article with pursue reconciliation with the Lagrangian approach encountered prior. 13. Modelling and control Will manually develop control for excavators. Then, will take on a Mathematica/SystemModeler or Modelica environment for simulation. assisting guides: -Xu, J. and Yoon, H. A Review on Mechanical and Hydraulic System Modelling of Excavator Manipulator System. Hindawi Publishing Corporation. Journal of Construction Engineering Volume 2016, Article ID 9409370, 11 pages -Zhang J. et al. (2010) Design of Intelligent Hydraulic Excavator Control System Based on PID Method. In: Li D., Zhao C. (eds) Computer and Computing Technologies in Agriculture III. CCTA 2009. IFIP Advances in Information and Communication Technology, vol 317. Springer, Berlin, Heidelberg. -Z. Jun et al., "Design of Electronic Control System of Hydraulic Excavator with CAN Bus and PID Method," 2010 International Conference on Intelligent System Design and Engineering Application, Changsha, 2010, pp. 570-573 -Q. Tu, M. Pan, J. Zhao and L. Qin, "Design and control of operating manipulator for excavator working device," 2012 IEEE International Conference on Computer Science and Automation Engineering (CSAE), Zhangjiajie, 2012, pp. 318-321. 14. Identifying in high detail powertrains (with performance parameters) that meet the demands of excavators. 15. Bringing it all together in a CAD and possible structural analysis for identification of possible vulnerabilities. Note: there are various models of backhoes. K. Building a Monowheel (TBA) L. TBA M. Engineering a 3D Printer # Part 1 DIY 3D-Printer Build (From Scratch)-YouTube Such a video comes in a part 1 to part 8 series. Such presentation and development have a layman’s terms tone. Such videos primarily to serve as guides and not to exactly mimic. Furthermore, one must determine whether embedded system or microcontroller(s) require a cooling system. Students should be aware there are different designs of different scales requiring different scale of motors, concerning size of projects they intend to pursue. Regardless, operating device should be optimal in energy usage and components. Certainty of proper voltage for respective device, etc. Again, one must determine whether embedded system or microcontroller(s) require a cooling system. For professionalism and knowledge of development independence, start with development in CAD. There will be choice of multiple objects to 3D print to put a 3D printer through its basis and benchmark it’s performance. Another example Arduino 3D Printer/Homemade-YouTube from RZtronics Such a video comes in a part 1 to part 3 series. Regardless of design, duration for completion of a printing project may or may not be a component in determination of performance. One should really concern themselves with programming that controls the motors and printing “pen”. Modelling actuation (physics, system equations, transfer functions, controllers, etc.) towards comprehension of “smooth” and competent behaviour. Apart from the feedback/automatic control one must comprehend the C/C++ programming instructions. Conceptual development and flow diagrams before writing and implementing programming instruction with developed feedback/automatic control. N. CNC Machine Development The term CNC stands for “computer numerical control', and the CNC machining definition is that it is a subtractive manufacturing process which typically employs computerized controls and machine tools to remove layers of material from a stock piece—known as the blank or workpiece—and produces a custom-designed part. Activity will be independent of any PLC course but doesn’t replace any PLC course Will focusing mainly on drilling, milling and turning development. Designs will vary term to term. NOTE: efficiency with control may be the biggest challenge. Appeasing industry tolerance levels may not be accomplished in this activity, but approaching that would be a great accomplishment. For the actuation components in unison, the ability to model them, identify the controllers and simulate tasks is crucial. Furthermore, simulators can’t overall account for the (geometrical) machine design impedance, the mass distribution and so forth on actuation components. What you simulate is really “simplified ideal motion functions” at most; resolution must be found Tangible sub-components applying to block diagram Servos, actuators, transmission/drivetrain schemes for position-velocity space Mechanic components relating to milling or turning Power supply and power electronics Cable track/cable tubes Structural members Cooling (if needed) Cutting fluid and lubricants (if needed) Block Diagram Input Devices – Part Programmes Machine Control Unit Data Processing Unit Control Loop Unit Display Unit Motion – Driving system Miscellaneous Function – Machine Tool Feedback System Position Feedback Velocity Feedback How does PLC come in? Understand what we’re configuring (software and other things) How configurations can adapter to your components Limits of your machines (sub-components in CNC machine, applicable materials, scale size tasks, etc.) What materials are suitable for your machines and what adjustments and precautions must be identified with resolutions. Two other crucial goals: 1. Even if the feedback system comes pre-developed, will still hypothesize and develop feedback based on design considered and machine tasks. Will test it in a simulator based on the essential components. How does it relate to data processing? 2. Even if the data processing unit is proprietary and pre-developed, will still hypothesize and consider what microcontrollers can be applied to develop a “bootleg” data processing unit. Will develop a beta experimentation processing unit for considered design and machine tasks. Will test it in a simulator based on the essential components. 3. Even if the feedback system comes pre-developed, will still hypothesize and develop feedback based on design considered and machine tasks. Will test it in a simulator based on the essential components. 4. Analysis of PLC components in function. Nevertheless, PLC programming based on design and machine tasks will be developed and tested in a simulator. CNC Machine Process: Designing the CAD model Converting the CAD file to a CNC program Preparing the CNC machine Executing the machining operation NOTE: Computer-aided manufacturing (CAM) and Computer-aided engineering (CAE) can be further fundamental required processes related to CAD Some assist guides: --Instructables. How To Make A 3-Axis CNC Machine (Cheaply and Easily) https://www.instructables.com/id/How-to-Make-a-Three-Axis-CNC-Machine-Cheaply-and-/ --Instructables. Building a CNC Router https://www.instructables.com/id/Building-a-CNC-router/ --Instructables. DIY Desktop 5-axis CNC Mill: 8 Steps https://www.instructables.com/id/DIY-Desktop-5-axis-CNC-Mill/ --D. P. Desai and D. M. Patel, "Design of Control unit for CNC machine tool using Arduino based embedded system," 2015 International Conference on Smart Technologies and Management for Computing, Communication, Controls, Energy and Materials (ICSTM), Chennai, 2015, pp. 443-448. --Xueguang LI, Pan YANG , Zhe CHEN and Liqin MIAO. The Modular Design and Analysis of Open CNC System Machine. MATEC Web of Conferences 220, 08003 (2018). The 2nd International Conference on Mechanical, System and Control Engineering (ICMSC 2018) --Altintas, Y. et al. Machine Tool Feed Drives. CIRP Annals-Manufacturing Technology 60 (2011) 779 – 796 --Feng, W. et al. (2014). Design and implementation of Five-Axis transformation function in CNC System. Chinese Journal of Aeronautics. Volume 27 Issue 2 Pages 425 – 437 Other pursuit --> Valentina E. Garcia, Jamin Liu, Joseph L. DeRisi. (2018). Low-Cost Touchscreen Driven Programmable Dual Syringe Pump for Life Science Applications, HardwareX, Volume 4, 2018, e00027 O. Unbalance Detection Critical speed analysis to be performed to determine the operating speed with sufficient separation margin. The unbalance response analysis is compared with the experimental results considering the balancing grade (ISO 1940-1 or whatever) and predicted vibration displacement with and without balancing. Based on these results, to successfully analyse the dynamics of a high-speed motor/generator or rotating system. For the given articles theoretical and analytical structuring will be analysed. As well, to develop the experimentation as close as possible and analyse. Such activities have great use to mechanical, aerospace, electrical and industrial engineering. (i). Primitive simulation guide: < http://blog.wolfram.com/2016/03/07/balancing-rotating-machinery-with-wolfram-systemmodeler/ > (ii). Heindel, S., et al, Unbalance and Resonance Elimination with Active Bearings on a “Jeffcott Rotor”, Mechanical Systems and Signal Processing 85 (2017) 339–353. Here, the Jeffcott Rotor may be something that can’t exactly be acquired, yet a rotor that’s highly similar should suffice. (iii) Heindel, S., Muller, P., C., and Rinderknech, S., Unbalance and Resonance Elimination with Active Bearings on General Rotors, Journal of Sound and Vibration, Volume 431, 29 September 208, pages 422-440 (iv). Hong, D., et al, Unbalance Response Analysis and Experimental Validation of an Ultra High Speed Motor-Generator for Microturbine Generators Considering Balancing, Sensors 2014, 14, 16117-16127 (v). Corres, J., M., et al Unbalance and Harmonics Detection in Induction Motors Using an Optical Fiber Sensor, IEEE SENSORS JOURNAL, VOL. 6, NO. 3, JUNE 2006 (vi) Stoesslein, M., Axinte, D., A, and Guillerna, A., B., Pulsed Laser ablation as Tool for In-situ Balancing of Rotating Parts, Mechatronics, Volume 38, September 2016, pages 54-67 NOTE: balancing machines will be built Live 2 Plane Balance -YouTube: https://www.youtube.com/watch?v=nmKPvMJ1Wno https://www.instructables.com/Simple-Rotor-Balancing-Machine/ Note: unless a particular motor or generator is specified for a respective article, make use of a common generator/motor experiment set-up with comparative analysis for experimentation from articles. Open to electrical engineering P. Replicating the following system: Design and Implementation of Real-Time Vehicular Camera for Driver assistance and Traffic Congestion Estimation. Analysis of the following --> Son, S., & Baek, Y. (2015). Design and Implementation of Real-Time Vehicular Camera for Driver Assistance and Traffic Congestion Estimation. Sensors (Basel, Switzerland), 15(8), 20204–20231. To then develop and run such system as close to the realistic system as possible. For section 5.1 to have Raspberry Pi, or Arduino or other in stack as substitute. Special invitation for constituents of computer science. Q. Design and construction of micro floating vessels subject to high speeds. Naval architecture for big vessels. Vessel construction. HARSH “BOOTCAMP” PART A (i) Length of vessel be at least four feet concerning sturdy vessels exposed to realistic natural water dynamics. Designs of focus will be rigger, hydroplane, jon boat, speed boat. The often-understood critical areas: 1. Ibrahim, R., A. and Grace, I., M., Modelling of Ship Roll Dynamics and its Coupling with Heave and Pitch, Mathematical Problems in Engineering, Volume 2010, Article ID 934714, 32 pages. 2. System Modelling and simulation The relevancy of stage (1) should be established in development towards simulation. 3. Design with dimensions in CAD for body geometry and body foundation. Students must understand the design of building components and how such in unison efficiently constitute the respective vessel’s body. The following is a quite constructive demonstration of CAD towards accessible and/or tangible development with personal projects 2010 05 10 11 39 Jet Boat Recording -YouTube 4. Then pursuit of a CAD model that accounts for placement for components concerning vehicle control based on system modelling & simulation and control, and time instantaneous sensing (gyro and speed primarily). Additional details issues of determining centre of gravity, buoyancy and body mechanics based on engine/motor configuration, shaft with bearings, prop, steering, power supply, sensing configurations, etc., etc.. As well, means to apply structural analysis with all such. Case of the electric motor involves motor control and speed control. For certain components insulation against water is a necessity. Velocity sensing w.r.t time. Gyroscope sensing w.r.t time. concerning rotations among the pitch, roll and yaw axes. Both velocity sensing and gyroscopic sensing must be synchronised in time. Such two types of data must be retrievable. 5. Development to then be analysed for aerodynamic and hydrodynamic properties, respectively, with use of Ansys CFX or OpenFoam . 6. For certain components insulation against water is a necessity, and those not exposed to drastic engine/motor heat.. Constructed vessel components are professionally and accurately developed or crafted. Consideration of various choices of polymer, PVC, carbon fiber, wood. 7. After successful construction of boat there will be designed sailing path plan towards interpretable data collection. Interaction between vessel in motion and respective water environment at various speeds, involving roll, heave and pitch. Stability in change of direction. One should also have determination of the (relative) power, momentum and speed of waves “on average” of the respective ambiance they are in interested in (if attainable). Wave element to be the scale of vessel length and vessel width, respectively; build up wave elements to such size in experimentation. Consider the length (or width) of vessel as a line element. Based on such, “local” power and “local” momentum values can be acquired. 8. Data will be compared among models developed from (1) and (2) towards learning and future upgrading attempts. Identify “curve or data properties” that will indicate whether vessel has competent performance overall when compared to ideal model. (ii) Marine Propellers 1. Will identify the various types of customary marine propeller designs applied to vessels, ranging from small fishing boats, large fishing vessels, speed boats, yachts, cruise ships, tugboats, ice cutters, military carriers, submarines. Will treat variable pitch models as well. 2. Will treat the hydrodynamics, geometry definitions with observation for each type of propeller, Navier-Stokes governance with boundary conditions pertaining to surface geometry and ailerons, and CFD. Will consider various different propeller types having the same length in propeller blade radius and based on hydrodynamics, modelling, Navier-Stokes and CFD will determine why a particular propeller is preferred for a particular type of vessel; structural analysis if there’s relevance to such. 3. Analysis and logistics with modelling, computation, process design and simulation for marine propellers and propulsion. The following text can serve as a strong guide for propeller design and efficiency, however, there’s no intention of reading 609 pages: Carlton, J. S. (2018). Marine Propellers and Propulsion Butterworth-Heinemann, 609 pages FAO. Technical Measures - http://www.fao.org/3/x0487e/x0487e04.htm Propellers have to be designed in a way to reduce noise and vibrations and hence cavitation to the lowest possible level in order to achieve propeller efficiency. Modifications made in the basic propeller geometries do not change the way we determine and analyse propeller performance. 4. Analysis and logistics with modelling, computation, process design and simulation for marine propellers and propulsion. Will also make use of OpenProp and Ansys BladeModeler PART B (i) Consider the following journal article: Lee, K., Ku, N. and Cha, J., Undergraduate Courses for Enhancing Design Ability in Naval Architecture, Int. J. Naval Archit. Ocean Eng. (2013) 5: 364 - 375 The objective is to administrate such within the 7 - 12 week activity along with the other described phases throughout. There is no focus on competition or placing. Note: will include strong immersion with DELFTship and structural analysis. (ii) Concerning different ship models of different scales students will be asked to investigate the hull design and structural integrity (structural loads); whether a given material will serve well structurally and for performance in terms of roll, pitch, yaw in variations w.r.t. particular weather/oceanic environments, and economics. Materials to investigate: Wood, carbon fiber, fiber glass, aluminium, steel, titanium (iii) Challenge (optional and time permitting) Students can extend (ii) to consider use of multiple materials applied to specific vessel geometry and components towards performance vs. strength; scale will likely play a huge factor. A major interest will be FEA and structural loads. PART C Design and construction of passenger aluminium boats. 1. Reviewing the following: --The Maritime Engineering Reference Book: A Guide to Ship Design, Construction and Operation, Chapter 4 Ship Structures, Pages 116, 118-180, Edited by Anthony F. Molland, Elsevier Science & Technology, 2008. --Ibrahim, R., A. and Grace, I., M., Modelling of Ship Roll Dynamics and its Coupling with Heave and Pitch, Mathematical Problems in Engineering, Volume 2010, Article ID 934714, 32 pages From such two sources above one must identify the relations and consistency between them. To then be followed by, 2. Single bottom structure design and construction Focus is aluminium boats. Choice of models to pursue out of: Rigger, Launch, Jon boats, Trimaran, Rodney, Skiff, Flat-bottomed. Vessels must be able to hold at least four passengers. Structural frame for strength, durability, weight, COG (with constituents for operation, sensing, steering, control), buoyancy etc. for the respective type of boat. Being content only with the easiest types of boats for design and construction, long term, only plays directly into limitations on knowledge, and inexperience will remain. There will be observation and analysis of stiffening in boat structural frame construction. Stiffening a ship by two means (to make a choice depending on type of boat): Transverse Stiffening Longitudinal Stiffening From such two types of stiffening students must identify the crucial structural components involved and geometries. Will sensitively identify detailed structural components and the geometries, contortions at various points, components for support and various holes (such as manholes, scallops, drain holes, etc.) wherever applicable. Why is longitudinal framing used when we could easily have provided transverse framing in longer ships too? Design to restrict bending (hogging and sagging), buckling and torsion. CAD for stiffening with be based on design from DELFTship. Will make extensive use of CAD for virtual design and virtual construction, then transfer to Patran/Nastran and ANSYS; must be able to develop structural analyse for intersecting, interconnected, joined areas, areas applying weigh and so forth. Based on the material characteristics of aluminium to determine what possible issues may arise concerning bending (hogging and sagging), buckling and torsion. Then from prior CAD development to then apply aluminium plating toward making the hull…then transferred back to Patran/Nastran and ANSYS for FEA structural analysis/structural loads. The principle design criteria must be decided based on all possible modes of failure, at various load cases, analysed by efficient and certified FEA tools, so as to attain a safe and economical factor of safety for the structure, from all possibilities of failures at sea. After completing such to proceed with hull hydrodynamics (OpenFoam or Ansys). By modelling and computation students must determine why structural bottom will float with anticipated max weight of top structure design, passenger weight, fuel, load, engine(s), steering and manoeuvering systems, communications, etc, etc, etc. applied. 3. Construction of single bottom design with aluminium based on (1) and (2) With data from (1) and (2) one may acquire the geometrical scale parameters, then proceed with construction. The following text can serve well in manufacturing: Welding Practices and Testing Welds, Ship Construction, 7th edition, Elsevier 2012, by D. J. Eyres et al. 4. Design of boat top structure This may be the most difficult part. Can be based on DELFTship and extensive use of other CAD for sensitive geometry details development. For any wiring or placement concerning devices for reads, manoeuvring, communication, etc., etc., etc. such must be accounted for. As well, finished design will be subjected to structural analysis and aerodynamics analysis via Patran/Nastran and ANSYS. 5. Construction of boat top structure. Text of D. J. Eyres et al prior may have some value to some extent here as well if welding applies. 6. Acrylic or other polymer transparent viewing integration, systems integration, fuel chamber integration 7. Rudder, Steering, Engine, Propeller integration. Static testing station for systems, steering and engine. 8. Water trial runs after full construction Velocity sensing w.r.t time. Gyroscope sensing concerning rotations among the pitch, roll and yaw axes w.r.t time. Both velocity sensing and gyroscopic sensing must be synchronised in time. There will be designed sailing path plan towards interpretable data collection. Interaction between vessel in motion and respective water environment at various speeds, involving roll, heave and pitch. Stability in change of direction. Involves gyroscope testing data and velocity data compared to ideal control model under various ambiance scenarios. An installed compass would be nice as well, apart from communication system and GPS. The following is an extravagant example (which will not be pursued): How to Build a 27 Aluminium Cabin Cruiser From a Kit - YouTube A more likely honest development at first go (just an example): Building Aluminium Boats 10 - YouTube PART D Types of roll stabilization systems used for ships 1. Bilge keels 2. Fixed fins 3. Active fins 4. Anti-rolling tanks 5. Gyro stabilization All systems concern lab and field development for verification. Various identical prototype crafts will be built to a certain scale to fairly compare efficiency of each stabilization system. The issue may be generating virtually identical wave types to fairly compare them. System (4) to will require uncorrelated development due to its components in unison that will drastically exceed scales of the other “competing” systems. System (3) likely will not be possible in lab and field due to scale considered with the necessary system integration. Gyroscope sensing data and speed data are necessities. For (1) and (2) their design will be thoroughly investigated for respective scale considered towards stability analysis. Especially for (2), hydrodynamics (similar to aerodynamics) in design is crucial. As well, construction material, weight distribution and fixing are crucial. Structural analysis is also crucial to determine structural integrity requirements concerning avoidance of hull damage/failure. Concerns: zero, low speeds and high speeds. How will it perform at various speeds, turning and combination? Concerning (4) there will passive and control passive types to develop. Developing passive designs are relatively easy as long as one can develop small scales component designs to construct. I’m not asking for a naval yard; it’s just fundamental mechanical/civil construction to desired scale after competent engineering design and analysis. Control passive anti roll tanks. Servo-controlled valve system which controls the flow of air, hence very little power is required. When the valve is closed, passage of air from one tank to the other is prevented and the resulting compression of air in the tank prevents flow of water also. When the valve opens, free movement of water and air is possible. Must develop highly competent system to observe good influence. Concerning (3), despite not likely being able to have lab and field development one can have engineering analysis, simulation and control development. The actuation components are generally not unorthodox, so physically developing a pair may be feasible to design scale, however, water-proofing them is an issue, and one must understand how to competently integrate them into the hull without leading to structural failure and leakage (even without the presence of structural failure). Fins’ cross section will be no different to aerofoils of aircraft, but design that provides strong lift is wanted. Rotor shaft must be light but quite strong. Apart from design of fins, composition must be resilient to water flow stresses at high speeds. Fins, shaft and actuation system must not apply considerable weight. Are the fins autonomous? Gyroscope sensing incorporated with microcontrollers and actuation may be the key. Certain systems will need to be waterproofed. Gyroscope sensing for control may need to be totally different from gyroscope sensing for data. An imaginative of things, but systems don’t need to be this luxurious (servos in use are great however) --> Zhang S, You P, Zhao P, Liang L, Li R (2019) Experimental Study on the Control Form of Fin Stabilizer at Zero Speed. PLoS ONE 14(5): e0216395. Concerning (5), gyro stabilization, one should first identify the type that leads to roll stabilization, not attitude/pitch stabilization. The advantage of this system is that it doesn’t need gyroscope sensing for roll stabilization, namely, its behaviour in operation does its job; that other independent gyroscope sensing for data is still relevant. Once must know how to competently incorporate gyro into ship to function optimally. Yet, will increasing ship speed increase the efficiency of gyro? If so, then what? First, deriving a second order roll angel model for a ship and associated solutions. Concerns the following parameters: vessel mass, moment of inertia about the centre of mass, distance along the boat centerline from its centre of mass to its metacentre, and gravitational constant. The following articles are possible assists, and there’s need to clarify explicitly what many equations are --> Ibrahim, R., A. and Grace, I., M., Modelling of Ship Roll Dynamics and its Coupling with Heave and Pitch, Mathematical Problems in Engineering, Volume 2010, Article ID 934714, 32 pages A. K. Poh et al., Gyroscopic Stabilisation of Rolling Motion in Simplified Marine Hull Model," 2017 IEEE 7th International Conference on Underwater System Technology: Theory and Applications (USYS), Kuala Lumpur, 2017, pp. 1-6 Talha, M., Asghar, F. and Kim, S. H. (2017). Design of Fuzzy Tuned PID Controller for Anti Rolling Gyro (ARG) Stabilizer in Ships. International Journal of Fuzzy Logic and Intelligent Systems. Vol. 17, No. 3, pp. 210-220 NOTE: gyro and associated system devices would naturally require insulation from water. R. TBA S. Advancing exposure to Structural analysis, aerodynamics and hydrodynamics Software of interest --> Catia Patran + Nastran, ANSYS (fluent, CFX) Cart3d, OpenFOAM CAESES, DELFTship, Onshape, Salome (+ Netgen + Gmsh), Open Cascade Technology, BrisCAD, OpenProp Open to aerospace engineering and industrial engineering constituents. Activity assumes proficient experience with CAD development. Begins with basic importation and/or development of CAD models (likely from various sources). Catia is well renowned with access to geometries of complex modern mechanical marvels. Examples such as commercial jet turbine engines, manifolds, commercial vehicle structural architecture, drive trains with frame and suspension, and many many more. To make most or all property tools that will best serve interests during duration. MD Nastran Essential Skills: Incorporating a CAD Model into Patran or Finite Element Analysis – YouTube < https://www.youtube.com/watch?v=vr-VfTIqqSE > Further progress, say: MSC Nastran and Patran Basics, Training via the MSC Learning Center – YouTube Direct access to CAD geometry, supports for multiple FEA, thermal, aerodynamic and hydrodynamic solvers; post processing and reporting tools for easy results evaluation. Both Patran and Nastran will be used abundantly with numerous applications an cases where both solutions are applied to each other. Some kindergarten treatment concerns Linear static analysis (and superposition), Principle stress, bending stress, stress transformation, buckling, steady state heat transfer, transient heat transfer with phase change. Multidisciplinary structural analysis concern performing static, dynamic, and thermal analysis across the linear and nonlinear domains, complemented with automated structural optimization and embedded fatigue analysis technologies. Stresses, strain, advance nonlinear analysis, embedded fatigue, embedded vibration fatigue. Ultimately we want FEM/FEA for big vehicle/systems projects. CAD models will vary in level of difficulty where mechanical, thermal, aerodynamic hydrodynamic interests are pursued. Examples: wind turbines, various sea vessel propeller designs (sailing and submarines), intricate devices with convection as part of heat transfer, supersonic compressors, etc. Regardless of taking the FE Modelling and Simulation course or not, activity will pursue the mentioned details extensively as a means to acquire hands on free will experience for competency and retention towards professionalism objectives in the future. Such activity WILL NOT REPLACE the FE modelling and Simulation course. T. Sensor Instrumentation Open to all engineering majors, however such will not undermine the integrity and level of activity. Activities concern practical immersion into field resembling the described mechanical engineering course. Towards acquiring and retention of comprehension and skills, objectives will have highly practical applications towards operations and systems that are conventional to studies and commercial use. Will treat Verilog with possible use of high level programming language or Mathematica; those who know C can cope with C++ when needed. Such activity will serve towards a comfortable transition into designated engineering course, hence a student can take part in such activity before enrolling in the designated engineering course. Must acquire official approval for this activity where a certain level of background in courses and skills are required. Activity does not replace required course in engineering. Will make use of, programmable boards, modules, VHDL, FPGA, sensors, computers/laptops, etc. U. TBA V. TBA W. Lathe Operations 1. Extensive development in CAD before hands on action. 2. Sequence towards lathe use--> --Lathe Components --Power Requirements --Safety Procedures and Lubrication for operation --Installing a Cutting Tool --Positioning the Tool --Feed, Speed and Depth of Cut A centre lathe is an example of standard lathe because on this machine we can perform the following operations: (a) Turning taper turning, contour turning and form turning (b) Facing (c) Parting off (d) Knurling (e) Chamfering (f) Cutoff (g) Thread cutting (versus manual with round die + diestock) Note: Thread pitch Gauge for measuring threads (h) Grooving (i) Drilling (j) Boring (k) Reaming (l) Square holes NOTE: Internal Threading is also a concern (manually) Projects will be diverse towards interest in mechanical engineering, aerospace engineering, manifolds for various purposes, piping, fittings, etc. Note: certain projects possibly will be “orders” from other engineering activities, chemistry, physics, and planetary sciences. NOTE: other machining processes and tools can be incorporated. X. Vehicle Control with Modernization PART A (i) Idea of vehicle mechanics Yang, S., Lu, Y. and Li, S., An Overview on Vehicle Dynamics, Int. J. Dynam. Control (2013) 1:385–395 Chen, K., Pei, X., Ma, G., Guo, X., Longitudinal/Lateral Stability Analysis of Vehicle Motion in the Nonlinear Region, Mathematical Problems in Engineering, Volume 2016, Article ID 3419108, 15 pages (ii) Will review the constitution of some “classic” steering system. Will intimately observe how the constituents are integrated. (iii) Observation and analysis of a modern main (electric) steering system-- Primary side: steering wheel steering column universal joint torque sensor torsion sensor pinion Secondary side: BLDC motor ECU ballscrew inner track-ro ball joints drivebelt steering rack (or rack housing) Front axle: tie rod idler arm drop arm outer track-rod ball joints ball-joint steering swivel wheel. Will pursue physical observation of steering systems and observe intimately how they are assembled. (iv) Electric Power Steering System Will have intimate inspection of vehicles to confirm the existence of such components in (III) nd their integration towards function. (v) Compare/contrast between electric and hydraulic steering systems (vi) Modelling and Position Control of an Electric Power Steering System Govender, V. and Steffen Müller, S., Modelling and Position Control of an Electric Power Steering System, IFAC-PapersOnLine 49-11 (2016) 312 – 318 Analyse and pursue means of replicating displayed curves by developing the controllers and simulations. Is this article compatible with articles in (I)? For the controller design in a real vehicle identify what hardware, designed code/software are needed to “automate” such a controller design? Then proceed with means of curve replication; one can develop the system in a simulator. (vii) Presence of yaw with steering-- Sun, T. et al, Study on Integrated Control of Active Front Steering and Direct Yaw Moment Based on Vehicle Lateral Velocity Estimation, Mathematical Problems in Engineering Volume 2013, Article ID 275269, 8 pages. Apart from analysis for modelling and control with try to identify what types of common sensors, microcontrollers, embedded systems and actuators are in place and how they are integrated with control and programming. One can develop the system in a simulator. Based on one’s conclusions or findings with modelling analysis, hardware, controllers, etc., is such harmonic to what was established in (vi)? PART B (i) The influence of differentials How a Differential works? – YouTube Review of open differential versus locked differential detailing components, advantages & disadvantages. --Teja, N. S. et al, Design and Analysis of Differential Gear Box in Automobiles, International Journal of Mechanical Engineering and Technology (IJMET) Volume 8, Issue 5, May 2017, pp. 175–185 --> https://www.iaeme.com/MasterAdmin/uploadfolder/IJMET_08_05_019/IJMET_08_05_019.pdf Along with: --Kapoor, N. et al, Design and Stress Strain Analysis of composite Differential Gear Box, International Journal of Science, Engineering and Technology Research (IJSETR), Volume 3, Issue 7, July 2014 --> http://ijsetr.org/wp-content/uploads/2014/06/IJSETR-VOL-3-ISSUE-7-1881-1895.pdf Followed by: -- Antoni, G. (2014). On the Mechanical Friction Losses Occurring in Automotive Differential Gearboxes. The Scientific World Journal, 2014, 11. Consider the following demonstration tool: Como funciona um diferencial -YouTube https://www.youtube.com/watch?v=cw5Judofbc8 One will like to construct such demonstration tool out of real components, but incorporation of rpm sensors and torque sensors upon the wheels collecting data in a time continuous fashion. The perturbation mechanisms beneath can be made to operate in a smooth pattern that can be modelled; there will always be disparity in height position between each perturbation as they rotate, but with two cases: One wheel in rotational motion while other is static Both wheels have rotational motion Torque and rpm data can be compared alongside perturbation function model; torque and rpm for the perturbation mechanisms in continuous time should also be known. Based on data analysis one can possible develop model dynamics/kinematics of differential gearbox components based on acquired data; comprehend that such model isn’t generic. (ii) Torque Vectoring Torque Vectoring Differential - Explained – YouTube Direct field activity observation of such components in above video would be greatly appreciated. Elementary mathematical modelling for torque-vectoring: --Rill, G. Reducing the Cornering Resistance by Torque Vectoring, Procedia Engineering 199 (2017) 3284 - 3289. Additionally, provide introduction for oversteering and understeering resolutions. As well, consider the following modelling and simulation --> Vehicle Modeling and Simulation: Implementing a Torque-Vectoring Stability Controller – YouTube However, preference to be a Modelica language or environment to develop such. For such modelling and simulation above the preference is that a Modelica language environment be used for development. Y. Building basic terrestrial vehicles Phase 1- Off Road Go Kart – How to Build – YouTube Such above is a clean and easily comprehensible blueprint. Will try to replicate as close as possible with assistance from the following: 1. Power & propulsion system characterisation 2. Determine the spectrum for power, torque and rpm 3. Determine whether system with its components are optimal concerning power, torque and rpm. 4. Is a ECU required for best functionality? What would the ideal module? Analysis and modelling will be expected 5. Analysis of structural design of motorcycle Geometrical orientation towards weigh distribution CoG with and without passenger Structural analysis 6. Better design for structural frame of motorcycle? Weight, weight distribution, system components and resulting weight distribution, strength of structure 7. Will try to replicate as close as possible with assistance from the following: Jazar R.N. (2008) Steering Dynamics. In: Vehicle Dynamics: Theory and Application. Springer, Boston, MA, pages 379-454 Will also seek assistance from the following: Jazar R.N. (2008) Steering Dynamics. In: Vehicle Dynamics: Theory and Application. Springer, Boston, MA, pages 455-512 As well, in reality the following are difficult to investigate and treat without actual vehicles towards performance, reliability and tire longevity: Camber Caster Toe Scrub radius -- > steering axis inclination (or king pin inclination) -- > squirm 8. Determination of ideal passengers’ weight 9. Determination of spectrum for power, torque and rpm based on possible amendments from all prior (theory and analytical modelling versus simulation versus acquired lab data) 10. How many seconds will it take to reach 0 - 60 mph? Theory and analytical modelling versus simulation versus acquired lab data (subject to ideal passengers’ weight). 11. Determination of typical mileage based on possible amendments from all prior (subject to ideal passengers’ weight) Determine theoretical top speed. Speed sensing, odometer and fuel meter likely. Phase 2- The next phase maybe concerns development of a frame that supports well the integration of two speed go Kart transmission onto engine. Combine all three aspects: --Making a Bigger Two Speed Go Kart Transmission – YouTube --Building a YZ85 Shifter Kart – YouTube (Part 1 – Part 3), etc. --Riding the Finished YZ85 Shifter Kart – YouTube Thorough machine design with scaling for high performance. Isolated engines considered have known performance parameters, but when integrated to the “transmission” system the power, torque and rpm at “full throttle” must not fall below a certain percentage; otherwise “transmission” system will be labelled nothing more than an impedance. Will likely first have a test station to compare torque values with rpm or speed values for gear shifts. Will pursue harmony with Jazar’s texts (for steering and suspension). As well, in reality the following are difficult to investigate and treat without actual vehicles towards performance, reliability and tire longevity: Camber Caster Toe Scrub radius -- > steering axis inclination (or king pin inclination) -- > squirm Determine theoretical top speed (with passenger of certain weight). Speed sensing, odometer and fuel meter likely for vehicle. In the future, may extend to the following integrated into a vehicle: 3 speed and reverse go kart gearbox home made – YouTube Phase 3- Electric Vehicle: Build a 1000W Electric Gokart at Home- Electric Car – Tutorial – Part 1 – YouTube https://www.youtube.com/watch?v=sZYGW4SwXdk Build a 1000W Electric Gokart at Home- Electric Car – Tutorial – Part 2 – YouTube https://www.youtube.com/watch?v=DwNzn-_G5_M Have some premature gauge on what minimum speed the vehicle will yield. Determination of mileage w.r.t. described weight accumulation is possible before actual vehicle operation. Determine theoretical top speed. Speed sensing, odometer and batteries meter likely. 1. Power & propulsion system characterisation Includes analysis of voltage, current, power dynamic due to system components, and vehicle “electric drive system” expressed in source prior. 2. Identify the spectrum for power, torque and rpm 3. Determine whether system with its components are optimal concerning power, torque and rpm. 4. Is a BMS required for best functionality? What would the ideal module? Analysis and modelling will be expected 5. Analysis of structural design of motorcycle Geometrical orientation towards weigh distribution CoG with and without passenger Structural analysis 6. Better design for structural frame of motorcycle? Weight, weight distribution, system components and resulting weight distribution, strength of structure 7. Will try to replicate as close as possible with assistance from the following: Jazar R.N. (2008) Steering Dynamics. In: Vehicle Dynamics: Theory and Application. Springer, Boston, MA, pages 379-454 Will also seek assistance from the following: Jazar R.N. (2008) Steering Dynamics. In: Vehicle Dynamics: Theory and Application. Springer, Boston, MA, pages 455-512 As well, in reality the following are difficult to investigate and treat without actual vehicles towards performance, reliability and tire longevity: Camber Caster Toe Scrub radius -- > steering axis inclination (or king pin inclination) -- > squirm 8. Determination of ideal passengers’ weight 9. Determination of spectrum for power, torque and rpm based on possible amendments from all prior (theory and analytical modelling versus simulation versus acquired lab data) 10. How many seconds will it take to reach 0 - 60 mph? Theory and analytical modelling versus simulation versus acquired lab data (subject to ideal passengers’ weight). 11. Determination of typical mileage based on possible amendments from all prior (subject to ideal passengers’ weight) Phase 4 (electric motorcycle) - Intelligence --> McFadden, C. (2021). A Guide to Building your Own electric “Streetfighter” style Motorcycle. Interesting Engineering: https://interestingengineering.com/video/build-your-own-electric-streetfighter-style-motorcycle Building an Electric Streetfighter Motorcycle – Complete Build & Test Ride – YouTube Engineering --> 1. Nonholomic Dynamics of a motorcyle 2. Power & proplusion system characterisation Acknowledging operational voltage, current, power dynamic, and vehicle “electric drive system” expressed in source prior 3. Analysis of applied motor Analytical methods of predicting rpm, torque, current, and torque-rpm relationship. Predicting peak and average supply current and efficiency. 4. Is a BMS required for best functionality? What would the ideal module? Analysis and modelling will be expected 5. Motor-wheel test Develop test station concerning torque and RPM and current. For rpm it’s either a laser tachometer or hall effect tachometer. As well, for torque measurement, a scheme that’s not a hindrance to performance. Quite obvious for current. will hive time dependent curves and the torque-rpm relationship curve. 6. Analysis of structural design of motorcycle Geometrical orientation towards weigh distribution CoG with and without passenger Structural analysis 7. Better design for structural frame of motorcycle? Weight, weight distribution, system components and resulting weight distribution, strength of structure 8. Determination of ideal passenger weight 9. Determination of spectrum for power, torque and rpm based on possible amendments from all prior (theory and analytical modelling versus simulation versus acquired lab data) 10. How many seconds will it take to reach 0 - 60 mph? Theory and analytical modelling versus simulation versus acquired lab data (subject to ideal passenger weight). 11. Determination of typical mileage based on possible amendments from all prior (subject to ideal passenger weight). Lab & Field Development --> Prototypes will be developed and constructed based on prior gathered intelligence and engineering. Z. Torque Vectoring for Electric Vehicles This activity concerns developing a “micro scale” vehicle with torque vectoring distribution to test in the field. To design a electric vehicles to scale where lateral and longitudinal stability become relevance. There will be two design cases: (1) Front wheels driven by a single motor with gear box; back wheels to have identical configuration (2) All wheel configure, say, each wheel has its own motor and gearbox Both cases to require programming for motor control, where each wheel will contribute harmoniously towards lateral and longitudinal stability. Will pick or design various drives courses constituted by moderate and radical archs. Vehicles will be RC controlled to operate at various speeds. Can also include high-banked test tracks with appropriate speeds. Motor controllers should be reprogrammable; it may be the case that various schemes perform well; hence comparative data analysis is required. For each course track, if different schemes are attainable, such schemes should be compared based on the track course operated on. Each course track may require multiple trials where each run requires vehicle inspection after for fairness. All vehicles will have the following sensing: speed Forward & backward acceleration gyroscopic motion gyroscopic velocities gyroscopic accelerations Some review: Yang, S., Lu, Y. and Li, S., An Overview on Vehicle Dynamics, Int. J. Dynam. Control (2013) 1:385–395 Chen, K., Pei, X., Ma, G., Guo, X., Longitudinal/Lateral Stability Analysis of Vehicle Motion in the Nonlinear Region, Mathematical Problems in Engineering, Volume 2016, Article ID 3419108, 15 pages Some torque vectoring guides: -De Novellis, L. Wheel Torque Distribution Criteria for Electric Vehicles With Torque-Vectoring Differentials. IEEE Transactions on Vehicular Technology, Vol. 63, No. 4, MAY 2014 -Wong, A. et al. Integrated torque vectoring and power management framework for electric vehicles. Control Engineering Practice 48 (2016) 22–36 -Koehler, S., Viehl, A., Bringmann, O., & Rosenstiel, W. (2017). Energy-Efficiency Optimization of Torque Vectoring Control for Battery Electric Vehicles. IEEE Intelligent Transportation Systems Magazine, 9(3), 59-74. -Chatzikomis, C. et al. An energy-efficient torque-vectoring algorithm for electricvehicles with multiple motors. Mechanical Systems and Signal Processing 128 (2019) 655 - 673 Simulation guides: The following links provide a more “block structuring view”. However, one isn’t confined to a MATLAB environment when it comes to Modelica and C: -Vehicle modelling and simulation: implementing a torque vectoring stability controller - YouTube: < https://www.youtube.com/watch?v=Cg0R7JsLvLQ > -Torque Vectoring: Controller Design, Tuning, and Testing: https://www.mathworks.com/videos/matlab-and-simulink-racing-lounge-torque-vectoring-controller-design-tuning-and-testing-100567.html NOTE: Integration with hardware architecture and sensors will be a great accomplishment. ACTUAL FIELD ACTIVITY FROM DEVELOPMENT. AA1. Gear systems Open to IE constituents Mechanical systems with configurations constituted by gears, shafts, bearings, chains and belts. --Range of gears: Spur, Helical, Herringbone, Double Helical, Spiral Bevel, Straight Bevel, Miter, Internal, Worm, Rack & Pinion, Planetary, Clutches, Differential, etc., etc. --Range of bearings: deep grove ball bearing, angular contact ball bearing, fluid bearing, magnetic bearing, Flexure bearing, roller bearing, bearing block Mechanical design, CAD development, structural analysis, failure analysis and reliability engineering will be applied. PART A Will place much emphasis on gear ratios with pitch matching, pressure angle matching, proper levelling & accurate fitting, and resulting kinematics. Gear ratios, angular velocity relation, rotation inertia relation, torque relation for different gear systems types. Note: for each system with pitch matching and pressure angle matching (perfectly configured) in a system will establish conservation of angular momentum. Will pursue analysis of how rotational inertia of different geometry bodies influence relations. Will construct various mechanical setups in CAD. To place gears correctly, the first step is to compute the centre distance. The position of the second gear can be found by a system of equations. Once the second gear is placed at the correct location, the next step is to align the teeth, or in this case mesh, of both gears. To accomplish this task, rotate the second gear with a mesh alignment angle whose formula involves mesh cycles and teeth numbers. Involute profile/curve. The tooth shape and size are specific to the gear’s application, so a different application would require another type of gear tooth. The following link, although from COMSOL it generally describes most CAD tools for gears towards professional construction: https://www.comsol.com/blogs/how-to-build-gear-geometries-in-the-multibody-dynamics-module/ It’s best that one practices development with various gear systems types. PART B Will determine efficiency of gear systems. Will be pursuing characteristic maps and efficiency factors based on statstical techniques and numerical methods tchniques from experiments. Extensive use of CAD to determine geometrical data (features and design angles w.r.t. size), along with mechanical engineering databases for material properties and behaviour. The following may service as great assistance : Gear Efficiency (Kevin Lynch) – YouTube https://www.youtube.com/watch?v=vVg8jb5vaMI Gear Efficiency Part 1 (Roland Larsson) – YouTube https://www.youtube.com/watch?v=gSOA6xgNi1Q Gear efficiency Part 2 (Roland Larsson) – YouTube https://www.youtube.com/watch?v=d912z-ygqi0 Diez-Ibarbia, A., del Rincon, A.F., Iglesias, M. et al. Efficiency analysis of spur gears with a shifting profile. Meccanica 51, 707–723 (2016). Will also extend to other gears PART C -Will also pursue structural analysis -Survey of the methods to apply failure analysis (walk throughs for experimentation development with typical data used for analysis). -Reliability modelling Extensive use of CAD to determine geometrical data (features and design angles w.r.t. size), along with mechanical engineering databases for material properties and behaviour. As well, may or may not pursue experimentation. Some possible helpful guides: Enjun Bai et al, "Reliability Modeling and Estimation of the Gear System", Mathematical Problems in Engineering, vol. 2018, Article ID 9091684, 9 pages, 2018 Zuo, Fang-Jun et al. (2015). Reliability Analysis of Gear Transmission with Considering Failure Correlation. Eksploatacja i Niezawodnosc- Maintenance & Reliability, 17(4): 617-623. S. Z. Lv, et al, "Reliability calculation model of gears considering strength degradation," 2009 16th International Conference on Industrial Engineering and Engineering Management, 2009, pp. 1200-1203 Da Cui, et al (2020), Reliability Design and Optimization of the Planetary gear by a GA based on the DEM and Kriging Model, Reliability Engineering & System Safety, Volume 203, 107074 Extend to general systems Yuan Z, Wu Y, Zhang K, Dragoi M-V, Liu M. Wear Reliability of Spur Gear based on the Cross-Analysis Method of a Nonstationary Random Process. Advances in Mechanical Engineering. December 2018. Extend to general systems PART D Then, physically constructed setups incorporating use of (aluminium) framing extrusions. An example (one of many possibilities) --> Types of Gears - YouTube https://www.youtube.com/watch?v=ihGFUAAwj7g However, will attempt to incorporate vibrational sensing, rpm and torque sensors without drastically reducing or hindering performance throughout. Will base our develop and anlysis on (A) through (C) PART E The next phase will be analysis and virtual intricate construction of industrial mechanical systems. Such include geared mechanical sharpeners, factory systems, conveyor systems, escalators, elevator systems, steam locomotives, electric trains, mechanical clocks. Students should be able to model how propulsion (electric, combustion) relates to transmissions and gear components. Will base our develop and anlysis on (A) through (C). Will pursue detail construction of mechanical modules into more complex systems. PART F Building gearboxes/transmisssions found in vehicles and other machinery. Concerning the following types of gearboxes/transmissions will acquire schematics and isolated components identification that constitute them. Autodesk Fusion 360 or Catia will serve well for sound observation and analysis along with field observation. There can be as well structural analysis if warranted. Such will be followed by prototype (mini) construction models mandatorily based on all prior (parts A through E) to the best of ability. Systematic and component models (ratios, mechanics, kinematics, kinematic ratios, efficiency factors, characteristic curves) when applied to a source that generates mechanical power (electric, fuel or manual labour): 1. Making a DRIVETRAIN and Installing the Micro V4 ENGINE on the RC Car - YouTube 2. Manual Transmission 3. Automatic Transmission 4. Rotorcraft Transmission 5. Motrcycle Transmission 4. Speedhub 6. Mechanical clock mechanism 7. More meaningfully advanced concoctions Likely to include machined or 3D printed components. The first pursuit will likely need a flat plate bottom chassis having a specific geometry with drilled holes and fitting placements to efficiently integrate the drive train (with engine, fuel chamber, etc.) involved. Else, a test station integrating ally such; likewise for the other pursuits. NOTE: all tobe pursued, and some components such as drive shafts and special fittings may or may not require ingenuity with machining. Interested in rpm and torque data for the various components to model the systems AA2. Fluid and Thermal Behaviour in (Civil) Engineering (check civil engineering post)

INDUSTRIAL ENGINEERING (some activities will also cater towards mechanical engineering, electrical engineering, civil engineering, operational research, revenue management and chemistry) A. Utilities data mining/management/ and forecasting Open to Electrical Engineering constituents (power) PART A (Empirical Analysis) Concerns electricity and water Examining an ambiance of concern in relation to its natural resources, and its utilities. Characterising the loads and energy consumption for various industries, urban and rural areas. Including supply failures, how do such vary among the seasons? Concerns 10-15 years. As well statististics for outages, respectively. Weibull, beta, gamma or Poisson modelling for outages and/or service restoration are also possible; will likely evolve due to properties from new data incorporated. Queue modelling for service restoration is also possible. A resonating issue of concern will be population dynamic over a determined duration (5 to 30 years) in relation to such issues, and a threshold point of breakdown in infrastructure. PART B (further stochastic utility modelling) Independent of the prior, to develop modelling of a respective utility (towards the ambiances of choice) in the form of the following: A. N. GIOVANIS and C. H. SKIADAS, A Stochastic Logistic Innovation Diffusion Model Studying the Electricity Consumption in Greece and the United States, Technological Forecasting and Social Change 61, 235–246 (1999). https://pdfs.semanticscholar.org/1838/e70306cd0aa96ba6fd4d03510fc847a0cad0.pdf For such SDE, its expectation model, variance model and standard deviation model. For such SDE will also pursue the probability density, to be “calibrated” with parameter determination from data; to be compared to density histograms. For SDE simulations use of confidence bands with recognition of optimal values. Compare empirical population dynamics with such prior model to determine compatibility (likely by distribution). Observe whether the empirical maximum and minimum energy consumption for time periods are consistent with the stochastic modelling. NOTE: water service counterpart is expected. PART C (quarterly time series anlysis) 1. For the past 10 -15 years quarterly, characterising data; whether there’s seasonality, trend, cyclic, etc.,). Forecasting future quaterly demand or consumption. For the past 10 - 15 years annually, characterising data; whether there’s seasonality, trend, cyclic, etc.,). Forecasting future quaterly demand or consumption. 2. Forecasting demand by mote carlo simulation (to be compared with time series prior). Some guides (also pursue electricity counterparts) --> -Blokker, E. & Vreeburg, J.. (2005). Monte Carlo Simulation of Residential Water Demand: A Stochastic End-Use Model. World Water and Environmental Resources Congress 2005 -Blokker, E. & Vreeburg, J. and van Dijk, J. C. (2010). Simulating Residential Water Demand with a Stochastic End-Use Model. Journal of Water Resource Planning and Management. Volume 136, Issue 1 -Tüzüntürk, Selim & Eren Şenaras, Arzu & Sezen, Kemal. (2015). Forecasting Water Demand by Using Monte Carlo PART D (ANN & PCA) Will develop such in the following journal article and compare with all prior methods --> Kheirkhah, A., Azadeh, A., Saberi, M., Azaron, A. and Shakouri, H. (2013). Improved Estimation of Electricity Demand Function by Using of Artificial Neural Network, Principal Component Analysis and Data Envelopment Analysis. Computers & Industrial Engineering. 64. 425–441. Annually, for maximum and minimum consumption (residences, businesses, public administration, respectively) is there correlation to any other quantitative measure such as population, holidays, venues, etc? PART E (Policy generation) To construct an operational supply policy that limits the amount of customer dissatisfaction or complaints. NOTE: past activities of this project in the future to be archived, where past student developed code is to be concealed away from those without experience in this project. Newly acclimated students are obligated write and improve their programming skills. Past data however, can be integrated with modern data for a grand picture towards models provided in the given link. Apart from engineering constituents, activity is open to Operations Management via special invite. B. TBA C. Four-phase water purification system Research project will benefit from constituents of other fields of engineering (Mechanical, Electrical, Computer and Civil) and Chemistry. Contesting water sources: tap water, river water, sea water, waste water. Each type of water will have its own purification system. Will have a manual control valve in front of everything; basic logic applies to its use. Solenoid valves to be quite useful throughout. 1. Through a screen sieve set of four different mesh sizes in decreasing order. 2a. Built filtration system where first layer to be large gravel, then fine gravel, coarse sand, fine sand, activated charcoal, through a screen sieve set, then towards low budget commercial filters. Filtration system: large gravel –> fine gravel –> coarse sand –> fine sand –> activated charcoal --> screen sieve set –> commercial filters Configured to use multiple filter paths beneath say, one main pipe branching into other pipes reaching a respective filter. Then, all lead towards H2O2 processing chamber. 2b. To develop a sensor-pump system to determine when water level is appropriate to be transferred to H2O2 processing chamber. 3a. Processing with H2O2 Disintegration of organic mass Disinfection Precipitation of impurities and harmful chemicals Chemistry of such three processes must analysed. Must acquire the duration to complete the respective process (three processes in total), then determine the optimal duration to account for completion of all processes; will concern analytical, modelling and simulation activities. Chemical or pollutant speciation may be tricky due to wide range; however, one can brain storm likely pollutants in black swan environmental accidents and determine a max duration range. Determine what concentration percentage of H2O2 is required; likely higher than conventional store-bought H2O2 solutions. As well, one must consider the volume the chamber holds in total, hence, one must consider what H2O2 concentration is necessary to treat chamber’s volume when mixed. Now, rather than constantly buying highly diluted H2O2 (around 3%) one can synthesis H2O2 that’s more potent (up 10%). Such will be done by electrosynthesis/electrochemical methods. Hence, there will be an integrated module in system for H2O2 production. One would like a production rate that’s economic w.r.t. power source for H2O2 production process. One major concern may be the type of water needed that will not have by-products undesired; or how to isolate unwanted by-products. Economically, water to be treated in purification process must be greater than H2O2 batch production. Another major concern for H2O2 production and collection is assurance of desired potency before integrated into water to be treated without destroying or weakening the H2O2 production batch. One would like autonomous function for H2O2 synthesis, sensing (accumulation, potency without destroying/weakening volume) and transfer regulation. Some guides to develop and construct H2O2 synthesis contraption --> Drogui, P., Elmaleh, S., Rumeau, M. et al. Hydrogen peroxide production by water electrolysis: Application to disinfection. Journal of Applied Electrochemistry 31, 877 – 882 (2001). Gyenge, E., Oloman, C. Electrosynthesis of hydrogen peroxide in acidic solutions by mediated oxygen reduction in a three-phase (aqueous/organic/gaseous) system Part I: Emulsion structure, electrode kinetics and batch electrolysis. Journal of Applied Electrochemistry 33, 655 – 663 (2003) Verdaguer-Casadevall, A. et al. Trends in electrochemical Synthesis of H2O2 :Enhancing Activity and Selectivity by Electrocatalytic Site Engineering. Nano Letters 2014 14 (3), 1603 -1608. Murray, T. et al. (2019). Electrosynthesis of hydrogen Peroxide by Phase-Transfer Catalysis. Joule Journal Volume 3 Issue 12, Pages 2942 - 2954 Then through a screen sieve set of four different mesh sizes in decreasing order. Processed liquid to then reach multiple filter paths beneath say, one main pipe branching into other pipes reaching a respective filter. There can be vials or beakers for demonstration of H2O2 with disintegration, disinfection, precipitation of impurities, respectively. Disintegration exhibition may require some microscopy set up amplifies to a projection or something. Audience can come back to observe final result. 3b. A sensor-pump system to determine when water level is appropriate to be transferred to photocatalyst chamber. 4. To then be pumped towards photocatalysis treatment towards a storage chamber: M. J. Wu, T. Bak, P. J. O’Doherty, et al., “Photocatalysis of Titanium Dioxide for Water Disinfection: Challenges and Future Perspectives,” International Journal of Photochemistry, vol. 2014, Article ID 973484, 9 pages, 2014. Leong, S. et al, TiO2 Based Photocatalytic Membranes: A Review, Journal of Membrane Science 472 (2014) 167–184 Lynch, L. (2016). Photocatalysis with a Raspberry Pi. Raspberry Pi Blog Again, there are numerous alternatives to Raspberry Pi Processing systems are constructed in a manner where one can extractsamples from each phase. Tools of concern: liquid level sensors, solenoid valves, voltage regulatorsconvertors, current regulators/converts, microcontrollers, relay modules, PLC, multimeter, oscilloscope with port interface towards software and laptop/computer for wave forms and data acquisition. --For DC supply (as secondary power source), to configure system to lock off water from purification system, diverted away from system when batteries are at a threshold low in power supply. --For AC supply (as primary power source), to have similar configuration system. There may be cases where AC voltage may change, thus such must be accounted for. AC supply should have circuit that routes to DC operation above. AC must provide charging to DC source, where when fully charged should disengage charging. System should also be able to run solely on AC. If AC goes out, then DC should automatically kick in, where DC system to lock off water from purification system, diverted away from system when battery is at a threshold low in power supply. --Concerns all electric circuits being insulated (from water/moisiture exposure, contact with voltage, stray voltage, etc.). Initially, each phase system to be independently constructed as prototypes and analysed, where at least three samples for each phase are collected. Includes respective operation duration, respective energy consumption, etc. The four-phase water system must be set up in a matter where each phase is considerate of each other, and knows how to regulate itself respectively. CAD design initially for system chanelling components with integration. Actuation components identification and specifications. Transfer functions, controllers, actuators, etc. Design appropriate process control system and virtual model with accommodating simulations via COCO (+ ChemSep), DWSIM (+ ChemSep), SystemModeler NOTE: between each phase will make use of solenoid control valves. Typical control for chambers (may or may not be complicated or exactly right for objectives): The tank will start filling (via a valve) whenever the start process button is enabled and the tank is below 50% full. It will shut off when the tank is 100% full. In case the level sensor is out of calibration or not working properly, there is a high-level safety limit to prevent the tank from overfilling. If the high limit is met at a pre-set value, say 102% full the process will shut down and a strobe light will turn on. Indicator lights are activated when the tank level reaches 50%, 75% and 100%. There is a slight dead band to prevent flickering lights when tank levels vary slightly due to filling or splashing. If the tank for some reason does not fill up to a minimum level of 50% within after a specified time after the valve energizes, an alarm will notify an operator. The operator will be able to silence the alarm for a specified time by pressing a silence button. After five minutes the alarm will trigger notifying the operator once again. The operator will be able to silence the alarm two times. If the silence button is pressed a third time, the alarm will remain on and an energized strobe light will notify anyone within the site of the tank. The silence button will be tamper-proof by utilizing a one-shot rising instruction to prevent an operator from holding the button in. If the tank remains under 50% full, the only way to de-energize the alarm and strobe is to stop the process. Instructions possibly structured by ladder logic: --On timers (TON) --Up Counter (CTU) --One-shot rising instruction (OSR) --Less than (LES), Less than or Equal to (LEQ), Greater than (GRT), Greater than or Equal to (GEQ) comparison instructions --Divide By instruction (DIV) (for scaling analog inputs) --Input and Output instructions (both internal and external) A tank information board and its corresponding I/O assignment. Chambers will make use of liquid level sensors. the PID alternativeis also possible. System to be simulated before building of processing systems. Active real time monitoring of built processing systems (if not troublesome). At the end of completing all phases there must be apparatuses to give data for the following parameters: pH, ORP, DO, EC, Temp and vis; concerns acidity, oxidation-reduction potential, dissolved oxygen, electrical conductivity, temperature and viscosity. Particularly for dissolved oxygen, there are DO sensor/meter kits relatively cheap that can be integrated. For such parameters consider the following journal article: Khatri, P. et al, Raspberry Pi-based Smart Sensing Platform for Drinking-Water Quality Monitoring System: a Python Framework Approach, Drink. Water Eng. Sci., 12, 31–37, 2019 With incorporation of viscosity parameter, excluding geographical smart sensing, and no commitment to the Python language. Algorithm to be extended by taking readings every 5-10 minutes within an hour. One can model such parameters over time or whatever. A respective water contestant to have its own segregated phase processing analysis and four-phase system. NOTE: to be compared with samples from each respective purification phase. Hence, each phase has port for sample taking can be sealed and unsealed. Microscope visualization should also be able to take pictures. Microscope observation of samples to detect any existence of microorganisms; test samples unique throughout to any samples for end product spectroscopy analysis. Observation of spectroscopy results: at least three sample sets in comparison per type of spectroscopy analysis. All spikes in spectroscopy graphs to be identified with an element, compound, etc., etc. Spectroscopy analysis to be UV, IR, Raman and NMR (each to be done with unique samples). Pictures of spectrographs should be possible as well. Note: all spectrograph results must be compared to professional spectroscopy databases. Know the utility bill rate for water and resulting total for a designated period. For a respective non-tap water contestant tally the cost of the respective purification system added with the electricity consumption cost, and subtracting such summation from the water cost saved by the purification system based on the water utility rate. Possibly, immersion of four-phase system into a mobile smart grid. NOTE: CAD design initially for system chanelling components with integration. Piping manifolds, acrylic chambers/tubes, vinyl tubing, carbon fiber molds to be employed. Chambers, channels and other crucial components for disassembly, towards checking for corrosion, matter build ups, changing of sediments, cleaning, etc. Concern with cleaners that may compromise refining/purification process. NOTE: ladder logic simulators, OpenPLC followed by economic PLCs based on Arduino or Raspberry Pi is possible. Othrerwise, direct use of microcontrollers with PID and so for is an alternative, but modelling, programming and simulation before integration will vary drastically. Life Cycle Assessemnt of developed four-phase system. Willl be highly comrehensive and highly computational. Propose and develop a similar sewage water treatment with such process. All facilities, tools, instruments, lines/pipes and equipment in operation for sewage treatment to be unique and isolated from all types of prior water treatment above. What stage(s) will one incorporate any necessary additional microbial diverse treatments? Will have similar microscopic and spectroscopy analysis; samples for microscope always be unique to spectroscope samples. Case of evolving microbial resistance and resolutions. Similar stage process data accumulation and extended economics/finance analysis from additional development and resources. NOTE: may draw huge interest with chemistry constituents. D. Analysis, Replication of Traffic Modelling, Simulation & Computation For the algorithms observed the type of language used or understood (Wolfram, R, C, C++) isn’t of any concern, unless quantitative simulations are needed to be observed with actual models. Interest directed towards constituents of of Computer Science, Industrial Engineering, Civil Engineering. Activity is open to Operations Management/Operation Research via special invite. (1) Field data collection and analysis PART A Will pursue at least two methods in the field for traffic data determination with pursuit of necessary associated parameters for traffic flows, rates, distribution, patterns, etc. Such field activities serve to educate students on the technologies they take for granted with highway migration. Some guides: --Al-Sobky, A. A. and Mousa, R. M., Traffic Density Determination and its Applications Using Smartphone, Alexandria Engineering Journal (2016) 55, 513–523 --Leduc, Guillaume. (2008). Road Traffic Data: Collection Methods and Applications, JRC European Commission, Working Papers on Energy, Transport and Climate Change --Yatskiv, I. et al, An Overview of Different Methods Available to Observe Traffic Flows Using New Technologies, European Commission, Eurostat CROS NTTS 2013 Programme Session 8P, Poster Session on Spatial and Mobility Statistics. --Soliño, A., Lara Galera, A., & Colín, F. (2017). Measuring uncertainty of traffic volume on motorway concessions: A time-series analysis. Transportation Research Procedia, 27(C), 3-10. General Guides --> --Ferrara, A., Sacone, S., & Siri, S. (2018). Freeway Traffic Modelling and Control (Advances in Industrial Control). Cham: Springer International Publishing. --Zambrano-Martinez, J. L., Calafate, C. T., Soler, D., Cano, J. C., & Manzoni, P. (2018). Modelling and Characterization of Traffic Flows in Urban Environments. Sensors (Basel, Switzerland), 18(7), 2020. One must consider what periods of interest should be pursued. For a respective traffic region one can pursue the case for a typical hour between some period daily of a typical weekday, however such will require very technical trials. Such can be specific towards morning commutes, or even commutes (both concerned heavily around education, labour and public administration activity purposes). The same goes for a weekend day. There may be interest for special events and associated traffic regions. PART B Example of development data accessible to the public: https://data.cityofnewyork.us/Transportation/Real-Time-Traffic-Speed-Data/qkm5-nuaq Can use model development to critique accomplishmentdsin part A. If you don’t want to directly run to such types of websites every time, where additionally you are interested specific types of data, what can you do? APIs and API keys are crucial. Such will include data manipulation towards data analysis. How can you structure your data to be of relevance to traffic models; can serve well towards microscopic and mesoscopic traffic models for interest at hand. LIKELY TO BE USED LATER ON. (2) Fundamentals of Microscopic Traffic Flow --> Link flow theory: modeling of traffic flow on an individual link. Fundamentals of traffic flow: --variables of interest, basic flow-speed-density relationship ("fundamental equation") --Introduction to microscopic car-following models: linear car-following models, asymptotic and local stability, steady-state behavior, nonlinear car-following models, steady-state behavior. --Nagel-Schreckenberg & traffic jams, or cellular automation. Understanding of a flow diagram of a microscopic model, and possible associated “pseudo code” development and simulation. Then, calibration, say, quantifying model parameters using real-world data. --Additional Microscopic guides: <Song, D., Tharmarasa, R., Zhou, G., Florea, M., Duclos-Hindie, N., & Kirubarajan, T. (2019). Multi-Vehicle Tracking Using Microscopic Traffic Models. IEEE Transactions on Intelligent Transportation Systems, 20(1), 149-161> < Treiber, M., Kesting, A., & Helbing, D. (2006). Delays, inaccuracies and anticipation in microscopic traffic models. Physica A: Statistical Mechanics and Its Applications, 360(1), 71-88> <A. Paz, V. Molano, E. Martinez, C. Gaviria, and C. Arteaga: Calibration of Traffic Flow Models Using a Memetic Algorithm, Transportation Research Part C, 55 (2015) 432–443> <M. Yu and W. Fan, Calibration of Microscopic Traffic Simulation Models Using Metaheuristic Algorithms, International Journal of Transportation Science and Technology, 6 (2017) 63–77> (3) Microscopic Traffic Flow Tools --> MITSIMLab Multi-Agent Transport System Toolkit (MATSim) Simulation of Urban Mobility (SUMO) Has the ability to Import road networks from common network formats such as OpenStreetMap, VISUM, VISSIM, NavTeq, MATsim and OpenDRIVE One must consider what periods of interest should be pursued. Means to determine consistency between analytical development prior in (2) and such tools. (4) Fundamentals of Mesoscopic Traffic Flow --> -- variables of interest -- Functions of the manner f(t, x, V) as a probability density function, expressing the probability of observing a vehicle at a particular time, at a specified position, traversing with a particular velocity. Methods similar to statistical mechanics for computing functions in likeness of the Boltzmann equation. -- Additional Mesoscopic guides: Note: Mezzo - Mesoscopic Traffic simulator https://www.ctr.kth.se/research/current-projects/mezzo-mesoscopic-traffic-simulator-1.726113 <Burghout, W., Koutsopoulos, H., & Andreasson, I. (2006). A discrete-event mesoscopic traffic simulation model for hybrid traffic simulation. 2006 IEEE Intelligent Transportation Systems Conference, 1102-1107> <Wang, Y. and He, Z. Mesoscopic Modelling and Analysis of Traffic Flow Based on Stationary Observations. Procedia Computer Science 151 (2019) 800 – 807> <Gangi, M. et al. Network Traffic Control Based on a Mesoscopic Dynamic Flow Model. Transportation Research Part C 66 (2016) 3 – 26> <S. Yu, Y. Xu, S. Mabu, M. K. Mainali, K. Shimada, and K. Hirasawa: Q Value-Based Dynamic Programming with Boltzmann Distribution in Large Scale Road Network, SICE Journal of Control, Measurement, and System Integration, Vol. 4, No. 2, pp. 129–136, March 2011> <E. Ben-Naim and P.L. Krapivsky: Steady-State Properties of Traffic Flows, J. Phys. A: Math. Gen. 31 (1998) 8073–8080. Printed in the UK> (5) Mesoscopic Traffic Flow Tools --> The following software cater specifically for mesoscopic modelling. Means to determine consistency between analytical development prior and such tools: Mezzo-Mesoscopic Traffic simulator DTALite: A queue-based mesoscopic traffic simulator for fast model evaluation and calibration Xuesong Zhou & Jeffrey Taylor | Filippo Pratico (Reviewing Editor) (2014) DTALite: A queue-based mesoscopic traffic simulator for fast model evaluation and calibration, Cogent Engineering, 1:1 (6) As well, the following software has a strong reputation: TRANSYT-7F Determine scale of applicability (7) Fundamentals of Macroscopic Traffic Flow - Macroscopic models: being parallel to fluid dynamics and PDE, which balance laws for specific gross quantities of concern, say, the density of vehicles, or their mean velocity. Mathematical models of traffic flow includes both ODE and PDE. Additional guides-- <G. Brettia, R. Natalinib, and B. Piccoli: Numerical algorithms for simulations of a traffic model on road networks, Journal of Computational and Applied Mathematics, 210 (2007) 71 – 77> <A. Spiliopoulou, I. Papamichail, M. Papageorgiou, I. Tyrinopoulos, and J. Chrysoulakis: Macroscopic Traffic Flow Model Calibration Using Different Optimization Algorithms, Transportation Research Procedia, 6 (2015) 144 – 157> <Khan, Z.H. & Gulliver, T. A Macroscopic Traffic Model for Traffic Flow Harmonization. European Transport Research Review. (2018) 10: 30> To then simulate developed macroscopic model based on such articles involving real data and compare with developed simulated microscopic model results from software. NOTE: unless one is very well seasoned and competent in traffic flow modelling the following topics likely will be counter-productive in regards to developing a foundational of endurance and clarity. Will not treat such subjects will high detail concerning this activity. Will mostly let the software tools guide use: Traffic signal control Route Guidance and Traffic Assignment in Networks The mathematical intellect may be too impeding, viscous, intangible or have the “cuffed to cannon ball and chain in water effect” concerning feedback/automatic control, embedded systems and programming logic controllers, which concerns of technical fields of engineering. Operational Research, Systems Control and Computer Science constituents can possibly tackle such two subjects independently. E. Allocating Yard Storage Space for Containers Special invitation towards constituents of Operations Management and Revenue Management Activity serves as immersion to the structuring of shipping and space allocation operations, and means to understand how consumers and operators are subject to optimisation and finance strategies towards serving their respective interests. Lack of understanding of modelling, strategy and planning will inevitably lead to financially disadvantages and/or elevated lack of efficiency with resources. -PART A (Firms of Interest) The toughest task may be finding allocation and storage firms not having high competition threats, to acquire transparency in their operations. Much data gathering to characterise and profile the firms, along with analysis of their allocation, storage and pricing policies/strategies. For the following parts, to analyse the given articles without bias or reference to the firms you have engaged. An obligation is to harmonize all such journal articles in a constructive, practical and fluid manner. There may be some reformulation requirements from likely backtracking. -PART B (Stacking Policies) Guven, C. and Eliiyi, D. T. (2014). Trip Allocation and Stacking Policies at a Container Terminal, 17th Meeting of the EURO Working Group on Transportation, EWGT2014, Sevilla, Spain, Transportation Research Procedia 3 ( 2014) 565 – 573 -PART C (Container Retrieval) Lin, D., Lee, Y. and Lee, Y.,(2015). The Container Retrieval Problem with Respect to Relocation, Transportation Research Part C 52, 132–143 -PART D (Optimal Space, Forecasts and Performance) Sauri, S. and Martin, E. (2011). Space Allocating Strategies for Improving Import Yard Performance at Marine Terminals, Transportation Research Part E 47, 1038–1057 Lee, D., Jin, J. G. and Chen J. H. (2012). Terminal and Yard Allocation Problem for a Container Transshipment Hub with Multiple Terminals, Transportation Research Part E 48, 516–528 Alcalde, E. M, Kim, K. H. and Marchan, S. S. (2015). Optimal Space for Storage Yard Considering Yard Inventory Forecasts and Terminal Performance. Transportation Research Part E 82, 101–128 Are observed firms conframative to any of such modelling? -PART E (Storage Pricing Strategies) Martín, E., Salvador, J. and Saurí, S. (2014). Storage Pricing Strategies for Import Container Terminals Under Stochastic Conditions. Transportation Research Part E 68, 118–137 -PART F (Relating to Firms of Interest) For conclusions or resolutions developed, to compare with development from part A. Identify compatibility, disparities (or divergences) NOTE: may be parallel to vehicle rentals and car holding facilities, but such may have more subtleties with instruments

F. TBA G. TBA H. Personnel Scheduling Optimisation 1. test guide article: Brucker, P., Qu, R., and Burke, E., Personnel scheduling: Models and Complexity, European Journal of Operational Research 210 (2011) 467–473 The above article to serve as a test guide. The following are differentiated types of planning from the article: (i) permanence centred planning (ii) fluctuation centred planning (iii) mobility centred planning (iv) project centred planning From your ambiance you will try to categorize which firms suits what type of planning. You will try to gather staff/operational data for each firm and determine whether the respective real firm is harmonic to its characterised planning. For a respective firm compare it’s data to both models and conventional proprietary software for scheduling. Quality of service is a unique issue not to be treated here. Will determine what simulations for evaluation are required and will develop in R and also likely compared to parameters of proprietary software; apprpriate simulations may possibly be found in mentioned articles. An example case: Kassa, B., A., and Tizazu, A., E., Personnel Scheduling Using Integer Programming Model-A application at Avanti Blue-Nine Hotels, SpringerPlus, 2013; 2: 333 2. Now the following case articles may or may not fall within the test guide article. (i) Becker, T., Steenweg, P., M., and Mareike, P., and Werners, B., Cyclic Shift Scheduling with On-Call Duties for Emergency Medical Services, Health Care Management Science, Springer Nature 2018 (ii) Semra Ağralı, S., Taskin, Z., C., and Tamer Ünal, A., T., Employee Scheduling in Service Industries with Flexible Employee Availability and Demand, Omega 66 (2017) 159–169 Note: for this particular research project, except for the test guide article, all other journal articles are subject to change in the future. Apart from Industrial Engineering, research project will interest constituents of Operations Management (Operational Research). I. Water Distribution Network’s Modelling & Calibration. Sensor Placement for Leak Location in Water Distribution Networks Using Genetic Algorithms Open to constituents of Civil Engineering, Mechanical Engineering, Operational Research (Operations Management) and Computer Science. (i) Acquaintance and modelling with EPANET2 and WDNetXL; may require use of a GIS and Google Maps later on. (ii) Modeling and calibration of a small and poorly documented (portion of the) water distribution network (WDN) that shows pressure problems. Field campaigns are conducted to reduce the inaccuracies found in the inventory’s drawings and to aid building a first WDN model. A trial and error procedure was then used to produce successive refinements for the desirable WDN’s model fit. The following article to serve as guide: --Alves, Z., Muranho, J., Albuquerque, T., and Ferreira, A., Water Distribution Network’s Modelling and Calibration. A Case Study Based on Scarce Inventory Data, Procedia Engineering 70 ( 2014 ) 31 – 40. (iii) Applying Data Assimilation (DA) methods to a Water Distribution System Model to improve the real time estimation of water demand, and hydraulic system states. A time series model is used to forecast water demands which are used to drive the hydraulic model to predict the future system state. Both water demands and water demand model parameters are corrected via DA methods to update the system state. The results indicate that DA methods improved offline hydraulic modelling predictions. Of the DA methods, the Ensemble Kalman Filter outperformed the Kalman Filter in term of updating demands and water demand model parameters. Incorporates EPANET2 (or WDNetXL) usage; may require use of a GIS and Google Maps. Data request from WASA or corresponding utility service may be needed. Develop such to the best of ability with ambiances of choice --> --Okeya, I. et al. Online modelling of water distribution system using data assimilation. Procedia Engineering 70 ( 2014 ) 1261 – 1270 (iv) Acquaintance with the RELOPT model Incorporates EPANET2 (or WDNetXL) usage; may require use of a GIS and Google Maps. Data request from WASA or corresponding utility service may be needed. After acquaintance with EPANET2 to analyse and comprehend the RELOPT model based on Journal article: --Mohamed Abdel Moneim (August 1st 2011). Modelling Reliability Based Optimization Design for Water Distribution Networks, Scientific and Engineering Applications Using MATLAB, Emilson Pereira Leite, IntechOpen < not content with MATLAB use as the only option >. Reliability-based optimization design prime directive for a water distribution network using modelling technique of Mathematica programming language. ill like to focus on ambiances of interestGoals: Acquainting optimum least-cost design for water distribution networks using new efficient and time consumed method. Define risk components for water distribution networks. Define the most critical components of water distribution networks that affect the level of serviceability under different cases of operation (i.e. define level of service under risk). Analysis, evaluation and treating reliability for water distribution networks. Define the reliability of water distribution network over a given period of time. Define the optimum solution of water distribution network that achieve the optimum lease-cost design and certain accepted reliability in one time (reliability-based optimization). Develop stand-alone reliability-based optimization model comprising all the above-mentioned objectives. Getting the reliability-based optimization design for water distribution networks requires searching among several available population set of solutions. RELOPT model consists of the following components: Hydraulic solver EPANET2: consists of the dynamic libraries that are required to be called by Mathematica program for hydraulic analysis. Pre-estimation model (AGM): this sub-model provides the lower and upper bounds that are required for OPTWNET to start optimization search process. Optimization model (OPTWNET): defines the optimum solution using LAGA. LAGA automatic search engine module. Reliability model (RELWNET): this model is connected with three sub-models <minimum cut-sets model; Generic Expectation Function model; reliability calculation model>. The model passes the final calculated reliability to the main model RELOPT. (v) Optimisation and Reliability Assessment of Water Distribution Networks Data request from WASA or corresponding utility service may be required, and and may require use of a GIS and Google Maps--- --M. Abunada, Trifunović, N., Kennedy, M., and Babel, M., Optimization and Reliability Assessment of Water Distribution Networks Incorporating Demand Balancing Tanks, Procedia Engineering 70 ( 2014 ) 4 – 13 --Djebedjian B., Reliability-Based Water Network Optimization for Steady State Flow and Water Hammer. ASME. International Pipeline Conference, Volume 3: Materials and Joining; Pipeline Automation and Measurement; Risk and Reliability, Parts A and B (): 727-737. Note: Acquiring NORAT (Networks Optimization and Reliability Assessment Tool) towards integration with EPANET 2 may or may not prove difficult. Nevertheless, there are alternatives which require more direct procedures integrating algorithms, CAD, EPANET 2, etc. (vi) Sensor placements to detect leakage: After after analysis of the following journal articles, to apply to local and chosen ambiances. Concerns water pressure readings at nodes and other places of interests for particular date(s) corresponding to leakage. To comprehend and implement algorithms towards predictions for actual source of leakage(s). by use of pressure history data in grid of interest where scheme will be applied and compared to past maintenance schedules at sites. Numerous genetic algorithms will be employed and compared. For robustness, will employ the different schemes from each article and compare results. Data request from WASA or corresponding utility service and may require use of a GIS and Google Maps along with EAPNET2 or WDNetXL --> --Steffelbauer, D., Neumayer, M., Gunther, M., and Fuchs-Hanusch, D., Sensor Placement and Leakage Localization Considering Demand Uncertainties, Procedia Engineering 89 ( 2014 ) 1160 – 1167 --Casillas, M., V. et al, Optimal Sensor Placement for Leak Location in Water Distribution Networks Using Genetic Algorithms, Sensors 2013, 13, 14984-15005 --Puleo, V., Freni, G., and La Loggia, G., Pressure Sensors Positioning for Leakages Detection Under Uncertain Demands, EPiC Series in Engineering, Volume 3, 2018, Pages 1713-1717 Note: there will likely be issues if there are multiple sources of leaks. For such a circumstance one must cleverly segment grid involving knowledge of models, formulas, etc.). (vi) Consider the following: -- Al-Ani, D., and S. Habibi, S., Optimal Operation of Water Pumping Stations, Water and Society II, WIT Transactions on Ecology and The Environment, Vol 178 To adjust to ambiance(s) of interest. Based on ambiance(s) to apply methodology of the given journal article and compare with the active authentic pumping settings operations of ambiance(s). Then will try to compare genetic algorithms with differential evolution applied in article to observe results. Incorporates EPANET2 or WDNetXL usage; may require use of a GIS and Google Map. Data request from WASA or corresponding utility service. (vii) To analyse and develop with environments of choice: Beygi, S., Tabesh, M., & Liu, S. (2019). Multi-Objective Optimization Model for Design and Operation of Water Transmission Systems Using a Power Resilience Index for Assessing Hydraulic Reliability. Water Resources Management, 33(10), 3433–3447. J. Inventory Control Systems Model for Strategic Capacity Acquisition White, A., S., and Censlive, M., Inventory Control Systems Model for Strategic Capacity Acquisition, Journal of Industrial Engineering, Volume 2016, Article ID 1650863, 16 pages The most difficult task actually may not be the journal article itself, but instead real-world systems in operation. Pursue such and observe whether data from actual operating system(s) conform well to developed model and forecasts. Special invitation towards constituents of Operations Management and Revenue Management. K. TBA L. TBA M. Modelling production cuts Production cuts are implemented for various reasons. A few of those reasons: Demand Material experiences (stationery, tools, commodities, energy) Labour costs and labour cost index Observation of product life cycle with no forseeable innovation Competition dynamic Catastrophe Tariffs Taxes Merger & Acquisition Economic forecast Such can have effect on employment, market share and firm equity. -This activity aims on developing efficient modelling for optimal percentage cuts in production based on the above scenarios (singular or multiple incorporated scenarios). Reduction may be local, national, international, specific targets in market segmentation, etc. -To extend, funds may not necessarily be a result only of the revenue cycle, but also from equity transactions (being stochastic), bonds financing, etc. However, also there are bond payment obligations (with interest), etc. -There may various approaches Finance Operational Research and Economics Stochastic Frontier Analysis, Data Envelopment Analysis PESTEL, SWOT AHP, Multi-criteria, Multi-Objective, Goal Programmimg, Perhaps both approaches can compliment each other for a wide view or alternative views. Open to Operations Management, Revenue Management and Economics constituents. N. Optimisation (Linear, Nonlinear and Dynamic) Minimum requirement for participation is a course in Optimisation course. Open to Operations Management/Operational Research constituents. Part A-- Students will be asked to provide LP and NLP models for various applications. Then, to pursue possible DP forms alternative. Instructor can also provide some problems with set up stages where students must fill in the algorithm patch or conditions. 1. Based on model analysis will pursue algorithm development either R or Mathematica or Excel. 2. Then will compare algorithm results with use packages or functions. 3. Concerning geospatial cases will also incorporate visual views via maps and GIS for a real world feel. Will have compare/contrasts with (Google) Maps of the various directions suggestions options concerning estimated time of trek and distance. 4. Will also be interested in applications industrial systems of the ambiance; likely will be more complex than descriptions in articles. —Solid background with LP and Mixed Integer Linear Programming Solid background with NLP is assumed —Objective and general procedure of DP —Production Planning Problem: From LP to DP Note: must have LP before development DP, to compare LP with DP concerning cost (time and accuracy) in a hands-on manner (and possibly with developed algorithms or packages) Example of DPPs: https://www.ime.unicamp.br/~andreani/MS515/capitulo7.pdf Will apply to real ambiances of different scales Stagecoach problem Distributing medical teams Distributing scientists to research teams Scheduling employment levels Wyndor Glass company problem Determining Reject Allowances Winning in las Vegas Lorigeon, T., Billaut, J., & Bouquard, J. (2002). A Dynamic Programming Algorithm for Scheduling Jobs in a Two-Machine Open Shop with an Availability Constraint. Journal of the Operational Research Society, 53(11), 1239-1246. —Solving Nonlinear Programming Problems with DP --> Ohno, K. (1978). Differential Dynamic Programming for Solving Nonlinear Programming Problems. Journal of the Operations Research Society of Japan Vo1.2I, No.3 http://www.orsj.or.jp/~archive/pdf/e_mag/Vol.21_03_371.pdf —Other Nonlinear forms: Bellman Petković, N., and Božinović, M. The Application of the Dynamic Programming Method in Investment Optimisation, Megatrend Review, Vol. 13, № 3 2016: 171-182 Haciyev, P., Dynamic Programming Methods Application for Investment Allocation Optimization at the Mill Factory, American-Eurasian J. Agric. & Environ. Sci., 12 (1): 77-84, 2012 O. Manufacturing Systems Open to Systems Control constituents of mechanical engineering Multiple tours of a particular manufacturing system may be required. Step 1 --> Suh, N. P., Cochran, D. S. & Lim, P. C., Manufacturing System Design. CIRP Annals, volume 47 Issue 2, 1998, pages 627 – 639 Step 2 --> Identifying and describing manufacturing systems based on step 1 in the ambiance that produce a single product, or mix of products in large numbers. Importantly one would like students to have a tour of such facilities. It’s very important however that for the ambiance of choice the manufacturing systems have no serious competition despite being required to produce a mix of products in large numbers. Else, operations administrators may be reluctant to provide tours. In addition, security clearance will be required. The prior article will serve as the students’ model guide where they pursue the data necessary to determine whether the manufacturing systems are harmonious to the models of the article. Students to develop findings. Keep in mind that the constituents of the manufacturing systems may not be “robotic” as one may pursue. Utilities plants (manufacturing energy or lean water) may be also considered, but must be analysed in context of the given journal articles throughout. Some manufacturing systems may not be modern enough to be described by succeeding steps, however, they will be observed and analysed to best of abilities. Step 3 --> Productivity measurement of the manufacturing systems. The following article can serve as a guide for productivity determination, however, there may be other more revered productivity measure models, say, practiced models from places such as Japan, Germany, France, USA, Canada, Malaysia, China, etc: Rawat, G. S., Gupta, A. and Juneja, C. Productivity Measurement of Manufacturing System. Materials Today: Proceedings 5 (2018) 1483–1489 Nevertheless, will methodologies be compatible with literature from step 1? Step 4 --> Implementation of Emergy and Life Cycle Assessmnet upon fields sites visited. Step 5 --> Tour identification of EMS and interest topics Identification of energy management systems (EMS), namely, identification of the harware, software, area network and data collection logistics about the energy consumption for a facility, building, campus, or manufacturing plant. Not just energy, but other concerns such as natural gas, water, compressed air, inert gases, etc. Likely, one manufacturing system may be different from another, say, an automobile manufacturer may monitor energy usage per vehicle, while a chemical manufacturing facility will need to normalize energy data per pound of production, and a food manufacturing plant may need to normalize against pallets shipped. Enterprise Resource Planning systems (ERP). The energy management system must be able to interface with vendors such as SAP or Oracle (or likely some other generic tools). In addition to many standard commercial energy management system communications protocols, such as BACnet and Modbus, in manufacturing the EMS must also interface with programmable logic controllers (PLC's) - often times from multiple vendors such as Omron, Rockwell, GE, or Siemens (or likely some other generic tools). This requires support for communications protocols such as EthernetIP, ModbusTCP, Profibus, ProfiNet, and others. And since a manufacturing plant can have multiple networking requirements, it is also necessary to be able to monitor the integrity of the network hardware through protocols such as SNMP (Simple Network Management Protocol). The manufacturing systems in ambiance may not be as sophisticated however. Similar to commercial EMS, industrial energy management systems must also be able to collect weather data, through the use of communications tools such as web services. Part of the overall manufacturing plant information requirements may require normalization of energy data against degree days, in addition to production KPIs. It’s not unusual to deal with hundreds of sensors and tens of thousands of data tags - all needing to be logged at relatively high speeds. This requirement is often beyond the capability of SQL-based databases and requires the application of a true industrial data historian. In some highly developed ambiances, the production equipment, alone, included 265 electrical energy meters. Contrast such with a 20-story building that might have an energy meter per floor. Some larger facilities are so dependent on the information systems, that the underlying architecture of the energy management system must support redundancy that allows for no loss of data in the event of server failure. The capability to have redundant data collection and redundant data logging is not an unusual requirement for manufacturing. Most manufacturing plants will have an equipment maintenance and/or asset management system in operation, requiring the industrial energy management system to be able to interface with these systems as well as to be able organize equipment in industry standard hierarchies using standards such as ISA-95. Step 6 --> Students will carry out energy audits on the different manufacturing systems or buildings. Some data features can possibly be compared with the EMS study observation. Step 7 --> The following textbook serves as (stochastic) modelling of manufacturing: Curry, G. L. and Feldman, R. M. Manufacturing Systems Modelling and Analysis, Springer-Verlag, Belin, 2009, 2011 Comparing A major task concerning this book is to identify what models govern the manufacturing systems encountered prior. May pursue some simulations for overall short term and long term behaviour. Step 8 --> If a respective manufacturing is old, students must use software or planning to redevelop manufacturing system into a modern version based on the discussed topics concerns, journal articles (and possibly the book as well). Steps 1 through 7 are relevant. All subject to production parameters of original manufacturing system. Such possibly includes CAD/CAM/CAE, additive manufacturing, automation, etc., etc. Literature in step 1 and step 7 can be structural guides. Possible green energy integration incorporated as well. Includes design of the EMS (also possibility for other utilities and materials). Factors of consideration: energy, other utliities, labour costs variance, material consumption. Implementing the following: emergy, life cycle assessment, Data Envelopment Analysis (for production and costs).

P. PEAST algorithm The acronym PEAST stems from the methods used: Population, Ejection, Annealing, Shuffling and Tabu. Some guides for the PEAST algorithm: --Kyngäs, N., Nurmi, K. and Kyngäs, J. (2013). Crucial Components of the PEAST Algorithm in Solving Real-World Scheduling Problems. Lecture Notes on Software Engineering, Vol. 1, No. 3 --Kyngäs N., Nurmi K., Kyngäs J. (2014) Workforce Scheduling Using the PEAST Algorithm. In: Yang GC., Ao SI., Huang X., Castillo O. (eds) Transactions on Engineering Technologies. Lecture Notes in Electrical Engineering, vol 275. Springer, Dordrecht --Nurmi, K., Kyngäs, J., and Kyngäs, N. (2014). The PEAST algorithm – The Key to Optimising Workforce Management and Professional Sports League Schedules. International Journal of Process Management and Benchmarking (IJPMB), Volume 4, Number 4 --Nurmi, K. et al. (2014). Scheduling a Professional Sports League using the PEAST Algorithm. Proceedings of the International MultiConference of Engineers and Computer Scientists 2014 Vol II, IMECS 2014, March 12 - 14, 2014, Hong Kong Will compare the performance of the PEAST algorithm to that of CPLEX (or other linear programming models) in real-world scheduling problems. Robustness of the PEAST algorithm versus linear programming (or other approaches). Will also like to apply what was applied for real leagues in different sports. For schedules generated will compare them to official schedules distributed by the leagues’ official media tools. Will identify the level of disparity, and consider the possible reasons for differences. Q. TBA R. Environmental Accountability -Chosen industrial emission systems or plants will be characterised, modelled (developing transfer functions and controllers), and simulated (COCO, DWSIM, SystemModeler, etc., etc.) -Emissions Emission factors Emission estimation protocol (plants, refineries, factories, etc., etc.) Hierarchy of emission measurement or estimation methods for various petroleum refinery (and other) emission sources, and provides a listing of pollutants for which emissions are anticipated for each source type The following source can assist with labs, where software identified from such source likely may not treat every system however, hence manual pursuits for such cases: https://www.epa.gov/air-emissions-factors-and-quantification/emissions-estimation-tools -Emergy Modelling and Assessment -Life Cycle Analysis (LCA) ISO 14000 Series Data sources used in LCAs are typically large databases Will identify databases and means towards assimilation Introspection, querying, etc., etc. OpenLCA Will have case studies and/or field activities with LCA -Energy Audit (EA) Review of field in energy accounting as guide for time efficient and accurate identification, profiling and record for energy systems EA being a process to reduce the amount of energy input into the system without negatively affecting the output Scheduled field activities -Energy Management Practices S. Life Cycle Costing (LCC) ISO 15686-5 Gov’t manual guides Data sources used in LCAs towards LCC are typically large databases Will identify databases and means towards assimilation Introspection, querying, etc., etc. --Kneifel, J. and Webb, D. (2020). Life Cycle Costing for the Federal Energy Management Programme. NIST Handbook 135 Software: https://www.nist.gov/services-resources/software/building-life-cycle-cost-programs Note: will not only consider BLCC (texts give other areas in LCC) --LCC with OpenLCA Will have case studies and/or field activities with LCC for alternatives and/or bids. T. Machine fault diagnosis based on Gaussian mixture model Also open to mechanical engineering constituents Yu, G., Li, C. and Sun, J. Machine Fault Diagnosis based on Gaussian Mixture Model and its Application. Int J Adv Manuf Technol (2010) 48: 205 – 212 A simple and efficient machine fault diagnosis approach based on Gaussian mixture model (GMM). After feature vectors that represent different machine conditions are extracted, a GMM for each of the machine conditions is built based on the corresponding extracted feature vectors, machine fault diagnosis can be accomplished through finding out the GMM whose posteriori probability for a given testing feature vector is the maximum of all. Experimental results based on the application on bearing fault diagnosis have shown that GMM can reliably diagnose not only the type of bearing faults, but also the degree of fault severity that are associated with incipient faults, moderate faults, and severe faults. Meanwhile, GMM has better diagnostic performance as compared to the multilayer perceptron neural networks. The above article provides an experimental design towards construction and data results that can be compared with administered experimentation. Such experimentation will be compared to other premier of incumbent methods/experiments for fault diagnosis; determine whether or not other assembled stations will be necessary with trials. Guides for other premier or incumbent methods/experiments for fault diagnosis: -Edwards, S. & Lees, Arthur & Friswell, Michael. (1998). Fault Diagnosis of Rotating Machinery. The Shock and Vibration Digest. 30. 4-13. -Suh, J., Kumara, S., & Mysore, S. (1999). Machinery Fault Diagnosis and Prognosis: Application of Advanced Signal Processing Techniques. CIRP Annals - Manufacturing Technology, 48(1), 317-320. -Wang, X., Makis, V., & Yang, M. (2010). A wavelet approach to fault diagnosis of a gearbox under varying load conditions. Journal of Sound and Vibration, 329(9), 1570-1585. -Villa Montoya, Luisa & Reñones, Anibal & Perán, José & Miguel, Luis. (2012). Statistical fault diagnosis based on vibration analysis for gear test-bench under non-stationary conditions of speed and load. Mechanical Systems and Signal Processing. 29. 436–446. -Lu C, Wang Y, Ragulskis M, Cheng Y (2016) Fault Diagnosis for Rotating Machinery: A Method based on Image Processing. PLoS ONE 11(10): e0164111. -Chen, X., Wang, S., Qiao, B. et al. Basic Research on Machinery Fault Diagnostics: Past Present, and Future Trends. Frontiers of Mechanical Engineering. (2018) 13: 264 - 291. -Liu, Ruonan & Yang, Boyuan & Zio, Enrico & Chen, Xuefeng. (2018). Artificial intelligence for fault diagnosis of rotating machinery: A review. Mechanical Systems and Signal Processing. 108. 33-47 -Yu Wei, Yuqing Li, Minqiang Xu and Wenhu Huang. A Review of Early Fault Diagnosis Approaches and Their Applications in Rotating Machinery. Entropy 2019, 21, 409 -Lei You, Wenjie Fan, Zongwen Li, Ying Liang, Miao Fang, and Jin Wang, “A Fault Diagnosis Model for Rotating Machinery Using VWC and MSFLA-SVM Based on Vibration Signal Analysis,” Shock and Vibration, vol. 2019, Article ID 1908485, 16 pages, 2019 U. TBA V. Developing algorithms for conditioning monitoring & predictive maintenance for industrial machinery OPEN TO Mechanical Engineering Concerning products or service the cost of failure is much higher than its apparent cost. Conventionally, many or most companies deal with this problem by being pessimistic and through accurate maintenance programs replace fallible components before failures. Despite regular maintenance as preference over failures, often the maintenance is carried out before it’s “needed”. Therefore, it’s not an optimal solution from a cost perspective, yet, risking it all during crucial operations generally will not seem logical. Predictive maintenance avoids maximizing the use of resources. Predictive maintenance will detect the anomalies and failure patterns and provide early warnings. PART A (comprehension) The following two sources provide solid concepts for predictive maintenance conveying high economic potential --> --Mobley, R. Keith. An Introduction to Predictive Maintenance (2nd ed.). Butterworth-Heinemann --Goriveau, Rafael; Medjaher, Kamal; Zerhouni, Noureddine (2016-11-14). From Prognostics and Health Systems Management to Predictive Maintenance 1 : Monitoring and Prognostics. ISTE Ltd and John Wiley & Sons, Inc. More modern strategies employing machine learning algorithms onto data acquiring from various sensing. A conceptual view of things Gonfalonieri, A. (2019). How to Implement Machine Learning for Predictive Maintenance. Towards Data Science. Website << https://towardsdatascience.com/how-to-implement-machine-learning-for-predictive-maintenance-4633cdbe4860 >> Often capturing dynamic and sound profiles of systems off the assembly line is a decent strategy. It’s imperative that a competent and practical model-based design of predictive maintenance be designed. How will the sensing and data processing features be integrated? Analysis should be in line with the expected performance or behaviour of the project when designed. PART B (planning and development) NOTE: much success will depend on part A For a strong foundation will begin with “small scale systems” where system constituents towards a predictive maintenance scheme aren’t very numerous and complex. The issue will be determining what system components will apply to monitoring. Various types of sensing and data gathering will be acquired. Based on the descriptions in such two links interfacing with CAS and simulators can be applied to develop an alternative personal platform. For Modelica based simulators or a SystemModeler environment there may be a decent chance that systems of consideration can be replicated to identify ideal modelling and simulations. Systems may take much work to develop in a simulator. In a pleasant world one will have both a behaviour profile for a new model developed, and a representative model in a simulator to compare with gathered data; often you only get one out of the two. Nevertheless, predictive maintenance is still highly feasible and practical. “Small scale” systems of consideration: Mechanical Electromechanical Thermal-Mechanical Three primitive concerns out of many that needs to be addressed–> Identify appropriate physics models for respective system that account for quantities towards sensing For particular data types based on sensing with formats to identify how respective data is structured and if appropriate to directly integrate into next phase The ability to provide proper controller designs Will rig together basic to intermediate size systems (mechanical and electromechanical). One approach may be to build a respective system in a simulator and acquire target responses and other ideal characteristic curves. Then one can construct the system in a lab or whatever and acquire the real data to compare with simulation data. It’s important that systems are well built to validate or have credible predictive data after many trials. Issues like elimination of unbalance, shaft misalignment (if relevant) and harmonious interfacing with system components must be well taken care of for new prototypes. There’s vibration sensing as well. One’s monitoring and prediction maintenance system can be constituted by target responses from simulation characteristic curves from simulation vibration sensing rpm sensing (if relevant) torque sensing if (relevant) unbalance detection (if relevant) even infrared radiation analysis A particular sensing example --> Wear Indication for bearings using edge computing with Spresense – YouTube https://youtu.be/KYhsp71sIcU PART C An industrial engineer will have to deal with systems described as “grids” where predictive maintenance development itself becomes verify complicated. However, in the long run such can efficiently procure maintenance labour in a preventive mode rather than a reactive one, where faults can neutralise a whole system. One would like to pursue development of predictive maintenance schemes on a SCADA scale, in a manner similar to what is described in the two sources in part A. For such to be constructive and rewarding complex systems must be well designed with much knowledge about its constituents on various scales. In the complex system there will be particular constituents of interest to monitor. Hence, will concern ourselves with premier and conventional systems in industries. Simulators like SystemModeler have features to deal with such complexity. Systems that are conventionally used with PLCs and SCADA in such simulators can also be versatile towards predictive maintenance schemes encountered prior, but on a grander scale. The only issue is accessibility to real data from real systems that are on par with designed models in simulators; will be pursued regardless. A major feet will be developing a competent algorithm that concerns components of interest in simultaneous function. PART D Yearly maintenance budget (YMB). The methodology suggested in this work will be a useful aid to maintenance managers in assigning YMB to their plant systems and provide indications for maintenance system corrections --> Srivastava, A. K., Kumar, G. & Gupta, P. Estimating Maintenance Budget Using Monte Carlo simulation. Life Cycle Reliab Saf Eng (2020) First, the scheme in the above article must be analysed and comprehended. Then, to determine what computational and simulation tools are practical towards developing something that’s constructive and useful long term. The pursuit is to try and incorporate the quantitative results structure from part B into the scheme described in the above article for yearly maintenance budget (YMB) in a fluid manner. It may also be recognised that the YMB scheme described in the above article may not necessarily be the best one. One can possibly choose an alternative, or, have a comparative analysis of different YMB schemes structured on predictive maintenance. W. Identifying Patent Infringement Open to Mechanical Engineering constituents Main goal is to analyse frameworks for patent infringement identification, then pursuit of implementation with competing products or services Park, H., Yoon, J. & Kim, K. Identifying Patent Infringement using SAO based Semantic Technological Similarities. Scientometrics 90, 515–529 (2012) Note: other frameworks should be applied as well for comparative developmet. Note: one may not find credible patent infringements, however, having a strong process that’s implementable is what’s important. X. Fluid and Thermal Behaviour in (Civil) Engineering (check civil engineering post) Y. Warranty Modelling Today, recognised is a fiercely competitive products market. Product warranty has an essential role. The modelling of failures during the warranty period and the costs for such policies are complex since the lifespan in these policies are not defined well and often it’s tedious to convey life measures for the longer period of coverage due to usage pattern/maintenance activities undertaken and uncertainties of costs over the period. Study of various warranty policies and models for predicting failures and estimating costs for different warranty policies. Some possible guides (not necessarily of order): Menke, W. (1969). Determination of Warranty Reserves. Management Science, 15(10), B542-B549. Murthy, D.. (2006). Product Warranty and Reliability. Annals of Operations Research. 143. 133-146 Z. Chen, T. Zhao, S. Luo and Y. Sun, "Warranty Cost Modelling and Warranty Length Optimization Under Two Types of Failure and Combination Free Replacement and Pro-Rata Warranty," in IEEE Access, vol. 5, pp. 11528-11539, 2017 Gopinath Chattopadhyay, Anisur Rahman, (2008). Development of Lifetime Warranty Policies and Models for Estimating Costs, Reliability Engineering & System Safety, Volume 93, Issue 4, 2008, Pages 522-529 NOTE: acquiring realistic parameters based on elusive data may or may not be a huge challenge. For chosen products or whatever apply such literature to try to the best of ability to establish warranty costs, warranty reserves and warranty policy, and whether your findings are comparable to observed warranty policies of the products. Z. Decision models applicable to industrial engineering Models and literature provided serve with the intension to synthesize general models that are quite robust in applications. Will then pursue also firms with accessible data to model analyse. There’s no intention to become stuck in a mathematical fantasy swamp, hence, applied analysis, and logistics towards modelling and computational implementation are priorities. Multiperiod Planning (PART A) -Just an overview guide of models (will not be the focus material) Schrage, L. (2018). A Guide to Optimization-Based Multiperiod Planning. INFORMS TutORials in Operations Research () 50-63 -Production/Inventory Planning Production Plan (for X periods) Objective: Minimize the total production and inventory cost. These costs must be calculated from the decision variables. Constraints: Demand must be met each month Constraints to define inventory in each period Production-capacity constraints. Non-negativity Optimization model in general terms: min: Total Production plus Inventory Cost subject to: Production-capacity constraints Flow-balance constraints Nonnegative production and inventory Developing the Multi-period Production Model Application literature: Hansmann, F. and Hess, S. W. (1960). A Linear Programming Approach to Production and Employment Scheduling. Management Science MT-1 (1) 46-51 Tadeusz Sawik (2019). Two-Period vs. Multi-period Model for Supply Chain Disruption Management, International Journal of Production Research, 57:14 Projects --> Logistics development Survey of R packages for multiperiod pl,anning Projects implementation Multi Objective Decision Analysis (PART B) Ching-Lai Hwang; Abu Syed Md Masud (1979). Multiple Objective Decision Making, Methods and Applications: A State-of-the-Art Survey. Springer-Verlag Miettinen, K. (1998). Nonlinear Multi Objective Optimisation. International Series in Operations Research & Management Science. Series Vol. 12 - Springer 4. Projects --> Logistics development Survey of R packages for multiperiod pl,anning Projects implementation Analytical Hierarchy Process (PART C) Analytical literature Logistics development Survey of R packages for AHP Projects implementation A1. Facilities Planning Various aspects of facilities planning process. Basic tools and methodologies used in this process, and exposure to the application of such tools. Both quantitative and qualitative tools (methods Technologies of activity: Autodesk Plant Suite Design, GIS, Mathematica, R, Excel EPANET2 (or WDNetXL) COCO (+ Chemsep) and/or DWSIM (+ Chemsep) SystemModeler and Modelica PART A: Computer Aided Plant Layout with Autodesk Plant Suite Design High emphasis on profiling plant or factory. Such will be used to develop detailed facility planning and design PART B: Warehouse Layout Problems Refresher of certain aspects from part A GIS development and optimisation models development followed by computation PART C: Facility Location Problems GIS development and optimisation models development followed by computation PART D: Minimax layout and location problem Refresher of certain aspects from part A to part C GIS development and optimisation models development followed by computation PART E: Processes Simulation Intelligence or data from prior parts will be crucial for characterisation and/or modelling. Processes may be hydraulic, chemical, mechanical or combinations, or more complex. For hydraulic EPANET2 (or WDNetXL) where modeling and simulation must be compatible with such software. For the chemical or thermochemical cases COCO (+ Chemsep) and/or DWSIM (+ Chemsep) to be applied, where modeling and simulation must be compatible with such software. If electroechanical then SystemModeler and/or Modelica to suffice, where modeling and simulation must be compatible with such software. As well, may be various combinations among priors. If more abstract/intricate then determnistic or stochastic modelling towards outputs to suffice. ELECTRICAL ENGINEERING & COMPUTER ENGINEERING (some activities will also cater towards mechanical engineering, aerospace engineering, civil engineering, industrial engineering, physics and chemistry) A. Power Flow Problem Compare developed execution programmes for power flow to professional modelling and simulations, say SystemModeler (and other practical accessories if needed). Incorporating an HVDC Transmission Line for Power Flow. (1) Find: voltage magnitudes and angles at every bus; real and reactive power flows through every branch. Concerns expansion, planning & daily operation, ETC.. A proposed network where “flow in” equals “flow out” at each bus. Use of Newton-Raphson to Newton-Krylov (includes strengths and weakness of both). Development of single variable to multivariable NR. Initially, to express complex power equations as equations with real coefficients. Then, Development of power balance equations into real and imaginary parts. Assume slack bus is the first bus with a fixed voltage angle/magnitude, then need to determine the voltage angle/magnitude at the other buses. To develop Sequential Conic Programming for radial networks involving change of variables and cast power ﬂow problem as conic program. As well for meshed networks resulting in extra constraints. Compare to SystemModeler (if feasible) and other tools. (2) To incorporate an HVDC transmission line and observe its influence on power transfer on another transmission line. To incorporate the operating principle of 12-pulse thyristor converters used in HVDC transmission systems. Consider a transmission line between buses 1 and 3 is an HVDC line. Observe the various characteristics of this HVDC system by examining its parameters. Concerns for various bus voltages and the power flow on various lines due to this HVDC line. Change the set point from 200 MW to 300, and then to 400 MW. Explain what you see. Acquire the waveforms of individual inverter DC voltage and combined 12-pulse DC voltage input, for different firing angles in a 12-pulse thyristor converter operating in the inverter-mode described in SystemModeler. From formulas, for different firing angles, calculate the DC voltage and match with the value obtained from the waveform. Involves quantity for rectifiers, inverters, and would likely involve simulations. Simulation models of rectifiers and inverters must be developed. Example: For Rectifier: w*Ls = 13.6791 ohm, VLL=213 kV, Id= Obtain from simulation. For Inverter: w*Ls=13.1843 ohm, VLL=207 kV, Id= Obtain from simulation. Obtain the waveforms of the input and output currents for both the transformers in rectifier and inverter. Observe the phase shift between the primary and secondary of Wye-Delta transformer. Explain what you see. Obtain harmonic components of secondary line current of Wye-Delta Transformer and harmonic components of the DC line voltage in the rectifier and inverter. What is the significance of the harmonics that appear? Note: Such to be followed by two or three more different scenarios with extensions. In addition, such a project can likely be compared and contrasted with a setup using one of given power engineering software and/or SystemModeler concerning design and simulations. Different variations every semester. Note: there will be variations and possible extensions in following semester operations. B. Synchronous Generators. Short Circuit Faults & Overloading of Transmission Lines. Fault Analysis with Relay Settings. Transient Stability. Crowbar circuit protectors. (1) To obtain the effect of sudden short-circuit on a synchronous generator output. Model a short-circuit on a synchronous generator as via SystemModeler. Obtain various waveforms and provide description. Verify the peak current transition at the three transient modes. (2) To study the effect of short-circuit faults and overloading of transmission lines. Simulate a fault: Provided code with fault at bus 2, then change the code for a three phase and a single line to ground fault at bus 3 instead of bus 2. Calculate three phase and single line to ground faults at bus 1, on the 1 to 3 line half way between bus 1 and 3 and on bus 3. For the line fault you need to click on the line fault tab and tell the program where on line. For each fault type and location you are to capture the results on the diagram showing the currents in amperes for all three phases. Which fault has the largest fault currents? Simulation circuits models must be developed as well. (3) You are given the two-generator system. You will use the program to analyse relay settings. The network you are to solve will be given. You are going to run several faults on this system and then see what various relays would have as input given the fault voltages and currents that the program outputs. The program is in SystemModeler and the data describing the network to execute the program. Concerns for Line to Neutral and Line to Line voltages at all buses in the network, as well as the zero, positive and negative sequence currents and the abc currents on each branch of the network. The program allows you to select three phase or line to ground fault, it allows you to select a bus or line fault, and which bus the fault is on. If it is a line fault it allows you to select how far down the line the fault appears and adds a new bus at that point where the fault takes place. (4) To simulate transient stability in a 3-bus example power system. SystemModeler programme to calculate Transient Stability in the example 3-bus power system is provided, concerning a power flow to initialize the simulation and then three separate simulations for prefault, during the fault, and post fault dynamics. The program initially simulates a three-phase fault on line 1-2 at 1/3 of the distance from bus 1 to bus 2. Execute this file get the plots of rotor angles of generators 1 and 2. When you get the program the clearing time is set to 0.2 second which results in a stable system. Start increasing the clearing time until the system goes unstable. Try to determine the “critical clearing time” which is the amount of time that can be allowed before the system goes unstable. Save the plots and note the maximum swing angle for each clearing time you try. Next you are going to convert generator 2 to an “infinite” generator by setting its H constant to a very large number. Then start the clearing time at 0.2 seconds and find the critical clearing time with gen 2 as an infinite generator. Assume that a three-phase fault occurs on line between buses 2 and 3, one-third away from bus 2. Modify the program to represent the fault on line 2-3 instead of line 1-2. Run with generator 2 as a normal generator (not an infinite generator). Start the clearing time at 0.2 second and then find the critical clearing time for this case. Note that the program you have for this lab has included some damping into the differential equations of the generators. (5) Applying crowbar circuit protectors. Analysis and designing simulation models with integration into previous models above. Note: there will be variations and possible extensions in current and following semester operations. C. Power Rectifiers, Inverters and Design and Integration of Timer IC (1) Kaayakesen, M. E., and Cadirci, I., A General Purpose Inverter Set-Up for Power Electronics Laboratory Experiments, Journal of Power Electronics, Vol. 10, No. 4, July 2010 One can compare modelling and simulation tools from Ansys electromagnetics, SystemModeler and SPICE with lab development. (2) Rectifiers Design and analysis of a single phase (uncontrolled) rectifier. Choosing the appropriate cmponenents for rectifier to be properly constructed; includes what level of resistance is required for safety. (3) Investigating why output voltage can’t be controlled for a diode rectifier (and possible alternatives such as thyristors). (4) Orchestration of the following: www.euedia.tuiasi.ro/lab_ep/ep_files/Lab_no_7_c1.pdf www.euedia.tuiasi.ro/lab_ep/ep_files/Lab_no_8_c1.pdf www.euedia.tuiasi.ro/lab_ep/ep_files/Lab_no_9_c1.pdf One can compare modelling with simulation tools and waveform simulations from Ansys electromagnetics, SystemModeler and SPICE, followed by lab development (5) Distinguishing between full wave and half wave rectifiers. One can compare modelling with simulation tools and waveform simulations from Ansys electromagnetics, SystemModeler and SPICE. Applications of rectifiers to variable speed DC drives, battery chargers, laser sources and electronic sets. Analysis and applications of three-phase full wave rectifiers concerning utilization factor. Conduction sequence for diodes. Voltage and waveforms. Feasibility of use of star or delta primary and secondary windings (due to symmetry). Average value and rms value of voltage output. Building a three-phase full wave rectifier circuit and switch on--switch off experiment (observing the input and output waveforms for each respective state); includes appropriate resistance for safety. Comparison between theoretical and practical results for input and output voltage and currents. Determination of the type of rectifier to be used depending on power considered. (6) Investigating the possibility of extending (4) to three-phase full wave. What applications are there? (7) The 555 Timeer IC Internal block diagram and virtual simulations. Internal schematic (bipolar version and CMOS version) and pinout diagram. Bistable, monostable and astable modes with virtual simulations. Can be used in various timer, pulse generation, and oscillator applications. Use as means for time delays and as a flip-flop as well. Interest in experimenting with its various applications and potential optimise devices that generally make use of larger circuitry components. (8) Making an inverter with use of a bread board, transformer, transistors, capacitors, battery, (at least a) 555 timer IC as a oscillator, and “resistor” (to tune the frequency of the “oscillator”), oscilloscope, AC/DC meter. Towards respective electronic device, say, light bulbs, fans, or stereos, etc. (but all test devices of the same voltage), yet a respective device with its unique watt specification. Verifying that respective device is functioning at optimal levels. Battery limit consideration (car battery, 12v, etc.) as the source. Determination of lifespan of the system. One can compare modelling with simulation tools from Ansys semiconductor, Ansys electromagnetics and SystemModeler, followed by lab development. D. Primitive Microwave, Radiowave and Infrared circuitry --How informantin travels wirelessly Electromagnetic Waves & Electromagnetics Radio frequency identification and tuning Signals, modulation, bits, etc., etc. Embedded systems and associated circuitry (transmission, reception, processing, interpretation) Planning, governing models, simulation building, hardware, software. Review components desired with requirements (safety and sustainability). Hands- construction/integration of modules following modelling simulation and virtual testing. Will then run filed experiments for (extra)terrestrial probing, audio, video and combination of prior two with analysis of data received --Circuits for electromagnetic frequencies and mudulatin SPICE simulators and Ansys tools to be available. Designing and simulation of circuits towards emission and reception of a respective chosen electromagnetic frequency range. Circuitry designs to include extensive physics, mathematical modelling, which includes the analysis/influence of semiconductor/transistor based components; accompanied by simulation of circuit if possible for a decent idea of ideal parameters values and characterising curves. Includes power gains, loss & noise contributions, filters, etc. Probability of detection and probability of false detection. --Physical system construction and data management likely to incorporate measurement modules, processing, and power electronics components. Charts, parameters and gauges to be centered around prior stage above. To build emitter and receptor systems for a respective wavelength range. --Provide the model synopsis for reception of signals received towards interpretation/analysis of natural terrestrial bodies, atmospheric bodies and extraterrestrial bodies. For microwave, radio wave and infrared to ientfy their use towards terrestrial bodies, atmospheric bodies and extraterrestrial bodies; followed by experiment with such wavelengths. Concerns for distance, speed, chemical composition and temperature. --Regarding pictures, audio and video (with audio) respectively, what additional tools and components are required concerning wave analysis, physics, mathematical statistics, filtering, engineering, etc? If feasible will construct communications systems with fundamentl components to to be harmonized (via power electronics, communications theory, etc., etc.). Open to Physics constituents. E. Li-fi Capability (1) Concerned mostly with employment of component circuitry devices for operations and data analysis, rather than gaudy, expensive commercial devices. (2) Visual Light Communication towards the idea of Li-fi. Comparing the primitive build set up to that of commercial components (Raspberry Pi/Arduino), namely, comparing task of circuits components by their roles. To be able to explain the engineering or physics process taking place for each components. Simulations, and waveform displays are welcomed that mathematically verifies processes; appropriate formulas. Consideration of light and circuit frequencies in operation. -Primitive Assembly: Transmitter Grid [Laptop, USB to UART module, LED Driver Circuit, LED] to Receiver Grid [Photo Diode, Inverter Amplifier, UART to USB Module, Message String Interpreter]. Assembly involves inverter scheme towards amplification (or commercial component), transformers, etc. Concerns appropriate current and voltage changes. -Contemporary Assembly: Battery, sensor, Message String Interpreter, Arduino/Raspberry pi as a emitter with LED, another Arduino/Raspberry Pi connected to PC using USB, etc. To provide a comparison setup with Wi-fi; involving radio wave frequencies, system model, mathematical analysis, energy consumption, heat output, radiation exposure, etc.), performance, advantages and disadvantages, etc. (3) Converting light signal into electric signal via optic transmission system based on laser diode. Analysis of the audio output transformer and modelling of its conversion process. System Components: media device, audio amplifier, solar cell, laser diode, audio output transformer, DC source. Then model a conversion process that provides media of both sound and video. Includes hardware and mathematics/physics/circuit modelling. (4) Comparative analysis between AD/DA & mixed singles, Laser transmission, Li-fi and Wi-fi. Includes energy consumption and costs for scale considered. F. Pursuit of Optical Angular Momentum Engineering challenging the prowess of Fiber Optics This activity may directly follow AA6 and activity (I). Special invitation for physics constituents. Process: 1. Modern physics for the possibility of a laser and DVD (CD). Such is a means to establish legitimacy for their intended or proposed usage in activity project. 2. Circuit model of for the laser. Includes virtual simulation for anticipation. 3. Components for construction: a. DVD or Blu-Ray writer (possible diode removal) b. Focus lenses c. Assemble driver circuit--with at least, an adjustable three-terminal positive-voltage regulator capable of supplying more than 1.5 A over an output-voltage range of 1.25 V to 37 V. It requires only two external resistors to set the output voltage. The device features a typical line regulation of 0.01% and typical load regulation of 0.1%. It includes current limiting, thermal overload protection, and safe operating area protection. At least three resistors. Possibly, conversion from AC to DC towards long experimentation if DC battery pack isn’t sufficient (at least 6 volts). The LM 317 is least example. d. Diode to connect driver circuit e. Possibly, an Aixiz module (can be built if such is necessary) f. Suspension frames. g. Dark room 4. Computer Generated Holography (CGH): --Relevant applications of CGH in optics --Basic stages in the synthesis of computer generated holograms: a.Formulating mathematical models of the object and usage of the hologram. b. Computing the mathematical hologram, an array of complex numbers that represent amplitudes and phases of hologram samples in the hologram plane. c. Encoding samples of the mathematical hologram for recording them on the physical medium. At this stage, which we refer as to hologram encoding, mathematical holograms are converted into an array of numbers that control optical properties of the physical recording medium used for recording the hologram. d. Fabrication of the computer-generated hologram. 5. Review of diffraction grating and uses 6. Anatomy and properly coordinated activity demonstrations using CDs and DVDs as diffraction grating and respective diffraction orders (explanation of groove spacing and overlapping of spectral orders). A means that’s cheap and analogous to towards the goal for general CGH. 7. Diffraction from CGH to alter wave front 8. Phase function influences: position on substrate and gaps between CGH lines. CGH phase curve. Intensity not being a considerable influence (if there’s sufficient light). 9. Holography by CDs or DVDs as analogy to holography from general CGH. 10. Recalling the physics of lasers and the thoroughly representative mathematical modelling. 11. Confirmation on whether DVD laser has mode as a Laguerre-Gaussian (or Gaussian) beam. If not identify what lasers are defined by such. The CGH to producing a Laguerre-Gaussian (Gaussian) beam resembles diffraction grating, but to have a "fork" in the centre that gives rise to the optical vortex. Analysis of modelling for the creation of “fork”. Mathematical modelling and laws of physics for optical vortex. 12. Based on (4), (6) through (11), can a domestic “fork” be synthesized (created)? https://arxiv.org/ftp/arxiv/papers/1605/1605.00831.pdf Chen, S. et al. (2016). Geometric Metasurface Fork Gratings for Vortex-Beam Generation and Manipulation. Laser and Photonics Reviews, Volume 10 Issue 2, pp 322 - 326 Possibly, say, (another DVD or Blu Ray) burner configured in a manner to write the slits of preference based on (4) and so forth. 13. CGH with fork in the centre to produce an optical vortex with a “topological charge” of 1, namely, the phase increases by 2*pi in a circular trajectory around the optical vortex, following, wave front spirals (once) around the axis per wavelength. Optimising for multiple spirals. Observation of diffracted orders from the "forked" grating possessing a dark "hole" in the centre, being typical of LG beams; point being a phase singularity where having zero electric field intensity for the beam Galvez, Enrique & Smiley, N. & Fernandes, N. (2006). Composite optical Vortices Formed by Collinear Laguerre-Gauss Beams. Proc SPIE. 6131. Li, F. et al. Images Rotation and Reflection with Engineered Orbital Angular Momentum Spectrum. Appl. Phys. Lett. 113, 161109 (2018) Pachava, S. et al. (2019). Generation and Decomposition of Scalar and Vector Modes Carrying Orbital Angular Momentum: A Review. Opt. Eng. 59(4) 041205 Turpin, A., Pelegrí, G., Polo, J. et al. Engineering of Orbital Angular Momentum Supermodes in Coupled Optical Waveguides. Sci Rep 7, 44057 (2017). 14. Recognition of the straight through "zero-order" beam, and the first diffracted orders possessing a charge 1 optical vortex responsible the dark centre. 15. Twisted photons can baggage more data in each transmission, while also durable or having integrity against interference caused by turbulent air (but yet to be confirmed in in general extreme weather, say meteorological and space). A major goal is the transfer of massive amounts of data with less energy. Lasers with the ability to carry optimal amounts of information involving splitting up light's different wavelengths to funnel more data down one pathway. Holograms permit photons to carry more than just the conventional binary bits of 0’s and 1’s used in modern digital communications. As well, to establish a data carriage ratio between vortex twists and conventional linear lasers (like to vary with wavelengths, etc.). With OAM identify generic equipment that permits data through photons that can be converted/interpreted towards media of interest; identify operational/tuning parameters for integrated system. Constuct system and test (whether audio, video, generic data). 16. Is such a OAM grand scheme integrable with Li-Fi? If not directly efficient, what reception adaptations are required? One to have a stationed fiber optics network system where data is to travel an equivalent distance. Compare to the OAM scheme observing the amount of data for a given period. G. Analysis and investigation experimentation of the following: Renger, J., Quidant, R., and Novotny, L., Enhanced Nonlinear Response from Metal Surfaces, Optics Express Vol 19, Issue 3, pp. 1777-1785 (2011) Special invitation for physics constituents. 1. Additionally, to observe the possible occurrence of the photoelectric effect; towards a photoelectric spectroscopy model and determination of work functions, and compare with actual spectroscopy results; crosscheck spectrograph with professional databases. H. Analysis and experimental investigative replication Special invitation for physics constituents. Quere, F. et al, Applications of Ultrafast Wavefront Rotation in Highly Nonlinear Optics, J. Phys. B: At. Mol. Opt. Phys. 47 (2014) 124004 (23 pp) http://www.femto.sims.nrc.ca/pdf/Quere_JPB_2014.pdf Experimentation is inexpensive as the previous. The issue will be establishing a femtosecond laser pulses and “attosecond lighthouses”, to perform time-resolved measurements of nonlinear optical processes, using “photonic streaking”, or to track changes in the carrier–envelope relative phase of femtosecond laser pulses. I. Engineering Electron microscope and Raman scattering microscope PART A Physics students welcomed as well. Such an experiment is a necessity because it highlights engineering and physics, say ability with constructs and development from non-commercial elements; encourages the advancement of natural talent. 1. Physics and mathematics modelling of particle tracing with magnetic lens. Succeeding such will be simulation for trajectories of charged particles and ions subject to the magnetic lens. 2. Observe and analyse the following: Park, J., et al, Design and Fabrication of a Scanning Electron Microscope Using a Finite Element Analysis for Electron Optical System, Journal of Mechanical Science and Technology 22 (2008) 1734-1746: http://www.j-mst.org/On_line/admin/files/11-12483_1734-1746_.pdf 3. Engaging and practical building an electron microscope with vacuum chamber Scanning Electron Microscope -YouTube (Applied Science): https://www.youtube.com/playlist?list=PLA9renIgK3NanGpSnphOobF8hRPZAychL Schematics and circuit analysis are emphasized (to be simulated as well). Provide the physics and associated mathematical modelling explaining imaging by electrons related to deBroglie wavelength and the atoms of the specimen observed. Confirm theoretically before building microscope the difference in results to anticipate between conductors and non-conductors. Mathematically (and via circuit analysis) verify that the resolving power of a microscope is directly related to the wavelength of the irradiation used to form an image. Relation between voltages and magnifications. Analyse and explain what specifications are needed to build a microscope to examine biological materials (such as microorganisms and cells), a variety of large molecules, medical biopsy samples, metals and crystalline structures, and the characteristics of various surfaces. As well, being a constituent of a production line, such as in the fabrication of silicon chips. Scanning electron microscopes usually image conductive or semi-conductive materials best; verify empirically and review the physics with the associated mathematics. Non-conductive materials can be imaged by coating the sample with a conductive layer of metal. Verify. Explain the physics of how the coating influences imaging. 4. Build electron microscope based on all analysis and development in (3). 5. Comparing (3) and (4). Determine whether theoretical results from (3) can be achieved in phase (4) to a high degree (charts and distributions) via modelling with data acquired, likely to include use of sensors, various meters and so forth. Physics and mathematical modelling must add up throughout. Will analyse the engineering and design for the possibility of construction of such a device. Will determine what materials in constitution for optimal and safe performance of prototype; concerns material science, radiation, power circuitry, electronics specifications, atmospheric insulation, etc. A prototype will be built. PART B The following articles provide sound intelligence towards development of lab Raman scattering microscopy. Will have “top-down” and “system-level” analysis and development. Physics will be enforced throughout with the resulting mathematical descriptions, followed by the engineering that makes the science feasible. Will not dive too much into comprehensive computer engineering details, but certain things should of CIVE should be recognised. --Zhang, X. et al, Label-Free Live-Cell Imaging of Nucleic Acids Using Stimulated Raman Scattering Microscopy, ChemPhysChem 2012, 13, 1054 – 1059 --Lu, F. et al (2015). Label-free DNA Imaging In Vivo with Stimulated Raman Scattering Microscopy, PNAS Volume 112 Number 37 --Wang, O. et al, Mechanisms of Epi-Detected Stimulated Raman Scattering Microscopy, IEEE Journal of Selected Topics IN Quantum electronics, Vol. 18, NO. 1, January/February 2012 J. “Reverse Engineering” the iPod Nano LCD interface (or old cheaper substitute). An (mixed single) oscilloscope and/or pulse generator are key components of activity. For determination of direction of signal sending (interface is going), possibly one may incorporate resistance in probing, forming central dividers, etc. (involves developments of schematics and simulations and probing). Acquire print out of lined up wave forms and write in the binary values. Place in boundaries with bit orders (identify formula involving pixels, bytes, etc., etc.). Determine length, ECC, data ID, where image data starts. Searching for other components information is crucial (thus source of component manufacturing, with security welfare, etc.). Note: bigger devices as well can be cheaper outside of iPod brand. Open to Computer Engineering constituents K. Multiphase Motor Drive System Development Abdel-Khalik, A., S. et al 2016, A Senior Project-Multiphase Motor Drive System Development, IEEE Transactions on Education, vol. 59, 4 Project described has become common place, thus, orchestrating it before senior level or before final senior term will be extremely advantageous. Experimentation will be compared along side design and simulation involving SystemModeler, Modelica, SPICE and Ansys [ SPEED and Motor-CAD by Advanced Electromagnetics Group (Netherlands) or through Motor Design Limited (U.K.)]. Then, compare to industrial scale in terms of power capability, intricacy in various circuit and system components, feedback control or automatic control, etc. Open to mechanical engineering, aerospace engineering and industrial engineering. L. Photonics Reinforcement Out of the following link provided is a variety of experiments beneficial to photonics engineering students. Despite being course oriented such can serve well towards structure and principles in a loose environment. Such experiments may also be of interest to physics constituents. Apply modern economic software applications and economical tools to suit experiments. Other detailed laser and photonics activities listed outside of the link will remain intact. https://www2.ece.ohio-state.edu/~anderson/Photonics_Lab_Manual.pdf M. LIDAR development Can be quite useful to Electrical, Mechanical, Aerospace and Civil engineering and physics students. (1) LIDAR system to be constituted by the following components: Linear Optical Array Sensor Analog Voltage Output Slip Ring (to pass power and signals to rotating scanning head) Encoder (like a RPI-352) IR Filter (interference bandpass filter) Electrical and mechanical parts Main PCB Lens (M12 lens, f ’ = 16mm) M12 Lens Holder (plastic lens holder) Motor Laser Module (3mw 780nm laser module) or one that’s economically efficient STM32F030 (microprocessors, microcontrollers, DSPs/ARM, RISC-Based microcontrollers) or whatever that’s economically efficient Base plate (plastic late or whatever holds bearing and motor) Ball bearing (6806zz) or efficient substitute Note: likely to have a belt connecting motor and slip ring...or developing an overwhelmingly advantageous gear system relating motor to slip ring fixed on base plate. Modest LIDAR parameter gauge to be around: 5 scans per second 180 measurements per rotation Maximum distance around 4 meters Measured accuracy to be around 5 cm at 2m, 10 cm at 3m, etc. Employ optical triangulation scheme towards distance measurement towards establishing consistency in measures with lidar system; likely a means of calibration with error margin determination. Repeat process two or three times comparing with triangulation scheme to observe variation in margin error with respect to larger distance measures. (2) The next step will be to improve this particular system towards acquiring further range and accuracy. When accomplished, build, test and compare to results of first prototype. Also will involve the optical triangulation process. (3) To then engineer the following: Hamad, A., Dhahir, D., Mhdi, B., Salim, W., Laser Distance Measurement by Using Web Camera, IOSR International Journal of Engineering, Vol. 04, Issue 04 (April. 2014), ||V3|| PP 25-28. Range and accuracy data structure must be comparable to all described in (2); this system can actually be viewed as another calibration setup to evaluate the LIDAR system with distance accuracy and issues with range. Before physical activities the method can be simulated in Mathematica and SystemModeler exhibiting crucial simulated data, etc. (4) Next phase will be to analyse and economically engineer the following: Zhang, Y. et al, Accuracy Improvement in Laser Stripe Extraction for Large-Scale Triangulation Scanning Measurement System, Optical Engineering 54 (10), 105108 (October 2015). Again, the prior setup with web camera can serve as calibration for comparing accuracy and range. Then from this article concerning figure 1 and the associated given description in the article, can such a scheme be use to analyses the accuracy of geometrical designs like aircraft wings for comparison with theoretical geometrical design towards aerodynamic efficiency? (5) Concerning (2) where accuracy and range are critiqued by (3), extending such towards the pursuit of environment mapping. (6) Engineer the following David Cambridge. Making a Lidar Scanner in the Home Shop with a Lathe, a pair of STM32s, and a Garmin Lidar Lite -YouTube https://www.youtube.com/watch?v=KGN82vLjguI Note: alternatives to STM32s is possible. Compare to what was developed in (5). N. Distance measurement systems schemes with lasers and their applications Can be quite useful to Electrical, Mechanical, Aerospace and Civil engineering and physics students. Concerns analysis and engineering of the following schemes for distance measurements: 1. Triangulation 2. Telemetry (pulse and phase comparison) via microcontroller 3. Interferometry (may be the most economically hazardous, but a Michelson design may suffice if practical) Each scheme to be accompanied by the respective appropriate distance formula for experimentation concerning the respective properties and components. Also, establishment of respective measurement uncertainties. The mathematics and physics for each scheme must be clear and concise for the whole respective operation process. Before physical activities a means to simulatethe different techniques would be nice. To be followed by engineering and activity implementation with data comparison. Simulated data to be alongside with experimental data. There will be compare and comparison among implemented schemes concerning range capability, accuracy and economics. Such schemes will also be investigated concerning their practicality towards determining deformations, cracks and vibrations in objects (metal sheets, etc., concrete, etc.). Then likely engineered and implemented with data comparison. The mathematics and physics for each scheme must be clear and concise for the whole respective operation process. Notions such as laser ablation, Lamb waves, ultrasound and EMAT may be relevant. O. Relevancy, reinforcement and competency in power engineering analysis of grids and power systems Concerns competency and development out of the following: << EMTP-ATP, OpenDss, MA-OpenDSS, ARTERE/RAMSES, Pandapower, PSAT: Power System Analysis Toolbox + GNU/Octave, MATPOWER + GNU/Octave >> As well, projects can include replication of real grids and systems towards understanding of functions, troubleshooting, micromanagement, etc. Visits to real grids and systems towards observing function and procedural protocols. Note: activity will not be content with one particular software, understanding that one particular software will have special features. Some software will generally serve towards the same purpose while other will not. P. Solar Tracker module First phase concerns crucial understanding of the function of each component and how to properly integrate. Heuristics for code followed by actual programming code building will be authentic. Concerns replication of the following: DIY Solar Tracker || How much solar energy can it save? - YouTube Components: 1x Arduino Nano or other 2x SG90 Servo or other 4x Photoresistor 4x 1kohm Resistor Heuristics for code followed by actual programming code building will be authentic. Will compare stationary placed solar panels with the mobile ones functioning in the solar tracker. Field sites likely to be at high altitudes or in places not influenced by shading from man made objects, vegetation, etc. Second phase concerns developing a large scale model where likely the servos/motors, processing/computing boards and solar panels are the only things not constructed. For third phase will entertain the relevance of MPPT and its integration. MPPT is the acronym for Maximum Power Point Tracker, as the name suggests this device is designed to extract maximum feasible Power = V x I, or wattage, from the panel and deliver it to the load. An MPPT will execute two main actions while in use: --Track the solar panel maximum available power (V x I) and try to deliver the most of it across the output or the connected load. --Monitor that the load does not attempt to hog the panel by extracting illegitimate or unfeasible amount of watts either due to a short circuit or shunting of the output leads of the MPPT. If such a condition is detected the MPPT's "shut down" feature instantly triggers in order to correct this unusual or incorrect load situation. The current to the battery is boosted and possibly doubled in order to keep the net input to output wattage ratio constant and efficient. Thus, the system ensures that the battery which even though has a much lower voltage specs than the panel continues to get optimum power from the panel, that is at the rate of 12 x 5 amps = 60 watts. This is the most interesting and valuable feature of MPPT chargers compared to other forms of ordinary chargers. However, when sun light begins diminishing as the day proceeds to dusk, the panel wattage also begins to deteriorate proportionately, so what does the MPPT do now? Does it continue to offer the same amount of power that it was delivering during the peak sunshine? The answer is no, the MPPT simply keeps tracking the maximum available power from the panel and reproduces the same at its output load. Although the MPPT is still trying to keep the input/output ratio to unity by rendering the same amount power to the battery that's being provided by the panel, but it's unable to restore sun ray's angle of incidence. Some journal article guides for analysis and construction: --Hohm, D., & Ropp, M. (2003). Comparative study of maximum power point tracking algorithms. Progress in Photovoltaics: Research and Applications, 11(1), 47-62. --W. M. dos Santos and D. C. Martins, "Digital MPPT technique for PV panels with a single voltage sensor," Intelec 2012, Scottsdale, AZ, 2012, pp. 1-8. --Balakishan, C., Sandeep, N. and Aware, M. V. Design and Implementation of Three-Level DC-DC Converter with Golden Section Search Based MPPT for the Photovoltaic Applications. Advances in Power Electronics Volume 2015, Article ID 587197, 9 pages --Z. Mehmood, Y. Bilal, M. Bashir and A. Asghar, "Performance analysis of MPPT charge controller with single and series/parallel connected PV panels," 2016 International Conference on Intelligent Systems Engineering (ICISE), Islamabad, 2016, pp. 278-282. --A. Elewa, M. M. Elkholy and M. El-arini, "Adaptive MPPT for PV systems under partial shadow condition and different loads using advanced optimization techniques," 2017 Nineteenth International Middle East Power Systems Conference (MEPCON), Cairo, 2017, pp. 152-162. --Ba, A., Ehssein, C.O., Mahmoud, M.E.M.O.M. et al. Comparative Study of Different DC/DC Power Converter for Optimal PV System Using MPPT (P & O) Method. Appl. Sol. Energy(2018) 54: 235. --http://www.ti.com/lit/ug/tidu404/tidu404.pdf For fourth phase will investigate the use of solar tracker versus MPPT. For the solar panels to be applied for both solar tracker methodology and MPPT methodology, the area measure, generation and constitution must be identical. Field sites likely to be at high altitudes or in places not influenced by shading from man made objects, vegetation, etc. Efficiency determination will be the most significant quantity of measure, however, power usage to operate the mechanism will also be considered. As scale of set ups increase which mechanism will become more efficient w.r.t to operation in time? Namely, such concerns beyond daylight hours each day in the long run. Suh doesn’t only concern the size increase of solar panel modules, but also development of vast energy collection grids. Will efficiency be dwarfed by operational power demand over time? Q. Parameter Estimation of Induction Motor (IN DEVELOPMENT) PART A Will concern ourselves with 2 - 3 types of induction motors Development progression --> --Circuit Model of respective Induction machine --Modelling and simulation of respective --Description of Method # X --Flow Chart of Method # X --Computational code development for chosen methods --Development and implementation of of experiment 1.Hardware used in experiments consists of DSP board, lock-out module, isolation module, IPM, XOR Gate, Interface Box, current and voltage measurement modules and power stage, to gether with motor . Must block diagram with integration with procedure arrows. Note: today there’s much generic options that are cost effective for experiment 2.Modulation Technique 3.Calibration of voltage measurement module 4.Calibration of voltage measurement module 5.Measurement of Torque & Speed 6.Measurement of Rotational Losses 7.Verification of core loss estimation 8.Verification of RMS value calculation of stator phase current 9.Verification of RMS value calculation of stator phase to neutral voltage 10.Verification of estimation of power factor 11.Simulation of induction motor --Verification of Speed Estimation Methods 1.Verification of estimation of power factor 2.Simulation of induction motor --Table of Calculated parameters from no-load and locked rotor tests results and estimated motor parameters for particular motor for the different applied methods. Possible assist for activity development--> ÇALAR HAKKI ÖZYURT. (2005). Parameter and Speed Estimation of Induction Motors from Manufacturers Data and Measurements. Middle East Technical University: https://etd.lib.metu.edu.tr/upload/12605774/index.pdf Note: it’s for the participants to analyse and determine accuracy of such paper if to be the used as a guide. Four example methods (out of the many possible methods) --> Haque M.H. (1993). Estimation of 3-phase induction-motor parameters, Electric Power Systems Research Lindenmeyer D., Dommel H.W., Moshref A., Kundur P. (2001). An Induction Motor Parameter Estimation Method, International Journal of Electrical Power & Energy Systems Pedra, J. , Corcoles, F. (2004). Estimation of Induction Motor Double-Cage Model Parameters From Manufacturer Data, IEEE Transactions on Energy Conversion Wu, R., Tseng, Y. and Chen, C. (2018). Estimating Parameters of the Induction Machine by the Polynomial Regression. Applied Sciences, 8, 1073 PART B Estimate motor parameters using motor control blockset parameter estimation tool: https://www.mathworks.com/help/mcb/gs/estimate-motor-parameters.html Analyse and pursue development. R. Safety protocols of high voltage facilities and measurements Note: students may or may not not have direct engagement with high voltage components of circuits, electrical/voltage lines, controllers, measurement tools, etc. Observance with certified professionals with equipment, safety gear, protocols and the enforcement of regulations. Facilities likely will include T&TEC and TSTT (or utilities for ambiance in question). Students will identify crucial industrial devices and components of facilities similar to what are found in a Siemens catalog, where respective purpose, specs, longevity limitations and handling are lectured and/or demonstrated. Safety gear for students required with likely signing of acknowledgement, etc. Topics from the high voltage engineering course can be directed to professional personnel. Other possible issues to address are shielding against corrosion, lightning activity, humidity, precipitation, trespassing and solar radiation. S. Security for power grid networks Open to computer science students. Will be an extension of activity (O). Apart from becoming well acquainted with power modelling and simulation. Based on design of power grids, students will properly identify where and how LAN, WAN, Wifi, IoT, etc. will be situated. Perhaps some exposure to SGAMToolbox RAMI 4.0 Toolbox https://code.nsa.gov after comprehension of respective power grid system at hand towards developing fast security system designs and tools in power grids. A major directive is to understand the role of various tools, applications, processes and how to tangibly apply or operate such towards a network, communications. Will include knowing how to integrate systems and communication, and how to appropriately implement procedures and code. Will include understanding of intrusion aware from monitoring of “special time varying geometrical curves”. Active participation will be modelled based on the following two journal articles; maybe more will be needed. Will also incorporate operational use of the following --> https://code.nsa.gov T. High Precision Digital Frequency Signal Source Based on FPGA Yanbin, S., Jian, G., Ning, C., High Precision Digital Frequency Signal Source Based on FPGA, Physics Procedia 25 ( 2012 ) 1342 – 1347 Observe and analyse article. Determine what tools and equipment are necessary towards accomplishing geometrical outputs. Develops logistics and engineer experimentation for such. Then to determine practical applications for such; pursue such applications in experimentation, with means towards confirmation that exhibited geometries and/or data are credible. Can possibly augment with succeeding analysis and experimentation of the following if economically feasible: Nunez-Perez, J. C. et al, Test Bed for Low-Cost Measurement of AM/AM and AM/PM Effects in RF PAs based on FPGA, 2015 International Conference on Electronics, Communications and Computers (CONIELECOMP), Cholula, 2015, pp. 87-92. Nunez-Perez, J. C. et al, FPGA-based Test Bed for Measurement of AM/AM and AM/PM Distortion and Modelling Memory Effects in RF Pas, INTEGRATION, the VLSI journal 52 (2016) 291–300 Open to Computer Engineering constituents. U. Physics and Engineering for Pulsed Nuclear Magnetic Resonance This activity concerns understanding the physics of NMR and how to engineer the means to accomplish such. There will be two engineering approaches towards demonstrating the phenomenon where the results of both experiments will be compared. Databased will also be used for confirmation with such two. Activity is primarily towards physics and engineering, however for chemistry constituents pursuing any NMR activity for determination of the structure of compounds, etc., they will be guided by engineering constituents. I. Some idea: Kauppinen, J. and Partanen, J. (2001). Chapter 7, Nuclear Magnetic Resonance (NMR) Spectroscopy. In: Fourier Transforms in Spectroscopy. Hoboken: John Wiley & Sons, Incorporated. II. Modules for pursued experimental activity: Takeda, K., OPENCORE NMR: Open-source Core Modules for Implementing an Integrated FPGA-based NMR Spectrometer, Journal of Magnetic Resonance, Volume 192, Issue 2, June 2008, pages 218-229. For OPENCORE NMR and OPENCORE NMR 2 there must be accountability with understanding the role of the crucial components and the relations among each other. OPENCORE NMR has a website. Namely, there is need of application that permits graphs to be compared on a common axis for respective sample or whatever. Alternatives to OPENCORE NMR and OPENCORE NMR 2: -- Open Source Console for Real-Time Acquisition (ORCA) -- COSI Transmit Anand, S.et al, “A Low-cost (<$500 USD) FPGA-based console capable of real-time control”, Proc Intl Soc Magn Reson Med, Paris, 2018, # 948 -- OpenVnmrJ A primitive case experimentation: Takeda, K. et al, Elemental analysis by NMR, Journal of Magnetic Resonance, Volume 224, 2012, Pages 48-52 Such to be compared with experimentation setup with FPGA Note: choice of strength of magnetic is dependent on user, but lower strength yields inferior results; some magnetics need not require usage of super cooled elements. However, if the case arises, a safe economic means: https://benkrasnow.blogspot.com/2008/08/diy-liquid-nitrogen-generator.html Liquid Nitrogen Generator - Overview -YouTube Pursue complimenting process control that’s tangible and “fluid” throughout if possible. Results from NMR to be compared with professional databases. NOTE: CCPN for NMR may be invaluable here and there. V. Immersion into Photonic Integrated Circuits and Silicon Photonics The following software can prove to be highly convenient, being practical, providing meaningfulness with technology and design: 1. Photon Design 2. From Synopsys RSoft Component Design + OptSim Circuit + Optodesigner Such software concern PIC builds and simulation (total and for components). Photonic Integrated Circuits – YouTube from Nptelhrd is only a rundown. Short but concise history of the emergence of photonic integrated circuits with comparison to EICs and their potential or practical uses. Applications will not be restricted to fiber optics communications. Will also treat PICs integrated with EICs and the practical applications. Simulating PIC integrated with EIC would be nice, if known software are capable of such. The following examples are not focus examples but rather being additional information: --K. Takano, C. Sugano, M. Inubushi, K. Yoshimura, S. Sunada, K. Kanno, and A. Uchida, "Compact Reservoir Computing with a Photonic Integrated Circuit," Opt. Express 26, 29424-29439 (2018). --Carroll, L., et al, Photonic Packaging: Transforming Silicon Photonic Integrated Circuits into Photonic Devices, Appl. Sci. 2016, 6, 426 --Behroozpour, B. et al, Electronic-Photonic Integrated Circuit for 3D Microimaging, IEEE JOURNAL OF SOLID-STATE CIRCUITS, VOL. 52, NO. 1, JANUARY 2017 Display examples with their integration and experimental operation alongside simulations with identification of their characteristics (wave forms or curves), if feasible. W. Transmission via Fiber Optics Constructing a fiber optic transmission system in terms of a solid-state semiconductor Class IIIb laser kept at a maximum of 5 mW (blinking and not staring would be greatly appreciated). Identifying circuit make up of solid state device components and their behavioural characteristics are important. As well block diagrams and general circuit analysis very much appreciated. Will need a spice simulator and SystemModeler (or whatever) concerning premature analysis and development. Goals are transmission of the following data through a fiber optic cable: 1. Audio. Hint example, sending audio signals by modulating the drive current of a laser with the audio output of a standard CD player. Propagating this signal through two different mediums, namely an air gap of about 10 centimeters and 3 meters of single-mode fiber optic cable. Receiving the signal using a photo-detector coupled with an amplifier, and demodulated the signal using a linear correspondence between audio voltage input, laser intensity, and voltage output. At last, plugging in a signal spectrum analyser, as well as a standard pair of computer speakers, into our amplifier to see if there was any appreciable loss in sound quality. Implement experimentation for different Hertz ranges (involving hearing and vocals). 2. Video 3. Packet-based information like that of TCP/IP, UDP, and other internet-based transmission schemes. X. Alternative means of environment mapping and distance determination Analyse, develop, engineer the following: Martel, J., N., P, et al, High-speed Depth from Focus on a Programmable Vision Chip Using a Focus Tunable Lens, Circuits and Systems (ISCAS), 2017 International Symposium on Circuits and Systems (ISCAS), May 28-31, pages 1-4. 2017. Such will be compared to environment mapping and distance feats accomplished in activity (N). Y. Electro-optic sensor for electric field measurement. Electro-optic sensor for magnetic fields (I). Magnetic field sensor: 1. Zhang, J., et al, An Integrated Electro-Optic Magnetic Field Sensor Based on Reflected Mach-Zehnder Interferometer, Optik 157 (2018) 315–318 2. Luo, Y., et al, A Novel Optical Fiber Magnetic Field Sensor Based on Mach-Zehnder Interferometer Integrated with Magnetic Fluid, Optik - International Journal for Light and Electron Optics 174 (2018) 252–258 3. Analog magnetic sensor with Arduino Uno (or whatever) and (volt)meter. Needs some programming 4. Economic commercial magnetic field sensor All developed apparatuses and contraptions to be compared in measuring various magnetic sources simultaneously. Will use various magnets of different sizes and strengths. One places respective sensors evenly space here magnetic source is of the same distance to each respective sensor. One have magnetic source displacement be linear with respect to all sensors along a ruler or measurement stick; distance apparatus with units labelled can be quite useful. Moved back and forth by a linear stepper motor driven a board (confirm whether one board can do simultaneous processing with analog magnetic sensor to possibly resource the use of resources). Stepper motor to be aligned parallelly to measuring stick. Note: magnetic fluid can be made, say, use of MICR (copier) toner with oil, and magnetite based. Note: oscilloscopes can probably be replaced by smartphone with appropriate apps if practical. Note: for the commercial sensors one must detail their circuit constitution and how they work. (II). Electric field sensor: 1a. Zeng, R., et al, The Development of Integrated Electro-Optic Sensor for Intensive Electric Field Measurement, 2007 IEEE International Symposium on Electromagnetic Compatibility, Jul. 9-13, 2007 1b. Zeng, R., et al, Design and Application of an Integrated Electro-optic Sensor for Intensive Electric Field Measurement, IEEE Transactions on Dielectrics and Electrical Insulation Vol. 18, No. 1; February 2011 2. Xiao, D., et al, A Power frequency Electric Field Sensor for Portable Measurement, Sensors (Basel) 2018 April; 18 (4): 1053 3. Another sensor with the following constituents: receive antenna, transmit antenna, analog front-end with sampling (ADC) towards demodulation(software), transmit resonator concerning waveform generation (timer-0-output compare). https://courses.cs.washington.edu/courses/cse466/10wi/pdfs/lectures/efield.pdf 4. Economic commercial electric field sensor To then determine if all candidates can be applied to the same experimentation comparing as in the magnetic field case. Note: oscilloscopes can probably be replaced by smartphone with appropriate apps if practical. Note: for the commercial sensors one must detail their circuit constitution and how they work. Z. TBA AA1. Measurement of Dynamic Deformations Lloret et al., Measurement of Dynamic Deformations Using a Path-Unbalance Michelson-Interferometer Based Optical Fiber Sensing Device, Opt. Eng. 42(3) 662–669 (March 2003) Develop experimentation, compare with structural analysis software (and possibly evaluation machinery). Open to Mechanical Engineering, Aerospace Engineering and Civil engineering. AA2. Low-Cost Detection of Lasers Benton, D., M, Low-Cost Detection of Lasers, Optical Engineering, 56 (11) , 114104 (2017) Analyse, develop and test. AA3. Shaft Misalignment --Simm, A., et al., Laser Based Measurement for the Monitoring of Shaft Misalignment, Measurement 87 (2016) 104–116 --Mohanty, A., R., and Fatima, S., Shaft Misalignment Detection by Thermal Imaging of Support Bearings, IFAC-PapersOnLine 48-21 (2015) 554-559 --A. M. Umbrajkaar, A. Krishnamoorthy, R. B. Dhumale, "Vibration Analysis of Shaft Misalignment Using Machine Learning Approach under Variable Load Conditions", Shock and Vibration, vol. 2020, Article ID 1650270, 12 pages, 2020. Compare finds for the 3 types of experimentation. Open to Mechanical Engineering AA4. TBA AA5. Thermoelectric effect with Semiconductors (I) Review of semiconductors, electrical junctions, Fermi energy and bands (II) Review of thermocouples with associated “junctions”. (III) Seedbeck effect 1. Identify effect and the relevance of electromotive forces modifying Ohm’s law by generating currents even in the absence of voltage differences (or vice versa); identify the model for local current density. Identify the electromotive field in terms of temperature gradient and acquire integral form as well. Can one derive the models? 2. Develop circuitry to experimentally demonstrate Seedbeck effect, and apply whatever tools and measures required for confirmation. Note: towards real systems one must account for resistance and conduction models, both to experimentally verify as well. 3. Then, consider the following text: Kasap, Safa. (2019). THERMOELECTRIC EFFECTS IN METALS: THERMOCOUPLES. First to analyse then to develop experimental verification for theoretical geometric figures, circuits and models in the text to the best of one’s ability with resources they have. 4. Seeback coefficient. Pursuing a descent mathematical model with temperature as the random variable. Can such have probability distribution characteristics (related to semiconductor doping)? (IV) Peltier effect 1. Identify effect and model for Peltier heat. Can one derive the model? 2. Develop a circuit to demonstrate the Peltier effect. Note: towards real systems one must account for resistance and conduction models, both to experimentally verify as well. 3. Establish the relation between the Peltier effect and Seedbeck effect. 4. Experimentally verify that if a simple thermoelectric circuit is closed, then the Seebeck effect will drive a current, which in turn by the Peltier effect will always transfer heat from the hot to the cold junction. Note: towards real systems one must account for resistance and conduction models, both to experimentally verify as well; experimental verification of relation between the Seedbeck and Peltier coefficients. 5. Can such relation between such coefficients serve as a means of calibration? One must clearly identify the crucial role that junctions play in effect and models. 6. Experimentally develop a Peltier heat pump and make observations. Note: towards real systems one must account for resistance and conduction models, both to experimentally verify as well. 7. Concerning task (4) apply pulsating DC and alternating currents towards confirmation of all of (4) and (5). Note: towards real systems one must account for resistance and conduction models, both to experimentally verify as well. (V) Thomson effect 1. Identify effect and model. The Seebeck coefficient is not constant in temperature, and so a spatial gradient in temperature can result in a gradient in the Seebeck coefficient. If a current is driven through this gradient, then a continuous version of the Peltier effect will occur. Can one derive the models? 2. Through circuitry experimentally verify the model effect, and the relation between the Thomson coefficient and Seedbeck coefficient. Note: towards real systems one must account for resistance and conduction models, both to experimentally verify as well. (VI) Full Thermoelectric relations 1. Identify model equations 2. Pursue means to experimentally verify such model equations and the first Thomson relation. Note: towards real systems one must account for resistance and conduction models, both to experimentally verify as well. (VII) Material Criteria 1. Efficiency of a thermoelectric device for electricity generation. Compare establish authentic data with results from experimentation investigation. 2. Power factor 3. Reviewing state density with metals and semiconductors with relevance to Fermi energy, conduction band and Seebeck coefficient. 4. Conductivity (electrical and thermal conductivity in competition) and reason for doping semiconductors. Students to gather details of various thermoelectric devices concerning the conductivities mentioned prior and doping descriptions. 5. Overview of Quality Factor (VIII) Thermal Analysis After design and CFD, for each to determine the effect or significance of temperature flow on devices when integrated. Followed by the after effects of fans and other devices applied to heat sinks. 1. Ansys Heat sink design and CFD. Heat sink thermal analysis. 2. Ansys CFD Free Convection Thermoelectric Cooler 3. Ansys CFD Forced Convection Heat Sink 4. Ansys CFD Photovoltaic Free Convection Heat Sink Design (if able) Journals of assistance: Montecucco, A., Siviter, J., and Knox, A., R., The Effect of Temperature Mismatch on Thermoelectric Generators Electrically Connected in Series and Parallel, Applied Energy 123 (2014) 47��54 Chen, Z., et al, Nanostructured Thermoelectric Materials: Current Research and Future Challenge, Progress in Natural Science: Materials International 2012; 22(6): 535–549 Zhang, X., and Zhao, L., Thermoelectric Materials: Energy Conversion Between Heat and Electricity, Journal of Materiomics 1 (2015) 92-105 AA6. Universal Motors Note: it must be determined whether experience with activities <Y> and (AA10) before this activity or together with this activity is most appropriate. Open to mechanical engineering constituents. Phase 1 --> Establish well the components and structure of a real circuit for a universal motor. It’s imperative that one observes and comprehends the physical components of a universal motor that permits the omission of inverters and rectifiers. Alongside such analysis and before field experimentation it would be highly recommended that students become well immersed in electromagnetics software. Such software gives quality access to ideal motor designs, characteristics and performance. Ansys Electromagnetics may serve well, while alternatives such as SPEED and Motor-CAD by Advanced Electromagnetics Group (Netherlands) or through Motor Design Limited (U.K.). Such software findings can later be compared to field experimentation results. Phase 2 --> Knowledge of at least ODE will be required to make sense of characterising curves or solutions. What major commonalities and disparities are observed between SystemModeler/SPICE/Modelica performance analysis and software mentioned in phase 1? Emphasis on both AC and DC abilities of universal motors. One should have reference circuit layouts and schematics for universal motors from companies such as General Electric and others. Interest in developing the following: SCR speed control unit Feed-back regulated SCR speed control Triac speed-control Torque control Direction control After modelling and control to make use of SPICE simulator, systemModeler/Modelica, etc. etc. Means to rest developed controllers. Then, how are all such controls integrated to perform harmonically? Phase 3 --> For additional field experimentation consider the following journal article: -- H. Xu, K. King and Y. Jani, "High Performance DC Chopper Speed and Current Control of Universal Motors Using a Microcontroller," 2007 IEEE Industry Applications Annual Meeting, New Orleans, LA, 2007, pp. 701-705. Before pursuing experimentation based on such journal article identify the structure of a chopper circuit and simulate to acquire the ideal characteristics. Determine whether a chopper circuit can be used as a substitute for a converter. Compare simulations between converter and chopper to to observe any similarities in behaviours. Is there more versatility with the chopper circuit? Then commence with experimentation similar to what is observed in journal article. Pursue torque and direction as well. If there’s any possible AC counterpart for above journal article (includes torque and direction), then develop such field experimentation. AA7. Optical Spectroscopy http://ipl.physics.harvard.edu/wp-uploads/2013/03/191a8.pdf Note: LabView is not mandatory, say, there are various substitutes to consider. Specified camera and lasers can be substituted with more economic substitutes, etc. Highly interested with applying setup to other items instead of hydrogen alone. Compare with professional databases for confirmation. Open to physics and chemistry students. AA8. Quantum Physics Immersion Same as the activity found in physics (see physics post) AA9. Infrared Cloaking Use the following journal article. Analyse and try to engineer the theoretical experiments in the journal articles: Mohamed Farhat, Pai-Yen Chen, Sébastien Guenneau, Hakan Bagci, Khaled Salama, et al.. Cloaking through cancellation of diffusive wave scattering. Proceedings of the Royal Society of London, Royal Society, The, 2016, 472 (2192) Farhat, M., Chen, P., Bagci, H., Amra, C., Guenneau, S., & Alù, A. (2015). Thermal invisibility based on scattering cancellation and mantle cloaking. Scientific Reports, 5, 9876. Based on modelling one may acquire parameter values for effective materials that can produce considerable results. Nevertheless, one may possibly not find or have available the optimal materials to accomplish results, however making use of semi effective materials to accomplish results is possible. Will also try to observe any significant evasion of infrared sensing. Infrared imaging for temperature readings over time to be used for confirmation of experiments administered. Radio waves also to be applied as temperature readings to be compared with infrared. Radio waves are also excellent for determining distance, speed and composition of source. Will also try to observe any significant evasion of radio wave observation. Open to Aerospace Engineering, Civil Engineering and Physics constituents. AA10. Primitive Electromagnetics Open to physics constituents. 1. Capacitive Rain Gauge: Students design a gauge that is sensitive to the fluid level in the gauge. This gauge is based on the principle that capacitance is dependent on the dielectric constant of the material between two conductors. Construct a container which will catch rain water in such a way that the volume of water will alter the capacitance of a home-made capacitor. In its simplest form, the container is two cylinders where the smaller one fits inside the larger one. Both cylinders are made of some conductive material and become the two sides of a capacitor. The cylinders are electrically isolated from one another and the rain water fills in the space between the cylinders thereby altering the measured capacitance. Students can measure the capacitance by making the capacitor the frequency determinant in an oscillating circuit and measuring the change in frequency by counting cycles over a fixed period of time. Of media besides rain likely will be pursued. Phases include-- Pursuit of solution Construction of the capacitor Method of measurement and calibration Comparison of Theory to Observation and Identification of Potential Enhancements Compare with meteorological data for respective ambiance if meaningful. 2. Transmission Line Characteristics: Students must calculate characteristic impedance and propagation speed of a coaxial cable based on measured dimensions. The two conductors of a transmission line make electric field measurements simple since we only need measure the electric potential between the two conductors. Therefore, one needs only derive a relationship between voltage and current, which is much easier to measure than the relationship between electric and magnetic fields. The time dependent voltage is, of course, related to the current through the characteristic impedance. This project can be conducted under the pretext of a power company or communications company who want to locate faults in their transmission lines. Characteristics-- Students are asked to find Velocity of propagation in the transmission line Length of the transmission line and use of various methods Attenuation coefficient of the transmission line Impedance of an unknown termination. Initial conditions-- Equipment need is an oscilloscope, function generator, transmission line, and various terminations for the line. Students are given a long length of coaxial cable to use as the transmission line. The minimum usable length depends on the equipment available. For example, if using a 100 MHz oscilloscope with a standard function generator, approximately 50 m of cable is needed. This project is simplified by using 50 Ω coaxial cables terminated with BNC connectors, typically the same as the lab equipment. Generally, students are given the characteristic impendance of the line, but it could be calculated by analysing the line with a known termination. 3. DC Electric Field Probe: Students design a non-contact probe that can detect the presence and polarity of a static (or slowly varying) electric field in air. Despite only requiring a small number of components to complete it pulls together several core concepts from electromagnetics, circuits, and transistor theory. Identifying that the DC impedance of space is relatively high. Referring to the DC impedance which is infinite for vacuum and very high for standard temperature and pressure conditions, which is not to be confused with the characteristic impedance of free space of 377 ohms. Students must recognize that the input impedance for an electric field probe must also be very high otherwise the probe will effectively “short” the electric field. A JFET transistor is well suited for this task. We further take advantage of the fact that the conduction channel from the drain to the source of the transistor is partially open when the gate is unbiased (floating). This allows the transistor to be sensitive to input polarization. In other words, if we use the output of the transistor to drive a resistive load, an unbiased gate will yield and intermediate voltage. A common type of circuit uses an n-channel JFET. Therefore, as the voltage of gate decreases, or becomes negative with respect to the source, the conduction channel closes and the voltage across the output resistor goes down. As the voltage of the gate increases the conduction channel opens and the voltage across the output resistor goes up. We can than feed this signal into two separate comparator circuits: one inverting and one non-inverting. The output of these comparators is coupled to LEDs in order to display the polarity of the field. Students can experiment with various ways to set the comparator thresholds, but there are circuits that exhibit methods for creating self-calibrating thresholds. One last consideration is the probe itself. Obviously, this circuit is sensitive to noise due to its high input impedance. Care should be taken to shield the circuit from electric field everywhere except the active portion of the probe. This can be effectively achieved by creating a probe from a section of coaxial cable with the outer conduction stripped back a short distance. In this sense it is the polarity of the electric field between the inner and outer conductors that will be detected. For best results the rest of the circuit should be placed in a shielded metal enclosure. 4. AC Current Meter: Students design a non-contact AC current meter. This project uses the AC current measurement to reinforce three core areas of electrical engineering: Electromagnetics-- Students must understand the relationship of current, magnetic fields, and electromotive force (emf) in order to make a current meter. Optimization-- In practice making a probe to detect current can be as simple as placing a loop of wire near the current to be measured. As an added layer of complexity, students can be asked to create a probe that is relatively insensitive to the position of the current that one wishes to measure while also being insensitive to neighbouring currents and magnetic field that we do not wish to affect the measurement. Basic circuit theory-- The emf in a wire loop is natively proportional to the time derivative of the magnetic field and in turn the time derivative of the current. This relationship is fine as long as the user is willing to do some post measurement integration to determine the true current. Alternately, the current probe can be turned into part of a self-integrator circuit so that the output is directly proportional to the current. Consideration of the relationship between EMF voltage, magnetic field penetrating a surface of a coil of wire with a number of turns. The magnetic field can be found approximately as the field from a long straight filament of current. The magnitude of the signal is determined by several factors including where the probe (coil) is placed relative to the object current we wish to measure. By experimenting with various geometry students may find that by passing the object current through the centre of a toroidal coil that the magnitude of the signal is relatively insensitive to the position of the object current as long as the current passes somewhere through the centre of the toroid. We can further improve performance by running one of the leads of the coil back along the axis of the toroid as shown. This will make the probe insensitive to currents that do not pass through the centre of the toroid. This configuration is sometime referred to as a Rogowski coil. Finally, processing the signal to obtain the true current requires integrating the signal over time. This can be done post measurement, or one makes the probe self-integrating by adding a small resistance parallel to the coil. The integration will be valid for times that are short compared to the L/R time constant of the circuit, where L is the inductance of the probe coil itself. 5. Metal Detector: Students design a metal detecting device based on mutual inductance. Metal detection can be done in a variety of different ways. Here we will outline two basic methods for metal detection. Both methods rely on the modification of the inductance of a circuit in the presences of a metallic object. Both detection scenarios rely on the fact that conducting materials have a diamagnetic response in the presence of an AC magnetic field. This diamagnetic response will lower the effective inductance of any coil that is near the metallic object. This turns out to be true even for ferromagnetic conductors like iron as the diamagnetic response is higher for most frequencies. Method 1—Mutual Inductance-- This method is perhaps the more primitive of the two. Two coils, a source coil and a detection coil, are placed close to one another (like the primary and secondary coils of a transformer). The source coil is driven with a voltage of some predetermined frequency. The optimal frequency depends on the physical attributes of the coil but is not terribly important. An emf in induced in the detection coil. Care should be taken that the diameter of the detection coil is less than or equal to the diameter of the source coil. As the mutual induction goes down in the presence of a metallic object so will the amplitude of the emf product on the detection coil. This amplitude change can easily be visualized by converting the output AC signal to DC using a rectifier bridge and a low pass filter. Once the output has been converted to DC the signal can be fed into a comparator with an adjustable threshold and displayed with an LED. Method 2—Self Inductance-- This method requires only one coil and relies on the fact that the self-inductance of a coil will diminish in the presence of a metallic object. If the inductance of the coil is made to be part of an oscillator circuit, then the oscillation frequency will change in the presence of a metal. If the output of oscillator is fed into a frequency to voltage converter as shown one can again use a comparator and LED to flag the presence of a metal. Alternatively, the oscillator output can be used to drive a speaker such that the tone of the sound is proportional to the size and/or location of the metallic object. We found that by measuring the frequency with a microcontroller that this method was sensitive enough to distinguish between common US coins. 6.Conclusions Additional lab exercises: Pejcinovic, B. and Campbell, R. L., Project-Based RF/Microwave Education, Proceedings of the 45th European Microwave Conference, IEEE 7-10 Sept 2015, Paris, France Venkataraman, J., Project Based Electromagnetics Education, IEEE 2009 For either of articles provided if software mentioned are obsolete then likely software from given list will be excellent substitutes. SystemModeler provides operational performance that’s faster than Mathworks tools and SystemModeler’s displays are not archaic. AA11. Plasma Propulsion (CHECK PHYSICS POST) AA12. Telemetry operations Open to computer science constituents Will take on in depth design structure and role of hardware components, logistics and hardware interfacing. Will then proceed with active implementing telemetry networks for motion of vehicles, possibility of agriculture grids, meteorology, measurements, etc. Will also pursue some tasks with C/C++ programming development. Will also include the practical implementation with software such as Snap Telemetry and Open MCT with independent active hardware networks, and “public clouds”. Beginner field experiment ideal example components (don’t have to be exact): -Omilex development board -Atmega328 at 16Mhz with Arduino Bootloader. -XBee Socket and 3.3V powered (I've included some holes near to the antenna so you can hold it with a strap) . -Can be powered with 2 and 3 cell LIPOS (diode protected and regulated). -Huge 4 line screen with backlight, very clear under the sun! (2 pots to control the backlight and contrast). -FTDI port to upload code, also the boards is ready to be programmed with XBee -Six button to navigate and change screen and options. -Very noisy buzzer that can be used to alert you when it has low battery or low altitude. -6 I/O analog pins available, including the I2C port. -2 powered SERVO OUTPUTS (Tilt & Pan) than can be used to control a directional antenna (NICEE!). -Extra 3.3V and 5V volts outputs. -Status LED's. -The software is ArduPilot compatible and Open Source (out of the box). Concerning such components students are to figure out what they can do concerning the wide range of possible applications. Then, proceed with development. This is just one case example. Case 2: Easy Arduino Data Logging and Telemetry – YouTube GPU-Accelerated Arduino Data Logging and Telemetry - YouTube Necessarily expand “Show more” on both videos. As well, if one can develop a C/C++ analogy then that would be nice. Concerning the robotic vehicle with “system curves” on telemetry viewer, confirm whether development in SystemModeler will lead to similar “system curves” if the same operational tasks are carried out for both. AA13. The physics and engineering at the root of fiber optics temperature sensing Fiber optics temperature sensors are not cheap. For the following journal articles analyse, comprehend the physics, mathematical models, then proceed with developing experimentation for temperature sensing with fiber optics, and compare results to that of infrared imaging measurements, radio wave measurements and contact measurements: Malik, J. V. et al, Effect of Temperature on Photonic Band Gaps in Semiconductor-Based One-Dimensional Photonic Crystal, Advances in Optical Technologies, Volume 2013, Article ID 798087, 8 pages Kumar, A. et al, Wide Range Temperature Sensors Based on One-Dimensional Photonic Crystal with a Single Defect, International Journal of Microwave Science and Technology, Volume 2012, Article ID 182793, 5 pages Lu, Y. et al, Temperature Sensing Using Photonic Crystal Fiber Filled With Silver Nanowires and Liquid, IEEE Photonics Journal Volume 6, Number 3, June 2014 AA14. Creating PLC projects and PLC programming Open to mechanical engineering students. Activity will be very progressive in the sense that the minimal requirement will be one year programming, namely, either C or C++ and General Physics I & II completion. For mechanical engineering students in the Systems Control concentration to proceed further with this activity administration must verify that they are successfully progressing with Assembly Language and Embedded Systems courses; each following “summer” or “winter” session activity will become more advanced for seasoned ME systems control students. Logically, activity can be done repeatedly before reaching course in senior year. T. R. Alves, M. Buratto, F. M. de Souza and T. V. Rodrigues, "OpenPLC: An open source alternative to automation, IEEE Global Humanitarian Technology Conference (GHTC 2014), San Jose, CA, 2014, pp. 585-589. OpenPLC Editor to set up a programme with variables and conditions where complexity depends on the project with the associated hardware, amount of different types of sensors, signalling, actuation and operation components. For either the LD, FBD, IL, ST or SFC students must develop the corresponding C/C++ structure to carry out operations; such will be tested against the chosen language out of the five (expressed with acronyms). Note: Controllino modules recognised as industrial grade provide full compatibility with Arduino. Determination on whether there are PLC modules that support different brand controller boards can be pursued. For professionalism students will have upper moderate sessions about connecting systems with open platform communication (OPC). Connecting an operations plant model and a real-world model PLC in SystemModeler to communicate with each other through OPC. The OPCClassic library is used to test a new design of a PLC before it is connected to the real process plant. Data from the process plant model is written from SystemModeler to the OPC server, and is then read by the external PLC. The PLC computes a control signal that is written back to the server, from where the process plant in SystemModeler can access it. Necessarily it’s critical that students are well acquainted with design and configuration software that’s highly applied in integrated architecture; a mainstream or greatly hyped example would be the Rockwell Automation Integrated Architecture. Pursuit of a versatile environment for students programming particular brand controllers coming in a variety of modules; concerns standard and safety configurations, redundancy, communication, motion, and I/O modules. Such is highly dependent of the resources of the utilities in the respective environment. AA15. Transmission Lines Part 1: Physics & Modelling (i) Transmissions lines (relevant usage and description) (ii) Ideal Model and dismissing the case of same phase throughout circuit for voltage (iii) Realistic Model (iv) Characteristics of voltage, current, capacitance, resistance, inductance; behaviours may be different at a given time for different parts of circuit. (v) Developing the transmission lines equations and solutions (vi) The relationship among voltage traveling waves, current traveling waves and the transmission line parameters can be represented by the wave equation, like a system of equations. (vii) Can one also deduce a hyperbolic PDE form for voltage (with and without the additional first terms w.r.t time)? (viii) Backtracking to small sections to include second order derivatives. What are the implications of such with deriving the transmission line equations and the corresponding solutions for (vi) and (vii), respectively ? Are such relevant in realistic constructions? (ix) Forward Waves (x) Forward + Backward Waves (xi) Is Fourier representation appropriate in any setting towards realistic applications? Are exponent forms more appropriate? Assist-> --Rangel, E. G. L. et al, Influence of Input Pulse Shape on RF Generation in Nonlinear Transmission Lines, IEEE TRANSACTIONS ON PLASMA SCIENCE, VOL. 44, NO. 10, OCTOBER 2016 (xii) Power Flow with Waveforms (xiii) Reflections (xiv) Reflection Coefficients (xv) Driving a Line (xvi) Multiple Reflections (xvii) Transmission Line Characteristics Integrated Circuits & Printed Circuit Boards Long Cables (coaxial and twisted pairs) Issue for long cables, high frequencies. Thresholds for audio, computers and radio/TV Emphasis on the adjective RF (xviii) Summary Speed of signals Forward and Backward Waves Voltage and Current Terminating Line Part 2: Simulation Will pursue the definitive system curves that characterise transmission lines (idealistic and real) with SystemModeler or SPICE tools or other based on many particular developments from part 1. Part 3: Determining Parameters for (medium) Transmission Lines (i) Developing ideal formulas for parameters of circuits (ii) Simulations and oscillations can prove useful (iii) The following journal articles also to be applied towards exercises with proposed transmission lines towards parameter estimations -> --Liao, Y. (2009). Some Algorithms for Transmission Line Parameter Estimation. 127 - 132. 10.1109/SSST.2009.4806781. IEEE 2009 --Ritzmann, D. et al, A Method for Accurate Transmission Line Impedance Parameter Estimation, IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, VOL. 65, NO. 10, OCTOBER 2016 Part 4: The physics behind electric shock or electrocution involving transmission lines. Part 5: Building small transmission lines for observation of characteristics Following the construction of (nonlinear) transmission lines, from Part3 the developed ideal formulas and parameter estimation methods can be compared upon built transmission lines. Part 6: Terminators (i) Why and when you need them (ii) Try to simulate characteristics with SystemModeler or other Follow through with activities such as-- #143: Transmission Line Terminations for Digital and RF signals – Intro/Tutorial - YouTube #208: Visualizing RF Standing Waves on Transmission Lines - YouTube Assists -> --Nikoo, M. S, Hashemi, S. M. and Farzaneh, F., Theory of Terminated Nonlinear Transmission Lines, IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES, VOL. 66, NO. 1, JANUARY 2018 --Nikoo, M. S. and Farzaneh, F., Theoretical Analysis of RF Pulse Termination in Nonlinear Transmission Lines, IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES, VOL. 66, NO. 11, NOVEMBER 2018 Part 7: Fault Traveling Waves --Dong, X., Wang, S. and Shi, S., Research on Characteristics of Voltage Fault Traveling Waves, of Transmission Line, Modern Electric Power Systems 2010, Wroclaw, Poland. IEEE --Pineda, J. T. R. and Kurokawa, S., Estimation of Parameters for Faulted Transposed Transmission Lines, 2018 IEEE Electrical Power and Energy Conference (EPEC) Part 8: Field inquiry & demonstrations for Parameter Estimations --> --Compare to actual field meter placement with measurements: Liao, Y., Power Transmission Line Parameter Estimation and Optimal Meter Placement, Proceedings of the IEEE SoutheastCon 2010 Will pursue observation of various types of transmission lines in operation, citing significant purpose of uses and how they are integrated, monitored and regulated in systems. Applications generally range from power to telecommunications. For on-site visits and demonstrations the following articles can be used as preparation or for comparative applications with actual methods applied for parameter estimations. If data from such facilities are accessible to then apply to the various parameter estimation methods and determine whether they are consistent with “the existent” means in such utilities. For some journal articles observation of the system at the utilities site is only possible (T&TEC assist) --> Compare to actual field meter placement with measurements. It’s possible that meter readings history can be compared with parameter estimation methods. Parameter estimation method to be compared with each other and real meter readings history: -Liao, Y., Power Transmission Line Parameter Estimation and Optimal Meter Placement, Proceedings of the IEEE SoutheastCon 2010 --Liao, Y. (2009). Some Algorithms for Transmission Line Parameter Estimation. 127 - 132. 10.1109/SSST.2009.4806781. IEEE 2009 --Ritzmann, D. et al, A Method for Accurate Transmission Line Impedance Parameter Estimation, IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, VOL. 65, NO. 10, OCTOBER 2016 --Li, C. et al, Measurement-Based Transmission Line Parameter Estimation with Adaptive Data Selection Scheme, IEEE TRANSACTIONS ON SMART GRID, VOL. 9, NO. 6, NOVEMBER 2018 --Mousavi-Seyedi, S. S., Aminifar, F. and Afsharnia, S., Application of WAMS and SCADA Data to Online Modeling of Series-Compensated Transmission Lines, IEEE TRANSACTIONS ON SMART GRID, VOL. 8, NO. 4, JULY 2017 --Mousavi-Seyedi, S. S., Aminifar, F. and Afsharnia, S., Parameter Estimation of Multiterminal Transmission Lines Using Joint PMU and SCADA Data, IEEE TRANSACTIONS ON POWER DELIVERY, VOL. 30, NO. 3, JUNE 2015 --Gajare, S. et al, A Method for Accurate Parameter Estimation of Series Compensated Transmission Lines Using Synchronized Data, IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 32, NO. 6, NOVEMBER 2017 <<Open to Physics and Industrial Engineering constituents>> AA16. Engineering a Battery Management System (BMS) Open to Mechanical engineering and Aerospace engineering (i) The battery management system (BMS) concerns safe operation, performance and battery life of battery pack under diverse charge-discharge and environmental conditions; battery pack is unique to car batteries in function. When designing a BMS engineers develop feedback and supervisory control that: --Constantly observes cell voltage and temperature --State-of-charge and state-of-health estimation --Limits power input and output for thermal and overcharge protection --Controls the charging profile --Balancing the state-of-charge of individual cells --Isolates the battery pack from the load when necessary The primitive case -- > making use of equivalent circuits with open circuit voltage, resistors in series, and one or more RC branches. Equivalent circuit must match real batter data at all temperatures, which is required for designing controls. For the several elements in the circuit their behaviour is not constant.; vary depending on the operating conditions in the states of the battery. One can find the behaviour of such parameters by using look-up tables, e-m voltage versus SoC versus temperature. One must be able to tune the parameters to make the simulation match the measured data. Generic or popular process: 1. Import measured data and select estimated data one wants to use 2. Identify parameters and set value ranges 3. Perform estimation 4. Validate estimation [SystemModeler] modelling and simulation capabilities enable BMS development, including single-cell-equivalent circuit formulation and parameterization, electronic circuit design, control logic, automatic code generation, and verification and validation. With SystemModeler, one can design and simulate the battery management systems by: --Modelling battery packs using electrical networks whose topology mirrors that of the actual system and scales with the number of cells --Parameterising equivalent circuit elements using test data for accurate representation of cell chemistry --Designing the power electronics circuit that connects the pack with the controls --Developing closed-loop control algorithms for supervisory and fault detection logic --Designing state observers for state-of-charge and state-of-health online estimation One can apply the battery management system over a range of operating and fault conditions before committing to hardware testing. One can generate C code from SystemModeler models to carry out your control algorithms for rapid prototyping of systems or microcontrollers. SystemModeler generates code from the battery and electronic component models, letting you perform real-time simulation for hardware-in-the-loop testing to validate your BMS before hardware implementation. (ii). A battery management system is any electronic system that manages a rechargeable battery cell or pack. Management involves restricting the battery from operating outside its safe operating range, monitoring its state, computing secondary data, reporting such data, controlling its environment, authenticating it and/or balancing it. The following articles provide some essential explicit and intricate details; experimental or simulation verification of findings in journal articles and textbooks of preference should be pursued. For the case of simulations, one should understand what the respective curve governs. Applying oscilloscopes and curve meters are also possible. Some SOC and SOH guides --> --Textbook: Pop, V. et al, Battery Management Systems: Accurate State-of-Charge Indication for Battery-Powered Applications, Volume 9, Springer 2008 --Cheng, K. W. E. et al, Battery-Management System (BMS) and SOC Development for Electrical Vehicles, IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, VOL. 60, NO. 1, JANUARY 2011 --Unterrieder, C. et al, Battery State-of-charge Estimation Using Approximate Least Squares, Journal of Power Sources 278 (2015) 274e286 --Wang, Y., Zhang, C. and Chen, Z., State-of-charge Estimation of Lithium-ion Batteries Based on Multiple Filters Method, Energy Procedia 75 ( 2015 ) 2635 – 2640 --Campestrani, C., Validation and Benchmark Methods for Battery Management System Functionalities: State of Charge Estimation Algorithms, Journal of Energy Storage, Volume 7, August 2016, pages 38 – 51 --Ren, H. et al, Design and Implementation of a Battery Management System with Active Charge Balance Based on the SOC and SOH Online Estimation, Energy 166 (2019) 908 - 917 (iii). BMS (DIY or Buy) Properly Protecting LI-Ion/Li-Po Battery Packs – YouTube https://www.youtube.com/watch?v=rT-1gvkFj60 All documents provided with products to be print copied multiple times for activity. Colin Hickey and Adam Welsh BMS videos to assist as well. In such one must clearly understand how SOC and SOH algorithms are situated and interfaced to implement them. Operations to somewhat align cooperatively with following outlines (order of articles not implied): --Sung, W. and Shin, C. B., Electrochemical Model of a Lithium-ion Battery Implemented into an Automotive Battery Management System, Computers and Chemical Engineering 76 (2015) 87–97 --Liu, K. et al, A Brief Review on Key Technologies in the Battery Management System of Electric Vehicles, Front. Mech. Eng. 2019, 14(1), 47–64 (iv). Do batteries need cooling? Consider how a cooling system will be configured to regulate the batteries. --Shabani, B. and Biju, M., Theoretical Modelling Methods for Thermal Management of Batteries, Energies 2015, 8, 10153-10177 --Lithium Battery Model with Thermal Effects for System Level Analysis: https://www.mathworks.com/videos/lithium-battery-model-with-thermal-effects-for-system-level-analysis-81886.html -https://www.wolfram.com/system-modeler/examples/energy/battery-stack.html Another concern is how many temperature sensors must be deployed in configuration, and to acquire the true state of the battery cells temperatures rather than just measuring the temperature of the surface of the battery pack configuration. Keep in mind that the external surface of the battery pack configuration isn’t necessarily a true means of monitoring the temperature of battery cells; heat shouldn’t be assumed as uniform throughout the total geometry, namely, the temperature within battery will likely be higher than what is measured on surface of battery. The external environment also has influence on the surface. May or may not, BMS and the various sensors will have their own power source. Succeedingng analysis and development: E. Kim, K. G. Shin and J. Lee, "Real-time battery thermal management for electric vehicles," 2014 ACM/IEEE International Conference on Cyber-Physical Systems (ICCPS), Berlin, 2014, pp. 72-83. AA17. Optics Research 1. Will have recitals for experiments done in the following courses: --Introduction to Optics --Advanced Optics Lab Students must develop certainty about purpose of experiments. Activity open to EE constituents. Will apply Optica integrated with Mathematica, or OSLO, to model and simulate optics laboratory set ups, acquiring ideal values, parameters, imagery, etc. to be compared with orchestrated optics experimentation lab setups. In addition, such pursuit of competency and professionalism will lay the foundation to develop most constructions for various types of spectroscopy (excluding mass spectroscopy). 2. Building a simple functional infrared spectroscopy system with single-board microcontrollers or microcontroller kits. Will then determine its competence and accuracy in terms of the role of vibrational spectroscopy for molecules, compounds, etc., comparing with professional databases. 3. Design and construction for: Raman spectroscopy UV spectroscopy CCD spectroscopy ( https://www.fzu.cz/~dominecf/spek2/vu.pdf ) Physics and mathematical modelling with be established before building and construction. Calibration. Results will be compared with professional databases. 4. TRTCDS Analyse the given journal article, logistics, and investigate the economic feasibility of such optical setup. Will like to develop such optic set up towards experimentation and means of confirming its credibility--> Auvray, F. et al (2019). Time Resolved Transient Circular Dichroism Spectroscopy Using Synchrotron Natural Polarisation. Structural Dynamics, Volume 6, Issue 5, 054307 Students must have at least Introduction to Optics course as prerequisite. AA18. TBA AA19. Photonic Dating Carbon dating only works for objects that are younger than about 50,000 years, and most rocks of interest are older than that. Carbon dating is used by archeologists to date trees, plants, and animal remains; as well as human artifacts made from wood and leather; because these items are generally younger than 50,000 years. Carbon is found in different forms in the environment – mainly in the stable form of carbon-12 and the unstable form of carbon-14. Over time, carbon-14 decays radioactively and turns into nitrogen. A living organism takes in both carbon-12 and carbon-14 from the environment in the same relative proportion that they existed naturally. Once the organism dies, it stops replenishing its carbon supply, and the total carbon-14 content in the organism slowly disappears. Scientists can determine how long ago an organism died by measuring how much C-14 is left relative to the C-12. Review of the physics of unstable C-14 in various objects. Review of radioactive decay modelling (Carbon-14). The level of innovation academia possesses is often an enemy of firms. The ability to be self-sufficient and versatile can be quite trouble for firms’ markets and recognition of market segmentation. Accelerator mass spectroscopy is a premier means of radiocarbon dating. Conventionally, higher education institutions that have passed through the socio-political and socioeconomic gauntlets are those who can afford and operate such massive technologies. However, an alternative means of carbon dating with optics or photonics yields credible results in shorter periods, but with more versatility in mobility, maintenance and training, thus costs can be greatly reduced. Fast overview of the physics and logistics of accelerated mass spectroscopy. Then, the following journal articles are to be analysed, then pursuit of actual development a module towards interactive experimental carbon dating: Mazzotti, Davide. (2013). Verso una datazione ottica al radiocarbonio; Towards an optical radiocarbon dating. Il Colle di Galileo 2 (1), 65 – 68. Labrie, D. and Reid, J, Radiocarbon Dating by Infrared Laser Spectroscopy, J. Appl. Phys. April 1981, Volume 24, Issue 4, pp 381–386 G. Giusfredi, S. Bartalini, S. Borri, P. Cancio, I. Galli, D. Mazzotti, and P. De Natale, “Saturated-Absorption Cavity Ring-Down Spectroscopy,” Phys. Rev. Lett. 104, 110801 (2010) Galli, I. et al, Optical Detection of Radiocarbon dioxide First Results and AMS Intercomparison. Radiocarbon, 55 (2), 213 0- 223. Galli, I. et al, "Spectroscopic detection of radiocarbon dioxide at parts-per-quadrillion sensitivity," Optica 3, 385-388 (2016) Fleisher. A. J. et al, Optical Measurement of Radiocarbon below Unity Fraction Modern by Linear Absorption Spectroscopy, J. Phys. Chem. Lett. 2017, 8, 4550−4556 Unfortunately, access to a mass spectrometer may be needed; or if geological databases for places of interest are available as a means to compare results from apparatuses built. Hopefully the latter prevails. Carbon-14 has a half life of 5730 years, meaning that 5730 years after an organism dies, half of its carbon-14 atoms have decayed to nitrogen atoms. Similarly, 11460 years after an organism dies, only one quarter of its original carbon-14 atoms are still around. Because of the short length of the carbon-14 half-life, carbon dating is only accurate for items that are thousands to tens of thousands of years old. Most rocks of interest are much older than this. Geologists must therefore use elements with longer half-lives. For instance, potassium-40 decaying to argon has a half-life of 1.26 billion years and beryllium-10 decaying to boron has a half-life of 1.52 million years. Geologists measure the abundance of these radioisotopes instead to date rocks. One must understand the respective decomposition with half life model. Will then pursue means to extend spectroscopy to date with such unstable isotopes. Will engineer module(s) to have actual interactive dating. AA20. Global Navigation Satellite Systems (GNSS) – Software GPS Receivers Open to Computer Science constituents. GNSS-SDR + Geopaparazzi, and possibly with hardware-based GPS receivers (if economically feasible). Alternatives to compare with as well. Overall, comprare and contrast with conventional methdologies: constituents, logisitcs, economics Conceptual coguides to comprehend function --> --Huafang Li, Hui Gao, Wei Pei and Song Shi, "Implementation of a software-based GPS receiver," 2013 IEEE 4th International Conference on Electronics Information and Emergency Communication, Beijing, 2013, pp. 140-143. --Hobiger, T. et al. A GPU Based Real-time GPS Software Receiver. GPS Solut (2010) 14: 207–216 --B. Beldjilali and B. Benadda, "Real time software based L1 C/A GPS receiver," 2017 Seminar on Detection Systems Architectures and Technologies (DAT), Algiers, 2017, pp. 1-8. --W. L. Edwards, B. J. Clark and D. M. Bevly, "Implementation details of a deeply integrated GPS/INS software receiver”, IEEE/ION Position, Location and Navigation Symposium, Indian Wells, CA, 2010, pp. 1137-1146. AA21. Electroluminescent Refrigeration (ER) Activity concerns identification and comprehension of the mechanisms responsible for electroluminescent refrigeration. Circuit analysis and design must be well established towards meaningfulness. There must be determination of what size scales such engineering/technology will be effective and how practical can such be. Students to try and design application models to implement electroluminescent refrigeration. Larger than the nano scale, the heat transfer (conduction, convection and radiation) of systematic or system components may or may not become domineering; as well the general respective environment to reside. How resistive will constructions be against higher scale heat processes? In addition, it may be possible to build such systems for electroluminescent refrigeration in software such as ANSYS (and others) to exhibit thermal effects influence in general systems (residing conventional thermal environment). The journal articles below may prove helpful--> --Yen, S., & Lee. (2010). Analysis of Heterostructures for Electroluminescent Refrigeration and Light Emitting Without Heat Generation. Journal of Applied Physics, 107(5). --Lee, K., & Yen. (2012). Photon Recycling Effect on Electroluminescent Refrigeration. Journal of Applied Physics, 111(1). --Liu, X., & Zhang, Z. (2016). High-Performance Electroluminescent Refrigeration Enabled by Photon Tunneling. Nano Energy, 26(C), 353-359. --T. P. Xiao, K. Chen, P. Santhanam, S. Fan and E. Yablonovitch, "Electro-Luminescent Refrigeration Enabled by Highly Efficient Photovoltaics," 2017 IEEE 44th Photovoltaic Specialist Conference (PVSC), Washington, DC pp. 2185-2189. --Chen, K., Xiao, Santhanam, Yablonovitch, & Fan. (2017). High-Performance Near-Field Electroluminescent Refrigeration Device Consisting of a GaAs Light Emitting Diode and a Si Photovoltaic Cell. Journal of Applied Physics, 122(14), Vol.122(14). --Xiao. T. P. et al (2018). Electroluminescent Refrigeration by Ultra-Efficient GaAs Light Emitting Diodes. Journal of Applied Physics 123 , 173104 --T. P. Xiao, K. Chen, P. Santhanam, S. Fan and E. Yablonovitch, "Design of Light-Emitting Diodes and Photovoltaic Cells for Electroluminescent Refrigeration," 2018 IEEE 7th World Conference on Photovoltaic Energy Conversion (WCPEC) (A Joint Conference of 45th IEEE PVSC, 28th PVSEC & 34th EU PVSEC), Waikoloa Village, HI, 2018, pp. 1868-1872. AA22. Nonlinear control of coherent absorption and its optical signal processing applications Xomalis, A. et al (2019). Nonlinear Control of Coherent Absorption and its Optical Signal Processing Applications. APL Photonics 4, 106109 . Will need to build conventional set ups versus proposed set up in journal article for determination; multiple trials (and possible controls). AA23. Potential Experiments with Surface Relief Gratings The following journal articles may be tangible and feasible guides towards experimentation, however, specific materials may be a challenge of acquire: Kiyoshi Yokomori, "Dielectric surface-relief gratings with high diffraction efficiency," Appl. Opt. 23, 2303-2310 (1984) X. Yuan, D.N. Qu & R.E. Burge (1992). Analysis of Far-field Diffraction Characteristics of Wavelength-sized Surface Relief Gratings, Journal of Modern Optics, 39:8, 1719-1732 D. N. Qu, X. Yuan, and R. E. Burge (1993). Polarization dependence of the electromagnetic field distribution across wavelength-sized relief grating surfaces. J. Opt. Soc. Am. A 10, 2317-2323 (1993) It may be of interests to also investigate gratings that are contrary to dimensional parameters considered in articles. AA24. Building a digital camera Part A Will try to mirror the following source: https://www.instructables.com/id/DIY-Image-Sensor-and-Digital-Camera/ For the applied hardware components students should under the roles and means of proper integration as a unit. Must become competent with applications software. This will not be treated as a “macaroni & glue” project. Part B (advance lab development) Will try to mirror the following source: http://unaligned.org/bigcam/ However, we are also committed to thorough engineering development: Tools: SPICE simulator Xilinx Vivado Design Suite (or other) Note: all circuitry, Analog schemes/blocks and power electronics must be confirmed. Will also include detail analysis and simulation of an CMOS image sensor/image pixel sensor. PCB design must be tested and validated. PART C (design development extensions in the future) -Multiple lenses -Zoom and clarity -Spectra (nothing to do with breaking up a camera or smartphone) Infrared, UV Visible, V and infrared imaging in astronomy & integrating with telescopes -Video recording development Open to CE AA25. Combining radar and sonar A. Fitzpatrick, A. Singhvi and A. Arbabian, "An Airborne Sonar System for Underwater Remote Sensing and Imaging," in IEEE Access, vol. 8, pp. 189945-189959, 2020 Doesn’t necessarily require a UAV, rather a suspended construction above various depth level trials AA26. Power generation via aquatic energy source systems for utilities demand; developing systems to regulate such. # Ocean treated as a battery medium Allowing the ions to exchange freely with water that flows through. Possibly, manganese dioxide as one electrode which can react with a sodium ion, while determination of an optimal and environmentally friendly counterpart such as titanium based compounds to react with chlorine. Of consequence, the two electrodes in the device can isolate the ions that form when sodium chloride dissolves in water, towards producing a charged battery. Will involve flow channels and means to constantly observe voltage/current flow. Contamination prevention is a top priority. Can have prototype microscale, then proceeding to larger scale. Chemistry modelling for microscale prototype and larger scale will be incorporated towards modelling the expected voltage/current/energy to be achieved; geometrical mechanism designs and water flux likely variable may have influence as well. Operations and activities involve: 1. Electrochemical concepts and methods. Electrochemical window. Electrode characterisation. Redox reaction. Gibbs free energy and equilibrium. Debye-Hückel theory. 2. Electron transfer rate theory compared to measurements for confirmation. Electron transfer process duration (if possible). Derivation of the Nernst Equation and applications. 3. Analytic solutions of applying differential equations. Applications of the Laplace transform and/or Fourier transform 4. Lab design and construction (include power storage and lock off) 5. Performance prediction based on (1) though (4) 6. Troubleshooting components and resolutions Towards anything substantial, battery modelling and design needs to be accomplished before construction of a high number of modules. A development guide examples: Zhang, Y., Senthilkumar, S., Park, J., Park, J., & Kim, Y. (2018). A New Rechargeable Seawater Desalination Battery System. Batteries & Supercaps, 1(1), 6–10. Supporting NASICON literature ---> Fergus, J. W. (2012). "Ion transport in sodium ion conducting solid electrolytes". Solid State Ionics. 227: 102–112 Anantharamulu, N. et al. (2011). "A Wide-Ranging Review on Nasicon Type Materials". Journal of Materials Science. 46 (9): 2821 Knauth, P. (2009). "Inorganic Solid Li ion Conductors: An Overview". Solid State Ionics. 180 (14–16): 911–916 AA27. Some power engineering pursuits I. GSM based substation monitoring and control system PART A Analysis and development the following Sachan, A. (2012). Microcontroller Based Substation Monitoring and Control System with Gsm Modem. IOSR Journal of Electrical and Electronics Engineering, 1, 13-21. PART B For real energy grids will like to identify the industrial sale analogy to what has been comprehended in part A. Will like to design the schematics of such large system with comprehension of the regulation systems in constant function. How much disparity is there between part A and part B? II. Power factor measurement and control PART A Power factor measurement using microcontroller. An idea of things: https://microcontrollerslab.com/power-factor-measurement-using-microcontroller/ PART B The following articles provide example methodologies for development of APFC controllers. Pursuing analysis and development with microcontrollers. Performance to be compared to proprietary means; design powerfactor tests to accommodate Wanfeng Zhang, Guang Feng, Yan-Fei Liu and Bin Wu, "A New Predictive Control Strategy for Power Factor Correction," Eighteenth Annual IEEE Applied Power Electronics Conference and Exposition, 2003. APEC '03, 2003, pp. 403-409 volume.1 K. M. Tsang & W. L. Chan. (2005). Active Power Factor Correction Using Nonlinear Control, Electric Power Components and Systems, 33:9, 973-983 S. Powniker and S. Shelar, "Development of Active Power Factor Correction controller using boost converter," 2016 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE), Pune, 2016, pp. 212-216 Philip C. Todd. UC3854 Controlled Power Factor Correction Circuit Design. Unitrode Application Note U – 134: https://www.ti.com/lit/an/slua144/slua144.pdf Toshiba (2019). Power Factor Correction (PFC) Circuits: https://toshiba.semicon-storage.com/info/docget.jsp?did=68570 AA28. Chaotic Secure Communication Systems PART A Additive Chaotic Masking Chaotic switching Forcing Function Modulation Multiplicative Chaotic Mixing Parametric Modulation Independent Source Modulation Generalised Modulation Synchronization Pecora & Carroll Hamiltonian Synchronization Approach OPCL Will like to construct communication modules to send and receive data (images, audio, video, documentation). Will like to implement such schemes to verify security; targeted reception being uncompromised by “infiltrators”. PART B How can CSCS be integrated with encryption cryptography? Development of concept. Will pursue development of framework and logistics. Then implementation experiments. AA29. Enginerering primitive a tachometer via laser and hall effect sensing Laser Development--> PART A Expected elements: lasers, LED, multimeters, oscilloscopes, spectrum analyzer, board modules Must have strong comprehension/analysis of board modules. Must develop the physics that conveys feasibility Develop any necessary coding with accompanied by conceptual elaboration PART B Develop the following: Zappala, D., Bezziccheri, M., Crabtree, C. J. and Paone, N. (2018). Non-Intrusive Torque Measurement for Rotating shafts using Optical Sensing of Zebra Tapes. Measurement, Science & Technology, 065207 (18pp) PART C: Develop the following Meng, Z. and Liu, B. (2006). Research on the Laser Doppler Torque Sensor. Journal of Physics: Conference Series, Volume 48, 037 Hall Effect --> Expected elements: LED, multimeters, oscilloscopes, spectrum analyzer, board modules, LCD screen Must have strong comprehension/analysis of board modules. Must develop the physics that conveys feasibility Develop any necessary coding with accompanied by conceptual elaboration Note: will test all developed schemes against commercial tools. AA30. Reliability Modelling of energy grids (COMING SOON) Will try to develop relaistic energy grids higly resemblant of various regions. realistic factrs will be incorporated (such as loads, demand, etc., etc., etc.). Then, will compare historical performance of such regions (failures, maintenance, etc.) assuming there’s no radical system innovation (or upgrades). AA31.Separation of Sounds in Audio Comparative Analysis of chosen methods. Methods expressed are just examples, hence not confined to them. Will implement them and compare/contrast by various means/standards. Not only interested in separation of vocals. -Z. Rafii and B. Pardo, "A Simple Music/Voice Separation Method Based on the Extraction of the Repeating Musical Structure," 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2011, pages 221-224 -Types of Neural Networks Techniques -Mavaddati, S. (2020). A Novel Singing Voice Separation Method Based on a Learnable Decomposition Technique. Circuits, Systems, and Signal Processing, Volume 39, Issue 7, Pages 3652 - 3681 -Various other types of methods out there COMPUTER ENGINEERING A. Technical reinforcement of semiconductor devices studies Alongside such analysis and field experimentation it would be highly recommended that students become well immersed in semiconductor software. Such software gives quality access to ideal designs, characteristics and performance. Such software to be compared to field experimentation results. Ansys Semiconductors and Ansys electromagnetics may serve as comparison with experimentation. A. Bipolar junction transistors reinforcement 1. Review of bipolar transistors 2. Simulation and system curves. Such activity is further verification that student understands systematic and operational outcomes. 3. Experimental building or observation towards confirmation. To the best of ability, physically construct asystem if possible towards empirical data gathering of characteristics, say, system curves. If such isn’t economic or physically practical, then to consider industrial made components and pursue empirical and essential characteristics in function; with emphasis on applications such as sensors, communications, control, computation, etc. B. Concerns study and practical experimental experience with semiconductor devices and IC circuits. * Wadsack, R., L., Fault Modelling and Logic Simulation of CMOS and MOS Integrated Circuits, The Bell System Technical Journal, Vol. 57, No. 5, May-June 1978. * Aissi, C., Gobovic, D., Olaniyan, J., A Method for Reducing Complex MOS Structures in Switch Level Simulators, 5th IPFA 95 Singapore. * Petkovic, P., M,, Milovanovic, D., P., Zivkovic, V., A., Symbolic Oriented Stuck Fault Modelling of CMOS Sequential Circuits, Proceeding of the 21st International Conference on Microelectronics (Miel 97), Vol. 2, NIS, Yugoslavia, 14-17 September 1997. * Tang, K., T., Friedman, E., G., Delay and Noise Estimation of CMOS Logic Gates Driving Coupled Resistive-Capacitive Interconnections, INTEGRATION, the VLSI journal 29 (2000) 131-165 Out of such four articles there are generally four phases in activity to implement: 1. Analysis 2. Simulation. Such activity is further verification that student understands systematic and operational outcomes. 3. Experimental building or observation towards confirmation. To the best of ability, physically construct and system if possible towards empirical data gathering of characteristics. If such isn’t economic or physically practical, then to consider industrial made components and pursue empirical and essential characteristics in function; with emphasis on applications such as sensors, communications, control, computation, etc. 4. Technological relevance. Determine if technologically relevant today based on current studies, with recognition of what proper components and/or methodologies are employed today. B. Electroncs Modernization & Scaling (incomplete) Going from old Boomboxes, Walkmans, CD players, rotary dial phones to Mp3 players and smartphones MOSFETS, CMOS, technologies in ICs, C. Design, construction and uses of multi-core and cluster stacks. Special invitation towards Mechanical Engineering, Computer Science and Physics entities. Parallel computing, with high concern in usage of multiple processors, shared memory, data logging, distributed databases, algorithmic implementation, supercomputing, and machine learning. Schematics, respective component responsibilities and logistics must be well established. Towards choice(s) of applications, such to be compared to respective standard or commercial devices in terms of capabilities, power usage, computational speed, security, etc. With cooler systems integrated (possibly both cooler tubes and brushless 30mm-92mm fans). Heavy usage of C/C++ programming and compilers to be expected. ---Will begin with common microcontrollers. architecture, logistics, routines, performance modelling, run time modeling. Towards meaningful applied tasks. Will first immerse with multicore capabilities of microcontrollers with meaningful applied tasks. ---Following , multicore microcontrollers will constitute a cluster. Architecture, logistics, routines, performance modelling, run time modeling. Towards meaningful applied tasks. ---Will then pursue cluster development with real conventional systems, mother boards in clusters. Architecture, logistics, routines, performance modelling, run time modeling. Towards meaningful applied tasks D. Digital Design & CPU Development Concerns computer engineering majors. Activities concern practical immersion into field resembling the described computer engineering course. Activity is highly dependent on successful completion of Digital Systems I & II courses with minimal grade of B- in latter, and computer engineering department permission. Towards retaining comprehension, skills and expansion of skills. Will make use of Logisim, Logisim Evolution or DLSim. Some ideas: Digital Design 5: Logisim Tutorial & Demo – YouTube Using My Even More Improved CPU in a Full-Fledged Computer Via Logisim – YouTube MY CPU/Computer: Conversion from Original Logisim to Logisim Evolution – YouTube Some applications (and possibly many more): Exhibition of data memory ALU to CPU Modify memory component to more sensibly Load/Store value Digital Clock Digital Stopwatch clock Scrolling LED circuit display Traffic Light Various 2D games As well, Will treat Verilog and/or VHDL with possible use of high level programming language. Such activity will serve towards a comfortable transition into designated computer engineering course, hence a student can take part in such activity before enrolling in the designated computer engineering course. Must acquire official approval for this activity where a certain level of background in courses and skills are required. Activity does not replace required course in computer engineering. E. CPU Simulation CPU Sim or YASS CPU OS Simulator Mustafa, B., YASS: A System Simulator for Operating System and Computer Architecture Teaching and Learning, European Journal of Science and Mathematics Education Vol. 1, No. 1, 2013 SKRIEN, D. 2001. CPU Sim 3.1: A Tool for Simulating Computer Architectures for Computer Organization Classes. ACM Journal of Educational Resources in Computing (JERIC) 1(4), 46-59. Note: simulator version in above journal article isn’t the most current version. Students will be very active with simulators concerning various crucial topics. Comprehension is extremely crucial. F. Building a CPU on an FPGA Note: Computer Science constituents may have interest --Robert’s Baruch’s constructing scheme Robert Baruch’s sequential guide (on YouTube) is quite strong. Necessarily, the “Zork” entertainment pursuit isn’t the most constructive, hence to make a decision on what interest serves to be optimally constructive (that can be built upon concerning future endeavors in science and engineering). Boards to be used will likely vary depending on interests. The following is the software flow before Xilinx: Virtual Box --> Ubuntu desktop --> Sublime Text --> Package Control --> Verilator The first above concerns the circumstance that your OS is Windows or Mac. --Constructing an Open Source CPU Florian Zaruba’s guide is quite informative from “Ariane: An Open source 64-bit RISC-V Application Class Processor and latest Improvements” (on YouTube). Pursue constructing a CPU in such a manner. Note: there will be comparative analysis between Robert Baruch’s scheme and Florian Zaruba’s scheme. There must be common interest(s) to fairly compare the two operations. Performance data is wanted. G. Building Working Computers out of Virtual Blocks 1. Basic Anatomy of a Computer 2. Virtual blocks towards the following -Inputting: process of entering data and instructions into the computer system. -Storing: saving data and instructions so that they are available for initial or for additional processing as and when required. -Processing: performing arithmetical operations or logical operations on data in order to convert them into useful information. -Outputting: process of producing useful information or results for the user such as a printed report or visual display. -Controlling: directing the manner and sequences in which all of the above operations are performed. Heavily dependent on software for components integration, block building related to circuit analysis, various levels of simulations. H. Programming Reinforcement towards Embedded Systems, Control and Autonomous Systems with C/C++, and Assembly language Will also have interest to constituents of systems control in mechanical engineering and computer science. Conceptual development and flow diagrams before writing and implementing programming instruction per device, object, etc. Activities may vary w.r.t to semester, say coding for different tools, robotics and devices. Students will observe and execute their codes with programmable boards compared to those of commercial firms, etc. There’s possibility that system level simulation will be involved before making used of hardware with developed code, etc. Includes robotics and other systems. Students must have at least one year of officially recognised programming background in C/C++. Mechatronics and Assembly Language background might be quite helpful as well; not to necessarily be only about automation. Activities with C/C++ and assembly with programmable boards concerns application and implementation into meaningful devices or projects. Will try to establish where and how Feedback/Automatic control comes in, and how to integrated such with the embedded systems aspects. I. Some Modern Microelectronics features (incomplete) Spin-Torque-Transfer-Operated Magnetic Tunnel Junctions (STT-MTJ) There may be much required intelligence build up to acquire comprehension and coherence with physics, applications, modelling, engineering, technologies and characteristic behaviour. Beneath are some helpful journal article guides. Some or all of the articles provide feasibility for macromodels with simulations and SPICE models with simulations --> Guo, W. et al. (2010). SPICE Modelling of Magnetic Tunnel Junctions Written by Spin-transfer Torque. Journal of Physics D: Applied Physics, 43(21), 8. Harms, J. et al. (2010). SPICE Macromodel of Spin-Torque-Transfer-Operated Magnetic Tunnel Junctions. IEEE Transactions on Electron Devices, 57(6), 1425-1430. Zhang, X et al. (2015). Simulation of Electric-Field and Spin-Transfer-Torque Induced Magnetization Switching in Perpendicular Magnetic Tunnel Junctions. Journal of Applied Physics, 117(17), Journal of Applied Physics, 07 May 2015, Vol.117(17). Mahmoudi, H. et al (2013). Implication Logic Gates using Spin-Transfer-Torque-Operated Magnetic Tunnel Junctions for Intrinsic Logic-In-Memory. Solid State Electronics, 84(C), 191-197. Xiaofeng Y. et al (2012). Magnetic Tunnel Junction-Based Spintronic Logic Units Operated by Spin Transfer Torque. IEEE Transactions on Nanotechnology, 11(1), 120-126. Diao, Z. et al. (2007). Spin-transfer torque Switching in Magnetic Tunnel Junctions and Spin-Transfer Torque Random Access Memory. Journal of Physics: Condensed Matter, 19(16), 13. Hui Zhao, P. et al. (2012). Spin-Transfer Torque Switching Above Ambient Temperature. IEEE Magnetics Letters, 3, 3000304. J. Pursuit of testing for semiconductor defects Stavola, M., and Fowler, W., B., Tutorial: Novel Properties of Defects in Semiconductors Revealed by their Vibrational Spectra, Journal of Applied Physics 123, 161561 (2018) A goal is to develop a scheme and logistics, then onwards to actual experiment for confirmation or disapproving such article. May involves trials of different samples. K. High Performance Computing with FPGAs Will introduce motivating circumstances and practical, tangible development. Will clearly differentiate between CPU, GPU, and FPGA with anatomy, logistics and the pathways, processing/computation, execution timing, computation speed and the role of parallelism. Will immerse with the tools to access GPU, FPGA and association with parallelism. Storage is often a highly treated topic. Will focus on applications that are widely accepted or growing in the fields of chemistry, physics, scientific computation, clusters, etc. Between CPU, GPU, and FPGA there will be operations exhibiting the power between such; the parallelism factor to be introduced as well. Will also actively treat respective role or relevancy with multicore and stacks. Energy requirements, heating and cooling will also be treated. Note: there is also the combination process between CPU, GPU, FPGA and parallel computation; may entertain such. Open to physics, computer science, geology and chemistry students. L. EMI Suppression Demonstrations of the following EMI suppression methods will be pursued: Filters Coils Differential Signalling Shielding Spread Spectrum Clocking (SSC) Note: such listed above may not be the only techniques for EMI suppression today. 1. The following journal articles can serve well for analysis and experimentation: --Z. Zhang and C. M. Johnson, "Suppression of electromagnetic interference using screening and shielding techniques within the switching cells," 2017 IEEE International Workshop On Integrated Power Packaging (IWIPP), Delft, 2017, pp. 1-5. --Jonghoon Kim, Dong Gun Kam, Pil Jung Jun, & Joungho Kim. (2005). Spread spectrum clock generator with delay cell array to reduce electromagnetic interference. IEEE Transactions on Electromagnetic Compatibility, 47(4), 908-920. --M. Kisić, Č. Žlebič, M. Damnjanović, K. Babković, A. Menićanin and L. Živanov, "Interference in digital circuits and some techniques for EMI suppression," 2012 IEEE 10th Jubilee International Symposium on Intelligent Systems and Informatics, Subotica, 2012, pp. 433-437. --Shuo Wang, F., & Lee. (2010). Analysis and Applications of Parasitic Capacitance Cancellation Techniques for EMI Suppression. IEEE Transactions on Industrial Electronics, 57(9), 3109-3117. --Shaowu Huang, Xiaoning Ye, Nan Kang, Beomtaek Lee, & Kai Xiao. (2016). Suppression of Couplings in High-Speed Interconnects Using Absorbing Materials. IEEE Transactions on Electromagnetic Compatibility, 58(5), 1432-1439. --H. K. Patel, "Flyback Power Supply EMI Signature and Suppression Techniques," 2008 Joint International Conference on Power System Technology and IEEE Power India Conference, New Delhi, 2008, pp. 1-6. 2. The following journal articles can serve well towards analysis and experimentation with converters for EMI suppression: --Guo, H. et al, Research on periodic switching frequency modulation for conducted EMI suppressing in power converter, Microelectronics Journal 42 (2011) 415–421 --Kuo, M. and Tsou, M., Novel Frequency Swapping Technique for Conducted Electromagnetic Interference Suppression in Power Converter Applications, Energies 2017, 10, 24 --Tse, K., Henry Shu-Hung Chung, Ron Hui, & So. (2002). A comparative study of carrier-frequency modulation techniques for conducted EMI suppression in PWM converters. IEEE Transactions on Industrial Electronics, 49(3), 618-627. 3. The following link is a guide from Texas Instruments, a major semiconductor/electronics firm. It describes a means of EMI treatment concerning microcontroller applications. Apart from being general guide, it also can serve as a step by step experimentation process towards EMI treatment concerning microcontrollers: http://www.ti.com/lit/an/snoa382/snoa382.pdf Model design and simulation can be done spice tools, SystemModeler, Ansys electromagnetics and Ansys semiconductor. Ideal behaviours can be acquired by simulation to establish consistency with experimentation. One must clearly identify differentiation between desired systems and those hampered by EMI suppression. Observing substantial EMI may not occur, but understanding, skills and competence are necessary. The prior journal articles for analysis with experimentation can be compared with such guiding experimentation towards determination on whether the link’s methods are either more robust or superior. 4. The following journal articles can serve well towards analysis and experimentation with drive systems for EMI suppression: --Yang, L., Wang, S. and Feng, J., Electromagnetic interference modeling and suppression techniques in variable-frequency drive systems, Front. Mech. Eng. 2018, 13(3): 329–353 --L. Yang, S. Wang and J. Feng, "Advances in electromagnetic interference modeling and noise reduction for adjustable speed motor drive systems," 2017 IEEE International Symposium on Electromagnetic Compatibility & Signal/Power Integrity (EMCSI), Washington, DC, 2017, pp. 249-254. M. Printed Circuit Board (PCB) Design PART A This activity concerns designing boards to meet one’s demands for projects. A major reward from this activity is acquiring freedom with development of systems that’s optimal in regard to necessary components and space. Such also gives one some level of freedom from commercial dependency thus likely cutting development costs. Considerations in activity will be highly application specific, namely, fulfilling needs of other engineering areas such as sensing, processing, control, synchronized data storage, parallelization, etc; combinations are possible. For designed boards wanted specifications will vary, dependent on respective application. Issues on current behaviour, voltage behaviour, time delay relay, counting, frequencies, etc., etc., etc. EMI treatment must be comprehensive. Mentioned software in “Goody Bag” post for such to be used. Requires permission from the Electrical Engineering department and Computer Engineering department. PART B 3D Printng PCBs Hack an old inkjet printer or go proprietary Will do both Note: part A will be crucial. Mean to integrate development from part A towards printing projects. N. Design and constructing microcontroller boards The following are strong illustrative guides to emulate: -Ben Eater YouTube Page Build and program a basic computer with the classic 6502 microprocessor How Do CPUs Read Machine Code? – YouTube Necessarily will pursue other projects observed on his page -Designing a Microcontroller Development Board: https://www.instructables.com/Designing-a-Microcontroller-Development-Board/ -Predictable Designs YouTube Page Tutorial -How to Design Your Own Custom Microcontroller Board – YouTube Tutorial -How to Design Your Own Custom Microcontroller Board (Part 2) – YouTube https://predictabledesigns.com NOTE: activity will place much emphasis on the following --Understanding Microcontroller Chips and other circuit components --Circuit properties (current, voltage, etc., etc.) and circuit analysis for proper function --Simulation development software --Programming --PCB board designing (development and pitfalls) --Ordering developed PCB boards towards construction Plannig, progrmming, sodering, testing, test projects, etc. ----The engineering programme is designed in a robust manner to have options in career paths, versatility to adapt readily, but also not to be a “Jack of All Trades, Master of None” ; electrical engineering is major case. The engineering programme has a core requirement that nurtures integration, adaptation and practical skill sets for progressing industries concerning the advancement of system design, technology, dynamics & control, and efficiency. Students will have skill sets that embrace the intersection of various areas of engineering now observed with modernization and innovation. **Engineering Core Structure (unless specified): --Intro Engineering & Design (first writing course) --Intro Engineering & Design II (second and last writing course) --Practical Programming in C for Engineering I & II --Calculus for Science & Engineering I – III --Ordinary Differential Equations --General Physics I & II --Circuit Analysis I & II --Feedback Control (labs included) Prerequisites: General Physics I & II, ODE --Probability & Statistics B (see computational finance post) --Automatic Control (labs included) Prereq: Feedback Control, Probability & Statistics B --Modelling & Simulation Lab Prereq: Calculus III, General Physics I & II, ODE, Feedback Control --Solid State Devices I Such courses are strictly designated core courses. --Concerning a core for Civil Engineering and Industrial Engineering students, they are to follow what curriculum is assigned to them. Civil Engineering has its own post (prior) --Concerning the concentration for “Classical” Mechanical Engineering students they are to drop Automatic Control and Solid State Devices I, and replace with Systems Modelling I & II courses. Will drop Circuit Analysis I & II. Every other course in the list above to remain for ME classical. --Concerning “Automation Design” Mechanical Engineering they are to drop Solid State Devices I, and Circuit Analysis I & II --Concerning Aerospace Engineering they are to drop Solid State Devices I. Will drop Circuit Analysis I & II. Every other course in the list above to remain for AE. --Concerning the Networks concentration in electrical engineering, those in such are exempted from Practical Programming in C for Engineering I & II, rather following the C++ track given. Additionally, will drop Automatic Control. --For Computer Engineering students they will drop Feedback Control, Automatic Control, and Modelling & Simulation Lab --Nevertheless, naturally expected for anyone new in engineering, they will have advance standing in mathematics, courses. --It’s inevitable that some degree concentrations will have 1- 3 courses more than others. That’s unavoidable if one is truly constructive and practical in their own best interest. Furthermore, most of your skills and talents will come from your undergraduate endeavour; the time to get the most out of things. Question: How many courses in short time do you take in graduate programmes to be recognised as “pros”? --Also expected, to invest 1 or 2 “summer” and “winter” terms doing away with college requirements in your freshman and lower sophomore eras. --It’s also VERY IMPORTANT that one doesn’t allow Mathematicians to dictate your skills or public perception of you to others. It’s important not to have a mathematician’s ideological curriculum and ego stratus dictate (whether it be of Caltech, Columbia, Yale, Brown, Rutgers), to poison or rot out your interests and resources with rent seeking, manipulation sand sabotage. YOU HAVE THINGS TO DO, OF THE HIGHEST TANGIBILITY, PRACTICALITY AND FLUIDITY. INVEST IN YOURSELVES NOW, RATHER THAN PAYING LATER (or be the suckers later). Now then --> Mechanical Engineering (classical) has further requirements: Machine Design I & II; Statics; Mechanics of Materials; Mechanics of Materials Lab; Manufacturing Processes; Numerical Analysis; Vibrations & Waves (check PHYS); Systems Modelling I & II; Mechanical Design Process; Mechanical Design; Fluid Mechanics (check PHYS); Fluid Machinery; Finite Element Modelling; Engineering Thermodynamics; Heat Transfer; Internal Combustion Systems; Powertrain Design; Powertrain Control Systems; Automated & Automatic Drivetrain Mechanical Engineering with specialization in Electric Transportation has the following requirements: Machine Design I & II; Systems Modelling I & II; Signals & Systems; Mechatronics I & II; Electric Drives I & II; Solid State Devices II; Power Electronics; Modelling & Control of Power Electronics; Power Electronics for Electric Drive Vehicles; Electrification of Transportation I & II; Engineering Thermodynamics; Electrochemical Engineering; Battery Management & Control Mechanical Engineering with specialization in “Mechanical Design” Machine Design I & II; Statics; Mechanics of Materials; Mechanics of Materials Lab; Numerical Analysis; Computer-Aided Design & Visualization I & II (check Comput FIN); Manufacturing Processes; Systems Modelling I & II; Mechatronics I & II; Engineering Thermodynamics; Mechanical Design Process; Mechanical Design; Precision Machine Design & Implementation; Digital Fabrication; Finite Element Modelling Mechanical Engineering with specialization in Systems Control has the following requirements: Systems Modelling I & II; Signals & Systems; Mechatronics I & II; Robotics I & II; Assembly Language; Embedded Systems & Control I & II; Applied Robotics; Sensor Instrumentation; Programmable Logic Controllers; Autonomous Systems I & II; Solid State Devices II, Electric Drives I & II Aerospace Engineering has further requirements: Statics; Mechanics of Materials; Mechanics of Materials Lab; Numerical Analysis; Mechatronics I & II; Partial Differential Equations; Fluid Mechanics; Fluid Machinery; Aircraft Theory; Aircraft Design; Aerodynamics; Compressible Flow; Aircraft Flight Dynamics I & II; Advance Flight Mechanics; Finite Element Modelling; Engineering Thermodynamics; Heat Transfer; Propulsion Systems I & II; Rocket Propulsion EE Power concentration by fulfilling the following requirements: Signals & Systems; Electromagnetics I; Power Electronics; Modelling & Control of Power Electronics; Electric Drives I & II; Solid State Devices II; Power System Analysis I & II; Engineering Thermodynamics; Electrochemical Engineering; Battery Management & Control; Modern Physics; Solid Sate Devices III; Solar Energy Photovoltaics; Energy Grid Systems & Innovative Power Devices; Electric Power Distribution Systems I & II EE Photonics concentration by fulfilling the following requirements: Electromagnetics I & II; Signals & Systems; Analogue & Digital Communications Systems; Modern Digital Communications; Optical Communications & Photonics; Optical Communications & Photonics Lab; Solid State Devices II; Methods of Mathematical Physics; Modern Physics; Quantum Physics I; Optoelectronics; Solid State Devices III; Solar Energy Photovoltaics; Silicon Integrated Photonics; Silicon Photonics Design Lab; Semiconductor Quantum Structures & Photonic Devices EE Networks concentration by fulfilling the following requirements: Signals & Systems; Image & Audio Processing; Mathematical Statistics; Image & Video Processing; Electromagnetics I & II; Analogue & Digital Communications Systems; Modern Digital Communications; Optical Communications & Photonics; Optical Communications & Photonics Lab; Solid State Devices II; Antenna Theory; RF & Microwave Circuits for Wireless Communications I & II; Computer Networks for Engineers; Wireless Networks; Satellite Communications (check Comput FIN); Hands-on Satellite Design (check Comput FIN) Computer Engineering pursuits concern fulfilling the following requirements: Assembly Language; Embedded Systems & Control I & II; System-on-Chip (SoC) Design; Electromagnetics I; Solid State Devices II; Modern Physics; Solid State Devices III (with labs); Electromagnetic Compatibility; Digital Design I & II; Microprocessors I & II; Microprocessor Lab I & II; CMOS VLSI Design; VLSI Testing & Validation; Analogue Circuit Design I & II; Mixed Signal Circuits; Digital Systems Design (senior standing) NOTE: for Computer Engineering, students are expected to have completed two terms of calculus before first freshmen year, or plan to take two terms of calculus in the “summer” and “winter” terms with freshman standing, along with general education appeasement courses (History; Humanities/Liberal Arts; Social/Society). NOTE: For CE, Practical Programming in C for Engineering I & II, Digital Design I & II should be taken at appropriate times for proper retention and freshness towards CMOS VLSI Design and VLSI Testing & Validation; CMOS VLSI Design followed by VLSI Testing & Validation also has Solid State Devices III prerequisite. NOTE: For the EE Networks concentration students, concerning the Wireless Networks course, with the Computer Networks for Engineers course as one of the prerequisites, such particular prerequisite must be completed right before taking the Wireless Networks course. For this concentration, aside from EE “summer” and “winter” activities under EE-COMPE, will also have interest in “summer” and “winter” activities administered under aerospace engineering and the planetary sciences (meteorology, oceanography and geology). As well, radio telescope building activities for astronomy purposes (under physics) and radar building activities for weather monitoring (under oceanic-meteorology)....if their rate of progression aligns with such.. ***Description of Engineering Writing courses Intro Engineering & Design I In this course, students will develop the scientific and technical reading and writing skills they need to understand and construct research articles. The course will be divided into two parts. In Part One of the course, students will learn the principles of writing research papers in science and engineering. First, they will learn what research is, and how the process of research is revealed in the structure of research papers. Next, they will look at software tools and corpora (collections of language samples) that can assist them in the writing of research papers. At the end of the section, students will create their own corpus of research papers and will use throughout the remainder of the course. In Part Two of the course, students will write a full research paper in their field of specialization, working separately on the title, abstract, introduction, materials/methods, results, and discussion in each unit. For each part of the research paper, students will first analyse the sample texts in their corpus and then present their findings to other members of the class. This will help all students to understand which elements are common to all science and engineering disciplines, and which are unique to individual disciplines. Next, they will apply what they have learned in their own writing, slowly constructing a full-research paper by the end of the course. Course Goals -Understand the importance of English in the fields of science and engineering. -Understand common problems associated with using technical vocabulary in specialist fields. -Use effective strategies to learn technical vocabulary in specialist fields. -Use text analysis tools to identify differences in the audience, purpose, structure, style, and presentation of technical texts in different fields. -Identify the structure of technical research papers in specialist fields. -Understand research journal Call for Papers and Instructions for Authors. -Write the title, abstract, introduction, materials/methods, results, discussion/conclusion sections of a research paper in a specialist field. -Write simple and extended definitions. -Explain methods and processes. -Explain information in figures and tables. -Know how to strengthen or weaken the interpretation of research findings through hedging. -Understand the importance of references, citations, and avoidance of plagiarism. -Follow common conventions for citing and referencing information in a research article. Typical Text: L. Anthony (2011). "Writing Up Research in Science and Engineering : Developments," DTP Publishing Grading --> Student evaluations will be based on a series of assignments, written reports, class participation, and an end of term report. Intro Engineering & Design II Second part of the mandatory sequence. WILL BE VERY INTENSE. Grading --> Student evaluations will be based on a series of assignments, written reports, class participation, and an end of term report. ***Descriptions of particular EE courses--- 1. Circuit Analysis I The course has been designed to introduce fundamental principles of circuit theory commonly used in engineering research and science applications. Techniques and principles of electrical circuit analysis including basic concepts such as voltage, current, resistance, impedance, Ohm's and Kirchoff's law; basic electric circuit analysis techniques, resistive circuits, transient and steady-state responses of RLC circuits; circuits with DC and sinusoidal sources, steady-state power and three-phase balanced systems, including Laplace and Fourier transforms applications for solving circuit problems. To develop problem solving skills and understanding of circuit theory through the application of techniques and principles of electrical circuit analysis to common circuit problems. Course Goals --> To develop an understanding of the fundamental laws and elements of electric circuits. To learn the energy properties of electric elements and the techniques to measure voltage and current. To understand waveforms, signals, and transient, and steady-state responses of RLC circuits To develop the ability to apply circuit analysis to DC and AC circuits. To understand advanced mathematical methods such as Laplace and Fourier transforms along with linear algebra and differential equations techniques for solving circuits problems. Typical Text: TBA Technology: Circuit builders and simulators Grading: Quizzes (10%) Homework (20%) Two Midterms (40%) Final exam (30%) Topics --> CIRCUIT PARAMETERS AND FUNDAMENTAL LAWS I Electric charge. Coulomb’s law. Electric work. Potential. Potential difference. Electric current. Power. Energy. Resistance. Resistivity. Ohm’s law. Kirchoff’s law. Branch. Node. Mesh. Circuit elements in series. Circuit elements in parallel. CIRCUIT PARAMETERS AND FUNDAMENTAL LAWS II Ideal current source. Ideal Voltage generator. Internal resistance. Mesh current method. Node voltage method. Thevenin’s theorem. Norton’s theorem. Superposition’s theorem. Capacity. Inductors. Electromagnetic flux. INSTRUMENTS The voltmeter. Internal resistance. The galvanometer. Internal resistance. The Ohmmeter. The Wheatstone bridge. The impedance bridge. COMPLEX IMPEDANCE and ADMITTANCE Resistance. Phasorial notation. Capacitive and inductive reactance. Impedance. Conductance. Capacitive and inductive susceptance. Admittance. Series and parallel equivalent circuit. RLC series and parallel circuits. CIRCUITS TRANSIENT RESPONSE. ODE RC, RL and RLC circuits. Time constant. Step and impulse response. Transient response. CIRCUITS TRANSIENT RESPONSE. LAPLACE TRANSFORM The Laplace’s transform . Initial value theorem and final value theorem. Studying transient phenomena with the Laplace transform. Circuit analysis in the s (complex variable) domain. Resonance. Frequency response. Cut-off frequency. Pole. Zero. Low-pass filter. High-pass filter. WAVEFORMS AND SIGNALS Periodic and non-periodic signals. Heavyside function. Impulse function. Ramp function. Triangular function. Peak value. Average value. Effective value (RMS). Sinusoidal and co-sinusoidal signals. Euler’s expression. Generic harmonic signal. Amplitude and phase. THE FOURIER TRANSFORM Fourier’s trigonometric series. Polar form of Fourier’s. Amplitude spectrum and phase spectrum. Application to linear circuits. The Fourier’s integral. The Fourier’s transform. Prerequisites: General Physics II, ODE 2. Circuit Analysis II Analysis of single-phase and three-phase circuits. Laplace transforms in circuit analysis. Fourier series. Two-port networks. Course objectives --> The overall course objective is to teach electrical and computer engineering students fundamental concepts and methods of single-phase and three-phase circuits. Specific objectives include the following: 1. Analyse ac (alternating current) circuits containing resistors, inductors, capacitors, transformers, and both independent and dependent electrical sources to determine current, voltage, power, and energy values. 2. Utilize Laplace transforms for circuit analysis. 3. Analyse periodic inputs using Fourier transforms. 4. Determine the frequency response of a given circuit. 5. Draw Bode plots and interpret them. 6. Design simple electrical filters that satisfy specific functional requirements. 7. Characterize linear networks with two-port parameters. 8. Simulate linear electric circuits and measure their properties. 9. Conduct laboratory experiments to confirm the analysis done in the class. 10. Prepare informative and organized lab reports that describe the methodologies employed, the results obtained, and the conclusions made in a laboratory experiment Labs --> All labs must be completed, and lab reports turned in or you will fail. You can make-up only one lab (missed for any reason) in the final week. More than one lab can be made-up only with the instructor’s permission. Make-up labs will only be allowed in special situations. The extraordinary circumstances requiring a make-up lab must be verifiable. Circuit simulators to accompany handson activities. Typical Textbook: Hayt, Kemmerly, and Durbin, Engineering Circuit Analysis, seventh edition, 2007 Grading: - Exam 1,2,3: 10%, 10%, 10% - Final exam (comprehensive): 25% - Homework: 10% - Labs: 20% - Quizzes: 15% Course Outline: WEEK 1 Overview & general course information Review of phasor-based analysis WEEK 2 Instantaneous and average power Apparent power, power factor, complex power WEEK 3 Polyphase systems Three phase Y-Y, delta connection Mutual inductance WEEK 4 Ideal transformer Complex frequency Laplace transform WEEK 5 Inverse transform techniques Theorems for Laplace transforms Review WEEK 6 Exam 1 Theorems for Laplace transforms Circuit analysis in the s-domain WEEK 7 Circuit analysis in the s-domain WEEK 8 Poles, zeros, and transfer functions Complex-frequency plane Frequency response – parallel resonance WEEK 9 High-Q circuits Series resonance Review WEEK 10 Exam 2 Other resonant forms WEEK 11 Bode diagrams WEEK 12 Filters Active filters WEEK 13 Exam 3 Two port networks; admittance parameters WEEK 14 Impedance parameters Hybrid parameters Transmission parameters WEEK 15 Fourier circuit analysis The use of symmetry WEEK 16 Complex form of Fourier series Fourier transform WEEK 17 Final Exam Prerequisites: Circuit Analysis I 3. Signals & Systems Topics related to the analysis of linear time invariant continuous and discrete systems and signal transformations, convolution, frequency spectra, Laplace transforms, Z transforms, and fast Fourier transforms. Lecture and lab combination. Laboratory activities to include the computer simulation, analysis, and numerical modelling of signals and systems. The students will demonstrate: 1. The knowledge of how to represent signals in the time, frequency, Laplace, and Z domains. 2. The knowledge of how to perform both discrete and continuous convolution. 3. The ability to design, build, and analyse linear time invariant systems. 4. The ability to program simple scripts and functions in Mathematica or C or C++ or whatever Typical text: Lathi, Signal Processing & Linear Systems, Oxford University Press Companion functions: Mathematica – Signal Processing Technology tools: Usage of oscilloscopes, spectrum analyzer, SPICE simulators, etc., etc. For quizzes and exams, along with conventional questions will have: 1.Cases where models, algorithms, etc. are given and students must choose the correct code that represents it. 2. Problems where students must recognise errors in code. 3. Problems where students must provide alterations to yield desired properties. 4. Given code may or may not do what is said. Grading: Homework & Quizzes 25% Laboratory Assignments 25% 2 Mid-term Exams (each) 30% Final Exam 20% Topic Outline (Chapters 1 through 11): 1. Continuous-time and discrete-time signals 2. Linear time invariant systems 3. Time Domain Analysis 4. Convolution (continuous) 5. Stability 6. Fourier Series 7. Fourier Transformation 8. Sampling 9. Discrete (and Fast) Fourier Transforms 10. Circular Convolution (discrete) 11. Laplace transform 12. Analog Filters 13. Z Transform (includes Z- Transform vs. Laplace) 14. Digital Filters Labs --> NOTE: Mathematica – Signal Processing to accompany manual analytical modelling development, coding and usage of oscilloscopes/analyzers, SPICE simulators, etc., etc. NOTE: Mathematica may have built-in functions, however such functions are generally only for comparing with built code. NOTE: all labs will try to incorporate solid skills building with coding. Will be given multiple exercise to complete; analytical structuring of code must be accomplished before writing and implementing code. 1. Using Mathematica or C or C++ 2. Signal Reconstruction 3. System Response to Periodic Signals 4. Impulse Response 5. System Response to periodic signals 6. Fast Fourier Transform 7. System Realization & Frequency Response 8. Filter Designs 9. Discrete Time system Response Prerequisites: Circuit Analysis II and ODE 4. Image & Audio Processing Broad treatment of the fundamentals in image and audio processing. General Pursuits --> 1. Understand the fundamentals of image and audio signal processing and associated techniques. 2. Understand how to solve practical problems with some basic image and audio signal processing techniques. 3. Have the ability to design and implement simple systems for realizing some multimedia applications with some basic image and audio signal processing techniques. Typical Texts: R.C. Gonzalez and R.E. Woods, Digital Image Processing, 2nd ed., Prentice Hall, 2002. Ken C. Pohlmann, Principles of Digital Audio, 4th ed., McGraw-Hill, 2000. Technology Tools: CVIPtools (Open Source) video processing software Mathematica Image Processing & Analysis Audio Processing C++ programming Lab activities --> Labs will concern apply construction towards realistic, practical and sustainable activities and experiments. The mentioned technology tools above concern analytical analysis, data analysis, logistics, algorithm development and so forth. Often there will be comparative activities to establish assurance, consistency and versatility. For quizzes and exams, along with conventional questions will have: 1.Cases where models, alogoritms, etc. are given and students must choose the correct code that represents it. 2. Problems where students must recognise errors in code. 3. Problems where students must provide alterations to yield desired properties. 4. Given code may or may not do what is said. Grading --> Homework Quizzes Labs 2 Exams Course Outline --> 1. Image processing 1.1 Fundamentals of digital image: Digital image representation and visual perception, image sampling and quantization. 1.2 Image enhancement: Histogram processing; Median filtering; Low-pass filtering; High-pass filtering; Spatial filtering; Linear interpolation, Zooming. 1.3 Image coding and compression techniques: Scalar and vector quantizations; Codeword assignment; Entropy coding; Transform image coding; Wavelet coding; Codec examples. 1.4 Image analysis and segmentation: Feature extraction; Histogram; Edge detection; Thresholding. 1.5 Image representation and description: Boundary descriptor; Chaincode 2. Audio processing 2.1 Fundamentals of digital audio: Sampling; Dithering; Quantization; psychoacoustic model. 2.2 Basic digital audio processing techniques: Anti-aliasing filtering; Oversampling; Analog-to-digital conversion; Dithering; Noise shaping; Digital-to-analog Conversion; Equalisation. 2.3 Digital Audio compression: Critical bands; threshold of hearing; Amplitude masking; Temporal masking; Waveform coding; Perceptual coding; Coding techniques: Subband coding and Transform coding. 2.4 Case Study of Audio System/Codecs: MP3; MP3-Pro; CD; MD; DVDAudio; AC-3; Dolby digital; Surround; SRS Surround system; Digital Audio Broadcasting, etc. Laboratory Experiments --> Note: the duration of each type of lab may be at least 1 week. Various ,methods, techniques, algorithms and analysis to be covered. The goal is to develop skills in a constructive and sequentially advancing manner. 1. Image processing techniques 2. Image compression 3. Audio processing techniques 4. Audio compression 5. Psychoacoustic behaviour Prerequisites: Signal and Systems, Practical Programming in C for Engineering I & II 5. Solid State Devices I COURSE DESCRIPTION: The objective of this course is the study of small scale semiconductor based components and designs. The fabrication of solid-state silicon based microelectronic devices has given rise to the modern era of integrated circuits. This course will build an understanding of these fundamental semiconductor electronic devices that serve as the building blocks of both discrete and integrated circuits. The focus will be on p-n junction diodes, Bipolar Junction Transistors (BJTs), Metal-Oxide-Semiconductor Field-Effect Transistors (MOSFETs) and Operational Amplifiers (Op Amps). COURSE OBJECTIVES: -Understand intrinsic and doped semiconductors and current flow in semiconductors -Understand biased and unbiased operation of p-n junction -Understand terminal characteristics of p-n junction diodes, modelling the diode forward characteristics, and operation in the reverse breakdown region of Zener diodes -Understand operation of MOS device and analyse current-voltage characteristics of MOSFET -Understand small signal operation and models with MOSEFT amplifier design 2 -Understand operation of BJT device and analyse current-voltage characteristics of BJT -Understand small signal operation and models with BJT amplifier design -Understand ideal Op Amp, inverting, non-inverting configuration -Analyse difference amplifiers, integrators, and differentiators Typical Texts (in unison): Fiore, J. M. (2020). Semiconductor Devices: Theory and Application. Independently published Fiore, J. M. (2020). Semiconductor Devices: Theory and Application Laboratory Manuals < http://www.dissidents.com/resources/LaboratoryManualForSemiconductorDevices.pdf https://www2.mvcc.edu/users/faculty/jfiore/Linear/labs/LaboratoryManualForSemiconductorDevices.pdf http://www.cs.ucf.edu/courses/eee5356/EEE5356_LabManual_Sp09.pdf > Required Software: SPICE simulator Wolfram System Modeler Modelica libraries GRADING: Homework: 10 % Lab: 20 % Exam 1: 20 % Exam 2: 20% Final Exam 3: 30 % COURSE OUTLINE 1. Semiconductors a. Intrinsic semiconductor b. Doped semiconductor c. Physical operation of p-n junction diodes d. Capacitive effects in the p-n junction 2. Diodes a. Ideal Diode b. Terminal characteristics of p-n junction silicon diodes c. Forward characteristics of p-n junction diodes d. Reverse bias characteristics of p-n junction diodes e. Zener diodes f. Rectifying circuits g. Limiting and clamping circuits 3. MOS Field Effect Transistors (MOSFETs) a. MOS Device structure and physical operation b. Current-Voltage characteristics c. The MOSFET as an amplifier and a switch d. Biasing the MOSFET e. Small signal operation f. Single Stage MOS amplifiers 4. Bipolar Junction Transistors (BJTs) a. BJT structure and physical operation b. Current-Voltage characteristics c. The BJT as an amplifier and a switch d. Biasing the BJT e. Small signal operation f. Single stage BJT amplifiers 5. Operational Amplifiers (Op Amp) a. The ideal Op Amp b. The inverting configuration c. The non-inverting configuration d. Difference amplifiers e. Frequency response f. Large signal operation of Op Amp g. Integrators and Differentiators Prerequisites: General Physics II, Circuit Analysis II, ODE, Calculus III 6. Solid State Devices II Typical Texts (in unison): Giorgio Rizzoni, Principles & Applications of Electrical Engineering, 4th Edition, McGrawHill 2004 Adel S. Sedra and Kenneth C. Smith, Microelectronic Circuits, 5th Edition, Oxford 2004 Technological requirements --> SPICE simularor Wolfram SystemModeler with Semiconductors Modelica libraries Ansys Semiconductors NOTE: such tools will play a heavy role concerning applications…SERIOULSY Note: Building with semiconductor components yielding circuitry strong circuitry analysis and simulations. SystemModeler also gives additional practice with the Modelica environment. The latter (ANSYS) additionally provides professional details and microscale descriptions that constitute performance characteristics, of particular components, etc. Grading: Assignments 10% Labs (like in prerequisite but a bit more advanced with applications) 15% Modelling, schematics, simulations activities (SystemModeler and Ansys) 15% Exam 1 20% Exam 2 20% Final 20% Course Outline I. Semiconductors and Diodes A. Electrical Conduction in Semiconductor Devices B. The pn Junction and the Semiconductor C. Circuit Models for the Semiconductor Diode a. Large-Signal Diode Models b. Small-Signal Diode Models c. Piecewise Linear Diode Model D. Rectifier Circuits a. The Full-Wave Rectifier b. The Bridge Rectifier E. DC Power Supplies, Zener Diodes, and Voltage Regulation II. Field-Effect Transistors: Operation, Circuit Models, and Applications A. Classification of Field-Effect Transistors B. Overview of Enhancement-Mode MOSFETs a. Operation of the n-Channel Enhancement-Mode MOSFET b. Biasing MOSFET Circuits c. Operation of the p-Channel Enhancement-Mode MOSFET C. MOSFET Amplifiers D. MOSFET Switches a. Digital Switches and Gates b. Analog Switches III. Bipolar Junction Transistors: Operation, Circuit Models, and Applications A. Transistors as Amplifiers and Switches B. Operation of the Bipolar Junction Transistor a. Determining the Operating Region of a BJT b. Selecting an Operating Point for a BJT C. BJT Switches and Gates IV. AC Transistor Equivalent-Circuit Models A. MOSFET High-Frequency Models B. MOSFET Amplifier Analysis C. The CMOS Digital Logic Inverter V. Electronic Instrumentation and Measurements A. Measurement Systems and Transducers a. Measurement Systems b. Sensor Classification c. Motion and Dimensional Measurements d. Force, Torque, and Pressure Measurements e. Flow Measurements f. Temperature Measurements B. Wiring, Grounding, and Noise a. Signal Sources and Measurement System Configurations b. Noise Sources and Coupling Mechanisms c. Noise Reduction C. Signal Conditioning a. Instrumentation Amplifiers b. Active Filters D. Analog-to-Digital and Digital-to-Analog Conversion a. Digital-to-Analog Converters b. Analog-to-Digital Converters c. Data Acquisition Systems E. Comparator and Timing Circuits a. The Op-Amp Comparator b. The Schmitt Trigger c. Multivibrators d. Timer ICs: The NE555 F. Other Instrumentation Integrated Circuits Amplifiers a. DACs and ADCs b. Frequency-to-Voltage, Voltage-to-Frequency c. Converters, and Phase-Locked Loops d. Other Sensor and Signal Conditioning Circuits G. Data Transmission in Digital Instruments a. The IEEE Bus b. The RS- Standard c. Other Communication Network Standards VI. Communication Systems A. Introduction to Communication Systems a. Information, Modulation and Carriers b. Classification of Communication Systems c. Communication Channels B. Spectral Analysis a. Signal spectra b. Periodic Signals: Fourier Series c. Non-periodic Signals, Fourier Transform d. Bandwidth C. Amplitude Modulation and Demodulation a. Basic Principle of AM b. AM Demodulation; Integrated Circuit Receivers D. Frequency Modulation and Demodulation a. Basic Principle of FM b. FM Demodulation E. Examples of Communication Systems a. Global Positioning System (GPS) b. Radar c. Sonar d. Computer Networks e. Wireless Networks and Personal Communication Systems f. The Internet Prerequisites: Solid State Devices I 7. Solid State Devices III Semiconducting materials and semiconductor devices play a very important role in modern technology. Semiconductor devices are not only indispensable parts of systems, such as computers, biomedical equipment, which are important in our daily life, but also from the basis for development of novel technology through their operational principles. Knowledge and understanding of semiconductors and devices are essential for applied physics graduates planning for a technological career. The aim of this course is to provide the students a sound understanding of semiconductor physics and the operational principles of some electronic devices, for learning and using modern technology. In this course, students can also develop the basic analytical skills required for learning or developing novel devices, their fabrication processes and technological applications for their future career. Course Intended Learning Outcomes --> Describe the physical characteristics, such as electronic structures and optical and transport properties of semiconductors and I-V characteristics of semiconductor devices. Relate the electronic structures of semiconductors to their atomic and crystal characteristics. Relate the transport and optical properties of semiconductors to fundamental physics processes. Apply fundamental principles and processes to operational semiconductor devices and their uses. Describe and model some semiconductor properties, processes and device characteristics using equations. Evaluate and analyse device characteristics in terms of the material properties and/or structural parameters. Typical Text: S.M. Sze and Kwok K. Ng, Physics of semiconductor devices (latest edition), Wiley Note: texts applied to lower level semiconductor courses can be used as personal refreshers. Technological requirements --> SPICE simulator Wolfram SystemModeler with Semiconductors Modelica libraries Ansys Semiconductors Note: Software will strongly complement each other. The former permits building with semiconductor components yielding circuitry strong circuitry analysis and simulations. SystemModeler also gives additional practice with the Modelica environment. The latter (ANSYS) additionally provides professional details and microscale descriptions that constitute performance characteristics, of particular components, etc. Grading: Assignments 15% Modelling, schematics, simulations activities (SystemModeler and Ansys) 15% Exam 1 20% Exam 2 20% Final 30% Course Outline --> I. Some Quantum Physics Wave-particle duality, postulates of quantum mechanics, Schrodinger equation, free particle and particle in a box solutions, periodic boundary condition (3 hours) II. Semiconductor Band structure (4 hour) Bloch theorem, formation of semiconductor energy bands from atomic orbitals, effect of impurity doping, impurity energy level, effective mass approximation, electrons and holes, optical processes in semiconductors. III. Semiconductor Transport Properties (4 hours) Drift and diffusion motions, continuity equation, generation and recombination of carriers, carrier lifetime, steady state carrier diffusion. (4 hours) IV. P-N Junctions (3 hours) Equilibrium properties of p-n junctions, space charge layer, I-V characteristics of p-n junctions and its mathematical description. V. Device Applications of p-n Junctions (2 hours) Rectifiers, photodiode, light emitting diode and carrier injection in semiconductor lasers. VI. Bipolar Junction Transistor (2 hours) Device structure and carrier transport, mechanism of current amplification. VII. Metal Oxide Semiconductor Field Effect Transistors (MOSFET) (2 hours) Device structure, formation of accumulation and inversion layers, current control mechanism, band-bending due to gate voltage, I-V characteristics, application examples. VIII. Junction Field Effect Transistors (JFET) (2 hours) Device structure, current control mechanism, I-V characteristics, application examples. IX. Integrated Circuits: fabrication steps. (1 hour) Prerequisites: Solid State Devices II, Modern Physics 8. Electromagnetics I Introduction to vector operation, Static electric and magnetic fields. Electric and magnetic fields with boundary conditions. Time varying electromagnetic fields and Maxwell's equations. Application to traditional circuit theory, RF circuit components, transmission lines, electromagnetic interference and electromagnetic compatibility. After participating in this course, a student will be able to: -Mathematically compute and describe the physical interpretation of vector calculus operations including gradient, divergence, and curl. -Interpret visualizations of electric fields, electric scalar potentials, and magnetic fields in terms of the forces that charged particles or currents would experience. -Sketch the electric fields, electric scalar potentials, and magnetic fields associated with a given set of charges and currents. -Discuss the superposition principle and describe its physical interpretation. -Describe the parameters used to characterize a material's response to electromagnetic fields and how these parameters are affected by variables such as temperature, frequency, and field strength. -Discuss the primary categories of materials, in electromagnetic terms, and how those materials respond to electric and magnetic fields. Sketch the deformation of external fields near different types of materials. -Describe the theory of magnetic induction and what variables could be altered to increase the electromotive force (EMF) produced by an electric generator. -Utilize image theory to simplify an electromagnetics problem, and describe the physical processes that image theory represents. -Mathematically describe plane waves of various polarizations and propagation directions, in the frequency domain. Interpret the ideal plane wave model in physical terms. -Calculate the reflected and transmitted power and propagation directions when a plane wave propagates between two dissimilar materials. -Calculate the decay in signal strength as a plane wave propagates through various materials. -Calculate the reflection coefficient, VSWR, reflected and transmitted power in a transmission line with various loads. Determine these values mathematically and using a Smith chart. ‘ -Describe the characteristics of several standard antennas, including the benefits and drawbacks of each type. -Select an appropriate polarization, frequency, and antenna type for a given transmission application. Calculate polarization loss and path loss. -Convert between linear and logarithmic power values. Convert between common values without a calculator. Describe the expected accuracies in various power measurements. -Apply the knowledge and understanding described above to explain how electromagnetic phenomena are utilized in various technical devices. -Build upon the knowledge and understanding described above to utilize electromagnetic phenomena in novel designs. Typical texts: Fundamentals of Applied Electromagnetics by Fawwaz Tayssir Ulaby, Eric Michielssen, Umberto Ravaioli, Prentice Hall Fundamentals of Engineering Electromagnetics by David Keun Cheng, Addison-Wesley Publishing Company, Electromagnetics by John Daniel Kraus, Mcgraw-Hill Publishing Company, Grading --> Homework 3-4 Quizzes Labs 3 Exams Labs --> Concerning the given literature for labs, apart from competent comprehension of logistics and implementation, each lab must be coherent, tangible and practical with course topics, and vice versa. Hence, a particular lab experiment may be done on multiple occasions with possible extensions/augmentations. Cloete, Reader, H. ., van der Merwe, J., du Plessis, F. ., & Becker, L. . (1996). Experiments for Undergraduate Courses in Electromagnetic Theory and EMC. Proceedings of IEEE. AFRICON ’96, 1, 362–365 vol.1. Mitchell, M., Blandford, D. and Chandler, K. M. (2016). Student Projects for an Electromagnetics Course. American Society for Engineering Education, 123rd Annual Conference & Exposition, New Orleans, LA, June 26-29 MIT OCW Electricity & Magnetism Experiments: https://ocw.mit.edu/courses/physics/8-02-physics-ii-electricity-and-magnetism-spring-2007/experiments/ Electrostatic filters Metal detector circuit Taghizadeh, S. and Lincoln, J. (2018). MRI Experiments for Introductory Physics. The Physics Teacher, Volume 56, Issue 4 Hard Drive Degausser development Eddy Current Magnetic Brake (simplistic setup) Molina-Bolívar, Jose & Abella-Palacios, A. (2012). A Laboratory Activity on the Eddy Current Brake. European Journal of Physics 33(3): 697-707 Course Outline--> -Review on vector operation with scalar and vector fields, and integrals (line, surface and volume), orthogonal coordinates, gradient, divergence, curl and Laplacian operations -Electrostatics: Electric force, electric field, electric potential, materials’ electric properties, Method of images. Developing solutions for field equations. -Magnetostatics and Inductance: Magnetic force, magnetic field, materials’ magnetic properties, curl/circulation, induced EMF, transformers. Developing solutions for field equations (ideal, real world engineering consideration subtleties, etc.) -Maxwell’s equations, frequency domain, plane waves, polarization, transmission/reflection, antennas, decibels, pathloss. Developing solutions for field equations (ideal, real world engineering consideration subtleties, etc.) -Review on Transmission lines (impedance, VSWR, Smith chart), skin depth, Smith chart. There will be an exam after completing each quarter. Prerequisites: Ordinary Differential Equations, General Physics II, Calculus III 9. Electromagnetics II: Maxwell’s equations for time-varying fields; plane wave propagation and reflection; waveguide structures; radiation and antennas. Topics in wave propagation include scattering, optics, principles of radar, signal integrity and mathematical solution techniques Outcomes --> Advance synopsis and model/solutions summary from prerequisite. Ability to apply Maxwell's equations to analyze time-varying electromagnetic problems. Ability to analyze plane wave propagation problems. Ability to compute reflection and transmission properties of plane waves on plane boundaries at normal and oblique incidence. Ability to analyse radiative emissions problems (including antennas). Perform experiments using antennas, radars, waveguides and optical components. Write technical lab reports, analyze and summarize results. Ability to use Matlab/Mathematica as a tool for engineering electromagnetic problem solving. Assignments --> Assignments will involve both prerequisite refresher and current course obligations. Use of Mathematica/Matlab will be incorporated into assignments. Exams --> Will have 4 exams that will reflect all aspects of assignments and course topics. Topical Outline --> Maxwell’s equations for time-varying fields. Faraday’s law for computing voltage from coils in time-varying magnetic field, electromagnetic generators, displacement current. Mathematical description of TEM waves, polarization properties of electromagnetic waves, current in conductors, resistance, power carried by an electromagnetic wave. Transmission properties of optical fibers. Characterization of the reflection and transmission of plane waves on plane boundaries at normal and oblique incidence. Characterization of wave propagation in rectangular waveguides and behavior of rectangular resonant modes. Fields radiated from a dipole antenna. Antenna radiation patterns, directivity, beamwidths and radiation resistance for antennas. Friis transmission formula for communications systems. Radiation patterns for antenna arrays. -- Experimental Lab 1 Optics: Explore basics of optical systems including diffraction and refraction phenomena, Young’s double slit experiment and Snell’s law. Characterize the reflection and transmission of plane waves on plane boundaries at normal and oblique incidence. Characterize wave propagation in rectangular waveguides. Determine the behaviour of rectangular resonant modes. -- Experimental Lab 2 Waveguides: Measure characteristics of rectangular waveguides including standing wave patterns. Calculate the fields radiated from a dipole antenna. Characterize radiation patterns, directivity, beamwidths and radiation resistance for antennas. -- Experimental Lab 3 Antennas: In this lab students characterize (horn) antennas and explore the concepts of antenna field patterns, beamwidth, gain, polarization and the range dependence of received power. Apply the Friis transmission formula to communications systems. Calculate radiation patterns for antenna arrays. -- Experimental Lab 4 Applications of radars: This lab uses radars to explore concepts of monostatic radar returns and Doppler frequency shifts. NOTE: the given labs are expected, however, they will be augmented by the following --> https://studylib.net/doc/18804173/eecs-330-applied-electromagnetics-ii-laboratory-manual-the However, software can be substituted by others. Prerequisite: Electromagnetics I 10. Electromagnetic Waves & Antennas Check Computational Finance post Electromagnetics II prerequisite 11. Antenna Theory Check Computational Finance post (Electromagnetics II prerequisite) 12. Optical Communications & Photonics: Check Computational Finance post Prerequisite: Analogue & Digital Communications Systems; Modern Digital Communications; Electromagnetics II Co-requisite: Optical Communications & Photonics Lab 13. Optical Communications & Photonics Lab: Check Computational Finance post Prerequisite: Analogue & Digital Communications Systems; Modern Digital Communications; Electromagnetics II Co-requisite: Optical Communications & Photonics 14. Optoelectronics (with labs) Check Computational Finance post Prerequisites: General Physics II, Calculus III, Modern Physics 15. Advanced Optics Lab Check Computational Finance post Prerequisites: Intro to Optics 16. Electric Drives I: Electric Drives efficiently control the torque, speed and/or the position of electric motors. This course has a multi-disciplinary nature and includes fields such as electric machine theory, power electronics, analogue and digital control theory, real-time application of digital controllers, mechanical system modelling and interaction with electric power systems. Topics include: phasor representation in sinusoidal steady state, switch-mode power electronics converters, power semiconductor devices, magnetic circuit, Faraday’s Law, leakage and magnetizing inductances, production of magnetic field, force of current-carrying conductor in a magnetic field, emf induced in a conductor moving in a magnetic field, DC machine (structure and operating principles), various operating modes in DC motor drives, feedback controllers, cascade control structure, small-signal analysis, AC machines, space vectors, sinusoidal field distribution in the air gap, synchronous motor drives, Brushless DC machine and drives, induction-motors, vector control of induction-motor drives, stepper-motor. Course Learning Objectives: i. Basic understanding of switch-mode power electronic converters in electric drives ii. Be able to analyse magnetic circuits iii. Understand the basic structure of electric machines and the fundamental principles of the electromagnetic interactions that govern their operation iv. Be able to design linear feedback controllers for motor drives v. Understand cascade control structure. Design the position control loop, speed loop and torque control loop vi. Understand induction motor operation vii. Be able to design V/f speed control for induction motor viii. Understand vector control of induction-motor ix. Understand stepper-motor and reluctance drives Textbook(s) and/or other materials: 1.Electric Drives, N. Mohan, MNPERE, 2003 (2007) edition 2.Power Electronics: Principles & Applications, J. Michael Jacob, Delmar, 2002 (optional) Grading --> Homework (5) 20% Exam1: 10% Exam2: 10% Exam3: 10% Comprehensive Final Exam: 50% Course Outline --> I. COURSE INTRODUCTION A. Course Overview 1.1-1.7 B. Syllabus II. MAGNETIC CIRCUIT (REVIEW) A. Magnetic field produced by current-carrying conductors Flux density and the flux linkage 5.1-5.2 B. Magnetic field structures with air gaps 5.4 C. Inductances, transformers, energy 5.5 Homework 1 III. DC-MOTOR DRIVES AND ELECTRONICALLY-COMMUTATED MOTOR DRIVES A. The structure of DC machines 7.1 B. Operating principles of DC machines 7.2 C. DC-machine equivalent circuit 7.4 D. Various operating modes in DC-motor drives 7.5 E. Power-processing units in DC drives 7.7 Homework 2 IV. DESIGN FEEDBACK CONTROLLERS FOR MOTOR DRIVES A. Control objectives 8.2 B. Cascade control structure 8.3 C. Steps in designing the feedback controller 8.4 D. Controller design 8.6-8.7 E. Modelling with SystemModeler V. AC MACHINES AND SPACE VECTORS A. Sinusoidally-distributed stator windings 9.1-9.2 B. Space vector 9.3 C. Space vector representation of combined terminal currents and voltages 9.4 D. Balanced sinusoidal steady-state excitation 9.5 Homework 3 VI. SINUSOIDAL PERMANENT MAGNET AC DRIVES A. The structure of permanent-magnet AC syn. machine B. Principle of operation 10.3 C. The controller and the Power-Processing Unit (PPU) 10.4 Homework 4 VII. INDUCTION MOTORS A. The operation of induction motor 11.3 B. Tests to obtain the parameters of the per-phase equivalent circuit 11.4 C. Line start and soft start of induction motors 11.8 VIII. INDUCTION MOTOR DRIVES: SPEED CONTROL A. Conditions for efficient speed control over a wide range 12.1 B. Starting considerations in drives 12.4 C. Capability to operate below and above the rated speed 12.5 D. Speed control of induction-motor drives 12.6 E. Pulse-Width-Modulated Power-Processing Units 12.7 Homework 5 IX. INDUCTION MOTOR DRIVES: VECTOR CONTROL A. D- and Q- axis winding representation 13.4 B. Torque, speed, and position control 13.7 C. Sensor-less Drives 13.8 X. RELUCTANCE DRIVES: STEPPER MOTOR A. The principles of reluctance motors 14.2 B. Stepper-motor controller and drives 14.3 Prerequisites: Circuit Analysis I & II, Solid State Devices I. Co-requsite or Prerequisite: Feedback Control 17. Electric Drives II: This is an advanced undergraduate course focusing on electric drive systems (power electronics driven electromechanical devices). It is essential that students have a basic background in classical control techniques such as the design of P, PI, PID controls, transfer function development, and stability analysis. The focus of the course will include permanent magnet synchronous machine and induction motor drives. There will be a heavy emphasis on operation, physical modelling, and applied control. Typical Text: Analysis of Electric Machinery, 2nd Edition, Krause, Wasynczuk, Sudhoff, IEEE Press / Wiley Inter-Science A student who successfully fulfills the course requirements will have demonstrated an ability to: Model and simulate electric drive systems. Design modulation strategies for power electronics converters. Design appropriate current-voltage regulators for electric drives. Design appropriate supervisory (example torque) control algorithms. Design speed and position controls for systems using electric drives. Tools: SystemModeler Modelica Libraries Grading: Homework 20% Exam 1 15% Exam 2 15% Labs 50% Lecture Topic (30 lecture periods at 2 per week) --> Reference Frame Theory 3 periods Modelling and Parameter Identification of SMPM Machines 1 period Fully-Controlled Bridge Converters 2 periods Modulation Techniques 5 periods Voltage and Current Regulation 3 periods Control of SMPM Drives 5 periods Modelling & Parameter Identification of Induction Machines 3 periods Volt/Hertz Induction Motor Drives 2 periods Indirect and Direct Field Oriented Control 5 periods Optimal Control of Induction Motor Drives 1 period Laboratory Topic (15 laboratory periods at 1 per week) --> Introduction to Advanced Continuous Simulation Language 2 periods Six Step Inverter Simulation 1 period Modulator Simulation 1 period Voltage / Current Control Simulation 2 periods SMPM Characterization 1 period SMPM Drive 2 periods Induction Machine Characterization 2 periods Induction Machine Volts Per Hertz Control 2 periods Induction Machine Constant Slip Control 2 periods Prerequisites: Electric Drives I; Feedback Control or Automatic Control 18. Power Electronics: http://ecee.colorado.edu/~ecen5797/syllabus.html Text: Fundamentals of Power Electronics, by Robert Erickson and Dragan Maksimovic, 2nd edition, Springer Science + Business (2000) Grading: Ten to twelve one-week homework assignments 20% Two Midterm Exams and one Final exam 45% Simulations + Labs 35% Labs --> Will make use of SPICE simulators, SystemModeler, Ansys Electromagnetics and Ansys Semiconductor for displays and simulation accompanying lab experiments. Such labs are crucial towards sustainability with knowledge and skills. NOTE: generally, primitive builds by students will be compared to simulators and power-pole boards for particular labs; modelling and simulations done before use of hardware. It’s essential to have compare/contrast between simulations and real systems. However, for safety, some (not all) primitive builds may not be applied directly; also, such is possibly being economic with the welfare of other components, such as motors, etc. There must be means to confirm the behaviour/performance of primitive builds before any integration is possible. Multimeters and oscilloscopes are essential. Labs --> (i) Laboratory and Power-pole Board Familiarization JoVE Science Education Database. Electrical Engineering. Introduction to the Power Pole Board. JoVE, Cambridge, MA, (2020). < https://www.jove.com/science-education/10254/introduction-to-the-power-pole-board > (ii) Voltage regulator and Step-down converter (iii) Switching Characteristic of MOSFET and Diode using Power-Pole Board (iv) Boost Converter (v) Step Down-Boost Converter (vi) Voltage-Mode Control (vii) Peak Current Mode Control (viii) Flyback Converter (ix) Forward Converter Lab Constituents: --SPICE simulator --Wolfram SystemModeler (and/or Modelica Libraries) --Generic featured hardware components --Heavy circuitry analysis and building --Board based diodes, regulators, converters, DC, AC, inverters, rectifiers, transformers (impulse and others), power-pole, microcontrollers --Meters Multimeters, oscilloscopes with port interface --Interface Desktop computer or laptop with software for capturing oscilloscope data via port (concerning software for captured waveforms or data for use) --Function generator --Voltage probe --Motors DC, AC --Alongside for comparison with lab activities will be simulation tools --SystemModeler, Modelica libraries, ANSYS (or other) building and simulations (with possibility of I/O activity). NOTE: there may be additional time required to become at least capable with an environment involving microcontrollers. Wolfram software and others have virtual modules for Arduino, Raspberry Pi and possibly others. With such modules will need to apply programming with such virtual modules towards power electronics systems labs. Some microcontrollers will be generic as well. Then, will proceed with physical projects. Prerequisite: Circuit Analysis II 19. Modelling & Control of Power Electronics: Advanced modelling and control topics in power electronics, and power factor corrected supplies. Averaged switch modelling of converters, computer simulation, ac modelling of the discontinuous conduction mode, the current programmed mode, null double injection techniques in linear circuits, input filter design, harmonics in power systems, low-harmonic rectifiers, and introduction to digital control. Textbook: Erickson and Maksimovic, “Fundamental of Power Electronics”, 2nd edition, Springer Science + Business Assessment --> Ten to twelve one-week homework assignments 20% Two Midterm Exams and one Final exam 45% Simulations + Labs 35% Access to web is required. Labs will make use of Modelica libraries, SystemModeler or a Spice simulator (check software portfolio list), and Ansys Electromagnetics for displays and simulation accompanying lab experiments. Such labs are crucial towards sustainability with knowledge and skills. Use of a simple spreadsheet, such as Excel, may be helpful but is not required. Outline: I. Averaged switch modelling and simulation Section 7.4 and Appendix B Deriving Average small-signal models of converters by averaging only the switching elements Objectives of Simulation Simulation of converter small-signal behaviour using averaged switched models II. Techniques of Design-Oriented Analysis, with Application to Switching Converters Middlebrook Extra Element Theorem Appendix C Null double injection technique to find how addition of an element alters a transfer function Input Filter Design Chapter 10 How the addition of an input filter disrupts the loop gain of a switching regulator How to design an input filter having adequate damping, so that the input filter does not change the loop gain The n-Extra Element Theorem Supplementary notes posted on the web site. Also, Section 8.1.8 will be covered An extension of the extra element theorem that allows exact expressions for complex transfer functions to be written "by inspection." Middlebrook's Feedback Theorem Supplementary notes posted on web site Analysis of feedback circuits using null double injection techniques III. Dynamic Modelling and Simulation of Converters Operating in Discontinuous Conduction Mode Chapter 11 and Appendix B Equivalent circuit modelling of converters operating in the discontinuous conduction mode, using averaged switch modelling How changing the operating mode leads to substantial changes in small-signal transfer functions. IV. Introduction to Sampled-data Modelling Supplementary notes posted on web site Sampled-data small-signal modelling Pulse-width modulator as a sampler, equivalent hold Application of the sampled-data model to discontinuous conduction mode V. Current Programmed Control Chapter 12 and Appendix B Introduction to this very popular technique for controlling switching converters Basic circuitry and slope compensation Averaged switch modelling Sampled-data modelling of current programmed converters Detailed small-signal analysis Simulation Effects of current mode control on basic transfer functions VI. Introduction to Digital Control of Switching Converters Supplementary notes posted on the web site Digital realization of the basic control loop Discrete-time converter model Examples of discrete-time compensator design VII. Modern Rectifiers Power and Harmonics in Non-sinusoidal Systems: Chapter 16 Pulse-Width Modulated Rectifiers: Chapter 18 Modelling, analysis, and control of low-harmonic rectifiers Boost, flyback, and other topologies for controlling the input current waveform of an ac-dc rectifier Average-current, peak-current-mode, critical conduction mode, and nonlinear carrier control techniques Determination of rms currents, and comparison of performances of popular topologies System considerations. Modelling losses. Simulation. Grade constitution: Midterm exam, Final exam, Homework (10-12 assignments), Labs. LAS --> Labs activities will be geared towards education, efficiency, ingenuity, economics and spatial optimisation. JoVE Science Education Database. Electrical Engineering. Introduction to the Power Pole Board. JoVE, Cambridge, MA, (2020). < https://www.jove.com/science-education/10254/introduction-to-the-power-pole-board > Will make use of SPICE simulators, SystemModeler, Ansys Electromagnetics and Ansys Semiconductor for displays and simulation accompanying lab experiments. Such labs are crucial towards sustainability with knowledge and skills. NOTE: generally, primitive builds by students will be compared to simulators and power-pole boards for particular labs; modelling and simulations done before use of hardware. It’s essential to have compare/contrast between simulations and real systems. However, for safety, some (not all) primitive builds may not be applied directly; also, such is possibly being economic with the welfare of other components, such as motors, etc. There must be means to confirm the behaviour/performance of primitive builds before any integration is possible. Multimeters and oscilloscopes are essential. For labs 1. will have recitals of chosen labs from prerequiste 2. http://web.eecs.utk.edu/courses/spring2019/ece482/experiments.php Constituents: --Heavy circuitry analysis and building --Board based diodes, converters, DC, AC, inverters, rectifiers, transformers (impulse and others), power-pole, microcontrollers --Generic featured hardware components --Meters Multimeters, oscilloscopes with port interface --Interface Desktop computer or laptop with software for capturing oscilloscope data via port (concerning software for captured waveforms or data for use) --Function generator --Voltage probe --Motors DC, AC --Alongside for comparison with lab activities will be simulation tools --SPICE simulator, Modelica Libraries, SystemModeler and/or ANSYS (or other) building and simulations (with possibility of I/O activity). NOTE: To determine credibility and accuracy of modelling and simulations such must be compared to real physical systems. There may be additional time required to become at least capable with an environment involving microcontrollers. Wolfram software and others have virtual modules for Arduino, Raspberry Pi and possibly others. With such modules will need to apply programming with such virtual modules towards power electronics systems labs. Some microcontrollers will be generic as well. Then, will proceed with physical projects. Prerequisites: Power Electronics 20. Power System Analysis I Check Computational Finance post Prerequisites: Circuit Analysis II, Signals & Systems, Power Electronics 21. Power System Analysis II A sequential regimen is crucial to towards any retention, competency, efficiency and professionalism. Course is an intensified version of its prerequisite. Prerequisite: Power System Analysis I 22. RF & Microwave Circuits for Wireless Communications I Check Computational Finance post Prerequisites: Electromagnetic Waves & Antennas, Antenna Theory. 23. RF & Microwave Circuits for Wireless Communications II Check Computational Finance post Prerequisite: RF & Microwave Circuits for Wireless Communications I 24. Electromagnetic Compatibility: Electromagnetic interference and susceptibility of electrical systems, with application to analog and digital circuits. Prototypical text: Ott, Electromagnetic Compatibility Engineering, John Wiley, 2009 Supplementary texts: Introduction to Electromagnetic Compatibility, Clayton R. Paul, John Wiley & Sons, New York, 2nd edition, 2006. Archambeault B.R. (2002) Introduction to EMI/EMC Design for Printed Circuit Boards. In: PCB Design for Real-World EMI Control. The Springer International Series in Engineering & Computer Science, vol 696. Springer Resources to apply: Technical papers and white papers for EMC/EMI and so forth from firms such as Texas Instruments, STM, NXT and various others. Such papers concern analysis and replication with lab. Will try to be most constructive as possible compared to lecturing texts; lecturing texts often may not be as modern as one would like. I. Upon successful completion of course, students will be able to --> Explain the basic causes of most electromagnetic compatibility (EMC) problems and implement design techniques that minimize those problems. Interpret FCC (or whatever sovereignty) limits on radiated emissions and be able to estimate those emissions for circuit subsystems. Calculate self and mutual capacitance and inductance for simple configurations of conductors. Estimate the noise coupled from one circuit to another through mutual capacitance and mutual inductance. Distinguish between differential-mode and common-mode currents, and be able to design devices such as common-mode chokes to suppress unwanted common mode currents. Explain some of the non-idealities of standard circuit components. Predict the high frequency content of digital signals based on their rise time and other characteristics. Describe the differences between analogue and digital circuits and the various sources of analogue circuit and digital circuit noise. Design decoupling capacitors to reduce switching noise in digital circuits. Design shields for near and far sources of electric and magnetic fields. Determine cavity resonant frequencies and circuit board resonant frequencies and explain their potential impact on EMC applications. II. Course Outline --> Introduction to EMC Problems Self and Mutual Capacitance Self and Mutual Inductance Capacitive & Inductive coupling Signal grounding & Ground loops Common-mode chokes and Balanced circuits Ideal RLC Circuits in the Time and Frequency Domains EM Fields in Lossy Media Conductors and Non-Ideal Resistors Non-ideal Capacitors & Inductors Ferrite beads Power Supply Noise & Decoupling Spectra of electrical signals Reflection and Crosstalk Noise in Digital Circuits Switching Noise & Decoupling in Digital Circuits Common-mode and Differential-mode Radiation Shield design for far-field and near field sources Cavity and Circuit Board Resonances Electrostatic charging mechanisms and discharge mitigation techniques III. Specific necessary concerns to arise throughout course topics --> -Signals and Spectra -General Formulation of Electric Circuit Theory -Non-ideal Behaviour of Circuit Components -Antennas -Modulation and the Measurement of Signals -EMC Regulations -Conducted Emissions & Susceptibility -Conducted Immunity -Radiated Emissions & Susceptibility -Radiated Immunity -RF Network Analysis and Measurement Components -Cabling and Cross Talk -Shielding -Electrostatic Discharge (ESD) -System Design: -Printed Circuit Board Design -Grounding -EMC filter design III. Lab Training Obligations in groups (in most constructive order) --> EMC Standards SPICE simulator Waveform Generator and the Oscilloscope Transmission lines with transient excitation (6 hours) Steady-state transmission lines (6 hours) Network Analyzer (6 hours) Spectrum Analyzer Signals and Spectra Non-ideal Behaviour of Circuit Components Conducted emissions Radiated emissions Note: all such prior serve as EMI and RMS testing systems. IV. Student Groups PCB Design Project --> Students will develop a PCB design towards serving a particular purpose (rocket system, robotic system, weather station, weather balloon, spectroscopy, etc. etc., etc.). Industrialization is becoming quite accessible to the common folk. What application you choose, the difficulty depends on the required tasks, processing, required sensing, and testing. In some cases, understanding systems or vehicle dynamics will be necessary to be able to develop anything meaningful or constructive. There are PCB design software in “Goody Bag” post that will not hit you or the college in the wallet; EMC verification is a major concern. Groups must be able to provide an abstract and outline for the EMC process accompanied quantitative/computational development that conveys appeasement of regulations and strong functionality. Note: your lab training and labs will be highly influential. At designated times students must submit to professor credible progress development. V. Labs -->: -Radiated Emission measurement of a telephone answering machine for EN55022 -Radiated Susceptibility measurement of an electronic product for EN61000-4-3 -Conducted Emission measurement of a good PCB layout and a poor PCB layout -E-field and H-field Close-Field Probe diagnostic measurement -Coupled lines - grounding effect noise reduction of coupling between PCB tracks -Measurement of common impedance interference on various PCB layouts -Harmonics and Flicker Measurement - To measure the harmonics and voltage fluctuations (flicker) caused by mains operated equipment -ESD –Electrostatic Discharge measurement of a pager for EN61000-4-2 -Filter selection for EMI suppression -Investigation of Texas Instruments papers The following documentation will be analysed. As well, there are design schemes and experimentation exhibitions to pursue in lab. It’s just fine if there are methods and schemes not encountered in course; elaboration of them compared to learnt methods is encouraged. Mammano, B. and Carsten, B. (2002). Understanding and Optimizing Electromagnetic Compatibility in Switchmode Power Supplies. Texas instruments < https://www.ti.com/seclit/ml/slup202/slup202.pdf > Getz, R. and Moeckel, B. (1996). Understanding and Eliminating EMI in Microcontroller Applications. National Semiconductor Application Note 1050. Texas Instruments < http://www.ti.com/lit/an/snoa382/snoa382.pdf > AN-643 EMI/RFI Board Design. SNLA016B–May 2004. Texas Instruments http://www.ti.com/lit/an/snla016b/snla016b.pdf NOTE: one isn’t confined to Texas Instruments -Open lab – projects and make-up -Open lab – projects and make-up Prerequisites: Circuit Analysis II; Electromagnetics I; Solid State Devices II 25. Solar Energy Photovoltaics: A conventional textbook: Modelling and Analysis of Photovoltaic, Thermal, and Electrochemical Solar Energy Systems by R. A. Adomaitis (2013). However, the journal articles listed will be applied to account for critical modern band engineering and technologies. Labs --> CORE LAB GOALS: 1. Locate the sun position at any given location and time, interpret sun path diagrams, analyze solar insolation on a collecting surface, and measure solar radiation measurements. 2. Understand the inner workings of p-n junctions, determine a circuit model of a PV cell, PV module and PV array, measure and interpret I-V curves, understand the impact of temperature and solar insolation on I-V curves, have a broad knowledge on different types PV technologies and their limitations. 3. Determine the operating point of basic electrical loads connected directly to a PV module or array. 4. Design a grid-connected PV system, including the PV array and balance of system (BOS), conduct an economic analysis, and be familiar with the impact of high PV penetration on the utility grid. 5. Have basic knowledge on different types of batteries and their electrical characteristics. 6. Design a stand-alone PV system by estimating the load, sizing and selecting the batteries, sizing and selecting the PV modules, charge controller and inverter. 7. Have basic knowledge on codes and standards associated with PV Systems. SOLAR CELL DEVELOPMENT LAB GOALS: For experimental solar cells development preference is to operate with bigger “acrylic” plates. Goal is to develop the beneath exhibiitions alongside the given core lab goals in the most constructive and productive manner; such experiments alongside the core lab goals that use commercial solar cells/plates. It’s crucial that students are able to develop prediction models for current and voltage before experiments development. We want graphs for current and voltage from experiments. -DSSC examples NurdRage – Making a Solar Cell – TiO2/Raspberry based – YouTube Neal Abrams – Constructing a Dye Sensitized Solar Cell – YouTube JuiceFromJuice – DSSC – YouTube -Perovskite examples: UW Clean Energy Institute – Constructing a Perovskite Solar Cell – YouTube The Physics Point – Preparation of high quality Perovskite thin films – YouTube Breitweiser Products – Organic – Inorganic Perovskite Hybrid Solar Cell – YouTube Projects Tools --> Modelica libraries Wolfram SystemModeler SPICE NREL System Advisor Model (SAM) RETScreen Hybrid2 HOMER Energy Note: for the various projects to be given students will make use of 2-3 software listed. Projects will concern circuit analysis, modelling & analysis of PV solar panel under various conditions subsystems, power analysis, grids & specified designs, demand requirements, economic feasibility, etc., etc., etc. Outline --> <1. Solar energy Thermonuclear energy source, Planck’s law and blackbody radiation, the solar spectrum, direct insolation, diffuse insolation. Modelling cloud cover, the projection effect, and computing the optimal tilt angle of a solar panel. <2. Physics of Photovoltaic Cells M. C. Di Piazza and G. Vitale, Photovoltaic Sources, Green Energy and Technology, Springer-Verlag London 2013, pp 19-53 < 3. Cell Construction PC cell architecture and fabrication steps, crystalline substrates, thin film deposition. Review of direct band-gap semiconductors, indirect band-gap semiconductors and their roles or places in PC cell construction. Loss processes in a standard solar cell. (I) First Generation PV: composition and cell structure. Average efficiency. Comparison of techniques (including band theory/engineering) of mono-si and multi-si, and respective efficiency; respective EPBT range and respective CO2-eq/KWh ranges. (II) Second Generation analogy (including band theory/engineering). Heavy metals usage and lack of heavy metals usage. Respective efficiency, respective EPBT range and respective CO2-eq/KWh ranges. (III) Third Generation variety and analogy A. Conibeer, G., Third-Generation Photovoltaics, Materials Today, Volume 10, Issue 11, Nov 2007, pages 42-50 (with emphasis on the physical structures and semiconductor physics): i. Multiple energy level approaches Tandem or multi-colour cells. III-V tandems; bandgap of each cell decreases from the front to the back, giving both spectrum splitting and photon selectivity B. Concentrator systems i. Thin-Film Tandems a-Si tandems Si-nanostructure tandems (where bandgap engineering can be done using either quantum wells or quantum dots of Si sandwiched between layers of a dielectric based on Si compounds. ii. Intermediate-level cells: impurity PV & intermediate band solar iii. Multiple Carrier excitation iv. Modulation of the spectrum: up/down conversion v. Hot Carrier Cells <4. It’s also essential that one definitively establishes the contribution or purpose of each layer component towards real circuitry, relating voltage to current, power, magnetic fields, etc. In other words, how the cell constitution really works towards a circuit. There may be different types of voltages at different points. Will comprehensively treat first, second and third generation cells. <5. Ad hoc PV circuit analysis (I) Computing PV cell power, equivalent circuit models, short- and open-circuit properties, fill factor, and parasitic resistances. (II) Secondly: Khatibi, A., Astaraei, F. R. and Ahmadi, M. H. (2019). Generation and Combination of the Solar Cells: A Current Model Review. Energy Science & Engineering, volume 7, Issue 2,pages 305 – 322 (III) Compared to prior, appropriate analysis and computations to third generation. (IV) Vinod, Kumar, R. and Singh, S. K. (2018). Solar Photovoltaic Modelling and Simulation: As a Renewable Energy Solution, Energy Reports 4, pages 701 - 712 Following appropriate modelling with make use of simulators of students’ choice to generate simulations. Diode equivalent circuit model with the stepwise detailed simulation of a solar PV module. I–V and P–V graphs of solar PV modules provide a broad understanding to researchers, manufacturers and social communities. The simulated result of the PV modules to be verified by the manufacturers’ data sheets of modules and maximum relative error percentages are to be verified for manufacturer values and simulated values. Data sheets applied will be unique to what is observed in article, and will be multiple different types catering for at least second and third generation). Will also like donated (or whatever) different second and third generation solar cell samples, where they will be integrated into a circuit and compared to both simulation results and manufacturers’ data sheets. <6. PV cell external and internal quantum efficiency and computing the spectral response. Appropriate extension for third generation. <7. Theoretical cell efficiency, multijunction devices, the Shockley-Queisser limit. Appropriate extension for third generation if needed to be accounted for. <8. Antireflection coatings, cell passivation, and cell optical properties. Appropriate extension for third generation if needed to be accounted for. <9. PV cells wired in series and parallel, shaded and faulty cell effects, system integration and inverters. <10. Concentrating PV and thermal energy systems <11. PV Systems (I) Grid connection and Stand-alone (II) Components (and possibly system level design and simulation) (III) Maximum Power Point Tracking (MPPT) Overview and logistics Rezk, H. & Eltamaly, A., M., A Comprehensive Comparison of Different MPPT Techniques for Photovoltaic Systems, Solar Energy 112 (2015) Tey, K., S. et al, A differential evolution Based MPPT Method for Photovoltaic Modules under Partial Shading Conditions, International Journal of Photoenergy, Volume 2014, Articled ID 945906, 10 pages Seyedmahmoudian, M. et al. "Simulation and Hardware Implementation of New Maximum Power Point Tracking Technique for Partially Shaded PV System Using Hybrid DEPSO Method". IEEE Transactions on Sustainable Energy. 6(3): 850–862 . Will pursue actual lab development. Prerequisites: Solid State Devices III (a must) 26. Energy Grid Systems and Innovative Power Devices Course treats the development and design of renewable energy systems integrated into standing energy grids. Solar energy power and wind energy power are emphasized. Will also incorporate detail engineering of wind turbines and the necessary power electronics applied; similar counterpart for solar panels in a unit. MPPT and PWM treatment. Much of this course will focus on lab and field development of “micro grids”. Texts in Unison --> Mukind, R. Patel Wind and Solar Power Energy Systems: Design, Analysis and Operation, CRC Press Wind Energy Systems, by Marcia-Sanz and C. H. Houpis, CRC Press The Gas Turbine Handbook, by the National Energy Technology Laboratory, United States Department of Engineering Additional literature (may or may not be the best) --> -Mhiri, N. et al. (2017). A Novel Analog Circuit Design for Maximum Power Point Tracking of Photovoltaic Panels. Advances in Power Electronics Volume 2017, Article ID 9409801, 9 pages -J. Prasanth Ram, N. Rajasekar, Masafumi Miyatake. (2017). Design and overview of Maximum Power Point Tracking Techniques in Wind and Solar Photovoltaic Systems: A Review. Renewable and Sustainable Energy Reviews, Volume 73, Pages 1138-1159 -Li, S., & Xu, L. (2008). PWM Converter Control for Grid Integration of Wind Turbines with Enhanced Power Quality. 2008 34th Annual Conference of IEEE Industrial Electronics, 2218-2224. -Mehdi, A. et al . PWM Converters and Its Application To The Wind-Energy Generation. Energy Procedia 42 ( 2013 ) 523 – 529 -Jaikhang, Wipobh & Chanjira, Puchong & Tunyasrirut, Satean. (2016). Application of Grid Connected for Wind Turbine using PWM Converter Permanent Magnet Synchronous Generator. AIP Conference Proceedings. 1775, 030024 (2016) -M. S. Kumar, K. L. Shenoy and G. B. Praveen, "PWM Techniques to Power Converters of the Wind Energy Conversion System," 2020 IEEE 9th International Conference on Communication Systems and Network Technologies (CSNT), Gwalior, India, 2020, pp. 155-160 Lab Simulation Software Tools --> SPICE SystemModeler/Modeler NOTE: course goes beyond simulation software; will have hands-on design and construction of energy systems to operate and analyse. Main topics --> 1.Wind Energy systems 2.Solar Power Energy systems 3.Gas Turbines for Electricity Production 4.The Grid: Wind, Solar and Transmission Lines Labs/Field Activities --> I. Wind Turbine Design, Simulation & Construction --Some inspiration: James Biggar: How I built a 3 kW Off Grid Wind Turbine – YouTube https://renewablesystemstechnology.com/project-blog/how-i-built-a-3-kw-off-grid-wind-turbine Profiling the environment for characteristic windspeeds & evolving direction Why odd count in blades? Relation between amount of blades, torque, rpm and amps. Profiling blade types concerning low wind speeds and high wind speeds (including structural integrity). Must reside 80 feet to 120 feet? Understanding wind flow upon obstacles. Avoiding turbulent wind from environment (buildings, trees, and high elevation land scapes over wind turbine) The majority of of components to be designed in CAD and possibly structural analysis. Carbon fibre may or may not be suitable for some components. Likely, motor/generator will not be bought. What type of motor/generator will best serve? Characteristing output based on rpm and torque. Yes, also insulation against mositure and precipitation. Blades can be bought or made (that suffices with weight and structural integrity) Note: incorporates RPM sensor, gyro sensor, heat sensors, oscilloscopes, multimeters and DAQs where all data to be time synchronized. Telemetry for data acquisition (RPM sensor, gyro sensor, heat sensors) is likely. Oscilloscopes and multimeters concern data acquisition from monitoring station. --Identifying the components of Wind Turbines and their analytical characteristics, respectively Wind turbine Rotor blades Drive shafts Bearings Main gearbox High speed shaft Generator Housing Tower Rectifier Reviewing circuit analysis Analysis (built vs. bought) Power storage Max capacity resolution Inverter Reviewing circuit analysis Analysis (built and bought) Modelling & simulation of components integrated Design of various controllers as well, wherever warranted Power systems analysis Wind turbine development (based on all prior) II. MPPT and PWM for wind energy systems PWM and MPPT controllers development Reviewing circuit analysis, controller development and simulation Analysis of proprietary modules III. Solar Design, Simulation & Unit implementation (made of numerous cells) Identifying the components and their analytical characteristics, respectively Modelling & simulation of components integrated Design of various controllers as well, wherever warranted Power systems analysis Premature hands-on operations 1. Locate the sun position at any given location and time, interpret sun path diagrams, analyze solar insolation on a collecting surface, and measure solar radiation measurements. 2. Identifaction of high altitude objects being hindrance on solar energy system with shadows based on the Sun’s changle altitude 3. Understand the inner workings of p-n junctions, determine a circuit model of a PV cell, PV module and PV array, measure and interpret I-V curves, understand the impact of temperature and solar insolation on I-V curves, have a broad knowledge on different types PV technologies and their limitations. 4. Determine the operating point of basic electrical loads connected directly to a PV module or array. 5. Design a grid-connected PV system, including the PV array and balance of system (BOS), conduct an economic analysis, and be familiar with the impact of high PV penetration on the utility grid. 6. Have basic knowledge on different types of batteries and their electrical characteristics. 7. Filters? 8. Design a stand-alone PV system by estimating the load, sizing and selecting the batteries, sizing and selecting the PV modules, charge controller and inverter. 9. Have basic knowledge on codes and standards associated with PV Systems. Note: make use of multimeters, oscilloscopes, heat sensors and DAQs wherever feasible among (1) through (7), where all data to be time synchronized. Oscilloscopes and multimeters concern data acquisition from monitoring station. IV. MPPT and PWM for solar energy systems PWM and MPPT controllers Reviewing circuit analysis, controller development and simulation Analysis of proprietary modules V. Design, develop and construct a powerwall to store energy from a solar umit and/or wing turbine. Use of cells types may vary (AA type or even multiple laptop cells). Challenge of designing an integrating foundation and systems together Cells A PCB is present on each side of the stack with wide traces. For monitoring the cells, A “block manager” is installed on each block, communicating wirelessly to a “Pack Supervisor” board that monitors the overall health of the system . Power connector, and a Few headers for the balance connector of a charger Filter? Cooling system integrated. How is it powered? Protection systems Electrical insulation Moisture insulation Fire containment May require a current convertor and/or voltage regulator Means of knowing charge level and a charging shut-off mechanism. How can one measure the charging load, and voltage characteristics in real time? Can such data e collected as well to characterise? Knowledge and skiils from prerequisites will play an influential role. VI. Integrating both wind energy and solar energy into a grid Prior activities (I) through (IV) will have pivotal relevance. MPPT controllers and PWM controllers may be different for wind and solar among each other. VII. Hydrogen generator (electrolysis) Analysis of hydrogen extraction from water (green hydrogen) Some electrochemistry for determination of production rate Expected production (and means to confirm) Will then develop hydrogen extraction system in lab Note: must well designed and developed with components (no crummy contraptions) Will be applying 13 – 40 gallons of water Will make use of solar power for process Development of safe storage for hydrogen Will be designing a hydrogen fuel cell powertrain May have to dig deep with the Modelica libraries or SystemModeler to simulate such a system Modelling & simulation of components integrated Design of various controllers as well, wherever warranted Power systems analysis General components in a hydrgen system Battery (auxiliary): In an electric drive vehicle, the auxiliary battery provides electricity to start the car before the traction battery is engaged and also powers vehicle accessories. Battery pack: This battery stores energy generated from regenerative braking and provides supplemental power to the electric traction motor. DC/DC converter: This device converts higher-voltage DC power from the traction battery pack to the lower-voltage DC power needed to run vehicle accessories and recharge the auxiliary battery. Electric traction motor (FCEV): Using power from the fuel cell and the traction battery pack, this motor drives the vehicle's wheels. Some vehicles use motor generators that perform both the drive and regeneration functions. Fuel cell stack: An assembly of individual membrane electrodes that use hydrogen and oxygen to produce electricity. Fuel filler: A nozzle from a fuel dispenser attaches to the receptacle on the vehicle to fill the tank. Fuel tank (hydrogen): Stores hydrogen gas onboard the vehicle until it's needed by the fuel cell. Power electronics controller (FCEV): This unit manages the flow of electrical energy delivered by the fuel cell and the traction battery, controlling the speed of the electric traction motor and the torque it produces. Filter needed? Thermal system (cooling) - (FCEV): This system maintains a proper operating temperature range of the fuel cell, electric motor, power electronics, and other components. Transmission (electric): The transmission transfers mechanical power from the electric traction motor to drive the wheels. Lab development of hydrogen fuel cell powertrain Validation Voltage, current, Power, RPM, efficiency, energy lifespan, practicality Multimeters, oscilloscopes, heat sensors, DAQs (all time synchronized) VIII. Inverter Generator Analysis use and makeup of inverter generators Modelling, control and simulation of components integrated Design of various controllers as well, wherever warranted Developing an inverter generator that can have fuel substitution From conventional fuel to rubbing alcohol Lab development Validation Voltage, current, Power, RPM, efficiency, energy lifespan, practicality Multimeters, oscilloscopes, heat sensors, DAQs (all time synchronized) IX. Peta-Pico-Voltron (time permitting) Schlatter, S., Illenberger, P. and Rosset, S. (2018). Peta-Pico-Voltron: An Open-Source High Voltage Power Supply, HardwareX, volume 4, e00039 NOTE: not primarily interested in dielectric elastomer actuators. Will pursue other services/uses of interest. Will have to develop the PCB then order its development to ship. Power electronics will not be taken for granted. Prerequisites: Signals & Systems, Modelling & Simulation Lab, Power Systems Analysis II, Modelling & Control of Power Electronics. 27. Power Electronics for Electric Drives Vehicles This course considers the design and control of power converters in electric drive vehicles. The course includes an overview of system architectures and covers system-level dynamic modelling and control using Mathematica/SystemModeler at levels appropriate to determine requirements and validate the performance of switched-mode power converters in the vehicle system. Analysis, modelling and design of switched-mode power converters in electric-drive vehicle systems are then covered, including battery DC-DC converters, battery management electronics, motor drive inverters and battery chargers. This course has no intention of teaching Power Electronics, rather, course is based on recognised knowledge of such from prerequisite: Textbooks & References: M. Ehsani, Y. Gao, A. Emadi, Modern Electric, Hybrid Electric, and Fuel Cell Vehicles: Fundamentals, Theory, and Design, CRC Press Mehrdad Ehsani, Yimin Gao, Sebastien E .Gay, and Ali Emadi, Modern Electric, Hybrid Electric, and Fuel Cell Vehicles, CRC Press A. Fuhs, Hybrid Vehicles: and the Future of Personal Transportation, CRC Press R. W. Erickson, D. Maksimovic, Fundamentals of Power Electronics, Springer Outline --> I. Introduction -Transportation electrification II. Electric Drivetrain System Overview -Architectures of hybrid (HEV), plug-in hybrid (PHEV) and electric vehicles (EV) -Vehicle dynamics, Modelling, Mathematica/SystemModeler/Modelica -System design considerations, rating and sizing of electric drivetrain components III. Analysis, Modelling, Simulations, and Design of Electric Drivetrain Components -Battery systems, battery management electronics -Bidirectional DC-DC converter. Filters -Filters, Inverters and motor drives -Chargers IV. Complete System Modelling and Simulations Prerequisites: Modelling & Simulation Lab; Power Electronics 28. Electrochemical Engineering Course will test theory versus actual experimentation concerning quantity precision (current, voltage, impedance, resistance, etc.) and durations (of mechanisms, reactions, dynamic); involves associated characteristic curves versus findings from experimentation. Topics introduced serve well towards lab experimentation. --Electromagnetism and Circuits Electrical Circuit Theory (concerned with designs only practical to course). --Fundamentals of Electrochemical Systems Electrochemical Reactions (include galvanic and electrolytic) Faraday’s Laws of Electrolysis Thermodynamics of Electrochemical Cells‐Nernst Equation and Pourbaix diagrams Electrochemical potential vs chemical potential Activity coefficient Debye-Huckel Theory and extensions Diffusion and Kinetic Controlled Electrochemical Reactions being the two limiting mechanisms Kinetics: Overpotential Kinetics: Electric double layer (Helmholtz model; Gouy-Chapman model; Stern model) Kinetics: Electrode kinetics model Kinetics: Butler-Volmer equation & simplified BVE Kinetics: Reference electrode Diffusion: Ionic flux (migration, diffusion, convection) Diffusion: Mass transfer boundary layer & limiting current Reiterate: Diffusion and Kinetic Controlled Electrochemical Reactions as the two limiting mechanisms --Components and Materials Note: The first module will resonate aggressively towards real understanding and strategies. Function and Material Selection: Active Electrodes‐ Battery materials Electrocatalysts‐metallic and oxides Electrolytes –solid and liquid Electrode Structures Stack and Ancillary Systems. --Electrochemical Energy Storage Systems Note: Past modules will resonate aggressively towards real understanding and strategies. Capacitors ‐Types – Double Layer and Pseudocapacitive Storage Rechargeable Batteries ‐Principles of operation, Materials, Performance, failure Modes Lithium Ion, Lead Acid, Nickel Metal Hydride, Redox Flow Batteries, Sodium Sulfur, Metal‐Air Batteries Applications and Challenges --Fuel Cells for Electrochemical Energy Generation Note: Past modules will resonate aggressively towards real understanding and strategies. Principles of Operation, Materials, Performance Polymer Electrolyte Membrane, Solid Oxide & Molten Carbonate Fuel Cell, Direct Methanol Fuel Cell, Phosphoric Acid and Alkaline Fuel Cells Fuel Processing Failure Modes, Applications, Challenges and Recent Research --Electrochemical Fuel Production Note: Past modules will resonate aggressively towards real understanding and strategies. Electrolysis of Water to make Hydrogen ‐Alkaline, PEM, Solid Oxide Electrochemical Conversion of Carbon Dioxide to Fuels Fuel Storage and Delivery, Designing Systems for Energy Generation and Storage (2 lectures), Definition of Requirements Mass and Thermal Management Hybridization for Improved performance Exercises in the Design of Electrochemical systems Prerequisites: General Physics II, ODE, Calculus III; at least Junior level. 29. Battery Management & Control This course covers battery modelling, control and diagnostic methodologies associated with battery management systems. Practical examples from automotive and consumer electronics are used throughout the course. Emphasis is placed upon system-level modelling, equivalent circuit models and surrogate models for estimation and on-board parameterization of the electric and thermal Lithium-Ion battery behaviour. Distributed spatiotemporal models of coupled Li concentration, potential, and thermal phenomena are reviewed and then we highlight their analogies with the equivalent circuit models introduced in the first part of the course. We then venture to apply these models in State of Charge (SOC), State of Power (SOP), and State of Health (SOH) estimation using Kalman filtering and recursive least-squares estimation to augment classical coulomb counting techniques. Cell balancing in a pack is then discussed and practiced in a realistic simulation. Battery cooling, thermal evolution and run-away behaviour will be the last course section. Estimation of battery core temperature will finally be developed that will guide thermal management and used for an improved SOP and SOH. Mathematica/SystemModeler and Modelica packages will be used in course instruction and projects. Textbook: pending Outline --> Module 1: Equivalent Circuit Models Overview Li Chemistry Voltage, Power, and the Electrical point of view Parameterization of Equivalent Circuit Models Constant Current Constant Voltage (CCCV) Module 2: Electrochemical Control -Oriented Models Butlet -Volmer, Kinetics Diffusion (electrolyte & solid) Numerical Approximations Electrode -Averaged Model Single Particle Model Module 3: Battery Controls State of Charge (SOC) Estimation Observability, Estimation, Kalman filters State of Power (SOP) Estimation State of Health (SOH) Estimation (optional) Module 4: Stack Management Cell thermal Dynamics, thermal Run -Away Pack thermal dynamics Monitor, Management Cell Balancing: Passive & Active Labs (determine best bundle order) --> Notes: development and notes from lecturing and assignments will serve as analytical foundation for labs. 1. Circuit building and simulation throughout 2. Numerical Methods throughout 3. Cs(X,r,t) versus r with Cse(X,r,t) concerning solid-electrolyte interface 4. Estimation and filtering Extended Kalman filter, Sigma-point Kalman filter Articles to analyses and develop: (i) Papazoglou, A., et al, Nonlinear Filtering Techniques Comparison for Battery State Estimation, Journal of Sustainable Development of Energy, Water and Environment Systems, 2(3), pp 259-269, 2014 (ii) Chun, C., Y. et al, A State-of-Charge and Capacity Estimation Algorithm for Lithium-ion Battery Pack Utilizing Filtered Terminal Voltage, EVS28 International Electric Vehicle Symposium and Exhibition, KINTEX, Korea, 2015 (iii) It’s only beneficial that such two be compared to tools in Mathematica/SystemModeler 5. Model a chemical electrical system. Model building to analyse how a battery responds to thermal conditions, as well as to charge and discharge cycles in the larger system. Combine Component- and Block-Based Modelling The battery is constructed with custom electrical components. Within components, the battery state is modelled using blocks. Explore Temperature Impact on Battery Cell Lifetime Connect SystemModeler to Mathematica to analyse different battery characteristics. The batteries are discharged in intervals of X seconds and then rested for Y seconds. Following, will pursue development of experimentation from the following literature in chapter 3 (Modelling of Battery Thermal Behaviour and Performance): Samadani, E. (2015). Modelling of Lithium-ion Battery Performance and Thermal Behaviour in Electrified Vehicles. PhD Thesis. University of Waterloo: https://core.ac.uk/download/pdf/144148204.pdf 6. BMS competence To model and build and simulate in systemModeler the various methodologies Z. B. Omariba, L. Zhang and D. Sun, (2019), "Review of Battery Cell Balancing Methodologies for Optimizing Battery Pack Performance in Electric Vehicles," in IEEE Access, vol. 7, pp. 129335-129352 Battery management systems balancing the state of charge of individual cells and ensuring the proper charging, discharging, and safe operation of rechargeable battery packs. 7. Developing a model of a three-cell battery pack (at least) that is charged using a constant-current constant-voltage (CCCV) profile, and simultaneously equalizes the state of charge of the cells using on-charge passive balancing. The balancing logic to be designed in, and it to be ready for automatic C-code generation for hardware implementation. 8. Design and simulation of battery systems Preliminary specifications to be drawn upwith expected theoretical characteristics and performance. Prior lab knowledge and skills expected. Applying the “SmartCooling” library to model an electric vehicle battery stack with a cooling circuit. Design and simulation of battery systems Rapidly develop complex cooling systems by using detailed library components. Analyse the complete system behavior and develop cooling strategies fulfilling system design criteria Demonstrating the usability of an on-off hysteresis control for the cooling fan to keep the maximum cell temperature between given limits. To be ready for automatic C-code generation for hardware implementation if feasible. 9. An accurate battery pack model is essential for hardware in-the-loop testing of Battery Management System (BMS). Scaling battery models from cell-level to pack-level and the subsequent preparation of the battery pack model for real-time simulation. Mathematica/SystemModeler tools create a battery pack model of arbitrary size and connectivity. The function partitions the model for concurrent execution on multicore real-time computers. The flexibility of scripting the creation of pack models allows the user to efficiently test multiple configurations for optimal utilization of multicore targets, including load balance, data transfer latencies, and scheduler overhead. Concerns: Automatically assemble a battery pack model from cell models Trade-off model partition methods for real-time simulation Estimate processor load for each partition using a PC Deploy battery pack model to HIL system for BMS testing 10. Hands-on development of a physical BMS for a constructed battery pack, and comparing performance/data to commercial model(s). Prior lab knowledge and skills will be put to test. Yes, use of actual hardware and software for BMS developlment. Assisiting articles: Kalmakov, V., Andreev, A., & Salimonenko, G. (2016). Development of Formula Student Electric Car Battery Design Procedure. Procedia Engineering, 150, 1391–1395. Tarle, N., Kulkarni, R., Desale, N., & Pawar, V. (2019). Design of a Battery Management System for Formula Student Electric Race Vehicle. 2019 5th International Conference On Computing, Communication, Control And Automation (ICCUBEA), 1–6. Baťa, M., & Mikle, D. (2019). Battery Management System Hardware Design for a Student Electric Racing Car. IFAC PapersOnLine, 52(27), 74–79 Prerequisites: Calculus III, Systems Modelling II, Signals & Systems, Modelling & Simulation Lab, Engineering Thermodynamics, Electrochemical Engineering 30. Computer Networks for Engineers Expertise in electromagnetics and networks would be quite limited without any knowledge or skills in networks and communications. Course presents the fundamental principles of computer networks and data communication. Most focus concerns current technologies and architectures for establishing direct link and packet-switched networks, sharing access to a common communication medium, internetworking and routing, end-to-end flow control, congestion control and recourse allocation, and network security. Typical Text: Peterson, L. L. and Davie, B. S. (2011). Computer Networks, A Systems Approach. Morgan Kaufmann Publishers. References: Bertsekas, D. and Gallager, R. Data Networks, Prentice Hall. Tanenbaum, A. S. nd Wetherall, D. Computer Networks. Prentice Hall Kurose, J. and Ross, K. Computer Networking, A Top-down Approach, Addison Wesley. This course will take a “hands-on” approach to develop purpose and worth in what you’re doing towards successful completion. Such a philosophy is economic in the sense that it will lead you to apply and practice your programming skills in C; you’re getting your money’s worth. You will become relevant in the field of communications. Assessment --> Homework assignments 15 % Programming Labs 20 % Midterm 20 % Group Project 20 % Final 25 % Course Outline --> Introduction to Computer Networks Applications of Computer Networks Basic Network Architectures The OSI Layering Model Network Performance Metrics Direct-Link Networks Hardware Building blocks Types of Network Links Bit Encoding Framing Error detection ARQ: Retransmission Mechanisms Medium Access The Channel Allocation Problem Multiple Access Protocols Ethernet, Wireless LAN, Bluetooth, Wi-Fi and WiMAX protocol standards Internetworking Simple internetworking Routing Algorithms Internet Routing, Autonomous Systems Multicast Routing End-to-End Protocols Elementary Transport Protocols A reliable transport service (TCP) Flow Control Mechanics Congestion Control and Resource Allocation The Resource allocation Problem Classification of Resource Allocation Methods and Evaluation Metrics TCP Congestion Control Congestion Avoidance Mechanisms Applications Electronic Mail The world Wide Web The Domain Name System Web Services Network Security Cryptography – Simple Cryptosystems Symmetric Key Cryptography Hash Functions Public Key Cryptography Authentication Protocols Transport Layer and IP Security Prerequisite: Practical Programming in C for Electrical Engineering I & II; also at least Calculus II 31. Analog & Digital Communications Systems Check Computational Finance post Prerequisite: Signals & Systems, Probability & Statistics B 32. Modern Digital Communications Check Computational Finance post Prerequisites: Analogue & Digital Communications Systems 33. Wireless Networks Check Computational Finance post Prerequisites: Signal & Systems; Probability & Statistics B; Analog & Digital Communications Systems; Modern Digital Communications; Computer Networks for Engineers 34. Silicon Integrated Photonics Check Computational Finance post Prerequisites: Signals & Systems, Electromagnetics II; Modern Physics; Solid State Devices III. 35. Silicon Photonics Design Lab Check Computational Finance post 36. Semiconductor Quantum Structures & Photonic Devices Check Computational Finance post Prerequisites: Modern Physics, Solid State Devices III, Optoelectronics, Quantum Mechanics I 37. Image & Video Processing Check Computational Finance post Prerequisites: Signal & Systems, C++ Programming II, Image & Audio Processing, Mathematical Statistics 38. Electrification of Transportation I Check Computational Finance post Prerequisites: Practical Programming in C for Engineering I & II, Machine Design I & II, Systems Modelling I & II, Mechatronics I & II, Modelling & Simulation Lab, Electric drives I & II, Power Electronics, Modelling & Control of Power Electronics, Power Electronics for Electric Drive Vehicles 39. Electrification of Transportation II Check Computational Finance post Prerequisite: Electrification of Transportation I 40. Satellite Communications Check Computational Finance post Prerequisites: Signals & Systems, Analogue & Digital Communications Systems; Modern Digital Communications; Modelling & Simulation Lab; Mathematical Statistics, Data Structures II 41. Hands-on Satellite Design Check Computational Finance post Prerequisites: Practical Programming in C for Engineering I & II, Satellite Communications 42. Electromagnetic Scattering from Random Media & Rough Surfaces Check Computational Finance post Prerequisites: Numerical Analysis; Partial Differential Equations (CHECK Computational Finance); Electromagnetics I & II; Electromagnetic Waves & Antennas; Mathematical Statistics 43. Electric Power Distribution Systems I: Prototypical text: Electric Power Distribution System Engineering, Turan Gonen, CRC Press, 2008 An 18 weeks in schedule. Course will involve considerable immersion into software activity (listed in goody bag post). Assignments will be constituted by handwritten solutions to assigned problems, Mathematica, SystemModeler + Modelica AND other tools also to be available for computations & simulations. Rest of grade to be constituted by midterm and final exam. There will be designated time towards quality implementation of power grid software. Class attendance is mandatory. Tools --> Engineering calculator Mathematica SystemModeler + Modelica Packages MATPOWER + GNU/Octave PSAT: Power System Analysis Toolbox + GNU/Octave NASA NPSS Electrical Power Systems Analysis Toolbox Grading --> Homework Labs 4 Exams Course Outline --> Distribution System Planning and Automation Smart Grid- Advanced Power Electronic Controllers in Distribution Systems (3 classes) Load Characteristics Application of Distribution Transformers (6 classes) Design of Subtransmission Lines and Distribution Substations (4 classes) Design Considerations of Primary Systems (2 classes) Design Considerations of Secondary Systems Voltage Drop and Power Loss Calculations Application of Capacitors to Distribution Systems (2 classes) Distribution System Voltage Regulation (3 classes) Distribution System Protection (6 classes) Distribution System Reliability Electric Power Quality Distributed Generation Prerequisites: Power Systems Analysis II, Lower Senior level 44. Electric Power distribution Systems II: A sequential regimen is crucial to towards any retention, competency, efficiency and professionalism. Course is an intensified version of its prerequisite. Assignments, Labs and Exams will be more intensified, and likely students may have to design and exhibit a project catering towards a rural ambiance or higher. Prerequisite: Electric Power distribution Systems I ***Descriptions of particular CE courses-- 1. Practical Programming in C for Engineering I Fundamentals of C, complexity and efficiency analysis, numerical precision and representations, intro to data structures, structured program design, application to solving engineering problems. Course will emphasize practicality towards engineering and physics interests. Course mainly serves engineering objects, NOT software engineering. By the end of this course, the student will be able to: i. Conceptualize engineering problems as computational problems ii. Handle the C programming language (syntax, IDE) iii. Understand fundamental software notation and coding principles iv. Design computer programs using recursive programming techniques v. Design computer programs using modular programming vi. Understand the basics of data structures vii. Implement algorithms viii. Perform dynamic memory management ix. Perform code debugging x. Pursue Automation with C libraries Broad Lecturing --> Rostamian, R. (2014). Programming Projects in C for Students of Engineering, Science, and Mathematics. SIAM Hanly, J. R. and Koffmann, E. B. (2001). C Programme Design for Engineers. Pearson Programming microcontrollers in C texts --> VanSickle, T. (2001). Programming Microcontrollers in C. Elsevier Science Ward, H. H. (2019). C Programming for the PIC Microcontroller. Apress NOTE: process abstraction and flowchart abstraction will accompany programming development. NOTE: at determined periods throughout progression microcontroller texts will be incorporated towards common tasks. Process abstraction and flowchart abstraction will accompany programming development. Assessment --> Homework Quizzes Labs Projects Advise --> Before jumping into actual programming it’s important to know what you want, what you are using to get there, and how to apply. Hence, conceptions, scheming and logistics should be well established before you get there. If there’s errors it’s often easier for one to “map” or locate them due to their pre-development; if you don’t have an affinity nor innate ability, it’s okay. Labs --> Aside from building and reinforcing lectures, to encourage a welcoming environment much emphasis will be focused on realistic and highly applicable problems in engineering and physics. To create sustainability and value, one must be immersed in activities that are valuable. Projects will involve the following areas: Introductory numerical methods algorithms Algorithm Building Simulation Programming Microcontroller Applications Data Acquisition and Modelling Physical Sciences Lab Experiments Use of C libraries for complex goals Projects --> Projects will be highly based on lectures and labs. However, they will be challenges given to grow on as a means not to solely expect memorizing code. Independence is quite important to becoming skillful. Students should not plainly copy code of others or plainly copy from sources. Students need to understand what they’re doing to recognise their potential and for any credible measure of success. Students are expected to develop a habit of incorporating commentary, unless there’s security or privacy issues. Outline--> I. Introduction to computer systems Engineering problems as computational problems Overview of computer systems Software design II. Introduction to C Code build process (editing, compiling, linking, executing) Elements of a C program, pre-processor directives, statements and expressions, functions, coding formatting style Simple data types, constants and variables, conversion between different data types, binary arithmetic representations The IDE environment III. Program flow control Conditions, relational operators, logical operators, precedence rules, selection structures Repetition and loop statements, while statements, for statements, increment and decrement operators, loop termination, nested loops, do-while statements Debugging Quadrature and numerical differentiation Engineering applications, IV. Modular programming User functions, library functions, function declaration and definition, function calls, pass by value, scope rules, programs with multiple functions Pointers and addresses, pass by reference, pointer arithmetic File input/output V. Simple data structures Arrays, declaration and initialization, multidimensional arrays, searching and sorting arrays, pointers and arrays String arrays, string library functions, substrings, concatenation, strings vs. characters Structures, structures and functions, arrays of structures, dynamic data structures Prerequisite: Calculus for Science and Engineering I 2. Practical Programming in C for Engineering II Retention, confidence, competency, sustainability, advancing skills, professionalism Prerequisite: Practical Programming in C for Engineering I 3. Digital Design I: NOTE: TAKE THIS COURSE AT A TIME WHEN OTHER COURSES THAT REQUIRE IT ARE CLOSELY AHEAD SO IT CAN REMAIN FRESH. Introductory course in digital logic and its specification and simulation. Boolean algebra, combinatorial circuits including arithmetic circuits and regular structures, sequential circuits including finite-state-machines, use of programmable logic devices. Simulation and high-level specification techniques are emphasized. Course Goals --> -Understanding of digital logic at the gate and switch level including both combinational and sequential logic elements. -Understanding of the clocking methodologies necessary to manage the flow of information and preservation of circuit state. -An appreciation for the specification methods used in designing digital logic and the basics of the compilation process that transforms these specifications into logic networks. -Facility with a complete set of tools for digital logic design with programmable logic devices as the implementation technology and the realization of medium-sized state machine controller and data paths using PLDs and discrete logic. -To begin to appreciate the difference between hardware and software implementations of a function and the advantages and disadvantages of each. Labs --> Simulations and hands-on laboratory that meets once a week. Each lab will accommodate multiple topics. Labs provide students the opportunity to put what they learn in lecture to practice using digital logic prototyping kits and modern computer-aided design tools. Laboratory assignments will be closely aligned to lecture and homework topics. For the most part, it will be possible to complete most physical prototyping tasks within the allotted time in the lab. Course Outline--> Introduction to modern digital logic design Combinational logic Switch logic and basic gates Boolean algebra Two-level logic Regular logic structures Multi-level networks and transformations Programmable logic devices Time response Case studies Sequential logic Networks with feedback Basic latches and flip-flops Timing methodologies Registers and counters Programmable logic devices Case studies Finite state machine design Concepts of FSMs Basic design approach Specification methods State minimization State encoding FSM partitioning Implementation of FSMs Programmable logic devices Case studies Elements of computers Arithmetic circuits Arithmetic and logic units Register and bus structures Controllers/Sequencers Microprogramming Computer-aided design tools for logic design Schematic entry State diagram entry Hardware description language entry Compilation to logic networks Simulation Mapping to programmable logic devices Practical topics Non-gate logic Asynchronous inputs and metastability Memories: RAM and ROM Implementation technologies Postcondition Abilities --> Map a problem statement to a digital logic solution including combinational and sequential (FSM) logic Map the implementation to programmable logic devices Optimise the implementation Verify the implementation Postcondition Skills --> Use of a hardware description language Use of synthesis tools to generate and map logic to programmable logic devices Simulation of digital logic 4. Digital Design II: NOTE: TAKE THIS COURSE AT A TIME WHEN OTHER COURSES THAT REQUIRE IT ARE CLOSELY AHEAD SO IT CAN REMAIN FRESH. Advanced techniques in the design of digital systems. Hardware description languages, combinational and sequential logic synthesis and optimization methods, partitioning, mapping to regular structures. Emphasis on reconfigurable logic as an implementation medium. Memory system design. Digital communication including serial/parallel and synchronous/asynchronous methods. Course Goals --> -To learn how to design digital systems, from specification and simulation to construction and debugging. -To learn techniques and tools for programmable logic design -To learn how to use modern laboratory test equipment, including logic analysers and oscilloscopes To understand the limitations and difficulties in modern digital design, including wiring constraints, high-speed, etc. -To design, construct, test, and debug a moderate-scale digital circuit. Labs --> Simulations and hands-on laboratory that meets once a week. Each lab will accommodate multiple topics. Labs provide students the opportunity to put what they learn in lecture to practice using digital logic prototyping kits and modern computer-aided design tools. Laboratory assignments will be closely aligned to lecture and homework topics. For the most part, it will be possible to complete most physical prototyping tasks within the allotted time in the lab. Course Syllabus --> I. Review of basic digital-logic design Combinational logic Structured logic implementation Sequential logic Finite-state machines II. Overview of digital technology Logic families Reading and understanding data books Interfacing Fixed-function devices TTL/CMOS glue logic RAM/ROM Programmable devices PROMs PALs and PLDs FPGAs Integrated circuits III. Electrical realities Resistance, capacitance and inductance Time constants Decoupling and ground Power dissipation and drops Wire delays Fanout and loading Ringing, reflections, and terminations Clock IV. Computer-aided design Hardware description languages (HDLs, esp. Verilog) Logic compilation Two-level and multi-level logic synthesis Technology-independent optimization Technology mapping Sequential-logic synthesis Tools for mapping to PLDs and FPGAs V. Laboratory realities Logic analyser and oscilloscope basics Repetitive versus single-shot triggering Timing, state, capture, bandwidth Glitches and transient events Wire, coax, probing VI. System-level components Static, dynamic, and non-volatile memories (RAM, ROM, PROM, EPROM, EEPROM) Memory controllers and timing Digital communication Serial and parallel protocols Synchronous vs. asynchronous data communication Busses Arbitration schemes VII. Technology MOSFETs FPGAs Integrated circuits Circuit boards High-speed circuits; controlling impedances 5. Assembly Language In this class, we will discuss how computers are organized and how primitive building blocks can be used to create a computing system. We will inspect a subset of the X86 instruction-set architecture and we will investigate how to program at the assembler level. We will introduce students to modern microprocessor memory hierarchy and other aspects of contemporary computing systems. Student participation and interest can partially influence the topics discussed and the assignments given, so feel free to suggest items of interest to you. The point of this course is to build up awareness of computer organization so the interested student is ready to pursue more advanced computer-architecture topics and to be a much better user and programmer of computers. There will be two in-class (70 to 80 minute) examinations. There will be a number of quizzes. There will be a final (150 minute) exam. On some weeks, homework will be assigned and due nine days later by class time; no homework will be assigned the last week of class, but there may be a homework due the last week of class. There will be approximately ten homework assignments given during the semester. Note: the laboratory assignments are important. Once a laboratory turn-in date has arrived, material concerning that laboratory may appear on an exam. Naturally, hints and some possible logistics will be given for labs. Labs will have meaningful purpose where abstracts and logistics will be precursors to actual programming and implementation. Tests and quizzes are open-book, open-notes affairs -- however, no electronic devices (laptops, cell phones, tablets, PDAs, calculators) of any kind are allowed during test and quiz events. As such, you may wish to have a physical copy of any materials that you believe will be helpful during quizzes and exams. Remember, cell phones are not allowed during exams; during exams the remaining time will be periodically announced. This class will be taught in an "inverted" style. That is, we will concentrate class time on examples, working through code, understanding architectural features by discussing examples, writing a simple ISA-level simulator, and modifying a block-level model of our ISA-level computer. There will be short lectures to introduce various topics, but primarily, we will use class time for problem solving and exchanging information. We will program in C. For examples and help with C-language use, you will find that there are many, many web pages and general literature devoted to C language programming. Why C, or its extension, C++? It is the language that is used to implement many systems, such as FreeBSD, Linux, MacOS, Windows, as well as many user tools (e.g., grep, ed, sed, emacs,...). Student will be introduced to C-language capabilities, such as referencing x86 processor-specific counters, that lie outside of the C-language. In some cases, it may be helpful to reference documentation about the x86 architecture. There will be reference material in a documents directory. In some cases, students may be asked to read small sections from these documents. Note that these documents are large -- these documents are indicative of the complexity of the x86 architecture. Other companies that develop and market x86 processors must fully comprehend the information contained in these documents; unfortunately, the information contained in these documents is insufficient to develop a competitive x86 processor implementation. There are many undocumented features (e.g., caching read-ahead strategies) that are necessary to make a x86 processor perform well on a litany of common benchmarks, and for a x86 processor to be competitive, it will need to contain these features. Tablet computes have a similar architecture, and although quite valid for study, we will not explore the memory hierarchy of tablet-based computers unless they contain a x86 processor. For students, a project must be proposed and approved by the instructor. The content of this kind of project is pretty flexible -- so long as it has to do with architecture. For instance, I am interested in the development of an ISA model of IBM's Harvest computer, which was a extension of IBM's Stretch computer. Another possible specification project might involve some older microprocessor, e.g., the Motorola 68030 or the National Semiconductor NS32032. Other independent study projects are possible; please discuss these with the instructor. For students there will be 2-3 projects. The value you get from this class will be directly related to the effort you (the student) put forward. This class will require that you learn to work on your own, and this class may be less structured than many of the classes you have taken. In this class, there will be some lectures, but only of a short duration. The remainder of class time will be used to directly address problems and seek their solutions. If you have a laptop computer, it will be very helpful for you to bring it to class -- this is not a requirement, but it's easier for students to be able to individually access information as required, and when we are discussing programming issues it may be helpful for you to immediately try it yourself. Please come to class prepared to work; we will regularly stop for a few minutes to make sure that everyone that has a chance to consolidate their thinking and to help students overcome problems with their understanding or with problems with the in-class presentations. Course Assessment: 10 Homework 3-4 Quizzes 2 in-class exams Labs 2-3 Projects Final The two lowest homework grades will be dropped in the computation of the final homework grade; homework is not accepted late. The lowest quiz grade will be dropped, and pop quizzes must be taken when given. Projects may be turned in one week late, but no later than the last day of class; late project submissions suffer a 20% reduction of the grade given for the content of the project. Examinations and quizzes must be taken at the scheduled times. Course Schedule --> Course Introduction C and Assembler programming, Laboratory 0 assigned X86 Memory System, Memory Mountain Development Tools, Subroutine Calling Conventions Memory Hierarchy, Pointer Chasing Laboratory 1 assigned, Laboratory 0 due X86 Memory Management System DRAM Memory Technology, caches Simple Microprocessor (SM) Presentation Writing code for SM, Exam review In-class Exam Review of SM, Laboratory 1 due SM Implementation Architecture, Laboratory 2 assigned Pipe-lined Implementation Techniques Combinational Logic Sequential Logic Logic Verification Further Sequential Logic Co-Simulation Exam Review, Laboratory 2 due In-class Exam Sequential Logic, continued, Pipelining Pipelining the SM, Laboratory 3 assigned Floating-Point Architecture Cache Design and Implementation Approaches High-Performance Programming, Performance-Measurement Mechanisms Out-of-Order Implementation Techniques Laboratory 3 due Course Summary Possible/Optional Review Session Final Exam, 2:00 pm -- 5:00 pm Prerequisites: Practical Programming in C for Engineering I & II 6. Embedded Systems & Control I: Check Computational Finance post Prerequisites: Practical Programming in C for Engineering II, Assembly Language I 7. Embedded Systems & Control II: Check Computational Finance post Prerequisites: Embedded Systems & Control I 8. Microprocessors I Check Computational Finance post Prerequisites: Digital Design II, Solid State Devices I, Assembly Language II 9. Microprocessors II (check computational finance post) Prerequisite: Microprocessors I 10. Microprocessor Lab I (check computational finance post) Prerequisite: Microprocessors I 11. Microprocessor Lab II (check computational finance post) Prerequisites: Microprocessors I, Microprocessor I Lab, Microprocessors II. Assembly Language I or Assembly Language II 12. Digital Systems Design (check computational finance post) Prerequisites: Senior Standing, Department Permission, Instructor Permission 13. CMOS VLSI Design (check computational finance post) Prerequisite: Solid State Devices III, Practical Programming in C for Engineering I & II, Digital Design I & II 14. VLSI Testing & Validation (check computational finance post) Prerequisite: CMOS VLSI Design 15. Analog Circuit Design I (check computational finance post) Prerequisites: Solid State Devices III, CMOS VLSI Design 16. Analog Circuit Design II (check computational finance post) Prerequisite: Analog Circuit Design I 17. Silicon Integrated Photonics (check computational finance post) Prerequisites: Signals & Systems, Electromagnetics II; Modern Physics; Solid State Devices III 18. Mixed Signal Circuits (check computational finance post) Prerequisites: Digital Design I & II; Solid State Device I-III, CMOS VLSI Design; VLSI Testing & Validation; Analog Circuit Design I & II 19. Sensor Instrumentation Homework assignments: 15% Labs: 55% Final Project: 20% Attendance: 10% NOTE: technical papers and white papers from Texas Instruments, Analog Devices and Arduino can be invaluable. Essential issues and objectives are not necessary written in a specified order where issues can be extensively implemented or applied throughout like Verilog and high level language: A. Instrumentation systems for barometric pressure, hydraulic pressure, temperature, speed, rpm, variable voltage, current, resistance, vibrations. B. Ability to evaluate the quality and safety of electronic products including reliability, physical testing, electrical safety and electromagnetic compatibility. C Ability to design systems schemes for sensing with appropriate devices and how they interface/interact with each other. Know how to independently analyse the dynamic system and select the appropriate sensors. Have knowledge of how to read sensor specifications and understand their performance and limitations. Know how to interface analog and digital sensors to digital computer systems. Implement and operate high performance laboratory electronic instrumentation, with emphasis on error analysis, calibration and virtual control. Advanced instrumentation systems architectures, and virtual instrumentation. Fault-tolerant design. Understand basic ideas of physical redundancy and analytic redundancy. D. Ability to integrate instrumentation systems with mobile devices, programmable boards, laptops, etc. Fault-tolerant design. Understand basic ideas of physical redundancy and analytic redundancy. E. Ability to deploy distributed instrumentation systems and sensor networks in various environments (aquatic, fluid, thermal, electrical, mechanical, electromechanical). Fault-tolerant design. Understand basic ideas of physical redundancy and analytic redundancy. F. Managing the acquisition, structuring, analysis and display of data and information in the chosen area of specialisation and critically assessing the results obtained. G. IEEE 1451 Smart sensor standard implementation (or possibly higher). As well: http://www.theremino.com/en/hardware/inputs/sensors H. Students will learn to use Verilog, high level language through lab exercises and assignments focused on understanding sensors, FPGA board, programmable boards, modules, etc. through lab exercises focused on understanding sensors. Use of high level language to communicate with various instruments, such as power supplies, multimeters and oscilloscopes. Developing test benches in a high level language for automatic data acquisition from computer controlled instruments. Design Verilog and high level code to send and receive high bandwidth data between FPGA and PC via USB 3.0 control; heuristic development before actual coding, testing and implementation. Investigate the fundamental limitations of data acquisition systems. I. Apply signal sampling and Kalman Filtering when practical and most beneficial. Will also require oscilloscopes, multimeters, data sheets, schematics, layouts, etc., etc. Labs--> (i) Students will become familiar with the working environment for Verilog and the FPGA board. They will write example codes to send data to and from the FPGA board and a PC using USB 2.0 or USB 3.0 data interface. The software code on the PC will be written in a high-level language. The FPGA code will be written in Verilog. Looking for a data acquisition card (that’s much cheaper than the OpalKelly XEM 6002), but function’s just as well with similar adaptable features. (ii) A (Pmod or other) ultrasonic sensor will be used for the lab. Students will write UART protocol on the FPGA to send data from the sensor to the PC via USB 2.0 or USB 3.0 interface. Once the data is received, a gesture recognition-controlled game will be implemented in a high-level language. (iii) Students will start putting together the building blocks to obtain an image from a custom analog CMOS sensor and transfer the data to the PC to be displayed. Beginning by understanding the light to electron conversion by controlling a single pixel from the imaging sensor. The different operating cycles of the pixel will be covered: reset, integration and sampling the data. Students will write a state machine in HDL to control the imaging sensor and use oscilloscope to ensure the proper operation of the sensor. (iv) Design a state machine in the FPGA to control all digital circuits in the imaging sensor, scan an image and correctly sample the analog data from the image sensor. Data aliasing, filtering and amplification to be covered in terms of acquiring the analog signal from the imaging sensor and correctly digitizing it. (v) Design the necessary interface in Mathematica/C/C++ to receive data from the FPGA to the PC via USB 3.0 and display data from the (CMOS) imaging sensor on the screen. USB 3.0 data transmission will be developed, debugged and tested. Raw data from the sensor will be also saved for analysis. (vi) Data collection from the (CMOS) image sensor using computer-controlled instruments will be covered. For example, pixel’s output voltage as a function of light intensity will be measured. A computer-controlled power supply will control the Led brightness and oscilloscope will capture the pixel’s output. Instrument synchronization will be covered. (vii) Students will evaluate the performance of the imaging sensor, such as SNR, FPN, dynamic range, using computer-controlled instruments via a high-level language. Note: for students that will not be able to complete the necessary state machines to control the imaging sensor module, a Verilog and high-level code will be provided to assist them with the data collection; this is the one and only exception (only this specific lab) where any code is given to students in course. (viii) Integrate magnetic (or resistive or optical) encoders with a motor and the FPGA environment. More information about the magnetic encoder can be found here. Design and test HDL code to control the motor and evaluate and encoder precision. Combine the ultrasound sensor with a motor to create a 3-D map of the environment. (ix) Test the precession of a compass sensor module. Integrate the compass module with the motor/encoder system and test its accuracy and precision. Note: there are economic sensors that account for three types of sensing (gyroscope, accelerometer and compass). (x) Pmod (or other) sensor module containing temperature, humidity, proximity, UV and light sensor, like the Silicon Labs Sensor-PMD board (Sensor PMOD Board). (xi) Capacitive sensor will be used for the lab. An example, the PmodCDC1. Students will test the sensitivity of the capacitive sensor using variety of computer-controlled experiments. (xii) Temperature sensors and I2C interface protocol. (xiii) Pressure sensors and USB interface protocol. (xiv). Automatic Room Light Controller using IR sensors This project employs a mechanism with room lights that switch on when a person enters the room and switch off as the person leaves the room. In addition, it also displays the number of persons entering or leaving by means of LCD. With this automatic operation, electrical energy can be saved. In this system, two sets of IR LED and IR sensors are connected to the microcontroller to detect the persons exiting and entering the room. The microcontroller is programmed in such a way that by receiving the signals entering from the IR sensor, it turns the lamp with a relay mechanism and also increments the counter. Similarly, for the exit sensor signal, it turns off the lamp and decrements the count which is also displayed in the display. (xv). Green house intelligent control system https://microcontrollerslab.com/green-house-intelligent-control-system/ Will like to extend lab further, say, preservation of some particular chemical, compound or whatever substance based on environmental specifications. Will like to assess performance and so forth. Prerequisites: Embedded Systems I & II 20. Programmable Logic Controllers Fundamental concepts, methods of analysis, and design of programmable logic controllers and systems, and programming. Prototypical textbook examples: (Primary) TBA (Supporting) Groover, M. P., Automation, Production Systems, and Computer-Integrated Manufacturing, Pearson Education. Note: generally, we are NOT interested in being subjugated to the Allen-Bradley Small Logic Controller (SLC 500) series of PLCs. There are very affordable PLCs in the market. There are Open Source PLCs as well. Engineering is not about brand, rather doing what you can optimally and responsibly with what you have. PLC simulators and software spectrum --> --Do-More Designer software --OpenPLC Editor to set up a programme with variables and conditions where complexity depends on the project with the associated hardware, amount of different types of sensors, signalling, actuation and operation components. Will be applied to various devices for desired tasks. T. R. Alves, M. Buratto, F. M. de Souza and T. V. Rodrigues, "OpenPLC: An Open Source Alternative to Automation," IEEE Global Humanitarian Technology Conference (GHTC 2014), San Jose, CA, 2014, pp. 585-589. --OPCClassic Modelica Library For professionalism students will have upper moderate sessions about connecting systems with open platform communication (OPC). Connecting an operations plant model and a real-world model PLC in SystemModeler to communicate with each other through OPC. The OPCClassic library is used to test a new design of a PLC before it is connected to the real process plant. Data from the process plant model is written from SystemModeler to the OPC server, and is then read by the external PLC. The PLC computes a control signal that is written back to the server, from where the process plant in SystemModeler/Modelica can access it. Necessarily it’s critical that students are well acquainted with design and configuration software that’s highly applied in integrated architecture. Assistance from constituents of utilities (WASA, T&TEC, TSTT, etc., or corresponding entities) concerning the OPCClassic Modelica Library to have on-site development, observation and analysis with PLCs residing in inventory storage and in function (operational specs and appropriate types of system integration). Includes components of PLC modules and network topology. Demonstrations of operations and protocols. As well Modelica with OpenModelica is a possibility Lava, A. et al (2008). Modelica Library for Logic Control Systems written in the FBD Language. The Modelica Association. Arduino, Raspberry Pi and C environments experience --> --CONTROLLINO --IONO ARDUINO --Raspberry PI PLC --Mitsubishi Electric C Language Controller NOTE: experience from Embedded Systems courses will not go to waste. Students will be expected to have competence with independent installment and loop coding (all part of your assessment). NOTE: there will be concise comprehension of the differentiation between ladder programming development, versus applying your embedded systems skills for hardware PLC environments. Concerns relevance and meaningfulness w.r.t. to PLC system integration. SPECIFIC OBJECTIVES --> I. One vital concern is to develop a strong understanding of the typical components that constitutes a PLC module. Design a PLC system, component, or process to meet a set of specifications. II. Design, conduct, and interpret a validation test of a PLC system. III. Students gain an understanding of the role of PLCs in safety critical systems. IV. Demonstrate effective communication through writing proficiency at the level expected for a engineering student and the use of engineering graphics. V. Identify the benefits of trade journals and web-based PLC resources of information for life-long learning. VI. Recognize the need to use modern tools to assist solving problems. VII. Identify and apply appropriate modern technologies to an assigned task. VIII. Students gain proficiency with a PLC simulation software package and utilize this software package to solve problems on a wide-range of PLC problems. IX. Students gain proficiency with a premier PLC programming packages and utilize such software package to solve problems on a wide-range of PLC problems. X. Pursuit of a versatile environment for students programming particular brand controllers coming in a variety of modules; concerns standard and safety configurations, redundancy, communication, motion, and I/O modules. Such is highly dependent of the resources of the utilities in the respective environment. OUTLINE --> Note: the course outline will be mostly geared towards ladder programming development, however labs will be much more real word, integrating microcontroller environments as well (based on prerequisites). I. Programmable Logic Controller Overview II. PLC and Control System Components (multiple sessions) III. Relay Logic Diagrams (multiple sessions) IV. PLC Programming (multiple sessions) V. Programming Logic Gate Functions in PLCs VI. PLC Functions (extensive sessions likely for such topics) VII. PLC Interrupts (multiple sessions) VIII. Process Control (3-4 sessions) IX. PLC Networks (3-4 sessions ) X. PLC Applications and Case Studies (extensive ) LABS --> Note: the course outline will be mostly geared towards ladder programming development, however labs will be much more real word, integrating microcontrollers and microcontroller environments as well. Each lab session will require 2-3 hours. Some labs may require at least 4 sessions. Students are allowed to video tape their labs with the appropriate regulations in place. I. Introduction to industrial control systems (at least 1 session) II. Sensors, actuators, AD/DA converters (2 lab sessions) III. Industrial Controllers: logic control systems (2 lab sessions concerning logic control circuits) IV. Industrial Controllers: ladder logic/PLCs V. Industrial Controllers: C based VI. Build and programme a desktop industrial automation trainer for experimentation in motor, and process control system concepts on their workbench (subject to IV and V) VII. Design and Implementation of a OPC/PLC (subject to IV and V) DC/AC Motor control Level controllers and advance liquid transport system Temperature control Lighting specifications VIII. Industrial Robotics: choice of individual industrial robotics towards identifying subroutines and so forth; at least planning and logistics if actual programming of robot is inaccessible. Nevertheless, rough robots can be pre-built and optimised. Design programming based on operation/action features and communication rules for the objects in question. Then incorporate and implement (subject to IV and V) IX. Numerical Control: development of drawing machines where students make use of programmable boards for comparison/contrast (subject to IV and V) X. Flexible Manufacturing Systems (FMS) & Computer Integrated Manufacturing (CIM) Concerns identifying subroutines of units and assembly/process chain, etc; concerns at least planning and logistics if actual programming is inaccessible. Following, Students will be asked to design programming based on operation/action features and communication rules for the objects in question XI. Developing a wireless primitive PLC with field testing. With field assignments. XII. The OPCClassic library to be used to test a new design of a PLC before it is connected to the real plant/system. Data from the process plant model is written from SystemModeler to the OPC server, and is then read by the external PLC. The PLC computes a control signal that is written back to the server, from where the process plant in SystemModeler/Modelica can access it. Necessarily it’s critical that students are well acquainted with design and configuration software that’s highly applied in integrated architecture. Assidtance from constituents of utilities (WASA, T&TEC, TSTT, etc., or corresponding entities) concerning the OPCClassic Modelica Library to have on-site development, observation and analysis with PLCs residing in inventory storage and in function (operational specs and appropriate types of system integration). Includes components of PLC modules and network topology. Prerequisites: ODE, General Physics I & II, Assembly Language I, Embedded Systems II 21. Silicon Photonics Design (CHECK COMPUTATIONAL FINANCE POST) 22. Semiconductor Quantum Structures & Photonic Devices (CHECK COMPUTATIONAL FINANCE POST) 23. System-on-Chip (SoC) Design (CHECK COMPUTATIONAL FINANCE POST) ***Descriptions of particular ME courses--- 1. Machine Design I: Design and application of machine components such as brakes, clutches, gears, mechanisms, bearings, ways, sleeves, and bushings. Lubrication of machine elements such as gaskets, seals, "o" rings, and fasteners. Design techniques and the design of a simple machine. Engineering is a precise discipline. One aspect of this class, in addition to the engineering principles studied, is to teach each student solid engineering problem-solving & presentation of analysis skills. This starts with clearly defining the problem and the information sought, identifying the engineering principles and equations applicable, and applying them properly in an orderly fashion. Analytical work should be neat, clear, concise, and easy to follow. Avoiding, identifying and eliminating errors are highly dependent on being able to clearly review the analysis presented, both in the classroom and in the workplace. Credit on homework, quizzes and tests will be highly dependent on how easy it is to follow the thoughts and judgments of the student. Work that is cluttered, overly sloppy, jumbled, or simply hard to follow will lose points, even if the final answer is correct. The following standards are expected and will result in maximum credit: Homework should be worked on Quad (4 squares/inch) or Quint (5 squares/inch) paper. Ampad’s Engineering paper (22-141, 22-142, or equivalent) is one of the best for this. Homework, test, & design project data should be worked on only one side of the paper. Each assignment should clearly identify the student’s name (first & last). Each separate sheet of homework, design project, or test should also clearly identify the class, the assignment & number (HW #1, HW #2, DP #1, Test #1, etc.), the date, and the problem number being worked. Each homework problem should be clearly identified with three primary sections, GIVEN, FIND, & SOLUTION, with each section title identified & underlined. GIVEN: List the data given in the problem statement. Usually this should be preceded or accompanied by a sketch with appropriate dimensioning and/or labeling that contains most, if not all of the given information. FIND: State what you are trying to find in this problem. SOLUTION: Solve the problem in a neat and logical manner. Each equation used should be first identified prior to substituting the appropriate values. Each step in solving the equation should be clearly shown in a linear fashion as you proceed down the page. Required Typical Text & Tools --> Budynas & Nisbett. Shigley’s Mechanical Engineering Design. 9th Edition preferred any addition acceptable. McGraw Hill. 2011. (Hardcopy Required) Pencil, Paper (Quad or Quint Pad Recommended), Engineering or Scientific Calculator Technology Tools --> Mechanical CAD (pre-developed and to be developed items) Structural Analysis software Homework Grading Procedure --> Each student must grade their own Homework prior to submitting to instructor, as follows: Using a colored pen or marker that stands out from your homework, score each problem next to its identification, and circle the score of each. Score each problem as follows: SETUP: Score 1 point if all the following is present in your solution: Problem Number - Identified (1, 2, 3, etc) & circled Given, Find, & Solution - Clearly marked & appropriate pertinent data recorded. Sketch – Pertinent sketch of problem shown. Neatness – Setup is legible & clear WORK: Score 2 points if all the following is present in your solution: Equations – All pertinent equations needed and/or used are shown Neatness – All work is legible and clear. Complete - Problem is worked to completion & all answers are boxed ACCURACY: Score 0, 1, or 2 points, as follows: If all answers requested match the answer provided, score 2 points. In only some of the answers provided match the solution, score 1 point. If no answer is provided, score 2 points. This means each problem score will range from 1 to 5 based on the above. Sum your scores to the top of the first page with the total points earned over the total possible (5 times the number of problems), and circle the total score conspicuously. If you failed to write your name at the top of the paper, or to staple your work together, score -3 next to the collective score. If you did something beyond the homework that you want me to see or score, write “See XYZ” or some such and I will take a look and evaluate. I will make any modifications to the grades as needed, and may score punitive point reductions if I feel the scoring is intentionally misleading. Any ungraded Homework will not be scored, and will show a zero in my gradebook. Project Development will have various phases --> Lab 1 Lab 2 Lab 3 Team Select Draft Schedule Report Template Preliminary Drawings Preliminary Calculations Draft Report 1 Draft Report 2 Early Project +2% Project Due Late Project (within certain period) -10% Late Project (following after) -20% Grading --> 14 Homeworks 20% Labs, Project Development & Quizzes 10% Master Project 40% Test #1 10% Test #2 10% Test (Final) #3 10% Course Outline --> WEEK 1 Introduction Shafting WEEK 2 – 4 Motors Gears – spur & helical design Gears – bevel Gears – worm Test 1 WEEK 5 Lubrication & Sliding Bearings WEEK 6 Bearings - Rolling Contact Bearings - Tapered Rollers WEEK 7 Weldments Test 2 WEEK 8 – 9 Clutches, Brakes, Couplings & FWs WEEK 10 – 11 Project Presentations WEEK 12 Final Exam 2. Machine Design II: Advanced topics in the design of machine components and mechanical systems for motion, dynamics, strength and stress requirements. Techniques that can be applied to the design of machine components and systems. Projects are open-ended and involve the design of mechanical components and machinery. Typical Text: Shigley’s Mechanical Engineering Design, Eleventh Edition, R.G. Budynas and J.K. Nisbett. McGraw-Hill Education, New York, 2020 The two exams are open book (must use your own copy of the Eleventh Edition of the book) and open lecture notes. Students have one week after receiving their graded projects, and exams to request a regrade. The course grade will be based on a straight scale. Technology Tools --> Mechanical CAD (pre-developed and to be developed items) Structural Analysis software Grading Policy --> Homework (12) Not collected: solutions will be posted on the course website Labs will concern design planning and development accompanied by use of mechanical CAD and structural analysis software 20% Projects 40% (Individual work) Late projects will not be graded and cannot receive any credit Mid-Term Exam 20% Open book and open lecture notes (no crib sheets) Final Exam 20% Open book and open lecture notes (no crib sheets) Course Outline: WEEK 1 Introduction. Single cylinder engine Kinematics and Dynamics Shaking Forces and Moments Project 1 Assigned WEEK 2 Reciprocating Unbalance Rotating Unbalance WEEK 3 Fatigue Failure Stress and Strength Considerations Stress Concentration WEEK 4 Shaft Design. Stress Analysis Deflections. Critical speeds Influence Coefficients WEEK 5 Surface Fatigue Spherical Surfaces Cylindrical Surfaces WEEK 6 Journal Bearings Petroff’s Law Reynold’s Equation WEEK 7 Spur Gear Geometry Loading on Gear Teeth Stress on Gear teeth WEEK 8 Gear Strength Bending Factor of Safety WEEK 9 Contact Factor Midterm WEEK 10 Cam Design Roller Follower Radius of Curvature Project 2 Assigned WEEK 11 Pressure Angle Flat Face Follower Dynamic Loads WEEK 12 Helical Tension Springs Spring Loads and Stresses Static Failure WEEK 13 Fatigue failure Torsion Springs Fatigue Failure WEEK 14 Brakes and Clutches Short Shoe Brakes Long Shoe Brakes WEEK 15 Uniform Pressure Uniform Wear Disk/Clutch Brake Final Exam Prerequisites: Machine Design I 3. Statics: Analysis of forces acting on particles and rigid bodies in static equilibrium; equivalent systems of forces; friction; centroids and moments of inertia; introduction to energy methods. Course will be 17 weeks long Primary Text: R. C. Hibbeler, Engineering Mechanics: Statics, 14th Edition, Pearson Prentice Hall Grading: Homework/Quizzes: 20% 3 Tests: 45% Common Final Exam: 35% (must score at least 40% to pass the course) There will be review for exams TOPICS --> Chapter 1 Chapter 2 (2.1 – 2.9) Chapter 3 (3.1 – 3.4) Chapter 4 (4.1 – 4.9) Chapter 5 (5.1 – 5.7) Chapter 6 (6.1 – 6.6) Chapter 7 (7.1 – 7.3) Chapter 8 (8.1 – 8.5) Chapter 9 (9.1 – 9.2) Chapter 10 (10.1 – 10.4) 2 Day Review for final Final Prerequisite: General Physics I, Calculus II 4. Mechanics of Materials: This course is intended to provide the students with both the theory and application of the fundamental principles of mechanics of materials. Understanding is based on the explanation of the physical behaviour of materials under load and then modelling this behaviour to develop the theory. The specific objectives consist of modelling of one-dimensional structural elements such as bars, shafts, beams, and columns with the aim of determining the stresses, strains, and deflections of these one-dimensional elements. The students are required to establish basic skills related to these structural elements by the end of the semester. Course will be 17 weeks long Typical Text: Hibbeler, R. C., Mechanics of Materials, Tenth Edition, Pearson Prentice Hall Course Grading: Homework (paper based & online) 15% Quizzes 15% 2 Tests 40% Final Exam 30% All work must be done on “Engineering Paper” or typed (and figures drawn) neatly using a computer. Work will be done on only one side of the paper (engineers do not write on the back of the paper). The course name, date, and assignment number are to be written only on the first page. Begin each homework problem in an assignment on a new sheet of paper, and present the solutions in the same order that the problems were assigned. In homework, quizzes, tests, and exams it is imperative that a proper free-body diagram is drawn even if it is not explicitly stated in the problem statement. The steps in drawing a proper free-body diagram area as follows: 1) Isolate the part/component of the structure/system of interest. 2) Set up a reference system and its origin. 3) Include the applied loads. 4) Remove the constraints and replace them with the equivalent reactions. 5) Include all necessary dimensions NOTE: There will be review for exams TOPICS --> Chapter 1 (1.1 – 1.7) Chapter 2 (2.1 – 2.2) Chapter 3 (3.1 – 3.7) Chapter 4 (4.1 – 4.6) Chapter 5 (5.1 – 5.5.) Chapter 6 (6.1 – 6.6) Chapter 7 (7.1 – 7.2) Chapter 8 ( 8.1 – 8.2) Chapter 9 (9.1 – 9.5) Chapter 10 (section 10.6) Chapter 11 (11.1 – 11.3) Chapter 12 (12.1, 12.2 & 12.5) Chapter 13 (13.1 – 13.3) 2 Day Review for final Final Prerequisite: Statics, Calculus III 5. Mechanics of Materials Lab Properties and behaviour of engineering materials including stress-strain relations, strength, deformation mechanisms, strength, deformation, fracture, creep, and cyclic fatigue. Introduces experimental techniques common to structural engineering, interpretation of experimental data, comparison of measurements to numerical/analytical predictions, and formal, engineering report writing. Lecture and laboratory. By the end of this course, the student will be able to --> 1. List and explain applicable experimental methods for characterizing material and component behaviour 2. Compare (and quantify differences) measured experimental results and calculated theoretical values. 3. Predict component behaviour using experimental test results and engineering formulae 4. Analyse experimental data, theoretical models and their scalability to components 5. Analyse (deduce) the inherent variability of materials subjected to multiple modes of loading and apply the results to component behaviour. 6. Formulate a solution path for analysing an actual multi-component structure using experimental, theoretical, and numerical tools/methods. 7. Evaluate the limits of structures by extending the experimental measurements using theoretical and numerical methods. Contribution of Course to Professional Component --> The aim of the course is to prepare students for engineering practices by familiarizing them with mechanical testing systems, conducting experimental work, advancing their fundamental engineering knowledge, cultivating professional engineering standards, and developing their technical communication abilities. Grading: 1) Reports 55% Formal Reports 30%, Memo Reports 20%, In-lab Report 5% 2) Exams 35% Midterm Exam 15%, Final Exam 20% 3) Homework 10% 4) Quizzes +1% Fundamentals of Engineering Exam Questions Typical Text: Dowling, N. E., 2007, Mechanical Behaviour of Materials: Engineering Methods for Deformation, Fracture, and Fatigue, Pearson/Prentice Hall Supplement: Shigley’s Mechanical Engineering Design, Eleventh Edition, R.G. Budynas and J.K. Nisbett. McGraw-Hill Education, New York, 2020 Tools Mechanical CAD (pre-develped items) + Structural Analysis software Serves to compare with theoretical models and experiments Course Outline: WEEK 1 No Lab Course Overview, Review of Mechanics of Materials Review of Material Science Lab Procedure - Significant Figures, Statistical Analysis Beam Bending WEEK 2 Lab: Strains, Deflections, and Beams in Bending (memo report) Transformations, Mohr's Circle Lab Recitation - Strain Gages, Memo Report Style Principal Stresses, 3D Stresses Failure Criteria, Max Normal, Tresca WEEK 3 Lab: Curved Beams and Photoelasticity (in-lab report) Lab Recitation – Photoelasticity von Mises Stress, Failure Factors Mechanical Testing WEEK 4 Lab: Tension and the Mechanical Properties of Materials (formal report) Stress/Strain - True vs. Engineering Lab Recitation - Instron, Formal Report Style Hooke's Law in 3D Deformation Model WEEK 5 Lab: Fracture (memo report, due in 2 wks.) Lab Recitation Plasticity in 3D Plasticity in Unloading/Cycling Loading Plasticity in Bending/Torsion WEEK 6 Lab: Torsion and the Mechanical Properties of Materials (formal report) Mid-Term Exam Lab Recitation Fracture, Crack, and Stress Concentrators WEEK 7 Lab: Stress Intensity Factors (in-lab report) Lab Recitation Creep WEEK 8 Lab: Structural Evaluation and Bike Frames (formal report) Cyclic Fatigue Lab Recitation Cyclic Fatigue, Stress Risers Fracture Crack Growth WEEK 9 Lab: Creep (memo report, due before Final Exam) & Fatigue (in lab report) Lab Recitation Compression Testing, Hardness, Fracture Compression, Yielding Buckling WEEK 10 Lab: Compression and Buckling (in-lab report) Lab Recitation Buckling Review Review Prerequisite: Mechanics of Materials 6. Sensor Instrumentation: Homework assignments: 15% Labs: 55% Final Project: 20% Attendance: 10% NOTE: technical papers and white papers from Texas Instruments, Analog Devices and Arduino can be invaluable. Essential issues and objectives are not necessary written in a specified order where issues can be extensively implemented or applied throughout like Verilog and high level language: A. Instrumentation systems for barometric pressure, hydraulic pressure, temperature, speed, rpm, variable voltage, current, resistance, vibrations. B. Ability to evaluate the quality and safety of electronic products including reliability, physical testing, electrical safety and electromagnetic compatibility. C Ability to design systems schemes for sensing with appropriate devices and how they interface/interact with each other. Have knowledge of how to read sensor specifications and understand their performance and limitations. Know how to independently analyse the dynamic system and select the appropriate sensors. Know how to interface analog and digital sensors to digital computer systems. Implement and operate high performance laboratory electronic instrumentation, with emphasis on error analysis, calibration and virtual control. Advanced instrumentation systems architectures, and virtual instrumentation. Fault-tolerant design. Understand basic ideas of physical redundancy and analytic redundancy. D. Ability to integrate instrumentation systems with mobile devices, programmable boards, laptops, etc. Fault-tolerant design. Understand basic ideas of physical redundancy and analytic redundancy. E. Ability to deploy distributed instrumentation systems and sensor networks in various environments (aquatic, fluid, thermal, electrical, mechanical, electromechanical). Fault-tolerant design. Understand basic ideas of physical redundancy and analytic redundancy. F. Managing the acquisition, structuring, analysis and display of data and information in the chosen area of specialisation and critically assessing the results obtained. G. IEEE 1451 Smart sensor standard implementation (or possibly higher). As well: http://www.theremino.com/en/hardware/inputs/sensors H. Students will will learn to use Verilog, high level language through lab exercises and assignments focused on understanding sensors, FPGA board, programmable boards, modules, etc. through lab exercises focused on understanding sensors. Use of high level language to communicate with various instruments, such as power supplies, multimeters and oscilloscopes. Developing test benches in a high level language for automatic data acquisition from computer controlled instruments. Design Verilog and high level code to send and receive high bandwidth data between FPGA and PC via USB 3.0 control; heuristic development before actual coding, testing and implementation. Investigate the fundamental limitations of data acquisition systems. I. Apply signal sampling and Kalman Filtering when practical and most beneficial. Will also require oscilloscopes, multimeters, data sheets, schematics, layouts, etc., etc. Labs--> (i) Students will become familiar with the working environment for Verilog and the FPGA board. They will write example codes to send data to and from the FPGA board and a PC using USB 2.0 or USB 3.0 data interface. The software code on the PC will be written in a high-level language. The FPGA code will be written in Verilog. Looking for a data acquisition card (that’s much cheaper than the OpalKelly XEM 6002), but function’s just as well with similar adaptable features. (ii) A (Pmod or other) ultrasonic sensor will be used for the lab. Students will write UART protocol on the FPGA to send data from the sensor to the PC via USB 2.0 or USB 3.0 interface. Once the data is received, a gesture recognition-controlled game will be implemented in a high-level language. (iii) Students will start putting together the building blocks to obtain an image from a custom analog CMOS sensor and transfer the data to the PC to be displayed. Beginning by understanding the light to electron conversion by controlling a single pixel from the imaging sensor. The different operating cycles of the pixel will be covered: reset, integration and sampling the data. Students will write a state machine in HDL to control the imaging sensor and use oscilloscope to ensure the proper operation of the sensor. (iv) Design a state machine in the FPGA that will control all digital circuits in the imaging sensor, scan an image and correctly sample the analog data from the image sensor. Data aliasing, filtering and amplification to be covered in terms of acquiring the analog signal from the imaging sensor and correctly digitizing it. (v) Design the necessary interface in Mathematica/C/C++ to receive data from the FPGA to the PC via USB 3.0 and display data from the (CMOS) imaging sensor on the screen. USB 3.0 data transmission will be developed, debugged and tested. Raw data from the sensor will be also saved for analysis. (vi) Data collection from the (CMOS) image sensor using computer-controlled instruments will be covered. For example, pixel’s output voltage as a function of light intensity will be measured. A computer-controlled power supply will control the Led brightness and oscilloscope will capture the pixel’s output. Instrument synchronization will be covered. (vii) Students will evaluate the performance of the imaging sensor, such as SNR, FPN, dynamic range, using computer-controlled instruments via a high-level language. Note: for students that will not be able to complete the necessary state machines to control the imaging sensor module, a Verilog and high-level code will be provided to assist them with the data collection; this is the one and only exception (only this specific lab) where any code is given to students in course. (viii) Integrate magnetic (or resistive or optical) encoders with a motor and the FPGA environment. More information about the magnetic encoder can be found here. Design and test HDL code to control the motor and evaluate and encoder precision. Combine the ultrasound sensor with a motor to create a 3-D map of the environment. (ix) Test the precession of a compass sensor module. Integrate the compass module with the motor/encoder system and test its accuracy and precision. Note: there are economic sensors that account for three types of sensing (gyroscope, accelerometer and compass). (x) Pmod (or other) sensor module containing temperature, humidity, proximity, UV and light sensor, like the Silicon Labs Sensor-PMD board (Sensor PMOD Board). (xi) Capacitive sensor will be used for the lab. An example, the PmodCDC1. Students will test the sensitivity of the capacitive sensor using variety of computer-controlled experiments. (xii) Temperature sensors and I2C interface protocol. (xiii) Pressure sensors and USB interface protocol. (xiv) Automatic Room Light Controller using IR sensors This project employs a mechanism which room lights on when a person enters the room and switch off as the person leaves the room. In addition, it also displays the number of persons entering or leaving by means of LCD. With this automatic operation, electrical energy can be saved. In this system, two sets of IR LED and IR sensors are connected to the microcontroller to detect the persons exiting and entering the room. The microcontroller is programmed in such a way that by receiving the signals entering from the IR sensor, it turns the lamp with a relay mechanism and also increments the counter. Similarly, for the exit sensor signal, it turns off the lamp and decrements the count which is also displayed in the display. (xv). Green house intelligent control system https://microcontrollerslab.com/green-house-intelligent-control-system/ Will like to extend lab further, say, preservation of some particular chemical, compound or whatever substance based on environmental specifications. Will like to assess performance and so forth. Prerequisites: Embedded Systems I & II 7. Robotics I: Robot terminology; spatial descriptions and transformations; manipulator kinematics; Jacobians and static forces; trajectory generation; linear and nonlinear control of manipulators; application of various robots. Course objectives: i. Learn robot terminology, classifications and applications in various fields. ii. Introduce to students mathematical modelling of manipulator. iii. Learn manipulator forward kinematics and inverse kinematics. iv. Use Jacobians matrix to analyse velocity and static forces. v. Learn trajectory generation. vi. Grasp linear control and nonlinear control techniques. vii. Use force control for manipulators. viii. Introduce to advanced robotic systems. Textbook: John. J. Craig, Introduction to Robotics: Mechanics and Control, 3rd Edition, Person Education, 2005 References: L. Sciavicco and B. Siciliano, Modelling and Control of Robot Manipulators, 2nd edition, Springer, 2000. Richard M. Murray, Zexiang Li, S. Shankar Sastry, A Mathematical Introduction to Robotic Manipulation, 1st edition, CRC Press, 1994. Grading --> Homework: 20% In-class Quizzes: 10% Exam 1 15% Exam 2 15% Final Exam (Comprehensive): 40% I. Introduction Review of Syllabus; Introduction to the history of robot; The Mechanics and Control of Mechanical Manipulators; Notation II. Spatial description and transformation Descriptions: Position, Orientation, and Frames; Mappings; Operators; Transform Equations; Representation of Orientation; Transformation of Free Vectors; Computational Considerations III. Manipulator kinematics Link Description; Link-Connection Description; Convention for Affixing Frames to Links; Manipulator Kinematics; Actuator, Joint, and Cartesian space; Industrial Robot Examples; Frames with Standard Names; Computational Considerations IV. Inverse manipulator kinematics Solvability; Manipulator Subspace Notation; Algebraic vs. Geometric Solutions; Examples of Inverse Manipulator Kinematics; The Standard Frames; Solving a Manipulator; Repeatability and Accuracy; Computational Considerations V. Jacobians: velocities and static forces Notation for Time-varying Position and Orientation; Linear and Rotational Velocity of Rigid Bodies; Velocity Propagation; Jacobians; Singularities; Static Forces in Manipulators; Cartesian Transformation of Velocities and Static Forces. VI. Trajectory planning Path description and generation; Joint and Cartesian Space Schemes; Geometric Problems with Cartesian Paths; Path Generation at Run Time; Planning Collision-free Paths. VII. Control of manipulator Feedback Control; Control Law Partitioning; Trajectory-following Control; Continuous Vs. Discrete Time Control; Industrial Robot Controller Prerequisites: General Physics I & II, ODE 8. Mechatronics I: Some skill with Mathematica programming will be assumed, including the ability to write programs including for loops, while loops and if-then-else branching statements. Expertise in MS Word and MS Excel or equivalent is assumed. If you do not have these skills, you should expect to spend extra time on this class to catch up with your peers. CAD and CAE software will be made available. Access to internet from a PC or laptop will be assumed. Course Objectives i. To build basic skills in the use of CAD/CAE programme ii. To introduce standard 2-D drawing and dimensioning practices for shop drawings iii. To introduce standard machining equipment and operations including the use of precision measurement tools such as Vernier callipers and micrometres. iv. To develop the ability to interpret manufacturers’ specifications for hydraulic and pneumatic actuators and for DC permanent magnet motors, and to select appropriate actuators and peripheral components for a particular design. v. To develop the ability to analyse input and output torque, speed and displacement for simple gear trains, belt/pulley systems, rack and pinion systems, and lead screws. vi. To develop the ability to analyse simple resistor networks, to design voltage dividers, and to specify current-limiting resistors for diodes and transistors. vii. To develop understanding of common methods for interfacing sensors and actuators to microcontrollers, including the use of pullup/pulldown resistors, transistor amplifiers and voltage dividers. viii. To develop a fundamental understanding of the use of microcontrollers in the design of electromechanical systems, including digital input/output and analogue input/output, programming the microcontroller in Mathematica to read and interpret sensor signals and to generate output commands to actuators to perform a specified task. ix. To introduce students to a few basic types of sensors and actuators that are useful in robotics and industrial control, such as proximity detectors, optical switches, light sensors, optical encoders, temperature sensors, LED indicators, DC electric motors and stepper motors. x. To build an ability to write Mathematica programme to perform simple control functions such as binary on/off control, binary control with deadband, proportional control with deadband, and proportional plus integral controlCourse Learning Objectives --> Students will be able to: i. Generate 3-D CAD Models of simple mechanical objects ii. Specify and use basic mechanical design elements, such as gears, belts, bearings, lead screws and other mechanisms at the level of functionality and application. iii. Use Mathematica to perform data acquisition and control functions, set up logic based sequential control algorithms and simple single-loop feedback control programs. iv. Specify and use common electro-mechanical sensors and actuators, including DC motors, stepper motors, optical encoders, proximity sensors, temperature sensors and micro-switches. v. Use laboratory equipment and tools such as a Digital Multimeter, Lab power supply, prototyping board, Vernier calliper and micrometer. vi. Work with other students to integrate mechanical, electronic and software components into a functioning mechatronic system. LAB ATTENDANCE --> Attendance for all labs is mandatory. You will be assigned a lab section and a lab station, and you must attend your assigned section unless you make prior arrangements to be absent. If you miss a lab you must make it up. This can be done either during one of the other lab sections or during open lab hours or by making special arrangements with one of the Tas Exam 1 100 points Exam 2 100 points Comprehensive Final Exam 200 points There will be several quizzes that may be taken in-class or in the laboratory, and other assignments (lab write-ups, CAD projects, design projects) as deemed appropriate by the instructor. Quizzes are worth 25 points each and “other” assignments will carry values that will be announced at the time the assignment is made. The lowest quiz score will be dropped. Curve points, if any, will be awarded separately for each assignment, with the goal of reaching a compromise between two objectives: 1) achieving a median class score of approximately 75 2) achieving a grade distribution with approximately 15% of the class receiving a grade of A on any given assignment. These two objectives may not be simultaneously achievable, and thus the award (or not) of curve points will be done solely at the discretion of the instructor. At the end of the semester, letter grades will be awarded based on the percentage of: (total points earned + curve points)/total points possible Typical text: TBA Course Outline: WEEK 1 Scale Measurement, Vernier Scales, Calipers WEEK 2 Modeling, Dimensioning and Machining Mechanical Power, Hydraulics, pneumatics WEEK 3 Hydraulic & pneumatic valves and controls Power transmission: Spur Gears 1 WEEK 4 Power transmission: Linear motion Intro to Bearings WEEK 5 Example Problems--power transmission Exam Preparation WEEK 6 Exam1: Mechanical Design Electric Motors: AC, Brushed DC WEEK 7 Example problems--electric motors Ohm's Law Review, Diodes WEEK 8 Electronics problems Binary Sensors and Switches, Transistors WEEK 9 Power Amplification, H-Bridge, PWM Stepper Motors, Driver Programs WEEK 10 Exam Preparation Exam 2: Electronics WEEK 11 Analog Sensors and Scaling Feedback Control: Binary, Deadband, Prop WEEK 12 P + I Control, Control Algorithms ADCs, quantization error WEEK 13 ADC problems, Lab Project Teams and Encoders & Position Control WEEK 14 Position Control Problems Semester Review: Mechanical Semester Review: Electronics Semester Review: Controls and Software Labs --> Note: each lab will have a 1 week duration Lab 1: CAD Lab 2: Gears & Power Transmission Lab 3: Intro to Arduino (or whatever), Digital I/O Lab 4: DC Motor Control Lab 5: Stepper Motors Lab 6: Analog I/O & P+I Control Lab Project (week 14 & 15) Prerequisites: General Physics I & II 9. Mechatronics II: Course topics: - functionality, modelling, and selection of basic elements of the mechatronic systems; - computer assisted measurements: data acquisition, processing, and analysis; - closed loop control; - the mechatronic design approach and introduction to artificial intelligence techniques. To provide the MAE students with an advanced perspective on the integrated design and operation of mechanical systems with electronic controls. Learning outcomes At the end of this course, the students should be able to: - describe the basic principles and the functionality of the main types of sensors and actuators. - select adequate sensors and actuators for complex applications. - model mechanical, electrical, fluid, and thermal systems using differential equations and transfer functions. - analyse first and second order system dynamic response. - use Mathematica and SystemModeler for modelling, simulation, and control of systems. - describe the functionality and role of the components of a measuring system. - build and analyse a measuring system using sensors, signal conditioning devices, and computers. - measure vibrations, process data through filtering, and perform Fourier analysis. - describe the use of artificial intelligence techniques (genetic algorithms, fuzzy logic, and neural networks) to solve engineering problems. Typical text: W. Bolton, Mechatronics - Electronic Control Systems in Mechanical and Electrical Engineering, 4th Edition, Prentice Hall, 2008 Exams --> Midterm (2) and final exams will be closed book. Final is comprehensive. Homework --> Homework is individual unless it is specifically assigned as a team/group effort. Late submissions are accepted, but they will be subjected to a 10% penalty per day. Tentative number of homework assignments: 10. Mini-Project --> This is a group assignment. Teams of 4-5 students will formulate the work statement for a complex robotic/mechatronic application and select the sensors and actuators necessary. A professionally written technical report is required. Quizzes --> You will take 4 or 5 short announced quizzes over the material - both lecture and lab - covered since the previous quiz or test. Lab Reports --> There will be 5 labs this semester. You will work in teams of 2. Each person must hand in his/her own lab report. This means that only the data, plots, and computer code may be identical within a group. Answers to questions, descriptions, comments, conclusions, etc. must be individual contribution. All submissions must have your name, the name of your partner, the lab number, and your lab section time in the title block. The format and content of the lab reports must comply with the handout provided and be professional. Reports are due in a week from the day of the lab. Late submissions are accepted, but they will be subjected to a 10% penalty per day. You must actually perform the lab and submit a report to receive any credit. You must attend and complete ALL labs to qualify for an overall course passing grade. Course Outline --> Chapter 1. Introduction Chapter 2. Basic system elements 2.1. Sensors and transducers 2.2. Signal conditioning 2.3. Data presentation and acquisition systems 2.4. Actuation systems (pneumatic and hydraulic, mechanical, and electrical) Chapter 3. System modelling 3.1. System models 3.2. Dynamic response of systems (time domain and frequency domain) 3.3. System transfer functions 3.4. Vibrations 3.5. Harmonic analysis – Fourier transform Chapter 4. Filtering - Mathematica tools and digital methods 4.1. Filter Classification 4.2. Digital filters in frequency domain 4.3. Implementation of digital filters 4.4. Mathematica filtering tools Chapter 5. Digital and microprocessor systems 5.1. Digital logic 5.2. Microprocessors 5.3. Input/output systems 5.4. Programmable logic controller 5.5. Fault finding Chapter 6. Closed-loop control 6.1. Stability criteria 6.2. Initial and final value theorems 6.3. Closed-loop control modes (P, D, I) Chapter 7. Introduction to artificial intelligence techniques 7.1. Genetic algorithms 7.2. Fuzzy logic 7.3. Artificial neural networks LABS --> 1. Advance recitals of chosen prerqusite labs (3-4) 2. Data Acquisition Using the Sound Card and the Mathematica/SystemModeler DAQ Toolbox - Analog Input 3. Temperature Measurement Using the National Instruments DAQ Card (or whatever) and the Mathematica/SystemModeler DAQ Toolbox - Analog Input 4. Data Acquisition Using Piezoelectric Accelerometers, NI DAQ Card, and the Mathematica/SystemModeler DAQ Toolbox - Analog Input. DAQ for other sensing. 5. Modelling and Simulation of a Measurement System Using SystemModeler 6. Vibration Measurement, Frequency Analysis, and Filtering NOTE: Time permitting, students will choose 2 or 3 additional labs from prerequisite to reinforce or advance. Prerequisites: Mechatronics I 10. Systems Modelling I: Note: course is neither a review nor repetitive scheme of any introductory calculus-based physics course (say General Physics I & II). Course builds on the General Physics I & II course sequence, differential equations, and introductory circuit analysis towards development of modelling for system control. Course places more emphasis on theoretical model building rather controller development and design; stressing primarily competence in building models for real systems with practicality concerning control in future endeavours. Learning Outcomes --> -Model different engineering systems to acquire mathematical models -Model different engineering systems using block diagrams and state space -Explain the concepts of transfer function and frequency response -Explain and use various methods for simulating the behavior of different engineering systems Tools --> Mathematica SystemModeler and/or Modelica Topic Areas --> --Modelling and Analysis of Mechanical Systems --Modelling, Mathematica, SystemModeler and Modelica --Laplace Transform --Review of Laplace Transform (LT), Inverse LT, Examples with LT and Transfer Functions --Transfer Function Models --State Space Modelling Note: this is not a matrix algebra course. Understanding logistics for matrices only when they are relevant (say, good approximation or whatever). I want results, not pig pen finesse on a transparent/sharpie board like some “YouTube douche”. FORGET ABOUT: ADJOINT[ADJOINT[ADJOINT]], MATRIX EXPONENTS, RAINING EXCREMENT AND THOSE OF THE MATHEMATICS DEPARTMENT. --Modelling of Electrical & Electromechanical Systems Will also include transfer function modelling and state-space modelling --Modelling of Fluid & Thermal Systems Will also include transfer function modelling and state-space modelling --Time Response Analysis of Linear Dynamic Systems --Computer Simulation of Various Systems --Frequency Response of Linear Dynamic Systems --Free Vibration of Multi-Degree of Freedom Systems --Input-Output Stability and Transient Response Analysis --View of Feedback Control Prerequisites: General Physics I & II, Ordinary Differential Equations. 11.Systems Modelling II: Advanced treatment of Systems Modelling for various systems (mechanical, thermal, thermal-mechanical, electrical, electromechanical). Without skills in system construction and modelling one is setting themselves up for extreme self-embarrassment and lack of ability to design and develop advance systems to be integrated. Tools --> Mathematica SystemModeler + SMAD, and/or Modelica Outline --> A. Vectors, matrices and phasors (handout only) B. Laplace transforms of first and second order realistic systems (handout only) C. Mechanical systems I. Fundamental principles, models of basic elements, and ways of analysis II. Newton’s laws for modelling III. Inertial, gravitational, spring, fluid, and damping systems; combination. IV. Review of Linear and Rotational kinematics 1 – dimensional, 2 – dimensional, projectiles Rotational systems V. Conservation of energy, momentum, angular momentum; coupled cases VI. Mechanics Translational Rotational Coupled cases VII. Geared systems Includes kinematics with ratios, and application of (V) and (VI). Gear box in transmissions. VIII. Free and forced vibration of multi-degree of freedom systems IX. Vehicle Mechanics (i) Longitudinal/Lateral Stability Analysis of Vehicle Motion in the Linear Region (ii) Chen, K., Pei, X., Ma, G., Guo, X., Longitudinal/Lateral Stability Analysis of Vehicle Motion in the Nonlinear Region, Mathematical Problems in Engineering, Volume 2016, Article ID 3419108, 15 pages (iii). Deriving a second order roll angel model for a ship and associated solutions. Concerns the following parameters: vessel mass, moment of inertia about the centre of mass, distance along the boat centerline from its centre of mass to its metacentre, and gravitational constant. (iv) Ibrahim, R., A. and Grace, I., M., Modelling of Ship Roll Dynamics and its Coupling with Heave and Pitch, Mathematical Problems in Engineering, Volume 2010, Article ID 934714, 32 pages X. Transfer function formulation for mechanical systems and time response analysis with chosen topics towards competency and professionalism XI. Input-Output Stability and Transient Response Analysis Must be robust in applications with chosen topics towards competency and professionalism. XII. State space representation and dominantly (by nature) general nonlinear systems. Must be robust in applications with chosen topics towards competency and professionalism. XIII. View of development for feedback control for various encountered prior D. Modelling of basic electrical circuits I. Fast and advance review of parallel, series and combination of such two for circuits components (no teaching of circuits). Such will be incorporated into differential equations models (first and second order) for circuits. Such concerns all principal modern components found in circuits. II. RLC circuits (series and parallel) III. Impedance treatment for (II) III. Electromotive force (DC and AC); will incorporate (I), (II) and (II) IV. Transfer function formulation for electrical systems and time response analysis with past topics towards competency and professionalism . V. Input-Output Stability and Transient Response Analysis. Must be robust in applications with chosen topics towards competency and professionalism. VI. State space representation and dominantly (by nature) general nonlinear systems. Must be robust in applications with chosen topics towards competency and professionalism. VII. View of development for feedback control for various encountered prior E. Practical modern electromechanical systems I. Anatomy a DC motor. Modelling (brushed and brushless) DC motors and current output II. Anatomy a AC motor. AC motor modelling and current output III. Electric Generators Dynamos (anatomy and modelling) Circuit diagram representation and mathematical modeling of Dynamos Alternators (anatomy and modelling) Linear electric (LE) Induction (I) Variable speed-constant-frequency (VsCF) Circuit diagram representation and mathematical modeling (LE, I, VsCF) IV. Vehicle electrical system, circuit representation & mathematical modelling V. Transfer function formulation and time response analysis with chosen topics towards competency and professionalism . VI. Input-Output Stability and Transient Response Analysis Must be robust in applications with chosen topics towards competency and professionalism. VII. State space representation and dominantly (by nature) general nonlinear systems. Must be robust in applications with chosen topics towards competency and professionalism. VIII. View of development for feedback control for various encountered prior F. Advance modelling of thermal and fluid systems I. Fluid systems (i). Fluid capacitance and fluid resistance (ii). Fluid capacitance and fluid resistance in pneumatic and hydraulic modelling (iii). Liquid-level systems (iv). Linear and Nonlinear suspension (hydraulic and possibly air) (v). Transfer functions development Filling a Tank Tank with an orifice Components of the tank fluid control and their transfer functions Liquid level systems (vi). Input-Output Stability and Transient Response Analysis (vii). State space representation and dominantly (by nature) general nonlinear systems II. Thermal systems (i). Fourier’s law (ii). Thermal Resistance Concerns models that are analogous to electric circuits involving series and parallel configurations. (ii). Simple harmonic oscillation of an isothermal ideal gas in a piston being driven by a pressure gradient. Piston in this case is assumed to be frictionless and thermal effects of successive expansion and compression of the gas are neglected. (iii). Extending (ii) to the case of friction with piston, with thermal effects of successive expansion and compression of the gas being considerable. (vi). Applications of transfer functions (vii). Input-Output Stability and Transient Response Analysis (viii). State space representation and dominantly (by nature) general III. Heat Transfer with Fluid Flow (i). The amount of heat going into a system due to fluid flow is proportional to the fluid's mass flow rate R, specific heat Cp, and the temperature differential between the inflow and outflow (θin- θout). (ii). Identify typical systems that have heat transfer and fluid flow, where the heat transfer mechanisms of the system are convection and conduction. Geometries and materials applied for system are highly relevant. For fluid flow advection (dependent of motion and momentum) is of interest, with the consideration viscosity being dependent on temperature. Friction may also need to be treated. The environment surrounding the system to have influence as well. Consider both gases and liquids. Don’t rely on the following too much for a well-rounded treatment. Will like to treat different geometries and configurations as well: Mahfouz, A. E., Abdelmaksoud, W. A., and Khalil, E. E. (2018). "Heat Transfer and Fluid Flow Characteristics in a Heat Exchanger Tube Fitted With Inserts." ASME. J. Thermal Sci. Eng. Appl. June 2018; 10(3): 031012 G. Thermoelectric systems NOTE: will try as much a possible not to get lost with the semiconductor physics implemented. (i). Thermoelectric generator and the Seebeck effect (ii). Thermoelectric effect Establish the relations between the following three effects Seebeck Peltier Thomson Real world applications of the Peltier and Thomson effects Full thermoelectric equations Pursue a real system that transitions from one effect to the other Recall Fourier’s law. Is it possible to relate it to Thermoelectric effect? If so, how meaningful would such be? Prerequisite: System Modelling I

12. Feedback Control Example text: Introduction to Control System Technology, 7th Ed., Robert N. Bateson. Reference: Rozhdestvensky, K. et al (2020). Computer Modeling and Simulation of Dynamic Systems Using Wolfram SystemModeler, Springer Grading: Homework Quizzes Labs 3 Exams Lecture outline --> -Introduction (week 1) -Modelling in Frequency Domain & Time Domain (week 2 & 3) -Time Response (week 4) -Stability (week 5) -Steady State Error (week 6) -Root Locus Design (week 7, 8 & 9) -Frequency Response Techniques (week 10 & 11) -Frequency Response Design (week 12, 13 & 14) -Digital Control Implementation (week 15) Labs --> Labs will make use of Mathematica and SystemModeler/Modelica alongside hands on activities. -Modelling of Inverted Pendulum. Balance Control -Modelling of motors. Motor Identification -Proportional Speed Control -Proportional plus Integral Speed Control -Motor Speed Control with Lead Compensation and Integral Control -Position and Velocity Control of Motor -Introduction to Optimal Control Prerequisites: General Physics I & II, ODE 13. Automatic Control Example text: Introduction to Control System Technology, 7th Ed., Robert N. Bateson. Reference: Rozhdestvensky, K. et al (2020). Computer Modeling and Simulation of Dynamic Systems Using Wolfram SystemModeler, Springer Grading: Homework Quizzes 3 Exams Advance Labs LECTURE OUTLINE --> -Review of Feedback Control Systems -Introduction to Automatic Controls Process control principles Process control block diagrams Evaluation of system performance -Review of OP AMPs -Scaling of sensor signals using OP AMPs -Open loop systems -Closed loop systems -Modeling Physical Systems Models of Mechanical Systems Electrical Electromechanical Liquid Thermal Mechanical -Proportional Control Mode Model of proportional control mode Proportional bandwidth Steady-state error of proportional control Practical realization of proportional control -Transfer Function Models Mathematical Models of Systems Self-regulating tanks Non-regulating tanks R-C circuits Liquid-filled Thermometers Control Valves Laplace Transforms Laplace transform pairs Laplace theorems Finding inverse Laplace transforms Transfer Functions and Block Diagrams Finding transfer functions Block diagram simplifications Bode Plots of transfer functions DC motor block diagram Introduction to SystewmModeler/ Modelica Control of Continuous Processes Modes of control Proportional Time and frequency response Transfer function Integral Time and frequency response Transfer function Derivative Time and frequency response Transfer function Proportional plus Integral Control Time and frequency response Transfer function Plus Derivative Control (PID Time and frequency response Transfer function Practical Circuit realizations of control modes -Analysis and Design of Systems Process characteristics Integral processes First order lag process Second order lag process Dead-time process -Methods of Analysis Bode plots of transfer functions Open-loop bode plots Closed-loop bode plots Error ratio and deviation ratio Generating Bode plots with SystemModeler/Modelica Bode stability criteria Nyquist stability criteria Routh-Hurwitz Criteria LABS --> 1. Analog Sensor Signal Conditioning Use analog OP AMP circuits to scale the output of a sensor to signal levels commonly found in practical control systems. To use OP AMP analog circuits to combine several simulated sensor inputs according to a predefined input signal formula. Produce an error signal using an OP AMP differential amplifier. (3 periods) 2. Proportional Control Action Construct a proportional controller using OP AMP circuits and measure its steady state and transient response. View the response of a first order process to proportional control action. (3 periods) 3. Introduction to Control System Modeling with SystemModeler/Modelica This laboratory introduces the SystemModeler/modelica programming and numerical simulation software. Learn how to generate frequency response and time plot common to control systems analysis and design. These include Bode plots and unit step response. Create basic open loop and closed loop block diagram systems using SystemModeler/Modelica and find their response using numerical methods that plot the response as graphs. (1 period) 4. Modeling Control Systems Using SystemModeler/Modelica This lab uses SystemModeler/Modelica software to model an antenna positioning system. Students develop the transfer function blocks from component parameters and construct the block diagram in Systemmodeler/Modelica. Observe the results of step input changes and external disturbances on the control performance using various types of control action. (1 period) 5. Motor-Generator Speed Control Using Proportional and Proportional/Integral Controllers Design and test a feedback control system that regulates the speed of a motor generator system. A dc tachogenerator measures the speed of the motorgenerator system. Build a proportional controller using OP AMPs to control the smotor speed as the generator load changes. Design a proportional-integral controller using OP AMPs. Compare the performance of the two systems. Also concerns observing lower steady-state error and better disturbance rejection than P. (4 periods) 6. Extending (5): effect of derivative action by constructing and evaluating a PID position controller with Constructed op-amp differentiator. 7. Extending (6) to account for both position and seed 8. Modelling of Inverted Pendulum. Balance Control of Pendulum 9. Liquid level and thermal lab. Prerequisite: Feedback Control, Probability & Statistics B 14. Robotics II: This course provides an in-depth coverage of the central topics in robotics, namely geometry, kinematics, differential kinematics, dynamics, and control of robot manipulators. The mathematical tools required to describe spatial motion of a rigid body will be presented in full. In addition, we will cover motion planning, including obstacle avoidance methods and nonholonomic systems Typical Text: Spong, Hutchinson, and Vidyasagar, Robot Modelling and Control Robotics “Toolbox” or package --> The “Toolbox” or package to provided many functions that are useful for the study and simulation of classical arm-type robotics, for example such things as kinematics, dynamics, and trajectory generation. The “toolbox” or package contains functions and classes to represent orientation and pose in 2D and 3D (SO(2), SE(2), SO(3), SE(3)) as matrices, quaternions, twists, triple angles, and matrix exponentials. The “Toolbox” also provides functions for manipulating and converting between datatypes such as vectors, homogeneous transformations and unit-quaternions which are necessary to represent 3-dimensional position and orientation. General method of representing the kinematics and dynamics of serial-link manipulators as Mathematica or Modelica or whatever objects – robot objects can be created by the user for any serial-link manipulator and a number of examples are provided for well-known robots from Kinova, Universal Robotics, Rethink as well as classical robots such as the Puma 560 and the Stanford arm. To also support mobile robots with functions for robot motion models (unicycle, bicycle), path planning algorithms (bug, distance transform, D*, PRM), kinodynamic planning (lattice, RRT), localization (EKF, particle filter), map building (EKF) and simultaneous localization and mapping (EKF), and a SystemModeler or Modelica model a of non-holonomic vehicle. Also including a detailed SystemModeler or Modelica model for a quadrotor flying robot. Additional interests: -The code to provide a point of comparison for other implementations of the same algorithms -The routines are generally written in a straightforward manner which allows for easy understanding, perhaps at the expense of computational efficiency. If you feel strongly about computational efficiency then you can always rewrite the function to be more efficient, compile the file using the whatever compiler, or create a version file in environment of choice -One would like comparison of different packages or “Toolbox” (Mathematica, Modelica, etc.) NOTE: there may be other robotics software in “Goody Bag” post to complement Grading: Homework 25% Midterm Exam 20% Project 30% Final Exam 25% Course Outline --> Chapter 1 -Introduction Chapter 2 -Translations and Rotations -Composition and Parameterization of Rotations -Rigid Motions and Homogeneous Transformations Chapter 3 -Kinematic chains, Denavit-Hartenberg parameters -Spherical wrists, workspaces -Inverse kinematics Chapter 4 -Differential kinematics and angular velocity -Jacobians -Singularities -Manipulability Chapter 5 -Configuration space, potential field -Roadmaps for planning Chapter 7 -Dynamics: Euler-Lagrange formulation -Dynamic equations of motion -Properties of robot dynamics -Dynamics: Newton-Euler formulation Chapter 6 -Single-joint control Chapter 8 -Control by feedback linearization -Adaptive/robust control Chapter 10 -Nonholonomic mobile robots -Planning for nonholonomic robots -Project presentations -Project presentations -Project presentations Prerequisites: Robotics I, Calculus III 15. Applied Robotics: I. COURSE DESCRIPTION The course introduces robotics-related technologies, including computer programming methodologies, data acquisition methods for sensors (such as infrared and optical imagers) and control methods for actuators and servo motors and microcontrollers. The subject of robotics is treated as an interdisciplinary engineering subject that includes mechanical engineering, electrical engineering, optical engineering, control theory and computer science engineering. The course addresses advanced robotic topics, including autonomous control, machine learning and applied artificial intelligence. Using a hands-on approach to applied robotics, the students in this course write their own controller programs and build their own robot prototypes based on standard microcontrollers The course material includes an introduction to programming based on C/C++ and Mathematica. The course introduces graphical processing unit (GPU) programming for achieving high-performance computing for robotic tasks and also introduces the topics of neural networks and machine-learning algorithms. The course introduces numerical methods for object detection, classification and tracking. Finally, the course provides laboratory hands-on applications of the concepts and theories presented throughout the semester. Students should have familiarity with a high-level functional programming language, such as C or C++. Familiarity with (as well as a willingness to apply) differential and integral calculus is helpful. Presented is an introduction to scientific programming based on the programming language applied to data acquisition and control of robotic subsystems. Demonstrations in the class will use symbolic mathematics (including Mathematica, etc.) and the use of a symbolic mathematics software application is highly recommended for the students as an aid to accomplishing the assigned problem sets and robotic algorithm designs. Each student will select an applied robotics topic of their choosing for a Final Project. The Final Project will entail: i. designing and building a digital/analogue robotic system for testing ii. writing a controller program for an electromechanical robotic with an optical and/or ultrasonic subsystem ii. implementing and testing the performance of the robotic system in achieving its design goal ii. explaining the tools and engineering methods used to construct and test the robotic system iii. and comparing predictions about the robotic system’s expected behaviour with the observed behaviour during testing. Each student will summarize his or her robotic system project in written Technical Report form for turn in as a final report. Basic reviews/refreshers for computer operating system and scientific programming are provided at the outset as needed. II. METHOD OF INSTRUCTION Lectures, class discussions and lab experiments Based on prerequisites for various robotics students will be asked to independently provide kinematics, dynamics and analysis of crucial applied topics from Robotics I & II. C/C++ libraries for support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. C/C++ libraries for scientific computing and technical computing. Mathematica demonstrations. Packages for controlling robots using C/C++ and Mathematica programming language. Communication using either USB or Bluetooth would be greatly appreciated. Based on prerequisites would like general tools and applications rather than LEGO because one would like foundation and experience with actual professional and versatile applications. One doesn’t want to be subjugated or determined by ideal brands and associated environments. GitHub may prove quite useful. III. PROSPECTUS i. Introduction Introduction to applied robotics, the course outline and programming foundations ii. Computer operating system, scientific programming and reporting -Introduction to the Linux operating system and the command-line language -Introduction to a program editor -C/C++ libraries, including libraries for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. Libraries for scientific computing and technical computing. Mathematica demonstrations. -Introduction to numerical arrays and parallel arithmetic -Introduction to numerical data plotting -Introduction to technical report writing and typesetting -Introduction to numerical regression techniques -Installing Raspbian OS on the Raspberry Pi 3 (or Arduino or whatever) iii. System on a chip microcontrollers -Introduction to microcontrollers (32-bit ARM-based devices or whatever) in embedded applications used in automobiles and home appliances (such as washing machines, microwave ovens, telephones, and computer system peripherals) -Controlling GPIO pins (e.g. connected to LEDs) on the Raspberry Pi 3 (or Arduino or whatever) using programming language and Mathematica -Controlling motors -Collecting sensor data (such as light-colour sensor, touch sensor, infrared proximity sensor and ultrasonic sensor) -Writing and uploading robotic control programs iv. Robotic actions and autonomous control algorithms -Robotic motion and autonomous responses -Path following, solving a Rubix cube, book scanning, and other fun problems v. Midterm -Midterm exam -In-class review of the solution set vi. General-purpose computing on graphics processing units (GPU computing) -Quad Processing Units (QPUs) on the Raspberry Pi 3 (or Arduino or whatever) -Compute Unified Device Architecture (CUDA) parallel computing platform and application programming interface model created by Nvidia; there are other open source alternatives. vii. Neural networks and machine learning -Introduction to artificial intelligence (AI)-Hopfield neural networks and associative memory -Machine learning algorithms for neural network pattern recognition viii. Object detection and classification (time permitting) -Edge detection algorithms -Nonlinear diffusion and GPU implementations -Perception and symbolic representation of physical objects ix. Final -Final exam and Student Project submitted as a Technical Report IV. PROBLEM SETS Problem sets are assigned weekly and tailored to the classes progress. Student generally have one week to complete any given assigned problem set. Selected Problem Sets will be submitted in Technical Report format using scientific typesetting software. Students will be provided with the scientific writing preparation and help. V. EXAM DETAILS NOTE: included in midterm and final exams will be programming knowledge. Such will include identifying instructions, what patches do, recognising errors and garbage, redundancy and means to correctly implement packages, etc. Exams can also include kinematics, dynamics and topics encountered in Robotics I & II. All such to complement standard exam problems, questions, etc. VI. COURSE REQUIREMENTS AND EVALUATION Problem sets, labs, written exercises, and computer robotic problems: 30% Midterm examination: 30% Final exam: 30% Class participation: 10% Prerequisites: Robotics II, Embedded Systems II 16. Autonomous Systems I: This two-quarter course will focus on Robot Motion Planning. Robot motion planning algorithms enable autonomous mobile robots to determine their movements in a cluttered environment so as to achieve a variety of goals while avoiding collisions. The ability of a robot to plan its motions without explicit human guidance is a basic prerequisite for robotic autonomy. This course will try to strike a balance between a review of the basic philosophies underpinning motion planning, practical algorithms, and theorems/proofs underlying important motion planning results. Will focus primarily on the basic theories underlying classical robot motion planning–planning when the geometry of the robot’s stationary surroundings is known in advance. Course will also introduce students to sensor-based motion planning–planning in the presence of a priori unknown or poorly known geometry of the robot’s surroundings. Course will focus on the classical motion planning framework, where the geometry of the environment is a priori known. With this theory in mind, the remainder of the course will focus on sensor-based motion planning problems, where the geometry of the robot’s environment is either a priori unknown, or poorly known. Heuristic goals: -Introduce basic robotic motion planning problems. -Provide students with a basic review of classical motion planning theory and an introduction to the most widely used classical motion planning algorithms. -Introduce sufficient terminology and concepts so that interested students can independently read the robotic motion planning research literature. -Introduce the basic concepts behind sensor-based motion planning algorithms. -Expose students practical issues involved in implementing a planner via laboratories involving small mobile robots. Some of the homeworks, and all of the labs, will require programming. There is no preferred programming language for the course, though Mathematica should suffice for most homeworks. For programming the “laboratory robots” Knowledge of C or C++ programming languages is required. Some students may choose to take advantage of the OOPSMP motion planning package which implements several of the most popular classical motion planning algorithms. However, knowledge of C++ particularly is required to most conveniently use this package; there are respected alternatives out there. Instructor probe you for (programming) academic integrity in report and with packages. The course-work will consist of 4-5 homeworks, approximately 4 – 6 labs, and a small final project. Homework: 40% Labs: 35% Final Project: 25% Typical text: Planning Algorithms by Steve LaValle (Cambridge Univ. Press, New York, 2006). The course lectures and content will roughly follow this tentative outline --> -An overview of robot motion planning problems. -Review of basic kinematics of rigid body motion. -The configuration space of a rigid body. -The classical motion planning paradigms: – the roadmap – the potential field method – the cellular decomposition and approximate cellular decomposition approaches -Graph search and discrete planning algorithms. -Sensor-Based Motion Planning Algorithms – the “Bug” algorithms – the TangentBug algorithm – the incremental Voronoi Graph – the D∗ algorithm Prerequisites: General Physics I & II, ODE, Practical Programming in C for Engineering II (or C++ Programming I & II), Probability & Statistics B; upper junior level standing. 17. Autonomous Systems II: Advanced sensor-based planning algorithms, robotic mapping and localization methods. Will extend the study of sensor-based planning algorithms, as well as introduce and incorporate the important capabilities of robotic localization and mapping. Heuristic goals: -Extend the review of sensor-based planning algorithms studied in prerequisite -Review some of the basic sensor-processing issues and algorithms needed to process the outputs of typical robotic sensors. -Enable students to implement sensor-based planning algorithms on a mobile robot. -Introduce and review the basic problems in robotic localization and mapping. -Review conventional estimation techniques (Kalman filter and Particle Filter) that underlie localization and mapping algorithms. -Review estimation-based localization and mapping techniques. -Allow students to implement a significant robot motion planning project Some of the homeworks, and all of the labs, will require programming. There is no preferred programming language for the course, though Mathematica should suffice for most homeworks. For programming the “laboratory robots” Knowledge of C or C++ programming languages is required. Some students may choose to take advantage of the OOPSMP motion planning package which implements several of the most popular classical motion planning algorithms. However, knowledge of C++ particularly is required to most conveniently use this package; there are respected alternatives out there. Instructor probe you for (programming) academic integrity in report and with packages. Programming activities will be more abundant and intense than in prerequisite. The course-work will consist of 4-5 homeworks, approximately 4 – 6 labs, and a small final project. Homework: 40% Labs: 35% Final Project: 25% Typical texts: Choset, H. et al. Principles of Robot Motion: Theory, Algorithms, and Implementations accompanied by Probabilistic Robotics (by Sebastian Thrun, Wolfram Burgard, and Dieter Fox Lynch). MIT Press, 2005. Prerequisites: Autonomous Systems I 18. Finite Element Modelling (check computational finance post) Use of Mathematica, Patran/Nastran, ANSYS AE Prerequsites: Calculus III, Numerical Analysis, General Physics I & II, Mechanics of Materials Lab, Aircraft Theory, Aircraft Design ME Prerequisites: Calculus III, Numerical Analysis, General Physics I & II, Machine Design I & II, Mechanics of Materials Lab 19. Engineering Thermodynamics Summary --> Definitions, terminology, properties of systems, pressure, temperature scale, heat and work as path dependent functions, zeroth law of thermodynamics, concept of a thermodynamic equilibrium, different kinds of work. The first law of thermodynamics, and its application to systems. Properties of a pure compressible substance, Phases & their transitions, P-V-T relation for gaseous medium, specific heats. Application of the first law to a control volume: energy relationship for flow processes. Transient flow processes. Cycles of heat engines, different kinds of processes, thermal efficiency of heat engines. The second law of thermodynamics, Corollaries of the second law of thermodynamics, reversible processes and irreversible processes. Entropy and entropy production. Entropy rate balance for a control volume. Examples of power generation systems. Typical Texts --> Fundamentals of Engineering Thermodynamics, byShapiro, Boettner, and Bailey, John Wiley & Sons Cengel, Y. and Boles, M. Thermodynamics: an Engineering Approach, McGraw Hill Reference: Reynolds, W. C. Thermodynamics. McGraw Hill Note: some problems for homework and exams will also come from the reference text. Tools --> Mathematica's ThermodynamicData. function Very resourceful Wolfram Demonstrations for thermodynamics --> Physical Sciences directory: Physics with subcategory of Statistical Mechanics, with subcategory of Thermodynamics. SystemModeler, Modelica Lab Resources --> Note: often built virtual models with simulations will be compared to experiments Granger, R. A. (1994). Experiments in Heat Transfer and Thermodynamics. Cambridge University press. Rutar, T. and Mason, G. Design of Experiments in Introduction to Thermodynamics Course. ASEE. AC 2011-1543 https://www.asee.org/public/conferences/1/papers/1543/download O’Connell, J. P. & Scott, T. C. Experiments to Accompany a First Engineering Thermodynamics Course. ASEE. Session 1613 https://peer.asee.org/experiments-to-accompany-a-first-engineering-thermodynamics-course.pdf Shepard, Thomas & George, Camille.. Desalination Design Project for Thermodynamics Lab Abstract. ASEE Annual Conference and Exposition, Conference Proceedings. https://www.researchgate.net/profile/Thomas_Shepard4/publication/288786373_Desalination_design_project_for_thermodynamics_lab_abstract/links/56cc739508ae5488f0dd0122/Desalination-design-project-for-thermodynamics-lab-abstract.pdf Refrigeration cycle (comparing simulation to experiment) Howison, J. (2019). A Simple, Economic Refrigeration Lab for Thermal/Fluids Courses. American Society for Engineering Education. Refrigeration Cycle: vapor compression system; pressure-enthalpy diagrams and tables; C.O.P. of a vapor-compression refrigeration system Grading --> Homework 15% Labs 25% 3 Exams 60% Syllabus --> --Concepts and Definitions --Mechanical Concepts of Energy, Understanding Work, Zeroth Law of Thermodynamics. --Understanding Energy and Energy Transfer by Heat --Energy Balance for Closed Systems --Energy Analysis of Cycles: Power; Refrigeration and Heat Pump --Evaluating Thermodynamic Properties --Applying Energy Balance --Using Thermodynamic Tables --ThermodynamicData from Mathematica --Introduction to Specific Heat --Generalised Compressibility Charts --Ideal Gas Laws and Combined Gas Laws --Internal Energy, Enthalpy and Specific Heat of Ideal Gases --Polytropic Process Relations --Control Volume Analysis Using Energy --Conservation of Energy for a Control Volume & Steady State --Nozzles, Diffusers and Turbines --Compressors and Pumps --Throttle Devices --Introduction To the Second Law of Thermodynamics --Applications of the Second Law of Thermodynamics --The Carnot Cycle --Entropy-A System Property --T ds Equations; Incompressible Substances and Ideal Gas --Vapor Power Systems-Rankine Cycles Course will make use of practical demonstrations and applications from thermodynamics applied to engineering. SystemModeler concerning systems and devices will be applied considerably towards relevance of laws and modelling. Prerequisites: General Physics I, Calculus III 20. Heat Transfer Study of conduction, convection, and radiation heat transfer, with applications to engineering problems. Course Outcomes: Outcome 1: To teach students the basic principles of conduction, radiation, and convection heat transfer. 1.1 Students will demonstrate an understanding of the basic concepts of conduction, radiation, and convection heat transfer. Outcome 2: To extend the basic principle of conservation of energy to systems that involve conduction, radiation, and heat transfer. 2.1 Students will demonstrate an understanding of the concept of conservation of energy and its application to problems involving conduction, radiation, and/or convection heat transfer. This principle will be used to formulate appropriate mathematical models and associated thermal boundary conditions. Outcome 3: To train students to identify, formulate, and solve engineering problems involving conduction heat transfer. 3.1 Students will demonstrate the ability to formulate practical conduction heat transfer problems by transforming the physical system into a mathematical model, selecting an appropriate solution technique, and evaluating the significance of results. Outcome 4: To train students to identify, formulate, and solve engineering problems involving radiation heat transfer among black surfaces and among diffuse gray surfaces. 4.1 Students will demonstrate the ability to formulate practical radiation heat transfer problems by transforming the physical system into a mathematical model, selecting an appropriate solution technique, and evaluating the significance of results. Outcome 5: To train students to identify, formulate, and solve engineering problems involving forced convection heat transfer, natural convection heat transfer, and heat exchangers. 5.1 Students will demonstrate the ability to formulate practical forced and natural conduction heat transfer problems by transforming the physical system into a mathematical model, selecting an appropriate solution technique, and evaluating the significance of results. Students will also demonstrate an ability to analyse the performance of heat exchangers. Tangibles --> After successful completion of this class, the students will be able to: 1) Understand the fundamentals of heat transfer processes occurring in natural and engineered systems and convey that understanding in course homework and exams. 2) Apply analytic procedures, numerical tools and problem-solving abilities to heat transfer problems such as those assigned in course homework and exams. 3) Understand and perform experimental measurement techniques for heat transfer measurements as illustrated by written laboratory reports describing methods and results. Grading: Homework: 15% Lab Reports: 25% Exam 1: 15% Exam 2: 15% Final: 30% Typical text: Fundamentals of Heat and Mass Transfer; Bergman, Lavine, Incropera, DeWitt; 7 ed. John Wiley Course Outline --> PRIMITIVES Introduction to Heat Transfer, Newton’s Law of Cooling, Elementary Modes of Heat Transfer, Lumped Capacity Modelling, Energy Balances CONDUCTION Conduction Heat Transfer, Fourier’s Law, 1-D Conduction, Fins, Multi-dimensional Conduction, The Heat Conduction Equation, Unsteady Conduction, Numerical Methods in Conduction; CONVECTION Fundamentals of Convection, Continuity, N-S and Energy Equations in BL flows, Scaling Analysis, Prandtl Number Effects, Convection Correlations, Problem Solving, Integral Methods, Internal and External Flows, Basic Principles of Heat Exchangers; RADIATION Radiation Theory, Stefan-Boltzmann law. Surface Radiation, View Factors, Solar Radiation, Kirchhoff’s Law. Directional and Spectral Characteristics of Radiation, Radiation Transfer in Engineering. Prerequisites: ODE, Numerical Analysis, Engineering Thermodynamics 21. Internal Combustion Systems: Naturally to apply knowledge of mathematics, science and engineering. Naturally to identify, formulate, and solve engineering problems. Ability to use the techniques, skills, and modern engineering tools necessary for engineering practice. An understanding of professional and ethical responsibility. The broad education necessary to understand the impact of engineering solutions in a global, economic, environmental, and societal context. Knowledge of contemporary issues There will be 5 – 8 labs with the following analysis software tools for design, operating parameters, quantitative modelling of physical measures, quantitative modelling of various components, critical modelling, operations analysis, operational curves, etc: ANSYS NASA WATE OpenWam Modelica libraries pyCycle STANJAN Mathematics, physics and engineering principles will support such lab activities. Students are responsible for proper referencing and identification with such three components, and relevant to observed data as well. For NASA WATE and OpenWam and pyCycle, activities will be detailed. Outcome 1: To teach students the operating characteristics and thermodynamic analysis of common internal combustion engine cycles. 1.1 Students will demonstrate knowledge of the operating characteristics of common IC engines. 1.2 Students will demonstrate the ability to perform a thermodynamic analysis of Otto, Diesel, and Dual cycle models. Outcome 2: To teach students to analyse the combustion process of common fuels. 2.1 Students will demonstrate knowledge of the characteristics of common liquid and gaseous fuels. 2.2 Students will demonstrate the ability to perform a combustion analysis of these fuels in the basic cycles. 2.3 Students will demonstrate an understanding of the generation of undesirable exhaust emissions and methods used to reduce them. Outcome 3: To make students aware of the roles of fluid flow and heat transfer in engine operation. 3.1 Students will demonstrate an understanding of the air and fuel induction processes. 3.2 Students will demonstrate an understanding of fluid flow in the combustion chamber and exhaust system. 3.3 Students will demonstrate an understanding of the various heat transfer mechanisms in the engine. Outcome 4: To teach students methods to mitigate engine vibration, friction, and wear. 4.1 Students will demonstrate the ability to analyse engine vibration and balancing mechanisms. 4.2 Students will demonstrate an understanding the role of lubrication in reducing friction and wear. Outcome 5: To teach students the environmental, social, and technological issues related to the future widespread use of internal combustion engines. 5.1 Students will demonstrate an understanding of environment impacts of wide-spread use of internal combustion engines. 5.2 Students will demonstrate an understanding of technological, environmental, and social impacts of alternative fuels Typical text --> Willard W. Pulkrabek, Engineering Fundamentals of the Internal Combustion Engine, Pearson Prentice Hall References --> Zeleznik, F. J. and McBride, B. J. (1985). Modelling the Internal Combustion Engine. NASA Reference Publication 1094: https://ntrs.nasa.gov/archive/nasa/casi.ntrs.nasa.gov/19850011423.pdf The Gas Turbine Handbook – National Energy Technology Laboratory. U.S. Department of Energy Topics Covered --> 1. Introduction and application survey 2. Operating characteristics 3. Engine cycles and analysis 4. Thermochemistry and fuels 5. Air and fuel induction 6. Combustion chamber fluid flow 7. Combustion 8. Exhaust flow 9. Emissions 10. Heat transfer 11. Engine dynamics 12. Friction, lubrication, and wear Prerequisite: Engineering Thermodynamics. Co-requisite or Prerequisite: Heat Transfer. 22. Powertrain Design: Check Computational Finance post Prerequisites: Internal Combustion Systems 23. Powertrain Control Systems: Check Computational Finance post Prerequisites: Systems Modelling I & II Feedback Control, Powertrain Design 24. Automated & Automatic Drivetrain: Check Computational Finance post Prerequisites: Mechanics of Materials Lab, Machine Design I & II, Systems Modelling I & II, Feedback Control, Modelling & Simulation Lab, Powertrain Design 25. Modelling, Analysis and Control of Hybrid Electric Vehicles Check Computational Finance post Prerequisites: Automatic Control, Internal Combustion Systems 26. Fluid Machinery Check Computational Finance post Prerequisites: Numerical Analysis, Practical Programming in C for Engineering I & II, Fluid Mechanics 27. Manufacturing Processes Manufacturing Processes This course focuses on basic and applied sciences in processing of materials. Specifically, effects of processing on the manufactured parts, selection of processing methods, and their relationship with material properties will be discussed. Contemporary and non-traditional processes used in manufacturing are also covered. Laboratory exercises are important components of the course. Quizzes --> There will be several unannounced quizzes given during the semester. Laboratory Assignments--> It will be necessary for some lab work to be performed outside of the scheduled lab meeting times. Sign-up sheets will be posted so that students may reserve equipment when this necessity arises. Project --> A semester project will be completed by each lab group. The project statement will be handed out within the first two weeks of class. The project is to be turned in by the given due date (TBA). Late projects will receive zero credit. Typical Text: Fundamentals of Modern Manufacturing, MP Groover, 3rd Edition, Wiley. Grading: HW & Quizzes: 10% Test 1: 15% Test 2: 20% Test 3: 20% LABS: 20% PJT: 15% WEEK 1 Ch. 1 - Introduction (Read Sections 1.3 & 1.4) Ch. 3 - Properties of Materials WEEK 2 – 3 Ch. 6 - Metals: Equilibrium Diagrams, Ferrous Alloys, Non-Ferrous Alloys WEEK 4 – 5 Ch. 27 - Heat Treatment Ch. 18 - Fundamentals of Metal Forming WEEK 6 Ch. 19 - Bulk Deformation Processes WEEK 7 Ch. 20 - Sheet Metalworking Processes, Deformation and Metalworking Cost Estimation WEEK 8 – 9 Ch. 21 - Theory of Metal Machining (and possibly some polymers) WEEK 10 Ch. 24 - Machinability and Machining Cost Estimation WEEK 11 Ch. 23 - Cutting Tool Technology WEEK 12 Ch. 22 - Machining Operations: Turning and Boring WEEK 13 Ch. 22 - Machining Operations: Drilling and Hole Making WEEK 14 Ch. 22 - Machining Operations: Milling WEEK 15 Ch. 22 - Machining Operations: Broaching, Sawing, and Filing LABS --> NOTE: safety and operations walk-through for each equipment before use. - Emergency protocols - Metrology: Vernier calipers, Steel Rule, Vernier Micrometre, Spirit Levels (types and ranges), Telescoping Gage, angular measurements, surface roughness - Process Heat Treatment - Strength Tensile (types) Impact Compressive - Treatments for Increased Strength - Alloy development Improvements and drawbacks - Bulk Deformation - Turning (metrology will come back to haunt) - Milling (metrology will come back to haunt) - Router (metrology will come back to haunt) - Lathe (metrology will come back to haunt) - Open Lab Prerequisites: General Physics I, Mechanics of Materials Lab, Calculus III, Maturity.

28. Mechanical Design Process (check Computational finance post) Prerequisites: Machine Design I & II, Systems Modelling I & II, Modelling & Simulation Lab 29. Mechanical Design (check Computational finance post) Prerequisite: Mechanical Design Process 30. Digital Fabrication (check Computational finance post) 31. Computer-Aided Design & Visualization I (check Computational finance post) 32. Computer-Aided Design & Visualization II (check Computational finance post) ***Descriptions of particular AE courses--- 1. Aerodynamics (check Computational finance post) Prerequisite: Fluid Mechanics 2. Aircraft Theory: Aerodynamics and aeroelastic forces, load and stress analysis of flight vehicles, aircraft design optimization, material selection along with, safe-life, fail-safe and damage tolerance in design. At the end of the semester, the student will be able to: · Use the fundamentals of aerodynamics and the application of the basic laws of physics to analyze problems in aerodynamics · Describe how aerodynamic forces originate in flight · Analyse how the forces are conventionally defined · Analyse how forces combine to determine airplane’s performance and stability · Describe the pitot-static concepts and how these pressures are correlated to the instrumentation readings. · Describe aircraft structural design; such as material selection, safe-life, and damage tolerance design philosophies as these relate to aerodynamics. Example Text: Fundamentals of Flight, by Richard S. Shevell, Prentice Hall. Note: may require other texts for more sensitive topics. Note: other professional sources may be required to properly treat certain subjects, that lead to credible computational ability. Labs --> i. Simulation of Bernoulli’s principles and Euler equation ii. Determine how a change in altitude affects temperature, pressure, density and the speed of sound through interactive atmosphere simulator; followed by fitting data to analytical formula. Students will also solve a problem related to dynamic pressure and the Mach number. iii. Aerofoil design. Airfoil data, wind tunnel studies (aerofoils, viscous flow & boundary layer). What analytical models are responsible for aerofoil design and aerofoil data? iv. Modelling and simulation of turbulent flow v. How lift and drag are influenced by the angle of attack. How the Lift-to-Drag ratio can provide useful information about an aircraft, such as whether it can lift a large payload or fly extended flights. Will also be data oriented. vi. Planned manoeuvres in flight simulation with acquisition of data (and curves) based on set environmental conditions, and how they relate to analytical modelling vi. Propeller propulsion: aerodynamic design of propellers and performance. Rpm and thrust, for respective propeller model. Simulating & describing contrasts in fluid flow for various propeller designs. vii. Net thrust of various types of jet engines with variable parameters. Modelling and graphs/charts: Combustive efficiency Combustive stability Energy efficiency Propulsive-performance viii. Foamboard RC airplane development and field observation Will choose a basic single prop design model to develop. There will be intimate development with geometric parameters for body. Two prototypes to be constructed, where they will differ by choice of aerofoils applied; much disparity in contrast. Both prototypes will incorporate accelerometers (speed and acceleration) and altimeter. Such three measure will be time synchronized for data acquisition. There must be identical throttle application, say, exact throttle w.r.t. lift actuation (same input lift quantity applied). Compare data from both prototypes. ix. Structural design and construction Ribs (types), stringers and spars (types) Structural members (identification of particular components) Based on such structural elements student groups will have activities of constructing such elements to constitute a body unit; to encapsulated with a skin and having stability elements. Two “vehicles” based on two unique aerofoils (much deviation between both), that will also be instituted into flight stability components. Materials range (cardboard, bendable acrylic, light wood, foam) Will test aerodynamics in open field. x. Introductory structural analysis Will design elements mentioned elements in CAD integrated to constitute vehicle units. Structural analysis with Ansys or Patran/Nastran. Evaluation --> Homework problems 15% Labs 25% 2 Mid-term Exams 30% Final Exam 30% Software in use in lectures and labs (all mandatory)--> - Mathematica - Atmosphere simulator - < DATCOM, XFLR5, Athena Vortex Lattice (AVL), XFOIL, OpenVSP VSPAERO, Open VOGEL, AVL > - < ANYS CFD, OpenFoam, Cart3d, OpenProp > - < ANSYS, Patran/Nastran > - < NASA WATE, pyCycle > FlightGear Flight Simulator Course Outline --> i. The Standard Atmosphere (with modelling, models and charts) ii. Lift and Drag Bernoulli’s Principles and Euler Equations iii. Aerofoils Physics and equations behind the effect of aerofoils Coanda Effect Aerofoil design and data. Includes use of DATCOM, XFLR5, Athena Vortex Lattice (AVL), XFOIL, OpenVSP VSPAERO, Open VOGEL, AVL iv. Viscous Flow and the Boundary Layer. Reynolds Numbers. v. Lift, Drag, Thrust and Power Calculations vi. Wing Planform Effects on the aerodynamics of a wing-tail-model. High Lift Devices. Includes use of DATCOM, XFLR5, Athena Vortex Lattice (AVL), XFOIL, OpenVSP, VSPAERO, Open VOGEL, AVL vii. Wind Tunnel Experimental Verification (with constructed apparatus) Analysis of various various aerofoils viii. Structural design and construction Ribs (types), stringers and spars (types) Structural members (identification of particular components) ix. Aero-Propulsion Propeller designs. Aerodynamics of propeller designs for thrust Blade Element Momentum Theory for propellers Combustion engine types (Fluid-thermal behaviour & modelling) Brayton cycle and Energy balance x. Determination of the following for different aircraft: Minimum distance and acceleration needed for take-off Rate of ascent w.r.t. prior two parameters Greatest altitude Maximum cruising speed at best performance altitude Maximum distance of travel Time of longest flight xi. Stability and Control Will have overview aircraft components for flight stability and control; includes geometric design for aerdynamic influence Will also have a mild introduction to models of stability and control xii. Transonic and Supersonic Flight xiii. Flight Envelope and Doghouse Plot xiv. Rotary Wing and Vertical Lift Technology xv. Review of structural design xvi. Structural Analysis. Aircraft Materials and Selection xvii. Aircraft Design Philosophies Safe Life, Fail Safe, Damage Tolerance Verification Methodologies xviii. The Design Process and Systems Engineering Prerequisites: Fluid Mechanics. Co-requisite: Aerodynamics. 3. Aircraft Design (check Computational finance post) Prerequisite: Aircraft Theory 4. Compressible Flow (check Computational finance post) Prerequisite: Aerodynamics 5. Aircraft Flight Dynamics I (check Computational finance post) Prerequisites: Aircraft Theory & Design, Aerodynamics, Systems Modelling II 6. Aircraft Flight Dynamics II: (check Computational finance post) Advance treatment is necessary for retention, competency, professionalism and readiness towards future endeavors. Prerequisites: Aircraft Flight Dynamics I 7. Advance Flight Mechanics I (check Computational finance post) Prerequisites: Aircraft Flight Dynamics II, Systems Modelling I & II, Automatic Control, Modelling & Simulation Lab 8. Advance Flight Mechanics II (check Computational finance post) Course is an advance treatment of Advance Flight Mechanics I, necessary to become well experienced, competent and professional with flight modelling. Prerequisites: Advance Flight Mechanics I 9. Propulsion Systems I: The theories and principles of jet propulsion. Thermodynamic cycles. The mechanics and thermodynamics of combustion. Turbine engine performance characteristics. Component and cycle analysis of jet engines and turbomachinery. CRUCIAL Course objectives: i. Familiarity with common types of aircraft propulsion systems. ii. Use of thermodynamic cycle analysis, including the thermodynamic treatment of chemically reacting systems. iii. Preliminary cycle design and performance analysis of propulsion systems for aircraft. iv. Working knowledge of the basic operation and design requirements of propulsion turbomachinery components (inlets, compressors, combustors, turbines, afterburners, and nozzles). Learning outcomes: i. Make design choices between jet and rocket propulsion systems based on performance issues ii. Calculate energy release, e.g., adiabatic flame temperatures, and equilibrium composition of gases at known temperature and pressure iii. Analyse the thermodynamic performance of jet engine cycles and compute relevant performance parameters iv. Perform and report preliminary design calculations to size jet engines to meet specific performance goals v. Analyse the thermodynamic performance of simple chemical and electrical rocket cycles and compute relevant performance parameters vi. Characterize the performance and operating/design constraints for inlets, compressors, combustors, turbines and nozzles NOTE: the following software will accompany thorough instruction AND designated labs of interest OpenFoam NASA WATE pyCycle MODELICA LIBRARIES STANJAN ANSYS- BladeModeler NASA SOFTWARE CATALOGUE (https://software.nasa.gov) Course Outline --> i. Overview: A. Aircraft propulsion systems B. General design goals ii. Mechanics and Thermodynamics of Gases A. Thermodynamics Review I. Systems II. Conservation/Transport equations III. Momentum conservation and thrust equations IV. Properties of perfect gases and perfect gas mixtures B. Equilibrium Chemical Thermodynamics I. Chemical energy/heats of reaction and formation II. Equilibrium composition C. Thermodynamic Cycle Analysis I. Carnot II. Brayton iii. Airbreathing Propulsion Systems A. Engine Performance Parameters I. Specific thrust II. Specific fuel consumption III. Propulsive, thermal and overall efficiencies B. Jet Engine Cycle Analysis and Performance; Cycle Design Optimization I. Ramjets II. Turbojets III. Turbofans (including optimum bypass) IV. Turboprops and turboshaft engines iv. Analysis of Turbine Engine Components A. Inlet and Nozzle Analysis, Design and Performance I. Subsonic and supersonic diffusers/inlets II. Nozzles and thrust reversers B. Combustor Analysis, Design and Performance I. Combustor configurations II. Stability, flammability operating limits III. Emissions C. Turbomachinery Analysis, Design and Performance I. Axial v. centrifugal configurations II. Euler turbomachinery equations III. Cascade analysis and single-stage performance; blade loading and flow coefficients; off-design performance and maps IV. Multistage compressors: start-up, operation and surge limits V. Turbines – compressor matching VI. Turbine materials and cooling: conduction and convection heat transfer analysis Prerequisites: Engineering Thermodynamics and Fluids Mechanics 10. Propulsion Systems II (check computational finance post) Prerequisites: Propulsion Systems I 11. Rocket Propulsion (check computational finance post) Prerequisites: Heat Transfer, Compressible Flow INDUSTRIAL ENGINEERING In addition to the IEEE having resources for various disciplines, there are various international societies that provide resources and support for Industrial Engineering. ISINDE under IAENG (International Association of Engineers) is another entity to consider. The administrations of Mechanical, Aerospace, Computer Engineering and Electrical Engineering are independent of Industrial Engineering. Note: degree programme recommends advance standing in mathematics (2 terms) Note: there will be designated courses to satisfy the Government, Humanities and History requirements in the “Winter” and “Summer” sessions as well. Core courses for Industrial Engineering: --Mathematics requirements Calculus I-III; ODE; Numerical Analysis; Optimisation; Probability & Statistics B; Mathematical Statistics --Physics requirements General Physics I & II Fluid Mechanics --Engineering requirements Intro Engineering & Design I & II; Machine Design I & II; Systems Modelling I & II; Applied Hydraulics (check CIVE); Engineering Thermodynamics --Industrial Engineering requirements Facilities Planning & Material Handling I & II; Manufacturing Systems Modelling & Analysis I & II; Quality Control; Energy Management; Reliability Engineering; Engineering Cost & Production Economics; Industrial Energy Processes Modelling; Safety Engineering --Human Factors Engineering (satisfies social/society requirement) --Business requirements Enterprise Data Analysis I & II (check FIN); Operations Management I & II (check OM/AOR); Logistics & Inventory (check OM/AOR); Service Operations Management (check RM); Operations Planning & Scheduling (check OM/AOR) NOTE: the latter 5 business courses will have the R environment, but such isn’t asking you to learn “Yucatec”. **Description of specified core courses for Industrial Engineering: 1. Facilities Planning & Material Handling I Facilities design functions, computer-aided plant layout, facility location, warehouse layout, Minimax location, deterministic and probabilistic conveyor models. This course introduces students to various aspects of facilities planning process. The objective is to provide the students with basic tools and methodologies used in this process, and to expose the students to the application of such tools. Both quantitative and qualitative tools (methods) are discussed. Outcomes --> Ability to apply knowledge of mathematics, science and engineering Measurables: 1. Students are able to use mathematical calculations in solving engineering problems. 2. Students are able to formulate engineering problems based on scientific and engineering principles. Students use operation research techniques to formulate and solve facilities planning problems. For example, they apply Integer Programming to design an optimal layout of a facility. Ability to design a system, component, or process to meet desired needs Measurables: 1. Ability to define and follow an iterative design procedure 2. Ability to think creatively Students are supposed to decide and design the right layout and material handling equipment for their projects. Identify, formulate, and solve engineering problems Measurables: 1. Ability to understand what is needed 2. Ability to formulate problems mathematically 3. Ability to build on fundamental knowledge and apply it to new situations Operations research techniques are taught in the lecture portion of this course. The students select the right technique and interpret the mathematical solution of their model to provide answers for their engineering problem. For example, graph theory is used to investigate the adjacency of production departments of a facility. Communicate effectively Measurables: 1. Effective oral presentation in senior design 2. Effective written laboratory reports 3. Effective written course project reports 4. Effective interview 5. Ability with engineering drawing Students have to present their project results by two oral and two written presentations. Knowledge of contemporary issues Measurables: 1. Knowledge of major technological issues facing society and the world 2. Appreciation for the society’s concerns with security in technology In the feasibility study phase of the term projects, the students are encouraged to select a facility, which is economically, technologically and operationally feasible. Ability to use the techniques, skills, and modern engineering tools necessary for engineering practice Measurables: 1. Demonstrate knowledge of computer usage in engineering analysis 2. Demonstrate knowledge of computer usage and technical approaches in engineering experimentation Simulation software, LP packages and other mathematical programming software tools are used to find the optimal design of material handling systems, plant layout and location. Typical texts: Facilities Planning (third edition), J. A. Tompkins, J. A. White, Y. A. Bozer, J. M. A. Tanchoco, John Wiley & Sons, 2003 Facility Layout and Location: An Analytical Approach, R. L. Francis, L. F. McGinnis, J. A. White, Prentice Hall, 1992 Supplementary text: Barker, G. B. The Engineer’s Guide to Plant Layout and Piping Design for the Oil and Gas Industries. Gulf Professional Publishing, 473 pages Software --> Autodesk Plant Design Suite GIS Mathematica R + RStudio Excel MAJOR LECTURE TOPICS --> Introduction 3 hours Computer-aided plant layout 8 hours Warehouse layout problems 8 hours Facilities location problems 8 hours Minimax layout and location problem 8 hours Deterministic and probabilistic conveyor models 10 hours LAB ACTIVITIES --> Note: lab hours are independent of lecture hours. Activities will be demanding and intense. Will start at some point during the Computer-aided plant layout module, all the way to the Deterministic and Probabilistic Conveyor models. Use of mentioned software will be related to such five latter modules. Scheduled lab activities concern strong immersion and skills building with software succeeding analytical development. The software may also possibly be a means to evaluate theory and possible operational and physical constraints not identifiable by mathematical governance. GROUP PROJECTS There will be 4 – 5 group projects involving the software based on labs progression. Prerequisites: Optimisation, Probability & Statistics B. 2. Facilities Planning & Material Handling II The prerequisite is recognised to be highly technical where repetition and sustainability are necessary to be constructive, useful and productive constituents in the field. Hence, repetition is a necessity, but done in a bit more advanced sense. Prerequisites: Facilities Planning & Material Handling I 3. Engineering Cost & Production Economics Basic principles and applications of economic decision-making between alternatives encountered in engineering systems projects. The analysis will include methodologies of economics and finance in addition to engineering fundamentals. Course provides the student with temperate mathematical, modelling, and conceptual skills to compare competing design proposals from the point of view of economic efficiency as well as engineering efficiency. Technical proposals must ultimately be expressed and measured in terms of material and development costs to provide a given product and service and those costs then measured against the likely cash flows to be generated in the market, allowing the overall profitability and financial feasibility of such projects to be assessed. Course Objectives --> -Understand the meaning of the “time value of money”, inflation, deflation, exchange rates, and interest and their application to economic analysis -Understand and apply the steps of the economic decision-making process, including defining a problem, generating solution alternatives, estimating cash flows, analysis, selection, implementation and post-implementation analysis -Be able to financially describe investment alternatives with cash flows and cash flow diagrams -Be able to estimate before tax cash flows and convert them into after-tax cash flows under the assumption of current ambiance tax law -Understand the concept of economic equivalence for the basis of comparing mutually exclusive alternatives -Be able to analyse cash flows diagrams, including finding the present worth, annual equivalent, future worth, internal rate of return, payback period, payback period with interest, and project balance -Be able to analyse a set of mutually exclusive alternatives, even if they have unequal lives, and identify viable alternatives -Understand the uncertainty inherent in cash flow analysis and be able to recognize its impact through the use of sensitivity analysis -Be able to understand risk and analyse risky projects with the use of probability theory, simulation and decision trees -Be able to evaluate multiple alternatives under constraints and with multiple attributes -Be able to solve common equipment replacement and economic life problems -Understand a government’s or municipality’s role in investment analysis and be able to apply benefit-cost analysis in these situations -Appreciate the difficulty with making a capital investment decision and understand the risk involved with such a decision Tools --> Excel R + RStudio R packages and Applied Methods FinCal, fAssets, cvar Multvariate Regression and Times Series (standard packages) Sensitivity analysis tools for regression: sensemkar Marginal Effects: margins R packages for Data Envelopment analysis and Stochastic Frontier Analysis Real Options: LSMRealOptions Mathematica Typical Text --> Hartman, J.C., Engineering Economy and the Decision-Making Process, Prentice-Hall (Pearson). Note: will also apply other literature. Skills activities bundles throughout course --> -Time value of money; future worth, present worth, NPV, internal rate of return, annual equivalent, and project balance -Discount rate (by WACC, cost of equity, APV, CAPM, Multi-factor models) -Streams of cash flow. Matching Strategy -Monte carlo for uncertainties; application to various prior activities bundles (1st, 2nd and 3rd) -Exploratory Data analysis of economic industries via data from the bureau of economic analysis. -Regression with forecasting and marginal effects. Done on multiple occasions in course tied to other mentioned activities and for assets Multivariate (OLS, Quantile, Nonlinear Quantile) -Time series: salient characteristics in data, forecasting. Done on multiple occasions in course tied to other mentioned activities and for assets). Smoothing time series data (when meaningful/appropriate) -Economic forecasting; industry forecasting; energy forecasting Quizzes --> 3 quizzes. Closed notes. Closed book. Exams --> 3 exams based on course objectives, quizzes and skills activities bundles. Mentioned tools will be necessary for some tasks. Limited amount of notes permitted during exams. Projects --> Professor will review the use/practice, models and logistics in seminar labs. Students will pursue computational development with real world projects. Will be written projects with inclusion of mathematical palette use in word processor converted to pdf files. Determine order that best compliments course progression. 1.Capital Budgeting Capital Budgeting in the Energy Industry Monte Carlo Method in Risk Analysis with Investment Projects Capital required to be at least 95% sure of having enough for a project 2.Cost-Benefit Analysis 3.Project Evaluation incorporating Inflation 4.Incorporating Risk and Uncertainty in Cost Benefit Analysis 5.Harmonizing 2 to 4 6.Data Envelopment Analysis & Stochastic Frontier Analysis NOTE: it’s important for students to develop such tools in projects with real and naturally occurring events rather than idealistic or synthetic problems. The ability to properly identify and/or conjure properties and quantitative structure in the real world with sustainability and competence can’t be acquired by idealistic or synthetic problems. Grading --> Attendance + Conduct 3 Quizzes Skills Activities 3 Exams 6 Projects Prerequisite: Enterprise Data Analysis II, Mathematics Statistics, Senior Standing 4. Energy Management: This course covers the basic principles and policies used in energy management and auditing. Proper application of these tools will improve facilities performance and operation, reduce operating costs and environmental impacts, and create a more sustainable business model. Students will learn the importance of monitoring and controlling energy and resource consumption in industrial and commercial settings. The course covers how to develop and implement energy management programs and conduct energy audits; when encountering energy data analysis subtopics to include modelling energy consumption, regression models, time series representations, and cumulative sum of variance plots. The course covers economic evaluation of energy conservation opportunities using (1) engineering economic formulas, (2) simple pay-back analysis, AND (3) life-cycle cost models. Applications for the course covers efficient operation of electric motors, lighting systems, boilers, furnaces, heater, ventilation and facilities’ climate control. The course surveys the current state of energy policy with an emphasis on LEED design and certification. Applications for the course covers efficient operation of electric motors, lighting systems, boilers, furnaces, heaters, ventilation and facilities’ climate control. Field Trips for intelligence and data gathering for course outline --> Sites: administrative offices, plants, public sector facilities, Operation of electric motors, lighting systems, boilers, furnaces, heaters, ventilation and facilities’ climate control. Term Project --> Life Cycle Assessment with OpenLCA Typical Text --> Guide to Energy Management, by Capehart, Turner and Kennedy, Fairmont Press References --> Energy Management Handbook, by Steve Doty and Wayne C. Turner, Fairmont Press Sources for Handbooks, Codes, Databases --> Global Facility Management Association (Global FM) International Facility Management Association (IFMA) International Institute of Refrigeration (IIR) + FRIDOC Database Software and Resources --> Microsoft Excel and Access and Word R + RStudio Mathematica Life Cycle Analysis (LCA) ISO 14000 Series Data sources used in LCAs are typically large databases Will identify databases and means towards assimilation Introspection, querying, etc., etc Software: OpenLCA NOTE: ability to convert developments to PDF files is required. Course Outline --> I. Introduction II. Developing Energy Management and Auditing Programs III. Electric theory, systems and measurements IV. Energy Costs and Bill Analysis V. Economic Analysis (will include LCA and LCC) NOTE: applications with such core topics include Lighting, Electric Motors, Mechanical Loads, Compressed Air & Process Systems, Office Network Systems, and factory/manufacturing systems (if not too daunting) Prerequisites: Enterprise Data Analysis I & II; General Physics I & II; Mathematical Statistics 5. Manufacturing Systems Modelling & Analysis I Course will introduce the students to an in-depth modelling and analysis of the workflow dynamics that shape the operation and the performance of contemporary production systems. At the same time, course will offer the students the experience of applying their formal background in stochastic modelling and analysis to practical problems and applications. In fact, a further intention of the course is to teach the students not only the particular models and algorithms that are covered in it, but also the thinking processes and the broader methodology that underlie the development of the presented results. Developing this skill is important for an effective application of the course material, in the face of the extensive complexities and intricacies of the modern production systems. Textbook: G. L. Currry and R. M. Feldman (2011). Manufacturing Systems Modelling and Analysis (2nd ed.), Springer. The above text will be a substantial base for the course development. Additional supplementary material will be provided either in class, or through a course website accessed from the instructor’s homepage, or through the library electronic reserves (in case that copyright clearance is necessary). Labs --> The lecturing text provides strong structuring and modelling. Nevertheless, one would like to some capacity encourage imagination and interactive tasks rather than only a shallow or mathematically mundane environment that destroys interest. Hopefully, there is strong connection between lectures and resources such as the following: - https://people.umass.edu/jmgsmith/lab/lab/software.htm - SIMPROCESS (if tangible and practical) - Tecnomatix Plant Simulation (if tangible and practical) NOTE: students should also be able to apply Mathematica or R alongside manual development with lectures and notes, and labs. Grading Scheme --> Homework: 15% Labs: 20% Midterm Exam I: 20% Midterm Exam II: 20% Final Exam: 25% Course Outline --> I. Introduction: Course Objectives, Context, and Outline Manufacturing System as a Transformation Process, Operations Management, and the role of Corporate Strategy Contemporary high-volume (discrete-part) manufacturing systems and their modelling as stochastic systems A taxonomy of the considered manufacturing systems based on their workflow management: Synchronous vs. Asynchronous, and Push vs. Pull and CONWIP models Course overview II. Design of Synchronous Manufacturing Systems/Assembly Line Balancing III. Modelling, Analysis and Design of Single-Station, Push-Controlled Manufacturing Systems as G/G/m queues IV. Modelling Pre-emptive and Non-Pre-emptive Operational Contingencies V. Extension of the results to multi-stage, single-product, push-controlled manufacturing systems VI. Modelling and analysis of multiple-product manufacturing systems VII. Batching schemes and their complications VIII. Modelling and analysis of certain pull-controlled manufacturing systems as closed queueing networks IX. Introduction to (combinatorial) scheduling theory Prerequisites: Systems Modelling I & II, Probability & Statistics B, Optimisation 6. Manufacturing Systems Modelling & Analysis II Practice and competency are needed. Maturity and professionalism with more experience. Prerequisite: Manufacturing Systems Modelling & Analysis I 7. Quality Control A comprehensive coverage of modern quality control techniques to include the design of statistical process control systems, acceptance sampling, and process improvement. Leraning Outcomes: i. Understand the philosophy and basic concepts of quality improvement. ii. Describe the DMAIC process (define, measure, analyse, improve, and control). iii. Demonstrate the ability to use the methods of statistical process control. iv. Demonstrate the ability to design, use, and interpret control charts for variables. v. Demonstrate the ability to design, use, and interpret control charts for attributes. vi. Perform analysis of process capability and measurement system capability. vii. Design, use, and interpret exponentially weighted moving average and moving average control charts. Course Assessment --> A. There will be 3 - 5 quizzes. You are allowed to drop one of 10 quiz scores. Therefore, the quiz portion of your grade will be 20% of your course grade and will be calculated using the average of your best nine quiz scores (each quiz is equally weighted). There will be no make-up quizzes except in the cases noted below (see fourth bullet point). B. Homework problems for each chapter will be assigned but will not be collected or graded; encourage discussions. Completing the homework problems is definitely an excellent way to prepare for the quizzes and exams. C. There will be three mid-term exams and one final exam. All exams are open book and closed notes. Using any other resources during exams is not allowed. Students are allowed to bring a calculator during exams. There will be no make-up exams except in the cases noted below (see fourth bullet point). Technology Requirements --> Scientific calculator Internet access to the course web site Mathematica R (qcc, qcr, ggQC) and others Microsoft Excel Grading --> 3-5 Quizzes 15% 3 Exams 45% Computational Labs 25% Final Exam 15% Texts in Unison --> Montgomery, Douglas C. (2009). Introduction to Statistical Quality Control, John Wiley & Sons Cano, E. L. et al (2015). Quality control with R: An Iso Standards Approach. Springer Santos-Fernández, E. (2013). Multivariate Statistical Quality Control Using R. Springer Topics--> -Quality Improvement in the Modern Business Environment (Chapter 1) -The DMAIC Process (Chapter 2) -Methods and Philosophy of Statistical Process (Chapter 5) -Control Charts for Variables (Chapter 6) -Control Charts for Attributes (Chapter 7) -Process and Measurement System Capability Analysis (Chapter 8.1-6) -Exponentially Weighted Moving Average and Moving Average Control Charts (Chapter 9.2-3) Course Outline --> WEEK 1 Course Introduction Definitions of Quality and Quality Improvement WEEK 2 Statistical Methods and Management Aspects for Quality Control and Improvement WEEK 3 – 4 The DMAIC Process WEEK 4 – 5 Statistical Process Control WEEK 6 SPC-The Magnificent Seven Applications of SPC WEEK 7 – 8 Control Charts for Variables WEEK 9 Control Chart for Individual Units Applications for Variables Control Charts WEEK 10 – 11 Control Charts for Attributes Choice between Attributes and Variables Control Charts WEEK 12 Process Capability Analysis WEEK 13 – 14 Process Capability Ratios/Analysis Exponentially Weighted Moving Average Control Chart WEEK 15 Moving Average Control Chart Prerequisites: Mathematical Statistics and Upper level standing 8. Reliability Engineering Reliability is a product or system’s capacity to perform as intended, without failure and within specified performance limits, for a specified time in its lifecycle conditions. Knowledge of reliability concepts and principles, as well as risk assessment, mitigation, and management strategies prepare engineers to contribute effectively to product development and life-cycle management and product safety. Problems about bulbs with normal distribution and hypothesis tests are often counterfeit or “con artists” idealistic. Instruction Textbooks --> Kailash C. Kapur, Michael Pecht, Reliability Engineering, John Wiley & Sons Tobias, P.A., Trindade, D.C. Applied Reliability, 3rd Edition, CRC Press O'Connor, Patrick D. T, Practical Reliability Engineering, John Wiley & Sons Some idea of things (but not course instruction): https://www.tce.edu/sites/default/files/PDF/Reliability-Engg.pdf Journal articles --> Journal articles in topic area are also viable Databases --> There are databases such as MIL-HDBK-217F, OREDA, and NPRD-95. Also, Kaggle has predictive maintenance databases. Mathematica may provide. Sources are not limited to the mentioned prior however. Software --> Mathematica R (WeibullR, SPREDA, openreliability.org and others) Excel Specialized software may also be possible Design Projects (DP) in Teams (case studies) --> Case Study Deliverables: DP1: Design project proposal (and presentation) DP2: Reliability measures and reliability block diagrams DP3: List of potential failures, risks from published databases DP4: FMEA results DP5: FTA & ETA results DP6: FRACAS reports DP7: Summary report for case study putting all the results together (presentation) Examples: Morteza Soleimani, et al, "Design for Reliability of Complex System: Case Study of Horizontal Drilling Equipment with Limited Failure Data", Journal of Quality and Reliability Engineering, vol. 2014, Article ID 524742, 13 pages, 2014 Nascimento, D. C., Ramos, P. L., Ennes, A., Cocolo, C., Nicola, M. J., Alonso, C., Ribeiro, L. G., & Louzada, F. (2020). A Reliability Engineering Case Study of Sugarcane Harvesters. Gestão & Produção, 27(4), e4569 Note: designated teams will be assigned a case study project chosen by instructor. Teams will schedule meetings with instructor on progress and to acquire insights. Industries, engineering fields and consumer products for case studies will be broad. Assessment --> Homework Computation and data analysis labs 4 Exams Team Project Prerequisites: Mathematical Statistics and Senior Standing 9. Human Factors Engineering A survey of Human Factors and Ergonomics with particular reference to human-systems integration and human functions in human-machine systems. We consider basic human capabilities and the ways that these capabilities are taken into account in the design of human-machine systems and work environments. Note: satisfies social/society requirement SLOs --> --the principles, assumptions, and methods on which the discipline of Human Factors is based --the systems approach and its implications for human factors --types of human error and the factors that influence their likelihood --facts and theories regarding human perception, cognition, and action and their implications for design --physical and environmental factors that need to be taken into account when designing for human use --specific methods, such as mental workload analysis for evaluating alternative designs --the steps for implementing human factors and ergonomics programs within organizations. Recommended Procedure --> 1. Read the assigned material from the course outline before the class for which it is assigned. 2. If you have questions pertaining to homework, you should consult with a teaching assistant (or whoever) first. Course Text --> R. W. Proctor & T. Van Zandt (2008), Human Factors in Simple and Complex Systems. Boca Raton, FL: CRC Press. Homework Projects (Groups) --> Homework projects will be assigned weekly. The projects should not copied from other groups. The cumulative grade for the projects will be the equivalent of an exam grade. Assessment --> Three exams will be held, each covering approximately 1/3 of the course. The last of these exams will be the final examination, which will not be comprehensive. The course grade will be determined from the three exam grades and the homework projects grade, each of which will be worth 25%. Course Topics --> Chapters: 1 – 19 Prerequisites: Upper level Standing 10. Safety Engineering This course concerns upper level IE students who in profession must serve in a holistic view. Occupational safety engineering and management with emphasis on control of hazardous materials, fire prevention, safety considerations in production facility design and maintenance, and operation of effective safety programs. Exposing students to the regulatory and professional aspects of occupational safety. Law and ethics are stressed throughout the course. Engineering skills are reinforced by requiring students to apply basic engineering principles to safety related problems. An 18 weeks course Typical Text --> Safety and Health for Engineers, by Brauer. John Wiley & Sons, Inc. Supporting Text --> Ericson, C. A. (2016). Hazard Analysis Techniques for System Safety. New York: Wiley. Note: may be more extensive for HAT than typical text. Tools --> Scientific Calculator Grading --> Homework 3-4 Quizzes Exam I Exam II Field Trips Intelligence Gathering Course Project Chapters for consideration in the following order: 4, 5, 3, 9, 10-13, 15, 16, 29, 17, 18, 23, 24, 28, 22, 31, 32, 34 Field Trips Intelligence Gathering --> Production facilities design and operations profiles. Occupational Safety and Health Administration standards; safety routines at different levels; risk management; hazard identification and elimination; hazard communication; gov’t agencies relevant to sites’ legal operation with metrics for appeasement. Professional licenses & certification, etc., etc. Students’ effort and maturity will have critical roles. Instructor will eventually administer a recknoning questionnare on safety standards relevant to sites visited; various accepted guidelines and standards to structure questionnare. Course Project --> 3-5 person student teams will be required to complete a system safety engineering analysis project. Teams will be permitted to select from a variety of real-world case studies (e.g., Indian Point Meltdown, Three-mile Island Unit 2 Plant meltdown, Love Canal tragedy, Space Shuttle Challenger incident, BP Horizon Rig accident, ammonium nitrate incidents, etc., etc., etc.) to align with their area of interest. Projects will require a literature on the incident, identification of various types of hazards that were present in the system, application of a systems safety analysis method based on published data, reporting of results of the method, and inferences and conclusions on how hazard exposures could have been reduced. Prerequisite: IE Senior Standing 11. Industrial Energy Processes Modelling Fundamentals and various levels of analysis of energy management of commercial buildings and industrial processes and buildings. Providing the knowledge and comprehension of need and techniques to maximize the utilization of energy, thus, leading to the implementation of the resulting skills acquired. The ability to apply the principles of thermodynamics and heat transfer to systems. Rigorous training in exergy and exergy analysis for evaluating industrial and commercial usage of energy. Case studies – Boilers, Furnaces, Cycles, IGCC plants, buildings, factories, agricultural, process industry – cement, natural gas power plants, renewables, etc. etc. An 18 weeks course with at least 2 lecture days per week, with 2 hours per lecture. Labs to be 2-3 hours per session. Primary Course Texts: Various literature (documents, articles, texts) Complement Engineering Thermodynamics texts (from prerequisite) NOTE: remain sharp with your prerequisites. Tools to apply rigorously --> DWSIM, COCO and Chemsep SystemModeler +Modelica libraries Excel R + RStudio Mathematica Additional tools in course --> NREL System Advisor Model (SAM) RETScreen Hybrid2 Life Cycle Analysis (LCA) ISO 14000 Series Data sources used in LCAs are typically large databases Will identify databases and means towards assimilation Introspection, querying, etc., etc Open Source Software: OpenLCA and other alternatives Life Cycle Costing ISO 15686-5:2017 Kneifel, J. and Webb, D. (2020). Life Cycle Costing for the Federal Energy Management Programme. NIST Handbook 135 Assessment --> Homework 15% Quizzes 10% Labs + Field activities 35% 2 of 3 Exams 20% Final 20% Course Outline --> -Review of the tools of Engineering Thermodynamics -Energy Analysis -Exergy & Exergy Analysis -Energy Carriers (ISO 13600 series) -Energy Accounting/Audits Professionals to lecture on thorough and practical development for data acquisition and reporting. Will also be field-based activities with plants, factories, buildings, etc, etc. -Data analysis with energy statistics (national, provincial, cities, districts, industrial sectors, manufacturing sectors, etc., etc.) Will have labs for data analysis, regression models, time series and stochastic modelling -Calculations and Simulations in Engineering Heat Transfer Will have overview of general models, then focus on geometries relevant to boilers, heaters and other forms of industrial combustion, e.g. in furnaces and kilns. Geometries may or may not be simple; CAD accompanied by CFD and FEA may be entertained for complex geometries, material properties and atmospheric/environment conditions, etc. -Fundamentals of Combustion and Heat Losses (boilers, heaters, and other forms of industrial combustion, e.g. in furnaces and kilns) Processes and products HHV and LHV; relation between heating values Will have labs (with an array of safe substances to prove the points) Dry flue gas loss (LDG) Loss due to moisture from the combustion of hydrogen Calculating boiler efficiency (LH) Loss due to radiation and convection (LR) Losses that are unaccounted for (LUA) Heat Transfer Efficiency HTE (HTE) HTE = 100 – (LDG+LH+LR+LUA) Note: for HTE prior heat transfer activities may be crucial -Introduction Process Design (encompassing, tangible and fluid) Will be introduced to some conventional industrial processing systems System types (chemical, agricultural, renewable fuels, electricity production, etc., etc.) Identification & uses Materials, products and by-products Components descriptions, modelling and controllers design Labs to develop and simulate typical systems System modelling, transfer functions, controllers design DWSIM, COCO, Chemsep, SystemModeler, etc. HTE (wherever practical) Energy Conversion Efficiency (ECE) May not be solely thermal Operation components and total -Pinch Analysis (must be tangible, practical and fluid with chosen applications) Will be thorough in development Involves design optimisation. Analysis with COCO (+ ChemSep), DWSIM (+ ChemSep) or SystemModeler Ideas to build on --> Kemp, I.C. (2006). Pinch Analysis and Process Integration: A User Guide on Process Integration for the Efficient Use of Energy, 2nd edition. Includes spreadsheet software. Butterworth-Heinemann. Ebrahim, M.; Kawari, Al- (2000). "Pinch Technology: An Efficient Tool for Chemical-Plant Energy and Capital-Cost Saving". Applied Energy. 65 (1–4): pages 45–49 Additional ideas Pinch analysis: For the Efficient Use of Energy, Water & Hydrogen, Natural Resources Canada http://cepac.cheme.cmu.edu/pasilectures/bagajewicz/BagajewiczHeatIntegration.pdf -Gasification -Integrate Gasification Combined Cycle (IGCC) Reviewing modelling and controllers development for various system components Lab development (DWSIM, COCO, Chemsep, SystemModeler) HTE and ECE Compare with the older alternatives (materials, efficiency, energy consumption, etc.) -Cogeneration Reviewing modelling and controllers development for various system components Lab development (DWSIM, COCO, Chemsep, SystemModeler, etc.) HTE and ECE -Natural Gas Powerplants Simple cycle Combined cycle The Gas Turbine Handbook – National Energy Technology Laboratory. U.S. Department of Energy Cogeneration schemes -Load Duration Curves Means to help plan for electrical utilities and other grids Data acquisition skills Maybee, J., Randolph, P. & Uri, N. (1979). Optimal Step Function Approximations to Utility Load Duration Curves. Engineering Optimization, 4:2, 89-93 Data analysis for planning -Corn Processing Dry Milling Identification, goals/products, processes Modelling, transfer functions and simulation (DWSIM, COCO, Chemsep, SystemModeler) HTE and ECE Wet Milling Identification, goals/products, processes Modelling, transfer functions and simulation (DWSIM, COCO, Chemsep, SystemModeler) HTE and ECE -Multigeneration Assisting literature: Dinçer I., Zamfirescu C. (2011) Integrated Multigeneration Energy Systems. In: Sustainable Energy Systems and Applications. Springer Dinçer I., Rosen, M. A. and Ahmadi, P. (2017). Chapter 11, Modelling and Optimisation of Multigeneration Systems. In: Optimisation of Energy Systems. Wiley Dincer, I. and Bicer, Y. (2019). Integrated Energy Systems for Multigeneration. Elsevier Science Evrin R.A., Dincer I. (2020) A Novel Multigeneration Energy System for a Sustainable Community. In: Dincer I., Colpan C., Ezan M. (eds) Environmentally-Benign Energy Solutions. Green Energy and Technology, Springer Identification, goals/products, processes Modelling, transfer functions and simulation (DWSIM, COCO, Chemsep, SystemModeler) HTE and ECE -Renewable Energy Systems Types System macro components Modelling and simulation of grids SystemModeler/Modelica libraries NREL System Advisor Model (SAM) RETScreen Hybrid2 HTE and ECE -Emissions Emission factors Emission estimation protocol (plants, refineries, factories, etc., etc.) Hierarchy of emission measurement or estimation methods for various petroleum refinery (and other) emission sources, and provides a listing of pollutants for which emissions are anticipated for each source type There will be labs to treat various past systems that were modelled and simulated. The following source can assist with labs, where software identified from such source likely may not treat every system however, hence manual pursuits for such cases: https://www.epa.gov/air-emissions-factors-and-quantification/emissions-estimation-tools -Energy Audit (EA) Review of field in energy accounting as guide for time efficient and accurate identification, profiling and record for energy systems EA being a process to reduce the amount of energy input into the system without negatively affecting the output Scheduled field activities -Energy Management Practices -Economic Analysis Will borrow some measures from regional economics to identify leading industries and industries responsible for stability; trend in chosen measures as well for long term outlook. Energy Resource Dynamics (to develop for chosen systems): https://www.wolfram.com/system-modeler/examples/energy/energy-resource-model.html Following prior will assume ideal conditions and determine pay back periods. Economy forecasting/outlook (methods and tools will be applied) Energy forecasts (methods and tools will be applied) in industries subject to economy forecasting Fossils fuels Loads Renewables For particular case studies based on all priors will have profiling of distribution channels and/or operations to develop a Life Cycle Assessment and Life Cycle Costing. Petrecca G. (1993) Principles of Economic Analysis of Energy-Saving Investments. In: Industrial Energy Management. Power Electronics and Power Systems. Springer Yen-Haw Chen et al, Economic Analysis and Optimal Energy Management Models for Microgrid Systems: A Case Study in Taiwan, Applied Energy, Volume 103, 2013, Pages 145-154 -Risk Exposure in Energy Tasks will be based on real data and computation: Díaz, A., García-Donato, G. and Andrés Mora-Valencia, A. (2019), Quantifying Risk in Traditional Energy and Sustainable Investments, Sustainability, 11, 720 Algieri, B. and Leccadito, A. (2020). CARL and His POT: Measuring Risks in Commodity Markets. Risk, 8, 27 -Energy Derivatives S.J. Deng and S.S. Oren. (2006). Electricity Derivatives and Risk Management. Energy 31, pp 940–953 Pineda, S., Conejo, A.J. (2013). Using Electricity Options to Hedge against Financial Risks of Power Producers. J. Mod. Power Syst. Clean Energy 1, 101–109 -Case study: winter storm in Texas (USA) 2021 and energy grid failure (equipment, service) and massive utility bills. What instruments lead to observed price shocks? Note: there may be other cases. Prerequisites: Enterprise Data Analysis I & II, Energy Management; Engineering Thermodynamics, Mathematics Statistics, Senior Standing NOTE: from CIVE the following activities are open to IE constituents: --Transportation Planning: Methodology and Techniques --Piping Design and Systems in the Energy Sector --Industrial Hydraulic Systems --Life Cycle Costing --Revolutionary Air Conditioner --Solar Powered Air Conditioner NOTE: Project Management activity in Economics-Political Science-Public Administration-Business post open to IE students

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CHEMISTRY

GENERAL BIOLOGY I, GENERAL CHEMISTRY I & II, ORGANIC CHEMISTRY I & II, POLYMER CHEMISTRY, ANALYTICAL CHEMISTRY to be accompanied by lab instruction; other courses with given syllabuses to have lab instruction if expressed. CHEMISTRY degree Students will progress based on the prerequisites successfully completed with minimal grade requirement. Chemistry curriculum is not ignorantly focused on organic chemistry, else, you’ve never observed the periodic table. It may be in the student’s best interest that General Education appeasement courses be fulfilled during the “summer” and “winter” sessions, or student to acquire advanced standing upon matriculation. Curriculum: --Mandatory Courses Calculus for Science & Engineering I-III, Ordinary Differential Equations, Probability & Statistics B, Data Programming with Mathematica, Mathematical Statistics. --Foundational Courses Scientific Writing I & II, General Biology I, General Chemistry I & II, Biochemistry, General Physics I & II --Essential Chemistry Career Requirements Analytical Chemistry; Organic Chemistry I; Inorganic Chemistry I; Environmental Chemistry; Chemical Physics I; Instrumental Analysis; Instrumental Analysis Lab; Process Dynamics & Control I & II, Spectroscopy; Chemistry Research (upper Senior level). --Organic Option Track: Organic Chemistry II; Organic Synthesis Laboratory; Advanced Organic Synthesis Laboratory; Polymer Chemistry; Advanced Topics in Polymer Chemistry. --Computational Option Track: Numerical Analysis (check COMPUT FIN post); Inorganic Chemistry II; Chemical Physics II; Molecular Modelling; Stochastic & Statistical Methods for Molecular Modelling. NOTE: for mathematics courses refer to Computational Finance post; for Physics courses refer to the physics post. Description of certain chemistry courses: General Chemistry I A first semester general chemistry course for students who have a reasonable background in high school chemistry. Proficiency in high school algebra (including solving for unknown variables, manipulating exponentials and logarithms, operating a calculator, etc.) is expected. Range of topics to be covered: Please note that this course is not a review class and is quite rigorous. Assessment --> 5 Recitation Quizzes 15% Homework + In-class activities 10% 2 Exams 30% Final Exam 25% Laboratory 20% Pre-Labs/Notebooks 0.15 Post-Labs 0.5 Lab Performance 0.1 Abstracts 0.15 Quizzes 0.1 Pre-Labs: Should be turned in before the start of lab. Late pre-labs will NOT be accepted. Notebooks: Each week before coming to lab, students should read the ENTIRE lab and write the appropriate notebook entry. See the Lab Manual for a description of what to include. Before you leave lab each week you will also be required to make a small entry about what you just complete. Be sure to check in with your instructor before leaving. Post – Labs: Each week there will be an assignment to be completed after the lab. This includes calculations and conclusions from your experiment. Be sure to carry out these calculations carefully and think about what you are analysing. Lab Performance: Grades will be based on the following: established rules, lab neatness, class participation, preparedness for lab (proper clothing, etc). In some labs you will be graded on how accurate your results are. Careful lab performance is important. Abstracts: Each week, students will write an abstract describing the previous week’s experiment. See the Lab Manual for how to write an abstract. These should be typed and printed for hand in. Quizzes: Each week there will be a short quiz about the lab for the day. If you read the lab before coming to lab, and completed the pre-lab assignment you should be able to answer the quiz questions. Curse Literature --> Ebbing and Gammon. General Chemistry 11th edition. Belmont: Brooks/Cole Cengage Learning, 2016 Moog & Farrell. Chemistry: A Guided Inquiry (Wiley), 2018 Course Materials --> Lab Manual Lab Notebook Scientific calculator Lab coat or apron Safety goggles Access to a graphing software program (Excel and Mathematica) Week 1. The Periodic Table and Nomenclature Week 2. Limiting Reactants & Stoichiometry Week 3. Solution Stoichiometry. Reactions in Solution Week 5. Kinetic Molecular Theory of Gases EXAM 1 Week 6 Thermochemistry Week 7. Thermochemistry. Quantum Theory Week 8. Quantum Theory Week 9. Periodic Trends EXAM 2 Week 10. Exceptions to the Octet Rule Week 11. Bonding a la Pauling: Valence Bond Theory Week 12. Molecular Orbital Theory Week 13. Phase Transitions FINAL EXAM Course Activities --> Atomic Structure The Mole Concept Empirical Formula Chemical Equations Molarity The Ideal Gas Law Enthalpy Changes in Chemical Reactions Electromagnetic Radiation Photoelectron Spectroscopy The Shell Model Electron Configurations and the Periodic Table Lewis Structures I – III Molecular Shapes Covalent Bonds and Dipole Moments Hybrid Orbitals Intermolecular Forces Lab Schedule --> Intro to Lab, Learning Excel/Mathematica Accuracy of Liquid Measuring Devices Avogadro’s Number and Moles Preparation of Magnesium Oxide Synthesis of Alum from Scrap Aluminium Chemical Reactions Gas Laws Hess’s Law Analysis of the Silver Group Cations Copper Cycle Vinegar Titration Beer’s Law Lewis Structures and Molecular Geometries Makeups General Chemistry II Second semester of General Chemistry sequence. The lectures cover the topics kinetics, equilibrium, acids, bases, thermodynamics, redox reactions, electrochemistry, and nuclear chemistry. Quizzes --> Weekly quizzes covering lecture material where lowest quiz grade to be dropped. Quizzes will be a combination of questions from prerequisite and current material of course. Exams --> Three exams (given during the lecture period) and a cumulative final are given. will be a combination of questions from prerequisite and current material of course. The lowest exam grade is dropped. Labs --> The lab experiments supplement and coordinate with the lecture topics. Prelab assignments (pre-study) must be done and handed in the X day before the lab is done; points are deducted if late. Lab reports involve filling in the report sheets in the lab manual, writing a title page, and an abstract page and are due a week after the lab is done unless otherwise indicated. The lowest pre-study and lab report grades are dropped. Chemistry On-line tools --> Required and is worth an exam grade. The assigned topics must be done online by the due date (day of final exam) for credit (100 points maximum). Your notes and course literature will serve towards assistance. The grade is based on overall percent correct of all assigned problems. Missed exams, quizzes or lab experiments will count as a drop. Course Literature --> General Chemistry, 9th Edition, Chang, 2007 Course Materials --> Lab Manual Lab Notebook Scientific calculator Lab coat or apron Safety goggles Access to a graphing software program (Excel and Mathematica) Course Outline --> Review of Basic Concepts Molarity Beer’s Law and Parts per Million calculations Chemical Kinetics Definitions and rate expressions Nature of reactants and reaction rate Concentration and temperature effects on reaction rates Reaction mechanisms Order of reaction and graphing in kinetics Activation energy and Catalysis Chemical Equilibrium Definition and conditions of equilibrium Law of Mass Action The equilibrium constant, Kc and Kp Le Chatelier's Principle: Factors affecting equilibrium Calculations and interpretation of Q and K EXAM 1 Acids and Bases Water dissociation; acid-base theories Strong and weak acids and bases Conjugate acids and bases The pH scale Acid/base dissociation constants, Ka and Kb Hydrolysis; Acidity and Basicity of Salts Acid-Base and Solubility Equilibria Buffer solutions, calculations and preparation Titration curves The solubility product constant, Ksp Fractional precipitation The common ion effect The effect of pH on solubility 19 EXAM 2 Chemical Thermodynamics: Entropy, Free Energy, Equilibrium The Three Laws of Thermodynamics Entropy, definition and calculations Gibbs free energy, definition and calculations Spontaneity of physical and chemical processes Free energy and equilibrium Electrochemistry Oxidation numbers of elements in compounds Definition of oxidation and reduction Balancing oxidation-reduction equations Redox Titrations Standard reduction potentials Voltaic and electrolytic cells EMF calculations and Nernst equation Cell voltage and free energy changes Cell voltage and equilibrium constants Electrolysis Nuclear Chemistry Nuclear Particles and Radioactivity Half-life and Dating Techniques Binding Energy, Fusion, Fission Kinetics of radioactivity and radiocarbon dating EXAM 3 FINAL EXAM Lab Schedule --> Check-In, Safety Spectroscopy: Beer's Law Ca Analysis by EDTA Titration Phenolphthalein-NaOH Kinetics Equilibrium Constant Determination Le Chatelier's Principle Ca Analysis by Atomic Absorption Group A Cation Analysis Group B Cation Analysis pH: Its Measurement and Uses Enthalpy of Neutralization Thermodynamics of Borax Dissolution Fe Analysis by Redox Titration Electrochemistry. Check-Out Prerequisite: General Chemistry I Organic Chemistry I In-depth study of: (i) The structure of organic compounds and the functional groups (bonding, acid-base properties, nomenclature, conformations, stereochemistry), and (ii) The synthesis and reactivity (including detailed mechanisms) of alkanes, alkenes, alkynes, halides, alcohols, ethers, epoxides, sulfides and organometallic reagents. Laboratory experiments are related to topics covered in lecture and emphasize organic laboratory techniques, synthesis and spectroscopic characterization of organic molecules. Typical Texts: McMurry, John E. Organic Chemistry. 8th Edition. Brooks/Cole, 2012. McMurry, Susan. Study Guide with Student Solutions Manual. 8th Edition. Brooks/Cole. Typical Lab Manual: Barbaro, John and Richard K. Hill. Experiments in Organic Chemistry. 3rd Edition, Contemporary Publishing Company of Raleigh, Inc., 2006 Grading: Quizzes (prerequisite tasks + course level) 2 Exams Cumulative Final Exam Labs +Lab Quizzes (On the occasion of significant improvement on the final exam, more weight will be placed on the final exam) INSTRUCTIONAL METHODS: List the different instructional methods you might use, in the course of the semester. List supplementary learning options, if any: Traditional lecture with use of chalkboard Computer assisted diagrams and graphics Molecular Models Team work in the laboratory Homework assignments Solving specific questions related to content studied Written exams and distribution of study questions/previous exams Use of the Internet UNIQUE ASPECTS OF COURSE (such as equipment, specified software, space requirements, etc.): Organic chemistry laboratories and their associated equipment, instruments and chemicals. Apart from use of software in lectures, students will use software to accompany experiments that provide detailed molecular/compound structure, target sites, functional groups, reaction (quantities, parameters), etc. etc. etc. Such exhibits will be in lab reports. Lecture Outline --> Ch. 1 Structure and Bonding Bonding; Hybridization; Drawing Chemical Structures; Functional Groups; Intro to IR Spectroscopy Ch. 2 Polar Covalent Bonds; Acids and Bases Chemical Bonding (Ionic and Covalent); Electronegativity and Dipole Moments; Formal Charges; Resonance Structures; Acid Base Theory (Bronsted-Lowry, Lewis); Acid and Base Strength (pKa); Acid-Base Reactions; Organic Acids and Organic Bases Ch. 3 Organic Compounds: Alkanes and their Stereochemistry Alkanes, Alkane Isomers, and Alkyl Groups; Properties of Alkanes; Conformations Ch. 4 Organic Compounds: Cycloalkanes and their Stereochemistry Cis-Trans Isomerism in Cycloalkanes; Stability and Conformations of Cycloalkanes; Chairs Ch. 5 Stereochemistry at Tetrahedral Centres Enantiomers, the Tetrahedral Carbon and Chirality; Optical Activity; R/S Sequence Rules; Diastereomers and Meso Compounds; Racemic Mixtures, Resolution of Enantiomers; Prochirality; Chirality in Nature Ch. 6 An Overview of Organic Reactions Kinds of Organic Reactions (Radical and Polar); Mechanisms; Describing a Reaction (Equilibria, Rates, Energy Changes, Bond Energy; Transition States, and Intermediates) Ch. 7 Alkenes: Structure and Reactivity Preparation and use of Alkenes; Cis-Trans Isomerism; Alkene Stereochemistry and E/Z Designation; Stability of Alkenes; Electrophilic Addition Reactions; Markovnikov’s Rule: Carbocation Structure and Stability; Carbocation Rearrangements Ch. 8 Alkenes: Reactions and Synthesis Preparation of Alkenes via Elimination Reactions; Addition Reactions of Alkenes (Halogenation, Hydration, Halohydrins, and Hydrogenation); Oxidation of Alkenes (Epoxidation and Hydroxylation); Addition of Carbenes; Radical Additions to Alkenes (Polymer Formation); Reaction Stereochemistry Ch. 9 Alkynes: An Introduction to Organic Synthesis Preparation of Alkynes; Addition Reactions of Alkynes (X2, HX, H2O, H2); Oxidative Cleavage; Alkyne Acidity and Alkylation; Introduction to Organic Synthesis Ch. 11 Reactions of Alkyl Halides: Nucleophilic Substitutions and Eliminations SN2, SN1, E2, E1, E1cB Reactions; Zaitsev’s Rule; Deuterium Isotope Effect Ch. 10 Organohalides Preparation of Alkyl Halides and Grignards; Radical and Allylic Halogenation; Organic Coupling Reactions, Redox in Organic Chemistry Ch. 17 Alcohols and Phenols Properties of Alcohols and Phenols; Preparation and Reactions of Alcohols; Reactions of Phenols Ch. 18 Ethers and Epoxides; Thiols and Sulfides Synthesis and Reactions of Ethers; Cyclic Ethers (Epoxides); Reactions of Epoxides: Crown Ethers; Thiols and Sulfides LABS --> Some experiments require more than one lab period to complete. Based on an instructor’s preference, availability of equipment/supplies or constraints within a given semester, this laboratory schedule is subject to change, including but not limited to, the addition or replacement of one or more of the given experiments with the following experiments: Addition of Bromine to E-Cinnamic Acid in Methylene Chloride Substitution Reactions of Alkyl Halides: Relative Rates Triphenylmethanol with Hydroiodic Acid https://open.bu.edu/handle/2144/1415 1. Check-in, Laboratory Safety, Practices and Waste Disposal. Simple Distillation. 2. Spectroscopy: Introduction to Infrared Spectroscopy 3. Recrystallization, IR and Melting Point of benzoic acid 4. Extraction of Organic Compounds from Natural Sources: Trimyristin from Nutmeg and other types 5. Paper Chromatography 6. Dehydration of Cyclohexanol 7. Dimerization of 2-Methylpropene 8. Preparation of Diphenylacetylene Starting from Trans-Stilbene 9. Preparation of Butyl Bromide/Preparation of t-Butyl Chloride (SN2/SN1) 10. Oxidation of Isoborneol to Camphor 11. The Williamson Ether Synthesis: Preparation of Aryloxyacetic Acid from Cresol Prerequisites: General Chemistry I & II Organic Chemistry II Evaluation of Performance --> Quizzes will consist of prerequisite questions and course level questions Exams will reflect quizzes. There will be 3-4 exams Laboratory Laboratory --> Organic laboratory and lecture complement each other. The lecture supplies fundamental theory about molecular and electronic structure, chemical reactions, and their mechanisms. In the laboratory you will put this knowledge into practice to help you more fully understand the chemical process in progress. Typical text: Janice Gorzynski Smith "Organic Chemistry" with Solutions Manual, 3rd Ed. McGraw Hill Typical Lab Text: Pavia, Lampman, Kriz, and Engel "Techniques in the Organic Laboratory, Microscale and Macroscale", Harcourt College Publishing. There will be specified software for use throughout course and labs. Apart from use of software in lectures, students will use software to accompany experiments that provide detailed molecular/compound structure, target sites, functional groups, reaction (quantities, parameters), etc. etc. etc. Such exhibits will be in lab reports. Course Outline --> Week 1 Mass spectroscopy. Infrared Spectroscopy Week 2 NMR: position of signals and strength of signals Spin-spin splitting, other 1 H NMR facts NMR: solving unknowns, 13C NMR Week 3 Reduction of alkenes, alkynes, R-X, and epoxides Epoxidation, dihydroxylation, oxidative alkene cleavage Oxidation of alcohols EXAM 1 Week 4 Radical reactions, alkane halogenation, chlorination of ethane Chlorination of other alkanes, bromination, allylic bromination Lipid oxidation, antioxidants, polymers Week 5 Resonance, conjugation, dienes Diene stability and the Diels-Alder reaction Week 6 Benzene nomenclature and structure Benzene’s unusual stability, criteria for aromaticity Aromatic rings of other types EXAM 2 Week 7 Halogenation, nitration and sulfonation Friedel-Crafts reactions, effects of ring substitution, limitations Disubstituted benzenes, side chain reactions, synthesis Week 8 Carboxylic acids: naming, properties, and preparation Carboxylic acid, reactions, and acidity Carbonyl chemistry: reductions of aldehydes & ketones Week 9 Reduction of carb. acid derivatives, organometallic reagents Synthesis, organometallic reactions EXAM 3 Week 10 Aldehydes and ketones: naming, properties, preparation Aldehyde/ketone reactions, nucleophilic addition, Wittig rxn Wittig rxn continued, imines Week 11 Acetal formation/hydrolysis/use in protecting C=O Carboxylic acids and their derivatives Reactions of acid chlorides, anhydrides Week 12 Reactions of carboxylic acids, esters, and amides Summary of acyl substitutions, applications Keto-enol tautomerism; the aldol reaction EXAM 4 Week 13 Review for final exam Week 14 comprehensive final exam LABS --> note: molecules, compounds, etc. subject to change -Spectroscopy overview and accessing professional spectroscopy databases -Exp. 1 FTIR, MS: Check in. Isolation and characterization of Eugenol (essence of cloves) -Exp. 2 MS, IR, NMR: Spectral Identification of Organic Compounds -Exp. 3 Oxidation: Oxidation of Cyclohexanol to Cyclohexanone -Exp. 4-1 Spectroscopy: Identification of a General Unknown, part 1 -Exp. 4-2 Spectroscopy: Identification of a General Unknown, part 2 -Exp. 5 Diels-Alder Reaction: Synthesis of 4-Cyclohexene-cis-1,2-dicarboxylic Anhydride -Exp. 6 Aromatic Substitution: Electrophilic Aromatic Substitution: the Nitration of Toluene -Exp. 7 Carbonyl chemistry: Reduction of Heptanal Using Sodium Borohydride -Exp. 8 Organometallic Reagents: Preparation & Carbonation of a Grignard Reagent: Benzoic Acid -Exp. 9 Carbonyl chemistry: The Synthesis of an Alkene Using a Wittig Reaction -Exp. 10 Carboxylic Acid Derivatives: Flavours & Fragrances: Isopentyl Acetate synthesis (Banana Oil -Exp. 11 Enolate Chemistry: Synthesis of 2 Methyl-2-pentenal --> An Aldol Condensation Check out Prerequisite: Organic Chemistry I Biochemistry: The study of biochemistry investigates the interplay between biological macromolecules such as proteins and nucleic acids, and low molecular weight metabolites (such as the products of glucose metabolism). In this course, you will apply your knowledge of intermolecular forces, thermodynamics (when a reaction occurs), chemical kinetics (how fast a reaction occurs), and chemical structure and functionality to understand how biological molecules (and life) work. COURSE GOALS AND OBJECTIVES (Our Roadmap!) -Be able to describe/identify the forces that direct/stabilize different levels of protein structure -Be able to predict how changes in amino acid (or nucleotide) sequence can affect macromolecular structure and function -Be able to explain how enzymes are able to affect reaction rate enhancement -Be able to articulate and apply what the enzyme parameters of KM, Vmax, kcat and kcat/KM tell us about an enzyme -Be able to describe the interactions of biomolecules both quantitatively and qualitatively (in many cases, including mechanistic details) -Be able to understand the flow of metabolic intermediates through a pathway and communicate information about metabolic pathways using diagrams -Be able to describe multiple experimental methods used in biochemistry, interpret data from these methods to form conclusions, and develop a testable hypothesis to answer a question -Be able to summarize and analyse primary literature and data, and apply gathered information to new situations -Increase problem solving skills such as: critical thinking, data analysis, graphical analysis -Increase process skills such as: communication of scientific concepts and experimental results, group dynamics and teamwork, management and self-assessment -Develop a community of active learners who are intentional about their educational choices Course Materials: Calculator Emphasis on reinforcing skills with software --> << VMD (with NAMS), GROMACS, VOTCA, Desmond, UCSF Chimera, Molsoft, CCPN, RedMD + RedMDStream >> << BLAST, Unipro UGENE, Bioclipse, Staden Package, Bioconductor >> << EMBOSS + JEMBOSS + Pise + wEMBOSS + EMBOSS-Explorer >> Typical Texts: Nelson DL and MM Cox. Lehninger Principles of Biochemistry (5th edition). (“Lehninger”) Loertscher J and V Minderhout. Foundations of Biochemistry (3rd edition). (“FOBC”) Lab Manual example --> http://sites.uci.edu/m114l/files/2014/09/M114L-Biochemistry-manual-COMPLETE.pdf Course Overview --> You will frequently be given initial assignments to work on as an individual before class. These assignments must be ready at the start of class – your preparation will form part of your weekly participation grade. During our class meeting time, you will frequently function as a member of a Learning Team, developing and examining chemistry concepts as a unit. Your team effort and participation is part of your weekly participation grade. The team responses to a few Key Questions on each in-class activity will be evaluated for strength of concept and effective communication of the concept. The team will also strategize on ways to improve teamwork and team products. These responses will also form part of your weekly participation grade. Application exercises will be assigned for each activity. Together with problems from the text, they will form your weekly problem set that will be collected and graded for each individual. These homework problems and exercises are important to your success in the course. Actively working these homework problems is essential for your understanding of the material, as they bring your concept development full circle. The questions will be drawn from lectures, in-class activities, problem sets and discussions, as well as relevant primary literature that you may not have been previously assigned. The purpose of doing biochemistry is to gain experience in experimental methods that you’ll be reading about throughout the semester. Attendance on your scheduled lab day is expected. Grading --> Team Participation Problem Sets/Other Laboratory 2 Midterm Exams Final Exam Lecture Outline --> Week 1 Introduction to Biochemistry Week 2 Intermolecular forces and water. Amino acids and peptide bonds Week 3 Protein Folding Week 4 Working with proteins Week 5 Enzyme catalysis. Enzyme Kinetics Week 6 Enzyme inhibition. Hemoglobin Week 7 Exam 1; Carbohydrates Week 8 Glycobiology Week 9 Lipids and membranes. Transport across membranes Week 10 Signal transduction. Metabolism overview Week 11 Glycolysis. Glycolysis regulation and related pathways Week 12 Glycogen metabolism and gluconeogenesis. Citric Acid Cycle Week 13 Electron Transport Chain / Oxidative Phosphorylation; Exam 2 Week 14 Lipid metabolism. Nucleotides and nucleic acids Week 15 Nucleic acids structure and function Week 16 Final Exam Prerequisite: General Biology I, Organic Chemistry I Analytical Chemistry Environmental, biochemical or toxicological problems are consistently defined in terms of chemical composition and measurement. Standards, measurements in the stratosphere, (neurological) tracers, and clean-up sites, they all require the use of chemical analysis to help define the issues. In this course we will learn how to apply the concepts of chemical reactivity and equilibrium from General Chemistry in a quantitative fashion to the field of chemical analysis. Through a combination of lectures, laboratories, and problems we will learn how to design and implement a well-defined chemical analysis that conveys the results with full scientific validity. Typical text: Text: Daniel C. Harris, Quantitative Chemical Analysis Required Materials 1. Safety goggles or safety glasses and a lab apron MUST be worn at all times. (available in the stockroom) 2. All of your data will be collected in a black composition notebook. Your Final Lab Report must be typewritten. All chemical structures are to be drawn with the whatever software package or other molecular drawing software. Laboratory reports are due one week from the last scheduled date of the experiment. Grading Problem Sets 10% Quizzes 15% 3 Exams 30% Laboratory 30% Final Exam 15% Lecture Outline --> Introduction and Review The Analytical Process Chemical Measurements Experimental Error Statistics Chemical Equilibrium, Part 1 (Fundamentals, Acids, and Bases) Chemical Equilibrium Activity and the Systematic Treatment of Equilibrium Monoprotic Acid-Base Equilibria Polyprotic Acid-Base Equilbria Acid-Base Titrations Electrochemistry Fundamentals of Electrochemistry Electrodes and Potentiometry Redox Titrations Electroanalytical Techniques Chemical Equilibrium, Part 2 (Complexation, Precipitation, Advanced Topics) EDTA Titrations Gravimetric Analysis, Precipitation Titrations, and Combustion Analysis Advanced Topics in Equilibrium Lab experiments Outline --> Experiment 1: Calibration of Volumetric Glassware Experiment 2: Challenges for Density Determination Experiment 3: Determining Acidity (visual measure and technical tools) Experiment 4: Measurement Statistics Experiment 5: Preparation of an NaOH Standard Solution using Direct Titration Experiment 6: Activity of Solutions Experiment 7: Determination of Aspirin using Back Titration Experiment 8: Percentage of compound in a sample Experiment 9: Potentiometric Titration of an HCl-H3PO4 mixture Experiment 10: Electrochemistry Analytical Electrochemistry: A Laboratory Manual. (2020, June 9) https://chem.libretexts.org/@go/page/60700 Experiment 11: Determining Water Hardness Using Complexometric Titration Experiment 12: Redox Titration of Vitamin C Prerequisites: General Chemistry II, Calculus II Organic Synthesis Laboratory Practice of organic laboratory techniques. Three hours of laboratory per lab session, twice a week. Approved chemical safety goggles meeting whatever national standards. The purpose of this laboratory course is to introduce students to the techniques that organic chemists (as well as biochemists, physical chemists, etc.) use in their daily routines. After learning and understanding those techniques, students will apply their knowledge to new situations to understand synthesis reactions, molecular structure determination, and analysis of (un)known compounds. Organic chemistry laboratory is important for several reasons. It introduces students to many different laboratory practices and concepts that will be used in subsequent chemistry laboratory classes and in other laboratory situations in biology, pharmacy, and chemical engineering (just to name a few!). It is anticipated that by the completion of this course, students will be familiar with all of the following topics and techniques: Safety in the laboratory Interpreting and following scientific directions Keeping a proper lab notebook Names and proper usage of lab instruments Understanding of general properties of compounds (including solubility, miscibility, acid/base chemistry, etc.) Proper usage of glassware Isolation and purification techniques (including filtration, solvent removal, drying solutions, distillations, chromatography (thin-layer, column, and gas) and crystallization/recrystallization) Characterization techniques including spectroscopy and melting point determination Interpretation of scientific results including percent yield and recovery, melting point, boiling point, IR and NMR spectra, and Rf values Required Materials: A laboratory notebook with carbon(less) pages Approved safety goggles Lab coats Lab manual will be posted through “Blackboard” Typical text: C.F. Wilcox, M.F. Wilcox, "Experimental Organic Chemistry, A Small-Scale Approach", (3rd edition, 2010). NOTE: Apart from use of software in lectures, students will use software to accompany experiments that provide detailed molecular/compound structure, target sites, functional groups, etc. etc. Such exhibits will accompany lab reports. Lectures --> Lecture sessions are designed to clarify the concepts covered in the lab, as well as give an overview of techniques that will be used in the lab. Attendance is expected: The labs are only 3 hours in duration, so these lectures will be where you learn everything that you’ll need. Lab exercises will be available on Blackboard for each week. Please be considerate of your fellow students during the lecture period. Disruptions of any kind will not be tolerated and may result in expulsion from the classroom. Laboratory --> You will be required to have appropriate clothing before being allowed to enter the lab. Pre-labs are due at the beginning of the lab, and results and postlabs are due at the beginning of the lab 1 week after completion of the experiment! You will be expected to adhere to all of the lab safety rules. You are all expected to do your part to maintain a clean lab environment as part of GLP (Good Lab Practices): All reagent and solvent bottles should be completely closed immediately after use; All spills and dribbles should be cleaned immediately; All glassware should be put away at the end of the lab, and walkways should be kept free of debris. The following is the distribution of possible points in the course: Library Searching Exercise Database Search Exercises (Spectroscopy and Chromatography) Lab Quizzes Reaction/Synthesis methods knowledge Appropriate choice of method Appropriate constituents and tools. Procedure/steps (summary and/or ordering) Stoichiometry problems Spectroscopy and/or Chromatography analysis/interpretation Applications and industries Multistep Reaction/Synthesis Labs Lab Cleanliness Pre-lab Submissions Lab Notebook and Reports Lab Final Day 1: Much resemblance to quizzes Day 2-3: Augmented with the following: Molecular modelling software exercises Two or Three Practicum Group Labs (open notes) Part A. Points deducted for incompetent questionnaire for safety procedures for respective lab Part B. 2-3 labs to be implemented with competent data recording and lab reports. YOUR LAB REPORT CONSISTS OF THREE (3) PARTS --> Part I - Prelab Report. A copy of your lab notebook pages containing the lab write-up and answers to any prelab questions. This is due at the start of each experiment. Part II - Results. A copy of your notebook pages containing observations noted during the lab experiment. Is due with Part III one week from the conclusion of the experiment. Part III - Postlab Report. A summary of results and answers to postlab questions. This can be written on separate loose-leaf paper. Is due with Part II one week from the conclusion of the experiment. Course Outline: Week1 Check-in/Safety Video/ Safety Procedures and Regulations Fractional Distillation Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation, results and analysis Week 2 Measuring the Melting Points of Compounds and Mixtures Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Consider other physical and chemical properties, such as solubility and spectroscopic data, to confirm the identity of the unknown compound. Results and analysis Week 3 Purification by Recrystallization and Melting Point Measurement Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Consider other physical and chemical properties, such as solubility and spectroscopic data, to confirm the identity of the unknown compound. Results and analysis Week 4 Nucleophilic Substitution: Synthesis (SN1 Mechanism and SN2 Mechanism) Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Consider other physical and chemical properties, such as solubility and spectroscopic data, to confirm the identity of the unknown compound. Results and analysis Week 5 Oxidation of Alcohols (Primary, Secondary and Tertiary). Infrared Spectroscopy. Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Infrared Spectroscopy Results and analysis Week 6 Elimination Reaction (E1 Mechanism and E2 Mechanism) Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Consider other physical and chemical properties, such as solubility and spectroscopic data, to confirm the identity of the unknown compound. Results and analysis Week 7 Synthesis of Aspirin. Chromatography and/or Spectroscopy Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Chromatography and/or Spectroscopy Results and analysis Week 8 Solvent Extraction Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Consider other physical and chemical properties, such as solubility and spectroscopic data, to confirm the identity of the unknown compound. Results and analysis Week 9 Electrophilic Aromatic Substitution: Synthesis of o- and p-Nitrophenol. No distillation; extract product with ethyl acetate. Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Consider other physical and chemical properties, such as solubility and spectroscopic data, to confirm the identity of the unknown compound. Results and analysis Week 10 Separation and purification of o- and p-Nitrophenol by Liquid Chromatography. Use 100 mg sample, check by chromatography. Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Results and analysis Week 11 Aldol Condensation Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Consider other physical and chemical properties, such as solubility and spectroscopic data, to confirm the identity of the unknown compound. Results and analysis Week 12 Grignard Reaction: Synthesis of Phenylmagnesium Bromide. Week 1: Part 1. Add methyl benzoate and sustain the desiccator for next week. Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Consider other physical and chemical properties, such as solubility and spectroscopic data, to confirm the identity of the unknown compound. Results and analysis Week 13 HCl workup of previous week’s product. Synthesis of Triphenylmethanol and recrystallization of product. Purity check by melting point measurement. Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Consider other physical and chemical properties, such as solubility and spectroscopic data, to confirm the identity of the unknown compound. Results and analysis Week 14 -15 Wrapping up/cleaning things up. Final Exam. Prerequisite: Organic Chemistry I Advanced Organic Synthesis Laboratory Course covers advanced and sustainable reaction/synthesis methods or techniques. First 3 weeks will be dedicated to review of primitive methods or techniques, namely, those encountered in prerequisite that are sustainable and may be part of more advanced methods/techniques to be encountered. Required Materials: A laboratory notebook with carbon(less) pages Approved safety goggles Lab coats Lab manual will be posted through “Blackboard” Laboratory --> NOTE: Apart from use of software in lectures, students will use software to accompany experiments that provide detailed molecular/compound structure, target sites, functional groups, etc. etc. Such exhibits will accompany lab reports. You will be required to have appropriate clothing before being allowed to enter the lab. Pre-labs are due at the beginning of the lab, and results and postlabs are due at the beginning of the lab 1 week after completion of the experiment! You will be expected to adhere to all of the lab safety rules. You are all expected to do your part to maintain a clean lab environment as part of GLP (Good Lab Practices): All reagent and solvent bottles should be completely closed immediately after use; All spills and dribbles should be cleaned immediately; All glassware should be put away at the end of the lab, and walkways should be kept free of debris. The following is the distribution of possible points in the course: Library Searching Exercise Database Search Exercises (Spectroscopy and Chromatography) Lab Quizzes Reaction/Synthesis methods knowledge Appropriate choice of method Appropriate constituents and tools. Procedure/steps (summary and/or ordering) Stoichiometry problems Spectroscopy and/or Chromatography analysis/interpretation Applications and industries Multistep Reaction/Synthesis Labs Lab Cleanliness Pre-lab Submissions Lab Notebook and Reports Lab Final Day 1: Much resemblance to quizzes Day 2-3: Augmented with the following: Molecular modelling software exercises Two or Three Practicum Group Labs (open notes) Part A. Points deducted for incompetent questionnaire for safety procedures for respective lab Part B. 2-3 labs to be implemented with competent data recording and lab reports. YOUR LAB REPORT CONSISTS OF THREE (3) PARTS --> Part I - Prelab Report. A copy of your lab notebook pages containing the lab write-up and answers to any prelab questions. This is due at the start of each experiment. Part II - Results. A copy of your notebook pages containing observations noted during the lab experiment. Is due with Part III one week from the conclusion of the experiment. Part III - Postlab Report. A summary of results and answers to postlab questions. This can be written on separate loose-leaf paper. Is due with Part II one week from the conclusion of the experiment Each module has the following process: Concept Applications in industries Logistics and safety Molecular modelling simulation with software Lab implementation Consider other physical and chemical properties, such as solubility and spectroscopic data, to confirm the identity of the unknown compound. Results and analysis Course Outline: 3 Weeks. Prerequisite Review Review and identification of methods/techniques are sustainable and may be part of more advanced methods/techniques to be encountered. 2 Weeks. Advanced reaction Techniques Lab(s) Catalytic Hydrogenation Suzuki – Miyuara Coupling Negishi-Heck Reaction 2 Weeks. Organocatalysis Lab(s) 2 Weeks. Asymmetric Synthesis Lab(s) 2 Weeks. Total Synthesis Lab(s) 2 Weeks. Advances Analytical Techniques Lab(s) X-Ray Crystallography Advanced Chromatographic Techniques 2-3 Weeks. Special Topics Lab(s) Flow Chemistry Megan H. Shaw, Jack Twilton, and David W. C. MacMillan. The Journal of Organic Chemistry 2016 81 (16), 6898-6926 Prerequisite: Organic Synthesis Laboratory Polymer Chemistry Mechanisms of polymerization reactions of monomers and molecular weight distributions of products; principles, limitations and advantages of most important methods of molecular weight determination; relationship of physical properties to structure and composition; correlations of applications with chemical constitution. Polymer materials are components of many common and sophisticated products and devices that are encountered on a daily basis. The breadth of applications for polymers is derived from the vast array of compositions and structures that lead to diverse properties. It is expected that by the end of this course students will have gained significant fundamental knowledge of polymer chemistry, as illustrated by the following capabilities --> -Describe polymer structural features -Illustrate various polymerization chemistries -Provide polymer structures, given reagents and conditions -Draw reaction mechanisms for polymerization strategies -Apply polymer modification chemistries -Apply concepts of polymer chemistry to the construction of complex polymer materials Analyse physical, chemical and mechanical properties data -Evaluate common products to recognize polymer components and identify their purpose(s) and performance criteria -Formulate structure-property relationships, i.e., relate the compositions and structures of polymers to expected physical, chemical and mechanical properties, and in the reverse, be able to transform purposes and performance criteria for polymer applications into chemical compositions and structures that could exhibit the appropriate properties -Construct retrosynthetic analyses for novel polymer structures -Design polymer structures based upon desired properties and applications Typical text --> Hiemenz, P. C.; Lodge, T. P. Polymer Chemistry, 2nd Edition; CRC Press, Taylor & Francis Group: Boca Raton, FL, USA, 2007 In addition, we will cover topics from the current literature, with appropriate literature articles being provided. Emphasis on reinforcing skills with software --> << VMD (with NAMS), GROMACS, VOTCA, Desmond, UCSF Chimera, Molsoft, CCPN, RedMD + RedMDStream >> << BLAST, Unipro UGENE, Bioclipse, Staden Package, Bioconductor >> << EMBOSS + JEMBOSS + Pise + wEMBOSS + EMBOSS-Explorer >> Note: rather than sole memorization of abstract processes and complicated naming, course will also be an environment of applying software (given) towards advance expectations and forecasting via molecular development and simulations. Harshly reinforced. Grading: Quizzes, 5 - 10 x 10 pts Examinations, 3 x 100 pts Final Examination, 100 pts Lecture Outline: General introduction to polymers Overview of polymerization mechanisms Week 2 Step-growth/condensation polymerizations Week 3 – 4 Macromolecular architectural control via step-growth polymerizations Exam 1 Week 5 – 6 Polymer characterization, in brief—molecular weight, viscosity, thermal analysis, mechanical properties Week 6 – 7 Polymer characterization, in brief—molecular weight, viscosity, thermal analysis, mechanical properties Week 7 – 10 Chain-growth polycondensations. Chain-growth polymerizations. Chain-growth polymerizations—anionic and cationic. Chain-growth polymerizations—radical. Chain-growth polymerizations—controlled radical. Chain-growth copolymerizations—(controlled) radical copolymerizations Exam 2 Week 11 – 12 Macromolecular architectural control via chain-growth polymerizations Exam 3 Week 13 – 14 Special topic in polymer chemistry, TBD Week 15 Review Final Examination Prerequisites: Biochemistry I, Organic Chemistry II Advanced Topics in Polymer Chemistry Course covers a range of specialized topics that build upon the foundational knowledge acquired in introductory polymer courses. Here are some advanced topics that could be included in a polymer chemistry course. course generally takes on 15 weeks; additional time applied for cleaning things up, integrity and labs. Emphasis on reinforcing skills with software --> << VMD (with NAMS), GROMACS, VOTCA, Desmond, UCSF Chimera, Molsoft, CCPN, RedMD + RedMDStream >> << BLAST, Unipro UGENE, Bioclipse, Staden Package, Bioconductor >> << EMBOSS + JEMBOSS + Pise + wEMBOSS + EMBOSS-Explorer >> Note: rather than sole memorization of abstract processes and complicated naming, course will also be an environment of applying software (given) towards advance expectations and forecasting via molecular development and simulations. Harshly reinforced. Homework --> Moderate and advance questions from prerequisite will be precursors to questions of this course. Sometimes (not always) what you have for prerequisite questions will need to make sense for questions of this course; make the connections. Labs --> ATTRIBUTE A. Labs will either incorporate software mentioned above. ATTRIBUTE B. Implementing lab experiments of interest. Some lab experiments from prerequisite will be preliminary development to advanced lab activities as part of labs in this course. ATTRIBUTE C. Many or most labs incorporate both (A) and (B). ATTRIBUTE D. For (A), (B) and (C), will also involve students comprehending and detailing chemical models/formulas, chemical processes (as in the reactions/equilibriums, advance stoichiometry), etc., etc. Exams --> Exams will be emulate to homework, but much more. Course Topics --> 1.Polymerization Mechanism Advanced study of polymerization mechanisms, including living polymerization, controlled radical polymerization (CRP), and ring-opening polymerization (ROP). 2.Advanced Polymer Characterization Techniques In-depth exploration of advanced techniques for characterizing polymers, such as NMR spectroscopy, mass spectrometry, and advanced chromatography methods. 3.Polymer Morphology Structure Understanding the relationship between polymer structure, morphology, and properties, including crystallinity, glass transition, and liquid crystalline polymers. 4.Polymers Blends & Alloys Study of polymer blends, alloys, and interpenetrating polymer networks (IPNs), including methods for preparation, phase behavior, and properties of these complex systems. 5. Advanced Polymer Synthesis Techniques Exploration of advanced polymer synthesis methods, including click chemistry, controlled radical polymerization, and metathesis polymerization. 6. Smart & Responsive Polymers Investigation of smart polymers that respond to external stimuli such as temperature, pH, or light, and their applications in drug delivery, sensors, and other fields. 7. Biodegradable and Bio-based Polymers Examination of environmentally friendly polymers, including biodegradable polymers and polymers derived from renewable resources. 8. Polymer Rheology & Processing Study of polymer rheology, melt processing, and shaping techniques. This includes understanding the behavior of polymers under various flow conditions. 9. Polymer Nanocomposites Exploration of polymer nanocomposites, where nanoparticles are incorporated to enhance mechanical, thermal, or barrier properties of polymers. 10. Polymer Physics In-depth study of polymer physics, including the behavior of polymers in solution, glassy and rubbery states, and the theoretical aspects of polymer chains. 11. Polymer Electrolytes and Conductive Polymers Investigation of polymers with conductive properties, such as conjugated polymers and polymer electrolytes, with applications in electronic devices and energy storage. 12. Polymer Chemistry in Medicine Exploration of the role of polymers in medicine, including polymer-drug conjugates, biomaterials, and polymer-based drug delivery systems. Polymerization Catalysis Advanced study of polymerization catalysis, including the design and mechanisms of catalysts for various polymerization processes. Prerequisite: Polymer Chemistry Chemical Physics I Physical chemists and physicists make extensive use of mathematical models to describe natural phenomena. The underlying assumption is that the universe has an organisation that can be expressed as a function of certain parameters. This semester we will concentrate on developing the models that describe the bulk thermodynamic and equilibrium properties of matter. We will make the connection between the microscopic (molecular level) properties of substances and these bulk properties using results from quantum mechanics. You should be able to use these models to predict the behavior of matter. This means both estimating the range in which a measurement will fall and solving mathematical story problems, using approximations where valid. A summary list of the models and the types of systems to which you should be able to apply them is at the end of this syllabus. Laboratory experiments will illustrate concepts being discussed in lecture and familiarize you with many of the tools used by physical chemists. The tools you will learn to apply include the chemical literature; written and oral communication; mathematical functions; error analysis; and mechanical and electronic equipment such as vacuum pumps and computers. Laboratory Exam Final: based on work done in labs. You will be able to refer to your textbooks, lab reports, and lab notebooks on the exam. You will only have enough time to use them as references to get constants, formuli and relationships correct. You will need to review your laboratory reports and correct any mistakes you made in order to do well on this exam. You will also be responsible for material from the pre-labs and assigned reading. Two non-graded problem sets will be distributed during the semester to assist your preparation for the exam. Homework will be due for each class and consist of three sections of one or more questions each. The first two sections will focus on material we will be discussing during the class meeting for which the assignment is completed. Critical Thinking Exercises/Discussion Questions: The questions are designed to help you learn how to use the textbook and other reference sources to prepare for class. For example, you might be asked to find definitions, compare two models and explain when it is appropriate to use each or work through some ‘what if’ calculations. Practice Exercises: These will come primarily from the exercises at the end of the chapter. The goal is to help you figure out what you need to ask about in class. Problems: These problems will be a little more challenging and based on material discussed in the previous class. On exams you will be provided with an equation sheet for each exam consisting of the fundamental equations of each model. Additionally, you will be allowed to bring in some handwritten notes to the exam Course Grade Constitution --> Homework Labs 3 Exams Lab Exam Final Course Textbooks: Cooksy, Physical Chemistry (2 volume set, Thermodynamics and Quantum Mechanics). Barrante, Applied Mathematics for Physical Chemistry, 3rd edition. Models you will learn to apply in lectures and labs: A. Model <Classical Thermodynamics [fugacity/activity; Maxwell Relations; Colligative Properties] > --> Apply to < Reaction enthalpies; entropies and free energies (ΔH,ΔS, ΔG); Constant pressure (isobaric) phenomena; Constant temperature (isothermal) phenomena; Heat engines (adiabatic versus isothermal processes); Equilibria (Phase, Electrochemical, Chemical); Physical changes (phase); Mixtures (Fp, Bp, vapor pressure and Osmotic pressure changes) > B. Models < Gas Laws [Ideal; van der Waals; Virial Expansion] --> Apply to < Pure Gases; Gas Mixtures; To simplify thermodynamic models > C. Model < Kinetic Molecular Theory> --> Apply to < Gases (molecular speeds and energies) > D. Model <Statistical Thermodynamics > --> Apply to < Heat capacities (Cp versus Cv); Entropy of matter; Equilibria; Chemical reactions; Physical changes; Classical thermodynamics > E. Model < Quantum Mechanics > --> Apply to < Particle-on-a-line; Particle-in-a-box; Allowed energies (Translation, Rotation, Vibration, Electronic); Boltzmann Distribution (most random distribution) > Course Outline --> I. Statistical Mechanics of Gases Introduction and Historical Background Intro to quantum and statistical mechanics Partitioning Energy Molecular Interactions Review II. Thermodynamics & Statistical Mechanics Heat Capacities First Law Second Law, Third Law & Mixing Review III. Thermodynamics of Equilibria, Mixtures and Reactions Phase Transitions Chemical Potential Solutions Reactions Review From lectures: 1. describe the structure and composition of matter; 2. apply theoretical and mechanistic principles to the study of chemical systems employing both qualitative and quantitative approaches; 3. use theories of microscopic properties to explain macroscopic behavior; 4. explain the role of energy in determining the structure and reactivity of molecules; 5. use mathematical representations of physical phenomena. Lab Schedule --> Library Assignment Real & Ideal Gases Remote Experiment on classical gases: To demonstrate the classical gas laws. A motor controls the position of a piston in a glass cylinder containing air whose temperature can be remotely adjusted by a heater. Sensors measure the pressure of the gas and its temperature. Their measurements are digitized. Given this setup, students can readily verify the classical laws of phenomenological thermodynamics, for example the Gay-Lussac relation between volume and temperature. However, one can clearly go beyond this experiment: By controlling the heater and the piston, students can run the system in a thermodynamic cycle process. The amount of heat energy induced is known due to the characteristics of the heater, and the amount of mechanical energy made available by a cycle can be computed from the area within the pV diagram, etc., etc., etc. Various gas laws to be experimentally confirmed; combines gas law as well. Means to demonstrate and validate the laws of thermodynamics Studying Phase Transitions with a Strain Gauge Avogadro’s Number Slabaugh, W. H. (1969). Avogadro's Number by Four Methods. Journal of Chemistry Education, 46, 1, 40 < https://www.if.ufrj.br/~moriconi/termo_fisest/avogadro.htm > Determine Avogadro’s Number by Observations on Brownian Statistical Mechanics Lopresto, Michael. (2010). A Simple Statistical Thermodynamics Experiment. The Physics Teacher. 48(3). p183-185 Singh, H. ( 1996). A Simple Experiment to Study the Statistical Properties of a Molecular Assembly with Two or Three State Dynamics. Reson 1, 49–59 Prentis, J. J. (2000). Experiments in Statistical Mechanics. American Journal of Physics 68, 1073 Heat of Combustion & Solution Calorimetry Comb/Sol'n Sol'n/Comb Partial Molar Volume, Refractometry and Viscometry Chemical Potential (ideal, non-ideal, mixtures) A. Introduction to development of models (multivariate) B. Analysis of Wolfram Demonstrations and the programming C. Design of experiments to test, followed by implementation Includes confirming consistency with (A) and (B) PMV/RV PMV/PMV RV/PMV Electrochemistry From Labs: 1. read and follow experimental protocols; 2. properly set up and safely manipulate laboratory equipment; 3. plan and execute experiments, including the use of the chemical literature; 4. maintain accurate records of experimental work; 5. analyze data statistically and assess reliability of results; 6. prepare effective written scientific reports; 7. use mathematical representations of physical phenomena; 8. use and understand modern instrumentation; 9. use computers for chemical applications; 10. retrieve specific information from the chemical literature; 11. work cooperatively in problem solving situations. Prerequisites: Calculus III, General physics I & II. Chemical Physics II This course concentrates on learning to use 20th and 21st century developments in chemical theory to model and understand reactivity and structure. We will begin at the microscopic level using quantum mechanics to describe molecular structure. The theoretical results will be compared to evidence from measurements of molecular spectroscopy and physical properties. We will finish by considering kinetics at both the macroscopic and microscopic levels. The experiments in lab will follow this same pattern. You should be able to use these models to predict the behavior of matter. This means both estimating the range in which a measurement will fall and solving mathematical story problems, using approximations where valid. A summary list of the models and the types of systems to which you should be able to apply them is at the end of this syllabus. A secondary, but very important goal of the course, is to help you develop effective communication skills. You will work on communication skills primarily in lab where you will produce written and web-based reports on your work. Course Grade Constitution --> Homework Labs 3 Exams Lab Exam Final Course Textbooks: Cooksy, Physical Chemistry (2 volume set, Thermodynamics and Quantum Mechanics). Barrante, Applied Mathematics for Physical Chemistry, 3rd edition. Supportive Texts: Atkins, Molecular Quantum Mechanics, QD462.A84 1997. This text expands on the quantum mechanics discussed in the course text. Jorgensen and Salem, The Organic Chemist’s Book of Orbitals, QC461.J68. This book has lots of nice electron density maps for the various orbitals of common molecules calculated using molecular orbital theory. Warren, The Physical Basis of Chemistry, QD475.P47. This book has nice simplified, but accurate, descriptions of many of the quantum, spectroscopic and thermodynamic concepts we will discuss. Models you will learn to apply in lectures AND labs --> Model: Quantum Mechanics [Schrödinger equation; Born-Oppenheimer; Rigid-Rotor; Franck-Condon principle] --> Apply to Molecular and atomic structure Molecular and atomic energy levels Spectroscopy of gas phase molecules (electronic, vibrational, rotational and ro-vibronic) Liquid phase spectroscopy (electronic, vibrational) Fluorescence Spectroscopy (UV-Vis, Raman, IR, photoelectric) Physical properties (dipole moments) Model: Kinetics [Macroscopic (mech); Microscopic; Collision Theory of Reaction Rates; Collision Theory of Solution Reactions; Transition State Theory] --> Apply to First order reactions Mechanisms made of first and second order reactions Unimolecular gas phase reactions Michaelis-Menten (be aware of limited experimental conditions for applicability) Potential energy surfaces Modeling of simple reactions (liquid and gas phase) Radiation processes (photochemical reactions, lasers, fluorescence) Course Outline --> I. Theory of Molecular Structure Introduction to Quantum Mechanics One Electron Atoms Molecular Structure Review II. Spectroscopy & Kinetics Electronic Spectroscopy/Lasers Vibrational & Rotational Spectroscopy Molecular Transport Elementary Reactions and Reaction Dynamics Review III. Kinetics II Multistep Reactions Catalysis Kinetic Modelling Review From Lecture: 1. describe the structure and composition of matter; 2. apply theoretical and mechanistic principles to the study of chemical systems employing both qualitative and quantitative approaches; 3. use theories of microscopic properties to explain macroscopic behavior; 4. explain the role of energy in determining the structure and reactivity of molecules; 5. use mathematical representations of physical phenomena. Lab Schedule --> Recital of chosen labs from prerequisite Math and Quantum Mechanics Spectroscopy of Conjugated Dyes Quantum Calculations HCl Vibrational Spectroscopy and Raman Spectroscopy Spectroscopy A Spectroscopy B Solution kinetics and TBA kinetics Kinetics A Kinetics B Thermochemistry Thermochemistry for molecular species(overview) Code development: Blecic, J., Harrington, J. & Bowman, M. O.(2016), TEA: A Code Calculating Thermochemical Equilibrium Abundances, Astrophysical Journal, Supplement Series, 225: 4 (14pp) ICT-Thermodynamic Code (analysis and code development) NOTE: besides TEA and ICT, other chosen labs will also incorporate analysis of Wolfram Demonstrations and the programming to compare with the theory and experiments. From Labs: 1. read and follow experimental protocols; 2. properly set up and safely manipulate laboratory equipment; 3. plan and execute experiments, including the use of the chemical literature; 4. maintain accurate records of experimental work; 5. analyze data statistically and assess reliability of results; 6. prepare effective written scientific reports; 7. use mathematical representations of physical phenomena; 8. use and understand modern instrumentation; 9. use computers for chemical applications; 10. retrieve specific information from the chemical literature; 11. work cooperatively in problem solving situations. 12. For programming assignments, the logisitics after analysis. Concept development before “diving into the ocean depths”. Prerequisite: Chemical Physics I Inorganic Chemistry I This course will (among other things) emphasize the shapes and symmetry of simple molecules. Topics will be more technical than expected. Note: this is not a course to finesse with diagrams; you are here with the mindset of being future industrial professionals contemplating various opportunities out there, else this course isn’t for you. Assessment --> Homework Quizzes 0.2 Labs 3 Exams Homework --> Concerns prerequisite refreshers and course topics. Quizzes --> Will reflect homework and lectures Exams --> Will reflect homework and quizzes Condensed Course Outline --> Note: course outline is a highly condensed summary; pay attention to course literature. PART 1 – General Considerations Electronic Structure of the Atom Introduction to Symmetry and Group Theory Structure & Bonding in Covalent Molecules Periodic Table & Chemistry –General Considerations (various) PART 2 – Transition Metals Co-ordination Chemistry: Bonding, Spectra & Magnetism Co-ordination Chemistry: Structure Co-ordination Chemistry: Mechanisms Transition Metals – Periodic Trends Organometallic Chemistry PART 3 – Miscellaneous (if time permits) Ionic Solids & the Solid State Lab Syllabus --> Typical Lab Manuals: Girolami, G. S., Rauchfuss, T. B. and Angelici, R. J. (1999). Synthesis and Technique in Inorganic Chemistry. University Science Books Descriptive Inorganic Chemistry Experiments by Geoff Rayner-Canham and Tina Overton Experimental Inorganic Chemistry by Gary L. Miessler and Paul J. Fischer Inorganic Chemistry Laboratory Manual by J. Derek Woollins Experiments in Inorganic Chemistry" by H. Rupert Thomas and Robert J. Angelici Each lab will have 3 components -- COMPONENT 1: highly immersed in modelling, simulation and computation with chosen syntheses and reactions that reflects lecture and lab topics. Analysis of chemical structure, special groups, bonds and mechanisms. Students will be given various molecules/components and possible reactions to investigate/simulate and compute/determine properties or outcomes. Will choose software out of the following that caters well to inorganic chemistry concerning synthesis, energy differences of complexes, decompositions relevant to the topics presented in the course outline. Note: will also take much advantage of the features of such software. Note: some mentioned software can provide predicted spectroscopy. This component of labs can be pre-analysis for component 4. << Dalton, CP2k, Firefly, Gaussian, GAMESS-US, MOLDEN, NWchem, GPAW, Octopus, ORCA, FreeON, PUPIL, VOTCA , BOSS >> << VMD (with NAMS), GROMACS, VOTCA, Desmond, UCSF Chimera, Molsoft, CCPN, RedMD + RedMDStream, (http://bionano.cent.uw.edu.pl/software/) >> << TINKER > COMPONENT 2: pre-lab development for hands-on activities COMPONENT 3: lab logistics and implementation of hands-on experiments. Results and analysis of respective experiment. OUTLINE: Week 1 – 2. General Laboratory Techniques & Safety Laboratory safety procedures and guidelines . Introduction to laboratory glassware and equipment. Basic techniques: weighing, measuring, and mixing. Week 3 – 4. Electronic Structure of the atom. spectroscopy techniques for studying electronic structure. Hands-on UV-Vis spectroscopy and electron paramagnetic resonance (EPR). Determination of electronic configurations of selected transition metals. Qualitative analysis of ions with transition metals (based on experiments). Week 5 – 6. Covalent Molecules – Synthesis and Bonding Synthesis of covalent molecules with emphasis on bonding. Characterization using spectroscopic techniques: IR and NMR. Analysis of bond types and electronic structure. Week 7 – 8. Periodic Table & Chemistry Investigation of periodic trends. Synthesis and characterization of representative elements. Correlation of experimental results with periodic trends. Week 9 – 10. Coordination Chemistry – bonding, Spectra and Magnetism Synthesis of coordination compounds. Characterization techniques: UV-Vis spectroscopy and magnetic susceptibility measurements. Exploration of bonding, electronic spectra, and magnetic properties. Week 11 – 12. Coordination Chemistry – Structure and Mechanisms Study of the structure of coordination compounds. Investigation of reaction mechanisms involving coordination complexes. Isomerisms. Stereochemical isomerism. Identification and characterization of isomers Hands-on experience with X-ray crystallography for structural analysis. Week 13 – 14. Transition Metals – Periodic Trends and Organometallic Chemistry Ligand Substitution Reactions Investigation of ligand substitution reactions in coordination compounds. Study of reaction mechanisms. Analysis of kinetics and thermodynamics. Hands-on experience with X-ray crystallography for structural analysis. Synthesis and characterization of organometallic compounds. Investigation of the role of transition metals in organic reactions. Week 15. Miscellaneous – Ionic Solids and the solid State Synthesis of ionic solids. Characterization using X-ray diffraction (XRD). Study of the solid-state properties of ionic compounds. Prerequisites: General Physics I, General Chemistry I & II, Calculus II Inorganic Chemistry II Fundamental principles of inorganic chemistry will be discussed. If you believe “you are that guy” after Inorganic Chemistry I, you will be a hazard and embarrassment to self and others. Note: this is not a course to finesse with diagrams; you are here with the mindset of being future industrial professionals contemplating various opportunities out there, else this course isn’t for you. Topics to be discussed EMPHATICALLY IN A ROBUST MANNER: Nucleogenesis Bonding Theory Molecular Symmetry Coordination Chemistry Vibrational Spectroscopy Electronic Structure & Molecular Orbital Theory Literature --> Housecraft, C. and Sharpe, A. G. Inorganic Chemistry, Pearson Murillo, C. A., Bochmann, M. and Cotton, F. A. and Wilkinson, G. (1999), Advanced Inorganic Chemistry, Wiley-Interscience Assessment --> Homework Quizzes Labs 3 Exams Homework --> Concerns prerequisite refreshers and advance treatment of topics. Quizzes --> Will reflect homework and lectures Exams --> Will reflect homework and quizzes Labs --> Note: some/many labs may repetitions(or quite similar) of those encountered in prerequisite, but it’s for your own good. May be a bit more advanced however. Software in prerequisite to apply in same manner with labs. Typical Lab Manuals: Girolami, G. S., Rauchfuss, T. B. and Angelici, R. J. (1999). Synthesis and Technique in Inorganic Chemistry. University Science Books Descriptive Inorganic Chemistry Experiments by Geoff Rayner-Canham and Tina Overton Experimental Inorganic Chemistry by Gary L. Miessler and Paul J. Fischer Inorganic Chemistry Laboratory Manual by J. Derek Woollins Experiments in Inorganic Chemistry" by H. Rupert Thomas and Robert J. Angelici NOTE: for augmented molecular orbital theory labs, Use computational software or theoretical models to predict the molecular orbital diagram; compare the predicted diagram with experimental data obtained from spectroscopic techniques; discuss the bonding and antibonding orbitals and their significance in the stability of the molecule. UV-Visible Spectroscopy of Conjugated Systems (often standard) Electron Density Mapping with Quantum Chemistry Software Utilize quantum chemistry software to calculate electron density maps for different molecules; choose molecules with interesting electronic structures; compare and analyze the electron density distribution, focusing on bond formation and molecular shapes; relate the findings to molecular orbital theory and explain how electron density influences molecular properties. Energy-Level Diagrams for Polyatomic Molecules Select a polyatomic molecule like ozone (O3) or benzene (C6H6); construct energy-level diagrams for the molecular orbitals using computational tools; investigate the impact of symmetry and molecular geometry on the electronic structure; discuss the implications of these diagrams on the reactivity and stability of the molecule. Synthesis and Analysis of Transition Metal Complexes Synthesize transition metal complexes with ligands of varying donor abilities; use spectroscopic techniques (UV-Vis, IR, NMR) to analyze the electronic structure of the complexes; discuss how the ligands interact with the metal orbitals, leading to the formation of molecular orbitals; relate the findings to the bonding theories specific to transition metal complexes. Modeling Molecular Orbitals with 3D Printing · 3D print models of molecular orbitals for simple molecules; use the models to visually demonstrate the spatial distribution of electrons in bonding and antibonding orbitals; uncourage students to manipulate the models to understand the geometry and symmetry of molecular orbitals; relate the hands-on experience to theoretical concepts learned in class. Prerequisite: Inorganic Chemistry I Environmental Chemistry Course covers a range of topics related to the chemical processes occurring in the environment, pollution, and the impact of human activities on natural systems. Note: course is neither a comprehensive course in analytical chemistry nor instrumental analysis (lab), but will apply a few techniques in labs for substance and practicality. Homework --> Will stem from course literature. Quizzes (“karma and dharma”) --> 1.HW problems from past. 2.Concern identification and classification of compounds, molecules and pollutants throughout modules. 3.Basic conversions related to the SI system 4.Stoichiometry problems 5.pH reaction problems (when treated) 6.Analytical equations use and quantitative aspects encountered in literature 7.Calculus in environmental chemistry (rate of reactions, transport processes, reaction kinetics, diffusion/dispersion, ocean acidification modelling). Note: will be constructive and “to the point” in this course, rather than obnoxious and unconstructive mathematical perversions of a mathematical modelling course. 8. Thermodynamics of specified molecules/compounds and spectra. Note: such above 8 features can show up arbitrarily, say, along with course progression. Exams (“karma and dharma”) --> Quizzes will serve as strong foresight for exams. Labs --> As described throughout syllabus. Course Assessment --> Homework Quizzes Exams Labs Course Outline --> A. INTRODUCTION TO ENVRONMENTAL CHEMISTRY Overview of EC and its significance Sources and transport of pollutants Environmental cycles: water, air soil B. ATMOSPHERIC CHEMISTRY Composition and structure of Earth’s atmosphere Stratospheric chemistry and the ozone layer. Ozone holes. Effect of aerosols on precipitation reactions Precipitation reactions in the atmosphere Hazards of aerosols in the atmosphere Chemistry of greenhouse gases (CO2, CH4, N2O, H2O, O3, CFCs) Thermodynamics of greenhouse gases Absorption of Infrared Radiation and spectra Radiative Forcing Emission of Infrared Radiation and spectra Saturation effects Air pollutants (SO2 and Pb) and their effects Lab: Analysis of air quality using air sampling techniques. Lab: Means to identify molecules/compounds via infrared emission and absorption. Lab: Satellite spectral data acquisition for assigned places to identify compounds or molecules; means to distinguish absorption from from emission. C. OVERVIEW OF BASIC ANALYTICAL TECHNIQUES Titration methods, gravimetric analysis, chromatography, spectroscopy (2-4 types), etc., etc. Such methods (and others) will apply to future labs throughout course. D. AQUATIC CHEMISTRY Chemical processes in water bodies Water quality parameters and standards Ocean Acidification. Total organic carbon. Aquatic Carbon Sequestration and related types of metabolism Lab: Water quality assessment through chemical analysis Lab: Nutrient pollution. Nutrient Inputs and Eutrophication Lab: Elementary carbon acidification experiment; includes Stoichiometry and reaction modelling; modelling acidification rates and testing for different temperatures compared to temperature sensitivity/scenario analysis. Lab: Chemical equilibrium models for carbon acidification. Analysis of the key components. Logistics for the key components. CO2SYS software package. Can results from CO2SYS be compared to other premier models (LOVECLIM, CESM, MITgcm, BIOGEM)? Ocean Carbon and Acidification Data System (OCADS). Can results from CO2SYS and the other mentioned models be compared to OCADS? Satellites/stations data analysis activities where students will directly immerse themselves into data acquisition methodology and data wrangling activities. Data analysis of ocean carbon dioxide levels and acidity for various locations across the globe: times series development with salient characteristics identification and forecasting. Such data will also be applied to correlation analysis with variables for ocean acidification, namely correlation heatmaps; advance variable selection methods. Multivariate OLS modelling and forecasting to compare to professional ocean acidification models. E. SOIL CHEMISTRY Botanic Carbon Sequestration and related metabolism Artificial Carbon Sequestration Soil composition and its role in nutrient cycling. Impact of pollutants on soil quality Lab(s): Soil analysis and assessment of pollutant impact F. POLLUTANTS & CONTAMINANTS Identification and classification of premier pollutants and contaminants Effects on ecosystems and human health (for prior). Metabolic effects of pollutants and contaminants (for prior) Lab: Detection and analysis of specific pollutants. Enzyme-Linked Immunosorbent Assay (ELISA) – detecting and quantifying specific organic contaminants like pesticides and toxins. Prerequisites: Organic Chemistry I, Inorganic Chemistry I, General Physics I, Calculus III, Ordinary Differential Equations. Instrumental Analysis This course concerns the theory and practice of instrumental methods for the separation, identification and quantitative analysis of chemical substances. Satisfactory completion of this course will afford students a working knowledge of analytical instrumentation typically employed in chemical/biochemical research and industry laboratories. It will also provide the student with an appreciation of the relative strengths and limitations of different instrumental based analysis methods. Typical Textbook: Principles of Instrumental Analysis (7th Edition) by Skoog, Holler and Crouch, published by Cengage Learning Supplementary course material, along with class handouts, will be provided in class or on the web and will be announced in-class. Students may also find the following supplemental texts useful: “Principles of Electronic Instrumentation” (3rd Ed.) by Diefenderfer and Holton and “Undergraduate Instrumental Analysis” by Robinson, Frame and Frame (7th Ed.). Specific Course Learning Objectives: * Demonstrate knowledge of sampling methods for all states of matter. * Distinguish between qualitative and quantitative measurements and be able to effectively compare and critically select methods for elemental and molecular analyses. Assess sources of error in chemical and instrumental analysis and account for errors in data analysis. * Recognise various interference in chemical and instrumental analysis. * Comprehend the concept of and perform instrument and method calibration. * Apply and assess concepts of availability and evaluation of analytical standards and formulate standardization methodology. * Integrate a fundamental understanding of the underlining physical principles as they relate to specific instrumentation used for atomic, molecular, and mass spectrometry, magnetic resonance spectrometry and chromatography. * Understand and be able to apply the theory and operational principles of analytical instruments. Important note: Reading the textbook is an essential component of the class. Students should read ahead and be prepared to ask/answer questions during class on the material as it is covered. In addition to class lectures based upon material in the textbook, we may cover material in more detail or discuss recent advances in instrumentation beyond what is covered in the textbook. In these cases, supplementary course material will be provided to the student either as handouts or as web links. Course Grade Constitution: Homework Sets 4 Exams Course Outline: I. Measurement Principles and Electronics a. Introduction to the analytical process (2 lecture) Chapter 1 b. Basic electronics (1 lectures) Chapter 2, 3, 4 c. Signals and noise (2 lectures) Chapter 5 II. Electrochemical Analysis a. Basic Concepts (Chapter 22) b. Potentiometry (Chapter 23) c. Voltammetry (Chapter 25) III. Basics of Spectroscopy a. Introduction to Spectroscopic Methods (2 lecture) Chapter 6 b. Components of Optical Systems (2 lecture) Chapter 7 IV. Atomic Spectroscopy a. An Introduction to Optical Atomic Spectroscopy (2 lectures) Chapter 8 b. Atomic absorption spectroscopy (2 lecture) Chapter 9 c. Atomic Emission Spectroscopy (2 lecture) Chapter 10 V. Molecular Spectroscopy – Electronic transitions a. Introduction to UV-Vis molecular spectroscopy (2 lectures) Chapter 13 b. Applications of UV-Vis spectroscopy (2 lecture) Chapter 14 c. Fluorescence, phosphorescence & chemiluminescence (2 lectures) Chapter 15 VI. Molecular Spectroscopy – Vibrational excitation a. IR absorption spectroscopy (2 lectures) Chapter 16 b. Applications of Infrared Spectrometry (2 lectures) Chapter 17 c. Raman spectroscopy (2 lectures) VII. Molecular Spectroscopy – Nuclear transitions a. NMR (3 lectures) Chapter 19 VIII. Additional Instrumental Methods for Organic Structural Analysis a. Mass Spectrometry (3 lectures) Chapter 20 IX. Separation Science a. Fundamentals of chromatographic separations (3 lectures) Chapter 26 b. Gas chromatography (2 lectures) Chapter 27 c. High performance liquid chromatography (2 lectures) Chapter 28 Prerequisites: Organic Chemistry I, Inorganic Chemistry I, Calculus III. Co-requisite: Instrumental Analysis Lab Instrument Analysis Lab Objectives: Analytical chemistry is a constantly evolving discipline. Analytical chemists constantly strive to improve the sensitivity, speed, and accuracy of established analytical techniques, to extend existing techniques to new analytical problems or applications, and to invent new instrumental tools for chemical and biochemical analyses. This laboratory is designed to supplement the Chem 5640 classroom instruction by familiarizing students with established instrumental techniques currently used in industrial and academic analytical laboratories. The overall goal of this laboratory is for the student to learn how to use analytical instrumentation to solve chemical problems. Analytical problem solving is a three-step process. First, you must recognize the nature and scope of the problem to be solved and identify those chemical and physical properties of a sample that can be exploited for providing the necessary information to help solve the problem. Second, you must learn to assess the relative merits of competing techniques and select an instrumental method that is most appropriate for the problem. Last, you must learn how to interpret your results within the limitations of the instrumental method used to obtain them. These problem-solving skills are sufficiently general that you should be able to apply them to new chemical analysis problems later in your career. For labs include details on the specific sample being analysed (source, manufacturer, unknown number, etc.). This is critical for proper grading. Each student should individually analyze duplicate samples for any quantitative experiment and students should each analyse a different set of samples. Group members, as needed, may share common reagents or calibration standards needed in a specific laboratory experiment. Each group member prior to use should confirm the proper preparation of such common reagents or calibration solutions (i.e., double check the preparation procedure). Course Grade Constitution --> 8 Specific Lab Reports 80% Special Project Design & Formal Report 20% Tabulated Data --> Include all data collected as part of the experimental procedure. Qualitative data collected (like spectra) should be printed out and added to the student’s notebook (leave a space to tape them in, you may cut and paste them, reducing them in size if necessary to fit) after the class period. Copies should be included with the submitted laboratory report. Calculations --> Include any pre-lab calculations and calculations performed during lab. NOTE: will also use software with spectroscopy prediction ability to be compared to actual lab spectroscopy investigation, with comparison to professional databases. Instrumental Analysis Labs to be performed --> Laboratory A McGonigle, A. et al (2018). Smartphone Spectrometers. Sensors (Basel, Switzerland), 18(1), 223. Laboratory B Electronics Laboratory Laboratory C Ion Selective Electrode Fluoride in Water Laboratory Laboratory D Atomic Absorption Laboratory Laboratory E UV-Visible Spectrometry Laboratory Laboratory F Fourier Transform Infrared Spectrometry Laboratory Laboratory G Raman Spectroscopy Laboratory H High Performance Liquid Chromatography Laboratory Laboratory I Gas Chromatography/Mass Spectrometry Laboratory Laboratory J Special Project Laboratory - Group Problem Solving Exercise --> Students will work on a special laboratory project during the last several weeks of the semester. This will include 3 scheduled weeks working in the lab on the project and 1 week for writing the final project report and final lab cleanup. An open unscheduled lab week (see attached schedule and is subject to change if required) is provided for each group to facilitate project planning. This year, there will be 3 or 4 special project groups composed of 2-4 students. You and your group should begin meeting to discuss and plan your group experiment (see details below) early in the semester. The last four weeks of the semester are reserved for the final group project (setting up, performing experiments, cleaning up the lab and writing the group project report). The Lab closes for experimentation on a specified date. Mandatory final lab clean up is to be completed no later than 7 days after. Group reports on the special project are due by designated date in the Instructor’s office (no late special reports accepted). As a group, your special project team will devise an appropriate set of experimental procedures to address a problem of your choice (see examples below) using any of the experimental analytical instrumental techniques from this semester’s laboratory. Any additional methods will need approval from the instructor (see Pre-Project Proposal). Each student must contribute to the project's goals and contribute to the writing of a detailed group laboratory report covering the basics of the problem, the methods employed, the experimental procedure followed and the experimental results obtained (either positive or negative). The report format should be similar to the regular laboratory report (see below), but should provide expanded sections covering experimental methods and a more detailed discussion and reference section (i.e., it should be proportionally longer given that multiple students are contributing to it). The cover page should also include the names and signatures of the student’s contributing to the report to certify that all group members participated significantly to the project. Pre-Project Proposal --> Your group is required to submit a short (2 - 5 pages suggested), written proposal, outlining the specifics of your group’s special project. This proposal should state the goals of the project, required chemicals and instrumentation, a concise justification of your analytical approach, and a brief outline of your experimental plan. It is strongly recommended that your group consult with your instructor well before it finalizes its proposal to ensure that the approach is viable. The instructor must approve all pre-project proposals. Early discussions will also allow time to order any special analytical reagents or standards that may be needed. The group pre-project proposal must be submitted no later than due date. Any reagents that will be required must be readily available from the Chem Stores stockroom or easily ordered (for nominal prices) from a chemical supply house and must not include restricted substances or chemical or biological hazards. Example Special Projects (Groups consist of 3 or 4 students, depending on class size) --> 1) Select several (4 or 5) inorganic species likely to be in various water samples for analysis. Choose several water sources (tap water, Logan river water, bottled water, great salt lake water, irrigation water, etc.) and determine the concentration of the species chosen. (Major instrumental methods to include: AA and ion selective electrodes and pH for H3O+ and OH- levels). You could alternately choose river sediment, seashells or (harder) plant materials. While involving additional sample preparation, a more ambitious project will be judged favorably as to final grades. 2) Analyze (qualitatively and quantitatively) various components of volatile fuels (lighter fluid, gasoline, etc.) including possibly those from several brands or sources. (Major instrumental methods to include: GC-MS and perhaps IR and UV spectrometry). Alternately, determine the minor volatile components of a flavor (such as peppermint oil, available from grocery store) or fragrance (such as a perfume). 3) Analyse the (active or inactive) ingredients from several over the counter medicines (liquids or solids) as to amounts and compare different brands. (Major instrumental methods to include: HPLC and perhaps IR, Raman and UV spectrometry). Examples cough syrup, pain medication, etc. 4) Determine the capsaicin content of various chili peppers using HPLC. Compare capsaicin content that you determine to the Scoville hot scale (for reference see: http://en.wikipedia.org/wiki/Scoville_scale), which is a subjective scale based upon the perceived hotness of human taste testers. Outside the laboratory, the group could also subjectively rank the chilies as to hotness by taste testing them outside of the laboratory. Prerequisites: Organic Chemistry I, Inorganic Chemistry I, Calculus III. Co-requisite: Instrumental Analysis Spectroscopy In this course we will use the basic principles of physical chemistry, quantum mechanics and classical electrodynamics to understand, analyse and predict the spectra of molecules. We will review the most relevant topics from quantum mechanics and classical electrodynamics before proceeding to molecular spectroscopy and its applications. The final unit of the course will be dedicated to lasers and laser spectroscopy. Real research problems will be used to illustrate the topics we cover in lectures. Learning outcomes: After completing the course, the student will grasp the fundamental principles of quantum mechanics and be able to apply them to understand and predict the spectra of atoms and molecules over a very wide range of wavelengths. This course is not simply a Instrumental Analysis course with Instrumental Analysis Lab. Physics students interested in course must acquire registering by permission from instructor and department chair; physics students must well prepare themselves to cope with terrain they are not well versed in. Chemistry students must fulfill prerequisites requirements, plainly because they aspire to be professional chemists. Homework assignments: Students are assigned homework assignments throughout the duration of the semester. They are assigned one week before the due date. In order to receive credit, students must provide full detail, including unit analysis, mathematical derivation, and insightful justification (essay format) unless otherwise noted. Labs --> Note: will also take much advantage of the features of such software. Note: some mentioned software can provide predicted spectroscopy to compare with actual spectroscopy experiments and databases. << Dalton, CP2k, Firefly, Gaussian, GAMESS-US, MOLDEN, NWchem, GPAW, Octopus, ORCA, FreeON, PUPIL, VOTCA , BOSS >> << VMD (with NAMS), GROMACS, VOTCA, Desmond, UCSF Chimera, Molsoft, CCPN, RedMD + RedMDStream, (http://bionano.cent.uw.edu.pl/software/) >> << TINKER > Referencing with professional databases AFTER mystery substances are unveiled by instructor. --ADVANCE RECTIAL OF SPECTROSCOPY LABS: advance recital spectroscopy labs will involve reacquaintance with labs from Instrumental Analysis Lab course. NOTE: will also use software with spectroscopy prediction ability to be compared to actual lab spectroscopy investigation, with comparison to professional databases. --SPECTROSCOPY HYPOTHESES: there will be given sets of molecules, compounds, and polymers, accompanied by tangible and fluid logistics to make spectra predictions compared to spectroscopy lab experiments for the mystery substances. FOR SPECTROSCOPY HYPOTHESES, STUDENTS ARE GENERALLY FORBIDDEN FROM USING SOFTWARE, HARDWARE AND DATABASES UNTIL PERMITTED TO DO SO; MUST PROPERLY APPLY ANALYTICAL AND COMPUTATIONAL MODELS PREMATURELY REGARDLESS. STRONG ANALYTICAL PREDICTION DEVELOPMENT MUST BE COMPLETED BEFORE USE OF SOFTWARE, HARDWARE AND DATABASES. Course Grade Constitution --> Homework 15% Labs 25% Advanced Recital Spectroscopy Labs 0.4 Spectroscopy hypotheses 0.6 4 Exams 60% Textbooks --> J. M. Hollas – Modern Spectroscopy, 4nd Edition (Wiley, 2009) D. Harris and M. Bertolucci, Symmetry and Spectroscopy: An Introduction to Vibrational and Electronic Spectroscopy, Dover Publications, New York, 1978 Tentative Course Outline --> 1. Introduction and overview 1.1. Macroscopic view of light-matter interaction 1.2. Effect of energy quantization 1.3. Units and dimensions 2. Light and its interaction with matter 2.1. Electromagnetic waves and polarization 2.2. Black body radiation and photon energy 2.3. Quantum description of matter 2.4. Interaction of light with matter 3. Atomic spectroscopy 3.1. The hydrogen atom 3.2. Poly electronic atoms 3.3. Atomic term symbols 3.4. Selection rules and atomic spectra 4. Rotational spectroscopy 4.1. The rigid rotor 4.2. Rotational levels and transition rules 4.3. Pure rotational spectra of molecules 5. Molecular symmetry (review only) 5.1. Symmetry operations 5.2. Point groups 5.3. Character tables 5.4. Total representation of a group 5.5. Symmetry and dipole moment 6. Vibrational spectroscopy 6.1. Diatomic molecules 6.2. Polyatomic molecules 7. Electronic transitions of polyatomic molecules 7.1. Molecular orbitals 7.2. Rovibronic transitions 7.3. The Franck-Condon principle 7.4. Photoelectron spectroscopy 8. Laser spectroscopy 8.1. Introduction and historic 8.2. Principles of operation 8.3. Different types of lasers 8.4. Laser techniques Note: Raman spectroscopy and infrared spectroscopy schemes can be built and function exceptionally. Prerequisites: Organic Chemistry I, Inorganic Chemistry I, Instrumental Analysis, Instrumental Analysis Lab, Chemical Physics I & II Molecular Modelling Course Objectives --> Course explores a wide range of techniques and applications in molecular modeling and computational chemistry, including ab initio quantum mechanics, semi-empirical MO theory, molecular mechanics, molecular dynamics simulation, coarse-grained models, electrostatic methods and biomolecular structure prediction. Familiarity with computers (text editing, writing scripts and programs) is expected. Textbook --> Leach, R. A. (1997). Molecular Modelling. Longman Pub Group Supporting Molecular Modelling Texts --> Introduction to Computational Chemistry, Jensen, 2007 Essentials of Computational Chemistry, Cramer, 2004 Molecular Modeling Basics, Jensen, 2010 Supporting Simulation Texts --> Molecular Modeling – Principles and Applications, Leach, 2001 Molecular Modeling and Simulation, Schlick, 2010 Computer Simulation of Liquids, M. P. Allen & D. J. Tildesley, 1987 Understanding Molecular Simulation, Daan Frenkel & Berend Smit, 2002 The Theory of Intermolecular Forces, Anthony Stone, 2013 Quantum Chemistry Algorithms Theory --> Modern Quantum Chemistry, Szabo & Ostland, 1982 (Dover) Quantum Chemistry, 3rd Ed., John Lowe and Kirk Petersen, 2006 Supporting Molecular Orbital Theory Text --> Frontier Orbitals – A Practical Manual, Nguyen Trong Anh, 2007 Molecular Orbitals & Organic Chemical Reactions, Ian Fleming, 2010 The Theory of Intermolecular Forces, 2nd Ed., Anthony Stone, 2013 Extensive use of software provided out of the following --> << Dalton, CP2k, Firefly, Gaussian, GAMESS-US, MOLDEN, NWchem, GPAW, Octopus, ORCA, FreeON, PUPIL, VOTCA , BOSS >> << VMD (with NAMS), GROMACS, VOTCA, Desmond, UCSF Chimera, Molsoft, CCPN, RedMD + RedMDStream (http://bionano.cent.uw.edu.pl/software/) >> << TINKER >> Note: will also take much advantage of the features of such software. Note: some mentioned software can provide predicted spectroscopy. Note: it’s inevitable that more than one software from each set will be used due to comparative advantages, complimenting circumstances and towards establishing consistency with computations. Course Grade Constitution --> Assignment Sets 3-4 Quizzes Labs 3 Exams Student Projects Student Projects --> Each student will choose a project based on their interests that applies molecular modelling. Areas of interest include pharmaceutics, virology with proteins, biochemistry/metabolism, molecular biology, determining properties of compounds in bulk, forensics, laser ink printers, materials science, algorithms & simulations, etc., etc., etc. Project must make good use of at least 2 - 3 software from each set; Mathematica/R can complement. Project includes hard copies reports and presentation documentation. Course Outline --> MODULE I: ab Initio and Semi-Empirical Quantum Mechanics WK1 Introduction to Molecular Modelling; Examples of Application Areas Potential Energy Surfaces and Optimization Methods Lab 1: Intro to chosen software (abilities, logistics, implementing, software comparing WK2 ab Initio Molecular Orbital Theory: From the Beginning Lab 2: Structure Optimization and Conformational Analysis WK3 Methods for Treating Electron Correlation Open Shell Systems and Excited States Lab 3: Thermochemistry in Different QM Model Chemistries WK4 Semi-Empirical MO Methods & Density Functional Theory Solvation Models for QM Calculations Tautomeric Preferences and Solvent Effects Lab 4: Density Functional Theory (DFT) Baseden, K. A. and Tye, J. W. (2014). Introduction to Density Functional Theory: Calculations by Hand on the Helium Atom. J. Chem. Educ. 2014, 91, 12, 2116–2123 Will try also for the H2 molecule Analysis the following code development and rebuilding: Blinder, S. M. (2019). Density Functional Computations on Noble Gas Atoms. Wolfram Demonstrations Project DFT simulations (given open source software) of specified structures with varying lattice constant parameters and analyse the results to: Developing understanding of variations in energy levels as a function of the interatomic distance, thereby understanding the effect of structure on electronic properties Determining the nature of the system (whether being metallic,nn-metallic, semiconducting or insulating) Interpreting the DFT band-structure results Comparing MOT simulations with DFT simulations (involves use of different software) WK5 Principles of Frontier Orbital Theory Applications of Frontier Orbital Analysis Lab 5: Stereoselectivity in Diels-Alder Reactions MODULE II: Molecular Mechanics and Dynamics Simulation WK6 Molecular Mechanics and Force Fields Advanced Aspects of Force Field Design and Parameterization Lab 6: Conformational Analysis of Substituted Cycloalkanes WK7 Basics of Molecular Dynamics Simulation Basics of Monte Carlo Sampling Techniques Lab 7: Generating and Analysing a Molecular Dynamics Trajectory WK8 Methods for Calculation of Free Energy Application to Intermolecular Interactions & Binding Energies Lab 8: Calculation of Diffusion Constants from MD WK9 Solvation Models for Use with Empirical Potentials Hybrid Potentials: Combined QM/MM Simulation Lab 9: Computing the Hydration Free Energy of Ions WK10 Application of QM/MM to Enzyme Reaction Mechanisms Prediction of Small Molecular Crystal Structures Lab 10: Folding of the World’s Smallest “Protein” MODULE III: Electrostatics, Coarse Graining & Biomolecular Structure Prediction WK11 Poisson-Boltzmann Equation & Associated Calculations Application to the Modelling of pKa Values Lab 11: Running PB Calculations with APBS WK12 Brownian Dynamics Simulations Coarse Grained Potentials: Tradeoffs & Applications Lab 12: Work on Individual Student Projects WK13 Useful Tools from Structural Bioinformatics Critical Assessment of Protein Structure Prediction Lab 13: Work on Individual Student Projects WK14 Presentation of Student Projects WEEK15 Final examination preparation & Final Examination Prerequisites: ODE; Numerical Analysis; Probability & Statistics B; Mathematical Statistics; Inorganic Chemistry II; Chemical Physics II. Co-requisite: Stochastic & Statistical Methods for Molecular Modelling. Stochastic & Statistical Methods for Molecular Modelling Course Objectives: A. Incorporating stochastic methods in molecular modeling into student labs using the R programming language. B. Incorporating statistical methods in molecular dynamics into student labs using the R programming language. NOTE: any topics and skills encountered in this course that’s done in the prerequisites for the Molecular Modelling co-requisite course will be advanced and fast-paced. NOTE: this is not a mathematics department course. You have economic goals. I am neither a con artist nor fungus nor pestilence ghoul/zombie. Tools --> R + R Studio with use of different packages. Manuals and vignettes for packages will be crucial. You will need to read quite a bit. If you’re here, obviously you have your big pants on; neither diapers nor pullups. Assessment Labs Participation Assignments 2-3 Lab Exams This is an immersion course. However integrity must be kept with certain analytical structure; will have moderate level tasks. Augmented with skills assessment in R; moderate amount of open notes where analytical development precedes R implementation. Course Outline --> PART 1: STOCHASTIC DEVELOPMENT FOR MOLECULAR MODELLING Overview of Molecular Modelling Molecular dynamics (MD) with Langevin Dynamics Analytically Developing Langevin Dynamics MD concepts and performing simulations with Langevin dynamics in R. Will try manual development coding in R Will employ specific R packages to compare with manually R development. Comparative observation of simulated data w.r.t. to parameter change. . Monte Carl (MC) Simulations 2-3 Analytical development of practical and relevant MC methods in molecular modelling Explore the fundamentals of MC simulations in R Implement MC simulations to sample different conformations and configurations. Metropolis Monte Carlo (MMC) in R Focus on the Metropolis algorithm for studying thermodynamic properties. Use R to implement MMC simulations and analyze results Brownian Dynamics (BD) in R Overview and Analytical development of BD Relationship between Langevin Dynamics and BD Extend MD knowledge to include BD simulations with stochastic forces Implement BD simulations using R packages with analysis of simulated data w.r.t. parameter change. Stochastic Boundary Molecular Dynamics (SBMD) in R Extend MD simulations to open systems with stochastic boundary conditions. Implement SBMD simulations using R and discuss applications. Stochastic Tunneling Methods in R Introduce the concept of stochastic tunneling in the context of molecular modeling. Implement and analyze tunneling simulations using R. Stochastic Rotational Dynamics (SRD) in R Explore rotational motion of molecules with SRD simulations. Use R packages or custom code to implement SRD simulations and analyze rotational diffusion. PART 2: STATISTICAL DEVELOPMENT FOR MOLECULAR MODELLING Descriptive/Summary Statistics in R Exploring data sets of molecules and their properties. This includes skew and kurtosis Descriptive statistics (including skew and kurtosis) to analyse the distribution of molecular properties obtained from MD simulations. This includes skew and kurtosis. Time-Averaging and Ensemble Averages in R Comprehending the concepts and analytical structure Performing averaging and calculating ensemble averages Extracting meaningful information from MD trajectories Probability Distributions in R Probability distributions in R to model and analyse fluctuations in molecular properties during MSD simulations. Note: distributions of interest to concern thermodynamics, statistical mechanics, etc., etc. Statistical Analysis in R Review of descriptive/ summary statistics implementation (including skew and kurtosis) Density Estimation upon real molecular data sets Goodness of Fit (determining distributions) relevant to encountered distributions earlier. Kolmogorov-Smirnov Shipiro-Wilk Anderson-Darling Maximum Likelihood Estimation (on large data sets) Correlation and Autocorrelation in R Explore correlations and autocorrelations between different molecular properties using R to identify patterns and timescales of motion. Treating simulated cases as well. Dimensionality Reduction and Feature Selection/Importance (DRFSI) Principal Component Analysis (PCA) in R. Implement PCA in R to reduce the dimensionality of MD datasets and identify principal components capturing major sources of variability. If data has non-linearity it may require use of t-SNE or UMAP. Boruta Algorithm and FSelectorRcpp: comprehension and implementation. Comparing both methods with PCA (or t-SNE and UMAP). Multilinear Regression Models can be used to make predictions of kinetic data of a series of chemically similar compounds. The molecular structure of a chemical compound determines its properties. A set of numerical descriptors are calculated to encode information about each of the molecular structures. These descriptors are then used to build statistical models using linear regression to predict the kinetics or activity of interest. Yet, this method is inductive, meaning it depends on having a set of compounds with known kinetic parameters or activities. DRFSI Model Testing/Validation Will like to test our prediction modelling for various cases Gaussian Process Regression in R Concept and analytical structure Applications in Computational Chemistry & Molecular Modelling Implementation practice. Is DRFSI relevant? Model Testing/Validation Will like to test our modelling for various cases Uncertainty and Sampling in Molecular Simulation Our goal is competently comprehending the usefulness and practicality of methods identified in the given articles. How are they implemented with relevance to implemented simulations? Then, very hands-on tasks. Grossfield, A. & Zuckerman, D. M. (2009). Quantifying Uncertainty and Sampling Quality in Biomolecular Simulations. Annual reports in Computational Chemistry, 5, 23–48 Grossfield, A. et al. (2018). Best Practices for Quantification of Uncertainty and Sampling Quality in Molecular Simulations [Article v1.0]. Living Journal of Computational Molecular Science, 1(1), 5067 Farmer J. et al (2017). Statistical Measures to Quantify Similarity between Molecular Dynamics Simulation Trajectories. Entropy (Basel) 19(12): 646. Statistical Mechanics Concepts in R Review of statistical mechanical concepts and structure relevant to molecular modelling. Apply statistical mechanics concepts in R to connect statistical averages obtained from MD simulations to thermodynamic quantities. Monte Carlo Methods for Analysis in R Demonstrating how Monte Carlo methods can be applied in R for both simulations and statistical analysis, emphasizing their versatility. Co-requisite: Molecular Modelling. Process Dynamics & Control I The dynamic behaviour and automatic control of processes are studied. Mathematical tools for analysing the transient behaviour of open and closed-loop systems are presented. The MANDATORY steps of controller development are treated: 1.Process characterization Mechanical, chemical, thermodynamic, thermochemical, combination Developing mathematical models of the processes 2.Controller design 3.Implementation Methods for assessing system stability and performance are investigated and are used in the design of controllers. 4. System simulation Prototypical texts --> Process Dynamics and Control (2nd ed) Seborg, Edgar, and Mellichamp, Wiley 2004 Chemical and Bio-Process Control, Third edition James B. Riggs and M. Nazmul Karim 2006 Ferret Publishing, Lubbock Texas Such texts can possibly be substituted with Springer and CRC press texts. Obligations --> A. Students are expected to be proficient at specifying and solving systems of differential equations in the time domain and using transfer functions. Depending on severity of the size of the system of differential equations you may only need to derive or model them and have a computational tool such as Mathematica complete the drastic time costing task; programming and homework assignments. B. Frequency response methods are introduced, as is the development and implementation of controller enhancements including feed-forward (feedback) and cascade control. Mathematical models of unit operations, transfer functions, feedback and feed-forward control, stability, instrumentation, digital control systems; computer methods, including simulation and commercial software use. Students will be tested on this material. C. Course is also constituted by activities in lab/field operation sites. Such consists of operating and evaluating PID flow, level, accumulation, and temperature control systems that operate using COCO (+ Chemsep) and/or DWSIM (+ Chemsep) Mathematica and SystemModeler/Modelica tools STANJAN Microcontrollers, interface cards, chemistry lab equipment, DAQ D. Particular tasks to accomplish 1. Characterising and modelling systems to acquire governing differential equations. Expressing time-dependent differential equations which describe real operations for single input/single output (SISO) systems. 2. Constructing control block diagrams (i.e. control logic diagrams) for everyday and conventional examples of controllable systems. 3. Implement Laplace transforms to evaluate process dynamics and to solve differential equations 4. Defining transfer functions for dynamic systems. 5. Evaluate and contrast open loop and closed loop behaviour of dynamic systems. 6. Express time-dependent differential equations which describe real operations for multiple input/multiple output (MIMO) systems. 7. Mathematically model time-dependent real processes. 8. Demonstrate understanding of the linkages between processes, dynamic behaviour of process inputs and outputs, and idealized transfer functions. 9. Analyse real or modelled process behaviour for identification and design of effective feedback control strategies, including the use of characteristic equations and specifying the mode of PID control. 10. Logically think through problems from conception to design. 11. Utilize mathematical and practical tools, say, Mathematica, SystemModeler, COCO (+ Chemsep), DWSIM (+ Chemsep) and STANJAN. 12. Familiarity with process control hardware, how it integrates with the process, and how it is represented in P&ID diagrams. 13. Demonstrate skills necessary to tune and troubleshoot basic feedback control strategies to SISO systems. 14. Demonstrate professional accountability for their dynamic modelling and control strategy recommendations. 15. Recommend improvements to systems involving cascade, ratio, and feedforward control. E. Lab Experiments (not necessarily in given order) For the following activities, not all will be done singularly, rather each activity can be an element of a meaningful and practical system for service. Such implies that for an intended project constituted from such activities, each activity to makes the system will be modelled, having controller development, then simulation. To then bring all relevant activities into a unit to be properly harmonized (calibrated) to produce the desired project. For each project, first, there must be analytical development with design, modelling, and controllers and simulation before physical development of experiments. Many experiments will include acquiring sensing data and voltage/current data to model the systems’ operation(s). --Immersion with COCO (+ Chemsep), DWSIM (+ Chemsep) & STANJAN --Immersion into the Mathematica, SystemModeler/OpenModelica --Virtual (Arduino) microcontrollers in Mathematica (or whatever) --Data acquisition with microcontrollers Voltage/current data Data acquisition (pressure, level, Ph, temperature) Storage: file types such as .xlsx, .csv, etc., etc., etc. 1. FLUIDS & ACIDITY ACTIVITIES: Note: may have to account for specification of piping configurations (say variance in diameter and pressure “resistance”, “capacitance”, etc.) when considerable. Fluids could be Koo-Aid mixtures, food colouring, or substances deemed low security/hazard risk. --Centrifugal pumps Modelling Controller development & characteristics --Solenoid control valve Modelling Controller development & characteristics --Pneumatic solenoid control valve Modelling Controller development & characteristics --Pressure control using PID controller (at various terminals, etc.) --Water flow control under oscillatory load disturbances --Liquid level sensing & controller --Interacting water tank level control --Integrating tank level control --Cascade control --Dye concentration control with load disturbances --Single tank pH control/controller --4-tank level water control --Multi-tank pH control Note: gases counterparts are also possible 2. TEMPERATURE ACTIVITIES: --Tuning of controller parameters --Temperature control using PID controller --Temperature control with variable time delay --Temperature and level control in a water tank --Dynamics of higher order systems --Measuring the heat of chemical reactions and heat capacity May or may not also require aquarium air pump --Infrared temperature sensing and alarm/trigger 3. COMPOSITION ACTIVITY (implementation of Raman spectroscopy) 4. PROJECTS (combination of fluid, acidity and temperature) Prerequisites: General Chemistry I & II; General Physics I & II; ODE; Calculus III; Chemical Physics I Process Dynamics & Control II Process Dynamics & Control Design II is concerned with the usage of techniques for control of digital systems, systems operating under constraints, optimal control that takes into account control efforts and control of multivariate processes. After learning the course the students should be able to: --Analyse and design advanced control systems --Understand industrial applications of control theory. --Learn the complex control techniques --Identify, formulate and solve problems for control system design of complete chemical plants or whatever processing facilities. Must have emphasis on design, modelling and control of real systems. Lab Experiments --> Note: COCO (+ Chemsep) and/or DWSIM (+ Chemsep) software, STANJAN, Mathematica, SystemModeler/Modelica will accommodate all labs. I. There will advance repetition of chosen experiments from prerequisite towards competency development. II. Bi-propellant liquid rocket engine (virtual) NOTE: for bi-propellant liquid rocket engines there’s necessity for competent rocket engineering analysis. Subjects like characteristics of oxidizer and fuel, O/F dynamic, turbopumps and values are critical. Can still be simulated. III. Will also take on more advance experiments. All will have both analytical development, hands-on real world development and lab/field testing Liquid dosing system Washer chemical system (dyes, muck, etc. can be used for safety) Chemicals control/monitoring system (a micro pool or other system) IV. Industrial Systems Processes (virtual) Characterisation Analytical Modelling (system modelling development, and control modelling) Advance implementation of mentioned software Syllabus --> --Process Characterization Mechanical, chemical, thermodynamic, thermochemical, combinations Developing mathematical models of the processes Controller design and implementation System simulation --Review of dynamic behaviour of linear systems and control system design for linear closed loop systems, Laplace transforms. --Analysis and Design of Advanced Control Systems: Feedback control of systems with large dead time, Cascade control, Feedforward control, Ratio control, Feedforward-Feedback control, Adaptive control, Inferential Control. --Discrete-Time control systems: Sampling and Z-Transform, Open-Loop and Closed-Loop response, Stability analysis of discrete-time control systems. --Multiple-Input, Multiple-Output (MIMO) Systems: Introduction to MIMO systems, degrees of freedom and number of controlled and manipulated variables, generation of alternative loop configurations, extension to interacting systems. --Analysis of Nonlinear Control Systems: Examples of nonlinear Systems, Methods of Phase-Plane analysis. --Design of control systems for complete plant: Case Studies. Prerequisite: Chemical Process Design I Note: elementary research participation begins at the upper sophomore level for “winter” and “summer” semesters, directed towards measurement and verification of fundamental characteristics or properties of matter. Many activities can be done before matriculating into courses with such activities. Students are also invited (or encouraged) to repeat or augment research/experimentation that they have done before if interested; for such students repetition has some dependence on current policy applied concerning beneficial experience towards new students, involving interest count and qualification. Note: any described spectroscopy activity will be operated independently from any lab course concerning spectroscopy. Such spectroscopy activities outside of courses concern building retention, competency and professionalism. Activities/Projects are also attractive and open to Physics majors. Consider a determined amount of trial samples to establish consistency; such may be relevant to theoretical or consensus values, etc. Can be extended to incorporate upper level sophomores. There will be a secure database archive for all participants and supervision constituents for respective activity in chronology. Activities will be classified. Apply samples, trials and controls whenever relevant. Activities repeated can be added to transcripts upon successful completion. Repeated activities later on can be given a designation such as Advance “Name” I, Advance “Name” II. As well, particular repeated activities serve to towards developing true comprehension, competency and professionalism. FOR ACTIVITIES IN THE “SUMMER” AND WINTER” SESSIONS ALL PARTICIPATING STUDENTS, ASSISTING/ADVISING INSTRUCTORS AND PROFESSORS MUST BE OFFICIALLY RECOGNISED; REQUIRES BOTH CIVILIAN ID AND STUDENT/FACULTY ID FOR CONFIRMATION OF INDIVIDUAL. THERE WILL ALSO BE USE OF IDENTIFICATIONS FOR ACTIVITIES FOR RESPECTIVE SESSION. SECURITY AND NON-PARTICIPATING ADMINISTRATION WILL ONLY IDENTIFY RESPECTIVE ACTIVITY BY IDENTIFICATION CODE. SECURITY AND NON-PARTICIPATING ADMINISTRATION MUST NEVER KNOW WHAT ACTIVITIES IDENTIFICATION CODES IDENTIFY: < Alpha, Alpha, Alpha, Alpha > - < # # # # # > - < session > - < yyyy > Such chemistry activities will also warrant criminal background check (CBC) in order to participate. Severely threshold may vary depending on administration. Administrators will provide dated letters of confirmation of thorough CBC to student affairs and other appropriate administration. Such also may include screening that’s parallel to customs & immigration processing where certain levels of criminal history warrants rejection. Email and physical letters with data. Such CBC protocol will not explicitly identify any particular titles or descriptions of any activity, rather, will only convey code as above. It may be the case some activities can be grouped and given a major title together; however, detailed descriptions will be required. Activities will be field classified. Particular projects of interest being stationary: --Organic Synthesis Laboratory Reinforcement A major pursuit is to acquire meaningfulness and relevancy with synthesis experiments, being both practical and economic, relevant to premier industry objectives. Note: such will be orchestrated in a manner where at a certain period in the activity students from biochemistry and microbiology can be integrated towards competently and efficiently pursuing their goals. Chemistry students must carry out their independent detailed pursuits with integrity. However, students of biochemistry and possibly microbiology will have unique debriefing and intelligence gathering suitable for their level, to then be integrated into activity at the appropriate time, where questions and issues of their interest are structured, unique and independent to chemistry (and possibly physics) students. Will apply spectroscopy activities for determination of purity. --Density Determination of Liquids with Varying Temperature Analyse the following journal article pursue development of experiment: Kazys, R. et al, Ultrasonic Technique for Density Measurement of Liquids in Extreme Conditions, Sensors 2015, 15, 19393-19415 1. For calibration, distilled uncontaminated water after undergoing a practical and economic degassing process towards experimentation, and compare results to professional data of the thermodynamic behaviour of water concerning density measure. 2. Repeat process for distilled water that never underwent degassing. 3. Will pursue process for different liquids that are safe for temperature range considered. 4. Consider the following journal article: McLinden, M. O., & Splett, J. D. (2008). A Liquid Density Standard Over Wide Ranges of Temperature and Pressure Based on Toluene. Journal of research of the National Institute of Standards and Technology, 113(1), 29–67. Developed experiment from Kazys et al (2015) will then be repeated for Toluene. Results will be compared. 5. Then consider the following theoretical journal article: Watson, K. M., Thermodynamics of the Liquid State, Ind. Eng. Chem., 1943, 35 (4), pp 398–406 Analyse and determine whether models are practical to compare with experimentation and the article of McLinden and Splett (2008). If so, try to establish consistency for density measures with experimentation and that of McLinden and Splett (2008). Note: for each liquid sample there will be determined multiple trials; respective liquid will be allowed to return to a starting temperature (likely naturally). It may be possible that readings for sensors will have time keep in programming. Source of heat will have controlled influence on samples. Confirmation with professional databases will also be applied. --Molecular Weight Determination by van der Waals’ Equation, Ebullioscopy, Cryoscopy, Rast’s method. To carry out such experiments (with numerous trials respectively); to make use of different molecules as well. Identify the parameters, quantities or properties that are possibly related among the specified experiments. Quantitatively establish such “correlation” if possible; derive or deduce a (mathematical) model that connects them. Confirmation with professional databases will also be applied. --Molecular Refraction Comprehend the notion or methodology. Identify the tools and logistics; Identify (three known) forms of the molecular refractivity equation, and how each form best serves towards experimentation. Oliveros-Belardo, L., Jannke, P., J. 1958. Correlation of Molecular Refraction with Structure in the Terpene Series, Journal of the American Pharmaceutical Association, Volume 47, Issue 1, 62-66. Other compounds are possible with multiple with trials. Observe whether there’s correlation between molecular refraction and structure. --Chosen spectroscopy methods orchestrated in lab Can be prep or reinforcement for Instrumental Analysis Lab course. Biology students welcomed. NOTE: will also use software with spectroscopy prediction ability to be compared to actual lab spectroscopy investigation, with comparison to professional databases. --Forced Constants from Vibrational Frequencies for Molecules A. Physics Newtonian theory for the harmonic oscillator and concept of vibrations (identifying the frequency model). Review of quanta in regards to radiation in relation to Planck’s constant and wave number. For Quantum Mechanics in the harmonic approximation the potential energy is a quadratic function of the normal coordinates. Why the Schrodinger Wave Equation? Solving the Schrodinger Wave Equation to acquire the energy states model for each normal coordinate (and recognise how frequency or wave number is associated). Where are we going with this? B. Vibrational Spectroscopy Motion and frequency effects in molecules by Raman spectroscopy and Infrared spectroscopy; how the types of radiation phenomena lead to quanta perturbations, and to the presence of mechanical physics and mechanical physical models to reveal the traits or properties of interest; how spectroscopy graphs relate to the mechanical phenomena and “chemical” interpretation. Properties or characteristics of interest Finger print Functional Groups Structure Changes in concentration of a species during a reaction Properties of bonds (bond, strength, force constraints) State and order parameters of phase transitions M. Reichenbacher and J. Popp (2012). Challenges in Molecular Structure Determination, Springer-Verlag Berlin Heidelberg, pp 63-143 Concerning both spectroscopy methods for each molecule identify what types of dynamic will it take on (harmonic, anharmonic, or whatever else possible); normal modes and wave number determination (for common place or abundant types of bonds; use of coordinate systems to determine dynamics on the curve; the greeks and what they mean in analysis. Exclusion rule, temperature effects and the exclusion rule. Nevertheless the various dynamics may be numerous and multi-dimensional. Customarily high focus with such types of spectroscopy towards organics, but activity may also include the study of inorganics. i. Infrared Spectroscopy for organics: concerns identifying the functional group region and the fingerprint region in Infrared spectroscopy. Pursuit of identifying bonds in molecules. Where a particular bond absorbs in the IR depends on bond strength and atom mass. Stronger bonds (say, triple > double > single) vibrate at a higher frequency, so they absorb at higher wave numbers. Bonds with lighter atoms vibrate at higher frequency, so they absorb at higher wave numbers. Four regions of an IR spectrum Bonds to hydrogen Triple bonds Double bonds Single bonds Key effects: conjugation; inductive effects; steric effects; strain effects; hydrogen bonding. IR spectroscopy is often used to determine the outcome of a chemical reaction. ii. Infrared Spectroscopy for inorganics Like organics pursuit of identifying bonds in inorganic molecules. As relevancy of bond strength and atom mass. Observation of strong bonds and the vibrations at frequencies and absorbance at specific wave numbers. Observance for case of lighter atoms as well with frequency, absorbance and wave number. iii. Analogy to IR spectroscopy for Raman concerning organics iv. Analogy to IR spectroscopy for Raman concerning inorganics Note: Raman spectroscopy and infrared spectroscopy schemes can be built and function exceptionally; a means to sustain independent skills. Then compare with proprietary equipment and professional databases. Note: all such will be orchestrated in a manner where at a certain period in the activity students from the biological sciences can be integrated towards competently and efficiently pursuing their goals. Chemistry (and possibly Physics) students must carry out the detailed description as above. However, students of the biological sciences will have unique debriefing and intelligence gathering suitable for their level, to then be integrated into activity at the appropriate time, where questions and issues of their interest are structured, unique and independent to chemistry (and possibly physics) students. --Molecular Modelling Reinforcement Concerns reinforcement (or crash immersion) of topics, algorithms and simulation in Molecular Modelling. General Assisting literature: Molecular Modelling Texts Introduction to Computational Chemistry, Jensen, 2007 Essentials of Computational Chemistry, Cramer, 2004 Molecular Modelling Basics, Jensen, 2010 Simulation Texts Molecular Modeling – Principles and Applications, Leach, 2001 Molecular Modelling and Simulation, Schlick, 2010 Computer Simulation of Liquids, M. P. Allen & D. J. Tildesley, 1987 Understanding Molecular Simulation, Daan Frenkel & Berend Smit, 2002 The Theory of Intermolecular Forces, Anthony Stone, 2013 Quantum Chemistry Algorithms Theory Modern Quantum Chemistry, Szabo & Ostland, 1982 (Dover) Quantum Chemistry, 3rd Ed., John Lowe and Kirk Petersen, 2006 Molecular Orbital Theory Texts Frontier Orbitals – A Practical Manual, Nguyen Trong Anh, 2007 Molecular Orbitals & Organic Chemical Reactions, Ian Fleming, 2010 The Theory of Intermolecular Forces, 2nd Ed., Anthony Stone, 2013 This set of software is focused more towards biochemical purposes: << VMD (with NAMS), GROMACS, VOTCA, Desmond, UCSF Chimera, Molsoft, CCPN, RedMD + RedMDStream (http://bionano.cent.uw.edu.pl/software/) >> << TINKER >> This set of software is focused more towards computational chemistry and physics: << Dalton, CP2k, Firefly, Gaussian, GAMESS-US, MOLDEN, NWchem, GPAW, Octopus, ORCA, FreeON, PUPIL, VOTCA, BOSS >> NOTE: will also use software with spectroscopy prediction ability to be compared to actual lab spectroscopy investigation, with comparison to professional databases. Additional computational pursuits (determine if/when constructive in activity) --> Try to situate coherently, tangibly and constructively with activity progression. 1. Density functional Theory Neese, F., Prediction of Molecular Properties and Molecular Spectroscopy with Density Functional Theory: From Fundamental Theory to Exchange-Coupling, Coordination Chemistry Reviews 253 (2009) 526–563 NOTE: will also use software with spectroscopy prediction ability to be compared to actual lab spectroscopy investigation, with comparison to professional databases. 2. Coordinate Chemistry Comba, P. and Kerscher, M., Computation of Structures and Properties of Transition Metal Compounds, Coordination Chemistry Reviews 253 (2009) 564–574 Tsipis, A. C., DFT Flavour of Coordination Chemistry, Coordination Chemistry Reviews 272 (2014) 1–29 3. Unorthdox Nakatsuji, H. et al, Solving the Schrodinger Equation of Atoms and Molecules without Analytical Integration Based on the Free Iterative-Complement-Interaction Wave Function, Physical Review Letters, 99, 240402 (2007), Dec 14 2007 Nerenberg, P. S. and Head-Gordon, T., New Developments in Force Fields for Biomolecular Simulations, Current Opinion in Structural Biology, Volume 49, April 2018, pages 129 – 138 4. Fast Multiple Method Interests Zhou, R. and Berne, B. J. (1995). A New Molecular Dynamics Method Combining the Reference System Propagator Algorithm with a Fast Multipole Method for Simulating Proteins and Other Complex Systems. J. Chem. Phys. 103 (21). Pages 9444 - 9459 Darve, E., The Fast Multipole Method: Numerical Implementation, Journal of Computational Physics 160 , 195 – 240 (2000) Kurzak, J., & Pettitt, B. M. (2006). Fast multipole Methods for Particle Dynamics. Molecular Simulation, 32(10-11), 775–790. Chau N.H. (2013) Parallelization of the Fast Multipole Method for Molecular Dynamics Simulations on Multicore Computers. In: Nguyen N., van Do T., le Thi H. (eds) Advanced Computational Methods for Knowledge Engineering. Studies in Computational Intelligence, vol 479. Springer, Heidelberg Ohno, Y. et al (2014). Petascale Molecular Dynamics Simulation using the Fast Multipole Method on K Computer. Computer Physics Communications. Volume 185, Issue 10, Pages 2575 - 2585 EXTRACURRICULAR --> Viscosity and Temperature Eckler, L. H, and Nee, M. J., A Simple Molecular Dynamics Lab To Calculate Viscosity as a Function of Temperature, J. Chem. Educ., 2016, 93 (5), pp 927–931 1. For calibration, distilled uncontaminated water after undergoing a practical and economic degassing process towards experimentation, and compare results to professional data of the thermodynamic behaviour of water concerning density measure. 2. Repeat process for distilled water that never underwent degassing. 3. Will pursue process for different liquids that are safe for temperature range considered. Will also compare with software like VMD (with NAMS) or other listed above for various molecules, compounds, etc. Additionally, from simulation result findings will try to establish consistency with the following: Seeton, C. J., Viscosity–Temperature Correlation for Liquids, Tribology Letters, Vol. 22, No. 1, April 2006 Will also investigate whether the listed software provide sound treatment for activation energy. The following journal article can serve as guide: Messaadi, A. et al, A New Equation Relating the Viscosity Arrhenius Temperature and the Activation Energy for Some Newtonian Classical Solvents, Journal of Chemistry, Volume 2015, Article ID 163262, 12 pages --Determining and computing properties of elements and molecules/compounds (investigation may or may not be in listed order). Will be given random unidentified chemical structures to investigate. Specific properties: Mechanical Strengths (if relevant or practical) Specific heat Thermal conductivity Activation energy Reactivity (concerns different circumstances, ambiances) Incendiary character (null, mild, aggressive) Electrical conductivity Magnetic properties Optical properties Resistance to high energy electromagnetic perturbation Phases Modelling Solubility (if relevant or practical) Acidity (if relevant or practical) Typical ambiances for respective stable sample Note: though a respective substance may show high measure for one property, overall it may be unfavourable when considering other properties. An ideal example would be high conductivity, but also aggressive concerning incendiary behaviour. Note: it’s important that there be integrity in students’ work without exposure to databases prematurely. Contrary behaviour is often a tell-tale revelation for the gap between competent students compared to “posers”. 1. It’s important to understand the chemistry and physics behind the prediction of such properties. To vindicate such chemistry and physics, one will begin with use of simple compounds, molecules, etc. where findings are compared to real “hands-on” investigative laboratory/field operation procedures for determination. Findings will be compared with professional databases and molecular modelling software. Note: activity will consider both organic and inorganic substances Note: pursuit of recognising functional groups is only one means of determining some chemical characteristic of molecules. Some cases, resorting to different types of spectroscopy in lab will be one of many investigative means applied. 2. Will then proceed with large complex inaccessible molecules and compounds where physics and chemistry will be compared with computational and molecular modelling software usage, compared with professional databases. 3. Chemical Reactivity Theory Will have a density functional view (incorporating calculus models). Will like to develop possible experimental schemes to validate CRT with DFT. Will then like to pursue CRT with alternatives to DFT if there exists such, and will like to compare with DFT analytically and experimentally if possible. Modelling and computational software will be a compliment (not a substitute) for analytical modelling and experimentation. 4. What makes a substance flammable? Will employ the following means Analytical modelling Molecular modelling with modelling/computational software Chemical Reactivity Theory Experiments Note: density, phase transitions, ignition temperature, combustion temperature, adiabatic flame temperature, stoichiometry may be of high interest concerning the the following elements in play Potassium Aluminium Magnesium Alkali metals Helium Oxygen Hydrogen Nitrogen Nitrous oxide Noble gasses Waxes NOTE: an issue, determining when employing condensed matter chemistry is sensible or practical towards investigating the specific properties mentioned earlier. To study the functionalities and chemical reactions of condensed matter with multi-level structures, characterized by strong intermolecular forces and local organizational order. In this perspective, we suggest possible ways to study their properties and reactions in relevance to specific organizational characteristics of their surroundings in the condensed-matter states, using solid-state materials with special functions and living organisms with complex high-order structures. Will all such translate to strong intelligence on the specific properties mentioned earlier?

--Graphene Research Synthesis of (different types of) graphene by various means. Choosing out of the most economically efficient. Quantitative modelling of chemical processes for prediction of consumption and product(s), compared to empirical results from lab activities. Mentioned software can be used to model and analyse anticipated product(s), and towards prediction of properties (electrical conduction, heat conduction, temperature threshold before chemical change, strength included). Determination of chemical properties (includes properties in water such as pH). Then to experimentally verify the predicted properties, and how they can be beneficial to various industries. Also includes prediction of hazard assessment for the environment (air, water, animal & plant metabolics, etc.). Examples: https://www.nature.com/subjects/synthesis-of-graphene https://hackaday.com/2012/12/21/making-graphene-with-a-dvd-burner/ https://www.cornellcollege.edu/physics-and-engineering/pdfs/phy-312/Theint-Aung.pdf --Desalination of Water with Graphene A. The following literature are idea guides for analytical development: David Cohen-Tanugi and Jeffrey C. Grossman. (2012). Water Desalination across Nanoporous Graphene. Nano Letters 12 (7), 3602-3608 Safaei, S. and Tavakli, R. (2017). On the Design of Graphene Oxide Nanosheets Membranes for Water Desalination. Desalination, Volume 422 pages 83 – 90 Li, Z. (2018). Optimal Design of Graphene Nanopores for Seawater Desalination. J. Chem. Phys. 148 , 014703 Shao, C., Zhao, Y. and Qu, L. (2020). Tunable Graphene Systems for Water Desalination. CHEMNANOMAT, Volume 6 Issue 7, pp 1028 – 1048 B. The following is just one literature for simulation (will not be restricted to it): Deepthi Konatham, Jing Yu, Tuan A. Ho, and Alberto Striolo (2013). Simulation Insights for Graphene -Based Water Desalination Membranes. Langmuir 29 (38), 11884-11897 Will employ molecular dynamics and simulation software for various candidate graphene species. This set of software is focused more towards biochemical purposes: << VMD (with NAMS), GROMACS, VOTCA, Desmond, UCSF Chimera, Molsoft, CCPN, RedMD + RedMDStream (http://bionano.cent.uw.edu.pl/software/) >> << TINKER >> This set of software is focused more towards computational chemistry and physics: Dalton, CP2k, Firefly, Gaussian, GAMESS-US, MOLDEN, NWchem, GPAW, Octopus, ORCA, FreeON, PUPIL, VOTCA, BOSS Will apply molecular dynamics and such software to acquire environment conditions and processes. Must be competent with all variables to apply: Feasible environmental conditions Real world constituents in seawater Polymer Chemistry Possible Chemical reactions (pre and post) with effects Products and by-products Molecular Dynamics Effective temperature ranges Acidity (before, during processes and after) Graphene Integrity (before, during processes and after) C. Pursue designing and synthesizing cheap/basic graphene to test for desalination efficiency and integrity. --Making Solar Cells For experimental solar cells development preference is to operate with bigger “acrylic” plates. NOTE: we are going from thorough chemistry (modelling and simulation) to sound physics and modelling before actual experiments. It’s crucial that students are able to develop prediction models for current and voltage before experiments development. We want graphs for current and voltage from experiments. -DSSC examples NurdRage – Making a Solar Cell – TiO2/Raspberry based – YouTube Neal Abrams – Constructing a Dye Sensitized Solar Cell – YouTube JuiceFromJuice – DSSC – YouTube -Perovskite examples: UW Clean Energy Institute – Constructing a Perovskite Solar Cell – YouTube The Physics Point – Preparation of high quality Perovskite thin films – YouTube Breitweiser Products – Organic – Inorganic Perovskite Hybrid Solar Cell – YouTube HONORABLE MENTION (if practical): Robert Murray-Smith – A Solar Cell From a Broken LCD Screen – Part 1 -Reclaiming the Materials – YouTube Robert Murray-Smith – A Solar Cell From a Broken LCD Screen – Part 2 -Recovering Indium – YouTube --Organic Solar Photovoltaics Project may emphasize a strong grasp of Organic Chemistry II, Polymer Chemistry and Physical Chemistry II. The latter towards grasping a solid understanding of band theory, whereas the earlier two mentioned courses concern advance understanding of engineering and optimal strategies with organics. Apart from the physics, a major task is delving into the chemistry of organic constituents in fabrication, say, identifying construction of their chemical makeup that yields the appropriate character for such (compared to dominant inorganic counterparts); such chemistry will go more deeply than the listed journal articles, relying on various chemistry software provided towards model building, predictions and character simulation. To acquire concise quality and characteristic of a general polymer towards fabrication; further identifying the best prospect candidates out of the vast archives of known polymers or organic compounds. For Polymers or compounds of interest to identify possible synthesizing method(s). Also, one may end up possibly discovering something new. Possible key terms: Organic semiconductor materials Organic semiconductor materials deposition techniques Optical and electrical properties of organic materials Organic semiconductor device architectures Organic cell electrode patterning and etching Successive depositions of the organic layer stack followed by metallization Encapsulation Organic solar cell testing-illuminated I-V, quantum efficiency, cell performance parameters Photo-Nernst Photo-Seebeck Testing and calibration of organic solar cells Journal Articles to possibly assist: Mayer, A., C., et al, Polymer-Based Solar Cells, Materials Today, Volume 10, Number 11, November 2007. Cheichi, R., C., et al, Modern Plastic Solar Cells: Materials, Mechanisms and Modelling, Materials Today, Volume 16, Numbers 7/8 July/August 2013 �� Nelson, J., Polymer: Fullerene Bulk Heterojunction Solar Cells, Materials Today, Volume 14, Number 10, October 2011 M.C. Scharber, M., C., and Sariciftci, N., S., Efficiency of Bulk-Heterojunction Organic Solar Cells, Progress in Polymer Science 38 (2013) 1929–1940 Xu, T., and Yu, L., How to Design Low Bandgap Polymers for Highly Efficient Organic Solar Cells, Materials Today, Volume 17, Number 1 January/February 2014 Qian, D., Zheng, Z., Yao, H. et al. Design Rules for Minimizing Voltage Losses in High-Efficiency Organic Solar Cells. Nature Mater 17, 703–709 (2018). Will investigate the photon wavelength absorption range of graphene type (or other polymer) photovoltaic cells and reason for such in terms of respective construction (there will be various); compared to various inorganic or conventional materials used to construct solar cells. Comparative quantum efficiency and comparative cell performance parameters. Following, students may propose their own theoretical strong organic solar cells based on research on polymers from various databases or whatever (if able). There must be integrity with chemistry, physics and circuit modules. Apply journal articles and texts that amplify progressive and advancing ideas in the field. Software mentioned in different places can apply, to serve only as computational, visual and exhibition assists. Ultimately: will try to synthesis graphene types that can be relevant to photovoltaic cells. Then pursuit of organic photovoltaic cells to operate. All prior intelligence and data will be necessary to develop credible research that can be exhibited. --Metal Aerogels Research Synthesis of (different types of) metal aerogels by various means. Choosing out of the most economically efficient. Quantitative modelling of chemical processes for prediction of consumption and product(s), compared to empirical results from lab activities. Mentioned software can be used to model and analyse anticipated product(s), and towards prediction of properties (electrical conduction, heat conduction, temperature threshold before chemical change, strength included). Determination of chemical properties (includes properties in water such as pH). Then to experimentally verify the predicted properties, and how they can be beneficial to various industries. Also includes prediction of hazard assessment for the environment (air, water, animal & plant metabolics, etc.). Example guides: Liu, W. et al 92015). Noble Metal Aerogels-Synthesis, Characterization, and Application as Electrocatalysts. Acc. Chem. Res. 48, 154−162 Applied Science - Supercritical Drying Chamber for Aerogel Production -YouTube: https://www.youtube.com/watch?v=FZeaAnguXCs Applied Science - Making Silica Aerogel at Home - YouTube: https://www.youtube.com/watch?v=X24np30GS2o --Speciation of Metals and impact on environment An issue is to find (contaminated) environments with such robustness in metal ion variety, whether aquatic or soil or flooding. Spectroscopy may be needed for identification. Goal is to develop active research verification of the following: Millero, F., Speciation of Metals in Natural Waters, Geochemical Transactions-Springer, 2001, 2, 57 Gupta, V. K., Ali, I., Aboul-Enein, H. Y., Metal Ions Speciation in the Environment Distribution, Toxicities and Analyses, Developments in Environmental Science, volume 5, 2007, pp-33-56 If soluble, include effects on bedrock, sedimentary types, igneous types and metamorphic types. Note: this activity may draw interest from students in the biological sciences and geology. --Review and Research on Biodegradable Polymers Journal articles and texts example resources: Okada, M., Chemical Synthesis of Biodegradable Polymers, Prog. Polym. Sci. 27 (2002) 87-133 Song, J., H., et al, Biodegradable and Compostable Alternatives to Conventional Plastics, Philos Trans R Soc Lond B Biol Sci., 2009 Jul 27; 364 (1526): 2127-2139 Guo, W. et al, (2012), Introduction to Environmentally Degradable Parameters to Evaluate the Biodegradability of Biodegradable Polymers, PLoS One, 7 (5) Rieger, B., et al Synthetic Biodegradable Polymers, Advances in Polymer Science 245, Springer Heidelberg Dordrecht London New York, 2012 Ren, J., Biodegradable Poly (Lactic Acid): Synthesis, Modification, Processing and Applications, Tsinghua University Press, Beijing and Springer Heidelberg Dordrecht London New York, 2010 # Part I Following the development of effective analysis of such resources above, students will engage in computational activity via software listed for building, simulations and predictions of polymers, compounds, etc. A means to establish consistency with such resources above. As well, students can access databases of numerous polymers that fit the desired characteristics described in such resources towards analysis with software. Polymers of digestion drug delivery, say, encapsulation plastics used in the construction of pills (each company may have different polymers). As well, encapsulation plastics of laundry detergent “pods” or “power packs” (each company may have different polymers). To identify the names (informal and chemical) and chemical structures. To analyse how they disintegrate in the digestive tract. Polymers easily degradable in terrestrial environments without hazardous by-products Polymers easily degradable in aquatic environments without hazardous by-products. The are very sensitive cases: Freshwater Environment State or By-products should not considerably alter eco-systems Treated water (in the case plastics have infiltrated) State or by-products should not be hazardous with digestion Seawater (not saltwater) State or By-products should not considerable alter eco-systems Numerous fish and aquatic mammalian digestive tracts; towards pleasant digestive function in aquatic animals. # Part II Part two of project will be acquisition and/or synthesis of chosen polymers of interest. Test samples of each polymer are placed in replicated environments of different climates to observe and acquire on the disintegration process. To acquire progressing eco-toxicity data through the duration of experiment or at experiment termination. --Engineering bioplastics What are bioplastics? How did they become considerable today? Why are physical properties important for bioplastics? What are they? What is a plasticizer? Why is it important? Describe polymerization….what does it mean? What are some challenges that bioplastics face that keeps them from dominating the industry? MAJOR SKILLS TO INCORPORATE: Intelligence on Substances (volatilities and dangers) Sources such as the National Library of Medicine: PubChem The Chemistry of Polymers Different polymers and molecules expected Detailed analysis of all chemical process (to include thermodynamics or thermochemical as well) Chosen software to model and simulate chemical process (to include thermodynamics or thermochemical as well) Analytical Chemistry (AC) The level of AC applied in activity may or may not be advance as what is encountered in a good AC course. Life Cycle Assessment (LCA) For the various experiments and potential uses of the bioplastics LCA will be applied. NOTE: in the future more advance biomaterials than what is detailed may be pursued, depending on the operational risk levels, economics, and observed maturity and competence. PART A1 Creating and testing a protein-based polymer bioplastic: gelatin The first bioglass recipe makes transparent sheets that can be used for replacing the glass in your picture frames. It has a small amount of a plasticizer in it, therefore, it will not be as flexible and its glass transition temperature will be different than that of a polymer with a large amount of plasticizers. The plasticizer is the water and glycerol mixture and the polymer is the gelatin. The polymer to plasticizer ratio is typically 4:1. Glycerol (or glycerin, glycerine) is a simple polyol compound. It is a colorless, odorless, viscous liquid that is widely used in pharmaceutical formulations. Glycerol has three hydrophilic hydroxyl groups that are responsible for its solubility in water and its hygroscopic nature. The glycerol backbone is central to all lipids known as triglycerides. Glycerol is sweet-tasting and of low toxic. Due to humidity conditions, the amount of plasticizer can be increased or decreased so that the bioplastic works for the intended “environment”. Pre-experiment Checklist Materials 1 glass heating flask/beaker or a pot 1 set of metal measuring spoons or a glass graduated cylinder 1 pair of scissors (optional) 12.6g (2 tsp) of glycerol 100 ml water 12.0g (4tsp) of gelatin 1 large metal spoon Hot plate or Bunsen burner 25cm x 15cm brownie/loaf pan or dish (preferable nonstick for clarity) Sandpaper or file or scissors Access to a refrigerator and freezer Making Bioglass 1. Measure out 100ml of (1%) glycerol solution 2. Add 12.0g of gelatin to glycerol solution 3. Stir this mixture. 4. Heat the mixture until a slight bubbly film occurs on the surface (slightly before boiling, approx. 95 C). 5. Remove heat and stir again so there are no lumps. 6. Wait for two to three minutes to allow froth to collect upon mixture surface. 7. Remove froth with a spoon; try to leave as much clear fluid in pot as possible. 8. Pour clear liquid into desired mold (pan). 9. Once liquid solidifies, remove mold (30-60 min.) 10. Trim solid plastic as needed (scissors are acceptable if plastic is still slightly soft, sand paper or a file may be appropriate is mold is very hard). Data Analysis 1. Compare your plastic to other plastics. What are differences and similarities? 2. Does your plastic scratch easier than other plastics? Why or why not? 3. Can you see light through it? 4. How flexible is it? Compare the flexibility of your plastic to plastic bottles or plastic wrap. PART A2 Testing Bioglass Now, you can perform tests on your bioplastic. You will attempt to determine the glass transition temperature of your bioplastic. Normally, the glass transition temperature, Tg, is obtained using a differential scanning calorimeter. You have a blank reference pan and another pan with the polymer in it. A set point temperature is chosen and then the polymer is heated to that set point. Then the heat flow versus the temperature is plotted to see when the change in heat flow increases rapidly and that is the Tg of the polymer. Since you do not have access to this piece of equipment you will use another method. It will not be an accurate measurement, but you can get an idea of what the temperature might be by seeing if it is higher or lower than the temperature in a refrigerator or freezer. PART A3 Lab Procedure 1. Take a sample of the bioglass made 2. See if it is flexible at room temperature. 3. Put your sample in the refrigerator. 4. If your sample is brittle after leaving in the refrigerator for 15 minutes, then the Tg is between the room temperature and the refrigerator temperature. 5. If your sample is still flexible at the refrigerator temperature, place in the freezer for 15 minutes and then check its flexibility. 6. If your sample is brittle at the freezer temperature, then the Tg is between the refrigerator temperature and freezer temperature. 7. If your sample is still flexible at the freezer temperature, then your bioplastic’s Tg is lower than the freezer temperature. PART A4 Data Analysis 1.Is your sample flexible at room temperature? 2. If answer to #1 is yes, then is your sample brittle after being in the refrigerator for 15 minutes? 3. If answer to #2 is no, then is your sample brittle after being in the freezer for 15 minutes? 4. After answering these questions, what do you conclude from the glass transition temperature test about your sample? PART B1 Creating and testing bioplastic from a carbohydrate-based polymer: cornstarch There is more carbohydrate on earth than all other organic material combined. Polysaccharides are the most abundant type and make up around 75% of all organic matter. The most plentiful is cellulose, found in plant cell walls. Starch is also a very abundant component of the planet’s biomass. It is found in corn, potatoes, wheat, tapioca, rice, sorghum, barley, peas, etc. The two major polymer components of starch are amylose and amylopectin. Cornstarch is typically 28% amylose and 72% pectin. You will be making and testing a “generic “bioplastic from cornstarch, water, glycerin, acetic acid (vinegar), and water. Pre-experiment Checklist 1 glass heating flask/beaker or a pot 1 set of metal measuring spoons or a glass graduated cylinder 1 pair of scissors (optional) 3g glycerol 80ml water 11g Acetic acid (vinegar) 10g corn starch 1 large metal/silicon spoon/stirrer Hot plate or Bunsen burner 25cm x 15cm brownie/loaf pan or dish (preferably nonstick for clarity) Sandpaper or file or scissors Access to a refrigerator and freezer PART B2 Procedure 1. Pour 80 ml of water into a 200-500ml beaker and place on top of a stir plate. 2. Put in the corn starch and stir vigorously with a spoon/stir rod until a homogenous white, even suspension occurs. 3. Mix in the glycerin and mix thoroughly. 4. Mix in the vinegar. 5. Stir mixture so that it is thoroughly mixed. 6. Turn on the heat to about a level 3, and allow the mixture to begin to turn into “thick goo”. The polysaccharide has long sugar molecule and the vinegar breaks this up, and because we added glycerol, which acts as a plasticizer it won’t be as brittle. 7. Heat a bit longer and it becomes clearer. 8. At this point you can pour onto the top of a cookie sheet and allow it to flow down a bit so that it spreads out a bit. It will be simply to a “jello” type of consistency. 9. Let it sit for a while and “gel”. Procedure 2b Testing Bioplastic Now, you can perform tests on your bioplastics as you did earlier PART B3 1. Take a sample of the bioglass made prior. 2. See if it is flexible at room temperature. 3. Put your sample in the refrigerator. 4. If your sample is brittle after leaving in the refrigerator for 15 minutes, then the Tg is between the room temperature and the refrigerator temperature. 5. If your sample is still flexible at the refrigerator temperature, place in the freezer for 15 minutes and then check its flexibility. 6. If your sample is brittle at the freezer temperature, then the Tg is between the refrigerator temperature and freezer temperature. 7. If your sample is still flexible at the freezer temperature, then your bioplastic’s Tg is lower than the freezer temperature. PART B4 Data Analysis 1. Is your sample flexible at room temperature? 2. If answer to #1 is yes, then is your sample brittle after being in the refrigerator for 15 minutes? 3. If answer to #2 is no, then is your sample brittle after being in the freezer for 15 minutes? 5. After answering these questions, what do you conclude from the glass transition temperature test about your sample? 6. Note differences between your two bioplastics? What do you conclude? PART C1 Compression Molding: Creating and processing a soy-based bioplastic product Creating and testing bioplastic from a carbohydrate-based polymer: cornstarch Compression molding is a method of molding in which the molding material, generally preheated, is first placed in an open, heated mold cavity. The mold is closed with a top force or plug member, pressure is applied to force the material into contact with all mold areas, while heat and pressure are maintained until the molding material has cured. Compression molding was first developed to manufacture composite parts for metal replacement applications; compression molding is typically used to make larger flat or moderately curved parts. This method of molding is greatly used in manufacturing automotive parts such as hoods, fenders, scoops, spoilers, as well as smaller more intricate parts. The material to be molded is positioned in the mold cavity and the heated platens are closed by a hydraulic ram. The mold is then cooled and the part removed. Materials are heated above their melting points, formed and cooled. The more evenly the feed material is distributed over the mold surface, the less flow orientation occurs during the compression stage. In compression molding there are six important considerations that an engineer should bear in mind: • Determining the proper amount of material. • Determining the minimum amount of energy required to heat the material. • Determining the minimum time required to heat the material. • Determining the appropriate heating technique. • Predicting the required force, to ensure that shot attains the proper shape. • Designing the mold for rapid cooling after the material has been compressed into the mold. Pre-experiment Checklist “KitchenAid” Mixer 15 ton Compression Molder Mold (cavity) Scale Balance Weight boats Beaker(s) Magnetic Stirrer Soy Protein Isolate Glycerol Water Sodium Sulfite Potassium salt Mixing bowl Spoon(s) 1 quart of water PART C2 Making another bioplastic 1. Soy-based Bioplastic “Inputs” Calculation 100 parts Soy Protein Isolate (start with 250g) 30 parts Glycerol _____75__________g 50-60 parts Water _______125-150________g 0.5 parts Sodium Sulfite ____1.25_______g 0.5 parts Potassium Salt _____1.25______g PART C3 Lab Procedure 1. Place a 400-600ml or larger beaker on top of a stir plate 2. Add the Sodium Sulfite and the Potassium Salt 3. Add the water 4. Add the glycerol 5. Add the magnetic stirrer & turn on the stir plate (low-med). Leave to stir for about 5 minutes 6. In the KitchenAid mixing bowl, add the Soy Protein Isolate(500g) 7. Turn the mixer on a VERY SLOW SPEED and begin to add the wet mixer from the beaker into the mixing bowl and into the Soy Protein Isolate 8. You may need to turn the mixer off to scrape the sides with a spoon & continue mixing 9. NO CLUMPS! Mix until a homogeneous/smooth mixture is obtained 10. Spray the mold cavity provided with Silicon lubricant. 11. Slowly…very slowly remove the mixing bowl by removing it from the side clamps gently, and it should unhook from the back as well. This can be a messy cleanup if done too fast and too hard (force). 12. Carefully spoon the mixture into the mold cavity to about 1/6” from the top. PART C4 Continuing toward product production Compression molder processing: manual operation procedure 1. Check for any debris around the molder or inside the front gate. 2. Check electrical and mechanical connections. 3. Ensure that safety shields and gates are closed. 4. Ensure safety latch/disconnect switch on the right/northwest top edge of molder is turned to the “ON” position. Molder will not run if it is “OFF”. 5. Check the oil reservoir indicated gauge on back, middle side of the molder.. If it is in the “GREEN” area the molder can be used. If the gauge indicates either “YELLOW” or “RED” contact the lab supervisor or undergraduate personnel. The molder is NOT ready for operation. The reservoir is Chevron Rando HDISO 46, and the tank holds approximately 15 gallons (approved by Wabash). The oil is pumped through a 10 micron absolute filter element. DO NOT pour oil directly into the reservoir, but pumped though the filter cart to the fill, full mark on the oil level gauge. 6. Turn on the inlet and outlet water valves located along the west, green wall to the “ON” positions. You will hear the water running through the pipes. 7. Turn air “yellow” valves located on the back of the compression molder’s top platen manifold. Turn both valves to “ON” position. You will hear the air come on. 8. Check that the air pressure regulator (west, green wall) reads below the water pressure (top of platen manifold). 9. Close the front safety gate. 10.Press the “CONTROL POWER ON” pushbutton and it will illuminate. 11.Press the “HYDRAULIC ENABLE ON” pushbutton and it will illuminate. 12.Select the ‘MANUAL” position of the “MAN/SEMIAUTO” selector switch. 13.Press the “PLATEN HEAT ON” pushbutton and it will illuminate. 14.Adjust the PLATEN 1 AND PLATEN 2 on the upper right corner of the control panel temperature to the desired cure temperature, 300°F. Push the up and down arrows to set temperature and push enter button in the lower right corner. This will allow the red light to disappear and set the temperature. 15.Allow platens to heat up to the desired temperature. 16.Once the temperature has been reached, place the mold on the lower platen of the compression molder. 17.Close the clamp by simultaneously depressing and holding the dual “CLAMP CLOSE” push buttons. The clamp will close at a rapid speed until the “SLOWDOWN” proximity switch is actuated. 18. When the “SLOWDOWN” proximity switch is actuated, the “CLAMP SEALED” light illuminates, indicating that the operator may release the “CLAMP” CLOSE PUSH BUTTONS. The clamp will continue to build pressure to the setting of the panel mounted adjustable relieve valve. The pump runs continuously to maintain this pressure setting. 19.Set the pressure for 15 tons. 20.For platen cooling continue through the following steps. 21.Pull the ‘AIR” push/pull button to activate the “AIR COOLING” feature. This will energize the air solenoid valve and illuminate the “AIR” light. The heat relays will also be de-energized. 22. We will use a Cure Time of 7 minutes. 23. After 7 minutes as elapsed, pull the blue “WATER ON” push/pull button. 24. Allow compression molder to cool down to around 60-70°F. 25. When the platen temperature drops to the desired level, push the blue “WATER ON” push/pull button to turn the “WATER COOLING” off. This will de-energize the water solenoid and extinguish the “WATER ON” light. 26. Open the clamp by depressing and holding the “CLAMP OPEN” pushbutton. The “CLAMP SEALED” light will de-energize and the clamp will open until the pushbutton is released or the “CYCLE RESET” proximity switch is actuated. 27. When the “CYCLE RESET” proximity switch is actuated, the press is ready for another cycle. 28. As a precaution: USE HOT GLOVES to remove the mold from the bottom platen, and place on “on table beside the compression molder. 29. Begin removing top of mold with two screw drivers to pry both ends up. 30. Continue removing mold from final bioplastic product you’ve produced. PART C5 Data Analysis 1. Is your product flexible, brittle, or hard? Describe your final product. 2. How would you improve your product in the future? What would make it better? Sodium sulfite (sodium sulphite) is a soluble sodium salt of sulfurous acid. It is a product of sulfur dioxide scrubbing, a part of the flue gas desulfurization process. It is also used as a preservative to prevent dried fruit from discoloring, and for preserving meats, and is used in the same way as sodium thiosulfate to convert elemental halides to their respective acids, in photography and for reducing chlorine levels in pools Potassium salt is a substitute for regular table salt (sodium-chloride) that contains only half of the amount of sodium as table salt. It is known as a “half-salt” substitute and provides all of the seasoning and flavoring benefits of regular salt without all of the bad side effects, such as high blood pressure. There are certain people that are more at-risk of these side effects than others. These people should take the necessary precautions (replacing table salt with potassium salt) to prevent these serious health risks from occurring. Glycerol is a syrupy, sweet, colorless or yellowish liquid, C3H8O3, obtained from fats and oils as a byproduct of saponification and used as a solvent, an antifreeze, a plasticizer, and a sweetener and in the manufacture of dynamite, cosmetics, liquid soaps, inks, and lubricants. Soy protein isolate is a highly refined or purified form of soy protein with a minimum protein content of 90% on a moisture-free basis. It is made from defatted soy flour which has had most of the non-protein components, fats and carbohydrates removed. Because of this, it has a neutral flavor and will cause less flatulence due to bacterial fermentation. Soy isolates are mainly used to improve the texture of meat products, but are also used to increase protein content, enhance moisture retention, and as an emulsifier. Flavor is affected, but whether it is an enhancement is subjective. Before 2006, the U.S. Food and Drug Administration (FDA) was examining flavor reversion concerns related to levels of the toxin furan in soy protein isolate and other foods.[5] This problem has been solved by David Min of the Ohio Agricultural Research and Development Center. The chlorophyll in soy oil was reacting in the presence of light to form trans-2- heptenal and 2- pentenylfuran . Chlorophyll in soy oil is now removed with diatomaceous earth filters. Pure soy protein isolate is used mainly by the food industry. It is sometimes available in health stores or in the pharmacy section of the supermarket. It is usually found combined with other food ingredients. PART D1 Making Casein Milk contains many molecules of a protein called casein. Each casein molecule is a monomer and a chain of casein monomers is a polymer. The polymer can be scooped up and molded, which is why plastic made from milk is called casein plastic. Pre-experiment Checklist 1 600ml beaker 1 Graduated cylinder 1 Magnetic stir rod 1 Heated stir plate 45.5g Powdered skim or 480ml skim milk 444.5g of water (if using powdered milk) 40ml of vinegar (30ml for skim milk) 1 strainer 1 pair of heat resistant gloves PART D2 Powdered Milk 1. In a 600ml beaker measure out 444.5g of water 2. In a separate container measure out 45.5g of the powdered skim milk 3. In a graduated cylinder measure out 40ml of vinegar 4. Stir the water and slowly add the powdered milk (add 1-2 drops of food coloring if desired at this point) 5. Heat the mixture to 70 C° 6. Remove the thermometer and add the vinegar 7. Take the beaker off of the hot plate and strain out the precipitates 8. Shape, cut and mold into desired shape 9. Allow the molded product to dry and set over the next few days. PART D3 Skim Milk 1. Measure out 480ml of milk (add 1-2 drops of food coloring if desired at this point) and approximately 30ml of vinegar 2. Stir and heat the milk until it reaches approximately 70 C 3. Remove the thermometer and add the vinegar 4. Take the beaker off of the hot plate and strain out the precipitates 5. Shape, cut and mold into desired shape 6. Allow the molded product to dry and set over the next few days PART D4 Data Analysis 1. Is your product flexible, brittle, or hard? Describe your final product. 2. How would you improve your product in the future? What would make it better? --Identification of compounds or molecules in produce, processed foods, medication and trace pesticides. Confidentially, will acquire produce, processed foods, and generic medication from various sources and ambiances. Will involve lab activities on samples to be compared with projected reactions in processes and the projected respective outcomes. Products from reactions and processes will be segregated as best as possible. Particular spectroscopy analysis (UV, HPLC, IR, Raman and NMR). Databases may also be heavily used. Note: this activity may draw interest from students in the biological sciences. --Machine Learning with spectroscopy It’s recommended that students complete the Mathematical Statistics course before entering this activity, and as well as means to stay fresh will their probability and statistics skills from then on out. Students must also have background in basic spectroscopy activities. 1. Will begin with a tangible and constructive outline identifying the purpose of Machine learning and its application to spectroscopy. 2. Will not aggressively engage any mathematics of statistics conventionally taken on by mathematics and statistics majors. However, towards integrity, competency and professionalism, will analyse the mechanics of crucial methods of machine learning, also recognising the critical drawbacks or inefficiencies concerning their service. 3. Will identify the significance and sustainable credibility of machine learning applied to spectroscopy, that leads the chemistry community to take it seriously. 4. Will moderately engage some machine learning skills concerning what and when to use…with the how. Objective and meaningful identification of what is pursued in a fluid and tangible manner; also the things not to take granted and what to be cautious of. 5. Concerning molecules, substances, etc. will need to investigate how accurate is machine learning applied to spectroscopy, compared to plain spectroscopy. Actual spectroscopy experiments will be done as detailed in activities under chemistry. Will compare the standard data and geometrical displays that arise naturally from chemistry activities to the data then processed in the R packages and Mathematica. 6. The mentioned spectroscopy and mass spectroscopy R packages in the GOODY BAG post will be employed concerning their usefulness and versatility towards the following (just examples), and compare to Mathematica: Goodacre, R. (2003). Explanatory Analysis of Spectroscopic Data using Machine Learning of Simple, Interpretable Rules, Vibrational Spectroscopy 32, pages 33–45 Barbon, S. et al, Machine Learning Applied to Near-Infrared Spectra for Chicken Meat Classification, Journal of Spectroscopy Volume 2018, Article ID 8949741, 12 pages N. O. Mahony, T. Murphy, K. Panduru, D. Riordan and J. Walsh, "Machine learning algorithms for estimating powder blend composition using near infrared spectroscopy," 2018 2nd International Symposium on Small-scale Intelligent Manufacturing Systems (SIMS), Cavan, 2018, pp. 1-6. Madden, M. G. and Ryder, A. G. (2003). Machine Learning Methods for Quantitative Analysis of Raman Spectroscopy, Proceedings of the SPIE, Volume 4876, p. 1130-1139 Conroy, J. et al, Qualitative and Quantitative Analysis of Chlorinated Solvents using Raman Spectroscopy and Machine Learning, Proceedings Volume 5826, Opto-Ireland 2005: Optical Sensing and Spectroscopy: (2005) Guevara, E., Torres-Galván, J. C., Ramírez-Elías, M. G., Luevano-Contreras, C., & González, F. J. (2018). Use of Raman Spectroscopy to Screen Diabetes Mellitus with Machine Learning Tools. Biomedical Optics Express, 9(10), 4998–5010. Old, O. J. et al, Vibrational Spectroscopy or Cancer Diagnosis, Anal. Methods, 2014,6, 3901-3917. Torrione, P., Collins, L. M. and Morton K. D., Multivariate Analysis, Chemometrics, and Machine Learning in Laser Spectroscopy, Laser Spectroscopy for Sensing, Fundamentals, Techniques and Applications, 2014, Pages 125-164. Ghosh, K. et al, Deep Learning Spectroscopy: Neural Networks for Molecular Excitation Spectra, Advanced Science Volume 6 Issue 9, May 3, 2019. --Chemistry of Stains PARTA Enzymatic stains, Oxidizable stains, Surfactant stains, Particulate stains The primary guide for this activity : https://chem.ku.edu/sites/chem.ku.edu/files/docs/CHEM190/stain_removal.pdf Lab experimentations will revolve around such guide above. Includes efficiency of stain removal w.r.t. to temperature. As well, other things besides temperature that may degrade quality. As well, does stain removal application always imply eradication of germs? Trials involving all such required; optimise logistics and tools usage towards economic pleasantry. Consideration of damage to material by applying removal (both long terms and short-term usage). Toxicity/hazard of stain removal substances and with possible by-products as well (long term and short term). Assessment of potential impact on environment/ecology in unperturbed state and when applied in removal process. Materials of consideration with stains: Types of fabric, concretes, dentures, acrylic resin, rocks, painted surfaces, plastics in households. In activity chemical formulas, chemical equations and reactions will be emphasized. Can make use of software towards chemical models of compounds/polymers predicting behaviour/properties and so forth. PART B Will also investigate the use of common “organic” items for stain removal. Candidates of consideration: Vinegar Baking soda + vinegar Club soda Corn starch Orange oil (both) Lemon juice Lemon oil Tea tree oil Such “organic” potential remedies my possibly treat various types of stains, hence falling into different types of classifications. Hence, one can use chemistry, physics and the tools available to them to predict the abilities of such potential remedies for different types of stains. Done regardless less of common knowledge, however knowledge on how to apply them as a means to not waste resources is highly welcomed; there must be concise explanation in terms of chemistry and/or physics to why items are applied in a certain way and why not by other means. Vinegar Baking soda + vinegar Club soda Corn starch Orange oil (both) Lemon juice Lemon oil All other concerns, questions and structure of part A to apply with trials. PART C Further lab experimentation Al-Huraishi, Haila & Moran, John & Jagger, Robert & Macdonald, E.. (2012). Evaluation of Stain Removal and Inhibition Properties of Eight Denture Cleansers: An In Vitro Study. Gerodontology. 30. Sharif, N., MacDonald, E., Hughes, J. et al. The Chemical Stain Removal Properties of 'Whitening' Toothpaste Products: Studies In vVitro. Br Dent J 188, 620–624 (2000) PART D Photonic removal of stains. For some period there are procedures using light in particular wavelengths of the electromagnetic spectrum to remove stains from teeth (maybe pulled ones) and possibly other things. Such apparatuses can be built that’s economic. Will pursue such towards different types of stains and surfaces for such stains. The chemistry and physics will be enforced to highly respectable degree. Trials will be required. PART E Organisms are known to create stains in particular environments, whether microbial, fungi, moss, bed bugs. Structure for Part A through Part D will apply here. --Synthesizing Antibiotics PART A Making penicillin, ampicillin and other “off-shoots” of penicillin. Advanced stoichiometry will be heavily enforced. Chemical kinetics and energetics involved in processes. Various mentioned software in the “Goody Bag” post can assist. Spectroscopy tests (likely Raman) with multiple samples and comparison with professional databases. Tests on microbial, viral organisms. Will acquire specimen from various sources and cultured to substantial population. Generally, one has an ambiance where antibiotics are known to be behave optimally. Will like chronological imaging for a chosen duration. Penicillin and the “off-shoots” of penicillin will be tested against various cultures, where at least three sample tests per culture. Students will then considerable theoretical development of large production by process design via simulators. Students must be creative with means of replicating environments, and possibly the acceleration of processes; possible hazards and volatilities identified. Accommodating simulation will be analytical quantization modelling of systems; models and values have decisive role concerning materials, energy usage, quantity of products (and possible by-products), pollution, carbon footprint, etc. A tangible heat transfer model that can lead to computation of heat exposure to the environment (if relevant). PART B Synthesizing sulfonamides. From the following link and journal articles will make great efforts towards the production of sulfonamides in the most economic and safe manner. Various mentioned software in the “Goody Bag” post can assist. Advanced stoichiometry will be heavily enforced. Chemical kinetics and energetics involved in processes. For sulfonamides there are many variants depending on the process applied. Spectroscopy tests (likely Raman) with multiple samples and comparison with professional databases. One will like multiple variables, hence difference processes of synthesizing. Tests on microbial, viral organisms. Will acquire specimen from various sources and cultured to substantial population. Generally, one has an ambiance where antibiotics are known to be behave optimally. Will like chronological imaging for a chosen duration. Will like chronological imaging for a chosen duration. Likely each type of sulfonamide will be tested against various cultures, where at least three sample tests per culture--> https://www.organic-chemistry.org/synthesis/N1S/sulfonamides.shtm Reza Massah, A., Sayadi, S., & Ebrahimi, S. (2012). A green, mild and efficient one-pot method for the synthesis of sulfonamides from thiols and disulfides in water. RSC Advances, 2(16), 6606-6616. Naredla, R. R., & Klumpp, D. A. (2013). Preparation of sulfonamides from N-silylamines. Tetrahedron letters, 54(45), 5945–5947 Students must be creative with means of replicating environments, and possibly the acceleration of processes; possible hazards and volatilities identified. Accommodating simulation will be analytical quantization modelling of systems; models and values have decisive role concerning materials, energy usage, quantity of products (and possible by-products), pollution, carbon footprint, etc. A tangible heat transfer model that can lead to computation of heat exposure to the environment (if relevant). PART C Antibiotics resistance modelling The following articles can be applied to antibiotics of part A and part B with a second stage of experiments, or to make use of the acquired data from the total process of the antibiotics administered towards modelling. Apart from differential equations will apply both linear regression, multilinear regression and possibly exponential regression. Make the adjustments to accommodate the antibiotics mentioned in part A and part B --> Spalding, C., Keen, E., Smith, D. J., Krachler, A. M., & Jabbari, S. (2018). Mathematical modelling of the antibiotic-induced morphological transition of Pseudomonas aeruginosa. PLoS computational biology, 14(2), e1006012 Bruce R. Levin, Klas I. Udekwu. Population Dynamics of Antibiotic Treatment: a Mathematical Model and Hypotheses for Time-Kill and Continuous-Culture Experiments. Antimicrobial Agents and Chemotherapy Jul 2010, 54 (8) 3414 – 3426 Jeffrey J. Campion, Patrick J. McNamara, Martin E. Evans. Pharmacodynamic Modelling of Ciprofloxacin Resistance in Staphylococcus aureus. Antimicrobial Agents and Chemotherapy Dec 2004, 49 (1) 209 – 219 Jeffrey J. Campion, Philip Chung, Patrick J. McNamara, William B. Titlow, Martin E. Evans. Pharmacodynamic Modelling of the Evolution of Levofloxacin Resistance in Staphylococcus aureus. Antimicrobial Agents and Chemotherapy May 2005, 49 (6) 2189 – 2199 PART D It’s only responsible that one investigates the performance of antibiotics in environments not optimal for respective antibiotic. That part will be somewhat and extension of part C, namely, modelling for environmental factors that can influence microbial populations subjected to antibiotics administered. Factors, such as sustenance, competition among species, temperature and so forth. One type of control may or may not be a culture without competition; there will be other controls in the experimentation process. Multiple regression will be employed for such a case with treatment of causal inference and possibility of lurking variables. --- Guide to the Expression of Uncertainty in Measurement (GUM) and transcendence Thoroughly identify and analyse GUM. Our goal is to develop a logistical framework that’s universal with any experimentation in science. developing competence to important is quite important. Re-orchestrating some basic physics and chemistry labs students may encounter uncertainty treatment. Will like to extend to such particular labs with the analysis from part A. PART A Analysis from the following guides --> 1. Evaluation of measurement data — Guide to the expression of uncertainty in measurement — JCGM 100:2008 https://www.bipm.org/utils/common/documents/jcgm/JCGM_100_2008_E.pdf 2. Evaluation of measurement Data – Supplement to the “Guide to the Expression of Uncertainty in Measurement” – Propagation of Distributions using a Monte Carlo Method. JCGM.101: 2008 3. Barry N. Taylor and Chris E. Kuyatt (1994). guidelines for Evaluating and Expressing the Uncertainty of NIST Measurement Results. NIST Technical Note 1297. 4. https://isotc.iso.org/livelink/livelink/Open/8389141 5. Ferrero, A., & Salicone, S. (2018). A Comparison Between the Probabilistic and Possibilistic Approaches: The Importance of a Correct Metrological Information. IEEE Transactions on Instrumentation and Measurement, 67(3), 607-620. Other applications ---Krouwer, J. (2003). Critique of the Guide to the expression of Uncertainty in Measurement Method of Estimating and Reporting Uncertainty in Diagnostic Assays. Clinical Chemistry, 49(11), 1818-21. ---Velychko, O., & Gordiyenko, T. (2009). The use of Guide to the Expression of Uncertainty in Measurement for Uncertainty Management in National Greenhouse Gas Inventories. International Journal of Greenhouse Gas Control, 3(4), 514-517. ---Exothermic and endothermic mixtures/reactions Note: activity will begin with basic elementary models and extend to general models involving summations and multivariable calculus. Note: some mixtures/reaction may require multiple trials and various concentration ratios. Some activities can’t make use of organic tools or materials for placement, confinement and storage. The danger of some activities may be more elevated than others. Develop proper protocols/logistics for safety. Some experiments may or may not involve some level of “environmental isolation”. Experimental quantities/measures of interest Discrete time recorded temperature data Continuous time recorded temperature data Mass Volume Density Pressure If technical temperature recording sensors/device aren’t economic, one can make use of infrared imaging or radio imaging to acquire continuous time recorded temperature data, being likely safer than direct interacting with temperature sensors/apparatuses. Will also be interested in continuous recording infrared imagery, and infrared pictures at discrete points in time. Some formalities that must be analytically developed and experimentally confirmed (if practical or feasible) --> Chemical reactions and stoichiometry Laws of Thermodynamics Phase changes and Chemical Potential (singular and mixtures) Formation of products (when relevant) State functions that must analytically developed and experimentally confirmed (if practical or feasible). Before any possible experimental verification one to pursue theoretical development of such state functions; rely on journal articles and other sources --> Internal Energy Enthalpy Entropy Gibbs function/Gibbs Free Energy Throughout activity the electron configuration of various elements and various types of bonding will be treated. Applications will generally fall into the following categories Alkali metals in water Includes reaction of magnesium with H2O subject to different water temperatures Theoretical models of flameless reaction heaters and experimental construction. Students to hypothesize other combinations based on chemistry knowledge and experimentally verify them Hydrogen peroxide and catalase (and other possible enzymes) Acid-base reactions Acids and hydrogen peroxide Note: not banking on Piranha solution, but this particular activity activity may exceptionally yield substantial data compared to the other cases; gather data on temperature, products, phases, mass conservation, etc. Then, followed by adding organic matter (processed meat, glue sticks, synthetic sponge, etc.) to solution towards experimental data gathering on process (temperature data gathering, products, phases, mass conservation, etc.). Results can be compared with other Acid-H2O2 mixtures towards a consistent model, and establish the cause of variations among different mixtures. Sulfuric acid and water Note: not banking on H2SO4 + H2O, but this particular activity activity may exceptionally yield substantial data compared to the other cases; gather data on temperature, products, phases, mass conservation, etc . Then, followed by adding organic matter (processed meat, glue sticks, synthetic sponge, etc.) to solution towards experimental data gathering on process (temperature data gathering, products, phases, mass conservation, etc.). Results can be compared with other Acid-H2O mixtures towards consistent models. Students should pursue a general exothermic model for general acids, alkali metals, flameless reactions, etc. Like for exothermic modelling and experimentation there will be analogy for the following: Cooling tools Engine coolant CPU liquid coolant Aerosol dust cleaners Ice packs Thermal insulators Neoprene Glycerol Antifreeze proteins (plant based) Synthetic Antifreeze Thermal phenomena in the electrochemistry of batteries Thomson effect and Peltier effect --Medical Drugs PART A: Drug Discovery Rather being a course, to operate as an activity. For mentioned tools and technologies it’s likely that generic versions can be substitutes. Fray, M. L. et al (2013). A Practical Drug Discovery Project at the Undergraduate Level. Drug Discovery Today Volume 18, Numbers 23/24 PART B: Drug Design for Undergraduates The given article is a basic guide towards drug design. Naturally, instructor can expand upon such article. Tantillo, D. J. et al (2019). Computer-Aided Drug Design for Undergraduates. Journal of Chemical Education, 96(5), pages 920 – 925 Any software specifically mentioned can possible be substituted by the following << Dalton, CP2k, Firefly, Gaussian, GAMESS-US, MOLDEN, NWchem, GPAW, Octopus, ORCA, FreeON, PUPIL, VOTCA, BOSS >> << VMD (with NAMS), GROMACS, VOTCA, Desmond, UCSF Chimera, Molsoft, CCPN, RedMD + RedMDStream (http://bionano.cent.uw.edu.pl/software/) >> << TINKER >> PART C: Drug Delivery Determine most constructive order: Farrell, S., Savelski, M., Hesketh, R. and Slater, C. S. (2006). Experiments in Drug Delivery for Undergraduate Engineering Students. American Society for Engineering Education Farrell, S and Hesketh, R. (2002). An Introduction to Drug Delivery for Chemical Engineers. Chemical Engineering Education http://users.rowan.edu/~hesketh/hesketh/cee%20drug%20delivery.pdf Farrell, S. and Vernengo, J. (2012). A Controlled Drug-Delivery Experiment Using Alginate Beads. Chemical Engineering Education, v46 n2 p97-109 Farrell, S. et al An Experiment to Introduce pH-responsive Hydrogels for Controlled Drug Delivery: Mechanical Testing. 120th ASEE Annual Conference and Exposition 2013 --Chemistry of Flavour and Fagrances Engineering compounds or molecules to replicate taste types and smells. Obligations --> Memory consolidation Include sensory and neural processes Some Key Areas in Development Considerable use of biochemistry and organic chemistry Modelling and Simulation software Hypotheses and means of validation Synthesizing processes and production models Stablization of compounds/molecules Behaviour with other substances and hazards analysis Means of safety testing Assisting texts --> Rowe, D. J. (2004). Chemistry and Technology of Flavours and Fragrance, WileyBlackwell Berger, R.G.. (2007). Flavours and Fragrances: Chemistry, Bioprocessing and Sustainability, Springer-Verlag Berlin Heidelberg Sell. C. S. (2006). The Chemistry of Fragrances: From Perfumer to Consumer. Royal Society of Chemistry NOTE: particular laboratory methods/techniques from texts will be pursued --Chemistry of Illegal Drugs Detection 1.Begin with profiling focus drugs of interest. Implied are cocaine, heroine, angel dust, speed, crystal meth. HOWEVER, there will be others. Classification of the types of illegal drugs with the spectrum of effects. 2. Followed by chemical structure of respective substance identifying functional groups, action sites, etc., etc. for the pathways. Simulation of such processes via chosen software. 3. Means of detection of such drugs. Will survey the various tools and kits applied by transportation security agencies, port authority, border control and homeland security. Detailed analysis of the chemistry (with materials) involved for each. Will also analyse the circumstance of false positives as well, identifying the causes and resolutions. Note: if not brazen with direct presence of substance, concealment comes in various forms, such as mixture liquids masqueraded as commercial or home made sustenance, drugs mixed into spices and such sort of things or with preservatives or preserved foods. Often its comes down to the relentless or persistent or innovative agents with their hands-on investigations to avoid fooling test kits. 4. Excluding high profile substances such as cocaine, heroine, angel dust, speed, crystal meth, pcp, etc., etc., students will apply lab detection methods/techniques to chosen narcotics and stimulants of small quantities. Determine a good number of test samples if need be. There will be security and safety protocols for securing and management of substances against oral or penetration intake, theft and smuggling. All laws readily apply without reservation (anywhere and any time). 5. Students will be given legal but complex substances to design test (kits) to identify them, that are highly accurate and low with false positives indications. Spectroscopy in this phase will only be considered a luxury and generally inaccessible. Complex substances will be concealed in different forms like actual drug trafficking concealment techniques. Literature assists for development throughout --> I. Recommended Methods for the Identification and Analysis of Cocaine in Seized Materials. United Nations Office on Drugs and Crime. 2012 https://www.unodc.org/documents/scientific/Cocaine_Manual_Rev_1.pdf Note: such above manual may have updated versions II. Other literature: Farmilo, C., G. and Levi, L. (1953). The Physical Methods for the Identification of Narcotics. Organic Chemistry and Narcotic Section, Food and Drug Laboratories Department of National Health and Welfare, Ottawa, Canada Other accompanying literature: -Introduction to Identification of Narcotics by Physical Methods by Charles G. Farmilo and Leo Levi, Organic Chemistry Section, Food and Drug Laboratories, Department of National Health and Welfare, Ottawa -The Common Physical Constants for Identification of Ninety-five Narcotics and Related Compounds by Charles G. Farmilo, P. M. Oestreicher and Leo Levi, Organic Chemistry Section, Food and Drug Laboratories, Department of National Health, and Welfare, Ottawa -The X-ray Diffraction Method on Powder by W. H. Barnes, Division of Physics, National Research Council, Ottawa -X-ray Diffraction Data on Powder for Eighty-three Narcotics by W. H. Barnes and Helen M. Sheppard, Division of Physics, National Research Council, Ottawa -The Ultra-violet Spectrophotometric Method by Charles G. Farmilo, Food and Drug Laboratories, Ottawa -Ultra-violet Spectral Data for Eighty-six Narcotics by P. M. Oestreicher, Charles G. Farmilo and Leo Levi, Food and Drug Laboratories, Ottawa -The Infra-red Spectrographic Method by Charles Hubley and Leo Levi, Defence Research Chemical Laboratories, and Food and Drug Laboratories, Ottawa -Infra-red Spectra of Narcotics by Charles Hubley, Leo Levi and Moira Smith, Defence Research Chemical Laboratories, and Food and Drug Laboratories, Ottawa NOTE: likely incorporation or more modern literature as well. --Sewage sludges and wastewater field activity Smith, R. (1984). A Laboratory Manual for the Determination of Inorganic Chemical Contaminants and Nutrients in Sewage Sludges. CSiR Technical Guide. K62. pp 1-40 Nutrient Control Design Manual: State of Technology Review Report, Environmental Protection Agency --Hazardous Waste Test Methods https://www.epa.gov/hw-sw846 --Life Cycle Assessment for Chemical Process Design (COMING SOON) --Labs from courses are recitable as well --Other Research interests are possible in organic chemistry, polymer chemistry, inorganic chemistry, physical chemistry and environmental chemistry. List of other activities open to Chemistry students --> Aerospace Engineering: H, S Mechanical Engineering: T, U, V, W, X Industrial Engineering: B, C Electrical Engineering: U NOTE: for engineering activities refer to engineering post. Invaluable textbooks for chemistry with Mathematica: https://www.wolfram.com/books/search.html?libraryquery=&collection=books&topic=Chemistry&language=&x=15&y=8 For oceanography and meteorology students they are permitted to participate in spectroscopy activities and separation methods.

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plumpoctopus · 4 years

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Meteorology & Oceanography

OCEANOGRAPHY Curriculum: --Core Courses Scientific Writing I & II; General Biology I; General Chemistry I & II; General Physics I; Organic Chemistry I --Mandatory Courses (check COMP FIN post) Calculus I-III; Ordinary Differential Equations; Numerical Analysis; Probability & Statistics B; Data Programming with Mathematica; Mathematical Statistics --Required Components Environment --> Geological Oceanography; Oceanography Field Experience; General Oceanography; Field Oceanography; Field & Lab Techniques in Marine Fisheries Biological --> Biological Oceanography; Coral Reef Dynamics; Coral Reef Resilience & Restoration Chemical --> Chemical Oceanography, Marine Pollution Physical --> Fundamentals of Atmosphere & Ocean Dynamics; Physical Oceanography Data Analysis --> Data Analysis in Atmospheric & Oceanic Sciences Mandatory Electives options track --> Option 1 Track (Chemical): Marine Zooplankton & Phytoplankton Analytical Chemistry (in CHEM) Organic Chemistry II (in CHEM) Advance Chemical Oceanography Option 2 Track (Computational): Partial Differential Equations (check COMP FIN post) Fluid Mechanics (check PHYS post) Physical Oceanography Techniques Coastal & Oceanographic Modelling, Simulation and Forecasting Note: if you’re interested in a strong Marine Biology curriculum then you should be a marine biology major. NOTE: for mathematics courses refer to Computational Finance post; for Physics courses refer to the physics post; for Chemistry courses refer to chemistry post. NOTE: logically in profession all developments and data from research in meteorology and oceanography are forever archived in a secured manner for later retrieval. Hence, all likely all field activities and most labs from courses will abide by such. MASSIVE FOREVER DATABASES ACCUMMULTION TO BE EXPECTED. NOTE: SUCH DATA DOES NOT IMPLY REDUCTION OR JOCKING ON PAST LABS AND FIELD OPERATIONS. Geological Oceanography: Typical texts (in unison) --> Press, F. and Siever, R. Earth. W. H. Freeman Kenneth, J. P. Marine Geology. Prentice Hall Tools for lectures and Labs --> Google Earth USGS tools and resources Wolfram Mathematica/Alpha Course Labs --> 1. Sea sediments and seafloor constitution Note: may require dispersed sample collections (in a adjacent manner along environments. Professional logs and professional processes are expected Sample collections of near seashore sediments from various sites Characterisation of environments Characterisation of sediments Identifying composition in sediment samples What properties do elements in composition samples have? Density, electrical, magnetic are hypotheses on origin Transport process towards origin of composition of samples Methods of verifying erosion Methods of identifying chemical weathering and the possible culprits 2.Location on Earth Use latitude and longitude on maps to identify locations on earth Global positioning systems used to find locations on Earth from satellite Logistics for GPS operations (technologies and process) -Bathymetric Charts (for regions of interest) Concept, methods and tools applied for bathymetry Recognize seafloor slope and texture in bathymetry maps Means of data acquisition and counter development Confirm accuracy with professional sources 3.Plate tectonics Tools and technologies for the study of plate tectonics Identify seafloor features. Applying methods to recognise unique plates Relationship between plate boundaries and earthquakes using data Overlay earthquake location data and relate that data to the features you observed and labeled in the previous activity. Using the relationship between the bathymetry and earthquake data, determine the various plate boundaries and types. Ring of Fire Applying methods to determine plates movement speed. Characterising plate boundary types based on movement data. Articulate some of the challenges that are faced when data does not fit simple models Develop a reasonable hypothesis for the potential natural hazards in the studied area 4.Seismology Concepts and purpose Tools and technologies applied in seismology Demonstrate skills working with data that include: distinguishing between raw and processed data; identifying relevant data to answer questions; reading multi-axes graphs Determining earthquake focii and epicentres Types of waves in seismology and their use in research. Applying methods of identifying waves types from data; inference from data analysis of such waves. Explain how water depth data are calculated from pressure data Describe the possible relationship between earthquakes and seafloor topography changes. Determine what earthquake & bathymetry data tell us about processes within a volcano Course Outline --> Part I: Geology & Geophysics of the Ocean Basins Ocean floor physiography Dynamics of mid-ocean ridges and transform faults Marine Seismology, seismic reflection, seismic refraction Earth’s Gravitational Field Global Hydrocarbon Resources Part II: Sedimentary Processes in the Oceans Nearshore sediments and processes Pelagic sediments: types, origin, distribution Sediment dynamics: erosion, transport processes Oceanic deposits I: Ferromanganese nodules, crusts Oceanic deposits I: chemical weathering and clays Stratigraphy I: litho- , bio- , and chronostatigraphy Stratigraphy II: sampling: radio- and stable isotopes Paleoceanography I: time series and time slices Paleoceanography I: paleogeography; extinctions Part III: Dynamics, Igneous & Metamorphic Processes in the Oceans Dynamics of ocean basins and subduction zones Hot spots and mantle plumes Introduction to oceanic minerals and rocks Igneous rocks, minerals, and processes in the oceans Metamorphic processes in the oceans Nature and origin of the oceanic crust Hot springs and polymetallic sulfide deposits Heat flow Part IV: Global Perspectives on Earth History Paleoclimate Paleotectonics and megacycles Prerequisite: Calculus I Oceanography Field Experience: This course focuses on the fundamental questions that many oceanography students have: “How do we know that?” and “How can we figure that out?”. The ocean is a large, complex, and often challenging place to find answers to what may initially seem like simple questions. Oceanographers must often use creative ways in order to find answers. In this class, we will explore some of the techniques and equipment that oceanographers use to take measurements and piece together information that helps us figure out the “hows” and the “whys”. The goal of this course is for you to develop an understanding of scientific investigations as applied to the four main components of oceanography (geologic, physical, chemical, and biological), and to give you an appreciation for the challenges that research scientists from all fields face. By the end of this course, you will gain experience: Working in groups and collecting data in fields and labs Reading and comprehending the way that scientists communicate information Organizing and analysing data Interpreting result and explaining why they make sense Discussing findings in a scientifically acceptable format There will be 3 in-class assignments during lab weeks that will focus on data organization, analysis, interpretation, and presentation of information that we collected the previous week. In addition, there will also be 3 homework assignments. In-class assignments (IC) will be done in small groups and turned in at the end of class, but Homework assignment (HW) must be turned in individually at the beginning of class. Quizzes will be based on the previous week’s information and will typically take the form of a few basic short answer questions to ensure that you understand what we have done. They will be held during the first 15 minutes of class. All quizzes will be collected after 15 minutes and there will be no extensions for late arrivals. There are NO make-ups for late arrivals or missed classes. Presentations – Due to the abbreviated nature of this course, we will be focusing primarily on general oceanography equipment and research techniques. However, some of the most interesting and exciting methods of field work that oceanographers do are impossible for us to experience in 8 weeks without a million dollar budget (involving submersibles, technologically advanced equipment, satellite imagery, etc). If you decide to go into oceanographic research science, you will be working on very detailed projects that involve much more in-depth research and equipment. In order to give you an idea about some of the more complex projects that oceanographers work on, your group will investigate a particular question that oceanographers have faced, and report back to the class about how they went about answering it. All presentation details, requirements, and example topics can be found on the course website. Transportation - You will be responsible for finding transportation to our 4 field sites. Unless otherwise noted, we will begin field work/quizzes exactly one hour after the official start of class to give everyone enough time to get to the field site. For the biological oceanography activity, the tide will dictate class start time and will be announced in class. All field activities will be held whether RAIN or SHINE. I recommend bringing a clipboard to field sites for taking quizzes and collecting data. While no particular textbook is required for the course, a general oceanography text will be very helpful for assignments and quizzes. Some field labs will have small user fees which will be detailed in class the previous week. We will often be walking over uneven terrain for long periods of time and students should be prepared with appropriate shoes, clothing, water and sunscreen. Sites may not have public restrooms so make sure you are fully prepared for a three hour class when you arrive at our sites. Class participation is a very important part of this course and will be taken into account for borderline grades, both up or down. If you feel a group member is not pulling their weight, see me and I may assign individual grades within the group for the same lab report or presentation. Grading --> Attendance/Punctuality/Preparation/Conduct in field participation 200 pts Assignments 400 pts Quizzes 160 pts Final Assignment 70 pts Presentations 70 pts Schedule Outline --> Week 1 Intro / Data Analysis / Geological Oceanography Week 2 Geological Oceanography Field Work – chosen beach Week 3 Beach Data Analysis from prior data collection / Physical - Oceanography Week 4 Physical Oceanography Field Work – chosen beach Week 5 Wedge Data Analysis from prior data collection / Chemical - Oceanography Week 6 Comparing Water Quality / Chemical Testing – chosen conservancy Week 7 Biological Oceanography / Marine Ecology – chosen aquarium Week 8 Collect Final Assignment Prerequisites: Geological Oceanography, Calculus II. Biological Oceanography: Biological oceanography is the study of marine organisms, their quantitative distributions in time and space and their interactions with each other and their ocean environment. The course is divided into 5 units. The first unit provides a brief history of biological oceanography and reviews the physical and chemical processes in the ocean that influence marine biota. In the second, third and fourth units we will explore the diversity of pelagic and benthic marine organisms, bio-elemental cycling within these life forms and the factors that influence their abundance and distributions. In the last unit we will learn about the consequences of shifts in the ocean biota throughout geological time and how they may be affected by future climate change. Learning Outcomes --> 1. Define the major life forms in the ocean, describe the characteristics that differentiate these life forms and how these forms interact with each other. 2. Explain how marine organisms influence the cycling of bio-elements, particularly carbon. 3. Define the environmental factors and processes that control the abundance and distributions of marine organisms in space and time on a variety of scales. 4. Describe methodological approaches for evaluating the biomass, growth, and mortality of plankton, nekton, and benthic marine organisms, including their strengths and weaknesses. 5. Explain how marine organisms have influenced the evolution of Earth and predict how ocean biota will be affected by future climate changes. Typical texts --> Lalli, CM & TR Parsons (1997) Biological Oceanography, An Introduction, Elsevier Butterworth-Heinemann Publishing Miller, CB (2004) Biological Oceanography, Wiley Blackwell Publishing Units --> 1. Introduction and Overview 2. Primary Production - Formation of organic matter 3. Secondary Production and the Microbial Loop – Cycling of organic matter 4. Benthos, Nekton & Fisheries Oceanography – Higher trophic level organic matter 5. Special topics in biological oceanography – Deciphering the past and predicting the future Grading --> Problem Sets 20% 2 Midterm Exams 30% Final Exam 30% Field Trip Assignment 5% Field Trip Presentation 10% Lecture Outline --> Week 1 Introduction and historical overview of biological oceanography General principles and nomenclature Week 2 The physical ocean environment The chemical ocean environment Ecological geography of the oceans Week 3 – 4 Phytoplankton diversity and primary productivity Regulation of primary productivity: physical controls and light Regulation of primary productivity: macro- and micro-nutrients Phytoplankton ecology Week 5 Phys-Bio interactions I: life in moving flow Phys-Bio interactions II: flux-divergence Week 6 Bacterial and Archaeal diversity Bacterial production and ecology Week 8 Zooplankton diversity and ecology Viruses Microbial Loop Week 9 Biological Pump Nekton diversity and reproductive/larval ecology Week 10 Community organization and biological interactions Fisheries resource management Week 11 – 12 The Deep Sea Ocean fertilization: past and present Nutrient eutrophication Natural Climate Cycles Climate change effects on marine organisms Week 13 Shallow water estuarine habitats Marine genomics Prerequisites: General Biology I Marine Zooplankton & Phytoplankton Course concerns the existence and function of zooplankton and phytoplankton. Some interest in the examination of metabolism to validate their roles in ecosystems. Additionally, environmental controls or shocks that influence their productivity and impact in ecosystems. Note: most lecturing time will be directed towards phytoplankton. Note: an 18 weeks course, having 3 sessions per week, and at least 2 hours per lecture session. Literature --> Standard texts (TBA) Texts for the Identification of phytoplankton Practical Sessions --> There will be five practical sessions held. These sessions will provide you with practical skills and experiences in identifying phytoplankton and measuring phytoplankton biomass and other growth characteristics. You will also be introduced to bioinformatic tools and methods currently implemented for in silico analyses of phytoplankton genomics. You will also be working with professionals who will assist you with your data analysis. Phyoplankton Classification I Phytoplankton Classification II Phytoplankton Physiology - cell density, biomass and growth rates Phytoplankton Physiology - variable fluorescence Phytoplankton genomics and bioinformatics (please bring laptop) Time Series Projects --> Projects involve learning to retrieve, manipulate, and interpret data derived from the following resources: Hawaii Ocean Time Series programme database Bermuda Atlantic Time Series Other Time Series databases (catering for ambiance) Field Trips and Labs (in sequence) --> Note: field trip activities will range from a few hours, to half day, or whole. FT: Snorkel Walkthrough/Snorkelling activities FT: Boat Trip to sample plankton (zooplankton) Lab: Sampling and analyses of zooplankton FT: Boat Trip to sample plankton (phytoplankton) Lab: Sampling and analyses of phytoplankton FT: Aquarium, Museum & Zoo FT: Cruise for phyto and zoo FT: Cruise for bioluminescence at night Lab: Bring back samples and initiate growth and grazing experiments Concerns various controls (temperature, minerals, iron, CO2, etc.) Interest in by-products from metabolism, etc. Lab: developing experiment from Yarimizu, Y. et al (2018) journal article Analysis and data processing schedule to be given Lab: Analyses & Experiments with collected phyto and zoo Lab: Sampling Lab: PCR FT: Field Trip Lab: Sampling Lab: Sampling and Data Processing FT: Cynobacteria/HAB field experimentation Lab: Analysis of data collected from prior FT Experimental Algal blooms system development (time permitting) --> Will encompass components expressed in module 3. Involves process concept, analysis of tools and their operation; network structure for data acquisition. Total logistics. Calibrations if needed. Development and testing, likely in controlled environment (lab construction with variables study). Note: iron diffusion schedules may also be required. Analysis of data and models. Major Course Topics --> 1. Zooplankton Taxonomic Groups with Morphology Protozoa Groups Mixotrophs Metazoa Groups Metabolism (various) Role in food webs Role in Biogeochemistry 2. Phytoplankton Taxonomic Groups with Morphology Metabolism (various) Ecology ad food webs Growth Strategies Role in biogeochemistry Behrenfeld, M.J. and Boss, E.S. (2018) "Student's Tutorial on Bloom Hypotheses in the Context of Phytoplankton Annual Cycles". Global Change Biology, 24(1): 55–77 Behrenfeld, M. J. et al. (2019). The North Atlantic Aerosol and Marine Ecosystem Study (NAAMES); Scientific Motive and Mission Overview. Frontiers in Marine Science. 6: 122 Engel, A. et al (2017). The Ocean’s Vital Skin: Toward an Integrated Understanding of the Sea Surface Microlayer. Frontiers in Marine Science 4 Factors affecting productivity Role of phytoplankton in aquaculture and mariculture Behrenfeld, Michael J. (2014). Climate-Mediated Dance of the Plankton, Nature Climate Change. 4 (10): 880–887 Iron and plankton blooms and with relation to carbon dioxide drawdown Yarimizu, Y., Cruz-López, R. & Carrano, C. J. (2018). Iron and Harmful Algae Blooms: Potential Algal-Bacterial Mutualism Between Lingulodinium Polyedrum and Marinobacter Algicola. Volume 5 Article 180 Will pursue replication of experiment in article Ocean warming impacts on global phytoplankton Impact on previous topic 3. Predicting Harmful Algal blooms. Methods or tools applied (real time data): Multi-day, continuous records (e.g., every 15 minutes to hourly) Deploying sondes (water probes) to collect real-time data and creating hyperspectral images and high-resolution spatial maps from the data collected to paint a more accurate picture of the distribution of cyanobacteria and nutrients in the water. Turbidity (murkiness) In-situ (in-water) sensors for frequent measurements of nitrate and dissolved organic matter (DOM) — “food” that stimulates cyanobacteria growth — hold great promise for characterising the chemical variations in waterbodies. Fluorometer (light-measuring) sensors to measure the fluorescence produced by certain “algae” or cyanobacteria indicators: Chlorophyll-a: a pigment concentration that is a representative measure of the amount of “algae” (both green and blue-green) in the water Phycocyanin: a pigment concentrations that is a better representation of the amount of cyanobacteria biomass (cell concentration) Dissolved organic matter (DOM): composition of DOM can be used to characterize cyanobacteria growth potential in the water and help identify total organic carbon concentrations, another fundamental building block for cyanobacteria growth. Water samples to compare to the fluorescence measurements Temperature, pH, and oxidation-reduction potential (a relative measure of decomposition) High-resolution spatial maps of the data to evaluate the spatial extent of the parameters measured Concurrent, high-resolution satellite imagery to compare remote observations with onsite spatial nitrate and algal data Note: will be acquiring and analysing high volumes of data for different regions. Then, will make use of machine learning tools 4. Course BBQ Prerequisites: Biological Oceanography, General Chemistry II. Must have moderate to advanced swimming ability. All participants in the course must be able to snorkel and must be comfortable in the water. General Oceanography: Investigates the broad-scale features and dynamics of the Earth’s oceans. The course is roughly divided amongst the four main disciplines of oceanography: marine geology, marine chemistry, physical oceanography, and marine biology. Students will learn that there is much overlap and interdependence between these disciplines. Specific topics include seafloor spreading, marine sediments, salinity, biogeochemical cycles, ocean structure, currents, waves, tides, primary production, marine ecology, global warming, and much more. Typical Texts: Garrison, Oceanography: An Invitation to Marine Science Invitation to Oceanography, by Paul R. Pinet Grading: Homework 20% 4 Exams 60% Lab 20% LECTURE OUTLINE --> Week 1 Sustainability and Oceanography Week 2 Plate tectonics: seafloor spreading, convection, paleomag, hotspots Plate boundaries: mid-ocean ridges, subduction zones, transforms Marine Provinces Marine sediments: sizes, Stokes Law, terrigenous, calcareous, siliceous Week 3 Physical Properties of Water Heat, temperature, light, sound Chemistry of seawater: salinity, density, steady state, residence time, inputs, outputs. Carbon cycle: fluxes, DIC, alkalinity, pH Week 4 Biogeochemical cycles: photosynthesis, respiration, Redfield ratios, nitrogen, phosphorous, oxygen Week 5 Global atmospheric circulation: heat transport, Coriolis effect, atmospheric cells Upper ocean circulation: Ekman transport, geostrophy, gyres Upwelling and El Niño: coastal and equatorial upwelling, ENSO dynamics Deep ocean circulation: vertical structure, thermohaline flow, heat transport Week 6 Waves at sea: wave forces, deep vs. shallow, wind waves, sea state Waves at the shore: breaking, refraction, seiche, tsunami Tides: Earth-moon-sun gravitation, amphidromic points Week 7 Coasts: primary vs. secondary, beaches, reefs, erosion Life in the sea: classification, adaptations, environments Week 8 Primary producers: production, phytoplankton, seaweeds, seasonal cycles Pelagic marine heterotrophs: energy & mass transfer, zooplankton, squid, fishes Fishes and cetaceans: fish classes, toothed whales, baleen whales Week 9 Benthic marine communities: ecology, rocky vs. sandy shores, coral reefs, deep sea Chemosynthetic communities: hydrothermal vents, cold seeps, whale falls Week 10 Marine resources: Law of the Sea, fossil fuels, direct energy, fisheries Marine pollution: toxicity, oil, sewage, eutrophication, plastics Week 11 Global warming and the ocean: Greenhouse effect, ocean warming, sea level rise. Heat budget acidification, carbon sequestration LAB OUTLINE --> Students will be evaluated based on the completion of several lab reports, a few smaller lab assignments, and “pre-laboratory” assignments. Each assignment will be typed, although figures and graphs may be drawn by hand. The reports will be typed and will follow the standard scientific format; abstract, introduction, methods, results, discussion, references. For some of the reports, a draft of a portion of the results section will be handed in first for evaluation and comments. Comments on the draft of the results section are intended to aid students in the completion of the final reports. Both the results-section draft and the final reports must be turned in on time to receive full credit. Late reports will receive a 10% grade reduction each day until the report is turned in. Details on the format of the major reports are given in the section of the syllabus entitled "Laboratory Report Format". Read this section carefully before you begin. The smaller assignments will be completed in question-and-answer format. All reports should be typed, double-spaced, and checked for correct grammar and spelling. You should read through the assignment, make notes, and think through the organization of all your responses before writing. Pre-laboratory assignments needn’t be typed but must be handed in at the beginning of each laboratory period to receive credit. Lab Grading for the 20%: Pre-lab assignments 0.1 Draft Reports 0.1 Full lab reports 0.8 Lab1 --> During this laboratory session we will study some of the properties of waves. We will create our own experiments in wave tanks, altering variables known to affect wave properties (see below), to explore the mathematical relationships among those properties. We will also set up an experiment to simulate the effects of waves on coastlines. Terminologies incorporated into various modelling: Wave height (H) is the vertical change in height between the wave crest and the wave trough. Wave amplitude (A) Wavelength (L) Steepness is wave height divided by wavelength (H/L): unique to the slope between a wave crest and its adjacent trough) Wave period (T) Wave frequency (f) Wave speed (termed celerity) can be related to wavelength and period Gravity waves at the water surface; calculate wave speed from wavelength and water depth. Deep water waves Shallow water waves Intermediate waves Refraction: Because wave speed for shallow-water waves is a positive function of water depth, waves slow as they approach the shoreline. Wave period remains constant so that a decrease in wave speed reduces wavelength. Parallel-crested waves approaching the shoreline at an angle, therefore, will refract, bending to become more parallel to the shore before they break. Bottom topography around bays and headlands will result in refraction patterns causing variation in the spatial distribution of wave energy, sediment erosion, and sediment deposition along the shore Breaking waves: As waves approach the shoreline, steepness increases. Theoretically, waves become unstable and should break when the steepness (H:L) reaches 1:7. In practice, this ratio rarely exceeds 1:12 due to other sources of instability. Bottom topography also affects breaking so that breaking occurs when H/d equals about 0.8, regardless of H:L. Will have lab procedures for Large wave tank 1. Prepare a coastline in the large wave tank and measure its geometry 2. Turn on the wave generator in the large tank Narrow wave channel 3. Trace the beach profile in the narrow wave channel and measure the water depth 4. Turn on the wave generator and measure the wavelength and speed of waves 5. Change the wave period, height, and water depth and repeat the measurements 6. Measure the change in the beach profile 7. Measure the wavelength and water depth at which waves break Large wave tank 8. Return to the large wave tank, measure the coastline and assess the effects of waves Etc., etc., etc. Lab 2 --> Vertical profiles of chosen bays. Examine how freshwater input affects the biology, chemistry and physics of Bellingham Bay. Second, we’ll observe the distribution of dissolved oxygen in the water column and consider what processes control DO concentration. Third, we'll collect samples for chlorophyll so that we can examine the distribution of phytoplankton biomass relative to Nooksack River input. Fourth, we'll collect nutrient samples that we will analyze in future lab periods. Finally, the data we collect will contribute to an ongoing monitoring program on water quality and dissolved oxygen in Bellingham Bay that I have been conducting with my classes. Important water column properties-- Nutrients: The primary limiting nutrient in coastal marine systems is typically nitrogen, although phosphorus availability may limit productivity as well. Availability of silica can limit the productivity of diatoms, which have silica frustules (outer shells). Nitrogen occurs in several forms – ammonium (NH4 + ), nitrite (NO2 - ) and nitrate (NO3 - ). Nitrogen waste products are released into seawater as NH4 + or as a compound such as urea that is quickly converted to NH4 + . Ammonium in seawater is oxidized to form NO2 - which is then oxidized to NO3 - by nitrifying bacteria. Phosphorus is found primarily as HPO4 2- in seawater. Its chemical form varies somewhat with seawater pH. Silica (silicic acid) is found mostly as Si(OH)4 at seawater pH. The productivity of coastal marine ecosystems is strongly dependent on concentrations of these nutrients. Light intensity: Primary production is also strongly affected by light intensity. Light interacts with algal pigments to drive photosynthesis; both the quality (spectrum, or color) and quantity of light are important in regulating this process. Secchi disk: A black and white disk is a low-tech way to measure the penetration of light into water. Named for Father Pietro Angelo Secchi, this primitive instrument has been used extensively in marine and aquatic systems for studying irradiance. Today, when the quantum sensor smashes against the side of the ship, the Secchi disk comes out. Lower the disk until it can no longer be seen, then raise it to the depth at which it just becomes visible again. Record this depth. You may have to repeat this several times to obtain a consistent Secchi depth. Spherical light sensor (4pi):This spherical light sensor measures the total amount of photosynthetically active radiation (PAR, radiation at wavelengths that can be used in photosynthesis). PAR wavelengths range from 400 to 700 nm for most photosynthetic organisms. Although light enters the water from above, it is scattered by water molecules so that, from an underwater vantage point, light comes from all directions. The spherical (4pi) sensor allows accurate measurement of this diffuse light field. Measuring phytoplankton pigments: The “CTD” has a fluorometer that measures in-situ seawater fluorescence. This measurement is related to the concentration of chlorophyll in the water. But, the in-situ fluorometer must be calibrated with laboratory measurements of chlorophyll from discrete water samples. To perform this calibration we will measure the concentration of chlorophyll on some of the samples we collect with the rosette. We will first extract the pigments using acetone. Then, using different type of fluorometer to measure the concentration of the extracted algal pigments. Survey methods: We will measure depth profiles of temperature, salinity, light, chlorophyll and dissolved oxygen at several locations in Bellingham Bay using a “CTD”. The “CTD” (conductivity, temperature, depth) is the oceanographer’s primary sampling device. It consists of a set of electronic probes attached to a metal rosette wheel that holds six Niskin bottles for collecting water samples. It will allow us to observe water properties as we lower it into the water. We will calculate salinity from conductivity. The more ions the water contains, the more electricity it will conduct. Salinity, when determined from conductivity, is usually expressed as psu (practical salinity units). The values of psu are the same as parts per thousand (‰). Temperature is expressed as degrees Celsius (°C). Other instrumentation on the CTD will measure light, dissolved oxygen, and seawater fluorescence, which is related to the concentration of chlorophyll in the water. The six Niskin bottles can be closed to collect water at different depths using a remote electronic closing mechanism that we will fire as the instrument ascends. We will collect a sample of surface water at each station and collect water samples from several depths at the deeper stations. At shallower stations we will collect seawater using buckets. We will also collect water samples from the designated strategic sites. Note: determination of the proper number of samples per location may become statistical. Dissolved oxygen: The dissolved oxygen content of water is influenced mainly by water temperature (cold water can hold more dissolved gas than warm water) and biological activity. Primary producers (including macroalgae and phytoplankton) add oxygen to the water as they photosynthesize. Recall that photosynthesis can only take place at depths shallow enough to receive light. Aerobic organisms (plants, animals, aerobic microbes) consume oxygen during metabolism. Waters containing high levels of organic matter (i.e. dead cells, organic-rich muds, dissolved organic matter from sewage or other sources) may have low levels of oxygen because heterotrophs use up the oxygen while decomposing the organic matter. Water samples: Use a clean bucket firmly affixed to a line to obtain a surface water sample from the shallow stations. Use a clean bucket to collect surface water samples at shallow stations. At deeper stations, collect water from the CTD rosette. Close (“fire’) the bottles electronically using the CTD software at selected depths. To sample the Niskin bottles, turn the knob at the top of the bottle to allow air to enter. Pull the nipple at the bottom, holding the sample bottle under the stream of water. Rinse the sample bottle twice with water from the Niskin bottle. Attach a glass fiber filter to the end of a 50-cc syringe. Rinse the syringe with water from the Niskin bottle and then fill it with sample water. Filter this water into the sample bottle. Also filter about 5-cc into a labeled plastic scintillation vial. Store samples in a cooler. These will be frozen for nutrient analysis during a later laboratory session. Relationship between temperature, salinity, and water density: Both temperature and salinity affect seawater density and density can be calculated from the following equation of state of seawater at a pressure of one atmosphere (Gill 1982). Ignoring pressure effects makes the equation a little less accurate, but it will be sufficient for this assignment since we will be working in shallow water. A more accurate equation of state of seawater is more complicated than we can program in excel. An excel spreadsheet with the equation of state formula included is posted on the course web site. Analyzing profile data: Plot profiles of T (deg C), S (psu), dissolved oxygen, light, fluorescence and sigma-t units (concerning density) for each station. Create a contour plot of surface salinity in Bellingham Bay. Consider the following questions: How do the profiles from the different stations compare? What might account for any differences? Which is more important in determining the density profile at the stations, temperature or salinity? (Assess this by using the equation of state to calculate the density of seawater for different values of salinity and temperature within the ranges we measured.) How does the Nooksack River affect salinity in Bellingham Bay? Are hypoxic conditions apparent anywhere in Bellingham Bay? Where is the dissolved oxygen lowest? Estimating mean rates of estuarine circulation and water column oxygen consumption: The mean rate of estuarine circulation (also called residual circulation) can be estimated from measurements of salinity and flow of the whatever river. Variables and parameters are related to particular locations. As well, concern with bottom-water residence time. Etc., etc., etc. NOTE: Following week to measure chlorophyll on samples we collected this week. Treated as a unique lab (say, being Lab 3). Lab 4 --> Nutrients in sea water (2 weeks) Part I: Nitrate (+ nitrite) and Ammonia Part II, the following week: Phosphate and silicate Lab 5 --> Measuring phytoplankton growth and grazing (2 weeks) Prereqs: General Biology I, Geological Oceanography, General Chemistry II Chemical Oceanography: The purpose of this course is to provide students with a basic understanding of the principles and processes controlling the distribution and speciation of chemical constituents in natural waters with primary emphasis on coastal marine waters. The first part of the course provides an overview of the chemical composition of natural waters and is descriptive in nature. A brief review of basic thermodynamics and chemical equilibria precede a discussion of carbonate equilibria and forms the basis for a more detailed examination of the distribution and speciation of nutrients, trace metals, trace organic compounds and radioisotopes. Finally in the last part of the course, the student is introduced to a number of "critical" processes that are of primary importance in controlling the distribution, transport and fate of chemicals in the aquatic environment. It is assumed that the student is well prepared in chemistry (undergraduate courses at least through organic) and has at least some familiarity with the physical and biological dynamics of aquatic systems (Physical and Biological Oceanography preferred but not required). Active participation and discussion encouraged. Primary text --> Emerson, S.R. and Hedges, J.I., Chemical Oceanography and the Marine Carbon Cycle, Cambridge University Press Assisting texts --> Stumm, Werner & Morgan James J. Aquatic Chemistry, John Wiley & Sons Schwarzenbach, Rene P. et al. Environmental Organic Chemistry, Wiley, There may be selected texts, readings from the primary literature and other resources. Student progress is assessed through performance on a combination of homework problem sets, field activities, mid-term exams and final exams, and participation in class discussions. Grading --> Problem sets Field Activities/Labs 3 Exams Participation Lecture Outline --> Descriptive Chemical Oceanography (fundamentals) - large scale circulation & water masses (conveyer belts) - 2 layer - vertical and horizontal distributions (basin scale) - nutrient-like behavior Physical Chemistry of Seawater (elementary or basic chemistry - physicochemical properties - properties and structure of water - major, minor, trace components - units, types of concentration - macroscopic, colligative properties - salinity, chlorinity, density (effect on circulation), vertical stability - PSU - constancy of composition - optical properties Equilibrium Concepts - remember your chemistry - chemical potential - activity and fugacity - Henry’s Law Geochemical Cycles (Broecker & Peng) - resonance time concept - nitrogen and posphorous cycles - controls on biological production and organic matter export - influence on atmospheric CO2 - sources & sinks weathering, atmospheric, hydrothermal, biosythesis - organic production/decomposition (Redfield Stoichiometry) - dissolved gases - solubility f(T,S,etc), AOU, gas exchange - nutrient biogeochemical cycles (N,P,Si) - seasonal cycles (coastal processes) - eutrophication Carbonate System - equilibria - basic equations, alkalinity, Henry’s Law - influence of master variables (pH, 3CO2, Alkalinity) - effects of organic production/decomposition - forcing of p CO2 variations - CCD and seafloor distributions - global carbon cycle Organic Geochemistry - basic organic chemistry of seawater - early diagenesis (humics) - production - degradation - preservation - modification - vertical transport - DOM and sediment organic matter Trace Metals/Metal Geochemistry - biochemical rules - Fe limitation and HNLC region - speciation - toxicity - anthropogenic influence Tracers (water column and sediment) - radioisotopes - stable - molecular Special Topics (case studies from instructor’s research in a model construct) - early diagenesis - carbon sequestration FIELD ACTIVITIES/LABS WILL STEM FROM THE FOLLOWING TWO SOURCES --> 1. Professor Rachel Narehood Austin Winter 2007 LaB Manual: https://silo.tips/download/chem-108b-lab-chemical-reactivity-in-the-marine-environment 2. Johnstone, R. and Preston, M. (1993). NUTRIENT ANALYSIS IN TROPICAL MARINE WATERS: Practical Guidance and Safety Notes for the Performance of Dissolved Micronutrient Analysis in Sea Water with Particular Reference to Tropical Waters. Intergovernmental Oceanographic Commission. UNESCO: https://www.jodc.go.jp/info/ioc_doc/Manual/096330eo.pdf 3. https://hahana.soest.hawaii.edu/hot/protocols/chap7.html Prereqs: General Oceanography, Organic Chemistry I Advance Chemical Oceanography Students get deeper insight into specific topics of chemical oceanography, including classical as well as actual relevant research topics treated in the research community. Students learn to compile knowledge from different literature sources for a synthesis and to present this synthesis in front of an audience. Course has focus on: The general relationship between processes that determine the distribution of chemical substances between the ocean and atmosphere Processes of importance for the climate and environment changes in a past, present and future perspective. The ocean's role in controlling the atmospheric CO2 concentration over time; mechanisms and impacts of ocean CO2 uptake and ocean acidification; nutrient cycling; oxygen and deoxygenation under climate change; changes in ocean ecosystems in Earth's past history and under human influence; the role of various functional groups in marine ecosystems; and land-ocean coupling. Topics of current interest will vary from year to year. Learning Outcomes --> Competence: Ability to critically read scientific articles and summarize them Ability to carry out a scientific literature search Reinforcement in scientific writing and scientific presentations Intelligence: Advanced knowledge about specific chemical oceanographic problems In-depth knowledge in one central biogeochemical topic of own choice Comprehends in which way biogeochemistry and climate change are linked Knowledge of actual research activities and progress in marine biogeochemical research Expected Skills: Ability to independently synthesize and extract information about expected climate and environmental changes suggested by the most updated research in the international scientific press and present this information in a critical and analytical perspective. Also, embedded to competently apply knowledge and skills from prerequiste to connect or integrate into advance topics and research treated in current course Ability to apply chemistry intelligence and skills to confirm processes and establish models Adequate mathematical skills to confirm quantitative processes and establish models Ability to present a selected topic within climate and environmental change based upon published literature from the international scientific press through a term paper Reinforcing and advancing foundations --> Reinforcing foundations from prerequisite, then advancement/maturity. Prerequisite texts will be applied when needed. Literature Analysis --> For chosen journal articles will pursue extraction of the crucial features. Will make strong, tangible, practical and fluid connections to prerequisite knowledge and skills. Will identify associated experimentation in the journal articles along with the logistics for development. May have critiquing of experiments as well (methods, robustness and possible statistical credibility) Labs --> There will be advance/augmented repetitions of chosen labs along with field activities from prerequisite to develop analysis. Additionally, for some chosen articles for current course will pursue replication of experiments. For field activities will make use of methods or guidelines for development from the EPA (search the science inventory), NOAA, USGS and other gov’t agencies. Must incorporate some spectroscopy activity as well. Much more sustainable exposure to chemical software to accompany labs and field activities. Quizzes --> Will test your knowledge and skills from prerequisite. Will test your knowledge and comprehension for current course. Yes, general chemistry to organic chemistry will also be immersed. Prerequisite: Chemical Oceanography Fundamentals of Atmosphere and Ocean Dynamics: The lectures will focus on the physical mechanisms responsible for the global energy balance and large-scale atmospheric and oceanic circulation. We will introduce fundamental concepts of fluid dynamics and we will apply these to the vertical and horizontal motions in the atmosphere and ocean. Fundamental concepts covered include: hydrostatic law, buoyancy and convection, basic equations of fluid motions, flow on a rotating planet, Hadley, Ferrel and Polar cells in the atmosphere, Walker circulation, thermohaline circulation, modes of climate variability (El-Nino, North Atlantic Oscillation, Southern Annular Mode), wind driven ocean circulation, turbulent flow. Computational and simulation assignments given to students follows only guidance setup by instructor. MATHEMATICA concerns expressing equations for given or derived models and simulations; lab sessions in which students will learn how to write and run simple MATHEMATICA programs to study the climate system. Assessment --> Modelling, Simulation and Data Analysis labs: 30% Midterm exam: 25% Homework: 25% Final oral presentation + class participation: 15% Example literature --> Atmosphere, Ocean and Climate Dynamics: An Introductory Text, by John Marshall and Alan Plumb, Academic Press 2008. I. Atmospheric Dynamics and the Equations of Fluid Motion --Introduction: The greenhouse effect. Global Energy balance. A basic Math/physics review. --Global Energy Budget --Vertical Structure of the Atmosphere and Ocean --Convection in the Atmosphere and Ocean --Horizontal Motion in the Atmosphere. Coriolis Force and Large-scale Dynamics of the atmosphere --Continuity and Thermodynamic Equations --Equations of Fluid Motion: Momentum Equations --Scaling the Equations of Motion: Dimensional Analysis --MATHEMATICA Lab 1. Your first simple climate models (energy balance box models) --MATHEMATICA Lab 2: Your second simple climate model. Ice-albedo feedback and multiple steady states. Energy balance box model. --MATHEMATICA Lab 3: Paleoclimate (extra credit) II. Ocean Dynamics & Climate --Intro to the Oceans: T, S, density and thermohaline circulation. --Introduction to the Carbon Cycle --Modes of Climate Variability, Ocean-Atmosphere Interaction, Annular Modes (El Nino, North Atlantic Oscillation, Southern Annular Mode) --Tracers of ocean circulation: biological tracers, CFCs, radiocarbon, Helium, Tritium --MATHEMATICA & OpenFOAM Lab 4: How diffusion drives the temperature, salinity and radiocarbon vertical distributions in the ocean (1D Advection-Diffusion models with no time dependence). --MATHEMATICA & OpenFOAM Lab 5 (1D Advection-Diffusion equation with time dependence) --Wind Driven Ocean Circulation: Ekman Flow and Pumping. Why are there gyres in the ocean? --Wind Driven Ocean Circulation: Sverdrup, Stommel and Western Boundary Currents: Why is there a Gulf Stream? --MATHEMATICA & OpenFOAM Lab 6: The Stommel model: simulating ocean gyres (2D advection-diffusion) --Vorticity; Conservation of Potential Vorticity --Geostrophy and thermal wind in the ocean. Sea surface height. --Eddies and baroclinic instabilities in the ocean and atmosphere --Summary of class. --Student presentations and final homework. Prerequisites: Calculus III, General Physics I, ODE Physical Oceanography: In this class you will: -Learn about many of the physical processes that occur in the ocean. -Learn about how these physical processes are observed and quantified. -Learn about where these processes occur in the ocean. -Learn about and access recent ocean datasets. -Get practice writing and thinking scientifically by focused study on particular processes. -You will also get a broader perspective and more practice by peer reviewing your colleagues’ efforts Typical texts --> Atmospheric and Oceanic Fluid Dynamics, by G. K. Vallis Cushman-Roisin and Beckers’s Introduction to Geophysical Fluid Dynamics Incorporated tool --> Ocean datasets Mathematica, Ocean Data View, ferret There will be short quizzes throughout the term. There will be no midterms of final exam. There will be five major assignments for this class, and all of them will be in the form of short scientific reports. You will be working on two assignments at a time, reviewing and revising the last one (a little work), and preparing the next one (more work). For any accompanying word processor there must be proper mathematical pallete use involved. Since you all have different preparation, you will all be able to take advantage of what you know. However, we are working to develop elements in all of the following: Quantitative Skills and Equations for the Ocean (Theory & Modelling Component) Descriptive Skills and Geography of Ocean Currents (Descriptive Oceanography) Understanding of Ocean Observations & Techniques (Observations & Engineering Component) Physical Intuition and Dynamical Understanding (Theory & Dynamics Component) Implications for Climate, Society, etc. (Policy & Climate Component) Folks with much quantitative experience will be able to use that to their advantage while folks with more substantial preparation in writing, argument, and logical structure will be able to use those abilities. We will be using the most up-to-date oceanographic datasets available, and so the work you are doing is potentially cutting edge research (but that’s up to you!). Also, in the future you will be expected to write much more complicated papers in a more tightly constrained time frame, you might as well get some practice now. I encourage you to work together, and I do not mind at all if you have similar papers or share figures or language scripts. However, in this case, I want you to list all of your study group as co-authors or put them in the acknowledgments section of your paper. You are all required to submit a version of each assignment as first author (that is, one that you wrote yourself). You need to be careful to cite your colleagues or the textbooks or papers you might be working from. You can use as much of these resources as is convenient in your version of the paper, but you need to properly cite the sources. We will discuss this topic more as the class (and the inevitable trouble) ensues. These issues of plagiarism and proper sourcing are a big part of what is to be learned in this method of assignments. Lecture Outline --> Observations What instruments are common to oceanography? How are these measurements used? How do the types of measurements influence the theoretical developments? Fluids Mechanics The differential equations describing a fluid The differential equations describing a Boussinesq fluid How the differential equations relate to budgets Rotation The equations for fluid motion in a rotating frame of reference Ekman boundary layers Geostrophic balance Stratification The temperature, salinity, and density stratification of the ocean Hydrostasy Baroclinic and Barotropic Potential temperature and potential density Thermal wind balance Vorticity Taylor-Proudman Flow Sverdrup Flow Ocean Circulation The Wind-Driven Ocean Circulation Simple Western Boundary Currents–Stommel & Munk The Meridional Overturning Circulation Theories of the Thermocline Wave Basics Dispersive Wave Kinematics: Phase & Group velocity Kinds of ocean waves: surface gravity, internal gravity, Rossby, Kelvin Prerequisites: General Physics I, Calculus III Physical Oceanography Techniques: Fluid Mechanics is one of the crucial disciplines applied to oceanography, however, the field by itself doesn’t yield direct, tangible and practical models for physical oceanography concerning the natural technical processes and physical concerns for oceans and coasts. Course emphasizes articles for analysis, modelling, simulation and micro-replication of environments in oceanography. Modelling and simulation --> Concerns immersion into tangible, practical and fluid settings, and conditions for models creation. Knowledge of physical oceanography from prerequisite will be quite useful. Will make use of fluid mechanics (thermodynamics may arise moderately). Will involve calculus skills (single, multivariate and vector calculus), differential equations (ordinary and partial). Solutions don’t concern liberal mathematical flattery, rather meaningfulness to geophysics. Numerical analysis applied will be constructive with debriefing of methods and rigorous application of computational tools. Field activities --> 1. Mapping (Google Earth and Google Maps) for preliminary observation of surroundings, geography, coordinates (2-d scale), terrain, geographical scale, accessibility, etc. 2. Climate exposure and weather profile, environmental and ecology intelligence. Assumptions or preliminary hypotheses. 3. Field reconnaissance of chosen sites (compare to 1 and 2) 4. Instrumentation analysis with logistics, and field measurements (subject to 1, 2 and 3). Labs --> Labs concern design and construction of systems to replicate environments and phenomena. Involves observation, data collection and modelling. Note: students will be responsible for relating labs to modelling from the Physical Oceanography course. Exams --> Exams will be open notes and open book. Use of laptops will be required. There will be 3-4 exams emphasizing: 1. Fields surveying, instrumentation preparation and practice. Measurement analysis. 2. For given data, to demonstrate modelling of environments and data analysis. Includes various types of mappings with data. Ambiance and environments will vary. 3. Modelling properties, forms, models and identify appropriate conditions. 4. Determining appropriate numerical methods with implementation. After determination will require manually setting up operations, followed by use of computers with CAS (Mathematica/OpenFOAM). Assessment constituents --> Punctual arrivals, attendance, conduct Field activities Labs 3-4 Exams Course Topics and Activities --> --Measurements (lecturing and field activities) Atmospheric Pressure, Temperature, Density --Oceanographic Instrumentation (lecturing and field activities) --Making a Depth Map with Bathymetric data Next, we take several geophysical surveys of the area. Creating a bathymetric (depth) map of the site and imaging the subsurface sediment at the bottom of the pond. To create a bathymetric map, we use a HydroLite. The HydroLite combines GPS technology with echo sound to create a depth map of the pond. We use this map to help decide where to core. It is usually best to core in the deepest area of the pond, because this is where the most sediment accumulates. --Making a Subsurface Map-Geophysical Data To image the subsurface sediment at the bottom of the pond, we use either Ground Penetrating Radar (GPR) or Chirp Sonar. Image creation of the subsurface showing layers of coarse grains in the sediment. In the image, the thicker black lines indicate coarser grains (relative to technology, may be different for other tools applied). --Density experiments (will be done in labs) http://moocs.southampton.ac.uk/oceans/2016/10/20/simple-density-experiments-to-do-at-home/ --Modelling behaviour among liquids. Will also consider the influence of temperature, concentrations, respective densities, and PH dynamic. Simulating solutions of models. Animation simulations as well based on CFD, etc., etc., etc. Seawater and Fresh water Seawater ranges in salinity from 33 to 38 ppt. The average salinity of ocean water is 35 ppt. Seawater with different salinity Seawater ranges in salinity from 33 to 38 ppt. The average salinity of ocean water is 35 ppt. Oil in (salt) water Will then make use of some literature and software from NOAA ( https://www.gfdl.noaa.gov/ocean-mixing/ ). If site doesn’t give you the CVMIx community software package, then pursue the GitHub repositories. Note: it’s also important to analyse the accompanying literature for its development. Software or models mentioned at bottom of page may also be useful. Also, GEMSS + COSIM + GIFT (gemss.com/index.html) may or may not have practical use with natural ocean mixing, but is good for pollution. --Heat and Salt Balances Lentz, S., Shearman, R., & Plueddemann, A. (2010). Heat and Salt Balances over the New England Continental Shelf, August 1996 to June 1997. Journal of Geophysical Research: Oceans, 115 (C7) --> Will acquire data from the ambiance of interest to suit, yet pretty much everything else to remain the same. For the case of data modelling such can be done through Wolfram’s “Earth Sciences: Data & Computation” if primary means isn’t feasible; location data is vital. --Gravity currents and stratified flow M. M. Nasr-Azadani and E. Meiburg. (2016). Gravity Currents Propagating into Ambients with Arbitrary Shear and Density Stratification: Vorticity-Based Modelling. Quarterly Journal of the Royal Meteorological Society. Volume 142, Issue 696 Experimentation pursuit: Longo, U. (2016). Gravity Currents in a Linearly Stratified Ambient Fluid Created by Lock Release and Influx in Semi-Circular and Rectangular Channels. Physics of Fluids (1994), 28(9), 096602 Amy, L. A , Peakall, J. and Talling, P. J. (2005). Density- and Viscosity-Stratified Gravity currents: Insight from Laboratory Experiments and Implications for Submarine Flow Deposits. Sedimentary Geology 179, 5 – 29 --Meridional Overturning Circulation Apart from identifying the phenomenon will analyse and try to replicate the findings for the following two journal articles. Models and data sources will be provided. For the case of data modelling such can be done through Wolfram’s “Earth Sciences: Data & Computation” if initial means isn’t feasible; location data is vital. Thibodeau, B. et al (2018). Last Century Warming Over the Canadian Atlantic Shelves Linked to Weak Atlantic Meridional Overturning Circulation. Geophysical Research Letters, 45(22), 12,376-12,385. Vial, J. et al. (2018). Influence of the Atlantic Meridional Overturning Circulation on the Tropical Climate Response to CO2 Forcing. Geophysical Research Letters, 45(16), 8519-8528. --Coastal Connectivity Mitarai, S. et al (2009). Quantifying Connectivity in the Coastal Ocean with Application to the Southern California Bight. Journal of Geophysical Research Vol. 114, C10026 Note: ROMS is listed beneath and can be acquired. Will like to replicate similar findings. If ambiance of choice can be used as substitute then so be it. --Stommel & Munk gyre models, β effect: https://empslocal.ex.ac.uk/people/staff/gv219/classics.d/oceanic.html Experimentation pursuit: Beesley, D et al. (2008). A Laboratory Demonstration of Coriolis Effects on Wind-Driven Ocean Currents. Oceanography, 21(2), 72-76. https://mitocw.ups.edu.ec/courses/earth-atmospheric-and-planetary-sciences/12-003-atmosphere-ocean-and-climate-dynamics-fall-2008/labs/lab13/ https://mitocw.ups.edu.ec/courses/earth-atmospheric-and-planetary-sciences/12-003-atmosphere-ocean-and-climate-dynamics-fall-2008/labs/lab12/ --Modelling the Ocean Thermohaline Circulation This activity describes the construction of and then experimentation with a model of the thermohaline circulation in the north Atlantic. Based on a famous paper by Stommel (1961), this model exhibits two stable states or attractors. The dynamics of this system are relevant to understanding episodes of abrupt climate change such as the Younger Dryas. The thermohaline circulation system of the North Atlantic Ocean is critically important to the climate system since it is involved with the transport of significant amount of heat to high latitudes of the northern hemisphere. In this exercise, students build a simple STELLA model of this system, which is surprisingly complex in its behaviour. The students carry out a series of experiments designed to help them understand how the system responds to changes and how its state is sensitive to the initial conditions. Requires knowledge of systems dynamics, including feedbacks, steady states, and so forth. The content/concept goals for this exercise are to understand some of the behaviours of systems with multiple stable states, including the importance of initial conditions and how perturbations can push the system over thresholds leading to an abrupt change of state. The higher order thinking goals for this exercise involve analysis of the quantitative output of the model and experimentation with models in order to answer questions. Stommel, H., 1961, Thermohaline Convection with Two Stable Regimes of Flow: Tellus, 8, 224-230. Mathematica ambiance is preferred over STELLA. A guide to development with questioning: https://d32ogoqmya1dw8.cloudfront.net/files/NAGTWorkshops/complexsystems/activities/stella_thermohaline_model.pdf One can observe whether developments are in agreement with the following: https://d32ogoqmya1dw8.cloudfront.net/files/NAGTWorkshops/complexsystems/activities/thermohaline_modeling_exercise.pdf In addition, may pursue model alternatives to that of Stommel and observe whether results will be consistent with prior when the same initial conditions, perturbations are applied. Experimentation pursuit: https://mitocw.ups.edu.ec/courses/earth-atmospheric-and-planetary-sciences/12-003-atmosphere-ocean-and-climate-dynamics-fall-2008/labs/lab14/ NOTE: additional pursuits in course will come from the following text: Artem S. Sarkisyan and Jürgen Sündermann (2009). Modelling Ocean Climate Variability. Springer Netherlands Prerequisite: Numerical Analysis, Fluid Mechanics, Physical Oceanography, Partial Differential Equations Coastal & Oceanographic Modelling, Simulation and Forecasting Course to provide a broad background on basic concepts in ocean modeling and prediction. Will demonstrate examples of different usages of ocean models. Students will learn about the history of the development of ocean circulation models, about the different types of models, the choices that modelers need to make, and what data are needed to set up models for various applications. Computational and programming skills will be extensively involved Textbooks --> Note: comprehension, logistics and comfort with computational and programming tasks are crucial to be successful in this course. Students may not be comfortable with one literature and are invited to apply out of the given, with the condition that tasks are completed as given. --Ocean Modelling Komen, G. J. et al (1994), Dynamics and Modelling of Ocean Waves, Cambridge University Press Haidvogel and Beckmann (1999). Numerical Ocean Circulation Modeling, Imperial College Press Griffies, (2004), Fundamentals of Ocean Climate models, Princeton University Press Kaempf, J. (2009). Ocean Modelling for Beginners: Using Open-Source Software. Springer-Verlag Berlin Heidelberg Kaempf, J. (2010). Advanced Ocean Modelling: Using Open-Source Software. Springer-Verlag Berlin Heidelberg --Numerical Methods O’Brien, J. J. (1986). Advanced Physical Oceanographic Numerical Modelling, Springer Kantha and Clayson, (2000), Numerical Models of Oceans and Oceanic Processes, Academec Press C.A. J. Fletcher, Computational Techniques for Fluid Dynamics, Volume 1, Fundamental and General Techniques C.A. J. Fletcher, Computational Techniques for Fluid Dynamics, Volume 2, Specific Techniques for Different Flow Categories Note: don’t assume finite difference will be used alone Note: will be compared alongside Mathematica and OpenFOAM --Forecasting and data assimilation Mooers (Ed.), Coastal Ocean Prediction, Coastal & Estuarine Studies Ser., 56, AGU Publ., 1999 Pinardi and Woods (Eds.), Ocean Forecasting: Conceptual Basis and Applications, Springer, 2002 Fu and Cazenave (Eds.), Satellite Altimetry and Earth Sciences, International Geophys. Ser., 69, Academic Press, 2001. (chapter 5 on data assimilation) Note: most likely Mathemartica environment go apply Tools --> OpenFOAM and Mathematica Labs --> Labs are dedicated to completion of assigned projects based on listed literature. Projects --> Based on intelligence and acquired skills students will make use of such two essentials to complete major projects. Projects for course are of three areas: Ocean Modelling (1-2) Numerical Methods (3-4) Note: don’t assume finite difference will be used alone Note: will be compared alongside Mathematica and OpenFOAM Forecasting and Data Assimilation (2-3) Grading --> Homework (8 to 10 assignments) Labs (10-15 tasks) 4 Exams Exams are open book and open note. Homework assignments will include computational and simulation activities given to students based only on guidance setup by instructor. For exams students will be required to provide mathematical conceptual simulation design for computational and simulation requests. NOTE: course will review and apply models encountered the Physical Oceanography prerequisite before attempting advance/general models of this course. Homework --> NOTE: your knowledge and skills from prerequisite courses will be put to good use without restraint Homework serves as the primitive grunt work for modelling. Namely, there are tasks for modelling and dynamic equations. Along with numerical methods development; development and building actual numerical methods. 1. Mathematica will be used to build numerical methods, as well as to compare results with default methods applied by mathematica for dynamic equations. 2. OpenFOAM tasks will be assigned to accompany (1) Labs --> We are not here to just to talk tech and concept flows. Labs concern vindication of the time applied acquiring intelligence. A specified amount of course lecturing is accompanied by lab development. MAJOR TOPICS --> 1.Introduction • Review and classification of different ocean models • Review of physical oceanography properties • The equation of state used in different ocean models • Review of terms used in modeling (vorticity, stream function, etc.) • Data sources (i.e., Altimeter, etc. etc., etc.) 2.Equations and approximations • Review of the equations of motion (Primitive Equations Models) • Common assumptions and their impact (Hydrostatic, Boussinesq) 3.Parameterization of mixing in ocean models • Horizontal and vertical diffusion & viscosity • Turbulence schemes & mixed-layer models 4.Finite differencing and grid choices • Basic finite differencing schemes and stability analysis • Staggered grids and their impact • Time split techniques and their effect on model efficiency • Horizontal grids (rectangular, curvilinear, triangular, unstructured) 5.Advance Alternatives to Finite Difference 6.Quasi-Geostrophic and Shallow-Water Models 7.Classification of ocean models by vertical grid choices • Z-level models and the BBL problem • Isopycnal and layer models: from simple 1.5L reduce-gravity models to global hybrid models • Terrain-following/Sigma-coordinate models - the pressure gradient problem - the horizontal diffusion problem • Generalized coordinate models • Comparison between models (idealized and realistic examples) 8.Boundary Conditions • Sea-bed/bottom boundary conditions and sediments • Surface boundary conditions and air-sea exchange • Lateral/coastal boundary conditions - Special cases: rivers, wetting and drying • Open boundary conditions - Radiation conditions, cyclical, buffer zones - Tides 9.Diagnostic models • 2D basin scale circulation models based on the vertically integrated vorticity balance equation: the JEBAR effect and climate studies. • 3D diagnostic models: robust-diagnostic, diagnostic-prognostic adjustment techniques and their applications for climate and coastal simulations 10.Data assimilation and Ocean Forecast systems • Assimilation Methods and concepts: - Simple methods (insertion, nudging) - Sequential methods (Optimal Interpolation, Kalman Filter, 3DVAR) - Non sequential methods (4DVAR/adjoin, inverse) • Examples from assimilations of Altimeter data • Examples from ocean forecast systems in various locations NECESSARY UNDERLYING CONCERNS --> -Governing equations and theoretical modelling of fluid systems. -When to use CFD: choosing the right model for the right application. -Spatial discretization: finite difference, compact scheme, finite element, spectral and pseudo-spectral methods, control volume. -Accuracy, strong and weak conservation forms, and truncation errors. -Time differencing: implicit, explicit, time splitting, variable time steps. -Numerical stability for advection and diffusion. -Elliptic, hyperbolic, and parabolic equations. -Pressure solution techniques, direct, iterative, multi-grid, sparse matrices, conjugate gradient, stopping criteria, pressure projection method. -Boundary conditions: Inflow, outflow, nested grids, forcing flows, Neumann, Dirichlet, relaxation regions. -Techniques for different types of flows: steady, incompressible, 2-D, variable density, inviscid, geophysical. -Sub-grid scale & turbulence modelling: LES, eddy viscosity, dissipation, k-ε -Variable grids: clustering, generalized coordinates, moving boundaries, free surface. -Model validation, testing, and evaluation -Special techniques: upwinding, staggered grids, vorticity formulation, sharp fronts. -Data assimilation and forecasting Note: don’t assume it will be a quick rush because it's mentioned late -Programming techniques: optimization, vector – parallel computing. Prerequisites: Numerical Analysis, Fluid Mechanics, Physical Oceanography, Partial Differential Equations, Data Programming With Mathematica, Mathematical Statistics

Field Oceanography: This course explores relationships between living organisms in the sea and the ocean environment. biological processes are introduced in the context of physical, chemical and geological oceanography. Course stresses a sea-going field work and includes day trips in local marine waters and hands-n laboratory investigation. Course will also reinforce some field activities encountered in prerequisites. Objectives and Outcomes: Operate various oceanographic instruments & equipment safely and effectively at sea & in the laboratory. Analyse oceanographic samples in the laboratory using common techniques and protocols. Explore data and samples collected and synthesized to identify trends. Apply concepts introduced in the classroom to interpret data and samples collected. Compare data and samples collected with those cited in published works. Present data and sample analyses in written format using figures and tables. Assess efficacy of sampling operations and offer suggestions for future work. Course Materials --> There is no textbook for this course. Students will be provided handout documents/objectives or will print such materials from course site, etc. Texts used in prerequisites can prove quite useful. Students must have access to a computer to complete the required work. Data and other files will be shared online and/or flash drives. Students should dress appropriately for field activities and bring drinking water. Be prepared for the weather since there will be limited shelter on the boat and elsewhere. Closed-toe shoes required. Course Assessment --> Participation 30% Exams 20% Manuscript 50% Students will be assessed on their active involvement in field and laboratory activities, as well as lecture discussions. Students must also demonstrate satisfactory seamanship skills such as knot tying and knowledge of vessel safety and emergency procedures. Students will complete online exams on course content from both lectures and field sessions. All exams must be completed by midnight on the last day of class. Students will be assessed on their contribution to a group-written scientific manuscript. It should incorporate all data collected during the course and should be written in the style of oceanography journals. Literature review should supplement the background and discussion sections. The manuscript must be submitted by email in pdf format. Late manuscripts will be penalised 10% per day late; there will be a cut-off deadline. Class meets 6 days a week for 14 days. Each day means 6 – 8 hours. Sessions per day to have both morning and afternoon schedules. Course is given at times that’s not during a “spring” or “fall” semester. There will schedule for sustenance, good hydration and restroom need if required. Sessions can be spent in the field or lab, or both, or both and lecture. Course Outline: Week 1 Lab – Introduction, safety briefing, natural history Field – Field introduction, safety briefing, bathymetry, “CTD casts” Field – Bathymetry mapping Lecture – Physical background Lab – “CTD” data plotting Beach BBQ – Get to know your classmates and instructors. Field – Optical measurements and water sampling (Niskin bottles) Lab – Nutrients Lecture – Optics, phytoplankton, and nutrients Lab – Secchi disk and PAR meter data analysis Field – Phytoplankton and pigment samples (Niskin bottles), phytoplankton net tows, deploy sediment traps Lab – Plankton microscopy Lecture – Respiration, grazing, BOD Lab – Pigment analysis Field – Deploy BOD bottles, benthic grabs, sediment coring Lab – Sediment sample processing Field – Recover BOD bottles, recover sediment traps, sediment coring Lab – Oxygen measurements, sediment sample processing Lecture – Vertical flux and benthos Lab – sediment sample processing Lecture – Biogeochemistry and sediment cores Lab – Open lab for catchup Lecture – Fish and fisheries, marine mammals Lab – Data analysis and writing Field – Fish and Marine mammals, passive acoustics Field – chosen island, swimming Brunch, BBQ and Bar – Celebrate your accomplishments Open Class – work on your manuscripts No Class – work on your manuscripts No Class – Manuscripts due before midnight! Be Good to yourselves and others! Prerequisites: Geological Oceanography, Biological Oceanography, General Oceanography, Organic Chemistry I, Chemical Oceanography Marine Pollution: An overview of marine (fresh water and saline), estuarine and watershed pollution with a focus on deleterious inputs The goal of Coastal and Marine Pollution is to provide students with an overview of the various inputs to estuaries and the ocean that constitute pollution, with an emphasis on coastal pollution. Both organic and inorganic pollutants will be covered, as will the problems caused by living organisms (indigenous and non-indigenous) that produce toxins and diseases. Students who successfully complete this course will have a knowledge and understanding of: The sources of inputs; The biological, chemical and/or physical nature of the inputs and how those inputs interact with water; The roles that freshwater, estuaries and the ocean play in receiving, altering and distributing inputs; How pollutants are sampled and measured; Mitigation approaches that can be taken to prevent or minimize pollution; The various policies, treaties, laws and regulations that affect pollution; The economic impacts of pollution. In course will enforce the following: Classification of contaminants Chemical composition Inorganic Organic Origin Natural substances, e.g. petroleum and its products Anthropogenic compounds, i.e. synthetized, produced by man, e.g. NPs- nonylphenols, OTs – tin organics, endocrine disruptors, PAHs, nets, etc, etc, etc, etc, etc. Toxicity or other toxic properties Usage – e.g. pesticides: fungicides, herbicides, insecticide, infrastructure, household, industrial, etc., etc, etc, etc. Sources of pollutants Marine contaminant cycle Monitoring Progressive regulation and guidelines Marine Strategy Framework Directive Groups of dangerous and harmful compounds indicated, and the marker compounds of these groups selected Models and rubrics for evaluation. Descriptors Course will also place good emphasis on picture slides exhibiting pollutant types and their influences on habitats and environments. Such includes ecological/ecosystems shocks related to oxygen content, acidity, salinity, migration, carcasses (Aves and aquatic), etc., etc. Typical text: Clark, R.B. 2001. Marine Pollution, 5th ed. Oxford University Press Supporting literature: Ángel Borja et al (2011). Implementation of the European Marine Strategy Framework Directive: A Methodological Approach for the Assessment of Environmental Status, from the Basque Country (Bay of Biscay), Marine Pollution Bulletin, Volume 62, Issue 5, Pages 889-904 Region counterpart to the following (sea-based & land-based sources) Victoria Tornero and Georg Hanke (2016). Chemical Contaminants Entering the Marine Environment from Sea-based Sources: A Review with a Focus on European Seas, Marine Pollution Bulletin, Volume 112, Issues 1–2, Pages 17 – 38 Grading --> Three - 100 point exams (300 pts,) Labs + field activity (400 pts.) Laboratory investigations Chemistry software (modelling, characterisations, analysis) Includes software from Organic Chemistry prerequisite Software for inorganic materials as well Field investigations A 100-point research paper 1 review of a current pollution research paper (50 pts.) Progressive aquatic/marine standards like those of Norway, Switzerland, Netherlands, Maldives or Greece, or if you have an elite sea front hotel where the water is a main attraction. --The research paper will consist of a pollution topic relevant to the student’s own area of thesis or dissertation research. A draft of the paper must be submitted by mid-semester for basic content and grammatical review and then it must be revised and submitted for final grading one week before the last exam. A short synopsis of the paper will be presented to the entire class during examination week. Term paper must be at least 12-15 pages long Must include Literature citations done in the oceanographic article style Final copy must be submitted BOTH in hard copy and electronically --Each student will be required to present an oral review and corresponding 2-page synopsis on one of the lecture topics at the end of that lecture. The oral briefing will consist of 10 minutes for the presentation and 5 minutes for questions. The reviews must cover a recent research paper (published within the past year) and relate to the lecture for that day. For example, if the student selects ocean acidification then a research paper from the peer-reviewed literature on that subject must be presented. All students will be given a copy of review papers 1-2 weeks before the presentation, so that they can read it before the lecture in which it is presented. Concerning research paper students will incorporate use of software encountered in Organic Chemistry I and labs. Such is a means to have strong exhibition of ability with compounds, molecules, etc. where student can provide detailed parameters, significant groups, simulations and so forth. Students must also try to incorporate ideas of treatment(s) for pollutant(s), where possibly software can possible be applied to simulate outcome(s); regardless of the type of treatment, often possible is a molecular view of things. LABS IDEAS --> serc.carleton.edu/NAGTWorkshops/oceanography/activities/72961.html serc.carleton.edu/NAGTWorkshops/intro/activities/25300.html serc.carleton.edu/NAGTWorkshops/sedimentary/SGP2014/activities/85105.html https://serc.carleton.edu/NAGTWorkshops/online_field/activities/236662.html https://serc.carleton.edu/NAGTWorkshops/intro/activities/95353.html The following journal article provides well established experiments to pursue: Bernt Zeitzschel (1978). Controlled Environment Experiments in Pollution Studies, Ocean Management, Volume 4, Issues 2–4, Pages 319 – 344 Prereqs: General Oceanography, Organic Chemistry I

Field and Lab Techniques in Marine Fisheries The course is designed as a field-oriented introduction to fisheries techniques in the marine and estuarine environment. We will conduct various small surveys that will help prepare you for designing field experiments (if you have an interest in graduate school) or conducting routine fisheries sampling (if looking into a state or federal position). Or if you are currently undecided on your future direction, this class will acquaint you with some of the ways biologists, ecologists, and fisheries professionals sample fish and invertebrate species for research as well as introduce you to a variety of fish and invertebrate species in the ambiance. As such, fieldwork will make up a large portion of the course (please read the Fieldwork section below), but the course will also consist of hands-on lab experiences and introduce some analytical methods as well. This course will be given during “summer” and “winter” sessions where one assumes they are not taking other courses during such time. My goal for you at the end of this class is to make you familiar with a variety of sampling techniques and associated lab procedures and provide a brief introduction into analysing the data you collected as well as why fisheries biology is important in the face of a changing climate and growing population. Lectures --> When we are not in the field or lab, lectures will occur in the morning. Lectures will provide an overview of certain techniques and real-world application. We will also be reviewing the primary literature to understand why certain techniques are used. For laboratory/field notebook --> You should keep and have a notebook with you at all times! Your notebook will not be graded, but the information that is disseminated during field/ lab activities will be on quizzes and the final. Keeping information in your notebook will also be very helpful when writing your final report and in tying together concepts from various activity days. Boat trips --> When we have a boat day, the boat leaves the dock at 8 am!!! This means be on board the vessel before 8 am. Final Report --> You will be required to write one report, the data will be collected in a group but the writing of the report will be up to you! Each report needs to include an Abstract, Introduction, Methods, Results, Discussion, and Literature Cited sections. Tentatively, the report will either examine the age-and-growth of near-shore fishes or compare larval recruitment at various locations. Your report should read like a scientific paper (primary literature) and will follow the guidelines of the Gulf and Caribbean Research. Fieldwork --> In addition to boat trips, we will spend MOST of our time outdoors. Students will be held responsible for information discussed by the instructor and/or the teaching assistant during field excursions. Please refer to the student handbook regarding appropriate preparation and dress for fieldwork. We will be conducting activities in clear to brown water, in marshes to beaches, and around seagrass beds to sharp oysters; therefore, flip-flops, sandals, crocks, and bare feet are not permissible. Please bring an old pair of sneakers that you do not mind ruining, or purchase a cheap pair of sneakers (thrift stores are great for this!). Most “aquashoes” are also not permissible because they slip off in mud. I have recently become aware of expensive sandals called “Chacos”; these are also not suitable to most of our field activities and can be consumed by the Mississippi mud in no time at all! Footwear that protects the entire foot is also required on all field trips and vessels. Sunscreen, sunglasses, and clothing that minimizes sun exposure are highly recommended; furthermore, we will likely get muddy and some grass is pointy so bring appropriate clothing. You may and should wear a swimsuit under your clothes if you anticipate getting wet (again will be in the field a lot). We will snorkel on some trips; snorkel gear will be provided, but you may bring your own if you have it. One-pagers --> These will be a one page maximum write-up of the particular activity for the day or a review of a scientific paper. The objective is to summarize why we performed the activity, what we found, and how it fits into the big-picture. These will be due within two days of the activity. Participation --> In addition to the execution of lab exercises and field trips, you will be expected to pitch in and help as needed. All students will assist in maintaining/cleaning the lab space, loading/storing equipment, recording data, and working gear/instruments Grades --> Your grade will be based on a final, a report, one-pagers, quizzes, and participation in activities/trips. Grades will be calculated as follows: Lecture/Participation/Fieldwork 20 % One-pagers 15% Quizzes 15% Report 25% Final 25% Course Schedule --> The schedule outlined below is a very, very tentative list of topics we will cover and the approximate timeline. Dates/topics are subject to change due to changes in field trip schedules (weather happens, machinery breaks down, and plans change). -Introduction to the class, local fauna, and various sampling gears -Field Trip -Morning off/Night sampling -Passive gears/Acoustic survey -Data analysis day/ start of age and growth -2 Day Trip -2 Day Trip -Lab day/data analysis/writing -Field Trip -Time to finish your assignments/ Final Prerequisite: Organic Chemistry I, Upper Level Standing Data Analysis in Atmospheric & Oceanic Sciences: Grading --> Homework 20% Labs 20% Midterm Exam 25% Final Exam 35%. Exams are open book and open note. Homework assignments will include computational and simulation activities given to students, where instructor is bly responsible for conceptual setups. For exams students will also be required to provide heuristic design for computational and simulation requests. Fundamentally statistical in nature are questions concerning the behavior of the atmosphere, climate and oceans. Computational and simulation assignments given to students follows only heuristics setup by instructor. Example concerns: (1) whether character of tropical storms and hurricanes alter with time; (2) whether warming of the globe is parallel with natural variability or not; (3) the influence of El Nino on global weather patterns. Emphasis on the application of the instruction to actual data. The prime objective is computation via Mathematica and so forth. NOTE: In the Mathematica environment there is the Wolfram Data Repository available; not necessarily confined to it however. Assisting Texts (but not confined to them) --> Thiebaux, H. J. (1994). Statistical Data Analysis for Ocean and Atmospheric Sciences. Elsevier Wilks, D. S. (2019). Statistical Methods in the Atmospheric Sciences. Elsevier COURSE TOPICS: ---Fast Fast Probability Distributions: Axioms, frequencies modelling, simulating random variables Data sources, APIs, file types. Introspection and querying Characterising the events of tropical storms and hurricanes; characterizing tropical Atlantic Sea surface temperature variations; characterising El Nino events; exploratory analysis of rainfall data; unmixing ice ages; testing for drought; fitting ocean currents. ---Some fast fast statistics review Data sources, APIs, file types. Introspection and querying. Generating summary statistics, box plots, skew, kurtosis, density plots, Q-Q, P-P, Shapiro-Wilk test, kolmogrov-Smirnov test, Anderson-Darling test, MLE and confidence intervals. ---Hypothesis Testing Priority is applying raw oceanography and atmospheric data to conjure hypothesis and test them for validity and meaningfulness...that’s all (Kentucky like). Beginner examples: questioning whether there are distinct regimes of atmospheric circulation behavior during the 20th century, or of Atlantic Hurricane activity. ---Regression (logistics and the computational substance) Note: this is not a regression analysis course, say, you will depend much on your mathematical statistics experience, where logistics towards credible computational substance is the prime directive. Review prerequisites notes, and take notes. Plan out your development flow, and be fluid and coordinated with your Mathematica/ functions or R packages. Multivariate regression Contemplating variables based on data analysis Heteroscedasticity and generalised least squares Model selection methods (Vuong’s test, F-test, AIC, BIC, HQC) Splitting data (training, testing) Forecasting and error Quantile Regression and Lasso Regression Most topics based on GLS prior to apply Scatter Plots Scatterplots are a useful first step in any analysis because they help visualize relationships and identify possible issues (e.g., outliers) that can influence subsequent statistical analyses, or need of regression beyond simple OLS/WLS/GLS, say, quantile regression (or generalized nonlinear models). Note: concerns for the number of variable pairs. Contemplating variables based on data analysis Model selection methods (Vuong’s test, F-test, AIC, BIC, HQC) Splitting data (training, testing) Forecasting and error Regression and Trend Analysis: global warming; whether El Nino is becoming more influential over time; whether the intensity of tropical storms and hurricanes are increasing over time. Identifying atmospheric and oceanic factors that control variations and trends in tropical storms and hurricane activity. ---Time Series (logistics and the computational substance) Note: this is not a time series analysis course, say, you will depend much on your mathematical statistics experience, where logistics towards credible computational substance is the prime directive. Review prerequisites notes, and take notes. Plan out your development flow, and be fluid and coordinated with your Mathematica/ functions or R packages. Time Series representation of data Difference equations and conditional expectation Linear and logarithmic forms Seasonality and trend (methods of identification) Autoregressive Moving averages Exponential Smoothing Box Jenkins Approach Model Identification Estimation Validation Box-Jenkins analysis on data Splitting data (selection, training, testing) GARCH development Fourier Tools? Spectral analysis and spectral representations? Filters? Multivariate time series models? Seasonal and cyclic patterns; modelling the behavior of El Nino; modelling the global temperature series; Fourier analysis and inverse problem; spectral analysis; seasonal rainfall; excessive abnormal respective regional temperatures into coming seasons making use of past a current data for seasons; excessive abnormal respective regional sea temperatures into coming seasons making use of past a current data; solar storms, aurora borealis, aurora australis. R. Modarres and T. B. M. J. Ouarda (2014). Modelling the Relationship Between Climate Oscillations and Drought by a Multivariate GARCH Model. Water Resources Research, Volume 50, pages 601 – 618 ---Ensemble/probabilistic prediction Analysis and logistics for Ensemble models to be implemented R Packages of interest: ensembleR, ensembleML, ensembleBMA, ensembleMOS, ProbForecastGOP, tsensembler, modeltime.ensemble CSTools SpecsVerification, scoringRule An R assist: Vannitsem, S., Wilks, D. S. and Messner, J. (2018). Statistical Postprocessing of Ensemble Forecasts. Elsevier ---Analyzing spatial data Understanding the spatial behaviour influence of El Nino and the North Atlantic Oscillation on atmospheric circulation patterns; infilling a sea-surface temperature data or a geologic map; tropical storm surges; range of Arctic/Antarctic ice packs and regional temperatures. NOTE: additional pursuits will come from the following text: H. von Storch and A. Navarra. (1999). Analysis of Climate Variability: Applications of Statistical Techniques Proceedings of an Autumn School Organized by the Commission of the European Community on Elba from October 30 to November 6, 1993. Springer-Verlag Berlin Heidelberg Prerequisites: Mathematical Statistics Coral Reef Dynamics Coral Reef Dynamics is an introduction to research on the biology and ecology of coral reefs. The course examines coral symbioses; reef types and their distribution; coral allies and associated species; and tropical nearshore community dynamics. Students will acquire the necessary foundation to conduct field research using standard subtidal sampling methods. The course culminates in an intensive field research experience in coral reef community ecology at field sites [wherever appropriate]. Students will design and conduct an original field research project and present their findings during a symposium held at Auditorium/Symposium. An extremely intensive course, and while in the field, we will work straight into Saturdays. Students are engaged in work that contributes directly to the national marine research plan and to growing knowledge about marine ecological dynamics of the Reef System. Work by Coral Reef Dynamics students will contribute directly to marine conservation and integrated coastal zone management in ambiance. Will pretty much appreciate having domestic underwater cameras among groups (photos and videos with audio capabilities) References (not limited to & not based on given order) --> -Goldberg, Walter. 2014. The Biology of Reefs and Reef Organisms, University of Chicago Press -Stoddart, D.R. and Johannes, R.E. (1978). Coral Reefs: Research Methods. Monographs on Oceanographic Methodology. UNESCO -Barnes, D.J (1983). Profiling Coral Reef Productivity and Calcification Using pH and Oxygen Electrodes. Journal of Experimental Marine Biology and Ecology. Volume 66, Issue 2, pages 149 – 161 -Madin, J.S.et al (2016). A Trait-Based Approach to Advance Coral Reef Science. Trends in Ecology and Evolution. Volume 31, Issue 6, Pages 49 – 428 -Costello, M. J. et al. (2017) Methods for the Study of Marine Biodiversity. In: Walters, M., Scholes, R (eds). The GEO Handbook on Biodiversity Observation Networks. Springer, Cham; pp 129-163 -Taxonomy and species coral catalogue -Taxonomy and species fish catalogue -Taxonomy and species invertebrate catalogue Course Materials & Preparation for Fieldwork --> -Students officially enroled in course must acquire course system ID & password (that can be changed by student) to upload developments, assignments and possibly logs to a secure course “cloud”. -A valid passport may or may not be necessary; criminal record doesn’t pay. -Acceptable Immunization record -Concerning travel and housing accommodation (if both are relevant), and places officially recognised for visits and research, students may be required to sign various documentation declaring their proper knowledge of such. Restrictions on venturing may be overall difficult due to students reaching adulthood age and freedom of “sight seeing”, etc. Consequently, a day or two before first departure to field activity there may be a required 2 hour seminar detailing travel safety and protocols with scheduled field sites operations; students then to sign documentation declaring they are well informed of travel precautions and protocols relating to research destination(s) and environments in ambiance. -Some courses require diving insurance. Hopefully not this one. -Snorkel Gear -Snorkels and Swimming Efficiency -Participation in a life guard Fit-Recreation snorkel skills analysis. Practice both swim and snorkel skills in the FitRec pool prior to departure for the field. In general, don’t wait on this course to learn how to be proficient in deep water. Will be evaluated as part of participation -Will very much appreciate having domestic personal underwater cameras among groups (photos and videos with audio capabilities) for field sites activities; charge your cameras accordingly for various activities. SD card adapters or interfaces for computers, flash drives/thumb drives. There must be competent means to identify which photos came from what particular cameras, subject to dating. There must be means to confirm that photos taken are not plagiarized. Expedition groups may or may not be assigned to grids. -Dive gloves (1-1.5mm or thin gardening gloves), dive hood (lycra or thin neoprene), underwater flashlight -Field gear and clothing required: light rain jacket, polarized sunglasses, sunscreen, insect repellant, light longsleeved clothes, hat, bathing suit. Recommended: headlamp, sandals (chacos or tevas), water bottles(s), and a few cool weather clothing items, toiletries, hair lotion (with brush or comb), deodorant, chapstick, body cream after showers. First aid kits. -Laptop stations and secure internet access -Heavy duty trash bags if needed (general and for recycling); not for drifting away in water. It's imperative that events are well planned out along with operational logistics. Precipitation generally will not be a deterrent against activities, so dress accordingly for pending weather with accommodating transportation. NOTE: before official operations at chosen field sites, during prior days close to date(s) of official operations will have site walk-throughs, and a few filed snorkeling/diving practices. Walk-throughs and snorkeling practices will be evaluated as part of participation. PART OF EXPECTATION: apart from corals video cameras will also record various elements of animalia. Will try to use such data concerning the relation between biodiversity/ecology and coral welfare. As well, what (multicellular) organisms in presence are typical of a health reef? What are the habitual lifestyles in regard to participation in the system? Student Evaluation --> A maximum total of 1000 points in scoring is possible. It’s quite easy to falter in this course without discipline, preparedness, accountability, patience and CONSIDERATION FOR OTHERS. Parameters as follows-- -Attendance and engagement in Class, Lab, and Field Sessions (100 points) Students must meet a minimum attendance criteria to sustain enrolment in course; failing to do so results in (respective) student forfeiting 690 points of total course grade. -Response to readings (100 points): On five occasions, students will write (1) an original, testable research question based on topics presented in the HW readings and (2) a brief statement on why the question is important. Students will email this assignment to the designated student discussion platform. -Survey of applied statistical methods of interest (100 points). There may be developed or cited questions that can prove difficult towards statistical experimental design. Will identify the quantitative and qualitative aspects. Students will be responsible for dealing with statistical designs concerning hypothetical questions and experiments considered. NOTE: efficient statistical sampling will be considered “kindergarten”. -Discussion of papers (100 points): on campus for designated seminar-style lectures will have discussion of a contemporary paper in tropical marine invertebrate biology. Preparedness and participation during discussion will be assessed. -Field Journal (100 points): Each student will keep a traditional naturalist’s field journal during the course of the class. Journals will be graded on the quality of information recorded on focal taxa (i.e., illustrations, technical descriptions, field sketches, and observations). Expectations for journals and exemplary journal entries will be presented in class. -Project proposal (100 points): Students will present their individual project proposals to the class during our final in-class session. Expectations will be discussed in class. -Field research (100 points): Individual students and student field teams will be evaluated for their conduct while carrying out field research. In addition to scientific merit, the rubric includes assessment of group cooperation, collaboration, division of labour and conduct in public. -Presentation notes (100 points): Each student will be required to submit a .docx of their ppt slides and talk notes prior to the final presentation of their research. This document will be graded for content and clarity. -Final Presentation (100 points): Students will present a ppt of their field research project during our Symposium/Auditorium. Each student talk will be 8 – 10 min. followed by 2 – 3 min. for questions. -Punctuality and preparedness for meetings or coral reef exploration with lectures in class and in the field (100) -NOTE: LITTERING AND POLLUTING WILL DRASTICALLY AFFECT YOUR GRADE. -NOTE: FiTRec, SITES(S) WALK-THROUGHS AND SNORKELING PRACTICES WILL DRASTICALLY AFFECT YOUR GRADE. -NOTE: WILL NOT TOLERATE IMBECILES AND SABOTEURS TRYING TO MAKE COURSE AND ITS ACTIVITIES INTO A RAW PUBLIC EVENT. PERSONAL TEXTING AND PERSONAL SOCIAL MEDIA WILL GENERALLY BE DISLIKED; KNOW YOUR PRIORITIES. NOTE: course concerns neither trapping of animals/living organisms for profit nor exploitation nor consumption. As well, if any trapping of specimens, lack of proper release into rightful environment will yield automatic failure in course, possible suspension or expulsion, and possible criminal charges. Prerequisites: Oceanography Field Experience, Geological Oceanography, Biological Oceanography, Chemical Oceanography, Field Oceanography, Mathematical Statistics. Upper Junior Standing Coral Reef Resilience and Restoration: The health of Caribbean coral reefs can be volatile for various reasons. We will learn about the coral reef as one element in a coastal landscape ecology, about methods to restore reef health, and you will help to further develop these methods by integrating across biological scales and disciplines, from molecule to biosphere, and cell biology to systems ecology. This course runs parallel to Coral Reef Dynamics and is built upon the same background skills and knowledge, but from a more applied, conservation and restoration-oriented perspective. The heart of the course is natural history study and field work in ambiance of interest, as part of the local coral reef stewardship and restoration activities on the particular reef. References (not limited to & not based on given order) --> Goldberg, W. 2014. The Biology of Reefs & Reef Organisms, University of Chicago Press For the following literature identify the counterpart strategy plan for the ambiance in question NOAA. Coral Reef Conservation Programme strategic Plan: https://repository.library.noaa.gov/view/noaa/19419/noaa_19419_DS1.pdf Ambiance Legal Acts and Ratified Policies for coral reef conservation and restoration, identifying implications and initiatives permitted to full extent. How well do legal parameters support or harmonize with strategic plan? Funded opportunities, funded projects and applications Ambiance Deep Sea Coral/Sponge Data Portal/Database Data Images Technical Reports Deep Sea Coral and Sponge Map Portal Site Characterisation and Habitat Models Metadata Literature on Professional Methods and Guidelines for Coral Reef Conservation and Restoration. One example: Precht, William. 2006. Coral Reef Restoration Handbook Stoddart, D.R. and Johannes, R.E. (1978). Coral Reefs: Research Methods. Monographs on Oceanographic Methodology. UNESCO Barnes, D.J (1983). Profiling Coral Reef Productivity and Calcification Using pH and Oxygen Electrodes. Journal of Experimental Marine Biology and Ecology. Volume 66, Issue 2, pages 149 – 161 Madin, J.S.et al (2016). A Trait-Based Approach to Advance Coral Reef Science. Trends in ecology and Evolution. Volume 31, Issue 6, pp 49 – 428 Costello, M. J. et al. (2017) Methods for the Study of Marine Biodiversity. In: Walters, M., Scholes, R (eds). The GEO Handbook on Biodiversity Observation Networks. Springer, Cham; pp 129-163 Taxonomy/species Coral catalogue Fish catalogue Invertebrate catalogue PART OF EXPECTATION: apart from corals, video cameras will also record various animalia. Will try to use such data concerning the relation between biodiversity/ecology and coral welfare. As well, what (multicellular) organisms in presence are typical of a health reef? What are the habitual lifestyles in regard to participation in the system? Concerning course material & preparation for fieldwork requirements will be identical to what is detailed in prerequisite. However, for certainty, expressed again--> -Students officially enroled in course must acquire course system ID & password (that can be changed by student) to upload developments and possibly logs to a secure course “cloud”. -A valid passport may or may not be necessary; criminal record doesn’t pay. -Acceptable Immunization record -Concerning travel and housing accommodation (if both are relevant), and places officially recognised for visits and research, students may be required to sign various documentation declaring their proper knowledge of such. Restrictions on venturing may be overall difficult due to students reaching adulthood age and freedom of “sight seeing”, etc. Consequently, a day or two before first departure to field activity there may be a required 2 hour seminar detailing travel safety and protocols with scheduled field sites operations; students then to sign documentation declaring they are well informed of travel precautions and protocols relating to research destination(s) and environments in ambiance. -Some courses require diving insurance. Hopefully not this one. -Snorkel Gear -Snorkels and Swimming Efficiency -Participation in a life guard Fit-Recreation snorkel skills analysis. Practice both swim and snorkel skills in the Fit-Rec pool prior to departure for the field. In general, don’t wait on this course to learn how to be proficient in deep water. Will be evaluated as part of participation -Will very much appreciate having domestic personal underwater cameras among groups (photos and videos with audio capabilities); charge your cameras accordingly for various activities. SD card adapters or interfaces for computers, flash drives/thumb drives. There must be competent means to identify which photos came from what particular cameras, subject to dating. There must be means to confirm that photos taken are not plagiarized. Expedition groups may or may not be assigned to grids. -Dive gloves (1-1.5mm or thin gardening gloves), dive hood (lycra or thin neoprene), underwater flashlight -Field gear and clothing required: light rain jacket, polarized sunglasses, aquatic eco-friendly sunscreen, light longsleeved clothes, hat, bathing suit. Recommended: headlamp, sandals (chacos or tevas), water bottles(s), and a few cool weather clothing items, toiletries, hair lotion (with brush or comb), deodorant, chapstick, body cream after showers. First aid kits. -Laptop stations and internet access -Heavy duty trash bags if needed (general and for recycling); not for drifting away in water. NOTE: before official operations at chosen field sites, during prior days close to date(s) of official operations will have site walk-throughs, and a few filed snorkeling/diving practices. Walk-throughs and snorkeling practices will be evaluated as part of participation. It's imperative that events are well planned out along with operational logistics. Precipitation generally will not be a deterrent against activities, so dress accordingly for pending weather with accommodating transportation. Coral Reef Resilience and Restoration is a field-centred case study of the challenges, triumphs, and travails of restoration ecology in tropical watershed and coastal ocean ecosystems. The pedagogical objective is to understand the processes that sustain the watershed, coastal ocean, and constructed landscape in which the coral reefs of today are embedded, and how these can be capitalized upon to accelerate coral reef recovery. The course begins with the study of coral reef environments, coupled human and natural system dynamics, and the basics of restoration ecology. Several days are spent in comparative study of framework building corals and how they interact to assemble- naturally and under directed recovery the reef fabrics of the Mesoamerican coral reef system. Each student will focus on a specific fabric; for example, the mixture of branching and massive corals typical of a Caribbean fore-reef terrace, the multi-coloured tapestry of lettuce, fire, and finger corals of ambiance’s massive shallow reef buttresses, and the strangely suspended coral communities of mangrove tidal channels. Each student will enumerate the constituent species of a fabric, identify the key species, ecological relationships and processes that determine the fabric’s ability to self-sustain and propagate, and finally propose means of nudging the fabric from a state of disintegration to one of reintegration, maturation, and stability. Grades are based upon one exam, on readings and lecture, and on presentation of a professional seminar based upon the student’s own research. The combined effects of anthropogenic climate change and cumulative local human impacts are profoundly altering coastal habitats where the greater part of humanity lives. These effects are pronounced in coral reef and associated habitats, where the loss of value to people is extreme, inspiring Sisyphean attempts at restoration, often on an impractically minute scale and at very great expense. A broader perspective is needed that takes into account the one to two century Great Hiatus during which human impacts, compounded by climate change and overpopulation, could eventually be brought under control. If they are, then we can expect to rehabilitate coral reef ecosystem function using the knowledge acquired and innovative methods to be developed during this course. Can coral reefs survive the harsh transition years of the Great Hiatus? Can we continue to benefit from the many values provided by coral reefs during this rocky interregnum? Through a mix of organismal, community and forensic ecology we will examine aspects of the biology and socioeconomics of coral reef recovery. We will then develop new knowledge and strategies for rebuilding the quality and resilience of coral reef habitats during the Great Climate Hiatus. Topics range from traditional practices to modern ecosystem-based management, from the monitoring of reef health through a chief’s eye, to advanced molecular diagnostics. The course hinges on theoretical questions that apply to all ecosystems, not just coral reefs. How does biological diversity influence ecosystem function? Is high biodiversity necessary for coral reefs to continue to provide food and livelihoods for people? Do ecosystems exhibit alternate metastable states? Is the behaviour of coupled human and natural systems lawful, and if so, predictable? However, we also recognize that the technological sophistication of coral reef restoration has been expanding rapidly; the idea has progressed from a joke, to a dream, to a practical reality. Today, coral reef restoration can mean any one of five different things. First, it could mean the reduction of human impacts so that coral reef systems have an easier time repairing themselves naturally. All the other meanings involve direct ecological manipulations directed toward some goal. The goal could be simply to replace hard coral coverage where it has been lost. It could be to recover one or more species from recognition as threatened or endangered. Many choose to focus on the restoration of ecosystem services; that is, a system is returned to a state where it once again provides well for human needs. Finally, coral reef restoration can mean that a degraded coral reef system has been brought back to a state in which all of its constituent species are secure, and the community can maintain and replace itself. Conditions, coverage, species recovery, restitution of immediate value to people, and a total ecosystem recovery. While not mutually exclusive, the paths to anyone are somewhat divergent. It matters to have specific goals in mind. The restoration ecology of coral reefs is in its infancy- we are barely at the stage where we can see the potential value of expanding our efforts…but we also see the pitfalls all the more clearly. One of the most important areas of missing information- and the focus of our class- is the natural history of coral reef framework-building communities. These communities are the tapestries of corals, algae, sponges and other invertebrates, and fishes that together weave the magic of growing and maintaining the coral reef as a physical entity. Our time in the field will hone skills in natural history, field survey, heuristic modelling, and short-term experimental studies. CCFS sits upon an atoll rim surrounded by a lush mosaic of littoral and mangrove forests, seagrass meadows, and varied coral reef environments. Students will explore how marine science can help in ecology improvement or in time of crisis, and prepare their results in a form that can be shared with other scientists as well as the many lay people who care greatly about the future of coral reefs in ambiance and elsewhere. This is an extremely intensive course, and we work straight through the weekends. Time in ambiance is in two parts beside the travel days: an initial two days of exploring the watershed landscape that supports coral reef growth at ambiance, and then the remaining days during which everybody will conduct their field research, analyse their data, and present their results in a professional manner. Grading --> Project proposal 0.2 Pre-field quiz 0.1 Conduct of field research 0.1 Oral project presentation 0.2 Written paper 0.4 CONCERNING WEIGHTS IN GRADING SOME ASPECTS OF GRADE SCORING FROM PREREQUISITE WILL BE NATURALLY APPLIED OR EMBEDDED. Topic Outline --> -Coral Reefs in Context: The comparative anatomy of tropical vanua ecosystems and what’s happening to them today. -Scleractinian Corals: Major Builders of Modern Coral Reefs -Cumulative human impacts on coral reefs -Rules of reef fabric assembly and turnover: a theoretical basis for restoration -Methods in Coral Reef Restoration I: Rapid expansion in sophistication and scale of Caribbean reef restoration -Restoration technologies II: Inspiration from nature and by necessity -Reef Crest Fabrics: acroporid, agariciid, and faviid framework dominants and their motile associates -Natural Reefs, No-Analog Reefs, Non-Reefal Coral communities, and Reiteratively Restored Reefs NOTE: course concerns neither trapping of animals/living organisms for profit nor exploitation nor consumption. As well, if any trapping of specimens, lack of proper release into rightful environment will yield automatic failure in course, possible suspension or expulsion, and possible criminal charges. Prerequisites: Coral Reef Dynamics Sources and software for Oceanographic Data: National Oceanographic Data Center Home Page (World Data Service) British Oceanographic Data Center SeaDataNet Copernicus Environment Monitoring Service SMHI ICSU United Nations Statistics Division United Nations Statistics Division Environmental Indicators UN Geo Data Portal NOAA # METEOROLOGY Curriculum: --Core Courses Scientific Writing I & II, General Physics I; General Chemistry I & II, Organic Chemistry I --Mandatory Courses Calculus I-III; Ordinary Differential Equations; Numerical Analysis; Data Programming with Mathematica; Partial Differential Equations; Probability & Statistics B; Mathematical Statistics --Required Components Culture --> General Meteorology; Meteorological Analysis I-III; Radar & Satellite Meteorology; Meteorological Instruments I & II Physical Modelling --> Fluid Mechanics; Fundamentals of Atmosphere & Ocean Dynamics; Physical Meteorology I & II; Tropical Meteorology Atmospheric Physical Science --> Aerosol Physics & Chemistry; Air Pollution Chemistry & Physics Meteorological Scales --> Synoptic Dynamic Meteorology; Mesoscale Meteorology Data Analysis & Forecasting --> Numerical Weather Forecasting; Data Analysis in Atmospheric & Oceanic Sciences NOTE: for mathematics courses refer to Computational Finance post; for Physics courses refer to the physics post. General Meteorology: The purpose of this course is to: Introduce to students the basic principles and phenomena in the atmosphere. Explore processes that shape daily weather conditions. Introduce to students how meteorologists create weather forecasts. By successfully completing this course, students will be able to: Understand and describe characteristics and scales of different processes in the atmosphere. Comprehend basic physical laws behind atmospheric processes. Recognize how to read and examine weather charts and reports. Describe and discuss issues in atmospheric sciences and weather forecasting. Course requirements: Typical text: Donald Ahrens and Robert Henson. Essentials in Meteorology: An Invitation to the Atmosphere. Cengage. Lab Manual: http://www-das.uwyo.edu/~geerts/atsc2000/lab/Manual_Fall09.pdf Technology: Computer, internet connection, web-browser. Scientific calculator. Grading: Problem Sets 15% Quizzes 21% Labs 25% 3 Exams 39% Course Outline: Weather Map Basics (appendix C): Time on weather charts Weather observations Data processing and weather charts The Atmosphere (chapter 1): The earth’s atmosphere Layers in the atmosphere Weather and climate Energy, Temperature, and Atmospheric Heat Transfer (chapter 2): Temperature and heat Heat transfer Radiating heat Seasonal and Daily Temperature Variation (chapter 3): Earth’s seasons Seasonal temperature Daily temperature Applications of temperature data Moisture in the Atmosphere (chapter 4): Water Phase change Water vapor and humidity Daily and regional variations in relative humidity Dew, Frost, and Fog (chapter 4): Dew Frost Fog Atmospheric Stability (chapter 5) Concepts of atmospheric stability Absolutely stable atmosphere Absolutely unstable atmosphere Conditionally unstable atmosphere Clouds and Cloud Development (chapter 4 & 5) Clouds Atmospheric conditions for cloud formation Observing clouds Precipitation (chapter 5) What is precipitation? Precipitation formation Types of precipitation Atmospheric Pressure and Forces in the Atmosphere (chapter 6) Atmospheric pressure Forces Influencing wind Determining wind direction and speed Local Winds (chapter 7) Scales of atmospheric motions Microscale motions Mesoscale motions Global Circulation (chapter 7) General circulation of the atmosphere Air circulation and pressure in the 'real world' Jet streams El Niño and La Niña Air Masses and Fronts (chapter 8) Air masses Fronts Midlatitude Cyclones (chapter 8) What is a Cyclone? How do cyclones and midlatitude cyclones form? Where do midlatitude cyclones form? Case study Thunderstorms and Tornadoes (chapter 10) Thunderstorms Tornadoes Hurricanes (chapter 11) General information about tropical cyclones Stages of hurricane development Hurricane structure- Measuring, categorizing, and forecasting hurricanes Hurricane threats Weather Forecasting (chapter 9) Weather forecasting steps Forecasting tools Numerical weather prediction Ensemble forecasts and spaghetti models Earth's Climate and Climate Change (chapter 13) Past climates Causes of climate change Climate feedbacks Predicting climate change Wrap up Review Final Prerequisite: Calculus I Meteorological Analysis I: Upon completion of this class, students will be able to: 1. Conduct a weather discussion and apply diagnostic, prognostic, and technological tools to evaluate atmospheric processes across a multitude of scales. 2. Apply critical and analytical thinking to solve relevant scientific problems in both individual and collaborative settings. 3. Effectively communicate scientific information orally and in writing, including by electronic means, at an appropriate level for their audience. 4. Demonstrate mastery of the mathematical and physical foundations of meteorology and climatology as well as key atmospheric processes that occur at a variety of spatial and temporal scales. Purpose: Weather information is readily accessible over the internet, but what does all this information mean, and how can we use it to make forecasts? Broadly speaking, the purpose of this course is to get you down and dirty with real meteorological data to answer these questions. We will examine in-situ observational data, human-generated data, computer-generated data, and remotely sensed data. Course may require 3 sessions per week for 15 weeks. Typical Text: Milrad, S. Synoptic Analysis and Forecasting: An Introductory Toolkit Materials: Traditional stationery (and maybe coloured pencils) Forecasting Lab journal/notebook/spreadsheet Computer with internet access and meteorological data sources Computational platform Scientific Calculator Class activities will contribute to your final grade as follows: Class Exercises 35% Labs and forecasting pursuits 20% Midterm Exam 20% Final Exam (comprehensive) 25% The following is a guide, but there may be major updates since 1964: F. W. Burnett, K. N. Rao and A. Rouaud. (1964). Note on the standardization of pressure reduction in the International Network of Synoptic stations: report of the Commission for Synoptic Meteorology. World Meteorological Organsation, No.154 The following topics are a few of the concerns for labs. Seek the most constructive sequence in progression --> Introduction, computer setup, time zones, and geography; units for temperature and pressure METARs and the station model. Decoding METARs NWS text data Pressure reduction exercises. Station model review. Thermal wind 500 mb and 850 mb analyses. Instruction on online analysis tools (GARP) 300 and 200 mb analyses. Thermal wind lab. Meted: Jet Streams Surface analysis. Cross sectional analyses Comparisons of weather prediction model forecasts Analysis of satellite imagery GARP analysis of three-dimensional structures, trajectory analyses using model data Streamline and isotach analysis Forecasting in labs --> Concerning forecasting in labs we will issue deterministic forecasts four times a week (Mondays through Thursdays). Forecast lab times will be applied to identifying and analysing methods, logistics and implementation towards actual forecasting, Will apply whatever needed data, models, computation, etc. The forecasting Lab journal/notebook/spreadsheet will concern methodology/analysis implemented and forecast data development; all data predicted will then be succeeded by identifying professional forecasts, to then record true revelation data from actual weather. Based on respected 3-set data students will try to explain any high disparities or high convergences, and possible explanations. Class exercises--> Due at the beginning of class one week after they are assigned. Often, you will have time to work on them in class, perhaps on the following class day. Sometimes, these assignments will require computer resources to complete. Quizzes--> Concerns being at least competent and vigilant with knowledge and skills with past topics. Will concern various topics thrown at you multiple times in throughout the total number of quizzes. Additional software --> Course may have introduction immersion with some technical meteorological software from “Goody Bag”; there are alternatives to software described in outline. Course Outline --> Introduction, computer setup, time zones, and geography. Units for temperature and pressure METARs and the station model Decoding METARs NWS text data Interpreting upper-air maps Analysis of upper-air observations Analysis of upper-air observations II Kinematics Plotting vorticity and divergence Advection Weather station field trip Plotting advection Geostrophic wind Thickness and the hypsometric equation Numerical weather prediction Model output statistics & BUFKIT (or ambiance counterpart) Ensemble forecasting Analysis of surface observations Analysis of surface observations II Synoptic climatology and forecasting tips Vertical structure of the atmosphere The skew-T diagram Severe weather parameters Plotting severe weather parameters Satellite imagery Radar imagery Prerequisite: General Meteorology Meteorological Analysis II: Synoptic meteorology is the study of the weather on the regional to continental scale. This course examines important phenomena such as jet streaks, fronts, and vorticity maxima that govern the weather over thousands of square kilometers during the course of a few days. We limit ourselves to the midlatitudes. Synoptic weather systems behave very differently in the tropics, and those systems are covered in Tropical Meteorology. Smaller-scale phenomena such as thunderstorms, tornadoes, lake-effect snows, and gravity waves will be covered in the spring. Larger-scale phenomena such as ENSO, the MJO, and the NAO are the domain of Climate Dynamics, although they can modulate synoptic weather patterns. They are also key players in sub-seasonal forecasting, which the Special Topics course covers. Synoptic Meteorology is not simply a weather forecasting course, although you will make plenty of forecasts during the semester. Making forecasts without understanding is what computers do, so you will spend ample time learning how the weather works. Typical text: Midlatitude Synoptic Meteorology: Dynamics, Analysis & Forecasting, by Gary Lackmann Supplemental: Mid-Latitude Atmospheric Dynamics, by Jonathan Martin Materials: Traditional stationery (and maybe coloured pencils) Forecasting Lab journal/notebook/spreadsheet Computer with internet access and meteorological data sources Computational platform Scientific Calculator Class activities will contribute to your final grade as follows: Class Exercises 35% Labs and forecasting pursuits 20% Midterm Exam 20% Final Exam (comprehensive) 25% Labs --> A. Advance repetition labs to be predecessors to current course labs. Namely, prerequisite labs will be chosen appropriately as precursors to current course labs. B. Concerning forecasting labs we will issue deterministic forecasts four times a week (Mondays through Thursdays) similar to what was done in prerequisite, accompanied by probabilistic forecasts each day with the forecast city fixed for two weeks at a time. Forecast lab times will be applied to identifying and analysing methods, logistics and implementation towards actual forecasting. Will apply whatever needed data, models, computation, etc. The forecasting Lab journal/notebook/spreadsheet will concern methodology/analysis implemented and forecast data development; all data predicted will then be succeeded by identifying professional forecasts, to then record true revelation data from actual weather. Based on respected 3-set data students will try to explain any high disparities or high convergences, and possible explanations. Class exercises--> Due at the beginning of class one week after they are assigned. Often, you will have time to work on them in class, perhaps on the following class day. Sometimes, these assignments will require computer resources to complete. Quizzes--> Concerns being at least competent and vigilant with knowledge and skills with past topics. Will concern various topics thrown at you multiple times in throughout the total number of quizzes. Additional software --> Course may have introduction immersion with some technical meteorological software from “Goody Bag”; there are alternatives to software described in outline. During labs one may have to account for pressure reduction standards. The following is a guide, but there may be major updates since 1964: F. W. Burnett, K. N. Rao and A. Rouaud. (1964). Note on the standardization of pressure reduction in the International Network of Synoptic stations: report of the Commission for Synoptic Meteorology. World Meteorological Organsation, No.154 << https://library.wmo.int/doc_num.php?explnum_id=2849 >> Course Outline --> Introduction, computer setup, time zones, and geography Weather discussions; units for temperature and pressure Lab session (2 1/2 hours) METARs and the station model (advance); Decoding METARs (advance) NWS text data (advance). GEMPAK Dynamics review More dynamics review Energetics Importance of ageostrophy Lab Session: GEMPAK II – Basic programs (2 1/2 hours) Manipulations of the ageostrophic wind Sutcliffe development theorem Lab Session: GEMPAK II – Scripting and four-panel plots (2 1/2 hours) Traditional QG omega equation 𝑄⃑ vectors Lab Session: Automated plot generation (2 1/2 hours) Le Chatelier’s Principle; 𝑄⃑ part 2 Lab Session: An idealized QG model Weather forecasting Wx forecasting competence Lab Session: Diagnosis of vertical motion (2 1/2 hours) Isentropic analysis Fronts Lab Session: Group project of cyclones and storm case study (2 1/2 hours in lab) Further development outside course Frontogenesis Frontogenesis and vertical motion Lab Session: continue group project Types of fronts Group Presentations Lab Session: Analyzing wx conditions at a pt (2 1/2 hours) Special fronts Friction Isentropic analysis Cyclogenesis Explosive cyclogenesis Cyclone life cycles Potential vorticity More potential vorticity NWP Special Lab Session (2 1/2 hours) Baroclinic instability Prerequisite: Meteorological Analysis I Meteorological Analysis III (Mesoscale): Upon completion of this class, students will be able to: 1. Conduct a weather discussion and apply diagnostic, prognostic, and technological tools to evaluate atmospheric processes across a multitude of scales. 2. Apply critical and analytical thinking to solve relevant scientific problems in both individual and collaborative settings. 3. Demonstrate mastery of the mathematical and physical foundations of meteorology and climatology as well as key atmospheric processes that occur at a variety of spatial and temporal scales. Overview--> Throughout the semester, we will focus on three main topics: [Winter] weather Mesoscale circulations Convective weather At the end of the course, you will be able to diagnose and predict complex meteorological scenarios involving any (or all!) of these themes. Hard work and dedication will be required! Typical text: Markowski and Richardson: Mesoscale Meteorology in Midlatitudes Supplemental: Lackmann: Midlatitude Synoptic Meteorology Milrad, S. Synoptic Analysis and Forecasting: An Introductory Toolkit Materials --> Traditional stationery (and maybe coloured pencils) Forecasting Lab journal/notebook/spreadsheet Computer with internet access and meteorological data sources Computational platform Scientific Calculator Class activities will contribute to your final grade as follows: Class Exercises 30% Labs 25% Midterm Exam 20% Final Exam (comprehensive) 25% Labs --> A. Advance repetition of labs from prerequisite. Note: some labs will be adjusted to accommodate some course topics B. Concerning forecasting labs we will issue deterministic forecasts four times a week (Mondays through Thursdays), and probabilistic forecasts each day with the forecast city fixed for two weeks at a time. Forecast lab times will be applied to identifying and analysing methods, logistics and implementation towards actual forecasting, Will apply whatever needed data, models, computation, etc. The forecasting Lab journal/notebook/spreadsheet will concern methodology/analysis implemented and forecast data development; all data predicted will then be succeeded by identifying professional forecasts, to then record true revelation data from actual weather. Based on respected 3-set data students will try to explain any high disparities or high convergences, and possible explanations. Class exercises--> Due at the beginning of class one week after they are assigned. Often, you will have time to work on them in class, perhaps on the following class day. Sometimes, these assignments will require computer resources to complete. Quizzes--> Concerns being at least competent and vigilant with knowledge and skills with past topics. Will concern various topics thrown at you multiple times in throughout the total number of quizzes. Additional software--> Course may have introduction immersion with some technical meteorological software from “Goody Bag”; there are alternatives to software described in outline. Will reacquaint ourselves with the likes of METARs and the station model; Decoding METARs, NWS text data and GEMPAK. NOTE: there will 10 -11 Labs/forecasting pursuits sessions, each having a during of 2 1/2 hours, catering for mesoscale topics, technical skills, technology and forecasting. Course Outline --> Definition of Mesoscale Precipitation Type Freezing Rain Climatology Forecasting of Heavy Snow Assessing Conditions for an East Coast Cyclone Mesoscale Snow Bands: Conditional Symmetric Instability Mesoscale Snow Bands: Lake Effect Snow Mesoscale Circulations Forced by Diabatic Heating Internal Gravity Waves and Forecast Verification Mesoscale Circulations Forced by Terrain Terrain Blocking Ensemble Forecasting and QPF Assessing Instability – Skew-Ts Assessing Vertical Wind Shear – Hodographs Mesoscale Boundaries and Mesoanalysis Stormscale Variation – Storm Types Synoptic Patterns Favorable for Severe Weather Radar Interpretation for Severe Prediction SPC Overview The Urban Boundary Layer and Low-Level Jets Mesoscale Convective Systems Flash Flooding Prerequisites: Meteorological Analysis II Radar and Satellite Meteorology: Weather forecasting expertise is developed through the hard work of studying and analysing case after case of weather scenarios to find underlying patterns in meteorological variables. Since our world is big, remotely sensed imagery from satellites and radars is the primary lens through which we view Earth’s atmospheric phenomena. This course begins with study of the sun, earth and radiation. Weather satellite and radar imagery cannot be correctly interpreted without understanding the sun/earth geometrics and the behaviour of electromagnetic radiation in our atmosphere. After developing some understanding of how radiation is emitted, scattered, absorbed, transmitted, reflected, and refracted, the design and utility of various satellite sensors and radar apparatus will make sense. The main work of the course will be to develop a “forecasting toolbox” using satellite and radar imagery to analyse case studies designed to provide practice in recognizing visual patterns in weather phenomena like mid-latitude cyclones, snow/ice events, MCSs, tornado outbreaks, and tropical storm events. Typical Texts (in unison): Rinehart, R. Radar for Meteorologists An Introduction to Satellite Image Interpretation by Eric Conway and The Maryland Space Grant Consortium Weather Analysis and Forecasting: Applying Satellite Water Vapor Imagery and Potential Vorticity Analysis, by Patrick Santurette and Christo Georgiev NOTE: latter book contains multitudinous examples using “PV thinking” to monitor and analyse synoptic development. The authors also present a method using water vapor imagery to discover NWP model forecast error, crucial for the prognosis of severe weather events. Tools --> GOES. POES & NPOESS; may be substitutes for such three concerning data GARP, NMAP2, NTRANS (the GUIs for GEMPAK) and McIDAS. There may more constituents concerning interface, etc, etc. 8-minute Answers --> Occasionally during the first eight minutes of class, you will be presented with a thought question designed to test your understanding of the course material and to integrate new vocabulary and concepts into your thinking and writing. Homework--> Homework assignments will range from small problem sets to guided online activities. The weight of each homework assignment will vary according to its intensity. You should expect to have an assignment due at each class session. In this way you will not lag behind in the material. No late homework will be accepted. Case Studies --> Each case will be broken into three components: 1) details of the weather situation 2) the pre-event satellite imagery/NWP model analysis 3) the radar presentation. Your goal will be to solve a forecasting dilemma and justify your solution using satellite and radar imagery. The data for each case will be accessible through GARP, NMAP2, NTRANS (the GUIs for GEMPAK) and McIDAS. You will be expected to compose brief case study reports including imagery analysis and loops using the tools provided. Exams --> The course includes four equally weighted examinations. They will include problem solving, short answer and essay questions Image of the Day/Weather Briefing --> Students will take turns 1) choosing and explaining an “image of the day” for the course webpage, or 2) presenting a once-a-week weather briefing. The weather briefings will not start until the semester is underway and the basic material has been covered. Assessment --> 8 minute answers 50 points Homework 300 points Case Studies 360 points Exams 240 points Images/Briefings 50 points Lecture Outline --> Week 1 Class Introduction, EM Spectrum Sun-Earth Geometry & Orbits. Earth’s orbit: seasons, days, sunrise and twilight Week 2 Flux, Principles of Radiation. EM Propagation. Emission Absorption, Reflection & Transmission Week 3 Surface Radiation Budget. Earth-atmosphere Global Energy Balance Exam 1 Week 4 Radar Hardware. Refractivity. Curvature & Radar Week 5 Radar Equations – Point Targets. Distributed Targets. Doppler Velocity Measurement. Week 6 The Doppler Dilemma. Velocity Errors. Exam Week 7 GOES. POES & NPOESS Week 8 Example Case – Rainy Season Synoptic Storm PVA/NVA GARP/Mc IDAS Fun Week 9 Case #1 Assigned – Clouds, Precip & Lake Effect Snow. McIDAS. GARP & Radar Week 10 Case #2 Assigned – Thunderstorms. Satellite. Radar Week 11 Case #3 Assigned –East Coast Explosive Cyclogenesis. Satellite. Radar Week 12 Exam 3 Case #4 Assigned – Tornadoes Week 13 Case #5 Assigned – Wind & Fire. Satellite. Radar Week 14 Case # 6 Assigned – Tropical Storms. Satellite. Radar Week 15 Wrap-up Final exam Prerequisites: General Physics I, Meteorological Analysis II Meteorological Instruments I Understand the history, operation, and use of meteorological instruments that monitor the atmosphere, with emphasis on practical applications. Instructor will provide hands-on experience with instrumentation where possible. Modern meteorology includes a wide variety of in situ and remote sensing instruments that are designed to observe aspects of our atmospheric environment. During this course students will develop skills in meteorological instrumentation, electronics, experimental design and logistics, computer-aided data analysis, and presentation of results. This course will be much longer than 15 weeks because the course has an investigative and experimental environment that needs to be done as least competently with skills building to retain. The technology challenge --> In modern times there is no standard brand or look to weather stations because technology has become accessible with microcontrollers, modules, power sources and sensors. Firstly, students must have understanding of what it is they’re trying to accomplish with respect to the environment considered. Secondly, understanding the operational specifications and limits of components to be incorporated into systems. Then, the most difficult part may be getting your devices and systems functioning long term in environments that may become harsh. As well good suspension against gravitational potential energy, in-place suspension against the elements and so forth. Students may have access to weather stations that are “old school status quo systems”. If accessible, they will be compared to innovative system designs in terms of technology, power requirements, data collection and management, and durability in the elements. Concerning windspeed and moisture such two measures may require classical instrument tools to be integrated into weather stations. Material guides: Course materials will be provided for each lecture. Students should make multiple copies of manuals for devices. IoT guides can prove handy. The brands of the devices also have project exhibitions available at their sites. Texts: Meteorological measurement systems and meteorological instrumentation books may be outdated in terms of innovation and independence. Yet, there may be some discipline towards theory and exams. Exams may include lab topics as well. Project Materials for devices (apart from screws, knots, bolts, frames, rods, etc.): Microcontrollers Modules Proper size heat sinks Sensors (depending on use may need protection form certain environmental conditions) Zebra cases (for microcontrollers and possibly modules) USB ports and cords Miniature RF antennas SD cards Intermediate size dish radio telescopes Power chords (some may need to be quite long) Power chords meaningful to microcontrollers and modules (some may need to be quite long) Power sources Miniature insulated pole RF antennas Standard computers/laptops Major Projects --> Unique to course labs there will be 4 major projects 1. Single site weather station 2. Weathercloud weather station Wanted parameters: coordinates, elevation and speed/velocity For a microscale (or mesoscale) weather system will like to monitor its movement process, to compare with forecasts concerning time of environment influence, and also comparing duration over ambiance from satellite data. 3. Weather stations at multiple sites with data from all fed to one location for use 4. Weathercloud weather station made to (actively) interface with the following Ferret, NWS text data, METAR, GEMPACK Other tools of possible interest in “Goody Bag” may just as good or better with interface and function. As well, Google Maps may be needed or a GIS. In all honesty students may excel in developing projects by one way, but terrible at another. Some tools guides of possible interest --> << https://www.youtube.com/watch?v=lnp6jo2XOU8 >> Make. Weekend Project: Raspberry Pi Weather Station – YouTube Buzing, Arnold. (2015). Build Your Own Weather Station in a Snap with the Wolfram Cloud! Wolfram Blog. << https://blog.wolfram.com/2015/03/17/build-your-own-weather-station-in-a-snap-with-the-wolfram-cloud/ >> Weather Station PCBs << https://www.raspberrypi.org/forums/viewtopic.php?t=234368 >> Arduino Weathercloud Weather Station << https://www.instructables.com/id/Arduino-Weathercloud-Weather-Station/ >> NOTE: in fairness one isn’t restricted to Raspberry Pi and Arduino brands. Grading: Take-home Exams 20% Written Lab Assignments 40% Research Paper & Presentations of Major projects 40% Note: presentations of for major projects can include photos and components of vlogs. Lecture & Lab Outline (by week) --> I. Introduction/Lab Reports/Course expectations Why observations are important; the utility of practical experience; the importance of calibration, response time, and error estimation in observations. The structure of a scientific report. History of early meteorological instruments. Instrument performance. Lab 1: Introductory lab II. Temperature: Direct Measurement What is temperature? How is temperature measured? Calibration; time response; ventilation. Lab 2: Calibration of several different temperature sensors. III. Temperature: Indirect Measurement Introduction to radiation – radiance, black body, IR temperature sensors. Solar and Earth radiation measurements. Lab 3: Documenting IR radiation in the environment. IV. Pressure What is pressure? Barometer concepts and instruments. Importance of calibration. Lab 4: Calibration and comparison of pressure sensors, analysis of data. V. Humidity Water, changes of state, relative and absolute humidity measurement. Lab 5: Calibration and comparison of humidity sensors, analysis of data. VI. GPS in Atmospheric Monitoring Ground-based and spaced based approaches and resulting data sets. Lab 6: Statistics, calculation of variance (standard deviation), correlations, log normal dist. VII. Rainfall Rain gauges, rain rate, placement of rain gauges. Lab 7: Extreme value analysis and Rainstorm recurrence interval. VIII. Near Surface Wind Measurement Wind-field measurement; vector measurement; different types of anemometer and physical principles involved. Importance of time response; distance constant; sonic anemometry. Calibration and comparison of anemometers in the field, data logging, analysis of time series. Lab 8: Variation of wind with exposure and height. Wind data analysis – wind rose plots. IX. Renewable energy Wind and solar power. Mid-term Take-home Exam X. Radiosondes Radiosonde instrumentation, calibration, deployment, ascent rates. Lab 9: Sounding analysis – lapse rates, stability indices, wind shear XI. Wind Profilers, Radio Acoustic Sounding Systems (RASS), Sodars, lidars. Basic principles of remote sensing of winds and temperature aloft. Lab 10: Geometry of profiler data XII. Radar Remote Sensing of Precipitation and Wind Basic principles; instrumental set-up; sensitivity; wavelengths used; antenna types/sizes; radar indicators (RHI, PPI, CAPPI); approximate radar equation and what it tells us. Importance of phase (ice/liquid), particle size and shape. Lab 11: Doppler radar – practical analysis of radar imagery XIII - XIV. Designing a Field Experiment. Site selection and field set-up logistics, data retrieval and analysis. Lab 12: Field Experiment. XV. Aerosols and Fugitive Dust Final Take-Home Exam Major Projects Presentations Prerequisites: General Meteorology, Upper Level Standing Meteorological Instruments II Meteorological Instruments is not a “one-shot deal” to becoming professionals. Competency and professionalism after experience are always needed. Prerequisites: Meteorological Instruments I Physical Meteorology I: This course introduces the physical processes associated with atmospheric composition, basic radiation and energy concepts, the equation of state, the zeroth, first, and second law of thermodynamics, the thermodynamics of dry and moist atmospheres, thermodynamic diagrams, statics, and atmospheric stability. This is one of the major “transitioning” courses towards professional meteorological modelling. Typical Text: Petty, G. W. A First Course in Atmospheric Thermodynamics. Sundog Publishing Supplemental (Strongly Encouraged and Recommended): Atmospheric Thermodynamics, C. F. Boren & B. A. Albrecht, Oxford University Press Grading --> Quizzes (4-5) 20% Examinations (3) 50% Comprehensive Final Examination (1) 30% Course Outline --> I. Atmospheric Composition and Structure-- Pressure and density; Hydrostatic balance; Atmospheric density; Composition; Temperature; Zeroth law of thermodynamics; and Atmospheric temperature profiles. II. Thermodynamic Systems and Variables-- Air parcels; System variables; State and process variables; Conserved variables; and Extensive and intensive variables. III. Physical Properties of Air-- Equation of state; Experimental properties of gases; The gas laws; Dry air gas constant; Equation of state for moist air; Mixing ratio and specific humidity; Virtual temperature; and Buoyancy calculations. IV. Atmospheric Pressure-- Hydrostatic balance; Hydrostatic equation; Geopotential height; Hypsometric equation; Pressure profiles of idealized atmospheres; U.S. standard atmosphere and international standard atmosphere. V. The First Law of Thermodynamics-- The first law of thermodynamics; Internal energy; Heat capacity; Poisson’s equations; Potential temperature; Dry adiabats; The dry adiabatic lapse rate; Heat engines; The carnot cycle; Reversible and irreversible processes; Enthalpy; and Diabatic processes. VI. The Second Law and Its Consequences-- Entropy; and Thermodynamic equilibrium. VII. Moist Processes-- Water vapor saturation; saturation vapor pressure; relative humidity; Dewpoint; Latent heat of condensation / vaporization; The Clausius-Clapeyron equation; Saturation mixing ratio; Moisture variables on the skew-T diagram; Lifting condensation level (LCL); Moist adiabatic lapse rate; Equivalent potential temperature; and Wet-bulb temperature. VIII. Atmospheric Stability-- The parcel method; Stable and unstable systems; Local (static) atmospheric stability; dry static stability; Brunt-Vaisala frequency; Potential instability; Parcel stability and atmospheric convection; and Stability indices Prerequisites: General Meteorology, General Physics I, Calculus III. Assumption is that Fluid Mechanics is taken concurrently or prior concerning Physical Meteorology II following. Physical Meteorology II (Cloud Physics, Atmospheric Electricity & Optics) This course provides fundamentals and principles for understanding of the physical states and processes of clouds and precipitation, as well as atmospheric electricity and optics. Typical text --> Rogers and Yau: A Short Course in Cloud Physics Reference Texts --> Wallace and Hobbs, Atmospheric Science Fleagle and Businger, An Introduction to Atmospheric Physics Projects --> Miyazaki, R., Dobashi, Y., & Nishita, T. (2002). Simulation of Cumuliform Clouds Based on Computational Fluid Dynamics. Eurographics Hadrich, T. et al (2020). Stormscapes: Simulating Cloud Dynamics in the Now. ACM Transactions on Graphics, 39(6), Article No. 175, pages 1 – 16 Xianing, X., et al (2013) Numerical Simulation of Clouds and Precipitation Depending on Different Relationships Between Aerosol and Cloud Droplet Spectral Dispersion, Tellus B: Chemical and Physical Meteorology, 65:1 Note: may be asked to simulate other more technical cloud types Grading --> Homework problems Quizzes 2 Exams Projects Final examination COURSE TOPICS --> Cloud physics: Review of thermodynamics Aerosols and nucleation Condensation growth Collision and coalescence Precipitation processes Observation studies Atmospheric electricity: Electrostatics Electromagnetic wave Thunderstorm charging Lightening Atmospheric optics: Reflection and refraction Optical phenomena Prerequisites: Numerical Analysis, Fluid Mechanics, Physical Meteorology I Fundamentals of Atmosphere and Ocean Dynamics: The lectures will focus on the physical mechanisms responsible for the global energy balance and large-scale atmospheric and oceanic circulation. We will introduce fundamental concepts of fluid dynamics and we will apply these to the vertical and horizontal motions in the atmosphere and ocean. Fundamental concepts covered include: hydrostatic law, buoyancy and convection, basic equations of fluid motions, flow on a rotating planet, Hadley, Ferrel and Polar cells in the atmosphere, Walker circulation, thermohaline circulation, modes of climate variability (El-Nino, North Atlantic Oscillation, Southern Annular Mode), wind driven ocean circulation, turbulent flow. Computational and simulation assignments given to students follows only guidance setup by instructor. MATHEMATICA concerns expressing equations for given or derived models and simulations; lab sessions in which students will learn how to write and run simple MATHEMATICA programs to study the climate system. Modelling and data analysis labs: 35%. Midterm exam: 25%. Homeworks: 25%. Final oral presentation + class participation: 15% Example literature: "Atmosphere, Ocean and Climate Dynamics: An Introductory Text" by John Marshall and Alan Plumb, Academic Press 2008. I. Atmospheric Dynamics and the Equations of Fluid Motion --Introduction: The greenhouse effect. Global Energy balance. A basic Math/physics review. --The Global Energy Budget --The Vertical Structure of the Atmosphere and Ocean --Convection in the atmosphere and ocean --Horizontal Motion in the Atmosphere. Coriolis Force and Large-scale Dynamics of the Atmosphere --Continuity and Thermodynamic Equations --Equations of Fluid Motion: Momentum Equations. --Scaling the Equations of Motion: Dimensional Analysis --MATHEMATICA Lab 1. Your first simple climate models (energy balance box models) --MATHEMATICA Lab 2: Your second simple climate model. Ice-albedo feedback and multiple steady states. Energy balance box model. --MATHEMATICA Lab 3: Paleoclimate (extra credit) II. Ocean Dynamics & Climate --Intro to the Oceans: T, S, Density and Thermohaline Circulation. --Introduction to the Carbon Cycle. --Modes of Climate Variability, Ocean-Atmosphere Interaction, Annular Modes (El Nino, North Atlantic Oscillation, Southern Annular Mode) --Tracers of Ocean Circulation: biological tracers, CFCs, radiocarbon, Helium, Tritium --MATHEMATICA & OpenFOAM Lab 4: How Diffusion Drives the Temperature, Salinity and Radiocarbon Vertical Distributions in the Ocean (1D Advection-Diffusion Models with no time dependence). --MATHEMATICA & OpenFOAM Lab 5 (1D advection-diffusion equation with time dependence) --Wind driven ocean circulation: Ekman Flow and Pumping. Why are there gyres in the ocean? --Wind driven ocean circulation: Sverdrup, Stommel and Western Boundary Currents: Why is there a Gulf Stream? --MATHEMATICA & OpenFOAM Lab 6: The Stommel model: simulating ocean gyres (2D advection-diffusion) --Vorticity; Conservation of potential vorticity --Geostrophy and Thermal Wind in the Ocean. Sea Surface hHeight. --Eddies and Baroclinic Instabilities in the Ocean and Atmosphere --Summary of class. --Student presentations and final homework. Prerequisites: Calculus III, General Physics I, and ODE/PDE

Aerosol Physics & Chemistry: The physical and chemical properties of aerosols impact the world around us, explaining many natural phenomena (e.g., the colour of the sky, presence of clouds, and blue haze commonly observed in the Whatever Mountains), as well as impacting global climate change, air quality, and human health. In order to understand how aerosols impact our environment (both indoors and outdoors), this course will consist of two major sections; aerosol physics and aerosol chemistry. First, in the aerosol physics section we will discuss the physical principles underlying the behaviour of particles suspended in air, which includes rectilinear and curvilinear motion of particles in a force field, diffusion, evaporation, condensation, coagulation and electrical properties. The principles learned from the aerosol physics section of the course will allow students to understand how to size and collect/remove aerosols. Owing to the fact that the second section of this course is devoted to understanding the chemistry that leads to atmospheric aerosol formation, principles gained from the first section will be important to understanding sources and fates of atmospheric aerosols. Primary focus in this section will be given on the chemistry that leads to the formation, evolution, and aging of organic aerosols, especially since organic compounds contribute a large fraction (i.e., 20-90%) towards the total mass of atmospheric fine (i.e., 2.5 µm and smaller) aerosol. High concentrations of atmospheric fine aerosol are known to have adverse human health effects and play a role in the Earth’s climate system. The impact of atmospheric fine aerosols on climate and health cannot be fully assessed without understanding their detailed chemical processes. In addition, students will learn how to chemically characterize aerosols using both off-line and on-line analytical techniques. Although the aerosol physics and chemistry examined in this course is primarily related to atmospheric aerosols, which is critical to those students pursuing careers in air pollution control, air quality and atmospheric chemistry, the physical and chemical principles learned during this course will also be invaluable to those students pursuing careers in industrial hygiene, nanotechnology, atmospheric science (or meteorology), chemical manufacturing, pharmaceuticals (e.g., drug delivery), public health, epidemiology, toxicology and material science. Grading: Problem Sets Quizzes Labs 2 Midterm Exam Final Exam Typical Texts (in unison) --> Hinds, W. C. and Zhu, Y. (2022). Aerosol Technology: Properties, Behaviour, and Measurement of Airborne Particles, Wiley Seinfeld, J. H. and Pandis, S. (2006). Atmospheric Chemistry and Physics: From Air pollution to Climate Change, Wiley Assisting Texts --> Baron, P.A. and K. Willeke, Aerosol Measurement: Principles, Techniques, and Applications, Wiley Interscience, 2005. Vincent, J. H. (2007). Aerosol Sampling: Science, Standards, Instrumentation and Applications, Wiley Interscience, 2007. Pramod Kulkarni, Paul A. Baron, and Klaus Willeke. Aerosol Measurement: Principles, Techniques, and Applications, 3rd Edition, 2011, Wiley. Data Sources --> NASA ASDC AERONET (AErosol RObotic NETwork) Meteorological data sources Labs --> Note: many will be bundled -Spreadsheet or CAS (Mathematica or R) to compute size distributions and integral quantities; fitting to a lognormal function. Why lognormal? -Aerosol measurement Aerosol Generation and Sizing Measurement Flow Measurement Soo, S. L., Stukel, J. J. and Martin Hughs, J. (1969). Measurement of Mass Flow and Density of Aerosols in Transport. Environ. Sci. Technol. 3(4), pages 386–393 Bemer, D. et al (2002). Measuring the Emission Rate of an Aerosol Source Placed in a Ventilated Room Using a Tracer Gas: Influence of Particle Wall Deposition, The Annals of Occupational Hygiene, Volume 46, Issue 3, Pages 347–354 Lizal, F. et al (2018). Experimental Methods for Flow and Aerosol Measurements in Human Airways and Their Replicas. European Journal of Pharmaceutcal Sciences, Volume 113, pages 95 - 131 -Depositional losses in sample lines -Impactors -Coagulation ageing of particles -Condensation particle counter/counting statistics -The Differential Mobility Analyzer -Hygroscopicity measurements, salts (or whatever) -Hygroscopicity measurements, organics -Cloud condensation nuclei measurements PART A For analysis and development: Uin, J. (2016). Cloud Condensation Nuclei Counter (CCN) Instrument Handbook. DOE/SC-ARM-TR-168 PART B For analysis. Identify methods and porocedures. Then replicate. As well, interest in other ambiances. Schmale, J., Henning, S., Henzing, B. et al. (2017) Collocated Observations of Cloud Condensation Nuclei, Particle Size Distributions, and Chemical Composition. Sci Data 4, 170003 Gen, C. (2020). Estimation of Cloud Condensation Nuclei Number Concentrations and Comparison to in situ and Lidar Observations during the HOPE Experiments, Atmos. Chem. Phys., 20, 8787–8806 -Particle optical sizing and counting techniques -Aerosol optical depth (AERONET data) -Investigating and replicating journal articles Hopefully resources are accessible to implement interests (else, pursue substitutes in development) Briant, R. et al (2017). Aerosol–Radiation Interaction Modelling Using Online Coupling between the WRF 3.7.1 Meteorological Model and the CHIMERE 2016 Chemistry-Transport Model, through the OASIS3-MCT Coupler, Geosci. Model Dev., 10, 927–944 Slater, J. et al (2020). Using a Coupled Large-Eddy Simulation–Aerosol Radiation Model to Investigate Urban Haze: Sensitivity to Aerosol Loading and Meteorological Conditions. Atmos. Chem. Phys., 20, 11893–11906 Carson-Marquis, B. N. et al (2021). Improving WRF-Chem Meteorological Analyses and Forecasts over Aerosol-Polluted Regions by Incorporating NAAPS Aerosol Analyses, Journal of Applied Meteorology and Climatology, 60(6), pages 839-855. Silveira, C. et al. (2021). The Role of the Atmospheric Aerosol in Weather Forecasts for the Iberian Peninsula: Investigating the Direct Effects Using the WRF-Chem Model. Atmosphere, 12, 288 COURSE OUTLINE --> NOTE: course may incorporate additional weeks concerning integrity, proper delivery and sustainability. PART 1 (AEROSOL PHYSICS) Week 1 Course introduction, objectives, policies, and schedule Particle size distributions: number, surface area, volume and mass Week 2 Particle size distributions: lognormal distributions and ambient size distributions Properties of gases Week 3 Uniform particle motion: Newton’s resistance law and Stoke’s law Uniform particle motion: slip correction and terminal settling velocity Uniform particle motion: terminal settling velocity @ high Re number and instruments that rely on settling Week 4 Shape correction to terminal settling, instruments that rely on settling, particle acceleration, and stopping distance Curvilinear motion and Stokes number Week 5 Respiratory Deposition and Health Effects Electric Forces, motion in an electric field Week 6 Particle charging and charge limits Brownian motion and diffusion Week 7 Kelvin effect, droplet equilibrium, condensation, nucleation, and evaporation Coagulation PART 2 (AEROSOL CHEMISTRY) -- Week 8 Introduction to atmospheric aerosol chemistry – atmospheric structure, sources, compositions Atmospheric organic aerosol – EC vs. OC Week 9 Review of chemical classes (including organics) important to aerosol formation Secondary Organic Aerosol (SOA): General mechanism and SOA Yields SOA: General gas-phase oxidation chemistry mechanisms – why they matter? Week 10 Modelling of atmospheric organic aerosols SOA: Gas-phase oxidation chemistry of isoprene and other hydrocarbon compounds SOA: Role of heterogeneous chemistry in isoprene SOA formation; other hydrocarbons treated Week 11 Chemical characterization of SOA Prerequisites: General Chemistry I & II, General Physics I, Ordinary Differential Equations, Calculus III, Mathematical Statistics Air Pollution Chemistry & Physics: Air pollution has significant effects on human health and the environment, through interrelated problems of ozone and particulate matter air pollution, acid rain, visibility degradation, mercury, stratospheric ozone depletion, and climate change. Significant strides have been made in the past few decades to improve our understanding of the sources, chemical transformation, transport, deposition, and impacts of different pollutants. We now understand that many air pollutants are linked together through complex chemical interdependencies. This course isn’t for learning chemistry but applying knowledge of chemistry and applied physics from prerequisites. Students will be expected to show mastery of relevant concepts drawn mainly from the Earth sciences, chemistry, physics, and engineering. By the end of this course, students will be able to: - Explain current air pollution research in the context of the history of air pollution science. - Explain the relationships between emissions of different air pollutants from different sources, their atmospheric concentrations, and the impacts that they ultimately cause. - Explain the factors that influence the transport of pollutants around the world. - Explain the chemical processes that govern the formation and destruction or removal of air pollutants, principally ozone and particulate matter. - Understand basic laboratory and field techniques in the measurement of air pollutants. - Participate in smog chamber analyses of chemical transformations of pollutants. - Apply quantitative analyses related to air pollution through homework problems and on tests. - Read and understand recent scientific findings from journal articles. Texts relevant to course --> Seinfeld, J. H. and Pandis, S. N. (2006). Atmospheric Chemistry and Physics: From Air Pollution to Climate Change, Wiley Jacob. D. J. (1999). Introduction to Atmospheric Chemistry. Princeton University Press Finlayson-Pitts, B. J. and Pitts, J. N., (1999). Chemistry of the Upper and Lower Atmosphere, Academic Press Jacobson, M. Z. (2005). Fundamentals of Atmospheric Modeling, Cambridge University Press Data Sources --> NASA ASDC Meteorological Data Sources Software --> EPA’s SCRAM < https://www.epa.gov/scram > Preferred and Recommended Models Alternative Models Note: with supporting literature investigated for prior two Enviroware TOXFLAM May also incorporate software encountered in Organic Chemistry I Research --> Students will be assigned various molecules/polymers both natural and from list of banned or highly regulated (EU, CAN). Will research them based on professional chemistry resources, environmental protection and agricultural sources (chemical characteristics). Journal article referencing included. Software will be applied to provide detailed analysis for characteristic structure groups, behaviour with atmospheric conditions, interactions with other polymers/molecules for relevant conditions, etc. etc. Grading: Homework assignments 15% In-class quizzes 15% Labs 25% 3 Exams 45% Course Outline: -Introduction to class, Historical view of air pollution problems -Atmospheric structure and composition, pressure, Ideal Gas Law, units of atmospheric composition -Atmospheric trace constituents: sulfur-containing, nitrogen-containing, and halogen-containing compounds, ozone -Atmospheric trace constituents: carbon-containing compounds, water vapor. -Simple models, atmospheric lifetime -Transport of pollutants, global meteorology -Meteorology: Atmospheric stability -Chemical kinetics, atmospheric radiation and photochemistry -Stratospheric ozone chemistry and the Ozone Hole -Air pollution measurements -Stratospheric ozone chemistry and the Ozone Hole -Tropospheric ozone chemistry -Tropospheric ozone chemistry, NOx and Radical cycles -Tropospheric ozone chemistry, role of CO and VOCs -Tropospheric ozone, reactions of individual VOCs -Urban ozone sensitivity and isopleths. Global ozone -The continuity equation and atmospheric modeling, Use of a chemical solver -Overview of Particulate Matter -Overview of PM -Measurements of PM -Inorganic PM -Inorganic PM -Inorganic PM, acid rain -Visibility, Air pollution health effects -Air pollution regulation -Air pollution health effects LAB Session(s): Modelling and Simulation --> Each lab will take on multiple sessions A. First part concerns employing particular software from EPA’s SCRAM. To first investigate the software descriptions and supporting documentation before models programming/implementation towards real world interests. B. Enviroware TOXFLAM Note: one isn’t sure of the full capabilities of TOXFLAM model applications concerning license, however, there is a simplified online version that may be enough. The following articles below to serve as modelling guidance towards interest with simulation. Can one have cross evaluation between part A and TOXFLAM? Related literature Bianconi R. and M. Tamponi (1993). A Mathematical Model of Diffusion from a Steady Source of Short Duration in a Finite Mixing Layer. Atmospheric Environment, Volume 27A, 781 – 792 Andretta M. et al (1993) The MRBT Model: An Analytical Dispersion Model in a Finite Mixing Layer. Sensitivity Analysis and Validation Against Tracer Measurements. Atmospheric Environment, Volume 27A, 11, 1665 – 1672 Bellasio, R. and Bianconi, R. (2005). On-Line Simulation System for Industrial Accidents. Environmental Modelling and Software. Volume 20, Issue 3, pages 329 – 342 Prerequisites: Organic Chemistry I, General Physics I, Ordinary Differential Equations, Calculus III Tropical Meteorology: The successful student will gain a strong understanding of tropical meteorology. The course material will provide a strong foundation from which students can build to make contributions to the peer-reviewed scientific literature. The course materials will be drawn from journal articles and lecture notes. This course will approach tropical meteorology from a decidedly large-scale perspective, with less emphasis on mesoscale aspects of tropical meteorology, although these will by necessity be brought in at points. However, one critical goal is to develop cyclone/typhoon/cyclone formation and structure in a mathematical modelling environment; such can’t be left idle so simulation development will also be pursued. As far as participation in discussion, some constituents may provide degenerate or toxic “contributions”; a populist and horde/scourge environment aren’t science. One doesn’t want to rotten out foundations and skills developed in prerequisites and other courses. For applied journal articles it’s important to have coherency, model structure comprehension and summative analysis. You are being allowed the opportunity to develop in practical tools and skills, rather than the overboard con artist “house built on sinking sand” terror tactics commonly applied. Skills Expected (done at appropriate times) --> -Radiative -Convective Model Development Reed, K. A. (2021). Using Radiative Convective Equilibrium to Explore Clouds and Climate in the Community Atmosphere Model. Journal of Advances in Modelling Earth Systems, 13 e2021MS002539 -Plot Soundings on Skew T Diagrams and make Buoyancy Plots Common Knowledge Quizzes --> The following to be used for quiz development Introduction to Tropical Meteorology, 2nd Edition, The COMET Program, The University Corporation for Atmospheric Research (UCAR) Based on knowledge and skills from prerequisites students will be asked to complete various modelling tasks; must be able to recognise and apply the required operations Collective Class Activities --> Note: will adjust to ambiance of interest with consideration of data being augmented with recent years. 1. Cyclone Structure Note: interested in matching models to past mature tropical cyclones based on data. Mathematica functions such as Manipulate, Dynamic and DynamicModule can serve well. https://www.atmos.millersville.edu/~adecaria/ESCI344/esci344_lesson10_TC_structure.pdf > Chanh Kieu, Quan Wang & Shouhong Wang (2018) On the structure and stability of the Hurricane Eyewall, Tellus A: Dynamic Meteorology and Oceanography, 70:1, 1-14 2. Anthes, R. A. (1974). The Dynamics and Energetics of Mature Tropical Cyclone. Reviews of Geophysics and Space Physics. Vol. 12, No. 3, pages 495 – 522 Note: interested in matching models to past mature tropical cyclones based on data. Mathematica functions such as Manipulate, Dynamic and DynamicModule can serve well. 3. Parasuraman, K. (2018). Hurricane Florence — Building a Simple Storm Track Prediction Model. Towards Data Science 4. Jing, R. and Lin, N. (2020). An Environment-Dependent Probabilistic Tropical Cyclone Model. Journal of Advances in Modelling Earth Systems, 12(3) e2019MS001975 5. Vickery, P. J. et al (2009). Hurricane Hazard Modeling: The Past, Present and Future. Journal of Wind Engineering and Industrial Aerodynamics, 97(7-8), pages 392-405 6. Hatzikyriakou, A. and Lin, N. (2017). Simulating Storm Surge Waves for Structural Vulnerability Estimation and Flood Hazard Mapping. Nat Hazards (2017) 89:939–962 7. Taramelli, A. et al (2008). Estimating Hurricane Hazards using a GIS System. Nat. Hazards Earth Syst. Sci., 8, 839–854 Group Term Projects --> https://ocw.mit.edu/courses/12-811-tropical-meteorology-spring-2011/pages/projects/ MIT Tropical Meteorology Study Materials (CRUCIAL with lectures) --> https://ocw.mit.edu/courses/earth-atmospheric-and-planetary-sciences/12-811-tropical-meteorology-spring-2011/study-materials/ Further Possible Articles of Interest --> Wheeler, M. and G. N. Kiladis, 1999: Convectively Coupled Equatorial Waves: Analysis of Clouds and Temperature in the Wavenumber–Frequency Domain, J. Atmos. Sci., 56, 374–399. [look at the figures on the AMS website. The PDF reproduction is poor]. Schumacher, C., R. A. Houze, I. Kraucunas, (2004). The Tropical Dynamical Response to Latent Heating Estimates Derived from the TRMM Precipitation Radar. J. Atmos. Sci., 61, 1341–1358. Chris D. Thorncroft, Nicholas M. J. Hall, and George N. Kiladis, (2008). Three-Dimensional Structure and Dynamics of African Easterly Waves. Part III: Genesis Atmos. Sci., 65, 3596–3607. Holloway, C. E., and J. D. Neelin (2009). Moisture Vertical Structure, Column Water Vapor, and Tropical Deep Convection. J. Atmos. Sci., 66, 1665–1683 Johnson, N. C., and S.-P. Xie, (2010). Changes in the Sea Surface Temperature Threshold for Tropical Convection. Nature Geoscience, 3, pages 842–845 Wolding, B. O, E. D. Maloney, and M. Branson, (2016). Vertically Resolved Weak Temperature Gradient Analysis of the Madden-Julian Oscillation in SP-CESM. J. Adv. Modeling. Earth. Sys., 8 Henderson, S. A., E. D. Maloney, and E. A. Barnes, (2016). The Influence of the Madden-Julian Oscillation on Northern Hemisphere Winter Blocking. J. Climate, 29, 4597– 4616. Wolding, B. O., E. D. Maloney. S. A. Henderson, and M. Branson, (2017), Climate Change and the Madden-Julian Oscillation: A Vertically Resolved Weak Temperature Gradient Analysis. J. Adv. Modeling Earth Sys., in press Final Exam --> Based on Common Knowledge Quizzes Course assessment weights --> Skills Expected 15% Common Knowledge Quizzes 15% Collective Class Activities 35% Group Term Projects and Presentations 20% Final Exam 15% General Course Modules --> -Radiative-Convective Equilibrium -The Zonally-Averaged Circulation -Asymmetric Steady Circulations -Interannual Fluctuations of the Walker Circulation – ENSO -Intraseasonal Oscillations -Higher Frequency Disturbances -Tropical Cyclones -Precipitation Frequencies, Cyclones Frequencies and Global Warming. Any Correlation? Course Lectures --> NOTE: the “explicit” weekly lectures MUST relate well with the listed General Course Modules prior Week 1: Overview: Mean distribution of meteorological variables, the seasonal cycle of the tropical atmosphere, phenomenology of the tropics Week 2: Tropical budgets: heat, moisture, moist static energy, kinetic/potential energy Week 3: Weak tropical temperature gradients Week 4: Modes of tropical convective heating and associated vertical velocity Week 5: Modelling tropical precipitation with the moist static energy (MSE) budget Week 6: Applications of the MSE budget to the tropical atmosphere Week 7: Moisture and tropical convection: Observations and implications for parameterization. Week 8: Equatorial wave dynamics Week 9: The Madden-Julian oscillation (MJO): observations and modelling Week 10: MJO theory and diagnosis Week 11: Moisture modes: Balanced disturbances and the weak temperature gradient Week 12: MJO teleconnections Week 13: Easterly waves: observations and theory Week 14: Tropical variability and climate change Week 15 -18: serving as possible insurance for obligations towards integrity, quality, fluidity and sustainability. Prerequisites: Numerical Analysis; Data Programming with Mathematica; Fluid Mechanics; Physical Meteorology I; Partial Differential Equations, Mathematical Statistics Synoptic Dynamic Meteorology: This course provides an introduction to contemporary synoptic-dynamic meteorology and its applications. The course is not restricted to the synoptic scale, but instead synthesizes observational and numerical analysis to understand weather across all scales, with an emphasis on the midlatitudes. Major course topics include basic dynamics (e.g., divergence, deformation, vorticity, and potential vorticity), upper-level waves, quasigeostrophic (QG) theory, diagnosis of vertical motion and height tendency, potential vorticity thinking, extratropical cyclones, and additional topics if time allows. At the end of this course, students should be able to apply and synthesize dynamics, observational analysis, and numerical analysis to diagnose and understand the past, present, and future weather. Regardless of whatever is encountered in Meteorological Analysis I & II, analytical strength is very important, while the science is a highly technical field. A comprehensive approach is needed. Course will have more mathematical emphasis than Meteorological Analysis I-III. Typical Texts: Midlatitude Synoptic Meteorology, Gary Lackmann. An Introduction to Dynamic Meteorology, James R. Holton & Gregory J. Hakim Tools for Labs --> SHARPpy UCAR UNIDATA IDV Unidata AWIPS Tools and software from Meteorological Analysis III course Tools and software from Radar and Satellite Meteorology course Mathematica or R Much meteorological data repositories Grading --> Labs (50%) Two mid-term exams (25% each) Final exam (25%) Grades on assignments will be reduced 15 points (out of 100) per day past the due date. Labs --> For some labs one needs to situate for ambiance of concern with tools, data sources and so forth. Lab ideas components: Advance recital of particular labs from Meteorological Analysis III Will be compact with multiple labs integrated Recital of particular labs from Radar and Satellite Meteorology Will be compact with multiple labs integrated Current course labs http://www.inscc.utah.edu/~steenburgh/classes/5110/lab1.html http://www.inscc.utah.edu/~steenburgh/classes/5110/lab2.html http://www.inscc.utah.edu/~steenburgh/classes/5110/lab3.html http://www.inscc.utah.edu/~steenburgh/classes/5110/lab4.html http://www.inscc.utah.edu/~steenburgh/classes/5110/lab5.html http://www.inscc.utah.edu/~steenburgh/classes/5110/lab6.html http://www.inscc.utah.edu/~steenburgh/classes/5110/lab7.html http://www.inscc.utah.edu/~steenburgh/classes/5110/lab8.html Course Overview --> Fundamental Math Concepts Essential meteorological concepts Skew – T review Divergence and Deformation Vertical Motion Circulation and Vorticity The Vorticity Equation Scale Analysis of the Vorticity Equation Introduction to Upper-Level Waves Dynamics of Upper-Level (Rossby) Waves Potential Vorticity Upper-Level Flow Climatology and Blocking Quasigeostrophic (QG) Theory and Applications Approximations and Equations Omega equation Q-Vectors Height Tendency Equation Behaviour of Upper-Level Troughs and Ridges Potential Vorticity Thinking and Tropopause Extratropoical Cyclones Climatology Cyclogenesis Norwegian Cyclone Model and Extensions Shapiro-Keyser Model Occlusion Process Conveyor Belts, Poisonous tails, and Sting Jets Prerequisites: Meteorological Analysis III, Radar and Satellite Meteorology, ODE, Data programming with Mathematica, Fluid Mechanics, Physical Meteorology I Mesoscale Meteorology: This course will cover the theory and application of mesoscale meteorology, and how mesoscale phenomena relate to features and processes on larger and smaller scales. The course will concern lectures, weather discussions, and time for working on class assignments and projects. Upon completion of this course, students will be able to: Describe the basic theories describing mesoscale weather phenomena Understand the techniques used in mesoanalysis and mesoscale numerical modelling Apply the theories to observed mesoscale phenomena through analysis of recent and historical weather events The last 15-20 minutes of the first class each week will be devoted to a class discussion of current or recent mesoscale weather, focusing on physical/dynamical processes. Some typical problem sets will be entertained in lectures There will be 4-6 lab exercises over the course of the semester. These will involve applying the concepts discussed in class, and will often involve analysing interesting recent mesoscale weather events. One or more will also involve running and processing output from a numerical mode Syllabus; Introduction; Definitions of mesoscale Typical Texts (in unison) --> Paul M. Markowski and Yvette P. Richardson, Mesoscale Meteorology in Midlatitudes, Wiley-Blackwell Robert J. Trapp, Mesoscale-Convective Processes in the Atmosphere, Cambridge University Press Mesoscale Meteorology and Forecasting, P. Ray Tools for Labs --> SHARPpy Unidata AWIPS Tools and software from Meteorological Analysis III course Tools and software from Radar and Satellite Meteorology course Much meteorological data repositories Assessment --> Lab Assignments 35% 3 Exams 40% Labs --> A. Chosen lab recitals from Synoptic Dynamic Meteorology Administrated in a manner to serve as strong precursors to current course labs in (B) with practicality, fluidity and compatibility. B. Current course labs. Labs to be pursued Radar Analysis Sounding and Stability Analysis Boundary Layer Evolution Identify the different layers within the boundary layer during day and night time hours Examine the mixed layer evolution Boundary Layer Convergence Zones, Boundary Layer Convection, and CI The purpose of this lab is to gain experience looking at and analyzing clear-air radar data that resolves a variety of boundary layer convergence zones and the convection they initiate. You will examine how these boundaries interact with each other to initiate convection and the characteristics of the boundaries Wind Shear Analysis – Hodographs Frontal Analysis and Frontogenesis Cell Dynamics and Forecasting Single cells Multi-cell clusters Multi-cell lines Supercells Organized Mesoscale Convective Phenomena Simulating convective modes Synoptic conditions favourable for severe storms Use of Radar for severe weather forecasting and warning Flash Floods, persistent convective events Lecture Outline --> Week 1 Syllabus; Introduction; Definitions of mesoscale Week 2 Ambiance climatology; mesoanalysis techniques, synoptic meteorology review Week 3 Potential vorticity; Fronts and frontogenesis Week 4 Low-level jets; instabilities Week 5 Instabilities, continued Orographic flows Week 6 Orographic flows, continued Week 7 Orographic flows, continued Convective processes (introduction) Week 8 – 10 Convective processes (continued) Week 11 – 13 Mesoscale convective systems Week 14 Flash floods; microbursts; derechoes Week 15 Wrapping up Week 16 Final Project Presentations Prerequisites: Meteorological Analysis III, Radar and Satellite Meteorology, Synoptic Dynamic Meteorology Numerical Weather Forecasting: This course will cover the scientific basis for numerical weather prediction models, and will examine how those models are applied for use in research and forecasting. This will include an examination of data assimilation methods, parameterization, ensemble forecasting, and forecast evaluation. Mathematics is obviously useful, however, toxicity and market failure stems from the entities brought in (whether useful, or permanent incursions-parasitism-viral) and the stakeholders. What are you trying to accomplish? Where do you want to go? The course is scheduled for three hours per week, and will include a combination of lectures, hands-on exercises with numerical models, and student-led research projects. Upon completion of this course, students will be able to: Describe the basic theories underpinning numerical weather prediction Design and run experiments using a state-of-the-art numerical weather prediction model Discuss the strengths and weaknesses of different subgrid parameterizations and modelling approaches Apply the basic ideas of data assimilation, probabilistic prediction, and model evaluation to research and forecasting problems Typical Textbook --> Thomas T. Warner, Numerical Weather and Climate Prediction, Cambridge University Press Supplemental --> David J. Stensrud, Parameterization Schemes: Keys to Understanding Numerical Weather Prediction Models, Cambridge University Press Eugenia Kalnay, Atmospheric Modelling, Data Assimilation, and Predictability, Cambridge University Press Fraley, C. et al. (2011). Probabilistic Weather Forecasting in R. The R Journal Vol. 3/1 Field Resource Literature --> Outline of the Operational Numerical Weather Prediction at the Japan Meteorological Agency, March 2019, Japan Meteorological Society: https://www.jma.go.jp/jma/jma-eng/jma-center/nwp/outline2019-nwp/index.htm World Meteorological Organisation Ensemble Literature --> Guidelines on Ensemble Prediction Systems and Forecasting. World Meteorological Organisation, WMO-No. 1091, 2012 Edition Guidelines on Ensemble Prediction System Postprocessing. World meteorological Organisation. WMO-No. 1254, 2021 Edition Ensemble Journal Articles --> Toth et al, The Use of Ensembles to Identify Forecasts with Small and Large Uncertainty, American Meteorological Society, 2001, 463 Magnusson et al., Initial State Perturbations in Ensemble Forecasting, Nonlin. Processes Geophys., 15, 751–759, 2008 Zhang, H., Pu, Z., Beating the Uncertainties: Ensemble Forecasting and Ensemble-Based Data in Modern Numerical Weather Prediction, Advances in Meteorology Volume 2010, Article ID 432160, 10 pages Tools --> Weather Models: WRF-ARW, RAMS, MM5, etc., etc., etc., etc. R Packages: ensembleR, ensembleML, ensembleBMA, ensembleMOS, ProbForecastGOP CaretEnsemble CSTools SpecsVerification, scoringRule R Ensemble Post Processing literature Messner, J. W. (2018). Chapter 11, Ensemble Postprocessing With R. In: Vannitsem, S., Wilks, D. and Messner, W. J. (2018). Statistical Postprocessing of Ensemble Forecasts. Elsevier. Numerical Models --> 1. One conventional numerical model that can be used for class activities, homework/lab exercises, and for the final project, is the Advanced Research Weather Research and Forecasting model (WRF-ARW; wrf-model.org). For such given site one must thoroughly search it to take advantage of its resources. Hopefully it will be one valuable experience to learn. Some basic working installations of WRF-ARW will be provided for computer systems, and for your own machine(s) as well. 2. In professional meteorological practice there is no confinement to one prediction model. Rather, multiple numerical models are compared to acquire consistency for effects in environments considered. Expected, students will apply at least 3 other numerical models towards their research (e.g., RAMS, MM5, etc. etc., etc.) for comparison and contrast with WRF. For final projects you are to use different established numerical models. 3. You will also be expected to apply ensemble models alongside models types described in (1) and (2). Lab Goals --> 1. Relevant and practical forms of deterministic equations applying to models. Surveying forms of equations and general solutions. Applying numerical tools from prerequisites. 2. Will have a constructive and sustainable process with multiple weather prediction models; in a matter that’s not overwhelming nor to rot things out when having to deal with multiple models competently. 3. Practical, fluid and tangible logistics of the structure of Ensemble models. How components and things in models work. Test runs follow. 4. Forecasts evaluations (both deterministic and ensemble) 5. There will be 4-5 major lab assignments expanded to 15 weeks over the course of the semester. Will be hands-on exercises with numerical model code (and/or associated pre- or post-processing code) and open source models. Concerns providing students an opportunity to work directly with the models, parameterizations, techniques, etc., that are discussed in class. More detailed instructions for these will be provided in class. Final Group Project --> The final project to take on the following: 1) Numerical modelling experiments on one or more interesting or significant weather events 2) Detailed evaluation of data assimilation method(s), parameterization(s), probabilistic prediction method(s) and/or post-processing technique(s) 3) Development or improvement to one of the items listed under (2) 4) Detailed or innovative evaluation of operational or real-time research model forecasts The project will involve a 10-115 pages paper, accompanied by development computation environment. and a 15-minute conference-style presentation to the class. By the end of the first month, please think of a possible topic and turn in a paragraph describing your idea. Then, by mid-following month, I will meet with you individually to discuss your proposed topic. (If you have other interesting ideas outside of the formats described above, please feel free to raise them with me!) The paper will be due on whatever due date, and the presentations will be given during the last week of class and during the final exam period. More details on the format and expectations for the project will be given in class. Assessment --> Homework 15% Lab exercises (35%) Final project paper and presentation (50%). Note: there will not be any exams. Plus/minus grading will be used. Lecture Outline --> Week 1 Syllabus; Introduction; discussion of expectations for course; the history of NWP Week 2 NWP theory: brief introduction to numerical methods, regional vs. global modelling Week 3 Current state of NWP systems Week 4 Introduction to the WRF model – configuration, options, etc.; practical aspects of numerical modelling; parameterizations Week 5 Parametrizations Week 6 Parameterizations, continued; experiment design, phenomena to simulate, etc. Week 7 – 8 Initialization and data assimilation Week 9 – 10 Ensemble/probabilistic prediction Analysis and logistics for Ensemble models to be implemented R Packages of interest: ensembleR, ensembleML, ensembleBMA, ensembleMOS, ProbForecastGOP CSTools SpecsVerification, scoringRule Fraley, C. et al (2011). Probabilistic Weather Forecasting in R. The R Journal Vol. 3/1 NOTE: above article specifies packages ensembleBMA and ProbForecastGOP, however, it’s often best to investigate other development options based on the other given packages, so you know that you’re not limiting yourselves. Assist for R: Vannitsem, S., Wilks, D. S. and Messner, J. (2018). Statistical Postprocessing of Ensemble Forecasts. Elsevier Week 11 Forecast evaluation. Must have hands-on ability Week 12 Integrating NWP models with other types of models Week 13 Space for guest presentations/ other topics of student interest Week 14 - 18 Cleaning up things, unfinished business, beginning of final student presentations Prerequisites: Numerical Analysis, Data Programming with Mathematica, Partial Differential Equations, Fluid Mechanics, Physical Meteorology I, Mathematical Statistics Data Analysis in Atmospheric & Oceanic Sciences: Grading --> Homework 20% Labs 20% Midterm Exam 25% Final Exam 35% Exams are open book and open note. Homework assignments will include computational and simulation activities given to students, where instructor is bly responsible for conceptual setups. For exams students will also be required to provide heuristic design for computational and simulation requests. Fundamentally statistical in nature are questions concerning the behavior of the atmosphere, climate and oceans. Computational and simulation assignments given to students follows only heuristics setup by instructor. Example concerns: (1) whether character of tropical storms and hurricanes alter with time; (2) whether warming of the globe is parallel with natural variability or not; (3) the influence of El Nino on global weather patterns. Emphasis on the application of the instruction to actual data. The prime objective is computation via Mathematica and so forth. NOTE: In the Mathematica environment there is the Wolfram Data Repository available; not necessarily confined to it however. Assisting Texts (but not confined to them) --> Thiebaux, H. J. (1994). Statistical Data Analysis for Ocean and Atmospheric Sciences. Elsevier Wilks, D. S. (2019). Statistical Methods in the Atmospheric Sciences. Elsevier COURSE TOPICS: ---Fast Review of Probability Distributions: Axioms, frequencies modelling, simulating random variables Data sources, APIs, file types. Wrangling. Characterising the events of tropical storms and hurricanes; characterizing tropical Atlantic Sea surface temperature variations; characterising El Nino events; exploratory analysis of rainfall data; unmixing ice ages; testing for drought; fitting ocean currents. ---Some fast statistics review Data sources, APIs, file types. Introspection and querying. Generating summary statistics, box plots, skew, kurtosis, density plots, Q-Q, P-P, Shapiro-Wilk test, kolmogrov-Smirnov test, Anderson-Darling test, MLE and confidence intervals. ---Hypothesis Testing Priority is applying raw oceanography and atmospheric data to conjure hypothesis and test them for validity and meaningfulness...that’s all (Kentucky like). Beginner examples: questioning whether there are distinct regimes of atmospheric circulation behavior during the 20th century, or of Atlantic Hurricane activity. ---Regression (logistics and the computational substance) Note: this is not a regression analysis course, say, you will depend much on your mathematical statistics experience, where logistics towards credible computational substance is the prime directive. Review prerequisites notes, and take notes. Plan out your development flow, and be fluid and coordinated with your Mathematica/ functions or R packages. Multivariate regression Contemplating variables based on data analysis Heteroscedasticity and generalised least squares Model selection methods (Vuong’s test, F-test, AIC, BIC, HQC) Splitting data (training, testing) Forecasting and error Quantile Regression and Lasso Regression Most topics based on GLS prior to apply Scatter Plots Scatterplots are a useful first step in any analysis because they help visualize relationships and identify possible issues (e.g., outliers) that can influence subsequent statistical analyses, or need of regression beyond simple OLS/WLS/GLS, say, quantile regression (or generalized nonlinear models). Note: concerns for the number of variable pairs. Contemplating variables based on data analysis Model selection methods (Vuong’s test, F-test, AIC, BIC, HQC) Splitting data (training, testing) Forecasting and error Regression and Trend Analysis: global warming; whether El Nino is becoming more influential over time; whether the intensity of tropical storms and hurricanes are increasing over time. Identifying atmospheric and oceanic factors that control variations and trends in tropical storms and hurricane activity. ---Time Series (logistics and the computational substance) Note: this is not a time series analysis course, say, you will depend much on your mathematical statistics experience, where logistics towards credible computational substance is the prime directive. Review prerequisites notes, and take notes. Plan out your development flow, and be fluid and coordinated with your Mathematica/ functions or R packages. Time Series representation of data Difference equations and conditional expectation Linear and logarithmic forms Seasonality and trend (methods of identification) Autoregressive Moving averages Exponential Smoothing Box Jenkins Approach Model Identification Estimation Validation Box-Jenkins analysis on data Splitting data (training, testing, validation) GARCH development (with selection, training, testing) Fourier Tools? Spectral analysis and spectral representations? Filters? Multivariate time series models? Seasonal and cyclic patterns; modelling the behavior of El Nino; modelling the global temperature series; Fourier analysis and inverse problem; spectral analysis; seasonal rainfall; excessive abnormal respective regional temperatures into coming seasons making use of past a current data for seasons; excessive abnormal respective regional sea temperatures into coming seasons making use of past a current data; solar storms, aurora borealis, aurora australis. R. Modarres and T. B. M. J. Ouarda (2014). Modelling the Relationship Between Climate Oscillations and Drought by a Multivariate GARCH Model. Water Resources Research, Volume 50, pages 601 – 618 --Ensemble/probabilistic prediction Analysis and logistics for Ensemble models to be implemented R Packages of interest: ensembleR, ensembleML, ensembleBMA, ensembleMOS, ProbForecastGOP, tsensembler, modeltime.ensemble CSTools SpecsVerification, scoringRule Fraley, C. et al (2011). Probabilistic Weather Forecasting in R. The R Journal Vol. 3/1 NOTE: above article specifies packages ensembleBMA and ProbForecastGOP, however, it’s often best to investigate other development options based on the other given packages so you know that you’re not limiting yourselves. An R assist: Vannitsem, S., Wilks, D. S. and Messner, J. (2018). Statistical Postprocessing of Ensemble Forecasts. Elsevier ---Analyzing spatial data Understanding the spatial behaviour influence of El Nino and the North Atlantic Oscillation on atmospheric circulation patterns; infilling a sea-surface temperature data or a geologic map; tropical storm surges; range of Arctic/Antarctic ice packs and regional temperatures. NOTE: additional pursuits will come from the following text: H. von Storch and A. Navarra. (1999). Analysis of Climate Variability: Applications of Statistical Techniques Proceedings of an Autumn School Organized by the Commission of the European Community on Elba from October 30 to November 6, 1993. Springer-Verlag Berlin Heidelberg Prerequisites: Mathematical Statistics Of great interest: Fraley, C. et al (2011). Probabilistic Weather Forecasting in R. The R Journal Vol. 3/1, June 2011: https://journal.r-project.org/archive/2011-1/RJournal_2011-1_Fraley~et~al.pdf Meteorological software and data sources of interest: World Meteorological Organisation (a UN agency) WRF https://www2.mmm.ucar.edu/wrf/users/ RAMS http://www.atmet.com/html/software.shtml IDV https://www.unidata.ucar.edu/software/idv/ ARPS www.caps.ou.edu/ARPS/ Nonhydrostatic Mesoscale Model Saito, K. et al (2006). The Operational JMA Nonhydrostatic Mesoscale Model, Monthly Weather Review, 134(4), 1266-1298. Retrieved Aug 17, 2021, from https://journals.ametsoc.org/view/journals/mwre/134/4/mwr3120.1.xml NOAA MetEd SPC Forecast Tools SSEC Satellite mages SMHI ICSU United Nations Statistics Division United Nations Statistics Division Environmental Indicators UN Geo Data Portal EPA Air Research ( https://www.epa.gov/air-research/models-tools-and-databases-air-research ) NOTE: for oceanography and meteorology students they are permitted to participate in spectroscopy activities and separation methods. They are generally prohibited from quantum chemistry-based activities and molecular modelling. SOME MORE POWERFUL ATMOSPHERIC-OCEANIC TOOLS One should not treat the following as just alternatives to each other, rather also prowess of comparative assessment or various “second opinions”: 1. ROMS (Regional Ocean Modelling System) https://www.myroms.org There are also packages and documentation 2. WRF (Weather Research and Forecast Model) www2.mmm.ucar.edu If link doesn’t work find download site via search engine. 3. CESM2 4. SWAN (Simulating Waves Nearshore) swanmodel.sourceforge.net 5. ECMWF software and packages MICROC5 CMIP5 6. General CMIP5 models and competing alternatives 7. Nucleus for European Modelling of the Ocean (with OASIS and XIOS) 8. Ariane Ariane is a numerical diagnostic tool developed at the Laboratoire de Physique des Océans (Brest, France) 9. TRACMASS 10. The Connectivity Modeling System (CMS) 11. LIGHT within MPAS-O 12. NEMO (the Nucleus for European Modelling of the Ocean) model 13. MITgcm (Massachusetts Institute of Technology General Circulation model) 14. HYCOM (the HYbrid Coordinate Ocean Model) 15. Octopus Octopus is an offline particle tracking code first written to conduct offline particle simulation using the Southern Ocean State Estimation 16. The Community Climate System Model (CCSM) CCSM 3.0 or CCSM 4.0 or higher Global RTOFS Data Access (+ Fukushima Tracers + Fukushima Surface Plume Study) 17. NOAA WAVEWATCH III 18. Possible interest in understanding the following data formats and how to incorporate them for various interests with computational tools applied: Data Format (NETCDF) and Open-source Project for a Network Data Access Protocol (OPENDAP). Note: one will not necessarily be confined to such two formats. 19. REMO 20. GEOS Systems (GEOS-5 Access at least) 21. NASA GISS GCM 22. Earth systems (CLM5) 23. Coupled-Ocean-Atmosphere-Wave-Sediment Transport (COAWST) Modelling System 24. GFDL-ESM 4.1 NOTE: UN IPCC data may prove invaluable for research “SUMMER AND WNTER SEMESTERS” Begins at upper sophomore level for “winter and “summer” semesters. Students can participate multiple times. There will be a secure database archive for all participants and supervision constituents for respective activity in chronology. Activities repeated can be added to transcripts upon successful completion. Repeated activities later on can be given a designation such as Advance “Name” I, Advance “Name” II. As well, particular repeated activities serve to towards developing true comprehension, competency and professionalism. Capabilities of activity will neither be influenced by local cultural ignorance and stigmas nor by ambiances not of concern to bride programme. Physics students and mathematics students to acquire special invitation. FOR ACTIVITIES IN THE “SUMMER” AND WINTER” SESSIONS ALL PARTICIPATING STUDENTS, ASSISTING/ADVISING INSTRUCTORS AND PROFESSORS MUST BE OFFICIALLY RECOGNISED; REQUIRES BOTH CIVILIAN ID AND STUDENT/FACULTY ID FOR CONFIRMATION OF INDIVIDUAL. THERE WILL ALSO BE USE OF IDENTIFICATIONS FOR ACTIVITIES FOR RESPECTIVE SESSION. SECURITY AND NON-PARTICIPATING ADMINISTRATION WILL ONLY IDENTIFY RESPECTIVE ACTIVITY BY IDENTIFICATION CODE. SECURITY AND NON-PARTICIPATING ADMINISTRATION MUST NEVER KNOW WHAT ACTIVITIES IDENTIFICATION CODES IDENTIFY: < Alpha, Alpha, Alpha, Alpha > - < # # # # # > - < session > - < yyyy > Such meteorology and oceanography activities will also warrant criminal background check (CBC) in order to participate. Severely threshold may vary depending on administration. Administrators will provide dated letters of confirmation of thorough CBC to student affairs and other appropriate administration. Such also may include screening that’s parallel to customs & immigration processing where certain levels of criminal history warrants rejection. Email and physical letters with data. Such CBC protocol will not explicitly identify any particular titles or descriptions of any activity, rather, will only convey code as above. It may be the case some activities can be grouped and given a major title together; however, detailed descriptions will be required. NOTE: logically in profession all developments and data from research in meteorology and oceanography are forever archived in a secured manner for later retrieval. Hence, all activities will abide by such. MASSIVE FOREVER DATABASES ACCUMMULTION TO BE EXPECTED. NOTE: SUCH DATA DOES NOT IMPLY REDUCTION OR JOCKING ON JOCKING ON PAST LABS AND FIELD OPERATIONS. Activities will be field classified. Particular projects of interest being stationary Perpetual research of concern to interpret, replicate and extend with models and data: I. Precipitation Probability The probability of precipitation forecast is one of the most least understood elements of the weather forecast. The probability of precipitation has the following features: The likelihood of occurrence of precipitation is stated as a percentage A measurable amount is defined as 0.01" (one hundredth of an inch) or more (usually produces enough runoff for puddles to form) The measurement is of liquid precipitation or the water equivalent of frozen precipitation The probability is for a specified time period (i.e., today, this afternoon, tonight, Thursday) The probability forecast is for any given point in the forecast area To summarize, the probability of precipitation is simply a statistical probability of 0.01" inch of more of precipitation at a given area in the given forecast area in the time period specified. Using a 40% probability of rain as an example, IT DOESN’T MEAN: (1) that 40% of the area will be covered by precipitation at given time in the given forecast area or (2) that you will be seeing precipitation 40% of the time in the given forecast area for the given forecast time period. Let's look at an example of what the probability does mean. If a forecast for a given county says that there is a 40% chance of rain this afternoon, then there is a 40% chance of rain at any point in the county from noon to 6 p.m. local time. This point probability of precipitation is predetermined and arrived at by the forecaster by multiplying two factors: Forecaster certainty that precipitation will form or move into the area X Areal coverage of precipitation that is expected (and then moving the decimal point two places to the left) Using this, here are two examples giving the same statistical result: (1) If the forecaster was 80% certain that rain would develop but only expected to cover 50% of the forecast area, then the forecast would read "a 40% chance of rain" for any given location. (2) If the forecaster expected a widespread area of precipitation with 100% coverage to approach, but he/she was only 40% certain that it would reach the forecast area, this would, as well, result in a "40% chance of rain" at any given location in the forecast area. MAJOR CONCERNS to resolve: --Probability model for precipitation development --Probability model for area coverage II. Meteorological Analysis Will concern chosen analysis and labs from the Meteorological analysis I-III course sequence. Range of activity will depend on student’s intelligence and skills from courses experience; for following schedules students groups can be segmented into newcomers for activity and those experienced with activity, where for latter segment to involve reinforcement and advancement, III. Atmospheric Tides PART A 1. Chapter 3 The Vertical Structure of the Atmosphere – MIT PAOC Questions at the end are of great interest PART B 1. From the following journal article will like to analyse the acquisition of the following equations: Horizontal momentum equations Energy equation Continuity equation Holton, J. R. (1975). The Dynamic Meteorology of the Stratosphere and Mesosphere, Meteor. Monog., 15 (37) To solve such set of equations for atmospheric tides, say, longitudinally propagating waves of zonal wavenumber s and frequency sigma. Zonal wavenumber is a positive integer so that positive values for frequency correspond to eastward propagating tides and negative values to westward propagating tides. Interested in expressions for the latitudinal and vertical structure of the tides. The latitudinal structure of the tides is described by the horizontal structure equation which is also called Laplace's tidal equation. What types of special linear operators do atmospheric tides take on? Determine the vertical structure equation and it’s solution, with physical meaningfulness for various conditions. 2. Elementary modelling --> Chapman S., Lindzen R.S. (1970) Quantitative Theory of Atmospheric Tides and Thermal Tides. In: Atmospheric Tides. Springer, Dordrecht Can such chapter be reconciled with what was developed in Part B1? Identify the consistencies or determine how well such chapter can explain prior results in Part B1. Second, from chapter abstract, “We then describe, rather simply, the sources of excitation included in various tidal calculations, and the specific responses inferred. Where possible, the effect of various approximations in these solutions is discussed.” Will like to analytically investigate such specific responses. Mathematica and its Manipulate function may prove quite invaluable. As well, some models may highly practical with data, namely, for chosen meteorological data will like to find interpolation functions and/or best fit functions to compare with theoretical (perfect) solutions. Next, the following journal article may be a sigh for relief, but concerns the tropical troposphere; reconcile with or relate what was found for the vertical structure prior to form(s) observed in the journal article --> Ortland, D. A. and Alexander, M. J. (2001). Solutions to the Vertical Structure Equation for Simple Models of the Tropical Troposphere, Journal of the Atmospheric Sciences 68(9): 2061 - 2072 -Now, how relatable or practical are developments of PART B to findings in part A? PART C Empirical Research--> Atmospheric tides are said to form an important mechanism for transporting energy from the lower atmosphere into the upper atmosphere, while dominating the dynamics of the mesosphere and lower thermosphere. Find professional sources that support such two claims. How are such two claims modelled? Chapman, S. and Lindzen, R.S. (1970). Atmospheric Tides: Thermal and Gravitational. Springer Netherlands. ISBN 978-94-010-3399-2 http://adsabs.harvard.edu/full/1969SSRv...10....3L Concerning the following chapters will choose topics of interest to analyse. Analytical analysis AND pursuit of data analysis that supports (or perhaps contradicts) the major findings or models. One can start with time frame of data applied to text, then pursue results with modern data: The Solar Daily Atmospheric Oscillations as Revealed by Meteorological Data The Lunar Atmospheric Tide as Revealed by Meteorological Data PART D Note: for empirical data towards any conclusion there must be certainty that there’s no substantial coupling effects involving insolation, lunar effects, tropical convection leading to large scale latent heat release, and the nonlinear interactions between tides and Rossby waves. would like to account for such influences uniquely from each other. I. Insolation influence Note: make use of the above text What evidence can support the presence of such influence? Is there data can be modelled to verify such? Proceed if able. As well, the GSWM Model can be of great interest (if relevant) --> http://www.hao.ucar.edu/modeling/gswm/gswm.html II. Lunar influence Kohyama, T. and Wallace, J. M. (2014). Lunar Gravitational Atmospheric Tide, Surface to 50 km in a Global, Gridded Data Set, Geophysical Research Letters. Lindzen, R. S. (1967). Lunar Diurnal Atmospheric Tide, Nature, 215, pages 1260–1261. Paulino, A. R., Batista, P. P. and Batista, I. S. (2013). A Global View of Atmospheric Lunar Semidiurnal Tide, Geophysical Research Letters 1. Develop empirical evidence for time frame by text, and then for more modern data. 2. As well, consider influence on barometric pressure and the possible resulting level of effect on rainfall. Articles with quantitative models for relation bewtten barometric pressure and precipitation can be pursued as reference. As well, to acquire high volume data for moon phases or distance from Earth and find time related precipitation data (global occurrences) where one tries to establish empirical evidence. Nonlinear interactions between tides and planetary waves resulting in periodic tidal variability III. Non-Linear Interactions Between Tides and Rossby waves --Beard, A. G. et al. (1999). Nonlinear interactions between tides and planetary waves resulting in periodic tidal variability, Journal of Atmospheric and Solar Terrestrial Physics, 61, 363 – 376 --Huang, K. M. et al, A nonlinear interaction event between a 16-day wave and a diurnal tide from meteor radar observations, Ann. Geophys., 31, 2039–2048, 2013 For such two prior articles to analyse, replicate findings and then try to pursue more modern data for development. IV. Large-scale Latent Heat release from tropical Convection Oberheide, J & E. Hagan, M & G. Roble, R & Offermann, D. (2002). Sources of Non-Migrating Tides in the Tropical Middle Atmosphere. Journal of Geophysical Research, Volume 107, Issue D21 From such an article there are many things to pursue, say, explicit identification of applied models, and data for data analysis towards verification. Such pursuits concerns replication of article findings. More modern data can be treated afterwards. Hagan, M. E. and Forbes, J. M. (2002). Migrating and Nonmigrating Diurnal Tides in the middle and Upper Atmosphere Excited by Tropospheric Latent Heat Release, Journal of Geophysical Research, Volume 107, Issue D24 One aims to replicate findings with use of the GSWM Model --> http://www.hao.ucar.edu/modeling/gswm/gswm.html PART E 1. Atmospheric Tides for a Chosen Island Concerning the following journal, after analysis one is to choose an island of interest and pursue means to model the atmospheric tides: KISER, W.L., CARPENTER, T. H., and BRIER, G. W. (1963): The Atmospheric Tides at Wake Island. Mon. Wea. Rev., 91, 566 – 572 2. To then be followed by development and implementation of the following: Wang, Y., Huynh, G. and Williamson, C. (2013). Integration of Google Maps/Earth with Microscale Meteorology Models and Data Visualization. Computers and Geosciences 61, 23 - 31. WILL LIKE TO EXTEND IT WITH INCORPORATION OF PRECIPITATION AND TEMPERATURE DATA EXHIBITION WITH WIND. PART F Impact of deforestation? Land climate interactions. Will try to gather vast meteorological data from various pat years towards atmospheric tides modelling and variation. IV. Oceanic and atmospheric Heat Cycles --OCEAN HEAT TRANSPORT It may be a challenge to establish harmony among the journal articles to follow; such to be pursued. For each journal article with the given model(s) to compare with empirical data for respective latitudal regions (equatorial, temperate, Arctic, Antartic) for at latest five to ten consecutive years, observing the seasonal variations for a respective year. As well, data fitting onto character curves, prediction by regression analysis models and time series. 1. Gnanadesikan, A. et al, 2005: The Energetics of Ocean Heat Transport, Journal of Climate, Volume 18, 2604 - 2616 2. Ferrari, R., and Ferreeira, D. (2011). What Processes Drive the Ocean Heat Transport? Ocean Modelling 38, 171–186 Analyse such above journal article and identify its practicality and tangibility with modern popular experimentation today. Design an empirical project of interest based on found level of practicality and tangibility. 3. Kamenkovich, I. et al, Factors Affecting Heat Transport in an Ocean General Circulation Model, Journal of Physical Oceanography, Volume 30, 175-194 For models in above journal article and prior (Ferrari and Ferreeira 2011) confirm whether they are harmonious in structure. If not, what are the significant disparities? There are various experiments with acronyms in the prior journal article (Kamenkovich, I. et al). For such experiments pursue identifying the detailed logistics with data access (modern data) and means to actively incorporate the respective data. Implement. 4. The following article concerns replicating the models and use of data. Then to have compare/contrast with (3): Donohoe, A. and Battisti, D. D, 2001: What Determines Meridional Heat Transport in Climate Models? JOURNAL OF CLIMATE, Volume 25, 3832 – 3850 --SEASONAL & ANNUAL CYCLE OF OCEAN HEATING & TEMPERATURE In the Atlantic ocean there are numerous stations or buoys that collect temperature throughout the year. Such stations are located along various points of latitude longitude. The following tasks to pursue --> 1. Develop data model for observed monthly mean sea surface temperatures in the eastern equatorial Atlantic (48S–48N, 168W–48E), it’s western counterpart; interested in the pacific, do so as well. Do this for 10 – 20 years of data. 2. Concerning the last 10 to 20 years, for each season (in the temperate sense) model the temperature for chosen latitudes, say 5-degree increments (from north pole to south pole). Develop both times series and regression for future predictions. It would be interesting to follow up on such models and the resulting predictions to determine Howell they compare with model acquired data. 3. Recall ocean circulation models or ocean current models and the influence of temperature. One may need to develop a heat/temperature gradient that models variations over the years based on ocean temperature data over such time span. Consider the last 10 years of data from (2) or (3) and observe any possible perturbation or amplification or expansion in behaviour for such circulation or current models. Is there drastic behaviour? Is there ever any convergence back to the first considered behaviour? --SEASONAL CYCLE OF ATMOSPHERIC HEATING & TEMPERATURE i. Donohoe, A. and Battisti, D. S., 2012: The Seasonal Cycle of Atmospheric Heating and Temperature, JOURNAL OF CLIMATE, volume 26, 4062 – 4980 Analyse journal article and pursue means to replicate. There are multiple models to compare and contrast (if accessible). Consider as well modern data to compare with such models. Are there drastic differences? V. Land Based Weather Stations Planning and logistics for modern generic land weather stations that collect various data. Followed by building of stations Activity will be not dependent on any course in oceanography and meteorology. PART A In this activity stations will not be permanent, rather to only capture data within the period for activities. All data will be secured archived where they can be properly recognised (which includes location of reference). Data should be in a form that can’t be tampered with. Data should be in format that’s integration with various processing hardware and CAS software. All data should be chronologically recorded and possibly time synchronized with each other. Each data type should also be naturally useful for modelling with the other types. Additionally, ability of stations sending real time data remotely Data of concern Temperature Humidity Pressure Wind Velocity (speed and direction) Precipitation (may prove challenging) Stations at various sites of different altitudes, latitude-longitude. This also incorporates stations at sites with high precipitation, low precipitation, near sea shore, etc.. Insulated programmable boards are possible. Concerns (seasonal) trends, cycles, volatility and so forth. Data can be associated to meteorological models. Activity is not dependent on the “Meteorological Instruments” courses. A beginner demonstration before pursuit: Arduino Data Logging Shield V1.0 - YouTube < https://www.youtube.com/watch?v=nCQZWdL3BGE > VI. Oceanic Stations PART A Designing and building underwater sensor nodes Identifying the key components/systems Power Embedded computers/Microcontrollers Identifier-GPS Radio Module Cameras Sensors Temperature Pressure Motion Sway, heave, surge Acidity Light Sensing There will be high effort design holding/placing system for all such major components/system. Task of configuration of the Identifier-GPS and Radio module for quality service. Determine which sensors to be encapsulated by strong but light body. Consideration of encapsulation resilient to determined pressure range at specified depth. Nodes may be loosely tethered to the sea floor where currents and storm activity aren’t strong enough to undermine tethering integrity. Storing data chronologically and instantaneously in installed memory location. As well, ability of stations sending real time data remotely (which also includes video) Note: developed underwater sensor nodes may constitute a network. PART B Sea surface stations Aim is to design and develop suspended oceanic stations. Major concerns are: 1. Insulating sensitive components that should not be exposed to water, salts. 2. Storing data chronologically and instantaneously in installed memory location 3. Ability of stations sending real time data remotely 4. Stations have strong power source life times. Power sources can be changed without losing data without water/sea salt exposure (if practical). 5. Stations are not to interpreted as sustenance by marine life. Not prone to marine life damage. 6. Stations don’t pollute or release toxic materials in the water. 7. Stations must be suspended and easily susceptible to being taken away by harsh weather. 8. Stations must be highly buoyant where water crashing/waves will not accumulate to weight that sinks stations. Includes overturns by tilts. May require some internal type of gyro stabilization. 9. Stations will float continuously at surface, but will be tethered to sea floor where currents and storm activity aren’t strong enough to undermine tethering integrity. 10. Ability of stations sending real time data remotely System design, development subject to (1) through (10) will be a challenge. Data of consideration: Video (saturation may prove a problem) Water Temperature near surface Air Temperature (saturation may prove a problem) Air Humidity (saturation may prove a problem) Air Pressure Wind Velocity (speed and direction) Water Acidity near surface In this activity stations will not be permanent, rather to only capture data within the period for activities. All data will be secured archived where they can be properly recognised (which includes location of reference). Data should be in a form that can’t be tampered with. Data should be in format that’s integration with various processing hardware and CAS software. All data data should be chronologically recorded. Each data type should also be naturally useful for modelling with the other types. VII. Weather balloon Meteorological Measurements, Observation AND Recovery Physics, Geology, Oceanography and Aerospace Engineering constituents to participate if desired. Using weather balloon integrated with (cheap) sensors and other hardware for measurement of meteorological/atmospheric properties. Multiple trials. A. FOUNDATIONAL PHYSICS MODELLING--> (1) Earth Atmosphere Model https://www.grc.nasa.gov/www/k-12/rocket/atmos.html (2) Berberan-Santos, M. N., Bodunov, E. N. and Pogliani, L. (1997). On the Barometric Formula. American Journal of Physics, 65 (5), pages 404 – 412 (3) U. S. Standard Atmosphere, 1976, U.S. Government Printing office, Washington, D. C. 1976 (4) Earth Global Reference Atmospheric Model 2010 (Earth GRAM 2010) (5) NRLMSISE-00 Picone, J., Hedin, A., Drob, D., & Aikin, A. (2002). NRLMSISE‐00 Empirical Model of the Atmosphere: Statistical Comparisons and Scientific Issues. Journal of Geophysical Research: Space Physics, 107 (A12), SIA 15-1-SIA 15-16. --The first phase of this activity concerns comparative analysis of pressure in (1) compared to the other sources. If the contexts are the same then one should pursue reconciling model models. Applicability towards experiment of interest is only crucial. All Models found in (1) through (5), not only pressure, will be compared to data acquired from weather balloon field experimentation. B. CONSISTENCY OF EXPERIMENT TRIALS WITH PROFESSIONAL METEOROLOGICAL FORECASTS AND REAL DATA Naturally, one needs acceptable weather for launches. In theory rough weather will provide data that’s not idealistic. Operational days concern only long periods of decent atmospheric weather. For a respective trial within its time window will also compare that experiment’s data with professional meteorological given prior forecasts and acquired data sets sources for the region of operation in question. (Atmospheric) GPS logging will be crucial in all this, where such logging can be compared to experimentation data. NOTE: atmospheric currents and air currents can have influence on atmospheric density. Hence, monitoring the most recent forecasts and real time data of such currents with definitive estimates for the region; barometric isobars (and determining gradients) may come in handy. Obviously, ascending crafts will also have atmospheric pressure sensing. C. EXPERIMENTATION TOOLS Experimentation concerns verifying standard properties of the Earth’s atmosphere by a developed radiosonde constituted by the following 10 tools: 1. Atmospheric temperature measurements 2. Barometer readings (to later be compared to derived theoretical variation model, forecasts and data from professional sources). 3. Altitude readings 4. Vertical velocity readings (to later be compared to derived theoretical variation model). Velocity readings and altitude readings to be confirmed with each other via some primitive calculus involving the data. 5. Atmospheric photography (earthly views and skyward) 6. UV index readings (frequency or wavelength) 7. Infrared sensing and strength (frequency or wavelength) 8. Microwave sensing and strength (frequency or wavelength) 9. Continuously active GPS 10. Parachute and trigger by sensing and actuation There must an elaborate means of triggering parachute appropriately. Once possibly means is by tension sensing in chord(s). Another possibility may be accelerometer sensing for radical earth-directed acceleration in atmosphere; processing has to be fast and accurate. 11. Remote retrieval of data during ascent and descent. 12. Signal frequency/wavelength variation data acquisition. 13. Means of cosmic and/or elementary particle detection (not being electrons) D. CONCERNS FOR OPERATIONS: 1. There may be need for redundancy concerning various tools, BUT all tools (1) through (13) must be synchronized in time. 2. Different tools and hardware must not disrupt or corrupt measuring and performances of each other 3. Programming boards will likely be required with parallel processing, multicore and/or stacks. 4. Systems will demand capable long-lasting DC supply; regulators, converters may or may be a major issue. 5. Microcontroller(s) for parallel computation/processing, multicore or cluster stack, etc. 6. Respective reading to carry out sensing measurements for specified time intervals. 7. All tools recording data in designated time intervals should have their readings chronologically acquired. 8. Under practical and reasonable conditions one should determine the maximum duration it would take balloon and its payload to reach apex altitude. Maximum power related to systems, and minimum required life of power source for journey. 9. System must be engineered to operate at very low temperatures. 10. Exceptional Insulation for those hardware that concern no contact with precipitation or moisture. There may issue of condensation internally as craft ascends. 11. Crafts are not to serve as exceptional lightning rods. 12. System should also be designed for the circumstance of high impact collisions. 13. Data from remote transfer is automatically stored upon acquisition by stations (that are also weather proof). 14. Station(s) on ground to track weather balloons concerning confirmation of position for specified times; reference frames relating algorithm(s) to be developed to confirm ground readings with balloon readings. Stations should also have an active clock that keeps time that’s also be perfectly associated to time interval measures of weather balloon labs. 15. There should be an active clock that keeps time that’s also be perfectly associated to time interval measures of weather balloon labs. Asocciate reference frames!!!! Sensor devices (just one example set, but may or may not be sufficient for considered environments) --> http://www.theremino.com/en/hardware/inputs/meteorology-sensor E. RESULTS With such treasure trove of data to be acquired there can be various data analysis towards research for various fields of physics Geophysics (accounts for geology, ocoeanography and meteorology) General Physics Relativity (special and general) Particle Physics Field activity also serves the following engineering fields --> Electromagnetics, Communications, Electrical Engineering, Control, Computer Engineering, Aerospace Engineering Some initial “kindergarten” modelling from data --> Temperature versus altitude can also be studied through models and compared to data from experimentation trials. Temperature versus time can also be studied through models and compared to data from experimentation trials. Atmospheric pressure versus altitude can also be studied through models and compared to data from experimentation trials. Atmospheric pressure versus time can also be studied through such models and compared to data from experimentation trials. Altitude speed versus altitude can also be studied through models and compared to data from experimentation trials. Altitude speed versus time can also be studied through models and compared to data from experimentation trials. NOTE: there are various other modelling to be considered besides the prior mentioned “kindergarten” examples. VIII. Radio Occultation Summary ---> Remote sensing technique used for measuring the physical properties of a planetary atmosphere. The technique relies on the detection of a change in a radio signal as it passes through a planet's atmosphere, i.e. as it is occulted by the atmosphere. When electromagnetic radiation permeates through the atmosphere it is refracted. The magnitude of the refraction depends on the gradient of refractivity normal to the path, which in turn depends on the density gradient. The effect is most pronounced when the radiation traverses a long atmospheric limb path. At radio frequencies the amount of bending cannot be measured directly; instead the bending can be calculated using the Doppler Shift of the signal given the geometry of the emitter and receiver. The amount of bending can be related to the refractive index by using an Abel Transform on the formula relating bending angle to refractivity. In the case of the neutral atmosphere (below the ionosphere) information on the atmosphere's temperature, pressure and water vapour content can be derived giving radio occultation data applications in meteorology. GNSS Radio occultation ---> Assists for activity: Melbourne et al. 1994. The Application of Spacebourne GPS to Atmospheric Limb Sounding and Global Change Monitoring. Publication 94-18, Jet Propulsion Laboratory Kursinski et al. 1997. Observing the Earth's Atmosphere with Radio Occultation Measurements using the Global Positioning System. J. Geophys. Res. 102: 23.429-23.465. Xie, F.; Haase, J. S.; Syndergaard, S. (2008). Profiling the Atmosphere using the Airborne GPS Occultation Technique: A sensitivity Study. IEEE Transactions on Geoscience and Remote Sensing. 46 (11) Pursuit: Goal is to implement GPS receivers stationed at very high non-residential altitudes. Concerns receiving “continuous” data with huge memory capacity. Such raw data to modelled towards interest. Alongside such field remote sensing, will make use of popular professional data acquisition databases; to confirm whether data modelled will be consistent to findings done by field remote sensing. Synchronising may be the biggest challenge. IX. Atmospheric Spectroscopy Activity mainly concerns completing atmospheric goals in the interest of meteorology (and oceanography to some degree). Activity is neither to be taken hostage, sophisticated, butchered nor corrupted by constituents outside of such fields. Will outline the structure and goals of Atmospheric Spectroscopy. Will revolve around the following topics and respective development and integration into operations: -UV, Infrared, Ultra-spectral, hyperspectral, multispectral, -Spectral resolution & sampling spacing, spectral smoothing -Spectrum-matching techniques for wavelength and spectral resolution calibrations -Solar spectral irradiance curve problems The spectrum of all planetary objects (and humans, for that matter) has a double hump - a one in the visible region due to reflected sunlight and another in the infrared due to thermal emission of the planet. On the intensity -wavelength spectrum students must comprehend where the following will reside: Emission lines (UV)- hot upper atmosphere Object absorbs blue light from the sun Thermal emission from the sun Object reflects red sunlight CO2 absorption bands- carbon dioxide atmosphere Thermal emission peak in infrared: surface temperature ~ 225 K Will make use of balloons to orchestrate tropospheric and stratosphere data collection. Concerns O2, N2, NO, N2O, O3, CO, CO2, etc, etc. Identifications are not limited to the seven mentioned compounds. Altitude, barometric and temperature data collected will also accommodate. Spectroscopy readings, altitude, barometric and temperature sensing must be synchronized in time with data storage. Based on altitude readings there would be indication to differentiate between tropospheric data and stratospheric data. Will pursue periods where respective season is at high point towards infrared imaging and infrared geological and oceanic temperature readings; will archive data with future seasons. Other experiment interests to pursue: Joly, L. et al (2016). Atmospheric Measurements by Ultra-Light SpEctrometer (AMULSE) Dedicated to Vertical Profile in Situ Measurements of Carbon Dioxide (CO₂) Under Weather Balloons: Instrumental Development and Field Application. Sensors (Basel, Switzerland), 16 (10), 1609. Hanst, P. L. IR-Spectroscopy of the Atmosphere, In: Analytic and Bioanalytical Chemistry. Z. Anal. Chem. (1986) Volume 324, Issue 6, pp 579 - 588 Note: findings will be compared to professional spectroscopy databases for confirmation. X. Relevance of greenhouse gases in the oceanic-atmospheric system (1) To then analyse/model the solubility of greenhouse gases in water as a function of temperature. A model for Ph levels possibly as a function of solubility, temperature and time, where solubility is probably also dependent on particular variables and parameters. Analyse and replicate with inclusion of more modern data (2) V. M. N. C. S. Vieira et al (2015). Comparing Solubility Algorithms of Greenhouse Gases in Earth-System Modelling, Biogeosciences Discuss, 12, 15925–15945 Will be a data, computational and simulation playing field. (3) Recreate experimentation as close as possible and compare results to the above journal article. Multiple trials likely needed. One may need to use to different types of water, say I. River/lake water II. Sea water (determine appropriate ranges of salinity) (4) From I - II respectively, model oxygenation/deoxygenation based on (1) - (2) and with additional chemistry ability. (5) Identify regions and/or periods of high deoxygenations, and determine whether the source(s) can be identified. XI. Hurricane Activity This activity concerns the frequency and hurricane characteristics annually for all times where credible data is accessible. Such should be accompanied by data analysis of temperatures per day for each month, to be integrated towards empirical stochastic/statistical model identifying each year. The following articles will be used as development guides in a Mathematica environment augmented with current data: Kossin, J. P. (2008). Is the North Atlantic Hurricane Season Getting Longer? Geophysical Research Letters, Volume 35, L23705 Lupo, A. R. et al (2008). The Interannual Variability of Hurricane Activity in the Atlantic and East Pacific Regions. National Weather Digest, Volume 32, Number 2 < http://weather.missouri.edu/gcc/Lupo-1-2Latham.pdf > Gutzler, D. S. et al (2013). Interannual Variability of Tropical Cyclone Activity Along the Pacific Coast of North America, Atmósfera, Volume 26, Issue 2, Pages 149-162 XII. GIS Weather Systems with Data A. Guides Taramelli, A., Melelli, L., M. Pasqui, M., Sorichetta, A., Estimating Hurricane Hazards Using a GIS System, Nat. Hazards Earth Syst. Sci., 8, 839–854, 2008 < https://www.nat-hazards-earth-syst-sci.net/8/839/2008/nhess-8-839-2008.pdf > Will develop an actual active programme/system for estimating hurricane hazards using a GIS system based on this journal article with incorporation of data concerning ambiances of interest. NOTE: if ArcGIS isn’t economically feasible then the following may serve well Smith, T. M. and Lakshmanan, V. Utilizing Google Earth as a GIS Platform for Weather Applications https://ams.confex.com/ams/Annual2006/techprogram/paper_104847.htm https://ams.confex.com/ams/pdfpapers/104847.pdf Nevertheless: there are other GIS tools mentioned in “Goody Bag” post. XIII. Storm Surges Means to develop the following for ambiance of interest. A. Will develop an actual active programme/system. Will apply hurricanes relevant to ambiance --> Li, H., Lin, L., & Burks-Copes, K. (2012). Modelling of Coastal Inundation, Storm Surge, and Relative Sea-Level Rise at Naval Station Norfolk, Norfolk, Virginia, U.S.A. Journal of Coastal Research, 29(1), 18-30. Hatzikyriakou, A. and Lin, N. (2017). Simulating Storm Surge Waves for Structural Vulnerability Estimation and Flood Hazard Mapping. Nat Hazards (2017) 89:939–962 B. Other future interest (towards ambiances of interest) when capable --> Wu, G. et al (2018). Modeling Wave Effects on Storm Surge and Coastal Inundation. Coastal Engineering 140, 371 - 382 Li, F., Zhou, J. and Liu, C. (2018). Statistical Modelling of Extreme Storms Using Copulas: A Comparison Study. Coastal Engineering, 142, 52 - 61 Li, J. et al (2018). Numerical Estimation of Extreme Waves and Surges Over the Northwest Pacific Ocean. Ocean Engineering 153, 225 - 241 XIV. Building a Radar System In similar fashion to astronomy observation telescopes, radar for meteorology to be built/developed. Despite pending possible capabilities with GOOGLE and so forth, having a foundation beyond external construction/dependency speaks of sustainability, skill and versatility with operations. The radar systems to be built/developed provide a comparative means of observation with other tools based on the crucial background of mathematics, physics, engineering and computer science (what you will not find much in developed platforms, etc.). Make the appropriate adjustments/calibrations to account for particular atmospheric activities. Concerns determining the distance (time-of-flight with pulse compression and frequency modulation), range, angle, or velocity (whether by coherent output with Doppler effect or continuous wave or time frequency analysis or chirplet transform) of objects, types of precipitation. Pulse-Doppler signal processing to measure radial wind velocity and precipitation rate in each different volume of air. This is linked with computing systems to produce a real-time electronic weather map. Echo heights above ground formula, etc. Colour coordination for dense and energetic regions by pixels or whatever; include temperature differentiation. As well, ocean surface air pressure sensing and high altitude atmospheric pressure sensing methodologies and implementation. Based on the mathematical and physics terminology, such is also a wonderful time to brush up on the relevant physics and mathematics without hindering radar system development. Such development will be crucial in acquiring independent data readily to be compared with other means for sense of accuracy, and/or integration into models, software, etc. Issues of limiting factors and civilian regulations. Engineering constituents welcomed. Like the astronomy, club, one can now have a “Climatology” club, parallel in obligations, intellectual property, security, etc. Professionalism and sustainability in meteorology are highly dependent on the ability to professionally record and store data, where structuring caters for the long term and augmentation. Radar system to be used in conjunction with local dispersed weather stations, GIS, GOOGLE Earth/Maps, open source software and data. By departmental permission involving a preferred academic level in meteorological studies, students can acquire participation. Students must attend a preliminary mini seminar sequence on the mathematics and physics of radar and signals for measurements. Note: not dependent on the “Radar & Satellite Meteorology” course; will exist way before taking that course, and will be a tremendous advantage towards such a future course. XV. Chosen course Labs recitation, projects and advancement for Numerical Weather Forecasting course ACTIVITY CAN ALSO BE DONE BEFORE COURSE XVI. Chosen course Labs recitation and advancement from Geological Oceanography, Oceanography Field Experience, and General Oceanography Repetion of labs. Advance field activites XVII. Chosen course Labs recitation and advancement for Marine Zooplankton & Phytoplankton Repetion of labs. Advance field activites. Can findings be indicators of environment health, or is it too short term? XVIII. Chemical Oceanography course labs recital and field experimentation - Chemical Oceanography Lab Manual of choice https://silo.tips/download/chem-108b-lab-chemical-reactivity-in-the-marine-environment - Johnstone, R. and Preston, M. (1993). NUTRIENT ANALYSIS IN TROPICAL MARINE WATERS: Practical guidance and safety notes for the performance of dissolved micronutrient analysis in sea water with particular reference to tropical waters. Intergovernmental Oceanographic Commission. UNESCO: https://www.jodc.go.jp/info/ioc_doc/Manual/096330eo.pdf -https://hahana.soest.hawaii.edu/hot/protocols/chap7.html Will perpetually carry out such described data gathering weekly with multiple samples areas in a particular chosen test region to test. A region of sea or ocean will be partitioned into “grids” where multiple samples will be taken for each grid. Regions of consideration are bays, inlets, etc. It’s imperative that data elements are extremely unique for recognition, referencing, backtracking, etc. Will try to evaluate physical models (involving measures such as salinity, Ph, CO2 count, temperature, viscosity, density, time) with data. Will employ regression models, time series, correlation computations and causality plausibility. Students may participate in this activity with completion of General Chemistry I & II regardless of the Chemical Oceanography course (but activity will not replace that course). In oceanography, image and competency are major means of attraction at any level, hence, encountering such labs early will be highly constructive. Activity likely be extended to incorporate spectroscopy and (phyto) plankton measurements. XIX. Ocean Modelling A. Will analyse the following article where one is free to compare with any encountered professional models Provost, C.L., Genco, M., & Lyard, F. (2013). Modelling and Predicting Tides Over the World Ocean. Quantitative Skill Assessment for Coastal Ocean Models, Volume 47 pages 175 – 201 Then pursue means of comparing data to modelling and possible simulations. Initial conditions and parameters must be determined; will acquire data from stations found in various seas and oceans. B. Is such modelling efficient compared to more modern models? Examples of modern models are Lagrangian Ocean Models (even though prior article may have some variational modelling). The following article gives an idea but may or may not be heavily dived into: Sebille, E. et al. (2018) Lagrangian Ocean Analysis: Fundamentals and Practices, Ocean Modelling 121 pages 49 -75 In such article, tools and codes are listed in a particular appendix, and can be found at the bottom of his post as well. One is concerned with making use of at least two of such platforms based on desired parameters and conditions to compare to results from first article and real data. XX. Oil spill treatments Open to Chemistry, Industrial Engineering and Geology constituents. Part I - dispersants (surface and underwater) The following text can be employed towards motivation and development of various oil spill dispersant experimentation: National Research Council. 2005. Oil Spill Dispersants: Efficacy and Effects. Washington, DC: The National Academics Press As well data and information from governing administrations of ambiances where corporate responsibility is highly subject to government in a western socialist manner. Journal articles can be of great assistance as well. In some cases, micro-environments are to be created. In other cases, ocean samples will be required. Chemistry modelling and analysis will be heavily enforced to a respectable level. There will be some lab sub-activities to confirm the behaviour of reactants, composition of samples, solubility, acidity, etc. Activity isn’t overall focused on experimentation on animalia, however, professional sources can be applied to identify or classify level of hazards, toxicity towards the ocean ecosystems and human life concerning the behaviour of specific dispersants. Duration for a respective dispersant is considered (consensus versus measured). The following can be replicated in a micro-environment: Ward, C. P. et al, Photochemical Oxidation of Oil Reduced the Effectiveness of Aerial Dispersants Applied in Response to the Deepwater Horizon Spill, Environ. Sci. Technol. Lett. 2018, 5, 226−231 Pat II - Sorbent materials Most often used in small spills or to remove the final traces of a large spill. Sorbent materials absorb oil in varying degrees, with some materials swelling more than 50 percent. The major concern with sorbent materials is that although they absorb the oil, the materials must be retrieved, which may prove extremely difficult, and could potentially make the situation worse. For each type of sorbent will identify the respective chemical structure that explains the absorption level behaviour; based on molecular structure one should prematurely have a range of absorption ability prediction, and whether there will be issues of buoyancy. In some cases, micro-environments are to be created. In other cases, ocean samples will be required. Chemistry modelling and analysis will be heavily enforced to a respectable level. -Natural organic sorbents: Examples of natural sorbents include peat moss, straw, hay, sawdust, feathers, pine shaving and even ground corncobs. Can soak up between 3-15 times their weight, but may sink as a result and tend to be difficult to collect; concur with investigation. -Natural inorganic sorbents: Clay, perlite, glass wool, sand or volcanic ash all can soak up 4 to 20 times their weight in oil; concur with investigation. These substances have similar concerns as natural organic sorbents, but are also inexpensive and available in large quantities, although they are not used on the water’s surface. -Synthetic sorbents: Similar to plastics and are designed to soak up liquids into their surface and can absorb liquids into their solid structures that causes the material to swell. Most synthetic sorbents can absorb up to 70 times their weight in oil; concur with investigation. Part III - Economically feasible gelling agents Some can possibly be synthesized in a lab or on stove top, or in bootlegging fashion, or some basic commercial items. Data and information from governing administrations of ambiances where corporate responsibility is highly subject to government in a western socialist manner. Journal articles can be of great assistance as well. In some cases, micro-environments are to be created. In other cases, ocean samples will be required. Chemistry modelling and analysis will be heavily enforced to a respectable level. There will be some lab sub-activities to confirm the behaviour of reactants, composition of samples, solubility, acidity, etc. Activity isn’t overall focused on experimentation on animalia, however, professional sources can be applied to identify or classify level of hazards, toxicity towards the ocean ecosystems and human life concerning the behaviour of specific gelling agents. Duration for a respective gelling agent is considered (consensus versus measured). Part IV - Hair booms Will develop prototypes. Treatment will be parallel to Part II. Part V - Water separation devices Unni, M. et al, Thermal Decomposition Synthesis of Iron Oxide Nanoparticles with Diminished Magnetic Dead Layer by Controlled Addition of Oxygen, ACS Nano 2017 11 (2), 2284-2303 Lesin, V. I., Levin, S. V. and Ivanov, E. V., Oxidative Cracking of Crude Oil by Hydrogen Peroxide in the Presence of Iron Oxide Nanoparticles. In: Petroleum Chemistry (2017) 57: 584; pages 584 - 588 Eric Butterman and Gareth McKinley, Oil and Water Don’t Mix Thanks to UV Light, ASME One can determine whether Activity C under Industrial Engineering is applicable and efficient to oil spill removal. With such mentioned, incorporation of a pump (with ability to run on both AC and DC), what stages in Activity C under Industrial Engineering would be omitted, and will the processing be economical? Will have a manual control valve in front of everything; basic logic applies to such. Consider proper sequencing with processes, and initial volume intake for processing. To only have spectroscopy test of multiple samples for end result. Automatic control for pumping and staging for the processes of interest considered; level conditions to also be instituted. All chambers and channels likely to be opaque and metal in the interest of safety. What are the effects of bulk oil accumulation in the system? How does one clean the chambers? Will iron oxide be an issue in later stages, and what process(s) can be instituted if such compound is to be isolated? Chemical properties of oil to consider: --density (homogeneous and the different mixtures) --boiling range (homogeneous and the different mixtures) --combustion temperature (homogeneous and the different mixtures) Chemical properties mainly concern the use of UV light. Consider the safe range of exposure to UV and the amount of power applied. Part VI – Oil booms This part will only have overview treatment because it’s quite straightforward. The buoyancy of oil in surface oil spills can be treated however. Part VII - Natural recovery In some areas, the environmental impact of cleaning up a spill could potentially outweigh the benefits of cleaning certain areas, especially if these places are highly dense with vegetation or relatively remote. Wave action, naturally occurring microorganisms, sunlight and natural water dispersion all contribute to break down oil leaked into the ocean. Although relying on natural forces and “doing nothing” may be hard for outsiders to swallow, in some cases it is the best environmental option. For many of the clean-up options available to crews, “natural recovery” is an important component. Pat VIII - Oil spills modelling Physics and mathematical modelling for oil spills. Some possible guides: Loncar, G., Paklar, G. B. and Janekovic, I., Numerical Modelling of Oil Spills in the Area of Kvarner and Rijeka Bay (The Northern Adriatic Sea), Hindawi Publishing Corporation Journal of Applied Mathematics Volume 2012, Article ID 497936, 20 pages Toz, A. C., Koseoglu, B. and Sakar, C. (2016). Numerical Modelling of Oil Spill in New York Bay, Archives of Environmental Protection Vol. 42 no. 4 pp. 22–31 Zafirakou, A. (2018). Oil Spill Dispersion Forecasting Models, Monitoring of Marine Pollution, Intechopen Software of concern are those mentioned in journal articles and of the following: << GEMSS + COSIM + GIFT >> << NOAA’s GNOME, ADIOS (Automated Data Inquiry for Oil Spills)>> In profession it’s customary to make use of multiple modelling software and compare findings; an attempt to span uncertainties in modelling and forecasting. The following journal article caters for subsurface spills: Lardner, R. and Zodiatis, G., Modelling Oil Plumes from Subsurface Spills, Marine Pollution Bulletin Volume 124, Issue 1, 15 November 2017, pages 94- 101 The following article for underwater treatment has experimental lab structure that can be replicated: Gao, F. et al, Hydrodynamics of Oil Jets without and with Dispersant: Experimental and Numerical Characterization, Applied Ocean Research 68 (2017) 77–90 XXI. Marine Biodiversity Field Investigation One of the best ways to retain anything in the field or study with meaningfulness is to be engaging with the environment without being a menace or catastrophe. Such is also humane and inviting, rather than cramming in class for momentary success; quick schemes burn out ability and interest very fast. Activity primarily serves towards the benefit of Oceangraphy constituents, and data conveyance towards public administration when conflicts of interest and exploitation are not at least moderately plausible. Data to any valuable international legitimate entity serves towards optimal prestige rather than appeasement to any CC or West Indies socio-political and socioeconomic noise and boundaries. Privacy of operations involving recognised oceanography constituents will be ruthlessly reinforced. Students must pass swimming and diving certification or exam sequence to participate in this activity; likely there will be waivers and what not. Conduct regulations will be noted regarding ecologically ethical procedures, holding of animalia, equipment, behaviour, transportation, punctuality, marine transportation vehicles, communications to external sources during commencement of operations, etc. Activities include both aquatic and nesting environments. Coral reefs will not be the only ambiance. Will try not to be intimidated by taxonomy. Planning and scheduling will be extremely hectic, and rain or shine it will be done; exemption will be storms categorized at a certain level. A small guide for structuring and organisation: Costello, M. J. et al. (2017) Methods for the Study of Marine Biodiversity. In: Walters, M., Scholes, R (eds). The GEO Handbook on Biodiversity Observation Networks. Springer, Cham; pp 129-163 Note: details in such text may be extremely condense, namely, tools, resources and logistics may be very wide range and intricate. Established models and designs of pre-existing recognised (academic and professional) marine associations and international marine professionals will be subject to “inquisition”. Experimental design will be emphasized, and the elements of statistical tests, will be considered in a variety of biological, planning and legal contexts; also, for students to consider the fundamental elements of developing their own sampling or experimental projects in an actual or simulated marine environment. Practical work involves use of structured thinking to be resolving spatial problems of sampling, computers and software, and will complement methods. Note: one may compare aquatic species data with long term temperature and long-term Ph and minerals data. NOTE: there will be a ruthless policy of research having no relation to capturing of living creatures for pets, collection, prize and reckless consumption. If any possibility of temporary captivation incorporates the well being of the organism regardless of any met emergencies. Can affect academic standing, enrolment standing and criminal record. XXII. Estimation of Relative Humidity Lawrence, M.G., 2005: The Relationship between Relative Humidity and the Dewpoint Temperature in Moist Air: A Simple Conversion and Applications. Bull. Amer. Meteor. Soc., 86, 225–234 From the above article, “There are several useful applications for the rule-of-thumb conversion in Eqs. (1) and (2). One that I have found to be helpful on various occasions is when maps of t and either td or RH (but not both) are available, and one is interested in knowing the approximate distribution of the other. In particular, weather forecast and analysis internet sites will often provide maps of the surface air t and td, but not RH. In this case, using the rule of thumb in (2) allows the distribution of RH (in regions with RH > 50%) to easily be estimated. With practice, one can place maps of t and td next to each other and directly read off an approximate map of the RH; as long as the main interest is knowing the basic range of the RH values (e.g., ~90% versus ~70%) distributed over a geographical region, the relatively small error (< 5%) is not critical.” One is to develop data investigation of such. Determine how accurate is such modelling for RH. One can also pursue creation of code that generates values for such with input of required data. As well, how will one develop a model for RH less than or equal to 50%? XXIII. Flying Rivers The ability to make use of professional and academic data form highly regarded and seclusive resources is key to becoming anything good in meteorology or climatology. Ability to use data and model atmospheric moisture will be a great accomplishment. Make use of time segments towards a respective year, where out of each year match the corresponding the duration. Such can be used as a measure for the effect of deforestation. Topics of interest: -Atmospheric moisture and cloud structure determined from SSM/I and global gridpoint analyses. [Special Sensor Microwave Imager]. One must understand the role or choice of microwave observation rather than radio and infrared observation. -Zveryaev, I. I. and Allan, R. P., Water Vapor Variability in the Tropics and its Links to Dynamics and Precipitation, Journal of Geophysical Research, Jul 2005 volume 110, D21112 -Okamoto, K. and Derber, J. C., Assimilation of SSM/I Radiances in the NCEP Global Data Assimilation System, Monthly Weather Review, Sep 2006, volume 134 2612 – 2631 Note: in prior journal article consider whether there’s any relevance for GEOS Systems -Ramos, A. M. et al, Atmospheric Rivers Moisture Transport from a Lagrangian Perspective, Earth Syst. Dynam. Discuss., 6, 2617–2643, 2015 NOTE: one must be concerned with the ability to distinguish between atmospheric moisture transport to land, and atmospheric moisture stemming from dense tropical forests. Includes Amazon rainforest, African rainforests and Asian rainforests. XXIV. Modelling the Carbon Cycle -Part A Many problems in the earth sciences involve understanding how mass is transferred among different geochemical reservoirs (e.g., Carbon transfer from biosphere to atmosphere). We concern ourselves with mass balances and how multiple systems evolve when there is mass flux both out of and into each system, and how those systems respond when the balance is upset. Atmospheric CO2 has the characteristic that it strongly absorbs infrared radiation given off from the earth’s surface. This energy is reradiated back to the earth, thus maintaining the surface temperature of the earth. An increase in CO2 may enhance this effect, thus causing general warming. Modelling the C cycle Using CAS or Excel simulations for conceptual understanding of how carbon is exchanged between the atmosphere, biosphere and shallow ocean, you will explore three important concepts: Steady state behavior Residence time Reaction of steady-state systems to a perturbation Such three above concerns unidirectional transport, bidirectional transport, transport among the three reservoirs. Will also pursue determination of the surface temperature effect of increasing CO2 in °C for a doubling of atmospheric CO2 or other dilation value. -Part B Primitive simulation: https://www.e-education.psu.edu/earth103/node/814 Will pursue comparing conceptual models from part A with prior simulation tool. Will pursue identifying convergence, and significance of discrepancies or deviations for particular values of the parameters. Linear approximations, series approximations, etc. can apply. -Part C Long-term Ocean-atmosphere-Sediment CArbon cycle Reservoir Model (LOSCAR): Zeebe, R. E. (2012). LOSCAR: Long-term Ocean-Atmosphere-Sediment CAarbon Cycle Reservoir Model v2.0.4, Geosci. Model Dev., 5, 149–166 Will compare models from Part A and Part B and try to determine where and how (drastic) deviations arise. Will also pursue acquisition of code for computational investigation. Further interest: Anav, A. et al (2013) Evaluating the Land and Ocean Components of the Global Cycle in the CMIP5 Earth System Models. J. Climate, 26, 6801–6843 PART D 1. Dynamical Integrated Climate-Economy model (DICE) Nordhaus, W. D. (1992). The DICE Model: Background and Structure of Dynamic Integrated Climate Economy Model of the Economics of Global Warming. Cowles Foundation Discussion Paper No. 1009 Nordhaus, W. D. and Sztorc , P. (2013). DICE 2013R: Introduction and User’s Manual: http://www.econ.yale.edu/~nordhaus/homepage/homepage/documents/DICE_Manual_100413r1.pdf Note: there are Excel and GAMS versions available. But before that, understanding the modelling is important. Will like to develop in a environment such as Mathematica and compare with Excel or GAMS. XXV. Integrated Assessment Models (IAM) ---Understanding purpose ---Modelling is important ---Differentiation between Aggregate Cost-Benefit models and Process-Based models. ---Will like to develop in a environment such as Mathematica and compare with any developed standing code (whether Excel, GAMS, Python, etc., etc.). Aggregate Cost-Benefit examples (ACBs) --> Our Goal is to have comparative assessment among the given ACB models 1. Dynamical Integrated Climate-Economy model (DICE) Nordhaus, W. D. (1992). The DICE Model: Background and Structure of Dynamic Integrated Climate Economy Model of the Economics of Global Warming. Cowles Foundation Discussion Paper No. 1009 Nordhaus, W. D. and Sztorc, P. (2013). DICE 2013R: Introduction and User’s Manual: http://www.econ.yale.edu/~nordhaus/homepage/homepage/documents/DICE_Manual_100413r1.pdf 2. Policy Analysis of the Greenhouse Effect (PAGE) Chris Hope, John Anderson, Paul Wenman, (1993), Policy analysis of the greenhouse effect: An application of the PAGE model, Energy Policy, Volume 21, Issue 3, Pages 327-338 3. Framework for Uncertainty, Negotiation and Distribution (FUND) http://www.fund-model.org/ https://www.fund-model.org/documentation/ https://www.fund-model.org/code/ Process-Based examples (PBs) --> Our Goal is to have comparative assessment among the given PB models 1. Integrated Model to Assess the Global Environment (IMAGE) Source A: https://www.pbl.nl/en/models/IMAGE%3A-Integrated-Model-Assess-Global-Environment Source B: https://models.pbl.nl/image/index.php/Welcome_to_IMAGE_3.0_Documentation 2. Global Change Analysis Model (GCAM) Source: http://www.globalchange.umd.edu/gcam/ ---Critique of IAMs Keppo, Ilkka Johannes et al (2021). Exploring the Possibility Space: Taking Stock of the Diverse Capabilities and Gaps in Integrated Assessment Models. Environmental Research Letters. 16 (5): 053006. ---Additionl Interests --> -The Model for Energy Supply Strategy Alternatives and their General Environmental Impact (MESSAGE) MESSAGE is usually also coupled with IIASA’s detailed Global Biosphere Management Model (GLOBIOM) to account for land-use and ecosystem changes. -The Integrated Model to Assess the Global Environment (IMAGE), developed by the Netherlands Environmental Assessment Agency (PBL). This is oriented towards environmental problems – with a detailed, grid-scale land-use module – and does not directly model the economy. It can be linked to numerous other modules to assess air pollution, flood risk and biodiversity loss, among others. -The Asia-Pacific Integrated Model (AIM), AIM is also sometimes referred to as AIM/CGE, reflecting the Computable General Equilibrium utilised in that version of the model. -The Global Change Assessment Model (GCAM) GCAM is known for its open-source code and for its focus on exploring uncertainty. -The Regional Model of Investments and Development (REMIND) REMIND has been coupled with the Model of Agricultural Production and its Impact on the Environment (MAgPIE) to incorporate land-use characteristics. -The World Induced Technical Change Hybrid (WITCH) model WITCH is often coupled with IIASA’s GLOBIOM for land-use. It has a particular focus on using game theory to explore co-operative versus non-cooperative climate action. WITCH also models technology cost reductions. -The Dynamic New Earth 21 Model (DNE21) -The General Equilibrium Model for Economy-Energy-Environment (GEM-E3) -IMACLIM from the Centre International de Recherche sur l’Environnement et le Développement (CIRED) in France, as well as researchers from around the world. -The Model for Evaluating Regional and Global Effects of GHG reductions policies (MERGE) -The New Econometric Model of Evaluation by Sectoral Interdependency and Supply NEMESIS -The TIMES Integrated Assessment Model (TIAM-UCL) -Prospective Outlook on Long-term Energy Systems (POLES) -WorldScan2 from the Netherlands Bureau for Economic Policy Analysis (CPB). XXVI. Guide to the Expression of Uncertainty in Measurement (GUM) and transcendence Thoroughly identify and analyse GUM. Our goal is to develop a logistical framework that’s universal with any experimentation in science. developing competence to important is quite important. Re-orchestrating some basic physics and chemistry labs students may encounter uncertainty treatment. Will like to extend to such particular labs with the analysis from part A. PART A Analysis from the following guides --> 1. Evaluation of measurement data — Guide to the expression of uncertainty in measurement — JCGM 100:2008 https://www.bipm.org/utils/common/documents/jcgm/JCGM_100_2008_E.pdf 2. Evaluation of measurement Data – Supplement to the “Guide to the Expression of Uncertainty in Measurement” – Propagation of Distributions using a Monte Carlo Method. JCGM.101: 2008 3. Barry N. Taylor and Chris E. Kuyatt (1994). guidelines for Evaluating and Expressing the Uncertainty of NIST Measurement Results. NIST Technical Note 1297. 4. https://isotc.iso.org/livelink/livelink/Open/8389141 5. Ferrero, A., & Salicone, S. (2018). A Comparison Between the Probabilistic and Possibilistic Approaches: The Importance of a Correct Metrological Information. IEEE Transactions on Instrumentation and Measurement, 67(3), 607-620. Other applications ---Krouwer, J. (2003). Critique of the Guide to the expression of Uncertainty in Measurement Method of Estimating and Reporting Uncertainty in Diagnostic Assays. Clinical Chemistry, 49(11), 1818-21. ---Velychko, O., & Gordiyenko, T. (2009). The use of Guide to the Expression of Uncertainty in Measurement for Uncertainty Management in National Greenhouse Gas Inventories. International Journal of Greenhouse Gas Control, 3(4), 514-517. XXVII. Measurement of Atmospheric Electricity PART A Bennett, A. J. and Harrison, R. G. (2007). A Simple Atmospheric Electrical Instrument for Educational Use. Adv. Geosci., 13, 11–15 Station developed must insulate equipment components that should not be exposed to moisture and precipitation. Data collection that can be geometrically displayed over time will be a huge triumph. It’s essential that one has precise coordinates of such developed station. Metrological satellite data providing atmospheric progression with applied time frame would be highly welcomed. As well accompanied by a weather station with chronological association (that also has cloud detection ability, say distance, altitude and velocity). Will also incorporate lightning strike data for the considered time frames. PART B Develop a station for the following --> Bennett, A. Measurement of Atmospheric Electricity During Different Meteorological Conditions. University of Reading: http://www.met.rdg.ac.uk/phdtheses/Measurement%20of%20Atmospheric%20Electricity%20During%20Different%20Meteorological%20Conditions.pdf Data collection that can be geometrically displayed over time will be a huge triumph. It’s essential that one has precise coordinates of such developed station. Metrological satellite data providing atmospheric progression with applied time frame would be highly welcomed. As well accompanied by a weather station with chronological association (that also has cloud detection ability, say distance, altitude and velocity). Will also incorporate lightning strike data for the considered time frames. XXVIII. Flume Experiments to pursue Murillo, Liana & Jokiel, Paul & Atkinson, Marlin. (2014). Alkalinity to Calcium flux Ratios for Corals and Coral Reef Communities: Variances Between Isolated and Community Conditions. PeerJ. 2. e249. Note: not restricted to prior journal article. XXIX. Physical Oceanography lab experiments The articles following can serve as strong guides for physical oceanography lab experiments. Hopefully, materials, resources and skills are quite economic. Journal of Geophysical Research: Oceans. Volume 96, Issue C7 --> Trizna, D. B. et al (1991). Laboratory Studies of Radar Sea Spikes at Low Grazing Angles. Pages 12529 – 12537 Buzyna, G., Kung, R. and Pfeffer, R. L. (1991). Response of Baroclinic Waves to Nonuniform Thermal Forcing at the Lower Boundary. Pages 12519 – 12528 Gibson, Carl H. (1991). Laboratory, Numerical, and Oceanic Fossil Turbulence in Rotating and Stratified Flows. Pages 12549 – 12566 Noh, Y. and Fernando, H. J. S. (1991). Gravity Current Propagation along an Incline in the Presence of Boundary Mixing. Pages 12586 – 12592 Helfrich, Karl R. and Battisti, Thomas M. (1991). Experiments on Baroclinic Vortex Shedding from Hydrothermal Plumes. Pages 12511 – 12518 Taylor, John. (1991). Laboratory Experiments on the Formation of Salt Fingers after the Decay of Turbulence. Pages 12497 – 12510 Davies, Peter A. (1991). Generation and Spreading of a Turbulent Mixed Layer in a Rotating, Stratified Fluid. Pages 12567 – 12585 D'Hieres, G. Chabert, Didelle, H. and Obaton, D. (1991). A Laboratory Study of Surface Boundary Currents: Application to the Algerian Current. Pages 12539 - 12548 XXX. Scientific Diver Training Concerns intelligence and comprehension of scientific diving activities. Major areas are Goals Methods Tools Logistics Diving equipment (identification and operation) Safety and field rules “Walkthroughs” Trial runs In addition to the predominant pursuits of scientific diving, will have field investigation for characteritics of rapid seafloor descents. Likely there will be multiple w.r.t. distance. Interest in the ecology or biodiversity at such areas. NOTE: swimming certification must be confirmed before diver training. XXXI. Coral Microfragmentation & alternative methods Experimental Comparative Analysis of methods for coral reef development or restoration. Will be making use of well constructed flumes and/or transparentchambers that are accessible towards data gathering. Will stress much data analysis, hence, advance data collection and photography use will be crucial. Microfragmentation will not be the only method, rather to have comparative assessmnet of growth methods; controls may be coral without applied methods, temperature, minerals concentration, CO2 concentration, and acidity; necessary to identify ideal environmental conditions for optimal growth. The following can be helpful guides --> --Forsman, Z. H., Page, C. A., Toonen, R. J., & Vaughan, D. (2015). Growing Coral Larger and Faster: Micro-Colony-Fusion as a Strategy for Accelerating Coral Cover. PeerJ, 3, e1313. --Christopher A. Page, Erinn M. Muller, David E. Vaughan, (2018) Microfragmenting for the Successful Restoration of Slow Growing Massive Corals, Ecological Engineering, Volume 123, Pages 86-94 --Boström-Einarsson L, Ceccarelli D, Babcock R.C., Bayraktarov E, Cook N, Harrison P, Hein M, Shaver E, Smith A, Stewart-Sinclair P.J, Vardi T, McLeod I.M. (2018). Coral Restoration in a Changing World -A global Synthesis of Methods and Techniques, Report to the National Environmental Science Program. Reef and Rainforest Research Centre Ltd, Cairns (63pp.): https://nesptropical.edu.au/wp-content/uploads/2019/02/NESP-TWQ-Project-4.3-Technical-Report-1.pdf XXXII. Design and Construction of Artificial Reefs PART A (theory and empirical evidence for the formation of coral reefs) Will acquire resources from the field of biological oceanography to draw conclusions. From required environmental conditions to biological catalysts, to intermediate development (processes, phases, biological agents, environmental conditions), to a mature and self-sustainable ecosystem. Will be extensive and tangible to field development. PART B (coral reef construction) NOTE: will be heavily dependent on part A NOTE: chosen sites must be environmentally stable and at depths that will not be disturbed easily by vessels and explorers. Some initial preliminary phases for determination of best sites: --Mapping (Google Earth and Google Maps) for preliminary observation of surroundings, geography, coordinates (2-d scale), terrain, geographical scale, accessibility, etc. --Climate exposure and weather profile, environmental and ecology intelligence. Assumptions or preliminary hypotheses. --Field reconnaissance of chosen sites --Characterisation of currents and sea flow --Diving/underwater reconnaissance May take multiple sessions --Oceanographic Instrumentation (field activities) May be tricky. Would like data that robustly characterises respective environment for typical conditions, night and day. --Making a Depth Map-Bathymetric data Next, we take several geophysical surveys of the area. Creating a bathymetric (depth) map of the site and imaging the subsurface sediment at the bottom of the pond. To create a bathymetric map, we use a HydroLite. The HydroLite combines GPS technology with echo sound to create a depth map of the pond. We use this map to help decide where to core. It is usually best to core in the deepest area of the pond, because this is where the most sediment accumulates. --Making a Subsurface Map-Geophysical Data To image the subsurface sediment at the bottom of the pond, we use either Ground Penetrating Radar (GPR) or Chirp Sonar. To image the subsurface sediment at the bottom of the pond, we use either Ground Penetrating Radar (GPR) or Chirp Sonar. Image creation of the subsurface. Design constituents: Aesthetics concern a design that’s pleasant along the seafloor distribution. Will like to construct environments that emanate colouring lighter than the general seawater colour environment, but designs will neither resemble a junk yard, nor dump, nor ship graveyard. Constituents for construction: Should not be generally be a contributor of acidity elevation. Materials of consideration --> Rocks Cinder blocks Wood Limestone Steel with geometries of conic sections, spheroidal, ellipsoid, etc. Oyster shells or clam shells Coral Implantation --> May implant lab grown specimens into environments. NOTE: activity will have two distinct field aspects in function 1. Monitoring and biodiversity field investigation for past constructed reefs 2. New projects at various other sites XXVII. Meteotsunamis 1. Typical weather that’s responsible 2. Dynamics in meteorological measures 3. Identifying geophysical properties of ideal environments 4. Assisting guides (order given doesn’t specify importance): Monserrat, S.; Vilibić, I.; Rabinovich, A. B. (2006). Meteotsunamis: Atmospherically Induced Destructive Ocean Waves in the Tsunami Frequency Band. Natural Hazards and Earth System Sciences. 6 (6): 1035–1051. Bechle, A., Wu, C., Kristovich, D. et al. Meteotsunamis in the Laurentian Great Lakes. Sci Rep 6, 37832 (2016) Shi, L., Olabarrieta, M., Nolan, D.S. et al. Tropical cyclone rainbands can trigger meteotsunamis. Nat Commun 11, 678 (2020) Williams, D. A., Horsburgh, K. J., Schultz, D. M., & Hughes, C. W. (2019). Examination of Generation Mechanisms for an English Channel Meteotsunami: Combining Observations and Modeling, Journal of Physical Oceanography, 49(1), 103-120 Dusek, G., DiVeglio, C., Licate, L., Heilman, L., Kirk, K., Paternostro, C., & Miller, A. (2019). A Meteotsunami Climatology along the U.S. East Coast, Bulletin of the American Meteorological Society, 100(7), 1329-1345 Rabinovich, A.B. Twenty-Seven Years of Progress in the Science of Meteorological Tsunamis Following the 1992 Daytona Beach Event. Pure Appl. Geophys. 177, 1193–1230 (2020) Bechle, A. J., Kristovich, D. A. R. and Wu, C. H. (2015). Meteotsunami Occurrences and Causes in Lake Michigan. JGR Oceans, volum 120, issue 12, pages 8422 – 8438 Geist, E.L., ten Brink, U.S. & Gove, M. A framework for the probabilistic analysis of meteotsunamis. Nat Hazards 74, 123–142 (2014) Dusek, G., DiVeglio, C., Licate, L., Heilman, L., Kirk, K., Paternostro, C., & Miller, A. (2019). A Meteotsunami Climatology along the U.S. East Coast, Bulletin of the American Meteorological Society, 100(7), 1329-1345 5. To identify or design analytical models to characterise the phenomenon. CFD may or may not be applied. 6. Analysis of chronological radar imaging of culprits 7. Collecting meteorological data of culprits (pre, during event and after) Analysis to develop typical characteristics 8. Challenge: pursuit of a transparent microenvironment to replicate phenomenon Competent data gathering for trigger conditions and evolution Is the data gathered at such scale consistent with the real environments? XXXIII. Bayesian Decision Theory for Disaster Management Hopefully can be geared towards meteorology and oceanography interests -Structure of Bayesian Modelling and Evaluation -The following articles serve as robust structure. Will be making use of ambiance data of interest and will pursue means of determining accuracy: Simpson, M. et al. Decision Analysis for Management of Natural Hazards. Annual Review of Environment and Resources 2016 41:1, 489-516 Guides to develop models and evaluation for places of interest: Economou, T., Stephenson, D., Rougier, J., Neal, R., & Mylne, K. (2016). On the Use of Bayesian Decision Theory for Issuing Natural Hazard Warnings. Proceedings. Mathematical, Physical, and Engineering Sciences, 472(2194), 20160295. Economou, T.; Stephenson, D. B.; Rougier, J. C.; Neal, R. A.; Mylne, K. R. (2016): Data and Loss Function Tool On the Use of Bayesian Decision Theory for Issuing Natural Hazard Warnings. The Royal Society. S Taskin & E J Lodree, Jr (2011) A Bayesian Decision Model with Hurricane Forecast Updates for Emergency Supplies Inventory Management, Journal of the Operational Research Society, 62:6, 1098-1108

XXXIV. Phytoplankton Culturing Techniques NOTE: must sucessfully complete “Marine Zooplankton & Phytoplankton” course as prerequisite. Will try to expand activity 3-4 weeks at most. Outline--: Welcome and Introductions: Safety Practices & Training Domestic issues (food breaks, bathrooms, accommodation, emergency drills). Introductions; What do you want to get out of the course (survey summary) Manual Internet access, course resources on website An introduction to and tour of Laboratory & resources Laboratory: Student Stations & prep for the week ahead About alcohol burners and other material at each student station Make pipette mouth pieces Drawing micropipettes from Pasteur pipettes & capillaries Sterile technique exercise Pipetting into organic media Testing benches, work areas with agar plate Testing Pipettemen for utility and sterility Laboratory Isolation techniques – picking cells (fresh sample and L1 for this exercise) – set up microtiter plates for isolation. Carm’s ‘cell sucker’ system Microcapillary cell picking Dilution-Extinction isolation Set up plates for culturing Discuss axenic vs. bacterized (xenotobiotic) cultures Bacteria freeing, pros and cons Laboratory: Principles of Flow Cytometry, Cell Sorting and discussion of different counting methods Monitoring Algal Growth Hemocytometer Fluorometer Flow Cytometry Growth curves Half Day Cruise Sampling Trip: FlowCam in the field GoFlo (bottle) casts to profile and collect phytoplankton Plankton tows to collect phytoplankton Environmental measurements (temp/salinity) via CTD Laboratory: FlowCam and analysis of sampling trip samples. Picking cells from cruise collections for culture isolation and genetic identification Laboratory Demonstration: Continue with isolations Identification of field isolates via microscopy Lysis of single-cell isolates for later whole genomic amplification (WGA) & Polymerase Chain Rreaction (PCR) Whole genome amplification setup History of Seawater Media Early Attempts of media making – Erd schriber The Provosoli & Guillard eras Defined media – Enriched sea water media Preparing sea water for media Filtration – filter types and effective pore sizes Sterilization – methods Processing glassware Matter of salinity Routine Media for maintaining numerous cultures Formats for cultivation Batch modes Semi-continuous Turbidostats Chemostats Laboratory – Making culture medium Laboratory – Impact of differential media enrichments – Microscopy Cell picking/isolations from enrichments Laboratory – Making culture medium Laboratory Demo – Impact of differential media enrichments – Microscopy Lab: Taxonomy How to use ‘Identifying Marine Phytoplankton’ Book and discussion on Morphological Taxonomy. Microscopic analysis of NCMA strains from the book (see separate handout). PCR setup of WGAs with 18S rRNA gene primers Circadian rhythms lecture and bioluminescence demonstration Laboratory: Collecting & Counting Samples How to collect samples Grabs, net tows, & pumps Other methods On site data needed Temperature & salinity Other variables How to store samples until arriving to the laboratory How to ship samples to offsite lab To preserve or not preserve – that is the question! Methods – Chambers – Sedwick Rafter Cells 1 ml Palmer Maloney 0.1 ml Haemocytometers Settling methods Movable settling chambers Fixed chambers Care and cleaning Laboratory: Culturing continued Other methods – Antibiotic drop cleaning Antibiotic wash methods Agar plate techniques Phototaxis Gravity separation Culture accounting techniques Assigning tentative names Culture codes, keeping records Sharing cultures – Purification Methods Droop Method Antibiotic plates Antibiotic suite on bucket of seawater Laboratory: Transferring cultures Working with agar plates, transferring colonies to growth medium. Streaking out stocks on agar plates/slants Laboratory: Cryopreservation (group A) Laboratory: PCR isolation for ID (group B) Laboratory: Cryopreservation (group B) Laboratory: PCR isolation for ID (group A) Data Analysis: Phytoplankton Molecular Taxonomy & DNA-based identifications BLAST sequences from single-cell isolates Mass Culture Laboratory: SeaCAP bag setup Photobioreactors in greenhouse Laboratory: Harvesting large volumes Centrifuge TFF Spray drying Wrap up: Finish mass culture demonstrations and related harvesting activities Packing up algal isolates for shipment/transport Final Q&A session XXXVI. Experimental Algal Blooms System Development Involves process concept, analysis of tools and their operation; network structure for data acquisition. Total logistics. Calibrations if needed. Development and testing, likely in controlled environment (lab construction with variables study). Note: iron diffusion schedules may also be required. Analysis of data and models. Multi-day, continuous records (e.g., every 15 minutes to hourly) Deploying sondes (water probes) to collect real-time data and creating hyperspectral images and high-resolution spatial maps from the data collected to paint a more accurate picture of the distribution of cyanobacteria and nutrients in the water. Turbidity (murkiness) In-situ (in-water) sensors for frequent measurements of nitrate and dissolved organic matter (DOM) — “food” that stimulates cyanobacteria growth — hold great promise for characterising the chemical variations in waterbodies. Fluorometer (light-measuring) sensors to measure the fluorescence produced by certain “algae” or cyanobacteria indicators: Chlorophyll-a: a pigment concentration that is a representative measure of the amount of “algae” (both green and blue-green) in the water Phycocyanin: a pigment concentrations that is a better representation of the amount of cyanobacteria biomass (cell concentration) Dissolved organic matter (DOM): composition of DOM can be used to characterize cyanobacteria growth potential in the water and help identify total organic carbon concentrations, another fundamental building block for cyanobacteria growth. Water samples to compare to the fluorescence measurements Temperature, pH, and oxidation-reduction potential (a relative measure of decomposition) High-resolution spatial maps of the data to evaluate the spatial extent of the parameters measured Concurrent, high-resolution satellite imagery to compare remote observations with onsite spatial nitrate and algal data Note: will be acquiring and analysing high volumes of data for different regions. Then, will make use of machine learning tools XXXVII. Integrated Global System Modelling (IGSM) Framework Integrated Global System Modelling (IGSM) Framework IGSM = EPPA + MESM A collaboration activity between Economics constituents and constituents of Meteorology and Oceanography. Economics constituents will be responsible for development with the following: Human System Model --> Economic Projection and Policy Analysis (EPPA) Meteorology & Oceanography constituents will be responsible for development with the following: Earth System Model: The MIT Earth System Model (MESM) ECONOMICS --> Human System Model: Economic Projection and Policy Analysis (EPPA) The EPPA simulates the evolution of economic, demographic, trade and technological processes involved in activities that affect the environment. https://globalchange.mit.edu/research/research-tools/human-system-model We use it to investigate the economic implications of a wide range of phenomena https://globalchange.mit.edu/research/research-tools/human-system-model/download Supporting literature: https://globalchange.mit.edu/research/research-tools/eppa Chen, Y. et al (2016): Long-term Economic Modelling for Climate Change Assessment. Economic Modelling, 52(Part B): 867–883 Morris, J. et al (2019): Representing the Costs of Low-Carbon Power Generation in Multi-region Multi-sector Energy-Economic Models. International Journal of Greenhouse Gas Control, 87, 170-187 Paltsev, S. et al (2005): The MIT Emissions Prediction and Policy Analysis (EPPA) Model: Version 4. Joint Program Report Series Report 125, 72 pages METEOROLOGY & OCEANOGRAPHY --> Earth System Model: The MIT Earth System Model (MESM) The MESM comprises coupled sub-models of physical, dynamical and chemical processes in the atmosphere, land and freshwater systems, ocean and cryosphere. It is used to calculate global and regional environmental responses to human activity and natural processes. The MESM draws on scientific knowledge combined with land, air, water and space-based measurements, and accounts for uncertainties about how the Earth system functions. https://globalchange.mit.edu/media/mesm-software-license-form Supporting literature: Sokolov, A. et al (2018). Description and Evaluation of the MIT Earth System Model. Journal of Advances in Modelling Earth Systems, Volume 10, Issue 8, pp 1759 – 1789 Libardoni, A. G. et al (2018): Baseline Evaluation of the Impact of Updates to the MIT Earth System Model on its Model Parameter Estimates. Geoscientific Model Development, 11(8): 3313-3325 RISK ANALYSIS --> To quantify risks at the global scale requires large ensembles of model simulations, and thus a numerically efficient model. For this purpose we use a version of the IGSM framework with a two-dimensional atmosphere and ocean. For regional and other high-resolution studies, the ocean, atmosphere and land systems are resolved in three dimensions. The IGSM framework is designed to address a wide range of quantifiable, policy-relevant questions that involve the integration of natural and social sciences, such as: What methods can be used to quantify global and regional risks of environmental change? What are the advantages and risks of waiting for better scientific understanding of such change? How does uncertainty about future climate or climate policy affect near-term investment decision? Supporting literature: Morris,J., J. Reilly, S. Paltsev and A. Sokolov (2021): Representing socio-economic uncertainty in human system models. Joint Program Report Series Report 347, February, 23 p. Morris, J., et al (2021): A consistent framework for uncertainty in coupled human-Earth system models. Joint Program Report Series Report 349 Schlosser, C.A., et al (2012): Quantifying the Likelihood of Regional Climate Change: A Hybridized Approach. Journal of Climate, 26(10): 3394-3414 XXXVIII. NICAM Intelligence and Research Replication -- Satoh , M. et al (2008). Nonhydrostatic Icosahedral Atmospheric Model (NICAM) for Global Cloud Resolving Simulations. Journal of Computational Physics, Volume 227, Issue 7, Pages 3486-3514 -- Tomita, J. (2008). New Microphysical Schemes with Five and Six Categories by Diagnostic Generation of Cloud Ice. Journal of the Meteorological Society of Japan. Ser. II. Volume 86A, pages 121 – 142 NOTE: a challenge may be trying to compare various simulated scenarios to radio satellite data. XXXIX. Numerical Models for Tsunami Simulation International Atomic Energy Agency. (2022). Benchmark Analysis of Numerical Models for Tsunami Simulation, TECDOC Series, IAEA, Vienna (will generalise to various habitats and surroundings) XXXX. Immersion with the International Monitoring System (IMS) and Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) 1. History of IMS 2. Analysis of the components of IMS 3. History of CTBT 4. Idea of its CTBTO applications Mialle, P. et al (2018). CTBTO International Monitoring System Data for Science and the virtual Data Exploitation Centre (vDEC). American Geophysical Union, Fall Meeting 2018 5. To concern ourselves with the means of event recognition from data Nuclear explosive tests Volcanic eruptions, earthquakes Meteorological events Tools and techniques will be much detailed and implemented Data will stem from the following source: virtual Data Exploitation Centre (vDEC) https://www.ctbto.org/specials/vdec/ Naturally, identifying past events and identifying data in the time neighbourhood of occurrence for each event. 6. Designing and construction of infrasound systems to implement (with appropriate arrays). A possible guide for such (but our interest is weather phenomenon): Stubbs, C. et al (2005). Tactical Infrasound. The MITRE Corporation JASON Programme Office Report # JSR-03-520 https://irp.fas.org/agency/dod/jason/infrasound.pdf Additional Literature for possible general knowledge: Daniels, F. B. (1962). Generation of Infrasound by Ocean Waves" J. Acoust. Soc. Amer., 34 Georges, T. M. (1973). Infrasound from Convective Storms: Examining the Evidence, Rev. Geophys. Space Phys., 11, pp 571-593 Donn, W.L. and D. Rind (1971). Natural infrasound as an Atmospheric Prob, Geophys J. Roy. Astro. Soc., 26, pp 111-133 May, P. T., K. P. Moran, and R. G. Strauch. (1989). The Accuracy of RASS Temperature Measurements" J. Appl. Meteorology, pp 1329-1335 Bedard, A.J. Jr and M. J. Sanders (1978). Thunderstorm-Related Wind Shear Detected at Dulles International Airport Using a Doppler Acoustic/Microwave Radar, a Monostatic Acoustic Sounder and Arrays of Surface Sensors. Proc. Conf. on Weather Forecasting and Analysis and Aviation Meteorology, pages 347-352 Bedard, A. J. Jr, and R. Craig (1998). Infrasonic detection of atmospheric turbulence in the vicinity of mountains" 8th Conference on Mountain Meteorology, Flagstaff, Az, 3-7 August 1998. Bedard, A. J. Jr. " Infrasonic detection of severe weather" Proc. 19th Conf. on Severe Local Storms Minneapolis, Minn., 14-18 Sept.1998. Bedard, A. J. Jr. and R. Bloemker "Detection of space Debris and Meteor Impacts using Atmospheric Infrasound" Proc. Annual Conf. SPIE, The International Soc. for Optical Engineering, 3116, pp177-191, July 1997. Wilson, C. R. (1969). Auroral Infrasonic Waves. J. Geophys. Res., 74, pp1812-1836, 1969. McKenna, M. H. et al (2021). Remote Structural Infrasound: Case Studies of Real-Time Infrastructure System Monitoring. J. Infrastruct. Syst., 27(3): 04021021 Cook, R.K. and A.J. Bedard Jr "On the measurement of Infrasound" Q.J. Roy. Astro. Soc. 67, pp 5-11, 1972. XXXX. Air Pollution Chemistry & Physics Lab Recitals XXXXI. Advance Aerosol Physics & Chemistry Lab Recitals XXXXII. Coastal Forecasts PART A 1.Guide to Wave Analysis and Forecasting. World Meteorological Organisation 2018, WMO-No. 702 The given above guide will be used for development. The above guide also contains a web-based Dynamic part, describing operational wave models, also available on the WMO website at https://community.wmo.int/activity-areas/Marine/Pubs/WMO702DynamicPart Expected will be applying real incoming meteorological and oceanographical data to develop future forecast. Such implies that your findings will be compared to multiple professional sources. 2.WAVEWATCH III < https://polar.ncep.noaa.gov/waves/wavewatch/ > -Investigate the use(s) of such model. Model description and construction logistics. Then there’s necessary task to implement for ambiances of interest. -Other interest pursuits where ambiance of interest is the concern Abdolali A., Roland, A., Van Der Westhuysen, A., Meixner, J. et al (2020), Large-scale Hurricane Modeling Using Domain Decomposition Parallelization and Implicit Scheme Implemented in WAVEWATCH III Wave Model, Coastal Engineering, 157, 103656, Abdolali, A., van der Westhuysen, A., Ma, Z. et al. (2021). Evaluating the accuracy and Uncertainty of Atmospheric and Wave Model Hindcasts During Severe Events Using Model Ensembles. Ocean Dynamics 71, 217–235 PART B For rip current hazard monitoring knowing shores where occurrences are prevalent is important. As well, profiling of the environment or topographic features that encourage rip currents are expected. Expected will be professional observational data collection that is sustainable and credible for many years past, the present and future continuity. Locate resources for such in your ambiance and analyse data along with respective topographic profile. Dusek, G. and H. Seim, H. (2013). Rip Current Intensity Estimates from Lifeguard Observations, Journal of Coastal Research 29(3), 505-518 Dusek, G. and Seim, H. (2013). A Probabilistic Rip Current Forecast Model. Journal of Coastal Research 29(4), 909 - 925 For the prior two articles expected will be applying real incoming meteorological and oceanographical data to develop future forecast. Such implies that your findings will be compared to multiple professional sources. Moulton, M., Dusek, G., Elgar, S., & Raubenheimer, B. (2017). Comparison of Rip Current Hazard Likelihood Forecasts with Observed Rip Current Speeds, Weather and Forecasting, 32(4), 1659-1666. Expected will be applying real incoming meteorological and oceanographical data to develop future forecast. Such implies that your findings will be compared to multiple professional sources.

XXXXIII. SENSITIVITY ANALYSIS: Variogram Analysis of Response surfaces (VARS).....COMING SOON NOTE: for oceanography and meteorology students they are permitted to participate in spectroscopy activities and separation methods. They are generally prohibited from quantum chemistry-based activities and molecular modelling. SOME MORE POWERFUL ATMOSPHERIC-OCEANIC TOOLS One should not treat the following as just alternatives to each other, rather also prowess of comparative assessment or various “second opinions”: 1. ROMS (Regional Ocean Modelling System) https://www.myroms.org There are also packages and documentation 2. WRF (Weather Research and Forecast Model) www2.mmm.ucar.edu If link doesn’t work find download site via search engine. 3. CESM2 4. SWAN (Simulating Waves Nearshore) swanmodel.sourceforge.net 5. ECMWF software and packages MICROC5 CMIP5 6. General CMIP5 models and competing alternatives 7. Nucleus for European Modelling of the Ocean (with OASIS and XIOS) 8. Ariane Ariane is a numerical diagnostic tool developed at the Laboratoire de Physique des Océans (Brest, France) 9. TRACMASS 10. The Connectivity Modeling System (CMS) 11. LIGHT within MPAS-O 12. NEMO (the Nucleus for European Modelling of the Ocean) model 13. MITgcm (Massachusetts Institute of Technology General Circulation model) 14. HYCOM (the HYbrid Coordinate Ocean Model) 15. Octopus Octopus is an offline particle tracking code first written to conduct offline particle simulation using the Southern Ocean State Estimation 16. The Community Climate System Model (CCSM) CCSM 3.0 or CCSM 4.0 or higher Global RTOFS Data Access (+ Fukushima Tracers + Fukushima Surface Plume Study) 17. NOAA WAVEWATCH III 18. Possible interest in understanding the following data formats and how to incorporate them for various interests with computational tools applied: Data Format (NETCDF) and Open-source Project for a Network Data Access Protocol (OPENDAP). Note: one will not necessarily be confined to such two formats. 19. REMO 20. GEOS Systems (GEOS-5 Access at least) 21. NASA GISS GCM 22. Earth systems (CLM5) 23. Coupled-Ocean-Atmosphere-Wave-Sediment Transport (COAWST) Modelling System 24. GFDL-ESM 4.1 NOTE: UN IPCC data may prove invaluable for research

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GEOLOGY

GEOLOGY It may be in the best interest for Geology students that the General Education appeasement courses be fulfilled during the “summer” and “winter" sessions, or done in junior and senior years of high school. Advancing standing upon matriculation will be a great advantage. Curriculum: This pursuit demands advance standing in mathematics and science; advance completion of general education appeasement courses would also greatly help. Most of the courses will involve field work and labs. Such are characteristic of any good Geology programme. Concerns that can likely have cumulative academic consequences and legal ramifications: Littering Low temperature high temperature combustible substances Illegal and unregulated fires Pesticides unsanctioned with environmental protection Toxic substances Substances with absurd Ph levels (high or low) that may be damaging to environment Levels of exhaust emissions from vehicles High volume audio and video Harassing or capturing animals Unsanctioned venturing, or ditching officially recognised groups Releasing animals unnatural to ambiance ecosystem NOTE: first aid kits may be expected on all field activities. --Core Courses: Scientific Writing I & II, General Physics I & II, General Chemistry I & II --Mandatory Courses: Calculus I-III, Ordinary Differential Equations, Numerical Analysis, Probability & Statistics B, Mathematical Statistics, Data Programming with Mathematica (check CS post) --Required Components: Culture --> Physical Geology, Historical Geology, Invertebrate Paleontology, Geomorphology, Geological Field Methods Chemical --> Geochemistry, Mineralogy Characterisation --> Igneous & Metamorphic Petrology; Sedimentation & Stratigraphy Physical --> Global Geophysics; Hydrology; Structural Geology; Plate Tectonics; Field Geology; Mathematical Physics for Geophysics; Seismology Data Analysis --> Geographical Information Systems Mandatory Option Tracks --> Option 1 (Chemical): Analytical Chemistry (check CHEM); Analytical Geochemistry; Geochemical Modelling; Environmental Geochemistry; Trace Element Geochemistry Option 2 (Physical): Potential Field Methods in Exploration Geophysics; Fluid Mechanics (check physics); Geodynamics; Computational Geomechanics; Signal Analysis NOTE: curriculum concerns mathematicians, general physicists, chemists and archaeologist NOT taking away jobs from geologists NOR dominating the field expertise of a geologists. NOTE: For mathematics courses refer to the Computational Finance post; for physics courses refer to the Physics post. Any activity under Physics refer to the physics post. For any Engineering activity that’s relevant, refer to the engineering post. The described tools in the following link can prove to be invaluable long term: https://reference.wolfram.com/language/guide/EarthSciencesDataAndComputation.html Remember, for such Wolfram language functions there’s often numerous different parameters to apply. As well, such Wolfram functions can be subjugated by other functions towards massive projects or interests. NOTE: the following text can be applicable of labs and field activities: Millard, S. P. (2013). EnvStats: An R Package for Environmental Statistics, Springer Course Descriptions: Historical geology Historical Geology is a foundational course for the major. Many of your later courses— Sedimentology & Stratigraphy, Structural Geology, Geochemistry, Field Geology, etc. —will draw upon methods, concepts, and terms derived from this class. If you hope to earn a good grade for the class, and to retain the information for future classes, make sure that you keep up with the readings (from the textbooks and the online lecture notes), and make sure you that you understand the concepts and information. If you are having problems, feel free to ask questions. As part of the nature of the course, there will be a lot of memorization (less than a foreign language class, but more than that found in more mathematically-oriented introductory science classes). This will include lots of anatomical, geological, and paleontological terms, as well as evolutionary and temporal relationships. If you have difficulty memorizing, this may not be the class for you. Also, if there are words or concepts with which you are not familiar, feel free to ask(in class, after class, over email, etc.) for an explanation or clarification. By the end of the semester, every student should be able to: --Identify the major techniques used by geologists to assess the paleoenvironments and sequence of events found in the rock record --Recognise the sequence of and interrelationships between major events in the history of the Earth, its surface, and its life forms --Properly classify different types of sedimentary rocks & structures and major groups of fossilizing organisms from hand samples --Correctly interpret geological cross-sections, fence-diagrams & other stratigraphic charts, and geologic maps Typical Text: Stanley, S. M. & Luczaj, J. A. (2015). Earth System History, W.H. Freeman & Co. Gastaldo, R. A., Savdra, C. E. & Lewis, R. D. (2006). Deciphering Earth History: Exercises in Historical Geology. , CPC Publishing) Tools --> A 10x hand lens A coloured pencil set Ruler/straight edge will be helpful in some of the labs Access to a scanner/photocopier (to make hardcopies of the labs to turn in) Loaded staplers Quizzes (15%) --> Weekly quizzes will be given either in class or in lab (depending on time available that week), but which emphasizes the material from the lectures. These will typically be multiple choice, fill-in-the-blank, matching, or true/false. The lowest two (2) quizzes will automatically be dropped: this is how missed quizzes will be accommodated. 2 Midterm Exams (20% each) --> Two pen-and-paper exams Final Exam (20%) --> A pen-and-paper final exam during the regularly scheduled exam season. Labs (25%) --> Essentially every week there will be a lab. Labs are due the week after they are assigned, allowing students time to examine specimens over the course of the week if they wish. Lab Policies --> -The point of the lab is to hone your skills as an observer and to teach you the methods of the field. It is vital that you actually examine the specimens yourselves so that you can discern the various features and attributes of the rocks and fossils. -Please read the introductory material in the lab manual by the time we meet in lab. -Labs are due the next lab meeting (1 week later). If they are turned in by the next class time after that there will be a 10% grade reduction; further reduction as days go by. Labs won’t be accepted for a grade later than 1 week overdue (barring legitimate extenuating circumstances.) -Lab specimens will remain out for your examination through the end of the week and on the following Monday. However, typically to replace some lab specimens sometime on throughout. -You are encouraged to collaborate and interact with each other and with Dr. Holtz while working on the labs. However, all work you turn in must be your own. 12 -DON’T be a specimen hog! Make sure that others get adequate access to the hand samples. -ALWAYS return specimens to their appropriate boxes. -We have limited samples, so please be careful with them. Doubly so with the fossils!! -Use the dilute HCl wisely: Use small drops, only leave it on long enough to validate whether there is effervescence or not; and wipe it up afterwards. Leaving acid on the hand samples will allow the reaction to run its course and leave a reaction rind on the rock. This will mislead students in the future) In general, only use acid on fresh surfaces In general, don’t drop acid on the fossils -If you are having problems, don’t be shy; ask for help! Course Outline --> WEEK 1 -- Introduction: It’s About Time Every Rock is a Record of History: Historical Approaches to Lithology Terrestrial sedimentary Environments WEEK 2 -- Fluvial & Deltaic Environments & Walther’s Law Coastal & Marine Environments; Transgressions & Regressions Physical Stratigraphy WEEK 3 -- Index Fossils, Correlations & Radiometric Dating Lithostratigraphy Biostratigraphy & the Geologic Timescale WEEK 4 -- Another Geography: Plate Tectonics Orogenesis I Orogenesis II & Geochemical Cycles WEEK 5 -- Fossils & Fossilization Evolution I: On the Origin of Species by Means of Natural Selection Evolution II: Patterns, Processes & Phylogeny WEEK 6 -- Midterm Exam I Strange Eons: Introduction to the Precambrian & the Hadean Eon The Archean Eon I The Archean Eon II WEEK 7 -- The Proterozoic Eon I The Proterozoic Eon II WEEK 8 The Proterozoic Eon III The Early Paleozoic Era I The Early Paleozoic Era II WEEK 9 -- The Middle Paleozoic Era I The Middle Paleozoic Era II The Middle Paleozoic Era IIII WEEK 10 -- The Late Paleozoic Era I The Late Paleozoic Era II The Late Paleozoic Era III WEEK 11 -- The Late Paleozoic Era IV Midterm Exam II The Early Mesozoic Era I Weekind FIELD TRIP: environment geology WEEK 12 -- The Early Mesozoic Era II The Cretaceous Period I The Cretaceous Period II WEEK 13 -- The Cretaceous Period III The Paleogene Period I The Paleogene Period II WEEK 14 -- The Neogene Period I The Neogene Period II The Quaternary Period I WEEK 15 -- The Quaternary Period II: To the Anthropocene and Beyond! WEEK 16 -- Final Exam LABS --> Introduction; Overview of Policies; Prior Knowledge Survey Sedimentary Rock Classification Sedimentary Structures & Depositional Environments The Ordering of Geological Events Biostratigraphy, Geochronology, Magnetostratigraphy Physical Stratigraphy Introduction to Paleontology: Fossils and Fossilization Common Fossilizing Organisms Applied Paleontology Geologic Map Interpretation Precambrian & Paleozoic Geology Post-Paleozoic Geology Quaternary Geology and Climate Change Physical Geology In this course you will learn about geologic materials (e.g., minerals, rocks, water, air) and processes (e.g., erosion, plate tectonics, climate change, volcanism). Through labs and other activities you will examine, evaluate, and apply problem-solving techniques to evidence to reach geologically plausible conclusions. You will practice technical writing, and several ways to graphically communicate the results of your work. Typical Text: Marshak, S. (2018). Earth: Portrait of a Planet. W. W. Norton & Company Labs --> There will be 9 formal lab exercises. The 10th lab will be review for the final exam. There will be 5 labs in the field where weather status must be highly hazardous or non-constructive to respectively field activity. Don’t be late! Wear clothing and shoes appropriate for the weather, rocky and/or muddy walking surfaces, and walking through brush. Field labs will require 2 – 3 page write-ups, explained during the lab. These should concisely describe what you did, how you did it, your results, and your interpretation of the results in terms of the geologic questions posed in lab. All field trip writeups must be computer printed OR sent in by e-mail, and submitted on the Friday following the lab. That means paper versions may be handed in, or electronic versions submitted by e-mail. Electronic versions must be a single file, with your last name at the beginning of the file name. Permitted formats: Microsoft Word (doc, docx), Adobe Acrobat (pdf), OpenOffice / LibreOffice (odt), Googlw Docs. Figures and tables must be legible, complete, labelled and numbered as figures and tables, and cited as evidence supporting your conclusions. Completing and understanding the readings will help you finish the labs with a minimum of fuss. Tests and quizzes --> There will be mid-term and final exams. Exams will be closed book and closed notes, and will contain mostly short answer questions, many related to figures given in the exam (a copy of an old final exam is here to give you an idea of the format). The exams will cover material from lectures, labs, and the textbook. Each Friday there will be a 2-point mini-quiz, for which you get 1 point for a wrong answer and 2 points for a right answer (all questions direct from figures in the text, no quiz week 1). Grading --> Mini-quizzes 10% Lab points (9 labs) 45% Mid-term exam 20% Final exam 23% Complete entrance quiz 1% Complete exit quiz 1% Course Outline --> WEEK 1-- Introduction. Structure of the Earth, plate tectonics introduction WEEK 2-- Plate tectonics - forming magmas and igneous rocks. Plate tectonics - sea-floor spreading. Lab 1 WEEK 3 -- Plate tectonics - subduction zones Subduction zones, volcanoes, and volcanic eruptions Folds and faults Realms of change – metamorphism Lab 2 WEEK 4 -- Geologic time - relative age relationships Geologic time - absolute age relationships Lab 3 WEEK 5 -- Geologic time - using both absolute and relative ages The Earth's climate - climate zones, climate controls Weathering and landslides Erosion on hill slopes Lab 4 WEEK 6 -- Midterm Running water - moving sediment and dissolved material Lab 5 WEEK 7 -- Running water - floods and related deposits Sedimentary rocks, origin and characteristics Ground water - concepts of ground water flow Ground water - storage and flow Lab 6 WEEK 8 -- Oceans - shoreline processes Oceans - shoreline advance and retreat Oceans - open ocean currents, shallow and deep Lab 7 WEEK 9 -- Deserts of sand, rock, and ice Evidence for climate change Deducing long-term climate from sedimentary rocks LAB 8 WEEK 10 -- Glaciers and ice ages Anatomy and dynamics of glaciers Topographic features, flood, landslide hazards Lab 9 WEEK 11 Geologic hazards WEEK 12 Final Exam Geological Field Methods This course will allow you to develop a basic understanding and working knowledge of many introductory techniques pertaining to geological field methods and map interpretation. This will include introductions to techniques involving topographic map interpretation; Brunton compass use to determine location and collect geologic data; identification of basic geologic relationships; interpretation and presentation of various geologic data in maps; and use of GIS in map production. Overall, each student will be able to collect, compile, analyse, interpret, and present basic map data of various types. Learning Outcomes --> Topographic Map Interpretation Brunton Compass Location Brunton Data Collection Basic Geologic Relationships Geologic Map Interpretation Geologic Map Data Presentation GIS Map Production Typical Text: Geologic Maps: A Practical Guide to the Preparation and Interpretation of Geologic Maps by Spencer Materials: Pencils (no pen on assignments unless noted otherwise) Pen for final inking; notebook; C-thru brand protractor-ruler, calculator Brunton compasses will be checked out at the start of the semester Rock hammers and map/clip boards will also be checked out as needed A GIS of your choosing; students will be debriefed on operational requirements A smartphone with at least strong optical range and strong focus; good GPS location parameters Altitude record keeping Mathematica Google Earth Google Maps Field Trips --> There will be a few afternoon field trips during Friday labs. In order to maximize the time allotted to complete lab assignments during these short field trips, the lab may run long on these days. For these short field trips to locales in town, you will be responsible for transportation to the field site and back to campus. Please talk with fellow students in advance to arrange shared rides. In addition to prior mentioned field trips, there will be one weekend field trip to a much further destination. Concerns looking at some basic field relationships and apply your new skills. Lodging for the trip will be at an established campground near the field sites, so please arrange tent, sleep bag, etc. etc., etc. Please notify your other professors of a potential absence due to these university excused absences. If necessary, and with proper notification in advance, I would also be happy to write a brief email explaining such an absence to any professor from another course. Grading: In-class assignments: 20% Comprehension Quizzes: 10% Lab Assignments: 30% Midterm Field Exam: 20% Final Exam Indoor Mapping Exam: 20% Topic Outline --> WEEK 1. Introduction; Topographic Maps (Ch 1 & 2). Lab 1: Topographic Maps WEEK 2. Map Interpretation Basics (Ch 3). Lab 2: Brunton Compass Basics Part 1 (Chosen site 1) WEEK 3. Map Interpretation Basics (CH 3). Lab 2a: Brunton Compass Basics Part (Chosen site 1) WEEK 4. Sedimentary Rocks; Aerial Photographs (Ch 4 & 5). Lab 3: Introductory Indoor Map Exercise WEEK 5. Geologic Maps of Bedrock; Homoclinal Beds (Ch 7). Lab 3 Continued WEEK 6. Lab 4: Structural Measurements (Chosen site 2) WEEK 7. Surficial Geology (Ch 6). Lab 5: Surficial Geology WEEK 8. Midterm Review. Midterm Exam: Brunton Compass/Field Location ID (Chosen site 3) WEEK 9. Unconformities; Faults (Ch 9 & 11). Lab 6: Unconformities and Faults WEEK 10. Fold Patterns (Ch 10). Seminar and debriefing on long range field trip. Signatures and absence documentation. WEEK 11. Long range field trip WEEK 12. Igneous and Metamorphic Rocks (Ch 10 & 12). Lab 7: Fold Patterns/Igneous/Metamorphic Rocks WEEK 13. Lab 8: Indoor Mapping Exercise 2 WEEK 14. Soils. Lab 9: Soils WEEK 15. Reconnaissance Mapping with GIS. Lab 10: Introduction to GIS Reconnaissance Mapping WEEK 16 – 17. Lab 11: GIS Mapping (long range field trip data) and further technical skills FINAL EXAMINATION WEEK Prerequisites: Physical Geology, Historical Geology Invertebrate Paleontology The purpose of this course is to introduce you to the most important groups of organisms in the invertebrate fossil record. We will survey the morphology, paleoecology, evolution, and geologic history of the protozoans and the 9 most abundant metazoan phyla. Lectures will address the geologic history of each group, its range of habitats, functional morphology, paleoecological and paleoenvironmental significance, and basic patterns of diversification and extinction. Lab exercises will focus on the recognition of basic morphological features of fossils and identification of important taxa. Four semester hours, three hours lecture, three hours laboratory per week. Morphology, classification, evolutionary history, ecology, and geologic significance of major groups of invertebrate fossils. Student Learning Outcomes -- the student is expected to understand and apply the following concepts to the environment: 1. Become familiar with the major fossil groups. 2. Recognize major taxonomical parts of each fossil groups. 3. Be able to identify the major guide fossils. 4. Learn to identify fossils. 5. Use fossils as a key indicator of the depositional environment. Text: TBA Lab Manual: TBA (may be document download and print activity or not) Grading --> A curve will be established on the following basis: Lab: 12 lab exercises @ 10 points each 120 points (25%) 3 lab exams @ 30 points each 90 points (20%) Quizzes treat both lecture and lab (15%) Lecture: 1 midterm 90 points (20%) 1 final exam 120 points (20%) Labs --> There will be 12 lab exercises as indicated. You will have 7 days to turn in respective lab. Lab will also have 2 filed trips that will not count into lab grading, but failing to promptly attend or being absent from either field trip warrants one letter grade reduction. You will provide details on what type of fossils are to be expected with strong arguments in profession and general geology for that belief; finds will also be detailed with comparative description to belief. There may or may not be area marking activities. Such field trips concern field planning, logistics and non-destructive/professional practices applied at excavation sites. You may not find anything substantial during activity, but skills in practice must be acknowledged. Quizzes --> Assignments or questions on quizzes can come from both lab and lecture. Exams --> All exams will include Multiple-choice section True/false questions Fill in the blank questions Short answer questions Figure illustration Short essay questions Such types of tasks or challenges will have no order. Don’t expect topic sequences. You are allowed to bring 2 loose leaf size paper sheets with notes for exams. It’s in your best interest that you don’t let others or even the instructor know your trends, strengths and weakness when developing your 2 sheets. Course Outline --> WEEK 1. introduction: evolution and the fossil record No Lab WEEK 2. Microfossils Lab: microfossils WEEK 3. poriferans; metazoan organization Lab: poriferans WEEK 4. Cnidarians Lab: cnidarians WEEK 5. Bryozoans Lab: bryozoans WEEK 6. Brachiopods Lab: brachiopods WEEK 7. Intro to molluscs; gastropods Lab: gastropods & “minor” molluscs WEEK 8. Pelecypods Lab: pelecypods WEEK 9. Cephalopods Lab: cephalopods WEEK 9. Arthropods Lab: trilobites & chelicerates WEEK 10. Arthropods Lab: crustaceans & trace fossils WEEK 11. Oral presentations Lab: No lab WEEK 12. Echinoderms Lab: echinoderms-1 WEEK 13. Echinoderms Lab: echinoderms-2, graptolites WEEK 14. Paleontology, Evolution, Creationism, ID Prerequisite: Historical Geology, Physical Geology Geomorphology Process Geomorphology will provide an in-depth investigation of the processes that determine the form and evolution of landscapes, starting with tectonic geomorphology and then focusing on hillslopes, rivers, and glaciers. The course will combine lectures, discussions, field data collection, calculations, and other activities. This is not a straight lecture class! Active learning and student participation will be an essential component. Course Objectives - To provide students with: -strong understanding of the linkages between landscape form and process -familiarity and experience applying fundamental concepts in physical systems -experience collecting and analysing field data -opportunities for developing scientific writing skills -opportunities to develop and apply skills in physics and mathematics -experience in interpreting and analysing literature from both secondary and primary sources -practice in using models, data, and logical reasoning to critically evaluate and connect information about geomorphic processes -experience communicating an understanding of the interrelationships among geomorphic concepts and theories to peers and others -experience working as members of productive, collaborative teams Typical Text: Anderson, R.S. and Anderson, S.P., 2010. Geomorphology: The Mechanics and Chemistry of Landscapes. Cambridge University Press. Additional Literature --> Journal papers and supplemental readings will also be assigned. General Tools --> Google Earth Mathematica Field Trip Tools --> TBA Crucial Note --> Calculus and physics will be used in the class. Computer literacy is also expected; assignments will be given involving computations, the use of spreadsheets and retrieval of data over the internet. The most important requirement is to be prepared to devote a lot of time and effort to this class (I will too). Journal articles --> To have a robust study one needs to incorporate an international geological study. This is a course is the geosciences realm. Some of the following journal articles examples may or may not fully suit one’s interest: -Burbank, D.W., 1996. Bedrock incision, rock uplift and threshold hillslopes in the northwestern Himalaya. Nature, 379: 505-510. -Dietrich, W.E., Bellugi, D.G., Sklar, L.S., Stock, J.D., Heimsath, A.M. and Roering, J.J., 2003. Geomorphic transport laws for predicting landscape form and dynamics. In: P.R. Wilcock and R.M. Iverson (Editors), Prediction in Geomorphology. American Geophysical Union, Washington D.C., pp. 103-132. -Dietrich, W.E. and Perron, J.T., 2006. The search for a topographic signature of life. Nature 439(7075): 411-418. -Egholm, D.L., Nielsen, S.B., Pedersen, V.K. and Lesemann, J.E., 2009. Glacial effects limiting mountain height. Nature, 460(7257): 884-887. -Gabet, E. J., and A. Bookter (2008), A morphometric analysis of gullies scoured by post-fire progressively bulked debris flows in southwest Montana, USA, Geomorphology, 96(3-4), 298- 309. -Kirchner, J.W. 2002. Subtleties of sand reveal how mountains crumble. Science 295: 256-258. -Koppes, M.N. and Montgomery, D.R., 2009. The relative efficacy of fluvial and glacial erosion over modern to orogenic timescales. Nature Geosciences, 2(9): 644-647. -Molnar, P., and England, P., 1990, Late Cenozoic uplift of mountain ranges and global climate change: Chicken or egg?: Nature, v. 346, p. 29–34. -Montgomery, D.R. and J.M. Buffington. 1997. Channel reach morphology in mountain drainage basins. GSA Bulletin 109. -Montgomery, D.R. 2007. Is agriculture eroding civilization’s foundation? GSA Today 17(10): 4-9. -Naylor, S. and Gabet, E.J.. 2007. Valley asymmetry and glacial vs. non-glacial erosion in the Bitterroot Range, Montana, USA. Geology 35(4): 375-378. -Perron, J.T., Kirchner, J.W. and Dietrich, W.E., 2009. Formation of evenly spaced ridges and valleys. Nature, 460(7254): 502-505. -Pinter, N. and M.T. Brandon. 1997. How erosion builds mountains. Scientific American. April: 74-79. -Trush, W.J., S. M. McBain, and L. B. Leopold. 2000. Attributes of an alluvial river and their relation to water policy and management. Proceedings of the National Academy of Sciences 97: 11858- 11863. -Whipple, K.X., Kirby, E. and Brocklehurst, S.H., 1999. Geomorphic limits to climate-induced increases in topographic relief. Nature, 401: 39-43. -Whipple, K.X., 2009. The influence of climate on the tectonic evolution of mountain belts. Nature Geosci., 2: 97-104. Labs --> Lab 1: Landscape attributes and metrics Lab 2 (field): Surveying and GPS There will be 4 - 5 other labs that will make heavy use of Google Earth Lab 3: HEC-RAS Lab 4: HEC-FIA Field trips --> Each of the field listed below is required. The data collected on these field trips will be the basis for much of your work in this class. See me right away if you have scheduling conflict. You will need a field book, and will require use of (many) other things. Data types can be become quite broad and entries can become high volume and complicated. Fields should NOT be viewed as a picnic. Another indicator of what to expect, fields activities and development will account for 50% of your final grade. If you weren’t doing much on field trips surely weighting would be quite lower. FT1: Exploring the conjuncture between landscape and contemporary human activity at sites shaped by the geologic epoch of the Pleistocene. Through our projects, we create contexts and speculative tools for humans to recalibrate their sense of place within the geologic timescale. Depending on environment one lives in Pleistocene may or may not be practical concerning environment scale. Possibly a substitute field trip activity type will re required. FT2: Hillslope Processes FT3: Creek streams versus rapids Course Evaluation --> 30% In-class & lab exercises, other homework, class participation, quizzes 50% Field trip attendance, participation and 3 field project reports 20% Final exam Topic Outline --> WEEK 1 Introduction Introduction continued; Lab 1: Landscape attributes and metrics WEEK 2 Tectonic geomorphology Lab 2 (field): Surveying and GPS WEEK 3 Tectonic geomorphology Tectonics & climate WEEK 4 Megafloods: Glacial Lakes. Late Pleistocene paleolakes Field trip prep WEEK 5 FT1 WEEK 6 Dating Weathering WEEK 7 Sediment budgets WEEK 8 Landslides & debris flows; FT 1 project report due Landslide mechanics; Field trip prep WEEK 9 FT2 WEEK 10 Slope stability Hillslope processes wrap-up Water in the landscape; Channel networks and drainage basins WEEK 11 Water in the landscape; Hillslope hydrology WEEK 12 Fluvial processes: alluvial rivers Fluvial processes: flow and sediment transport; FT 2 project report due Field trip prep WEEK 13 FT3 WEEK 14 Fluvial processes: Hydraulic geometry, channel patterns, long profiles Fluvial processes: floods, dominant Q, channel adjustments, classification WEEK 15 Glacial processes: intro Glacial processes: flow mechanics WEEK 16 Glacial processes: flow mechanics FT 2 project report due WEEK 17 Glacial processes: landforms Glacial processes: jokulhaups, glacial hydrology WEEK 18 Human effects on geomorphic processes, course wrap-up Course Wrap-up WEEK 19 Final Exam Prerequisites: Historical geology, Physical Geology, Calculus I. Co-requisite or Prerequisite: General Physics I Mineralogy In this course you will learn about the structure and chemical makeup of Earth materials. We will concentrate on the physical and chemical properties of minerals, from macroscopic to microscopic. Since this is a geology course, we will investigate how geologic materials and processes influence mineral occurrence, stability, and composition. The course is divided into three main sections in which we will cover a lot of ground, so to speak. The first unit reviews pertinent chemistry investigates how and why minerals are classified, and introduces optical mineralogy, which is essentially the physics of how light interacts with minerals. We will begin our examination of specific minerals in detail during the second unit, as we study minerals that form within characteristic geologic environments. In the third unit, we will tackle the nitty-gritty aspects of crystal chemistry that control all physical properties of minerals. In lectures and labs students will make extensive use of spectral libraries to have consistency with chemical structures in question; the converse may also be of interest. Some goals for this course are to understand: (1) the characteristics of major mineral groups in hand specimen and thin section (2) phase equilibria, formation environments and associations of rock-forming minerals (3) crystal symmetry, crystallography, and atomic structure At the end of this course, you will be able to: (1) identify common rock-forming minerals in hand specimen and in thin section using diagnostic physical, optical, and chemical properties (2) infer something about the formation environment of a silicate mineral using only its formula (3) read a phase diagram (4) predict the physical properties of a substance from its symmetry content (5) plot crystal faces on a stereo projection (6) travel anywhere in the world, and speak intelligently about your surroundings …and etc. etc. Required Texts: Klein, Manual of Mineral Science 22nd Ed. Nesse, Introduction to Optical Mineralogy 2nd Ed. Tools --> --Bring a calculator to class each day. Periodically, we will work problems out in real time together. Coloured pencils or pens may be helpful. --A tool such as Mathematica with emphasis on chemical data and geological data interests that can fetch data interests based on specified parameters applied may prove highly useful to assist texts. --USGS Mineral Resources Data System --You are required to obtain a hand lens for this course. You will use this tool frequently, not only in this class, but in many of the upper division Geology courses. --A real geologist always has a hammer and a hand lens when going into the field!) --USGS Spectral Library is of interest: https://www.usgs.gov/labs/spec-lab/capabilities/spectral-library The USGS Spectral Library is tool one of many possible tools. Homework --> Homework has 2 main features: Will keep you on your toes with rigorous skills in chemistry that are highly applicable to minerology. Minerology trivia and mineral properties. Explaining spectral lines for chemical structures. Quizzes --> Each week there will be at least one short, unannounced quiz in class. They will cover reading assignments, which will be announced in class. The purpose of the quizzes is to motivate you to do the reading, so you are prepared for class discussion. Exams --> Exams will reflect homework and quizzes. There will also be practical components, say, requiring use of microscopes and other lab materials. Grading --> Homework (25%) Labs (35%) Quizzes (10%) 3 Tests – two midterms + a final (30%) Topic Outline --> NOTE: in lectures for identified minerals chemical formulas and structures will be identified, then to establish consistency with spectral lines from professional. Such knowledge and skill will also emerge on exams. Unit 1: Chemical and Physical Fundamentals --Atoms, ions, periodic table, bonding --Crystallization, crystal imperfections (defects, zoning, twinning), crystal precipitation, mineral classification schemes, physical properties of minerals (appearance, crystal shape, strength, density, magnetism, reaction with acid) --Polarized light, refractive index, uniaxial and biaxial indicatrices, interference figures --First Exam Unit 2: Rock-Forming Minerals --Sedimentary minerals (zeolites, clays, sulphates, halides, oxides, carbonates), weathering processes; ore minerals --Igneous minerals (silicates), phase relations --Metamorphic minerals, textures, reactions, phase equilibria, and thermodynamics --Economic minerals (magmatic, hydrothermal , and sedimentary ores; native metals, sulphides and sulfosalts, oxides and hydroxides, gems) --Second Exam Unit 3: Symmetry, Crystallography, and Atomic Structure --Symmetry, stereo diagrams, forms and crystal morphology --Unit cells and lattices in two dimensions and three dimensions, Bravais lattices, unit cell symmetry and crystal symmetry, crystal structures, crystal habit and crystal faces --2 X-ray diffraction --3 Ionic radii, coordination number, packing, Pauling’s rules, silicate structures, substitutions, structures of nonsilicates --2 – 4 additional labs (to encompass or reinforce curriculum, or make ups, or review) --Final Exam LABS MODULES --> NOTE: a module may require multiple sessions. NOTE: in labs for identified minerals chemical formulas and structures will be identified, then to establish consistency with spectral lines from professional. A. Mineral classification – What’s in a Name? Students derive their own scheme for identifying and naming minerals. Content Goals: To become familiar with the most important mineral properties used for mineral identification. Higher Order Thinking Goals: This project involves analysing a complex problem, synthesizing information of different sorts, and then deriving a logical and practical mineral classification scheme. It also involves evaluation of the ways early mineralogists approached the same problem. B. Properties of Minerals Students examine a number of key mineral properties and how they are displayed by different minerals. Content Goals: Students learn about the details and subtle implications of some key mineral properties. C. Properties of Minerals and intro to Polarizing Microscopes Continue the study of the physical properties of minerals and an introduction to a petrographic microscope. Content Goals: Become more familiar with mineral properties. Become familiar with the basic components of a petrographic microscope and with the most important mineral optical properties. D. Properties of Amphiboles, Micas, Pyroxenes, and Olivines and an introduction to Mineral Properties in Thin Section Students look at mafic igneous minerals, learning to distinguish and identify them in hand specimen. They also look at a few of the minerals in thin section. properties. Content Goals: Learn to identify mafic minerals. Be able to identify and describe the properties of minerals seen in thin section. Learn the basic techniques of optical mineralogy. Higher Order Thinking Goals: Students learn to group and classify minerals according to their physical properties. E. Examination of the Quartz, Feldspathoids, Feldspar, Zeolite group and other Framework Silicates. Ore Minerals. PART A Students study hand samples of light-coloured igneous minerals and related mineral species. They look at some of the same minerals, and others, in thin section. Content Goals: Learn to identify important light-coloured minerals. Learn to identify the most important minerals in thin section. Higher Order Thinking Goals: Begin to think about why minerals of the same chemical group have similar properties. F. Crystallography and Symmetry (based on modules D and E) G. Use of CrystalMaker software (or alternative) Overview H. CrystalMaker Labs (based on modules D, E and F) For viewing minerals in 3-D, determining coordination. Crystal and molecular structures, modelling, visualisation software Diffraction pattern simulation. I. Pauling’s Rules (Ionic Radius and Bond Strength) Learn how cation and anion size relate to coordination number. Pauling's "electrostatic valency" principle. Understand the nature and strength of ionic bonds. Think about crystals as systems governed by fundamental physical/electrostatic laws. Use of USGS PHREEQC Use of USGS NETPATH J. Calculating Oxide Weight Percentages from formulae and Normalizing Chemical Analyses This exercise involves converting chemical analyses to mineral formulas, and mineral formulas to oxide and element weight percentages. Higher Order Thinking Goals: This exercise involves application of basic chemical principles. K. Crystallizing Minerals from Aqueous Solutions & Crystal Shapes Students dissolve selected salts and other compounds in water, let the water evaporate, and examine the crystals that grow. Content Goals: To learn about the ways minerals crystallized from aqueous solutions Higher Order Thinking Goals: Learn to think about crystal shapes and to classify them in a logical way. Other Goals: To continue to improve experimental technique. Students will also identify environments where crystal salts are predominant (both aqueous and arid). Will try to establish any commonalities of crystallization between lab experimentation and the accepted crystallization processes for natural crystals from those open environments. Prerequisites: Historical Geology, Physical Geology, General Chemistry II Geochemistry Example texts --> Geochemistry: Pathways and Processes. McSween, Richardson and Uhle, 2nd edition (2003). Columbia University Press. Principles and Applications of Geochemistry. Faure. (1998). Prentice Hall. Course Assessment --> 2 Midterms 30% Final 30% Labs 40% Lectures --> WEEK 1 (2-3 lectures). Crystal Chemistry to planetary differentiation Composition of chemical reservoirs in earth Principles that control the distribution of the elements WEEK 2 (3 lectures) Trace element distribution example - rare earth elements Thermodynamics of geological systems Equilibrium and free energy concept. Gibbs function, how changing P and T changes equilibrium. WEEK 3 (2-3 lectures) How changing composition changes equilibrium Henry's and Raoult’s laws WEEK 4 (3 lectures) Trace Element Geochemistry clues to geological processes Element partitioning between minerals and magma Differentiation and geochemical reservoirs WEEK 5 (3 lectures) Radioactivity and geochronology Radiogenic isotope signatures and differentiation K-Ar system, Rb-Sr system and U-Th-Pb systems Sedimentary rocks, soil development, solubility WEEK 6 (3 lectures) Planetary differentiation Global elemental and isotopic reservoirs Nucleosynthesis: age and origin of the elements WEEK 7 (3-4 lectures) Aqueous geochemistry and natural waters Solubility calculations Non-ideal solutions WEEK 8 (3 lectures) pH and carbonate equilibria Aluminosilicate reactions, rock weathering Stable isotopes - introduction WEEK 9 (2-3 lectures) Stable isotope fractionation of H, C, O, S. Paleothermometry Stable isotope tracers and fingerprinting (3 lectures) WEEK 10 (2-3 lectures) Global geochemical cycles and time perspectives Carbon and strontium cycles on short and long timescales --Laboratory/Field --> Naturally there will be activities of field samples collections (solids and liquids). Some essentials tools and activities to implemented for various labs: Magnifying glasses, Microscopes, Gravimetry CrystalMaker software (or alternative) MINTEQA2 (accompanies comprehension and application of analytical models) PHREEQC (accompanies comprehension and application of analytical models) Lab Topics --> Review and warm-up problem set Silicate crystal chemistry Determining P and T of mineral formation Trace element geochemistry (introduction to databases) Trace element geochemistry: < faculty.washington.edu/stn/ess_312/labs/ess_312_lab_4_trace_elts.pdf > Intro Radioactivity Radioisotopes and mantle differentiation Weathering reactions and mineral stability Trace elements and stable isotopes in corals Modelling the carbon cycle (PART A) Will pursue comparing analytical quantitative models with given simulation tool. Will pursue identifying convergence, and significance of discrepancies or deviations for particular values of the parameters. Linear approximations, series approximations, etc. can apply. < https://personal.ems.psu.edu/~dmb53/Earth_System_Models/Carbon_Cycle.html > Modelling the carbon cycle (PART B) Long-term Ocean-atmosphere-Sediment CArbon cycle Reservoir Model (LOSCAR) Zeebe, R. E., LOSCAR: Long-term Ocean-atmosphere-Sediment CArbon cycle Reservoir Model v2.0.4, Geosci. Model Dev., 5, 149–166, 2012 Will compare models from Part A and Part B and try to determine where and how (drastic) deviations arise. Will also pursue acquisition of code for computational investigation. Prerequisites: General Chemistry II, Calculus II, Historical Geology, Physical Geology Analytical Geochemistry The course concerns analytical chemistry methods catering specifically to geochemistry. Course will be composed primarily of field exploration for samples and lab experiments. MAJOR FEATURES OF COURSE: Motivations and comprehension of a respective activity. Planning and logistics for lab activity. Samples Collection (will not be done in one fell swoop because not all interesting samples will be found at one location). Geological profiling relevant to motivations for respective activity Knowledge and skills from earlier geology obligation courses would make visual identification credible. Sample size determination (overview, not necessarily implemented) Will be emphasized to cater for each unique activity Logistics and walkthrough for respective sample collection Includes not contaminating environment and possibly the samples Samples Collection Data and Error Analysis (only for first 4 topics in Bulk Techniques) Fluid and constructive comprehension and process of respective method or technique Logistics for tools and equipment for respective method or technique Includes not contaminating the samples; depending on the method or technique (for bulk and point) even water may be a contaminant. Implementation of respective method or technique For all spectroscopy experiments students will also be required to explain spectral lines for chemical structures. Analysis of results and interpretation and conclusion Suggestions for improvement NOTE: for sample size determination, although emphasized to cater for each unique activity, it may not be implemented throughout all activities due to limitations with tools and resources (such as well-being of equipment, transportation issues, time constraints, preservation of environments, mitigating the risk of bodily hazards w.r.t. environment exposure, etc.) NOTE: any types of spectroscopy that aren’t specified concerns applying types of spectroscopy that are robust and dexterous, namely, high “bang for buck”; economics always dominate, plus you can’t remember everything with every type of spectroscopy. Will be comparing all spectroscopy results to professional spectroscopy databases (USGS or whatever available). USGS Spectral Library is of interest: https://www.usgs.gov/labs/spec-lab/capabilities/spectral-library The USGS Spectral Library is tool one of many possible tools. ASSESSMENT ---> Attendance Lab Quizzes (3-4) Elements for quizzes Identification, referencing appropriate methods Detailing processes and procedures Lab Exams (3) Concerns Major Features of Course with respect to the Course Outline Identification, referencing appropriate methods Detailing processes and procedures True or False questions Concerns making sense of formulas, models and results Students will also be required to explain spectral lines for chemical structures specifically for spectroscopy topics Field Trips and Labs Attendance and behaviour Preparation Operations Quality of data collection Modelling of data (if relevant) Analysis, interpretation, conclusions, suggestions Note: suggestions for each lab concerns possible improvement of field and lab operations. COURSE OUTLINE ---> 1.Bulk (Whole Rock) Techniques Density Testing Gravimetric Techniques Titration Techniques Wet Chemical Methods Types of Spectroscopy UV Spectroscopy Infrared Spectroscopy 1-2 other types 2.Point Chemical Analysis (minerals) Types of Spectroscopy Infrared Spectroscopy Raman Spectroscopy 1-2 other types 3.Aqueous Environments Chemical composition of water from environments of interest Prerequisite: Analytical Chemistry, Calculus III. Igneous & Metamorphic Petrology The main objective of this course is to get students acquainted with a wide range of igneous and metamorphic rocks and their corresponding geological settings. Deductive skills (such as identifying minerals and other phases, understanding their geologic occurrence and inferring environmental conditions from the mineral assemblage, texture, and tectonic setting) will be emphasized over memorization of nomenclature, although we will also examine why mineral and rock names are important and may convey great meaning. The petrogenesis of igneous and metamorphic rocks (the source ‘DNA’ of a given rock, its temperature, pressure, path through the earth’s crust, its interactions with other rocks and/or magmatic bodies) will be explored through different geodynamic contexts of the Earth. The importance of basic sciences (specifically chemistry and physics) in gleaning geological processes from hand samples will be emphasized throughout the course. Examination with a variety of techniques, samples that were collected during and after this eruption. Students will conduct a semester-long project using samples (e.g. from a past eruption, other locations in a islands chain, or other localities). The goal will be to recover as much information as possible from these samples through observations, identification of petrological clues, in order to constrain the geological history. The goals of these activities are to scaffold upon the students’ prior knowledge from prerequisites; apply and practice new observational and analytical skills; address frontier science questions pertaining to the plumbing systems and dynamics of Hawaiian volcanoes; and gain experience communicating scientific content in accord with accepted norms—both orally and in writing. Considered Texts: Principles of Igneous and Metamorphic Petrology, J.D. Winter An Introduction to Igneous & Metamorphic Rocks (John Winter) Labs --> Expect ALL knowledge and lab experience, and lab activities from Mineralogy prerequisite to be included with the conventional pursuits; other prerequisites to some degree. Chosen labs activities from mineralogy course will augment the given labs Grading --> Homework + Quizzes + Classroom and Fieldtrip Participation (15%) Laboratory (25%) Lab Assignments 0.5 Laboratory Practical 0.5 Two 1¼ hour exams (15% each) Comprehensive final exam (25%). Course Outline --> WEEK 1. Introduction: Overview of petrology, rocks. Structure and dynamics of the Earth. Where are igneous rocks generated? Chap 1 WEEK 2. Classification and nomenclature (Chapter 2 & 8) WEEK 3. Textures. Structures and field relations (read); Intro to Thermodynamics (Chapter 3, 4 & 5) WEEK 4. Phase rule, unary and binary systems (Chapter 6) WEEK 5. Ternary Systems (Chapter 7) WEEK 6. Mantle melting & generation of basalts. Diversification of magmas (Chapter 10 & 11) WEEK 7. Igneous Rock Associations (subduction zones and granitoids), Chapter 12 – 18. WEEK 8. Review for exam WEEK 9. Exam. Introduction to metamorphism, types of metamorphism (Chapter 21 & 22) WEEK 10. Introduction continued, Types of metamorphism (Chapter 21 & 22). Chemographics and metamorphic phase diagrams (Chapter 24) WEEK 11. Pelitic Rocks: Barrow’s zones, AFM projections, discontinuous and continuous reactions (Chapters 26 & 28) WEEK 12. Types of metamorphic reactions (Chapter 26). Metamorphism of mafic rocks (Chapter 25). WEEK 13. Metamorphism of Ultramafic rocks (Chapter 29) WEEK 14. P-T paths and orogeny (Chapters 25, 27). WEEK 15. Review for Exam WEEK 16 – 17. Exam. Extremes: UHP and UHT metamorphism (chapter 25). Thermodynamics of metamorphic reactions (Chapter 27) WEEK 17 – 18. Thermobarometry (Chapter 27). Metamorphic Fluids, mass transport and metasomatism (Chapter 30) WEEK 19. FINAL EXAM Labs --> NOTE: some 1 or 2 labs will require full week or operations. NOTE: expect ALL knowledge and lab experience, and lab activities from Mineralogy prerequisite to be included with the conventional pursuits; other prerequisites to some degree. Such chosen labs activities from mineralogy will augment the following labs: --Review of Microscopy, Petrography of rocks, textures and mineral review --Granites and related rocks --Rhyolites, tuffs, scoria, pumice and obsidian --Intermediate volcanic rocks --Mafic volcanic and plutonic rocks --Ultramafic rocks and alkaline rocks --Metamorphic minerals and textures (read Chapter 23 in advance) --Structures and textures of metamorphic rocks (read Chapter 23, esp. 23.1, 23.4.1 and 23.4.5 in advance) --Progressive metamorphism of metapelites --Metamafic rocks, metamorphic facies and disequilibrium textures --Metamorphosed calcareous and ultramafic rocks --Minerals and textures of HP and UHP rocks --Review. Preparation for laboratory practical. Prerequisite: Historical Geology, Physical geology, Geological Field Methods, Mineralogy Sedimentation & Stratigraphy Sedimentary rocks contain a wealth of information on past environments, climate, biology, tectonics, and sea level. Stratigraphy is essentially a history of geomorphic processes occurring on short timescales (seconds to days) to long timescales (thousands and millions of year) as well as a record of the forces that shaped and altered Earth’s landscapes and seascapes. This class has three main parts. First, we will cover the generation, transport, and deposition of sediments, and link these processes with their depositional products (i.e., sedimentary rocks). Second, we will examine terrestrial and marine environments on Earth and how their respective geomorphic processes impart patterns on the deposition of sedimentary rocks. Third, we will cover the spatiotemporal relationships amongst these depositional environments (i.e., stratigraphy) and the interpretation of major events in Earth’s history In a nutshell: Classification of Sedimentary Rocks -> Identification of Geomorphic Process & Environment -> History of Earth’s Surface Outlines --> 1. Understand classification of sedimentary rocks. 2. Understand the link between sedimentary structures and sediment transport processes. 3. Understand facies associations and links to depositional environments. 4. Understand how to use a Brunton compass and Jacob staff. 5. Understand transmission of geomorphic processes into stratigraphy and recovery of tectonic, climatic, and eustatic signals from stratigraphy. Objectives --> 1.1. Identify unknown siliciclastic, chemical, and biochemical rocks. 2.1. Rank grain size, bedforms, and sedimentary structures in order of increasing/decreasing fluid energy conditions. 2.2. Predict sedimentary structures given changes in fluid flow conditions and bedforms. 2.3. Calculate paleoslopes from measured input parameters. 3.1. Draw typical vertical and horizontal spatial trends in sub-environments and rock types in different depositional systems. 3.2. Identify vertical patterns in lithofacies and link them to movement and evolution of the depositional system. 4.1. Measure a stratigraphic section and support a depositional environmental interpretation from the data. 5.1. Reconstruct topographic and depositional evolution of an active sedimentary system. 5.2. Formulate and propose feasible tests of hypotheses regarding the causes of depositional patterns with experimental and field datasets. Typical Text: Nichols, G. 2009. Sedimentology & Stratigraphy. Third Edition: Wiley-Blackwell Lab Manual: TBA Lab Equipment: Hand lens Millimetre ruler Laboratory handouts (print it or notebook, or whatever) Rock hammer Containment for field samples Mineral I.D. kit Required Field Trips: There will be 2 – 3 required field trips. Will occur on particular exposures of the chosen formations, etc. Grading --> Readings and Discussions 10% Labs 30% Lab Exam 20% 2 Exams 40% Reading Reflections --> Approximately once a week we will be discussing journal articles that are pertinent to the subject matter that week. You are expected to come to class having read and thought about the material. This is a reading-heavy class. I truly believe in scouring the literature, consuming, and digesting articles for ideas, inspiration, and raw data. Labs --> There are 7 labs and one lab exam. Labs will start with a short introduction. In some cases, there will be a demonstration or an example that we work through together. The remaining time will be for you to work in groups. Each person turns in an individual lab due the following week at the start of lab. The labs may take longer than the allotted 2 hours. For designated labs students will apply their knowledge of skills and analysis from prerequisites. Students must know how to situate/associate such skills and analysis to reinforce or boost findings; will not be lab oriented, but will be data driven. If any use of spectroscopy, means of incorporating spectrographs to become identification of constituents, bonds, groups, etc. Much will be expected from associating/situating knowledge of skills, analysis and data. Topic outline --> Week 1 Introductions, Class Overview, Syllabus, Source-to-Sink, Geologic Intuition Sedimentary Basins & Weathering (Ch. 1, 6, & 24) Week 2 Grain Size and Siliciclastic Rocks (practice ID exercise) (Ch. 2) Lab 1: Siliciclastic Rock Classification Chemical & Biochemical Rocks (practice ID exercise) (Ch. 3 & 15) Week 3 Lab 2: Carbonate Rocks Sediment Transport & Facies Analysis (Ch. 4 & 50 Week 4 Discussion of readings (discussion papers) Lab 3: Sedimentary Structures (how to use a Jake staff) Exam 1 Week 5 Alluvial Fans & Rivers (Ch. 9) Rivers & Soils (Ch. 9) Formation site 1 (presentation example & discussion) – readings Lab 4: Formation site 1 field trip Week 6 Deltas (Ch. 11, 12) Deltas & Trace Fossils (Ch. 11, 12) Estuaries & Beaches (Ch. 13) Formation site 2 (presentation example & discussion) – readings Lab 5: Formation site 2 field trip Week 7 Shallow & Deep Marine (Ch. 14, 16) Deep Marine (Ch. 16) Discussion & Strat Column/Sea Level Exercise (discussion papers) Formation site 3 (presentation example & discussion) – readings Lab 6: Formation site 3 field trip Week 8 Inverse Problem & Discussion (discussion paper) Lab Exam Week 9 Lab 7: Turbidite Stratigraphy Lab 7: Turbidite Stratigraphy (discussion papers) Post-Deposition Processes & Hydrocarbons (Ch. 18) Week 10 Stratigraphic Correlations (Ch. 19 – 23) Week 11 Exam #2 11/30 Final Presentations Final Presentations Prerequisites: Historical Geology, Physical Geology, Geomorphology, Mineralogy

Environmental Geochemistry Course will cover the geochemical and hydrologic processes/mechanisms essential in releasing and fixing metals and metalloids on land and in aquatic environments. Focus will be on comprehending the basic principles causing metal/metalloid contamination in rivers, lakes, groundwater and lands around the world. The course will have readings and discussion of past and recent literature, and examination of existing data, to examine the processes controlling the transport and fate of contamination in various environments. Succeeding topics will build on prior topics, hence, know your priorities. Development in course will be geared to perform well on field trip. You will be expected to interact in class and participate in the discussion of the readings. Course requires a conference/meeting on restoring rivers and lands in question impacted by development or mining. Gathering data and profiling sites of choice. Accompanied by a following two-day field trip to whatever planned site(s). NOTE: field trip happens rain or shine. NOTE: NO LITTERING (no hypocrisy) NOTE: Analytical Chemistry will not be a prerequisite because of the time gap it would cause between Geochemistry and this course. This course has labs to treat specific analytical chemistry concerns toward field trip operations. Literature --> Texts from prerequisites and selected journal articles will be applied throughout Resources & Databases --> National Institute of Environmental Health Sciences Department of Agriculture Centre for Disease Control National Library of Medicine Environmental Protection Agency (may have open source) National Institute of Health Wildlife Agency USGS Analysis Tools --> USGS models and tools/software EPA models and tools/software EQ3/6: software package for geochemical modeling of aqueous systems Will find substitute if not accessible Lab Components --> The following components will be done on multiple occasions and will compliment each other in successive manner on multiple occasions: -Applying various analytical chemistry techniques after field trips. -Will have advance replication of chosen labs from geochemistry course as precursors to course labs -Course labs will cater to course topics. -Labs will incorporate use of databases and software tools (apart from EQ3/6) -EQ3/6: software package for geochemical modeling of aqueous systems Will find substitute if not accessible Field Trip Tools --> Smartphone Proper Field Attire (for nettle, stone. rocks, rain, mud, excrement) Skin protection if need be Hopefully not much conflict with environment temperatures Safety Attire (at least two pair of gloves, KN95 masks and other things) First Aid Kit Typical geological field tools Notepad and writing utensils Course Assessment --> Attendance, Participation and Conduct Quizzes Labs Exams Fieldtrips for samples (attendance, preparation, performance, conduct, data analysis, reports) Life Cycle Assessment Report Life Cycle Assessment Report (LCAR) --> A 2-3 day field trip and post discussion along with dedicated labs following field trips for samples. COURSE OUTLINE --> Introduction and geochemical fundamentals (lecture and discussion) Geochemical fundamentals and sediment transport concepts (lecture and discussion) Development and Mining wastes and rivers (discussion of readings) Basic geochemical environments (discussion of readings, D.O.R.) Solid Phase Chemistry compositional classes and occurrence of common soil minerals precipitation and dissolution structural classification of common soil minerals structural chemistry Mineral surface properties and sorption general sorption/partitioning ion exchange surface charge and surface complexation surface charge and colloidal properties Weathering and soil development Mineralogical controls on metals and metalloid concentrations Adsorption processes for metals and metalloids Diagenesis effects on the historical records of metal contamination Geochemistry of arsenic contamination in groundwater Structure and Properties of Metalloids of interest Mobilization/fixation of metals and metalloids by acid rock drainage (D.O.R) Key factors that influence acidity Aqueous chemistry for metals and metalloids (processed water, purified water and natural mineral water) acid-base - activity - alkalinity - gas exchange aqueous complexes redox EQ3/6: software package for geochemical modeling of aqueous systems Will find substitute if not accessible Effect of metalloids on vegetation Toxicology of metals and metalloids Review of major concepts and discussion of important research needs Field Planning and Operations Determined Sites Conference Intelligence (location, geological aspects, data) Initial Profiling Attend 2-3 day fieldtrip and talks Review/Discussion of: Meeting/conference and fieldtrip Analysis of data from fieldtrip Restoration techniques/methods for contaminated sites from mining or development (bring ideas based on reading and meeting) Prerequisites: Historical Geography, Physical Geology, Geological Field Methods, Geochemistry Trace Element Geochemistry Focus of this course is to use Trace Element Geochemistry to comprehend the origin and evolution of igneous rocks. Concerns for the parameters that control partitioning of trace elements between phases and to develop models for the partitioning of trace elements between phases in igneous systems, especially between minerals and melt. Of relevance are published papers detailing examples of utilizing Trace Element Geochemistry are read and discussed. Literature --> Course will require use of multiple texts ad published articles USGS publications Reinforcement & Development for Sustainability --> 1. There will be much reinforcement with the chemistry of trace elements concerning bonds and behaviour of compounds. Done before introducing certain topics. 2. Trace elements study will often be consistent with inorganic chemistry, however, as aspiring geologists a specific path with specialized logistics focused on trace elements geochemistry. 3. Advance recitation of chosen labs from Mineralogy, Geochemistry, and Igneous & Metamorphic Petrology before introducing certain topics. 4. Software will often be used to model and characterise various igneous (and metamorphic) specimen USGS and EPA may provide open source software that can work well for trace element geochemistry; will be unique to software of interest prior. Course Assessment --> Practice Problems Quizzes Labs (software and advance recitation labs) 3 Exams Note: for quizzes and exams there will be policy on notes that will vary as course progresses. COURSE OUTLINE: --What are Trace Elements? Modern Development of Trace Element Geochemistry. Sites for Trace Elements (TE) in Minerals --Thermodynamic Considerations of Trace Element Solid Solutions --Partition Coefficient --Ionic Model for Bonding and Role of Ionic Radii in Comprehending the Partitioning of Trace Elements between Phases --Nomenclature for Trace Element Classification --Determination of Partition Coefficients --Determination of Partition Coefficients: Discussion of Experimental Approach --More Experimental Approaches for Determination of Trace Element Partition Coefficients --Trace Element Abundance Variations in Simple Melt-Solid Systems --Fractional Crystallization --Fractional Melting --Complex Melting Models --Constraints on Melt Models Arising from Disequilibrium in the Th-U Decay System --Ion Exchange Chromatography Prerequisites: Mineralogy, Geochemistry, Calculus III Geochemical Modelling Geochemical modeling is a powerful tool used in the Earth sciences to understand and predict the distribution and behavior of chemical elements in geological systems. It involves applying principles of chemistry, thermodynamics, and kinetics to simulate the processes that control the composition of rocks, minerals, soils, water, and other environmental media. Geochemical models can be used to investigate a wide range of geological processes, including mineral precipitation and dissolution, water-rock interactions, and the impact of human activities on natural systems.. OVERVIEW OF THE KEY ASPECTS OF GEOCHEMICAL MODELLING --> Thermodynamics-- Chemical Equilibrium: Geochemical models often use principles of chemical equilibrium to predict the distribution of elements between different phases (e.g., minerals, water). Thermodynamic databases provide information about the stability of minerals and chemical species under specific conditions. Gibbs Free Energy: The Gibbs free energy is a key parameter in thermodynamics that determines whether a reaction is spontaneous. Geochemical models use Gibbs free energy to calculate equilibrium constants and predict the direction of chemical reactions. Eh-pH Diagrams: These diagrams, also known as Pourbaix diagrams, display the stability fields of different chemical species as a function of pH and redox potential (Eh). They are useful for understanding the stability of minerals and the solubility of elements under different conditions. Kinetics-- Reaction Rates: Kinetics plays a crucial role in geochemical modeling, especially when dealing with processes that occur over time. Understanding reaction rates and the factors influencing them is essential for accurate modeling of dynamic systems. Reactive Transport Modeling: This involves modeling the movement of fluids and the transport of chemical species through geological media. Reactive transport models integrate both thermodynamics and kinetics to simulate how chemical reactions evolve over space and time. Geochemical Modeling Software-- Various software tools are available for geochemical modeling. Popular options include PHREEQC, MINTEQA2, WATEQF Geochemist's Workbench, EQ3/6, CHESS (Chemical Equilibrium Software for Solution Systems), OpenGeoSys, ChemPlugin, Thermokin. These tools allow researchers to perform thermodynamic and kinetic calculations, create models, and analyze geochemical data. Applications-- Environmental Studies: Geochemical modeling is used to assess the impact of human activities, such as mining, waste disposal, and pollution, on the environment. Mineral Exploration: Predicting the distribution of economically valuable minerals and understanding their formation processes. Water Quality Assessment: Modeling the interactions between water and rocks to evaluate water quality and identify potential sources of contamination. Diagenesis and Sedimentation: Understanding the diagenetic processes that affect sedimentary rocks and their impact on reservoir quality in petroleum systems. Primary Textbook -- “Geochemical Modeling: Concepts and Applications", by Craig M. Bethke Supporting Texts -- Earth Crust Evolution < "Principles of Igneous and Metamorphic Petrology" by Anthony Philpotts and Jay Ague > Mantle dynamics, Crustal Evolution, and the History of Earth < "Isotope Geochemistry" by William M. White > Geochemical Consequences of Human Influence on Earth's Systems < Biogeochemistry: An Analysis of Global Change" by William H. Schlesinger and Emily S. Bernhardt > ASSESSEMENT --> Analytical Assignments (modules 1-7 & 9) Practical Assignments using modeling software (modules 1-7 & 9) Geochemical Data Sources Assignments (module 8) Midterm Exam Group Project Real-world Application of Geochemical Modelling Modelling a Specific Earth Evolution Scenario Final Exam COURSE OUTLINE --> MODULE1: Introduction to Geochemical Modeling Overview of geochemical modeling and its applications in Earth evolution Introduction to essential software tools (e.g., PHREEQC, Geochemist's Workbench) Basics of chemical thermodynamics and kinetics MODULE2: Thermodynamics in Geochemical Modeling Review of thermodynamic principles Gibbs free energy and chemical equilibrium Activities, activity coefficients, and their significance Introduction to Eh-pH diagrams MODULE3: Application to Understanding Early Earth Differentiation & Mantle Dynamics MODULE4: Geochemical Equilibrium Models Introduction to speciation and complexation reactions Acid-base equilibria in natural waters MODULE5: Applications of Equilibrium Models in Crustal Evolution and Petrogenesis MODULE6: Reactive Transport Modeling Fundamentals of reactive transport processes Introduction to mass transport and advection-diffusion equations Incorporating kinetics into reactive transport models MODULE7: Geochemical Modelling of Weathering MODULE8: Geochemical Data Analysis and Interpretation Introduction to geochemical data sources Data quality control and validation Statistical analysis of geochemical data Applications to interpreting geochemical records in sedimentary rocks and ice cores MODULE9: Advanced Topics in Geochemical Modeling Non-equilibrium thermodynamics in geological systems Modelling coupled processes (e.g., climate-geochemistry interactions) MODULE10: Human Impact on Geochemical Cycles and Environmental Consequences Prerequisites: Historical Geology, Physical Geology, Geochemistry, General Physics I, Calculus III Structural Geology The identification and analysis of tectonic forms to determine the physical conditions of formation and the context of historical geological events in which they occur. Six contact hours (three lecture hours and three laboratory hours), four credits. FIELD TRIPS REQUIRED Upon successfully completing the course, students should be able to explain and apply knowledge and skills central to the domain of professional geologists, including: -Concepts of stress, strain, and deformation -Significance of brittle, plastic, and ductile deformations and their products -Origin and mechanisms of formation of faults, fractures, and folds -Effects of time, temperature, and pressure on deformation -Processes and fabrics that occur in shear zones & their kinematic significance -Field techniques for measuring linear and planar geologic features using a Silva compass -Making and recording observations of mesoscopic rock features in the field -Techniques of presentation/analysis of linear and planar fabric data (stereonets) -Construction of objective cross-sections -Determining deformation histories derived from microscopic and mesoscopic rock fabrics -Deriving tectonic histories from analysis of geologic maps Typical Text: Earth Structure: An Introduction to Structural Geology and Tectonics (2nd edition), 2004, Ben Van der Pluijm and Steve Marshak: Norton and Co. [V&M] Lab Manual: Basic Methods of Structural Geology, 1988, Steve Marshak and Gautam Mitra, Prentice Hall. [M&M] Materials needed for labs and lab tests Coloured pencils (10 or so--good quality) 4H pencils Set of drafting triangles Protractor (accurate to at least ½ degree) Good quality tracing paper Ruler (centimetres and inches) and/or engineer's scale Graph paper (10 or 20 squares per inch) Drawing compass (for making accurate circles) Calculator with trigonometric functions clipboard (for recording data on field trips) Lab --> Completed labs must be extremely legible or they will not be graded. All constructions and calculations must be clearly organised, and the final answers clearly labelled. Lab work in the course will require extensive work outside of class. When the classroom is free, you may use this room to work quietly on assignments. Distracting activities (loud talking, computer games/videos, etc.) are not to be conducted in the room. Late work is not accepted without documentation of a student’s serious personal or medical emergency Field Trips and Field Activities --> The number of contact hours in this course was increased from 5 to 6 hours to enable more field activities and to support student success, particularly in lab. Students must either provide their own transportation to the field site or carpool with other students; if you have serious concerns about this requirement, contact the instructor as soon as possible. Field trips will involve data collection and other field skills; no pets, pals, smoking, etc., are allowed on the trips. All students must sign the liability waiver required by the University. Field Trip 1: Setters quartzite -- collecting orientation data for layering, joint sets Field Trip 2: fault orientations, kinematic data; slip vectors Field Trip 3: Gneiss. Foliation, lineation, fold hinges Field Trip 4: Setters Schist and Cockeysville Marble. Measurement of schistosity, crenulation hinges and cleavages Exams --> Course pedagogy is a combination of "transmission" for introductory knowledge and guided inquiry in developing visualization and graphical skills. Lecture and lab may seem like two separate courses at times, but both aspects are essential to the discipline of structural geology. Exams will require the student to develop the entire spectrum of knowledge skills: recall, comprehension, application, analysis, synthesis, and evaluation. Synthesis Project --> he synthesis project will involve the detailed analysis of a local geological quadrangle and associated rock samples. More details will be provided later in the course Grading --> Lecture Exam I: Brittle Deformation 25% Lecture Exam II: Ductile Deformation 25% Lab Exercises 30% Synthesis Project 20% Topic Outline --> WEEK 1 Introduction to Course; Strike & Dip; Intro. to Maps Outcrop Patterns WEEK 2 Force & Stress; Mohr Circles Attitude Determinations WEEK 3 Brittle Deformation Joints & Veins Stereographic Projections WEEK 4 Faults & Faulting FT1 WEEK 5 Focal Mechanisms; Hydraulic Fracturing & Marcellus Shale Dimension Calculations WEEK 6 Lecture Exam I Determination of slip vectors WEEK 7 FT2: Begin Synthesis Project WEEK 8 Strain & Ductile Deformation FT3 WEEK 9 Folds Fold Analysis WEEK 10 Deformation Fabrics Deformation Fabrics WEEK 11 Ductile Shear Zones Cross-sections WEEK 12 Appalachian Tectonics; Muller & Chapin article Structural Analysis WEEK 13 Lecture Exam II FT4 WEEK 14 Work on Synthesis Project Work on Synthesis Project WEEK 15 Work on Synthesis Project Work on Synthesis Project WEEK 16 Present Synthesis Project Prerequisites: Historical Geology, Physical Geology, General Physics I, and at least Calculus II. Co-requisite or Prerequisite: Plate Tectonics Plate Tectonics Large-Scales processes affecting the Earth’s crust(structure and properties) Course requires much reading to progress through topics. However, it’s easy to become lost in translations. A detailed course topics outline is given to stay on track, and be constructive, productive and sustainable. In science, vocabulary and recycled statements aren’t enough to support one’s science foundation. Tectonics study isn’t valuable without some level of analytical modelling, empirical and data studies, rather than looking at sophisticated historical geological charts. Typical text (optional): Global Tectonics, by P. Kearey and F.J. Vine Supporting Text: Fundamentals of Geophysics” by. W. Lowrie (Cambridge University Press) Tools: Mathematica GPlates, GPlates data sets Grading --> Individual Assignments 20% ? Class Seminar Labs 20% 3 Exams 60% Topic Outline --> I. General Background 1.1) Division of the Earth's interior 1.2) Isostacy 1.3) Satellite altimetry 1.4) Geothermal gradient and heat flow 1.5) Marine magnetic anomalies, paleomagnetism (paleogeography/timescales) 1.6) Global seismicity and focal mechanisms II. Plate Tectonics 2.1) Evolution and breakup of Pangea 2.2) Classification of plate boundaries 2.3) Triple junctions and Velocity-Space diagrams 2.4) Euler poles of rotation III. Divergent Plate Boundaries, Passive Margins, and Basin Analysis 3.1) Continental rifting and evolution to oceanic rifting 3.2) Passive margins: structure and development 3.3) Cratonic basins 3.4) Backstripping and basin analysis IV. Convergent Plate Boundaries 4.1) B-subduction (ocean-ocean & ocean-continent convergence). Examples from the western Pacific (Marianas), Andes, and western cordillera of North America. 4.2) A-subduction (continent-continent convergence). Examples from the Himalayas and Appalachians. 4.3) Episutural basins and continental collision - examples from the Alpine belt of Europe V. Conservative Plate Boundaries 5.1) Transform faults and wrench fault tectonics VI. Mantle convection and the driving forces of plate motion. 6.1) Hot spots 6.2) Configuration of mantle convection 6.3) Driving forces of plate motion LABS (examples)--> Part A Tasks (Empirical/ Data Research) 1. Comprehending and directly developing the Eltanin 19 profile 2. During the 20th century, improvements in and greater use of seismic instruments such as seismographs allowed scientists to learn that earthquakes tend to be concentrated in specific areas, most notably along the oceanic trenches and spreading ridges. By the late 1920s, seismologists were beginning to identify several prominent earthquake zones parallel to the trenches that typically were inclined 40–60° from the horizontal and extended several hundred kilometers into the Earth. These zones later became known as Wadati–Benioff zones, or simply Benioff zones, in honor of the seismologists who first recognized them, Kiyoo Wadat of Japan and Hugo Benioff of the United States. Students will pursue developing empirical evidence to support the various statements. This means students will actually harvest raw data and model to verify the statements. 3. Modelling annual plate motions in mm/year 4. For points where three plates meet will make use of historical data for a designated timeline. Will characterise neighbouring regions based on the movement of the triple joints. 5. Tectonic processes began on Earth between 3.3 and 3.5 billion years ago. How is such determined? Pursue, modelling and data that lead to such estimate. 6. Mid-Ocean Ridge Spreading and Convection Students will identify conventional or premier field methods applied (with identification of instruments) needed to acquire data for observing such two phenomena. What major conclusions or findings have been established. Acquire the raw data to model in order to support such conclusions or findings. 7. simple Euler poles https://sites.northwestern.edu/sethstein/simple-euler-poles/ https://sites.northwestern.edu/sethstein/north-america-pacific-plate-boundary/ PART B The following literature may or may not appear quite repulsive concerning detailed or attentive reading for proper analysis, however, the rewarding prime directive may be to either: (1) Identify the data used to develop or proceed throughout. To find sources for such data, acquire them and develop modelling to confirm (the majors) findings of the literature (2) Analyse analytical models and replicate findings Note: depending on publication or respective journal article one may not be restricted to the applied time frames used in the given journal articles. Can also be extended with more modern data. Crucially, for some articles it may be of great importance to compare more modern data with data for time frame observed in respective journal article. --Gibbons, A., Zahirovic, S., Muller, R.D., Whittaker, J., and Yatheesh, V. 2015. A Tectonic Model Reconciling Evidence for the Collisions between India, Eurasia and Intra-oceanic Arcs of the Central-Eastern Tethys. Gondwana Research --Beghein, C. et al. (2014). Changes in Seismic Anisotropy Shed Light on the Nature of the Gutenberg Discontinuity. Science, Vol. 343, Issue 6176, pp. 1237-1240 --Alec R. Brenner, Roger R. Fu, David A.D. Evans, Aleksey V. Smirnov, Raisa Trubko, Ian R. Rose. Paleomagnetic Evidence for Modern-like Plate Motion Velocities at 3.2 Ga. Science Advances, 2020; 6 (17): eaaz8670 https://science.sciencemag.org/content/suppl/2014/02/26/science.1246724.DC1 --For the following article, after analysis and logistics development is it possible to apply modelling to a GIS? Hayes, G. P et al. (2018). Slab2, A Comprehensive Subduction Zone Geometry Model. Science, eaat4723 --Mason, Ronald G.; Raff, Arthur D. (1961). "Magnetic survey off the West Coast of the United States between 32°N latitude and 42°N latitude". Bulletin of the Geological Society of America. 72 (8): 1259–66 --Raff, Arthur D.; Mason, Roland G. (1961). "Magnetic survey off the west coast of the United States between 40°N latitude and 52°N latitude". Bulletin of the Geological Society of America. 72 (8): 1267–70. Prerequisites: Historical Geology, Physical Geology, General Physics I, and at least Calculus II. Prerequisite or Co-requisite: Structural Geology Geographic Information Systems: The field of Geographic Information Systems, GIS, is concerned with the description, analysis, and management of geographic information. This course offers an introduction to methods of managing and processing geographic information. Emphasis will be placed on the nature of geographic information, data models and structures for geographic information, geographic data input, data manipulation and data storage, spatial analytic and modelling techniques, and error analysis. The course is made of two components: lectures and labs. In the lectures, the conceptual elements of the above topics will be discussed. The labs are designed in such a way that students will gain first-hand experience in data input, data management, data analyses, and result presentation in a geographical information system. The basic objectives of this course for students are: 1. To understand the basic structures, concepts, and theories of GIS 2. To gain a hand-on experience with a variety of GIS operations Typical Texts: Longley P.A., M.F. Goodchild, D.J. Maguire, D.W. Rhind, 2011.Geographic Information Systems and Science. John Wiley and Sons Chang, K.T., 2012. Introduction to Geographic Information Systems (Sixth Edition). McGraw Hill, New York de Smith, M., Goodchild, M., Longley, P., 2013. Geospatial Analysis: A Comprehensive Guide (www.spatialanalysisonline.com) Tools: A GIS of your choosing; students will be debriefed on operational requirements Mathematica Google Earth Google Maps Resources: https://www.google.com/earth/outreach/learn/ support.google.com/maps/answer/144349 There are highly established freeware GIS tools for use. Premier such available are SAGA GIS, ILWIS, MapWindow GIS, uDig, GRASS GIS and others; check Goody bag post. NOTE: GRASS GIS Will be preference for GIS. Major priorities are sustainable skills in logistics, data management, accessibility & integration of data sets for project development and exhibition. Project(s) to have considerable life cycles with future use. Additionally, Wolfram Mathematica tools, Google Earth and Google Maps can possibly coexist or be a substitute in such a instruction environment, primarily for rapid data visualisation. Course is concerned with the ability to develop meaningful professional data analysis and visualisation of sustainable value to whatever specified target audience. Unique talent development among such tools are encouraged, under the condition that the interests or demand of the target audience is appeased, of high quality. Some highly capable students will be able to develop projects with various systems, while for others finding an environment that suites them is key (highly dependent on what they comprehend and the effort they give). Mathematica has the computational prowess among the rest, but isn’t visually savvy or accommodating as the rest. For those with high preference for Mathematica the following search topics in Wolfram Documentation and topics from Wolfram Blog will prove quite fruitful Earth Sciences: Data and Computation Geographic Data & Entities Geospatial Formats Geodesy Cloud Execution Metadata Create Instant APIs https://community.wolfram.com/content?curTag=geographic%20information%20system It’s recommended that those who choose such Mathematica path are those who have successfully completed the Data Programming with Mathematica course to a high degree, or of their own business have deployed Mathematica successfully with various projects. It takes a bit of skill with methods emanating from the above Mathematica (search) topics; not the favouritism propaganda you have acquired. Class Presentation --> Students need to review a journal article (or multiple articles) and give a presentation in the class. The article or articles can relate to GIS concepts, theories, or applications. An article in your discipline is preferred for you to review, for the reason that it would help you to think how to apply GIS in your work in the future. To present your reviewed article, you need to prepare five to eight slides in the format of PowerPoint, which would take approximately five to six minutes to present. In your slides, one of them would be how GIS is helpful in the article. You will have to give a small demonstration of some partial development for your project that substantially relates to your goals with whatever choice of tool employed. Followed by some substantial development (already done) with a GIS or other tool, or combination. You will have two or three minutes to answer the questions raised by the audience. Grading --> Lab Exercises 30% Exam I 25% Exam II 25% Presentation 20% Labs --> There are two components for labs: 1. Having GRASS GIS as preference concerns standard developments with course progression. 2. Extracurricular activities with Addons for GRASS GIS. Primarily, there must be strong development for a specific topic in (1) in order to commence with a respective Addons activity -- https://grass.osgeo.org/grass82/manuals/addons// Multicriteria decision decision analysis must be one topic for Addons extracurricular activities. An example: Massei, G., et al (2014). Decision Support Systems for Environmental Management: A Case Study on Wastewater from Agriculture, Journal of Environmental Management, Volume 146, Pages 491-504 However, PROMETHEE is not our only interest, and multiple MCDA addons will be pursued. Course Outline --> WEEK 1 Course Overview GIS Overview The Nature of Geographic Information WEEK 2 Data Representation Measuring Systems: Location – Coordinate Systems Data Representation Measuring Systems: Location – Coordinate Systems (Continue) WEEK 3 Data Representation Measuring Systems: Location – Coordinate Transformation Data Representation Measuring Systems: Topology Measuring Systems: Attributes WEEK 4 Data Representation Spatial Data Models: Introduction to spatial data models Spatial Data Models: Raster data models Data Representation Spatial Data Models: Relational Data Models Spatial Data Models: Vector Data Models (I) WEEK 5 Data Representation Spatial Data Models: Vector Data Models (II) Data Representation Spatial Data Models: TIN Summary of Spatial Data Models: Raster, Vector, TIN WEEK 6 Data Representation Linking attribute data with spatial data Recent Development of Data models WEEK 7 GIS Database Creation and Maintenance (I) Data Input & Editing GIS Database Creation and Maintenance (II) DBMS and its use in GIS WEEK 8 Review for Exam 1 Exam 1 WEEK 9 GIS Database Creation and Maintenance (III) Metadata / Database creation Guidelines / NSDI Data Analysis Measurement & Connectivity WEEK 10 Data Analysis Interpolation WEEK 11 Data Analysis Digital Terrain Analysis Data Analysis: Statistical Operations & Point Pattern Analysis WEEK 12 Data Analysis Classification Data Analysis GIS-based Modelling and Spatial Overlay (I) WEEK 13 Data Analysis GIS-based Modelling and Spatial Overlay (II) Data Analysis Summary Uncertainty WEEK 14 Geo-representation, Geo-presentation, and GeoVisualization GIS Applications WEEK 15 Student Presentations Student Presentations WEEK 16 Review for Exam Exam II Prerequisite: Historical Geology, Physical Geology, Geological Field Methods, Upper level Standing. Field Geology Geology is first and foremost a field science. Field geology and field geologists provide literally the ground truth for geologic concepts and theories of how the earth works. The degree to which we, as geologists, are successful observers and interpreters of rocks in the field depends in large measure on what we are prepared to see and record. Without sufficient experience and preparation, we can’t attach meaning to (and thus frequently ignore) what we don’t recognise or understand. Field experience generates purpose and professional relevance. Field proficiency has long been a distinguishing characteristic of our science. As a geoscientist, you are expected to be a proficient scientific observer and recorder. Your unique skills and training in this area separate you from lawyers, engineers, chemists and other professionals with whom you might one day work. Without proper preparation, including a strong grounding in field methods, we would be little better than rockhounds out for a day of casual collecting. Field geology is not merely collecting data and samples; it is about making sense of the geology around you, about making geologic interpretations. Landscapes are histories, with time marked by boundaries in the rocks, soil and sediment. A geologic map or a measured section is the articulation of that history, with each line marking a before and after, a hiatus that might last a second or a billion years. Through our maps and graphical logs, we represent time as space. The ability to create, read and interpret such product is best developed from training and practice in a field setting. It all begins by making and recording observations. An accurate record in the form of a map, measured section, photograph, sketch, a carefully documented sample, field notes, etc. provides a permanent, solid basis upon which to develop testable ideas and interpretations – the plot of the story. Without such evidence, interpretations are fanciful fables; there is no scientific basis to objectively evaluate them. Course is designed to engage you in the process of inquiry over the course of a semester, providing you with the opportunity for independent investigation of a question, problem, or project. You should therefore expect a substantial portion of your grade to come from the independent investigation and presentation of your work. The course consists of ~ 15 single or multi-day projects that focus on aspect of field description and interpretation. Products generated include measured sections, reports, photopan interpretations, cross sections, maps and stereonets. NOTE: realistically activities will take more than 6 weeks as mentioned later on. Such 6 weeks is simply ideal, say, if everything goes right. For the case that black swans appear and cancels visits for a substantial amount of destinations course will be canceled for the term and students will have to reschedule for a future term; course is highly dependent on data that’s of relatively high volume and the quality. This is arguably the most crucial course towards being called a real geologist. As well, there may be other opportunities available in the vast ambiances with other “treasures” such as pitch lakes (La Brea), mud volcanoes, geysers, lakes having pebbles with high amounts of distributed coloration, rainbow rock sediments, natural hot springs, high cliff waterfalls (and/or regular waterfalls), basins or other geologies being fossil fuel reserves, etc. For such distinct exhibitions in nature, if the opportunities arise field activity must be extended to accommodate field study for the crucial or unique properties/characteristics. Course will require dedicated and intricate planning and logistics. Transportation, shelter (only when extreme cases arise), self preservation, health and equipment (vitals and transporting) are crucial. Required Materials: Field notebook (e.g., engineer’s field book) Clipboard (8 1/2 x 11 size) with cover Hand lens (10x) Geology Kit Small squirt bottle of dilute (approx. 10%) HCl Containers for samples to possibly label Grain size card Six-inch ruler (best is the Post ruler with protractor on it) Protractor (bring spare rulers & protractors; many students lose several) Pencils and erasers (again, the number depends on how many you lose) 2 or 3 drafting (mechanical) pencils (recommend Pentel or equivalent 0.5 mm or 0.3 mm lead, hardness F or 3H) and spare leads Coloured pencil set that will keep a point (at least 10 colours); pencils with hard, water-fast lead are preferred Pencil sharpener or pointer, and/or sandpaper – for coloured pencils Technical pens with fine-line points and black ink (Sizes 00, 0, 1, are desirable) Tablet of 8 1/2 x 11” tracing paper Tablet of 10 square to the inch of 8 1/2 x 11” graph paper Liquid paper (optional) The textbooks and lab manual Laminated Geological Catalogues for later cross examination Calculator Watch Carrying bag (shoulder bag or daypack) Proper field clothes, long pants, long-sleeve shirts, jacket (see note on gear) Sun screen/block lotion Hat, wide brim Hiking boots, broken in (avoid non-lace boots; see note on gear) Rainwear (it will rain; see note on gear) Canteen (2 or 3, one-quart/litre water bottles, a Camel-Back or some other water storage container) Warm sleeping bag and pad** (see note on gear) Tent (can be shared; see notes on gear) Towels, washcloth Plate, cup, silverware GPS Desirable Materials --> GIS (GRASS GIS with addons use) GPS Google Earth Google Maps Digital Camera or very capable charged smart phones with smart phone with excellent range & focus Masking tape Scotch tape Tweezers (important for run-ins with cactus) Insect repellent Minor first aid kit for bug bites, thorns, blisters (moleskin), etc. Small pair of binoculars Whistle (if you are prone to getting lost and have a weak voice) Safety goggles or other eye protection (see field course policy handout regarding this and hard hats) Sharpie markers to label rocks Prohibited Items --> Consumption of alcohol in vehicles Illegal drugs Firearms Excessive exposure or flaunting of currency Highly gaudy fashionable apparel and jewelery Luxury Vehicles All participants should have their heads on a swivel and be attentive of your surroundings. Music playing during active operations is prohibited; refrain from such as well at camp sites because your life may depend on the alertness and consideration for the presence of others. Concerns that can likely have cumulative academic consequences and legal ramifications: Littering Low temperature high temperature combustible substances Illegal and unregulated fires Pesticides unsanctioned with environmental protection Toxic substances Substances with absurd Ph levels (high or low) that may be damaging to environment Levels of exhaust emissions from vehicles High volume audio and video Harassing or capturing animals Releasing animals unnatural to ambiance ecosystem Unsanctioned venturing, or ditching officially recognised groups There will be at least 12 difference sites considerably distant from each other. However, the number of sites to visit will depend on the field activities such sites can support; yet don’t want the majority of activities carried out be centred on a minimal number of places. WEEK 1 -Interpretation of depositional processes. Seeking environments where tertiary faulting and uplift causing the exposure of a shelf-to-basin setting that contains both carbonate and terrigenous sediments. -High elevation of carbonate and clastic shelf, slope and basin deposits are laid out in spectacular vistas. We will present the stratigraphic setting, and then sketch and interpret several of these major walls in terms of stratal geometric relationships and depositional processes. Will be interested in multiple sites for such. -Aeolinites and evaporites – sedimentology and stratigraphy WEEK 2. Volcanology -Geology and volcanology of a supervolcano. Classic locality for understanding the nature of large-volume caldera eruptions. Exception preservation and outstanding exposures of Pleistocene eruptive products (ash flow and air fall tuffs, lava flows, lava domes) provide an unparalleled opportunity to examine, map and describe the hallmarks of these gigantic eruptions. A field trip our first afternoon examines the caldera proper and its youngest products. The main eruptive rocks and their precursors are studied the following day. Days 2-4 are devoted to learning to recognize, interpret and map the intrusive and eruptive products of calderas through a mapping exercise that examine the geometry and sequence of volcanic deposits. -Visit to an active volcano may or may not be feasible, but if the opportunity arises field activity must be extended to accommodate field study for the crucial or unique properties/characteristics. -Late Miocene to Pliocene eruptive rocks and interlayered sediments exposed in gorges. To document and map the eruptive history of the Servilleta Basalts, older more silic lava flows and domes, and the interlayered alluvial fill. What are the relative ages of the rocks, how do we tell them apart, and when did the river gorges form? WEEK 3. Basement-Cored Structures -Paleoshorelines -With topographic maps and aerial photos, we will map the structural and stratigraphic relationships and interpret the subsurface geology of a small Laramide anticline. This will be accomplished with the aid of a stereonet and cross section. We will also visit some regional geology and become familiar with the complexity of natural fractures. This relatively simple mapping and cross section exercise is a prelude to later, more complex mapping and subsurface interpretation. -For whatever region to observe Laramide fold and fault geometries and speculate on their subsurface continuations. This information will inform your ~E-W regional cross section of whatever (mountain) range and Basin at the latitude of such region, which you will complete before day’s end. WEEK 4 – 5. Structural Geology of Thin-skinned Deformation -Growth strata. Basin and older folded and faulted stratigraphy are brought above ground to partially onlapped by strata deposited, and involved uplifts. -Measure and map in cross section the geology and geometry of the leading edge of the whatever belt; interested in a Late Cretaceous to Early Paleogene belt of thin-skinned deformation. The end result of our field work is a cross section constrained by surface observation, map data, and a seismic reflection profile. You will learn how practicing structural geologists make use of a combination of tools and techniques to arrive at a constrained subsurface interpretation in a structural complex setting. -You will learn how to map, measure and describe the geology of this fold-dominated salient of the whatever Belt. This is accomplished during two 3-day projects, a day off, and a field mapping test. Each of the projects share common components: Day 1: Introduction to setting and stratigraphy Compile a stratigraphic column of map units, recon. the field area, begin mapping Day 2: Continued mapping Begin constructing cross section and stereonets Day 3: Finish mapping Turn in map, cross section and stereonets Evening lectures provide information on stereonets, cross-section construction and the geology of the Region WEEK 6. Ore deposits -Giant porphyry copper deposits (or other). Here we spend four days documenting and unravelling field relationships among deformation, plutonism, contact metamorphism and mineralization within facies equivalents of the same rocks mapped in the previous two projects. -This project integrates different geological disciplines to unravel the geological history of this late 1800’s (or whenever) mining district or area. Field data will be collected over four days to understand the sedimentary, structural, metamorphic, magmatic and hydrothermal history of this area and to produce a concise report that synthesizes this information. In addition to introducing concepts in metamorphic and ore geology, this exercise offers a unique chance to integrate different types of data to understand the geological history of an area – a common exercise for any earth scientist. OUTCOMES OF TRAVELS AND ACTIVITIES --> 1. Sedimentary geology A. Classification of rocks and sediment by texture You must be able to classify terrigenous sediments and rocks by texture (e.g., poorly sorted, immature, fine-grained sandstone). This means that you must be able to identify the mean grain size, estimate the grain sorting, recognize the four stages of textural maturity, and recognize grain shape and roundness. B able to tell if the sorting reflects a unimodal, bimodal or polymodal grain distribution. Impact scars on pebbles and larger grains are important to identify. Rock colour also reflects important aspects of the rock. You must have comprehension of the factors that control these sediment/rock characteristics. For sandstones and conglomerates be able to estimate the abundance of framework grains, matrix, cement, and porosity using your hand lens. You must be able to distinguish those rock aspects that are depositional in nature from those that result from weathering. For example, weathering commonly results in the oxidation of pyrite and other ferrous minerals, differential dissolution of minerals, hydration, oxidation, and case-hardening of joints. Precipitation of travertine crusts and soluble white salt crusts (efflorescence), as well as Liesegang bands, are post-depositional products. In addition, it is usually possible on outcrop to recognize basic lithology (e.g., sandstone, limestone, shale) by weathering habit. Be able to classify carbonate rocks according to the Dunham classification, including identification of major grain types. Know the major taxonomic groups of invertebrate fossils and their environmental significance. Know the marine evaporite mineral sequence. B. Classification of rocks and sediment by mineralogy Be able to classify sediment and rocks by mineralogy (e.g., arkose). For sandstones be able to estimate the type of common cements (quartz, calcite, dolomite, siderite, iron oxides, kaolinite), the abundance of QFR components, and clan name using the Folk classification. Understand the relationship between mineralogy, source area, and other controls such as climate, tectonism and nature of transport. C. Sedimentary structures You must be able to identify sedimentary structures and understand under what conditions they form. Be able to identify common fossils, know their age ranges, and environmental significance. Below are listed some common sedimentary structures and other features of sedimentary rocks. You should be able to recognize these, understand how they form, and interpret their genetic significance. Laminations Wind-ripple laminations Trough cross-strata Tabular cross-strata Current ripple and climbing ripple cross-strata Wave ripple cross-strata Hummocky cross-strata Textural mottled bedding Structureless (massive) bedding Graded and reverse graded bedding Contorted bedding Nodular bedding Flaser and lenticular bedding Herringbone cross-strata Scour-and-fill structures Channel walls and channel-fills Cryptalgal laminations, stromatolites (laterally linked & stacked hemispheres) Bouma sequence Wave and current ripple marks Trace fossils: burrows, tracks, and trails Flute casts, groove casts, load casts Parting lineation Mud cracks Stylolites Liesegang bands Chert & other nodules, calcite-cemented concretions (& other types) Cone-in-cone structure Adhesion structures Breccia Paleokarst Evaporite moulds Inter vs. intraparticle porosity Boundstone Geopetals Fenestral fabric D. Depositional and diagenetic environments and processes You must be able to make a basic interpretation of environment of deposition (e.g., deep-sea turbidite sequences, meandering fluvial channel). You should be able to determine whether the seafloor was well oxygenated, suboxic, anoxic. Clues are TOC (reflected in rock colour), presence of absence of trace fossils, abundance of pyrite, etc. Most information is derived from the larger-scale geometry of the strata. You should always scan an outcrop for the continuity of beds, the overall strata arrangement, faults, channel structures, and vertical trends before studying the rock up close. For carbonate and evaporite environments, review the shelf-to-basin facies tract, the environmental factors important for carbonate/evaporite production, the different styles of carbonate shelf architecture as a function of changes in sea level, climate, time in geologic history. Review the principal mechanisms proposed for: changing sea level dolomitization subaerial and subaqueous evaporite deposition cyclic sediment deposition. E. Field methods You must be able to perform basic field procedures including: measuring a section with a staff and Brunton compass or similar instrument identifying textures and mineralogies with a hand lens, and using a Brunton compass or similar instrument to measure bedding and foreset orientations operate a hand-held GPS instrument. F. Data presentation You must be able to display geological information in various formats including vertical sections scaled field sketches cross-sections neatly drafted maps stereonets G. Basin-scale processes You must have a basic understanding of (1) tectonic basin types (2) the types of environments associated with these, and (3) the types of sediments characteristic of the different types of basins and source areas. H. Global-scale processes You must have a basic understanding of the depositional architectures and their scales as a function of cycles of sea level, climate and tectonism. Know the general history of Earth change (e.g., greenhouse/icehouse periods, first-order sea-level curve), and the basics of higher order processes such as orbital forcing of Earth’s climate. 2. Structural Geology & Mapping Notes, texts, old labs and web sites for prerequisite courses are particularly valuable resources for review. A. Be able to read a topographic map, construct a topographic profile along a line of section, and have the ability to accurately locate yourself with a topographic map. B. Have a good understanding of strike lines (structure contours), 3-point problems, the rule of V's, and how these are manifest on geologic maps by unit contacts, fault traces, fold axial traces. C. Be able to correctly use a compass to measure the attitudes of linear and planar features. D. Be able to construct stereographic projections of the attitudes of lines and planes, and determine a fold axis from attitude measurements of folded layers. E. Be able to appropriately label maps and cross sections (and where these items belong on a finished product): title, author, date, north arrow, scale bar, contour interval, stratigraphic symbols, explanation of symbols, location of cross section; endpoints of cross section, orientation of cross section, vertical scale, and vertical exaggeration. F. Be able to draw a structural cross section; know how to project data from a map into the plane of a cross section. G. Know fold terminology and map symbols: fold axis, axial surface, hinge line, axial trace, plunge, fold limbs, cylindrical, overturned vs. upright, parallel vs. non-parallel, angular vs. curved. H. Know fault terminology and map symbols: thrust, normal, strike slip, footwall, hanging wall, displacement, dip and strike separation, fault tip, fault ramp, detachment, listric, thin-skinned vs. thick-skinned, releasing and restraining bends. I. Be able to interpret a geologic map, including relative ages from superpositional or cross-cutting relationships, dip directions from map patterns, anticlines vs. synclines and directions of plunge, axial trace symbols, up vs. down sides of faults from map patterns. 3. Igneous Geology A. Know how to classify igneous rocks using compositional criteria (intrusive rocks: granite, granodiorite, gabbro, peridotite; extrusive rocks: rhyolite, andesite, dacite, basalt) and textural criteria (tuff, welded tuff, vitrophyre, etc.), and apply appropriate adjectives (porphyritic, aphanitic, phaneritic, etc.). B. Be able to identify common minerals in igneous rocks with a hand lens. These include, but are not limited to, quartz, plagioclase, k-feldspar, biotite, muscovite, clinopyroxene, amphibole (hornblende) and olivine. C. Have an appreciation for the geological settings in which different igneous rocks might be found 4. Metamorphic Geology A. Know how to classify metamorphic rocks (slate, phyllite, schist, gneiss, hornfels) and apply appropriate adjectives (granoblastic, porphyroblastic, foliated, etc.). B. Be able to identify common metamorphic minerals with a hand lens. These include, but are not limited to: i) minerals common to most metamorphic rocks: quartz, plagioclase, k-feldspar, biotite, muscovite, chlorite, ii) pelites: garnet, aluminosilicates (andalusite, kyanite, sillimanite), staurolite, iii) metabasites: clinopyroxene, orthopyroxene, amphibole (hornblende, tremolite/actinolite), and iv) metacalcsilicates/metacarbonates: calcite, dolomite, talc, tremolite, wollastonite, diopside. C. Have an understanding of the concepts of metamorphic facies, P-T and T-X grids and isograds, including an appreciation of the dependence of mineral assemblages on rock composition, temperature, pressure and fluid composition/availability. D. Understand the relationship of fabrics defined by metamorphic minerals to minor and major folds and faults/shear zones. E. Know metamorphic index minerals for pelitic and mafic rocks. Prerequisites: Physical Geology, Historical Geology, Geological Field Methods, Geomorphology, Mineralogy, Sedimentology & Stratigraphy, Structural Geology, Geographic Information Systems

Global Geophysics Application of classical physics to the study of the Earth and the solution of problems in Earth sciences, including analysis of geomagnetics, the Earth’s gravitational field, seismic analysis, sequence stratigraphy, well log interpretation, and applications to petroleum exploration. Typical text: The Solid Earth: An introduction to Geophysics, 1st Edition. Author(s): C.M.R. Fowler. Publishers(s): Cambridge University Press (1997) Will also make use of Mathematica’s “Earth Sciences Data and Computation” and “Geographic Data & Entities”. Some projects will require a GIS. Assessment --> Weekly lab assignments: 70% 3 Exams: 30% WEEK 1-- Lect 1: Introductions, elementary physics (wave theory) Lect 2: Reflection and refraction Lab 1: Basic physics (as applied to geology) WEEK 2-- Lect 1: SP and resistivity logs Lect 2: Gamma ray logs Lab 2: Well log correlation exercise 1 WEEK 3-- Lect: Generation of petroleum; Migration of petroleum Lab 3: Well log correlation exercise 2 WEEK 4-- Lect 1: Petroleum reservoirs Lect 2: Neutron activation logs; Density and other logs Lab 4: Mapping exercises WEEK 5-- Lect 1: Isopach maps; First Exam (take-home) Lect 2: Fence-post diagrams and other graphical techniques Lab 5: Seismic correlations WEEK 6-- Lect 1: Introduction to seismic methods Lect 2: Seismic stratigraphy Lab 6: Seismic correlations WEEK 7-- Lect 1: Sequence stratigraphy part 1: surfaces and systems tracts Lect 2: Sequence stratigraphy part 2 Lab 7: Sequence stratigraphy interpretations WEEK 8-- Lect 1: Plate motions on the Spherical Earth Lect 2: Plate circuit diagrams Lab 8: Field surveys with GPS receivers WEEK 9-- Lect 1: Earthquake seismicity Lect 2: Earthquake seismicity; 1st motions studies Lab 9: Seismic reflection modeling WEEK 10 -- Modelling the Earth’s internal temperatures 1. Analysing seismic waves to determine the depth of the boundaries. 2. Determine the pressure at the boundaries from a mathematical relationship between depth and pressure. 3. Then, model the likelihood of different phases (primarily made from O, Fe, Si and Mg) undergoing the transformation. For instance, the transformation of olivine is likely the cause of the 410 km discontinuity. So we subject a sample of olivine to the pressure found at 410 km, then heat it up until it transforms to a new phase. The temperature of the earth at 410 km is then assumed to be the temperature at which the olivine transformed. 4. In such a way, the pressure/temperature profile of the earth is constructed. This profile is called the geotherm. Hence, without relying on “Wolfram Alpha” type tools build a temperature profile (geotherm) for the inner parts of Earth based on prior knowledge and skills applied. 5. Since Earth is around 94% Mg, Fe, Si and O, then the mineralogy of the earth can be studied by examining the phases into which these elements combine along the conditions of the geotherm. More elaboration on the temperature of Earth’s core 1. The core consists of two distinct regions, being the inner core which is solid, and the outer core which is liquid. We know this by examining the velocity profiles. Shear waves do not propagate in the outer core (why?). 2. The (mostly) Fe core. Hence, to vindicate statement 1, it’s logical to analyses the phases of Fe regarding temperature and pressure. Comprehension of conventional phases (alpha, delta, gamma, liquid). The epsilon phase. How are phases boundaries determined? X-ray analyss and Raman spectroscopy analysis Saxena, S. K. et al. (1995). Science, volume 269 Yoo, C. S. et al (1995). Science, volume 270 D. Andrault (1997). Science, volume 278 Transformations related to pressure and vibration. Slopes involving the “greeks”. Will the phase diagram match the geotherm data at the inner/outer core boundary? Why or why not? Gilder, S. & Glen, J. (1998). Science, volume 279 Steinle-Neumann, G. et al (2001). Nature, volume 413 Buffet, B. A. & Wenk, H. R. (2001). Nature, volume 413 3. Theory & Experiments Boehler, R. (1993). Temperatures in the Earth's core from melting-point measurements of iron at high static pressures. Nature 363, 534–536 Chen, G. Q. & Ahrens, T. J. (1996). High-Pressure Melting of Iron: New Experiments and Calculations. Philosophical Transactions: Mathematical, Physical and Engineering Sciences , Vol. 354, No. 1711, pp 1251 - 1263 Jephcoat, A. P. & Besedin, S. P. (1996). Temperature Measurement and Melting Determination in the Laser-Heated Diamond Anvil-Cell. Philosophical Transactions: Mathematical, Physical and Engineering Sciences, Vol. 354, No. 1711 pp. 1333-1360 WEEK 11-- Lect 1: Climate Heat cycles characterstcs and modelling Lect 2: Geothermal heat flow Assisting literature: Morgan P. (1989) Heat Flow in the Earth. In: Geophysics. Encyclopedia of Earth Science. Springer, Boston, MA. Heat flow characteristics of the Earth; Heat flow modeling Lab 10: Heat flow modeling and simulation (climate and geothermal) WEEK 12-- Lect 1: Review from week 11 deduced magnetic properties of the Earth’s core. The dominant main field originates in the Earth's fluid core. The second internal contribution comes from magnetized rocks in the lithosphere. The third contribution, varying rapidly in time, comes from outside the Earth (External field). Amongst the sources which contribute to the geomagnetic field, the oceanic magnetic field is the faintest. Geomagnetism theory and application. Lect 2: Interpretation of geomagnetic data Lab 12: Interpretation of geomagnetic data WEEK 13-- Lect 1: Geochronology theory and application Lect 2: ... Lab 13: Calculation of isochron and Concordia diagrams and age estimates WEEK 14-- Lect 1: Kinematics of fault systems Lect 2: Thrust fault geophysics and geometric constrains Lab 14: Balanced cross-sections WEEK 15-- Lect 1: Physics of exhumation models Lect 2: Modelling exhumation Lab 16: Modelling exhumation WEEK 16-- Lect 1: Earth’s gravitational field; Correlations with tectonic boundaries Lect 2: Gravity anomalies; Isostacy Lab 10: Gravimeter data collection and reduction. Modelling. Prerequisites: Historical Geology, Physical Geology, Calculus I & II, General Physics I & II, Geological Field Methods, Ordinary Differential Equations, Data Programming with Mathematica. Co-requisite: Hydrology Based on such prerequisites students will be on track to be currently taking or have taken Calculus III when they have matriculated into this course. Hopefully the latter prevails. Hydrology Students will be expected to acquire a basic understanding of: (1) The hydrological cycle: where does the water come and where does it go? (2) The use of simple probability and statistics to describe geohydrologic phenomena. (3) The process of interception, evaporation and transpiration, whereby water is transferred from geosphere to atmosphere. The generation of runoff, factors controlling storage and transfer of water within the channels. (4) Flow through porous media and treatment of saturated flow with Darcys law (5) Well hydraulics, estimation of hydraulic conductivity from slug test. (6) Principles governing the flow in an unsaturated condition. (7) Contaminant migration in underground aquifer. (8) Water quality issues. Typical Text: Fetter, 2003: Applied Hydrogeology, Prentice Hall Tools --> Mathematica GIS (GRASS GIS with addons use) Hydrology (RHESSys) SWMM HEC-RAS HEC-HMS iRIC MODFLOW PRMS (Precipitation Runoff Modeling System) NOTE: will make emphasis use of Mathematica, HEC-HMS, MODFLOW and RHESSys in lectures and labs for modelling and computation. Grading --> Attendance 5% Homework 15% Labs 35% 3 Exams 45 % Topic Outline --> Chapter 1. Introduction Delineation of watershed, hydrological cycle, water as a resource, water supply in whatever ambiance. Chapter 2. Atmospheric aspects of hydrological cycle Weather and climate, humidity, latent heat of condensation, fusion and sublimation, and evapotranspiration Chapter 3. Precipitation and runoff Cloud, formation of precipitation, rise of the air mass, temporal and spatial distribution of precipitation, method of measuring the precipitation amount and effective precipitation depth in a watershed. Chapter 4. Stream flow Runoff, infiltration, effluent and influence streams, runoff, baseflow separation , stream flow velocity profile hydrograph and routing (rating) curves, stream ordering and bifurcation ratio. Chapter 5. Flood analysis Flood frequency duration, recurrence interval, flood attenuation and translation, hydraulic jump, Reynolds number and its relationship to turbulent and laminar, steady and uniform flow. First Midterm Test Chapter 6. Groundwater Basics 1). Primary and secondary porosity, specific yield, perched water table, aquifer types. Hydraulic head and potential. Homogeneous, heterogeneous aquifers, intrinsic permeability and hydraulic conductivity. 2). Darcy’s law, groundwater discharge (Q=Kdh/L*A), Validity of Darcy’s law 3). Storativity, specific storage (Ss) specific yield (Sy) and storativity (S) 4). Major aquifers in ambiance Chapter 7. Principles of Groundwater-Flow 1). Flow nets and conductivity ellipse, tangent law, steady and transient flow 2). Dupuit assumption. Chapter 8 (14,15,-16,17 in the text). Well Hydraulics. 1). Pumping test and Theis type curve analysis, Well drawdown, cone of depression in confined and unconfined aquifers, step-drawdown and its purpose, 2). Jacob method, distance drawdown method of conductivity and storativity Second Midterm Test Chapter 9. Leakly confined aquifer and slug test 1). Leaky confined aquifer, well screen, partial penetrating well. 2). Rising and falling head slug test, conductivity estimate from slug tests. Chapter 10. Multiple wells. 1). Multiple wells and superposition principles 2). Image wells for barrier boundaries 3). Image wells for recharge boundaries Chapter 11. Groundwater modeling 1). Model types and popular modeling programs. Finite difference and finite elements 2). Boundary conditions Chapter 12. Unsaturated flow 1). Capillary rise, soil characterisitic curve, hysteresis 2). Infiltration rate and tests, perc tests Chapter 13. Mass transport of solutes 1). Advection, dispersion and diffusion concepts 2). Types of common contaminants: Organic and Inorganic 3). Remediation Chapter 14. Water Law 1). Common laws and Legislative laws 2). Riparian Doctrine and Prior appropriate doctrine 3). Water Regulations Final Exam LABS --> -Hydrology Problems. Students will be partitioned into groups in lab where they are to assigned problems in hydrology (3 – 5). Such group exercises will be done in various labs where types of problems and level of difficulty is dependent upon point in course lessons. Students will be asked to demonstrate their methods of solution to class. Lab will have quiz periods at times based on such questions assigned to various groups. Such type of activity will be done at the beginning before other mentioned activities. -Introduction to Contouring and Digital Elevation Models. Try to find professional development to compare with. -Climate data is available from various sources. Cooperative weather stations are set-up throughout, providing a historical record of weather data. Some of these stations date back to quite some time. The types of climate data include precipitation (daily, monthly, yearly), air temperature, humidity, precipitation, etc. Meteorological records represent a fundamental hydrologic data set from which to build an understanding of the Earth's hydrosphere. The objective of this lab exercise is to use spreadsheet software or Mathematica (or R) to analyse and interpret hydrologic data, in this case, climatological information. Will need creativity/ imagination to develop something substantially meaningful. Charts will be done manually and with technology tools, ranging from Mathematica to a GIS. Try to find professional development to compare with. -Associating countering and digital elevation models to hydrological data analysis development. One would like to characterise seasonal precipitation for particular elevations. Charts will be done manually and with technology tools, ranging from Mathematica to a GIS. -Water budget of ambiance of particular region: precipitation and evaporation. A guide idea: https://people.wou.edu/~taylors/es476_hydro/monolake.pdf Not restricted solely to Excel. Charts will be done manually and with technology tools, ranging from Mathematica to a GIS. -Developing an isohyet map for a given area or region. Charts will be done manually and with technology tools, ranging from Mathematica to a GIS. Try to find professional development to compare with -Region or area ice budget The objective of this lab is to analyse glacial ice budgets for a select set of areas and to determine the factors that control the spatial distribution of ice and snow in the whatever ambiance. Glacial retreat is a high priority. Such will be done for 5 - 35 years. Additionally comparing each year and determining whether there’s variation in the ice budget over time, and how drastic is the variation over time. Scatter plots and column charts (histograms) may or may not be useful in early stages. For particular elevations will also like to develop a temperature time series for decided upon time span. For particular elevations will also like to develop a precipitation time series for decided upon time span. For particular elevations or chosen peaks (or whatever) how well are temperature and precipitation correlated. Is there any conclusive relation between elevation, temperature and precipitation? Is there any conclusive relation between latitude, elevation, temperature and precipitation? Is there any conclusive relation between ice volume, latitude, elevation, temperature and precipitation? Describe all relationships that you observe relating mountain elevation, latitude position, ice volume, and ice areas. Is there a consistent pattern that emerges Which mountain or whatever is associated with the greatest ice volume, and the least? Explain the relationships that you observe. -Surface water. Surface water processes are driven by the interplay between meteorological processes and geomorphic configuration of the landscape. Watersheds of varying scale represent the fundamental hydrologic unit at the Earth's surface. This lab employs data techniques that are commonly applied to the analysis of surface water hydrology. Flood climatology. List of world record rainfall intensities (inches of precip.) for specific durations (lengths of time). The rainfall and durations may or may not be expressed as Log 10 values; may have to convert back to original values. Plot the data on a scatter chart with a (log x) axis (duration in days) and a (log y) axis (total rainfall inches). Format the scatter plot with titles, labels and grid lines. Fit a power-function curve to the data. Answer related questions. Historical Discharge Analysis / Recurrence Intervals. Whatever River at Whatever State Park is gauged by the National Geological Survey. Discharge data have been collected since whenever. Develop a summary of annual peak discharge data from whatever gauging station. The recurrence interval of a given flood discharge is commonly calculated from a set of historical data. Develop the annual peak discharges for the Whatever gaging station; represents the maximum discharge recorded at the station for a given water year. AMBITION: recurrence interval of annual peak discharge represents an estimation, based on the historical record, of the probability of a given flood discharge occurring over a given time period. For example, the "100 yr flood" is a flood-discharge magnitude that has a probability of occurring once every 100 yrs. Generally, the lower the magnitude of event, the statistically more frequent the chance of occurring, and vice-versa. Once the recurrence intervals for given discharges are calculated, the relations may be visually plotted on a Gumbel-type graph. This is more-or-less a semi-log graph relation (Gumbel graph paper is available in the lab data section of the class web site). Determine a list of procedures on how to analyse frequency-discharge data and implement. Parameters of interest: rank of Discharge, total number of observations, and probability of occurrence. Watershed Morphometry and Hydrologic Relations. Collection of channel network data from three watersheds wherever. The data are organized by stream order and channel segment length for each area. Drainage areas, lengths from divide, and basin relief are also listed for each site. Calculate the drainage density for each watershed in m/km^2. Determine the Shreve Magnitude for each watershed (M = frequency or count of first order stream segments). Using the given empirical hydrologic relations, calculate the maximum discharge expected for each of the chosen watersheds (answer in cubic meters per second). Using the given empirical hydrologic relations, calculate the discharge expected for a recurrence interval of 2.33 years at each of the watersheds. Using the rational runoff method, assume that each watershed is covered with a clayey-soil colluvium. Now consider a regional rainfall event with an average intensity of 127 mm/day. Calculate the peak runoff discharge anticipated at each of the three watersheds, answer in cubic meters per second. What would happen to the peak discharge at each watershed if they were totally paved in asphalt (like with respect to urban development)? Using the Time for Hydraulic Concentration empirical formula from the equation list, calculate Tc for each of the watersheds (NOTE: for this empirical formula to work, the units must be in English as listed on the equation sheet). Answer questions in the Express the relationship between World Record total rainfall and duration as a power-function equation. How well do the data fit this equation? For some arbitrary region chosen, predict the region of the graph where typical Rainfall-Duration relationships will fall; think about the style of precipitation that chosen place typically receives. Based on the graph, discuss the types of rainfall events that are likely associated with widespread regional flooding. Based on your calculations of Recurrence Interval of a Given Discharge of Rank, probability of occurrence, and the Gumbel Curve, calculate a unit discharge for the highest and lowest peak discharge events observed in the record. Calculate the unit discharges for the 30 yr floods on the Ling Ling River and Ping Ping River. Which has a higher unit discharge? Compare and contrast the Gumbel plots for the Ling Ling and Ping Ping drainages. What geologic/climatic/hydrologic variables account for the similarities and differences between the two (you will have to look at a basic geologic map of the region, locate the watersheds by long. and lat., then comment on the geologic environment, etc.). Using your graphs, hypothesize what the maximum peak discharge would be for a 150 year recurrence interval on the Ling Ling and Ping Ping Rivers. Answer in cubic meters / sec. Which one is higher and why? Discuss the relationship between watershed morphometry (physical characteristics of the watershed network), climate, and river hydrology. Consider all of the calculations and relationships that you examined in this section. Place your discussion in the context of flood hazards planning. -Stream Order https://people.wou.edu/~taylors/es476_hydro/stream_ordering_ex.pdf -Rational Runoff https://people.wou.edu/~taylors/es476_hydro/river_lab_flood_analysis.pdf INSTEAD, student groups will be assigned regions. They will pursue all data for development independently. The only major issue will be acquiring clear drainage maps for respective region. -Groundwater Flow Model https://people.wou.edu/~taylors/es476_hydro/intro_groundwater_flow_model.pdf HEC-RAS activities -Choose hydrogeology exercises from the following: Ming-Kuo Lee (1998) Hands-On Laboratory Exercises for an Undergraduate Hydrogeology Course, Journal of Geoscience Education, 46:5, 433 - 438 -Working with Groundwater Contour maps There will be multiple sets to complete https://people.wou.edu/~taylors/es476_hydro/gw_contour_map_ex.pdf Co-requisite: Global Geophysics Prerequisite: Geomorphology Mathematical Physics for Geophysics This course isn’t concerned with being a perfectionist, nor towards retarding attempts to unfairly treat or critique others by claiming teaching education based on something trivial one has practiced a thousand times with nothing better to do. Affinity or innate ability makes the world turn, not a parasitic mathematical fanatic; you can’t compare a mathematician to an engineer or physicist or chemist. Any directive of this course doesn’t primarily concern repulsive trivial matrix algebra prowess; people have better things to do than trying to intimidate others with boxes of numbers abiding by linear models. All modules mentioned and detailed subjects will be completed with quality instruction. Course will have integrity in a firm foundation of physics. A major directive of this course is to introduce practical and relevant mathematical tools in a pleasant manner towards the physical sciences and geophysics. It’s really constructive that students consume and digest the material through such fluid and tangible course layout given, rather than them questioning their decision making in career goals, and them not questioning the instructor’s true worth in society. One wants to model physics, rather than attempts of mathematical superiority towards nothing. Mathematical theory will neither drown course nor weaken the focus of the course. Course will be treated in a manner that emphasizes practicality, being a solid foundation for the physical sciences and geophysics, rather than mathematical frolic and parasitic mathematical obnoxiousness. Assessment --> Homework 25% 3 Exams 75% Course Outline --> --Geometrical Vector Spaces This module will only concern objects physically meaningful to the physical sciences; notion of dimension will be physical and nothing more. To be relevant to physics one must have a background in physics and understand the physics. Topics in module will be described, developed and categorized towards constructive practical usage in applications. Matrices done manually will be no larger than column size or row size of 3 and will be limited; larger sizes concern computational tool. 1. Structure for Euclidean space Definitions of field Vector space Inner product Norm Normed vector space Metric 2. Linear independence and bases vectors with relation to coordinates and transformations. Note: I don’t care about about a bunch of given weirdo matrices out of no where. I only care about coordinate systems and transformations. 3. Gram-Schmidt Process (vectors) and its relevance to basis vectors. Modified Gram-Schmidt (vectors) 4. Transformations between Cartesian coordinate systems: shifts, Euler angle rotations and relation to spherical coordinates. 5. Transforming differentials and vectors among Cartesian, polar, cylindrical and spherical coordinates. 6. For a respective system identify the basis. Change of basis between prior mentioned coordinate systems. Confirm that magnitude and direction remains unchanged. How does one know that orientation is preserved? 7. Eigenvectors and Eigenvalues of geometric transformations (Mathematica usage to complement). Don’t evangelise the boxes of gibberish finesse, rather, why is it so special that it’s not wasting time --Properties of vectors spaces in Euclidean space with application to coordinates 1. Observing the orientations of vectors and covariant vectors at point p. Mapping for contravariant and covariant vectors, and respective transformation matrices (and will apply actual coordinates). 2. Covariant bases and contravariant bases and observing the orientations at point p (will also apply coordinate systems and transformations). 3. Kronecker delta; dual relationship between contravariant and covariant (basis) vectors 4. Defining the norm via contravariant-covariant “contraction” and its invariance w.r.t to coordinate transformations. 5. Euclidean Metric i. Properties of distance (or the norm) validated in Euclidean space, namely positive definiteness, non-degeneracy, symmetry and triangular inequality. ii. Transformation of metric components iii. Transformation of metric components w.r.t to actual coordinate transformations, and preservation of distance iv. Use of the Euclidean metric to relate contravariant and covariant components --Common Tensorial Operators Note: higher order tensors will be confined to rank 2. 1. Introducing the concept and structure of the tensor product, it’s geometrical view, and it’s transformation (”egg shell” form and explicit cases with coordinate systems). Explicit change of coordinates for tensor products among the basis vectors. For various coordinate transformations to determine how the basis vectors in the tensor product change and the explicit consequences for tensor components; for a given coordinate transformation how will chosen basis vectors transform. NOTE: will not indulge much on rotation matrices and shifts, because there are more interesting transformations. Among various coordinate systems will investigate how tensor components (within the tensor product) adjust to preserve equivalence in the manifold. Can we identify explicit images of such components based on homeomorphisms being the explicit coordinate transformations? 2. The metric tensor. Will identify its properties by formally recognising tensorial structure and employing (1) prior towards its properties. 3. Review of gradient (with properties) and the displacement gradient; change of coordinates and verifying equivalency among coordinate systems. 4. Review of directional derivative and properties; change of coordinates and verifying equivalency among coordinate systems. 5. Review of divergence and properties; change of coordinates and verifying equivalency among coordinate systems. 6. Gradient of a tensor field; change of coordinates and verifying equivalency among coordinate systems. 7. Directional derivative of a tensor field; change of coordinates and verifying equivalency among coordinate systems. 8. Divergence of a tensor field; change of coordinates and verifying equivalency among coordinate systems. 9. Review of divergence theorem; change of coordinates and verifying equivalency among coordinate systems. 10. Divergence theorem of a tensor field; change of coordinates and verifying equivalency among coordinate systems. 11. Applications of the Levi-Civita symbol i. Definition and properties ii. Determinants iii. Vector cross product, curl & irrotational fields iv. Curl of tensor fields; change of coordinates & verifying equivalency among coordinates v. Review of Green’s theorem and Stokes theorem vi. Tensorial forms of Green’s Theorem and Stokes Theorem; change of coordinates & verifying equivalency among coordinates for the theorems 12. Will identify non-relativistic tensors in the physicals sciences and apply various coordinate transformations as practice. 13. Electromagnetism Review of Maxwell Equations Maxwell Equations in terms of electromagnetic potentials Verifying prior holds under coordinate transformations Is gauge invariance unique to coordinate transformations? Is gauge invariance preserved under coordinate transformations? --Orthogonalization of Functions 1. Why do we care about this in physics? 2. Proof of economical practicality in use 3. Seaborn, J. B. (2002). Orthogonal Functions. In: Mathematics for the Physical Sciences. Springer, New York, NY. 4. Gram-Schmidt Orthonormalization (functions) --Applications that make Complex Variables Relevant 1. Complex numbers 2. Is there any economical practicality in representing geometries or physical bodies with complex variables? 3. Should Complex Variables courses be turned back into conferences in rooms locked from the outside? Animal shelter selection or something. 4. Geometrical properties of complex variables (no representation of geometries because people have better things to do) 5. Complex exponential as a power series leading to Euler’s formula; cosine and sine expressed in terms of complex exponents. 6. What is so special about the complex conjugate outside of a math course in a classical physics sense? Get to the point with fast practicality. 7. Simple harmonic oscillator i. Modelling classical physical systems of SHM ii. Solutions of ODE of SHM (solutions in trigonometric & exponential form) iii. Damping & comparing solutions to ideal SHM (trigonometric & exponential forms) iv. Superposition of waves (trigonometric and exponential forms) 8. Eigenvalue Analysis of Vibrations Note: if I look at something and can’t make it out to be physics, don’t bother; boxes of numbers are not physics. Matrices are mundane algorithmic tools. If system requires matrices higher than 2 by 2, your graphing calculator skills and Mathematica should be relevant. If you have infinite time to doodle with matrix theory, go find a math department and stay there. Mechanics Systems One dimensional Membrane 3D Continuous media 9. Fourier Series i. Review of trigonometric integral identities and the associated complete orthogonal system ii. Periodic functions, definition of Fourier series and computations iii. Going from [-pi, pi] to [-L, L] via change of variables iv. Complex Fourier series v. Convergence criteria via Dini’s test and boundary conditions; with exemption functions examples. Calderon, C. P. (1981). On the Dini Test & Divergence of Fourier Series, Proceedings of the American Mathematical Society, 82(3), pp. 382-384 vi. Dini continuity and Dini criterion. vii. Recognising Eigenfunctions and Eigenvalues through the method of separation of variables upon the linear wave equation and linear heat equation involving Fourier series. Eigenfrequencies of vibration and the eigenvectors as shapes of the vibrational modes. May consider representation in spherical and cylindrical coordinates as exercises. 10. Fourier Transform i. Differentiating between “series” and “transform” ii. Counterparts to Dini (test, continuity and criterion) for Fourier transform? iii. Differentiation and integration properties iv. Applications in geophysics 11. Heavyside Step function and the Dirac function i. Rectangular shifts and rectangular pulses ii. Function types in terms of Heaviside and Dirac functions iii. Applications Claude Wendell Horton; On the use of electromagnetic waves in geophysical prospecting. Geophysics 1946;; 11 (4): 505–517 Seismic data exploration iv. Show that particular functions (Gaussian, sinc, Airy, Bessel function of the first kind) all converge to the Dirac delta function for a specific limit. 12. Investigating of Mathematica functions --Overview of the Heat Equation and Wave Equation 1. Development of models 2. Basic solving method 3. Practical conditions for geophysics Initial Conditions and Boundary Conditions Resulting Solutions --Bessel’s Equation 1. Solving the Laplace equation in cylindrical coordinates 2. Solution of Bessel’s equation (first and second kind) via method of Frobenius and recurrence 3. General solution of Bessel’s equation of order p 4. Applications in physical settings 5. Investigating of Mathematica functions --Legendre Equation 1. Solving the Laplace equation in spherical coordinates 2. Solving the Legendre equation (first and second kind) via method of Frobenius and recurrence 3. Solving Helmholtz equation in spherical coordinates 4. Expansion of potentials and the physical roles of terms (gravitation and magnetospheres) Note: for gravitation, applying motion of inertia and McCullough’s formula with Legendre polynomials can prove to be very insightful. 5. Investigating of Mathematica functions --Eigenfunctions in Geophysics Concerned with a robust but intuitive exposure to Eigenfunctions arising naturally with geophysical phenomena and their meaningfulness; NOT a broken sewage line cascading mathematical gibbersh. Ben-Menahem A., Singh S.J. (1981) Asymptotic Theory of the Earth’s Normal Modes. In: Seismic Waves and Sources. Springer, New York L. Zhao, F. A. Dahlen (1993), Asymptotic Eigenfrequencies of the Earth's Normal Modes, Geophysical Journal International, Volume 115, Issue 3, Pages 729–758 L. Zhao, F. A. Dahlen (1995), Asymptotic Normal Modes of the Earth—II. Eigenfunctions, Geophysical Journal International, Volume 121, Issue 2, Pages 585–626 L. Zhao, F. A. Dahlen (1995), Asymptotic Normal Modes of the Earth—III. Fréchet Kernel and Group Velocity, Geophysical Journal International, Volume 122, Issue 1, Pages 299–325 Investigating Mathematica functions Prerequisites: General Physics I & II, ODE, Calculus III. Potential Field Methods in Applied Geophysics By the end of this class you will have: • Comprehension of the theory and application of gravity surveys in environmental studies • Understanding of the link between geophysical properties controlling gravity surveys and subsurface environmental parameters • Knowledge of field procedures for gravity surveys • Informed interpretation of gravity survey data sets • Comprehension of the theory and application of electric surveys in environmental studies • Understanding of the link between geophysical properties controlling electric surveys and subsurface environmental parameters • Knowledge of field procedures for electric surveys • Informed interpretation of electric survey data sets • Comprehension of the theory and application of magnetic surveys in environmental studies • Understanding of the link between geophysical properties controlling magnetic surveys and subsurface environmental parameters • Knowledge of field procedures for magnetic surveys • Informed interpretation of magnetic survey data sets • Comprehension of the theory and application of NMR surveys in environmental studies • Understanding of the link between geophysical properties controlling NMR surveys and subsurface environmental parameters • Knowledge of field procedures for NMR surveys • Informed interpretation of NMR survey data sets • Note: different methods can be combined or applied along each other (among electric, magnetic, electromagnetic, NMR) for geophysical analysis, surveys and prospecting. Students should recognise such and may be quizzed and/or tested on such. Typical Texts --> Potential Theory in Gravity & Magnetic Applications, by Richard J. Blakely Environmental & Engineering Geophysics, by P. V. Sharma, Cambridge University Press Recommended Texts and Resources: Applied Geophysics by W. M. Telford, L. P. Geldart Multivariable & Vector Calculus Texts Will also make use of journal articles Wolfram Mathematica: Apart from computation will also make use of Mathematica’s “Earth Sciences Data and Computation” and “Geographic Data & Entities”. Course Grade --> Homework Quizzes Computational & Data Assignments with Modelling 3 - 8 field/lab activities 2 Exams Course Outline --> I. Gravity Potential -Introduction to Fields -Math Review: vectors, scalars, vector multiplication and properties, spherical and cylindrical coordinates. -Math Review: partial derivatives, gradients, Laplacian, divergence, curl, conservation & non-conservative fields, differential equations -Math Review: Volume Integrals, Surface integrals, line integrals, divergence theorem -Introduction to gravitational potential and gravitational acceleration -Density of materials -Gravitational acceleration due to simple shapes -Gravity measurements -Earth’s Gravitational Field -Deriving the gravitational potential in terms of Gauss law, involving the Poisson equation in spherical coordinates towards a radial model. -Deriving the gravitational potential in terms of moment of inertia, namely, manipulated with McCullough’s formula and Legendre’s formula; identify the total potential decomposed into gravitational force, centripetal force and other possible following terms. Observation of gravitational potential for varying distance and latitude; convergence back to classical model. -Gravity survey- indirect (surface) means of calculating the density property of subsurface materials. -The Gal unit and cause of its variation. Gravity gradient. Gravity gradiometry. 1-component of the gravity field in the vertical direction versus full tensor gravity gradiometry measures (all components of the gravity field). Being the derivatives of gravity, the spectral power of gravity gradient signals is pushed to higher frequencies; this generally makes the gravity gradient anomaly more localised to the source than the gravity anomaly. Gravity anomalies and corrections. -Image subsurface geology to aid hydrocarbon and mineral exploration. Gravity surveys highlight gravity anomalies that can be related to geological features such as salt diapirs, fault systems, reef structures, Kimberlite pipes, etc. Types of gravity gradiometers. Transforming relative gravity survey measurements to absolute gravity values and gravity anomalies (will require some mathematical models). -Introduction to forward modelling and inverse theory -Forward modelling and inversion of gravity data Phelps, G. A. (2015). 2D Forward Modelling of Gravity Data Using Geostatistically Generated Subsurface Density Variations. American Geophysical Union Geoff Phelps, (2016), "Forward modelling of gravity data using geostatistically generated subsurface density variations," GEOPHYSICS 81: G81-G94. Will also include Mathematica assignments II. Geoids -Geoids. Comparison between ellipsoid, Earth’s surface, geoid and ocean. -Geoid + Ellipsoid = Earth. -Means to more accurately calculate depths of earthquakes, or any other deep object beneath the earth’s surface. -“WGS84” version (World Geodetic System of 1984). https://www.ngs.noaa.gov/GEOID/ https://beta.ngs.noaa.gov/GEOID/xGEOID/ III. Electricity -Self Potential Additional assist article guide: Jouniaux, Maineult, Naudet, Pessel, & Sailhac. (2009). Review of Self-Potential Methods in Hydrogeophysics. Comptes Rendus - Géoscience, 341(10-11), 928-936. There will be two experimental activities (with trials) to develop: 1. Rittgers, J. B. et al. (2013). Self-Potential Signals Generated by the Corrosion of Buried Metallic Objects with Application to Contaminant Plumes. Gophysics, VOL. 78, NO. 5, P. EN65–EN82 2. The following can article can used to develop field experimentation, where expensive and fancy equipment aren’t required, rather they can be developed and have data acquisition-- Leitch, A. M., & Boone, C. R. (2007). A Study of the SP Geophysical Technique in a Campus Setting. Atlantic Geology, 43, Pages 91 - 111. -Resistivity Additional guide: Herman, R. (2001). An Introduction to Electrical Resistivity in Geophysics. Am. J. Phys., Vol. 69, No. 9 Include the duality relation between resistivity and conductivity methods. Scenario Evaluator for Electrical Resistivity (SEER) Survey Pre-Modelling Tool: 1. Terry, Neil, Day-Lewis, F.D., Robinson, J.L., Slater, L.D., Halford, Keith, Binley, Andrew, Lane, J.W., and Werkema, Dale, 2017, Scenario Evaluator for Electrical Resistivity Survey Pre-modelling Tool: Groundwater 2. Terry, Neil, Day-Lewis, F.D., Robinson, J.L., Slater, L.D., Halford, K., Binley, A., Lane, J.W. Jr., and Werkema, D., 2017, The Scenario Evaluator for Electrical Resistivity (SEER) Survey Design Tool v1.0: U.S. Geological Survey Provisional Software Release Field operations of the resistivity method is feasible. One can succeed SEER with development of a field system without fancy and expensive instrumentation, but having data acquisition ability. Would like to compare field operations with data from professional sources, done in the environment of interest; experimentation with trials will be done regardless, and compared to SEER preliminary prediction. -Induced Polarization Additional interest: Wynn, J. and Roberts, W. (2009). "The Application of Induced Polarization Techniques to Detect Metal‐Bearing Offshore Anthropogenic Waste and Unexploded Ordnance," Symposium on the Application of Geophysics to Engineering and Environmental Problems Proceedings: 1104-1113 IV. Magnetic Potential -Introduction to magnetic potential -Magnetic susceptibility -Magnetic susceptibility of materials -Magnetic potential due to simple shapes -Magnetic measurements -Earth’s magnetic field -Major geomagnetic models -Secular Variation -Forward modelling and inversion of magnetic data With use of Mathematica with tasks -Magnetic surveying Field Experiments to implement: Tronicke, J. and Trauth, M. H. (2018). Classroom Sized Geophysical Experiments: Magnetic Surveying Using Modern Smartphone Devices, European Journal of Physics, Volume 39, Number 3 < https://archive.epa.gov/esd/archive-geophysics/web/html/magnetic_methods.html > IV. Electromagnetism --Ground penetrating radar Jol, Harry M. (2008). Ground Penetrating Radar Theory and Applications. Elsevier Science. For the following two sources with links the process is detailed, and will pursue data to be used for modelling, analysis, representation and prospecting purposes in the Mathematica environment: Forde, A.S., Bernier, J.C., and Miselis, J.L., 2018, Ground Penetrating Radar and Differential Global Positioning System Data Collected in April 2016 from Fire Island, New York: U.S. Geological Survey Data Series 1078 Zaremba, N.J., Smith, K.E.L., Bishop, J.M., and Smith, C.G., 2016, Ground-Penetrating Radar and Differential Global Positioning System Data Collected from Long Beach Island, New Jersey, April 2015: U.S. Geological Survey Data Series 1006 --Magnetotelluric method (MT) General Guide: Chave, A. D., & Jones, A. G. (Eds.) (2012). The Magnetotelluric Method: Theory and practice. New York: Cambridge University Press. Will pursue data to be used for data modelling, analysis, representation and prospecting purposes in/with the Mathematica environment: Tikhonov, A.N., 1950. in 1953, On Determining Electrical Characteristics of the Deep Layers of the Earth's Crust, Doklady, 73, 295-297 Cagniard, L (1953). Basic theory of the Magnetotelluric Method of Geophysical Prospecting. Geophysics. 18 (3): 605–635 Zhang, L. et al. Magnetotelluric Investigation of the Geothermal Anomaly in Hailin, Mudanjiang, Northeastern China. Journal of Applied Geophysics 118 (2015) 47–65 --Electromagnetic Waves for Prospecting Claude Wendell Horton; On the Use of Electromagnetic Waves in Geophysical Prospecting. Geophysics 1946; 11 (4): 505–517 Thiel, D.V. (1988). VLF Electromagnetic Prospecting. In: General Geology. Encyclopedia of Earth Science. Springer, Boston, MA. --Induction There is additional interest besides what is found in textbooks. The given sources to serve as guide towards acquiring data from ambiances of interest towards data modelling, analysis and prospecting: Prinos, S.T., and Valderrama, Robert, 2016, Collection, Processing, and Quality Assurance of Time-Series Electromagnetic-Induction Log Satasets, 1995–2016, south Florida: U.S. Geological Survey Open-File Report 2016–1194, 24 pages. Valderrama, R., 2017, Time Series Electromagnetic Induction-Log Datasets, Including Logs Collected through the 2016 Water Year in South Florida: U.S. Geological Survey data release V. Nuclear Magnetic Resonance Introduction to Nuclear magnetic resonance (NMR) -NMR Theory and material properties -NMR measurements -Basic inversion of NMR data (will be both lecture-based and active use of real external data towards modelling analysis, representation and prospecting) Additional guides: Legchenko, Baltassat, Beauce, & Bernard. (2002). Nuclear Magnetic Resonance as a Geophysical tool for Hydrogeologists. Journal of Applied Geophysics, 50(1-2), 21-46. Legchenko, A., & Legtchenko. (2013). Magnetic Resonance Imaging for Groundwater. Somerset: John Wiley & Sons, Incorporated. Nicot, F. (2013). Link Between SNMR and Aquifer Parameters. In Focus Series (pp. 121-142). Hoboken, USA: John Wiley & Sons. Vouillamoz, J.M., Legchenko, A., Albouy, Y., Bakalowicz, M., Baltassat, J.M., & Al-Fares, W. (2003). Localization of saturated karst aquifer with magnetic resonance sounding and resistivity imagery. Ground Water, 41(5), 578-586 Prerequisite: Global Geophysics Seismology Classical seismology. Topics to be covered: theories of wave propagation in the earth, instrumentation, Earth's structure and tomography, theory of the seismic source, physics of earthquakes, and seismic risk. Emphasis will be placed on how quantitative mathematical and physical methods are used to understand complex natural processes, such as earthquakes. Note: Such a course is crucial towards any possible sociability or commerce with professionals in other areas such as physics and mathematics; else you will be bumped off by such entities and they will take your job or possible jobs because they know the mathematical modelling, etc. Such a course provides credibility towards graduate school. Conventional textbooks --> S. Stein & M. Wysession (abbreviated SW), “An Introduction to Seismology, Earthquakes, and Earth Structure” T. Lay & T.C. Wallace (abbreviated LW), “Modern Global Seismology” P.M. Shearer (abbreviated S), “Introduction to Seismology” Manuals --> Bormann, P. (Ed.)(2012): New Manual of Seismological Observatory Practice (NMSOP-2), Potsdam : Deutsches GeoForschungszentrum GFZ; IASPEI. Peterson, J. R. (1993). Observations and Modelling of Seismic Background Noise. U.S. Geological Survey. Series number 93- 322. Tools --> Mathematica HypoDD Waldhauser, F. (2001). hypoDD-A Program to Compute Double-Difference Hypocenter Locations. USGS 2001-113 CIG (computational Infrastructure for Geodynamics): https://geodynamics.org/resources/notebooks Unified Geodynamics Earth Science Computation Environment (UGESCE) USGS Earthquake Hazards Software Without such software incorporated professionally and applied consistently, seismology studies are not credible. Courses of such are never to be held hostage by pure mathematicians. Course will also emphasize heavy usage of real seismological data to develop practical and sustainable skills. Grades will be determined as 20% HW 20% Labs: Software and data activity 20% Exam 1 20% Exam 2 20% Final Exam Lab Components --> The following components will be done on multiple occasions, often with multiple components being connected on multiple occasions: --Basic plot generation with Generic Mapping Tools (GMT), and discussion of general patterns of earthquakes in space, time, and magnitude. --Will involve professional understanding, logistics, acquisition and implementation of data from various professional sources, technologies and software --Event and waveform databases. Applications will include an introduction to strategies for organizing data, available catalogs, principles of earthquake location, and hypocentral location software. --Seismic recording and seismograms. Applications will include time series analysis, digitization, filtering, and Seismic Analysis Code (SAC). --Seismogram plotting, and correlation detection. --Calculating background seismic noise reductions --Lienert, B. R., Berg, E. and Frazer, L. N. (1986). HYPOCENTER: An Earthquake Location Method using Centered, Scaled, and Adaptively Damped Least Squares. Bulletin of the Seismological Society of America 1986; 76 (3): 771–783 Concern for this article is the implementation of the method from manual build, say, in Mathematica and so forth. As well, comparing to method applied in HypoDD (qualitatively at least); will need supporting documentation for HypoDD --Determination of physical properties of media based on wave type and behaviour. --Will try to replicate to best of ability: Kennett, B.L.N. & Furumura, T. (2019). Significant P Wave Conversions from Upgoing S Waves Generated by Very Deep Earthquakes Around Japan. Prog Earth Planet Sci 6, 49 Study or more modern data is also expected Can also pursue other regions around the globe COURSE OUTLINE --> Overview of course, simple harmonic oscillator, elasticity (Readings: SW Chapter 1, 2.1-2.3) -Simple harmonic motion -Stress & strain -Hooke’s law; isotropic elasticity; transverse anisotropy -Moduli for different stress conditions (Young’s modulus, bulk modulus) Waves, ray solutions to the acoustic wave equation (Readings: LW Chapter 3, SW Chapter 3.1-3.3) -Acoustic (hydrostatic) wave equation in 1D, plane waves, velocity -2D/3D wave equation: Eikonal, Helmholtz & transport equations, WKBJ solution -Layer over a halfspace: Reflection/transmission coefficients, Snell’s Law, head waves -Continuous velocity with depth, tau-p analysis Full wave solutions, elastic waves (Readings: SW Chapter 2.4-2.6, 3.4-3.5) -Finite difference solutions, wavefield continuation & FK migration, Kirchoff migration -Elastic wave equation, potentials & separation into P&S waves -Reflected waves: Zoeppritz equations, Snell’s Law for P&S waves -Body waves in the earth (P, S, PcP, PKP, …) -Adams-Williamson equation Surface waves, travel-time tomography (Readings: SW Chapter 2.7-2.8, 7.3) -Love and Rayleigh waves, eigenfunctions -Dispersion, phase and group velocity -Tomography theory, inverse methods Normal modes, attenuation (Readings: SW Chapter 2.9, 3.7) -Modes in 1D, modes of a sphere, spherical harmonics -Torsional, spheroidal modes, synthetic seismograms -Attenuation, mode splitting, mode coupling Sensitivity kernels, determination of Earth structure (Readings: SW Chapter 7.4, LW Chapter 4.7) -Depth sensitivity kernels for surface waves, Mode sensitivity kernels -Sensitivity kernels for tomography, Fresnel zones Theory of seismic sources (Readings: LW Chapter 8) -Static and elastodynamic sources -Green’s function for seismic waves (straight to the point & nothing else) -Elastic dislocations, seismic moment, moment tensors Point source solutions (Readings: SW Chapter 4) -Double couple and radiation pattern -Retrieval of source parameters from body waves and long-period waves Finite-fault solutions and physics of earthquakes (Readings: LW Chapter 9) -Haskell model; Rupture directivity, stress drop, energy partitioning -Earthquake scaling relations, earthquake statistics Prerequisites: Global Geophysics, Mathematical Physics for Geophysics. Geodynamics The mechanics and dynamics of the Earth's interior and their applications to problems of Geophysics. This course considers several rheological descriptions of Earth materials (brittle, elastic, linear and nonlinear fluids, and viscoelastic) and emphasizes analytical solutions to simplified problem. Students will gain an in-depth understanding of the mechanics of the lithosphere, deformation, stress, fluid mechanics as it applies to the Earth's interior, including thermal convection. Students will derive analytical solutions to simplified problems that reveal the fundamental characteristics of more complex geodynamical models and provide a toolkit to interpret geological observations. Students will understand the relation between physics concept, especially continuum mechanics and (laminar) fluid dynamics, and geological observations (Interdisciplinary understanding). Note: Such a course is crucial towards any possible sociability or commerce with professionals in other areas such as physics and mathematics; else you will be bumped off by such entities and they will take your job or possible jobs because they know the mathematical modelling, etc. Such a course provides credibility towards graduate school. Homework --> Homework will involve (BUT NOT LIMITED TO) the following topics: --Various mathematical refreshers embedded in homework following. I am neither a @55hole nor jackass nor sentient virus from the math department) --Stress --Strain + dikes --Elasticity --Fluid Mechanics --Geophysical gravitational models Tidal Gravity Models Spherical Harmonics EGM 2008 and EGM 2020 Anomaly (Bouguer, free-air) --Plates --Asthenospheric flow --Isostatic rebound --Heat --Thermal catastrophe --Wave mechanics through various media --Rheology Note: occasionally, homework may sometimes require access to Internet tools, computer calculation and simple programming. Tools for Course --> Mathematica/Python/R OpenFoam OPM (opm-project.org) USGS Coulomb software Potent ( http://www.geoss.com.au/potent.html ) MODFLOW (+ Gridgen) HEC-HMS CIG (computational Infrastructure for Geodynamics): https://geodynamics.org/resources/notebooks Unified Geodynamics Earth Science Computation Environment (UGESCE) GPlates, GPlates data sets LABS --> Labs concern strong acquaintance with the given software tools in a professional manner. Emphasis on the following: Models in question Comprehension of uses of chosen software for course topic Software Logistics Implementation Group Term Project --> PART A The group term project should address some topic or issue in geodynamics. You will present an overview of your term project to the class. You are encouraged to think more broadly than simply reviewing the literature – Concerns outline an approach or approaches to addressing an unresolved question or towards premier interests in the field – Actually solve a problem or Investigation Develop procedure and logistics Perform some numerical calculations Lab experiments skills Come up with Mathematica-based activities, Apply geodynamics/geomechanics software listed (in software portfolio alongside Mathematica/Python/R), Interpret data with what we learned in class. PART B Data Oriented Gravitational Models. Describe (concept, history, process, data source to be applied, modelling of data, analysis of model, conclusion) Satellite gravimetry models (GRACE or GOCE) Inversion models Forward modelling (USGS gravmagsubs) Airborne Gravity Gradiometry Surveys Regardless of what you do, you will need to write term paper in the form of a scientific journal article; The final term project will be submitted in a format and length similar to Geophysical Research Letters papers. Templates and length limitations for these papers be downloaded by the journal homepage. Incorporate figures, tables and development with the applied tools. Done for both part A and part B. Grade Constitution --> Homework Labs 3 Exams Group Term Paper Course Text: Turcotte, D. L. and Schubert, G. (2013). Geodynamics, Cambridge University Press Note: physics and constructive, practical mathematical modelling based on prerequisites will be reinforced to properly treat geodynamics; other texts that don’t restrict such demands can support. COURSE OUTLINE: WEEKS 1 – 2 Plate Tectonics Introduction to geodynamics and plate tectonics Types of plate boundaries, triple junctions, Euler poles, plate tectonics on a sphere WEEKS 2 – 4 Stress, strain and elastic deformation Force, stress and pressure Strain and strain rate Elastic deformation Bending and buckling of plates Dynamics of basins 3 days: practical and constructive usage of Mathematica and other tools for geodynamics WEEKS 5 – 6 Heat Transfer Fourier's law Steady and unsteady heat transfer, moving boundaries WEEKS 6 – 8 Fluid Mechanics Channel flows, plumes, thermal convection, gravity currents High and low Re flows, and dimensional analysis Numerical simulations of mantle convection WEEK 9 Gravity Deformation of the Earth Gravity anomalies (free-air, Bouguer, ) WEEKS 10 Porous Media Darcy's law Aquifers Geothermal systems Magma migration WEEK 11 – 12 Biot Formulation & Generalised Biot Formulation (GBF) Biot Formulation Means of competently applying conditions and data to Biot formulation Highly porous, moderately porous, low porous Generalised Biot Formulation Means of competently applying conditions and data to GBF Highly porous, moderately porous, low porous WEEK 13 Mechanical & Acoustic Waves through Non-Porous Media Seismic Waves Types with velocity, reflection and refraction. Relevance to the exploration for oil and gas, engineering studies, and understanding the Earth's interior. Acoustic Waves Compressional Waves with similarities to P-waves in seismic contexts. Velocity Application to well-logging tools Elastic Properties Three types of modulus Poisson’s Ratio Stiffness and Compliance Attenuation Energy loss is seismic and acoustic waves Anisotropy Non-porous rocks can exhibit anisotropy, where wave velocities vary with direction. This can be due to the alignment of minerals or fractures within the rock. WEEK 14 – 15 Rheology of geological materials and faulting Diffusion and dislocation creep Rheological models Friction and faulting WEEK 16 Rotation, Nonlinear flow, Nonlinear corner flow Prerequisites: Historical Geology, Plate Tectonics, Global Geophysics, Numerical Analysis., Calculus III Computational Geomechanics Essential Attributes of course: (a) Theory, laws and governing equations (with expected solutions if practical) for field application in question. This is not a math course; you have real economical goals with time constraints. (b) Understanding structure, logistics, practicality and limitations of a respective numerical method. (c) Computational BVPs are simulated Manual construction of numerical process to problems Actual approximations/simulations by manually implementing numerical methodology Implementing given software to compare with manual constructions. Grading: Homework Exam 1 Exam 2 Projects Final Exam Homework assignments will include computational and simulation activities given to students based only on analytical set-up and logistics by instructor. For exams students will be required to provide analytical summary and logistics for computational and simulation requests. Exams will require simulation tasks. Exams are open book and open notes. Note: such a course is crucial towards any possible sociability or commerce with general physicists and mathematicians, so they can’t take your jobs. Software that will accompany Mathematica/Python with homework, projects and exams in course: OpenFoam OPM (opm-project.org) USGS Coulomb software Potent ( http://www.geoss.com.au/potent.html ) MODFLOW (+ Gridgen) HEC-HMS CIG (computational Infrastructure for Geodynamics): https://geodynamics.org/resources/notebooks Unified Geodynamics Earth Science Computation Environment (UGESCE) GPlates, GPlates data sets Note: there may be other geodynamics software listed in software portfolio. Course Topics: 1.Fluid Flow and Pressure Diffusion Finite Element Methods Conservation Equations and Galerkin Approximation 2D Triangular Constant Gradient Elements 1D Isoparametric Elements 2D Isoparametric Elements and Numerical Integration Transient Behavior - Mass Matrices Transient Behavior - Integration in Time 2.Mass Transport and Reaction Conservation of Mass and 1D Models 2D Constant Gradient Elements Sorption and Reactive Transport 3.Momentum Transport Fluids, Navier-Stokes Equations 4.Solid Mechanics 1D and 2D Elements Constitutive Equations Summary and Preamble for Coupled Systems 5.Coupled Multiphysics Systems Dual-Porosity-Dual-Permeability Models Coupled Hydro-Mechanical (HM) Models OpenFoam Models for HM Coupling 6.Alternative Solution Methods Note: not all will be done, rather choosing the most robust and versatile w.r.t. to field applications. Lagrangian-Eulerian Methods Level Set Methods Boundary Element Methods SPH - Smoothed Particle Hydrodynamics LBM - Lattice Boltzmann Methods PFM - Phase Field Methods XFEM - Extended Finite Element Methods BEM - Indirect and Direct Boundary Element Methods DEM - Distinct Element Methods DLSM - Discrete Lattice Spring Methods PDM - Peridynamic Methods Prerequisites: Field Geology, Plate Tectonics, Global Geophysics, Potential Field Methods in Exploration Geophysics, Numerical Analysis, Fluid Mechanics Signal Analysis Any signal which is varying conveys valuable information. Therefore, to comprehend the information embedded in such signals, it’s necessary to 'detect' and 'extract data' from such quantities. Most geophysical data consist of “signals” which are sequences of measurements sampled in time (“time series”) or in space. Course would not be much if real data isn’t applied. There will be emphasis to apply topics and methods as tangibly, practical, fluid and constructive as possible. Talking and presenting mathematical frolic is one thing, but actually applying it to meaningful things is another. Practical skills are essential. Will be emphasized in lecturing, exercises and labs. In this course we will examine, and learn techniques for analysing signals containing random elements and study their applications in Earth Science. Course Assessment --> Exercises Labs NOTE: course will not be meaningful without incorporation of software involving use of data and computation within realms of interest. Extensive use of software accompanies modelling upon real data. Software applied in prerequisites will also apply to this course, crucially alongside signal analysis tools for this course. Labs --> Preprocessing (filtering and decimation); Time-Domain Analysis (amplitude measurement and arrival-time picking); Frequency-Domain Analysis (Fourier transform and spectral analysis); Waveform Analysis (waveform modelling and waveform cross-correlation); Spectral Ratios Analysis; Seismic Imaging (seismic tomography); Machine Learning (pattern recognition, clustering and classification); Event Location (hypocenter determination); Response Spectrum Analysis. SEISMOLOGY. Seismology interest will be one of the areas treated. Will reacquaint ourselves with selected topics and labs from the seismology course. Treatment and activities will be much more in depth with various methods and tools introduced in this course. Labs applied will be highly coherent and practical to course topics; multiple labs can apply for a single topic. Note: texts and manuals from seismology course may also be reviewed along with literature tailored to this course. Topics to be treated: NOTE: for each prior mentioned lab topic students will be working with real seismology data sets, else the process will not be sensible and economic. A fluid, constructive and sustainable work flow from one topic to the next with the seismology data. Despite course being signal analysis focused, the economic knowledge and skills acquired from the seismology prerequisite course should not be rotted out; you did a seismology course for a reason. POSSIBLE ADDITIONAL: insight into the possibility of occurrence of a natural calamity such as volcanic eruptions Delclos, C., E. Blanc, P. Broche, F. Glangeaud, and J.L. Lacoume "Processing and Interpretation of Microbarograph Signals Generated by the Explosion of Mount St. Helens" J. Geophys. Res., 95, 5,484, 1990. Cook, R.K. and Bedard, A.J. (1972). On the Measurement of Infrasound. Q.J. Roy. Astro. Soc. 67,pp 5-11 De Angelis, S. et al (2012). Detecting Hidden Volcanic Explosions from Mt. Cleveland Volcano, Alaska, with Infrasound and Ground-Coupled Airwaves: Geophysical Research Letters, v. 39, L21312, 6 p. Fee, D. (2010). Characterization of the 2008 Kasatochi and Okmok Eruptions Using Remote Infrasound Arrays: Journal of Geophysical Research, v. 115, n. D00L10, 15 p. Fee, D. & Matoza, R.S. (2013). An Overview of Volcano Infrasound: from Hawaiian to Plinian, Local to Global: Journal of Volcanology and Geothermal Research, v. 249, p. 123-139 Note: from raw infrasound data will like to implement the tools and techniques learnt in course to recognise possible volcanic eruptions. POTENTIAL FIELD METHODS. For chosen labs from the Potential Field Methods in Applied Geophysics course will investigate the possible role of signal analysis intimately. Labs from such prerequisite course with data applied will be highly coherent to course topics; multiple labs can apply for a single topic. Note: texts and manuals from the potential field methods course may also be reviewed along with literature tailored to this course. Magnetic fields and magnetometers Gravitational fields and gravitometers NOTE: for each prior mentioned lab topic students will be working with real potential field methods (PFM) data sets, else the process will not be sensible and economic. A fluid, constructive and sustainable work flow from one topic to the next with the PFM data. Despite course being signal analysis focused, the economic knowledge and skills acquired from the PFM prerequisite course should not be rotted out; you did a PFM course for a reason. EXPLORATION Geothermal Energy Mapping Fossil Fuel Exploration NOTE: for each prior mentioned lab topic students will be working with real exploration data sets, else the process will not be sensible and economic. A fluid, constructive and sustainable work flow from one topic to the next with the exploration data. Despite course being signal analysis focused, the economic knowledge and skills acquired from the PFM prerequisite course should not be rotted out; you did a PFM course for a reason. NOTE: each lab will have seismology, PFM and exploration activities. Course Topics --> Week 1-2: Geophysics Signal Analysis Overview of geophysical signals: seismic, electromagnetic, gravitational. Basic concepts of signals and systems. Week 3-4: Time-Domain Analysis TD representation of signals Discrete and Continuous Time Signals Signal Operation: convolution, correlation. Week 5-6: Fourier Transform and Frequency-Domain Analysis Fourier Series and Fourier Transform Power Spectral Density Filtering in the frequency domain Week 7-8: Sampling and discrete Signal Processing Nyquist Theorem and sampling Discrete Fourier Transform and Fast Fourier Transform Digital Filtering and Windowing Week 9-10: Signal Processing in Seismology, Potential field Methods and Exploration Week 11-12: Waveform Analysis and Filtering Techniques Waveform Modelling Deconvolution and convolution processing Week 13-14: Spectral Analysis in Gravity and Magnetic Data Analysis of gravity and magnetic signals Power spectral density estimation for potential field data. Application of Fourier analysis in gravity and magnetic data interpretation. Week 15-16: More Applications Time-frequency analysis methods (wavelet analysis) Non-stationary signal analysis Applications in subsurface imaging and exploration Prerequisites: Numerical Analysis; Data Programming with Mathematica; Mathematical Statistics; Global Geophysics; Potential Field Methods in Applied Geophysics; Mathematical Physics for Geophysics; Seismology Note: Geology endeavor will carry out the following listed particular technical field and lab exercises, independent of the lab and field exercises of designated courses. Some of the labs and exercises to be mentioned will also be done by Civil Engineering Students with a satisfactory or unsatisfactory designation. Will also incorporate Physics, Engineering and Computer Science constituents for certain cases. The given list exhibits activities administered during “Fall” , “Winter”, “Summer” and “Spring” semesters. Students will earn a satisfactory or unsatisfactory designation. All students will qualify for a number of activities based on the mathematics, physics, chemistry and geology courses successfully completed. Past participants are welcomed to participate in repeated of activities, dependent on approval and official class count for the respective semester. Activities repeated can be added to transcripts upon successful completion. Repeated activities later on can be given a designation such as Advance “Name” I, Advance “Name” II. As well, particular repeated activities serve to towards developing true comprehension, competency and professionalism. FOR ACTIVITIES IN THE “SUMMER” AND WINTER” SESSIONS ALL PARTICIPATING STUDENTS, ASSISTING/ADVISING INSTRUCTORS AND PROFESSORS MUST BE OFFICIALLY RECOGNISED; REQUIRES BOTH CIVILIAN ID AND STUDENT/FACULTY ID FOR CONFIRMATION OF INDIVIDUAL. THERE WILL ALSO BE USE OF IDENTIFICATIONS FOR ACTIVITIES FOR RESPECTIVE SESSION. SECURITY AND NON-PARTICIPATING ADMINISTRATION WILL ONLY IDENTIFY RESPECTIVE ACTIVITY BY IDENTIFICATION CODE. SECURITY AND NON-PARTICIPATING ADMINISTRATION MUST NEVER KNOW WHAT ACTIVITIES IDENTIFICATION CODES IDENTIFY: < Alpha, Alpha, Alpha, Alpha > - < # # # # # > - < session > - < yyyy > Such geology activities will also warrant criminal background check (CBC) in order to participate. Severely threshold may vary depending on administration. Administrators will provide dated letters of confirmation of thorough CBC to student affairs and other appropriate administration. Email and physical letters with data. Such CBC protocol will not explicitly identify any particular titles or descriptions of any activity, rather, will only convey code as above. It may be the case some activities can be grouped and given a major title together; however, detailed descriptions will be required. Activities will be field classified. Particular projects of interest being stationary: --Magnetic field experimentation and modelling Physics students welcomed 1. Comparing experimentation methods for measuring the Earth’s magnetic field. (i) Cartacci, A., and Strulino, S., Measuring the Earth’s Magnetic Field in a Laboratory, Physics Education, Volume 43, Number 4 (ii) Nelli, F. (2014). Arduino: Measuring the Earth’s Magnetic Field with the Magnetometer HMC5883L. Meccanismo Complesso: https://www.meccanismocomplesso.org/en/arduino-magnetic-magnetic-magnetometer-hmc5883l/ There may be generic alternatives to specified sensor hardware. Develop stations at different places when times are synchronized. Measurements will time continuous (iii) Then compare finds from both with known recognised data 2. Modelling the Earth’s magnetic field in terms of spherical polar coordinates (determine field potential) assuming the Earth’s magnetic dipole is aligned along the “z-axis”, then plot; find the field components and total field magnitude, and plot to view their respective behaviour. Boundary conditions: magnetic field at the north pole, south pole, and equator for the radial and latitudal magnetic field components respectively. What coordinate values applied to the magnetic field strength model makes it near to what was found with experimentation methods in (1)? 3. Comparing common experimentation methods for measurement of magnetic inclination (i) Arabasi, S., and Al-Taani, H., Measuring the Earth’s Magnetic Field Dip Angle using a Smartphone-Aided Setup: A Simple Experiment for Introductory Physics Laboratories, European Jounrnal of Physics, Volume 38 Number 2, 2016. (ii) Using a simple dip needle measure the three components of the Earth’s magnetic field and find your latitude. A dip needle can also be made. Compare findings with results from experimentation in journal article above. Constituents for the dip needle experiment: Magnetic Dip Needle, Protractor. Alternatively, you can make a dip needle with: Small bar magnet (~1 cm long), 20 cm Thread. To make a dip needle, tie the thread around the centre of gravity of the bar magnet. (For a bar magnet, this is the centre of the longest axis.) Secure the thread to the bar magnet with a dab of glue and let it dry. *Hold up the dip needle. Point out that it has three perpendicular axes, so that it can rotate freely in space. Ask a student to measure the dip of the needle with the protractor and write the value on the board. *Now slowly move toward the wall. Again, to measure and record the dip of the needle with the protractor. *Now slowly move toward a desk. Again, to measure and record the dip of the needle with the protractor. *Using the equation for latitude, find the latitude of your room from the dip of the needle. *Point out the large errors which you would get if you used the values from near the wall or desk. (iii) Then compare finds from both with known recognised data 4. Magnetic field in terms of Legendre polynomials (zonal and tesseral) and comparing to what was found in (2). Magnetic field components in terms of Legendre polynomials (zonal and tesseral) with significance and geometrical exhibitions. Time varying magnetic field components in terms of Legendre polynomials (zonal and tesseral) with significance and geometrical simulations. 5. Particle trajectories in Earth’s magnetosphere (modelling and simulation) based on (4). 6. Inductive Electric field in the Teresstrial Magnetosphere, and Multiscale Field‐Aligned Currents: Characteristics Part A --> Analyse modelling and replicate findings in a CAS such as Mathematica or other: Ilie, R. et al (2017). Calculating the Inductive Electric Field in the Teresstrial Magnetosphere. Journal of Geophysical Research Space Physics, Volume 122, Issue 5, pages 5391 – 5403 PART B --> Will pursue replication the following journal (includes use data from data sources) McGranaghan, R. M., Mannucci, A. J. and Forsyth, C. (2017). A Comprehensive analysis of Multiscale Field-aligned Currents: Characteristics, Controlling Parameters, and relationships. Journal of Geophysical Research Space Physics, Volume 122, Issue 12, pages 11931 - 11960 Are inductive electric fields in the teresstrial magnetosphere related to Multiscale Field-aligned Currents? Identify modelling that would agree or prove otherwise. As well, identify the source(s) or mechanism(s) for respective phenomenon. 7. Trapped particle radiation belts and models of the trapped proton and electron populations. Will use the following source for development with SPENVIS --> https://www.spenvis.oma.be/help/background/traprad/traprad.html#APAE 8. Secular Variation 9. Causes for short term variation in the magnetic field 10. Outstanding event: “Earth’s north magnetic pole has been skittering away from Canada and towards Siberia, driven by liquid iron sloshing within the planet’s core. The magnetic pole is moving so quickly that it has forced the world’s geomagnetism experts into a rare move”, Alexandra Witze, Nature.com, circa 9th January 2019. 11. Identifying major geomagnetic models and pursuit of an explicit mathematical description (if possible for independent computational experimentation), respectively. Anticipate activities with computational tool for modelling or forecasting that’s independent to what is given by recognised sources. However, independent establishments will be compared to what is given by recognised sources. Here are the major geomagnetic models: World Magnetic Model (WMM) International Geomagnetic Reference Field (IGRF) BGS Global Geomagnetic Model (BGGM) Model of the Earth’s Magnetic Environment (MEME) Determine which above models are most appropriate to provide estimates of the average secular variation; linear extrapolations of the magnetic field from the observed change in the previous few years; comparing models directly and understanding of respective model time when comparing; comparing models to independent observatory data collected on the ground. Critical articles: Beggan, C., and Whaler, K., Forecasting Secular Variation Using Core Flows, Earth Planets Space, 62, 821-828, 2010 Finlay, C. C. et al. (2010). Evaluation of candidate geomagnetic Field Models for IGRF-11, Earth Planets Space, 62, 787–804 Satellite-derived geomagnetic field measurements: Aiken, P., et al, Geomagnetic Main Field Modelling with DMSP, Journal of Geophysical Research: Space Science, May 2014, Vol. 119 (5), pp. 4010-4025 Computationally implement such and compare with models above that have incorporated ground observatory data. 12. Magneticstorm comprehension and data collection For development or comprehension of the K-index and Kp-index the following literature to serve well Bartels, J., Heck, N. H. and Johnston, H. F. (1939). The Three Hour‐Range Index Measuring Geomagnetic Activity. Journal of Geophysical Research. 44 (4): 411–454 Fleming, J. A., Harradon, H. D. and Joyce, J. W. (1939). "Seventh General Assembly of the Association of Terrestrial Magnetism and Electricity at Washington, D.C., September 4–15, 1939". Terrestrial Magnetism and Atmospheric Electricity. 44 (4). pp. 477–478, Resolution 2 Interested in the develpemnt of the A-index as well The NOAA has tools for planetary K index and Kp index (and also possibly academics or professional institutions). Will identify which index values gives the best chance to directly observe the northern and southern lights. With the Kp index will identify time coverages and coordinates for locations, and the Kp levels for such locations. Will differentiate between latitude and geomagnetic latitude. Will identify various sources (Mathematica included) to observe the magnetic storm activity; displays of (nano)Tesla versus (universal) time r distance). Will identify geomagnetic storm arrivals at satellites (ACE satellite is just one example): volatility, intensity, temperature, speed, density, Phi, Bz. How are such measureds determined? Determining estimated time of arrival at Earth for storm (based on magnetosphere graph). How is time of arrival determined? Journal articles useful for data research where students are expected to pursue coherency and consistency among them: M.S. Bobrov, (1973). Kp Index Correlations with Solar-Wind Parameters During the First and Second Stages of a Recurrent Geomagnetic Storm, Planetary and Space Science, Volume 21, Issue 12, Pages 2139-2147 Verbanac, G. et al (2011). Solar Wind High-Speed Streams and Related Geomagnetic Activity in the Declining Phase of Solar Cycle 23. Astronomy & Astrophysics, 533, A49 Elliott, H. A., Jahn, J. and McComas, D. J. (2013). The Kp Index and Solar Wind Speed Relationship: Insights for Improving Space Weather Forecasts. Space Weather, Vol. 11, 339–349 Hofmeister, S. J. et al. (2018). The Dependence of the Peak Velocity of High-Speed Solar Wind Streams as Measured in the Ecliptic by ACE and the STEREO satellites on the Area and Co-latitude of Their Solar Source Coronal Holes. Journal of Geophysical Research. Space Physics, 123(3), 1738–1753

--Measuring the diurnal variation of Earth’s magnetic field Concerns building a proton magnetometer. Will like to measure the Earth’s magnetic field continuously. Such may include stations at various places on Earth. Will like to have “long term” compare/contrast with professional data sources and possibly the professional magnetic models mentioned in prior activity. There may be some considerable physics with the mathematical support that need explaining to convince anyone. It’s very important that measurements are associated with reasonable dates and times. All data will be securely archived. The following are guides towards developing such a measuring apparatus --> 1. Ruhunusiri, Suranga & Jayananda, Malagalage. (2008). Construction of a Proton Magnetometer. Proceedings of the Technical Sessions, 24 (2008) 78-85 << http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.607.6035&rep=rep1&type=pdf >> 2. F. Mahboubian, H. Sardari, S. Sadeghi and F. Sarreshtedari, "Design and Implementation of a Low Noise Earth Field Proton Precession Magnetometer," 2019 27th Iranian Conference on Electrical Engineering (ICEE), Yazd, Iran, 2019, pp. 345-347. Article was observed through the IEEE database. 3. http://ilotresor.com/build-a-proton-precession-magnetometer/ Such three prior guides may or may not be efficient. However, articles and other sources with the intent of NMR construction usually are more detailed --> 1. Sato-Akaba, H., Itozaki, H. Development of the Earth’s Field NMR Spectrometer for Liquid Screening. Appl Magn Reson 43, 579–589 (2012). 2. The following informing source may be decent, but it may employ Python here and there: PyPPM: A Proton Precession Magnetometer for All << https://hackaday.io/project/1376-pyppm-a-proton-precession-magnetometer-for-all >> << https://github.com/geekysuavo/pyppm >> Further technical intelligence --> 1. Liu, H et al. (2018). A comprehensive study on the weak magnetic sensor character of different geometries for proton precession magnetometer. Journal of Instrumentation, 13(09), T09003-T09003. 2. Liu, H et al. (2017). Noise characterization for the FID signal from proton precession magnetometer. Journal of Instrumentation, 12(07), P07019. --Earth radius, gravity variations (gravitational field, average body shape) and use of satellite data immersion. Physics students welcomed. 1. Measuring the radius of the Earth with (i) Sunset method with multiple trials (ii) Carroll, J., and Hughes, S., Using a Video Camera to Measure the Radius of the Earth, 2013 IOP Publishing Ltd, Physics Education, Volume 48, No. 6 (iii) Then compare finds from both with known recognised data (iv) For methods (i) and (ii), if economical, consider such activities at different latitudes (chosen increments), with designated trials. 2. Gravitational force exerted by a solid sphere The following source is quite similar to the derivation found in a typical “Fundamentals of Physics” textbook --> https://www.gregschool.org/gregschoollessons/2017/10/30/gravitational-force-exerted-by-a-sphere-rdyjt-dcss2 The following concern is a “solid” spherical body that possesses layers with different densities. Extend prior to such. 3. Modelling gravitation potential in terms of a Legendre polynomial to identify significant terms that constitute the gravitational potential. 4. Deriving the gravitational potential in terms of Gauss law, involving the Poisson equation in spherical coordinates towards a radial model, to compare with (2). 5. Deriving the gravitational potential in terms of moment of inertia, namely, manipulated with McCullough’s formula and Legendre’s formula; identify the total potential decomposed into gravitational force contribution and centripetal force contribution, namely the geo-potential. Then compare such two terms in ratio w.r.t. to distance and latitude. 6. Derive Earth’s variable radius approximation w.r.t. mean radius, rotational velocity, mass, gravitational constant and latitudal angle (involving Legendre polynomial) and compare with other known forms of radius models (includes their instantaneous rates with respect to angle). Compare derived model to (1) to have some idea of your latitude location. 7. Acquire tesseral gravitational effects model. From such a model what effects apply to satellite orbits? 8. Gravity Gradient Modelling 9. GRASS GIS for gravity anomaly computation and mapping 10. Comparative Models: The following article to analyse and develop in a CAS such as Mathematica. How do the various given potentials affect orbits? Compare among each other along with the basic basic form Jesco von Puttkamer. (1967). Survey and Comparative Analysis of Current Geophysical Models. NASA George C. Marshall Space Flight Centre. Technical Memorandum X – 53677 --> https://ntrs.nasa.gov/api/citations/19680007574/downloads/19680007574.pdf 11. The Gravity Recovery and Climate Experiment (GRACE) The references in the following (including time-varying modelling) link may be crucial in development: https://en.wikipedia.org/wiki/GRACE_and_GRACE-FO PART A (preliminary) -- Identification and History Physics, (relevant applied) mathematics, engineering technology behind grace gravity anomalies measurements, leading to determination of mass distribution around the planet and how it varies over time. Part B (Goals) -- NOTE: Mathematica will be one tool that may be highly integrable, having geosciences functions (with parameter calls) and data (also with parameter calls). However, it’s also likely that one will have to pull data from addresses or databases that are more exotic. NOTE: for satellite data use towards a respective goal it’s essential that one comprehends The technologies applied Logistics of systems in operation Physics, mathematics that make data development meaningful or possible for research interest The appropriate data analysis for modelling or representation The goals in mind: (i) Ability to acquire the needed data, and data analysis to develop the gravity anomaly map (ii) Detected changes in the distribution of water across the planet; interested in different time periods. Sea level rise (whether it is the result of mass being added to the ocean - from melting glaciers, for example - or from thermal expansion of warming water or changes in salinity (iii) Estimate ocean bottom pressure (the combined weight of the ocean waters and atmosphere); estimate monthly changes in deep ocean currents. Compare with ocean currents estimations by an ocean buoy network data. High-resolution static gravity fields estimated from GRACE data have helped improve the understanding of global ocean circulation. The hills and valleys in the ocean's surface (ocean surface topography) are due to currents and variations in Earth's gravity field. GRACE enables separation of those two effects to better measure ocean currents and their effect on climate. (iv) Use GRACE data to establish record of mass loss within the ice sheets of Greenland and Antarctica; Greenland has been found to lose 280±58 Gt of ice per year between 2003 and 2013, while Antarctica has lost 67±44 Gt per year in the same period. What level of sea rise does this amount to? Independently determine rather than chattering written facts, then compare results with structured mainstream data chat. Will also pursue 2014 to at least 2020. (v) Interest in groundwater depletion for various chosen areas. Annual hydrology for various critical reasons (Amazon basin is only one example). (vi) Glacial Isostatic adjustment). GIA signals appear as secular trends in gravity field measurements and must be removed to accurately estimate changes in water and ice mass in a regions (vii) Identify permanent gravitational changes due to past earthquakes (viii) Analyse the shifts in the Earth's crust caused by the earthquake that created the 2004 Indian Ocean tsunami (and others). (ix) Improvement in models for corrections in the equipotential surface which land elevations are referenced from. This more accurate reference surface allows for more accurate coordinates. (x) GRACE is sensitive to regional variations in the mass of the atmosphere and high-frequency variation in ocean bottom pressure. These variations are well understood and are removed from monthly gravity estimates using forecast models (NWP) to prevent aliasing (relating to signal processing). Of latitude and longitude and for less error in the calculation of geodetic satellite orbits. (xi) Measure lunar tidal influence on mass orientation (land and earth); may or may not have coupling issues with possible solar tidal effects (and perhaps other celestial bodies and geological/geophysical activities). --Earth Rotation Variations For the given literature beneath to accomplish anything, analysis interest must be strong. One needs to convince themselves with various formulas or equations, to be in tune with the literature leading to sustainability. It’s imperative that for all figures in the literature students can replicate them with possible inclusion of modern data. It’s imperative that for all tables in the literature students can comprehend competently their use in models and means of developing or acquiring them (whether being from data sources, or numerical methods, or error analysis, or analytical means). Gross, R. S. (2007). Earth Rotation Variations – Long Period, in Physical Geodesy, edited by T. A. Herring, Treatise on Geophysics, Vol. 11, Elsevier, Amsterdam, in press --Geocenter Determination One major concern will be finding consistency among modelling, methods applied and analysis. This activity doesn’t concern perversions with matrix algebra because we are doing something quite meaningful overall where one’s use of time needs to be optimised. Use of a CAS for any matrix monstrosities. Don’t be intimidated or hoodwinked by someone’s perversion with symbolic matrix algebra, because above have the time they don’t know what such matrices really hold and how to acquire such elements for whatever data or modelling structure (unless you let them parasite off you). Whatever matrix structure encountered when directly recognised in development will be treated by geoscience professionals towards the prime directive. Whatever matrix algebra needs to be comprehended you will learn its task structure and how to acquire meaningful results when you need to do so. You have been applying vectors in physics for quite some time with accuracy and competence, so one doesn’t need some entity trying to make you look inferior over luxury frolic. What’s the point? AGAIN: one major concern will be finding consistency among modelling, methods applied and analysis. Physics of Geocenter Motion Guide --> -Wu, X., Ray, J. and van Dam, T. (2012). Geocenter Motion and its Geodetic and Geophysical Implications. Journal of Geodynamics 58, pages 44–61 The following journal articles are to be used for development. Will like to develop at least 2 schemes to compare with each other & other systems in operation. Mathematica will be one tool that may be highly integrable, having geosciences functions (with parameter calls) and data (also with parameter calls). However, it’s also likely that one will have to pull data from addresses or databases that are more exotic ore exotic --> -Swenson, S., Chambers, D., Wahr, J., 2008. Estimating Geocenter Variations From a Combination of GRACE & Ocean Model Output. J. Geophys. Res. 113. -Kang, Z., Tapley, B., Chen, J. et al. Geocenter motion time series derived from GRACE GPS and LAGEOS observations. J Geod 93, 1931–1942 (2019). -Razeghi, M. et al (2019). A Joint Analysis of GPs Displacement and GRACE Geopotential Data for Simultaneous Estimation of Geocenter Motion and Gravitational Field. Journal of Geophysical Research: Solid Earth, 124, pages 12241 – 12263 -F. Bouillé, A. Cazenave, J. M. Lemoine, J. F. Crétaux, Geocentre motion from the DORIS space system and laser data to the Lageos satellites: comparison with surface loading data, Geophysical Journal International, Volume 143, Issue 1, October 2000, Pages 71–82, Physics students welcomed. --“Local” Geoid Mapping with GPS Physics students welcomed. Numerical integration method Least-squares collocation method Point mass method There will be actual field experimentation for the mentioned three types of methods, and respective results will be compared. Example journal article guides: Novak, P. Geoid Determination Using One-Step Integration. Journal of Geodesy (2003) 77: 193 de Min, E. A Comparison of Stokes Numerical Integration and Collocation, and a New Combination Technique. Bulletin Geodesique (1995) 69: 223 Jekeli, C. and Kwon, J. H. (2002). Geoid Profile Determination by Direct Integration of GPS Inertial Navigation System Vector Gravimetry. Journal of Geophysical Research Solid Earth. Volume 107 Issue B10 Idhe, J., Schirmer, U., Stefani, F. and Toppe, F. (1998). Geoid Modelling with Point Masses. Proceedings of the Second Continental Workshop on the Geoid in Europe, Budapest, March, 199-204. Antunes, C., Pail, R. and Catalao, J. (2003) Point Mass Method Applied to the Regional Gravimetric Determination of the Geoid. Studia Geophysica et Geodaetica, Volume 47 Issue 3, pp 495 -509 Denker H., Torge W., Wenzel G., Ihde J., Schirmer U. (2000) Investigation of different methods for the combination of gravity and GPS/levelling data. In: Schwarz KP. (eds) Geodesy Beyond 2000. International Association of Geodesy Symposia, vol 121. Springer, Berlin, Heidelberg Will then try to make use of software tools from the following links (if relevant to ambiance), and possibly compare with results from the three prior methods: https://www.ngs.noaa.gov/GEOID/ https://beta.ngs.noaa.gov/GEOID/xGEOID/ Determining Geoids with atomic clocks. In the future use of atomic clocks for geological and gravitational studies is the converging with the present. Primiarly concerned with a basic model to institute atomic clocks for such; means to experiment with atomic clocks may not be economic at this time, but comprehension is important: https://phys.org/news/2012-11-surveying-earth-interior-atomic-clocks.html https://phys.org/news/2012-10-atomic-clocks-good-earth-geoid.html The Earth's geoid – the surface of constant gravitational potential that extends the mean sea level – can only be determined indirectly. On continents, the geoid can be calculated by tracking the altitude of satellites in orbit. Picking the right surface is a complicated, multivalued problem. The spatial resolution of the geoid computed this way is low – approximately 100 km. Using atomic clocks to determine the geoid is an idea based on general relativity that has been discussed for the past 30 years. Clocks located at different distances from a heavy body like our Earth tick at different rates. Similarly, the closer a clock is to a heavy underground structure the slower it ticks – a clock positioned over an iron ore will tick slower than one that sits above an empty cave. Ultraprecise portable atomic clocks are on the verge of a breakthrough. An international team lead by scientists from the University of Zurich shows that it may be possible to use the latest generation of atomic clocks to resolve structures within the Earth. Guides: Ruxandra Bondarescu, Mihai Bondarescu, György Hetényi, Lapo Boschi, Philippe Jetzer, Jayashree Balakrishna, Geophysical applicability of atomic clocks: direct continental geoid mapping, Geophysical Journal International, Volume 191, Issue 1, October 2012, Pages 78–82 https://arxiv.org/abs/1209.2889 --> https://arxiv.org/ftp/arxiv/papers/1209/1209.2889.pdf In the future “older methods” will be compared with use of atomic clocks. Be prepared. --Foucault’s Pendulum Physics students welcomed (i) Comprehend the derivation of the precession of Foucault’s pendulum, and derive the governing equations in terms of x and y components: newt.phys.unsw.edu.au/~jw/pendulumdetails.html (ii) Such also done in polar coordinates: http://www.sciencebits.com/foucault (iii) Use Newton’s law and vector calculus to verify that the speed and direction of the pendulum’s rotation depends only on latitude. Then use such to determine distance from the north pole. (iv) Simulate (i) and (ii) via use of appropriate numerical methods. (v) Build Foucault’s pendulum. Make use of long-lasting video display with timer that goes off upon release. Preference in length of pendulum need not be as long as what is described in video but must be considerably long, with sensible initial angle and small maximum angular velocity. A simple guide: Foucault’s Pendulum: Watch the World Turn -YouTube where students concern themselves with longer durations. Environment must always have adequate light. Environment must lack considerable air resistance or wind. Surface of contact in environment must have virtually no incline. Beginning with time duration in video and proceed. Then use three to five other larger duration trials, each approaching 24 hours. How well do the results compare with accepted professional measure? (vi) For what data acquired from built pendulum, does such coincide with simulation models? (vii) Observe the following video: Flat Earth and Foucaults Pendulum -YouTube Applying the pendulum at numerous different latitudes and analysis results, can such verify that the Earth is not flat? (viii) Role of Foucault’s pendulum in use with total relativistic precessions on Earth. What type of precession can Foucault’s pendulum account for in total relativistic precession? Will implement the experimental procedure (at different latitudes). --Analysis of various types of rocks and soils Can also be done by Civil Engineering Students. Vast sampling and examination of rocks (sedimentary, igneous, metamorphic, conglomerate) and soil through the following: 1. Minimal number of specimens for laboratory, and may warrant field investigation --> Gill, D. E. Corthesy, R. and Leite, M. H. Determining the Minimal Number of Specimens for Laboratory Testing of Rock Properties. Engineering Geology 78 (2005) 29 – 51 Note: such development prior may influence all following tasks 2. Mass and Density Evaluation of Various Rocks Direct methods by sampling 3. Estimating Rock Mass Strength. Field/lab experimentation may or may not be feasible --> Hoek, E. and Brown, E. T. Practical Estimates of Rock Mass Strength. Int. J. Rock Mech. Min. Sci. Vol. 34, No. 8, pp. 1165 - 1186, 1997 4. Brittleness of Rocks Meng, F., Zhou, H., Zhang, C. et al. Evaluation Methodology of Brittleness of Rock Based on Post-Peak Stress-Strain Curves. Rock Mech Rock Eng (2015) 48: 1787. Hajiabdolmajid, V. and Kaiser, P. (2003). Brittleness of Rock and Stability Assessment in Hard Rock Tunnelling. Tunnelling and Underground Space Technology, Volume 18 Issue 1, pp 35 - 48 Hucka, V., & Das, B. (1974). Brittleness Determination of Rocks by Different Methods. International Journal of Rock Mechanics and mining Sciences & Geomechanics Abstracts. Volume 111 Issue 10, pp 389 – 392 Kaunda, R. B. and Asbury, B. (2016). Prediction of Rock Brittleness using Nondestructive Methods for Hardrock Tunnelling. Journal of Rock Mechanics and Geotechnical Engineering. Volume 8 (2016) 533 -540 Note: would like to pursue lab tests for rock brittleness if feasible. However, in general, concerning journal articles of interest the analysis, models, rubrics and criteria are mandatory. 5. Rock Mass Modulus Experimentation may or may not be possible, but data sets for particular ambiances are accessible towards modelling. Hoek, E. and Diederichs, M. S. Empirical Estimation of Rock Mass Modulus. International Journal of Rock Mechanics & Mining Sciences 43 (2006) 203 – 215 Sonmez, H., & Gokceoglu, C. (2006). Discussion of the paper by E. Hoek and M.S. Diederichs “Empirical Estimation of Rock Mass Modulus”. International Journal of Rock Mechanics and Mining Sciences, 43(4), 671-676. Nejati, H., Ghazvinian, R., Moosavi, A., & Sarfarazi, S. (2014). On the use of the RMR system for estimation of rock mass deformation modulus. Bulletin of Engineering Geology and the Environment, 73(2), 531 - 540. Ajalloeian, R., & Mohammadi, M. (2014). Estimation of limestone rock mass deformation modulus using empirical equations. Bulletin of Engineering Geology and the Environment, 73(2), 541-550. 6. Rock Slope Stability Analysis Experimentation may or may not not be possible; if not data sets for particular ambiances are accessible towards modelling (particularly for the latter). Norrish, N. I. and Wyllie, D. C. Chapter 15, Rock Slope Stability Analysis. Landslides: Investigation and Mitigation. (1996). Issue Number 247. Transportation Research Board. ISSN 0360 – 859x Park, H., West, T., & Woo, I. (2005). Probabilistic analysis of rock slope stability and random properties of discontinuity parameters, Interstate Highway 40, Western North Carolina, USA. Engineering Geology, 79(3), 230-250. Roy, D., & Maheshwari, P. (2018). Probabilistic Analysis of Rock Slopes Against Block Toppling Failure. Indian Geotechnical Journal, 48(3), 484-497. 7. Continuum mechanics and bulk wave dynamics (stability/instability in oscillation, stress, strain, shear) due to travelling/forced/driven waves. Includes finite element modelling with such. 8. Estimating Rock Mass Properties using Monte Carlo Simulation. To develop all such with computational/simulation tools involving whatever data is required. However, to focus on ambiance of interest unlike article --> Sari, M., Karpuz, C., & Ayday, C. (2010). Estimating Rock Mass Properties using Monte Carlo Simulation: Ankara Andesites. Computers and Geosciences, 36(7), 959 - 969 9. Spectroscopy examinations of soil and rock samples 10. Rock weathering and resistance ability to such Physical types Chemical types Pedochemical types Some tasks (chemical and pedochemical may or may not require reapplication of (9). For physical types, apart from the description of the process and observation, examination of structure and composition may be necessary to recognise specimen that are not comprised with chemical type influences. Will choose various rocks based on their classification (sedimentary, igneous, metamorphic). As well, it may be difficult, but will like to develop physics models to simulate weathering or degradation by physical processes’ time of degradation will be of high interest. To compare with professional confirmed geological time scales of the respective environment. For chemical and pedochemical phenomena will choose various rocks based on their classification (sedimentary, igneous, metamorphic). Then consideration of a range of substances that may degrade rock integrity in a chemical nature. How to model the chemical reactions? Validate the reactions with chemistry knowledge fllwed by sftware verification. Such includes the types of molecular/compound decomposition with the energies required. Will pay care to identify the respective “conventional potency” in the environment towards determination of respective deterioration rate. Some hypotheses may require experimental verification, where some major issues of concern being: By-products Potency Energies involved in the chemical processes Time of degradation Influence of by-products to environment Ph after activity (may be time dependent and dynamic over time) Possible transportation methods of by-product (or pollutant) in to broader ranges (earth, rock, aquatic, air, vegetation) 11. Soil Ph levels. Field investigation involving various samples from various sites. Possible causes identified by (lab) observation based on field collections concerning the ideal composition of samples versus observed, and ambiance history with the influence of weather with surroundings, and human activity. --Measurement of Atmospheric Electricity PART A Bennett, A. J. and Harrison, R. G. (2007). A Simple Atmospheric Electrical Instrument for Educational Use. Adv. Geosci., 13, 11–15 Station developed must insulate equipment components that should not be exposed to moisture and precipitation. Data collection that can be geometrically displayed over time will be a huge triumph. It’s essential that one has precise coordinates of such developed station. Metrological satellite data providing atmospheric progression with applied time frame would be highly welcomed. As well accompanied by a weather station with chronological association (that also has cloud detection ability, say distance, altitude and velocity). Will also incorporate lightning strike data for the considered time frames. PART B Develop a station for the following -> Bennett, A. Measurement of Atmospheric Electricity During Different Meteorological Conditions. University of Reading http://www.met.rdg.ac.uk/phdtheses/Measurement%20of%20Atmospheric%20Electricity%20During%20Different%20Meteorological%20Conditions.pdf Data collection that can be geometrically displayed over time will be a huge triumph. It’s essential that one has precise coordinates of such developed station. Meteorological satellite data providing atmospheric progression with applied time frame would be highly welcomed. As well accompanied by a weather station with chronological association (that also has cloud detection ability, say distance, altitude and velocity). Will also incorporate lightning strike data for the considered time frames. --Reinforcement of Geochemistry labs and field studies Activities concern the reinforcement of the specified labs from the Geochemistry course. Thus, the Geochemistry course will be a prerequisite; activities will be more accelerated than course. Relevant lectures topics will be reviewed before lab operations. It may be quite constructive to professionally and permanently store and secure data with identification of location(s). One may find trends or consistencies with respect to location and seasons. Labs and field studies may be augmented, advanced, or new activities incorporated. --Reinforcement of Mineralogy labs and field studies Activities concern the reinforcement of the specified labs from the Mineralogy course. Thus, the Mineralogy course will be a prerequisite; activities will be more accelerated than course. Relevant lectures topics will be reviewed before lab operations. It may be quite constructive to professionally and permanently store and secure data with identification of location(s). One may find trends or consistencies with respect to location and seasons. Labs and field studies may be augmented, advanced, or new activities incorporated. --Seismic Recording, data storage and processing and filtering systems Can also be done by Civil Engineering Students. PART A Synopsis: Includes logistics and use of programmable boards with sensor integration and modelling for the novice (possibly both cooler tubes and brushless 30mm-92mm fans integrated); independent of Computer Science and Engineering curriculums. Recording data towards organisation and engagement with mathematical models (seismology, etc. incorporating the appropriate initial and boundary conditions), etc. Chronological readings for within 4-12 weeks, where also data will be thrown to mathematical models that consistently describe dynamics. For activity, the chosen island or region must be to scale with the models, etc. Location records are also crucial. The key components for an amateur seismographic station are the same as for the professionals: 1) the sensor 2) preamplifier 3) low pass filter 4) amplifier 5) analog-to-digital converter 6) computer programs and hardware for the (permanent) collection of data 7) computer and monitor for the display of the data 8) printer (or drum recorder), if you want to print the seismograms Note: Example software are WinSDR with WinQuake, Earthworm. Programmable boards must be shielded from high temperatures, moisture, dust and precipitation. With the following wave analysis review, one must practically and tangibly situate the prior mentioned 8 components (which may not flow in such given order): 1. Vibration principles (ideal models, superposition, impedance, resonance, scattering) 2. Fourier (representation & transforms) 3. Signal Analysis towards geophysical interests 4. Signal detectors, source requirements and design considerations. Digital recording systems. Analog-to-Digital signal converters. 5. Signals and noise Seismic signals are usually transient waveforms radiated from a localized natural or manmade seismic source. They can be used to locate the source, to analyse source processes, and to study the structure of the medium of propagation. In contrast, the term “seismic noise” designates undesired components of ground motion that do not fit in our conceptual model of the signal under investigation. What we identify and treat as seismic noise depends on the available data, on the aim of our study and on the method of analysis. Accordingly, data treated as noise in one context may be considered as useful signals in other applications. For example, short-period seismic noise can be used for microzonation studies in urban areas, and long-period noise for surface-wave tomography (Yanovskaya, 2012). Seismic noise conventionally relates to the following: Ambient vibrations due to natural sources (like ocean microseisms, wind, etc) Man-made vibrations (from industry, traffic, etc) Secondary signals due to wave propagation in inhomogeneous media (scattering) Effects of gravity (Newtonian attraction of atmosphere, horizontal accelerations due to surface tilt) The following guides can be used: Bormann, P. (Ed.)(2012): New Manual of Seismological Observatory Practice (NMSOP-2), Potsdam : Deutsches GeoForschungszentrum GFZ; IASPEI. Peterson, J. R. (1993). Observations and Modelling of Seismic Background Noise. U.S. Geological Survey. Series number 93- 322. The role(s) of (various) filters must be emphasized and implemented. Design of target-oriented signal detection. 6. Other causes of seismic noise that may become quite influential: Signals due to the sensitivity of seismometers to ambient conditions (temperature, air pressure, magnetic field, etc) Signals due to technical imperfections or deterioration of the sensor (corrosion, leakage currents, defective semiconductors, etc) Intrinsic self-noise of the seismograph (like Brownian noise, electronic and quantization noise) Artifacts from data processing Building seismometers: Seismometers will be built. Built seismometers concerning sensing, testing and calibration to be similar in the following link, but must meet all prior demands (synopsis, key components, the detailed wave analysis review, hardware & software): https://www.instructables.com/id/This-Seismometer-is-no-toy/ To compare seismology data from seismology/geology institutes or government administrations from multiple locations,of relatively near distances. Make use of wave mechanics, P & S wave analysis, etc., etc. Seismology readings are generally chronological, instantaneous and daily, with the ability to differentiate one day from another. Seismic wave recordings to be graphically exhibited with its counterpart from seismology or geology institutions and government administrations via common units scale. Field activities. Using data from professional sources data fit/calibrate models and acquire geometric representation of seismic wave forms (P, S, Love and Rayleigh), computation of epicenter and focus, extracting the critical properties or parameters, reflection, refraction for determination of matter (densities). Likely, will also involve some time series use to estimate parameters. As well, possibly to compare built seismometers to professional commercial seismometers (schematics only) for understanding of efficiency and sensitivity, and to contemplate resolutions of improvement. Some earthquake location assists: Waldhauser F. and W. L. Ellsworth, A Double-Difference Earthquake Location Algorithm: Method and Application to the Northern Hayward Fault, Bull. Seism. Soc. Am., 90, 1353-1368, 2000 Waldhauser, F., HypoDD: A Computer Program to Compute Double-Difference Earthquake Locations, USGS Open File Rep., 01-113, 2001. Araya, M., C., Application of the Double Difference Earthquake Relocation Algorithm Methodology using HypoDD at Four Seismic Sequences in Costa Rica, Revista Geológica de América Central, 57, 7-21, 2017 After engagement with such two articles and HypoDD, students will engage in comparative view between seismic operations done earlier and HypoDD. As well, computational comparative analysis with the following: Wu, H., Chen, J., Huang, X., and Yang, D., A New Earthquake Location Method Based on the Waveform Inversion, Commun. Comput. Phys., Vol. 23 (2018), pp. 118-141 Barmin, M., P., Levshin, A., L., Yang, Y., and Ritzwoller, M., H., Epicentral Location based on Rayleigh Wave Empirical Green’s Functions from Ambient Seismic Noise, Geophys. J. Int. (2011) 184, 869–884. << Mathematica is highly useful with Green functions >> Determining the complexity of paths of earthquake waves. The speed of sound varies for different media. Such is evident in elementary experiments with media ranging from solid to fluids. The paths of earthquakes curve because the different rock types found at different depths change the speed at which the waves travel. There are compressional waves (P), shear waves (S) and other types. S waves do not travel through the core but may be converted to compressional waves (marked K) on entering the core (PKP, SKS). Waves may be reflected at the surface (PP, PPP, SS). A pursuit is to develop the means to interactively study the Earth’s interior based on such seismic waves’ dynamics. All relevant aspects will be thoroughly applied --> Physics Mathematics Technologies Data sources Such four aspects will be thoroughly analysed, and integrated together in the most fluid, tangible and practical means. Mathematics will be applied as a tool with purpose and nothing more; activity has a meaningful objective. PART B International Atomic Energy Agency (2022). Methodologies for Seismic Soil–Structure Interaction Analysis in the Design and Assessment of Nuclear Installations, TECDOC Series, IAEA, Vienna (will generalise to habitats and surroundings of interest) --Plate Tectonics 1. Discovering Plate boundaries. A data rich exercise to assist students in discovering the processes that occur at plate tectonic boundaries. Observation and classification of data. < http://plateboundary.rice.edu/downloads.html > Note: GRASS GIS (with addons can apply). Elements in observation: a. Global data maps b. Earthquake location and depth c. Location of (recent) volcanic activity d. Sea floor age e. Topography & bathymetry Tools for observation: a. Seismology b. Volcanology c. Satellite Geodesy d. Geochronology 2. Subducting Plate Graphs i. Graph the longitude and depth of earthquakes associated to the continent in question. ii. Use such a graph to visualize the descending slab of oceanic crust at this subduction boundary. iii.compare the graphs for various latitudes and describe their similarities and differences. Note: can be in conjunction with 3D activity modelling. Observations about the depth of the earthquakes as you go further inland from the coast. What appears to be happening to meeting plates along the coast of (whatever continent in question) according to model? Description of the type of plate boundary believed to be present along the coast of (whatever continent in question) Explanation of trenches off coasts. 3. Hot Spot activity. The useful mechanism of measuring the age of different islands formed from a hot spot, and take the ratio of the distance to the age, to determine the rate of speed of the plate. Consider islands, outlets, shoals, reefs and banks for hot spots. Instructions: i. There will be a key for measurement conversion concerning the map(s). Use a ruler or other measuring device to measure the distance between the first volcano (which ever that may be) and the other island volcanoes. Conversion to kilometers or meters and record on a data table for the islands and outer seamounts. ii. Create a graph. Distance (in kilometers) on the vertical axis, while age (in millions of years) on the horizontal axis. Create best bit line from such dispersion. Slope of line distance over time will yield the speed of the plate (in kilometers per millions of years). Segregating the ages of islands and outlets into different age ranges w.r.t. distance can provide some idea of the rate of change in speed for an age range in question. One can determine roughly whether plate motion is increasing or reducing throughout existence; particular rates or drastic change in slope can likely be matched with major events if age ranging is chosen appropriately. Are findings consistent with professional data sources? iii. One can convert the speed from kilometers per millions of years to centimeters per year, and repeat (ii). iv. Hotspot hypothesis. Does trend conform to such hypothesis? v. Space geodetic techniques with focus on the theory and practice of the Global Positioning System (GPS). Hands-on experience using GPS data to address scientific problems in the Geosciences. Hands-on experience in data processing techniques, including programming a simple GPS data processing software. Measuring the movements of a house, other buildings, etc. GPS station positions change as plates move. By repeatedly measuring distances between specific points, geologists can determine the movement along faults or between plates. The separations between GPS sites are already being measured regularly around the Pacific basin. By monitoring the interaction between the Pacific Plate and the surrounding mostly continental plates, scientists are learning more about events that build up to earthquakes and volcanic eruptions in the circumPacific “Ring of Fire”. Space-geodetic data have already confirmed that the rates and directions of plate movements, averaged over several years, compare well with rates and directions of plate movements averaged over millions of years. Students should be able to: Describe generally how GPS works Interpret graphs in a GPS time series plot Determine velocity vectors from GPS time series plots Explain relative motions of tectonic plates in Iceland Explore global GPS data. Example guides: http://www.earthscope.org/sites/default/files/escope/assets/uploads/misc/measuring-plate-motion-presentation-revised-20150801.pptx.pdf https://www.unavco.org Will make use of similar tools for determination plate movements. The mentioned guides are highly useful towards to strong foundation for understanding tectonic plates movement via GNSS/GPS. vi. The following literatures may or may not appear quite repulsive concerning detailed or attentive reading for proper analysis, however, the rewarding prime directive may be to either (1) Identify the data used to develop or proceed throughout. To find sources for such data, acquire them and develop modelling to confirm (the majors) findings of the literature (2) analyse analytical models and replicate findings Note: depending on publication or respective journal article one may not be restricted to the applied time frames used in the given journal articles. Can also be extended with more modern data. Crucially, for some articles it may be of great importance to compare more modern data with data for time frame observed in respective journal article. --Gibbons, A., Zahirovic, S., Muller, R.D., Whittaker, J., and Yatheesh, V. 2015. A Tectonic Model Reconciling Evidence for the Collisions between India, Eurasia and Intra-oceanic Arcs of the Central-Eastern Tethys. Gondwana Research --Beghein, C. et al. (2014). Changes in Seismic Anisotropy Shed Light on the Nature of the Gutenberg Discontinuity. Science, Vol. 343, Issue 6176, pp. 1237-1240 --Alec R. Brenner, Roger R. Fu, David A.D. Evans, Aleksey V. Smirnov, Raisa Trubko, Ian R. Rose. Paleomagnetic Evidence for Modern-like Plate Motion Velocities at 3.2 Ga. Science Advances, 2020; 6 (17): eaaz8670 https://science.sciencemag.org/content/suppl/2014/02/26/science.1246724.DC1 --For the following article, after analysis and logistics development is it possible to apply modelling to a GIS? Hayes, G. P et al. (2018). Slab2, A Comprehensive Subduction Zone Geometry Model. Science, eaat4723 --Mason, Ronald G.; Raff, Arthur D. (1961). "Magnetic survey off the West Coast of the United States between 32°N latitude and 42°N latitude". Bulletin of the Geological Society of America. 72 (8): 1259–66 --Raff, Arthur D.; Mason, Roland G. (1961). "Magnetic survey off the west coast of the United States between 40°N latitude and 52°N latitude". Bulletin of the Geological Society of America. 72 (8): 1267–70. --Volcanic Explosion Measures The given literature concerns methods to measure the explosion energy of volcanoes. Methods will range from analytical schemes to data analysis-data modelling. Note: there may be other methods from elsewhere to incorporate. 1. Analysis of the various methods 2. Logisitics for implementation 3. Implementation and compare/contrast The literature: Gorshkov, G. S. (1960). Determination of the Explosion Energy in Some Volcanoes According to Barograms. Bull Volcanol 23, pages 141–144 Steinberg, G. S. (1976). On the Determination of the Energy and Depth of Volcanic Explosions (paper dedicated to G. S. Gorshkov). Bull Volcanol 40, pages 116–120 Volcanic Explosivity Index Cmprehension of the development of such index is also warranted; critcisms as well --Magnitude–Frequency Distribution of Volcanoes PART A The given literature concerns only explosive volcanoes. Objectives are to analyses articles and pursue replication. Then consideration of other regions of interest to analyse. Nishimura, T., Iguchi, M., Hendrasto, M. et al. (2016). Magnitude–Frequency Distribution of Volcanic Explosion Earthquakes. Earth Planets Space 68, 125 Nishimura, T., Iguchi, M., Hendrasto, M. et al. (2017). Correction to: Magnitude–Frequency Distribution of Volcanic Explosion Earthquakes. Earth Planets Space 69, 143 PART B REMINDER: not all volcanoes are explosive. After analysis of the followng article pursue replication, then augment with more modern data and draw conclusions. Papale, P. (2018). Global Time-size Distribution of Volcanic Eruptions on Earth. Sci Rep 8, 6838 --Geodynamics and Seismology Software Immersion 1. Students to become well experienced with at least two Geodynamics software from what was provided. Choice must at least two since one software generally isn’t best in every area of geodynamics. Heavy physics and mathematical modelling will be premature phase before getting into software. 2. Students to become well experienced with seismology software. Concerns are the ability to intake seismometer data and structurally express it (seismographs and models); includes recognition of P, S, Love and Rayleigh waves. Include reflection seismology and refraction seismology. Heavy physics and mathematical modelling will be premature phase before getting into software. --Understanding Earth Neutrino Tomography without Nuclear & Particle Physics expertise Fiorentini, G., Lissia, M. and Mantovani, F., Geo-neutrinos and Earth’s Interior, Physics Reports 453 (2007) 117 – 172 Borriello, E., et al, High Energy Neutrinos to see inside the Earth, Nuclear Physics B (Proc. Suppl.) 190 (2009) 150–155 Winter, W., Atmospheric Neutrino Oscillations for Earth Tomography, Nuclear Physics B 908 (2016) 250–267 Matias M. Reynoso, M., M., Sampayo, O., A., On Neutrino Absorption Tomography of the Earth, Astroparticle Physics 21 (2004) 315–324 To then recall methods of Earth density variation determination by seismology, where error analysis level is compared to the error analysis level of the mentioned neutrino tomography methods. --Mapping and Classification of Rivers, Water sources and Vegetation A directive is to trace all rivers systems from start to end (including branches) towards a detailed mapping and the associated vegetation and weather variations. Will also aim to map such river systems, water sources, vegetation, with GIS in detail involving altitudes and coordinates. To also be compared with the official geological, environment, ecological mapping and data of the ambiance. Satellite data may or may not be applicable or tangible for cross reference. Software of interest --> Grass GIS (with addons) iRIC PRMS (Precipitation Runoff Modeling System) SWAT(http://swat.tamu.edu/) LANDIS II < http://www.landis-ii.org > PnET < http://www.pnet.sr.unh.edu > Use of Pnet Models and/with LANDIS II. One may need to be immersed with each separately before possible integration with each other. Gustafson, E. J. (2015). New LANDIS-II succession extension: PnET-Succession. LANDIS II.org. < www.landis-ii.org/blog/newlandis-iisuccessionextensionpnet-succession > Above source may have other crucial literature cited besides the following two: Aber JD, SV Ollinger, CA Federer et al.(1995). Predicting the effects of Climate Change on Water Yield and Forest Production in the Northeastern United States. Climate Research 5:207 - 222. De Bruijn A., Gustafson E.J., Sturtevant B.R., Foster J.R., Miranda B.R., Lichti N.I., Jacobs D.F. (2014).Toward More Robust Projections of Forest Landscape Dynamics Under Novel Environmental Conditions: Embedding PnET within LANDIS-II. Ecological Modelling 287:44–57. HEC-RAS activities All data involved in activity will be archived. (i) River classification guides: <Rosgen, D. L., A Classification of Natural Rivers, Catena 22 (1994) 169-199>. <Buffington, J. M., and Montgomery, D. R., 2013. Geomorphic classification of rivers; Source: Shroder, J. (Editor in Chief), Wohl, E. (Ed.), Treatise on Geomorphology. Academic Press, San Diego, CA, vol. 9, Fluvial Geomorphology, pp. 730–767>. For numerous rivers will physical identify source and ends (including all branches); such to include altitude data gathering with coordinates for chosen distance increments. Will also identify the vegetation variation around such rivers involving altitudes and coordinates. For a specific vegetation in the respective area one should identify the source of hydrological abundance that sustains it. All sources and ends must be physically observed. Note: man made tools, structures, alterations and pollution may or may influence the environment and locations, hence, one must carefully observe, recognise and consider such presence if any. It’s also vital that one recognises a credible theory on respective river (concerning formation and evolution). As well, historical geomorphology by official record keeping and chronological imaging consistently accounting for vast past dates will be invaluable. (ii) Location of lakes with altitudes and coordinates (to high degree). Geomorphic description of lake surroundings and lake beds, bed layers, etc. Pursuit of cause of respective lake and its age. Note: man made tools, structures, alterations and pollution may or may influence the environment and locations, hence, one must carefully observe, recognise and consider such presence if any. It’s also vital that one recognises a credible theory on respective lake (concerning formation and evolution). As well, historical geomorphology by official record keeping and chronological imaging consistently accounting for vast past dates will be invaluable when compared to field data. (iii) Wetlands Classification Will identify various international wetlands classifications systems and identify however they differ. Then, will observe numerous wetlands and gather data with respect to location and altitude (high accuracy). Formation with history. Water depths may or may not be useful. As well, be very specific with vegetation types and how a respective vegetation’s dispersion and density various w.r.t. numerous directions. Such can be and identification on climate and weather types. It’s also vital that one recognises a credible theory on respective wetland (concerning formation and evolution). As well, historical geomorphology by official record keeping and chronological imaging consistently accounting for vast past dates will be invaluable. Note: man made tools, structures, alterations and pollution may or may influence the environment and locations, hence, one must carefully observe, recognise and consider such presence if any. All such data gathered to be applied to the different wetlands classification systems and to analyse the respective strengths and informativeness of each classification.

--Stratigraphic Observation, Invertebrate and Vertebrate Palaeontology field activity Professional verbiage will be heavily instituted and reinforced. Requires a course in Stratigraphy and Paleontology. Observe the seriousness of the geomorphology activity described later on; such should provide an idea of the seriousness to take place. 1. Will identify the fossiliferous stratigraphic units and try to identify any uniqueness with location. Reference locations in relation to historical volcanic, seismic or plate tectonic activities. 2. Observation and data collection on the Tobago Volcanic Group of fossils. Will pursue identifying what geological and geomorphic regions of the island exhibit highly substantial data for designation of this group. Pursuit of Radiolaria and Ammonite fossils dating back to the Albian period. One should not eliminate the circumstance of finding other fossil types and the possibility of other geologic periods. Fossil pursuits can at times yield poor gains, nevertheless, preservation of sites will be a prime directive. Dated data gathering will also be augmented by other particular information such as Coordinate location, elevation Geological description of region and possible hydrology Rock or soil description Vegetation Such to be followed by input into a GIS (GRASS GIS with addons). GIS development will be securely archived and compared to future development in this activity. Will try to identify any contradictions between stratigraphic findings from (1) and palaeontology findings, with possible explanations for such and the evidence. Other places of interest can do such with the level of abundance available. --Field Geology reinforcement The Field Geology course will be prerequisite. This activity will likely impede one from taking taking any other activity concurrently, unless, the other activities (excluding paleontology) involve high amounts of time outdoors with GIS (GRASS GIS with addons) activity and so forth, in manner that other types of geological activity can be administered alongside. Such experience in course and repetition allows one to accumulate “fast” growing experience towards improving their knowledge and skills; for guides, instructors/professors such will be direct experience towards better planning, logistics and improved professionalism. Relevant lectures topics will be reviewed before operations. --Photonic dating Such activity is administered by the Physics administration. Check Physics post --Surface Exposure Dating The following are decent guides for the understanding and experiment development of Surface Exposure Dating: Ivy-Ochs, S. and Kober, F., Surface Exposure Dating with Cosmogenic Nuclides, E&G Quaternary Sci. J., 57, 179-209 Applegate, P. J. et al, Modelling the Statistical Distributions of Cosmogenic Exposure dates from Moraines, Geosci. Model Dev., 3, 293–307, 2010 Gliganic, L. A. et al, OSL Surface Exposure Dating of a Lithic Quarry in Tibet: Laboratory Validation and Application, Quarternary Geochronology 49 (2019) 199 – 204 Pursue the most economic but highly accurate means to orchestrate such forms of dating. One can possibly compare with results from the photonic dating activity. --Conventional Field Experiments and Measurement in Geomorphology NOTE: GRASS GIS with addons may serve well alongside other tools. NOTE: HEC-RAS may serve throughout well also. A. Slope morphometry Field Observation To evaluate the effect of substrate on slope morphology, map various geomorphologic features, and perform basic surveying techniques and slope profiles. B. Drainage bin morphometry To better appreciate the usefulness of topographic maps as tools for investigating drainage basins and to master several morphometric variables used to characterize and analyse drainage basins. Satellite imaging of high volume in frames for a respective duration would also help A Few Fundamental Basin Parameters Drainage Networks Hypsometric Curves Laboratory Exercise C. Quaternary Stratigraphy The objectives of this exercise are to learn how to describe unconsolidated sediments and to draw inferences about the depositional and weathering history of those sediments, based on their observable characteristics and the surrounding environment. We will be studying a roadcut exposed along a chosen site. D. Hypothesis testing and flume The principal objectives of this lab are to familiarize yourself with the concept of hypothesis testing and to learn some of the basic processes of stream flow and sediment transport. To accomplish the goals of this lab you will form small groups and formulate a hypothesis to test. The hypothesis must involve some aspect of stream flow or development, sediment transport, or related issues that may be tested using the flume in the lab location. Ideally, you will explore the controls on channel geometry as a function of discharge, slope, or sediment supply. After your hypothesis has been approved, you will investigate the validity of the hypothesis and the assumptions that underlie it. E. Fluvial landforms To review and observe drainage patterns, introduce fluvial landforms study and observations, as well as concepts of hydrographs and flood dynamics. Many of the exercises and observations focus on the relationship between flood and channel characteristics. 1. Drainage Patterns 2. Fluvial Landforms 3. Hydrologic concepts (analysing flood hydrographs, rating curves & flood frequencies) F. Fluvial and Karst Landforms (data) Involving Google Earth with USGS Topographic Maps Learn how to quickly and efficiently analyse topography using Google Earth and realize which applications it is and is not appropriate for. Critically ponder fluvial landscapes and the processes that shape them. Learn to recognize and think about karst topography. G. Eolian and Arid Region Landforms (data) The objective of this lab is to familiarize yourself with a few basic desert and eolian landforms. Answer the following problems completely. You may need to utilize the lecture text to supplement your answers. Google Earth with USGS Topographic Maps Analysis using stereographic photographs Eolian concepts Use of Entrainment Equations H. Glacial Features and Interpretation of Imagery To learn to recognize, analyse, and interpret glacial landforms, and to learn to map these landforms using aerial photographs and topographic maps. To learn to quickly extract elevation profiles from Google Earth for preliminary analyses. Likely to incorporate satellite imaging of high volume in frames for a respective duration 1. Identifying landforms produced by Alpine glaciation 2. Identifying landforms produced by continental glaciation 3. Mapping glacial topography in a chosen river 4. Analysing the chosen valley morphology via Google Earth with topographic profile related to prior chosen river, glacial erosion, etc. Use the cross-sections to measure the cross-sectional area eroded by fluvial processes and the cross-sectional area eroded by glacial processes. To do this, calculate the area by parcelling the profile into rectangles. Feel free to do this by hand. Or, use a CAS. According to the prior calculations, which process -- glacial or fluvial -- appears to have been the more effective erosive agent in the chosen river? Ratio of the amount of glacial erosion to the amount of fluvial erosion. Discuss the assumptions involved in this method of calculation and whether they appear valid here. Briefly describe and compare the morphologic processes that were involved in creating the two distinct morphologies represented by your cross sections. I. River Field Trip To gain field experience in measuring fluvial geomorphic variables and experience in analysing flow and sediment transport processes and controls on channel morphology. Data Collection: Form groups of 3 people. Each group will be responsible for surveying and describing one reach of the channel, following these steps: 1) Select a study reach. Your study reach should be several times longer than channel width, and should be distinct from reaches studied by other groups. Also select a cross section site to survey. 2) Each group member should make a sketch map of the site, including both a plan-view sketch showing the valley and channel morphology along your reach, and a cross-section view sketch of your cross section. The sketches should note particle-size characteristics of various sediment patches (visually estimated into size classes; see table at end of handout), bedforms, general dimensions (widths, depths, lengths), vegetation, flow characteristics, scale and orientation, and any other details that might improve your data interpretation after you leave this site. Use this sketch to focus on specific details of the study area. You can also use your sketch map as a guide or framework on which to note locations of data collection, which is critical during fieldwork. 3) Using a hand level, tape, and stadia rod, survey a cross section within your reach in order to characterize channel form. Survey the entire valley bottom along your cross section. Identify and survey the bankfull level, which may be evidenced by a break-in-slope, a change in vegetation characteristics, or other high-water marks. In addition, note any other indicators of past high flows (such as fluvial sediments, driftwood, or algae stains on the rocks bordering the channel) above the bankfull level. Your cross-section survey should also include data points at the channel edges, and survey points in the channel at ten percent intervals across the river (at one-tenth of active channel width, two-tenths, etc.). Record flow depth (using the stadia rod) at each survey point. 4) Measure the channel bed gradient of your study reach. To do this, complete a simplified longitudinal profile by surveying two points in the channel thalweg; one point at the upstream end of your reach and one point at the downstream end (using level, rod, and tape), and by measuring the distance between them with a tape. Gradient points should be on consistent bedforms (e.g. if your upstream measurement point is in a riffle, your downstream point should be as well, rather than in a pool). 5) Measure velocity at ten percent intervals across the channel along your cross section (at the same positions as you surveyed) using a current meter. At each position, measure velocity for one minute, and at a position 0.4*flow depth up from the bed (measurement at this position is intended to provide a rough approximation of vertically averaged velocity). 6) Characterize bed material: (a) Measure particle size on a bar along your cross section using a pebble count of 100 clasts. Select clasts for measurement using a random-walk or grid method. For sand-sized particles, record the size as < 2mm. For particle > 2mm measure the diameter of the intermediate particle axis in metric (mm). It’s essential to select an area where particles representative of your reach. Qualitatively characterise armouring of the bed material in the area of your pebble count; remove surface layer of clasts and visually estimate the dominate size of subsurface particles (sand, gravel cobble). Then compare the size of the subsurface clasts with that of surface particles. Such gives insight into the relationship between sediment supply and transport capacity in his reach. (b) Qualitatively describe embeddedness of the bed material along your cross section. Examine the interstices of coarse particles on the bed in terms of the degree to which they are filled with fine sediment. Assign a rating from 1 to 5, where 1 implies that interstitial space is entirely filled with fine sediment, and 5 indicates that no fine sediment is present in the interstices of larger particles. This is another way of examining the relationship between supply and transport capacity. Data Analysis (case example): 1) There is a gaging station located near our study site: USGS Station 06752000 (Cache La Poudre River at mouth of canyon, nr Ft Collins, CO). For the purposes of this exercise, you can assume the gage is representative of flows at our study site. Obtain the historic peak flow data for this site from the USGS: http://waterdata.usgs.gov/co/nwis/nwisman/?site_no=06752000&agency_cd=USGS Construct a flood frequency curve for this site, using the following steps: (a) Download annual peak data into a spreadsheet. Convert the data to metric (i.e., from cfs to m 3 /s; hint 35.3 cfs=1cms). Sort the data from highest to lowest peak flow, and assign each flow a rank (the highest recorded flood will have a rank of 1; the lowest will have a rank equal to the number of years in the period of record). (b) Calculate recurrence interval (RI) using the formula: RI=(n+1)/m, where n is the number of years of record and m is the rank. (c) Construct a semi-log plot of Q versus RI, with Q on the y-axis (normal scale) and RI on the x-axis (logarithmic scale). This is easily done in Excel by right-clicking the x-axis in your graph, selecting “Format Axis”, “Scale”, and checking the box for “Logarithmic scale”. Most of your data points should lie along something approximating a straight line. Fit a line to the data, either by hand or using Excel. 2) Plot your cross-section with no vertical exaggeration. Calculate mean flow depth, cross section area, and hydraulic radius (R) for field conditions at the time of the survey and for estimated bankfull conditions. Note that R=area/wetted perimeter. 3) Calculate cross-section averaged velocity from your current-meter data. 4) Using your field measurements of channel dimensions and velocity, calculate discharge at the time of the fieldtrip using the continuity equation: Q = wdv, where Q is discharge (m3 /s), w is width (m), d is depth (m), and v is mean velocity (m/s); Compare your estimate of Q with the Q recorded at the gaging station for the day of your survey. You can find the provisional flow data for the day of our survey at either http://www.usbr.gov/gp/hydromet/claftcco.htm http://dwr.state.co.us/Hydrology/flow_search.asp 5) Determine bed slope for your reach based on your survey data. Then calculate boundary shear stress at the time of the field survey and for bankfull conditions (the formulas below should have numerous Greek letters; see TA for help if yours don’t print out properly). Next, calculate stream power per unit area for bankfull conditions. 6) Analyse pebble count data as follows: (a) Enter particle size data into a spreadsheet (for particles < 2mm, enter the size as 1mm) (b) Sort particle sizes from smallest to largest (c) In a new column adjacent to the sorted particle size data, rank the particle sizes from 1 to 100 (or higher if you counted more than 100 clasts) (d) If you counted more or less than 100 particles, in a new column, calculate % finer for each particle as follows: % finer = (n/m)*100, where n is the rank of the particle and m is the total number of particles counted. If you counted 100 particles, n=% finer. (e) Plot % finer (y axis, normal scale) versus grain size (x-axis, log scale). Determine D50 (median grain size) and D84 (the particle size for which 84% of particles are finer). 7) Calculate critical boundary shear stress (the shear stress associated with initial movement of bed sediment) for the bed material in your reach 8) Based on your field identification of bankfull level and the continuity equation Q=wdv, calculate Qbf. Use field estimates of bankfull width and depth, and calculate bankfull velocity using 2 methods: a) Estimate Manning’s n resistance coefficient using the table from Van Haveren (1986) (provided in lab), calculate Rbf from your cross-section, and calculate velocity from the Manning equation. b) Assume the velocity you measured in the field equals bankfull velocity. This will result in 2 estimates of bankfull discharge. Determine the frequency (RI) of these discharges at the USGS gaging station. Bankfull discharge (Qbf) is often approximated as having a 1.5-year recurrence interval. Use your flood frequency curve to determine Q1.5 (the discharge with RI=1.5) at the USGS gage. Questions: 1) Discuss uncertainty in your field estimate of Q at the time of the survey. Among other things, consider whether the assumption that the gage data are representative of our field site is appropriate. 2) Using your results from (5) and (7), compare your calculated values for τ bf (boundary shear stress at bankfull conditions) and τc (critical boundary shear stress). Does your analysis suggest that bed sediments at this site are mobilized at close to bankfull discharge, or at some lower or higher flow level? How does this result compare to your field observations about grain size and channel morphology in the Poudre? 3) Compare the 3 discharge estimates developed in (8) above and discuss the results of this analysis. This discussion should, at the least, address the following points: (a) What are sources of error/uncertainty in the methods of estimating Qbf? (b) Do your estimates of Qbf based on field estimates seem reasonable? (c) How do these estimates compare to Q at the time of the survey? (d) Do you think that approximating the bankfull discharge as the 1.5-year event is reasonable in the Poudre River? 4) Discuss the controls on channel and valley morphology at the Poudre River field site, incorporating your data, your observations in the field, other knowledge of the Poudre, and what you have learned in lecture and lab about fluvial geomorphology. Consider the driving and resisting forces at work here, including geology, climate, anthropogenic impacts, etc. Discuss how stable you think the present channel configuration is -- if you were to return to this spot in 10 years, or 50 years, how might it appear different? Be specific about potential changes or lack thereof in channel characteristics (grain size, width, planform). 5) Discuss your observations of bed material, including dominant size class of your bed material, qualitative assessment of armouring, and embeddedness. Based on your observations, do you think your reach is supply-limited (i.e., sediment transport capacity exceeds sediment supply) or transport-limited (i.e., the supply of sediment to the channel exceeds the ability of the channel to transport that material downstream)? 6) Channel classification can be a valuable tool for describing a stream in a way that can be easily communicated to others. Classify your study reach using the Montgomery-Buffington classification system. Justify the classification you selected, and discuss whether you think this classification system is appropriate for describing this channel. 7) Does this channel appear to be in need of “restoration”? That is, based on what you have learned about fluvial forms and processes, is there evidence that this site has been altered by human activities in a way that could/should be reversed, or does the channel appear to be functioning reasonably? If you do think that restoration measures are merited here, what types of measures would you advocate? 8) The City of Fort Collins and other parties are planning on raising Halligan Dam on the North Fork Poudre River, which enters the main Poudre a few miles upstream of our study site, in order to increase storage capacity. Do you think that this will affect channel morphology at our study site? If so, how and why? If not, why not? In following hours or days, we will go over and provide time to work on the data analysis requested above. You will need to bring data to move forward with other analysis. At a minimum, you should bring the following data to lab next week: flood frequency analysis particle size data, including calculated D50 and D84 survey data (cross section and long profile), including calculated bed slope, channel width, and channel depth In addition to answers to the questions above, your report should include the following: sketch maps (from each person in your group) (plan-view and cross-section view); flood frequency curve cross-sectional plot of channel, showing the active channel width, bankfull width, labels, title, etc (no vertical exaggeration); Summary table describing physical characteristics (measured and calculated) of channel Reach and various discharge estimates Appendix showing all calculations Raw data (survey, pebble count, velocity). I. Coastal Processes (example): https://sites.warnercnr.colostate.edu/g454/wp-content/uploads/sites/93/2016/12/Lab-12-DS.pdf --Reinforcement of Hydrology labs and field studies Activities concern the reinforcement of the specified labs from the Hydrology course. Relevant lectures topics will be reviewed before lab operations. Thus, the Hydrology course will be a prerequisite; activities will be more accelerated than course. One may find trends or consistencies with respect to location and seasons. Labs and field studies may be augmented, advanced, or new activities incorporated. --Influence of Floods on Landscapes PART A NOVA – Killer floods (Season 44 Episode 18, 2017) The USGS has software that can simulate large floods over large terrains; complemented by GIS (GRASS GIS with addons) RHESSys, HEC-HMS, HEC-RAS, HEC-FIA. iRIC, MODFOW + MT3DMS, PRMS (Precipitation Runoff Modelling System) First step is analyse supporting document for such software. Second Step is to run such application(s) over terrains of preference to observe the impact on landscapes. Perhaps, such mentioned software provides references and/or modelling and development papers. As well, a few guides that may assist: -Haider S. et al, Urban Flood Modelling Using Computational Fluid Dynamics, Proceedings of the Institution of Civil Engineers - Water and Maritime Engineering 2003 156:2, 129-135 -Rojas, S. G. S. et al. (2014). Macquarie River Floodplain Flow Modelling: Implications for Ecogeomorphology. In: A. J. Schleiss, G. de Cesare, M. J. Franca, & M. Pfister (Eds.), Proceedings of the International Conference on Fluvial Hydraulics, RIVER FLOW 2014 (pp. 2347-2355). Boca Raton, FL: CRC Press/Balkema. -Grenfell, M. C., Modelling Geomorphic Systems: Fluvial, Geomorphological Techniques, Chap. 5, Sec. 6.4 (2015) -Guan, M, Wright, NG and Sleigh, PA (2015). Multiple Effects of Sediment Transport and Geomorphic Processes Within Flood Events: Modelling and Understanding. International Journal of Sediment Research, 30 (4). pp. 371-381. -Biscarini, C. et al, On the Simulation of Floods in a Narrow Bending Valley: The Malpasset Dam Break Case Study, Water 2016, 8, 545 -Tamminga, A., Linking Geomorphic Change due to Floods to Spatial Hydraulic Habitat Dynamics, Ecohydrology Volume 11 issue 8 December 2018 PART B Counterpart to part A The USGS has software catering to landslide hazards: https://www.usgs.gov/programs/landslide-hazards/software Further pursuits: Dai, F.C & Lee, C.F & Ngai, Y.Y. (2002). Landslide risk assessment and management: An overview. Engineering Geology. 64. 65-87. Pardeshi, S.D., Autade, S.E. & Pardeshi, S.S. (2013). Landslide hazard Assessment: Recent Trends and Techniques. SpringerPlus 2, 523 --Modelling History and Evolution of River Systems Will pursue modelling of very dynamic river systems, such as the Amazon and the Orinoco. Will pursue models with initial conditions for such systems and simulate. An example: Coulthard T. J. and Van De Wiel M. J. Modelling River History and Evolution, 370, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences Note: other models likely will be applied for comparatve analysis Software to compare development with --> GIS (GRASS GIS with addons) iRIC RHESSys HEC-HMS HEC-RAS HEC-FIA MODFOW + MT3DMS WILL try to match and/or compare development cases with satellite data (high volume of frames per duration) --Avalanche Models & Simulation PART A1 Beginning with analytical structure for model avalanches. Hopefully such two articles are not that highly conflicting leading to great confusion and lost of direction. Additionally, will pursue “microscale” experiment setups and try to confirm theory with experimentation based on such articles. Bartelt, P., Salm, B., & Gruber, U. (1999). Calculating Dense-Snow Avalanche Runout Using a Voellmy-Fluid Model with Active/Passive Longitudinal Straining. Journal of Glaciology, 45(150), 242-254. Faug, T., Naaim, M. and Naaim-Bouvet, F. (2004). An Equation for Spreading Length, Centre of Mass and Maximum Run-Out Shortenings of Dense Avalanche Flows by Vertical Obstacles, Cold Regions Science and Technology, Volume 39, Issues 2–3, Pages 141-151 Note: the following may be used as cross reference Savage, S. and Hutter K. (1989). The Motion of a Finite Mass of Granular Material Down a Rough Incline. Journal of Fluid Mechanics, 199: 177-215. Balmforth, N. J. and Provenzale, A. (2001). Geomorphological Fluid Mechanics. Springer Berlin, Heidelberg Ancey C (2001) Snow Avalanches. Geomorphological Fluid Mechanics, Springer, In, pp 319–338 PART A2 Being aspiring geologists, hence, with the “natural” ability to acquire topography and elevation measures for various landscapes, where elements in data are quite "compact” with each other, say, not being highly discrete w.r.t. to each other. Can such models be extended for the elevation z = f(x, y) in question? After findings for above question, pursue analysis of the following article, then pursue replication or emulation Li, X., Sovilla, B., Jiang, C. et al. (2021). Three-Dimensional and Real-Scale Modelling of Flow Regimes in Dense Snow Avalanches. Landslides, 18, pages 3393–3406 PART B Simulation development. Comparative development and simulation based on the given journal articles. Norem, H., Irgens, F., & Schieldrop, B. (1989). Simulation of Snow-Avalanche Flow in Run-Out Zones. Annals of Glaciology, 13, 218-225. Sartoris, G. and Bartelt, P. (2000). Upwinded Finite Difference Schemes for Dense Snow Avalanche Modeling, Int. J. Numerical. Methods. Fluids, 32, pages 799-821. Norem, Harald & Irgens, Fridtjov & Schieldrop, Bonsak. (1989). Simulation of Snow-Avalanche Flow in Run-Out Zones. Annals of Glaciology. 13. 218-225. Zugliani, D. and Rosatti, G. (2021). TRENT2D❄: An Accurate Numerical Approach to the Simulation of Two-Dimensional Dense Snow Avalanches in Global Coordinate Systems, Cold Regions Science and Technology, Volume 190, 103343 Note: the following may be used as cross reference Savage, S. and Hutter K. (1989). The Motion of a Finite Mass of Granular Material Down a Rough Incline. Journal of Fluid Mechanics, 199: 177-215. Balmforth, N. J. and Provenzale, A. (2001). Geomorphological Fluid Mechanics. Springer Berlin, Heidelberg PART C Models for Snow Avalanche Runout. Among the articles it’s important that the the model process (variables choice, estimation, validation, etc.) be probed, despite such articles now being appreciated by consensus; self assurance of models thrown at you. Regardless, goal will be comparatively applying recognised models from each article to different terrains and determine how well they performed based on determined modern data as test/validation sets. Bovis, M. J., & Mears, A. I. (1976). Statistical Prediction of Snow Avalanche Runout from Terrain Variables in Colorado. Arctic and Alpine Research, 8(1), 115–120. Bakkehoi, S., Domaas, U., & Lied, K. (1983). Calculation of Snow Avalanche Runout Distance. Annals of Glaciology, 4, 24-29. Lied, K. & Toppe, R. (1988). Calculation of Maximum Snow-Avalanche Run-Out Distance by use of Digital Terrain Models. Annals of Glaciology. 13. pages 164-169. McClung, D.M. (2000). Extreme Avalanche Runout in Space and Time. Canadian Geotechnical Journal. 37(1): 161-170. McClung, D. M. (2001). Extreme Avalanche Runout: A Comparison of Empirical Models. Can. Geotech. J. 38: 1254–1265 Delparte, D., Jamieson, B. and Waters, N. (2008). Statistical Runout Modelling of Snow Avalanches Using GIS in Glacier National Park, Canada, Cold Regions Science and Technology, 54(3), pages 183 -192 Oller, P., Baeza, C., & Furdada, G. (2021). Empirical α–β Runout Modelling of Snow Avalanches in the Catalan Pyrenees. Journal of Glaciology, 67(266), 1043-1054. Note: the follwing may be pursued later on Sinickas, A. and Jamieson, B. (2014). Comparing Methods for Estimating β points for Use in Statistical Snow Avalanche Runout Models. Cold Regions Science and Technology, Volumes 104–105, Pages 23-32 McClung, D. M. (2022). The Scale Effect in Extreme Snow Avalanche Runout Distance. Canadian Geotechnical Journal. 59(5): 625-630. --Scaled Physical Models for Lab Experimentation 1. Flume construction and channels Consideration of types of flumes for use. Well built to accommodate experimentation with formulas, and prediction for real natural systems. https://www.sciencedirect.com/topics/earth-and-planetary-sciences/flume-experiment Assisting literature and resources Wahl, T. L. Equations for computing submerged flow in Parshall flumes, Bureau of Reclamation, Denver, Colorado, USA: https://www.usbr.gov/tsc/techreferences/mands/wmm/new/chap08/eqsubmergedparshall.pdf Recking, A. (2010). A Comparison Between Flume and Field Bed Load Transport Data and Consequences for Surface-Based Bed Load Transport Prediction, Water Sources Research, 46(2) Wyss, C. R. et al (2016). Laboratory Flume Experiments with the Swiss Plate Geophone Bed Load Monitoring System: 1. Impulse Counts and Particle Size Identification, Water Sources Research, 52(10), pp 7744-7759 Wyss, C. R. et al (2016). Laboratory Flume Experiments with the Swiss Plate Geophone Bed Load Monitoring System: 2. Application to Field Sites with Direct Bed Load Samples, Water Sources Research, 52(10), PP 7760-7778 Heyrani, M., Mohammadian, A., Nistor, I., & Dursun, O. F. (2022). Application of Numerical and Experimental Modeling to Improve the Efficiency of Parshall Flumes: A Review of the State-of-the-Art. Hydrology, 9(2), 26. Ishihara, M. and Yasuda, H. (2022). On the Migrating Speed of Free Alternate Bars. JGR Earth Science, 127(10), e2021JF006485 2. Lillquist and Kinner - Stream Tables and Watershed Geomorphology Education 3. Analogue modelling Used to simulate different geodynamic processes and geological phenomena, such as small-scale problems – folding, fracturing, thrust faulting, boudinage and shear zone. Large-scale problems – subduction, collision, diapirism and mantle convection. One must identify the rock dynamics, sub-crust dynamics or type of (compressional, extensional, strike-slip) tectonics in play for the respective phenomena. Note: each geodynamical process orchestrated in the field/lab will be accompanied by identification of the chemistry, physics and mathematical modelling that governs them. Crucial concerns: Scaling Open and closed systems Constructing experimental apparatuses Materials for respective apparatus to exhibit particular phenomenon Pursue development of articles in the most constructive sequence: -Ranalli, Giorgio (2001). "Experimental tectonics: from Sir James Hall to the present". Journal of Geodynamics. 32 (1–2): 65–76. -Mead, Warren J. (1920). "Notes on the Mechanics of Geologic Structures". The Journal of Geology. 28 (6): 505–523. -Schellart, W. P. and Strak, V. (2016). A review of analogue modelling of geodynamic processes: Approaches, scaling, materials and quantification, with an application to subduction experiments". Journal of Geodynamics. 100: 7–32 -Konstantinovskaia, Elena; Malavieille, Jacques (2005-02-26). "Erosion and exhumation in accretionary orogens: Experimental and geological approaches". Geochemistry, Geophysics, Geosystems. 6 (2): Q02006 -Kincaid, Chris; Olson, Peter (1987-12-10). "An experimental study of subduction and slab migration". Journal of Geophysical Research: Solid Earth. 92 (B13): 13832–13840. -Koyi, H. (2007). Analogue modelling: From a qualitative to a quantitative technique — A historical outline". Journal of Petroleum Geology. 20 (2): 223–238. Analogue modelling involves the simplification of geodynamic processes, of consequence there are some disadvantages and limitations (discussed in given articles): A. Concerning natural rock properties, the more accurate the input data, the more accurate the analogue modelling. B. Likelihood of heterogeneous systems involving isostatic compensation, erosion, other unknown factors, etc. Such can make simulations difficult to replicate systems. C. The variation of natural rocks is greater than in simulated materials, hence it’s difficult to fully model the real situation. D. Analogue modelling cannot simulate chemical reactions E. There are systematic errors in the apparatus, and random errors due to human factors. Analogue modelling have neat displays, however, it’s crucial that the phenomena of concern can be represented by geophysical modelling in a tangible and practical manner, else geological dynamics study would be extremely limited. 4. The following articles will be applied towards quantitative comparison between conventional natural geodynamics and ideal microscale lab experiment representations Articles to be used on comparative terms with natural geodynamical processes. Such articles concern fitting models described with acceptable parameters for the scale of the experiments. Note: it may be highly constructive to have an idea on the applied forces and applied displacements pertaining to experiments of relevance. Likely, due to the materials used in experiments there will inconsistencies to considered real geodynamic behaviour; computational/quantitative determination of the lack of character to real geodynamic behaviour for chosen particular physical characteristic measures--> Green, D. L., Modelling Geomorphic Systems: Scaled Physical Models, Geomorphological Techniques, Chap. 5, Sec. 3 (2014) Li, Z., & Ribe, N. (2012). Dynamics of free Subduction from 3‐D boundary Element modelling. Journal of Geophysical Research: Solid Earth, 117(B6), N/a. Yoshida, M. (2017). Trench dynamics: Effects of dynamically migrating trench on subducting slab morphology and characteristics of subduction zones systems. Physics of the Earth and Planetary Interiors, 268, 35-53. Göğüş, O., Pysklywec, R., Corbi, F., & Faccenna, C. (2011). The surface tectonics of mantle lithosphere delamination following ocean lithosphere subduction: Insights from physical‐scaled analogue experiments. Geochemistry, Geophysics, Geosystems, 12(5), N/a. --Earth’s Interior & Consequences of Earth’s Radioactive Power Part A Probing Earth’s interior with neutrinos << Fiorentini, G., Lissia, M. and Mantovani, F., Geo-neutrinos and Earth’s Interior, Physics Reports 453 (2007) 117 – 172 >> Part B 1. The following are decent guides towards discussion and development for the study of Earth’s radioactive power: Korenaga, J. (2008). Urey Ratio and the Structure ad Evolution of Earth’s Mantle, Reviews of Geophysics, 46, RG2007, 32 pages Dye, S. T. (2012). Geoneutrinos and the Radioactive Power of the Earth, Reviews of Geophysics, 50, RG3007, 19 pages Sramek, O., McDonough, W. F. and Learned, J. G., Geoneutrinos, Advances in High Energy Physics, Volume 2012, Article ID 235686, 34 pages Sramek, O. et al, (2013). Geophysical & Geochemical Constraints on Geoneutrino Fluxes from Earth’s Mantle, Earth & Planetary Science Letters, Vol 361, pages 356 – 366 Ludhova, L. and Zavatarelli, S., Studying the Earth with Geoneutrinos, Advances in High Energy Physics, Volume 2013, Article ID 425693, 16 pages Huang, Y. et al A Reference Earth Model for the Heat Producing Elements and Associated Geoneutrino Flux. Geochemistry, Geophysics, Geosystems. Volume 14, Issue 6, Jun 2013, pages 2003 - 2029 2. Will pursue means of acquiring data from KamLAND, SNO and other possible sources. Will review how each experimentation site works, the logistics with making use of data, interpretation of data or application of data to models of: Earth’s radioactive power Thermal history Mantle evolution Note: operations with data will be interactive. 3. Radioactive emissions from lava (apart from infrared)? 4. Why are life forms not exposed to hazardous (amounts of) geo-radioactive emissions? National Research Council (US) Committee on Evaluation of EPA Guidelines for Exposure to Naturally Occurring Radioactive Materials. Chapter 2, Natural Radioactivity and Radiation. In: Evaluation of Guidelines for Exposures to Technologically Enhanced Naturally Occurring Radioactive Materials. National Academies Press (US), Washington DC, 1999, Pages 25 - 61 5. Consider construction of “Geiger counters” where students investigate the possibility of residing radioactive rocks and other geophysical bodies. Signalling should be processed and stored as possibly time series data. One must be careful to mark or identify the sector of observation to avoid confusion and overlaps; spots must be assured and marked, also date logging (and possibly GIS inputs) should be considered. Time series for respective sector and duration with date must be recognisable always. 6. Identify places on the planet with high access to natural radioactive elements in abundance. For such places one can investigate the origins of such elements, geophysical structure of environment, geochemistry of such locations and continental geological history. 7. Origins of radioactive sources inside Earth. Are any conditions, models or theories ranging from early solar planetary formation to current time sufficient to create radioactive isotopes? Identify conditions, natural environments, activities, phenomena, models for sufficient conditions towards nucleosynthesis of radioactive isotopes. Generally where is all such found? 8. Pursue data for unique radioactive signatures from astronomical observation. How refined are such unique radioactive signatures compared to other celestial bodies? In current times ease in observing such unique radioactive signatures w.r.t position may not be convincing. However, for earlier times of the universe are there models that strongly support dispersed sources of unique radioactive signatures and the appropriate nucleosynthesis parameters for radioactive isotopes? 9. Neutrino tomography can probe the Earth’s interior. As well, recall that the Earth’s interior can also be probed by use of seismic waves. One will like to determine how well seismic analysis of Earth’s interior is consistent with neutrino tomography. One will like to analyse the respective models, parameters, data, etc., etc. to establish any consistency. --Immersion with the International Monitoring System (IMS) and Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO) 1. History of IMS 2. Analysis of the components of IMS 3. History of CTBT 4. Idea of its CTBTO applications Mialle, P. et al (2018). CTBTO International Monitoring System Data for Science and the virtual Data Exploitation Centre (vDEC). American Geophysical Union, Fall Meeting 2018 5. To concern ourselves with the means of event recognition from data Nuclear explosive tests Volcanic eruptions, earthquakes Meteorological events Tools and techniques will be much detailed and implemented Data will stem from the following source: virtual Data Exploitation Centre (vDEC) https://www.ctbto.org/specials/vdec/ Naturally, identifying past events and identifying data in the time neighbourhood of occurrence for each event. --Bayesian Decision Theory for Disaster Management Hopefully can be geared towards geology interests Structure of Bayesian Modelling and Evaluation The following articles serve as robust structure. Will be making use of ambiance data of interest and will pursue means of determining accuracy: Simpson, M. et al. Decision Analysis for Management of Natural Hazards. Annual Review of Environment and Resources 2016 41:1, 489-516 Guides to develop models and evaluation for places of interest: Economou, T., Stephenson, D., Rougier, J., Neal, R., & Mylne, K. (2016). On the Use of Bayesian Decision Theory for Issuing Natural Hazard Warnings. Proceedings. Mathematical, Physical, and Engineering Sciences, 472(2194), 20160295. Economou, T.; Stephenson, D. B.; Rougier, J. C.; Neal, R. A.; Mylne, K. R. (2016): Data and Loss Function Tool On the Use of Bayesian Decision Theory for Issuing Natural Hazard Warnings. The Royal Society. S Taskin & E J Lodree, Jr (2011) A Bayesian Decision Model with Hurricane Forecast Updates for Emergency Supplies Inventory Management, Journal of the Operational Research Society, 62:6, 1098-1108 --Detecting, Extracting, and Monitoring Surface Water from Space using Optical Sensors The given journal article can serve well towards development of water detection from satellite data and technology tools. Such may be extendible to celestial bodies. Students can test out their development on the Serengeti Plain as an example to compare the different seasons; other geography should be considered as well that doesn’t rely on such a vast time scale. Huang, C. et al (2018). Detecting, Extracting, and Monitoring Surface Water from Space using Optical Sensors: A Review. Reviews of Geophysics, 56(2), 333–360. --Guide to the Expression of Uncertainty in Measurement (GUM) and transcendence Thoroughly identify and analyse GUM. Our goal is to develop a logistical framework that’s universal with any experimentation in science. developing competence to important is quite important. Re-orchestrating some basic physics and chemistry labs students may encounter uncertainty treatment. Will like to extend to such particular labs with the analysis from part A. PART A Analysis from the following guides --> 1. Evaluation of measurement data — Guide to the expression of uncertainty in measurement — JCGM 100:2008 https://www.bipm.org/utils/common/documents/jcgm/JCGM_100_2008_E.pdf 2. Evaluation of measurement Data – Supplement to the “Guide to the Expression of Uncertainty in Measurement” – Propagation of Distributions using a Monte Carlo Method. JCGM.101: 2008 3. Barry N. Taylor and Chris E. Kuyatt (1994). guidelines for Evaluating and Expressing the Uncertainty of NIST Measurement Results. NIST Technical Note 1297. 4. https://isotc.iso.org/livelink/livelink/Open/8389141 5. Ferrero, A., & Salicone, S. (2018). A Comparison Between the Probabilistic and Possibilistic Approaches: The Importance of a Correct Metrological Information. IEEE Transactions on Instrumentation and Measurement, 67(3), 607-620. Other applications Krouwer, J. (2003). Critique of the Guide to the expression of Uncertainty in Measurement Method of Estimating and Reporting Uncertainty in Diagnostic Assays. Clinical Chemistry, 49(11), 1818-21. Velychko, O., & Gordiyenko, T. (2009). The use of Guide to the Expression of Uncertainty in Measurement for Uncertainty Management in National Greenhouse Gas Inventories. International Journal of Greenhouse Gas Control, 3(4), 514-517. --Geography Technology Development Concerning geology one can’t be every for whatever time period considered. Technology and credible community development are key for studies in geophysics. Hence, our concerns in this activity are the following data: maps, charts and geospatial data from global sources in all categories: topographic, 3D, DEM, GIS, vector, nautical, aeronautical, geological, scientific, and imagery (to include LIDAR). There are three possible means towards goals: PART A 1. Open Source GIS --> SAGA GIS, ILWIS, MapWindow GIS, uDig, GRASS GIS, QGIS, Whitebox GAT, JUMP GIS, BeeGIS + GeoPaparazzi. GRASS GIS with addons may or may not be preference. PART B Fieldwork can be integrated well with BeeGIS + GeoPaparazzi De Donatis, M. et al (2010). BeeGIS: A New Open-Source and Multiplatform Mobile GIS. U.S. Geological Survey Open-File Report 2010–1335 NOTE: this GIS generally makes no default choice upon part A, comprehending that the other GIS mentioned in part A have unique and powerful features. -- Geospatial Processing Service --> Google Earth Engine (GEE) This service likely will not be learning to tie different knots. Requires much focus and dedication. Students who are competent with coding may find GEE less challenging. Crucial steps are: I. Comprehending what GEE is and what it can do for you II. Immersion strictly based on a practical, tangible and fluid beginner tasks to complete. With such a complex tool, asking you to explore carefree may or may not be productive. Tasks that are crucial: Set goals/objectives and end result expectations Analytical schemes/drafting and how GEE works with such Understanding data: where from and how to integrate Analytical idea of algorithms in play subject to prior Prior two elements may be applied multiple times in one objective Sequential interests Embedding or integrations Successful completion of a particular goal/objective doesn’t guarantee future success because the development spectrum in very broad with various intricacies for a respective pursuit. There are beginner video tutorials, however, you will not accomplish much without further drive, imagination and innovation. Overall, GEE can be a high reward investment if you can maintain value to audiences of interest. Also, the USGS can be augmented with data towards GEE. Additionally, there’s the rgee R package. --Environmental Restoration Economic Modelling and Evaluation For environmental perturbations of interest (mainly geological) to develop economical modelling and evaluation. Concerns for developing and/or mining. Note: will be making use use of professional literature (ISO, UN, gov’t published, peer reviewed journal articles). PHASE 1(Life Cycle Assessment) Environmental burdens connected with a product or service have to be assessed, back to the raw materials and down to waste removal. LCA will be identified and analysed Development or mining site(s) in question to be analysed Depletion and/or wastes and/or contamination Developing LCA model(s) for site(s) in question Logistics for LCA implementation for respective site Implementation of the LCA Results and analysis Software: OpenLCA, ACV-GOST, OpenIO, One Click LCA, etc. PHASE 2 (Restoration Alternatives) The choice of restoration alternatives and the methodology for implementing them depend on the specific environmental issues, site characteristics, and desired outcomes. Note: methods such as Economic Valuation of Ecosystem Services, Net Environmental Benefit Analysis (NEBA), Hedonic Pricing, Habitat Equivalency Analysis (HEA) and Resource Equivalency Analysis (REA) should be properly incorporated. Here is a general methodology for evaluating and implementing environmental restoration alternatives -- Site Assessment: Conduct a thorough site assessment to understand the nature and extent of environmental degradation. Identify the contaminants, pollutants, or ecological imbalances present. Evaluate the historical land use and potential sources of pollution. Ecological Risk Assessment: Assess the risks to ecosystems and human health associated with the environmental degradation. Evaluate the potential for ecological harm and prioritize restoration efforts based on risk levels. Stakeholder Involvement: Engage stakeholders, including local communities, regulatory agencies, and environmental organizations. Consider their perspectives, concerns, and input throughout the restoration process. Define Restoration Goals and Objectives: Clearly define the goals and objectives of the restoration project. Identify specific ecological, social, and economic outcomes that the restoration aims to achieve. Restoration Alternatives Analysis: Identify and evaluate various restoration alternatives based on their feasibility, effectiveness, and cost. Consider both natural and engineered solutions, such as bioremediation, phytoremediation, habitat restoration, or engineered containment. Cost-Benefit Analysis: Conduct a cost-benefit analysis for each restoration alternative. Evaluate the economic feasibility of different approaches, considering short-term and long-term costs and benefits. Technical Feasibility: Assess the technical feasibility of each restoration alternative, considering factors such as available technology, infrastructure, and expertise. Environmental Impact Assessment: Evaluate the potential environmental impacts of each restoration alternative. Consider the short-term and long-term effects on soil, water, air quality, and biodiversity. Regulatory Compliance: Ensure that the chosen restoration alternative complies with relevant environmental regulations and permits. Consult with regulatory agencies and obtain necessary approvals. Implementation Plan: Develop a detailed implementation plan for the chosen restoration alternative. Define the step-by-step process, timeline, and milestones for implementation. Monitoring and Adaptive Management: Implement a monitoring program to track the progress of the restoration. Incorporate adaptive management strategies to adjust the restoration approach based on monitoring results. Community Education and Outreach (only discuss general ideas): Educate the local community about the restoration project. Provide updates on progress and involve the community in stewardship efforts. Long-Term Maintenance and Management: Plan for the long-term maintenance and management of the restored environment. Consider strategies to ensure the sustainability of the restored ecosystem. Documentation and Reporting: Document all aspects of the restoration process, including methodologies, data, and outcomes. Prepare regular reports for stakeholders and regulatory agencies. Post-Restoration Monitoring and Evaluation (may not be implementable in this project): Conduct post-restoration monitoring to assess the success of the restoration efforts. Evaluate whether the goals and objectives have been achieved and identify any lessons learned for future projects.

An invaluable textbook for geosciences with Mathematica: “Computational Geosciences with Mathematica”, by Willian C. Haneberg. The provided CD may be outdated but the book itself with Mathematica is a good resource. Sources and software for Geology Data: UN Geo Data Portal The provided ESA and NASA sources may prove beneficial as well. Such software and data sources can be used for lecturing, lab seminars coordinated and/or scheduled appropriately, without compromising the designating core courses, time and scheduling of the designated core courses. JBA Trust: https://www.jbatrust.org OTHER POWERFUL COMPUTATIONAL GEOLOGY SOFTWARE 1. Computational Infrastructure for Geodynamics (CIG): https://geodynamics.org/cig/software/ 2. EPA (SWMM, VLEACH) 3. MINTEQA2 4. PHREEQC 5. Generic Mapping Tools (GMT) 6. GPlates 7. Energy Data Exchange (EDX) from the National Energy Technology Laboratory: https://edx.netl.doe.gov/tools Other software to be found in first part notes of structure. Note: Towards the planetary sciences, the Wolfram environment greatly provides computation, programming, simulation, data management (import, manipulation and visualization). Data mentioned throughout can be incorporated as well. Examples of the Wolfram platforms: Environmental Sciences Geosciences 8. Forest landscape processes (Landis-II) 9. General CMIP5 models and competing alternatives 10. USGS Water Resources Software: https://water.usgs.gov/software/lists 11. USGS Design Ground Motions: https://earthquake.usgs.gov/hazards/designmaps/

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PHYSICS

GENERAL PHYSICS I & II to be accompanied by lab instruction. Courses of General Physics I & II and Vibrations & Waves can have lab experiments for mechanical, electromagnetic and electromechanical systems involving simulation, coding and microcontrollers. Such includes becoming introduced early to elementary debugging and calibrating schemes. Modelling through sensing (with curve fitting) compared to theoretic modelling, analytical solutions. Simulations for of real systems concern central scheme finite difference, Runge Kutta, etc., etc., etc. In this “modern era” the ability to competently execute simulation and coding with primitive real systems will be crucial to a student’s future with innovation, relevance, commerce and self-reliance. Such activities builds personal independence and ability with the potential for various projects that’s quite cost effective. Students in such foundational physics courses should be exposed to microcontroller usage at such an early stage, to remain relevant in the future and to build professional relevance with necessary technology. An additional economic incentive is that with such skills developed one opens themselves to engineering paths and “real world ability”; physics ultimately can’t be separated from engineering and programming in the long run. Coding is very important, namely, repetitive copying is not enough; one must really understand what they’re doing in order to really advance in anything. Code lines will be analysed concerning respective purpose. There will be quizzes and the final will involve coding. Questions concern interpretation, filling in lines & patches, truth or false, set up procedures, sensibility of codes with logistics and procedure. The following are just a few experimentation examples of the modernized versions of labs done in course labs. For the other conventional labs one must develop the modernized experiment counterparts. --Comparative schemes for free fall Estimate your local gravitational acceleration with Arduino: https://www.subsystems.us/arduino-project---gravity.html Interfacing DIY Arduino Photogate Timer: http://community.wolfram.com/groups/-/m/t/1047262 Medida de g com a placa Arduino em um experimento simples de queda-livre: https://arxiv.org/pdf/1511.08231.pdf Moya, A. A., An Arduino Experiment to Study Free Fall at Schools, Phys. Educ. 53 (2018) 055020 (4pp) --Mass-Spring system Tong-on, A., Saphet, P. and Thepnurat, M. et al, Simple Harmonics Motion Experiment Based on LabVIEW Interface for Arduino, Journal of Physics: Conf. Series 901 (2017) 012114 Will try modules for different masses and springs to observe any possible deviation from the ideal model; different combinations among those three parameters. Varying amplitude, frequency, period and means to model possible air resistance. Pursuit of determining spring constants. --Pendulum Wong, W. et al, Pendulum Experiments with Three modern Electronic Devices and a Modelling tool, J. Comput. Educ. (2015) 2(1):77–92 https://app.ph.qmul.ac.uk/wiki/_media/ajm:teaching:arduino-pi:projects:arduino:simple_pendulum.pdf https://create.arduino.cc/projecthub/coderscafe/automated-simple-pendulum-7c5bc3 (disregard laser cutter) In some coding design one retrieves information such as the pendulum’s period from voltage applied in respective module. Will try modules for different acute angles (up to 60 degrees), lengths and masses to observe any deviation from the ideal model; different combinations among those three parameters. Varying amplitude, frequency, period and means to model possible air resistance. --Espindola, P. R. et al, Impulse Measurement Using an Arduíno, Phys. Educ. 53 (2018) 035005 (4pp) --An experiment in Moment of Inertia with Raspberry Pi/Arduino https://community.wolfram.com/groups/-/m/t/181641 In this experiment one must determine the right model for objects down an incline plane. Objects of concern are spherical in nature, but some are solid spheres while others are spherical shells. For such objects there two types of kinetic energy, being translational and rotational, where both play important roles in dynamics and trajectories. Proof: consider the conservation problems where a ball starts at some altitude on some incline plane. The results you would get in the experiment exceeds the case of only considering translational kinetic energy. --Goncalves, A. M. B., Cena, C. R. and Bozano, D. F., Driven Damped Harmonic Oscillator Resonance with an Arduino, Phys. Educ. 52 (2017) 043002 (4pp) --Prima, E. C. et al, Heat Transfer Lab Kit using Temperature Sensor based Arduino for Educational Purpose, Engineering Physics International Conference, EPIC 2016, Procedia Engineering 170 (2017) 536 – 540 --Galeriu, C., An Arduino Investigation of Newton's Law of Cooling, Physics Teacher, v56 n9 p618-620 Dec 2018 --Freitas, W. P. S., Arduino-based Experiment Demonstrating Malus’s Law, Phys. Educ. 53 (2018) 035034 (4pp) --Organtini, G. et al, Arduino as a Tool for Physics Experiments, Journal of Physics: Conf. Series 1076 (2018) 012026 Here, one can extend to more advance circuits (up to RLC) --Sanjaya, W. S. et al, Numerical Method and Laboratory Experiment of RC Circuit using Raspberry Pi Microprocessor and Python Interface, Journal of Physics: Conf. Series 1090 (2018) 012015 Here, one can extend to more advance circuits (up to RLC). As well, one isn’t to be subjugated to populism with Python. --Bezerra et al, Using an Arduino to demonstrate Faraday’s Law, Phys. Educ. 54 (2019) 043011 (6pp) --Huang, B., Open-source Hardware – Microcontrollers and Physics Education - Integrating DIY Sensors and Data Acquisition with Arduino, 122nd ASEE Annual Conference & Exposition June 14 -17, 2015 Seattle, Washington --Arduino in the Physics Lab https://ec.europa.eu/programmes/proxy/alfresco-webscripts/api/node/content/workspace/SpacesStore/59719c38-c26e-4a8d-b853-ce56e04be930/MoM_PRESENT_Monday_Arduino%20in%20the%20Physics%20Lab_C_A.pdf Here, one can extend to more advance circuits (up to RLC) --For labs involving conservation of energy (translation and rotational influence) one can apply toy ramps and rolling rings, discs, hollow balls and solid balls. One can observe whether neglecting rotational kinetic energy can be catastrophic concerning destination of rolling. Conservation of momentum can be incorporated into labs as well. --Conservation of angular momentum Part A Conservation of Angular Momentum Example – YouTube https://www.youtube.com/watch?v=DtxxmTdQ2Jc In such an experiment would like to extend experiment to fit two torque sensors and two angular momentum sensors without considerably distorting the mass distribution of the rotating bodies. One would like to acquire time continuous data for both measures. Angular momentum to be expressed in terms of angular velocity. All masses applied should be known. Motor operation measures should be known for time T when initiating experiment and what not. How can one verify conservation of angular momentum? How are the torques related to conservation of angular momentum? Co-rotation and counter rotation ability would be nice. Trials in lab may be warranted. Part B One would like to then construct an apparatus where a portion of its mass can contract or extend during the apparatus’ rotation. A torque sensor and a angular momentum sensor without considerably distorting the mass distribution of the rotating bodies. One would like to acquire time continuous data for both measures. Angular momentum to be expressed in terms of angular velocity. All masses applied should be known. Motor operation measures should be known for time T when initiating experiment and what not. How can one verify conservation of angular momentum? How is torques related to conservation of angular momentum? Co-rotation and counter rotation ability would be nice. Trials in lab may be warranted. Physics technology for the biological sciences, social sciences, business, computational finance and actuarial studies: PHYPHOX https://phyphox.org and https://www.youtube.com/watch?v=sGAZQNUBYCc Such can be directed to students in career pursuits outside of engineering and the physical sciences. Technology resources for the physical sciences and engineering shouldn’t be exhausted or marginalized by those in other fields. Curriculum: --Core Courses Scientific Writing I & II, General Chemistry I & II, General Physics I & II, Vibrations & Waves, Fluid Mechanics, Advanced Mechanics I, Electromagnetic Theory I, Modern Physics, Methods of Mathematical Physics, Quantum Physics I & II --Mandatory Courses Found in Computer Science post Data Programming with Mathematica Found in Computational Finance post Calculus for Science & Engineering I-III Ordinary Differential Equations Numerical Analysis Partial Differential Equations Probability & Statistics Mathematical Statistics NOTE: after Calculus III and General Physics II things become hectic, so plan well. Specialization tracks to pursue (being mandatory options tracks): 1. Advanced Mechanics II; Electromagnetic Theory II; Introduction to Astronomy; Stochastic Models & Computation (COMP FIN); Machine Learning for Physics & Astronomy 2. Chemical Physics I & II (check CHEM); Introduction to Astronomy; Stochastic Models & Computation (COMP FIN); Machine Learning for Physics & Astronomy 3. Intro to Astronomy; Techniques in Observational Astronomy I & II; Space Science I & II; Machine Learning for Physics & Astronomy 4. Intro to Astronomy; Techniques in Observational Astronomy I & II; Space Science I & II; Particle Physics I 5. Introduction to Astronomy; Space Science I & II; Tensor Analysis & Riemannian Geometry; Computational General Relativity 6. Intro to Astronomy; Techniques in Observational Astronomy I & II; Tensor Analysis & Riemannian Geometry; Computational General Relativity 7. Introduction to Astronomy; Techniques in Observational Astronomy I & II; Particle Physics I & II 8. Introduction to Astronomy; Space Science I & II; Particle Physics I & II 9. Introduction to Astronomy; Introduction to Optics; Advanced Optics Lab; Particle Physics I & II 10. Chemical Physics I & II (check CHEM); Stochastic Models & Computation (COMP FIN); Statistical Physics I & II 11. Intro to Astronomy; Techniques in Observational Astronomy I; Stochastic Models & Computation (COMP FIN); Statistical Physics I & II Physics electives options --> Introduction to Optics Advanced Optics Lab Introduction to Astronomy Techniques in Observational Astronomy I & II Machine Learning for Physics & Astronomy Space Science I & II Tensor Analysis & Riemannian Geometry Computational General Relativity Statistical Physics I & II Particle Physics I & II NOTE: students can make a mandatory specialization track with departmental guidance with courses outside of physics -- Chemistry electives options --> Organic Chemistry I Analytical Chemistry Inorganic Chemistry I & II Chemical Physics I & II Molecular Modelling Special permission from both Chemistry department chair and course instructor towards proper and official enrolment

Mathematics electives options --> Stochastic Models & Computation R Analysis (requires special permission from instructor and chairperson) Data Science Sequence (requires special permission from instructor and chairperson) Oceanography/Meteorology electives options --> Physical Oceanography Physical Oceanography Techniques Fundamentals of Atmosphere & Ocean Dynamics for Oceanography Coastal & Oceanographic Numerical Simulation Techniques Data Analysis in Atmospheric and Oceanic Sciences. NOTE: for course electives outside of physics there are others posts with their detailed descriptions. NOTE: General Physics I & II are to be considered elementary requirements in the physical sciences and geophysics. If you want to be a perfectionist in General Physics I & II, practice those problems OVER AND OVER INDEPENDENTLY...AND PERSONALLY BUY THE SUPPLEMENTAL MANUAL; problems are never going to change in nature. Anything else, being a bunch of impractical junk collector’s contraptions to whosoever’s interest. Else, there’s Systems Modelling I & II you can take out of engineering as electives, but will have no influence on the Physics programme. Description of some courses--> General Physics I (with labs): This is the beginner level course as an introduction to physics. Students must have Calculus I as prerequisite. Calculus will be used in course to exhibit its foundational role in physics. Texts: Fundamentals of Physics, by Halliday, Resnick and Walker Physics for Scientists & Engineers, by Serway and Jewett Tools: Engineering calculator Stationery Graphing paper Standard measuring stationery Grading Homework: 10% 6 Quizzes (best 5 out of 6): 15% 3 Midterm Examinations (best 2 out of 3): 30% Final Examination: 25% Labs 20% Quizzes --> Don’t be careless with performance on quizzes, say, the accumulation is often taken for granted. Homework --> Homework will come from texts AND others sources Quizzes --> Quizzes will be based on lectures and homework Labs Students are expected to print out their lab documents to be prepared for lab. Labs will also have quizzes. Labs will be what was described in the beginning. Exams --> Exams will be based on homework and quizzes Lecture Topics --> Vectors Rectilinear motion Motion in 2 or 3 dimensions Projectile Motion Newton’s Laws of motion Applying Newton’s Laws Free-body diagrams & applications Work & Kinetic Energy Circular Motion & Centripetal Force Potential Energy & Energy Conservation Momentum Impulse and Collisions Rotation of rigid bodies Dynamics of Rotational Motion Periodic Motion Mechanical waves Sound and Hearing Fluid Mechanics Gravitation (well treated) Prerequisite: Calculus I General Physics II (with labs): The objectives of this course are: (1) To develop a basic understanding of the laws of electromagnetism. (2) To develop the ability to apply these new concepts to physical situations. (3) To develop an appreciation for the role that electromagnetism plays both in our modern society and in the universe. Texts: Fundamentals of Physics, by Halliday, Resnick and Walker Physics for Scientists & Engineers, by Serway and Jewett Tools: Engineering calculator Stationery Graphing paper Standard measuring stationery Grading Homework: 10% 6 Quizzes (best 5 out of 6): 15% 3 Midterm Examinations (best 2 out of 3): 30% Final Examination: 25% Labs 20% Quizzes --> Don’t be careless with performance on quizzes, say, the accumulation is often taken for granted. Homework --> Homework will come from texts AND others sources Quizzes --> Quizzes will be based on lectures and homework Labs Students are expected to print out their lab documents to be prepared for lab. Labs will also have quizzes. Labs will be what was described in the beginning. Exams --> Exams will be based on homework and quizzes Lecture Topics --> Electric Charges & Electric Forces The Electric Field Gauss’ Law Electric Potential Potential & Field Current & Resistance Fundamentals of Circuits The Magnetic Field Electromagnetic Induction Electromagnetic Fields & Waves AC Circuits Interference & Light Prerequisites: General Physics I, Calculus II Vibrations & Waves: Grading: 25%: Assignments (set weekly) 25%: Mid-term 25%: Labs 25%: Final exam Typical Texts: Georgi, Howard. (1992). The Physics of Waves. Benjamin Cummings Vibrations and Waves, by A. P. French LABORATORY COMPONENT --> Laboratory skills are highly practical and give you an appreciation for difficulty of working both precisely and accurately. This requires discipline and patience, that can take time to develop. 1. Physics of sound -How is all such manipulated to achieve acoustic goals? Physics of blunt mechanics (striking, plucking, blowing, etc., etc.) to generate sound. Physics at the microscopic level for sound generation. -Modelling the transfer of sound waves -Speed of sound Modelling the speed of sound w.r.t. media. Modelling for variability with pressure, density, elasticity, temperature Measuring the speed of sound with a single-board microcontroller and ultrasonic sensor; confirm experiment results with prior modelling. May try to experimentally verify as well for variability with pressure, density, elasticity, temperature 2. To avoid massive expense for laboratory with particular contraptions and “classical equipment” some of the lab activities will highly resemble microcontroller applied experiments described at the beginning of this post. Mechanical systems (various) Review physics and modelling Electric Circuits (various) Review physics and modelling 3. Fluid Damped Harmonics -First, will review modelling and consequences -https://www.thepocketlab.com/educators/lesson/damped-simple-harmonic-motion 4. Chladni Plates -Physics and modelling must be developed. -Understanding the role of nodes and anti-nodes. -Can Chladni Plates be simulated? -Will also be building multiple Chladni Plates to observe and record behavior. With respect to the properties and geometry of the membrane will try to analytically develop a model to map the nodes and anti-nodels. Can such be simulated? -How to map nodes and anti-nodes on instruments? -We want data. Data for frequencies and (Eigen)modes will be of interest towards models. 5. Will also pursue vibrations where particles come together to form microspheres “fluids”. What conditions are the cause for such “fluid” behaviour? 6. Acoustic levitators -Physics and mathematical modelling must be developed -Understanding the role of nodes and anti-nodes. Gor’kov potential, accoustic radiation force, and elastic constant as a second order derivative. Modelling the complex acoustic pressure. Assisting Literature: Jackson, D. P. and Chang, M. (2021). Acoustic Levitation and Acoustic Radiation Force. American Journal of Physics, volume 89, Issue 4, 383 Andrade, M. A. B., Pérez, N. & Adamowski, J. C. (2018). Review of Progress in Acoustic Levitation. Braz J Phys 48, 190–213 Andrade, M. A. B., Marzo, A. & Adamowski, J. C. (2020). Acoustic Levitation in Mid-Air: Recent Advances, Challenges , and Future Perspectives. Applied Physics Letters, Volume 116 Issue 25 -Developing the model, pressure field code and simulation -An example of what must be pursued: Acoustic Levitator DIY – TinyLev-Levitate Liquids & Insects at home – YouTube Basic components: Ultrasonic transducers Aluminium reflector Driver board Arduino board (or whatever substitute) Oscilloscope Infrared imaging applicable Data from experimentation will be gathered to reconcile with the physics and mathematical modelling. 7. Vibration analysis of an electric motor Wang, C.& Lai, J. (1999). Vibration Analysis of an Electric Motor. Journal of Sound and Vibration. 224. 733-756. Will pursue lab investigation based on such article, etc., etc. 8. Fault detection -Fault detection of electric motors based on vibration analysis -Yamamoto, G. K., da Costa, C. and da Silva Sousa, J. S. (2016). A Smart Experimental Setup for Vibration Measurement and Imbalance Fault Detection in Rotating Machinery, Case Studies in Mechanical Systems and Signal Processing, Volume 4, Pages 8-18 9. Sound from electrical instruments (time permitting) -Modulators, electric keyboards and synthesizers Modelling the process May pursue development of scaled down versions, namely, based on single board computers to demonstrate COURSE OUTLINE --> 1. Introductory concepts Periodic motion, superposition of periodic motion. Free vibrations of physical systems. 2. Damped Systems Under/over and critically damped systems. “Q” parameter. 3. Forced Vibrations and Resonance Variation in amplitude with driving frequency. Resonances in damped and undamped systems. 4. Coupled Oscillators Coupled pair of oscillators. Modes of oscillation. Application to N coupled oscillators. 5. Continuous Systems Vibrations on a string. Driven continuous systems. Note: all continuous systems considered will be finite in length 6. Waves and Optics Energy in a wave, boundaries and interference. Huygens-Fresnel principle. Double-slit experiment 7. Nonlinear Vibrations Wagg D. & Neild S. (2010). Nonlinear Vibration with Control. Solid Mechanics and Its Applications, vol 170. Springer, Dordrecht Juan Carlos Jauregui, J. C. (2014). Parameter Identification and Monitoring of Mechanical Systems Under Nonlinear Vibration, Woodhead Publishing Prerequisites: Calculus III, General Physics I & II, ODE Advance Mechanics I This course covers Lagrangian and Hamiltonian mechanics, systems with constraints, rigid body dynamics, vibrations, central forces, Hamilton-Jacobi theory, action-angle variables, etc. Course will make use of 14 – 15 weeks. Textbook: TBA Two functions in Mathematica that may be useful (but only for reference) EulerEquations VariationalD Basic Expectations --> Modelling with Newton’s Second Law Identify generalized coordinates and system representation Ignorable coordinates & system representation Lagranigan (Hamiltonian) determination of various systems Finding Ignorable coordinates to recognise conserved quantities Resulting explicit set of equations from Euler-Lagrange equations Solutions of found explicit equations prior Comparing E-L solutions to solutions of Newton’s 2nd second law Systems must be treated by both E-L and Newton’s second law Hamiltonian determination of various systems Hamiltonian Systems Comparing Hamilton treatment to solutions of Newton’s 2nd second law Systems must be comparatively treated by both E-L and Newton’s second law NOTICE FOR BASIC EXPECTATIONS: -Some mentioned subjects prior will arise on multiple occasions, or will simply resonate throughout. -I will be a stickler with past intelligence and skills as one advances in course. Hence, for more advance obligations as one progresses will treat prior expectations as primitives to be included, to be well developed and detailed. Homework --> Constituted by typical problem sets Quizzes --> Will reflect homework. There will be 3-5 quizzes. Exams --> There will be 3 exams that will reflect lectures, homework and quizzes. Grading: Homework 15% Quizzes 25% 3 Exams 60% Course Outline --> Block 1 (will be rapid)-- Translational Kinematics Rotational Kinematics Newton's Laws of motion Free-body diagrams Mechanics of general bodies (translational, rotational, combination) Special studies (tension, pulleys, ring, disks, ball, solid sphere, gears) in planes, inclines, contact surfaces, etc. Second order differential equations model development for systems (subjugated by Newton’s laws of motion modules and free-body diagrams module). Block 2 (will be rapid)-- Conservation laws: Energy, Linear momentum and angular momentum Applications: ballistics (neglecting air resistance), harmonic oscillator (various systems. Frictionless ramps/terrain with relative extrema, etc., etc. involving rings, disks and spheres (hollow and solid). Will also have the alternative approach of acquiring models for systems by making use of energy, linear momentum, angular momentum (some systems will require use of all three physical measures); compare this method to Newton second law approach for all problems. Block 3 -- Generalized coordinates & representation of systems Constraints D'Alembert's principle. Informal exposure to the role of Euler-Lagrange equations and ideal examples Examples of constrained systems Block 4 -- Principle of Least Action (PLA) and its development. Explicit examples. Acquiring the Euler-Lagrange equations from the (PLA). Explicit examples. Euler-Lagrange equations applications Block 5 -- More Lagrangian Mechanics: Unconstrained and constrained Dynamics of excavators and cranes. Will likely need a CAS AFTER analytical development of models. I don’t care about any pig pen matrix algebra finesse because we don’t have no time for it; no true professional has time for rent seeking ideology. Block 6 -- Hamiltonian Mechanics Block 7 -- Oscillations: normal modes, Kapitza pendulum, Foucault pendulum, Parametric resonance Block 8 -- More Hamiltonian Mechanics, Action. Liouville’s theorem. The Hamilton-Jacobi equation, Action-angle variables, Adiabatic invariants Prerequisites: General Physics I & II, ODE, Calculus III. There is no requirement of Methods of Mathematical Physics as a prerequisite course. Advance Mechanics II Second course in the Advanced Mechanics sequence. Course focus is to further establish theory in classical mechanics. Course is not a runaway mathematical trainwreck. We have meaningful developments, say, what you’ve analysed or learnt should generally be applicable in the real world, else, you really don’t understand much, and for some reason like "diving off a boat holding a 50 pound cannon ball”. We’re dealing with classical mechanics here, not untested String Theory. Assessment --> Homework (prerequisite tasks and course level tasks) 3-5 Quizzes (will reflect homework) 3 Exams (will reflect quizzes and homework) Outline--- --Fast review of applied Lagrangian formalism 1. Common coordinates and generalised coordinates; ignorable coordinates; generalized forces and momenta General notations must be accompanied with various explicit dynamical systems; a means to deter incompetence with real dynamical systems, without reservation. 2. Advance review of the least action principle 3. Ideal systems Systems without constraints Summary of coupled oscillations and normal modes using Lagrangian; reconstructing the motion of the system from the normal modes. 4. Central force problems Obtain the equation of motion in terms of an effective potential and solve for standard central force problems. Lagrangian and Hamiltonian treatment: Orbit equation Precession Deriving a scattering cross-section for a given central force problem 5. Conservation laws, cyclic coordinates symmetries and Noether’s theorem 6. Miscellaneous problems (Newtonian versus Lagrangian) Coriolis effect; rotating top about a fixed point on a flat plane in the presence of gravity; Coriolis gyroscope; Gimbal gyroscope; Rayleigh dissipation function. Townsend, N.C., Shenoi, R.A. Modelling and Analysis of a Single Gimbal Gyroscopic Energy Harvester. Nonlinear Dyn 72, 285–300 (2013) --Role of Lagrange multipliers in constrained systems and solving --Holonomic and non-holonomic constraints 1. Determining the nature of the constraints (holonomic or non-holonomic, time-dependent or static) and forces (conservative or non-conservative) for a given problem, and thereby identify the number of degrees of freedom and select appropriate generalized coordinates. 2. Integrability and Non-Integrability of Holonomic and Nonholonomic systems Flannery, M., R., The Enigma of Nonholonomic Constraints, Am. J. Phys. 73 (3), March 2005. 3. Pendulum examples involving constraints (with or without friction) --Various Nonholonomic constraints applications 1. Swaczyna, M., Several examples of Nonholonomic Mechanical Systems, Communications in Mathematics 19 (2011) 27–56 2. Rolling disc on a horizontal plane (compare with 2 in prior module) 3. Homogeneous sphere rolling without sliding on a horizontal plane rotating with non-constant angular velocity about a vertical axis. Apart from constant gravitational force, no other external forces to act on the sphere. 4. The Bicycle 5. Del Rosso, V., et al, Self-Balancing Two-Wheel Drive Electric Motorcycle Modelling and Control: Preliminary Results, 2018 5th International Conference on Control, Decision and Information Technologies (CoDIT’18), IEEE 2018. 6. Control of Space Vehicles with Fuel Slosh Dynamics 7. Control of a manipulator with a Jerk Constraint 8. PPR robot and 3-PPR planar robot 9. Jin Jung, M., Hwan Kim, J., Development of the Fault-Tolerant Omnidirectional Wheeled Mobile Robot Using Nonholonomic Constraints, The International Journal of Robotics Research Vol. 21, No. 5-6, May-June 2002, pp. 527-539 --Hamiltonian theory 1. Recognise the concepts of Hamilton’s principle and phase-space 2. Hamiltonian and conservation; conserved quantities from cyclic coordinates perspective; recognising the resulting equations of motion 3. Solve Hamilton’s equations of motion for standard problems. 4. Valle, G., Campos, I., and Jim, Jimenez, J., L., A Hamilton-Jacobi Approach to the Rocket Problem, Eur. J. Phys. 17 (1996) 253–257 --Canonical transformations 1. Finding canonical transformations for simple problems to make the problem easy to solve (cyclic coordinates). 2. Testing for the canonical condition using generating functions, the symplectic condition, and Poisson brackets. 3. Applying Poisson bracket formalism to identify constants of motions. Determining time evolution of a generic dynamic variable of interest for a given Hamiltonian using Poisson bracket formalism. --Hamilton-Jacobi Theory (HJ) 1.The prime directive for development concerns only how and when we want to use it with applications; neither how mathematically contorted nor honouring mathematical "magic mushrooms spam”. 2. Applications: mechanics, gravitational, electromagnetic fields Will also emphasize separation of variables w.r.t to coordinates 3. Numerical Methods 4. Verify that for system in question Lagrangian, Hamiltonian and HJ are consistent with each other --Perpetual Motion and the Laws of Thermodynamics Will have cases studies of attempted devices. Namely, description and modelling, and challenges based on laws of thermodynamics. Prerequisite: Advance Mechanics I Fluid Mechanics To develop a fundamental understanding of the science and engineering of fluid mechanics, through rigorous theoretical discussions, analytical examples, practical applications, and computational projects. Fluid properties, hydrostatics, conservation equations, analytic description of simple flows, flow measurement, empirical description of engineering flows, similitude, lift, drag, boundary layers, compressible flows, some engineering applications. Students must have familiarity with conservation principles, vector calculus, and differential equations. Computationally, proficiency in a high-level programming environment (e.g. C/C++, Mathematica, OpenFOAM) to design algorithms and perform calculations, and compared to solutions given by Mathematica. Course will also engage software such as OpenFOAM. Prototypical textbook --> Munson, et al., Fundamentals of Fluid Mechanics Lab textbooks --> Ferziger, J. H., Peric, M. and Street, R. L. (2020). Computational Methods for Fluid Dynamics. Springer International Publishing · F. Moukalled, L. Mangani and M. Darwish (2015). The Finite Volume Method in Computational Fluid Dynamics: An Advanced Introduction with OpenFOAM and Matlab, Springer Tools --> Mathematica, OpenFOAM Labs --> Labs will follow determined lecture sets. Will characterise the fluid behaviours of concern, accompanied by characterisation of the differential equations that govern. Analytical solution methods will be mostly overview. Students will initially pursue solutions in Mathematica, identifying the chosen method applied by Mathematica concerning NDSolve; followed by assigned numerical methods building in Mathematica. Will incorporate development with OpenFOAM; manual development of numerical methods in Mathematica will accompany alongside results from Mathematica selection methods and OpenFOAM development. Labs concern modules 5, 7 and 8 treating all topics in respective module. Exams --> -Exams will be based on homework -Exams will incorporate Mathematica activities -Exams will incorporate OpenFoam activities when appropriate to compare with your acquired Mathematica usage and development. You are permitted 2-3 sheets of loose leaf notes ONLY FOR Mathematica and OpenFoam use. Computational Fluid Dynamics Project --> Independent projects based on all prior OpenFoam skills development. Assessment --> Homework Labs 4 Exams Computational Fluid Dynamics Project Topics outline --> 1.Fluid Statics -- Pressure variation in a fluid at rest -- Hydrostatic forces on plane and curved surfaces -- Buoyancy and flotation principles 2.Bernoulli Equation -- Derivation of streamline and normal components of the momentum equation -- Static, dynamic and total pressures -- Restrictions on the use of the Bernoulli equation 3.Fluid Kinematics -- Eulerian and Lagrangian descriptions -- Velocity and acceleration field -- Control volume and system representation -- Reynolds transport theorem 4.Integral control volume analysis -- Conservation of mass, momentum and energy for incompressible flow 5.Differential analysis of fluid flow Module will apply Mathematica and OpenFOAM -- Velocity and acceleration field -- Conservation of mass and momentum -- Euler’s inviscid equations of motion -- Potential Flow -- Navier Stokes Equations 6.Dimensional Analysis -- Buckingham Pi Theorem -- Modelling and similitude 7.Viscous Flow in Pipes Module will apply Mathematica and OpenFOAM -- Laminar and turbulent flow -- Entrance region and fully developed flow 8. External Flow Module will apply Mathematica and OpenFOAM -- Lift and drag concepts -- Boundary layer concepts 9. Computational Fluid Dynamics Project Prerequisites: Calculus III, Numerical Analysis, and General Physics I. Methods of Mathematical Physics This course isn’t concerned with being a perfectionist, nor towards retarding attempts to unfairly treat or critique others by claiming teaching education based on something trivial one has practiced a thousand times with nothing better to do. Affinity or innate ability makes the world turn, not a parasitic mathematical fanatic; you can’t compare a mathematician to an engineer or physicist or chemist. Any directive of this course doesn’t primarily concern repulsive trivial manual matrix algebra prowess; people have better things to do than trying to intimidate others with boxes of numbers abiding by linear models. All modules mentioned and detailed subjects will be completed with quality instruction. Course will have integrity in a firm foundation of physics. A major directive of this course is to introduce practical and relevant mathematical tools in a pleasant manner towards the physical sciences and geophysics. It’s really constructive that students consume and digest the material through such fluid and tangible course layout given, rather than them questioning their decision making in career goals, and them not questioning the instructor’s true worth in society. One wants to model physics, rather than attempts of mathematical superiority towards nothing. Mathematical theory will neither drown course nor weaken the focus of the course. Course will be treated in a manner that emphasizes practicality, being a solid foundation for the physical sciences and geophysics, rather than mathematical frolic and parasitic mathematical obnoxiousness. Homework 20% 4 exams (for ease of mind and for constructiveness) 80% Course Outline --> --Geometrical Vector Spaces This module will only concern objects physically meaningful to the physical sciences; notion of dimension will be physical and nothing more. To be relevant to physics one must have a background in physics and understand the physics. Topics in module will be described, developed and categorized towards constructive practical usage in applications. Matrices done manually will be no larger than column size or row size of 3 and will be limited; larger sizes concern computational tool. 1. Structure for Euclidean space Definitions of field Vector space Inner product Norm Normed vector space Metric 2. Linear independence and bases vectors with relation to coordinate systems and transformations. Note: I don’t care about about a bunch of given weirdo matrices out of no where. I only care about coordinate systems and transformations. 3. Gram-Schmidt Process (vectors) and its relevance to basis vectors. Modified Gram-Schmidt (vectors) 4. Transformations between Cartesian coordinate systems: shifts, Euler angle rotations and relation to spherical coordinates or cylindrical coordinates. 5. Transforming differentials and vectors among Cartesian, polar, cylindrical and spherical coordinates. 6. For a respective system identify the basis. Change of basis between prior mentioned coordinate systems. Confirm that magnitude and direction remains unchanged. How does one know that orientation is preserved? 7. Eigenvectors and Eigenvalues of geometric transformations (Mathematica usage to complement). Don’t evangelise the boxes of gibberish finesse, rather, why is it so special that it’s not wasting time --Properties of vectors spaces in Euclidean space with application to coordinates 1. Observing the orientations of vectors and covariant vectors at point p. Mapping for contravariant and covariant vectors, and respective transformation matrices (and will apply actual coordinates). 2. Covariant bases and contravariant bases and observing the orientations at point p (will also apply coordinate systems and transformations). 3. Kronecker delta; dual relationship between contravariant and covariant (basis) vectors 4. Defining the norm via contravariant-covariant “contraction” and its invariance w.r.t to coordinate transformations. 5. Euclidean Metric i. Properties of distance (or the norm) validated in Euclidean space, namely positive definiteness, non-degeneracy, symmetry and triangular inequality. ii. Transformation of metric components iii. Transformation of metric components w.r.t to actual coordinate transformations, and preservation of distance iv. Use of the Euclidean metric to relate contravariant and covariant components --Common Tensorial Operators Note: higher order tensors will be confined to rank 2. 1. Introducing the concept and structure of the tensor product, it’s geometrical view, and it’s transformation (from “egg shell” form to explicit cases with coordinate systems). Explicit change of coordinates for tensor products among the basis vectors. For a given coordinate transformation how will chosen basis vectors transform. Can you account for all transformed basis vectors? NOTE: will not indulge much on rotation matrices and coordinate, because there are more interesting representations of geometrical objects. Among various coordinate systems will investigate explicitly how tensor components (unique to the tensor product) adjust to preserve equivalence in the manifold. 2. The metric tensor. Will identify its properties and formally recognise tensorial structure, and employing (1) prior towards its properties. 3. Review of gradient (with properties) and the displacement gradient; change of coordinates and verifying equivalency among coordinate systems. 4. Review of directional derivative and properties; change of coordinates and verifying equivalency among coordinate systems. 5. Review of divergence and properties; change of coordinates and verifying equivalency among coordinate systems. 6. Gradient of a tensor field; change of coordinates and verifying equivalency among coordinate systems. 7. Directional derivative of a tensor field; change of coordinates and verifying equivalency among coordinate systems. 8. Divergence of a tensor field; change of coordinates and verifying equivalency among coordinate systems. 9. Review of divergence theorem; change of coordinates and verifying equivalency among coordinate systems. 10. Gauss’ Divergence theorem of a tensor field; change of coordinates and verifying equivalency among coordinate systems. 11. Applications of the Levi-Civita symbol i. Definition and properties ii. Determinants iii. Vector cross product, curl & irrotational fields iv. Curl of tensor fields; change of coordinates & verifying equivalency among coordinates v. Review of Green’s theorem and Stokes theorem. Tensorial forms of Green’s Theorem and stokes theorem; change of coordinates & verifying equivalency among coordinates. 12. Will identify non-relativistic tensors in the physical sciences and apply various explicit coordinate transformations as practice, verifying equivalency among coordinates. 13. Electromagnetism Review of Maxwell Equations Maxwell Equations in terms of electromagnetic potentials Lorentz force from Faraday’s Law Verifying prior holds under coordinate transformations Is gauge invariance unique to coordinate transformations? Is gauge invariance preserved under coordinate transformations? Differentiation between Lorentz transformations and coordinate transformations Investigate the Lorentz transformations Subject to gauge invariance, that’s subject to coordinate transformations Covariant formulation (with incorporation of all prior developments) Derivation of Lorentz force law Field, J. H. Derivation of the Lorentz Force Law and the Magnetic Field Concept using an Invariant Formulation of the Lorentz Transformation. CERN: https://cds.cern.ch/record/630753/files/0307133.pdf Electromagnetic Field Tensor Will verify preservation under various coordinate transformations Lorentz transformations under coordinate transformations, say, if is not interested in “Cartesian-like representation”, rather wanting (t, x, y, z) in terms of cylindrical coordinates or spherical coordinates or other, and vice versa. Model for charged particles with the electromagnetic field tensor --Basic Lagrangian Modelling in Classical Physics For this module, purpose and logistics are emphasized. Namely, comprehending what you’re trying to accomplish, what one needs to formulate, and finishing. For all mechanical systems encountered, reconciliation with Newton’s second law must be established; includes solutions through Newton’s law to compare with E-L approach solutions. 1. Variational principle: curve, surface and general pat for which a given function has a stationary value with existence of extremum. Arriving at the Euler-Lagrange equation. 2. For two-dimensional Euclidean space proving that the shortest distance between two fixed points is a straight line Conventional calculus (CC) via Euler-Lagrange equation (E) For both CC and EL, change of variables (coordinates) amongst Cartesian, cylindrical, and spherical coordinates and establishing equivalence. Geodesics on the sphere analogy to priors 3. Going from spatial geometries to physics. How does one connect Lagrangian formalism to physics? Was the Lagrangian a meaningful physics concept before being a mathematical “vanity”? 4. Case studies of consideration Reformulating Newton’s equations of mechanics. Change of variables (coordinates) amongst Cartesian, cylindrical, and spherical coordinates and establishing equivalence. Validating equivalence between Newtonian mechanics and Lagrangian modelling for various classical mechanics problems. Finding the curve that will allow a particle to fall (by gravity as inverse square model) under the action in minimal time. Then extending to incorporate atmospheric resistance, what will be then? Finding the Lagrangian density of a vibrating string fixed at both ends, then applying the Euler-Lagrange equations, yielding the wave equation. Determining the Lagrangian for electromagnetic interaction. Does the resulting E-L equation translate to the Lorentz force? If not, then what? 5. Advance guides --> Ferrario, C. and Passerini, A. Transformation Properties of the Lagrange Function. Rev. Bras. Ensino Fís. [online]. 2008, vol.30, n.3 [cited 2020-02-28], pp.3306.1-3306.8 Sudarshan, E. C. G. and Mukunda, N. (2015). Chapter 5 Invariance Properties of the Lagrangian and Hamiltonian Descriptions, Poisson and Lagrange Brackets, and Canonical Transformations. Pages 31 -44. In: Classical Dynamics a Modern Perspective. World Scientific. 6. Hamiltonian analogy to Lagrangian Modelling Will also include why there’s preference at times for the Hamiltonian over Lagrangian modelling. Basic practical applications. Prior literature excerpt to also apply 7. Hamilton-Jacobi (HJ) The prime directive for development concerns only how and when we want to use it with applications; neither how mathematically contorted nor honouring mathematical "magic mushrooms spam”. Applications: mechanics, gravitational, electromagnetic fields Will also emphasize separation of variables w.r.t to coordinates Numerical Methods Verify that for system in question Lagrangian, Hamiltonian and HJ are consistent with each other 8. Investigating Mathematica functions --Orthogonalization of Functions 1. Why do we care about this in physics? 2. Proof of economical practicality in use 3. Seaborn, J. B. (2002). Orthogonal Functions. In: Mathematics for the Physical Sciences. Springer, New York, NY. 4. Gram-Schmidt Orthonormalization (functions) --Applications that make Complex Variables Relevant 1. Complex numbers 2. Is there any economical practicality in representing geometries or physical bodies with complex variables? 3. Should Complex Variables courses be turned back into conferences in rooms locked from the outside? Animal shelter selection or something. 4. Geometrical properties of complex variables (no representation of physical bodies because people have better things to do) 5. Complex exponential as a power series leading to Euler’s formula; cosine and sine expressed in terms of complex exponents. 6. What is so special about the complex conjugate outside of a math course in a classical physics sense? Get to the point with fast practicality. 7. Review of Laplace transforms (limited) 8. Simple harmonic oscillator i. Modelling classical physical systems of SHM ii. Solutions of ODE of SHM (solutions in trigonometric & exponential form) iii. Damping & comparing solutions to ideal SHM (trigonometric & exponential forms) iv. Superposition of waves (trigonometric and exponential forms) 9. Eigenvalue Analysis of Vibrations Note: if I look at something and can’t make it out to be physics, don’t bother; boxes of numbers are not physics. Matrices are mundane algorithmic tools. If system requires matrices higher than 2 by 2, your graphing calculator skills and Mathematica should be relevant. If you have infinite time to doodle with matrix theory, go find a math department and stay there. Mechanics Systems One dimensional Membrane Circuits (optional) 10. Fourier Series i. Review of trigonometric integral identities and the associated complete orthogonal system ii. Periodic functions, definition of Fourier series and computations iii. Going from [-pi, pi] to [-L, L] via change of variables iv. Complex Fourier series v. Convergence criteria via Dini’s test and Dirichlet boundary conditions; with exemption functions examples. Calderon, C. P. (1981). On the Dini Test and Divergence of Fourier Series. Proceedings of the American Mathematical Society, Vol. 82, No. 3, pp. 382-384 vi. Dini continuity and Dini criterion. vii. Recognising Eigenfunctions and Eigenvalues through the method of separation of variables upon the linear wave equation and linear heat equation involving Fourier series. Eigenfrequencies of vibration and the eigenvectors as shapes of the vibrational modes. May consider representation in spherical and cylindrical coordinates as exercises. 11. Fourier Transform i. Differentiating between “series” and “transform” ii. Counterparts to Dini (test, continuity and criterion) for Fourier transform? iii. Differentiation and integration properties iv. Applications 12. Heavyside Step function and the Dirac function i. Rectangular shifts and rectangular pulses ii. Function types in terms of Heaviside and Dirac functions iii. Applications iv. Show that particular functions (Gaussian, sinc, Airy, Bessel function of the first kind) all converge to the Dirac delta function for a specific limit. v. Fourier relevance to priors 13. Investigating of Mathematica functions/operations for many prior applications --Bessel’s Equation 1. Solving the Laplace equation in cylindrical coordinates 2. Solution of Bessel’s equation (first and second kind) via method of Frobenius and recurrence 3. General solution of Bessel’s equation of order p 4. Applications in physical settings 5. Investigating of Mathematica functions --Legendre Equation 1. Solving the Laplace equation in spherical coordinates 2. Solving the Legendre equation (first and second kind) via method of Frobenius and recurrence 3. Solving Helmholtz equation in spherical coordinates 4. Expansion of potentials and the physical roles of terms (gravitation and magnetospheres) Note: for gravitation, applying motion of inertia and McCullough’s formula with Legendre polynomials can prove to be very insightful. 5. Investigating of Mathematica functions --Eigenfunctions in Quantum Physics Brandt S., Dahmen H.D., Stroh T. (2003) Bound States in One Dimension. In: Interactive Quantum Mechanics. Springer, New York, NY Brandt S., Dahmen H.D., Stroh T. (2003) Bound States in Three Dimensions. In: Interactive Quantum Mechanics. Springer, New York, NY Rotenberg, A. (1963). Calculation of Exact Eigenfunctions of Spin and Orbital Angular Momentum Using the Projection Operator Method. The Journal of Chemical Physics, Volume 39, Issue 3, p.512-517 Bunge, C. F. and Bunge, A. (1971). Eigenfunctions of Spin and Orbital Angular Momentum by the Projection Operator Technique. Journal of Computational Physics, volume 8 Issue 3. Pages 409 - 416 1. Bound States in One Dimension Additionally, confirming whether various wavefunctions are eigenstates of linear momentum and kinetic energy (or neither or both). Hydrogen atom Wavefunctions. 2. Classical Angular Momentum Classical Angular Momentum Angular Momentum Operators Eigenfunctions of the Angular Momentum Operators 3. Orbital Description in Quantum Mechanics Angular Momentum Vectors and Quantum Mechanical Operator 4. Spin Angular Momentum Description in Quantum Mechanics 5. Investigating Mathematica functions NOTE: as well, there can be analysis of projects for such topics found in Wolfram Demonstrations Projects. Prerequisites: General Physics I & II, ODE, Calculus III. Electromagnetic Theory I This is not a mathematics course. Modelling and derivations generally follow the text of Bo Thide. However, problem sets to come from other sources emphasizing physics and practicality. Questions and tasks in homework and exams will be of the most practical and realistic in physics (”an example”, "Classical Electrodynamics", by John David Jackson, or text of Grifiths). --Questions and tasks in homework and exams will be of the most practical and realistic in physics. --For PDEs encountered the ICs, BCs and solutions will be treated. --Course will not provide a relativistic treatment of Electrodynamics. Homework --> There will be some vector calculus refresher Problem sets to treat course level Quizzes --> Quizzes will reflect homework. There will be 3. Exams --> There will be 3-4 exams. Homework assignments and quizzes will be a strong indicator of what’s to be on exams. There will be minimal required derivations of crucial equations and laws, or I may ask you to apply conditions and/or techniques to complete a derivation. Labs --> Concerning the given literature for labs, apart from competent comprehension of logistics and implementation, each lab must be coherent, tangible and practical with course topics, and vice versa. Hence, a particular lab experiment may be done on multiple occasions with possible extensions/augmentations. Cloete, Reader, H. ., van der Merwe, J., du Plessis, F. ., & Becker, L. . (1996). Experiments for Undergraduate Courses in Electromagnetic Theory and EMC, Proceedings of IEEE. AFRICON ’96, 1, 362–365 vol.1. Mitchell, M., Blandford, D. and Chandler, K. M. (2016). Student Projects for an Electromagnetics Course. American Society for Engineering Education, 123rd Annual Conference & Exposition, New Orleans, LA, June 26-29 MIT OCW Electricity & Magnetism Experiments: https://ocw.mit.edu/courses/physics/8-02-physics-ii-electricity-and-magnetism-spring-2007/experiments/ Electrostatic filters Metal detector circuit Taghizadeh, S. and Lincoln, J. (2018). MRI Experiments for Introductory Physics. The Physics Teacher, Volume 56, Issue 4 Hard Drive Degausser development Eddy Current Magnetic Brake (simplistic setup) Molina-Bolívar, Jose & Abella-Palacios, A. (2012). A Laboratory Activity on the Eddy Current Brake. European Journal of Physics 33(3): 697-707 COURSE OUTLINE --> --Classical Electrodynamics 1. Electrostatics i. Coulomb’s law ii. Electrostatic field 2. Magnetostatics i. Ampère’s law ii. Magnetostatic field 3. Electrodynamics i. Equation of continuity for electric charge ii. Maxwell’s displacement current iii. Electromotive force iv. Faraday’s law of induction v. Maxwell’s microscopic equations vi. Maxwell’s macroscopic equations --Electromagnetic Waves 1. The Wave equations i. Wave equation for E ii. Wave equation for B iii. Time-independent wave equation for E 2. Plane waves i. Telegrapher’s equation ii. Waves in conductive media 3. Observables and Averages --Electromagnetic Potentials 1. The electrostatic scalar potential 2. The magnetic vector potential 3. Poisson equation for electrostatic potential and magnetic vector potential 4. Maxwell Equations in terms of the potentials 5. Wave Equations for potentials Prerequisites: General Physics I & II, ODE, Calculus III. This course is not a prerequisite of Quantum Physics courses because this course is a comprehensively classical description. Electromagnetic Theory II This is not a mathematics course. Modelling and derivations generally follow the text of Bo Thide. However, problem sets to come from other sources emphasizing practicality and physics. --Questions and tasks in homework and exams will be of the most practical and realistic in physics. --For PDEs encountered the ICs, BCs and solutions will be treated. --Course will not provide a relativistic treatment of Electrodynamics. Homework --> Assignments will be constituted by prerequisite tasks and current course tasks. Course serves towards retention of crucial knowledge and skills. Quizzes --> Quizzes will reflect homework, There will be 3-4. Exams --> There will be 3-4 exams. Homework assignments will be a strong indicator of what’s to be on exams. There will be minimal required derivations of crucial equations and laws, or I may ask you to apply conditions and/or techniques to complete a derivation. NOTE: course will not have labs for safety reasons, but will make effort to highlight relevance in the real world: Radiation fields, radiated energy Electromagnetic Radiation and Radiating Systems Multipole radiation Radiation from a localised charge in arbitrary motion Course Outline --> --Advance synopsis, summary of models and their solutions for Classical Electrodynamics, Electromagnetic Waves, and Electromagnetic Potentials from prerequisite. --Electromagnetic Fields and Matter 1. Electric polarisation and displacement i. Electric multipole moments 2. Magnetisation and the magnetising field 3. Energy and momentum i. Energy theorem in Maxwell’s theory ii. Momentum theorem in Maxwell’s theory --Electromagnetic Fields from Arbitrary Source Distributions 1. The magnetic field 2. The electric field 3. The radiation fields 4. Radiated energy i. Monochromatic signals ii. Finite bandwidth signals --Electromagnetic Radiation and Radiating Systems 1. Radiation from extended sources i. Radiation from a one-dimensional current distribution ii. Radiation from a two-dimensional current distribution 2. Multipole radiation i. The Hertz potential ii. Electric dipole radiation iii. Magnetic dipole radiation iv. Electric quadrupole radiation 3. Radiation from a localised charge in arbitrary motion i. The Liénard-Wiechert potentials ii. radiation from an accelerated point charge iii. Bremsstrahlung iv. Cyclotron and synchrotron radiation v. Radiation from charges moving in matter Prerequisite: Electromagnetic Theory I. Course is not a prerequisite of Quantum Physics courses because it’s a comprehensively classical description. Introduction to Optics Homework 10% Quizzes 20% Labs & lab notebook 20% Mini Project 10% Midterms 20% Final 20% Dependent on the severity of conduct infractions, conduct percentage of final grade may warrant amplification to 69%. Course schedule will be much longer than the conventional case. Prototypical Textbook: “Optics”, 5th Ed., E. Hecht This course will be divided into three main sections: i) Geometrical Optics: (Ch 5, 6) Reflection, Refraction, Mirrors, Lenses, Prisms, Optical systems, Aberrations. ii) Physical Optics: (Ch 2, 3, 4, 7, 8, 9, 10) Wave Motion, Electromagnetic waves Theory, Propagation of light, Superposition of waves, Polarization, Interference, Diffraction. iii) Modern Optics: (Ch 11, 12, 13) Laser theory, types of lasers, laser resonators, properties of laser beams, laser applications, holography. TENTATIVE TOPICS: ---Geometrical Optics: Lenses, Mirrors, Prisms, Optical systems, Aberrations (Ch. 5, 6). ---Wave motion: One dimensional waves, plane waves, Differential wave equation, Complex notation (Ch. 2). ---Electromagnetic Wave Theory: Basic Laws, Light in Bulk matter, Quantum Field Theory, Photons (Ch. 3). ---The Propagation of Light: Interaction of light with matter (Ch. 4). ---The Superposition of Waves: Superposition Principle, Periodic waves, Non-periodic waves, Stationary waves (Ch. 7). ---Interference: General considerations, Conditions for interference, Interferometers, Applications of interferometry (Ch. 9). ---Diffraction: Preliminary considerations, Fraunhofer and Fresnel diffractions (Ch. 10). ---Coherence: Temporal and Spatial Coherence (Ch. 7, 9, 13). ---Polarization: Nature of polarized light, Mathematical description (Ch. 8). ---Birefringence and Retarders: Ch. 8. ---Imaging: Abbe Theory of Imaging (Ch. 7, 11 and 13). ---Lasers: Photons and lights, Principles of Lasers, Basic applications (Chap. 3 & Chap. 13). Tentative Labs The “what, why, how and why again about what” process will be implemented for all experiments. Experiments should be HIGHLIGHTED BY MEANINGFUL APPLICATIONS --> Students will responsible for setting up many of the labs based on documented guidance and limited instruction. Will apply Optica integrated with Mathematica, or OSLO, to model and simulate optics laboratory set ups, acquiring ideal values, parameters, imagery, etc., to be compared with experimentation. Lab# 1 Handling and cleaning the optics, mechanical assembly. Lab# 2 Laws of geometrical optics (Reflection and Refraction), Thin Lens Equation, Thick Lens Equation, Introduction to optical system, handling the optics. Lab# 3 Imaging, Lenses, Combination of lenses Lab# 4 Setting up and Aligning Prism spectroscopy; with characteristic results Lab# 5 Expansion of Laser beams Lab# 6 Diffraction gratings (applications and use with general light sources and lasers) Lab# 7 Diffraction of Circular Apertures Lab# 8 Gaussian beams and variations (i) Irradiance model. Gaussian beam waist (convergence and divergence). Variation of the beam waist as a function of propagation distance. Curvature of the wave front. (ii) From developments in (i) towards measuring the Gaussian profile of the laser using a scanning detector and the computer interface. The data will be in the form of a text file (or whatever) with two columns of numbers – one for time and the other for voltage that will be proportional to the irradiance. You will acquire data with the computer and then fit the data to a Gaussian (if so). Note: The calibration of the scanner displacement vs time (as recorded by the computer) is obtained in the following way. The motor driving the scanner screw rotates at say (something like) 600 rev/min and the screw pitch is (something like) 10 turn/cm. A check of the calculated scanner speed should be done by actually measuring the time taken to travel a known distance. (iii) Bessel beam (theoretical highlights) (iv) Tophat beam (theoretical highlights) (v) Laser beam profiler (and comprehension of limitations from one device to another). Lab# 9 Interference, single slit and double slits Lab# 10 Michelson Interferometer Lab# 11 Setting up and Aligning a Fabry-Perot Interferometer; with characteristic results Lab# 12 Optical Rotation Lab# 13 Coherence Lab# 14 Polarization Note: for review with lab activities video recording of operations may be possible. Students may also record their own lab activities, but under contract such will never be live feeds with personal devices. Prerequisites: General Physics I & II, Calculus III, ODE Advanced Optics Lab The optics lab consists of experiments which introduce the techniques and devices essential to experimental work in modern optics from the Physics and Engineering perspectives, with an emphasis on Computational Optical Sensing and Imaging (COSI). Lab sessions will require a full day, running 2 days per week, and conflicts with the scheduled time are OK because labs will literally require a full day. Plan on 9AM-9PM, maybe even leaving at midnight. The enrolment limit is listed as 12 (2 days with 3 groups of 2 each) but we might be able to accommodate 1 more via setup holes, or we may go down to 1 day a week with 3 groups of 3. You will probably find that the Advanced Optics Lab (AOL) is a gruelling bootcamp of optics laboratory techniques and will require a substantial commitment. If you are not fully committed to such a possibly gruelling lab schedule or do not have the required background of at least one or optics courses you should probably drop. NOTE 1: many or most lectures will require mathematical skills sets ranging from Calculus III to Methods of Mathematical Physics. NOTE 2: course will also assume some experience with Optics Labs. Labs from prerequisite optics course will be reviewed and advanced replicated, to be tangible, practical and fluid with current course labs of concern. For each lab from prerequisite to be advanced replicated, will be predecessor to a relating lab of current course; making connections, fluidity and gaining competence. NOTE 3: for labs will need proper student identification and check-in regulations and protocols. In general student groups must have agreement on schedule. Makeup labs may be possible proper levels of consent. Primary Reference: Hobbs, Building Electro-Optical Systems: Making It All Work, 2000 Saleh & Teich, Fundamentals of Photonics The second reference only serves as refresher guide for basic experiments and technologies encountered in prerequisite optics course. Additional background references will be available in the lab or on-line. Documentation for key devices and equipment will be available in the lab and should be read prior to the lab if you are not familiar with the equipment. For texts that will assist students with lectures the professor/instructor will provide suggestions pertaining to whatever particular topic. We will assign the groups, and change them each change (3-3-3), trying to mix. Lab setup will be done on the weekends preceding each 3-3-3 group. You will sign up to help with the setup of that lab, and devote at least a FULL weekend day (Fri or Sat) to setup, maybe more. Students will responsible for setting up many of the labs based on documented guidance and limited instruction. Before orchestrating labs students will apply Optica integrated with Mathematica, or OSLO, to model and simulate optics laboratory set ups, acquiring ideal values, parameters, imagery, etc., to be compared with orchestrated experimentation. Possibility of project labs or other labs in last month, but may also be off. Labs Outline --> The “what, why, how and why again about what” process will be implemented for all experiments. Experiments should be HIGHLIGHTED BY MEANINGFUL APPLICATIONS LAB 0. Optional Basic Skills Lab The idea is to practice skills you will need to utilize throughout the labs and need to become facile in order to finish at a reasonable time. Laser alignment Spatial filtering Collimation and collimation testing Use of an oscilloscope Use of an optical power meter Use of a CCD detector array or knife-edge beam profiler 1. Fourier Optics What you will learn in this lab Fourier transforms in 1-D time and 2-D space. Diffraction and imaging. Plane waves and k-space – Propagation to the far field is given by a spatial Fourier transform A lens takes a Fourier transform 4F afocal imaging systems and spatial filtering in the Fourier plane Holographic spatial filtering for pattern recognition – Dynamic polarization holography in doped dye-polymer Computer Generated Holography 2. Interferometry What you will learn in this lab Plane wave interference. Spherical wave interference Division of Wave front Interferometers – 2-slit interference, Lloyd’s mirror, biprism Introduction to Coherence – Temporal Coherence and Fourier Transform Spectroscopy Division of Amplitude Interferometers – Mach-Zehnder, Michelson, Sagnac, Shearing Polarization Interferometry Multiple Beam Interference – Fabry-Perot Interferometer Discussion of Spatial Coherence Aberrations and the interferometric characterization of Wave fronts 3. Polarization and Crystal Optics What you will learn in this lecture and lab Polarization representation and the Poincare sphere Transverse field representation of polarization in terms of Jones vectors Transformation of polarization by polarizers and waveplates as Jones matrices Stokes vector/Poincare sphere to represent polarization Intensity measurements Mueller matrices of polarizers and retarders and Poincare sphere visualization Polarimetry, calibration and the Meadowlark liquid crystal polarimeter Using waveplates to produce then verifying an arbitrary state of polarization Crystal optics using k-space Anisotropic propagation represented using k-space and geometrical surfaces Anisotropic refraction to explain Conoscopy, Glans, Wollastons, Soleil-Babinets Electro-optic and liquid crystal artificial birefringence 4. Photorefractive Crystals What you will learn in this lecture and lab Photorefractive effect Volume Holography Kuktarev band transport equations Two-wave mixing Anistropic Electrooptic effect Photorefractive Grating Recording and Readout Photorefractive beam fanning Photorefractive Oscillators Photorefractive Four-Wave Mixing Self-Pumped Phase Conjugation 5. Acousto-Optics 6. Spectroscopy Linear Spectroscopy Techniques 7. Wave front Shaping: Wave front Sensing/Adaptive Optics 8. Optical Coherence Tomography 9. Adaptive Optics 10. Spatial Light Modulators Huang, D. et al (2012). A Low-Cost Spatial Light Modulator for use in Undergraduate and Graduate Optics Labs, American Journal of Physics 80, 211 Fei Wang, Italo Toselli, and Olga Korotkova, "Two Spatial Light Modulator System for Laboratory Simulation of Random bBeam Propagation in Random Media," Appl. Opt. 55, 1112-1117 (2016) 11. PSF Engineering References for Lab activities --Hajj, B., El Beheiry, M. and Dahan, M. (2016). PSF Engineering in Multifocus Microscopy for Increased Depth Volumetric Imaging. Biomedical optics express, 7(3), 726–731. --King, Sharon V. et al. “Implementation of PSF Engineering in High-resolution 3D Microscopy Imaging with a LCoS (reflective) SLM.” Photonics West - Biomedical Optics (2014). --Ashok, Amit & Neifeld, Mark. (2010). Point Spread Function Engineering for Iris Recognition System Design. Applied Optics. Volume 49. Number 10, pages B26 – B39. --Sreya G. et al (2012). Double Helix PSF Engineering for Computational Fluorescence Microscopy Imaging. Proc. SPIE 8227, Three-Dimensional and Multidimensional Microscopy: Image Acquisition and Processing XIX, 82270F --Fang, Y., Kuang, C., Ma, Y. et al. (2015). Resolution and Contrast Enhancements of Optical Microscope Based on Point Spread Function Engineering. Front. Optoelectron. 8, 152–162 --Zhou, Y. et al (2019). Advances in 3D Single Particle Localisation Microscopy. APL Photonics 4, 060901 --Gustavsson, A., Petrov, P.N., Lee, M.Y. et al. (2018). 3D Single-Molecule Super-Resolution Microscopy with a Tilted Light Sheet. Nat Commun 9, 123 12. Tentative Independent Project LABS Prerequisites: Introduction to Optics Co-requisite: Methods of Mathematical Physics Modern Physics description: The course will provide an introduction to the special theory of relativity and particle physics. Quantum mechanics, including their applications to atomic, molecular, nuclear and solid-state physics. The course is heavily calculus based and relies heavily on problem solving and computational development. Course aims to provide a sturdy introductory foundation in physics outside of classical mechanics, electromagnetism and thermodynamics. However, “many will not be a rocket man as a kid.” Namely, to be meaningful to the class body constituted by those who have met all prerequisites and are officially enrolled, in a manner not to be wrecked and tidal washed with excessive mathematical indulgences. Textbook --> Serway, R. A., Moses, C. J. and Moyer, C. A. (2005). Modern Physics. Brooks/Cole Tools--> QMTools Mathematica Engineering calculator Homework --> Homework will come from text AND other sources. Quizzes--> All quizzes will be based on homework and lectures QMTools with Exercises and Mathematica --> Students will be tasked with assignments in QMTools. Then will investigate means of developing counterparts in in Mathematica, followed by the actual construction and implementation in Mathematica. With Mathematica usage commentary notes are expected throughout. There may also be analysis of chosen Wolfram Demonstrations Labs --> www.physics.purdue.edu/~fqwang/teaching/Phys340-Manual.pdf Software applied likely will be different to what’s in above lab manual Grading --> Homework 3-4 Quizzes Operating QMTools with Exercises & Mathematica Labs 3 Exams LECTURING --> Unit 1. Relativity Unit 2. Light as Particles Unit 3. Matter as Particles and Waves Review for Exam I Exam I Unit 4 Quantum Mechanics in 1D Unit 5. Quantum Mechanics in 3D Review for Exam II Exam II Unit 6. Nuclear Physics Unit 7. Molecular Structure Unit 8. Statistical & Solid-State Physics Review for Exam III Exam III Prerequisites: Calculus III, ODE, General Physics I & II Quantum Physics I: Typical Text --> D. Griffiths, Introduction to Quantum Mechanics, Prentice-Hall Mathematica Resources --> Baumann, G. (2005). Mathematica For Theoretical Physics: Electrodynamics, Quantum Mechanics, General Relativity, and Fractals Vol. 2, Springer Schmied, R. (2019). Using Mathematica for Quantum Mechanics: A Student’s Manual. Springer < https://arxiv.org/pdf/1403.7050.pdf > Feagin, J. M. (1994). Quantum Methods with Mathematica. Springer Wolfram Demonstrations (with Quantum Mechanics) Despite various texts making use of the word “mechanics” with the adjective quantum, this is firstly a physics course, as in Quantum Physics. “Without knowing how your body works w.r.t. to motion and gravity, participating in a cheese roll contest likely will not be quite rewarding. Matrices will not help you from breaking your neck, arms, legs and spine. As well, matrices by themselves are meaningless without grasping the relevance of physics. As well, matrices are to establish ideal structure. Not interested in being swine in a pig pen.” This is a course neither administered by the Mathematics department, nor is it a “excrement show” to be carried about by a mathematician. This is a physics course overall, and will be treated and presented as such. Don’t be a spoiled, viral, repulsive con artist, fascist punk from the mathematics department; 99% of time I don’t care for such kind, and I don’t need that kind towards anything. STOP THE RENT-SEEKING, CONFUSION, OPPRESSION AND HATE. AS WELL, PREREQUISITES ARE PREREQUISITES. Fundamental Question: What are you trying to explain or convince me to acknowledge in the science that is Physics? Labs Tools and Resources --> Note: labs chosen will be in a manner that best serves course topics progression and sustainability for future endeavors Beck, M. (2012). Quantum Mechanics: Theory & Experiment. Oxford University Press Summers, M. K. (1978). A Quantum Mechanics Experiment for the Undergraduate Laboratory. Physics Education 13(1), 22 >> Prutchi, D. and Prutchi, S. (2012). Exploring Quantum Physics Through Hands‐On Projects. Wiley deBroglie wavelength and the Davisson-Germer experiment hyperphysics.phy-astr.gsu.edu/hbase/DavGer.html The Franck-Hertz Experiment and the Ramsauer-Townsend Effect: Elastic and Inelastic Scattering of Electrons by Atoms >> (http://web.mit.edu/8.13/www/JLExperiments/JLExp07.pdf) Galvez, E. J. et al (2005). Interference with Correlated Photons: Five Quantum Mechanics Experiments for Undergraduates American Journal of Physics 73(2), 127 Delayed Choice Quantum Eraser Experiment >> How the Quantum Eraser Rewrites the Past - Space Time - PBS Digital Studios – YouTube Kaur, M., Singh, M. Quantum Double-Double-Slit Experiment with Momentum Entangled Photons. Sci Rep 10, 11427 (2020) >> Electron Spin: Stern-Gerlach experiment hyperphysics.phy-astr.gsu.edu/hbase/spin.html Mathematica activities for Quantm Physics (QP) Exploration of functions with parameters applicable to QP Analysis of Wolfram Demonstrations (with Quantum Mechanics) You may be asked to augment or build upon what’s there based on written instruction by instructor Open Source tools in molecular modelling and simulation Dalton, CP2k, Firefly, Gaussian, GAMESS-US, MOLDEN, NWchem, GPAW, Octopus, ORCA, FreeON, PUPIL, VOTCA , BOSS >> QuTiP NOTE: the various mentioned software above can possibly accommodate particular quantum physics interests if deemed practical and constructive. NOTE: will have a look-through with the supporting documentation and articles that elaborate on the applied models and algorithms of chosen software before implementing chosen software. Pursuits will be constructively relevant to lecturing topics. Software chosen must be well understood to fully capitalize on their potential with lecturing topics. Homework --> Homework will come from texts AND resources. Quizzes --> Quizzes will be based on homework and lectures Exams --> Exams will reflect both homework and quizzes. Grading --> Homework 2-3 Quizzes Labs (TBD) 4 Exams LECTURING --> Predicaments of Classical Physics Energy quantization Boltzmann distribution Energy of harmonic oscillator Equipartition Specific heat of solids Blackbody radiation Quantization of Normal Models Wave equation Normal modes of cavity Periodic boundary conditions Counting modes Planck law Other early evidence for quantum behaviour Photoelectric effect Ritz principle Bohr model Motion of wave packet Electrons as waves Schrödinger equation I Dynamics of Schrödinger’s “wave” function Spherically symmetric potential (H atom) 1D simple harmonic oscillator Particle in electromagnetic field Schrödinger equation II Probabilistic interpretation of ψ-fctn Fourier transform Measuring a particle’s momentum Uncertainty principle Operator formalism I (tangible, practical and fluid to physics) Momentum operator Expectation values Inner products Hermitian adjoint Eigenstates and eigenvalues Operator Formalism II (tangible, practical and fluid to physics) Completeness Measurement Parity Hilbert space & matrix mechanics (tangible, practical & fluid to physics) Dirac’s bra and ket notation Postulates and probability Position representation Angular Momentum I (tangible, practical & fluid to physics) Orbital angular momentum operators L-eigenvalues from ladder operators Eigenvalues from Schrodinger Eqn Commutation rels. -- spherical potential L generates rotations Angular momentum II (tangible, practical & fluid to physics) Central forces & pseudopotential H-atom bound states QM 2-body problem Reduction to 1-body problem Spin I (tangible, practical & fluid to physics) Electron spin Pauli spin matrices 2 spin-1/2 particles Many particles Electron magnetic moment, precession Spin II (tangible, practical & fluid to physics) Absorption Resonant scattering t-matrix Measurement I Superposition Collapse of wave function Role of observer Measurement II Superposition Collapse of wave function Prerequisites: Calculus III, ODE, General Physics I & II, Modern Physics, Methods of Mathematics Physics Quantum Physics II: Second semester of an introduction to the quantum theory, as formulated in the 1920’s and 1930’s by Born, Bohr, Schrodinger, Heisenberg, Dirac and others. Foundations of measurement theory, methods of quantum mechanical perturbation and scattering theory. Applications of quantum mechanics to atomic, condensed matter, and particle physics. If you somehow managed to con your way out of the prerequisite, with some cult-memorization nonsense and faculty/administration tampering crap, well, “may the maker have mercy on your soul in this course.” Many things from the prerequisite course will be situated in a manner to haunt you with the advance topics introduced in this course. Fundamental Question: What are you trying to explain or convince me to acknowledge in the science that is Physics? Typical Text --> D. Griffiths, Introduction to Quantum Mechanics, Prentice-Hall, 2004 Mathematica Resources --> Schmied, R. (2019). Using Mathematica for Quantum Mechanics: A Student’s Manual. Springer < https://arxiv.org/pdf/1403.7050.pdf > Baumann, G. (2005). Mathematica For Theoretical Physics. Electrodynamics, Quantum Mechanics, General Relativity, and Fractals Vol 2, Springer Feagin, J. M. (1994). Quantum Methods with Mathematica. Springer Wolfram Demonstrations (with Quantum Mechanics) You may be asked to augment or build upon what’s there based on written instruction Labs --> Note: labs chosen will be in a manner that best serves course topics progression and sustainability for future endeavors Some labs from prerequisite will be replicated in an advanced manner with relevance to course topics. Described experiments in prerequisite not done in prerequisite can possibly serve this course well. Other experiments and tools that my prove useful: Wave-Particle Duality Seen in Carbon-60 Molecules >> Arndt, M., Nairz, O., Vos-Andreae, J. et al. Wave–particle duality of C-60 molecules. Nature 401, 680–682 (1999). If carbon-60 isn’t economically feasible then to consider molecule substitutes that will abide by mechanisms of the experimentation setup; will experiment with different molecules. Note: in general pursue molcules of different scales. Spectroscopy (multiple cases) Hong–Ou–Mandel Effect Hong, C. K., Ou, Z. Y. and Mandel, L. (1987). "Measurement of SubpicoSecond Time Intervals Between Two Photons by Interference". Phys. Rev. Lett. 59 (18): 2044–2046. Jachura, M. and Chrapkiewicz, R. (2015). Shot-by-Shot Imaging of Hong–Ou–Mandel Interference with an Intensified sCMOS Camera. Opt. Lett. 40 (7): 1540–1543 Lopes, R. et al. (2015). Atomic Hong–Ou–Mandel Experiment, Nature. 520 (7545): 66–68. Kaufman, A. M. et al (2018). The Hong-Ou-Mandel Effect with Atoms. ArXiv.org, 67, 377-427. Alternatively: Kaufman, A. Kaufman, A. M. et al (2018). The Hong-Ou-Mandel effect with Atoms. In: Advances in Atomic, Molecular, and Optical Physics. Academic Press. Volume 67. 2018, Pages 377-427. Kobayashi, T. et al. (2016). Frequency-Domain Hong–Ou–Mandel Interference. Nature Photonics. 10 (7): 441–444. Restuccia, S. et al. (2019). Photon Bunching in a Rotating Reference Frame. Phys. Rev. Lett. 123(11) Hacker, B.et al, Deterministic Creation of Entangled Atom-Light Schrodinger-Cat States, Nature Photonics 13, 110–115 (2019) Aspect, A., Grangier, P. & Roger, G. (1982). Experimental Realization of Einstein-Podolsky-Rosen-Bohm Gedankenexperiment: A New Violation of Bell's Inequalities. Phys. Rev. Lett. 49, 91 Mathematica activities for Quantm Physics (QP) Exploration of functions with parameters applicable to QP Analysis of Wolfram Demonstrations (with Quantum Mechanics) You may be asked to augment or build upon what’s there based on written instruction by instructor Open Source tools in molecular modelling and simulation Dalton, CP2k, Firefly, Gaussian, GAMESS-US, MOLDEN, NWchem, GPAW, Octopus, ORCA, FreeON, PUPIL, VOTCA , BOSS >> QuTiP NOTE: the various mentioned software above can possibly accommodate particular quantum physics interests if deemed practical and constructive. NOTE: will have a look-through with the supporting documentation and articles that elaborate on the applied models and algorithms of chosen software before implementing chosen software. Pursuits will be constructively relevant to lecturing topics. Software chosen must be well understood to fully capitalize on their potential with lecturing topics. Homework --> Some problems will serve as personal review of prerequisite Course level homework will come from text AND other resources. Quizzes --> Quizzes will be based on homework and lectures Exams --> Exams will reflect homework and quizzes. Grading --> Homework 2-3 Quizzes Labs (TBD) 4 Exams COURSE TOPICS: Measurement Theory Superposition Collapse of wave function Measurement Theory II Role of observer Paradoxes: EPR, etc. Resolution for paradoxes Charged Particle in Magnetic Field Review of classical problem of particle in magnetic field Gauge invariance Charged Particle in Magnetic Field II Bohm-Aharonov effect Landau levels Integer Quantum Hall effect Time-ind. Perturbation Theory I Small perturbation of a quantum system DC Stark effect (quadratic) Degenerate perturbation theory Time-ind. Perturbation Theory II Fine structure Hyperfine interaction 21 cm line in H Atomic Structure I Variational principle Ground state of He He excited states Pauli revisited Atomic Structure II Atomic structure systematics Be-C sequence H2 molecule Time-dependent Pert. Theory. I Two-level system Stimulated emission Fermi Golden Rule Time-dependent Pert. Theory II Spontaneous decay--Einstein argument Decay of excited hyperfine state in H Scattering Theory I Kinematics of scattering Optical theorem Born approx. (weak scatt.) Low energy limit Scattering Theory II Central force & pseudopotential Coulomb scattering Partial wave expansion s-wave scattering Hard spheres Scattering Theory III Absorption Resonant scattering t-matrix Quantum Computing From prerequisite to this course, what applies tangibly to QC? You don’t want to learn all prior then feel stupid about what QC is. Final Note: a chemist should not make fun of physicists about Molecular Modelling, because it all comes from Quantum Physics (and Computational Physics) for them to be able to compute, plot or simulate anything. Many physicists just don’t have the time to deal with all those species of molecules that are not dominant or fundamental in the universe. Prerequisite: Quantum Physics I Particle Physics I: This course is an introductory course in elementary particle physics (i.e. high energy physics or HEP) to cover a broad spectrum of the subject including accelerators and detectors; real data and its analyses. Students apply materials that they have already acquired (Modern Physics, Quantum Mechanics, Differential Equations, etc.) to theoretical framework of particle physics. Then examine from literature and professional data sources, and experimental techniques on how to conduct research in particle physics. Students also recognise the Interconnection between particle physics and cosmology. Course will be least 2 hours per lecture having 2-3 lectures per week for 15-18 weeks. Textbooks --> Modern Particle Physics by Mark Thompson Collider Physics, by Barger and Phillips Particle Physics by B. R. Martin, G Introduction to High Energy Physics by D. H. Perkins Quarks & Leptons: Introductory Course in Modern Particle Physics by Halzen & Martin Resources --> Physics Open Lab (take it seriously): https://physicsopenlab.org NOTE: some of the labs found at such site may be substitutes or augmentations for the given detailed labs described later on. Tools --> Geant4 Virtual Machine + Geant4 ROOT (and possibly ROOT R package) USPAS Code Downloads: https://uspas.fnal.gov/resources/downloads.shtml SPENVIS (quite robust in applications for various fields) NISTXCOM: Photon Cross Sections Database NIST Electron-Impact Cross Sections for Ionization & Excitation Database NIST database of cross sections for inner-shell ionization by electron or positron impact Mathematica Lab Topics --> Means to work or intern or whatever at CERN (and Fermilab) is a “complicated” process. Are you an engineer or machinists or programmer? Otherwise, unless you are considered an elite among the elites in physics with practical skills to be there, it’s all a waste of money and time. Furthermore, CERN and Fermilab serves the academic public, else its purpose would not be clear. Authenticity and quality in experimental data is generally open to the public so that the brightest minds in the world (whoever they are) can stimulate or catalyse progression. Anything other would be monstrous rent seeking or negative externality or market failure and rat nest with function beyond my comprehension. So, it doesn’t matter if you’re confined to Skid Row Los Angeles or a “Buy Bust” slum in the Philippines; CERN and Fermilab can still be useful to you. Be happy it’s not Amazon Corp. or something like such. 1.Electromagnetic momentum and the relativistic dispersion relation (RDR) How would we model electromagnetic waves carrying momentum based on Faraday-Maxwell physics? Is prior equivalent to momentum found via Planck’s constant and wavelength? Pulling force and pushing force: Minkowski versus Abraham Minkowski H 1908 Nachr. Ges. Wiss. Göttn. Math.-Phys. Kl. 53–111 Abraham M 1909 Rend. Circ. Matem. Palermo 28 1 Identify experiments that verify Minkowski’s pulling force and pursue implementation Li Zhang et al (2015). Experimental Evidence for Abraham Pressure of Light. New Journal of Physics. 17 053035 Analyse and pursue experiment replication Radiation pressure in space Comet trajectory perturbations. Will pursue means of determining radiation pressure on comets and/or satellites based on trajectory data and/or accelerometer data in the solar system; hopefully any other influences can be isolated from radiation pressure (such as atmospheric drag, various gravitational influences, etc., etc.). Probes throughout the solar system may also be applicable with their data. Relativistic dispersion relation (RDR) Origins and purpose Derivation methods based directly on physics Is momentum observed in RDR the same as momentum of electromagnetic waves? 2.Nuclear Energies PART A- Binding Energy Review The relativistic energy expression is the tool used to calculate binding energies of nuclei, and the energy yields of nuclear fission and fusion. How did this come to be? It’s found that the mass of a nucleus is always less than the sum of the masses of its constituent neutrons and protons (nucleons). What is the reason for this? PART B- Developing plots (mass number - MeV): For binding energy of nucleon (for the periodic table) Nuclear fission (for the periodic table) List of exotic particles Both fission and fusion cases Note: if you resort to whatever lookup databases you will still have to analytically confirm such. Certain radioactive elements emit specific particles for whatever reasons, hence with pursue determination of their energies; recoil energies may also be an issue. 3.Nuclear Decay Radioactive decay differential equation (RDDE) development and properties How is the RDDE relatable to discrete time stochastic processes (both Waiting and Poisson)? How does the Z distribution become relevant here? Geiger Counter Experiments and The Statistics of Nuclear Decay The radioactive decay chain 4.Measuring mass of electrons and protons Note: also an active lab 5.Cloud Chamber for exotic particles (premature activity) Will be developed. Scaling the chamber. Cameras (picture taking, video recording) subject to the scaling of the chamber, etc. etc. Identifying tools or methods used to detect what’s there. 6. Properties of elementary particles Part I: General requirements Basics of the Standard Model of particle physics; elementary particles and their properties: decay modes, lifetime, quantum numbers; strong, weak and electromagnetic interactions; relativistic kinematics, particle detectors and accelerators. The bubble chamber: experimental setup; analysis of events: Determination of the magnification; stereo-shift method; analysis of particle tracks: charge and momentum of particles by measuring the curvature and the range, specific energy-loss/ bubble density Using bubble chamber films (coming from CERN or Fermilab or wherever) concerning 24GeV proton-proton reactions, single events have to be analysed and the total cross section has to be determined. pp interaction: Elastic and inelastic scattering, cross sections; multiplicity, conversion of photons into e +e − pairs, radiation length. Part II: Properties of proton-proton interactions using a 24 GeV/c proton beam. Note: it may be the general case that a 24 GeV/c proton beam will not be accessible for active operations. Nevertheless, importantly to establish the operations logistics with such laser experiment. Data from results are generally accessible from CERN or Fermilab or wherever to at least competently pursue interests. A. Measure the total and estimate the elastic cross section in pp interactions using 50 events: Count the number of primary interactions as well as the number of incoming protons. Determine the z-distribution of the incoming protons (depth distribution of the protons in the bubble chamber). Calculate the total cross section. Give an estimate of the elastic cross section. B. Determine the most probable inelastic process (50 events). What is the typical slope of an elastic interaction? Why can you determine only a small fraction of all elastic interactions? Measure the average charged multiplicity for inelastic interactions. Estimate the average number of π 0 per event using the number of converted photons associated with the primary vertex. Redo the calculation using the charged multiplicity and compare the results. Part III: Weak decays A. Measurement of the momentum of the νµ in a decay π → µνµ. Find a π − µ − e-decay with the pion decaying at rest. This should be verified by measuring the pion momentum with the sagitta-method. Determine the decay length of the pion by measuring the length of the track. Compare your results with the decay length determined from the momentum measurement using the energy loss. Do a rough correction of the pion momentum by accounting for the energy loss due to the measured decay length. The selected event can only be used for the subsequent analysis if the pion is decaying at rest! Determine the momentum of the muon using the momentum-decay-length relation. Calculate the muon-momentum and compare your result with the measurement. B. Pair production and decay of strange particles. Analyze the kinematics of a proton-proton interaction where a strange neutral particle (V 0 ) is produced and try to identify the V 0. Search the film for two V 0 -decays where the V 0 is associated with the primary vertex of the event. Determine the three-momentum of all decay products and the decay length of the V 0. Prove that the V 0 is associated with the primary vertex. Try to identify the V 0 . Make use of the invariant mass between the decay products (for different particle hypotheses), the decay length, the density of the bubbles and (if possible) the momentum-decay-length relation. Try to identify all particles coming from the primary vertex using conservation of momentum, energy and quantum numbers. 7.Electron-Positron Pair Production Theoretical obligations: Calculate the threshold photon energy for pair production from a free electron Compute the threshold photon energy for pair production from interactions with the photons that constitute the cosmic microwave background radiation (CBMR). Identify the CBMR blackbody temperature. This process limits the transparency of the universe for high energy photons. Peralta, L. (2006). A Simple Electron-Positron Pair Production Experiment, American Journal of Physics, Volume 74, Issue 5 Alternative to prior: http://instructor.physics.lsa.umich.edu/adv-labs/Pair_Production/PairProd_writeup_v5.pdf 8.Determine the muon lifetime https://www.physlab.org/wp-content/uploads/2016/04/Muon_cali.pdf https://www.physics.uci.edu/~advanlab/muon.pdf https://www2.ph.ed.ac.uk/~muheim/teaching/projects/muon-lifetime.pdf 9.Analysis of Z0 Decays Experiment is an introduction to modern analysis methods in high energy physics. Data collected from e+e − collisions with the OPAL detector at the LEP collider are analysed with a computer. The analysis strategy is optimized with the help of simulated events. Prerequisites for lab: Elementary particles and their properties, symmetries and conservation laws, standard model, scattering reactions and their angular dependence, s- and t-channel reactions, Feynman diagrams, unification of electromagnetic and weak interactions. Interaction of particles and matter, particle accelerators and detectors, (esp. the OPAL detector). Statistical analysis, χ 2 test, weighted mean, Breit-Wigner distribution. Part I: Graphical analysis of Z0 decays. In the first part of the experiment you will get acquainted with the different decay channels of the Z0 -boson on an event-by-event basis. You are supposed to learn how to find characteristic properties which allow to distinguish between the various final states. To achieve this, the signatures of the various processes and the detector properties must be understood thoroughly. Part II: Statistical analysis of Z0 decays. Using the knowledge achieved in the first part a large data sample is analysed. The resonance parameters of the Z0 boson (cross section, mass, decay width) are measured in various decay channels. The Weinberg angle is measured from the forward backward asymmetry of the reaction e+e − → µ +µ −. Lepton universality is to be verified and the number of light neutrino generations should be determined. The data samples for the second part were made using a preselection in data and Monte Carlo events. This has to be taken into account as a correction when determining the cross sections. The correction factor is the ratio of the number of generated Monte Carlo events and the number of events in the corresponding n-tuple. I.e.: for the τ Monte Carlo 100000 events were generated, 79214 events pass the preselection cuts Correction factor: 100000/79214 = 1.262 There are 6 different data samples. The corresponding luminosities are listed in the table below. The data sample that you will use is chosen by the lab assistant. Will have radiation corrections as well 10.ATLAS Experiment This laboratory exercise introduces you to the physics at the Large Hadron Collider. The main focus is on physics processes that are investigated by the ATLAS experiment. In 2008 the ATLAS detector started to collect data. Until sufficient amounts of data are available, the exercise will be based on simulated data, which are a good representation of what we can expect at the LHC. Data analysis will be the main focus of the exercise. Students should be familiar with relativistic kinematics, symmetries and conserved quantities, the Standard Model, properties of W± and Z 0 bosons. Students will work on assignments 1 and 2 and either assignment 3 OR 4. Assignment 1 (Event displays): This assignment allows you to become familiar with the ATLAS detector and to learn about the characteristics of LHC collisions as recorded by the detectors. For this you study graphic representations, so called event displays, and work on introductory tasks. Assignment 2 (Calibration of electrons): As electrons play an important role in the last two parts of this experiment the measurement of the electron energy is calibrated. To do so the data analysis software ROOT is used. Assignment 3 (Measurement of the W± boson mass): Based on the previous assignment, the mass of the W± boson in the decay channel, being the case of W− → e −ν¯e is measured. Assignment 4 (Search for new physics): In this part of the experiment, events with four leptons are investigated. In addition to Z 0 pairs there are numerous scenarios for new physics, which can contribute to this final state. Students study the kinematic properties of Z 0 pairs and search for signs of new physics. 11.Computational Tools Skills What can Mathematica do for you in Particle Physics? The ParticleData and investigation of its parameters Means of data analysis with such function ROOT (and possibly ROOT R package) Moderate immersion with data analysis similar to Mathematica prior 12.Liquid Scintillator Detector Two or three will be developed and put to use with groups. 13. Accelerator Development and Codes Simulation of closed circuit magnetic fields via FEM and FEA Permanent magnet (spheroidal, cuboid, ring discs, cylindrical) Augment prior with magnetics in rows to produce an accelerator For particle with charge X and mass Y develop the acceleration, velocity and trajectory models Electromagnetic counterpart to priors Augment with: Sogabe, Y., Yasunaga, M. & Amemiya, N. (2020), Simplified Electromagnetic Modelling of Accelerator Magnets Wound With Conductor on Round Core Wires for AC Loss Calculations. In IEEE Transactions on Applied Superconductivity, vol. 30, no. 4, pp. 1-5, Art no. 4004005 S. Russenschuck. Design of Accelerator Magnets. CERN, 1211 Geneva 23, Switzerland Codes for pursuit USPAS Code Further resource for accelerator physics codes -- https://en.wikipedia.org/wiki/Accelerator_physics_codes For chosen code will first have analysis of supporting documentation or literature. Followed by development with chosen code. 14.Strong Immersion into Geant4 Virtual Machine + Geant4 Such software is often the only means for many getting close to any particle accelerator with premier experiments. Will have analysis for the use of such software. Will investigate some of the models, algorithms and monte carlo techniques via supporting documentation and academic articles. Will then simulate well known and premier experiments. Will be AT LEAST three weeks. 15.SPENVIS Software has many uses such as safety operations of electronics in space, atmospheric bombardment, etc., etc. Specific files and databases need to be called or inserted for interest with use. Grade --> Homework Assignments 2-3 Quizzes 2 Midterms Labs Final Course Outline --> WEEK 1-4: Review of wave functions relative to position and angular momentum Review of spin and quantum entanglement Properties and characteristics of spin and entanglement Relativistic Kinematics Particle Decays Feynman Diagrams, LHC Introduction to Particle Physics (Chap. 1) - Why High Energy? Standard Model (SM), Particle classification, Particles and antiparticles Lepton flavours, Quark flavours, Cosmic connection Parton Distribution Functions – Structure of Proton Symmetries and Quarks - Conservation Laws (Chap. 2) WEEK 5-8: Antiparticles (Chap. 3) Electrodynamics of Spinless Particles (Chap. 4) Dirac Equation (Chap. 5) Electrodynamics of Spin-½ Particles (Chap. 6) WEEK 9-12: The Structure of Hadrons (Chap. 8) Building Cross Sections (Chap.8 extended) Weak Interactions (Chap. 12) Electroweak Interactions (Chap. 13) WEEK 13-15: Gauge Symmetries (Chap. 14) Physics beyond the SM (Chap. 15) Prerequisites: Methods of Mathematical Physics, Modern Physics, Quantum Physics I & II, Mathematical Statistics Particle Physics II: Second course in the Particle Physics sequence. There will be attempt to avoid any abrupt immersion into advance topics without having prerequisite topics relevant in foundation. For topics introduced in prerequisite there will be good effort to place or situate the theory, learnt models under whatever appropriate conditions towards the new topics in this course; such a policy likely to be reflected on quizzes and exams. Course will be least 2 hours per lecture having 2-3 lectures per week for 15-18 weeks. Textbooks --> Modern Particle Physics by Mark Thompson Collider Physics, by Barger and Phillips. Particle Physics by B. R. Martin, G. Introduction to High Energy Physics by D. H. Perkins Quarks & Leptons: Introductory Course in Modern Particle Physics by Halzen & Martin Tools --> Geant4 Virtual Machine + Geant4 ROOT (and possibly ROOT R package) USPAS Code Downloads: https://uspas.fnal.gov/resources/downloads.shtml SPENVIS (quite robust in applications for various fields) NISTXCOM: Photon Cross Sections Database NIST Electron-Impact Cross Sections for Ionization & Excitation Database NIST database of cross sections for inner-shell ionization by electron or positron impact1 Mathematica Resources --> Physics Open Lab (take it seriously): https://physicsopenlab.org NOTE: some of the labs found at such site may be substitutes or augmentations for the given detailed labs described later on. Labs --> Will have advance repetition of chosen labs. Some labs from prerequisite will be augmented to have relevance to current course topics. May also have new labs included. The given resources will also serve well. Homework --> Constituted by both prerequisite exercises and exercises appropriate for this course. Quizzes --> Quizzes will reflect homework Exams --> Will reflect homework and quizzes Grade --> Homework Assignments 2-3 Quizzes 2 Midterms Labs Final Course Outline --> --Field Lagrangian (scalar, spinors, vectors) --Symmetries and conservation laws (E, p, L, P-parity, C-parity, T-invariance, CP, CPT, Isospin, G-parity) --Building QED and its phenomenology (running α) --Building QCD and its phenomenology (running α’s , confinement, jets) --Building Weak Force and its phenomenology (P-parity violation, quark mixing, CP-violation) --Problem of masses, Higgs boson and its phenomenology, discovery prospects --Neutrinos revised (mass, oscillations) --Beyond the Standard Model (GUT, SUSY, extra dimensions, strings) Prerequisite: Particle Physics I Introduction to Astronomy: Course is the first crucial environment towards developing competency, professionalism, relevance and sustainability in astronomical studies. Course serves to benefit its constituents, and no direction nor nutrition towards urban and minority domains labeling. Such a policy will be vehemently reinforced. The course includes classroom lectures and discussion, indoor laboratory work, data analysis, and outdoor telescope observations. Course grade: Labs Field observation Assignments 3 Exams Dependent on the severity of conduct infractions, conduct percentage of final grade may warrant amplification to 69%. Essential tools --> Graphical Astronomy & Image Analysis Tool (GAIA), DS9 & OSCAAR SPLAT/SPLAT-VO Necessities --> I. Astronomy Almanacs/Calendars II. Celestial atlases and Catalogues III. Data from observatories and satellites Quantitative observation Resources (photometry, radio, UV, X-ray) IV. NASA HEASARC software and NASA HEASARC Astro-Update. V. Google Sky With Google Sky knowledge of coordinates and/or name of celestial body or interstellar object. Google Sky usage doesn’t replace field activities and labs nor the software mentioned for operations. VI. Mathematica Astronomical Computation & Data Astronomy & Space Entities Rewarding Mathematica functions: AstronomicalData, StarData, PlanetData, PlanetaryMoonData, MinorPlanetData, CometData, ExoplanetData, GalaxyData, StarClusterData, NebulaData, SupernovaData, PulsarData. Each function has its unique range of parameters to be knowledgeable about. Such functions can be subjugated or embedded into more sophisticated codes. Regardless, it’s also important to learn how to access, introspect and query data from professional sources. VII. Wolfram Demonstrations. One should also take advantage of Wolfram Demonstrations with subject areas categorized. Note: such resources serve to augment instruction, assignments, labs and activities in this syllabus Outdoor observatory field activities AND labs --> Essential towards development in self-sufficiency with discovery and authentic research. Google Sky can accompany the field exercises towards confirmation of objects observed. Course Outline --> 1. Inverse square law of light. Laws for telescope optics. 2. Solar Observation --Position of the Sun in a geocentric perspective --Determining the curvature of the Earth (activity-based) A. Eratosthenes experiment B. https://www.astro.princeton.edu/~dns/teachersguide/MeasECAct.html --Calculating sunrise and sunset --Sun’s position A. Calculating the Sun’s position Walraven, R. (1978). Calculating the Position of the Sun. Solar Energy. Volume 20 , Issue 5, pages 393 – 397 Kalogirou, A, Solar Energy Engineering, Chapter 2: "Environmental Characteristics." pp. 51-63. Reda, I. and Andreas, A. (2003). Solar Position algorithm for Solar Radiation applications. NREL Report N. Tp-560-34302, Revised January 2008 https://www.aa.quae.nl/en/reken/zonpositie.html B. SunPosition function in Mathematica to explore the following: Position of the Sun for a specified latitude/longitude and date Augment with TimeSeries function in Mathematica Interested in the last 20 years, each treated uniquely Equator (0°) Tropic of Cancer (23.5° north) Tropic of Capricorn (23.5° south) Arctic circle (66.5° north) Antarctic circle (66.5° south) North Pole (90° north) South Pole (90° south) Latitude of interest For each time series identify and seasonality and cyclic trends. For each season for each year determine a unique analytic function for each time series. Can such data verify Earth’s curvature? --Eclipses (solar and lunar) Modelling eclipses activity Catalogue of eclipses (solar and lunar) Calendar of future events 3. Heliocentric Model Development --Empirical studies: Mars retrograde about the constellations (Opiuchus, Scorpius, Libra, Virgo) Will acquire high volume of frames in chronological manner Will simulate and/or interpolate Mar’s orbit to capture timing of turning points to match with retrograde characteristics Earth retrograde about the constellations (Ares, Taurus, Perseus, Auriga) Will acquire high volume of frames from the Curiousity Rover Will simulate and/or interpolate Earth’s orbit to capture timing of turning points to match with retrograde characteristics --Earth seasons due to orbit and tilt Earth’s orbit around the Sun as the mechanism for seasons. Identifying the equinoxes and solstices; angle between rotation axis and north pole during such events. Position of the north star during such events and seasons. Identifying the major lines of latitude and the amount of solar radiation exposure for each major line of latitude for a respective season. --Measuring Earth’s tilt Experiments to pursue A. Işıldak R. S. (2009). A Hammer and Nails are just the Tools to Measure the Earth’s Axial Tilt. Physics Education. 44, 225 – 6 B. Isildak. (2016). Measuring the Tilt of the Earth’s Axis with the help of a Plastic Pipe and a Piece of Wood. Physics Education, 51(2), 25002– C. Isildak, Küçüközer, H. A., & Isik, H. (2017). Measuring Earth’s Axial Tilt with a Telescope. Physics Education, 52(3), 33003– D. The 5 major lines of latitude and relation to Earth’s tilt. Will have field experiment using a vertical pole with its casted shadow, and applying some trigonometry. Will be done every three days for the whole semester; identify value of convergence. Will also be gathering data for The distance between Earth and the Sun Angle with Polars, Vega, Alpha Draconis and Demeb, respectively. Will develop a model comprising of all such data sets. 4. Constellations, and position of the stars towards determination of latitude on Earth from the (circular) path of stars in the night sky for a determined duration. Excluding the earth curvature question what was done with data for sun position in module (2) can likely be done for stars with coordinates over time. Pursue such. For 10-15 chosen stars (Polaris must be included) will gather position data of w.r.t. from different astronomy viewing stations across the world. What are the conic sections observed based on the eccentricity formula? Do any of the paths intersect? Why is/isn’t there intersections? 5. Precessions, Charting and Location --Axial precession (not perihelion precession), A. Precession around the north ecliptic pole and south ecliptic pole. Comprehension for the cause(s) of changing pole stars and such precession is expected as well. What field experiments can be applied to verify such occurrences? B. What modelling can represent the following physics statement? Being an oblate spheroid, Earth has a non-spherical shape, bulging outward at the equator. The gravitational tidal forces of the Moon and Sun apply torque to the equator, attempting to pull the equatorial bulge into the plane of the elliptic, but instead causing it to precess. C. What is the difference between the precession rate and the spin rate about the axis of symmetry in terms of formulas/equations? D. Can the rate of tilt be modelled via (B) and/or (C) or something else? --Equinox Precession A. Concept. Comprehension for the cause(s) of such shift. B. What field experiments are applied to confirm such. Descriptions of such experiments. C. Westward shift of the vernal equinox among the stars over the chosen years. To be modelled. --Means of determining our location in the Milky Way Galaxy; will administer multiple method(s) to acquire such. --Means of determining the shape of the Milky Way Galaxy; will administer method(s) to acquire such. 6. Advance treatment of the SI system, solar, light year, parsec astronomical unit scales. Parallax principle and its accuracy limit. 7. Advance treatment coordinate systems in astronomy and conversions 8. Classical Gravitation A. Newton’s law of gravitation. Determining the mass of the sun without specifically knowing the mass of Earth (using gravitational force and centripetal force). B. Developing Kepler’s laws (only the law of orbits will not be encountered in any testing). Characterising a Keplerian Orbit. Do all major celestial bodies and satellites in the sola system abide by the Keplerian orbit model? For a non-Keplerian orbit identify the conditions for the eccentricity, semi-major axis, and associated conic section. How does one determine the eccentricity and semi-major axis of an orbit? Followed by activities for such. Determine the mass of the sun by Kepler’s law of periods and compare with what was found in (A). The general form of Kepler’s law (adding of masses) not being cooperative with such methods of finding a body’s mass. C. Derivation of the Newtonian Orbit Shape equation as a second order ODE and its solution. Determination of bound and unbound orbits. From the solution of the orbit shape equation determination of the apsis, towards finding the periapsis and apoapsis. D. Orbital velocities of the planets (and Pluto) as a function of their distance from the Sun (semi-major axis in AU) yielding Keplerian rotation. 9. The planets of the Solar system History of the discovery of the planets and the primitive methods applied to detect them. Verification of apparent reversal of motion (retrograde motion) observed with planets in the backdrop of stars. What modern methods do we have today that are fundamentally similar to primitive ancient methods prior? Will have actual field activity towards actual observation of the planets with telescopes based on respectable analysis from astronomical calendars and procedures. Overview of the major characteristics and anatomy of the planets. Observation of extraterrestrial atmospheres and and anatomy: Mars, Jupiter and its satellites (include rings, Europa, Callisto and Ganymede), Saturn (rings and Titan moon), Uranus (including its rings) and Neptune (including its rings). Transit method may be actively administered if scheduling fits. Modelling gravitational assists scenarios in the solar system Modelling and simulation The Hill Sphere and Roche limit 10. Sun activity Sun spots, corona plumes, solar prominence, coronal mass ejection Physical and chemical measures (size, speed, temperature, composition) Data analysis applicable whichever capable Times series (occurrence, intensity/strength) Space weather for Aurora Borealis and Aurora Australis Determinants for forecasting Aurora strength and visual range Tools and models for such will be introduced and applied 11. Computation of Ephemeris. Finding orbits of asteroids: the six orbital elements that uniquely define the orbits Instructor primary pursuit is use of structured radio telescope(s); else instructor is to convey sporadic confirmed data for students to “extrapolate” on. To be credible in astronomy use of telescopes is inevitably essential. A. Process: choosing the asteroid, observing the asteroid at different times; then least squares plate reduction (LSPR) to be expressed as programmed; followed by orbit determination to find the orbital elements that describes the asteroid’s orbit via Gauss’ method for orbit determination expressed and programmed involving taking data from observations. Note: observation of asteroid of choice to be consistently recorded for a determined period, leading to a chronological animation w.r.t stars in the background. Also, simulation code to be developed where parameters are allowed to vary. B. Acquire authentic professional observation data (from ESA, NASA, higher education institution, etc.) to be situated in the space of the determined orbit, with the major solar orbits identified if scale is reasonable. How accurate or consistent is the predicted orbit from (A)? C. If such an asteroid orbit determination method was applied to the moon or heliocentric planets, would there be high consistency with Kepler’s laws based on established data of the moon and planets? D. Pursue orbits of the planets in the solar system as well. 12. Read the following: Emily Lakdawalla’s web article, “How Radio Telescopes Get Images of Asteroids”, The Planetary Society, April 29, 2010. A. Consider a 3D coordinate frame towards identifying points of the body based on the reflection-time scheme. Create a (smooth) simplex of body construction from points based on data. B. Critical thinking: considering various similar radio telescopes at various distances around the world in the same hemisphere (either north or south) all able to observe well an asteroid for a designated duration; each radio telescope is accompanied by an accurate clock. Clocks are synchronized and all observations begin at precisely the same time. Can gathered data from all observations be decently integrated w.r.t a decided upon coordinate frame? It’s believed that a respective radio telescope can acquire data elements unique to the data of the other radio telescopes elsewhere; to identify a data “span”. Will pursue data from radio telescopes in such a setting, and find whether shape determine is much more accurate than what is done in (A). 13. Solar System Remnants A. Asteroid belts B. Kuiper belt Bernstein, G., and Khushalani, B., Orbit Fitting and Uncertainties for Kuiper Belt Objects, THE ASTRONOMICAL JOURNAL, 120: 3323 - 3332, 2000 December. Students will choose two or three well known constituents of the Kuiper belt, acquiring data on and properties, located positions at particular times, and employ model(s) in journal article, applying the relevant data. Assuming conic sections, identify the significant points of the conic sections as a means to compare with predicted orbit trajectories from professional institutions or entities. Will also apply the methodology from (11) and compare with such to observe differences in orbit. Kenyon, S. J., and Bromley, B. C., The Size Distribution of Kuiper Belt Objects, The Astronomical Journal, 128: 1916–1926, 2004 October Will acquire data for numerous bodies in the Kuiper belt and try to match parameters of placed to the prediction models in the journal article. C. The Oort cloud (computational exercises with comets and the orbits/trajectories that support this theory). Additionally, will try observation field activities if capable. 14. Locating the centre of the Milky Way galaxy and location of the solar system from astronomical maps with respect to constellations (student activity). Can one conceive such a location (of the centre of the Milky Way galaxy) based on optical telescope observation of constellations and Milky Way band? Based on findings from astronomical maps with respect to constellations students will pursue field observation with “optical” telescopes towards vindication with confidence. 15. Astronomical catalogue(s) overview and field observation of astrophysical bodies A. Optical telescope field observation of cosmic dust, galaxies, nebulae, proto-stars, planetary nebulas. Einstein rings & cluster arcs. B. Radio telescope field observation There will be exercises of distance determination, comparing with established data; such as distance(s) of the moon, sun, and other astrophysical bodies. Finding the temperature of the sun and other bodies. Presence of Pulsars (and possibly) Quasars/Blazars. 16. Further mass determination methods A. Determining the mass of a gravitational source from application of the Einstein ring; considerable lensing is considered. B. Deflection of light by gravity, namely, 2*(Schwarzschild radius/r) for determination of mass. Compare such with Einstein ring result C. Approximating the mass of a star on the main sequence by luminosity: apply luminosity formula to sun and main sequence star in question, then apply approximation formula concerning the ratio of a main sequence star in question and the sun concerning their masses. Solve for the mass of the main sequence star in question. D. Compare all results with (A) and (B) in module (8) if such are relatable. 17. Star classification How did we come to view the Sun as a star, or how was it determined that many or most stars should look like the Sun? Hertzprung-Russel diagram Can all characteristic properties be described by only two equations, namely, the Stefan-Boltzmann Law and Mass-Luminosity relation? To demonstrate for: Distance, Size, Power, Temperature, Lifetime Is the H-R diagram based solely on those two equations? 18. Electromagnetic spectrum, Blackbody and Applications. 19. Photometry in Astronomy Will introduce the methodology and logistics of modern photometry in astronomy. Such will be followed by field activities concerning finding luminosity, distance and temperature via analysis with use of software (GAIA, DS9 and OSCAAR in field activities); results to be compared with established professional data. 20. Spectral lines: A. Review of laws relevant to electromagnetic waves and emissions B. Hydrogen as the most abundant element in the universe. C. Doppler effect, and use to calculate precisely how fast stars and other astronomical objects move toward or away from Earth or each other. D. Doppler effect For determination of radial velocities Discovering solar planets, exo-planets. Black holes (motion of hydrogen in accretion discs around them) E. Tinetti, G., Encrenaz, T. and Coustenis, A., Spectroscopy of Planetary Atmospheres in our Galaxy, Astron Astrophys Rev (2013) 21: 63, Springer Text, pp 1 - 65 F. Spectroscopy of exoplanets Transmission Reflectance Thermal emission spiff.rit.edu/classes/resceu/lectures/spectra/spectra.html Will acquire raw data from professional sources to intimately analyse/model and draw conclusions, and compare with accepted knowledge by the consensus in the field. Concerns orbit ecentricity, orbital velocities, radial velocities, size and atmospheric composition. Raw data of planets within the solar system towards development can be a starter before exoplanets. G. Balmer series for determination of distances between galaxies. Exercises with raw data H. Balmer series and formula for determination of surface temperature of stars, surface gravity Exercises with raw data I. Rydberg formula and composition of stars and planets Exercises with raw data. 21. Spectral analysis with radio telescopes A. Review of methodology and logistics for radio telescope usage towards astrophysical observation. Followed by corresponding field activities with celestial objects. B. Methodology & logistics for spectroscopy with SPLAT/SPLAT-VO; may or may not have to develop a specific file format before use with SPLAT/SPLAT-VO. Followed by corresponding field/lab activities. Results to be compared with data from professional databases integrated into resourceful SPLAT/SPLAT-VO. 22. Scale of the universe and red-shifting The website has various links where one should develop a logical plan of knowledge succession with such links < hyperphysics.phy-astr.gsu.edu/hbase/Astro/hubble.html > Prerequisites: General Physics I & II, ODE, Numerical Analysis, Calculus III Techniques in Observational Astronomy I Course focuses on the fundamental principles and techniques used in planning, making, reducing, and analysing modern astronomical observations. Course to have strong focus on connecting with the knowledge and primitive experience from “Introduction to Astronomy” course. The course includes classroom lectures and discussion, indoor laboratory work, data analysis, and outdoor telescope observations. The material covered provides an introduction to numerical treatment of observations, CCD imaging, digital image processing with Graphical Astronomy and Image Analysis Tool (GAIA) or DS9, OSCAAR and spectroscopy (SPLAT-VO). Course grade: Labs Field observations Assignments 3 Exams Dependent on the severity of conduct infractions, conduct percentage of final grade may warrant amplification to 69%. Essential tools --> GAIA, DS9 and OSCAAR SPLAT/SPLAT-VO Necessities --> I. Astronomy Almanacs/Calendars II. Celestial atlases and Catalogues III. Data from observatories and satellites Quantitative observation Resources (photometry, radio, UV, X-ray) IV. NASA HEASARC software and NASA HEASARC Astro-Update. V. Google Sky With Google Sky knowledge of coordinates and/or name of celestial body or interstellar object. Google Sky usage doesn’t replace field activities and labs nor the software mentioned for operations. VI. Mathematica Astronomical Computation & Data Astronomy & Space Entities Rewarding Mathematica functions: AstronomicalData, StarData, PlanetData, PlanetaryMoonData, MinorPlanetData, CometData, ExoplanetData, GalaxyData, StarClusterData, NebulaData, SupernovaData, PulsarData. Each function has its unique range of parameters to be knowledgeable about. Such functions can be subjugated or embedded into more sophisticated codes. Regardless, it’s also important to learn how to access, introspect and query data from professional sources. VII. Wolfram Demonstrations. One should also take advantage of Wolfram Demonstrations with subject areas categorized. Note: such resources serve to augment instruction, assignments, labs and activities in this syllabus Outdoor observatory field activities AND labs --> Essential towards development in self-sufficiency with discovery and authentic research. Google Sky can accompany the field exercises towards confirmation of objects observed. Course Outline --> 1. Basics of Observational Astronomy: History, Coordinates and Time, Planning Observations, Atmospheric Effects, Sky Brightness 2. Advanced recital of modules 6 through 8 from prerequisite 3. Acquiring Astronomical Data: Basic Techniques, Calibration Images, Filters, Exposure times, Dithering, Statistics/Errors/Signal-to-Noise (this last topic may or may not be suitable in a later module) 4. Optics and Telescopes: Geometric Optics, Lens Equation, Telescope Designs, Practical Telescope Considerations 5. Detectors: Types of Detectors, Fundamentals of Charge Coupled Devices, Read Noise, Dark Current, Exposure Times 6. Advanced recital of modules 11 and 12 from prerequisite 7. Photometry: A. Magnitude Systems, Photometric Calibration, Impacts of Atmosphere B. Advance repetition of field activities with optical telescopes having CCD cameras integrated towards data development for research. B. Advance review of Hertzprung-Russel diagram and Lifetimes. The mass-luminosity relation (for main sequence stars) and temperature-luminosity relation. C. Computational guide for photometry observation-- web.physics.ucsb.edu/~jatila/LambdaLabs/Globulars/HRdiagramlab_JKV.pdf Student groups will be assigned a particular set of stars, and will pursue data to establish their place in the Hertzprung-Russel model; detailed formulas to be provided (includes using Ballesteros' formula and that sort). If TOPCAT or Mathematica or R is needed, then so be it. For reinforcement of integrity in software (OSCAAR, GAIA, DS9) students will also have activities where they randomly choose 5-15 stars to determine luminosity, distance, temperature and age based on acquired data; comprehension of models and formulas in play is expected. D. Results from (C) above for masses, temperatures, distances and ages by photometry to be compared with established professional data. E. Logistics of modern field photometry in astronomy. Such will be followed by field activities concerning finding luminosity, distance and temperature via analysis with use of software (GAIA, DS9 and OSCAAR in field activities); results to be compared with established professional data. E. The Light Curve (with OSCAAR usage or other ) i. Definition ii. Types of light curves (periodic, Cepheid variables, transiting extra solar planets, aperiodic, star accretion, supernova, occultation, “asteroid”, etc.) iii. Thorough methodology/practical for determining the rotation period of a minor object (minor planet, a moon, comet, asteroid); to be compared with established professional data. iv. Asteroid shapes from light curves. A great accomplishment would be acquiring light curves of asteroids which can be used to determine physical shapes. The following articles provide some insight into acquiring such: Kaasalainen and Torppa, (2001) Optimisation Methods for Asteroid Light Curve Inversion; I. Shape Determination, Icarus 153, 24-36 Kaasalainen, Torppa and Muinonen, (2001) Optimisation Methods for Asteroid Light Curve Inversion; II. The Complete Inversion Problem, Icarus 153, 37-51 Note: articles in the references of such two journal articles may prove highly useful in developing a tangible and fluid practical schemed. Will try establishing light curves from field observation or data from databases and pursue shape determination of asteroids; else data from professional sources to establish light curves is the secondary means. v. Recalling the module (12) from the prerequisite course about Emily Lakdawalla’s web article, with the additional task of the simplex imaging strategy. If the same celestial body in (iv) is chosen, then compare geometry results in (iv) with simplex imaging strategy. vi. Transit data are rich with information. By measuring the depth of the dip in brightness and knowing the size of the star, scientists can determine the size or radius of the planet. The orbital period of the planet can be determined by measuring the elapsed time between transits. Once the orbital period is known, Kepler's third law of planetary motion can be applied to determine the average distance of the planet from its star(s). vii. Traub, W. A, and Oppenheimer, B. R., Direct Imaging of Planets, Exoplanets, edited by S. Seager. Tucson, AZ: University of Arizona Press, 2010, p.111-156. Will develop the walk-through logistics for field observation. 8. Spectroscopy Includes point and region spectra extracted from cubes, and Spectral Analysis Tool-Virtual Observatory (SPLAT/SPLAT-VO) for astrophysical objects via data sources. A. Doppler effect (i). Makes the wavelength of waves from an emitter appear shorter when the source approaches, and longer when the source moves away. Thorough methodology and field practical for measuring the motions on the Sun and other bodies by measuring changes in the wavelengths of emission lines. (ii). Acquirng radial velocity data towards constructing radial velocity versus time curves; pursuing nonlinear curving fitting models (with possbly sinusoidal features). Note: statistical filter or smoothng operation may be required Note: if star doesn’t reside in perfect line of sight the radial velocity isn’t the true velocity but an approximation; orbit of inclination must be known. What information can be extracted from the velocity-time curve, having knowledge of Newton’s law of gravitation, Kepler’s laws of planetary motion, with the conservation laws? (iii). Consider the sun with multiple planets. For a specific time interval acquire the radial velocities data towards constructing (likely sinusoidal) the various radial velocity versus time curves; regression modelling with sinusoidal features. Compare curves towards making a deduction about the massiveness of orbiting “planets”, orbital period, eccentricity, etc. (iv). Discovering exo-planets. This subsection goes beyond an informative treatment. Will use astronomy databases concerning various confirmed exoplanet detection cases via Doppler effect and apply the logistics and modelling for the exoplanet confirmation, respectively. From the velocity-time curve, concerns for the periodic variation in the star’s orbital speed reveals an unseen planet; velocity change (amplitude variation) revealing the star’s speed which in turn tells of the planet’s mass; determining the planet’s orbital period. B. Advance REPETITION of module (20) and (21) from prerequisite course. Confirmation of elements (hydrogen, helium, iron, carbon, oxygen, etc.) via radio telescope observation with SPLAT/SPLAT-VO; to be compared with established professional data. C. Hydrogen line(s) detection field activity The sun may be used as one type of prototypical specimen, and data acquired will be compared to data from professional databases. D. Balmer series and formulas for determination of surface gravity and surface temperature of stars. The sun may be used as one type of prototypical specimen, and data acquired will be compared to data from professional databases. 9. Planet atmospheres A. The most successful method for measuring chemical composition of an Planetary atmosphere is the transit spectroscopy method. Will thoroughly examine the transit spectroscopy method and make use of raw data from databases for such; concerns the logistics, models, astronomical software tools with raw data towards knowledge about a respective exoplanet’s atmosphere. Note: if the opportunity presents itself will have for field labs to take advantage of solar and lunar eclipses as the “great inquisitors” of our comprehension and skills. B. With the occultation technique we can also learn the sizes of smaller bodies that have formed in the outer solar system: Charon, the Centaurs, Esri, Triton and other KBOs. Will thoroughly examine the occulation method and make use of raw data from databases for such; concerns the logistics, models, astronomical software tools with raw data towards knowledge about a respective exoplanet’s atmosphere. Note: if the opportunity presents itself will have for field labs to take advantage of solar and lunar eclipses as the “great inquisitors” of our comprehension and skills. 10. Redshift Advance recital of module 22 from prerequisite Hubble Lab: A. Establishing Hubble’s law and making a Hubble’s diagram to confirm it. Understanding how astronomers/astrophysicist use redshift and magnitude. Galaxy lookup for redshift and magnitude (at least six galaxies). B. Turning direct measurements of galaxy properties into actual measurements or relative distances. Distance of galaxies despite size appearance and intensity level. Observation of clusters of galaxies to determine which galaxies are members of the same cluster. Observation of 3-4 galaxy clusters in the same area of space, and find the relative distances of to galaxies in each in each cluster; will involves different past sets of data to identify any variation in such distances, and to create a model. C. Observing redshifts from data. Then will calculate redshifts themselves and compare with prior. Will then include past sets of data to observe any variation, and to create a model. D. Bringing together the conclusion from (B) and (C) to create a better Hubble diagram. 11. Presenting Astronomical Results: Colour Images, Presentation Skills, Literature Searches 12. Multiwavelength Astronomy (visible, ultraviolet, infrared & X-ray) (i). Identifying technology systems for the various spectra (ii). For each spectrum mentioned will identify usage (iii). For each spectrum mentioned will identify limitations related to Electromagnetic radiation from sources at different temperatures Gas interference Cosmic dust interference Earlier galaxies being more redshifted, Earth’s atmosphere absorbing X-rays and need for space telescopes (iv). Concerning (ii) and (iii) what’s the relation to Wien’s Law and Stefan-Boltzmann Law? Must establish the concise physics for imaging in such wavelengths. Logistics and implementation with data for each wavelength to analyse various astronomical interests (v). Routines carried out towards integration of visual, infrared and ultraviolet wavelengths. Development of a more complete structure, composition and behaviour of distant celestial bodies, objects when three wavelength ranges (visible, ultraviolet, infrared) are applied. Logistics and implementation to analyse various astronomical interests involving the integraton of such three wavelengths. --What can the Fermi Gamma-ray Telescope (or any general gamma ray telescope) provide that’s unique to priors? Technology for gamma ray telescopes. Will also acquire data to analyse various astronomical interests. Namely, logistics an implementation. --Concerning X-ray observation data, If time permits, maybe cross evaluating Chandra data with different sources for consistency if constructive Modelling data Fitting data to formulas/equations X-ray sources ROSAT EXOSAT eROSITA NICER Data Usage/NICERDAS Chandra Observations --> heasarc.gsfc.nasa.gov/W3Browse/chandra/chanmaster.html --Will acquire “raw data” from artificial satellites such as Galileo and intimiately use the data to orchestrate (re)discoveries of atmospheric and physical properties of the moons Callisto and Europa (and others likely in the future). Any spectrographic applications applied must be comprehensively developed concerning the prcessed raw data, validating the outputs. The following guides provide strong assists to pursue such: i. Ionospheric Kliore, A. J.,et al. Ionosphere of Callisto from Galileo Radio Occultation observations, J. Geophys. Res., 107(A11), 1407 ii. Atmospheric Carlson, R. W. et al. (1999). A Tenuous Carbon Dioxide Atmosphere on Jupiter’s Moon Callisto. Science. 283 (5403): 820–821. Liang, M. C. et al (2005). Atmosphere of Callisto, J. Geophys. Res., 110, E02003 iii. Internal structure O.L. Kuskov, V.A. Kronrod, (2005), Internal structure of Europa and Callisto, Icarus, Volume 177, Issue 2, Pages 550-569 Kuskov, O.L., Kronrod, V.A. Models of the Internal Structure of Callisto. Sol Syst Res 39, 283–301 (2005). --Black hole detection with X-Rays Will replicate searches based on raw satellite data towards confirmation. Prerequisite: Introduction to Astronomy Techniques in Observational Astronomy II Course focuses on the fundamental principles and techniques used in planning, making, reducing, and analysing modern astronomical observations. The course includes classroom lectures & discussion, indoor laboratory work focused on application of observational techniques to astronomical research. Students in this class are also expected to become competent with Linux (or compatible OS) and the standard software tools used in astronomical research. GAIA (or DS9), OSCAAR, SPLAT/SPLAT-VO, TOPCAT, Mathematica, R whenever needed. Data Archives (integrable with mentioned software prior). Imaging & Photometry lab(s), Spectroscopy lab(s). Photometry and Spectroscopy treatment generally to be at level of prerequisite. Note: there must be connections to the determination of physical and chemical properties (distance, luminosity, lifetime, mass, radius, temperature, composition, density, rotation, orbit, speed, etc.). Course Assessment --> Assignments (R and Mathematica) Labs Field Activities Research Conduct Research Project Dependent on the severity of conduct infractions, conduct percentage of final grade may warrant amplification to 69%. Essential tools --> R and Mathematica. TOPCAT possibly as well GAIA, DS9 and OSCAAR SPLAT/SPLAT-VO Necessities --> I. Astronomy Almanacs/Calendars II. Celestial atlases and Catalogues III. Data from observatories and satellites Quantitative observation Resources (photometry, radio, UV, X-ray, infrared) IV. NASA HEASARC software and NASA HEASARC Astro-Update. V. Google Sky With Google Sky knowledge of coordinates and/or name of celestial body or interstellar object. Google Sky usage doesn’t replace field activities and labs nor the software mentioned for operations. VI. Mathematica Astronomical Computation & Data Astronomy & Space Entities Rewarding Mathematica functions: AstronomicalData, StarData, PlanetData, PlanetaryMoonData, MinorPlanetData, CometData, ExoplanetData, GalaxyData, StarClusterData, NebulaData, SupernovaData, PulsarData. Each function has its unique range of parameters to be knowledgeable about. Such functions can be subjugated or embedded into more sophisticated codes. Regardless, it’s also important to learn how to access, introspect and query data from professional sources. VII. Wolfram Demonstrations. One should also take advantage of Wolfram Demonstrations with subject areas categorized. Note: such resources serve to augment instruction, assignments, labs and activities in this syllabus Outdoor observatory field activities AND labs --> Essential towards development in self-sufficiency with discovery and authentic research. Google Sky can accompany the field exercises towards confirmation of objects observed. Note: throughout course one should take advantage of Wolfram Demonstrations with subject areas categorized, and Wolfram Language & System Documentation Centre, towards designated subjects in syllabus. However, such will not be substitute for designed instruction in this syllabus. NOTE: In the Mathematica environment there is the Wolfram Data Repository available; not necessarily confined to it however. R to serve as well. LECTURES CONCENTRATION --> 1. Course Overview, Computer Accounts (only if need be) and Linux (or other OS) 2. Discussion of Independent Projects and Linux (or other OS) 3. FITS format, Data Archives, Databases, and Image Viewers Note: at this point students must understand what their strengths and comfort are, based on the prior two astronomical courses. Understanding such and making use of such will likely translate to projects of high caliber and professionalism. Students can take advantage of their strengths and comforts augmenting with things learnt in other courses such as the Space Science sequence or even relativity if they have reached that level. 4. Fast review logistics of astronomical software DS9 or Graphical Astronomy & Image Analysis Tool (GAIA) OSCAAR and elements of image Processing 5. Stellar and Galaxy Photometry 6. Elements of Spectroscopic Data Reduction and SPLAT/SPLAT-VO 7. Recall Wolfram Mathematica tools and resources from prerequisites 8. Distribution of minor planets via Mathematica or R or Python semimajor axis versus inclination semi major axis versus eccentricity orbital distances versus inclination With labeled vertical colored lines identify the family groups in each chart and possible influence of orbital resonance in distributions plotted. Then students must develop such distributions without use of Mathematica astronomical functions (but will still be done in Mathematica, or use of TOPCAT or R). 9. Distribution of asteroids (similar to module 8) Development and interpretation of the Kirwood Gap from distribution of the semi-major axes; causes for the loss of objects in gaps. Prominence of gaps reflected by strong resonances. Identifying main gaps by resonance. Articles to analyse and replicate: Greenstreet, S., Ngo, H. and Brett Gladman, B. (2012). The Orbital Distribution of Near-Earth Objects Inside Earth’s Orbit. Icarus 217, pages 355 – 366 Kazantsev, A. M. and Serdyukov, I. V. (2012). Asteroid Space Distribution Near the Earth's Orbit at Different Seasons. Astronomical School's Report, Volume 8, Issue 1, pages 71 – 74 10. Galaxy Mapping, Dynamic and Mass (analysis and active development) -Measuring the speed of a galaxy -Measuring the rotation Mapping out a line like Hα across the galaxy and compare it to the value from a source at rest. Measuring the 21-centimeter emission line of hydrogen to reveal galaxy rotation -Rotation Curve of the Milky Way and the Dark Matter Density Yoshiaki Sofue, (2017), Rotation & Mass in the Milky Way & Spiral Galaxies, Publications of the Astronomical Society of Japan, Vol. 69, Issue 1, R1 -3D Imaging of the Milky Way Galaxy Chen, X., Wang, S., Deng, L. et al. (2019). An Intuitive 3D Map of the Galactic Warp’s Precession Traced by Classical Cepheids. Nat Astron 3, pages 320–325 -Measuring size and age of a galaxy 11. Basic Stochastic and Data Analysis The prime directive: the usefulness of stochastic and statistical tools only for meaningful and practical analysis in astronomical study concerning simulation, data retrieval and modelling, with constructive use of time in regard to quality completion of other topics in course. Instruction modules are focused on the logistics and computational development. Majority of practice and competence will be the responsibility of students; pen-and-paper finesse isn’t absolute here. High knowledge of Mathematica or R or Python will be an invaluable asset. (A) Simulating probability distributions from real data of interest. Distribution fitting. Determination of explicit probability densities for probability distributions simulated from real data. (B) FAST FAST review of ideal probability distributions (Uniform, Exponential, Poisson, Binomial, Normal): determining when relevant and representative. (C) Goodness-of-Fit-Tests for distributions Chi-Square Goodness of fit test Kolmogorov-Smirnov test Shipiro-Wilk test Anderson-Darling (D) Advance practical MLE applications examples: Whidden, P. J. et al, Fast Algorithms for Slow Moving Asteroids: Constraints on the Distribution of Kuiper Belt Objects, The Astronomical Journal, 157: 119 (15pp), 2019. Aghajani, T., and Lindegren, L., Maximum Likelihood Estimation of Local Stellar Kinematics, A&A 551, A9 (2013). Luminosity function for galaxies (involving Schechter function): Vmax versus MLE estimation. Mengfan, X., et al, A Fast Pulse Phase Estimation Method for X-ray Pulsar Signals Based on Epoch Folding, Chinese Journal of Aeronautics, (2016), 29 (3): 746 - 753. (E) Models for Exoplanets Review the conventional techniques for detecting exoplanets. Logistics for a respective technique for acquiring exoplanet properties. Chu, Jennifer. (2022). Astronomers Discover a Multiplanet System Nearby. MIT News For the above article, concern is to analyse and develop logistics to acquire the findings. Then will pursue replication. THEN also to take some runs on the Exoplanet Population Observation Simulator (EPOS): eos-nexus.org/epos/ The following articles are decent guides for comprehending the development of the EPOs simulator. The latter two articles are directly structured towards EPOS. The first two articles may involve some activities with use of TOPCAT or Mathematica or the R environment Udry, S. & Santos, N. C. (2007). Statistical Properties of Exoplanets, Annu. Rev. Astron. Astrophys. 2007. 45: 397–439 Bashi, D., Helled, R. and Zucker, S. (2018). A Quantitative Comparison of Exoplanet Catalogs, Geosciences, 8, 325 Mulders, G. D. et al (2018). The Exoplanet Population Observation Simulator. I. The Inner Edges of Planetary Systems, The Astronomical Journal, volume 156, number 1 Mulders, G. D. et al (2018). The Exoplanet Population Observation Simulator. II. Population Synthesis in the Era of Kepler, Arxiv.org Extrasolar Planet Population Synthesis Articles may involve some activities with use of TOPCAT or Mathematica or the R environment or Python Mordasini, C., Alibert, Y. and Benz, W. (2009). Extrasolar Planet Population Synthesis. I. Method, Formation Tracks, and Mass-Distance Distribution. Astronomy and Astrophysics, Vol 501, Issue 3, 2009, pp.1139-1160 Mordasini, C. et al. (2009). Extrasolar Planet Population Synthesis. II. Statistical Comparison with Observations. Astronomy and Astrophysics, Volume 501, Issue 3, 2009, pp.1161-1184 Alibert, Y., Mordasini, C. and Benz, W. (2011). Extrasolar Planet Population Synthesis. III. Formation of Planets Around Stars of Different Masses. Astronomy and Astrophysics, Volume 526, id.A63, 12 pp. Mordasini, C. et al. (2012). Extrasolar Planet Population Synthesis. IV. Correlations with Disk Metallicity, Mass, and Lifetime. Astronomy & Astrophysics, Volume 541, id.A97, 23 pp. (F) Pulsar Population The following articles to serve for analysis and replication; data subject to change, say, things out there change in time. A. G. Lyne, R. N. Manchester, J. H. Taylor (1985), The Galactic Population of Pulsars, Monthly Notices of the Royal Astronomical Society, Volume 213, Issue 3, Pages 613–639 T. R. Clifton, et al (1992). A High-Frequency Survey of the Galactic Plane for Young and Distant Pulsars, Monthly Notices of the Royal Astronomical Society, Volume 254, Issue 2, Pages 177–184 Note: may ask to develop for other star classifications as well. (G) Practical Regression -Not equivalent to a regression course. Focus is on competent computational logistics and implementation rather than comprehensive treatment. The goal is to establish practical and meaningful astronomic/astrophysical research models; knowledge and skills from prerequisites will be extremely vital towards establishing anything with substance. Take notes and save your files/notebooks. Get the computational logistics down. Fast Review of correlation and bivariate regression analysis Fast Review of Multivariate regression Contemplating variables based on data analysis OLS/WLS/GLS Model selection (Vuong’s test, F-test, AIC, BIC, HQC) Splitting data (training, testing, validation) Forecasting and error methods A. M. Sardarabadi, A. Leshem & A. van der Veen (2015), "Computationally Efficient Radio Astronomical Image Formation Using Constrained Least Squares and the MVDR Beamformer," 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Brisbane, QLD, pp. 5664-5668. Concerning the setting of the above article will pursue a telescope with such criteria and assimilate the data to be applied in fashion to the article. Will employ Mathematica functions or R functions from packages. Köhnlein, W. (1996). Cross-Correlation of Solar Wind Parameters with Sunspots (‘Long-term variations’) at 1 AU During Cycles 21 and 22. Astrophys Space Sci 245, 81–88 Replicate with data for time interval considered Then augment with new data Scatter Plots Scatterplots are a useful first step in any analysis because they help visualize relationships and identify possible issues (e.g., outliers) that can influence subsequent statistical analyses, or need of regression beyond simple OLS/WLS/GLS, say, quantile regression (or generalized nonlinear models). Note: concerns for the number of variable pairs. Model selection methods (Vuong’s test, F-test, AIC, BIC, HQC), Splitting data (training, testing), and Forecasting and error all still apply. (H) Binary Regression, Binary Choice Models, & Gamma Regression Focus is on computational logistics and implementation rather than comprehensive treatment. The goal is to establish practical and meaningful astronomic/astrophysical research models; knowledge and skills from prerequisites will be extremely vital towards establishing anything with substance. Take notes and save your files/notebooks. Not equivalent to a regression course. The following to apply as guides, however there will be active usage of data from sources towards development: Beitia-Antero, L., Yáñez, J., & Castro, A.I. (2018). On the Use of Logistic Regression for Stellar Classification. Experimental Astronomy, 45, pages 379 - 395 de Souza, R.S. et al. The Overlooked Potential of Generalized Linear Models in Astronomy, I: Binomial Regression. Astronomy and Computing 12 (2015), pages 21 – 32 Elliot, J. et al. The Overlooked Potential of Generalized Linear Models in Astronomy, II: Gamma Regression & Photometric Redshifts. Astronomy & Computing, Volume 10, April 2015, pages 61 - 72 (I) Practical Time series Not equivalent to a Time Series course. Will employ Mathematica functions, or R functions and R packages. Will not be comprehensive, rather, will speed immerse with the logistics and procedures in Mathematica, R, etc. Take notes and save your files/notebooks. Get the computational logistics down. Time series representation of data Salient features (methods of identification with decomposition) Autoregressive Moving averages Exponential Smoothing (practical uses) Box Jenkins Operation Approach Model Identification Estimation Validation Box-Jenkins analysis on various astronomical data Splitting data (training, testing) Common pursuits: Sunspots, solar space weather, Milankovitch cycles Periodic pursuits: Light curves, radial velocity, planetary distances Estimate parameters such as Period, amplitude, waveform Perturbations (small) in period, resonance, etc. Cepheid Variable Brightness related to luminosity & distance calculation Transient pursuit: Supernovae, stellar activity, novae, gamma ray bursts. Detection Identification/classification Automatic triggers Estimate parameters: Duration Fluence Profile shape Multi-“lambda” comparison (J) Survival Analysis Applications to Sun activity, pulsar beams, gamma-ray bursts LABS --> Labs will take on multiple sessions in a manner to span at least 15 weeks. There’s enough time allocated to develop competence and advancement. Note: there must be strong connections to the determination of physical and chemical properties (distance, luminosity, lifetime, mass, radius, temperature, composition, density, rotation, orbit, speed, etc.). 1. Linux Operations for Research 2. Data Archives and Databases exercises 3. Use of DS9 or GAIA or OSCAAR (may be dependent on prior) 4. Indoor activities: Imaging & Photometry Labs 5. Spectroscopic logistics and use of SPLAT/SPLAT-VO 6. Indoor activities: Spectroscopy Labs 7. Telescope Checkout (both photometry and spectroscopy) with diagnostics, calibrations, field observations Prerequisites: Techniques in Observational Astronomy I, Mathematical Statistics Machine Learning for Physics & Astronomy The course is designed as an introduction to the concepts and exposure to tools of Machine Learning, which are making huge inroads in many fields of research in physics and astronomy. The course will focus on exploratory data analysis, supervised learning, and ensemble learning. Emphasis is placed on concepts and hands-on applications, with examples drawn from diverse areas of physics and astronomy. This is not a mathematician’s nitpicking course. NOTE: you will have to do a lot of independent reading. However, you will not be cyphering clunky textbooks. To get comfortable and competent don’t expect the instructor’s construction to be absolute. NOTE: expect to encounter lots of errors throughout your developments; otherwise, you’re not learning anything. No caste system here nor any social entitlement. You will determine your success. ESSENTIAL RESOURCES --> DataCamp (R and Python) Scikit-Learn CRAN R searches for computational documentation and vignettes Wolfram Documentation Center Various astronomical Data archives and Databases Wolfram Data Repository Websites: Towards Data Science, Geeks for Geeks, Medium, Github, Kaggle, KNuggets, Astrobites, Bing Search, Google Search NOTE: you will be given some leeway with computational environment. Such concerns future economic reasons and speed with competence. NOTE: topics to consistently resonate or underlie -- Bias vs variance Overfitting Underfitting Cross Validation Hyperparameter Tuning COURSE GRADING --> Quizzes (closed book, closed notes and no electronic devices) Note: any prior concept or topic can come to haunt Scores above 80% will result in points on final grade Scores range from 70% to 79% gives no contribution to final grade Scores ranging from 0% to 69% will sum in weight of 10% on final grade Note: quizzes given concern definitions, multiple choice, T/F and elaboration of data/results. 4 Take Home Projects 60% Open Notes Midterm (includes essential resources) 25% Final Project 15% COURSE OUTLINE --> The course content is divided in two parts: Kindergarten computations (fast run-through/review) Arithmetic operations, parentheses and exponents Analytical functions (polynomial, exponential, logs, trigonometric, piecewise) Normal function calls Defining Functions Evaluation, arithmetic operations, parentheses and exponents Making good notebooks and publishing (fast run-through/review) Headers, layouts, references and conversions (pdf and html) Arrays and Data Frames Identification, Constructions, Conversions between Probability & Statistics and Exploratory Data Analysis (review) Generating summary statistics for data Simulating random variables (analytically and with CAS) Plotting distributions with data (single variable & bivariate relationships) Time Series operations Salient characteristics with decomposition Model determination from software Summary statistics interpretation Forecasting and error Correlation matrices and Heatmaps. What can you conclude? Machine Learning Fundamentals Learning Concepts Data Preparation Skills Reviewing Arrays and Data Frames (identification and construction) Data Cleaning/Data Wrangling Feature Engineering Methods (practical basics) Segmenting Data into Training and Test Sets Manually with code Packages/Libraries Supervised Learning Classification Decision Trees (DT) Logistic Regression (LR) Standard to Multi-Logistic Support Vector Machine (SVM) Comparative Performance (DT vs LR vs SVM) Regression OLS (will not get stuck in a swamp of gradient descent methods). Summary Statistics Performance Quantile Regression Summary Statistics Performance Comparative Performance (OLS vs Quantile) Decision Trees for Regression. Do you have a choice between OLS and Quantile? Feature Importance and Selection Methods Univariate Ridge Logistic Comparative view (univariate vs Ridge vs logistic) Ensemble Learning Random Forest (RF) Gradient Boost (GB) Comparative Performance (RF vs GB) Feature Importance and Feature selection with RF and GB Prerequisites: General Physics I & II, Data Programming with Mathematica, Mathematical Statistics Space Science I: Note: course concerns no 25 session limitation cap. Labs and activities will take much time. Note: the course is structured towards acquiring a temperament and focus in multiple advanced activities of study, observation and research. Course to make heavy use of group activity and patience. For exhibited articles, at times, it may be the case that the instructor(s) prepare lecturing based on designated textbook(s) and the articles. Otherwise and often, articles will be used by students and instructors for lecturing and discussions. Course can be augmented with Google Sky, but usage doesn’t replace any lecturing. Use of journal articles in course will be moderate. Course serves as a means for students to become immersed in professional academics of Astrophysics, not to be intimidated by professionalism and competency involving critical research. As well, a means not to be fearful of having one’s own analytical drive. Calculus usage (single to multivariate) for modelling (and derivations) will be employed for general treatment as much as possible. Course concerns at least three open-notes class examinations. Such examinations will not be given until a determined number of homework sets are graded and returned. Subjects for examinations will not be explicitly conveyed in any form, rather an examination will reflect the graded and returned homework sets. Course grade to depend considerably on homework and labs. Problems in examinations to be: 1. Topics out of instructed lectures 2. Homework problems involving models and equations, determination of specified parameters or quantities. Solving for parameters may take steps of multiple equations based on data provided. Particular steps may or may not require students to discern the need of use of calculus. 3. Homework problems extended towards solving other problems. Course grade to depend heavily on homework and labs, being at least 60% combined. Cumulative grade percentage of 25% concerns exams. Excellent resource: The SAO/NASA ADS: ADS Home page (under Harvard’s web domain). After entering topic of interest in search engine, the “F” link generally provides free publish articles. The “X” link is also free but provides some received articles before publishing, yet still useful. Note: Course is not close to a proper treatment of General Relativity. Class participation and attendance to be 15%. Dependent on the severity of conduct infractions, conduct percentage of final grade may warrant amplification to 69%. Syllabus: --Karman line McDowell, J. C., The edge of space: Revisiting the Karman Line, Acta Astronautica 151 (2018) 668 – 677 --Newton’s Law of Gravitation and equilibrium distances between multiple gravitational sources. Magnitude of gravitational along Cartesian axes. Derivation of gravitational field outside of a solid sphere: use of shell theorem and extension to a solid sphere. Kepler’s third law. Gravitational sources of tidal forces. **Lab: A. Derivation of the Newtonian Orbit Shape equation as a second order ODE and its solution. Determination of bound and unbound orbits. From the solution of the orbit shape equation determination of the apsis, towards finding the periapsis and apoapsis. B. Orbital perturbations via simulation (Runge Kutta): https://portia.astrophysik.uni-kiel.de/~koeppen/ue32/perturb.pdf . Compare with orbits in (A). --The Hill Sphere and Roche limit --Gravitational potential with zonal harmonics harmonics (1). Gravitational potential in terms of the Poisson equation (derivation): changing from Cartesian coordinates to spherical coordinates, and making use of spherical symmetry towards having a model whose only independent variable is radial; based on acquired model deduce gravitational potential inside and outside of sphere of uniform mass density having a specified radius R and total mass M. Normalize potential so it vanishes at infinity. (2). Then to consider a sphere of same R and M, but with mass density that varies due to unique layers. Consider each layer to be spherical and bounded (at least four layers); an extension of (1). Can there be a governing potential normalized to vanish at infinity? (3). Identifying the physical measures from the gravitational potential expansion (4). Distance between a degree of latitude differs from that expected from a sphere; ellipticity of the Earth measured by the distance between latitudes of the Earth compared to a sphere. (5). Reference spheroid can be determined from the gravitational potential and Legendre polynomials yielding (zonal) spherical harmonics. Use of MacCullagh’s formulas and importance of centripetal influence. (6). Approximate model for the radius of Earth as a function of average radius, angular velocity, mass and co-latitude. (7). With geocentric (or chosen planet) data for (4), compare to findings of (6) for confirmation. --Gravitational potential with Tesseral harmonics Pursue a gravitational potential model for Tesseral harmonics. Cook, G. E. (1963). Perturbations of Satellite Orbits by Tesseral Harmonics in the Earth’s Gravitational Potential. Planetary and Space Science, Volume 11 Issue 7 pages 797 – 815 Gedeon, G.S. (1969). Tesseral resonance effects on satellite orbits. Celestial Mechanics 1, 167–189 Analogy to (2), (3) and (4). Pursue an explicit gravitational potential accounting for both zonal and tesseral harmonics, and confirm that such gravitational potential converges to GM/r for vast distances from gravitational source. --Asteroid Gravitation Sebera, J. et al. (2016). Spheroidal Models of the Exterior Gravitational Field of Asteroids Bennu and Castalia, Icarus, Volume 272, Pages 70-79 Fukushima, Toshio. (2017). Precise and Fast Computation of the Gravitational Field of a General Finite Body and Its Application to the Gravitational Study of Asteroid Eros. The Astronomical Journal. Volume 154, Number 4 Takahashi, Yu & Scheeres, D. & Werner, Robert. (2013). Surface Gravity Fields for Asteroids and Comets. Journal of Guidance, Control, and Dynamics. 36(2): 362-374. With such articles will chose arbitrary asteroids with robust astronomical data to apply sensitive parameters that will identify the unique gravitational field for each asteroid. --Astronomical Measurements 1.SI system, astronomical unit, light year, parsec, solar mass. 2.Conversion among different units of time, distance, energy and power, and interrelation with SI units. --Parallax principle and its accuracy limit --Sun Structure & Mechanisms 1.Solar Anatomy (layers and atmosphere) Respective constitution, states of matter, processes, types of energy/radiation/convection transfer & temperatures 2.Governing equations for an isolated, approximately static & spherically symmetric star Hydrostatic Equilibrium Conservation of Mass Equation of State Mass Fraction Thermonuclear Reactions and Conservation Convection Energy Transport with adiabatic temperature gradient. An alternative assistance [Wang, J., Miesch, M., S., Liang, C. 2016. Convection in Oblate Solar-Type Stars, Astrophysical Journal, 830: 45, 21 pages] Opacity, Equation of Energy Transport by radiation Radiation pressure & flux Note: direct, tangible development where all such equations connect mathematically will be a student assignment. 3.Governing Sun Mechanism Outline Gravitational force is balanced by thermal pressure Energy is generated from star’s hot core (thermonuclear reactions), then moves outward to cooler surface (radiative and convective). Nuclear reaction are kept under control by a pressure-temperature “thermostat”. 4.Self-Regulation: Any slight change in fusion rate results in temperature increase, pressure increase, core expansion. Then pressure and temperature decreases, fusion rate decreases. 5.Core Shrinkage and Collapse in a Self-Gravitating System Case of no energy generation in the core, pressure in core still to be high, hence core to be hotter than envelop. Energy would escape (radiation, convection, etc.), leading to core shrinkage under gravity; leading to a further increasing in temperature, thus further energy escape. A feedback loop takes place. Note: all star cores are not the same as the sun 6.Photosphere, Sunspots, filaments, Prominences and Plumes (include respective composition, temperature ranges, duration) 7.Chromosphere & Corona (respective composition, temperature ranges, and theories for coronal heating) 8.Magnetosphere & Solar Wind Includes behaviour of particle dynamics in magnetospheres (sun, and aurora). **Lab: Data Collection (sunspot regions & time duration, magnetosphere, storm signals); will make use of Mathematica data sources and Wolfram Alpha data (incorporated into Mathematica), as well as incorporating governmental/universities’ data into Mathematica platform. **Lab): calculating the size of sunspots (must be competent will industry formats applied). Determining the rotation period of the Sun. Determination of solar cycle. **Lab: Mass/Charge ratio experimentation (gas in toroidal tube with Hemoltz coils experiment related to circular motion in tube). **Lab for simulation of charged particles in magnetic fields: a. Simulation must have the superposition of circular motion orthogonal to magnetic field line (gyro-radius). As well, knowledge of the gyro-frequency (or angular frequency) b. Modelling the Earth’s magnetic field in terms of spherical polar coordinates (determine field potential) assuming the Earth’s magnetic dipole is aligned along the “z-axis”, then plot; find the field components and total field magnitude, and plot to view their respective behaviour. Boundary conditions: magnetic field at the north pole, south pole, and equator for the radial and latitudal magnetic field components respectively c. Reviewing the physiology of the Earth’s magnetosphere with respect to solar winds. Particle mechanisms with Earth’s magnetosphere (decompositions, gaps, cascades, radiation, etc.) d. Trajectories of charged particles trapped in Earth’s magnetic field (to simulate): Öztürk, M. K. (2012). Trajectories of Charged Particles Trapped in Earth’s Magnetic Field. American Journal of Physics, Volume 80, Issue 5, 420 < open version: https://arxiv.org/pdf/1112.3487.pdf > e. Trapped particle radiation belts and models of the trapped proton and electron populations. Will use the following source for development with SPENVIS: https://www.spenvis.oma.be/help/background/traprad/traprad.html#APAE --Electromagnetic Radiation & Spectrum. Notion of blackbody radiation. Laws of Planck, Wien, Stefan-Boltzmann. Establish relation among these laws. **Lab: Transmission Diffraction Gratting (hydrogen, helium, oxygen, nitrogen, carbon dioxide, argon, neon). --Solar Energy Use of Stefan-Boltzmann law and Wien’s law. Method for a continuous time interval. Determination of lifespan by power output. --Star classifications, stellar evolution on Hertzprung-Russel diagram. 1. Physical and time measures (mass, radius, density, constitution, luminosity, age) 2. Main sequence stars http://www.astronomy.ohio-state.edu/~pogge/Ast162/Unit2/mainseq.html . Note: not all stars have the same anatomy as Sun class stars. 3. Taylor, R. F., Convective Cores in Stars, Mon. Not. R. Astr. Soc. (1967) 135, 225-229. 4. For stars on the Hertzprung-Russel diagram, determination of lifespan by power output via Stefan-Boltzmann law and Wien’s law. **Lab: choose at least 20 stars for a respective spectral categorization on the Hertzsprung-Russell diagram, where for all stars there is the following specified array for data acquisition: luminosity, temperature, mass, age, brightness. For each star with official database name to identify with a combination of its spectral categorization with an assigned number. For future geometrical display purposes stars can be colour coordinated based on their spectral categorization and known colour. a. Classify in either the lower M-S or upper M-S or off M-S based on the mass condition criteria with the core temperature criteria (regardless if they do or don’t satisfy M-S) when compared to the mass and temperature of the sun (based on lectures). b. Analytically, consider the rate of change of luminosity w.r.t temperature and observe the geometrical trend of such. Then do the same for luminosity-mass, luminosity-age and luminosity-brightness. Among the various rates identify any commonalities or considerable uniqueness between them. c. To plot these stars (with the colour coordination) w.r.t a (L-T)-axes with regression curve model accompanying. Then do the same for Luminosity-mass, luminosity-age and luminosity-brightness. Compare the rates of change and regression models. Note: regression models don’t have to be linear. d. From the data of stars segregate data into upper M-S, lower M-S and off M-S based on mass size conditions and core temperature conditions; categorize whether under the P-P chain or CNO cycle and type of internal structure. e. For the chosen stars, observe their physical locations w.r.t. to the galactic nucleus. Is there anything (remotely) consistent? --Atoms, quanta & energy, spectral lines. A. Hydrogen as the most abundant element in the universe. B. Doppler effect, and use to calculate precisely how fast stars and other astronomical objects move toward or away from Earth or each other. C. Balmer series (Doppler effect) for determination of radial velocities. Discovering solar planets, binary stars, exo-planets, black holes (by the motion of hydrogen in accretion discs around them), etc. D. Balmer series for determination of distances between galaxies. E. Balmer series and formula for determination of surface temperature of stars, surface gravity. F. Rydberg equation. Composition of stars and planets. --Overview of Special Relativity NOTE: this module doesn’t and can’t be a substitute for a special relativity course. 1. What settings and conditions lead to the theory without consideration of gravity? Clarify how Newtonian descriptions fail or are inadequate, concerning the appropriate types of matter, and frames of consideration, etc. 2. Postulates, Simultaneity & Lorentzian frames, Minkowski space-time, four-momentum. 3. Statement to prove or disprove: It’s said that a massive particle is relativistic when its total mass-energy (rest mass + kinetic energy) is at least twice its rest mass. This condition implies that the particle's speed is close to the speed of light. According to the Lorentz factor formula, this requires the particle to move at roughly 85% of the speed of light. 4. Electromagnetic momentum and the relativistic dispersion relation (RDR) How would we model electromagnetic waves carrying momentum based on Faraday-Maxwell physics? Is prior equivalent to momentum found via Planck’s constant and wavelength? Radiation pressure in space Comet trajectory perturbations. Will pursue means of determining radiation pressure on comets and/or satellites based on trajectory data and/or accelerometer data in the solar system; hopefully any other influences can be isolated from radiation pressure (such as atmospheric drag, various gravitational influences, etc., etc.). Probes throughout the solar system may also be applicable with their data. Solar sailing Relativistic dispersion relation (RDR) Origins and purpose Derivation methods based directly on physics Is momentum observed in RDR the same as momentum of electromagnetic waves? 5. Velocity Time Dilation. Velocity addition formula. Mass-Energy equivalence. Can bulk matter objects (like a coin, cricket bat, bullet, cocktail) ever operate under special relativity for length contraction to take place? Can any particle accomplish FTL travel? 6. Is there a limit to relativistic mass, and if so, what determines such? 7. Additional elementary modelling: https://www.astro.umd.edu/~miller/teaching/astr498/srpractice.pdf 8. Tensors in special relativity: Energy-Momentum tensor and Electromagnetic tensor. In what ways are they applicable? 9. Particles relevant to special relativity and modern physics based on 1 through 7. The standard model, hadrons and antiparticles. Will identify the presence and/or creation of various particles with astrophysical phenomena and atmospheric bombardment phenomena; environmental conditions, conservation between mass, energy and momentum will be reinforced. --Overview of General Relativity NOTE: this module doesn’t and can’t be a substitute for a general relativity course. 1. Highlighted concepts of General Relativity Inadequacy of Galilean references frames The uniformly accelerated frame Curving of space. What is the most transparent and simple way to demonstrate that’s convincing? Space-time is both dynamic and interacting with matter-energy fields Differentiating the SR energy-momentum tensor from GR energy-momentum tensor Consequences of General Relativity: Precession orbits contrary to Newtonian gravity in the solar system Gravitational red-shifting (blue-shifting) Gravitational time dilation Gravitational lensing Frame-dragging Black holes Gravitational waves 2. Use of the least action principle for determination for a “test particle” under classical gravitational influence. Arrive at a geodesic equation. Acquiring the models for energy conservation and angular momentum conservation towards an effective potential. How can one validate the accuracy of the deduced effective potential? 3. Identify a Lagrangian in terms of a weakly relativistic metric for a gravitationally bound/stable orbit. Deriving the geodesic equation in terms of a general metric and identifying the Christoffel symbols. Will the effective potential be unique to what is observed in (2)? Considering such a metric under different coordinate systems, will one acquire the same equation(s) of motion? 4. Defining and modelling the Newtonian limit Three requirements: The “particles” in the background are moving slowly with respect to the speed of light The gravitational field is weak, namely, can be considered a perturbation of flat space The field is also static, say, unchanging with time Modelling in the Newtonian Limit Consequences on the geodesic equation based on prior 3 requirements; must recover the Newtonian potential formula. In the Newtonian limit such potential is identified with Poisson’s equation. Identifying g_00. 5. Speed of Newtonian Gravity Haug, E. G. (2021). Demonstration that Newtonian Gravity Moves at the Speed of Light and not Instantaneously (Infinite Speed) As Thought! Journal of Physics Communications Volume 5 Number 2 For gravitational attraction which can be identified with force in Newtonian gravity, the force magnitude is simply dependent on masses present and the relating distance among the masses, which doesn’t identify the speed of “relation”. 6. Comprehending the difference between the Newtonian limit and the speed of Newtonian gravity 7. Synopsis of Schwarzschild spacetime. Derivation of the Schwarzschild Orbit Shape equation as a second order ODE and its solution. Determination of bound and unbound orbits. From the solution of the orbit shape equation determination of the apsis, towards finding the periapsis and apoapsis. 8. For rotating black hole, discover the gravity well from Bardeen, J. M., Press, W. H. and Teukolsky, S. A., Rotating Black Holes: Locally Nonrotating Frames, Energy Extraction, and Scalar Synchrotron Radiation, Astrophysical Journal, Vol. 178, pp. 347-370 (1972), strictly restricting to pages 349-353. ---Description of matter in the background geometry NOTE: this module doesn’t and can’t be a substitute for a general relativity course NOTE: not all systems in GR are Schwarzschild, Reissner-Nordstrom, Kerr, Kerr-Newman, nor require the presence of a black hole. Astrophysical considerations for gravitational dominance, classical electrodynamics or special relativity (rubric): v/c test (v being the magnitude of velocities of matter within system) Ratio of summed electrostatic force to gravitational force Ratio of pressure to density Jeans Instability and Jeans Length E-M frequency change in gravitational fields (to determine metric) -Example candidate metrics in environment Weak field limit versus Newtonian gravity Hartle-Thorne metric Solar metric (deduced from the Hartle-Thorne metric) Earth metric -Two static observers bound in orbital plane of constant radial orbit -One observer is radially further away from source than the other -Apply first metric component for point A and point B Find ratio with such two Frequency change from point A to B How does it compare to found ratio? Ratio of length scale of curvature to typical size of system Environment examples for such rubric: 1. Electrons under Lorentz force 2. Molecules of an ideal gas under the Maxwell distribution 4. Molecules of a gas subject to increasing temperature 5. Anions or cations for chosen temperatures 6. Violent emissions Coronal plumes, solar flares, Mass ejections Cosmic jets, pulsar beams, quasars, blazars 7. Astrophysical environments Sun’s magnetosphere Pulsar magnetosphere Pulsar atmospheric mechanisms, pulsar cascades from pair creation Magnetohydrodynamics Magnetic flux frozen into accretion discs Currents in accretion disks Solar system Galaxies clusters Diverging galaxies --Tests for at least a weak general relativistic system (rubric) NOTE: this module doesn’t and can’t be a substitute for a general relativity course 1. Case of a system that’s gravitational bound being at least weakly relativistic, then all forms of energy density within the system must not exceed the maximum value of the Newtonian potential in it; (Newtonian) potential being a function of the average mass density, typical size of the system, and the Newtonian gravitational constant. 2. Velocities of gravitational bound objects within the system must not approach the speed of light. 3. Potential must be greater than or equal to the order of magnitude of the velocities of the matter within the system squared. 4. For the (Newtonian) potential described it must also be greater than or equal to the ratio of (uniform) pressure-and average mass density ratio as well. Note: verify all such for the Earth-Moon system, planets with satellites, solar system, small asteroids with satellites. Are all such 4 also valid for star clusters and galaxy clusters? For all matter with mass, Newton’s gravitational law is fundamentally applicable, yet actual “satellite” orbits must be further distinguishable from fundamentalism: a descriptive model beyond two arbitrary mass objects with arbitrary distance between them; considering Newton’s law of gravitation where asteroid and its satellites don’t necessarily collide. Beyond fitting mathematical Kepler models based solely on observations which don’t explain precessions and other things. What limit can provide a good model for a small asteroid with satellites? --Speed of Gravity in GR Haug, E. (2019). Extraction of the Speed of Gravity (Light) from Gravity Observations Only. International Journal of Astronomy and Astrophysics, 9, pages 97-114. Concerning mass-energy-momentum (MEM) configurations and the curvature of the background geometry, such (non-radiative) curvature stemming from a metric isn’t identified with speed. --Interstellar Clouds and Gravitational Instability The following source is a rough guide to complement sound modelling: http://star-www.st-and.ac.uk/~kdh1/ce/ce06.pdf Hydrostatic equilibrium. In what state do interstellar clouds exist concerning fluid dynamics, thermodynamics and electromagnetic influences? Characteristic mass for system to collapse is Jean mass. Deduce or derive such. Recall the Poisson equation for gravity, and the wave equation (for a fluid). Deduce the dispersion relation for sound waves incorporating the Poisson equation for gravity. Find the critical value of kc at which an instability occurs. What is that infamous value? Pressure wining over gravity implies oscillations (sound waves) Jeans Instability: Jeans criterion for collapse of spherical cloud --> 1. Initial collapse occurs whenever gravity overcomes pressure. Cooling lowers pressure. How is cooling caused? Jeans length. Jeans length as oscillation wavelength. As well, the important scales in star formation are those on which gravity operates against electromagnetic forces. 2. Jeans Mass: definition, modelling and derivation 3. Gravitational instability sets in if the free-fall time is less than the sound crossing time. How is sound crossing time modelled (or possibly derived)? How is free fall time modelled (or possibly derived)? 4. Condition for nuclear fusion. What typical amount of collapse mass in required to initiate nuclear fusion? 5. Case of Fragmentation (must have strong modelling) **Lab: Data collection and analysis of stellar clouds/gases (interstellar matter, nebulae, protostars, etc.). Labs will pursue consistency between parameters or conditions necessary and retrieved data, concerning the critical processes, formations, etc. Temperatures, breaking the threshold of Jeans mass, Jeans length, etc. Distributions, correlations, LS regression, probit, logit, etc. are applicable if needed or wanted. Conditions and ratios from the following link can serve well as threshold test values/parameters: http://star-www.st-and.ac.uk/~kdh1/ce/ce06.pdf --Magnetohydrodynamics in Astrophysics A good source: https://warwick.ac.uk/fac/sci/physics/research/cfsa/people/valery/teaching/khu_mhd/KHU_mhd_handout.pdf 1. MHD couples Maxwell’s equations with hydrodynamics to describe the macroscopic behavior of conducting fluids such as plasmas. 2. MHD describes large scale, slow dynamics of plasmas Characteristic time >> ion gyroperiod and mean free path time Characteristic scale >> ion gyroradius and mean free path length Plasma velocities are not relativistic (it’s a special relativistic reference, but for our purposes will not entertain general relativity even though it may apply with consideration of the type of astrophysical bodies) 3. Identification of how t establish coupling between Maxwell’s equation and hydrodynamics. What conditions are required? How does each equation contribute? 4. MHD Equilibrium. What is it, and why relevant? Models/equations of governance and solution(s). 5. Beta of a plasma: influence of magnetic field and pressure force. Will have data gathering assignments for the sun’s physiology AND other various astrophysical bodies; concerning orientation of magnetic flux/flied and pressures, MHD equilibrium and consequence on temperature. 6. Thermal Conduction Thermal conduction as an extension of MHD Heat diffuses much more quickly along magnetic field lines than orthogonal to them 7. MHD Waves There are three primary waves that arise from MHD Alfven wave, Slow magnetosonic wave, Fast magnetosonic wave Deducing 8 equations; splits into two partial subsets with appropriate consistency conditions to differentiate the types of waves. Properties of respective wave based on partial sunsets and associated consistency conditions Note: may have additional topics. Resource given above also serves well for further data collection activities. 8. Major applications It’s essential for one to have the ability to situate or apply development/models prior (1 through 7) to the following, and means to apply data form various sources competently Earth’s magnetosphere Solar Pulsars Accretion discs Additional resources: i. Somov B.V. (2013) Magnetohydrodynamics in Astrophysics. In: Plasma Astrophysics, Part I. Astrophysics and Space Science Library, vol 391. Springer, New York ii. Shu, F. H. et al (2007). Mean field Magnetohydrodynamics of Accretion Discs. The Astrophysical Journal, 665: 535 - 553 iii. Priest, E. (2014). Magnetohydrodynamics of the Sun. Cambridge University Press Further remarks: MHD is appropriate for large-scale, low-frequency behavior MHD is a good predictor of stability Non-MHD effects sometimes stabilize or destabilize MHD is often inappropriate when there are non-Maxwellian distribution functions Including in collisionless plasmas or when there are energetic, non-thermal particles MHD is a reasonable approximation for most solar physics applications, but there are many effects beyond MHD that will often be important MHD usually does not usually work well for laboratory plasmas General approaches beyond MHD (only mention) Extended MHD Kinetic Theory Hybrid between two prior Magnetic Reconnection (idea) --Structure and Dynamics of Galaxies 1. Formation of Galactic Discs: Fall, S. M. and Efstathiou, G., Formation and Rotation of Disc Galaxies with Haloes, Mon. Not. R. Astr. Soc. (1980) 193, 189-206 Hernquist, L., Analytical Model for Spherical Galaxies and Bulges, The Astrophysical Journal, 356: 359 - 364, 1990 June 20 Mo, H. J., Mao, S. and White, S. D. M., The Formation of Galactic Discs, Mon. Not. R. Astron. Soc. 295, 319–336 (1998) From the 3 given journal articles above, the biggest challenge will be not causing carnage or a gruesome train wreck with (all) such articles 2. Dynamics of Collisionless Systems **Labs: pursuit of vindicating the characteristic models in collisionless dynamics, namely, simulation versus animation of real data of various galaxies. For the latter, software that can apply coordinate frames with geometrical orientations towards prematurely identifying stellar ranges (semi-major, semi-minor axes, etc., etc.). Will also try to account for motions by animating data to exhibit evolution in spatial motion properties (translational speeds, axisymmetry, moments, angular velocities, angular momentum, etc.). May stem from Doppler methods and so forth. Lab can make use of Aladin Sky Atlas (+ Simbad + VizieR) or GAIA software or DS9 with astronomical data. A respective group will be given a unique set of given galaxies to work on. For the simulation must have credible initial conditions and well defined initial boundary conditions. --Galaxies and properties leading to the idea of Dark Matter 1. Geometrical types (respective size, bulge, age and evolution) 2. Analysis and logistics for differentiating galaxy types and behaviour by spectral analysis [geometry, composition, age of stars/matter, speed moving (away) w.r.t to Earth and/or each other]. **Lab: student groups will be given different sets of galaxies (20-25). They will acquire spectral data in the most professional manner and pursue categorization of galaxy types concerning geometry and age. Statistical methods can also be added if practical. Data collection for galaxy spectra towards determination of size, distance of galaxies and the speed galaxies are moving w.r.t to each other (away or towards). Concerns elliptic, spiral, etc. Statistical methods can also be added if practical. 3. Application of Local Standard of Rest (LSR). Velocity of stars relative to LSR. Solar motion. Velocity distribution of stars (for 3 to 4 star classifications). Measuring the mass of a galaxy. 4. According to CERN, “ Galaxies in our universe seem to be achieving an impossible feat. They are rotating with such speed that the gravity generated by their observable matter could not possibly hold them together; they should have torn themselves apart long ago. The same is true of galaxies in clusters.” Will like to verify such. How is structural integrity related to rotational speed? Is fluid dynamics the foundation of this model for the relation between structural stability and rotational speed? If yes, demonstrate. 5. Dark Matter Properties **Lab for detecting the presence of dark matter by comparison of mass estimates based on the Virial theorem to estimates based on the luminosities of galaxies; will acquire data for various galaxies and galaxy clusters to recognise any significant difference among the two methods of mass measurement. 6. Oort limit and discrepancy (suggesting the presence of dark matter in the disk) 7. Find a rotation curve of specified galaxy, and a predicted one from distribution of the visible matter; discrepancy between the two curves can be accounted for by adding a dark matter halo surrounding the galaxy. Confirm whether rotation curve exhibits Keplerian rotation or not. Multiple cases. --Globular Clusters and Galaxy Clusters (Synopsis) --Overview of Cosmology 1. Cosmological Constant and the concept of the Scale Factor 2. Robertson-Walker geometry 3. Friedmann equations (FE) & incorporating the Cosmological Constant 4. Cosmological Redshift 5. Hubble Law & Constant 6. Dark Matter 7. Dark Energy **Lab: A. Observing redshifts from data. Concerns calculation of redshifts from raw data to compare with developed data for respective time frames. Will then make use of past data sets to observe any variation, and to create a model. B. Turning direct measurements of galaxy properties into actual measurements of relative distances. 1. Size of galaxies despite their distance, intensity level and luminosity. 2. Observation of clusters of galaxies to determine which galaxies are members of the same cluster. 3. Observation of 3 - 4 galaxy clusters in the same area of space, and find the relative distances of galaxies in each in each cluster for different time frames; will involve different past sets of data to identify any variation in such distances, and to create a model. May require procedure to apply to other galaxies. 4. For such same 3 - 4 galaxy clusters will also find the relevant distance of each cluster to each other for different time frames; will involve different past sets of data to identify any variation in such distances, and to create a model. May require procedure to apply to other galaxy clusters. 5. Establishing Hubble’s law and making a Hubble’s diagram to confirm it. Review on how astronomers/astrophysicist use redshift and magnitude. Data will be used to confirm Hubble’s law towards diagram development. Prerequisites: Calculus III, Ordinary Differential Equations, Numerical Analysis, General Physics I & II, Methods of Mathematical Physics, Upper level standing.

Space Science II: The continuation from Space Science I. Course emphasis more use of journal articles and reading. There will be advance repetition of some activities from prerequisite. Note: course concerns no 25 session limitation cap. Labs and lecture activities will take much time, respectively. Course to make heavy use of group activity and patience. For exhibited articles, at times, it may be the case that the instructor(s) prepare lecturing based on designated textbook(s) and the articles. Otherwise and often, articles will be used by students and instructors for lecturing and discussions. Course can be augmented with Google Sky, but usage doesn’t replace any lecturing. There will be considerable exposure to journal articles in Space Science II. Course also serves as a means for students to become immersed in professional academics of Astrophysics, not to be intimidated by professionalism and competency involving critical research. As well, a means not to be fearful of having one’s own analytical drive. Course concerns at least three open-notes class examinations. Such examinations will not be given until a determined number of homework sets are graded and returned. Subjects for examinations will not be explicitly conveyed in any form, rather an examination will reflect the graded and returned homework sets. Problems in examinations to be: 1. Topics out of instructed lectures 2. Homework problems involving models and equations, determination of specified parameters or quantities. Solving for parameters may take steps of multiple equations based on data provided. Particular steps may or may not require students to discern the need of use of calculus. 3. Homework problems extended towards solving other problems. 4. Some topics instructed in prerequisite may reappear in homework in various forms, or will be situated in a manner to solve homework problems in this course, hence, such will appear on exams. Course grade to depend heavily on homework and labs, being at least 60% combined. Cumulative grade percentage of 25% concerns exams. In this course, students may be required to have journal articles to answer some questions on exams; some questions will be comparative, others concern completion tasks in modelling, while for others students may be required to use one or two journal articles to complete or verify a model in another particular journal article. Excellent resource: The SAO/NASA ADS: ADS Home page (under Harvard’s web domain). Class participation and attendance to be 15%. Dependent on the severity of conduct infractions, conduct percentage of final grade may warrant amplification to 69%. Syllabus --> Note: course will not review “special relativity”, “general relativity”, and “determination of Newtonian gravity or relativity” methods from prerequisite; however, in lab tasks students often student must provide additional assessment with such three modules for celestial bodies, astrophysical bodies, stellar matter, particles, stellar systems, dynamics, etc. --Hill sphere and the Roche limit (rigid and fluid satellites) Determination and derivation of formulas --Binary stars www-astro.physics.ox.ac.uk/~podsi/lec_b3_10_c.pdf Paczyński, B. (1971). Evolutionary Processes in Close Binary Systems. Annual Review of Astronomy and Astrophysics, vol. 9, p.183 **Lab: 1. Simulate binary star orbit (and degeneration if possible). 2. Methods to acquire Lagrange points 3. Simulate the motion of a test particle in the field of two masses M1 and M2 in orbit about each other (making use of Roche potential). 4. Extend all prior to trinary star orbit, and find test particle orbits as well if possible. An example system, say, Alpha Centauri. Then try acquiring data on the orbital properties of such system. How (well) does your deduced system orbit relate to the data of the orbital properties? What model best describes the data of such system? Keplerian? Perturbation of Keplerian? 5. The following will make a strong activity Leahy, D.A., Leahy, J.C. A Calculator for Roche Lobe Properties, Comput. Astrophys. 2, 4 (2015) Develop calculator from the above article in the Mathematica environment. For recognised binary systems in astronomica data, whether via Mathematica or calling from an outside database source, to identify what properties your calculator will convey for various systems. Some actual Roche Lobe data may be attained from such sources, hence, you can observe how well your calculator stacks up concerning “accuracy” and quality of data. --Atoms, quanta & energy, spectral lines, etc. (advance recital from Space Science I) --Advance recital of Sun Structure & Mechanisms from Space Science I --Advance recital of Magnetohydrodynamics in Astrophysics from prerequisite (including labs/activities) Note: will be augmented by the following literature catering for Earth’s magnetic field A. How does the Rice convection model fit into the coupling of electromagnetism and fluid mechanics concerning MHD? B. NASA Model Info. Rice convection Model < https://ccmc.gsfc.nasa.gov/models/modelinfo.php?model=RCM > C. Basic theory of the equations that RCM solves Wolf, R. A. (1983), The Quasi-Static (slow-flow) Region of the Magnetosphere, in Solar Terrestrial Physics, Edited by R. L. Carovillano and J. M. Forbes, pp. 303-368, D. Reidel, Hingham, MA. Toffoletto, F., S. Sazykin, R. Spiro, and R. Wolf (2003), Inner Magnetospheric Modelling with the Rice Convection Model, Space Sci. Rev., 107, 175-196. D. Some of the physics studied with the RCM Sazykin, S., R. A. Wolf, R. W. Spiro, T. I. Gombosi, D. L. De Zeeuw, and M. F. Thomsen (2002), Interchange Instability in the Inner Magnetosphere Associated with Geosynchronous Particle Flux Decreases, Geophys. Res. Lett., 29(10), 1448 Wolf, R. A., R. W. Spiro, S. Sazykin, and F. R. Toffoletto (2007), How the Earth's Inner Magnetosphere Works: An Evolving Picture, J. Atmos. Sol.-Terr. Phys., 69(3), 288-302 E. Dynamo Theory of Solar Flares Hopefully the following two articles are highly compatible Sen, H. k. and White, M. L. (1972). A Physical Mechanism for the Production of solar Flares. Solar Physics 23, 146 – 154 Kan, J.R., Akasofu, S. & Lee, L.C. A Dynamo Theory of Solar Flares. Sol Phys 84, 153–167 (1983) F. Sunspot Rotation There are various statements and equations to be investigated or solved Sturrock, Z., Hood, A. W., Archontis, V. and McNeill, C. M. (2015). Sunspot Rotation I. A Consequence of Flux Emergence. Astronomy & Astrophysics 582, A76 Sturrock, Z. and Hood, A. W. (2016). Sunspot rotation II. Effects of Varying the Field Strength and Twist of an Emerging Flux Tube. Astronomy & Astrophysics 593, A63 ADDITIONAL LAB: PHANTOM SPH Code ( https://phantomsph.bitbucket.io ) --Corona Heating Theory for coronal heating: Mathiudakis, M., Jess, D.B. & Erdelyi, R. (2013). Alfven Waves in the Solar Atmosphere. Space Science Reviews 175, 1 – 27 van der Holst, B. et al (2014). Alfven Wave Solar Model (AWSoM): Coronal Heating. The Astrophysical Journal, 782:81 (15pp) Reference: Alfven, H. (1942). Existence of Electromagnetic-Hydrodynamic Waves. Nature 150, 405 - 406 Evidence of coronal heating by Alfven waves: Grant, S. D. T., Jess, D. B. et al (2018). Alfven Wave Dissipation in the Solar Chromosphere. Nature Physics 14, 480 – 483 Kohutova, P., Verwichte, E. and Froment, C. (2020). First direct observation of a Torsional Alfven Oscillation at Coronal Heights. Astronomy & Astrophysics Volume 633, L6 --Helioseismology Christensen-Dalsgaard. J., Helioseismology, Rev. Mod. Phys., Oct. 2002 Gough, D., Inverting Helioseismic Data, Solar Physics 100 (1985) 65-99 Schou, J., Christensen-Dalsgaard, J., Thompson, M., J., (1994). On Comparing Helioseismic Two-Dimensional Inversion Methods, The Astrophysical Journal, 433: 389-416 Thompson, M. and Gizon, L. Solar Interior and Helioseismology: https://star.pst.qub.ac.uk/webdav/public/SolarNET5/Belfast-v1.pdf > Lab Part A activity: Data analysis for sunspot number counts (yearly and decade wise) Data analysis for sunspots with a latitude – time axes (augment with more modern data) Interest in plumes, flares, prominences as well Lab Part B activity: Means of implementing helioseismology analysis via acquirable data. It’s essential that students acquire active competency with model(s), data schemes and logistics for implementation with real data. Pursue professional data sources towards integration with models, and analysis to develop competent probing analysis of the Sun. REMINDER: the Sun is not representative of all stars, namely, certain stars have convection cores and other unique properties. Lab Part C activity: Determination of consistency between spectral method and star seismology concerning star composition. Raw data will be acquired for both methods for stars on the Hertzsprung-Russell diagram; will make use of actual stars from different star clusters or different galaxies. Each chosen star categorization to have at least three test samples. --Advance Recital of Interstellar Clouds and Gravitational Instability from space Science I --Star Formation Sources: Lada, Charles J., Kylafis, N.D. (1991). The Physics of Star Formation and Early Stellar Evolution. Springer Netherlands Christopher F. McKee and Eve C. Ostriker. (2007). Theory of Star Formation. Annual Review of Astronomy and Astrophysics 45:1, 565-687 Krumholz, M., R. (2017) Star Formation, World Scientific publishing, Hackensack (NJ). If this source is the focus, develop a robust model that saves time (from the crucial chapters and sections); must be sound in physics and mathematics. Where and when does Jean’s Instability have relevance if any? How well does the physics and mathematics conform with study in prerequisite? **Lab(s): 1. Evidence from giant molecular clouds (high number in sample). Probe data to draw conclusions based (possibly with any astrophysical bodies in companion) 2. will be similar to (1) prior) The Initial Mass Function: Theory versus Observations Protostellar Disks and Outflows: Theory versus Observations 3. Star Formation Estimators (SFE) --> Students must be able to comprehend and apply at least two methods with real data from various sources. The following article may or may not serve strongly in pursuit --> Daniel Rosa-González, Elena Terlevich, Roberto Terlevich, (2002), An Empirical Calibration of Star Formation Rate Estimators, Monthly Notices of the Royal Astronomical Society, Volume 332, Issue 2, Pages 283–295 The SFE methods of interest: Hα observations, which gives the number of ionizing photons if one assumes that all ionizing photons are used and eventually re-emitted - ionizing photons are almost exclusively emitted by massive (hot) stars which have short lifetimes; the effects of dust can be large Far-IR flux - this assumes that a constant fraction of the emitted stellar energy is absorbed by dust Radio continuum emission - this statistically correlated very well with the IR radiation- physics is complex since radio emission comes from synchrotron radiation from relativistic electrons + thermal Bremmstrahlung from hot gas Far-UV flux: primarily emitted by young (hot) stars- but older/less massive than those responsible for Hα X-ray emission- produced by 'high mass' x-ray binaries (a Neutron star or black hole with a massive companion) **Lab: Will try to implement such SFE methods with possible assistance from provided above literature concerning any need of calibration. Data collection from astronomical catalogues. May need to identify gas collapses and/or protostars serving our interests. How well does data analysis converge to theory? Data samples must be considerably large. --Advance recital of Star Classifications, Stellar Evolution on Hertzprung-Russel diagram from Space Science I. Augment with www.astronomy.ohio-state.edu/~pogge/Ast162/Unit2/lowmass.html www.astronomy.ohio-state.edu/~pogge/Ast162/Unit2/himass.html --Stellar Structure From Wikipedia, “Stellar structure models describe the internal structure of a star in detail and make predictions about the luminosity, the color and the future evolution of the star. Different classes and ages of stars have different internal structures, reflecting their elemental makeup and energy transport mechanisms". Will try to validate such statement. Equations of stellar structure: https://www.astro.princeton.edu/~burrows/classes/403/equations.virial.pdf Concerning such provided above resource can the equations consistently match with any star classification on the Hertzprung-Russel diagram (along with the augmentations)? Namely, if a specific condition was altered in the equations, would the consequences upon the essential properties match to the H-R diagram? Can such equations model the existence of convection core stars? --Mechanism of Core-Collapse Supernova Foglizzo, T., et al (2015). The Explosion Mechanism of Core-Collapse Supernovae: Progress in Supernova Theory and Experiments. Publications of the Astronomical Society of Australia, 32, E009. Langanke, K. and Martinez-Pinedo, G. (2014). The Role of Electron Capture in Core-Collapse Supernovae. Nuclear Physics A, Volume 928, pages 305 – 312 Is electron capture contrary to electron orbital theory with lowest possible shells? --Physics of Neutron Stars (include role of the Chandrasekhar limit, and the Tollman-Oppenheimer-Volkoff limit) Possible appropriate guides: Cameron, A. G. W. (1969). How are Neutron Stars Formed? Comments on Astrophysics and Space Physics, Vol. 1, p.172 Silbar, R., Reddy, S., Neutron Stars for Undergraduates, Am. J. Phys. 72 (7), July 2004 --> https://www.rpi.edu/dept/phys/Courses/Astronomy/NeutStarsAJP.pdf Lattimer, J. M. The Nuclear Equation of State and Neutron Star Masses, Annu. Rev. Nucl. Part. Sci. 2012. 62: 485 – 515 --Pulsar as a special case of the neutron star: Sturrock, P., A.(1971). A Model of Pulsars, The Astrophysical Journal, 164: 529 - 556 Ruderman, M. A. and Sutherland, P. G. (1975). Theory of Pulsars: Polar Gaps, Sparks, and Coherent Microwave Radiation. The Astrophysical Journal, 196: 51 – 72 Zdunik, J. L., Fortin, M. and Haensel, P. (2017). Neutron Star Properties and the Equation of State for the Core. Astronomy & Astrophysics 599, A119 --Mechanisms or conditions to differentiate black hole formation from neutron star/pulsar formation, and white dwarf formation. What are the conditions and limits? Based on such conditions and limits, aside from primordial black holes, which of the three/four celestial “bodies” should be most abundant? What tools or techniques can support such? Demonstrate if able. --Primitive Model for Accretion Discs & Damping of Oscillation: Pringle, J. E. (1981), “Accretion Discs in Astrophysics”. In: Annual Review of Astronomy and Astrophysics. Volume 19. (A82-11551 02-90), p. 137-162. --Magnetodyhrodynamics of Accretion Discs Review any necessities in MHD before jumping into the accretion disc case, if needed. --Advance recital of Stellar Dynamics and Structure of Galaxies from prerequisite (including the labs) ADDITIONAL LABS: will immerse into software for modelling and simulation GADGET-2 NEMO (Stellar Dynamics Toolbox) ZENO Illustris Project Price, D. J. (2012). Smoothed Particle Hydrodynamics and Magnetohydrodynamics, Journal of Computational Physics, volume 231, Issue 3, pp 759 – 794: http://users.monash.edu.au/~dprice/ndspmhd/price-spmhd.pdf Apart from downloading and installing the NDSPMHD code one will also need SPLASH (http://users.monash.edu.au/~dprice/splash/ ) NOTE: software generally comes with documentation that describes the applied models, tools and schemes. --Thermochemical Equilibrium Blecic, J., Harrington, J. and Bowman, M. O. (2016). TEA. A Code Calculating Thermochemical Equilibrium Abundances. The Astrophysical Journal Supplement Series, 225: 4. 14 pages Stock, J. W. et al. (2018). FastChem: A Computer Program for Efficient Complex Chemical Equilibrium Calculations in the Neutral/ionized Gas Phase with Applications to Stellar and Planetary Atmospheres, Monthly Notices of the Royal Astronomical Society, Volume 479, Issue 1, Pages 865–874 **Lab(s): Will have analysis of the above given articles. Then codes will be developed in Mathematica or whatever. Then will choose various planetary atmospheres, stellar atmospheres and galactic gaseous regions of space and try to confirm with the codes. Code results will be compared with astronomical data (photometry and spectroscopy methods) from various professional sources. --Quasars (existence from another time and other places) Definition, features and time of existence Comprehensive journal article guide: Dermer, C., D. and Schlickeiser, R., (1993) Model for High Energy Emissions from Blazars, Astrophysical Journal, 416, 458-484 [omit this article if it’s too broad, condense and brutal] **Lab: Developing quasar light curves Quasar colour variation The structure function Macleod, C. L. et al, A Description of Quasar Variability Measured Using Repeated SDSS and POSS Imaging (2012), The Astrophysical Journal, Volume 753, Number 2 Note: the above lab areas concern access to data from professional astronomical/astrophysics sources and computational skills to be successful; there may be alternatives to SDSS and POSS. Statistical and computational tools of consideration are R, Mathematica and TOPCAT. Such labs are not just blind activities, rather, students must understand practical goals for doing such and the respective logistics to get there. --Advance recital of Galaxies and Properties leading to the idea of Dark Matter from prerequisite (including labs) --Zavala, J. and Frenk, C. S. Dark Matter Haloes and Subhaloes. Galaxies 2019, 7, 81 --Galactic Potential Models Bajkova, Anisa & Bobylev, V. (2017). Parameters of Six Selected Galactic Potential Models. Open Astronomy. 26. 72-79. **Lab: Replication with fitting results. May also be extended. From the above article, the bulge and disk potentials stem form Miyamoto M., Nagai, R. 1975, PASJ, 27, 533-543 For the halo potential model candidates (models I-VI) the associated mentioned works should be illuminated [such as Irrang, A. et al (2013). Milky Way Mass Models for Orbit Calculations. Astronomy & Astrophysics. Volume 549 A137]; all mentioned works also have further potential model alternatives for halo, bulge and disk. Dinescu D. I. et al related papers may also provide potentials --Globular Clusters and Galaxy Clusters (Synopsis Recital & Augmentation) 1.Synopisis Review 2.Kurth, R. (1955). Stellar Orbits in Globular Clusters. Astronomische Nachrichten, volume 282, Issue 6, p.241 **Lab: Comparative development/replication between the following with appropriate data sources Odenkirchen, M. and Brosche, P. (1992). Orbits of Galactic Globular Clusters, Astronomische Nachrichten. 313, 2, 69 – 81 Malasidze, G.A. and Dzigvashvili, R.M. (1994). On the Orbits of Globular Clusters of Stars in the Galaxy. Astrophysics 37, 350–357 --Recital of Cosmology from prerequisite (topics and labs) ADDITIONAL LABS: will immerse into software for modelling and simulation Bolshoi Cosmological Simulation CosmoSim A. Klypin’s (NMSU) Bolshoi Cosmological Simulation Website MultiDark Database CLUES-Constrained Local UniversE Simulations https://wwwmpa.mpa-garching.mpg.de/millennium/ NOTE: software generally comes with documentation that describes the applied models, tools and schemes. There may be alternatives as well. --Big Bang Nucleosynthesis Focus on Lectures 3 and 4: https://www.astro.uvic.ca/~jwillis/teaching/astr405/ **Lab(s): Big Bang Nucleosynthesis Elements Simulation Code (PRIMAT) < http://www2.iap.fr/users/pitrou/primat.htm > Note: treat documentation before pursuits, augmented with the following Coc, A., Pitrou, C., Uzan, JP., Vangioni, E. (2019). A Public Code for Precision Big Bang Nucleosynthesis with Improved Helium-4 Predictions. In: Formicola, A., Junker, M., Gialanella, L., Imbriani, G. (eds) Nuclei in the Cosmos XV. Springer Proceedings in Physics, vol 219. Springer, Cham. Prerequisites: Space Science I

Tensor Analysis & Riemannian Geometry Such a course is crucial towards realising how symbolic modelling compacts and conceals the true explicit forms of tensors, metrics, connections and so forth when coordinate systems or reference frames are employed. Else, one is really modelling on “sophisticated egg shells” without observing the true “personalities” of manifolds, tensors, fields and so forth. Manual work alone isn’t practical nor constructive towards strong analysis and research. Course will involve computational lab activities and homework for establishing meaningful quantities. Such skills necessary to acquire meaningful computations in General Relativity. Course will pursue algorithm development in Mathematica AND in a more general algorithmic structure that’s generally friendly to any language environment. Course is a huge and worthy investment towards the succeeding course. If you don’t do this, relativity will not seem credible or economic. Often in a non-religious manner, “you have to see it to believe it”, instead of continuously smug “eggshell gunk”. NOTE: this is not mathematical psychadelics wonderlic course; the prime objective is students having the computationally explicit knowledge and skills for general relativity substance. The prime directive of this course is towards physics students with interest in sustainable general relativity studies; there is real purpose after this course. Course doesn’t concern mathematicians bullying and sabotaging students for the sole purpose of mathematicians portraying themselves as invaluable; economics evidently is applicable anywhere. Competence building is expected, but perfection is equivalent to spending your time elsewhere mastering origami or some ergodic trackable nonsense. Yes, perfection is seemingly practical on your own time by yourself. You can’t validate perfection by screwing others over. Course grade: Problem sets 15% Labs 20% 4 Exams 60% Homework --> Problem sets will come from various sources. Homework in this subject can often be discouraging in the sense that problems are not nurturing or seemingly constructed in a deliberate manner to be not retainable. I will try to give problems sets that contain “objects” with highly explicit forms towards tangible purposes. I am not interested in a drastic cosmos of mathematical flattery with no sense of direction. Course concerns having a computational foundation in Riemannian geometry towards General Relativity, and nothing more. Labs --> For labs instructor serves as guide and orchestrates exhibition of concepts; most computational or programming activities are the obligation of students. Exams --> Exams will be mostly based on subjects and activities in course outline. Latter exams will also concern AT LEAST: A. Cases where tensorial objects are given and students must choose the correct code that represents them. B. For tensors of rank 2 with explicit tensor components, students will be asked to provide tensor products explicitly via explicit determination of change of basis pair under tensorial operation stemming from given coordinate transformations. Verification of tensorial preservation among different bases. C. Demonstrating explicitly operations of raising indices, lowering indices, contractions w.r.t. coordinate explicit tensor products: D. Expression for Lie derivatives (on rank 1 and rank 2 tensors) with w.r.t. specified coordinates; includes showing explicitly coordinate transformations and verification of tensorial preservation. E. Expression for covariant derivatives (on rank 1 and rank 2 tensors) with w.r.t. specified coordinates; includes showing explicitly coordinate transformations and verification of tensorial preservation. F. Determining explicit Killing fields and applied coordinate transformations explicitly G. Means of determining whether a chart is adapted to a point; natural basis as orthonormal at a point in neighbourhood(s) of consideration, but not necessarily at other points in such neighbourhoods. Will be explicit, rather than the axiomatic, nauseating and repulsive pile on. In other words, we don’t want nonsense or excrement like the following examples --> Are Prime Numbers Made Up? - Infinite Series - PBS Digital studios: Defining Infinity - Infinite Series - YouTube: I don’t want such above sabotaging, perverted excrement shows, con artist excrement in my course. Such are what being “stuck in a black hole” is really like. I will not encourage the destruction or oppression of talented students. It’s not a student’s fault that a mathematics department doesn’t know the talents of students outside their luxury space (often with rent seeking courses). H. Problems where students must recognise errors in code. I. Problems where students must provide alterations to code to yield desired properties. J. Given code may or may not do what is said. K. Students will be given code for tensors of rank 2 to 4. They will be asked to provide operations upon given code to initiate a raising and lowering of indices, contractions, and scalar product with a vector. L. Tasks mentioned in syllabus Driving Text --> De Felice, F. and Clarke, C.J.S.(1990). Relativity on Curved Manifolds. Cambridge Monographs on Mathematical Physics. Cambridge University Press. Dependent on the severity of conduct infractions, conduct percentage of final grade may warrant amplification to 69%. NOTE: in this course shifts and rotations are not our main focus. Course Outline --> ---Elementary Geometry, Primitive Maps and Linear Algebra (no perverted matrix algebra pig pen goose chases or loitering) A. Topological Spaces, Maps and Coordinate Neighbourhoods Includes coordinate transformations, Jacobian and invertibility. Conformal transformations. Coordinate singularities and removal by transformation. Given EXPLICITLY QUANTITATIVE maps towards realisation of the following properties: Injective Bijective Continuous Homeomorphisms Building explicit coordinate neighbourhoods and atlases; validating and debunking B. Differentiable Manifolds, Maps of Manifolds Establish diffeomorphisms with given EXPLICITLY QUANTITATIVE maps; topics in (A) may come back to haunt. C. Vector space of functions. For function in a span, determine whether a given different function is an element of this span. Is orthogonality or orthonomality implied if an element? For a given function determine the appropriate span. NOTE: some topics from Methods of Mathematical Physics prerequisite having explicit activities can be reintroduced throughout progression (Geometrical Vectors Spaces module, and Properties of vectors spaces in Euclidean space with Application to Coordinates module) D. Tangent Space. Bases in the Tangent Space. Transformation Properties of Vector Components. Tangent Map. Note: any vector can be a tangent vector at a point of interest, if one has the right curve (surface) generator through that point. For vectors in a span, determine whether a given unique vector is an element of this span. Is orthogonality or orthonomality implied if an element? For a given tangent vector determine the appropriate span. Linear algebra comprehension (NOT matrices indulgences and repulsion) Verifying tangent vector spaces Finding and verifying bases in the tangent space E. The Cotangent Space. Bases in the Cotangent Space, and the Dual Tangent Map. For covectors in a span, determine whether a given unique covector is an element of this span. Is orthogonality or orthonomality implied if an element? For a given covector determine the appropriate span. Finding explicit forms of covectors. Finding and verifying dual bases in cotangent spaces F. Developing row vectors, column vectors and matrices in Mathematica. Identifying different basis and establishing the appropriate transformation operators, via modelling. Understanding the interpretation of vectors and covectors respectively involving the use of coordinates. Change of coordinates. Explicit activities of vectors with coordinate transformations and verifying that the values of the components remain invariant; same done for covectors. NOTE: we’re not here for trivial matrix pig pen finesses; don’t assume trivial linear transformations. Establishing that for a given point Euclidean geometry holds (Kronecker delta) via tangent vectors and covectors. ---Tensors NOTE: some topics from Methods of Mathematical Physics prerequisite having explicit activities can be reintroduced throughout progression (Common Tensorial Operators module) A. Recognising vectors and co-vectors as tensors; each an element of a respective vector space. B. Higher Ranked Tensors i. Defining the tensor product and its basis, vector space and tensor transformations ii. Tensor product and its basis. Tensor vector space. Tensor transformations among various coordinates (restricting manual labour coordinate transformation exercises to rank 2 tensors). Explicit change of coordinates for tensor products among the basis vectors. For various coordinate transformations to determine how the basis vectors in the tensor product change and the explicit consequences for tensor components; for a given coordinate transformation how will chosen basis vectors transform. NOTE: will not indulge much on rotations and shifts, because there are more interesting transformations. Among various coordinate systems will investigate how tensor components (within the tensor product) adjust to preserve equivalence in the manifold. Can we identify explicit images of such components based on homeomorphisms being the explicit coordinate transformations? iii. Contravariant, Covariant, Mixed (restricting manual labour coordinate transformation exercises to rank 1 and rank 2 tensors). iv. Tensor Product between Tensors v. Geometrical exhibitions of tensor components and applications to fluids and other continuum materials. Here will identify tensors in the physical sciences and apply various coordinate transformations as practice and verifying preservation. C. Symmetry Operations D. Tensors in Mathematica’s “Documentation Center” towards sections (A), (B) and (C); will employ tensors of various rank, order and mixed cases https://reference.wolfram.com/language/guide/Tensors.html E. Metric Tensor i. Properties of interest: Non-degenerate, Positive Definiteness, Symmetry, and Triangular inequality? Will pursue cases studies to determine whether examples are ideal or cases of being pseudometrics, quasimetrics, metametrics, semimetrics, etc; behaviours under basis/coordinate transformations will also be investigated (shifts and rotations are not primary interests), namely, verification of conserved quantity under transformation. ii. Make use of the differential representation of the distance formula to find the circumference of a circle. Under a change of coordinates (besides rotations and shifts) confirm circumference is conserved. On a general curved surface will all such be the same? iii. Sum of the interior angles of a triangle on a sphere; will observe angular measurements of spheroidal geometries with increasing eccentricity. Surface area on a sphere, compared to the area of its flat planar circle projection; generalisation to topography where surface functions are decent. The surface activity may also be extended to the case of a sphere with increasing eccentricity. iv. Review definition of the metric tensor and its properties. v. Manifestation of the metric components in matrix form w.r.t to chosen basis vectors. With such students may be given validation tasks for the properties of the metric tensor. vi. Coordinate singularities and means to remove them. vii. Isomorphisms between tangent space and cotangent space. Expressing a vector in terms of its covector and the metric, and vice versa; will try to confirm this also explicitly in various coordinates. At point p, is the inner product of two tangent vectors equivalent to the inner product of their dual covectors counterparts? Validate among various coordinate systems. viii. Riemannian manifold Locally, transforming the general metric into a “Lorentzian” signature by choice of matrices (1.15.21); manually verified by examples are needed. Locally, for two orthonormal vectors their inner product yielding a “Lorentzian” signature. Locally, an orthonormal vector expressed in terms of a natural (coordinate basis) concerned with (1.15.23 through 1.15.32); manually verified by examples, then computationally verified. Finish up with pp 46; manually verified by examples, then computationally verified. F. Raising and lowering of tensor indices (includes contractions). Will need to show this explicitly among different coordinates. G. Computationally verify that the metric tensor with its inverse admit Euclidean geometry locally (applying various coordinates). Developing the metric tensor in Mathematica and verify prior. H. Concerning equations (1.18.16) through (1.18.19) will provide a “run around the ogre” explanation that’s tangible, say, solely towards the interest of physicist (not a mathematician). Will like to computationally exhibit the statement following equation (1.18.19) among various explicit charts, with condition of orientation preservation; will not get into the acid bath or tar pit that’s equation (1.18.20) to (1.18.24). ---Differentiation A. Tensor Fields and Congruences B. The Lie Derivative For computational purposes to be confined to the commutator with vectors, covectors, and operation on rank two tensors. Includes some manual practice with vectors and covectors w.r.t to chosen coordinates. Will be applying explicit vectors, covectors and rank two tensors to verify tensorial preservation, namely, from operation verifying that transformations and measure computations are preserved among various explicit coordinate systems. C. The Connector I. Properties: Linearity, Consistency, Parametrization Independence, and Differentiability. Can one find explicit maps that satisfy all 4 prior restrictions? II. Verify that tangent vectors at different points on a curved surface (of no inflection) will never reside in the same plane. D. Parallel Propagation After analysis, will make use of special geometries like spheres and ellipsoids (with interpolating one-parameter family of curves) to explicitly demonstrate (2.4.1) to (2.4.12). Must have ingenuity to avoid crashes with “dense” or “vague” symbolic objects. E. Geodesics After analysis extend prior in (D) towards (2.4.13) to (2.4.19) have explicit forms with substance. F. Transformation Properties of the Connector and Connection After analysis, will like explicit cases for the connector, vectors and basis vectors, and the resulting consequences from (2.5.1) to (2.5.6). G. Manually acquire the Christoffel symbols for chosen coordinates via Euler-Lagrange equations. Compare with developed code for Christoffel symbols. H. The Covariant Derivative Includes some manual practice with vectors and covectors w.r.t to chosen coordinates, and limited practice with rank two tensors w.r.t to chosen coordinates. Includes verifying tensorial property among various coordinates after operation. For computational purposes to be confined to vectors, covectors, and operation on rank two tensors w.r.t to chosen coordinates. I. Torsion and Normal Coordinates After analysis, will have explicit environments case examples to validate (2.7.19) and (2. 7.10); from explicit structuring it may also be possible to yield agreeing results in Mathematica. J. Compatibility of Metric with the Connection (leading to the Christoffel symbol) After analysis, will also administer explicit case examples. K. Parallelism Given explicit environments, what does (2.9.5) look like? Can you recover the conventional expression for the geodesic equation? How should such be developed in Mathematica? L. Covariant Derivative Applications (Divergences of tensors of various rank) Will pursue means to verify divergences (2.10.7) based on (2.10.5) and (2.10.6). M. Isometries on the Manifold, and Problems of finding a Killing field w.r.t. to a given metric in terms of the Lie derivative. Finding Killing fields that are space-like and time-like respectively w.r.t to the given metric. Determining forms of Killing fields due to coordinate transformations involving the metric. N. Lab(s): Quick review of B, E, G, H, I, L & M Topics B, E, G, H, I, L & M to be coding exercises in Mathematica. For Lie derivatives and covariant derivatives, on exams you will be asked to operate on covariant, contravariant, and rank 2 tensors (consider different valences) with respect to different coordinates. On some exams you will be given coordinates and must determine the associated metrics, hence determination of the Christoffel symbols. With the geodesic equation to provide explicit forms. I may ask to apply coordinate transforms based on given substitutions. ---Curvature I. Mapping an arbitrary vector from some point by the connector into a different vector at another point using two unique paths; difference between v(q) and v’(q) depends on the curvature. Can one develop explicit case examples concerning (3.1.2) to (3.1.6)? What do the higher order terms in (3.1.6) look like?For (3.1.7) comprehend why it is an approximation, and the possible consequences of only assuming the approximation with the parallel propagation difference. Can one elaborate with explicit cases? Moving forward, prematurely, we may often require exposure to non-flat metrics for constructive development; as well, verifying that a single chart is not adapted to all points the manifold; the curvature tensors them selves to indicate non-vanishing results from the metrics applied. In explicit environments cases, can one synthesize (3.1.8) for the respective environment? Assuming that the fifth term in (3.1.8) vanishes due to natural or local coordinates, appropriately identify each of the first four terms from the messy stuff. How does one programme the left-hand side of equations (3.1.9) and (3.1.10), and likewise for the right-hand side of such equations? Concerns verification of the Ricci identity. II. Explicit Verification of Torsion Free Condition III. Symmetry Properties IV. Ricci Tensor, Curvature Scalar, and the Weyl Tensor V. Consequences of conformal transformations (3.4.18) on the Riemann tensor, Ricci Tensor, Curvature Scalar, and the Weyl Tensor. We want explicit examples. VI. Bianchi identities. What do we understand about them? VII. Equation of Geodesic Deviation Note: comprehending the purpose and properties of (3.6.11) and (3.6.12) are important. VII. The Covariant Derivative of the World Function Note: overall, taking the authors’ word is not good enough. The calculus and terms may seem exhausting. Computational environment development is expected in labs. Make sense of the higher order terms in (3.7.18) to (3.7.21). VIII. Maximally Symmetric Spaces IX. Labs: Quick review of subsections I-VIII Subsections I-VII to be coding exercises in Mathematica. The consequence of applying the Minkowskian and Euclidean metrics to the Riemann tensor, Ricci tensor and curvature scalar. In some parts of exams I will give explicit vectors based on whatever coordinate system, where metric must be established, and to show ability to provide expect components of the Christoffel symbol(s). I will not ask you to explicitly write all components of the Riemann curvature tensor (RCT), however for an explicit vector with inner products one should be apple to convey how the components of the RCT are affected or acted upon; will have similar tasks for raising and lowering indices. ---Frobenius Theorems (if time permits) If time permits and students are willing, sections 2.12 and 2.13 can be tackled in a special lab. We just don’t want to see such two sections as a fancy “vault with no accessibility”. In a non-religious sense, say, “seeing is believing”. Namely, will try to establish all in an explicit environment for substance; may spell doom for structure coefficients due to the need of specifying explicit coordinates for meaningfulness, but hopefully all isn’t lost. Prerequisites: Numerical Analysis, Methods of Mathematical Physics, Upper level standing Computational General Relativity: Course concerns models and computation towards the confirmation of General Relativity, and its usefulness towards Astrophysics. Firstly, students must come to terms with the difference between LAWS of gravitation and the General THEORY of Relativity (GTR). Despite exact solutions for the Einstein Field Equations, they are in fact ideal descriptions, firstly understanding that not all astrophysical bodies are black holes. For the space-time solutions considered the respective coordinate configurations and metric components to be provided. The space-time geometry for any considered respective solution of Einstein Field equations will be described based on the symmetries of the space-time (Killing fields), frames and the respective metric with considered appropriate coordinate configurations. Symmetries of a respective ideal space-time solution in regards to Hamilton-Jacobi equations and geodesics are described in short. Course emphasizes an environment and tone of manoeuvrability towards ability for computation, rather than a non-explicit mathematical swamp lacking accessibility and purpose. Hence, will pursue descriptions that are as explicit as possible (all the way down to vectors, covectors and reference frames applied with coordinates, so the real value in labour isn’t diminished). “Egg-shell” formulation and models are not good enough, say, for example, an explicit form of the Hartle-Thorne metric may at least take up a whole page, then to imagine what happens when you apply such to Christoffel symbol, covariant derivative, Einstein Tensor and other things. What do you gather by just watching the “egg shell” alone? Pen and paper creepy cults and chalkboards/sharpie-boards are extremely limited. Don’t be the short-term con-artist, and the long-term sucker. Thus limits of “realistic” astrophysical bodies such as the sun, various star classifications and discs can be treated; may or may not be tedious and intricate with parameters and boundary conditions. Use of scientific computation will be involved considerably based on what was accomplished in the expressed prerequisite for this course; without such activity studying general relativity becomes daunting and extremely limited. Course is generally structured around the Cambridge University Press book of De Felice & C. J. S. Clarke; else the designated journal articles to be incorporated. Course is geared towards substance, a tangible structure and useful retention. Students should be vigilant against con-artists known for hoodwinking others with mathematical memorization of trivial problems and complex expressions; subjects taught in this course are the most practical and relevant, unique to faux intellect that amounts to nothing through and through. Acquiring a niche with such subjects equates to ability towards meaningful computational research. Students are responsible for various computational activity stemming from knowledge of the TARG prerequisite. Overall, the physics major is quite tasking. This course isn’t designed to accommodate one with the luxury of a mathematician’s career to memorizing everything of specialties and indulgence to pick at others with sheltered impudence. However, a few things need to be basic knowledge in memory. Course concerns building a tangible foundation with manoeuvrability. One will never find everything in one text, namely, most of the tangible things will be found in journal articles. Hence, a student may become more useful than rigid modelling practitioners. Like what you do, regardless of those who are premier and privileged. Driving Text (MANDATORY) --> De Felice, F. and Clarke, C.J.S. (1990). Relativity on Curved Manifolds. Cambridge Monographs on Mathematical Physics. Cambridge University Press, 448 pages. Text for problem sets --> Moore, T. A. (2013). A General Relativity Workbook, University Science Books. NOTE: book of Moore will not replace the given driving text because there are many things that are unique to the text of De Felice & Clarke. Software of Interest --> Mathematica Black Hole Perturbation toolkit < https://bhptoolkit.org/toolkit.html > Einstein Toolkit (on Github) Loffler, F. et al (2012). The Einstein Toolkit: A Community Computational Infrastructure for Relativistic Astrophysics. Classical and Quantum Gravity, volume 29, Number 11 Kranc < http://kranccode.org > Note: concerning explicit reference frames, vectors, covectors, metrics, other tensors and the Christoffel symbol, the mentioned other software will not replicate the economics of Mathematica labour; other software serve very specific purposes. Prerequisite is highly economic. Course grade: Homework problem sets and computational assignments 25% Note: some of the topics from course outline will be designated for homework assignments. Homework will also involve computational usage involving tensorial structures with metrics and other compact objects whose essence can’t be directly observed; skills from prerequisite must be retained to be successful. Some developed problems or exercises will also come from journal articles and other sources as well. Solutions will be provided at appropriate times. Some topics in course outline will be computational assignments where professor may only provide analytical structuring. Treatment of solutions (done after respective due date) will be part of some (not all) lectures. Attendance and conduct 15% Dependent on the severity of conduct infractions, conduct percentage of final grade may warrant amplification to 69% impounded. 4 Exams 60% Exam questions will be based on lectures, driving text, text of Moore, homework, journal articles, and prerequisite (ALL SUCH ELEMENTS). COURSE OUTLINE: ---Spacetime Manifold This is NOT A COURSE FOCUSED ON SPECIAL RELATIVITY. MOST OF THE COURSE WILL CONCERN GENERAL RELATIVITY. MOST OF THE TIME WILL BE APPLIED TO GENERAL RELATIVITY. READ THE TITLE OF THE COURSE. Will identify the types of matter relevant to special relativity and move on. For honourable mention concerning the Lorentz transformations the following are the well-known derivations --> Albert Einstein, Morgan document, 1921 Minkowski, H. (1909), " Raum und Zeit", Physikalische Zeitschrift, 10: 75–88 Feynman, R. P. (1970). “21 – 6. The Potentials for a Charge Moving with Constant velocity; the Lorentz Formula”. The Feynman Lectures on Physics, 2. Reading: Addison Wesley Longman A. Comprehending the construction of the spacetime manifold. Why is the spacetime manifold concept needed? Matter and fields relevant to non-classical such descriptions. What settings must reside to make special relativity relevant? B. Issues of concern Minkowski metric and various explicit transformations Writing four-velocity vectors explicitly in Lorentzian space and coordinate transformations; expected to know how to express four vectors explicitly in terms of coordinates with incorporation of relativistic parameters (same for acceleration and momentum vectors). Differentiating between ordinary coordinates transformations and Lorentz transformations. Lorentz transformations under coordinate transformations, say, if not interested in “Cartesian-like representation”, rather going from (t, x, y, z) to cylindrical coordinates or spherical coordinates or other with the Lorentz transformations; particles, electromagnetic fields for such. C. Some special relativistic physics 1. What settings and conditions lead to the theory without consideration of gravity? Clarify how Newtonian descriptions fail or are inadequate, concerning the appropriate types of matter, and frames of consideration, etc. 2. Postulates, Simultaneity & Lorentzian frames, Minkowski space-time, idea of four-momentum. 3. Statement to prove or disprove: It’s said that a massive particle is relativistic when its total mass-energy (rest mass + kinetic energy) is at least twice its rest mass. This condition implies that the particle's speed is close to the speed of light. According to the Lorentz factor formula, this requires the particle to move at roughly 85% of the speed of light. 4. Electromagnetic momentum and the relativistic dispersion relation (RDR) How would we model electromagnetic waves carrying momentum based on Faraday-Maxwell physics? Is prior equivalent to momentum found via Planck’s constant and wavelength? Radiation pressure in space Comet trajectory perturbations. Will pursue means of determining radiation pressure on comets and/or satellites based on trajectory data and/or accelerometer data in the solar system; hopefully any other influences can be isolated from radiation pressure (such as atmospheric drag, various gravitational influences, etc., etc.). Probes throughout the solar system may also be applicable with their data. Solar sailing Relativistic dispersion relation (RDR) Origins and purpose Derivation methods based directly on physics Is momentum observed in RDR the same as momentum of electromagnetic waves? 5. Velocity Time Dilation. Velocity addition formula/light in moving media. Mass-Energy equivalence. Can bulk matter objects (like a coin, cricket bat, bullet, cocktail) ever operate under special relativity for length contraction to take place? Can any particle accomplish FTL travel? Is there a limit to relativistic mass, and if so, what determines such? 6. Is there a limit to relativistic mass, and if so, what determines such? 7. Additional elementary modelling: https://www.astro.umd.edu/~miller/teaching/astr498/srpractice.pdf 8. Tensors in special relativity: SR Energy-Momentum tensor and Electromagnetic tensor. In what ways are they applicable? 9. Particles relevant to special relativity based on 1 through 5. 10. Aleshkevich, V. A. (2012). On Special Relativity Teaching Using Modern Experimental Data. Physics-Uspekhi 55 (12) pp 1214-1231 D. Tensors and Other Things in Minkowski Spacetime: i. For Minkowski spacetime to investigate the influence of Lorentz transformations on tensor products explicitly with the basis vectors. Namely, for the explicit basic vectors (based on actual coordinates) in the tensor products, how such transformations effect their forms, as well as components of the tensors considered. ii. For the Electromagnetic field tensor will see how the Lorentzian transformations affect the tensorial components explicitly. Will the “axiom” of the speed of light being the limit prevail? ii. For the energy-momentum tensor will see how the Lorentz transformations affect the tensorial components explicitly. E. Vector spaces and tetrads for spacetime manifold What makes a tetrad unique to general bases? Concerns sections 4.1, 4.2, 4.4 and 4.5 in De Felice & Clarke text. Note: section 4.3 (pages 135 - 137) to be excluded because it’s a highly “viscous” and unimaginative description; consider it as structured for one’s own personal interest. Otherwise, encouraging such environment can encourage out-of-place, parasitic, toxic and degenerate “elements” that only take up unnecessary time and rot out fluid and tangible development and sustainable skills. For such four sections you will have to establish many things in a explicitly tangible manner to identify meaningfulness. Computational verification of equations (4.1.5), (4.1.6), (4.1.9) and use of various coordinate bases or coordinate transformations. How does one explicitly identify the metrics in (4.1.11) and (4.1.12)? Why tetrads and not “bases”? Do all tetrads satisfy (4.2.2)? What conditions must be met to satisfy (4.2.2)? With respect the Minkowski metric what forms can the four set of vector fields have? Develop a sufficient means to produce different tetrads. Concerning (4.2.12) how does one characterise spacetime without coordinate representation? F. The measurement of time intervals and space distances, section 9.2, pages 275 - 280. Much of this section will not be computationally accessible without application of meaningful reference frames (and coordinates). Will like manual justification of equation set (9.2.10), accompanied by explicit computational findings; likewise for other other things. Overall, for section 9.2 accessible substance needs to be established for computation usage. NOTE: sections 9.3 to 9.6 are optional, however if pursued, accessibility will depend on application of meaningful reference frames (and coordinates). Skills from prerequisite course will be needed. G. Velocity composition law, section 9.7, pages 295 - 297. For equations (9.7.1) to (9.7.10) will like to consider “real world” case examples for experiments, say, experimentation satellites with explicitly defined frame features. Hence will consider “observers” involving various reference frames (and coordinates) to situate or make such equations explicit in form. To confirm the velocity composition law is invariant. Overall, for each observer will consider a unique reference frame, being a robust condition to validate the velocity composition law; many case exercises are possible. Reference of interest: De Felice F. (1979). On the Velocity Composition Law in General Relativity. Lett. Nuovo Cimento 25, 531 Reconciling the velocity composition law in section 9.7 with the basic Lorentz Velocity Transformation Law from (B) Is the “metric” after equation (9.7.7) equivalent to equation (9.2.21)? H. Propagation Laws for tetrads (pages 138 - 139) Verify with explicit reference frames I. Fermi-Walker Transport Lambare, J. P., Fermi-Walker Transport & Thomas Precession, Eur. J. Phys. 38 (2017) 045602 (11 pp). Bini, D., de Felice, F. and Jantzen, R. (1999). Absolute and Relative Frenet-Serret and Fermi-Walker Transport, Class. Quant. Grav. 16, 2105 Note: for prior two journal article there will be effort to provide explicit examples for the equations to exhibit good transparency, rather than just plain memorization of “egg shells” models. In addition, there will be emphasis to identify consistency in structure between (H) and (I); computational exhibitions may accommodate such. j. Ricci Rotation Coefficients (pp 139 - 141) The tetrad case of the Christoffel connection (pp 139 - 141). How does this look in terms of a respective metric (w.r.t. explicit tetrad frames)? Can equation (4.5.6) in any way serve as a measure of rate of precession related to the Lense-Thirring effect? ---Equivalence Principles Origin of general relativity lies in Einstein's attempt to apply special relativity in accelerated frames of reference; adding acceleration as a complication to formulate. An immediate consequence of the equivalence principle being, gravity bends light. Yet, for the elevator problem what significant amount of acceleration is required to observe the bending behaviour? For very small accelerations, how similar will such accelerated frames be to non-accelerated frames? 1. Weak Equivalence Principle (WEP) i. The property of a body called “mass” is proportional to the “weight” ii. The trajectory of a freely falling “test” body not influenced by electromagnetism and too small to be affected by tidal gravitational forces) is independent of its internal structure and composition. iii. Dropping two different bodies in a gravitational field, the bodies fall with the same acceleration 2. Einstein Equivalence Principle (EEP) i. WEP is valid. ii. The outcome of any local non-gravitational experiment is independent of the velocity of the freely falling reference frame in which it is performed. This is identified as Local Lorentz invariance (LLI). Note: come up with examples and prove. iii. The outcome of any local non-gravitational experiment is independent of where and when in the universe it is performed. This identified as Local Position Invariance (LPI). Note: come up with examples and prove. iv. Behaviour of photon wavelengths when traversing against a “gravity well” according to EEP. How does the EEP diverge from the postulates of special relativity? How are tetrads relevant to EEP? Do tetrad frames appease the EEP conditions? ---Development of Einstein Field Equations (pages 185 - 195) A. Newtonian Fluids 1. Convective derivative: a derivative with respect to a moving coordinate system. Does such derivative have coordinate invariance? From the perspective of an “observer” with a different frame (stationary or in motion), is the convective derivative meaningful and existent? Note: one may even consider an “observer” with some form of acceleration. Physics and mathematical structure for all such questions should be developed. 2. Are equations (6.1.2) through (6.1.6) tensorial? Verify. 3. Concerning the set of equations in (6.1.9) one must definitively identify the unique physical characteristics each equation is responsible for. Excluding plasma, will such set of equations be characteristic of all states of matter? Is all of (6.1.9) subject to the Newtonian gravitational potential influence among “bulk matter” interactions if its “Newtonian”? In (6.1.10) what does the lack of symmetry, or, lack of equality imply? Is it an issue of physical measure/nature (nature of the Newtonian beast)? 4. In the Faraday-Maxwell realm determine the electromagnetic counterpart to (6.1.9) and (6.1.10). Is there such “non-symmetry” or “non-equality” issue? B. Generalization to Special Relativity; problem of no gravitation 1. In the beginning of section 6.2 on page 187, to have proper analysis of the following: “Hence momentum density and energy flux density must be equal, up to a factor of c^2, so the special relativistic form of the matrix [requires symmetry, or alpha-component of the momentum density be equal to alpha-component of the energy flux density up to a factor c^2]”. Develop a sound physics and mathematical structure for such, namely, elaborating on “up to a factor c^2″. As well, “while the space-space components [..] remain symmetric in order to ensure the torque balance of any isolated fluid configuration.” For such a statement one must have arguments beyond such crude “matrix” rational, because physics must “add up” at the end of the day, hence, one also needs to convey this argument in terms of physics. For (A3), in terms of SR one must elaborate or reinforce the SR foundation. 2. Considering the types of matter applicable to special relativity with reference frames, will (6.1.9) be uncharacteristic of (6.2.1) concerning “free falling” and matter interactions? 3. Note: one should hold on dearly to the form of the “fluid” four-velocity accompanying equation (6.2.1), concerning not becoming embarrassed when computational activity arises. Other circumstances may be coordinate or frame transformations applied. C. The Field Action (pages 188 to 191) D. Gravitational Action and Einstein Equations (pages 191 to 195) ---Geodetic Effect and Schiff’s formula In the curved spacetime of general relativity, Thomas precession combines with a geometric effect to produce de Sitter precession (or geodetic precession). Note: such mentioned precessions must also be distinguished from Lense-Thirring precession, and known means to distinguish between such through experimentation. <Buchman, S., et al. (2000), The Gravity Probe B Relativity Mission, Adv. Space Res. Vol. 25, No. 6, pp. 1177-1180> <Conklin, J. W. (2008) The Gravity Probe B Experiment and Early Results. Journal of Physics: Conference Series, Volume 140, Number 1> <Gerlach, E., Klioner, S., Soffel, M., Consistent Modelling of the Geodetic Precession in Earth Rotation. In: VII Hotline-Marussi Symposium on Mathematical Geodesy, pp 307-311, Proceedings of the Symposium in Rome, June 6-10, 2009. Springer 2009> <Trencevski, K., and Gelakoska, E., G. (2011), Geodetic Precession and Frame Dragging Observed far from Massive Objects and Close to a Gyroscope, Cent. Eur. J. Phys. 9(3), 654 - 661> <Hajra, S., Classical Interpretations of Relativistic Precessions, Chin. Phys. B, Vol. 23, No. 4 (2014) 040402>. Focus on Chapter 6. <Nordtvedt, K., On the Geodetic Precession of the Lunar Orbit, Classical and Quantum Gravity, Volume 13, Number 6> <C. W. F. Everitt et al. (2015). The Gravity Probe B Test of General Relativity. Class. Quant. Grav. 32, 224001> Recalling the Geodetic effect and Schiff’s formula for the combined gyroscope precession, and observing the Einstein tensor, which curvature term or form measure is most relatable to the geodetic precession term in Schiff’s formula when metric is applied computationally? ---Alternative Frame-Dragging Experiments Ciufolini, I., Pavlis, E., & Peron, R. (2006). Determination of Frame-Dragging using Earth Gravity Models from CHAMP and GRACE. New Astronomy, 11(8), 527-550. Identifying explicitly the mentioned gravity models and models used in the orbital analysis will be crucial. Assimilating the real data towards analysis and modelling will be crucial, and to be compared to analytical development. Our results serve to compare findings with the Gravity Probe B results. Supporting article: Renzetti, G. (2014). Some Reflections on the Lageos Frame-Dragging Experiment in View of Recent Data Analyses. New Astronomy 29, pages 25 – 27 ---Energy-Momentum Tensor for different types of matter A. Energy-Momentum tensor of Incoherent Matter (dust) Constituted by the proper density of the flow and the four-velocity of the flow. Express the components of the four-velocity in terms of the usual special relativity speed factor (gamma), following by the energy-momentum tensor in terms of such factor. If a matter field of dust with some proper density and some 3-D velocity flows past a fixed observer, what will that observer measure as the density? What would be the relativistic energy density of the matter field? http://ion.uwinnipeg.ca/~vincent/4500.6-001/Cosmology/EnergyMomentum_Tensors.htm B. Energy-Momentum Tensor of a Perfect Fluid (pages 195 -198) C. Note: for (B) consider the following cases: Part a Star with a spherically symmetric density that rotates about an axis with angular velocity omega (slowly rotating star, Kerr geometry, etc., etc.) Oblate counterpart Part b Based on part A to identify the explicit components of the four-velocity Identify explicitly the spatial vector components. Part c Completely explicit descriptions of the energy-momentum tensor of a perfect fluid, and verifying the symmetry. Part d Based on (a) through (c ) may also request various reference frames. Followed by different observers with highly unique reference frames, how to relate their measurements D. Energy-Momentum Tensor of a Single “Particle” (pages 198 - 200) E. Energy-Momentum Tensor of the Electromagnetic Field (page 200) F. Energy-momentum of a scalar field G. For a general relativistic energy-momentum tensor abiding by (6.3.6a) or (6.3.6b) identify the Lagrangians for various fields (single particle, perfect fluid, EM field, scalar field, (6.5.12), (9.10.11) and (9.11.1)) and show that they abide by either (6.3.6a) or (6.3.6b); as well for dust. Such exercises are means to vindicate section 6.3. Consider why (6.3.6a) and (6.3.6b) yield the same result as the variational principle. For each type of energy-momentum tensor students will be responsible for correctly matching the components with components of the Einstein tensor (with proper explanation). H. Various energy-momentum tensors in different reference frames. Various energy-momentum tensors under different coordinate transformations; confirm equivalency among the different representations. ---Curvature measures w.r.t. various metrics (involves algorithm development) Metrics of concern to be applied prematurely: Euclidean, Minkowski, Schwarzschild, Weak field metric, Earth metric, Kerr, Kerr-Newman, Slowly rotating black hole. All such metrics for --> Metric scalar Connection coefficients & resulting geodesic equations Riemann Curvature tensor Ricci tensor Curvature Scalar Compare results with computational development. As well, how do the commutations with covariant derivatives leading to the Riemannian curvature tensor in Riemannian geometry differ to commutations with covariant derivatives in special relativistic spacetime? ---Energy-Momentum Pseudotensor (pages 201 - 205) Concerns incorporation of the Einstein complex, Landau & Lifschitz superpotential, and the complete equations of conservation (with computational interest). Explicit computational expression of the energy-momentum tensor of a perfect fluid for chosen metrics. Explicit computational expression of the energy-momentum tensor of a single particle for chosen metrics. Computational explicit expression development for equation (6.8.8) from De Felice and Clarke pp. 202 for chosen metrics, and the Landau & Lifschitz super-potential for chosen metrics. Note: the following may accompany pages 201 - 205 of De Felice and Clarke; may or may not make things more explicitly computational Babak, S. V. and Grishchuk, L. P. (1999). Energy-Momentum Tensor for the Gravitational Field. Physical Review D, 61, 024038 < https://cds.cern.ch/record/392913/files/9907027.pdf > ---Speed of Gravity in GR Haug, E. (2019). Extraction of the Speed of Gravity (Light) from Gravity Observations Only. International Journal of Astronomy and Astrophysics, 9, pages 97-114. Concerning mass-energy-momentum (MEM) configurations and the curvature of the background geometry, such (non-radiative) curvature stemming from a metric isn’t identified with speed. ---Description of matter in the background geometry: Astrophysical considerations for gravitational dominance, classical electrodynamics or special relativity (rubric): v/c test (v being the magnitude of velocities of matter within system) Ratio of summed electrostatic force to gravitational force Ratio of pressure to density Jeans Instability and Jeans Length E-M frequency change in gravitational fields (to determine metric) -Example candidate metrics in environment Weak field limit versus Newtonian gravity Hartle-Thorne metric Solar metric (deduced from the Hartle-Thorne metric) Earth metric -Two static observers bound in orbital plane of constant radial orbit One observer is radially further away from source than the other Apply first metric component for point A and point B Find ratio with such two; frequency change from point A to B Ratio of length scale of curvature to typical size of system Examples to apply to such environment rubric: 1. Molecules of an ideal gas under the Maxwell distribution 2. Molecules of a gas subject to increasing temperature 3. Solar emissions Coronal plumes, solar flares, Mass ejections Cosmic jets, pulsar beams, quasars, blazars 4. Astrophysical environments Sun’s magnetosphere Pulsar magnetosphere Pulsar atmospheric mechanisms, pulsar cascades from pair creation Magnetohydrodynamics Magnetic flux frozen into accretion discs Earth-Atmospheric Clouds (lowest to highest) Earth-Moon Solar system Galaxy forms Galaxies clusters Diverging galaxies 5. Einstein-Maxwell equations (not treating n-forms nor any exterior algebra) We are concerned about purely electromagnetic energy within background geometry to alter the background’s geomtery. The following journalarticle is one probable treatment, however, use of equation 11 in such journal article instead of conventional (7.6.2) of de Felice and Clarke is cause for concern that needs to be vindicated Maknickas, A. A. (2013). Biefeld-Brown Effect and Space Curvature of Electromagnetic Field. Journal of Modern Physics, Volume 4 No.8A, Paper ID 36094, 6 pages Without consideration of any bulk mass attribute, what amount of electromagnetic energy in a specified volume of space can induce curvature effects? Consider energy formula(s) for electromagnetic waves in a modern physics setting, then consider compact masses that are in the vicinity of at least weakly general relativistic; such will give a guage on the least energy required. Make an interesting choice of region size, say, the Sun with it’s mass to radius scale as a beginner case because dispersion is relevant w.r.t. to energy present. Assuming purely electromagnetic ejection, can pulsar beams or magnetars or Gamma-ray bursts qualify (for ejection volume w.r.t to energy) to directly investigate? ---Tests for at least a weak general relativistic system (rubric) 1. For a system that’s gravitational bound being at least weakly relativistic, then all forms of energy density within the system must not exceed the maximum value of the Newtonian potential in it; (Newtonian) potential being a function of the average mass density, typical size of the system, and the Newtonian gravitational constant. 2. Velocities of gravitational bound objects within the system must not approach the speed of light. 3. Potential must be greater than or equal to the order of magnitude of the velocities of the matter within the system squared. 4. For the (Newtonian) potential described it must also be greater than or equal to the ratio of (uniform) pressure-and average mass density ratio as well. Note: verify all such for the Earth-Moon system, planets with satellites, solar system, small asteroids with satellites. Are all such 4 also valid for star clusters and galaxy clusters? 5. Based on such prior 4 elements what additional conditions permit differentiation between the small curvature limit, the Earth metric and the Solar metric? 6. For all matter with mass, Newton’s gravitational law is fundamentally applicable, yet actual the orbits of natural satellites must be further distinguishable from fundamentalism: a descriptive model beyond two distinct arbitrary mass objects with arbitrary distance between them; asteroid and its satellites don’t always necessarily collide. Beyond fitting mathematical models (Kepler) based solely on observations which don’t explain precessions and other things. What limit can provide a good model for a small asteroid with satellites? ---Further evidence of non-Newtonian gravitational effects in the solar system A classical case would be Mercury’s perihelion, and others ---Test of Shapiro Delay van Straten W., et al (2001). A Test of General Relativity from the Three-Dimensional Orbital Geometry of a Binary Pulsar. Nature 412(6843): 158-60 Our concern is coherent and tangible development of the logistics for such development, followed by raw data collection to complete the test. There may or may not be more “operationally accessible” articles concerning pulsar use. Furthermore, other known Shapiro delay tests with closer astrophysical bodies or satellites can be replicated. ---Geometry of Congruences NOTE: will exclude section 8.3 Much of this chapter isn’t much transparent or constructive without computational activity development; one needs to see beyond the “egg shells” exhibited to really have use for this chapter. For computational development chosen equations will be pursued that fluidly benefits other modules in course layout. Applying tetrads and coordinate systems. What “classical” terms or measures can be recognised/synthesized from the explicit complication? As well, concerning equations (8.1.21) and (8.1.22) with relativistic fluidodynamics to comprehend what types of matter are considered, and whether they are astrophysically feasible --> Ellis G.F.R. (1967). Dynamics of Pressure Free Matter in General Relativity, J. Math. Phys. 8, 1171 Stewart, J.M. and Ellis, G.F.R. (1968). Solutions of Einstein Field Equations for a Fluid which Exhibits Local Rotational symmetry. J. Math. Phys. 9, 1072 Will try to make sense of relation between (8.2.11) and (8.2.12), namely, what the additional terms in (8.2.11) really represent. Concerning section 8.4 may be asked to pursue computational development for verification. In addition, equations (8.4.1) and (8.4.3) are two of those to be concerned with for the future. Section 8.5 can be useful for Newman-Penrose formalism (but will not get into), and as well to some extent gravitation waves. Else, with personal luxury such section will find much use with the following text: Stephani, H. et al (2009). Exact Solutions of Einstein’s Field Equations. Cambridge Monographs on Mathematical Physics. Cambridge University Press ---Energy Conditions Based on Wikipedia, for the relativistic classical setting for general relativity an energy condition is one of various alternative conditions that can be applied to the matter content of the theory when it is either not possible or desirable to specify this content explicitly. The hope is then that any reasonable matter theory will satisfy this condition or at least will preserve the condition if it is satisfied by the starting conditions. [Layman’s terms interpretation to pursue]. Additionally, energy conditions are not physical constraints per se, but are rather mathematically imposed boundary conditions that attempt to capture a belief that "energy should be positive". Many energy conditions are known to not correspond to “physical reality”, say, the observable effects of dark energy are well-known to violate the strong energy condition. In general relativity, energy conditions are often used (and required) in proofs of various important theorems about black holes, such as the no hair theorem (which basically identifies the properties appropriate to characterise a black hole) or laws of black hole thermodynamics. Reverting now back to practicality for a beginner seeking a real foundation, hence, no sabotage, toxicity and hoodwink. Hohmann, Manuel (2014). Selected Topics in the Theories of Gravity (restricted to sections 1 and 2): http://kodu.ut.ee/~manuel/teaching/2014_kv_gravity/lecture02.pdf To get straight to the point, without wasting brain cells on perversion, simply determine what makes application of an eigenvector meaningful, rather than things just falling straight in your face based on the mathematician’s interest of toxicity and sabotaging fantasy (a rat nest). Pursue explicit examples of eigenvectors relevant to the background geometry, yielding whatever special property, and why to take advantage of such. The two sections to be restricted to in the above literature provide a decent “deduction” for the weak energy condition. Note: pursue the other conditions as well in such a manner. Further rewarding literature for the energy conditions: Martín–Moruno P., Visser M. (2017) Classical and Semi-classical Energy Conditions. In: Lobo F. (eds) Wormholes, Warp Drives and Energy Conditions. Fundamental Theories of Physics, vol 189. Springer, Cham. Now then, concerning section 8.6 a major task with equation (8.6.2) is acquiring meaningful explicit forms w.r.t. the background geometry, and whether it satisfies (6.36a) or (6.3.6b); prior two articles will be of great assistance for explicit forms for equation (8.6.2) of De Felice and Clarke. How does one verify that equation (8.6.3) is most compatible with (8.6.2)? Why hyperbolic coordinates in (8.6.4)? Making sense of equations (8.6.4) to (8.6.7) in a explicit setting. Follow through with the rest; explicit expression for equation (8.6.11). Some results in section 8.6 are applicable to Friedmann solutions development in section 10.16 later on. Only for personal interest --> Clarke, C.J.S. The Analysis of Spacetime Singularities. Cambridge University Press. Hawking, S.W. and Ellis, G.F.R. (1973). The Large Scale Structure of Spacetime. Cambridge University Press. The following journal article is quite compatible with sections 9.10 and 9.11 of De Felice and Clarke for a more “realistic fluid” Kolassi, C. A., Santos, N. O. and Tsoubelis, D. and (1988). Energy Conditions for an Imperfect Fluid. Class. Quantum Grav. 5 1329 – 1338 ---Dynamics on Curved Manifolds (excluding sections 7.2 and 7.3) NOTE: sections 7.2 and 7.3 will only be project based (outside of course) if students are interested. We want to verify how feasible such sections are with real systems (solar system, “isolated galaxies, proto-stars, nebulae, globular clusters, etc.) A. Review of section 6.8 (pages 201 - 205) B. Conservation Laws (pages 206 - 211) Concerning equation (6.8.23) covariant only w.r.t. linear coordinate transformations, such should be verified. Necessarily (6.8.23) must be explicit in terms of explicit metrics. One may or may not assume that the energy momentum-tensor should be represented by an ideal fluid; recall the various types of energy-momentum tensor forms for different matter-energy systems encountered earlier, with inclusion of equation (9.11.1). What does covariance only w.r.t. linear coordinate transformations say about the kind of energy-matter system? Will like to identify or determine explicit forms of equations (7.1.7), (7.1.8), (7.1.10), and (7.1.16) to (7.1.18) to be realistically computable. Namely, metrics of interest, hypersurface orthogonality, etc. must be applied. C. Motion of a “Point Particle” & the Hamilton-Jacobi Equation (pages 221 - 225). Includes extraction of explicit form of four-momentum from computational development (subject to metric tensor). D. Constants of Motion (pages 225 - 226) Needs to be analytically maintained towards “particles, orbits and trajectories. Computational verification involving inner product and in terms of particular metrics would be nice (both manually and with Mathematica). E. Maxwell’s Equation for a Free Electromagnetic Field (pages 226 - 228). Includes extraction of explicit forms of chosen equations from computational development. F. Maxwell’s Equation in the Presence of Charges and Currents (pages 228 - 231). Includes extraction of explicit forms of chosen equations from computational development. G. The Light Cone (pages 236 - 238) 1. Causal structure 2. Surfaces of Transitivity (restricted Lorentz group, say, branches of “hyperboloid” in two sheets, branches of the light cone, hyperboloid in one sheet). Models, and generators of such geometries. Geometries and displays from such models/generators in Mathematica. 3. Relating trajectories of particles with the sign of the metric {-, 0, +}, and respective location in the light cone geometry and relevance to causal structure. H. Stationary Spacetimes (pages 238 - 244) Note: not everything will be done in detail. However, there may be computational tasks to make them explicit and physically meaningful. Necessarily --> Stationary & Axisymmetric spacetimes (manifold symmetries essential for realistic astrophysical understanding). Recognised, real celestial bodies or systems exhibit some form of rotational variation w.r.t. an axis. Sections 7.2 and 7.3 accounts for such (but will not get into it). As well, being aware of classical physics descriptions. Section 7.10 is critical, without destructive indulging in any mentioned theorems; proofs are not to be enforced at this level. From the defined conditions involving Killing fields one may try to generate geometrical exhibitions of stationary spacetimes, static spacetimes and null surfaces (pages 238 to 239); the issue is identifying explicit forms of Killing fields that will do such, namely, a means to establish computational practicality and tangible use. On page 239, detailing a spacetime as axisymmetric when the metric is invariant under the particular action, vega:SO(2) x M to M, where SO(2) is one parameter rotation group, towards generation on a two-dimensional surface embedded in M, called the axis of symmetry, such must be computationally established, leading towards the ability to exhibit practical and tangible geometrical examples (trajectories being topologically closed “circular” lines). On pages 239 - 240, detailing a spacetime as stationary & axisymmetric, namely, concerned with a map of the form, rho:R(1) x SO(2) x M to M of the two-parameter Abelian group R(1) x SO(2), such must be computationally established, leading towards the ability to exhibit practical and tangible geometrical examples; with confirmation that both the time-like and space-like Killing fields commute. On page 240, will not indulge in proving (7.10.6), although one can verify that such is computationally valid. Without indulging in any mentioned theorems and proofs, will try to acquire some explicit examples of equation (7. 10. 7) based on the former two discussions involving the unique Killing fields, spacetimes and actions, subject to equation (7.10.8). Note: the structure of (7.10.6) can be explained, if one has the luxury with their own time to tackle section 2.12 involving Frobenius Theorems, which justifies (7.10.6) and (7.10.8); same goes for (7.10.9). At the bottom of page 240, the given proposition may be computationally verified, but will not indulge in proving (7.10.6), although one can verify that such is computationally valid. An alternative view which may feel “civil” comes from the following text --> Stephani, H. et al. (2003). Exact solution of Einstein Field Equations. Cambridge University Press. 701 pages; specifically pages 292 - 297, whereas pages 304 - 306 may seem like familiar territory in the future with De Felice and Clarke. Nevertheless, (if PERSONALLY interested) additional sources for proof of (7.10.6): 1. Carter B. (1969) “Killings Horizons and Orthogonal Transitive Groups in Spacetime”, J. Math. Phys. 10, 70 2. General Relativity, by Wald (Chapter 7 with Appendix B) Will then directly focus attention to pages 242 - 244 without indulging in any mentioned theorems (and will be the last topic in chapter 7 in De Felice and Clarke). Within pages 242 to 244 the “physical property” that is angular velocity is identified in terms of inner products involving Killing fields tied to gravitational dragging. Will conclude chapter 7 by terminating at the end of the first paragraph in section 7.11; to be constructive and fluid for sake of the course, in this case will take a stance that we don’t know any explicit spacetime metric, hence, anything further in section 7.11 is mostly mathematical structure that isn’t computationally accessible in general, part from the covariant derivative properties and commutation properties that synthesize the Riemann curvature tensor and Ricci tensor. One needs the Christoffel connection in terms of the metric. Note for the future: for equation (7.10.22) involving (7.10.23) will determine how well they translate in Kerr spacetime for time-like particles. Note for the future: What’s established in pages 389 to 390 is a consequence of the “brutality” from pages 238 to 244; tangible primitive metric (11.1.15) stems from Lewis (1932) and Papapetrou (1963, 1966). One should confirm that (7.10.7) yields (11.1.15). ---The External Schwarzschild metric A. Being spherically symmetric conveys "having the same symmetries as a sphere." In this context "sphere" means S2, rather than spheres of higher dimension. One is concerned with the metric on a differentiable manifold, hence, concerned with those metrics that have such symmetries. Such symmetries are given by the existence of Killing vectors. To determine: the Killing vectors of S2, being three in total, and the uniqueness of each. Confirm: a spherically symmetric manifold is one that has three Killing vector fields which are just like those on S2. Confirm that the commutative relations of Killing vectors on S2 satisfying SO(3), the group of rotations in three dimensions. Trivial uniqueness when compared to anticipated axial symmetry involved in a spacetime manifold from (H) of “Dynamics on Curved Manifolds” module prior. What is Birkhoff’s theorem? What metric form does it imply concerning spherical symmetry? Abbassi, A. H. (2001). General Birkhoff’s Theorem http://cds.cern.ch/record/493064/files/0103103.pdf https://arxiv.org/pdf/gr-qc/0103103.pdf Note: an exact solution of Einstein field equations based on Birkhoff’s theorem and spherical symmetry doesn’t have much fluidity towards recognition of real physical systems. All such prior will characterise (10.1.1) to (10.1.12). Nevertheless, follow through with (10.2.1) to (10.2.15). ---Geometry of Schwarzschild spacetime (stationary region, event horizon, singularity). A. “Coordinate singularity” rg=2GM/c^2 has physical ramifications. Curvature invariants are one means of recognising true singularities from “horizons”. The simplest curvature invariant known (10.5.1) can be applied to the Schwarzschild metric concerning r = 0 and rg. Note: students to try develop computational builds to verify such. The following four journal articles may or may not provide more tangible insights --> McNutt, D. D. (2017). Curvature Invariant Classification of Event Horizons of Four-Dimensional Blackholes Conformal to Stationary Blackholes. Phys. Rev. D 96, 104022 Gregoris, D., Ong, Y. C. and Wang, B. (2019). Curvature Invariants and Lower Dimensional Black Hole Horizons. Eur. Phys. J. C 79: 925 Thorpe, J. A. (1977). Curvature Invariants and Spacetime Singularities. Journal of Mathematical Physics 18, 960 Yoshida, D., & Brandenberger, R. (2018). Singularities in Spherically Symmetric Solutions with Limited Curvature Invariants. Journal of Cosmology and Astroparticle Physics, 31 pages It’s also debatable whether Eddington-Finkelstein coordinates, Kruskal coordinates and Penrose diagrams fluidly/tangibly integrate with astrophysical study. As well, such three mathematical concepts or conveyances often don’t encourage retention, rather regurgitation and the idea of “pointless” mathematical frolic; physics is easier to retain or is more practically constructive than mathematical vanity. The succeeding description yields a straightforward and tangible conveyance that supports curvature invariants --> 1. Find integral curves for future in-going and outgoing null trajectories that constitute the surface of the light cone. In other words, for the external Schwarzschild metric consider null trajectories that’s equatorial with constant “angular velocity orbit”. Hence, one can deduce dt/dr = (1-rg/r)^-1 and solve to acquire integral curves for r > rg and r < rg. Show that such integral curves are meaningful towards (G) in the “Dynamics on Curved Manifolds” module. 2. In the (t , r ) space situate the event hrizon boundary. Verify that the null “trajectories” result in light cone contraction when approaching rg = 2GM/c^2; one integral curve to then eventually coincide with rg. For ingoing null trajectories, observe the orientation that constitute the light cone beneath rg and observe why a “heavy particle” (that always resides within the light cone) can’t re-emerge from beneath rg. Why so concerning the speed of light and speed of heavy particles (time-like and null nature respectively)? Note: ingoing light trajectories also have orientations that can’t emerge beneath rg = 2GM/c^2. 3. What does time divergence as one approaches rg convey? What is proper time and how is it relevant to such a divergence situation? Calculation of proper distance and proper time for the External Schwarzschild metric. B. Stationary null surface has the characteristic as a one-way membrane. Concerning the bottom of page 240 with the given proposition, such a surface can be stationary in the sense that it’s the boundary of events from which it’s possible to escape to infinity; beneath this surface, a “particle” can’t escape, but only plunge. A stationary null surface is termed an event horizon. Being a null surface, the only possible particles to reside on it are photons based on the structure of the light cone. Surface or sphere rg=2GM/c^2 is identified as a stationary null surface from (A) and (B) prior. From the stationary null surface with the proposition on page 240 constituted by inner products with the Killing fields, one will like to (but not necessarily so) express such surface explicitly in a Schwarzschild geometry point of view, hence, determine the Killing fields in such metric and the observed inner products to structure the stationary null surface. Goal is to exhibit that our null integral curves behave in a manner that equates the stationary null surface as equivalent to r = rg. However, does a Schwarzschild geometry yield axisymmetry towards having a space-like Killing field? C. Hamilton-Jacobi equation in the context of the external Schwarzschild metric and constants of motion. Use of a separation constant towards equations of motion (four equations). An issue that remains is convincingly relating Killing fields being “geometrical” to (conserved) physical quantities, in a manner that’s more “accessible” than (10.7.1), (10.7.3) and (10.7.4). What is the explicit form of the action relating (10.7.1), (10.7.3) and (10.7.4)? Equations (7.4.3) to (7.4.11), and (7.5.1) to (7.5.5) can be such a remedy. Concerning (7.4.10), if one can mathematically relate the found time-like integral curves to the “tangent” in (7.4.10), then the four-momentum becomes explicitly meaningful; remember that for (10.7.3) and (10.7.4) the four-momentum can be expressed in terms of the geodesic tangent vector field, where there’s a special property concerning the inner product of Killing fields with the geodesic tangent vector field. Consequently, the Killing field in (7.10.3) w.r.t. (10.7.10) or (10.7.11) can be ratified; (10.7.10) is preferred, say expressing E in terms of the parameters c and rg, and variables v and r; E has dependency on Sqrt(- g_00); determine whether such E is compatible with a static (zero angular velocity) observer in a static space-time; keep in mind that this doesn’t account for KE rotational which may have consequence on actual particle orbits. Concerning (10.7.4) with the azimuthal angular momentum it can be expressed in terms of azimuthal angular coordinate (10.7.9b), hence angular velocity of black hole has influence on such; but that identifies some sense of “rotation”. Is (10.7.9b) literally identifying black hole rotation, or is it just identifying angular variation of the traversing particle w.r.t to the black hole’s axis of symmetry? Apparently, knowing tangential speed makes things practical. Now, for (10.7.3) expressed as (10.7.10) and (10.7.4) expressed in terms of (10.7.9b), trajectories or orbits aren’t necessarily circular, hence (10.7.9d) comes into play, where total angular momentum (sum of the particle spin and orbital/trajectory angular momenta) must be determined. Must have the ability to prove (10.7.9) based on (10.7.3) through (10.7.7). D. Take equations (10.7.9a) and (10.7.9d) on page 344 concerning time-like geodesics (”heavy particles”). Then acquire dt/dr, then the resulting integral curves for r > rg and r < rg. How are they situated w.r.t. null integral curves from (B)? Can the orientation of such time-like integral curves intersect the null integral curves (being the boundaries of the light cone) beneath rg ? Will then invert and consider dr/dt, yielding “radial velocity”. Compare null cases and time-like cases in terms of such “velocity”. Will null cases ever be less or beneath time-like cases? E. Orthonormal frames or frames of reference for Schwarzschild geometry (pp 349-350 is one example). Time-like Killing fields in terms of the Schwarzschild metric. F. Derivation of the (Schwarzschild) Orbit Shape equation as a second order ODE and its solution. Determination of bound and unbound orbits. From the solution of the orbit shape equation determination of the apsis, towards finding the periapsis and apoapsis. G. Acquiring/deducing the Schwarzschild Effective Potential as function of the radial coordinate and its use with effective potential curves i. Compare with Newtonian effective potential ii. Condition on the ODE in (F) leading to a circular orbit. Schwarzschild effective potential counterpart to prior. iii. Relation between eccentricity and energy. Observe how the variations in eccentricity affects the type of conic section. iv. In Schwarzschild geometry simulating (equatorial) trajectories (includes retrograde and prograde). Acquire the following essential orbits: co-rotating & retrograde photon orbits (unique to the event horizon), marginal bound orbit, marginally stable orbit. For co-rotating & retrograde time-like mb and ms orbits to as well identify difference in distance in orbit radius. Note: effective potential, energy and angular momentum to be useful tools for such. H. The Precession of the Apsidal Points (pages 347-349) Following the completion of this topic students may be required to identify whether ODE (10.8.2) is any recognised special type of nonlinear ODE and if there’s any special transformation method necessary to find a general solution; such will be compared to solution (10.8.5). For the found solution of (10.8.2) identify a comparative result to (10.8.10). Will concern explicit identification of the space-like vector connecting two radial geodesics, and verification that such is space-like via norm computation. How does the space-like vector connecting two radial geodesics behave when considering approach to the event horizon, singularity and infinity? I. The Plunging-in Observer (pages 349 - 351). Concerning (10.9.8) what is the explicit form of the space-like vector connecting two radial geodesics in Schwarzschild geometry? Means to verify calculations (10.9.9) and (10.9.10). J. The Bending of Light Rays (pages 354 - 357) What experiments have confirmed (10.11.7)? Note: conventionally, by skill students must know how to transform the external Schwarzschild metric with Eddington-Finkelstein coordinates; (10.5.12a) and (10.5.12b); (10.5.15a) and (10.5.15b). However, WILL NOT indulge the confusion they bring. Further assist: Travel time delay of photon in geodesic path --> Falco, V., Falanga, M. and Stella, L. Approximate Analytical Calculations of Photon Geodesics in the Schwarzschild metric. A&A 595, A38 (2016) ---It’s the students’ responsibility to independently extend ALL Schwarzschild treatment prior to Reissner-Nordstrom Geometry. Personal interest only. ---Homogeneous and Isotropic Cosmology (pages 372 - 378) The following excerpt gives quite a extravagant or expanded treatment: Peacock, J. (1998). The Isotropic Universe. In Cosmological Physics (pp. 65-100). Cambridge: Cambridge University Press. Pages 65 – 100 Will focus primarily on the following tasks --> 1. Equation (3.1) in such above excerpt needs to be thoroughly and explicitly determined based on an actually meaningful expression for the velocity strain tensor. Namely, just accepting that for blindly makes things a bit difficult to comfortably proceed. Same goes for equation (3.2). 2. Verify equations (3.5) and (3.6). 3. Concerning figure (3.2) what realistic experiment is possible based on such well-known means of synthesizing the curvature measure from differential geometry? 4. Verify equation (3.9) based on the given development. 5. Verify equation (3.15). 6. Confirm equations (3.38) to (3.40). Further equations and terms in such excerpt are just given. Other equations in succession may be interesting challenges. The prior tasks can be treated as an explicit elaboration of equations (10.15.1) through (10.15.17) in the text of De Felice and Clarke. However, one may be hard pressed to relate them to equations (10.15.12) through (10.15.17). Nevertheless, to: 1. Independently (from prior journal article) verify development starting from (10.15.4) to (10.15.11). 2. For the field of tetrads observed in (10.15.12) one must determine explicit forms of the “Kronecker delta” entities to have any chance of computational development. 3. Can one confirm (10.15.13)? 4. As well to verify (10.15.14). 5. Confirm (10.15.15) and (10.15.16). Note: for (10.15.17) where book references equation (10.10.12), well likely authors meant (10.15.12). ---The Friedmann Solutions (pages 378 - 384) The following journal article provides development that honours physics: Uzan, J. and Lehoucq, R. (2001). A Dynamical Study of the Friedmann Equations. European Journal of Physics, Volume 22, Issue 4, pp. 371 – 384 http://cds.cern.ch/record/515592/files/0108066.pdf 1. One may require convincing with equation (3) 2. Verify the form of the last term in equation (11) 3. Make sense of (12) and (13), and the conceptual model, say, “The force deriving from EΛ is analogous to the one exerted by a spring of negative constant” on page 4. 4. Pursue vindication equations (20) through (22), and (24) 5. There may be other interesting things to prove or vindicate in the remainder of the journal article. Replicating the charts and family of curves may also be quite interesting. Now then, back to the text of De Felice and Clarke --> 1. For equation (10.15.11) make sense of the singularity r = 1 singularity 2. In the (t , r) space what is the form of the null trajectory model? Behavior of the light cone w.r.t. Such may become more meaningful if R(t) is known. 3. One must be able to deduce (10.16.1). 4. Upon arriving at (10.16.4) one must substitute in the expansion trace found in (10.15.13). Furthermore it’s said that (10.16.4) is actually (9.11.8), yet, after reviewing section 9.10 what conditions must be placed on (10.16.4) for such to be equivalent formula-wise? 5. Recognising the various terms in (9.11.8) based on section 9.10 how will one describe the behaviour of matter and radiation? 5. Consider equation (9.11.9) and (10.16.4), is there anything interesting that one can deduce about (rho + p)? Then, compare prior to (10.16.5) and (10.16.6) when the conditions are applied. So, what? 6. With the universe matter dominating condition, to acquire (10.16.5) it’s just about observing it simply as a ordinary differential equation; treat rho as the dependent variable and R as the independent variable, where one can disregard the dt’s since they are on both sides of the equation. You will acquire natural log upon integration and so forth. Follow through with the universe radiation dominating condition and do likewise with ODE solving. 7. The rest of section 10.16 concerns verification (in this case manually before any pursuit of computational development). ---Cosmological Effects (pages 384 to 388) 1. How does equation (10.17.1) come about? Pursue confirmation via equations (7.8.8) and (10.15.11). 2. On such same page 385, “we can separate the space-dependent terms from the time-dependent ones which can be written as (10.17.2)”. What is going on here? What did they do with the space-dependent terms? 3. Verify (10.17.9) The rest of section 10.17 concerns following through with verification. ---Earth Metric Ashby, N., Relativity in the Global Positioning System, Living Rev. Relativity, 6, (2003), 1. A. Concerning such a metric how do components of the energy-momentum tensor match with those of the Einstein tensor (if possible)? Can explicit forms of the energy-momentum tensor components be found? Try to determine explicit forms of the components of the energy-momentum tensor via astronomical or geophysical data. One should acquire an energy-momentum tensor that satisfies (6.3.6a) or (6.3.6b). B. Include orthonormal frames or frames of reference. How does such frames apply to fields, quantities, etc.? Observe computationally. Determination of proper distance and proper time. General vectors and Killing fields in terms of these frames with coordinates; compare the results between the earth metric and Schwarzschild metric. C. Consider red-shift or blue-shift for a photon traversing radially from point a to point b as compared to Schwarzschild geometry. D. Recognising frame dragging through geodesics. A radially in-falling geodesic (at the equator). Constituents of the equation --> Variables Dependent: azimuthal angle Radial positioning Independent: time Parameters Magnitude of the angular momentum of the spinning “massive” body Angular velocity of the rotating coordinate system Speed of light Recall the precession measuring model involving a gyroscope (Gravity Probe B or whatever). Can one exhibit consistency with (D)? E. Derive the effective potential as a function of “radial distance” based on the four equations of motion (or whatever). Apply whatever energy and angular momentum conditions to acquire circular, elliptic and parabolic orbits; include means for prograde and retrograde orbits. F. Consider the Earth metric from the prior mentioned journal article (Ashby 2003). One often assumes a well form for the gravitational potential. However, one would like to expand on such. 1. Consider the geometrical orientation of Earth and mass element of Earth w.r.t. an internal reference point and an external point for test particle(body). Going from trigonometrical ingenuity leading to the gravitational potential expressed in terms of Legendre polynomials and the associated zonal spherical harmonics. Note: such new form of potential converges back to the classical form for large distances away from Earth. 2. Next phase will be to incorporate moment of inertia (of an ellipsoid) into our “zonal spherical harmonics potential”, namely, such potential in terms of MacCullagh’s formula. Due to symmetry the potential can be reduced to an expression involving the moment of inertia for two axes. Then express back in the harmonics. 3. Furthermore, one can also recognise a rotational/centrifugal potential to be incorporated into the general potential, hence in total a geo-potential. Can the rotational/centrifugal potential be related to the frame dragging model of the Gravity Probe B findings or what was found by satellite observations? If not, try to model any disparity among them. 4. The developed geo-potential resulting from putting together results from (2) and (3) to be now substituted into in the Earth metric (Ashby 2003). Concerning the geo-potential one would only like to consider orbits or trajectories that are fixed to (latitudal) planes. Often one only considers the equatorial plane, but for the case of the geo-potential will like to investigate for different planes to identify particular effects; generally however, not to consider instantaneous latitudal variations to drastically simplify things. What are the implications for such new metric with the equations of motion in the four dimensions, say the analogy to (10.7.9) in the text of De Felice and Clarke? One can also see what your built geodesic function in Mathematica spits out. 5. Determine the total energy of a “particle” and also angular momentum relevant to such metric spacetime. Deduce or derive the energetics and angular momentum orientation towards photon, bound, stable and escape orbits with prograde and retrograde orientations in mind. G. From (pages 354 - 358) pursue development leading to (10.11.10) in terms of the Earth metric based on development from (F). Acquire the following essential orbits: marginal bound orbit, marginally stable orbit. For mb and ms to as well identify difference in distance in orbit radius. Consider different reference frames that apply; relevant region(s) of spacetime may apply. H. From the Earth metric and development from (F), pursue null trajectories, namely g = 0 and deduce the (t , r) – curves. As well, pursue finding the curvature invariant for such geometry. Do integral curves provide well the location for divergences and possible asymptotes? How do integral curves for time-like trajectories behave compared to integral curves for null trajectories? Will then invert and consider dr/dt, yielding “radial velocity”. Compare null cases and time-like cases in terms of such “velocity”. Will null cases ever be less or beneath time-like cases? I. May try to replicate the TOPEX/POSEIDON Relativity Experiment in Ashby’s article with acquisition of the data towards modelling. ---Kerr metric A. What’s established in pages 389 to 390 is a consequence of the “brutality” from pages 238 to 244 Fast review of (G) and (H) in “Dynamics on Curved Manifolds” module. B. Axially symmetric line element: canonical form (pages 389 - 397) Support article: Sloane, A.(1978). The Axially Symmetric Stationary Vacuum Field Equations in Einstein's Theory of General Relativity. Aust. J. Phys., Vol. 31, p. 427 - 438 C. The Kerr Solution (pages 392 - 397) D. Physical interpretation of the Kerr Metric (pages 397 - 400) Marck. J. A. (1983). Solution to the Equations of Parallel Transport in Kerr Geometry; Tidal Tensor. Proceedings of the Royal Society of London. Series A, Mathematical and Physical Sciences, 385 (1789), 431-438 For (11.4.1) verify that the Weyl tensor in this case involving the Carter tetrad (11.4.2) is identical to the Riemann tensor for the two-forms. E. Kerr spacetime structure (pages 400 - 406) Marck, J. A. (1983). Solution to the Equations of Parallel Transportation Kerr Geometry; Tidal Tensor. Proc. Roy. Soc. London A 385, 431 De Felice F. and Bradley, M. (1988). Rotationally Anisotropy and Repulsive Effects in the Kerr Metric. Classical and Quantum Gravity, 5, 1577 Verify the curvature invariant (11.4.4) with computational development. Additionally, from the Kerr solution concerning null trajectories acquire the (t, r) – integral curves and identify all significant characteristics; to also identify any time divergences and confirm whether the behaviours are evident in the curvature invariant zeros (8) and (9) from the journal article of De Felice and Bradley or book. What coefficients of the Kerr metric generate such zeros? If there are time divergences with the null integral curves, what does such convey and their relevance to proper time? Calculation of proper distance and proper time for the Kerr metric. Note: conventionally for exams, by skill students must know how to transform the Kerr metric with (11.4.5), (11.4.7), Kerr-Schild coordinates and Kerr coordinates. Use of the Kerr metric coefficients and their properties to discriminate various regions or boundaries in question. Concerning the proposition at the bottom of page 240 will identify which metric coefficients translate to such; also relates to (7.10.17) and (7.10.18). What surfaces or regions in Kerr geometry identify with V = 0 and V < 0, with relevance to the Kerr metric coefficients? Limit of stationarity Ergosurface, Ergosphere & frame-dragging Event horizons Points where ergosphere and outer event horizon reach (quantitative via the metric coefficients). The equatorial (maximum) radius of an ergosphere corresponds to the Schwarzschild radius of a non-rotating black hole (quantitative via the metric coefficients); the polar (minimum) radius can be as little as half the Schwarzschild radius, etc. (quantitative via the metric coefficients). How are null trajectories in the ( t , r) space situated among the prior Kerr regions. At the beginning of page 241, concerning the one-form leading to (7.10.9) --> What does the inner product with itself produce? What form does it take in Kerr spacetime? What form does (7.10.18) take on within this one-form in Kerr spacetime? Does it generate of bring to light the surfaces or regions in Kerr spacetime? What would such a one-form represent? What is the relation between such one-form and (7.10.22)? How does (7.10.22) behave when approaching a Kerr blackhole? Note: when appropriate one can make use of the following (which contains the KerrGeodesics tool) to compare with “analytic” models, theory, etc: https://bhptoolkit.org/toolkit.html F. One should understand the significant difference between (11,5.3) and (10.7.9b). The former is a dynamic stemming from black hole rotation whereas the latter is based on particle’s positional change w.r.t. (Schwarzschild) black hole axis of symmetry; tangential velocity being a needed “parameter”. Thus, setting a = 0 can throw one off concerning black hole physics/background behaviour. H. Orthonormal frames or frames of reference for Kerr geometry (pp 398, 400, 408 as LNRF, 409 are some examples). ZAMO. Observe computationally. Killing vector fields and Killing one forms in terms of these frames (static observer in stationary space-time, pp 398-400, LNRF, ZAMO). I. Similar treatment as for time-like trajectories (four equations) acquired from the Hamilton-Jacobi equation. How do the (t, r) – integral curves for time-like trajectories behave compared to null trajectories? Are there any ergosphere asymptotes for time-like (t, r) – integral curves? Are there any asymptotes at all? Is the behaviour of time-like (t, r) – integral curves consistent with (7.10.22)? Will then invert and consider dr/dt, yielding “radial velocity”. Compare null cases and time-like cases in terms of such “velocity”. Will null cases ever be less or beneath time-like cases? J. Parameters for Kerr orbits: Bardeen, J. M., Press, W. H. and Teukolsky, S. A., Rotating Black Holes: Locally Nonrotating Frames, Energy Extraction, and Scalar Synchrotron Radiation, Astrophysical Journal, Vol. 178, pp. 347-370 (1972), restricting to pages 349-358 (up to equation 3.21). NOTE: in progression derive equations (2.9a) to (2.9b) in such journal article based on what the authors convey that lead to the conjuring. Then onwards to --> Equatorial circular motion condition(s) Energy & angular momentum conditions for orbit direction (retrograde, prograde) Energy conditions for bound, stable, unstable or photon orbits (parabolic, elliptic, hyperbolic) Kerr effective potential in mould of the junior high quadratic formula -->> In terms of such effective potentials determine the types of stable, unstable and photon orbits, and identify whether they are consistent with those found in the prior journal article (Bardeen et al) concerning equation (2.10) and textbook (De Felice and Clarke) with equation (11.5.9); same goes for the energy and angular momentum models. Does the effective potential found in link satisfy condition (2.11) in the article of Bardeen et al. for circular and equatorially restricted trajectories? Deduce as well the Kerr effective potential for photons. Now, from the text of De Felice and Clarke concerning equation (11.8.3) and/or journal article of Bardeen et al, concerning equation (2.12), how does KE rotational factor in? What does it do to orbits? Concerning equations (3.3) to (3.5) of Bardeen et al, can the identified connection coefficients be interpreted as Ricci rotation coefficients observed in De Felice and Clarke for equations (4.5.2) to (4.5.5)? K. The Geodetic Effect in Kerr Spacetime Tsoubelis, D., Economou, A., and Stoghianidis, E. (1986). The Geodetic Effect along Polar Orbits in the Kerr Spacetime, Physics Letters A, Volume 118, number 3 Semerak, O. (1997). Gyroscope on a Polar Orbit in the Kerr Field, General Relativity and Gravitation, Vol. 29, No. 2 Consider the case of equatorial orbits as well. L. Gravitational Dragging (pages 242 - 244); concerned with equation (7.10.18), and (7.10.22) to end of paragraph on page 244; concerns gravitational dragging effects in terms of angular velocity, v= -(W/X) = -(g_0phi/g_00) via equation (7.10.7). Express v in terms of Kerr metric coefficients. Compare v with the angular velocities for minimal orbits at the ergosurface, within the ergoregion, outer horizon and inner horizon. What forms does the v measure take outside the static limit, and at the static limit? Where does the gravitational dragging formula equate to the angular velocity of the Kerr black hole? M. Consider red-shift or blue-shift for a photon traversing radially from point a to point b as compared to Schwarzschild geometry and the Earth metric. N. What is the explicit energy-momentum tensor for the Kerr body, and it’s corresponding explicit Einstein tensor? Find the corresponding lagrangian that satisfies (6.3.6a) or (6.3.6b) in the text of De Felice and Clarke. O. Rotationally Induced Effects (pages 408 - 412) For a particle with negative energy w.r.t. infinity what model or form permits such? What reference frame makes such practical? Can this negative energy measure be realised explicitly? A particle with local positive can have negative energy w.r.t. infinity. How is this possible? Conjure computational model/representation. Going back to the article of Bardeen, J. M., Press, W. H. and Teukolsky, S. A. (1972), explicitly verify velocity formula (3.10) for equatorial and circular orbits. Pursue a velocity formula for non-circular equatorial orbits. From page 409 of De Felice and Clarke, particles need to be highly relativistic for the Penrose extraction process (PEM) to be possible; more details of such can be found in Bardeen, J. M., Press, W. H. and Teukolsky, S. A. (1972), specifically equations (3.8) to (3.21) which can yield some elaboration. From this same journal article, on page 356 for velocity plane, say the following form ( V^(phi), V^(r) ) somewhere inside the speed of light circle. Confirm that the squared sum of such two velocities yields unit. Certain regions of the two-dimensional velocity space at radius r correspond to bound, stable orbits; other regions to hyperbolic orbits which escape to infinity; other regions to “plunge” orbits which go down the hole. What types of relativistic particles are candidates to produce electromagnetic superradiance? Are any in the Standard Model of particle physics? What determines the difference between electromagnetic superradiance emergence and gravitational superradiance emergence? From De Felice and Clarke, equation (11.6.4), being the Klein-Gordon equation, will like to verify Lorentz covariance w.r.t. to the Kerr background geometry. Note: remember, Hamilton-Jacobi formulation for wave mechanics permits motion of a particle representable as a wave that’s practical in general relativity. Note: for equation (11.6.6) of De Felice and Clarke how does one argue the need for such transformation r -> z upon the radial part of the massless Klein-Gordon equation? Is it just a “dumb luck” observation skill from ODE experience? Does equation (11.6.7) of De Felice and Clarke have compatibility or equivalence with equation (4.11b) of Bardeen et al? Pursue such. Is equation (4.13) of Bardeen et al, to be identified with the explicitly deduced V^(r) of the velocity plane found earlier? Another concern to validate in Bardeen et al, being (4.22). Then follow through to equation (4.30). Starobinskii, A. A. & Churilov, S. M. (1974). Amplification of Electromagnetic and Gravitational Waves Scattered by a Rotating “Black Hole". Soviet Physics JETP, Vol. 38, p.1 Note: the concern for the above journal article, is to make use of section 8.5 in De Felice and Clarke, namely, The Geometry of Null Rays to comprehend the relationship between tetrads and the basis in the complex tangent space. Will pay no attention to a off-path complex variables course, yet reassure yourselves that (8.5.1) does form a basis in the complex tangent space; don’t want any incursions by mathematicians creating a nasty “cascade of junk”. Just establish the linear independence and span. The article of Bardeen, J. M., Press, W. H. and Teukolsky, S. A. (1972) shares highly compatible structuring with Starobinskii, A. A. & Churilov, S. M. (1974) for electromagnetic and gravitational waves. Non-con artist crucial phases for explicit gravitational waves forms: 1. Interest yourself in finding explicit forms for Psi-0 and Psi-4 (of the Weyl-NP scalars) with respect to the standard choice of (complex) tetrad at infinity; yet remember in empty space the Weyl tensor is equivalent to the Riemann tensor. The idea of “empty space” may seem confusing, so reinforce your understanding of the setting (Petrov Type D classification or whatever; “don’t try to eat the whole jar of mayonnaise” in some weird competition show). 2. Comprehending the transvers-traceless gauge in a fluid and competent manner. TT gauge and linearized gravitational waves; the complicated crusty egg shell stuff is for your personal endeavor. How are linearized gravitational waves related to the Riemann tensor components? Note: I am not going to ask you to remember all this in detail like a CUNY math major zombie or civilised virus cultivated for it be unleashed at certain times when feeling threatened. Development here is for your personal use towards the future, for personal refining. 3. Make use of the following: Thorne, Kip S. (April 1980). Multipole Expansions of Gravitational Radiation. Rev. Mod. Phys. 52 (2): 299–339 4. Matched filtering: LIGO process with PyCBC and GstLAL (or use other detector elsewhere, like LISA, Virgo, DECIGO). Concepts and overview, logistics. Then may try a couple of runs with LIGO data (or other). NOTE: sources generally will be merging bodies (black holes or neutron stars/pulsars) instead of the Penrose process. Convince yourselves that the superradiance structure developed in the Penrose extraction setting to be the same as gravitational emissions from such merging bodies. Pursue electromagnetic waveforms with the subtleties to gravitational waveforms. Namely, the most practical astrophysical process contemplated that would make the Penrose process feasible is the Blandford-Znajek Process; the following articles may take some effort to cypher, to acquire good computational logistics: Blandford R. D. and Znajek, R. L. (1977). Electromagnetic Extraction of Energy from Kerr Black Holes, Mon. Not. R. Astr. Soc. 179, 433-456 Znajek, R. L. (1977). Black Hole Electrodynamics and the Carter Tetrad, Mon. Not. R. Astr. Soc. 179, 457-472 Hirotani, K. and Okamoto, I. (1998). Pair Plasma Production in a Force Free Magnetosphere around a Supermassive Blackhole, The Astrophysical Journal, 497: 563 - 572 P. Area and Mass Formula Smarr, L. (1973). Mass Formula for Kerr Black Holes. Physical Review Letters. Volume 30 Number 2. Note: take the condition of the rotating black hole not having charge. For the area formula observed on page 412 try to relate it to what is observed in the journal article. For the mass formula (De Felice and Clarke), namely (11.6.17) or (11.6.19) try to relate to the different forms found in the journal article. The journal article has other insightful points. Q. Honourable Mention article (this article not pursued in lectures) Bini, D., Geralico, A., and Jantzen, R. T. (2017). Gyroscope Precession Along General Time-Like Geodesics in a Kerr Black Hole Spacetime, Phys. Rev. D 95, 124022 The above article can generate much interest personally. As well, its reference has great articles and books, for example, Drasco, S. & Hughes, S. A. (2004), Phys. Rev. D 69, 044015. Others as well. ---Modelling of Relativistic Fluid Disks Around a Kerr Black Hole Note: one doesn’t have remember everything in detail, however, the physics setting and modelling should be considered with care. What is the minimal orbit for matter in such disks and how does matter distribution in the outer parts influence them? Fishbone, L., G., Moncrief, V. 1976, Relativistic Fluid Disk Orbiting Around a Kerr Black Hole I, The Astrophysical Journal, 207, 962-976 Fishbone, L., G. 1977, Relativistic Fluid Disk Orbiting Around a Kerr Black Hole II, The Astrophysical Journal, 215, 323-328 Tejeda, E., Taylor, P. A. and Miller, J. C. 2013, An Analytic Toy Model for Relativistic Accretion in Kerr Space–Time, Monthly Notices of the Royal Astronomical Society, Volume 429, Issue 2, 21 February 2013, Pages 925–938 ---Kerr-Newmann geometry test particles (photon, charged, “heavy”) The following are assisting journal article guides: Hackmann, E., and Xu, H. (2013). Charged Particle Motion in Kerr-Newmann Spacetimes, Physical Review D, 87, 124030 (2013) Yang, X., L., and Wang, J., C. (2014). ynogkm: A New Public Code for Calculating Time-Like Geodesics in the Kerr-Newman Spacetime, Astronomy and Astrophysics, 561, A127 Bacchini, F. et al. (2018). Generalised, Energy – Conserving Numerical Simulations of Particles in General Relativity I. Time-like and Null Geodesics. The Astrophysical Journal Supplement Series,237:6(20pp) Bacchini, F. et al. (2019). Generalised, Energy – Conserving Numerical Simulations of Particles in General Relativity II. Test Particles in Electromagnetic Fields and GRMHD. The Astrophysical Journal Supplement Series, 240: 40 (25pp) O Ruiz et al (2019). Thermodynamic Analysis of Kerr-Newman Black Holes, Journal of Physics: Conference. Series. 1219 012016 Babar, G.Z., Babar, A.Z. & Atamurotov, F. Optical Properties of Kerr–Newman Spacetime in the Presence of Plasma. Eur. Phys. J. C 80, 761 (2020) Tinguely, R.A., Turner, A.P. Optical Analogues to the Equatorial Kerr–Newman black hole. Commun Phys 3, 120 (2020). What is the explicit energy-momentum tensor for the K-N body, and it’s corresponding explicit Einstein tensor? Find the corresponding lagrangian that satisfies (6.3.6a) or (6.3.6b) in the text of De Felice and Clarke. Note: will like to simulate particle trajectories in K-N geometry ---The Hartle-Thorne Metric Ability to describe both internal astrophysical configurations and external spacetime geometry. Competent guide: Hartle, J., B., and Thorne, K., S. 1968, Slowly Rotating Relativistic Stars II, Models for Neutron Stars and Supermassive Stars, The Astrophysical Journal, Vol 153, pp 807 - 834 (focus mainly on external solution). A. For the internal description modelling at this level is not mandatory. However, a basic understanding of the physics to acquiring internal form should remain. Concerning that internal metric, the student should be competent with computational use concerning treatment of parameters. B. Concise external metric found in the appendix. Approximation to the Kerr metric. Orthonormal frames or frames of reference in such a metric. Concerning such a metric how do the components of the energy-momentum tensor match with those of the Einstein tensor? Would like a form that satisfies (6.3.6a ) and (6.3.6b). Determination of proper distance and proper time. Killing fields in terms of these frames and their application to fields, quantities, etc. Consider red-shift or blue-shift for a photon traversing radially from point a to point b; compare the results between the external Hartle-Thorne metric, Earth metric, Schwarzschild metric and Kerr metric. C. Acquire the following essential orbits: co-rotating & retrograde photon orbits (unique to the event horizon), marginal bound orbit, marginally stable orbit. The following articles provide such, but one must deduce/prove them to be considered legitimate: Boshkayev et al 2015, Geodesics in the Field of a Rotating Deformed Gravitational Source, International Journal of Modern Physics A. For mb and ms to as well identify difference in distance in orbit radius. D. External metric for the Sun also found in the Hartle-Thorne appendix (in regards to the relative magnitudes of the various quantities in the external line element), concerns equations (A1) to (A4), pp 833 - 834. Such specified metric may imply that one will not go by the assumption that the Sun is a perfect sphere. Concerning such a metric how do explicit components of the energy-momentum tensor match with those of the Einstein tensor? Try to determine explicit form(s) of the components of the energy-momentum tensor of the Sun via astronomical resources and data. It’s anatomy with different layers may or may not lead to a description that’s quite technical. Additionally, states and processes ongoing likely will not tolerate an ideal fluid description. One should acquire an energy-momentum tensor that satisfies (6.3.6a) or (6.3.6b). For the bending of light rays traversing near the Sun, apply the acquired external metric for the Sun in the manner of section 10.11 of De Felice and Clarke to confirm (10.11.7); keep in mind that the isotropic coordinates applied to the external Schwarzschild metric may or may not be applicable. Consider red-shift or blue-shift for a photon traversing radially from point a to point b; compare the results between the external Hartle-Thorne metric, Earth metric, Sun external metric, external Schwarzschild metric, and external Kerr metric. Sound literature for the Cassini general relativity experiment: Iess, L., Giampieri, G., Anderson, J. D. and Bertotti, B. (1999). Doppler Measurement of the Solar Gravitational Deflection. Class. Quantum Grav. 16, pages 1487–1502 Note: article’s reference has good literature (if personally interested). The test of general relativity experiment using radio links with the Cassini spacecraft. Will the Earth-based observer be a ECI frame or ECEF, or other? Identify the operational procedures for the experiment. Recalling the orientation or state required for CASSINI, what is such reference frame? How will the signals be transmitted and received in terms of respective reference frames? Establish all required observers w.r.t. to their reference frames and pursue establishing consistency with the Cassini experiment w.r.t. to such reference frames. Can one confirm that the Cassini result is compatible with the external Sun metric found previously concerning curvature? Note: make ask students to determine the reference frames for points on other bodies in the solar system as well if similar Cassini experiments were done. E. Then for developments from (D) prior compare to the following (with consideration of 9.10 and 9.11 from De Felice and Clarke): Kaufmann, W. J., III. (1968). A New Energy-Momentum Tensor and Exterior Solution for Radiating Spheres in General Relativity. Astrophysical Journal, vol. 153, p.849. Confirm whether the identified energy-momentum tensor satisfies (6.3.6 a) or (6.3.6b) in the text of Clarke and De Felice. Then, identify the explicit components of the Einstein tensor that matches with the components of the energy-momentum tensor. Compared to the Sun metric determine the disparities for the following Form of the Killing fields Energy and momentum of a “particle” Deduce the analogy to (10.7.9) Geodesics Energetics & angular momenta (stable, bound, parabolic, hyperbolic) Photon frequency shifts Recall the orbit equation in general solar celestial mechanics, and profile the planets in the solar system with such involving use of astronomical data. Particularly for the energetics and angular momenta for stable, bound, parabolic, and hyperbolic orbits found earlier (Sun -based and Kaufmann based), how much will such quantity models throw off or lead to conformity with the empirically identified orbits in the solar system? F. From the Sun metric, pursue null trajectories, namely g = 0 and deduce the (t , r) – curves. As well, make use of the curvature invariant for such geometry. Do integral curves provide well the location for divergences and possible asymptotes? How do integral curves for time-like trajectories behave compared to null trajectories? G. Will then invert and consider dr/dt, yielding “radial velocity”. Compare null cases and time-like cases in terms of such “velocity”. Will null cases ever be less or beneath time-like cases? H. From De Felice and Clarke, pp 354- 358, pursue development leading to (10.11.10) in terms of the external Sun metric. I. Consider the precession of apsidal points (pages 347 - 349). In terms of the external metric from prior can one deduce equation (10.8.1) based on the external metric Sun counterparts of equations (10.7.9d) and (10.7.9b) that would trickle down to (10.8.1)? J. Analyse the following the journal article, then proceed with redeveloping such with the Sun metric from the appendix of the article of Hartle & Thorne: Shahid-Saless, B. and Yeomans, D. K. (1994). Relativistic Effects on the Motion of Asteroids and Comets. The Astronomical Journal. Volume 107, number 5. Will then compare findings with data compared to the results from the metric applied by Shahid-Saless and Yeomans. ---A Lagrangian in the Solar System Schettino, & Tommei, G. (2016). Testing General Relativity with the Radio Science Experiment of the BepiColombo Mission to Mercury. Universe (Basel), 2(3), 21 Consider equation (4) and the explicit definitions for each lagrangian type involved following after. Can one show that the Post-Newtonian General Relativistic Lagrangian is valid? Can the Post-Newtonian General Relativistic Lagrangian satisfy (6.3.6 a) or (6.3.6b) of De Felce and Clarke? ---Spinning Test Particles in General Relativity With spin there will exist rotational kinetic energy. For equation (10.7.10) there’s no presence of rotational KE. As well, from the text of DeFelice and Clarke concerning equation (11.8.3) and/or journal article of Bardeen, J. M., Press, W. H. and Teukolsky, S. A. (1972) concerning equation (2.12), there’s no presence of rotational KE. The concern of this module is to “amend” the equations of motion and effective potential for a respective spacetime geometry (Schwarzschild, Earth, Kerr, Hartle-Thorne, Sun); concerns circular, parabolic and elliptic orbits treatment; possibly as well consideration of prograde and retrograde orbit orientation well. Will like to simulate orbits without spin considered versus orbits with spin considered (concerns all prior metrics). Assisting journal articles (to treat all prior metrics regardless of specification in each) --> 1. Burman, R.R. (1977). Paths of Spinning Particles in General Relativity as Geodesics of an Einstein Connection. Int J Theor Phys 16, 211–225 2. Semerak, O. (1999). Spinning Test Particles in the Kerr Field. Mon. Not. R. Astron. Soc. 308, 863 - 875 3. Semerak, O. and Kyrian, K. (2007). Spinning test particles in a Kerr field – II. Mon. Not. R. Astron. Soc. 382, 1922–1932 4. Bini, D. and A. Geralico, A. (2011). “Spin-Geodesic Deviations in the Kerr spacetime,” Phys. Rev. D 84, 104012 5. Costa, L. F. O., Lukes-Gerakopoulos, G. and Semerak, O. (2018). Spinning Particles in General Relativity: Momentum-Velocity Relation for the Mathisson-Pirani Spin Condition. Phys. Rev. D 97, 084023 6. Bini, D. and De Felice, F. Centripetal Acceleration and Centrifugal Force in General Relativity. In: Nonlinear Gravitodynamics - The Lense-Thirring Effect - A Documentary Introduction to Current Research, edited by Remo Ruffini, and Costantino Sigismondi, World Scientific Publishing Co Pte Ltd, 2003 For the (t , r) – curves is there any significant difference between time-like particles having no consideration of particle rotation versus the inclusion of rotation? ---Other Energy-Momentum Tensors Note: will run through the development of each literature. As well, some equations will require verification. 1. In review, from De Felice and Clarke, equations (9.10.12) to (9.10.15), will like to consider observers with explicit different frames, and how their measures relate or are compatible with each other; confirm equations (9.10.16) to (9.10.22) as well. Note: for chosen space-times it may be useful to express each observer’s four-velocity in terms of Killing fields admitted by the background geometry, as well as explicit expression for the the spatial velocity; different observers may not be subject to all the same Killings due to the amount of influence (distance) from the source. 2. Energy-Momentum Tensor for Collapsing Stars Atkinson R. (1964). AN ENERGY-MOMENTUM TENSOR FOR COLLAPSING STARS. Proceedings of the National Academy of Sciences of the United States of America, 51(5), 723–730. 3. Energy-Momentum Tensor & Exterior Solution for Radiating Spheres in GR Kaufmann, W. J. (1968). A New Energy-Momentum Tensor and Exterior Solution for Radiating Spheres in General Relativity. The Astrophysical Journal, Vol. 153, pages 849 – 854 4. Boson Stars Van der Bij, J. J. and Gleiser, M. Stars of Bosons with Non-nominal Energy-Momentum Tensor. Fermilab – Pub – 87/41 – A 5. Energy-Momentum Tensor of the Electromagnetic Field Inside Matter Balazs, N. L. (1953). The Energy-Momentum Tensor of the Electromagnetic Field Inside Matter. Phys. Rev. 91, 408 6. Blackhole Energy-Momentum tensor Balasin, H. and Nachbagauer, H. (1993). The Energy-Momentum Tensor of a Blackhole, or what curves the Geometry? Classical and Quantum Gravity, Volume 10, Number 11 7. Try extending to Kerr and Kerr- Newmann 8. Stress - Energy Tensor near a Rotating Blackhole Fawcett, M. S. (1983). The Energy-Momentum Tensor Near a Black Hole. Commun. Math. Phys. 89, 103 – 115 Frolov, Valeri P. and Thorne, K.S. (1989). Renormalized Stress - Energy Tensor Near the Horizon of a Slowly Evolving, Rotating Black Hole. Phys. Rev. D., Volume 39. Pages 2125 – 2145 9. Confirm that the identified energy-momentum tensors of (2) through (8) satisfy (6.3.6a) or (6.3.6b) in the text of De Felice and Clarke. ---Neutron Star Spacetime Geometry Morsink, S., M., and Stella, L. (1999). Relativistic Precession Around Rotation Neutron Stars: Effects Due to Frame Dragging and Stellar Oblateness. The Astrophysical Journal, 513: 827 - 844 Activities will be similar to other modules ---Kinetic Theory Ray, J. R. (1982). Kinetic Theory in Astrophysics and Cosmology. Astrophysical Journal, 257: 578 – 586 One of the first tasks will be finding (explicit) lagrangians related to the given energy-momentum tensor (2.2), (2.8) in the above journal article that satisfies (6.3.6 a) or (6.3.6b) in the text of Clarke and De Felice; explicit forms for quantities may be troublesome. For static spherical symmetry some “strong” explicit models and equations are provided. However, one may be interested with axisymmetry included in spacetime. Well, does axisymmetry imply a stage beyond gravitational instability? ---Unresolved needed substance 1. How does one make equation (8.1.31) of De Felice and Clarke relevant to the Earth metric, Sun metric, Kerr geometry and Kerr-Newman geometry? How convergent is (8.1.31) to (8.1.32) when applying the Earth metric or Sun metric?. How do the additional terms in (8.1.32) contribute? 2. From De Felice and Clarke, concerning equation (7.1.8) is the notion of radiation of a different context to gravitational radiation? Prove or disprove. Prerequisites: Tensor Analysis & Riemannian Geometry, Upper level standing. Note: Space Science I & II are not prerequisites for this course.

Statistical Physics I Statistical mechanics bridges the gap from the microworld, as described by quantum mechanics, to the macroscopic properties of many-particle (N ∼ 1024) systems. Fortunately, once we take recourse to statistical methods, we can take advantage of the fact that in the thermodynamic limit N → infinity the associated probability distributions typically become extremely sharp, and average quantities suffice for a quantitative description. Statistical mechanics thus not only provides a foundation for thermodynamics and the properties of gases, but generally for condensed matter in the form of fluids, glasses, crystals, semiconductors, superconductors, polymers, biomaterials, etc. Its concepts find broad applications in astrophysics, geophysics, particle physics, chemistry, biology, and engineering science. Assessment --> Homework 15% Labs 25% 4 Exams 60% HOMEWORK --> Homework will incorporate relevant Quantum Physics questions Homework will come from various texts concerning statistcal physics/mechanics EXAMS --> Exams will reflect homework LABS (choose best sequential order) --> 1. Remote Experiment on classical gases: To demonstrate the classical gas laws. A motor controls the position of a piston in a glass cylinder containing air whose temperature can be remotely adjusted by a heater. Sensors measure the pressure of the gas and its temperature. Their measurements are digitized. Given this setup, students can readily verify the classical laws of phenomenological thermodynamics, for example the Gay-Lussac relation between volume and temperature. However, one can clearly go beyond this experiment: By controlling the heater and the piston, students can run the system in a thermodynamic cycle process. The amount of heat energy induced is known due to the characteristics of the heater, and the amount of mechanical energy made available by a cycle can be computed from the area within the pV diagram, etc., etc., etc. Various gas laws to be experimentally confirmed; combines gas law as well. Means to demonstrate and validate the laws of thermodynamics. 2. Studying Phase Transitions with a Strain Gauge 3. Avogadro’s Number Slabaugh, W. H. (1969). Avogadro's Number by Four Methods. Journal of Chemistry Education, 46, 1, 40 https://www.if.ufrj.br/~moriconi/termo_fisest/avogadro.htm Determine Avogadro’s Number by Observations on Brownian 4. Lopresto, Michael. (2010). A Simple Statistical Thermodynamics Experiment. The Physics Teacher. 48(3). p183-185 5. Singh, H. ( 1996). A Simple Experiment to Study the Statistical Properties of a Molecular Assembly with Two or Three State Dynamics. Reson 1, 49–59 6. Blackbody Radiation Measurements of the intensity and spectrum of a blackbody radiator as a function of temperature. Theoretical curves from the Wein and the Stefan-Boltzmann T^4 laws will be compared to measurements. Emphasis on nonlinear curve fitting and high temperature techniques. 7. Prentis, J. J. (2000). Experiments in Statistical Mechanics. American Journal of Physics 68, 1073 8. Discussion of chosen Wolfram Demonstrations - Statistical Mechanics Includes analysis and development of code COURSE TOPICS --> --Review of the Development of Classical Gas laws --Essentials of Equilibrium Thermodynamics --Review of Probability, Combinatorics and Statistics --Kinetic Theory --Elements of Ensemble Theory --Interacting Systems: virial and cluster expansions; van der Waals theory; liquid-vapor condensation --Basics of Quantum Statistics and Theory of Simple Gases --Ideal Bose systems --Ideal Fermi systems Prerequisites: Probability & Statistics, Quantum Physics I Statistical Physics II Canonical and grand canonical ensembles, quantum statistics, ideal Bose and Fermi systems, classical non-ideal gases, virial expansion, phase transitions, fluctuations, transport coefficients, non-equilibrium processes. Assessment --> Homework Labs Computational Development (CD) + CD from applied topics 4 Exams HOMEWORK --> Prerequisites refreshers (from both courses) Exercises for this course level EXAMS --> Exams will reflect homework LABS --> --Chosen labs (multiple) from Statistical Physics I (SPI) will be repeated, but in a advance manner (with linkages to current course topics). Additionally, any labs identified in SPI not done in SPI can be done in this course (if they accommodate current course topics strongly). --Raman Scattering implementation with selection rules --Flinn, P. A. and McManus, G. M. (1963). Lattice Vibrations and Debye Temperatures of Aluminum. Physical Review Journals 132, 2458 Note: must have credible experimentation to accompany analytical development for compare/contrast --Debye experiment (from prior, apply whatever activities that serve as a preliminary circumstance to Debye) A. We investigate the behaviour of the specific heat of an [X]−crystal for the temperature range between 4.2 K and room temperature. The cooled [X]−crystal is heated by a low energy pulse whereas the temperature increase within the crystal is measured. Due to the experimental setup we also gain results for thermal and heat conductivity. Finally we verify the data theoretically given by the Debye model: http://www.thphys.de/docs/F14_Debye_Experiment.pdf B. Deacon, C. G., de Bruyn, J. R. & Whitehead, J. P. (1992). A Simple Method for Determining Debye Temperatures. American Journal of Physics 60(5), 422 -- << Dalton, CP2k, Firefly, Gaussian, GAMESS-US, MOLDEN, NWchem, GPAW, Octopus, ORCA, FreeON, PUPIL, VOTCA , BOSS >> NOTE: the various mentioned software above can possibly accommodate particular statistical physics interests if deemed practical and constructive. NOTE: will have a look-through with the supporting documentation and articles that elaborate on the applied models and algorithms of chosen software before implementing chosen software. Pursuits will be constructively relevant to lecturing topics. Software chosen must be well understood to fully capitalize on their potential with lecturing topics. COMPUTATIONAL DEVELOPMENT --> Computational development will require some amount of coding. ANY computer language may be used. Computational activities will be orchestrated to be harmonic with progression of course. Literature and interests of concern: -Sokal A. (1997) Monte Carlo Methods in Statistical Mechanics: Foundations & New Algorithms. In: DeWitt-Morette C., Cartier P., Folacci A. (eds) Functional Integration. NATO ASI Series (Series B: Physics), vol 361. Springer -Krauth. (2006). Statistical Mechanics Algorithms and Computations. Oxford University Press. -Lauwers, P G. (1990). Multiscale Monte Carlo Algorithms in Statistical Mechanics & Quantum Field Theory. Bonn Univ. Physikalisches Inst., Germany -A. L. Yuille and J. J. Kosowsky, (1994). Statistical Physics Algorithms That Converge. Neural Computation, vol. 6, no. 3, pp. 341-356 POSSIBLE APPLIED TOPICS IN COURSE --> 1. Density functional theory of dense liquids, Hydrodynamics, Transport equations, surfaces, evaporation and condensation. DFT case: Archer, A. J. (2006). Dynamical Density Functional Theory for Dense Atomic Liquids. Arxiv. Nascimento E. S. et al (2007). Density Functional Theory for Dense Nematic Liquid Crystals with Steric Interactions. Phys Rev E. 96(2-1): 022704. Forsman, J., Woodward, C. E Trulssn, M. (2011). A Classical Density Functional Theory of Ionic Liquids. Phys. Chem. B, 115, 16, 4606–4612 2. Astrophysical applications to white dwarf stars, neutron stars and black holes, Hawking radiation 3. Biochemistry/Molecular Biology (hopefully no overwhelming chemistry) Note: it’s essential that computational development be pursued, else, articles can not be validated. Chalkboards and sharpies aren’t good enough Ramanathan, S. & Shakhnovich, E. (1994). Statistical Mechanics of Proteins with “Evolutionary Selected” Sequences. Phys. Rev. E 50(2), 1303 Dewey T. G. (1999). Statistical Mechanics of Protein Sequences. Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics. 60(4 Pt B): 4652-8. Zhang, Y. and Crothers, D. M. (2003). Statistical Mechanics of Sequence-Dependent Circular DNA and Its Application For DNA Cyclization. Biophysical Journal Volume 84, 136–153 COURSE SYLLABUS: Canonical ensemble Grand canonical ensemble Formulation of quantum statistics: density matrix Photons, the Planck distribution, and thermal radiation Lattice vibrations and Debye theory Ideal Bose gas and Bose condensation Ideal Fermi system: degenerate electron gas in metals Magnetic behavior of an ideal Fermi gas: Pauli paramagnetism and Landau diamagnetism Virial expansion; cluster expansion First-order phase transitions Mean field theory Ising model and Ising-Glauber development Second-order phase transitions Critical phenomena, scaling Brownian motion: Langevin theory, Fokker-Planck theory. Transport phenomena: conduction (Drude theory), diffusion, thermal transport Onsager relation, fluctuation-dissipation theorem Far from equilibrium systems; non-ergodicity Prerequisite: Statistical Physics I, Stochastic Models & Computation (check COMP FIN) FOR ACTIVITIES IN THE “SUMMER” AND WINTER” SESSIONS ALL PARTICIPATING STUDENTS, ASSISTING/ADVISING INSTRUCTORS AND PROFESSORS MUST BE OFFICIALLY RECOGNISED; REQUIRES BOTH CIVILIAN ID AND STUDENT/FACULTY ID FOR CONFIRMATION OF INDIVIDUAL. THERE WILL ALSO BE USE OF IDENTIFICATIONS FOR ACTIVITIES FOR RESPECTIVE SESSION. SECURITY AND NON-PARTICIPATING ADMINISTRATION WILL ONLY IDENTIFY RESPECTIVE ACTIVITY BY IDENTIFICATION CODE. SECURITY AND NON-PARTICIPATING ADMINISTRATION MUST NEVER KNOW WHAT ACTIVITIES IDENTIFICATION CODES IDENTIFY: < Alpha, Alpha, Alpha, Alpha > - < # # # # # > - < session > - < yyyy > Such physics activities will also warrant criminal background check (CBC) in order to participate. Severely threshold may vary depending on administration. Administrators will provide dated letters of confirmation of thorough CBC to student affairs and other appropriate administration. Such also may include screening that’s parallel to customs & immigration processing where certain levels of criminal history warrants rejection. Email and physical letters with data. Such CBC protocol will not explicitly identify any particular titles or descriptions of any activity, rather, will only convey code as above. For the “summer” and “winter” sessions this activity repeated can be added to transcripts upon successful completion. Repeated activities later on can be given a designation such as Advance “Name” I, Advance “Name” II. As well, particular repeated activities serve to towards developing true comprehension, competency and professionalism. It may be the case some activities can be grouped and given a major title together; however, detailed descriptions will be required. Observational Telescope Modelling & Construction Activity is a major and critical opportunity for students to become technology relevant, competent, confident and independent. Course treats both optical telescope applications and radio telescope applications. I. Optical Telescope Analytical Development --> Laws of optics (mirrors and lens) Telescopes (Refracting, Reflecting and Catadioptric Telescope) Physics and quantitative models taking place with types Configuration types simulated with at least Optica 4 or alternative (will be helpful with validating prior) Surface resolvability Angular Resolution Focal length and focal ratio Light gathering power Magnification Visual (ratio of focal length to eyepiece); limiting the FOV Minimum (ratio of length of aperture to length of exit pupil) Optimum Relation between true FOV and apparent FOV Max FOV Image Scale Aberrations Telescope Resolution Chung J. (2015). Astro-Imaging Projects for Amateur Astronomers. The Patrick Moore Practical Astronomy Series. Springer, Cham. II. Optical Telescope Lab Development --> PART A NOTE: students must establish consistency with analytical development Open source platforms like the following pursued: A Powerful Telescope You can Build at Home – YouTube One should understand clearly the operational capabilities of the platform. Overall a range limited to the solar system is not acceptable. Secondly, one should not assume such is the only place to acquire an open source platform. Sanitary and hygiene protocols. Physics of photometry and spectrophotometry It’s necessary to have various tests (configurated bodies, celestial bodies and constellations) Photometry and spectrophotometry (configurated bodies) Luminosity, temperature, composition Photometry and spectrophotometry (celestial bodies and constellations) Luminosity, temperature, composition How does relativity affect your astronomy optical observations? How is such accounted for in data development? Note: today, general CAD designs and specs for optical telescopes are open source, towards 3D printing. For our interests the smallest scale generally will not suffice however concerning integration with a CCD camera and its feed components; extracting data as well. Smartsphones and smartpads may have CCD cameras, but data extraction is the concern with proper integration with the optical telescope. PART B The alternative, an even more manual build, from Peter Smith. CAD development is crucial to accomplish anything --> Making a Telescope - YouTube Telescope Design and Building - YouTube Literature self-construction if pursued: Chung J. (2015). Astro-Imaging Projects for Amateur Astronomers. The Patrick Moore Practical Astronomy Series. Springer, Cham. NOTE: students must establish consistency with analytical development. NECESSARILY HOWEVER, for part A and/or part B one wants to incorporate particular technological features: --The ability to implement photometry operations. Gathering light in a telescope then passing it through specialised photometric optical bandpass filters, and then capturing and recording the light energy with a photosensitive instrument. Standard sets of passbands are defined to allow accurate comparison of observations. CCD camera is required with technical procedures where various forms of photometric extraction can be performed on the recorded data (choice out of relative, absolute, and differential); either of the three requires extraction of the raw image magnitude of the target object, and a known comparison object. The observed signal from an object will typically cover many pixels according to the point spread function (PSF) of the system; implementing aperture photometry and use of de-blending techniques such as PSF fitting (whenever necessary), etc., etc., etc. Concerning the point source, a flux is measured. Then, after determining the flux of an object in counts, the flux is normally converted into instrumental magnitude. Then, the measurement to be calibrated, depending on what type of photometry is being done. Photometric measurements can be combined with the inverse-square law for determination of luminosity of an object. Additionally, other physical properties of interest for an object, its temperature, chemical composition, can be determined via broad or narrow-band spectrophotometry. Photometric measurements of multiple objects obtained through two filters are plotted on a colour-magnitude diagram, which for stars is the observed version of the Hertzsprung-Russell diagram. ASSUMED: integrable with Graphical Astronomy & Image Analysis Tool (GAIA), DS9 and OSCAAR; would be a tremendous accomplishment. Sanitary and hygiene protocols. It’s necessary to have various tests (configurated bodies, radiated objects, celestial bodies, etc.) Photometry and spectrophotometry (configurated bodies) Luminosity, temperature, composition Photometry and spectrophotometry (celestial bodies and constellations) Luminosity, temperature, composition How does relativity affect your astronomy optical observations? How is such accounted for in data development? III. Analytical Radio Telescope Analysis & Development --> Critical concerns: Radio spectroscopy and its uses The Doppler effect and its uses Balmer Series and its uses Rydberg formula and its uses Note: for the 4 prior topics it’s essential that exercise problems are given, ALONG WITH activities involving raw data to extract astrophysical data (motion, physical, chemical, etc.); a tangible, practical and fluid process is expected for the activities. Wilson, T., Rohlfs, K., & Hüttemeister, S. (2013). Tools of Radio Astronomy. Springer Berlin Heidelberg Radio Communication Bureau (2013). Handbook of Radio Astronomy, International Telecommunication Union: https://www.itu.int/dms_pub/itu-r/opb/hdb/R-HDB-22-2013-PDF-E.pdf Gaylard, M. (2012). Radio Astronomy with a Satellite Dish. Hartebeesthoek Radio Astronomy Observatory: < https://avntraining.hartrao.ac.za/images/radio_astronomy_with_a_satellite_dish.pdf > IV. Radio Telescope Lab/Field Development --> Testing concerns: distance, speed/velocity, convergent or divergent speed between bodies, temperature, chemical composition. Demonstrating the ability to acquire various data from Doppler with configurated bodies Demonstrating the ability to acquire a treasure trove of data from spectroscopy activities with configurated bodies Celestial bodies and constellations How does relativity affect your astronomy radio observations, and how is such accounted for in data development? Then, followed by pursuits similar to the following (where inquisition on relativistic “interference” will be applied upon the following resources): Flavio Falcinelli (2017). Amateur Radio Astronomy Equipment. How to use RAL10KIT and RAL10AP to build a Microwave Radio Telescope http://www.radioastrolab.com/pdf/How_to_build_an_amateur_radio_telescope_with_RAL10KIT_RAL10AP.pdf Additional Strong Ideas: https://www.rtl-sdr.com/low-cost-hydrogen-line-telescope-using-rtl-sdr/ https://www.rtl-sdr.com/building-a-hydrogen-line-front-end-on-a-budget-with-rtl-sdr-and-2x-lna4all/ https://www.rtl-sdr.com/observing-21cm-hydrogen-line-linrad-rtl-sdr/ https://www.rtl-sdr.com/hydrogen-line-observation-with-an-rtl-sdr/ https://www.rtl-sdr.com/some-new-rf-filters-from-adam-9a4qv/ NOTE: one can make use of those old large mesh disk dishes that have high detection ability, but system components and power must appease such. Construction of a decent size radio telescope as such. One principle is to have strong detection and competency with data readings. Implementation of software to enable the telescope to track sources in a celestial co-ordinate system (if able). Initial installation of at least C-band receiver so that first observations could make use of the existing feed system. Parameters and concerns to consider: 1. Azimuth Maximum (Tracking and Slewing) 2. Elevation Maximum (Tracking and Slewing) 3. Azimuth Working Range (as defined by soft limits) 4. Elevation Working Range (as defined by soft limits) 5. A clock (set and regulated from network time) 6. Telescope Pointing Error Correction (may also concern optical telescopes in the first part) 7. Correction for atmospheric refraction ASSUMED, the mentioned software like SPLAT/SPLAT-VO will be integrable. Account for both red-shifting or blue-shifting and dilations to high degree when necessary. Sanitary and hygiene protocols. Prereqs: General Physics I & II, ODE, Numerical Analysis, Calculus III, Introduction to Astronomy NOTE: any possibility of an astronomy club to begin is contingent on the determined accumulation of telescopes built (optical and radio). As well, students to constitute the astronomy club must have grades at the B level in the “Introduction to Astronomy” course, and successfully complete the “ Observational Telescope Modelling & Construction” activity. In club students must declare and implement projects with reports towards supervising instructor/professor, and possibly towards appropriate astronomical societies or associations. After qualification and matriculation into astronomy club, to remain in this club a member must have at least continuous course registration in the “Techniques in Observational astronomy I & II” courses. Capable club members can possibly supervise enthusiastic students who don’t have a primary interest in astronomy; such visiting non-club students must suffice security approval and behavioural code with registry; they must acquire scheduling with astronomy club students and supervising instructors/professors. Students/Faculty officially in academic pursuits of astronomy, astrophysics and relativity (SFOAPAAR) as physics majors to be differentiated from common students with interest; scheduling for SFOAPAAR may have higher priority when the economics is right. SFOAPAAR must have confirmed continuous research or studies for use of telescopes. If SFOAPAAR constituents have no true intention of professional use they must be identified as common constituents in scheduling. Visiting SFOAPAAR constituents must also clear security and behavioural requirements. Concerning the astronomy club, it’s quite essential the students are knowledgeable of credible astronomical news sources concerning astrophysical activities and events (notifications via club site/email registry, smartphone notifications, etc., etc. It’s also quite essential to have access to a practical and constructive calendar concerning meteors, asteroids, planets, eclipses, stars, constellations, etc. --Students in astronomy club are required provide a monthly astronomical editorial on their activities and research interests, with due credits and bridge foundation structure. --All observation data of the astronomy club are to be archived with professional categorizations that welcomes updating and extensions. Blockchains and blockchain databases on data and sent documentation (includes date and time) may be economical. Observation data also concerns security access and storage backups. --Editorial to also be archived. Editorial likely also have website with copyright integrity. Such to be followed by pursuit of published research or projects in amateur/professional astronomy or astrophysics (undergraduate or not) journals. --Essentially, works must be chronologically established, stored and secured in/on “domain” before pursuit of publication in professional astronomy or astrophysics (undergraduate or not) journal; emphasizing blockchain usage and practical encryptions with conveyance of works. Hence, there will be much logistics development and common practice for official observation form documentation (use and secure storage), astronomical observations and recording in blockchain databases, and discovery reporting. --Field activities expressed will be done in a advanced manner. Additionally, students will extend asteroid orbit trajectory forecasts to include the effects of radiation pressure (and possibly moment of inertia with angular momentum). Simulation of orbits (likely through central scheme finite difference and/or Runge Kutta) based on either or both of the following articles: Veras, D., Eggl, S., and Gansicke, B.,T., The orbital Evolution of Asteroids, Pebbles, and Planets from Giant Branch Stellar Radiation and Winds, Monthly Notices of the Royal Astronomical Society, 451, 2814–2834 (2015) Martyusheva et al, Solar Radiation Pressure Influence in Motion of Asteroids, Including Near-Earth Objects, 2015 International Conference on Mechanics, IEEE There may be times where data and parameters must be acquired; some can be acquired through credible sources. Forecast trajectory simulations (likely in AU distance measure or SI) for various chosen asteroids, etc. in reference to the Sun and planets. Such simulations to be geometrically compared with trajectory prediction from observation, radiometry and professional credible sources for determination of consistency/accuracy. As well, open to the possibility of compare and contrast with tools of Bayesian and Markov Chain (algorithms) if able. Astronomy/Astrophysical Observation Pursuits Such activity concerns expanding or strengthening interests encountered in any of the Astronomy courses. Such will serve well towards members of the astronomy club, making constructive use of time in such a club towards academic record. It’s also possible to reinforce or expand topics out of the Space Science courses involving astronomical/astrophysical data acquired from observation and databases. PART A Chosen topics out of any of the courses PART B --- Orbits of near-earth asteroids 1. Influences on “particle” orbits in the (near earth) solar system: Gravitational effects Non-gravitational effects: Solar radiation pressure Poynting-Robertson effect Yarkovsky effects Solar wind pressure Corpuscular Drag Electromagnetic interaction We will not focus on orbits of charged dust particles, so the last “sub-effect” may be omitted concerning asteroids categorized overall by bulk mass. For such influences will like to construct orbit models for various objects (asteroids and comets) in the solar system. Then for each object will acquire orbit data and extrapolate or model (whether least squares or whatever) to compare with our analytic/numerical methods models. Will choose 5-10 (or appropriate sample set) of near earth orbit asteroids for contrast between simulation and data based orbit modelling. 2. As well, gather data for the essential parameters of the Orbital elements involved from professional sources to yield more definitive orbit models. Then proceed with simulation of orbits based on appropriate initial conditions for long term trajectories. Such will be compared to orbit data for respective asteroid to see how close simulated orbits are to real orbit data. Confirmation of Keplerian orbits. What are the significant characteristics of Keplerian orbits? Will not focus solely on a compact Newtonian description, rather, investigating orbital parameters and geometries. Will choose a sample set of celestial bodies to confirm? Then, identify range of conic sections possible. Will all such prior mentioned effects (gravitational and non-gravitational together) appease a Keplerian model? 3. For all prior chosen objects to develop the light curves and extract properties. Will determine various information from the light curves, characterising orbits, velocity, other characteristics etc., etc. How does orbit determination from light curves compare to orbit models acquired from numerical/statistical methods? Some guides that may be valuable to activity: Solar Radiation Pressure --> Vokrouhlicky, D and Milani, A., Direct Solar Radiation Pressure on the Orbits of Small Near–Earth Asteroids: Observable Effects? Astron. Astrophys. 362, 746–755 (2000) Poynting–Robertson Effect --> Klacka, J. et al, The Poynting–Robertson effect: A critical perspective, Icarus 232 (2012) 249–262 Yarkovsky and YORP --> Vokrouhlicky, Bottke, Chesley, Scheeres, & Statler. (2015). The Yarkovsky and YORP Effects. ArXiv.org, Feb 4, 2015. Golubov, O. et al, Physical Models for the Normal YORP and Diurnal Yarkovsky Effects, MNRAS 458, 3977–3989 (2016) Bottke, Jr., William F.; et al. (2006). "The Yarkovsky and YORP Effects: Implications for Asteroid Dynamics". Annu. Rev. Earth Planet. Sci. 34: 157–191 Chesley, Steven R.; et al. (2003). "Direct Detection of the Yarkovsky Effect via Radar Ranging to Asteroid 6489 Golevka". Science. 302 (5651): 1739–1742 General --> Dobrovol’skii, O. V., Egibekov, P. and Zausaev, A. F., Nongravitational Effects on the Evolution of Dust Particles in Elliptical Orbits Around the Sun, Atron, Zh, 50, 832 – 835, 1973 PART C --- Oumuamua Investigation 1. The following article has detailed statements to investigate, where sources for data to investigate are quite uber. Note: in such journal article one will be highly reliant on the cited journal articles to progress with investigation. Bialy, S. & Loeb, A. (2018). Could Solar Radiation Pressure Explain ‘Oumuamua’s Peculiar Acceleration? The Astrophysical Journal Letters, 868: L1, 5 pages 2. Also interested in development of its light curve from raw data to acquire the customary information (velocity, orbirt, and the other attributes). 3. The following articles provide much detailed analysis on the physical make up and composition conditions to support the observed dynamics or trek of Oumuamua during its time in the solar system: Jackson, A. P. and Desch, S. J. (2021). 1I/'Oumuamua as an N 2 Ice Fragment of an Exo‐Pluto Surface: I. Size and Compositional Constraints, Journal of Geophysical Research: Planets Desch, S. J. and Jackson, A. P. (2021). 1I/'Oumuamua as an N 2 Ice Fragment of an Exo‐Pluto Surface II: Generation of N 2 Ice Fragments and the Origin of 'Oumuamua, Journal of Geophysical Research: Planets Are the findings from the articles of Jackson <--> Desch consistent with the of Bialy-Loeb? Solar System Trajectories PART A (elementary model of the Solar System) Numerical integration in 3-dimensional space. One starts with a high accuracy value for the position (x, y, z) and the 3-velocity for each of the bodies involved. When also the mass of each body is known, the 3-acceleration can be calculated from Newton’s law of gravitation. NOTE: tidal effects incorporation will be appreciated throughout. Each body attracts each other body, the total acceleration being the sum of all these attractions. Next, one chooses a small time-step and applies Newton’s second Law of Motion Acceleration multiplied by time increment gives a correction to the velocity; velocity multiplied by time increment gives a correction to position. Such position is repeated for other bodies. An Euler algorithm is likely involved. PART B (VSOP) To develop a description of long term changes (secular variation) in the orbits of planets, from mercury to Neptune. The following article describes the mathematical means to acquire such variations. Will compare particular simulated time events to real data from astronomical data sources. Simon, J. L, et al. (2013). New Analytical Planetary Theories VSOP2013 and TOP2013. Astronomy & Astrophysics 557, A49 PART C (constructing a Ephemeris) Analyse the following literatures. Aside from making any necessary amendments to develop our independent ephemeris system. The first article serves to develop the analytical and numerical integration approach. For the second literature our aim is to identify the models, data and developmental logistics. Then develop. Will compare particular simulated time events to real incoming data from astronomical data sources. Pitjeva, E. V. (2007). The Dynamical Model of the Planet Motions and EPM Ephemerides. Highlights of Astronomy, Volume 14, p. 470-470 Viswanathan, Vishnu & Fienga, Agnès & Gastineau, Mickael & Laskar, Jacques. (2017). INPOP17a planetary ephemerides < https://www.researchgate.net/publication/320035644_INPOP17a_planetary_ephemerides/citation/download > PART D (compare and contrast) There may be some events or behaviours that can be compare/contrasted among VSOP and Ephemeris PART E (further interests being optional) Emel'yanov, E. V. and Arlot, J. E. (2008). The Natural satellites Ephemerides Facility MULTI-SAT. Astronomy & Astrophysics 487, 759-765 Applied Electrodynamics & Nuclear Settings in Astrophysical Nature I. Solar and cosmic particles upon the earth’s magnetosphere. Modelling of gyro-radius with traverse for particles in magnetosphere. Will simulate such without neglecting the strength influence of the magnetic field w.r.t. radial distance and angular positioning. Types of radiation processes associated with magnetospheres and particles. Each type of radiation will be accommodated by mathematical model. Identify what man-made experiments can replicate the products, and compare scale specifications. II. Synchrotron radiation From the general knowledge the Earth is known to have a magnetic field. Description of particle trajectories subject to magnetic field dynamics can be modelled. Particles (charged) in magnetic fields accelerate and emit electromagnetic radiation (likely synchrotron radiation). Furthermore, particles tend to move to either the north or south pole. Have radio receiver tuned to around the frequency of such waves to hear the effect of all the particles coming from the Sun in a solar wind, capture by Earth’s magnetic field (short wave radio related). Apart from “hearing clicks and screams”, will also like to see what we’re hearing, and how to model such data towards something definitive to characterise. Will explore whether such data is a treasure trove for determining what types of matter or particles we are observing. Naturally, space weather forecasts will be pivotal for observation. May be of interest: determining time of event at source, time of reception, distance from source, gravitational shifting model (likely based on the geo-potential) Is it often for many to confuse such synchrotron radiation with astronomical data of other sorts (other planets, stars, etc., etc.). If so, what resolutions are available? III. Hearing Radio Signals from Jupiter Jupiter is a source of powerful bursts of natural radio waves that can produce exotic sounds when picked on Earth using simple antennas and shortwave receivers. Short wave radio signals from Jupiter or Saturn are likely due to plasma instabilities in Jupiter’s magnetosphere. Ionized gas in the upper atmosphere of above Jupiter’s magnetic poles often behave as a powerful radio laser or maser. For the case of Jupiter, it starts on volcanic moon Io. Tidal forces from Jupiter and its other large satellites superheat the interior of Io leading to volcanic activity. Thus, volcanic materials are hurled high above the surface of Io entering around Jupiter forming a gaseous “donut” around Jupiter. As Io’s orbital motion carries it through such ring of ionized gas, a vast electrical current flow between Io and Jupiter. Tasks: 1. Tidal forces from Jupiter and its other large satellites superheat the interior of Io leading to volcanic activity. Acquire planetary geophysical model to confirm such with appropriate parameters. 2. One needs confirmation of the size of such torus comparable to Io’s orbit and possible interaction with Jupiter’s magnetic field for theory to be valid. 3. As Io’s orbital motion carries it through such ring of ionized gas, a vast electrical current flow between Io and Jupiter. Identify the electromagnetic law(s) towards such electrical current based on the astrophysical setting described; along with mathematical model. Why is it direct current? 4. Plasma physicists believe that the current in the Io-Jupiter system is carried by a type of magnetic plasma called Alfven waves. Provide model description of Aflven waves through physics and possible mathematical models; to also make sure the such in (3) is compatible towards the creation of such waves. 5. An estimate is around two trillion watts of power, say, a powerful DC electrical circuit in the Solar system. How can one confirm such measure of power is valid based on the physics of the astrophysical setting with mathematical modelling? 6. How do such mechanisms of (3) through (5) lead to laser radio signals? How does one establish that emissions away from Jupiter’s magnetic poles in cone shaped beams are “radio” and not other through and through? 7. Beams are said to rotate with the planet every 9 hours and 55 minutes, say, similar to a pulsar. Confirm such via professional data and field observation. When the beams past Earth, listeners can receive the Jovian radio bursts in shortwave bands between 15 and 40 MHz, hence, confirm such via professional data sources and by field observation. Note: knowledge of pulsar beam rotation speeds will be known to distinguish pulsars from that of Jupiter. As well, Saturn is also known to produce radio signal, hence, develop means to distinguish between such two planets. Furthermore, determine how are Saturn’s radio signals produced, and one can pursue similar activity to that done for Jupiter, however, mechanisms, etc. may be completely different. IV. Neutron star physics Silbar, R. and Reddy, S., Neutron Stars for Undergraduates, Am. J. Phys. 72 (7), July 2004 -- http://www.rpi.edu/dept/phys/Courses/Astronomy/NeutStarsAJP.pdf Students may be tasked to verify some equations. Bildsten, L. and Cumming, A. (1998). Hydrogen Electron Capture in Accreting Neutron Stars and the Resulting g-Mode Oscillation spectrum. The Astrophysical Journal, 506: 842 - 862 Is electron capture contrary to electron orbital theory with lowest possible shells? Lattimer, J. M., The Nuclear Equation of State and Neutron Star Masses, Annu. Rev. Nucl. Part. Sci. 2012. 62: 485 – 515 Concerning the following journal article, a challenge may be reconciling it with prior journal articles. Furthermore, “This review summarizes the progress, which has been achieved over the last few years, in modeling neutron star crusts, both at the microscopic and macroscopic levels. The confrontation of these theoretical models with observations is also briefly discussed.” One will also like to choose a sample set of neutron stars from arbitrary locations, acquiring data to compare/contrast theory with data concerning neutron star surfaces/crust --> Chamel, N., & Haensel, P. (2008). Physics of Neutron Star Crusts. Living reviews in relativity, 11(1), 10 Differentiating between the source of magnetospheres from main sequence stars and pulsars. V. Will analyse pulsar mechanisms and physiology What separates the general nuetron star designation from pulsar designation despite the latter being a special case of the former? Consider the following two journal articles: --Ruderman, M. A. and Sutherland, P. G. (1975). Theory of Pulsars: Polar Gaps, Sparks, and Coherent Microwave Radiation, The Astrophysical Journal, 196: pages 51-72 --Goldreich, P. and Julian, W. H., Pulsar Electrodynamics (1969), The Astrophysical Journal, Vol. 157 Concerning the above two journal articles one major goal is to identify correctly counterpart or peer definition of quantities/models and determine which among the peers are more versatile or practical with computations. Often will be the case that one article is more explicit towards computational and numerical modelling, or be more parameter based for mechanisms. It is for students assisted by instructors to recognise all critical quantity models and parameters necessarily to well model pulsars and the unique properties. One can develop a table for model quantities and parameters that are comparable or relatable from both journal articles. Likely one will find many equations and parameters with no peer. Such will be followed by analysing the models for the toroidal magnetic field, and polar magnetic field; identify boundary conditions to be placed, respectively. Then to analyse the relation between such two magnetic fields (Goldreich and Julian). Models of the two magnetic fields (with their boundary conditions) and the relation between such two magnetic fields can possibly be applied to the journal article of Ruderman and Sutherland towards more explicit modelling with polar gaps, sparks, particle pair creation, cascades, etc. VI. Incorporating Killing Fields into descriptions The following describes a description relatable to the Hartle-Thorne metric: Kim, H. et al, Pulsar Magnetospheres: a General Relativistic Treatment, Mon. Not. R. Astron. Soc. 358, 998–1018 (2005) One must be able to comprehend why the time-like Killing field has no direct appearance in modelling. As well, one should acquire an explicit representation for the Killing fields. VII. Further, the following journal article then applied can make things much more numerical or computational: Michel, F. C., Rotating Magnetosphere: A Simple Relativistic Model, The Astrophysical Journal, 180: 207- 225, 1973, February 15 This journal article above provides computation or numerical modelling for field lines not found in other journals. The aim is pursuit of the magnetic field components in terms of such field lines that’s agreeable with Killing field association to prior articles. VIII. Detecting pulsars From constructed radio telescopes will establish means to differentiate between pulsar detection and detection of other astrophysical bodies. Includes source distance and reference to the coordinate positioning, etc., etc. http://pulsarsearchcollaboratory.com/wp-content/uploads/2016/01/PSC_search_guide.pdf Lab/Field Experimentation << http://www.astro.utoronto.ca/~astrolab/files/Lab4_AST326_2018_Winter_v1.1.pdf The mentioned observatory likely will not be available but there many data sources around the world. Nevertheless, actual use of constructed radio telescopes will be done and data compared to established radio telescopes for determination of accuracy and consistency. How does one distinguish solar data (Sun, planets, auroras) from pulsar data? Neutron star data and fitting the theoretical models The international space station has installed its NICER equipment to acquire data of astrophysical bodies such as neutron stars (includes pulsars and magnetars). Means of data acquisition: NICER with NICERDAS Now, NICER with NICERDAS may not accommodate radio waves astrophysical activity, but there are counterparts to compliment NICER/NICERDAS for such (whether in space or terrestrial or databases). Pursue such as well. Will apply fairly high sample of neutron stars (includes pulsars and magnetars) A. Neutron star characteristics of interest relating modelling with data: Properties (mass, temperature, density, pressure, magnetic field, gravity, equation of state Structure Energy Source Radiation (pulsars, non-pulsing neutron stars, Type I and Type II X-Ray bursts, spectra) Rotation (spin down, spin up, glitches & starquakes, anti-glitches) Population and distances Binary neutron star systems (X-ray binaries, neutron star binary mergers & nucleosynthesis) Orbits B. As well, from data and theoretical model fittings one should also observe whether establishments appease the Hertzsprung - Russell Diagram theory. SOME POSSIBLE USEFUL LITERATURE TO ASSIST IN RESEARCH: The following articles (not listed in terms of rank of importance) will be invaluable, however, they will likely not encompass everything: Physiology --> Silbar, R., Reddy, S., Neutron Stars for Undergraduates, Am. J. Phys. 72 (7), July 2004 Oppenheimer, J. R.; Volkoff, G. M. (1939). "On Massive Neutron Cores". Physical Review. 55 (4): 374–381 Cameron, A. G. (1959). Neutron Star Models. Astrophysical Journal, vol. 130, p.884 Physiological Profiling --> Özel, Feryal et al (2012). "On the Mass Distribution and Birth Masses of Neutron Stars". The Astrophysical Journal. 757 (1): 13 Chamel, N.et al (2013). "On the Maximum Mass of Neutron Stars". International Journal of Modern Physics. 1(28): 1330018 Ozel, Feryal; Freire, Paulo (2016). "Masses, Radii, and the Equation of State of Neutron Stars". Annu. Rev. Astron. Astrophys. 54 (1): 401–440. Jiang, Nan, & Yagi, Kent. (2019). Improved Analytic Modelling of Neutron Star Interiors. Physical Review D, 99(12) Note: astrophysical data with clustering or PCA techniques may be applicable Relativistic Techniques --> Rezzolla, L. Most, E. R. and Weih, L. R. (2018). "Using Gravitational-wave Observations and Quasi-universal Relations to Constrain the Maximum Mass of Neutron Stars". The Astrophysical Journal. 852 (2): L25 Morsink, S., M., and Stella, L. (1999). Relativistic Precession Around Rotating Neutron Stars: Effects Due to Frame Dragging and Stellar Oblates, The Astrophysical Journal, 513 : 827-844, Pulsars --> Ruderman, M. A. and Sutherland, P. G. (1975), Theory of Pulsars: Polar Gaps, Sparks, and Coherent Microwave Radiation, The Astrophysical Journal, 196: 51-72 Goldreich, P. and Julian, W. H. (1969). Pulsar Electrodynamics, The Astrophysical Journal, Vol. 157 X-Ray Bursts --> Cumming, A. (2004). Thermonuclear X-Ray Bursts: Theory vs. Observations. Nuclear Physics B – Proceeding Supplements. Volume 132, pages 435 – 445 Cumming, A. (2003). Models of Type I X-Ray Bursts from 4U 1820-30. The Astrophysical Journal, 595: 1077-1085 Bildsten, L. (2000). Theory and Observations of Type I X-Ray Bursts from Neutron Stars. AIP Conference Proceedings 522, 359 Selecting and Utilizing Pulsars for Galactic Navigation (INCOMPLETE) Sala, J. et al (2004). Feasibility Study for a Spacecraft Navigation System relying on Pulsar Timing Information. European Space Agency Shemar, S., Fraser, G., Heil, L. et al. (2016). Towards practical autonomous deep-space navigation using X-Ray pulsar timing. Exp Astron 42, 101–138 Vidal., Clément (2017). "Millisecond Pulsars as Standards: Timing, Positioning and Communication". In: Pulsar Astrophysics – The Next Fifty Years – Proceedings of the 337th Symposium of the International Astronomical Union. Russel, R. A. (2020). Galactic Navigation using the Pioneer Spacecraft Pulsar Map. Deep Space Exploration Society Russel, R. A. (2020). A Practical Guide for Selecting and Utilizing Pulsars for Galactic Navigation. Deep Space Exploration Society Finding Black Holes PART A (X-Ray Method) Prominent X-Ray emissions are (often) identified with the presence of blackholes. Will acquire X-Ray satellite raw data towards modelling and analysis for confirmation. There are numerous X-Ray satellite options out there. PART B (use of doppler shift and ellipsoidal variability measurements) The following is the forefront article for the new method of black hole detection, subject to some necessary particular settings (blackhole - star binary): Thompson, T. (2019). A Noninteracting Low Mass Black Hole – Giant Star Binary System. Science 01, Vol. 366, Issue 6465, pp. 637 – 640 Analyse the above journal article, develop logistics for replication, then pursue verification of experiment. Will then apply such method to other known black hole-star binary systems to determine consistency. How much systems are enough? Yes, mass determination is of interest. PART C (comparing part A to part B will field cases) Can the X-Ray method be applied strongly to black hole-star binary systems? Will X-Ray results be consistent with the new method of Thompson et al? Comparative estimation of mass via X-ray emission with method from Thompson et al if possible Spin Determination of Black Holes In addition will identify some further tests of general relativity and measuring parameters for black holes: 1. For the following article, apart from required analysis will identify the logistics for the use of data and means to acquire such data for sources towards replication of results: Collett, T. E. et al. A precise extragalactic test of General Relativity. Science 22 Jun 2018: Vol. 360, Issue 6395, pp. 1342-1346 2. For the following articles, apart from required analysis will identify the logistics which includes the additional required mentioned journal articles towards data acquisition, applying such data to models, simulations and replications of findings. Also, students can investigate other blackholes and compare findings with professional sources. Also, students can investigate other blackholes and compare findings with professional sources: --Kulkarni, A. K. et al. Measuring black hole spin by the continuum-fitting method: effect of deviations from the Novikov–Thorne disc model. Mon. Not. R. Astron. Soc. 414, 1183–1194 (2011). Note: spin parameter formula in article may be a bit different compared to what is observed in other texts and articles concerning M. --Gou, L. et al. (2014). CONFIRMATION VIA THE CONTINUUM-FITTING METHOD THAT THE SPIN OF THE BLACK HOLE IN CYGNUS X-1 IS EXTREME. The Astrophysical Journal, 790:29 (13pp) 3. Measuring Black Hole Spin-Strong Gravity Project The following link provides a simplistic but deceptive synopsis, in the sense that the processes are much more tedious than conveyed: http://stronggravity.eu/how-to-measure-black-hole-spin/ One is to recognise the various methods for black hole spin measurement and recognise the instruments, resources and logistics necessary to carry out the respective method. Will apply the methods that are feasible through acquisition of data usage, and compare with each other, then to compare with the continuum-fitting method from (2). The following is the general link where one should access the links on the site (especially “Consortium”, “Project”, “Results”, “Public Outreach”): http://stronggravity.eu

Blandford-Payne-Znajek Modelling (incomplete) 1.Dashboard Development There must be verification that the modelling process among the articles fall in line with each other’s development, exhibiting that pair creation involving a force free magnetosphere is valid in black hole electrodynamics. It may be constructive to create a table to input essential bullent material for both articles, then to reconcile or harmonize such material based on extensive anaysis/research. Blandford R. D. and Znajek, R. L., Electromagnetic Extraction of Energy from Kerr Black Holes, Mon. Not. R. Astr. Soc. (1977) 179, 433-456. Znajek, R. L., Black Hole Electrodynamics and the Carter Tetrad, Mon. Not. R. Astr. Soc. (1977) 179, 457-472 Hirotani, K. and Okamoto, I., Pair Plasma Production in a Force Free Magnetosphere around a Supermassive Blackhole, The Astrophysical Journal, 497: 563 - 572, 1998 April 20 2.Computational Environment Computational coding involving quantities or measures w.r.t to the metric or quantities found in the Kerr metric (and tetrads) provide explicit details one can’t observe with “symbolic shells”. Only by such can one observe or reach the real models; for many magnetic models, formulas and differential equations, developing plots, solutions and simulations may be helpful towards understanding or visualizing behaviours. 3.Trying to relate the BZ process with jets and AGNs Pursue a robust connection with jets & AGNs through physics & mathematical modelling. Prior journal articles for structure will be crucial. The possible articles to assist in making the connections: BZ type models for jets: Blandford, R. D. and Payne, D. G. (1982) Hydromagnetic Flows from Accretion Discs and the Production of Radio Jets. Mon. Not. R. astr. Soc. (1982) 199, 883 - 903 Ding-Xiong W. et al. (2008). The BZ–MC–BP Model for Jet Production from a Black Hole Accretion Disc. Monthly Notices of the Royal Astronomical Society., Vol. 385 Issue 2, p841-848 Wei Xie et al (2012). A Two-Component Jet Model based on the Blandford-Znajek and Blandford-Payne Processes. Research in Astron. Astrophys. Vol. 12 No. 7, 817–828 Raw AGN Models: Rees, M. J. (1984). Black Hole Models for Active Galactic Nuclei, Ann. Rev. Astron. Astrophys. 194. 22: 471- 506 Park, S. J. and Vishniac, E. T., (1988). The Evolution of the Central Black Hole in an Active Galactic Nucleus.. I. Evolution with a Constant Mass Influx. The Astrophysical Journal, 332: 135-140 Park, S. J. and Vishniac, E. T., (1990). The Evolution of the Central Black Hole in an Active Galactic Nucleus.. II. Evolution with an Exponentially Decreasing Mass Influx. The AstrophysicalJournal, 353:103-107 Meier, D. L. (2011). The Formation of Relativistic Cosmic Jets. Jets at All Scales, Proceedings of the International Astronomical Union, IAU Symposium, Volume 275, p. 13-23 4.Acquire data astronomical data for AGNs and jets, say X ray eruptions, radio waves (eruptions),etc.. Fairly decent sample required. The following article may be a decent guide towards development of data analysis; other data of interest to augment is plausible Fabian A. C. (1999). Active Galactic Nuclei. Proceedings of the National Academy of Sciences of the United States of America, 96(9), 4749–4751. https://doi.org/10.1073/pnas.96.9.4749 5.Galaxy Imaging --Optical image of galaxies obtained with the Hubble Space Telescope (from Hubble Heritage) data (or alternative), overlaid by contours of the total radio intensity and polarization vectors at 6cm wavelength, combined from radio observations with the Effelsberg and VLA radio telescopes (from Fletcher et al. 2011). The magnetic fields should follow well the galactic structure, but in the case of spiral galaxies, the regions between the spiral arms also should contain strong and ordered fields. Scale of 1 arcminute or about 9000 light years (about 3 kiloparsecs) at the distance of the galaxy, or whatever appropriate. --Optical image of galaxies in the Hα line overlaid by contours of the polarized radio intensity and radio polarization vectors at Xcm wavelength, combined from observations with the Effelsberg and VLA radio telescopes. In the case of spiral galaxies there should be strong regular fields between the optical spiral arms. --Intensity of the total radio emission at Xcm wavelength (colours) and polarization vectors of galaxies, observed with the Effelsberg telescope. The radio emission should be concentrated where the magnetic field is exceptionally regular on scales of several kiloparsecs. --Optical image in the Hα line of galaxies, overlaid by contours of the intensity of the total radio emission at Xcm wavelength and polarization vectors, observed with the VLA. The field lines are parallel to the disk near the plane, but turn vertically above and below the disk. 6. Is it possible emprically fit a BZ model to AGN/jets features. What measures or quantities will be required for cresdibility? Optics Research 1. Will have recitals for particular experiments done in the following courses: --Introduction to Optics --Advanced Optics Lab Students must develop certainty about purpose of experiments. Activity open to EE constituents. Will apply Optica integrated with Mathematica, or OSLO, to model and simulate optics laboratory set ups, acquiring ideal values, parameters, imagery, etc. to be compared with orchestrated optics experimentation lab setups. 2. In addition, such pursuit of competency and professionalism will lay the foundation to develop most constructions for various types of spectroscopy (excluding mass spectroscopy). Building a simple functional infrared spectroscopy system with single-board microcontrollers or microcontroller kits. Will then determine its competence and accuracy in terms of the role of vibrational spectroscopy for molecules, compounds, etc., with calibrating and comparing with professional databases. 3. Design and construction for: Raman spectroscopy UV spectroscopy CCD spectroscopy (https://www.fzu.cz/~dominecf/spek2/vu.pdf) Physics and mathematical modelling with be established before building and construction. Calibration. Results will be compared with professional databases. 4. TRTCDS Analyse the given journal article, logistics, and investigate the economic feasibility of such optical setup. Will like to develop such optic set up towards experimentation and means of confirming its credibility--> Auvray, F. et al (2019). Time Resolved Transient Circular Dichroism Spectroscopy Using Synchrotron Natural Polarisation. Structural Dynamics, Volume 6, Issue 5, 054307 Students must have at least Introduction to Optics course as prerequisite. Photonic Dating Carbon dating only works for objects that are younger than about 50,000 years, and most rocks of interest are older than that. Carbon dating is used by archeologists to date trees, plants, and animal remains; as well as human artifacts made from wood and leather; because these items are generally younger than 50,000 years. Carbon is found in different forms in the environment – mainly in the stable form of carbon-12 and the unstable form of carbon-14. Over time, carbon-14 decays radioactively and turns into nitrogen. A living organism takes in both carbon-12 and carbon-14 from the environment in the same relative proportion that they existed naturally. Once the organism dies, it stops replenishing its carbon supply, and the total carbon-14 content in the organism slowly disappears. Scientists can determine how long ago an organism died by measuring how much carbon-14 is left relative to the C-12. Review of the physics of unstable C-14 in various objects. Review of radioactive decay modelling (Carbon-14). The level of innovation academia possesses is often an enemy of firms. The ability to be self-sufficient and versatile can be quite trouble for firms’ markets and recognition of market segmentation. Accelerator mass spectroscopy is a premier means of radiocarbon dating. Conventionally, higher education institutions that have passed through the socio-political and socioeconomic gauntlets are those who can afford and operate such massive technologies. However, an alternative means of carbon dating with optics or photonics yields credible results in shorter periods, but with more versatility in mobility, maintenance and training, thus costs can be greatly reduced. Fast overview of the physics and logistics of accelerated mass spectroscopy. Then, the following journal articles are to be analysed, then pursuit of actual development a module towards interactive experimental carbon dating: Mazzotti, Davide. (2013). Verso una datazione ottica al radiocarbonio; Towards an optical radiocarbon dating. Il Colle di Galileo 2 (1), 65 – 68. Labrie, D. and Reid, J, Radiocarbon Dating by Infrared Laser Spectroscopy, J. Appl. Phys. April 1981, Volume 24, Issue 4, pp 381–386 G. Giusfredi, S. Bartalini, S. Borri, P. Cancio, I. Galli, D. Mazzotti, and P. De Natale, “Saturated-Absorption Cavity Ring-Down Spectroscopy,” Phys. Rev. Lett. 104, 110801 (2010) Galli, I. et al, Optical Detection of Radiocarbon dioxide First Results and AMS Intercomparison. Radiocarbon, 55 (2), 213 0- 223. Galli, I. et al, "Spectroscopic detection of radiocarbon dioxide at parts-per-quadrillion sensitivity," Optica 3, 385-388 (2016) Fleisher. A. J. et al, Optical Measurement of Radiocarbon below Unity Fraction Modern by Linear Absorption Spectroscopy, J. Phys. Chem. Lett. 2017, 8, 4550−4556 Unfortunately, access to a mass spectrometer may be needed; or if geological databases for places of interest are available as a means to compare results from apparatuses built. Hopefully the latter prevails. Carbon-14 has a half life of 5730 years, meaning that 5730 years after an organism dies, half of its carbon-14 atoms have decayed to nitrogen atoms. Similarly, 11460 years after an organism dies, only one quarter of its original carbon-14 atoms are still around. Because of the short length of the carbon-14 half-life, carbon dating is only accurate for items that are thousands to tens of thousands of years old. Most rocks of interest are much older than this. Geologists must therefore use elements with longer half-lives. For instance, potassium-40 decaying to argon has a half-life of 1.26 billion years and beryllium-10 decaying to boron has a half-life of 1.52 million years. Geologists measure the abundance of these radioisotopes instead to date rocks. One must understand the respective decomposition with half life model. Will then pursue means to extend spectroscopy to date with such unstable isotopes. Will engineer module(s) to have actual interactive dating. Moderate Proton Magnetometer/NMR Schemes based on Earth’s Magnetic Field NOTE: this activity will NOT replace any other NMR activity available to physics constituents from EE. Options and alternatives can be great. NOTE: required will be explanation of the (heavy) physics and supporting mathematics to convince. The guides of interest --> 1. Sato-Akaba, H., Itozaki, H. Development of the Earth’s Field NMR Spectrometer for Liquid Screening. Appl Magn Reson 43, 579–589 (2012). 2. The following informing source may be decent, but it may employ Python here and there: PyPPM: A Proton Precession Magnetometer for All << https://hackaday.io/project/1376-pyppm-a-proton-precession-magnetometer-for-all >> << https://github.com/geekysuavo/pyppm >> Further technical intelligence --> 1. Liu, H. et al (2017). Noise Characterization for the FID Signal from Proton Precession Magnetometer. Journal of Instrumentation, 12(07), P07019. 2. Liu, H, et al. (2018). A Comprehensive Study on the Weak Magnetic Sensor Character of Different Geometries for Proton Precession Magnetometer. Journal of Instrumentation, 13(09), T09003-T09003. 3. Hyun Shim, J. H. et al (2015). Proton Spin-Echo Magnetometer: A Novel Approach for Magnetic Field Measurement in Residual Field Gradient. Metrologia, Volume 52, Number 4. Goals and observations that may be feasible --> NOTE: DON’T CARE FOR FLUORINE WITH ANYTHING -Observe both Proton and Fluorine (or distilled water or gasoline) Free Precession -Discover both the Curie Law and Spin-Lattice Relaxation -Measure Spin-Lattice Relaxation as a Function of: Paramagnetic Ion Concentration Viscosity Temperature -Observe and Measure Proton-(whatever) J-Coupling -Measure Absolute Value of gproton/g(whatever) -Precisely Measure Earth's Magnetic Field -Hear the Precessions on Built-In Audio System -Study Bucking Coils for Enhancing Signal-to-Noise -Examine Effects of Tuning on Signal-to-Noise -What is the possible physics of proton spin? If so, is this experiment an alternative means to prove elementary spin? Is such a type of spin with proton magnetometers unique to itself or is it influenced by nuclear activity? How does such proton spin modelling compare to electron spin modelling? For apparatuses to be built by students, do they provide a tangible means of investigating proton spin? If one was ignorant of the existence of protons, is there any approach based on such apparatuses to prove the existence of protons? NOTE: one may start off with distilled water. However hydrogen-rich fluids or hydrocarbons are alternatives. Interested in determining whether hydrogen-rich fluids or hydrocarbons will provide better performance, sensitivity, etc. Will fluids with heavier or more sophisticated bonds be more troublesome or better suited. A minor concern may be possibly being exposed to ignition temperatures and combustion temperatures. Will like to investigate by comparing different builds that employ unique types of hydrogen-rich fluids or hydrocarbons; all prior goals and observations to apply. Foundation in Particle Physics This activity serves towards learning with substance for retention in the interest of particle physics. A background with courses in Modern Physics and/or Methods of Mathematical Physics will be sufficient enough towards attaining the easily comprehensible aesthetics for recognition of advance civilisation; contact instructor. NOTE: the given experiments listed will be organised in a manner to yield the best delivery and sustainability. Environment of learning will be more like a camp bedazzlement to attract interest in particle physics. Built experiments will accompany strong physics emphasis and mathematical modelling. For any involved circuits and schemes they will be simulated before actual building (even the duoplasmatrons). It’s essential that the mechanisms and structuring of experiments can be competently and coherently related to physics and mathematical modelling in the realms of mechanics, particles physics and some relativity to relate with each other. Additionally, will incorporate some students with at least one year in C/C++. 1. Structure of Matter -Basic constituents of atoms -The Standard Model of Particle Physics: a simple rundown and history 2. Mass-to-charge ratio experiment with Helmholtz coils. Will treat the process with the physics and modelling for determining the mass of an electron. Then followed by activity with Helmholtz coils (in dark room) for verification. Will possibly identify any reasons for differences in experiment value compared to the theoretical value, such as unstable current, imperfect circular coils, construction, etc., etc. 3. Beta and Alpha Particles -PhysicsOpenLab. (2016). Some Alpha and Beta Spectra --> http://physicsopenlab.org/2016/11/05/some-alpha-spectra/ -PhysicsOpenLab. (2016). DIY Alpha Spectrometer --> http://physicsopenlab.org/2016/10/28/diy-alpha-spectrometry/ For any involved circuits they will be simulated before actual building. Then will apply tools to confirm performance of actual builds. Compare results from both with professional databases as well. 4. Proton mass determination I. Will pursue experimental electrolysis with emf source, water, strong salt to separate oxygen gas from hydrogen gas. For electrolysis two sets of generator plates must be constructed, where one will serve as anode and the other to be the cathode. Materials of consideration: Stainless steel scrap metal plates (three different sizes) 4” ABS clean out fittings 3/8” Poly Tubing Clear silicone 1 caulk ABS Cement 1/4” 90 degree Elbow 1/2” drill bit 18 Thread TAP Pipe Tape 3/8” Swivel Elbow 5/16 drill bit Bench vice Stainless steel jam nuts Acrylic glue Potassium hydroxide or sodium hydroxide or sodium bicarbonate 100 grit sandpaper Necessarily, the sandpaper serves to sand the two different sizes of generator plates (likely in a crisscross pattern), however the connector bands will not be sanded. The following is only an example of demand for neat construction and containment, however one is building an apparatus to separate oxygen gas from hydrogen gas, not oxyhydrogen (not sure what the bubbler does): HHO Generator-Water to Fuel Converter - YouTube Such apparatus to be amended towards separation of hydrogen gas from oxygen gas. Then, passaged through an accessible small duoplasmatron to have bare protons (in a beam or some sort). Consider a setting where proton production is to permeate through a magnetic field that influences a conic section path or perhaps a gyroradius. Pursue means to determine mass of proton. A potentiostat included may or may not be practical. Such can also be augmented to demonstrate wave-particle duality for protons. NOTE: goal is to compare results with mass spectrometer methodology. II. Based on developments can one make use of (3) to develop a proton spectrometer? Think it through and determine whether possible. Wanted physics. If possible, built and test. III. The following to serve as alternative comparing scheme to (II). Chen, H, Hazi, A, Van Maren, R, Chen, S, Fuchs, J, Gauthier, M, . . . United States. Department Of Energy. (2010). An Imaging Proton Spectrometer for Short-Pulse Laser Plasma Experiments. Journal Name: Review Scientific Instruments, Vol. 81, No. 10, October 19 Physics wanted, and both builds can possibly evaluate each other concerning spectra. Compare results from both with professional databases as well. As well, from article, “but also provide its angular characteristics”. What is the physics for such? Results to confirm as well. 5. Discovery of neutrons -Discussing theory and methods of validation -Consider the following means: << https://www.orau.org/PTP/collection/proportional%20counters/bf3info.htm > << http://physicsopenlab.org/2017/01/30/neutron-detector/ >> Vindicate or disprove such. If valid develop experiment and acquire the results or data. For any involved circuits they will be simulated before actual building. Then will apply tools to confirm performance of actual builds. Are there any results or data towards mass determination of neutrons? 6. Special relativity -Foundational arguments, theory of special relativity and transformations. -Will also review the relativistic kinematics and velocity composition law -Will emphasize also what conditions particles must have to be applicable to special relativity. -What lead to theory of special relativity without presence of gravitational influence? 7. Speed and momentum of light -Review the classical electrodynamics modelling for the momentum and energy of electromagnetic waves, and establish how they relate to special relativistic treatment? -Photon counting and statistics For all circuits they will be simulated before actual building. Then will apply tools to confirm performance of actual builds. For all such experiments it’s important that products can be related to the definition and model of quanta. What mechanism within each scheme is responsible for quanta? A major hurdle will be acquisition of multiple photomultiplier type H7828 Hamamatsu (or alternative) PhysicsOpenLab. (2016). Light as a Particle --> http://physicsopenlab.org/2016/03/03/light-as-particles/ PhysicsOpenLab. (2016). Photon Counting --> http://physicsopenlab.org/2016/06/20/photon-counting/ PhysicsOpenLab. (2016). Photon Counting and Statistics --> http://physicsopenlab.org/2019/01/07/photon-counting-statistics/ -Measuring the speed and momentum of light For all circuits they will be simulated before actual building. Then will apply tools to confirm performance of actual builds. Building multiple different schemes to compare will be productive. << www.phys.ksu.edu/personal/rprice/SpeedofLight.pdf >> PhysicsOpenLab. Speed of Electromagnetic Signal --> http://physicsopenlab.org/2016/10/28/measurement-of-an-electromagnetic-signal-speed/ PhysicsOpenLab. (2016). Light Speed Measure with a Time-of-Flight (TOF) Sensor --> http://physicsopenlab.org/2018/09/21/light-speed-measure-with-a-time-of-flight-tof-sensor/ 8. Cloud Chamber for exotic particles -Seeing Subatomic Particles With the Naked Eye – YouTube BBC Earth Lab -Cloud Chamber – YouTube Harvard Natural Sciences Lecture Demonstrations Experiment will be pursued. Chamber to be constructed likely to be bigger that such observed in demonstrations. At least 91% alcohol concentration (no exceptions). Will pursue the most efficiently engineered constructions towards acquiring optimal effect concerning the placement and containment of alcohol, dry ice (and its desired thermal influence). Dry ice should be efficiently placed in a manner that optimises its role upon chamber, and not upon the external environment. Will likely try to incorporate high speed photography, or filming where minute time scale behaviour can be synthesized; such to be oriented for all four viewing sides. Will pursue observation of splitting and other stand out geometric path observations or more general geometric displays (classifications). From observation, knowledge of experiment constitution, and physics to consider, will try to determine what particles are (were) present. Consideration on how to make a stronger chamber will also be considered. Similarities and differences between this environment and that of our planet’s atmosphere concerning ozone, atmospheric gases, etc. 9. Particle Identification In Camera Image Sensors Using Computer Vision Experiment design and construction will take high advantage of CCDS. The given article serves as a means for pursuit, however, there may be other methods with CCDS without usage of Deep Learning and neural networks; if different types can be developed then can possibly compare amongst each other for consistency with detections. Physics and mathematical modelling will be necessarily for a good foundation. Phase 1 development --> For all circuits they will be simulated before actual building. Then will apply tools to confirm performance of actual builds. PhysicsOpenLab. (2016). DIY Webcam Particle Detector http://physicsopenlab.org/2016/05/18/diy-webcam-particle-detector/ Phase 2 development --> Winter, M. et al (2019). Particle Identification In Camera Image Sensors Using Computer Vision. Astroparticle Physics. Volume 104, pages 42 - 53 Both builds and data can be compared. Designs and builds are generally scaled down versions of constructions found at CERN. 10. Cosmic Rays and Muons Primitive Muon Construction --> For all circuits they will be simulated before actual building. Then will apply tools to confirm performance of actual builds. https://www.cornellcollege.edu/physics-and-engineering/pdfs/phy-312/2014-2015/Special-Relativity-and-Muons.pdf PhysicsOpenLab. (2016). Cosmic Ray Monitoring --> http://physicsopenlab.org/2019/12/21/muon-rate-monitoring/ PhysicsOpenLab. (2016). DIY Water Cherenkov Detector --> http://physicsopenlab.org/2016/04/24/diy-cherenkov-detector/ PhysicsOpenLab. (2016). Cosmic Ray Muons and Muon Lifetime --> http://physicsopenlab.org/2016/01/10/cosmic-muons-decay/ PhysicsOpenLab. (2016). Muon Telescope --> http://physicsopenlab.org/2019/12/21/muon-telescope/ For any involved circuits they will be simulated before actual building. Then will apply tools to confirm performance of actual builds. 11. Solar panels as air Cherenkov detectors for high energy cosmic rays Involves constituents of engineering (with a solid semiconductor background) and physics students. It’s best that one reviews Cherenkov radiation. Will like to build and test modules in suggested environments that yield best results. There will also be high scrutiny. -Cecchini, S., D'Antone, Degli Esposti, Giacomelli, Guerra, Lax, . . . Spurio. (2000). Solar panels as air Cherenkov Detectors for Extremely High Energy Cosmic Rays. Nuclear Physics B (Proceedings Supplements), 85(1-3), 332-337. -Stella, Palatiello, Assis, Brogueira, Goncalves, Pimenta, & De Angelis. (2014). Solar panels as cosmic-ray detectors. ArXiv.org, Nov 20, 2014. 12. Constituents that make up electrons, protons and neutrons Reasons for contemplation and theory that lead to propositions; will include some quantitative models at an elementary level. 13. Review of Derivation of Schrodinger equation. States and Angular momentum 14. J. Electron Spin: Stern-Gerlach experiment [ hyperphysics.phy-astr.gsu.edu/hbase/spin.html ] 15. Determining Models for spin for various particles 13. The Standard Model of Particle Physics (reacquaintance) Overview at least at the level of a Modern Physics course. Corresponding famous or recent experiments. As well, done experiments throughout will also be vindicated by the standard model. 14. Antiparticles -Reasons for contemplation Dirac, P. A. M. (1928). The Quantum Theory of the Electron. Proceedings of the Royal Society A 117 --> http://wwwhome.lorentz.leidenuniv.nl/~boyarsky/media/Proc.R.Soc.Lond.-1928-Dirac-610-24.pdf -Propositions for particular antiparticles or antimatter with corresponding quantitative models. Definitive journal articles can assist, and known experimental validation for each: positron antiproton antineutron anti helium anti alpha particles antineutrino -Will pursue the following experimentation and findings: Sarri, G. et al (2015). Generation of Neutral and High-Density Electron-Positron Pair Plasmas in the Laboratory. Nature Communications, 6, 6747. Experiment will also be vindicated by the standard model. -A second part: if another construction can be developed where positrons can be separated, and with use of a small duoplasmatron, then mass determination of positron can be determine through a Helmholtz coils-like apparatus. -A third part: confirmation of wave-particle duality with use of a small duoplasmatron. -A fourth part: having electrons collide with the positrons to exhibit annihilation occurrences; consideration of means to detect gamma rays in a chamber. Detection (curves) over time would be great; gamma ray detector with a “clean chamber”. -Idea of antimatter spectra determination (this part concerns only intelligence gathering for now) A New Era of Precision for Antimatter Research: https://home.cern/news/news/physics/new-era-precision-antimatter-research https://www.youtube.com/watch?v=gsHUsLnqViw Ahmadi, M., Alves, B., Baker, C. et al. Observation of the 1S–2S transition in trapped antihydrogen. Nature 541, 506–510 (2017). In the future, methods will likely become more efficient and technology accessible. Stay tuned until then. 15. Extensions of the standard model Developed theories and predictions 16. Immersion into GEANT4 In the GEANT4 software will determine what computational ability software has; likely incorporating use of ROOT alongside. All computations and simulations to be developed must follow the identified appropriate applied physics and mathematical descriptions; solutions identified as well. Will simulate creation of particles and acquire the expected properties and quantities. Will pursue simulation of the behaviours of famous particles, with associated properties of respective particle. Will also treat the meaningfulness of data available from sources like CERN and other international sites. Will develop the logistics and implementation of data towards meaningful and productive use. 17. Further frontiers (will have experimentation components) Part A First, to have the “mainstream” or “popular culture” contemplation and discovery of the the neutrino. Then, one to “clean up” the following towards educating a undergraduate student --> http://lss.fnal.gov/archive/2013/conf/fermilab-conf-13-453-t.pdf Part B 3D Liquid Scintillator Detector --> Analysis of the following three texts: (i) Darne, C. D. et al. (2017). Performance Characterisation of a 3D Liquid Scintillation Detector for Discrete Spot Scanning Proton Beam Systems. Physics in Medicine and Biology, 62(14), 5652–5667. Features of (3) will be highly beneficial; consideration of electron beams and photon beams as well. (ii) Sun Heang So et al, Development of a Liquid Scintillator Using Water for a Next Generation Neutrino Experiment. Advances in High Energy Physics, Advances in High Energy Physics, Volume 2014, Article ID 327184, 7 pages (iii) Bignell, L. et al. (2015). Characterization and Modelling of a Water-based Liquid Scintillator. Journal of Instrumentation, volume 10, December 2015 Proceed with investigation into the possible development of a liquid scintillator detector for detection of subatomic particles; not necessarily focused solely on neutrinos and anti-neutrinos. If feasible, proceed with engineering module(s) and test. Will compare with conventional laboratory operations concerning parameters such as resources with construction difficulty, time consumed for construction, accuracy, and safe operational time scale for a single operational run; GEANT4 may provide simulation modules for conventional operational sites. 18. Secondary topics of consideration (time pending and if able): --Probing Earth’s interior with neutrinos Fiorentini, G., Lissia, M. and Mantovani, F., Geo-neutrinos and Earth’s Interior, Physics Reports 453 (2007) 117 – 172 --Dark Matter. Direct and Indirect Detection of Dark Matter Gorini, Gorini, V., Matarrese, Sabino, & Moschella, Ugo. (2010). Dark Matter and Dark energy (Astrophysics and space science library; 370). Dordrecht ; London: Springer; chapters 5 - 8 Feng, J. L. Dark Matter Candidates from Particle Physics and Methods of Detection. Annual Review of Astronomy and Astrophysics 2010 48:1, 495-545 Modelling and Computation: a. Einstein Theory with cosmological constant and reasoning for Dark matter and dark energy. b. Will review diverging galaxies, cosmological redshift and their relation to prior. c. Fitting a theoretical model of the composition of the universe to the combined set of cosmological observations, to come up with the composition percentages. d. Direct and Indirect Detection of Dark Matter (overview and possible logistics) Sumner, T. J., Experimental Searches for Dark Matter, Living Rev. Relativity, 5, (2002), 4. NOTE: one should not be ill advised that the above activity by itself will be enough to professionally venture into Particle Physics or High Energy Physics. However, this activity will serve as an exceptional tangible prep (with repetition serving as advancement) towards Particle Physics I & II. Particle Physics is accessible. Big Bang Nucleosynthesis Elements Simulation Code (COMING SOON) NOTE: prior to any and all code development respective documentation must be analysed. Eventually model contrasts and results contrasts must be established. PRIMAT (Mathematica): http://www2.iap.fr/users/pitrou/primat.htm PArthENoPE (FORTAN): https://parthenope.na.infn.it AlterBBN (C programming): https://alterbbn.hepforge.org Further reading: Kurki-Suonio, H. (2000). Alternative Solutions to Big Bang Nucleosynthesis. Symposium - International Astronomical Union, 198, 25-34. Note: for the above article pursue means of models contrast to priors then code development and implementation to contrast with priors (results). X Ray Spectroscopy Open to engineering students One often assumes that such type of spectroscopy is only made possible by industrialized producers. However, activity concerns pursuing a lab built scheme to operate and compare results with professional databases. A background with courses in Modern Physics and Methods of Mathematical Physics will be sufficient enough towards attaining the easily comprehensible aesthetics for recognition of advance civilisation; contact instructor. Built experiments will accompany strong physics emphasis and mathematical modelling. For any involved circuits and schemes they will be simulated before actual building. It’s essential that the mechanisms and structuring of experiments can be competently and coherently related to physics and mathematical modelling in the realms of mechanics, particles physics and some relativity to relate with each other. For all circuits they will be simulated before actual building. Then will apply tools to confirm performance of actual builds. PhysicsOpenLab.(2016). X Ray Spectroscopy with PIN Photodiode http://physicsopenlab.org/2017/06/22/x-ray-spectroscopy-with-pin-photodiode/ MUST: Physics will be harshly enforced. Circuit analysis will be heavily enforced. Apart from actual X ray activity, circuitry will be simulated before pursuing actual builds. Compared to standard scale X Ray spectrometers what will one have observation access to with chemical nature, oxidation states of metallic NPs, and environment of associated atoms in molecules? Namely, how powerful will the “domestic” build be for atomic/molecular natures and semiconductor interests? Three-Dimensional Structure of Galaxy Clusters The following journal articles to serve as foundation for development with data. Will chose various sample sets as well that are unique to the sample set applied in the journal articles. De Filippis, E. et al (2006). Measuring the Three-Dimensional Structure of Galaxy Clusters. I. Application of a sample of 25 Clusters. The Astrophysical Journal, 625: 108–120 Sereno, M. et al (2005). Measuring the Three-Dimensional Structure of Galaxy Clusters. II. Are Clusters of Galaxies Oblate or Prolate? The Astrophysical Journal, 645: 170–178 N-body Simulations Open to computer science constituents as collaboration. It’s recommended that students have completed General Physics I & II, with completion of Numerical Analysis, Calculus III and possibly Methods of Mathematical Physics. Will highly encourage those with at least 1-year experience in C/C++. Focus is mainly towards galaxy formation and evolution. Planetary nebulae may or may not be considered. 1. Will begin with basic classical mechanics of N-body systems. Main body with N “particles”. Value of N will be fairly high in value: -Will identify all active gravitational interactions in the system. Develop the centre of gravity model. Will pursue means of developing the centre of gravity for the particles disregarding the main body. Will pursue means of developing the centre of gravity for the particles including the main body. -Recall from elementary Newtonian gravitation where one finds the “equilibrium point” between two masses for a test particle. Is the centre of mass equivalent to the “equilibrium point”? Then consider the case for a general system of N particles with no concern about orbits. Pursue means to acquire the “equilibrium point”. Is there any possible distribution of point masses that yield the case where the centre of mass is equivalent to the “equilibrium point”? -If the particles together constitute a gravitational field that is considerable compared to the main body, what would such imply for an effective potential and possibly including consideration of relativistic effects? Will (naively) try to simulate orbits via finite difference central scheme and/or Runge Kutta methods (neglecting both tidal effects and relativistic effects). -Boatto, S., Dritschel, D. G., & Schaefer, R. G. (2016). N-body Dynamics on Closed Surfaces: the Axioms of Mechanics. Proceedings. Mathematical, Physical, and Engineering Sciences, 472(2192), 20160020. Develop a model via Lagrangian and/or Hamiltonian description for such. Now, one can’t just assume that all particles will miraculously reside perfectly in an orbit equatorial plane. How does one represent such a general circumstance via Lagrangian and/or Hamiltonian description? 2. Strong Modelling examples https://people.ast.cam.ac.uk/~vasily/Lectures/SDSG/sdsg_5_coll.pdf https://www.astro.umd.edu/~richard/ASTRO620/QM_chap2.pdf 3. Use of Aladin Sky Atlas (+ Simbad + VizieR) or GAIA software or DS9 with geometrical orientations, with frames having duration with motion evolution, towards prematurely identifying dimensions (major and minor axes) and spatial motion properties translational velocity, angular velocity, rotational inertia, angular momentum. Would like make such relevant with (2) and (3) concerning dynamic parameters fits. Parsecs and other AU measurements should be accounted for. Else, will have to directly observe data from astronomical databases (kills the fun). Anyways, try to compare with Doppler methods and what not. 4. Immersion into advanced simulation -Brute Force Method for N-body systems -For the following optimisation method will identify the appropriate circumstances for practical application, with detailed investigation of the mathematical and algorithmic structure before making use of any software, libraries, packages, etc. Will try to run some examples. 5. Barnes-Hut Simulation (a tree method) The following may or may not be useful towards development. Mainly, one’s goal is to have development that’s practical, fluid and versatile in the long run: Winkel, M. et al, A Massively Parallel, Multi-disciplinary Barnes–Hut Tree Code for Extreme-scale N-body Simulations, Computer Physics Communications 183 (2012) 880–889 Grama, A., Kumar, V. and Sameh, A., Scalable Parallel Formulations of the Barnes–Hut Method for N-body Simulations, Parallel Computing 24 (1998) 797–822 Other articles: Grimm, S. L. and Stadel, J. G., The GENGA Code: Gravitation Encounters in N-Body Simulations with GPU Acceleration, The Astrophysical Journal, 796:23 (16pp), 2014 November 20 Oshino, S., Funato, Y. and Makino, J. et al, Particle–Particle Particle–Tree: A Direct-Tree Hybrid Scheme for Collisional N-Body Simulations, Publ. Astron. Soc. Japan 63, 881–892, 2011 August 25 6. Star and Plant formation simulation Hubber, D. A. et al (2011). SEREN – a New SPH Code for Star and Planet Formation Simulations. Astronomy & Astrophysics, volume 529, A27, 28 pages Will make good effort to comprehend the physics, models and code. Will try to implement. NOTE: determine which theory is most compatible wth above journal artcle: Core Accretion versus Gravitational Instability. Regardless of findings, why is the core accretion model often preference over the gravitational instability model? 7. Galactic & Stellar Simulation -GADGET software Will pursue detailed review of the involved physics, mathematical modelling, algorithm/programming structure, software and GUIs, etc. to develop such. Will identify what hardware computational specifications are required to competently run such software effectively. Will try to run some examples. -NEMO (Stellar Dynamics Toolbox) Will make good effort to comprehend code. Will try to implement. -ZENO Will make good effort to comprehend code. Will try to implement. -Illustris Project Will have overview of such concerning the logistics involving the physics, mathematical modelling, algorithm/programming structure, software, etc. Will try to make practical use of data from this simulation project towards any possible comparative examination with data or findings with astronomy software, and professional astronomy/astrophysics sources. -Bolshoi Cosmological Simulation CosmoSim A. Klypin’s (NMSU) Bolshoi Cosmological Simulation Website MultiDark Database CLUES-Constrained Local UniversE Simulations https://wwwmpa.mpa-garching.mpg.de/millennium/ Modelling for simulation structure to encounter may or may not be more advance and complex than what was observed in any prior software or text. Will have overview of such concerning the logistics involving the physics, mathematical modelling, algorithm/programming structure, software, etc. Will try to make practical use of data from this simulation project towards any possible comparative examination with data or findings with astronomy software, and professional astronomy/astrophysics sources. The sources mentioned provide codes for development. 8. Stellar Population Synthesis Technique This subject is conventionally presented in a manner that subjugates students to an unimaginative and excluded role. Will investigate the models and methods applied towards acquiring a tangible and computationally accessible structure. Giudes: Pasetto, S., Chiosi, C., & Kawata, D. (2012). Theory of Stellar Population Synthesis with an Application to N-Body simulations. Atron. Astrophys. 545 , A14 (2012) Conroy, C., Gunn, J. E. & White, M. (2009).The Propagation of Uncertanties in Stellar Population Synthesis Modelling. I. The Relevance of Uncertain Aspects of Stellar Evolution and the IMF to the Derived Physical Properties of Galaxies, The Astrophysical Journal, 699: 486 – 506 Conroy, C., White, M. & Gunn, J. E. (2010). The Propagation of Uncertanties in Stellar Population Synthesis Modelling. II. The Challenge of Comparing Galaxy Evolution Models to Observations, The Astrophysical Journal, 708: 58 – 70 Considering the sensitive conditions from both Conroy et al articles, and then applying to Pasetto et al. If code and simulations can be developed, compare to simulations without the sensitive conditions and as well to the acquired from the other different mentioned N-body simulation programmes with the same instituted conditions. Daniel Price’s SPH Pages --> You will need to read the article first: Price, D. J. (2012). Smoothed Particle Hydrodynamics and Magnetohydrodynamics, Journal of Computational Physics, vol. 231, Issue 3, pp 759 – 794 http://users.monash.edu.au/~dprice/ndspmhd/price-spmhd.pdf Apart from downloading and installing the NDSPMHD code one will also need SPLASH (http://users.monash.edu.au/~dprice/splash/ ) Other journal artcles as possble substtutes for prior activity: Wetzstein, M. et al (2009). VINE – A Numerical Code for Simulating Astrophysical Systems Uang Particles. I. Descriptions of the Physics and the Numerical Methods.The Astrophysical Journal Supplement Series, 184: 298–325 Nelson, A. F., Wetzstein, M. and Naaab, T. (2009). VINE – A Numerical Code for Simulating Astrophysical Systems Uang Particles. II. Implementation and Performance Characteristics. The Astrophysical Journal Supplement Series, 184: 326–360 Merlin, E. et al (2010). EvoL: the new Padova Tree-SPH Parallel Code for Cosmological Simulations. I. Basic Code: Gravity and Hydrodynamics, Astronomy & Astrophysics 513, A36 Lia, C. and Carraro, G. (2000). A Parallel TreeSPH code for Galaxy Formation, Mon. Not. R. Astron. Soc. 314, 145 – 161 Miki, Y. and Umemura, M. (2017). GOTHIC: Gravitational Oct-Tree Code Accelerated by Hierarchical Time Step Controlling. New Astronomy 52, 65 – 81 Pelupessy, F. I. (2013). The Astrophysical Multipurpose Software Environment, Astronomy & Astrophysics. Volume 557, A84, 23 pages From science.gov: https://www.science.gov/topicpages/n/n-body+code+pkdgrav Modelling and Logistics for the first ever Picture of a Black Hole 1. Salutations Drake, N. (2019). First Ever Picture of A Black hole Unveiled. National Geographic < Likely there will be accompanying video>. 2. Event Horizon Collaboration The Event Horizon Telescope Collaboration. First M87 Event Horizon Telescope Results. Part I – VI. The Astrophysical Journal Letters (2019) There are at least 6 parts in the journal article sequence. Analysis and logistics development. Will try to replicate with resources with whatever resources available. Why M87? Why is such imaging or findings credible or not shunned? Are there any outstanding assumptions or ideal cases taken that diminishes the credibility of the findings? Throughout the process of the project are there any technological means (data or simulations) or models applied that can provide the characterising parameters (mass, spin and charge) of the M87 black hole? Presence of any lensing effect? Can one define, model or simulate a black hole outside the General Relativity environment? Developments in the project can be compared with the following journal articles concerning significant Kerr properties an dynamics: Bardeen, J. M., Press, W. H., and Teukolsky, S. A. (1972). Rotating Black holes: Locally Nonrotating Frames, Energy Extraction, and Scalar Radiation, The Astrophysical Journal, 178: 347-369 Sereno, M. and De Luca, F. (2008). Primary Caustics and Critical points behind a Kerr black Hole. Phys. Rev. D 78, 023008 Rauch, Kevin & Blandford, Roger. (1993). Optical Caustics in a Kerr Spacetime and the Origin X-ray Variability in Active Galactic Nuclei. The Astrophysical Journal. 421. 46-68. James, O. et al. (2015). Gravitational Lensing by a Spinning Black Hole in Astrophysics, and in the Move Interstellar. Quantum Grav. 32 065001 Cunningham, C. T and Bardeen, J. M. (1973). Optical Appearance of a Star Orbiting an Extreme Kerr Black Hole. The Astrophysical Journal, 183: 237 - 264 NOTE: may or may not need to extend to the Kerr-Newmann setting. Planet Formation PART I Core Accretion versus Gravitational Instability. Why is the core accretion model often preference over the gravitational instability model? Aim is to highlight the major features and modelling for both theories, say, not to be caught in a swamp of confusion. There are many A. Core accretion guides to model data (some journals have unique features to not disregard) --> 1.Pollack, J. B., Hubickyj, O., Bodenheimer, P., et al. 1996, Formation of the Giant Planets by Concurrent Accretion of Solids and Gas. Icarus, Volume. 124, Issue 1, pp 62 – 85 2.Hubickyj, O., Bodenheimer, P. and Lissauer, J. J. Core Accretion - Gas Capture Model for Gas Giant Planet Formation. American Geophysical Union, Fall Meeting 2005, abstract id.P42A-07 3.Ikoma, M., Nakazawa, K. and Emori, H. (2000). Formation of Giant Planets: Dependences on Core Accretion Rate and Grain Opacity. The Astrophysical Journal, 537: 1013 - 1025 4.Alibert, Y. et al. Models of Giant Planet Formation with Migration and Disc Evolution. A & A 434, 343–353 (2005) 5.Bitsch, B., Lambrechts, M. and Johansen, A. The Growth of Planets by Pebble Accretion in Evolving Protoplanetary Discs. A & A 582, A112 (2015) Lambrechts, M., Johansen, A. and Morbidelli, A. Separating Gas-Giant and Ice-Giant Planets by Halting Pebble Accretion. A & A 572, A35 (2014) B. Gravitational instability guides to model data (some journals have unique features to not disregard) --> 1.Boss, A. P. (1997). Giant Planet Formation by Gravitational Instability. Science, Vol. 276, No. 5320, p. 1836 - 1839 2.Boss, A. P. 2001. Gas Giant Protoplanet Formation: Disk Instability Models with Thermodynamics and Radiative Transfer. The Astrophysical Journal, Volume 563, Issue 1, pp. 367-373 3.Youdin, A. N. and Shu, F. H. 2002. Planetesimal Formation by Gravitational Instability. The Astrophysical Journal, Volume 580, Issue 1, pp. 494-505 4.Rafikov, R. R. (2005). Can Giant Planets Form by Direct Gravitational Instability? The Astrophysical Journal, Volume 621, Issue 1, pp. L69-L72. 5.Zhu, Z. et al (2012). Challenges in Forming Planets by Gravitational Instability: Disk Irradiation and Clump Migration, Accretion, and Tidal Destruction. The Astrophysical Journal, Vol. 746, Issue 1, article id. 110, 26 pp 6.Lee, A. T. et al . Formation of Planetesimals by Gravitational Instability. I. The Role of the Richardson Number in Triggering the Kelvin-Helmholtz Instability. The Astrophysical Journal, 718: 1367 – 1377, 2010 August 1. 7.Lee, A. T. et al. Formation of Planetesimals by Gravitational Instability. II. How Dusts Settles to its Marginally Stable State. The Astrophysical Journal, 725: 1938 – 1954 (2010) 8. Shu, F. H. et al. Sling Amplification and Eccentric Gravitational Instabilities in Gaseous Disks. The Astrophysical Journal, 358: 495 - 514, 1990 August 1 9.Boss, A. P. The Effect of Protoplanetary Disk Cooling Times on the Formation of Gas Giant Planets by Gravitational Instability. The Astrophysical Journal, 836:53 (15pp), 2017 February 10 10.Pickett, B. K. et al. (2003). The Thermal Regulation of Gravitational Instabilities in Protoplanetary Disks. The Astrophysical Journal, 590: 1060 – 1080 **Lab: PART I For the following journal article will try to analyse, develop the logistics along with code, then implement: Hubber, D. A. et al (2011). SEREN – a New SPH Code for Star and Planet Formation Simulations. Astronomy & Astrophysics, volume 529, A27, 28 pages Regardless of outcome does article better facilitate core accretion model or gravitational instability model? PART II Data collection for circumstellar disks around stars (being planet nurseries with orbiting “pebbles”). For each case identify how the resident star falls into the star classification, and development of a frequency distribution for such; determination of a good sample. Comparing the planet-to-star mass-ratio distribution measured by gravitational microlensing to core accretion theory predictions from population synthesis models. Assisting journal article: Suzuki, D. et al (2018). Microlensing Results Challenge the Core Accretion Runaway Growth Scenario for Gas Giants. The Astrophysical Journal Letters, 869: L34 (6pp). Determine a good sample size. PART III For the following journal article there are many features or results where astronomy data can be acquired for comparative assessment; choice of models to implement with such data will be crucial. As well, adequate sample sizes are important. D'Angelo, G.; Bodenheimer, P. (2013). "Three-Dimensional Radiation-Hydrodynamics Calculations of the Envelopes of Young Planets Embedded in Protoplanetary Disks". The Astrophysical Journal. 778 (1): 77 (29 pp.) Circumstellar Discs for Planet Formation. Simulation of Discs and Arms (incomplete) For the competing models, say, core accretion versus gravitational instability will identify the respective conditions and associated models. Make use of articles given in the Space Science II course for planet formation; may also require further readings. Substantially, gas giants akin to Jupiter’s size are recognised to be the first to form, whereas the leftovers lead to “solid” planetary formation. Will like simulations to emphasize all such. Simulations will be developed based on the two models. Do simulations support planetary chemistry among the system constituents? What configurations can be done to simulations to acquire feasible outcomes akin to our residency? May be applicable to other planetary systems. Particle Impact Ionization Cross Sections for Molecules PART A For particle impact ionization cross section for molecules will like to identify meaningful applicatons in radiation physics, particle physics and astrophysics. Kim, Y., Irikura, K. K. and Ali, M. A. (2000). Electron-Impact Total Ionization Cross Sections of Molecular Ions. Journal of Research of the National Institute of Standards and Technology, Volume 105, Number 2, 285 1.Means of coming to terms with such models rather than just bluntly accepting them. 2.Can algorithms be built towards general molecules? Will try...and compare with NIST’s databases Note: databases of interest from NIST: ESTAR, PSTAR, ASTAR Note: CERN and Fermilab may also have databases PART B Like 1 and 2 in part A, will be done for proton, helium and positron particles as well. May also be possible for muons and pions. PART C Applications to develop: Bautista, M. A., Lind, K. and Bergmann, M. (2017). Photoionization and electron impact excitation cross sections for Fe I. Astronomy & Astrophysics, Volume 606 A127, 6 pages Note: references in article will be crucial Note: above article may be focused on late-type stars with iron lines. Hence, we are further interested in order star classifications where othe lines may be more crucial. de Avillez, M. et al (2019). Relativistic Electron Impact Ionization Cross Sections of Carbon Ions and Application to an Optically Thin Plasma. Astronomy & Astrophysics, Volume 631 A42, 9 pages Note: a daunting tasks may be comparative cross examinaton of methods among all three journal articles, and determiination on why whatever preference with each artcle. Note: overall one may not be confined to stars alone. Namely, atmospheres, stellar bodies, stellar clouds and so forth may be applicable.

Plasma Propulsion Open to engineering and computer science constituents Activity in general will be virtual and analytic. 1. Identify/define plasma propulsion and the customary mechanisms to produce such. 2. From gas to plasma, the physics and mathematical modelling to be developed. May concern both cold plasma and hot plasma. 3. A specific gas may provide unique results and efficiency concerning energy requirements and output, unlike another gas. Conditions/thresholds should be accounted for concerning a specific gas for the plasma propulsion process. 4. Thoroughly identifying the characteristics of the most critical components in the plasma propulsion process is inevitable and a necessity. For each influential component the physics, mathematical modelling, control and circuitry associated must be highly tangible and fluid with device function. Such will include the specs/parameters/limits for efficient use. Such will lead to the necessary controller designs (and commands/instructions). 5. For plasma propulsion to be practical there must be developed programming/coding based on (4) towards implementing any simulation. 6. GEANT4 may provide some gargantuan modules that translate towards integration for simulations. Such to be compared to what’s achieved from (1) through (5)....IF ITS PRACTICAL. In the long haul we are interested in a small scale “gizmo”. 7. Plasma thruster/nozzle design (likely different to solid, hybrid and liquid propellant rocket motors). Essentially, one has to know the behaviour of accelerated plasma in flux or whatever to design thruster/nozzle in CAD or whatever. Modelling, computations and simulations based on all prior can reveal temperature gradients, fluxes (velocity, pressure), towards designing an efficient and sturdy extrusion (thruster). 8. Modelling, computations and simulation can reveal radiation output and temperatures for different parts of the system. Concerning radiation possibility is important to identify what materials are needed for particular components in critical areas. Thrust and specific impulse are of great interest. GEANT4 may or may not be helpful, however, we are interested in a small scale “gizmo”. 9. Power engineering likely influenced by (5) and (6) towards safe function at different demands must be well developed. Possibility of use of solar energy eventually to be integrated here and there for recharging systems. 10. For some mechanism components there exists scaled down versions used for interests outside of particle/nuclear physics and engineering. Hence, there will be a repetitive scaling down process; however, there must be considerable scaling down with technologies concerning (6) through (9). Hence, (1) through (4) must be amended to well govern the scaling down process. Operational parameters and safe use of scaled down virtual environments concerning systems remaining intact (against volatile kinetics, unwanted thermal behaviors and radiation) must be well developed; all related to control, programming, power engineering and shielding. Each time one becomes more efficient the following concerns will govern the economics --> Energy Analysis and Power Output Stability Thrust, Pressures and Specific Impulse Developing Safety, Reliability, Predictive Maintenance Design & Analysis Resources and Sustainability The goal is to have at least a competent system compatible with spacecraft design. 11. Phase 10 primary concerns self reliance and maturity, so pursuing such isn’t necessarily blunt overkill. If it becomes too abstract then, one can observe and analyse several advanced plasma propulsion designs developed and characterized. However, phases (1) through (9) are still essentially relevant. To name a few designs: TIHTUS, AF MPD ZT1 ZT2 advanced iMPD designs NOTE: in general, chambers and what not are constructed from industrial pipes, chambers, synthetic polymers and what not; machining and welding are generally what brings it all structurally together. A possible constructive aspect is designing the geometries to incorporate placements and containment for gases, integration for critical mechanisms devices, circuitry,plasma containment & transportation, sensing configurations, control and other electronics. Such development makes one much more tangible and sociable with the expected economics for materials and resources. Such pipings, chambers, etc. can be amended to account for all such constituents in a CAD; structural analysis wherever warranted. Apart from GEANT4, the following guides may prove quite useful: Jahn, Robert G. (1968). Physics of Electric Propulsion (1st ed.). McGraw Hill Book Company. Biersmith, J. A. and Pette, D. V. Theory and Development of Plasma Based Propulsion in VASIMR and Hall Effect Thrusters Chang-Diaz, F. R. Plasma Propulsion for Interplanetary Flight. Thin Solid Films 506 – 507 (2006) 449 – 453 Bering, E. A. et al. Electromagnetic ion cyclotron resonance heating in the VASIMR. Advances in Space Research 42 (2008) 192 – 205 Herdrich, G. et al. Advanced Plasma (Propulsion) Concepts at IRS. ADVANCES IN APPLIED PLASMA SCIENCE, Vol.8, 2011

Guide to the Expression of Uncertainty in Measurement (GUM) and transcendence Thoroughly identify and analyse GUM. Our goal is to develop logistics that’s universal with any experimentation or lab actvity in science. Developing competence is quite important. Re-orchestrating some basic physics and chemistry labs students may encounter uncertainty treatment. Will like to extend to such particular labs with the analysis in part A following. PART A Analysis from the following guides --> 1. Evaluation of measurement data — Guide to the expression of uncertainty in measurement — JCGM 100:2008 https://www.bipm.org/utils/common/documents/jcgm/JCGM_100_2008_E.pdf 2. Evaluation of measurement Data – Supplement to the “Guide to the Expression of Uncertainty in Measurement” – Propagation of Distributions using a Monte Carlo Method. JCGM.101: 2008 3. Barry N. Taylor and Chris E. Kuyatt (1994). guidelines for Evaluating and Expressing the Uncertainty of NIST Measurement Results. NIST Technical Note 1297. 4. https://isotc.iso.org/livelink/livelink/Open/8389141 5. Ferrero, A., & Salicone, S. (2018). A Comparison Between the Probabilistic and Possibilistic Approaches: The Importance of a Correct Metrological Information. IEEE Transactions on Instrumentation and Measurement, 67(3), 607-620. Other applications ---Krouwer, J. (2003). Critique of the Guide to the expression of Uncertainty in Measurement Method of Estimating and Reporting Uncertainty in Diagnostic Assays. Clinical Chemistry, 49(11), 1818-21. ---Velychko, O., & Gordiyenko, T. (2009). The use of Guide to the Expression of Uncertainty in Measurement for Uncertainty Management in National Greenhouse Gas Inventories. International Journal of Greenhouse Gas Control, 3(4), 514-517. NOTE TO SELF: DETECTING SUPERNOVAS WITH NEUTRINOS. RESOURCES AND THEIR SCHEMES, LOGISTICS, DATA SOURCES FOR ANALYSIS (LOGISTICS AND IMPLEMENTATION). Note: physics students have the ability to also participate in various engineering, planetary sciences and chemistry activities during the “summer” and “winter” sessions. List of “summer” and “winter” activities from engineering open to physics constituents-- Aerospace Engineering: A, H, L, M, N, S, T, U Mechanical Engineering: F, K, L, O, Q, R, T, W Electrical Engineering: D, F, G, H, I, L, U, Y, AA5, AA7, AA9, AA10, AA13, AA21 Computer Engineering: C All such engineering activities in the different fields of Engineering will be found in the engineering post. Oceanography & Meteorology: Weather balloon meteorological measurements-observation & recovery. Go to post. There are other activities open to Physics students under Chemistry (mainly spectroscopy types and molecular modelling, but others are still accessible). Check such section. Refer to post. There are other activities open to Physics students under Geology. UBER! UBER! Check such post. Some useful texts for Physics and Engineering oriented students to become well immersed in Mathematica: 1. Introduction to Mathematica for Physicists (Andrey Grozin) 2. A Physicist’s Guide to Mathematica (Patrick T. Tam) 3. Mathematical Methods Using Mathematica: For Students of Physics & Related Fields (Sadri Hassani) 4. Elasticity with Mathematica (Andrei Constantinescu & Alexander Korsunsky) 5. Mathematica for Theoretical Physics- Classical Mechanics & Nonlinear Dynamics (Gerd Baumann) 6. Mathematica for Theoretical Physics- Electrodynamics, Quantum Mechanics, General Relativity & Fractals (Gerd Baumann) 7. Dynamical Systems with Applications Using Mathematica (Stephen Lynch) 8. Foundations of Fluid Mechanics with Applications: Problems Solving Using Mathematica-Modelling and Simulations in Science, Engineering & Technology (Kiselev, Vorozhtsov, Fomin) SIDE NOTE: The mentioned software for Computational Chemistry, Molecular Modelling and specified labs in certain chemistry courses can possibly accommodate particular physics courses.

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Actuarial Science & Data Engineering

The Actuarial Science programme includes of Risk Theory and Life Contingencies courses. The Actuarial Science curriculum: --Foundation Courses Scientific Writing I & II; Calculus for Business & Economics I-III; Theory of Interest for Actuarial Science; Optimisation; Probability & Statistics B; Mathematical Statistics --Mandatory Courses Introduction to Macroeconomics (check ECON), Money & Banking (check ECON), Enterprise Data Analysis I & II (Check FIN), International Financial Statement Analysis I & II (check FIN), Corporate Finance (check FIN) --Actuarial Regulation Requirements Insurance Operations; Policies & Risk Management in Insurance; Insurance Accounting; General Insurance Financial Reporting & Valuation --Computational Necessities R Analysis; Risk Theory; Probability Models with Actuarial Applications --Option Tracks (MUST CHOOSE ONE) OPTION TRACK 1: Life Contingencies I Life Contingencies II Retirement Income Models Personal Finance OPTION TRACK 2: Investment & Portfolios in Corporate Finance (check FIN) Applied Decision Analysis (check OM/AOR) or Personal Finance Corporate Risk Management for Non-Life Insurance Rate Making for Non-Life Insurance --Remainder of academic career to be focused on fulfilling rest of general education appeasement, interest electives and activities. Theory of Interest for Actuarial Science Deterministic treatment of fixed interest rate instruments in the interest of actuarial science. You’re not in this course for mathematical wonder. Course focuses on students simply being competent with the features and behaviour of fixed instruments, because such instruments are serious business where time is quite limited. Typical Text: Kellison. S.G. Theory of Interest. McGraw-Hill/Irwin Computational Tools required: Accepted Calculator RStudio + R packages tvm, YieldCurve, jrvFinance, BondValuation, credule, AnnuityRIR R packages serve to compliment analytical development. In other words, the packages will not make sense to you, or you will not be constructive with them if you don’t comprehend well what you’re trying to do. Grading: Homework 20% 4 Quizzes 20% 2 Exams 60 % Course Topics --> Chapter 1. Measurement of Interest Chapter 3. Basic Annuities Chapter 4. More General Annuities Chapter 5. Yield Rates Chapter 7. Bonds and other Securities Chapter 9. Durations, Immunization, Matching Assets & Liabilities Prerequisite: Calculus II Ordinary Differential Equations: Linear Algebra is not a Matrix Algebra course. Minimal use of manual matrix algebra will be confined to 2 by 2 matrices and nothing further (use of software and calculators for higher matrices, say time is precious). Rigorous instructions to be followed by ODE numerical solvers: As well, pay attention to all links and directions in the given links above. Outline: 1. Introduction to Differential Equations (4 hours) Definitions and terminology Initial-value problems Differential equations as mathematical models 2. First-Order Differential Equations (11 hours) Solution curves without a solution; direction fields, autonomous first-order differential equations Separation of variables Linear equations Exact equations Solutions by substitutions Numerical methods; Euler's method, numerical solvers 3. Modelling with First-Order Differential Equations (6 hours) Linear models: exponential growth and decay, Newton's law of cooling, mixture problems Non-linear models and system of DE: logistic growth Tsoularis, A. (2021). On Some Important Ordinary Differential Equations of Dynamic Economics. In (Ed.), Recent Developments in the Solution of Nonlinear Differential Equations. IntechOpen. 4. Higher-Order Differential Equations (15 hours) Linear differential equations; initial-value and boundary-value problems, homogeneous equations, non-homogeneous equations Reduction of order Homogeneous linear equations with constant coefficients Undetermined coefficients; superposition approach, annihilator approach Variation of parameters Cauchy-Euler equation Solving systems on linear equations using elimination Non-linear differential equations 5. Modelling with Higher-Order Differential Equations (6 hours) Linear models with initial value problems: gravitational free fall with and without resistance; spring-mass systems with free undamped motion, free damped motion, and driven motion; series circuit analogue Linear models with boundary value problems Nonlinear models 6. Series Solutions of Linear Equations (6 hours) Review of power series Solutions about ordinary points Solutions about singular points 7. The Laplace Transform (10 hours) Prerequisite: Calculus II Insurance Operations The principal objective of this course is to develop an in-depth and thorough understanding of the unique operations of an insurance company including regulation, underwriting, claims, rate-making, risk control, the financial accounting process and global strategies (including the use of reinsurance) of an insurance organisation. At the end of the course the student should be able to --> Classify types of insurers and their goals and understand how to measure their performance. Explain fully the regulatory environment of insurance and describe the major regulatory activities associated with the insurance industry. Describe the unique characteristics of insurance marketing. Explain an insurer’s underwriting function in terms of its purpose, its methods and how to measure its effectiveness and how these differ for property vs. liability coverages. Describe the risk control and premium auditing functions of an insurer and explain the importance of these functions. Characterise property and liability claims processes of an insurer. Define insurer ratemaking, explain various actuarial ratemaking approaches and distinguish between them. Identify and explain various forms of reinsurance and describe their uses. Interpret insurer financial statements and describe the differences between Statutory Accounting Principles and Generally Accepted Accounting Principles. Explain and provide written support for various forms of insurer strategic management. Engage in informed, logical discussions on modern issues in insurance operations. Article Summaries --> You will be assigned 4 articles. You will be given at least 1 weeks’ notice to select, summarize and submit the summary. Part A Summaries of assigned articles related to specific topics in course. Part B Accompanied by specified questions that will vary among the articles. Exams --> Exams will be a mix of multiple choice questions, short essays, some quantitative tasks and accounting tasks (which will incorporate real insurance financial statements and financial/ accounting notes). To study for these exams, make certain you have accomplished the objectives for the chapters. Additionally, a review will be provided several days before the exam. EXAM 1: Chapters 1 and 2 EXAM 2: Chapters 3, 4 and 5 EXAM 3: Chapters 6 and 7 EXAM 4 (Final Exam): Insurance Accounting (materials provided) & Chapter 9 Typical Text --> Insurance Operations, CPCU 520 Tools --> Accepted Calculator Office 365 R + RStudio Course Topics --> 1) 3 classes. Overview of Insurance Operations: Assgmt. 1 2) 4 classes. Insurance Regulation (Text: Assgmt. 2) 3) 2 classes. Insurer Marketing and Distribution (Text: Assgmt. 3) 4) 5 - 6 classes. The Underwriting Function (Text: Assgmt. 4) & Risk Control and Premium Auditing (Text: Assgmt. 5) 5) 2 classes. The Claim Function (Text: Assgmt 6) 6) 2 classes. Actuarial Operations (Text: Assgmt. 7) 7) 4 classes. Insurance Accounting & Financial Management (Assigned) 8) 2 classes. Business Needs & Information Technology Alignment (Text: Assignmt 9) 9) 2 - 3 classes. Catch-up and Review 10) Accounting Problems all Due. Final Exam (Not cumulative) Grading: Exams (4) 60 240 points Accounting Assignments (8) 10 80 points Article Summaries (4) 20 80 points I will count your highest article summary grade twice. Prerequisite: Enterprise Data Analysis I & II, International Financial Statements Analysis I & II Policies & Risk Management in Insurance The terminologies and application of insurance instruments and risk management are often not well understood by customers. Is it in the best interest for customers to be well educated on insurance instruments and policies? A question for debate. Yet, for the insurer and its retainers, to be profitable and manageable, instruments and contracts must be well developed and understood to themselves and for legal incentives. Furthermore, the associate risks that are naturally in play with customers must well serve instruments and contract policies for insurers to be profitable. Contracts can be indifferent to a customer’s plight and resolve. Insurance is the primary mechanism by which risk is managed within society. This course covers the process by which insurance is sold and how individuals and organisations manage risk via insurance products. Students will explore the contractual aspects of insurance policies and attempt to understand how claims come into existence and are managed. Attention will also be given to social insurance and uninsurable risks. RUDIMENTARY NOTIONS FORMALITY : Premiums - Define and explain Insurance and uninsurable risks – Identify and classify Risk management methods – Define and match with the appropriate risk Private insurance market – Explain the role it plays and how it functions Insurance finance – Identify and calculate Regulation – Explain the role it plays Insurance law and contracts – Explain how each function Life insurance – Define and explain Health insurance - Define and explain Retirement plans - Define and explain Personal property insurance - Define and explain Commercial insurance - Define and explain Social insurance – Define and explain TOOLs & RESOURCES: Specified type of scientific calculator Office 365 (or capable substitute) Insurer Financial Statements Legal Literature Court Literature Bureau of Statistics pertaining to insurance (or whatever repository) FRAMEWORK FOR DEVELOPMENT (apply whatever is applicable to the field topic) --> Chosen course topics will have Component A and Component B. Students should know how to structure their notes well to profile and analyse. Each kind of insurance product or case is described fully and analysed within the current marketplace, with the following structure (always to be applied throughout course): COMPONENT A: Common Policy Concepts Insurable Interest Given a case, evaluate one or more entities’ insurable interests. Explain why insurance to value is important to property insurers, how insurers encourage insurance to value, and what insureds can do to address the problems associated with maintaining insurance to value. Property Valuation Methods Explain how property is valued under each of the following valuation methods in property insurance policies (there will also be active computations as well for the mentioned methods): • Actual cash value • Replacement cost • Agreed value • Functional valuation Valuation of Liability Claims Explain how the amount payable for a claim covered under a liability insurance policy is determined. Will also have active computations as well. Reasons for Property Insurance Deductibles Explain how deductibles in property insurance benefit the insured. Liability Deductibles and Self-Insured Retentions Explain when and why deductibles and self-insured retentions are appropriate for use in liability insurance. Other Sources of Recovery Describe the multiple sources of recovery that may be available to an insurance policyholder for a covered loss COMPONENT B: Insurance Policy Analysis. For type of insurance treated features and structures are to be elaborated upon --- Distinguishing Characteristics of Insurance Policies For respective type of insurance to describe all relevant characteristics of insurance policy out the following that apply, including common exceptions to these characteristics: • Indemnity • Utmost good faith • Fortuitous losses • Contract of adhesion • Exchange of unequal amounts • Conditional • Nontransferable Structure of Insurance Policies Describe these approaches to insurance policy structure and how they can affect policy analysis: • Self-contained and modular policies • Preprinted and manuscript policies • Standard and nonstandard forms • Endorsements and other related documents Types of Policy Provisions Describe the purpose(s) and characteristics of each of these types of policy provisions in a property casualty insurance policy: • Declarations • Definitions • Insuring agreements • Exclusions • Conditions • Miscellaneous provisions TAG ALONG TEXT: Principles of Risk Management and Insurance by George Rejda, Pearson Education, Inc. Note: such text will not dominate over the framework, rather it will serve as the social substance. Inevitably other literature will come into play. COURSE TOPICS: --Insurance Companies --Insurance Markets --Risk Management in Insurance Finance --Insurance Law --Homeowners Insurance --Life Insurance --Regulation in Life Insurance --Auto Insurance --Commercial Insurance --Annuities --Retirement plans --Social Insurance --Health & Group Insurance ISSUES IN THE FIELD: Topics out of the given following will be practically situated with course topics on multiple occasions. At times may require legal referencing. Overall the goals of reusable educational value and sustainability for the course. Risk Tolerance Demutualisation of Companies Reinsurance Subrogation Specialty Coverage Liability (includes spectrum, limits and conditions) Compliance Salvage Law (tort, liability, negligence and claims) Fraud No fault For any issue above the following mode to be adopted: 1. Relevance to course topics and/or framework. 2. Terms of contract relevant to issue of concern 3. Legal structure and application to case (if relevant) May have much influence if relevant 4. Positions and actions taken by respective side and justifications (practical and constructive case studies). Quizzes --> Quizzes can come in the form of multiple choice, completing statements with the appropriate patch, and elaboration on concepts or circumstances. Some computation in possible. Likely to be a combination of all prior. Quizzes can incorporate some elements of CASACT training/practice exams. Exams --> Exams will include the features of quizzes. ASSESSMENT --> 4-5 Quizzes 3 Exams Prerequisites: Enterprise Data Analysis I & II, International Financial Statements Analysis I & II Insurance Accounting Course introduces students to accounting principles and practices in the realm of insurance. Such development is crucial knowing that conventional financial statements courses don’t directly treat the intricacies of insurance firms. Yet, a solid background and skills in financial statements analysis will be essential to be competent. Excel/Office 365 expertise expected as well. Data for Activities --> Financial Statements (fetch from securities exchange commissions or wherever official) Insurer Annual Statement Balance sheet Income statement Cash flow statement Notes and disclosures Development Tools --> Office 365 Microsoft Dynamics Management Reporter Accepted Calculator RStudio + R packages tvm, YieldCurve, jrvFinance, BondValuation, credule, AnnuityRIR Literature --> CASACT literature geared to topics (MANDATORY) AICPA.(2019). Audit and Accounting Guide: Property and Liability Insurance Entities 2018. Wiley AICPA.(2018). Audit and Accounting Guide: Life & Health Insurance Entities 2018. Wiley Altman, E. and Vanderhoof, I. T. (2013). The Fair Value of Insurance Liabilities. Springer Assessment --> Homework (4) Spreadsheet Labs 3 Assignments (pairs of at least four) 4 Quizzes Midterm Final Exam Note: if any R packages are applied, such must succeed manual analytical development. Commentary expected in R scripts. Quizzes --> Will concern notions; accounting formulas and taxes with implementation relevant to insurance financial data; cross examinations. Spreadsheet Lab Modules --> Assets and Liabilities (characterisation, models, pricing and evaluation) Insurance Financial Statements (models, formula, structure, analysis, ratios development) Insurance financial statements construction (given assets and liabilities at with initial date to apply on future date; horizontal analysis, vertical analysis, ratios development) Midterm Exam --> Will reflect homework, labs, quizzes and assignments Exams --> Will be akin to midterm, but “all knowledge and skills on deck”. COURSE OUTLINE: 1. Types of Accounting Frameworks Statutory Accounting Principles Literature (NAIC or ambiance of interest) Leyman Idea: Kenton, W. (2021). Statutory Accounting Principles. Investopedia Will have overview of the actual principles IFRS vs Statutory Accounting Principals Insurer Annual Statement 2. Valuation of Insurance Company Assets (active immersion and implementation) P&L Assets and Life Insurance Assets Premium Accounting Blanchard, R. S. (2005). Premium Accounting. CASACT Insurance Cash Flows Hoyt, R. E. (1994). Modelling Insurance Cash Flows for Universal Life Policies. Journal of Actuarial Practice 2(2) Felix, JP. (2016). Cash Flow Projection Models. In: Laurent, JP., Norberg, R., Planchet, F. (eds) Modelling in Life Insurance – A Management Perspective. EAA Series. Springer, Cham. Note: find non-life insurance counterpart Teng, M. and Perkins, M. (1996). Estimating the Premium Asset on Retrospectively Rated Policies. Casualty Actuarial Society, 1996 Proceedings, Vol. LXXXIII, pages 611-647, excluding Section 5 Accessible from CASACT Data to vary among students Brehm, P. and Ruhm, D. (2007). Risk Transfer Testing of Reinsurance Contracts. Variance Journal, Volume 01, Issue 01, pages 9-17 Accessible from CASACT Data to vary among students Review of Equity Structure and valuation of shares Fixed Income types (discrete and continuous compounding Valuation Accrued Interest and Effective Interest Rate Hedonic pricing for properties or rents Fair value versus historical cost (assets and liabilities) Insurer Investment Policy 3. Liabilities of Insurance Companies What are applicable liabilities for insurance financial reporting? Claims Valuation Kagan J. (2022). Valuation Clause. Investopedia Note: identify what valuation methods apply to other assets, life insurance and health insurance; along with calculation. Comprehensive treatment Altman, E. and Vanderhoof, I. T. (2013). The Fair Value of Insurance Liabilities. Springer Luke N. Girard F.S.A., F.C.I.A. (2000) Market Value Of Insurance Liabilities: Reconciling the Actuarial Appraisal and Option Pricing Methods, North American Actuarial Journal, 4:1, 31-49 < accessible through the SOA > Fair Valuation of Insurance Liabilities: Principles and Methods, American Academy of Actuaries, Public Policy Monograph September 2002 Note: bond payments may also be applicable Loss Reserves and LAE Policyholder Surplus 4. Fundamentals of Insurer Financial Statements Describe the purpose and primary components of these key schedules of an insurer’s financial statements: Insurer Annual Statement Balance sheet Income statement Cash flow statement Notes and disclosures 5. Insurance Accounting Operations Problems Insurance Accounting Exercises (IAEs) 7 Sessions of IAEs 6. Insurance Accounting Performance Measures (5-7 sessions) Use of Annual Statement Analyse Performance of a P&L Insurer Assigned (IRIS Ratios) NAIC-Insurance Regulatory Information System (IRIS) Ratios Manual Use of other Financial Statements (Balance sheet, Income Statement and Cash Flow Statement) for analysis 7. Research Assignment (4-6 sessions allocated) Prerequisites: Enterprise Data Analysis I & II, International Financial Statements Analysis I & II

General Insurance Financial Reporting & Valuation Instruments and revenue of insurance firms are quite unique to conventional corporate firms, banks, credit unions, thrifts, etc. Thus, in function are various technical manuals and statements that guide the insurance process of financial reporting and financial analysis of insurers. Course serves for students become knowledgeable and highly immersed concerning future career paths in the insurance industry. Student Learning Objectives--> -Students will understand the elements of financial reporting for general insurance companies. -Students will understand the analysis of a general insurer’s financial health through prescribed formulas, ratios and other solvency regulation methods. -Students will be able to apply the standards of practice regarding the responsibilities of the actuary as defined by regulators and the ambiance association of actuaries. Data for Activities --> Financial Statements (fetch from securities exchange commissions or wherever official) Insurer Annual Statement Balance sheet Income statement Cash flow statement Notes and disclosure NOTE: as well, literature from prior course may serve well for review Development Tools --> Office 365 Microsoft Dynamics Management Reporter Accepted Calculator RStudio + R packages tvm, YieldCurve, jrvFinance, BondValuation, credule, AnnuityRIR Note: if any R packages are applied, such must succeed manual analytical development. Commentary expected in R scripts. Resources --> https://www.soa.org/education/exam-req/syllabus-study-materias/edu-multiple-choice-exam Case Study Example --> Society of Actuaries Exam – General Insurance, Financial and Regulatory Environment – U.S. Case Study Spring 2018: https://www.soa.org/globalassets/assets/Files/Edu/2018/spring/edu-2018-gifreu-case-study.pdf Note: will like to develop other cases studies catering to subjects in course. Possibly, one can use other Society of Actuaries or CASACT cases studies related to topics as guides to develop unique case studies with acquired data. Prerequisites Refreshers --> Some tasks from prerequisite course (Insurance Accounting) to be given as assigned advance repetition. Involves both data activities and refurbished exam questions. Course Assessment --> Stated activities in the modules 3 Quizzes (will cover both prerequisite activities and current course topics) Prerequisite activities (Insurance Accounting) Current course topics concerns building upon prerequisite topics and new topics introduced in course 3 Exams (will cover both prerequisite activities and current course topics) Team Case Study Development Term Project Team Term Project Student groups will be given a (large) portfolio of assets, liabilities and transactions at one given date and time to develop the three major financial statements for a specified date and time. Then will proceed with implementing financial analysis. Students will apply all their knowledge and skills from course and prerequisites. COURSE MODULES --> MODULE 1. INSURANCE ACCOUNTING REINFORCEMENT a) Review of knowledge and skills from prerequisites meaningful to course progression MODULE 2. FURTHER ACCOUNTING TOPICS a) Understand and apply the elements of discounting for general insurance loss reserves b) Understand and apply the concepts of reinsurance accounting c) Demonstrate knowledge of taxation for general insurers MODULE 3. FINANCIAL HEALTH MEASUREMENT a) Recital of IRIS ratios determination b) Understand and apply the elements of the NAIC RBC formulas Life, Fraternal, P&C, Health MCO Possible contrast with various sovereignty as well c) Solvency II Standard Formula Concept d) Overview of the Canadian Minimum Capital Test https://www.casact.org/sites/default/files/2021-03/6C_OSFI_MCT.pdf Each chapter identifies a particular of risk and elements of concern. Will also be identifying the associated tests, models and formulas, what they are appropriate for, and comprehension of the elements of each test or model or formula. Balance sheets and other financial statements to be applicable and practical in use for many. e) Overview of Life Insurance Capital Adequacy Test https://www.osfi-bsif.gc.ca/Eng/fi-if/rg-ro/gdn-ort/gl-ld/Pages/LICAT19_index.aspx Each chapter identifies a particular of risk and elements of concern. Will also be identifying the associated tests, models and formulas, what they are appropriate for, and comprehension of the elements of each test or model or formula. Balance sheets and other financial statements to be applicable and practical in use for many. f) Demonstrate knowledge of the Solvency II Standard Formula and NAIC Risk-Based Capital (RBC). How to implement with insurance companies. https://www.casact.org/sites/default/files/database/forum_12fforumpt2_rbc-dcwprpt3.pdf Will also be identifying the associated models and formulas, what they are appropriate for, and comprehension of the elements of each test or model or formula. Balance sheets and other financial statements to be applicable and practical in use for many. g) Demonstrate knowledge of ORSA and its implementations https://content.naic.org/sites/default/files/legacy/documents/prod_serv_fin_recievership_ORSA-2014.pdf From the above ORSA Guidance Manual the tangible material resides in: A. Section 3 – Group Assessment of Risk Capital and Prospective Solvency Assessment B. Appendix – Glossary The examples provided in section 3 are not everything out there. Some stochastic knowledge and skills are needed to implement a few of them, say, stochastic knowledge and skills for Quantification Method Risk Capital Metric Defined Security Standard Aggregation and Diversification h) Compare different solvency standards i) Discuss the function of credit rating agencies and their influence on general insurers j) Performance Measures RAROC Goldfarb, R. (2010). Risk-Adjusted Performance Measurement for P&C Insurers. CASACT. Note: much interest in pursuing case studies of insurers if data accessibility is possible. Other types of insurances may have drastic components. Comparative Development (with real financial data) Kraus, C. (2013). EVA/RAROC vs. MCEV Earnings: A Unification Approach. The Geneva Papers, 38, pp 113–136 Will pursue cases studies based on data. Additional literature: Ward, L. S. and Lee, D. H. (2002). Practical Application of the Risk-Adjusted Return on Capital Framework. CASACT: MODULE 4. TESTS FOR INTEGRITY AND FRAUD The following will be analysed then implemented on insurers’ financial data: Horizontal Analysis and Vertical Analysis Beneish model, Dechow F model, Modified Jones model, Altman Z model, Merton’s model for default (via equity); extend prior to KMV model. MODULE 5. ANALYSIS AND VALUATION OF INSURANCE COMPANIES Concerning 3 to 6 assigned insurance companies will be acquiring market data and financial statements to apply valuation methods Assisting literature: P&C Insurance Blackburn, W. E. et al. The Application of Fundamental Valuation Principles to Property/Casualty Insurance Companies. CASACT NOTE: exhibits and sheets in prior may prove invaluable Goldfarb, R. (2010). P&C Insurance Company Valuation. CASACT Danhel, J. and Sosik, P. Acquisition Valuation of P&C Insurance Companies. CASACT Non-Life Insurance Bride, M., & Lomax, M. W. (1994). Valuation and Corporate Management in a Non-Life Insurance Company. Journal of the Institute of Actuaries (1886-1994), 121(2), 363–440. Life Insurance Gold, M. L. (1962). Valuing a Life Insurance Company. Transactions of Society of Actuaries vol.14 PT. 1 NO.38 AB Randolph, K. and Sittler, L. (2018). Unique Aspects of Valuing Life Insurance Companies. Stout Prerequisites: Corporate Finance, Insurance Accounting, Probability & Statistics Optimisation: Course focuses on the development and sustainability of linear programming, integer programming, and nonlinear programming; MILP may be unavoidable at times. Course will require 27 lecture sessions. Note: Course is not a Linear Algebra course. Course focuses on applications development, extensive modelling, and computational implementation with R. You will not see bases nor a “Peter Pan World” of Eigenvectors nor Eigenvalues and Adjoint[Adjoint[ Adjoint]]. Note: This is not a Matrix Algebra course. Minimal use of manual matrix algebra when needed will be confined to 2 by 2 matrices and nothing further (use of software and calculators for higher matrices, say, time is precious). I don’t care about you pretending that you understand optimisation with shows of "Pac Man” prowess or “pig pen trap game skills”. If you can’t develop, it doesn’t matter. I will not encourage bamboozles with matrix perversions. If I ask you to model and optimise I don’t care what upper triangular, lower triangular and Adjoint[Adjoint[Adjoint] looks like. Homework --> will be mostly based on interpretation and modelling, accompanied by solutions with R. Will be focused on modelling from interpretation of application problems, recognition of what type of optimisation is in play, recognising use of specific algorithms (and detail the respective methodology), sensitivity and stability. Will develop manually on paper to be accompanied by development in R. I expect your literature/commentaries in the R environment along with the computational development. Exams --> Will be based on style of homework provided. Computational Tools --> R packages + RStudio cplexAPI, CVXR, gradDescent, lpSolve, lpSolveAPI, NlcOptim, nloptr, Rglpk, Rsolnp Homework 15%, 4 Exams 40%, Final 30%, Project 15% It’s imperative that students take interest in acquiring skills with computational tool; contrary pursuits will result in quite a dismal future. Project --> Choices for project: Supply Chain Fundamental Theorem(s) of Asset Pricing Portfolio Selection Arbitrage Detection Data Envelopment Analysis Project will make use of real data and real assets. Topics must make use of real financial/economic/agricultural/public data and a GIS (if relevant) with their project. Must pick 2 out of the 5 topic above. If topic can be done with multiple types of programming (out of LP, ILP, MILP and NP) then such must be done; topics involving multiple types of programming/optimisation will receive extra credit IF AND ONLY IF done competently. MANDATORY APPLICATIONS OF FOCUS THROUGHOUT COURSE: LINEAR PROGRAMMING Resource Allocation Firm manufacturing/production with assets/resources Labour Scheduling Inventory Optimisation Supply Chain Transportation Planning Asset/Liability Cash Flow Matching Short Term Financing, Dedication Fundamental Theorem(s) of Asset Pricing Portfolio Selection Arbitrage Detection Data Envelopment Analysis INTEGER PROGRAMMING Firm manufacturing/production with assets/resources Labour Scheduling Inventory Optimisation Transportation Planning Territorial Planning Asset/Liability Cash Flow Matching Telecommunications Network or Cellular Networks NONLINEAR PROGRAMMING Portfolio Selection Water Resources Planning Constrained Regression Bracken, J., & McCormick, G.P. (1968). Selected Applications of Nonlinear Programming. Wiley & Sons. NOTE: each type of programming/optimisation module will focus only on the given applications to develop sustainability. Syllabus-- To buy into the importance of this course, tangible and fluid applications are essential towards meaningfulness and relevance. 1. Real-life situations as optimisation problems overview (1 lecture) 2. Linear programming (11 lectures) Linear Programming Models Graphical solution Algorithmic solution (Simplex) Sensitivity Analysis and understanding what the software tells you Stability Analysis and understanding what the software tells you Network Models and Algorithms web.mit.edu/15.053/www/AMP-Chapter-08.pdf 3. Integer programming (7 lectures) Modelling with integer variables Cutting Plane methods Branch-and-bound methods Heuristic Methods Sensitivity and Stability Analysis 4. Nonlinear programming (8 lectures) Nonlinear Models Method of Lagrange Multipliers KKT conditions Gradient Descent (avoid the filthy swamp) Trust-Region Methods Sequential Quadratic Programming Constrained optimization vs Unconstrained optimization Algorithms Sensitivity Analysis for NLP with software Stability Analysis for NLP with software Prerequisites: Multivariate Calculus. Department and instructor approval.

Probability & Statistics B Note: for Actuarial, Data Engineering, Economics, Finance, Revenue Management, and Operations Management majors the RStudio environment will serve appropriately. MEMO: based on the listed majors prior, course serves to be sustainable and future useful; not a sabotage excrement show with all sorts of weird support regions and weird dependence relations among random variables. Course doesn’t serve for pestilence to conjure mess just for the hell of it. Course Literature IN UNISON: Wagaman, A. S. and Dobrow, R. P. (2021). Probability with Applications and R. Wiley. Horgan, J. M. (2020). Probability with R. Wiley & Sons. Cohen, Y. and Cohen, J. Y. (2008). Statistics and Data with R. Wiley and Sons. Note: students will be guided to develop multivariate extensions when called upon. Reading will be fundamental concerning use of R. Outside sources are also feasible/likely. Assessment: Homework (analytical and with R) 3-4 Lecture quizzes Lectures + R Immersion (with open notes/book) Labs 3 Exams COURSE OUTLINE --> 1. Descriptive Statistics -- Measures of Central Tendency -- Measures of Dispersion 2. Elementary Probability -- Axiomatic Approach -- Combinatorics Note: Selections, arrangements, combinations and such sort are not lifesaving tools, thus such problems will be quite limited. -- Probability Theorems Note: Drawing balls, picking cards, gender matching and such sort are not lifesaving tools, thus such applications problems to be limited to 2 sessions. 3. Discrete Probability Distributions -- Discrete random variables. Cumulative distribution and its properties for discrete random variables -- Expected value, variance and standard deviation -- Poisson Distribution -- Binomial Distribution -- Negative Binomial -- Poisson as approximation to binomial (or vice versa) 4. Continuous Probability Distributions -- Continuous random variables. Cumulative distribution its properties for continuous random variables -- Expected value, variance and standard deviation -- Uniform Distribution -- Exponential Distribution and relation to Poisson distribution -- Normal Distribution; binomial distribution converging to normal distribution for large trials -- Normal distribution and Law of large numbers -- Central Limit Theorem -- Gamma Distribution and related distributions 5. Multivariate Probability Distributions (independent and dependent RVs) -- Multivariate Distributions -- Marginal and Conditional distributions -- Sums of Independent Random Variables -- Expected values for a function of random variables -- Bivariate Normal Distribution -- Conditional Distributions and Expectations 6. Covariance and Correlation 7. Moment Generating Functions (optional) Meaningful use. If it’s not practical with realistic applications, don’t bother. Limit MGF determination exercises, table will be provided. COMPUTATIONAL LABS --> Most (not all) built-in or package functions along with Tidymodels encountered or learnt are mainly for establishing consistency. Instructors are only responsible for reviewing analytical structure and computational logistics development, whereas students will be responsible for actual code writing and implementation, complemented by chosen R packages. Instructor will assign problems while students will be responsible for modelling, computation and simulations. Students will have available guides and on-line sources to complete their assignments. For each module there will also be questions sets where students will be required to provide analytic writing that complements data analysis or plotting or computational or simulation activities. Note: students should apply commentary with RMarkdown usage. NOTE: labs will have quizzes with R at your disposal. 1. Elementary statistics Computation of probabilities, expectation, variance and standard deviation (univariate) from data sets. Students will be responsible for pursuing different types of real data sets to generating summary statistics. 2. Random variables and distributions Probability mass and density plotting for intervals and inequalities; includes cumulative distribution determination (discrete and continuous). Concerns Geometric, uniform, binomial, Poisson, normal, Gamma, Gamma related. Review of determination of respective expectation, variance and standard deviation (discrete and continuous). Interpretation and applications of d, p, q, r probability functions for each encountered pmf or pdf. General Plots Histograms and mass/density Inequality or intervals Simulating random variables from experiments (analytical and with R). Simulate practical experiments (uniform, exponential, Poisson, binomial, normal). Learning to generate simulation (sample) data from from different distributions. Students will be responsible for pursuing different types of real data sets, providing histogram/frequency representation with comparative view of densities believed to model data. 3. P-P plots, and Q-Q plots Students will be responsible for pursuing different types of real data sets to apply. 4. Simulation insight into the Law of Large numbers and Central Limit Theorem versus the Law of Large numbers. Development of real experiments or circumstances. 5. Multivariate Distributions (independent and dependent RVs) Review of multivariate distributions and properties (discrete and continuous). Plotting PDFs and CDFs. Simulating pairs of jointly distributed random variables (monte carlo) Simulating joint density and accompanying histogram (monte carlo) Simulating probability conditions (monte carlo versus direct functions) 6. Conditional Probabilities & Conditional Expectations 7. Estimating probabilities and expectation with dependent random variables (like meeting a date to a movie problem). Simulation or computation insight into the Birthday Problem example (investigates the least number of people required if the probability exceeds one-half that two or more of them have the same birthday); other problems similar to such. 8. Extend (6) to dependent variants. 9. Learning to generate simulation (sample) data from bivariate distributions, having data geometrical display alongside marginal distributions and joiint distributions. Will also have real data counterpart. Commentary expected throughout. 10. Monte Carlo methods in practice -Estimate and simulate Buffon’s experiment. Estimating various quantities. Univariate and multivariate integrals by hit-or-miss Monte Carlo; where students must develop each monte carlo and estimate. Commentary expected throughout. -Univariate and multivariate integral evaluation by expectation via uniform random variables; where students must develop each monte carlo and estimate. Commentary expected throughout; to be compared to Hit-or-Miss approach. -First Year Net Profit Monte Carlo Identification of formula Uncertain Variables (Unit Cost, Sales, Price) Uncertain Functions (Net Profit) & Statistics The Flawed Average Model -Product demand forecast -Cobbs-Douglas production function and CES production function -Yee, W. (2019). Monte Carlo Simulations: The Intersection of Probabilistic and Deterministic. Towards Data Science. Critical question---concerning the prior article blog, what will be the new structure if one considers market segmentation in seating class where each class has a seat cap? -Value at Risk Comprehending the measure and structure Monte Carlo simulation Expected will be coding and simulation with customary functions versus package usage. -CVar and Expected Shortfall (ES) monte carlo Comprehending the measures and structures. How are CVar and ES approaches unique to simple VaR? Expected will be coding and simulation with customary functions versus package usage. 10. Covariance and correlation A. Will decide upon densities to generate random sample sets, where each set has 20 – 25 elements. Based on earlier analytical modelling with covariance and correlation for discrete sets will programme covariance and correlation in R. correlation matrix for a high number of variables. B. Use of financial data, economic data, etc., etc. C. Generating scatter plots with data for visual information D. Correlation as the geometric mean of regressions E. Generating heat maps and interpretation F. Applying the ggpairs() function Prerequisite: Multivariate Calculus (no exception)

Life Contingencies I This course covers actuarial models including life contingencies, survival models, life insurances, annuities and premiums. This class covers parts of CAS Exam 3L and SOA Exam MLC. Calculators --> Accepted Calculator R environment --> Additionally, in the real-world there’s modelling, computation, simulation and data, hence there must be an environment that encourages and reinforces such. Tables are also subject to updates (with ambiance to consider). Data may not be accessible or not robust, and thus will often depend on modelling theory and simulation. Most activity will be in labs extensively, and moderately in lecture instruction. Progress and competency in your homework will reflect greatly in labs. R packages of interest --> actuar, bootruin, ChainLadder, DCL, FactoMineR, gnm, LDPD, lifecontingencies, LifeInsuranceContracts, queuecomputer, queueing, raw, reinsureR, survival Vignettes and reference manuals are crucial towards good development. Depending on type of development students may use R packages outside of the above list. Particularly for the lifecontingencies and actuar packages there are strong vignettes; other packages may be as strong as well. Course texts --> Dickson, C.M.D. et al (2013). Actuarial Mathematics for Life Contingent Risks, Cambridge University Press Chapters 1-6 Assisting texts for R --> Chapter: Life Insurance. In: Carpentier, A. (2016). Using R: Computational Actuarial Science with R. Chapman & Hall/CRC Milevsky, M. (2020). Retirement Income Recipes in R: From Ruin Probabilities to Intelligent Drawdowns. Springer. Course Grade Constitution --> Homework 20% Simulation and Computation Labs 20% Exam 1 20% Exam 2 20% Final Exam 20% Course Outline --> PROBABILITY REVIEW CHAPTER 1– INTRODUCTION TO LIFE INSURANCE (1 lecture) Brief introduction on the terminology and major types of life insurance, annuity and pension CHAPTER 2 – SURVIVAL MODELS (4 lectures) Future lifetime random variable Survival function and (deferred) probability of death Force of mortality and some common laws Complete and curate future lifetime CHAPTER 3 – LIFE TABLES AND SELECTION (4 lectures) Life table construction and national life tables Fractional age assumptions Select and ultimate survival models Mortality trends CHAPTER 4 – INSURANCE BENEFITS (6 lectures) Valuation and analysis of the benefits in various traditional life insurance policies, including whole life insurance, term life insurance, pure endowment, endowment insurance, deferred contracts and variable insurance Recursion formulae and approximations for insurance benefits with different payment type CHAPTER 5 – ANNUITIES (7 lectures) Valuation and analysis of the life contingent annuities, including whole life annuity, term life annuity, deferred contracts, guaranteed annuity and increasing annuity Recursion formulae and approximations for annuities with different payment type CHAPTER 6 – PREMIUM CALCULATION (5 lectures) Future loss random variables Equivalence principle of net and gross premium calculation for insurance policies and annuities The portfolio percentile premium principle Profit and extra risk analysis Prerequisite: Probability & Statistics B

Life Contingencies II This course is a continuation of the study of life contingencies. Topics include insurance and annuity reserves, characterization of discrete and continuous multiple decrement models in insurance and employee benefits, and multiple life models. This class further develops the students’ knowledge of the theoretical basics of actuarial models in life insurance and the application of these models. By the end of the course, the student will be able to: 1. Calculate gross premiums that should be charged for various life insurance policies accounting for expenses of the insurance company. 2. Calculate the policy values (benefit reserves) for different types of insurance contracts and explain the appearing quantities. 3. Calculate the expected value of, and variation in, payments contingent on multiple lives or payments that are subject to multiple contingencies. There will be tentatively 5 quizzes, two mid-term examination, and one final examination. The final exam covers the entire course with emphasis on the more recent material. The lowest quiz score (missed quizzes receive a ’0’ score) will be dropped/disregarded. Please contact me if you miss more than one quiz; under extraordinary circumstances, special arrangements can be made. Weekly homework will be assigned and collected irregularly. You can act on the assumption that homework will be collected approximately 2-3 times over the entire semester. Late work will not be accepted. Calculators --> Accepted Calculator R environment --> Additionally, in the real-world there’s modelling, computation, simulation and data, hence there must be an environment that encourages and reinforces such. Tables are also subject to updates (with ambiance to consider). Data may not be accessible or not robust, and thus will often depend on modelling theory and simulation. Most activity will be in labs extensively, and moderately in lecture instruction. Progress and competency in your homework will reflect greatly in labs. R packages of interest --> actuar, bootruin, ChainLadder, DCL, FactoMineR, gnm, LDPD, lifecontingencies, LifeInsuranceContracts, queuecomputer, queueing, raw, reinsureR, survival Vignettes and reference manuals are crucial towards good development. Depending on type of development students may use R packages outside of the above list. Particularly for the lifecontingencies and the actuar packages there are strong vignettes; other packages may be as strong as well. Course texts--> Dickson, C.M.D. et al (2013). Actuarial Mathematics for Life Contingent Risks. Cambridge University Press Mainly Chapters 7-10 R immersion literature --> Dutang, C., Goulet, V. and Pigeon, M. (2008). actuar: An R Package for Actuarial Science. Journal of Statistical Software Volume 25 Issue 7, 37 pages Chapter: Life Insurance. In: Carpentier, A. (2016). Using R Computational Actuarial Science with R. Chapman & Hall/CRC Milevsky, M. (2020). Retirement Income Recipes in R: From Ruin Probabilities to Intelligent Drawdowns. Springer. Jan Beyersmann, Arthur Allignol and Martin Schumacher (2012). Competing Risks and Multistate Models with R. Springer, New York, NY Therneau, T., Crowson, C. and Atkinson, E. (2021). Multi-State Models and Competing Risks. CRAN R Goulet, V. actuar: An R Package for Actuarial Science: https://www.actuaries.org/ASTIN/Colloquia/Orlando/Papers/Goulet.pdf Shailaja Rajendra Deshmukh. (2012). Multiple Decrement Models in Insurance: An Introduction Using R. Springer India Course Grade Constitution --> Homework + Quizzes 20% Prerequisite course HWs will be predecessor tasks to activities in this course level for each HW and quiz Simulation and Computation Labs 20% Prerequisite course labs will be predecessor tasks to activities in this course level for each lab Exam1 20% Will reflect lecturing, HW, quizzes and labs as well Exam2 20% Will reflect lecturing, HW, quizzes and labs as well Final 20% Course Outline --> INTRODUCTION (3 hours) Review Chapters 1-6 about the traditional actuarial models and theory of life contingencies CHAPTER 7 – POLICY VALUES (11 hours) Prospective loss random variables and (gross and net premium) policy values with traditional and general cash flows (4) Recursive and retrospective methods, Thiele’s differential equation and policy values at fraction age (4) Policy alterations, gain/loss analysis, asset share, deferred acquisition- expenses and full preliminary term (3) CHAPTER 8 – MULTIPLE STATE MODEL (12 hours) Discrete-time Markov Chain and Markov multiple state models in discrete time (including the transition probability, Chapman-Kolmogorov equation, EPV of premiums/benefits) (4) Continuous-time multiple state models (including assumptions, probabilities, Kolmogorov’s forward equation, premiums and policy values) (4) Multiple decrement models (Multiple decrement table and the associated single decrement tables with fractional age assumptions) (4) CHAPTER 9 – JOINT LIFE AND LAST SURVIVOR BENEFITS (9 hours) Distributional properties of the joint life and last survivor random variables (2) Insurance and annuity benefits for joint life and last survivor statuses (3) Multiple state models for multiple life analysis (3) The common shock model (1) CHAPTER 10 – PENSION MATHEMATICS (6 hours) Introduction to pension mathematics (replacement ratio, the scale function, benefits, service table) (4) Defined benefit pension plans and defined contribution pension plans (2) Prerequisite: Life Contingencies I

Mathematical Statistics: Usage of R accompanies lectures and all assigned tasks. A major portion of the course will be focused on simulations and development of computational structure with real raw data for professional and constructive practice based on instructed analysis and modelling from lecturing. A computational environment is emphasized towards developing professionalism and integrity, else much would be useless or barely meaningful in modern society. Instructors are mostly responsible for conceptual development and flow for code and computation, whereas students will be responsible for actual writing and implementation. For R, students’ style will vary. Course Literature IN UNISON --> Literature from prerequisite Everitt, B. S. and Hothon, T. A Handbook of Statistical Analyses Using R. CRAN Denis, D. J. (2020). Univariate, Bivariate, and Multivariate Statistics Using R: Quantitative Tools for Data Analysis and Data Science. Wiley. Apart from assigned texts and the designated journal articles, the following provides a very “fresh air” guide to some modules: https://www.itl.nist.gov/div898/handbook/ Note: students will be guided to develop multivariate extensions when called upon. Reading will be fundamental concerning use of R. Outside sources are also feasible. Homework and Projects 20%--> Selected analytical problems Recital of chosen prerequisite labs Computational and simulation homework assignments and projects to be included with considerable weight in final grade, which accompanies handwritten homework problem sets to be turned in. Labs with R 40% --> Without experience and competence with a CAS concerning Statistics, an analytical framework is extremely limited. Such follows the relevant fast review of analytical structure. Furthermore, expect labs to have labs quizzes. Exams 40% --> Hand written tests cannot exceed 40% percent of final grade. There will be 4 exams, hence cramming will not be encouraged. Limited open notes. I don’t like setting up myself and students for embarrassment; you are not perfect with statistics, so expect exams to be primarily knowledge based and the calculus related fodder. Most of your development will come from homework and labs; it is what it is. COURSE OUTLINE: 1. Generating summary statistics for raw data 2. Review of Probability Distributions and properties (Uniform, Exponential, Poisson, Binomial, Normal) 3. Simulations (with R + RStudio): Identifying frequencies from real data & finding cumulative distribution Techniques for simulating random variables Will make use of real experiments Simulating data from distributions in module(2) 4. Distribution of data Import and Wrangling (addresses, file types, APIs) Elementary methods to determine distributions Summary Statistics Density Plots P-P and Q-Q 5. Law of Large Numbers and the Central Limit Theorem Introduce the Central Limit Theorem (CLT) and Law of Large Numbers (LLN). Identify Exponential, Poisson and Binomial data and respectively determine in a manner to confirm LLN and CLT. Routledge, R., Chebyshev’s Inequality, Encyclopaedia Britannica Is there too much reliance on assuming normal or Gaussian distribution? Towards Chebyshev’s inequality what amount of repetition (regarding LLN and CLT) of an experiment is adequate towards Chebyshev becoming relevant? Overview and goals of various concentration inequalities (just a survey). 6. More Normal distribution analysis Limpert, E. and Stahel, W. A. (2011). Problems with Using the Normal Distribution--and Ways to Improve Quality and Efficiency of Data Analysis. PloS one, 6(7), e21403 Ghasemi, A., and Zahediasl, S., Normality Tests for Statistical Analysis: A Guide for Non-Statisticians, Int J Endocrinol Metab v.10(2); Spring 2012 7. Estimation and properties of estimators. Method of maximum likelihood Method of moments NOTE: practice examples for particular distributions manually done only serve towards establishing primitive mathematical mechanics with MLE and MoM. Realistically, very small sample size data yield highly erroneous estimations; one can’t acquire a smooth and appropriate density with small data sizes. Computational skills (in R) are critical to be relevant in any field at all. A. Binomial parameter estimation from sample data Small binomial sample for manual practice, then followed by large sample towards immersion with computational tool. Is your data well behaved towards binomial? Then what? B. Poisson modelling by use of real practical data Small Poisson sample for manual practice, then followed by large sample towards immersion with computational tool. For Poisson modelling with large sample choose ambiances with high activity. Is your data well behaved towards Poisson? Then what? Examples: The number of gun related injuries per day, followed by per week, then by per month, then by per year. Such is a means to observe what specified durations fit the model well and what periods yield the highest activities for the respective duration. Patients arriving at emergency rooms per day, followed by per week, then by per month, then by per year). Such is a means to observe what specified durations fit the model well and what periods yield the highest activities for the respective duration. The number of bankruptcies that are filed in a week, followed by month, then by year. Such is a means to observe what specified durations fit the model well and what periods yield the highest activities for the respective duration. C. Normal, Maxwell-Boltzmann, Weibull Small sample concerning respective distribution for manual practice, then followed by large samples towards immersion with computational tool. Is your data well behaved towards binomial? Then what? D. Cramer-Rao inequality, Rao-Blackwell theorem 8. Confidence intervals (with relevance to module 6) Normal confidence interval Standardization of variables. Why? Uniform confidence interval Exponential confidence interval Poisson confidence interval Binomial confidence interval Lognormal confidence interval 9. The Chi-Square distribution The bottom line is to establish the flow of the uses competently with applications involving real raw data. The Chi-Square structure and its features Comprehending categorical and ordinal data. Probing real data sets. Includes means to converts character instances to numeric. Sensitivity of categories concerning traits of interest. Test for independence McHugh ML. (2013). The chi-square Test of Independence. Biochem Med (Zagreb). 23(2): 143-9. Using Fisher’s Exact Test as an alternative Test of homogeneity Test of variance Applications of the Chi-Square distribution with confidence intervals for the exponential lifetime mean. Why the emergence of Chi-Square? 10. T-Distribution & F-Distribution Often such distributions are introduced to intimidate and discourage students by means of memorization for paper tests. Realistically, such distributions barely exists in the real world. In this course understanding why and when to use, with applicability and practicality in a computational environment for such distributions is the only goal. Will not use bamboozle intellect with synthetic hypothetical parameters and data, rather, will make use of real raw data. Memorizing the mathematical models for the distributions will not be forced, rather use of computational tools with real raw data and practice for such. T- distribution Structure and Parameters of concern for the T-distribution Kim T.K. & Park J. H. (2019). More About the Basic Assumptions of T-test: Normality and Sample Size. Korean J Anesthesiol. 72(4): 331-335. Determinations with the T-distribution Sample size determination Population parameter estimation Confidence intervals F-distribution Structure and Parameters of the F-distribution Assumptions for the F-distribution Determine if the variances of two populations are equal by the F-distribution Note: consult with R resources; style will vary among students. The bottom line is to establish the flow of the uses competently with real data. 11. Goodness-of-Fit Note: assumption generally by many is that hypothesis testing should be before goodness-of-fit. However, I don’t like jumping into things assuming normal distribution for every all. A contrary stance is dangerous. Comprehension and logistics for particular measures and values involved will be treated concerning their presence in active computational modelling. Primitive computations and analysis: Review module (4) Box Plots Skewness Kurtosis Statistical Tests Definition, hypotheses (null & alternative), one-sided, two-sided, paired Types of test statistics and applied distributions Comprehending critical values for ideal distributions Significance levels Comparing critical values for real raw data sets Does your data distribution match well with ideal models? Advance Distribution Determination Tests: Jarque–Bera tests of normality Ghasemi, A., and Zahediasl, S., Normality Tests for Statistical Analysis: A Guide for Non-Statisticians, Int J Endocrinol Metab v. 10(2); Spring 2012 Chi-square Goodness of fit test Kolmogorov-Smirnov test Anderson-Darling test Shipiro-Wilk Test A project based component of the module, to make use of various data that one suspects will follow the Poisson distribution concerning the following article < Brown, L. D., and Zhao, L. H., A Test for the Poisson Distribution, Sankhyā: The Indian Journal of Statistics, Series A, Vol. 64, No. 3 > Note: students will also be responsible applying other test distributions to identify possible better candidates for distribution fit. Olson, D. L. and Wu, D. (2013). The Impact of Distribution on Value-At-Risk Measures. Mathematical and Computer Modelling 58, 1670 – 1676 Note: students will also be responsible applying other test distributions to identify possible better candidates for distribution fit. MLE and/or MoM for parameter estimations based on assumed or determined distribution. Note: it’s customary to implement MLE and/or MoM manually for integrity, but in the real world data sets are extremely large. 12. Hypothesis testing (exploratory and project based module for real world decision making) Note: I don’t like cult paraphrasing or degenerative attempts to minimalize ability. If you’re not here to be practical, then get out of my class. Lecturing primarily concerns the competent development of logistics for computational activity in hypothesis testing. There is no “cue card” lecturing/problems involved, rather, what and when to use for meaningfulness in applications. Will recognise promptly the limitations of z- scores with normal distribution rather than being overwhelmed with fodder; cases where sample sets or measures just aren’t normal at all is most realistic. I will not ask you to memorize formulas, rather knowing what they’re used for and how to implement them in a computational environment. A. Steps of Hypothesis Testing: I. State the two hypotheses so that only one can be right. II. Formulate an analysis plan, which outlines how the data will be evaluated. III. The third step is to carry out the plan and physically analyze the sample data. IV. The fourth and final step is to analyze the results and either reject the null hypothesis, or state that the null hypothesis is plausible, given the data. Based on such steps students will acquire real data out there to administer hypothesis testing. NOTE: modules (10) and (11) will be crucial. Question to consider: Are your hypotheses even practical? Topics of concern (all to be done): Testing the significance of the correlation coefficient Module (9) Regression models (interpretation of the summary statistics) Note: no use of T-tests and F-tests extensively. Else, if you want that you can go find various texts and work with faculty that actually likes you and your attributes with your personal time. If you do you use it, you must confirm it’s applicability sans any data transformation/manipulation. If assumptions for respective test is not met, then identify appropriate alternatives and apply. Students will develop projects with various real data. Then will implement the prior 3 topics of concern based on the given HT steps. Not interested in being dictated to with applications not of interest to students, rather how HP can be of use; else it’s pointless. You’re not here for a math department’s biased and subjugating culture of Nurgle and Skeksis. Students will be divided into groups for them to choose real raw data to work on. Personal interest and understanding of such interests are often the best ways to grasp and implement towards competency and professionalism; you might end up liking this module at the end based on projects of interest. Functions or packages in R for hypothesis testing only concerns cross checking; one must inevitably understand clearly what they’re trying to discriminate from in sample data. Projects will make use of R + RStudio. 13. Applying bivariate normal and other bivariate distributions Using two standard normal variables to build a general bivariate normal distribution; onwards to the five significant parameters where the random variables are expressed in terms of such. Recalling the form of correlation in terms of covariance. Change of variables and Jacobian leading to a bivariate form that’s inviting to data, and compact matrix form. Mardia test for multivariate normality. Goodarzi, E., Mirzaei, M., and Ziaei, M., Evaluation of Dam Overtopping Risk Based on Univariate and Bivariate Flood Frequency Analyses, Can. J. Civ. Eng. 39: 374–387 (2012) As well, find data for wherever to intimately develop Yue, S., A Bivariate Gamma Distribution for use in Multivariate Flood Frequency Analysis, Hydrol. Process. 15, 1033–1045 (2001) As well, find data to intimately develop after 14. Covariance and Correlation Reviewing practical use of Covariance and Correlation Mukaka M. M. (2012). Statistics Corner: A Guide to Appropriate Use of Correlation Coefficient in Medical Research. Malawi Medical Journal: the Journal of Medical Association of Malawi, 24(3), 69–71 Data Analysis Applications B. Use of financial data, economic data, etc., etc. C. Generating scatter plots with data for visual information D. Correlation as the geometric mean of regressions E. Generating heat maps and interpretation F. Applying the ggpairs() function 15. Regression Include the following---> Bivariate regression Multivariate regression OLS Assumption Choosing variables based on data analysis to support regression models Heinze, G., Wallisch, C., & Dunkler, D. (2018). Variable Selection - A Review and Recommendations for the Practicing Statistician. Biometrical Journal. Biometrische Zeitschrift, 60(3), 431–449. olsrr: Tools for Building OLS Regression Models; compare to Heinze et al MANDATORY: Summary statistics that convey whether models are good or bad 16. Detection of Data Fabrication Using Statistical Tools NOTE: must be applied computational as well with real data out there to get the points across. Will use common labs in the natural and applied sciences as examples where students may tend to fabricate data. As well as trustworthy data sets from various sources. Hartgerink C, Wicherts J, van Assen M (2016) The Value of Statistical Tools to Detect Data Fabrication. Research Ideas and Outcomes 2: e8860. Hartgerink, C. H. J., Voelkel, J. G., Wicherts, J. M., & van Assen, M. A. L. M. (2019, August 19). Detection of Data Fabrication Using Statistical Tools. LAB SYLLABUS --> NOTE: package functions often to be applied in R in labs towards cases of abundant data and sources. Note: concerning the course for R students with external files, URLs, databases and so forth, data structure functions such as filter(), select(), mutate(), order(), merge(), scan() may be highly relevant. Note: R utility is mainly for establishing consistency. Use of such functions succeed manual analytical writing. Note: topics will be bundled for each lab. For each lab there will also be questions sets where students will be required to provide analytic writing/solutions that complements. Topics of concern –> —Review of conventional probability distributions. Simulating random variables from phenomena. Frequency simulations. —Data acquisition and modelling Data sources (.htm, .html, .xls, .xlsx, .csv) Acquisition & Probing data Data Wrangling (basics) Generating summary statistics Correlation matrix and heatmaps. The ggpairs() function Distribution of a variable (revisiting module 4) Univariate distribution among variable pairs —Probability distributions with MLE During lecture instruction, manual modelling synthesis of estimators will be at least intermediate with respect to the given probability distribution models. High volume sample data: Binomial, Poisson, Gamma, Weibull, Normal. —Method of moments (mean, variance, skewness, kurtosis) towards real high volume sample data, along with P-P plots, Q-Q plots, and comparing to MLE above; difficult moments to be provided. —Review and computational repetition with modules 8, 9 & 10 for various data —Goodness-of-fit with external raw data —Simulating data from densities when real data is scarce or not acquirable —Olson, D. l. and Wu, D. (2013). The Impact of Distribution on Value-at-Risk Measures. Mathematical and Computer Modelling 58, pp 1670 - 1676 For such given article one will not only be confined to normality and logistic distributions, but will also introduce lognormal distribution. MLE may or may not be applied. Crucially, one must also be able to apply VaR to the true distribution of the data (compared to the three ideal distributions). More relevant real stock data will be applied. Will also pursue a scheme or currency exchange risk based on such three distributions. —Modules 10-12 conjoint —Module 13 with external real data —Fraile, R., and Garcia-Ortega, E., Notes and Correspondence, Fitting an Exponential Distribution, Journal of Applied Meteorology, Volume 44, 2005, pages 1620 – 1625 From what was described in this journal article, applied will be at least three sets of unique data each from different natural behaviours or phenomena. Will make use of (least squares) regression, MLE, and method of moments to compare (or comparison). How is there certainty that either of the three methods will be most accurate or appropriate? —Lucas, C., C. and Soares, C. G. (2015). Bivariate Distributions of Significant Wave Height and Mean Wave Period of Combined Sea States, Ocean Engineering 106, 341–353 The data set in the journal article can be applied but will be updated. Will also pursue two to three other data sets from different ambiances. —Tao, S. et al, 92013). Estimating Storm Surge Intensity with Poisson Bivariate Maximum Entropy Distributions Based on Copulas, Nat Hazards (2013) 68:791–807 Will pursue data that’s not of Qingdao, rather, of the Caribbean and other places of interest. —Nelson, J. F. (1985). Multivariate Gamma-Poisson Models. Journal of the American Statistical Association, Vol. 80, No. 392, pp. 828-834 The above article concerns analysis with confirmation of the probabilities and statistical models/tools applied. However, ambiances of interest to apply and data may be augmented with more recent times with associated data. Hence, conclusions may differ from article. Will also try to determine any robustness and adaptability of such “headliner” distribution, compared to ordinary Poisson distribution models and ordinary Gamma distribution models. —Module 14 —Regression (will be active with vast raw data) —Detection of Data Fabrication Using Statistical Tools Hartgerink C, Wicherts J, van Assen M (2016) The Value of Statistical Tools to Detect Data Fabrication. Research Ideas and Outcomes 2: e8860. Al-Marzouki, S., Evans, S., Marshall, T., & Roberts, I. (2005). Are these data real? Statistical methods for the detection of data fabrication in clinical trials. BMJ, 331 (7511), 267–143. Yamamoto, K., & Lennon, M. L. (2018). Understanding and Detecting Data Fabrication in large-scale assessments. Quality Assurance in Education,26(2), 196–212. Prerequisite: Probability and Statistics B (no exception).

R ANALYSIS This course concerns students in Actuarial Studies (as in insurance), Economics, Operations Management, Revenue management and Finance. For quality instruction and sustainable skill sets the duration of the course to be 18 weeks, meeting at least two days per week, for a minimum of two and a half hours each day. Extensive computations and “coding” accompany practical and fluid mathematical modeling, etc. Module areas of the class must be completed in full. Development of “code” concerns credibility towards professional endeavors in various industries of society. There will be written and coding assignments intertwined. Instructors are mostly responsible for developing logistics for code and computation, whereas students will be responsible for actual writing and implementation. Algorithms to be designed in class, and independently outside of class based on assignments and projects. On exams students are required to comprehend mathematical structure and modelling, accompanied by logistical design of code, then implementation of R code. One crucial component of this course is the ability for research and development outside of the class; students’ potential isn’t confined to the ambiance tone nor rhetoric. Course doesn’t assume students have an affinity or innate ability for such technical activities (aside from mathematical modelling as a preliminary skill), however, active interest in applications and study outside of class sessions are the best means for a student to become comfortable with language structures or syntax schemes. There is neither regressive nor cap policy regarding the level of mathematical coding; prerequisites satisfaction for this course are Multivariate Calculus and Mathematical Statistics B. Exposure to elementary computation activities in such two mentioned classes will be an invaluable asset. In R one’s style can vary. Ultimately, progress and advancement goes beyond the classroom; one really has to personally reinforce their personal interests, by reading many highly recognised R sites, JOSS R journals, package vignettes, R books and sound investigation of packages manuals. NOTE: for any journal articles used one will also like to replicate simulations and/or computations exhibited in them in the R environment. NOTE: if you think you are going to turn this course into Markov chains fodder with matrix algebra, find another course immediately outside of the institution. I don’t care about you pretending that you understand what’s going on with shows of matrix algebra. If you can’t develop, it doesn’t matter. I will not encourage bamboozles about modelling and algorithms as the successor to matrix perversions. If I ask you to model, simulate or compute, then just do that. I don’t care what upper triangular, lower triangular and adjoint[adjoint[adjoint] looks like. NOTE: students should practice drawing up the logistics for computational schemes, rather than diving blindly into large tasks or projects; your logistics is your business, namely, you will be doing actual programming. Don’t mess yourselves and the future students of this course; your antics can carry over to the future. Your lecturer, etc. should belong in this course, not because of some sociopolitical excrement show, thug rent seeking and nonsense social toxicity. NOTE: analytical development in a word processor with use of mathematical palette for formulas to accompany developed R documentation. NOTE: an 18 weeks course with 2 sessions per week and 2 hours per session. Assessment --> Assignments 25% Analytical + R Computational intertwined Projects 45% Analytical + R Computational intertwined 3 Exams 30% Assignments --> Assignments concern specific modules Analytical + R Exams --> Exams concern specific modules Analytical + R Projects --> Each project will have two components A. Refresher prerequisite labs related to current course tasks (0.3) Analytical + R B. For current course tasks specific modules bundled (0.7) Analytical + R Course Outline --> 1. Calculus Techniques & Operations in R (single and multivariable) ---Deterministic Modelling (FAST PACED) Plotting functions (single, multiple plots simultaneously, aesthetics) ---Calculus Operations (FAST PACED) Finding roots, points of intersection among curves, derivatives, relative extrema, absolute value (minimum and maximum), indefinite integrals, definite integrals ---Constructing Generic functions function operation Includes plotting and multiple parameter specifications in a plot ---Plotting data sets (single, multiple plots simultaneously, aesthetics) ---Scatter plots with data sets (data generation from functions, data files, aesthetics) 2. Preliminary computational stochastics ---Probability axioms review ---Simulation for a random variable of chosen sample size that contains a set of values with the correct relative frequencies, such that a respective given proportion corresponds to a respective given value from the set. ---Real Experiments Histograms, measures of central tendency and frequency simulations ---Simulating data sets from probability densities manually ---Generating simulated data sets in order to explore modeling techniques or better understand data generating processes with simstudy package (or alternatives). Prior with probability densities must resonate under. The user defines the distributions of individual variables, specifies relationships between covariates and outcomes, and generates data based on these specifications. The final data sets can represent randomized control trials, repeated measure designs, cluster randomized trials, or naturally observed data processes. Other complexities that can be added include survival data, correlated data, factorial study designs, step wedge designs, and missing data processes. 3. Data Manipulation ---Import from websites, etc. (.xls, .xlsx, .csv, .txt, FCV, APIs) ---Cleaning ---Wrangling ---Developing summary statistics (include skew and kurtosis) ---Development of random variables (corresponding probabilities to outcomes from the data) Simulating random variables from real data sets manually with small data sets Histograms, density plots, q-q plots --To pursue: Kang H. (2013). The Prevention and Handling of the Missing data. Korean J Anesthesiol. 64(5): 402-6. R tools for handling missing data 4. Exploratory Data Analysis Note: analytical structure being predecessor to following R based topics listed. Summary statistics (include skew and kurtosis) The R Packages CADStat and ggplot2 towards the following: Variable Distributions Histograms Boxplots Cumulative Distribution Functions Q-Q Plots Scatter Plots Correlation Analysis (CADStat and ggpairs() function) Mukaka M. M. (2012). Statistics Corner: A Guide to Appropriate Use of Correlation Coefficient in Medical Research. Malawi Medical Journal: The Journal of Medical Association of Malawi, 24(3), 69–71. Generating heat maps and interpretation (apply other package) What can you infer about the results? Applying the ggpairs() function from GGally R Package Conditional Probability Analysis (CADStat package) 5. Goodness-of-Fit: Distribution finding ---Advance recital from prerequisite with real raw data ---MLE and MoM in R 6. Treatment of Outliers Note: it’s up to the analyst (or a consensus process) to decide what will be considered abnormal. Before abnormal observations can be singled out, it is necessary to characterise normal observations. Generally, in financial risk management, actuarial science, economics, the physical sciences, and planetary sciences, having normal distribution is a pipe dream. Graphical techniques for identifying outliers: scatter plots and box plots. More commonly used outlier tests for assumed normally distributed data: Grubb’s Test Tietjen-Moore test Generalised (extreme Studentized deviate) ESD test Assisting literature: Boris Iglewicz and David Hoaglin (1993), "Volume 16: How to Detect and Handle Outliers", The ASQC Basic References in Quality Control: Statistical Techniques, Edward F. Mykytka, Ph.D., Editor. Barnett and Lewis (1994), Outliers in Statistical Data, 3rd. Ed., John Wiley and Sons. 7. Multivariate Regression ---OLS/WLS/GLS (6 phases) Variable selection techniques Model Selection Model Verification Summary Statistics Forecasting & Error More Summary Statistics ---Feature Importance Feature importance regression method ---Quantile Regression (multivariate) Scatter Plots Scatterplots are a useful first step in any analysis because they help visualize relationships and identify possible issues (e.g., outliers) that can influence subsequent statistical analyses, or need of regression beyond simple OLS, say, quantile regression (or generalized nonlinear models). Note: concerns for the number of variable pairs. Model structure and advantages over OLS/WLS/GLS Counterpart development to OLS/WLS/GLS (6 phases); comparing to OLS/WLS/GLS results. ---Nonlinear Quantile Regression (counterpart to prior) 8. Feature Selection Note: a feature is the same as a predictor variable; a target is equivalent to a response variable. First, for datasets chosen will develop correlation matrices. Then heatmaps, then use of ggpairs(). Second, will explore a method for feature selection. Will identify the concept, followed by (practical, tangible and fluid) analytical structure of the method. Then implementation logistics. Then implementation in the R environment. Will make use of datasets with considerable amounts of features. Univariate feature selection method. Implications for module 7 (will be hands-on) Compare prior to feature importance regression method Third, comprehension of Principal Component Analysis (PCA). Applying FactomineR (or other) R package for implementation. If data has non-linearity it may require use of Kernel PCA. Fourth, R packages to be applied: Boruta and FSelectorRcpp Compare to all methods encountered prior (first to third) 9. Logit Regression and Multinomial-Logit Regression Outline Purpose and analytical structure Relevant types of data Variable selection techniques Model Selection Model Verification Summary Statistics Forecasting & Error More Summary Statistics Feature importance logistic regression method Then compare to: Boruta and FSelectorRcpp PCA, Kernel PCA (or t-SNE and UMAP) 10.Primitive Time Series Analysis of Data (logistical & implementation focused) ---Concept and Structure ---Types of Time Series Decomposition Importance of knowing which components are in your time series Implementations ---Data characteristics and computational R tests/tools (such to cross-reference/validate with prior) Trends Seasonality Stationarity ---Time Series Models and Analysis (logistical and implementation focused). AR, MA, ARMA, ARIMA Constructive time table for: Uses. Fluid, tangible and practical analytical structure in short time Decompositions and Salient characteristics of interest with R computational tools/tests relevant to respective model Model development, model validation, summary statistics Further robust applications with real data Forecasting & error EWMA Constructive time table for: Uses. Fluid, tangible and practical analytical structure in short time Decompositions and Salient characteristics of interest with R computational tools/tests relevant to respective model Model development, model validation, summary statistics Further robust applications with real data Forecasting & error Extending EWMA Extending EWMA to handle different variations of time series data, such as trend and seasonality, through methods like Holt's method (double exponential smoothing) and Holt-Winters' method (triple exponential smoothing). GARCH (extending basic EWMA) Constructive time table for: Uses. Fluid, tangible and practical analytical structure in short time Decompositions and Salient characteristics of interest with R computational tools/tests relevant to respective model Model development, model validation, summary statistics Further robust applications with real data Forecasting & error ---Outlier Detection in Time Series Note: it’s up to the analyst (or a consensus process) to decide what will be considered abnormal. Before abnormal observations can be singled out, it is necessary to characterise normal observations. Generally, in financial risk management, actuarial science, economics, the physical sciences, and planetary sciences, having normal distribution is a pipe dream. Question: which TS model is best for the particular data applied? 11.Elementary Monte Carlo methodologies for ideal phenomena (with simulations): ---Monte Carlo method as any process that consumes random numbers ---Coin tosses and other binomial processes (rapid review) What applications can be modelled and simulated by such? Analytically and in R. ---Waiting and Poisson processes (rapid review) What applications can be modelled and simulated by such? Analytically and in R with real data. ---Normal Distribution. What applications can be modelled and simulated by such? Analytically and in R with real data. How practical is the law of large numbers with finite data sets? How much do you need for respective case, and is it a practical theorem? How practical is the CLT with finite data sets? How much do you need to see it happen for respective case study, and is it a practical theorem? ---Hit-or-miss methodology for Buffon-like processes (rapid review and R development) ---Crude (or Mean-value) Monte Carlo ---Comparison between Hit-or-Miss approach and Crude Monte Carlo by analysis of unbiasedness and minimal variance. R structuring. ---Applications for monte carlo First year net profit Demand forecast Yee, W. Monte Carlo Simulations: The Intersection of Probabilistic and Deterministic. Towards Data Science (2019) Platon, V. and Constantinescu, A. Monte Carlo Method in Risk Analysis for Investment Projects. Procedia Economics and Finance 15 (2014) 393 – 400 Clark, V., Reed, M. and Stephan, J. Using Monte Carlo Simulation for a Capital Budgeting Project. Management Accounting Quarterly 20 Fall 2010, Volume 12, Number 1 ---Value at Risk monte carlo Comprehending what you’re trying to measure Model Development and Computation Note: may not assume normal distribution. Simulations in R. ---Expected Shortfall monte carlo and Stress Expected Shortfall monte carlo Comprehending what you’re trying to measure with the models. Disparity to basic monte carlo VaR. Model Development and Computation Note: may not only assume normal distribution. Simulations in R. ---Variance Reduction Methods (Control Variates) and its influence on monte carlo computations/simulations. One must determine with high practicality how control variates apply to various prior applied monte carlo methods, and if beneficial or even meaningful: Hit-or-miss, crude First year net profit Demand forecast Yee, W. Platon and Constantinescu Clark, et al VaR, expected shortfall and stressed expected shortfall 12.Elementary Stochastic Differential Equations (3 weeks minimum) ---Brownian Motion (BM) A. https://www.mit.edu/~kardar/teaching/IITS/lectures/lec6/lec6.pdf B. Drunkard’s Walk construction in a plane and constructing a simulation by means of a developing a binomial lattice (BL) model, say, repeated highly compact Bernoulli trials. Simulate for various parameter values. C. Deriving solution, and derivation for models of mean and variance D. The distribution of Brownian motion is normal (with proof) E. Random Walk modelling, and simulation by loop design. What is noise and what is the cause? ---Geometric Brownian Motion A. First, Informally, introduce the SDE for Geometric Brownian motion and its features that differentiates it from BM B. For the exact form of GBM find the resulting expectation and variance of GBM. For GBM SDE establish the probability distribution (with proof) C. Simulate via use of loop and probability density; developing BM simulation in the R environment. Simulate for various parameter values. D. BL simulation from (A) as an approximation to GBM; develop convergence to GBM. Note: emphasis done without specific application of stocks. E. Ruin and Victory probabilities for GBM ---Hull-White and Ornstein-Uhlenbeck A. First, Informally, introduce the SDEs and their features B. For the exact forms of HW and OU, respectively, find the resulting expectation and variance. Establish the probability distribution (with proof), respectively. C. Simulate via use of loop and probability density; developing in the R environment. Simulate for various parameter values. D. Application with Economic Scenario Generation ---Parameter Estimation of Stochastic Differential Equations Will have analytical development based on the given articles, however, will only concern ourselves 2 or 3 methods that are easily retainable, fluid, practical, robust and practical with R; we want competent and sustainable computational activity wr.t. parameters. Will have limited analytical development based on the given articles, however, will only concern ourselves 2 or 3 methods that are easily retainable, fluid, practical, robust and practical with R; we want competent and sustainable computational activity wr.t. real data paramaters. Hurn, A. S. and Lindsay, K. A. (1999). Estimating the Parameters of Stochastic Differential Equations. Mathematics and Computers in Simulation 48(4 – 6), pages 373 – 384 David A. McDonald & Leif K. Sandal (1999) Estimating the Parameters of Stochastic Differential Equations using a Criterion Function, Journal of Statistical Computation and Simulation, 64:3, 235-250 Nielsen, Jan & Madsen, Henrik & Young, Peter. (2000). Parameter Estimation in Stochastic Differential Equations; An Overview. Annual Reviews in Control. 24. 83-94. Bishwal, J. P. N. (2008). Parameter Estimation in Stochastic Differential Equations. Springer Weber, GW., Taylan, P., Görgülü, ZK., Rahman, H.A., Bahar, A. (2011). Parameter Estimation in Stochastic Differential Equations. In: Peixoto, M., Pinto, A., Rand, D. (eds) Dynamics, Games and Science II. Springer Proceedings in Mathematics, vol 2. Springer, Berlin, Heidelberg. Strong applications with Economic Scenario Generation --SDE R Packages Langevin, sde, Sim.DiffProc, stochvol, yuima -Packages will be investigated concerning treatment of all prior SDEs and the various primitive tasks done for each SDE encountered -Monte carlo statistics (within a confidence band or not) -Mean path, Min and Max within confidence bands -Means to acquire distributions -Parameter estimation -Additional packages: DiffusionRimp, DiffusionRgqd, DiffusionRjgqd Critique such 3 above packages with acquired analytical skills and among the prior 5 packages learnt. --Advance Implementation of SDEs with Economic Scenario Generation Prerequisites: Mathematical Statistics

Risk Theory An introduction to modelling and important actuarial methods useful in modelling. A thorough knowledge of calculus, probability, and mathematical statistics is assumed. This course covers the syllabus for the professional actuarial exam on model construction - SOA Exam C/CAS Exam 4. Students will be introduced to useful frequency and severity models beyond those covered in SOA Exam MLC. The student will be required to understand the steps involved in the modelling process and how to carry out these steps in solving business problems. Students should be able to: 1) analyse data from an application in a business context; 2) determine a suitable model including parameter values; and 3) provide measures of confidence for decisions based upon the model. Students will be introduced to a variety of tools for the calibration and evaluation of the models. Students will become familiar with survival, severity, frequency, and aggregate models and use statistical methods to estimate parameters of such models given sample data. Students will be able to identify steps in the modelling process, understand the underlying assumptions implicit in each family of models, recognize which assumptions are applicable in a given business application, and appropriately adjust the models for impact of insurance coverage modifications. Lecturing literature: Loss Models: From Data to Decisions, by Klugman, S.A., Panjer, H.H. and Willmot, G.E. CAS (CASACT) and SOA literature and guides R immersion literature: Kaas, Rob, Goovaerts Marc, Dhaene, Jan, Denuit, Michel (2008). Modern Actuarial Risk Theory Using R. Springer Other Additional Guides: https://www.r-project.org/conferences/useR-2009/slides/Goulet.pdf https://cran.r-project.org/web/packages/actuar/vignettes/risk.pdf Calculator --> Accepted Calculator R environment --> Additionally, in the real-world there’s modelling, simulation and computation, hence there must be an environment that encourages and reinforces such. Tables are also subject to updates (with ambiance to consider). Some cases may require pursuing data from ambiance of interest. Computation and simulation will often depend on modelling theory and real data. Most activity will be in labs and minimal in lecture instruction. Progress and competency in your homework will reflect greatly in labs. Note: one’s style in R may vary due to personal preferences and what not. R packages of interest (aside from pre-installed packages): actuar, bootruin, ChainLadder, DCL, extraDistr, FactoMineR, gnm, LDPD, lifecontingencies, queuecomputer, queueing, raw, reinsureR, survival NOTE: vignettes and reference manuals are crucial towards good development. Depending on type of development students may use multiple R packages, within or outside of the above list. NOTE: to be highly successful with computation and simulation one must have a tangible, practical and fluid foundation with analysis and modelling. You are a actuarial science major, and not “a weird mathematical frolic major”. What is your value to an executive or BOT? Modules and topics introduced will be goal oriented. The “what, why, when, how, why again process” is necessary throughout. Course Grade Constitution: Homework 10% Analytical + R Computation and Simulation Labs 10% Exam 1 20% Exam 2 20% Exam 3 20% Final Exam 20% For the most part, these sections will be covered in the order observed here: Chapter 2 (2.1-2.2) Chapter 3 (3.1-3.5) Chapter 4 (4.1-4.2) Chapter 5 (5.1-5.4) Chapter 6 (6.1-6.5, 6.7) Chapter 8 (8.1-8.6) Chapter 9 (9.1-9.7, 9.11.1-9.11.2) Chapter 12 (12.1-12.4) Chapter 13 (13.1-13.3) Chapter 14 (14.1-14.4) Chapter 15 (15.1-15.4, 15.6.1-4, 15.6.6) Course Outline --> A. Severity Models 1. Calculate the basic distributional quantities: a) Moments b) Percentiles c> Generating functions 2. Describe how changes in parameters affect the distribution. 3. Recognize classes of distributions and their relationships. 4. Apply the following techniques for creating new families of distributions: a) Multiplications by a constant b) Raising to a power c> Exponentiation d) Mixing 5. Identify the applications in which each distribution is used and reasons why. 6. Apply the distribution to an application, given the parameters. 7. Calculate various measures of tail weight and interpret the results to compare the tail weights. B. Frequency Models: For the Poisson, Mixed Poisson, Binomial, Negative Binomial, Geometric distribution and mixtures thereof: 1. Describe how changes in parameters affect the distribution. 2. Calculate moments. 3. Identify the applications for which each distribution is used and reasons why. 4. Apply the distribution to an application given the parameters. 5. Apply the zero-truncated or zero-modified distribution to an application given the parameters. C. Aggregate Models 1. Compute relevant parameters and statistics for collective risk models. 2. Evaluate compound models for aggregate claims. 3. Compute aggregate claims distributions. D. For Severity, Frequency, and Aggregate Models 1. Evaluate the impacts of coverage modifications: a) Deductibles b) Limits c> Coinsurance 2. Calculate Loss Elimination Ratios. 3. Evaluate effect of inflation on losses. E. Risk Measures 1. Calculate VaR and TVaR and explain their use and limitations. F. Construction of Empirical Models 1. Estimate failure time and loss distributions using: a) Kaplan-Meier estimator, and approximations for large data sets b) Nelson-Aalen estimator c> Kernel density estimators 2. Estimate the variance of estimators and confidence intervals for failure times and loss distribution: a) Unbiasedness b) Consistency c> Mean squared error G. Construction and Selection of Parametric Models 1. Estimate the parameters of failure time and loss distributions using: a) Maximum likelihood b) Method of moments c> Percentile matching d) Bayesian procedures 2. Estimate the parameters of failure time and loss distributions with censored and/or truncated data using maximum likelihood. 3. Estimate the variance of estimators and the confidence intervals for the parameters and functions of parameters of failure time and loss distributions. 4. Apply the following concepts in estimating failure time and loss distributions: a) Unbiasedness b) Asymptotic unbiasedness c] Consistency d) Mean squared error e) Uniform minimum variance estimator 5. Determine acceptability of a fitted model and/or compare models using: a) Graphical procedures b) Kolmogorov-Smirnov test c] Anderson-Darling test d) Chi-square goodness-of-fit test e) Likelihood ratio test f) Schwarz Bayesian Criterion H. Credibility 1. Apply limited fluctuation (classical) credibility including criteria for both full and partial credibility. 2. Perform Bayesian analysis using both discrete and continuous models. 3. Apply both Buhlmann and Buhlmann-Straub models and understand the relationship of these to the Bayesian model. 4. Apply conjugate priors in Bayesian analysis and in particular the Poisson-Gamma model. 5. Apply empirical Bayesian methods in the nonparametric and semi-parametric cases. I. Simulation 1. Simulate both discrete and continuous random variables using the inversion method. 2. Estimate the number of simulations needed to obtain an estimate with a given error and a given degree of confidence. 3. Use simulation to determine the p-value for a hypothesis test. 4. Use the bootstrap method to estimate the mean squared error of an estimator. 5. Apply simulation methods within the context of actuarial models. Prerequisite: Mathematical Statistics

Probability Models with Actuarial Applications This course covers statistical estimation procedures for random variables and related quantities in actuarial models. Students are expected to be familiar with survival, severity, frequency and aggregate models, and use statistical methods to estimate parameters of such models given sample data. Students are further expected to identify steps in the modeling process, understand the underlying assumptions implicit in each family of models, recognize which assumptions are applicable in a given business application, and appropriately adjust the models for impact of insurance coverage modifications. Lecturing literature --> Loss Models: From Data to Decisions, 2008, by Klugman, S.A., Panjer, H.H. and Willmot, G.E. SOA and CAS manuals, guides and papers R immersion literature --> Kaas, R. et al. (2008) Modern Actuarial Risk Theory: Using R. Springer, Heidelberg Access the actuar package vignettes Loss Distribution. CASACT https://www.casact.org/sites/default/files/presentation/rpm_2017_presentations_workshop-4_5.pdf Calculator --> Accepted Calculator R environment --> Additionally, in the real-world in actuarial science a strong statistical tool is needed. Hence, there must be an environment that encourages and reinforces such. Tables are also subject to updates (with ambiance to consider). Some cases may require pursuing data from ambiance of interest. Some to be real, while others to be simulated based on preferences. Most R activity will be in labs and a little in lecture instruction. Progress and competency in your homework will reflect greatly in labs. Note: one’s style in R may vary due to personal preferences and what not. R packages of interest (aside from pre-installed packages): actuar, bootruin, ChainLadder, cplm, DCL, extraDistr, FactoMineR, gnm, LDPD, lifecontingencies, queuecomputer, queueing, raw, reinsureR, survival Note: must have good effort with elaboration of analytical models associated to packages (speculation or identification) Vignettes and reference manuals are crucial towards good development. Depending on type of development students may use R packages outside of the above list. NOTE: to be highly successful with computation and simulation one must have a tangible, practical and fluid foundation with analysis and modelling. You are a actuarial science major, and not “a weird mathematical frolic major”. What is your value to an executive or BOT? Modules and topics introduced will be goal oriented. The “what, why, when, how, why again process” is necessary throughout. Course Grade Constitution: Homework 10% Analytical + R Computation and Simulation Labs 30% 4 Exams 60% PART IV PARAMETRIC STATISTICAL METHODS 13 Frequentist estimation 13.1 Method of moments and percentile matching 13.2 Maximum likelihood estimation 13.3 Variance and interval estimation 13.4 Non-normal confidence intervals 13.5 Maximum likelihood estimation of decrement probabilities 14 Frequentist Estimation for discrete distributions 14.1 Poisson 14.2 Negative binomial 14.3 Binomial 14.4 The (a, b, 1) class 14.5 Compound models [Not Covered] 14.6 Effect of exposure on maximum likelihood estimation 15 Bayesian estimation 15.1 Definitions and Bayes’ theorem 15.2 Inference and prediction 15.3 Conjugate prior distributions and the linear exponential family 15.4 Computational issues 16 Model selection 16.1 Introduction 16.2 Representations of the data and model 16.3 Graphical comparison of the density and distribution functions 16.4 Hypothesis tests 16.5 Selecting a model [Chapters 17 – 19 have a combined weight of 20% - 25% of the SOA Exam C] PART V CREDIBILITY 17 Introduction and Limited Fluctuation Credibility 17.1 Introduction 17.2 Limited fluctuation credibility theory 17.3 Full credibility 17.4 Partial credibility 17.5 Problems with the approach 17.6 Notes and References 18 Greatest accuracy credibility 18.1 Introduction 18.2 Conditional distributions and expectation 18.3 The Bayesian methodology 18.4 The credibility premium 18.5 The Buhlmann model 18.6 The Buhlmann-Straub model 18.7 Exact credibility 19 Empirical Bayes parameter estimation 19.1 Introduction 19.2 Nonparametric estimation 19.3 Semi-parametric estimation Augment with the following: Sukono et al 2018 Model Estimation of Claim Risk and Premium for Motor Vehicle Insurance by using Bayesian Method. IOP Conf. Ser.: Mater. Sci. Eng.300 012027 (find data to suit ambiance interest) PART VI SIMULATION (will be done with much immersion and quality) 20 Simulation 20.1 Basics of simulation 20.2 Simulation for specific distributions 20.3 Determining the sample size 20.4 Examples of simulation in actuarial modelling Augment with simulation of actuarial data (with actuar and others) Augment with simulation of life insurance portfolios Prerequisite: Mathematical statistics. Co-requisite or Prerequisite: Risk Theory Ratemaking for Non-Life Insurance Ratemaking is a key driver of insurance profitability and hence a primary actuarial responsibility. Actuaries employ a variety of ratemaking techniques depending on specific circumstances. For example, techniques used to price short-tailed lines of insurance (e.g., personal automobile) are different than techniques used in long-tailed lines (e.g., workers compensation). Even within the same insurance product, actuarial techniques may differ due to regulatory requirements and data limitations. Furthermore, actuarial techniques are constantly evolving due to enhanced information and advances in technology. Industries of concern --> Home Insurance, Automobile, Health Insurance, P&C Insurance Tangibles --> -For one particular industry at a time will identify and analyse relevant ratemaking formulas and the techniques associated. -Will go through the logistics for each ratemaking formula and associated techniques. Then, having credibility and competence with their implementation for meaningfulness. -Simulating data for pursuits if external data isn’t accessible. Must develop highly active competence with what you are specifically trying to acquire for actual use based on whatever settings, conditions and models. -Will try to match market price quotes with our development and computations. Statement for applied Literature --> It’s considered a luxury to have a professional lecturer of ratemaking, rather than the common hoodwink of mathematicians building themselves in their own world. Nevertheless, ability will come from navigating different literature to establish good comprehension and a development process towards implementation; reading is fundamental. So, you will likely be reading more than one book. Don’t expect me to “cut your mango nicely and place it on a stick” for everything. Furthermore, ratemaking has evolved where it’s difficult to determine what really is premier and revered professionally in the industries; loss management and profitability is the game, subject to regulation. R packages (along with pre-installed packages) --> actuar, bootruin, ChainLadder, cplm, DCL, FactoMineR, gamlss, gnm, insurancerating, LDPD, nlirms, NetSimR, raw, reinsureR, survival Assessment --> There will only be exams and projects. Apart from exams, course focuses on making the models/formulas, techniques, logistics and computations quite tangible, practical and fluid with skills retention and sustainability. Course will not be approached as a mathematical fantasy swamp jungle; rather actual concern for the non-life actuarial profession with premiums. --Exams 20% Topics from Risk Theory course and Probability Models course 0.35 Will have analytical modelling tasks Simulating data when real data not available 0.25 Done on numerous occasions concerning appropriate data structure for models and evaluation Resonating R Literature (Kass, R. et al) 0.4 --Projects with R will be highly demanding 80% Based on Basic Literature Based on Generalised Linear Models Literature Based on CAS Research Library Based on Applications Literature Alternative and Extended Models (optional) NOTE: course may also have use for the Excel environment. Basic Literature --> Young, Virginia R. (2014). “Premium Principles.” Wiley StatsRef: Statistics Reference Online. ACAS Robert Brown (2015). Introduction to Ratemaking and Loss Reserving for Property and Casualty Insurance, ACTEX Publications Meyers, G. G. An Analysis of Retrospective Ratemaking. CASACT Werner, G., Modlin, C. and Watson, W. T. et al (2016). Basic Rate Making, Casualty Actuarial Society Fisher, G. K. et al (2017). Individual Risk Rating. Casualty Actuarial Society Pechon, F., Trufin, J. and Denuit, M. (2018). Preliminary Selection of Risk Factors in P&C Ratemaking. Casualty Actuarial Society, Volume 13 Issue 1 Bühlmann, Hans. 1985. “Premium Calculation from Top down.” ASTIN Bulletin: The Journal of the IAA 15 (2): 89–101 Witt, R. (1977). Monte Carlo Simulations of Pure Premium Distributions in Automobile Insurance. The Journal of Insurance Issues and Practices, 1(2), pages 49-64. Note: will have other interests besides automobile insurance. Resonating R Literature --> Kaas, R. et al. (2008) Modern Actuarial Risk Theory: Using R. Springer, Heidelberg Note: concerns construction/development of special primitive/primordial features often taken lightly Resources --> CAS Research Library Generalised Linear Models Literature --> Ohlsson, E. and Johansson, B. (2010). Non-Life Insurance Pricing with Generalised Linear Models. Springer Goldburd, M. et al (2020). Generalised Linear Models for Insurance Rating, Casualty Actuarial Society Coskun, S. Introducing Credibility Theory into GLMs for Ratemaking on Auto Portfolio. Centre d’Etudes Actuarielles Klinker, F. (2010). Generalized Linear Mixed Models for Ratemaking: A Means of Introducing Credibility into a Generalized Linear Model Setting, Casualty Actuarial Society E-Forum, Volume 2 Applications Literature --> Venezian, E. C. (1985). Ratemaking Methods and Profit Cycles in Property and Liability Insurance. The Journal of Risk and Insurance, 52(3), 477–500 Müller, H. (1987). Economic Premium Principles in Insurance and the Capital Asset Pricing Model. ASTIN Bulletin, 17(2), 141-150 Note: if extendable to multi-factor models then proceed Internal Rate of Return Method: Feldblum, S. (1992). Casact Vaughn, T. R. Misapplication of Internal Rate of Return Models in Property/Liability Insurance Ratemaking. CASACT Bauer, Daniel, Richard D. Phillips, and George H. Zanjani. (2013). Financial Pricing of Insurance. In: Handbook of Insurance, 627–45. Springer Frees, E. W., Meyers, G. and Cummings, A. D. (2014). Insurance Ratemaking and a Gini Index. Journal of Risk and Insurance 81 (2): 335–366. Wenjun Zhu, Ken Seng Tan & Lysa Porth (2019). Agricultural Insurance Ratemaking: Development of a New Premium Principle, North American Actuarial Journal, 23:4, 512-534 Alternative and Extended Models --> McNulty, G. (2013). Extending the Asset Share Model: Recognizing the Value of Options in P&C Insurance Rates. Casualty Actuarial Society E-Forum Klein, N. et al. (2014). Nonlife Ratemaking and Risk Management with Bayesian Generalized Additive Models for Location, Scale, and Shape, Insurance: Mathematics and Economics, Volume 55, Pages 225-249 Stasinopoulos, D. M., & Rigby, R. A. (2007). Generalized Additive Models for Location Scale and Shape (GAMLSS) in R. Journal of Statistical Software, 23(7), 1-46. Stasinopoulos, D. M., Rigby, B. A., Akantziliotou, C., Heller, G., Ospina, R., & Motpan, N. (2010). gamlss. dist: Distributions to Be Used for GAMLSS Modelling. R package version, 4-0 Prerequisites: Probability Models with Actuarial Applications, R Analysis, Insurance Operations

Personal Finance Bankruptcies and debt collections are accepted as common place in society. In large part, this is due to inadequate financial planning by individuals and businesses. Course serves to prepare the student to deal with a constantly changing economy by having the student: 1) Learn the importance, and have a basic understanding of planning techniques 2) Develop and identify analytical skills, by lecture and class discussion to facilitate effective financial decision-making, including informed decisions regarding budgets, investment, insurance, retirement, and estate planning. 3) Develop technical skills to accommodate priors. 4) The “fiduciary” and its importance to the financial planner; the practical (real world) application of academic information in the financial planning marketplace; and the tremendous impact financial planning has on the lives of individuals. Lecturing Literature --> Charupat, N., Milevsky, M. A. and Huang, H. (2021). Strategic Financial Planning over a Lifecycle: A Conceptual Approach to Personal Risk Management, Cambridge University Press Lab + Homework Text --> Keown, A. (2016). Personal Finance: Turning Money into Wealth Plus, 7/E, Pearson Required Tools and Resources --> Accepted calculator MyFinanceLab PersonalFinanceLab Excel R + RStudio Internal Revenue gov’t agency Department of Labour (provincial and federal) Bureau of census/statistics This course is an introduction to financial planning providing exposure to a broad range of financial planning practice areas. Will also be highly beneficial for management of financial affairs and how to make wise financial decisions. Course Topics --> Topics and activities from the lecturing literature, ranging from Chapter 1 – 12. Lab + Homework --> There will be much effort to competently and fluidly link topics from lecturing literature to the activities from the Lab + Homework text. Expect much use of BOTH MyFinanceLab and PersonalFinanceLab, and the other tools and resources. Refresher Assignments --> Refresher Assignments will compliment homework and labs. Concerns topics from the Theory of Interest for Actuarial Science course Some probability and statistics modelling and computation when the time comes for monte carlo or sensitivity analysis incorporation with course projects. Course Projects --> 1.STRESS TESTING YOUR PERSONAL FINANCES: Will consider synthetic data cases and scenarios. Components of your personal finance portfolio: THE FEATURES: --Liquidity:-> you need to be sure of the liquidity available in your Finances. If tomorrow the regular income stops, how may months’ expenses can be managed sans dipping into the savings. Concerned with only the basic needs and mandatory expenses like sustenance, hygiene, utilities, college dependents, credit cards, car insurance premiums (if relevant), Loan EMIs (say car, home, personal student loan, etc.). Note: rent may be substitute for home loan, and transportation budget may be of concern if no car insurance premiums. Household insurance coverage:-> It’s not only income loss that may bother you. Any major health problem also has potential to put stress on your personal finances. And If it comes along with income loss, just imagine the damage it may give. Insurance premiums are those mandatory and important expenses that you should not even think to discontinue in these times. Health, Life, Personal Accident policies all need to remain active, to take care of any eventuality. Concerned about the risk covers and not the investment policies which may become one of the non-essential investment/expense. Bank balances, cash in hand, Investments in Liquid mutual funds, etc., etc. Make a list of all easy withdrawable Investments (excluding the ones that are kept for long term), employment insurance (if applicable) and calculate, how many months’ expenses are there? Credit cards don’t count. --Asset Allocation:-> though long-term investments should not be considered while reviewing the liquidity profile in your allocation, still liquidity in your Long-term allocation should be observed to manage the third stage of financial stress. This is to manage the situation where your Emergency fund and even insurances are not enough to take care of the crises. If your investments are more into lock-in products like Insurance ULIPs or Endowment Insurances or in some locked in post office savings or Saving bonds or in Real Estate then you may find yourself in a fix in a troubling situation. Be sure to maintain good and liquid asset allocation and invest in (some, not all) products with less or no lock-in. Though you may be told that these products are eligible for loans, but why --Jimmy Funds:-> just Imagine if you have put the major percentage of your investments into Jimmy Funds which have been wound up now. Or have given soft loans to some of your family members or friends by compromising with your liquidity and now they are finding it difficult to repay. What limits are there? Certainty of such (with interest)? Identify models where features (liquidity, asset allocation, jimmy funds) and data can be incorporated towards stress testing. Students will be given various financial settings to implement stress testing. 2. RETIREMENT INCOME PLAN CREATION CHALLENGE --> Students will be assigned this project at a designated time PART A With a Template Start your retirement income plan with one row for each calendar year, with your respective age (and if married spouse’s age) listed next to each calendar year. Extend this projection through life expectancy. Make column headings for each item you will add to it. Use the list below to determine what items to add. I. List fixed Sources of Retirement Income Add columns for each source of fixed income such as: Social Security: exhibit amount beginning in the year/age to begin and continue such life expectancy Spouse’s Social Security: similar as prior, but with consideration of age and/or health difference between mates; upon first death, surviving spouse keeps the larger of their own social security or their spouse. Thus, if one has a shorter life expectancy, your retirement income timeline would only include the larger social security after the expected longevity of the other spouse… Pension: exhibit the amount starting in the year/age of planning to take it. Separate column is used for each source of pension income. If, married, account for the pension survivor option that was chosen. Spouse’s Pension: likewise as prior Annuity: input only if you have an annuity that will pay you guaranteed minimum amount starting at a specific age or date, with the payment continuing for life, joint life, or for a set period of time. Earnings: If you plan on working part-time, input earnings for the year you plan to work. Don't forget, if you take Social Security before full retirement age and have earnings in excess of the earnings limit, your Social Security will be reduced, so you may need to reduce what is in the Social Security column based on your expected earnings. Other: Input any other fixed or regular sources of income such as rental income or alimony or allowances Other Time sources of Income: input expected lump sums, such as life insurance proceeds, an inheritance or net proceeds from the sale of a piece of property. Do not input investment income sources such as dividends, interest, or capital gains. Instead, you will use your retirement income plan to calculate how much you will need to withdraw from your financial accounts. When it comes to withdrawals, check out the 1,000-Bucks-a-Month Rule to reverse-engineer how much you need to save for retirement. Personal investments such as securities, derivatives, gold, mutual funds, Bank CDs, real estate, indexed funds, ETFs, etc. are volatile. Fortunate if you do well; they will also be taxed with gains. II. Add Expenses, Including taxes Next, estimate your total annual living expenses. List items such as a mortgage that may be paid off in a few years in a separate column. In the example at the bottom of the page, you see the mortgage will be paid off halfway through 202X, so that year the total annual mortgage payment is half what it was the year before, and then that expense goes away. Tax rates will vary depending on your total income and deductions. It is best to do tax planning each year to accurately project this. In the example I am using, this person only has IRA savings. Any withdrawal they must take will have to come from their IRA and will be taxable income. They worked with their tax planner, and used their retirement income timeline, to estimate that they would need a gross $xx,000 IRA withdrawal at their age BB, which is their first planned year of retirement. Of that withdrawal, about $PP,R00 will go to taxes. The following year they will have more Social Security income and estimated they would only need about a $AB,000 IRA withdrawal. Their tax planner estimated their tax liability would be about $J,J00 that year. They used that number for the remainder of their projection. III. Calculate the Gap Next, your retirement income plan should calculate the gap, which is a deficit to be withdrawn from savings, or a surplus available to be deposited to savings. In our example add up income sources (Social Security plus pension), then subtract expenses (living expenses, mortgage, and estimated taxes) to get to the -$AB,CDE shown in the first row under the column labelled "Gap". If this "Gap" is a negative number, this is what you would need to withdraw from savings and investments to have your desired retirement lifestyle. If the "Gap" is a surplus then you have enough fixed sources of income to meet your desired retirement lifestyle and could add to savings or possibly spend a little more. This simplistic retirement income plan does not account for inflation or investment returns, but it gives you a starting place; a year-by-year outline of where your retirement income may come from. IV. Once you have this pattern of projected withdrawals you can use it to create an investment plan that is customized to when you will actually need to use your money. NOTE: estate planning may need to be incorporated. V. Will compare results with free, proprietary calculators PART B Metrics to measure retirement preparedness Financial Independence Number Retirement Replacement Ratio Age-Based Salary Multipliers Unit-Benefit Formula Flat-Benefit Formula Net Worth 3. NET WORTH PART A Creating a personal balance sheet and determining net worth. Will be given 3-4 profiles for development. PART B Assume here is that no current black swan events in economy or market results in loss of income. As well, no current major hazards relating to common expenses and premiums hikes (health, auto, home, life, etc.). B1: Based on balance sheet development for assets and income will try to: Identify the most volatile assets on the balance sheet. Risk types: liquidity, interest, credit, volatility, inflation, exchange. Identification or formidable indicators. How can the risks be modelled and measured? Your prerequisites skills will be needed. Sensitivity analysis also expected. Means to hedge and resulting costs. If too high, then what to do with assets constitution being a viable allocation strategy? B2: Based on balance sheet development for liabilities will try to: Identify liabilities likely subject to inflation/increase cost and possibly interest hikes on debt instruments. Identification of formidable indicators. What can be done about it? What do forecasts conveys upon liabilities? Sensitivity analysis also expected. B3. Do assets and liabilities go well together in the long term and short term? Course Grading --> Participation/Discussions – 10% Labs + Assignments – 25% Projects – 25% 2 Exams 40% Prerequisites: Enterprise Data Analysis II, International Financial Statement Analysis II, Theory of Interest for Actuarial Science [or Theory of Interest for Finance (check COMPUT FIN)], Corporate Finance, Mathematical Statistics. Note: the later this course is taken, the better.

Retirement Income Models This course introduces advanced topics in personal finance. Much concentration on the management of uncertainty (randomness) consumers face towards the end of the lifecycle in the areas of longevity, mortality, inflation, investment returns, pensions and income taxes. The environment of this course is interactive and computational. Students will learn how to create R-scripts that optimize and solve real-world retirement income problems. Course Literature (IN UNISON) --> (A) Milevsky, M. A. (2020). Retirement Income Recipes in R. Springer Cham (B) Charupat, N., Milevsky, M. A. and Huang, H. (2021). Strategic Financial Planning over a Lifecycle: A Conceptual Approach to Personal Risk Management, Cambridge University Press (C) Milevsky, M. A. (2006). The Calculus of Retirement Income: Financial Models for Pension Annuities and Life Insurance, Cambridge University Press (D) Milevsky, M. A. (2013). Life Annuities: An Optimal Product for Retirement, CFA Institute Course Tools --> R + RStudio Country Pension Plan Current Income Tax Regulations Federal and Provincial Tax Schedules Historical Returns Database Mortality Tables Database Course Assessment --> Homework Assignments 40% 2- 3 Exams 30% Based on analytical models & their applications Technical Group Project 30% Homework Assignments --> Elements in each homework set Tasks that will help (force) student to familiarize/reinforce development and computational skills in R. It will involve the use of R-scripts and various functions included in the standard package. Tasks from prerequisites. Expect R development to complement such topics. Tasks from course literature (A) and (B). Expect R development to complement such topics. Tasks from course literature (C) and (D). Expect R development to complement such topics. Technical Group Project --> PART A Students will be placed into groups of (no bigger than) three by Week #6. Although the precise topic of the project itself will be discussed and agreed with the instructor, the underlying objective (and deliverable) will be a detailed analysis of a Retirement Income strategy or product. Examples of such products or strategies include, Sustainable Withdrawal Rates, Guaranteed Living Withdrawal Benefits, Tontine Annuities, Mediaeval Corrodies, Income Buckets, Longevity Insurance, etc. The deliverable is a 15-20 page description & write-up. Expect all knowledge and skills to apply. PART B For the course projects 1-3 from prerequisite (Personal Finance particularly) you will be applying advance repetition of particular skills concerning uncertainty or randomness with assets and liabilities. Details will be given. COURSE ELEMENTS --> 1.Background & Social Context Learning Outcome: Students will learn the main challenges facing (elderly) retirees in the 21st century as well as the business opportunities. Book A, Book B chapter 2 & 3 Review the lifecycle model (LCM) Statement of the main challenge. Rational economic theory dictates that a consumer with no labor income (zero human capital value) will want to “smooth” consumption over the remainder of their lifetime, perhaps with some funds setaside for legacy. If the elderly knew (i.) exactly how long they were going to live, (ii.) the real interest rates and investment returns they will earn, (iii.) the income tax rates they will experience, and (iv.) the medical costs they will incur, retirement income planning would be an easy problem to solve. Questions addressed: Assuming that you lived on a distant planet with absolutely no uncertainty or (income taxes) what fraction of your salary should you save at the age of 40, 50 and 60 if you want to maintain and enjoy a relatively constant standard of living over the course of your entire life? What multiple of your salary should be accumulated or stockpiled in your retirement account (nest egg) at the age of 40, 50 and 60 in order to maintain the optimal trajectory? How does the answer depend on whether you plan to retire at age 70 and live to age 90 vs. retire at the age of 80 and live to 100? Of course, I plan to live for a very long time, but the point is to see how the horizon affects (or maybe not) the results. 2.Overview of the R use for this course. Identifying some of the basic R skills required. Charting out the R usage of the course with R packages and functions. 3.Portfolio Longevity Learning Objectives: Understanding the concept of portfolio longevity Book A Longevity of Money. Computing the “ruin time” of an investment portfolio under fixed investment returns and fixed inflation-adjusted withdrawals. A quick review of the time value of money (present value and future value) under a full term-structure (or yield curve) of interest rates. You are 70 years-old with $1,000,000 in an investment account earning 6% compound interest every year, but you are withdrawing and spending $80,000 (i.e. 8% of your initial nest egg) every year. Ignoring income taxes for the moment, how long does the money last? What is the longevity of the portfolio? Now continue to assume that you are earning 6%, but that every year you are withdrawing 8% of the value of the account, in how many years will the account be worth less than $1? What if you increase your yearly withdrawals by an inflation factor (for example 2%)? Now what is longevity of the portfolio? You will continue to learn R-scripts 4.Mechanics of Defined Benefit (SB) pensions Learning Objectives: A detailed understanding of rules governing the Canadian Pension Plan (CPP) with some international comparison. Book A, CPP rules from website Review of the country pension plan (CPP). A short digression to review the current rules regarding eligibility, structure and payout from CPP as well as OAS & GIS claw-backs. Discuss internal rates of return (IRR) as well as subsidies and transfers. Questions addressed: You are a member of a DB pension plan that promises to provide you with a retirement income for the remainder of your life, based on a formula. You contribute 4% of your salary and your employer contributes 6% of your salary to this plan up to $50,000 per year of your salary. The formula stipulates that for every year of work and contribution to the plan you are entitled to 2% of your salary (again, up to $50,000) in the final year of work, but this is capped at 70% of your final salary. The rules can be complicated, but what is the internal rate of return (IRR) from this pension plan if you start contributing at the age of 25, retire at the age of 65 and live to age 95? To what age would you have to live to earn a 4% IRR from you pension? If you work from 20 to 70, then retire and die at 100, would you have been better off investing the money in a savings account earning 1% real (inflation adjusted) interest every year? You will be computing your CPP benefit in R-scripts 5.Implementing non-linear income taxes Learning Objectives: How do income taxes complicate the process of consumption smoothing? Book A, Current Income Tax Regulations Inverting the tax function and the tax treatment of different (retirement) investment accounts, such as RRSPs, TFSA, and fully taxable accounts. The Registered Retirement Income Fund (RRIF) rates and rules. Discussion of taxes due upon death and the single vs. joint problem. Questions addressed: Assume that you have equal amounts of money in three different types of tax-accounts. The first (A) is a fully taxable account in which you pay income taxes on all realized gains. The second (B) is a tax-deferred account. You received a tax deduction when you contributed (added) funds to this account, so when you (eventually) make withdrawals they will be taxed at your marginal tax rate. The third (C) account is a tax-free savings account in which all investment gains aren't taxable and you can withdrawal as much as you want without paying any income taxes. Now assume that you would like to live on a fixed after-tax income every year during retirement. What is the optimal sequence of withdrawals to maximize the longevity (as defined in module #2) of your money? Which accounts do you empty first/last if you want so smooth your retirement income (as defined in module #1)? How exactly does it depend on your marginal tax rate and/or the type of investments you are holding in your taxable account? You will be coding Federal and Provincial tax schedules in Rscript and solving optimization problems. 6.Long-term Investment Returns and Interest Rates Learning Objectives: Intelligent conversation on long-term returns. Book A and historical returns database Discussion and review of historical investment returns from various asset classes to simulate and/or forecast portfolio behavior over the long run. Plausible models for equity and bond returns. Questions addressed: You have $100,000 invested in a stock-index fund and you are adding or saving $1,000 to this account every month. This particular fund has been in existence for 50 years (600 months). What is a reasonable estimate or range for what your investment account will be worth in 5, 10 or 25 years on a pre-tax basis? What will it look like on an after-tax basis and how does it depend on realized vs. unrealized investment gains? What if you diversify your portfolio and add a bond fund to the mix? More importantly, what will the investment account be able to purchase on an after-inflation basis? Given the limited history, how confident can we be with the answer? Simulating asset class returns using R-scripts 7.Reading Session & Strengthening R Skills 8.Simulating Withdrawal Strategies Learning Objectives: In depth understanding of the so-called Sequence of Returns (Sor) risk and the impact on accumulation vs. de-accumulation. Book A Investigating the Sequence of Investment Returns. How long does a portfolio last (in retirement) when investment returns are stochastic? How does the longevity of the portfolio correlate with the realized returns during various sub-periods? How can non-linear instruments (such as put and call options) be used to protect a portfolio in withdrawal mode? Questions addressed: Combine the motivating question from module #2 and module #5. Assume that you retire with $500,000 in an account that is 100% invested in a diversified stock-index fund and you are withdrawing $25,000 every year from this account, adjusted by inflation. The longevity of the portfolio is now random. What is a reasonable estimate or range for how long the money will last? How sensitive is the answer to the (random) investment performance of the account during the first few years? Could the portfolio longevity range be improved if you allocated part of the account to bonds or even to risk-less cash? Are there other ways -- for example using derivative securities such as put and call options -- or techniques to extend the longevity range and life of the retirement account? Monte Carlo simulation using R-scripts 9.Modeling Random Lifetimes Learning Objectives: Understanding & working with randomness in life Book A Understanding Mortality Tables and Longevity Projections. How long do people live? How random (uncertain) is lifetime? What does it depend on? How do statisticians (actuaries) model the remaining lifetime? How has this changed over the centuries? What are the statistical distributions used to analyze mortality and longevity? Questions addressed: The length of human life is (obviously) random and the odds that a 70-year old will survive or live for another 5 years are (much) higher than they are for a 90-year-old. But, what are the probabilities (exactly) and where do they come from? What exactly is a mortality table? Why are there so many of them and why are they outdated? How do I know which one (of the many) to select when reporting survival and mortality probabilities? How do I adjust these numbers for couples and joint-survival probabilities? Download mortality tables from the Society of Actuaries (SoA) and Human Mortality Database (HMD) at Berkley. Basic computations using R-script 10.Continuous Laws of Mortality Learning Objectives: Appreciate the biological and historical basis of various laws that govern human mortality. Implication for pricing Book A and Book C chapter 5 Develop (convenient) approximations to discrete mortality tables. The force of mortality as a force of interest. Introduction to the GompertzMakeham model used for modeling mortality. Contrast with an exponential distribution assumption for future lifetimes. Can life be normal? Why does the Bell curve not work? Questions addressed: Ok, I know how to use a mortality table to compute the odds of dying or living in any given year, but how can I use that table to compute a 65-year-old's expected remaining lifetime? More importantly, since it is obviously random, what is the variance (or standard deviation) of their remaining lifetime? What is more uncertain? Is it your remaining lifetime? Or is it the investment return on your portfolio? How do these concepts relate to the (commonly heard and widely abused) term longevity risk? Are there any (easy) formulas that can be used to compute the mean and standard deviation or the moments of the distribution of remaining lifetime? What will these moments look like for a 65-year-old, but in 10, 20 or 30 years from now? Are there any patterns in the mortality data? Does death follow any rules? I have heard that 50\% of babies born this year will live to the age of 100. What sort of improvement (reduction) in current mortality rates would be required to achieve these probabilities? Fitting various survival curves using continuous approximations in R-scripts. 11.Life Annuities and Life Insurance Learning Objectives: What is the proper price for a pension annuity? Book A and Book D Chapter 1 & 2 Pensions in Discrete and Continuous Time. Advanced Life Delayed Annuities (ALDA), the tax-treatment of annuity income as well as registered and non-registered annuities in Canada. Questions addressed: I am 70 years-old and being offered a so-called (pension) annuity that will pay me 10\% income for the rest of my life, but the purchase is completely irreversible, the product is illiquid and if-and-when I die my heirs will receive absolutely nothing. The money is lost. Is this a fair deal? What mortality (table) assumptions underlie this payout rate? The insurance company is willing to refund the money to my heirs when I die, but that will reduce the payout from 10% (initial) to only 6%? Is that a better deal? Or should I take the higher 10% and use some of the money to purchase life insurance (with a payout to my heirs)? What metric of formula should I use to properly compare all these (pension) annuity options on both a pre-tax and aftertax basis? Why do the payout rates (and taxable portion) differ across companies? Creating R-scripts to price all forms of annuities. 12.Mortality and Longevity Derivatives Learning Objectives: Can a GLWB with synthesized? Book A Pooling of risk. Pricing by equivalence. Reserves and capital requirements. Questions addressed: An insurance company is offering me a (variable annuity) product that appears to combine elements of a mutual fund and life annuity. It is called a Guaranteed Lifetime Withdrawal Benefit (GLWB) and this is how it works: A $100,000 investment can be allocated to a combination of stocks and bonds which will grow (randomly) over time and is completely liquid. Once I reach the age of 65 I can withdraw 5% of the (then) account value for the rest of my life, even if the account is emptied and hits zero. But, if I wait until age 70 the company offers 6% of the account value. Can I manufacture this (derivative) by allocating some of my money to a cheaper mutual fund and part to a life annuity? Should I turn-on the income at age 65 (getting 5%) or wait until age 70 (for the 6%)? More importantly, is it worth paying 100 basis points every year for this option? Using R-scripts to analyze GLWB payouts Prerequisites: Life Contingencies I & II Corporate Risk Management for Non-Life Insurance Course will make use of computation and simulation tools. Specific Learning Outcomes (not necessarily in given order) BUT WILL BE GREATLY ENFORCED: -Identify and explain various interpretations of risk -For each interpretation of risk, understand and be able to calculate various measures of risk -Calculate and interpret characteristics of probability distributions -Conduct and interpret Monte Carlo simulations -Evaluate circumstances under which risk reduction will increase firm value -Interpreting types of Value-At-Risk (VaR), calculation in simple settings, & know the faults -Understand the factors that determine the price of insurance in a competitive market -Construct simulation models to price insurance contracts -Understand contractual provisions in commercial insurance contracts -Understand the types of derivative contracts and how they can be used to reduce risk -ISO IEC 31010:2019 Risk Management — Risk Assessment Techniques Assessment --> Lab Assignments Will incorporate R and Excel 10 Assignments Groups Projects Required tools --> R with RStudio and packages Excel and @RISK software ISO 31000: 2019 (or more modern) Risk Management Techniques Course to make use of various data and financial sources. Course will also make use of balance sheets, income statements, cash flows statements, etc. Journal articles of interest to be introduced at designated times with topics. Course Computational Outline --> A. Introduction to Corporate Risk Management 1.What is risk? 2.The risk management process 3.Objectives of corporate risk management 4.Potential behaviour biases that can impact risk management decisions 5. Decision making with less-than-perfect information B. Probability Distributions and use of R 1.Characteristics of Probability Distributions 2.Covariance and Correlation Includes forms of correlation and appropriate usage 3.Sums of Random Variables 4.Analysing Sums of Random Variables 5.The Normal Distribution 6. EDA & Goodness of Fit Summary Statistics (augmented with skew and kurtosis) Correlation heat maps. Applying the ggpairs() function Box Plot Q-Q plot Advance tests: Chi-Square test, Kolmogorov–Smirnov test, Anderson-Darling, Shapiro-Wilk test MLE and MoM Confidence intervals (not confined to normal) GROUP PROJECT: first assigned groups projects will be based on (A) - (B) C. Reacquaintance Modelling, Simulation with R 1.Historical Simulation 2. Monte Carlo Simulation (towards uncertainty in formulas/models) Basic Modelling Concepts Inputs: constants versus random variables Assigning probability densities to random variables Simulations in RStudio and Excel 3.Expenditure Probabilistic Risk Estimate Eu, Z. (2020). Building a Probabilistic Risk Estimate Using Monte Carlo Simulations. Medium, Analytics Vidhya Such article above can be used to frame expenditure operations for other business types. Will have both Excel and R pursuits. 4.Value at Risk Historical simulation Variance-covariance Monte Carlo Note: applications to be hands-on computational for all priors. For the methods that aren’t monte carlo, concerns and practical resolutions for when data isn’t normal. 5.Conditional Value at Risk (with computational applications) with assumption of non-normality. 6.Stressed Value at Risk (with computational applications) with assumption of non-normality. 7.Niclas, A., Jankensgård, H. and Oxelheim, L. (2005). Exposure-Based Cash-Flow-at-Risk: An Alternative to VaR for Industrial Companies. Journal of Applied Corporate Finance 17, no. 3 (2005): 76-86. Note: compare to VaR methods GROUP PROJECT: second assigned groups projects will be based on (C) D. When does Reducing Risk Increase Value Effect of expected losses on expected cash flows Effect of variability of cash flows on the cost of capital Effect of variability of cash flows on expected cash flows How Taxes can influence risk management decision GROUP PROJECT: third assigned groups projects will be based on (D). E. Investment Decisions 1. Gov’t registries and legal standing 2. Securities exchange, commerce, trade commission: operational standing 3. Insurance Financial Statements and Analysis Basic Horizontal analysis and Vertical analysis methods 4. Financial Ratios (data driven tasks via insurance financial statements) Coverage Ratios, Liquidity Ratios, Solvency Ratios, Profitability Ratios, and Efficiency Ratios. Finding trend in ratios. 5.Tools and techniques to identify possible insurance financial statements fraud: Beneish Model, Modified Jones Model, Dechow F Score, Altman Z Model, Zeta Analysis 6.Off-Balance Sheet notes by insurances 7.Special Purpose Vehicle/Entity (SPV/SPE) Purpose, tactics and deception 8.Capital Budgeting framework and essential features 9.Discount Rate Cost of equity WACC Adjusted Present Value (APV) framework Risk adjusted value (CAPM and multi-factor models). 10.Clark, V., Reed, M. and Stephan, J. (2010). Using Monte Carlo Simulation for a Capital Budgeting Project. Management Accounting Quarterly, Volume 12, Number 1 11.Eu, Z. (2020). Building a Probabilistic Risk Estimate Using Monte Carlo Simulations. Medium Analytics Vidhya Topics will vary 12.Platon, V. and Constantinescu, A. Monte Carlo Method in Risk Analysis for Investment Projects. Procedia Economics and Finance 15 (2014) 393 – 400 Almeida, Heitor, and Thomas Phillippon. "Estimating the Risk-Adjusted Costs of Financial Distress." Journal of Applied Corporate Finance 20, no. 4 (2008): pages 105-109. 13.Penalized Present Value. how to compare to (12) and (13)? 14.Confidence Capital required to be at least 95% sure of having enough for a project (possibly with other ongoing projects)? Amount in reserves needed to be at least 95% sure of covering the risks in business? GROUP PROJECT: fourth assigned groups projects will be based on (E). F. Cost-Benefit Analysis (highly quantitative) 1.Framework analysis of monetised aspects 2.Project-based development (logistics and will be highly quantitative) Means to competently account for costs and benefits Critical values like discount rate Cost of equity, APV, WACC, CAPM, multi-factor models Tools such as RIMS -II, IMPLAN, Chmura, LM3 or REMI may factor in 3. Campbell, H., & Brown, R. (2003). Benefit-Cost Analysis: Financial and Economic Appraisal using Spreadsheets (pp. 194-220). Cambridge: Cambridge University Press 4.Inflationary Environment Velez-Pareja, Ignacio, (1999). Project Evaluation in an Inflationary Environment. Cuadernos de Administracion, Vol. 14, No. 23, pp. 107-130 Velez-Pareja, Ignacio and Tham, Joseph, (2002). Valuation in an Inflationary Environment 5.Sener Salci & Glenn P. Jenkins, 2016. “Incorporating Risk and Uncertainty in Cost-Benefit Analysis”, Development Discussion Papers 2016-09, JDI Executive Programmes. GROUP PROJECT: fifth assigned groups projects will be based on (F). G. Insurance Aspects 1.Purpose of insurance 2.Insurance Rate Making (to be implemented) The following journal article to be analysed, then will investigate the feasibility and practicality. Namely, making the formulas, measures and parameters meaningful from data or computation. We want competent and fluid applicability Williams, C. A. (1954). An Analysis of Current Experience and Retrospective Rating Plans. The Journal of Finance Vol. 9, No. 4, pp. 377-411 (35 pages) Internal Rate of Return Method Feldblum, S. (1992). CASACT Vaughn, T. R. Misapplication of Internal Rate of Return Models in Property/Liability Insurance Ratemaking. CASACT Generalised Linear Models Tober, S. (2020). Basics of Insurance Pricing: With a Quick Intro to GLM Models. Towards Data Science Ohlsson, E. and Johansson, B. (2010). Non-Life Insurance Pricing with Generalised Linear Models. Springer 3.Contractual provisions (deductibles, limits, exclusions) 4.Price Regulation For our purposes we are not concerned with getting poisoned by rough mathematical displays, rather, how development and models are relevant to data for analysis? How will you apply such to the the actual field? Doherty, Neil A. and James R. Garven (1986). Price Regulation in Property / liability Insurance: A Contingent Claims Approach, Journal of Finance, 41, pp. 1031-10 Oh, K., & Kang, H. B. (2004). A Discrete Time Pricing Model for Individual Insurance Contracts. Journal of Insurance Issues, 27(1), 41–65. 5.Claims Valuation and Calculation 6.Estimating Claims Settlement with Generalised Linear Models 7.Occurrence vs. claims made coverage GROUP PROJECT: sixth assigned groups projects will be based on (G). H. Currency Risk 1.For the following journal articles will like to incorporate more modern data and treat other industries as well: Hekman, C. R. (1983). Measuring Foreign Exchange Exposure: A Practical Theory and Its Application. Financial Analysts Journal, 39 Khoo, A. Estimation of Foreign Currency Exposure: An Application to Mining Companies in Australia. Journal of International Money and Finance. Vol 13, Issue, June 1994, Pages 342 – 363 2.For the following literature will focus on development of VaR for multiple currencies in portfolio: Papaioannou, M. (2006). Exchange Rate Risk Measurement and Management: Issues & Approaches for Firms. IMF Working Paper WP/06/255 3.Currency Swaps (definitions and scenarios) Cross-currency coupon swap Cross-currency basis swap GROUP PROJECT: seventh assigned groups projects will be based on (H). I. Weather Risk Instruments Note: will emphasize realistic and practical applications, modelling and operations. Literature for realistic and tangible engagement. 1.Weather Index Insurance For such articles there will be labs to develop and compare with data for chosen environments Taib, C. M. I. C. T. and Benth, F. E. (2012). Pricing of Temperature Index Insurance. Review of Development Finance. Volume 2, Issue 1, pages 22 – 31 Shirsath, P. et al. (2019). Designing Weather Index Insurance of Crops for the Increased Satisfaction of Farmers, Industry and the Government. Climate Risk Management, Volume 25, 100189 Andrea Martínez Salgueiro, (2019). Weather Index-Based Insurance as a Meteorological Risk Management Alternative in Viticulture. Wine Economics and Policy, Volume 8, Issue 2, Pages 114-126 Andrea Martínez Salgueiro, (2019). Weather Index-Based Insurance as a Meteorological Risk Management Alternative in Viticulture. Wine Economics and Policy, Volume 8, Issue 2, Pages 114-126 Boyd, M. et al. (2020). The Design of Weather Index Insurance Using Principal Component Regression and Partial Least Squares Regression: The Case of Forage Crops, North American Actuarial Journal, 24:3, 355-369 GROUP PROJECT: eighth assigned groups projects will be based on (I). J. International Organisation for Standardization - ISO 31000 1.ISO IEC 31010:2019 - Risk Assessment Techniques (RAT) GROUP PROJECT: based on assigned elements in RAT Prerequisites: Enterprise Data Analysis I & II, International Financial Statements Analysis I & II, Corporate Finance, Mathematical Statistics, R Analysis

Resource Software of great interest from the SOA and CASACT: CASACT literature database Actuarial Toolkit Annuity Factor Calculator Relative Risk Tool Retirement Income Calculator Retirement Probability Analyzer Software Additional SOA resources: Disability Morbidity Tables Annuity Valuation Morbidity Table (with ability for standard valuation purposes for individual annuities) Mortality and Claim Utilization rates Financial Impact of Health Plan Provider Network Risk Longevity tool MORT Interest Rate and Equity Generator https://www.actuary.org/content/economic-scenario-generators Pyesg FOR ACTIVITIES IN THE “SUMMER” AND WINTER” SESSIONS ALL PARTICIPATING STUDENTS, ASSISTING/ADVISING INSTRUCTORS AND PROFESSORS MUST BE OFFICIALLY RECOGNISED; REQUIRES BOTH CIVILIAN ID AND STUDENT/FACULTY ID FOR CONFIRMATION OF INDIVIDUAL. THERE WILL ALSO BE USE OF IDENTIFICATIONS FOR ACTIVITIES FOR RESPECTIVE SESSION. SECURITY AND NON-PARTICIPATING ADMINISTRATION WILL ONLY IDENTIFY RESPECTIVE ACTIVITY BY IDENTIFICATION CODE. SECURITY AND NON-PARTICIPATING ADMINISTRATION MUST NEVER KNOW WHAT ACTIVITIES IDENTIFICATION CODES IDENTIFY: < Alpha, Alpha, Alpha, Alpha > - < # # # # # > - < session > - < yyyy > Activities repeated can be added to transcripts upon successful completion. Repeated activities later on can be given a designation such as Advance “Name” I, Advance “Name” II. As well, particular repeated activities serve to towards developing true comprehension, competency and professionalism. It may be the case some activities can be grouped and given a major title together; however, detailed descriptions will be required. ECONOMIC SCENARIO GENERATOR Activity concerns identifying the purpose of an economic scenario generator and developing fluid and tangible logistics towards accomplishing goals. Literature guides --> Wilkie, A.D. (1986) A stochastic investment model for actuarial use. Transactions of the Faculty of Actuaries, 39, 341–403. Wilkie, A.D. (1995) More on a Stochastic Asset Model for Actuarial Use. British Actuarial Journal, 1(5), 777–964 Huber, P. (1997) A Review of Wilkie’s Stochastic Asset Model. British Actuarial Journal, 3(1), 181–210. Ahlgrim, K.C., D’Arcy, S.P. and Gorvett, R.W. (2005) ModeLling Financial Scenarios: A Framework for the Actuarial Profession. Proceedings of the Casualty Actuarial Society, vol. 92, pp. 177–238. Arlington, VA, USA: Casualty Actuarial Society. Bégin, J.-F. (2019) Economic Scenario Generator and Parameter uncertainty: A Bayesian approach. ASTIN Bulletin, 49(2), 335–372. Pedersen. H. et al (2016). Economic Scenario Generators: A Practical Guide. Society of Actuaries: https://www.soa.org/Files/Research/Projects/research-2016-economic-scenario-generators.pdf Conning, “A User’s Guide to Economic Scenario Generation in Property/Casualty Insurance.” Casualty Actuarial Society, CAS Research Papers, 14 Oct. 2020 PART A Concerns assets and financial instruments tied to markets. Will develop multiple portfolios, each constituted by stocks, bonds [both corporate and gov’t (domestic and foreign)], and currencies based on mean-variance, factor models and PCA, respectively, in the R environment. Assumption is that asset allocation and portfolio rebalancing methods will be applied in the future. Each portfolio may have 25 - 50 elements to be realistic. PART B From the given literature there will be analysis followed by logistics for R implementation. Identifying what types of R tools, R programming and R packages will be needed for its development. To analyse the different portfolios for various scenarios. Circumstances may be a single issue, or most often the coupling of multiple issues. PART C Will then make use of the ESG and R package to analyse the different portfolios for various scenarios. Circumstances may be a single issue, or most often the coupling of multiple issues. Compare development with develpment in (B). A “pivoting” task will be determining the ability range of (B) and the ESG R packages compared to Conning’s GEMS® Economic Scenario Generator propiertary software and the given literature guides. Side-side-by-side development would be nice but will not want to exhaust our “change purses”. PART D (pursue development) Whitten, S. and Thomas, R.G. (1999) A non-linear stochastic asset model for actuarial use. British Actuarial Journal, 5(5), 919–953 Chen, W., Koo, B., Wang, Y., O’Hare, C., Langrené, N., Toscas, P., & Zhu, Z. (2021). Using a Stochastic Economic Scenario Generator to Analyse Uncertain Superannuation and Retirement Outcomes. Annals of Actuarial Science, 15(3), 549-566 DYNAMIC FINANCIAL ANALYSIS PART A (portfolio development) A major challenge will be portfolio selection, followed by balancing or optimisation to favourable position before use of DFA. Portfolios need to be of considerable size to make DFA worthwhile. PART B (analysis of given literature) Kaufmaann, R., Gadmer, A. and Klett, R. (2001). Introduction to Dynamic Financial Analysis. ASTIN BULLETIN, Vol. 31, No. 1, pp. 213-249 < https://www.casact.org/sites/default/files/database/astin_vol31no1_213.pdf > D’Arcy, S. P., & Gorvett, R. W. (2004). The Use of Dynamic Financial Analysis to Determine Whether an Optimal Growth Rate Exists for a Property-Liability Insurer. The Journal of Risk and Insurance, 71(4), 583–615. PART C (logistics) Logistics development based on (A) and (B) for R usage. PART D (scenarios) Implementing multiple scenarios in R. ISO 31010 – RISK ASSESSMENT TECHNIQUES (RAT) For various industries in the private sector and elements of the public sector will pursue RAT comprehensively. For any quantitative or computational tools/technique application will not be restrained. RETIREMENT ASSESSMENT PART A (“Universal” Pension Model) International Labour Organisation. Social Protection Department. (2018). The ILO Pension Model: A Technical Guide. ILO, Geneva c2018 Goal: development (logistics and implementation) for ambiance of interest. PART B (Selection and Retirement Outcomes) Bieker, R.F. (2002). Using Simulation as a Tool in Selecting a Retirement Age Under Defined Benefit Pension Plans. J Econ Finan 26, 334–343 Sneddon, T., Zhu, Z. and O’Hare, C. (2016) Modelling Defined Contribution Retirement Outcomes: A Stochastic Approach using Australia as a Case Study. Australian Journal of Actuarial Practice, 4, 5–19 MONTE CARLO AND RATINGS FOR MAJOR SPORTS Capabilities of activity will neither be influenced by local cultural ignorance and stigmas nor by ambiances not of concern to bridge programme. Activity does not encourage intrusive entities due to repulsive cultural habits concerning Trinidad, CC, Africa, Black America and Latin America. Any media developed is not geared to pop culture and minority trends or stereotypes. Activities will be field classified. Particular projects of interest being stationary: Will take on a Mathematica environment and will also develop an R analogy. Will pursue monte carlo for major international leagues in international football, cricket and other possible integrated international sports. Outside of football the technical issue will be acquiring all the crucial statistics into consideration; high level knowledge of sports and sports statistics will be crucial, else monte carlo will be weak. A. Will mainly focus on determining winning probabilities. Some useful literature: Lock, D., & Nettleton, D. (2014). Using Random Forests to Estimate Win Probability Before Each Play of an NFL Game. Journal of Quantitative Analysis in Sports, 10, 197 - 205 Kissell, R. and Poserina, J. (2017). Optimal Sports Math, Statistics, and Fantasy. Academic Press S. E. Hill (2021). In-game Win Probability Models for Canadian Football, Journal of Business Analytics NOTE: much interest in active implementation for ongoing games. PART B B. Elo Rating System Lasek, J., Szlávik, Z., and Bhulai, S., The Predictive Power of Ranking Systems in Association Football, Int. J. Applied Pattern Recognition, Vol. 1, No. 1, 2013 Comprehensive analysis towards and logistics towards its implementation with data. C. Consider the following: Bernard, Etienne (2014). Predicting Who Will With the World Cup with Wolfram Language. Wolfram Blog Bernard, Etienne (2014). World Cup Follow-Up: Update of Winning Probabilities and Betting Results. Wolfram Blog Such blogs are to be analysed, then pursuit of counterpart development in R. Students will be responsible for developing multiple predictions demonstrations for different sports venues. Note: Detailed analysis of programming is mandatory. D. Glicko rating systems Like (B) and (C) there will be analogy for Glicko ratings, and will compared to (B) and (C). Develop a means to assimilate Glicko ratings into computation flow. E. Consider different pro international football leagues, cricket and tennis (ATP). Each likely to have unique means of ratings. Develop a means to assimilate respective ratings into computation flow. A strong background in Probability Theory and R. For R constituents style may vary. Students of interest: Actuarial Mathematics majors, Economics majors, Finance majors, Operations Management majors, Revenue Management majors. CASE STUDIES https://regulation.pstat.ucsb.edu/sites/actprojects/shared_projects.html https://regulation.pstat.ucsb.edu/sites/actprojects/description.html https://www.casact.org/publications-research/publications/cas-e-forum SOA Student Research Case Study Challenge FRAUD DETECTION Applications of interest Election Fraud Scientific Data Economic & Financial Data Financial Reports/Accounting NOTE: applied laws and models will be compared to vertical analysis, horizontal analysis and ratio analysis PART A --> Newcomb-Benford Law (Significant-Digit Law) Students to become acquainted with NBL. Comprehension of its structure, logistics and application to real data. Crucially, it’s for students to comprehend circumstances or conditions of invalidity of NBL through different types of data. Types of data applied will be broad in range to develop robust practice and competence. Will make use use of the R environment. Areas of concern (regardless of given journal article guides beneath): --Hill, T. P. (1995) A Statistical Derivation of the Significant‐Digit Law. Statistical Science 10(4), 354– 363. --Goodman, W. (2016). The Promises and Pitfalls of Benford’s Law. Significance volume 13 Issue 3 pages 38 - 41 --Klaus Henselmann, K., Scherr, E. and Ditter, D. (2012). Applying Benford’s Law to Individual Financial Reports: An empirical investigation on the basis of SEC XBRL Filings. Working Papers in Accounting Valuation Auditing Nr. 2012-1 --Ensminger, J., Gillen, B., Katz, J., Olken, B., & Rangel, A. (2018). Measuring Strategic Data Manipulation: Evidence from a World Bank Project. --Uwe Hassler & Mehdi Hosseinkouchack (2019) Testing the Newcomb-Benford Law: Experimental Evidence, Applied Economics Letters, 26:21, 1762-1769 --Cerioli, A. et al (2019). Newcomb–Benford Law and the Detection of Frauds in International Trade. PNAS vol. 116 no. 1 pages 106 – 115 --Rauch, B., Göttsche, M., Brähler, G. and Engel, S. (2011) Fact and Fiction in EU‐Governmental Economic Data. German Economic Review, 12( 3), 243– 255. --Günnel, Stefan and Tödter, Karl-Heinz, Does Benford's Law Hold in Economic Research and Forecasting? (2007). Bundesbank Series 1 Discussion Paper No. 2007,32. --Cho, W. K. T. and Gaines, B. J. (2007) Breaking the (Benford's) law: Statistical Fraud Detection in Campaign Finance. American Statistician, 61( 3), 218– 223. PART B --> Vertical Analysis (accounting) Horizontal Analysis (accounting) Laws and models to apply comparatively to part A Beneish Model (accounting) Beneish, M. D. (1999). The Detection of Earnings Manipulation. Financial Analysts’ Journal, 55(5): 24-36. Modified Jones Model (accounting) Dechow, P. M., Sloan, R. G., & Sweeney, A. P. (1995). Detecting Earnings Management. The Accounting Review, 70(2), 193–225. Dechow F Score (accounting) Dechow, Patricia & Ge, Weili & Larson, Chad & Sloan, Richard. (2010). Predicting Material Accounting Misstatements. Contemporary Accounting Research. 28(1), 17 – 82 Altman Z Model (accounting) Altman, E., (1968). Financial Ratios, Discriminant Analysis and the Prediction of Corporate Bankruptcy, Journal of Finance, Volume 23, Issue 4, pages 589 – 609 Zeta Analysis (accounting) Altman, E., R. Haldeman, and P. Narayanan, (1977). "ZETA Analysis: A New Model to Identify Bankruptcy Risk of Corporations, Journal of Banking and Finance, Volume 1, Issue 1, 29 – 54 PART C Zipf’s Law (universal) Development and application to various types of data. Will also compare with Newcomb-Benford Law (universal) PART D --> Will likely dive into some machine learning activities for fraud detection. Significantly, understanding how to appropriately implement machine learning techniques with appropriate interpretation of results. A specific field of data may require unique treatment to other fields. Compare with part B and part C. Note: activity is open to mathematics, economics, business, public finance, political science, life sciences, geophysical sciences, chemistry and physics constituents. A high level of statistics and computational software is required to develop anything substantial and credible. PARAMETER UNCERTAINTY Hartman, B.M., Richardson, R. and Bateman, R. (2017) Parameter Uncertainty. Technical report, Casualty Actuarial Society, Canadian Institute of Actuaries, and Society of Actuaries Report. QUANTITATIVE AND STATISTICAL CRIMINOLOGY IN AMBIANCES Activity can provide special invitation for political science, and public administration and operations management constituents. Will have heavy immersion with the R environment PART A Concerning the following paper one to establish comparative model on how crime is measured in the ambiances of interest. James, N. and Council, L. R. (2008). How Crime in the United States Is Measured. CRS Report for Congress. Order Code RL34309 This part also includes developing competent means of database querying, introspection and building via RStudio and DMS (both will be intense). Addresses will be called via syntax commands, with the ability to specify parameters. For official government report structure(s) consider whether or not accuracy varies with likelihood that people will report crimes to police; particularly for murders and rape assault. Consider the possibility as well that theft frequency to be underrepresented because people often will not report minor theft, but over-represent the value of thefts because people don’t always report minor theft. As well, long term analyses of report(s) data may be questionable because computers only have permitted better police record keeping in the last 20 years. Hence, rate of frequencies and value may increase due to improved recording of crimes by police. Can one legitimately refute such rates? PART B Methods for Estimating Crime Rates of Individuals Rolph, John E., Jan M. Chaiken, and Robert L. Houchens, Methods for Estimating Crime Rates of Individuals, Santa Monica, California. RAND Corporation, R-2730-NIJ, 1981 https://www.rand.org/content/dam/rand/pubs/reports/2006/R2730.pdf The above text describes methods for analysing offenders' crime commission data and deriving (1) Individuals' crime commission rates (2) Rate distributions for groups of offenders with specified characteristics. Uncertain data are treated as censored observations, to obtain nonparametric maximum-likelihood estimates of the distribution of observed crime rates. No standard distributional form was found satisfactory for all crime types, and some types apparently do not occur according to a Poisson process. Shrinkage estimators of individuals' crime commission propensities are obtained by dividing offenders into groups and shrinking data toward a regression estimate of an individual's propensity, based on personal characteristics. A new multivariate distributional form for characterizing the joint distribution of individual crime counts is derived and fit to inmate survey data. Populations that can be surveyed (e.g., prisoners) are unrepresentative of target offender populations of primary interest. Sampling probabilities of surveyed individuals are estimated with stochastic models, allowing estimation of crime rate distributions in target populations. Well pursue means of development in ambiances of interest with acquisition of data. Conclusions from data (likely with more modern input) may diverge from paper. PART C For the following two journal articles to have comparative analysis, but with ambiances of interest via acquisition of credible data compatible with modelling and time range; time range likely will be extended to incorporate more modern times. As well, the types of race identified in a respective ambiance may be quite unlike those in the give journal articles, hence resolve such. Note: results due to more modern data may alter conclusions. Steffensmeier, D. J. et al. Age and the Distribution of Crime. American Journal of Sociology, Vol. 94, No. 4 (Jan., 1989), pp. 803-831 Hirschi and Gottfredson. Age and the Explanation of Crime. The American Journal of Sociology, Vol. 89, No. 3. (Nov., 1983), pp. 552-584. The following article to be analysed and statistically verified or disapproved. Britt, C. (1992). Constancy and Change in the U.S. Age Distribution of Crime: A Test of the "Invariance Hypothesis". Journal of Quantitative Criminology, 8(2), 175-187. Above article revolves around the article of Hirschi and Gottfredson prior. Data augmented by modern input for ambiances of interest will influence. Modern Alternative view (required) --> Prieto Curiel, R., Collignon Delmar, S. & Bishop, S.R. Measuring the Distribution of Crime and Its Concentration. J Quant Criminol (2018) 34: 775. Pursue means of acquiring data towards countries used. Develop means of replicating data via probability and statistical skills; then, for ambiances of interest pursue data for such with inclusion of more modern years. Analyse findings. Concerning ambiances of interest with time and data augmented, besides analysis of concentration, are statistical conclusions of distribution involving incorporation of modern data with old harmonious with the prior article? PART D -How to make a thorough criminal background check. Likely will extend beyond national jurisdiction, namely, (which will involve foreign databases, Interpol and Europol). There is no tolerance for censorship to data access and social ideologies. -Main elements of background checks Identity Verification and Personal Information Identity Reports Credit Reports Others Associated with Subject's SSN Residencies (past and current) Names of persons at each address where subject has resided Include spouses, family members, roommates, and live-in lovers Possible Properties Owned by Subject Ambiance or National Death Index Financial Information If you have a judgment or are considering a lawsuit to collect money you are owed, real property - with the exception of exempted real property - vehicles, boats and aircraft, are the easiest to attach. Business Associations & Professional Information An individual's assets are often discovered in the name of a business or partnership. Nationwide & Foreign Property Ownership Records Uniform Commercial Code Filings Personal and business collateral are often provided for loans UCC filings may include name of banks providing loans Deed Transfers Faced with a court ordered judgment, some will transfer threatened property to a relative or friend. Boats and Aircraft Ownership Database provides easy access to National Registrations, State Registrations, Coast Guard Documented Vessels, and Boat Accident Reports from various government agencies. Foreign places as well. Civil Court Records (national and foreign) Lawsuits, Judgments and liens, Bankruptcies Civil and Criminal Courts Search Search all federal courts (all regions). Any one of these records could indicate financial and other difficulties. Criminal Records (national and foreign) Confirm your subject's prior addresses Nationwide Criminal Records Provincial Criminal Records Offender Search Source: Data is provided by each of the provinces. The information contained in each province is compiled from various law enforcement agencies within each jurisdiction. The accuracy and completeness are believed to be as up to date as possible, however the information received should not be construed as 100% exact. Sanctions Databases: HM Treasury, OFAC, EU and UN Not always identical with sanctions Terrorist Listing National, USA, UK, EU, UN Interest groups and public groups Political affiliations Employment type with foreign gov’ts Include the following Confirmation of degree requirements (accredited & preferences) Confirmation of certificates (accredited & preferences) PART E The following article concerns analysis with confirmation of the probability and statistical models applied. However, ambiances of interest to apply and data may be augmented with more recent times with associated data. Hence, conclusions may differ from article. Blumstein, A. and Nakamura, K. (2009). Redemption in the Presence of Widespread Criminal Background Checks. CRIMINOLOGY VOLUME 47 NUMBER 2 One will also likely to compare with models developed from data with actual repeat offenders if able. COMPUTER-ASSISTED ANALYSIS OF MIXTURES PART A: Tangible and practical development Algorithmic approaches for computing the maximum likelihood estimator of the mixing distribution of a one-parameter family of densities and provides a unifying computer-oriented concept for the statistical analysis of unobserved heterogeneity (i.e., observations stemming from different sub-populations) in a univariate sample. The program C.A.MAN (written in FORTRAN77) provides a semiparametric analysis of mixtures of densities with the following main option. Bohning, D., Schlattmann, P. and Lindsay, B. Computer-Assisted Analysis of Mixtures (C.A.MAN): Statistical Algorithms. Biometrics, Vol. 48, No. 1 (Mar., 1992), pp. 283-303 Bohning, D., Dietz, E. and Schlattmann, P. (1998). Recent Developments in Computer-Assisted Analysis of Mixtures. Biometrics 54 , 525 - 536 Bohning, D. (1999). Computer Aided Analysis of Mixtures and Applications: Meta Analysis, Disease Mapping, and Others. Chapman and Hall/CRC Schlattmann, P. (2009). Medical Applications of Finite Mixture Models. Springer. Gu, J. Koenker, R. and Volgushev, s. (2018). Testing for Homogeneity in Mixture Models. Econometric Theory, 34 (4), 850 – 895. Ng, S. K., Xiang, L. and Yau, K. (2019). W. Mixture Modelling for Medical and Health Sciences. CRC Press. Activity may become highly dependent on the programming expertise of computer science constituents. Whereas for others, understanding what and stochastic models/tools are employed; each model or tool will be probed in detail concerning its association in the code. Naturally, will make use of data that’s assumed to be governed by a basic ideal probability model, but the data isn’t idealistic. As well, will make use of the CAMAN package in R and compare with performance of code in FORTRAN and likely C++ as well concerning data and so forth. NOTE: confirm whether there’s also applicability to distributions other than Poisson. If applicable to other distribution types, consider what types of data or applications are tangible and practical to apply. Open to biology, economics, revenue management, operations management and finance constituents. NOTE: will be pursuing real raw data out there. PART B: Field and lab operation -Gupta, C., Gondhi, N., & Lehana, P. (2019). Analysis and Identification of Dermatological Diseases Using Gaussian Mixture Modelling. IEEE Access, 7, 99407-99427. From the given journal one would like to develop the methodology and construct an operating detection system. Will like to invite individuals with dermatology conditions that will not lead to unethical or legal circumstances; a means to test system. -Kim, M. et al. Two Step Gaussian Mixture Model Approach to Characterise White Matter Disease Based on Distributional Changes. Journal of Neurosci Methods. 2016 September 01: 270: 156 – 164 -Boussari, O. et al. (2012). Use of a Mixture Statistical Model in Studying Malaria Vectors Density (Mixture Model for Malaria Vectors Density). PloS one, 7(11), e50452. The above journal article serves an exceptional guide for outdoor/field experimentation. Can be extended to study other types of mosquito-related diseases. CREDIT SCORING Special invitation to Finance, Operations Management and Economics constituents. A credit scoring model is a mathematical model applied to estimate the probability of default, being the probability that customers may cause a credit event (such as bankruptcy, obligation default, payment lapse, and cross-default events). With credit scoring models, the probability of default is conventionally conveyed in the form of a credit score. The higher score implies a lower probability of default. There are various common credit factors in credit scoring models, however different types of loans may involve different credit factors catering towards the loan characteristics. Namely, the credit factors for a credit card loan may include payment history, age, number of account, and credit card utilization; the credit factors for a mortgage loan may include down payment, job history, and loan size. Accurate and predictive credit scoring models aid in maximizing the risk-adjusted return of a financial institution. Yet, markets and consumer behaviour can change rapidly throughout economic cycles, such as recessions or expansions. Hence, risk managers or credit analysts need not only to create the models, but also quickly adjust and validate them. A strong outline or credit score development and management to emulate (with data set subject to change) : Guide to Credit Scoring in R, DS. CRAN R < https://cran.r-project.org/doc/contrib/Sharma-CreditScoring.pdf > Some other techniques applied to produce and validate credit scoring models include: Predictive Analytics Logistic/Probit regression and (multi)linear regression Machine learning Binning algorithm (i.e., monotone, equal frequency, and equal width) For ML expect training sets, test sets and validation, as well as the relevance of the following: Cumulative Accuracy Profile (CAP) Receiver Operating Characteristic (ROC) Kolmogorov-Smirnov (K-S) statistic Activity will not be solely focused on logistic regression and linear regression. The following are additional strong journal articles and texts guides for development and towards compare and contrasts among the techniques in R: --Xie, S. and Thomas, M. Developing a Credit Scorecard. CRAN R [ https://cran.r-project.org/web/packages/scorecard/vignettes/demo.html ] --Bensic, M. Sarlija, N. and Zekic-Susac, M. (2005). Modelling Small-Business Credit Card Scoring by Using Logistic Regression, Neural Networks and Decision Trees. Intelligent Systems in Accounting, Finance and Management 13, 133-150 --Abdou, H, A. et al (2016). Predicting creditworthiness in Retail Banking with Limited Scoring Data. Knowledge-Based Systems 103, pages 89 – 103 --Saberi, M. et al (2013). A Granular Computing-Based Approach to Credit Scoring Modelling. Neurocomputing 122, pages 100 – 115 --Tuffery, S. (2011). Chapter 12, An Application of Data Mining: Scoring. In: Data Mining and Statistics for Decision Making. Wiley Publishing, Pages 555 – 616. Other chapters in text may be vital. --Yap, B. W., Ong, S. H. and Husain, N. H. M. (2011). Using Data Mining to Improve Assessment of Credit Worthiness via Credit Scoring Models. Expert Systems with Applications 38, 13274 – 13283 --Irwin, R. J. and Irwin, T. C. (2013). Appraising Credit Ratings: Does the CAP Fit Better than the ROC? International Journal of Finance & Economics. 18: 396 – 408 --Su, E. and Huang, S. (2010). Comparing Firm Failure Predictions Between Logit, KMV, and ZPP Models: Evidence from Taiwan’s Electronics Industry. Asia-Pacific Finan Markets, 17: 209 – 239 --Khandani, A. E., Kim, A. J. and Lo, A. W. (2010). Consumer Credit-Risk Models via Machine learning Algorithms. Journal of Banking & Finance, Volume 34, Issue 11, pages 2767 - 2787 --Melendez R. (2019) Credit Risk Analysis Applying Machine Learning Classification Models. In: Arai K., Bhatia R., Kapoor S. (eds) Intelligent Computing. CompCom 2019. Advances in Intelligent Systems and Computing, vol 997. Springer, Cham. COMPUTABLE GENERAL EQUILIBRIUM MODELS (CGE) FOR NATURAL DISASTERS (with GAMS) PART A (general development) Burfisher, M. E. Introduction to Computable General Equilibrium Models, (2011). Cambridge University Press. Perali, F., & Scandizzo, P. (2018). The New Generation of Computable General Equilibrium Models: Modelling the Economy. Cham: Springer. PART B (programming and simulation guide) The following text provides guidance for programming and simulation. Hosoe, N., Gasawa, K., & Hashimoto, H. (2010). Textbook of Computable General Equilibrium Modelling: Programming and Simulations. London: Palgrave Macmillan Limited. Chang, G. (2022). Theory and Programming of Computable General Equilibrium (CGE) Models: A Textbook for Beginners. World Scientific. PART C (natural disaster implementation into CGE programming and simulation) GAMS environment interest for development --> Rose, A. et al (2017). Economic Consequence Analysis of Disasters (Integrated Disaster Risk Management). Singapore: Springer Singapore. Rose A., Guha GS. (2004) Computable General Equilibrium Modeling of Electric Utility Lifeline Losses from Earthquakes. In: Okuyama Y., Chang S.E. (eds) Modeling Spatial and Economic Impacts of Disasters. Advances in Spatial Science. Springer, Berlin, Heidelberg Yoshio Kajitani & Hirokazu Tatano (2018) Applicability of a Spatial Computable General Equilibrium Model to Assess the Short-term Economic Impact of Natural Disasters, Economic Systems Research, 30:3, 289-312 Dixon, P. et al. (2017). Economic Consequences of Terrorism and Natural Disasters: The Computable General Equilibrium Approach. In A. Abbas, M. Tambe, & D. Von Winterfeldt (Eds.), Improving Homeland Security Decisions (pp. 158-192). Cambridge University Press. Rose, A. and Liao, S. (2005). Modelling Regional Economic Resilience to Disasters: A Computable General Equilibrium Analysis of Water Service Disruptions. Journal of Regional Science, Volume 45, Issue, pages 75 – 112 Koks, E. E. et al (2016). Regional Disaster Impact Analysis: Comparing Input–Output and Computable General Equilibrium Models. Nat. Hazards Earth Syst. Sci., 16, 1911–1924 Xie, W. et al (2014). Modelling the Economic Costs of Disasters and Recovery: Analysis Using a Dynamic Computable General Equilibrium Model. Nat. Hazards Earth Syst. Sci., 14, 757–772 Verikios, G. Chapter 5: CGE Models of Infectious Diseases: with a focus on Influenza. In: Bryant, T. (2016). The WSPC Reference In Natural Resources and Environmental Policy in the Era of Global Change. World Scientific Note: pursue epidemic or pandemic of interest PART D (ARIO and ARCASDIA-ARI models to develop then fit to events of ambiance of interest) Hallegatte, Stéphane. (2008). An Adaptive Regional Input-Output Model and Its Application to the Assessment of the Economic Cost of Katrina. Risk Analysis 28(3) :779-99 Guan, D., Wang, D., Hallegatte, S. et al. Global Supply-Chain Effects of COVID-19 Control measures. Nat Hum Behav 4, 577–587 (2020) Apply to other contagion as well PART E (compare/contrast to other tools) The following economic assessment tools are also applicable to natural disasters. Compare/contrast with the various prior CGE development Input-Output Model: RIMS -II, IMPLAN, Chmura, LM3 From Rutgers University: R/ECON™ I-O: An Economic Impact Model Simulation Models: General Equilibrium, econometrics, REMI Note: documentation may be necessary to understand such tools before implementing them. HEALTH DECISION SCIENCES WITH R Note: open to Economics and Public Administration students PART A Packages for microsimulation. Note: purpose is to start with some general microsimulation of populations of interest concerning health related issues. -hesim R Package: Health-Economic Simulation Modelling and Decision Analysis Such R package has vignettes to accompany the reference manual -msm R package may also serve well Such R package has vignettes to accompany the reference manual Jackson, C. H. Multi-State Models for Panel Data: The msm Package for R. Journal of Statistical Software, January 2011, Volume 38, Issue 8 -MicSIM R package Sabine Zinn, 2014. The MicSIM Package of R: An Entry-Level Toolkit for Continuous-Time Microsimulation. International Journal of Microsimulation, International Microsimulation Association, vol. 7(3), pages 3-32. PART B Cost Effectiveness Analysis: World Health Organization, Baltussen, Rob M. P. M, Adam, Taghreed, Tan-Torres Edejer, Tessa, Hutubessy, Raymond C. W. et al. (‎2003)‎. Making choices in health : WHO Guide to Cost-Effectiveness Analysis / edited by T. Tan-Torres Edejer ... [‎et al]‎. World Health Organization. Walker D. (2001). Cost and Cost-Effectiveness Guidelines: Which Ones to Use? Health Policy Plan;16(1):113-21 Detsky AS, Naglie IG. (1990). A Clinician's Guide to Cost-Effectiveness Analysis. Ann Intern Med. 1990 Jul 15;113(2):147-54. Sanders GD, Neumann PJ, Basu A, et al. (2016). Recommendations for Conduct, Methodological Practices, and Reporting of Cost-effectiveness Analyses: Second Panel on Cost-Effectiveness in Health and Medicine. JAMA;316(10):1093–1103 NOTE: alternative measures to QALY Carlson JJ, Brouwer ED, Kim E, Wright P, McQueen RB. Alternative Approaches to Quality-Adjusted Life-Year Estimation Within Standard Cost-Effectiveness Models: Literature Review, Feasibility Assessment, and Impact Evaluation. Value Health. 2020 Dec;23(12):1523-1533 Gafni, A. (1997). Alternatives to the QALY Measure for Economic Evaluations. Support Care Cancer 5, 105-111 PART C CEA in R (vignettes accompany manuals for each package) Jalal, H., et al (2017). An Overview of R in Health Decision Sciences. Medical Decision Making, 37(7), 735–746. Krijkamp, E. M., et al. (2018). Microsimulation Modelling for Health Decision Sciences Using R: A Tutorial. Medical Decision Making, 38(3), 400–422. NOTE: in each journal article one must not take for granted the mentioned resources; GitHub is only one of the mentions. dampack: Decision Analytic Modelling Package BCEA: Bayesian Cost Effectiveness Analysis DALY: The DALY Calculator - Graphical User Interface for Probabilistic DALY Calculation in R -rcea: https://hesim-dev.github.io/rcea/ Further assists for some of the packages: Williams C. et al (2017). Cost-Effectiveness Analysis in R Using a Multi-state Modeling Survival Analysis Framework: A Tutorial. Med Decis Making, 37(4): 340-352 Baio, G., Berardi, A. and Heath, A. (2017). Bayesian Cost-Effectiveness Analysis with the R package BCEA. Springer Ideas of Real world Projects: Brenzel, L. (1993). Selecting an Essential Package of Health Services Using Cost-Effectiveness Analysis: A Manual for Professionals in Developing Countries. World Bank Group and Harvard School of Public Health PART D Budget Impact Analysis (BIA) BIAs focus on the financial impact of the new drug or new technology; the value to the overall healthcare system is examined through other economic analyses, such as cost-effectiveness analyses (CEAs). BIA is often a strong supplement to CEA. Mauskopf JA, Sullivan SD, Annemans L, et al. (2007). Principles of Good Practice for Budget Impact Analysis: report of the ISPOR Task Force on Good Research Practices— Budget Impact Analysis. Value Health. 2007;10(5):336-347. Sullivan SD, Mauskopf JA, Augustovski F, et al. (2014). Budget Impact Analysis-Principles of Good Practice: Report of the ISPOR 2012 Budget Impact Analysis Good Practice II Task Force. Value Health 17(1):5–14 Mauskopf J, Earnshaw S. (2016). A Methodological Review of US Budget-Impact Models for New Drugs. Pharmacoeconomics. 2016;34(11):1111–31 Note: R package heemod may serve well. The bimp R package is also possible but it’s not on CRAN. PART E Programme Budgeting and Marginal Analysis (PBMA) An example literature: Edwards, R. T. et al (2014). A National Programme Budgeting and Marginal Analysis (PBMA) of Health Improvement Spending Across Wales: Disinvestment and Reinvestment Across the Life Course. BMC Public Health, 14, 837

UNDERWRITING First and foremost: getting access to a underwriting manual will be a daunting task due to many insurance firms operating in strongly competitive markets. As well, there a various types of insurances to consider, so one manual isn’t necessarily encapsulating. However, it’s still possible to acquire some rough frameworks/guidelines for assessing customers and potential customers. The following R packages will be beneficial: Actuarial (actuar, bootruin, ChainLadder, DCL, FactoMineR, gnm, LDPD, lifecontingencies, LifeInsuranceContracts, queuecomputer, raw, reinsureR, survival) PART A (an inquisition) The following literature serves to be under inquisition. Kluza, J. B., Kraynak, J. F., Treese, W. J. and Wicklund, J. B. (2007). Long Term Care Insurance Underwriting: Building a Risk Scoring Model for John Hancock Insurance & Financial Services. A Major Qualifying Project Report submitted to the Faculty of Worcester Polytechnic Institute: https://digital.wpi.edu/concern/parent/cf95jc89b/file_sets/707959084 PART B (active development) Cummins J.D., Smith B.D., Vance R.N., VanDerhei J.L. (1983) Underwriting Medical Impairments. In: Risk Classification in Life Insurance. Huebner International Series on Risk, Insurance, and Economic Security, vol 1. Springer PART C (further interests) There’s much interest in understanding what quantitative models and formula make such manuals meaningful. The following literature may serve well: Mahler, Howard C. (1987). An Introduction to Underwriting Profit Models, Proceedings of the Casualty Actuarial Society, Volume 71. Pages 239-277: https://www.casact.org/pubs/proceed/proceed85/85239.pdf Chugh, L., Meador, J., & Chatterjee, S. (1987). Determinants of Underwriting Profitability in the Property and Liability Industry. The Journal of Insurance Issues and Practices, 10(2), 1-15. R study notes idea (if not contradictory to prior articles): http://theorem.ca/~csloss/publications/exam_9_notes/Exam+9+Notes+Robbin+D4-D5.html PART D Will like to acquire intelligence on possible technology innovation to assist (not replace) underwriters. Analysis of network development Kareem S. Aggour, Piero P. Bonissone, William E. Cheetham, and Richard P Messmer (2006). Automating the Underwriting of Insurance Applications. AI Magazine Volume 27 Number 3: https://www.aaai.org/ojs/index.php/aimagazine/article/view/1891/1789 Berkovsky, S., Eytani, Y., Furman, E., & Makov, U. (2004). Developing a Framework for Insurance Underwriting Expert system. In: Proceedings of the International Conference on Informatics, ICI 2004, pp. 191 – 197 NOTE: for ambiance one resides will like to identify the constituents, information systems and software tools required for competent integration. How is data coordinated and organised into formats and structure for data analysis and computational purposes? Will be interactive concerning registries, network construction, channels, calls, etc., etc. How do you proceed with he data acquired? PARALLEL IN R AND CONCEALMENT PART A Will serve well towards students in Actuarial Science, Revenue Management, Operational Management, Finance (and possibly of the biological sciences). There will be various tasks incorporating parallelism. Activities of consideration: Evaluation Procedural programming Numerical methods Optimisation Stochastic simulation Various activities with data Advance Algorithms In active operations students will apply their academic experience with R towards parallelism. To provide short presentations on the use of parallelism towards their foundations and interests. Accompanying active operations students to submit two larger unique projects based out of the unique activities above. Students with a solid or strong background with R can take advantage of the opportunity to “expand” on past projects activities done in other courses and activities. Activity assumes at least decent skills in R usage. Example source guides: 1. Schmidberger, M., Morgan, M., Eddelbuettel, D., Yu, H., Tierney, L., & Mansmann, U. (2009). State of the Art in Parallel Computing with R. Journal of Statistical Software, 31(1), 1 - 27. 2. Schmidberger, M. et al, State of the Art in Parallel Computing with R, Journal of Statistical Software, August 2009, Volume 31, Issue 1. 3. Hofert, M., & Machler, M. (2016). Parallel and Other Simulations in R Made Easy: An End-to-End Study, Volume 69, Issue 4. 4. Ostrouchov, G., Chen, W., and Schmidt, D., Parallel Statistical Computing with R: An Illustration on Two Architectures, 61st ISI World Statistics Congress 5. Gerber, F.., and Furrer, R., optimParallel: an R Package Providing Parallel Versions of the Gradient Based Optimization Methods of optim(), The R Journal 6. Mahdi, E., A Survey of R Software for Parallel Computing, American Journal of Applied Mathematics and Statistics, 2014, Vol. 2, No. 4, 224-230 7. https://cran.r-project.org/web/packages/doParallel/vignettes/gettingstartedParallel.pdf 8. eRum 2018 – May 16 – David Smith - YouTube https://www.youtube.com/watch?v=AYld5NYZ0SE&feature=youtu.be PART B Data Concealing Students will apply to pass assignments and projects or new given tasks; will compare unconcealed with concealed to confirm academic integrity in work -Hiding columns -Hide code, text output, messages -Data Anonymization HEDGING WITH REINSURANCE & DERIVATIVES INSTRUMENTS IN THE INSURANCE INDUSTRY --Reinsurance and Reinsurance Pricing (incomplete) https://www.nber.org/system/files/chapters/c7951/c7951.pdf --Derivatives (incomplete) Rahman, H., & Rahmanx, H. (1992). Optimal Hedge Ratios for Property & Liability Insurance Companies. Journal of Insurance Issues, 15(2), 83-96. VALUE, GROWTH AND SUSTAINABILITY WITH TECHNOLOGY Will also be useful to business, public administration and microeconomics constituents. NOTE: process may not be absolutely a “top-down” flow evaluation, namely, developing a rubric to serve well; the “top-down” processing may lead to some extremely conservative stances, however, understanding that not all risks can be eliminated in the real world; interestingly, a major driver of advancement, new markets, options, production, etc., etc. NOTE: will have competing products/technologies In various industries of business and the public sector one often hears that to be legitimate or credible use of the following gaudy products are necessities: IBM, SAP, Oracle, Microsoft, etc. etc. etc., etc. Open source is also a competitor. Applying fields: Government, Human resources, Finance, Accounting, Budgeting, Analytics, Manufacturing, Service, etc. etc. STRATEGY AND PLANNING PROCESS --> 1. Discern the various elements and questions related to workplace technology 2. Create a strategy for technology planning 3. Decide on technology plans and how to choose technology. Note: must include 5C Analysis implementation for options. Develop Trend observation. Note: must include financial analysis for options, plus Beneish, Dechow and Altman Z. Develop trend observation in all such. Note: [PESTEL/SWOT for competing firms 4. Cybersecurity scheme subjugating/constraining priors Note: for steps 1 - 4 the following literature provides guidance for different industries with technology integration -> *Quinn, S. D. et al (2018). National Checklist Program for IT Products – Guidelines for Checklist Users and Developers. NIST Special Publication 800-70 Revision 4 *Information Technology Investment Management: A Framework for Assessing and Improving Process Maturity. GAO March 2004 Version 1.1 GAO-04-394G *National Centre for Education Statistics – Forum Unified Education Technology Suite: https://nces.ed.gov/pubs2005/tech_suite/index.asp *Health & Human Service ECLKC: https://eclkc.ohs.acf.hhs.gov/organizational-leadership/article/whats-involved-technology-planning *Campise, J. A. (1972). Choosing a Computer System for Project Management. Project Management Quarterly, 3(4), 13–16. *Bhangoo, T. (2020). How To Select The Right Technology Solution: Five Strategies For Leaders. Forbes Note: groups may be given sets of technologies products concerning a particular sector of non-profits, to gather intelligence and analyses towards choice selection. PRELIMINARY DASHBOARD DEVELOPMENT BEFORE STRATEGY AND PLANNING PROCESS --> What is the purpose of your firm? What are your areas of commerce? Your business is a system, or part of a system. What are the distribution channels? What are the critical associated needs for your commerce or communications? How is data relevant or crucial to the prior questions, and what such data types are there? What goals or operations must your firm complete in the short term and long term? Stimuli for change (operational, systematic, environmental) relevant to firm goals. Technology trends (in favour of or not) and forecasting product’s industry How does one get access to practical and concise demonstrations of products, services in the real world? How does one determine whether a platform, product or service is practical and tangible for their firm? What are you getting into? How does one forecast or understand emerging innovation? How is such relevant to you? How will the considered technology/innovation affect firm structure in regard to required skills, sizes of firm sectors and daily labour hours? Firm optimisation. What aspects? Premature gauging of costs before assimilation or function of the technology Consultation costs Purchase & integration costs Influence on Personnel Training costs Operating costs (include subscription contracts and expected utility bills) Possible environmental and taxation incentives Influence of technology on Distribution Channel(s) and Operations. Influence of technology on Strategy Fundamentals and Corporate Strategy. What are the economic advantages and disadvantages in all aspects? Profitability ratios, efficiency ratios and solvency ratios of competing firms; establish historical trends as well. Beneish, Dechow, Altman Z Score, Zeta Analysis, and probability of default based on equity (via Merton’s model) Note: pursue trends for all SWOT for competitor companies and products/portfolio In markets Standing with government agencies Better Business Bureau, Federal Trade Commission (provincial, national and international), Consumer Product Protection, Commerce, National Security, Intellectual Property Legal quandaries and actions records Security profiling and Planning (internal) Customer Support Longevity & Upgrades potential Downtime and failures – Understanding their true costs Maintenance and product/service assistance Enterprise risk assessment Review prior 3 and systems components of relevance Reiterating security policies Life Cycle Assessment Operating or expected finance from all prior Options with budget based on all prior analyses Cost-Benefit Analysis DEPOSIT INSURANCE Comprehension and implementation of tools for deposit insurance. Will be highly data driven PART A (General) Augment with more modern data as well O’Keefe, J. P. and Ufier, A. B. Determining the Target Deposit Insurance Fund: Practical Approaches for Data-Poor Deposit Insurers. FDIC CFR WP 2017 – 04 Bretschneider, B. and Benna, R. (2017). Risk-Based Premium Models for Deposit Insurance Systems. World Bank Group Note: will also be fitting various banks to such modelling from literature. PART B (Credit Risk approach) Bennett, R. L. (2001). Evaluating the Adequacy of the Deposit Insurance Fund: A Credit-Risk Modelling Approach. Federal Deposit Insurance Corporation Working Paper 2001 – 02 Maccario, A., Sironi, A. and Zazzara, C. (2003). Applying Credit Risk Models to Deposit Insurance Pricing: Empirical Evidence from Italian Banking System., Federal Deposit Insurance Sironi, A. and Zazzara, C. (2004). Applying Credit Risk Models to Deposit Insurance Pricing: Empirical Evidence from the Italian Banking System. J Bank Regul 6, 10–32. Note: will also be fitting various banks to such modelling from literature. PART C (Pricing) Flood, M. D. (1990). On the Use of Option Pricing Models to Analyse Deposit Insurance. Economic Research, Federal Reserve Bank of St. Louis. Volume 72 Number 1 Ronn, E., & Verma, A. (1986). Pricing Risk-Adjusted Deposit Insurance: An Option-Based Model. The Journal of Finance, 41(4), 871-895 Risk Measures Used to Determine Risk‐Based Premium Rates for Banks with Assets Less than $X (and Greater than X). Will be fitting various banks to such. STRESS TESTS FOR DEFINED PENSION PLANS Adjust to ambiance and financial institutions of interest Impavido, G. (2011). Stress Tests for Defined Benefit Pension Plans – A Primer. IMF Working Paper WP/11/29 James Farrell, J. and Shoag, D. (2016). Simulating Public Pension Funding Stress with Realistic Shocks. Harvard Kennedy School RWP16-053 REGULATION TOWARDS FIRMS (to implement) Will consider ideal firms and identify laws/regulation to apply (for domestic and foreign cases) -> OECD international Standard Cost Manual: https://www.oecd.org/regreform/regulatory-policy/34227698.pdf

WEATHER RISK INSTRUMENTS Note: will emphasize realistic and practical applications, modelling and operations. Literature for realistic and tangible engagement. PART A. Weather Index Insurance For such articles there will be labs to develop and compare with data for chosen environments Taib, C. M. I. C. T. and Benth, F. E. (2012). Pricing of Temperature Index Insurance. Review of Development Finance. Volume 2, Issue 1, pages 22 – 31 Shirsath, P. et al. (2019). Designing Weather Index Insurance of Crops for the Increased Satisfaction of Farmers, Industry and the Government. Climate Risk Management, Volume 25, 100189 Andrea Martínez Salgueiro, (2019). Weather Index-Based Insurance as a Meteorological Risk Management Alternative in Viticulture. Wine Economics and Policy, Volume 8, Issue 2, Pages 114-126 Boyd, M. et al. (2020). The Design of Weather Index Insurance Using Principal Component Regression and Partial Least Squares Regression: The Case of Forage Crops, North American Actuarial Journal, 24:3, 355-369 PART B. Weather Derivatives For such articles there will be labs to develop and compare them involving data of consideration for chosen environments. Example: Muller, A. and Grandi, M. (2000). Weather Derivatives: A Risk Management Tool for Weather-Sensitive Industries. The Geneva Papers on Risk and Insurance Vol. 25 No. 2 273 – 287 CUSTOMER LIFETIME VALUE (OPEN TO REVENUE MANAGEMENT CONSTITUENTS) Note: also open to Actuarial students 1. Customer Segmentation Customer Segmentation Models Customer Segmentation with R Chapman, C., Feit, E.M. (2019). Segmentation: Clustering and Classification. In: R For Marketing Research and Analytics. Use R!. Springer, Cham. Dolnicar, S., Grun, B. and Leisch, F. (2018). Market Segmentation Analysis: Understanding It, Doing It, and Making It Useful. Springer 2. CLV Rundown -Customer Lifetime Value - Wikipedia -References for CLV --> Berger, P. D. & Nasr, N. I. (1998). Customer Lifetime Value: Marketing Models and Applications. Journal of Interactive Marketing. 12 (1): 17–30 Fader, P. S. et al (2005) RFM and CLV: Using Iso-Value Curves for Customer Base Analysis. Journal of Marketing Research: November 2005, Vol. 42, No. 4 Gupta, S. (2006). Modelling Customer Lifetime Value. Journal of Service Research, 9(2), 139-155 Jasek, P. et al (2018). Modelling and Application of Customer Lifetime Value in Online Retail. Informatics 2018, 5, 2 Jašek, P. et al (2019). Comparative Analysis of Selected Probabilistic Customer Lifetime Value Models in Online Shopping. Journal of Business Economics and Management, 20(3): 398-423 Calciu, M. (2008). Numeric Decision Support to Find Optimal Balance Between Customer Acquisition and Retention Spending. J Target Meas Anal Mark 16, 214–227 -Investigation Comparative assessment of the various literature prior to the following: OWOX, M. (2019). 5 Simple Ways to Calculate Customer Lifetime Value, Medium Which is more practical and robust? 3. Predicting CLV Gauthier, J. (2017). An Introduction to Predictive Customer Lifetime Value Modelling. Oracle AI & Data Science Blog Hariharan S. (2020). A Definitive Guide for Predicting Customer Lifetime Value (CLV) - Analytics Vidhya Google Guide --Predicting Customer Lifetime Value with AI Platform: https://cloud.google.com/ai-platform/docs/clv-prediction-with-offline-training-intro 4. CLV specific R package CLVTools R Package Reference manual and vignette for CLVTools Vignettes How does structure in 2 and (3) translate to this R package? Estimating individual Customer Lifetime Values: the CLVTools Package – YouTube 5. Misuses and Downsides with CLV 6. Heterogeneity --> Calciu, M. (2009). Deterministic and Stochastic Customer Lifetime Value Models. Evaluating the Impact of Ignored Heterogeneity in Non-Contractual Contexts. J Target Meas Anal Mark 17, 257–271 Fader, P. S. and Hardie, B. G. S. (2010). Customer-Base Valuation in a Contractual Setting: The Perils of Ignoring Heterogeneity. Marketing Science, Vol. 29, No. 1, pp. 85–93 7. Clusters --> Shih, Y., Liu, C. (2003). A Method for Customer Lifetime Value Ranking — Combining the Analytic Hierarchy Process and Clustering Analysis. J Database Mark Cust Strategy Manag 11, 159–172 Zare Hosseini, Z., & Mohammadzadeh, M. (2016). Knowledge Discovery from Patients' Behavior via Clustering-Classification Algorithms Based on Weighted eRFM and CLV Model: An empirical study in public health care services. Iranian journal of pharmaceutical research: IJPR, 15(1), 355–367. 8. Customer Acquisition Cost (CAC) Following detail comprehension will be applying formulas to calculate CAC. I. The basic method: Numerator: Total marketing cost for acquiring customers (not regular customers): Denominator: Total customers acquired II. Operational sensitivity in formulation: Apart from costs incurred in marketing, there’s other costs due to tools, various labour, etc., etc. III. Numerator constituted by sum of: Total marketing cost for acquiring customers (not regular customers) Wages connected with sales and marketing All the marketing and sales associated software cost (inc. E-Commerce-Platform, automated marketing, A/B-testing, analytics etc.) Every additional professional service in marketing / sales (Designer, consultant, etc.) Other overheads associated with marketing and sales IV. Denominator: Total customers acquired V. Customer acquisition costs in relation to customer lifetime value: Recall purpose of CLV Ratio of CLV to CAC Toxic {< 1:1} Bad {1:1 to < 3:1} Healthy {3:1} Dreamer {> 3:1}

DATA ENGINEERING PROGRAMME This is not a computer science science major. When there are things to be done....to be done with strong relevant skills. There’s no interest in taking students for a ride nor them getting aboard a track just to jackknife for a train wreck. Brain cells are precious and academics should not be made into OD drugs; object-oriented programming, analysis of algorithms and such sorts are not acceptable here. The Data Engineering programme: --Foundation Courses Scientific Writing I & II; Calculus for Business & Economics I-III; Probability & Statistics B; Mathematical Statistics --Mandatory Commerce Courses Enterprise Data Analysis I & II (Check FIN); International Financial Statement Analysis I & II (check FIN); Intro Macroeconomics (check ECON); Intermediate Macroeconomics (check ECON) --Data Science Necessities Geographic Information Systems; R Analysis (check Actuarial); Introduction to Data Science; Advanced Data Science; Data Integrity & Debugging in Data Science --Data Engineering Foundation Necessities Intro to Database Concepts; Intermediate SQL; NoSQL Databases; Advance Topics in SQL; Advance NoSQL; Database Security; Database-Driven Web Sites; Extendable Markup Language; Application Programming Interfaces Introduction to Database Concepts This course will provide an introductory look at database concepts, emphasizing the relational database model. The course will also illustrate concepts and application of the entity relationship diagram as well as the principles and application of normalization. The student will understand the use of structured query language (SQL) to extract information from the database. We will also take a broad overview at some advanced databases topics such as, Web Database Development, Data Warehouses and Database Administration. Upon completion of this course, learners should be able to: Describe the reasons and purpose of using a database Explain the conceptual foundation of the relational model for databases Demonstrate basic SQL statements for creating, querying, modifying and deleting data from a relational database Discuss the basic stages of database development and the role of the data model. Describe basic database design principles Explain the need for and importance of database administration and the need for security, backup and recovery Describe Web database processing Describe the basic concepts of data warehousing, OLAP, and data mining. Required Texts --> Kroenke, D. M., and Auer, D. J., (2013). Database Concepts (6th ed.). Pearson Prentice Hall Required Resources --> Student Data Files for the 6th edition of the textbook at: http://www.pearsonhighered.com/kroenke/ Technology Tools --> Microsoft Access Microsoft Visio Course Sequence --> Chp: 1-2, 4 then 3, Appendix E (online), 5, 6, 8, then 7 Assessment --> MS Access Assignments (5) 40% 1. MS Access Exercise – Create a Database 2. MS Access Exercise – Create a Database (more advanced things) 3. MS Access Exercise – SQL Queries 4. MS Access Exercise – Add database tables & update the Entity- Relationship Diagram 5. Will be given “raw” data to make spread sheets. Augmented by construction of additional columns from elder columns. As well, merging Excel files appropriately. Then incorporation into MS Access towards evaluation based on all prior MS Access Exercises. Entity Relationship Diagram 5% Projects with MS Access & SQL 25% (based on knowledge and experience from assignments) Campus Data Development (individuals in data will not be personally identified) Gov’t Data (Labour, Economic Statistics Bureau, Census, Surveys, etc.) 3 Exams 30% Analytics + Hands-on Tasks Attendance service as a pass/fail instance valuation, namely, 1 or 0 for a certain amount of absences and/or tardiness. Prerequisite: Enterprise Data Analysis II Intermediate SQL Topics covered include: Entity-Relationship modeling, the Relational Model, the SQL language: data retrieval statements, data manipulation and data definition statements. All interactive reading problems involve the use of "live" SQL. Homework will be done using databases running in PostgreSQL which students install on their machines. Note: students develop a real-world database project using PostgreSQL during the course. Course Objectives: Learn structured query language (SQL) to an intermediate/advanced level. Be able to write data retrieval queries and evaluate the result set. Be able to write SQL statements that edit existing data. Be able to write SQL statements that create database objects. Comprehend nd the structure and design of relational databases. Comprehend the importance and major issues of database security and the maintenance of data integrity. NOTE: will have 4-5 PostgreSQL Immersion Lab Sessions; unique to general labs assignments. Learning Text --> An Interactive SQL online learning programme Software for students to install --> PostgreSQL literature NOTE: PostgreSQL is the flagship tool for this course. Assessment --> Will have some prerequisite assignments and projects as HW (but will not undermine heavy immersion into PostgreSQL) Homework assignments based on this course level with extensive use of PostgreSQL will be assigned in a series of assignments. Homework will be submitted via the interactive SQL material. A grade and feedback will be provided on each homework assignment. PostgreSQL Lab Assignments Project: a project will be developed by students during the course. The project is an opportunity to exercise the knowledge and skills learned in the text and homework in a creative/constructive manner. Note: students develop a real-world database project using PostgreSQL. Grade Breakdown: HWs 50% PostgreSQL Lab Assignments 30% Term Project 20% PostgreSQL Immersion Lab Sessions. Competence and completion timing as a course pass/fail instance valuation, namely, 1 or 0. Attendance and completion timing with online activity as a course pass/fail instance valuation, namely, 1 or 0. Prerequisite: Introduction to Database Concepts NoSQL Databases This course will cover the design and implementation of NoSQL databases. Students will manage database structures; understand basic NoSQL data-management concepts; create and manipulate NoSQL database objects using scripts; model logical data requirements using entity-oriented techniques; transform a logical data model into a database structure. Course will emphasize practical and sustainable/recyclable development. NOTE: will have 4-5 Opensource NoSQL tool immersion Lab Sessions; unique to general labs assignments. Learning Text --> An Interactive NoSQL online learning programme Software for students to install --> Open source NoSQL literature (Apache application or MongoDB) Assessment --> Will have a few prerequisite assignments Homework + Quizzes based on NoSQL Labs will be tangible and practical w.r.t. course topics. Lab will be sustainable and recyclable. NoSQL open source tool Immersion Sessions for Certificate(s) of Accomplishment R INTEGRATION -Concerns competent integrating of R with NoSQL databases -R packages of interest: NoSQL Interface/integration with R environment Tidyverse, Tidymodels, Caret Concerns Exploratory Data Analysis and Data Science -Introspection, Imports, Data Wrangling, Exploratory Data Analysis Project: a project will be developed by students during the course. The project is an opportunity to exercise the knowledge and skills learnt in the course in a creative/constructive manner. Note: students develop a real-world database project using a NoSQL open source tool. OUTCOMES: Install, configure, and administer a NoSQL database Create, configure, and manage database structures, including indexes, collections, documents and users Administer database recovery and backup Create and manipulate NoSQL database objects using scripts Model logical data requirements using entity-oriented techniques Understand basic database security with NoSQL database Comparative structure to SQL/RDMS throughout course (advantages and disadvantages). To recognise and appreciate the value/economics of NoSQL. TOPICS: NoSQL DB Installation Introduction to NoSQL Basic NoSQL Query Language Advanced NoSQL Query Language Entity Relation Design and Index NoSQL for Software Developers Data Aggregation Framework Basic and Advanced Data Aggregation Aggregation Performance and Pipeline Optimization Database configuration Basic replication concepts and security Database Testing (functional testing, compatibility testing, load testing, and regression testing) R integration Prerequisite: Intermediate SQL. Fair assumption with no withdrawing of such assumption that students have AT LEAST successfully completed Probability & Statistics; will not ask. Advanced Topics in SQL This course is broad and practical, covering indexes, transactions, constraints, triggers, views, authorization and testing, all in the context of relational database systems and the SQL language. This course concerns students advancing their understanding and use of relational databases. Note: course will be 18 weeks (2 hours per session & 2-3 sessions per week). NOTE: PostgreSQL is the flagship tool for this course. Assessment --> Theoretical Content 10% Prerequisite Assignments (assignments and projects) 20% Labs 30% Problem Analysis (involve language code activities and data) 20% Solution Design and Verification 20% INDEXES & TRANSACTIONS Covers two important features of database systems from the application-builder's perspective: indexing for increased performance, and transactions for concurrency control and failure recovery. CONSTRAINTS & TRIGGERS Explains key, referential integrity, and "check" constraints, followed by comprehensive coverage of database triggers. VIEWS & AUTHORIZATION Extensive coverage of how database views can be created, used, and updated, and introduces standard techniques for authorization in relational databases. DATABASE TESTING Database testing is a process used to ensure the accuracy and completeness of data in a database. Functional testing, compatibility testing, load testing, and regression testing. R INTEGRATION -Concerns competent integrating of R with PostgreSQL. -R packages of interest: RPostgreSQL and RPostgres both provide fully DBI-compliant Rcpp-backed interfaces to PostgreSQL. rpostgis provides the interface to its spatial extension PostGIS. RGreenplum provides a fully DBI-compliant interface to Greenplum, an open-source parallel database on top of PostgreSQL. -Imports, Probing, Data Wrangling, Exploratory Data Analysis - Boruta, FSelectorRccp, Tidyverse, Tidymodels Concerns for Data Science Prerequisite: Intermediate SQL. Fair assumption with no withdrawing of such assumption that students have AT LEAST successfully completed Probability & Statistics; will not ask. Advance NoSQL Course has two purposes for student development 1. Reinforce knowledge and skills from prerequisite. 2. Introduce advance topics with practical and sustainable activities Assessment --> Will have prerequisite assignments Homework + Quizzes based on NoSQL Labs will be tangible and practical w.r.t. course topics. Lab will be sustainable and recyclable. NoSQL open source tool Immersion Sessions for Certificate(s) of Accomplishment R INTEGRATION -Concerns competent integrating of R with NoSQL databases -R packages of interest: NoSQL Interface/integration with R environment Tidyverse, Tidymodels, Caret Concerns Exploratory Data Analysis and Data Science -Imports, Data Wrangling, Exploratory Data Analysis Project: a project catering for advanced topics will be developed by students during the course. The project is an opportunity to exercise the knowledge and skills learnt in the course in a creative/constructive manner. Note: students develop a real-world database project using a NoSQL open source tool. Prerequisite: NoSQL Databases Database Security NOTE: this is a laboratory course. The course provides a strong foundation in database security and auditing. This course utilizes - A) PostgreSQL B) Proprietary comparative counterpart to (A) C) NoSQL tool D) Security Testing Tools (SQL and NoSQL) The following topics are covered: security, profiles, password policies, privileges and roles, Virtual Private Databases, and auditing. The course also treats topics such as SQL/NoSQL injection, securing the DBMS, enforcing access controls, and APIs. OBJECTIVES: The objective we share in this course is that each student understand the application of security concepts to database technology and demonstrate the ability to work hands-on. Specific topic objectives in this course are: · Understand the fundamentals of security, and how it relates to information systems · Identify assets in your organization and their values · Identify risks and vulnerabilities in operating systems from a database perspective · Learn good password policies, and techniques to secure passwords in your organization · Learn and implement administration policies for users · Use SQL and NoSQL environments to create policies, profiles and roles · Understand the various database security models and their advantages or disadvantages · Learn how to implement a Virtual Private Database using views, roles, and application context · Gain an overview of auditing fundamentals, and create your own auditing model · Learn the purpose and use of data dictionaries, encryption and SQL/NoSQL injection · Explore an interesting research topic of your choice related to database security Course Literature (PostgreSQL and proprietary counterpart; NoSQL counterparts): Texts/literature (professional publishers, national gov’t agencies, IGOs) to concern the following topics -- Database Security and Auditing Protecting Data Integrity and Accessibility NOTE FOR DBMS: -The DBMS you use for this course must be available to you at any time you need. You will need complete control of the database to work on this course because database security is a database administrator level job. This usually means that you should not use an employer’s DBMS. Assessment: Homework 10% Quizzes 10% Labs 30% 2-3 Exams 30% Term Project 20% Course Topics: -Security Concepts -Security Architecture -Operating Systems Security -User Creation & Administration -Profiles, Passwords, Privileges, and roles -Security Models for Database applications -Virtual Private Databases -Database Auditing Models -Application and Data Auditing -Auditing Database Activities -Security and Auditing Project Cases -Encryptions Note: will not lavish in a mathematical swamp. Rather focusing on concepts, structure, applications, logistics and implementation. Concerning the applied encryptions, if asked to implement on and test for various asset types of interest (at least 15-20), will you be able to do so in 30-45 minutes minimum? We’re dealing with commerce and business. -Advance topics Laboratory Operations: Labs will be based on all course topics. All labs will be task oriented and hands-on; following analysis and logistics. In many cases prior labs will be precursors or augmentations within later labs. There will be various assets applied, such as document types, file types, web spaces, directories, communication methods and databases. Do you make your own encryptions or apply market tools (proprietary and/or open source)? Exam Elements: Exams will incorporate the other following course assessment features: Homework Quizzes Labs Elements of prior exams (for the second and third exam) Project Evaluation Criteria: The term project should explore or present original material in database security. You may choose your own project topic or choose from a selected topic. We will be discussing project topics in class, after which you will submit the topic you want to explore. Project topics are subject to instructor approval. The following characteristics will be used to grade the term project: · Application of basic security concepts to the specific topic · Demonstrated understanding of technologies involved · Proper academic formatting including table of contents, abstract, · Describe methodology · Comprehensiveness and depth · Demonstrates technology · Breach & Attack (open source) simulator applications Idea, structure, objective(s), results & analysis Hands-on demonstration as part of presentation · Regulations and standards (national governance and IGOs) · Helpful contrasts · Coherent · References in proper format · Presentation Prerequisites: Advance Topics in SQL; Advance NoSQL Database-Driven Web Sites This course concerns development of dynamic Web applications that interact with a database using server-side scripts and server programs. The material covered includes database fundamentals, server-side scripting language functions for database manipulation and server considerations. Course Objectives: · Develop an understanding of relational database concepts and design principles. · Develop an understanding of basic and advanced SQL statements. · Apply the PHP server-side scripting language and PostgreSQL database management system to the creation of dynamic web site applications. · Understand and implement realistic PostgreSQL/PHP web applications. · Use the Web effectively to locate reference and tutorial resources for PostgreSQL and PHP ASSESSMENT: A. Theoretical Content 20% Introduction to “data structures” and their implementation in a database management system. Topics include data models. Models include but are limited to hierarchical, network and relational data models. Normal forms of data, data description languages and query are also discussed. B. Problem Analysis 25% Emphasizes problem analysis in the areas of programme development of databases. Students learn how to create PHP or other current database language code to describe a solution to a problem, select appropriate data types, and test the resulting program. C. Solution Design 25% Requires students to produce a number of programmes that lead to a design solution for a programming problem. Each program is entered and modified to achieve a desired result. D. Labs 30% COURSE OUTLINE – Major Content Areas: · Review: the PostgreSQL database server; creating and querying databases, the basic concepts · Identifying database anomalies, normal forms and other database basics · Building PostgreSQL tables with the Structured Query Language · Extracting database information with PostgreSQL selects and functions · Working with multiple tables using joins and unions · PHP server-side scripting language · Working with PHP variables, operators, control structures, and functions · Writing readable, maintainable PHP code · Using object-oriented techniques in PHP · Performing simple and advanced database operations with PHP scripting · Using PHP built-in functions · Creating user-defined functions in PHP · Implementing simple PostgreSQL/PHP applications: e.g., a guestbook and a survey · Developing more sophisticated PostgreSQL/PHP applications: e.g., a catalog, a content manager, a threaded discussion, a problem tracking system, and a shopping cart. · Creating HTML forms LABORATORY PROJECTS: Labs include a number of different database and PHP projects. PHP projects are taken from the following list: · Generic dynamic Web sites · Social Networking Site · Blog/Discussion forum · E-commerce Site · Content management system · News site Prerequisite: Advanced Topics in SQL, Advance NoSQL Extendable Markup Language This course will introduce Extensible Markup Language or XML. Course will treat the importance of XML in the storage, transportation, and use of data, with particular focus on its use in libraries and other cultural heritage organizations. Students will learn to create and validate XML, to transform it for new uses, and to extract data from it. By the end of the course, students will understand the importance of XML for discovery and data management, and they will have a strong foundation for future work and learning. This is a technology relevant course, hence, the only way to learn a technology is to use it often. There will be small assignments due most weeks; the majority of such assignments will be working directly with XML and its related technologies and essential operations. Upon successful completion of the course, students will be able to: Analyse XML for well-formedness and validity. Understand the structure and functioning of XML. Describe the importance of XML in the discovery, storage, and use of data in libraries and other organizations. Application Programmer Interface (API) < at appropriate multiple times in course for constructiveness, robust applicability and retention > Extract data from XML Understand how XML is used to transport and display data. Transform XML Course Literature: TBA Assessment --> Weekly XML Assignments Lab Exercises Occasional Quizzes Based on weekly assignments and labs 2 Exams Based on weekly assignments, labs, and quizzes Semester Project (MANDATORY) Prerequisite: Senior Standing Application Programming Interfaces The course provides an in-depth exploration of Application Programmable Interfaces (APIs, focusing on their design, implementation, and practical use in software development. Through hands on labs and projects, students will acquire proficiency in consuming and building APIs using R programming language. Learning Objectives: Comprehend the fundamental concepts APIs and their role in modern software development. Evaluate and select appropriate APIs for different development scenarios. Apply to tools and frameworks to interact with and consume APIs. Design and implement RESTful APIs for various applications. Develop and deploy API-driven projects with real-world applications. Assessment: Labs and Assignments 40% 4 Projects 40% Final Exam 20% Part A. Vocabulary, multiple choice, T/F and reasoning of issues. Part B. Hands-on/interactive basics tasks concerning various topics throughout the course. Literature (Optional) “RESTful API Design” by Mark Masse “API Design Patterns” by JJ Geewax Applied Resources: Online documentation for popular APIs (Google Maps, Twitter API, gov’t agencies, congressional libraries, reviews sites, etc., etc.) Data for statistical analysis via APIs (USGS, NOAA, national weather service, USDA, FDA, FED, Federal Reserve, government agencies (local provincial and national), Kaggle, etc., genome databases, environmental protection agency, UN main bodies, IMF, WTO, UNCTAD, UNODC, OECD, etc., etc., etc.) Course Outline: MODULE 1. Introduction to APIs Comprehending APIS and their significance in software development. Types of APIs (RESTful, SOAP, GraphQL, etc.). Overview of HTTP methods (GET, POST, PUT, DELETE) and status codes. MODULE 2. Consuming APIs with R Using R packages for API (httr, jsonlite) Handling JSON data from APIs. Authentication methods (API keys, OAuth) with R. MODULE 3. Building Simple APIs with Plumber Introduction to Plumber package for building APIs in R. Designing basic RESTful endpoints with R. Testing APIs using R scripts. MODULE 4. Advanced API Concepts Handling request parameters and query strings with R. Error Handling and response formats (JSON, XML) with R. Versioning and documentation of APIs. MODULE 5. API Design Best Practices Design patterns for APIs. Implementing HATEOAS (Hypermedia as the Engine of Application State) with R. Security Considerations in API design. MODULE 6. Real-World class API activities Group Project: collaboratively design an API-driven application using R. Presentation and demo of projects. MODULE 7. API Deployment and Management Deploying R-based APIs to cloud platforms (AWS, Azure). Monitoring and analytics for APIs. Continuous Integration/Continuous Deployment (CI/CD) for R-based APIs. MODULE 8. API Testing and Performance Writing unit and integration tests for R-based APIs. Load testing and performance optimization. Troubleshooting common API issues. Labs: LAB 1. API Basics and Consumption Objective: comprehend the basics of APIs and how to consume then using R Tasks Use the httr package to make HTTP requests to a public API. Parse and manipulate JSON responses using jsonlite. Implement basic error handling for API requests in R. LAB 2. Building and Testing Simple APIs with Plumber Objective: Learn to build and test simple RESTful APIs using the Plumber package in R. Tasks: Design and implement CRUD (Create, Read, Update, Delete) operations as API endpoints. Write unit tests for the API endpoints using testthat. Test the API using httr or other HTTP client libraries. With jsonlite too? LAB 3. Advanced API Concepts Objective: explore advanced API concepts and implement security measures. Tasks: Handle request parameters and query strings in API endpoints. Implement OAuth2 authentication with an API using R. Explore SSL/TLS encryption and secure communication practices LAB 4. API Design Best Practices Objective: Apply design patterns and best practices to API development in R. Tasks: Implement HATEOAS in API responses. Design API endpoints for scalability and maintainability. Document APIs using tools like Swagger or R Markdown. Projects: PROJECT 1. Sentiment Analysis with various review websites. PROJECT 2. API Integration and Automation Objective: develop an R-based application that integrates with multiple external APIs. Description: build a dashboard or utility tool that fetches data from different APIs (e.g., weather, finance, social media) and presents insights or performs automated actions. PROJECT 3. Custom API Development Objective: design and implement a custom RESTful API using Plumber. Description: develop an API that serves a specific purpose (e.g., data retrieval, predictive modelling) and document its usage with examples. FINAL PROJECT. API-Driven Web Application Objective: collaboratively create an API-driven web application using R and related technologies. Description work in teams to design and implement a web application that leverages R-based APIs for data retrieval, processing, and visualization. Present the project with a demo and documentation. Prerequisite: R Analysis, Advanced Topics in SQL, Advance NoSQL. Familiarity with web development concepts (HTMAL/CSS, HTTP OR HTTPS). Geographic Information Systems: The field of Geographic Information Systems, GIS, is concerned with the description, analysis, and management of geographic information. This course offers an introduction to methods of managing and processing geographic information. Emphasis will be placed on the nature of geographic information, data models and structures for geographic information, geographic data input, data manipulation and data storage, spatial analytic and modelling techniques, and error analysis. NOTE: course will have botanical interests, ecological interests, geological interests, and climate/meteorological elements. The course is made of two components: lectures and labs. In the lectures, the conceptual elements of the above topics will be discussed. The labs are designed in such a way that students will gain first-hand experience in data input, data management, data analyses, and result presentation in a geographical information system. The basic objectives of this course for students are: 1. To understand the basic structures, concepts, and theories of GIS 2. To gain a hand-on recyclable/sustainable experience with a variety of GIS operations NOTE: to be successful in this class, a student needs self-motivation and self-discipline to complete all obligations on time competently. Typical Texts: Longley P.A., M.F. Goodchild, D.J. Maguire, D.W. Rhind, 2011.Geographic Information Systems and Science. John Wiley and Sons Chang, K.T., 2012. Introduction to Geographic Information Systems (Sixth Edition). McGraw Hill, New York de Smith, M., Goodchild, M., Longley, P., 2013. Geospatial Analysis: A Comprehensive Guide (www.spatialanalysisonline.com) Tools --> A GIS of your choosing (but GRASS GIS is preference); students will be debriefed on operational requirements There are highly established freeware/opensource GIS tools for use. Premier such available are SAGA GIS, ILWIS, MapWindow GIS, uDig, GRASS GIS and others; check Goody bag post. NOTE: GRASS GIS to be preference. Major priorities are sustainable skills for logistics and data (accessibility, operations, management, modelling, exhibition). Project(s) to have considerable life cycles with future use. Additionally, Google Earth and Google Maps can possibly coexist in such a instruction environment, primarily for rapid data visualisation. Course is concerned with the ability to develop meaningful professional data analysis and visualisation of sustainable value to whatever specified target audience. Unique talent development among such tools are encouraged, under the condition that the interests or demand of the target audience is appeased, of high quality. Some highly capable students will be able to develop projects with various systems, while for others finding an environment that suites them is key (highly dependent on what they comprehend and the effort they give). NOTE: in this course data from prerequisites can/will be applied to be constructive; dates and times must be instituted. Meteorological and oceanographic data may also be incorporated. Term Project --> This project will help students understand and experience the entire process of GIS application, which includes understanding the problem, data collection, database development, data analysis and manipulation, project documentation, and poster presentation. Grading --> Lab Exercises 40% Exam I 15% Exam II 15% Student initiated GIS project proposal 10% Term Project Presentation 20% Labs --> There are two components for labs: 1. Having GRASS GIS as preference concerns standard development with course progression. 2. Extracurricular activities with Addons for GRASS GIS. Primarily, there must be strong development for topics in (1) in order to commence with a respective Addons activity -- https://grass.osgeo.org/grass82/manuals/addons// Multicriteria decision decision analysis must be one topic for Addons extracurricular activities. An example: Massei, G., et al (2014). Decision Support Systems for Environmental Management: A Case Study on Wastewater from Agriculture, Journal of Environmental Management, Volume 146, Pages 491-504 However, PROMETHEE is not our only interest, and multiple MCDA addons will be pursued. PROJECT GUIDELINE: 1. Project Description Brief descriptions of the project including: a. Brief introduction and background information of the project b. What is the significance of the project or why do you think it is important to do this project? c. What is the objective of the project? Or what are the specific tasks? 2. Criteria (i.e. How do you apply the principle of the discipline to this study specifically?) What are the criteria and how specifically you are going to apply the criteria to this project? Why? 3. Data and data sources a. Where is your study area? b. What data are needed for the project? c. Where do you get the data needed? d. How long does it take for you to get all data needed for the project? 4. Methods What GIS tools are you going to use? Step by step processes planned? Explain what and why in each step. 5. Results What kind of results (maps) do you expect? Does your expected result address the question ( or objective) above? 6. Timeline How long does it take to finish the project? What is your timetable? PROJECT POSTERS GUIDELINE: 1. Make a layout in tool (used primarily to view, edit, create, and analyze geospatial data). Tool containing your project-related maps and graphs. The minimum size of the layout (poster) is 36 (height) x 42 (width) and the maximum height of the plotter paper is 42 in. Note: I may not ask you print them out, but they must be applicable for demonstrations and public viewing. 2. Your posters should contain the following components: a. Title of your project b. Author’s name and course title c. Affiliation, “Rutgers Program, Course Name/Number, Rutgers University” d. Abstract, briefly describe the objective of the project, general methodology, major results, and conclusion. The abstract should be clear and professionally written e. Introduction, briefly describe the background and the significance of the. Introduction should be easy to understand and professionally written f. Objective, brief and clear. One or two sentences g. Methodology, describe the methods that you used in the project using easy to understand language. Methods include: - Data and data sources - Data manipulation and analysis h. Results, brief, clear, logical, and graphical - Present your results with maps and graphs and/or tables - Each map/graph/table should have a title, self-explanatory legend, and a brief caption about the meaning of the graph (what you want the reader to see). i. Experimenting with the R package rgrass towards GRASS GIS. Minimum requirements: (1) some exploratory data analysis, AND (2) incorporation of other R packages (Tidyverse, Tidymodels and Caret; all included, no exception). Note: it will be assumed without question that students are intelligent enough to independently acquire and read literature for the mentioned packages (from CRAN, vignettes, JOSS, RStudio, Springer texts, CRC press, etc. etc.). j. Conclusion and discussion, brief and well written - What is the significance of the project results? k. The posters should be well organised, colorful, clear, and self-explanatory. COURSE OUTLINE --> WEEK 1 GIS Overview The Nature of Geographic Information WEEK 2 Data Representation Measuring Systems: Location – Coordinate Systems Data Representation Measuring Systems: Location – Coordinate Systems (Continue) WEEK 3 Data Representation Measuring Systems: Location – Coordinate Transformation Data Representation Measuring Systems: Topology Measuring Systems: Attributes WEEK 4 Data Representation Spatial Data Models: Introduction to spatial data models Spatial Data Models: Raster data models Data Representation Spatial Data Models: Relational Data Models Spatial Data Models: Vector Data Models (I) WEEK 5 Data Representation Spatial Data Models: Vector Data Models (II) Data Representation Spatial Data Models: TIN Summary of Spatial Data Models: Raster, Vector, TIN WEEK 6 Data Representation Linking attribute data with spatial data Recent Development of Data models WEEK 7 GIS Database Creation and Maintenance (I) Data Input & Editing GIS Database Creation and Maintenance (II) DBMS and its use in GIS WEEK 8 Review for Exam 1 Exam 1 WEEK 9 GIS Database Creation and Maintenance (III) Metadata / Database creation Guidelines / NSDI Data Analysis Measurement & Connectivity WEEK 10 Data Analysis Interpolation WEEK 11 Data Analysis Digital Terrain Analysis Data Analysis: Statistical Operations & Point Pattern Analysis WEEK 12 Data Analysis Classification Data Analysis GIS-based Modelling and Spatial Overlay (I) WEEK 13 Data Analysis GIS-based Modelling and Spatial Overlay (II) Data Analysis Summary Uncertainty WEEK 14 Geo-representation, Geo-presentation, and GeoVisualization GIS Applications WEEK 15 - 17 Tying up Loose Ends Review for Exam Exam II WEEK 18 Student Presentations Student Presentations Prerequisites: Mathematical Statistics Introduction to Data Science Applying data science tools to summarize, visualize, and analyze data. Sensible workflows and clear interpretations are emphasized, using R in Quarto notebooks in RStudio. To be successful in this course...and quote, “yuh gots to read”. I can’t dictate everything you need to read because that’s not possible in data science when its applicable to all industries and fields. “Yuh gots to be able to clean a cow’s carcass if yuh want beef.” Students will be introduced to the implementation of basic data science workflows, including data analysis and visualizations, using the R programming language. Some of the Learning Outcomes: Read data using computation from various sources (local and remote plain text files, spreadsheets and databases) Wrangle data from their original format into a fit-for-purpose format. Identify the most common types of research questions and map them to the appropriate type of data analysis. Create, and interpret, meaningful tables from wrangled data. Create, and interpret, impactful figures from wrangled data. Apply, and interpret the output of simple classifier and regression models. Make and evaluate predictions using a simple classifier and a regression model. Apply, and interpret the output of, a simple clustering algorithm. Distinguish between in-sample prediction, out-of-sample prediction, and cross-validation. Cross-validation emphasis for most or all machine learning models Accomplish all of the above using workflows and communication strategies that are sensible, clear, reproducible, and publishable. Tools --> RStudio with Quarto Tidyverse, Tidymodels, Caret (and other) packages for operations Course Text --> TBA Homework --> Hands-on R based prerequisite assignments to be precursor tasks in homework assignments for this course. Note: hypothesis testing module from prerequisite will not be included. Hands-on R based assignments based on course topics. NOTE: after data wrangling (DW) module is treated expect DW tasks to be naturally included in succeeding topics. Exams --> Will be hands-on with R. Will have 3 exams. To be mostly open notes, namely, use of homework and your developed prior projects is always admissible. 2 in-class exams and one take home exam Minor component (closed book): concerns vocabulary, comprehension concepts, properly situating, and T/F. Major component: mini projects to develop, being open notes The third (take home) will be “brutal” and will require much effort and the extra mile independently. I don’t train students to take exams because such doesn’t work with real jobs. Will have 5% more weight. Projects --> Will be based on course development in bulk loads, meaning that skills acquired prior will be applied in bulk. At times, may or may not be straightforward. NOTE: homework, exams and all project reports will be done using Quarto with RStudio. Assessment --> Homework 20% 3 Exams 35% Major Projects 45% Course Topics --> Introduction to R, Quarto with RStudio Procedures for structuring professional documents Mathematical expressions in non-R scripts Issue with the view function and rendering the document Primitive Data Frames (assumption of having small arrays) Constructing data frames with various arrays Selecting columns in a data frame ($ method) Creating features from elder columns ($ method) rbind and cbind functions Importing Data into RStudio (sources and various files) .xlsx files, .csv files Dealing with spreadsheet files having multiple spreadsheets How to choose the spreadsheet of interest .txt files and VCF files Data Wrangling (on established public data frames and tibbles) The Tidyverse and dplyr packages Adjusting/fixing headers of a data frame (delimiter issues) data(), head(), glimpse() and str() functions Missing values/data check Resolutions for missing values (for numerical data) Removal? Replacement with Mean or median? Select(). Differentiating from $ method. Filter() Rename() Mutate(). Differentiating from $ method. Merge(), Join(). Differentiating from rbind and cbind functions Issue with .txt files and FCV files having multiple unique classes with multiple delimiter types in a “column” or variable. Resolutions. Wide format to long format pivot_longer() melt() transpose function rownames_to_columns() Long format to wide format Dcast() Exploratory Data Analysis (EDA) Generating summary statistics and interpretation (include skew and kurtosis) Correlation (Pearson, Spearman and Kendall) Which serves best? Correlation heat maps for the features/variables with correlation type What can you learn? The ggpairs() function with (Pearson, Kendall and Spearman) Note: one should construct individual plots at a time if the number of variables are large. Feature Engineering Basics Data Wrangling Review (advanced) Feature Scaling techniques (standardization, normalization, robust). Why and when? When is it constructive? When Misleading? Merging columns into a common variable (due to sub-classes, sub-groups, etc.) Constructing ordinal variables from continuous variables Quantiles and exotic specifications. Rescaling ordinal variables Modelling ordinal variables towards categorical variables Converting ordinal and categorical variables to numeric Transform character type instances to integer instances (and keeping track) Data Visualization (feature engineering skills will re-emerge) Basic bar plots Histogram development ggpairs() review (when variables aren’t too much) Pearson, Kendall and Spearman Box plots (development and interpretation) Single and simultaneous plots Correlation heatmaps review (Pearson, Kendall and Spearman) Scatter plots Line plots Linear and nonlinear lines Time series Classification (KNN & SVM) Multilinear Regression (OLS and Quantile) Review of EDA module OLS and Quantile Includes summary statistics interpretation (OLS vs Quantile) Nonlinear Quantile Regression (NQR) Also summary statistics interpretation (OLS vs Quantile vs NQR) Logit Regression (simple and multivariate) Data that’s meaningful to logit regression Includes summary statistics interpretation Decision Trees Unsupervised Learning Methods Principal Component Analysis (with assumptions) Include validation methods Kernel Principal Component Analysis (with assumptions) Include validation methods Clustering (Centroid and Density based) Includes: Silhouette Score and Davies-Bouldin Index Prerequisite: Mathematical Statistics

Advanced Data Science Course will be much more technical, bulkier and fast paced than prerequisite course....NOT KIDDING ABOUT THAT. Field applications will be extensive and highly diverse. Course will apply the Quarto-RStudio environment to publish professional pdf formats. NOTE: notes and activities from prerequisite will be vital. NOTE: continuation with Tidyverse and Tidymodels is implied concerning its abilities, however, I can ask also for development comparatively with other R packages. As well, Tidyverse and Tidymodels may not have all the required tools for course topics, so it may inevitably be the case that other packages will be incorporated regardless. Independence and consensus are strong complements to each other. For R tools the following link can serve well --> https://cran.r-project.org/web/views/MachineLearning.html Such list from above source may not have all R packages of interest. Examples such as the following --> caret, caretEnsemble, crossval, EnsembleBase, EnsemblePCReg, forecastML, FuncNN, XGBoost, mlbench, neuralnet, pROC, Rfast Concerning such packages link and the succeeding mentioned packages there may be vignettes. GitHub repository also provides guides in R and for general environments. NOTE: cross validation emphasis for most or all models. A small idea of what is expected for cross validation with R (but not necessarily the only way) --> Venturini, S. (2016). Cross-Validation for Predictive Analytics Using R, Milano R. NOTE: knowledge, notes, projects and skills from prerequisite will be invaluable. Course Literature --> TBA Homework --> Prerequisite hands-on activities [data acquisition, data wrangling, exploratory data analysis, feature engineering, data visualization, classification, regression, logit regression, unsupervised learning methods] will be incorporated predecessor tasks to current course topics in each homework. NOTE: expect data acquisition, wrangling, EDA and feature engineering tasks to be naturally included in the afterwards mentioned prior bolded topics in the above. Hands-on assignments based on course topics. NOTE: expect data acquisition, wrangling, EDA and feature engineering tasks to be included in advance course topics. Exams --> Will be hands-on with R. Will have 3 exams. To be open notes, namely, use of homework, notes and your developed prior projects is always admissible. 2 in-class exams and one take home exam Minor component (closed book): concerns vocabulary, comprehension concepts, properly situating, and T/F. Major component: mini projects to develop, being open notes The third (take home) will be “brutal” and will require much effort and the extra mile independently. I don’t train students to take exams because such doesn’t work with real jobs. Will have 5% more weight. Projects --> Will be based on course development in bulk loads, meaning, skills acquired prior will be applied in bulk. At times, may or may not be straightforward. NOTE: homework, exams and all project reports will be done using Quarto with RStudio. Assessment --> Homework 20% 3 Exams 35% Projects 45% COURSE TOPICS --> 1. Advanced review from prerequisite. Advanced FAST review. You are here because of the prerequisite. A. Importing Data Augment with APIs/API keys B. Data Cleaning C. Data Wrangling/Featuring Engineering Basics 2. Exploratory Data Analysis Summary Statistics (includes skew and kurtosis) For Tidyverse and Tidymodels R packages will have advance development of prerequisite activities For the R packages CADStat and ggplot2 Histograms, Boxplots, Cumulative Distribution Functions, Q-Q plots, and Scatter Plots Note: other R packages expected. 3. Detecting fabricated data Hartgerink C., Wicherts J., van Assen M. (2016). The Value of Statistical Tools to Detect Data Fabrication. Research Ideas and Outcomes 2: e8860. Yamamoto, K., & Lennon, M. L. (2018). Understanding and Detecting Data Fabrication in Large-Scale Assessments. Quality Assurance in Education, 26(2), 196–212. 4. Unsupervised Learning (advanced treatment) PCA and Kernel PCA Clustering (advanced treatment) Includes: Silhouette Score and Davies-Bouldin Index Will restrict to applications implementation for demographics, census and biological data since such data will be easy to acquire and dive into. 5. Feature Selection Note: a feature is the same as a predictor variable; a target is equivalent to a response variable. First, for datasets chosen will develop correlation matrices. Then heatmaps. Second, will explore easily implementable methods for feature selection/importance. Will identify the concepts, followed by (practical, tangible and fluid) analytical structure of the method. Then implementation logistics. Then implementation in the R environment. Will make use of datasets with considerable amounts of features. Univariate feature selection method (will be hands-on) The Boruta, FSelectorRccp and Caret R packages. Compare priors to module (4) High correlation among significant/selected variables? 6. Advanced Regression NOTE: based on prerequisite course and its prerequisite, basic multilinear regression will not be treated as first encounter. Development will be fast concerning analysis and R tools. Exploratory Data Analysis review Variable Selection Heinze, G., Wallisch, C., & Dunkler, D. (2018). Variable selection - A Review and Recommendations for the Practicing Statistician. Biometrical journal. Biometrische Zeitschrift, 60(3), 431–449 Dong, J., Rudin, C. Exploring the Cloud of Variable Importance for the Set of All Good Models. Nat Mach Intell 2, 810–824 (2020) Module (5) review and implementation Choosing between OLS, WLS and GLS Will also use summary statistics for regression with interpretation Training, testing and validation Response variable distribution & conditional expectation For multilinear models to develop the probability distributions for a respective explanatory variable (or multiple) with the response variable, w.r.t. data range. Evaluating Conditional probabilities and conditional expectation. Marginal Effects Notion and structuring for implementation Applications Casual Inference and omitted variables Quantile Regression (QR) Advanced Review Feature importance & feature selection review Scatter Plots Beginning with scatterplots is a useful first step in any analysis because they help visualize relationships and identify possible issues (e.g., outliers) that can influence subsequent statistical analyses, or need of regression beyond simple OLS, say, quantile regression (or generalized nonlinear models). Note: concerns for the number of variable pairs. Practical and fluid analysis towards computational logistics; includes variable selection. Then implementation. Comparing with least squares types prior for modelling, estimation (with summary statistics) and validation, forecasting and error Applications in economics (GDP, employment, trade models) quantreg package with manual and vignettes Response variable distribution & conditional expectation For multilinear models to develop the probability distributions for a respective explanatory variable (or multiple) with the response variable, w.r.t. data range. Evaluating Conditional probabilities and conditional expectation. All such is for compare/contrast with OLS/WLS/GLS multilinear models Marginal Effects compared to OLS/WLS/SLS models Coefficient of determination in quantile regression models compared to OLS/WLS/GLS models and for other summary statistics Ando, T., & Tsay, R. S. (2011). Quantile Regression Models with Factor-Augmented Predictors and information criterion. The Econometrics Journal, 14(1), 1–24. Nonlinear Quantile Regression review Is the trend (positive or negative) in scatter plots absolute? OLS versus Quantile versus LOESS/LOWESS versus Spline Observing trend and summary statistics Implications for multivariate models and forecasting 7. Linear Classifier (simple and multivariate) Multiple Logistic Regression (LGR) - Advance Recital Motives Model Structure and Computational Structure Evidence for variables Model Selection/fitting Parameters pursuit Summary Statistics analysis Calculating Probabilities/Predicted Probabilities Marginal Effects Applications Feature Importance logistic regression method Then to compare to feature importance/selection methods encountered prior Applications implementation in political science, labour economics, astronomy, biological sciences, credit models, etc. Support Vector Machine (SVM) Logistic Regression versus SVM Recursive feature selection (logistic estimator versus SVM estimator) Then to compare to feature selection/importance methods encountered earlier 8. Decision Trees (will not assume better than LGR or SVM) For our purposes there is the goal of high clarity, strong logistics and practical implementation. NOTE: for applications of Decision trees students must develop definitive schemes with data being immersible with structure. DT vs KNN vs SVM Decision Tree Feature Importance (will be R oriented) CART Regression and CART Classification types Then to compare such prior two to feature importance/selection methods encountered earlier 9. Ensemble Learning Will focus mainly on Random Forest (due to familiarity with underlying estimators), and maybe a bit of exposure to Boosts. Will have R development. Random Forest Feature Importance (will be R oriented) Then compare to feature importance/selection methods encountered earlier 10. Artificial Neural Networks (theory, tangible/practical/fluid structuring, logistics, applications implementation). With applications will like to make use of “flowchart abstraction” before any possible engagement with code design and implementation. Perceptron Single layer Multi-layer Recurrent Neural network Feedforward Neural Network (and backpropagation) NOTE: cross validation is mandatory with any pursuit. Will pursue diverse applications use of of data. Other possible applications for hands on activity: Uwamahoro, J., Habarulema, J.B. Empirical Modelling of the Storm Time Geomagnetic Indices: A Comparison Between the Local K and Global Kp Indices. Earth Planet Sp 66, 95 (2014). Note: develop regression models and compare to NNs. Spectroscopy to implement Ch. Affolter, J.T. Clerc (1993). Prediction of Infrared Spectra from Chemical Structures of Organic Compounds using Neural Networks, Chemometrics and Intelligent Laboratory Systems, Volume 21, Issues 2–3, Pages 151-157. Note: hopefully there’s no need to be well versed in chemistry. Note: may also compare to regression models. 11. Categorical Variables and Ordinal Logistic Regression (TIME PERMITING) Categorical Variables Review of Categorical Variables Chi-square test for association with categorical variables Fisher test as alternative to prior Treating categorical variables with large amounts of uniqueness instances. An example, instances for, “why did you leave your job?” Ordinal Variables Review of Ordinal Variables; differentiation between categorical and ordinal Constructing ordinal variables from continuous data Modelling ordinal variables into categorical variables and the numeric transformation Ordinal Logistic Regression (OLR) Models and construction in R Comprehension of OLR What feature importance/selection methods from earlier are applicable? Test for Proportional Odds in the Proportional-Odds PoTest function in R and interpretation AIC, BIC, Cox & Snell, and Nagelkerke for OLR model fit Complicated Data Sets (TIME PERMITING) Dealing with data sets whose features are continuous, binary, categorical and ordinal in unison. Note: skills of data cleaning, data wrangling and featuring engineering from prior are expected to resonate without restraint. Clinical Trials Group Study Data Astronomical/Astrophysical Data Gov’t Open data (various agencies and offices) What machine learning models/algorithms are best suited for such? Prerequisite: Introduction to Data Science Data Integrity and Debugging in Data Science Data integrity and debugging are critical aspects of data science, ensuring that data remains accurate, consistent, and dependable throughout its lifecycle. This course provides an in-depth exploration of data integrity principles, common data integrity issues, debugging techniques, and compliance with European standards. Emphasis is placed on understanding the most troublesome types of data integrity issues and debugging challenges encountered in real-world scenarios, including various types of data science files and formats. SUCH emphasis attributes will also be hands-on extensively. NOTE: module 1 will come back to haunt you IN ALL following modules. NOTE: module 2 will come back to haunt you IN ALL succeeding modules. NOTE: prior modules general will intensively resonate in succeeding modules. Assessment -> 4-5 individualized intensive projects 60% Each student will receive a different project. Yes, almost everywhere is a treasure trove of messy stuff. Students will randomly draw sticks to determine the project that will be individually assigned to them; all to reveal to class their project title, where instructions will be assigned to each student in a manner that verifies the level of tasks being the same level for each student. Projects will reflect all of the course. 2 In-class exams 40% For each exam there are two elements: 1. Vocabulary, knowledge, T/F, elaborations to be 30 min 2. Hands-on processing, debugging and cleaning tasks (being open notes) Course Outline -> MODULE1. ADVANCED DATA WRANGLING IN R Loading data Data frame and Tibble conversion Probing the data with str() and glimpse(), summary() Advance Review of Data Cleaning/Data Wrangling from prerequisite Variable conversion (factor, character, numeric…and back and forth) Include algorithms for high number of random columns Means to output the encoding rule for each column Consider the case of converting character to number. Prematurely you observe actual numeric encoding, however, when you want the encoding rules output you get an error or warning about variables only having one or no levels. Descriptive Statistics summary() and moments package (for skew and kurtosis) MODULE 2. FILES AND FORMAT Immersion into data files and formats. Emphasis on how to integrate, probe and manipulate the data concerning skills from module 1. File types of interest: JSON, XML, SQL, NoSQL, Avro or (Parquet), Feather, XBRL, and if feasible also GIS (data types and data files). Writing your data frame or tibble in R to various data types/files XLXS, CSV, JSON, SQL, NoSQL, etc. Writing explanatory notes for the data within the data files for the prior formats MODULE 3. INTRODUCTION TO DATA INTEGRITY Definition and Importance of Data Integrity Factors Influencing Data integrity Consequences of compromised data integrity MODULE 4. COMMON DATA INTEGRITY ISSUES Data Duplication and redundancy Missing values and outliers. When is normal distribution practical Methods to identify and treat The real world In the natural, physical, and planetary sciences…the statistical and stochastic laws Financial Risk Modelling Actuarial Inconsistent data formats and types Data quality issues and anomalies MODULE 5. TROUBLESHOOTING DATA INTEGRITY ISSUES Advanced review of Data Profiling and Exploratory Data Analysis (EDA) Advance review of outliers from module 4 Validation and verification strategies MODULE 6. DEBUGGING TECHNIQUES Error detection and error handling Debugging data pipelines and data workflows Version control reproducibility Logging and monitoring for data debugging MODULE 7. INTERNATIONAL STATANDARDS FOR DATA ITEGRITY General Data Protection Regulation (GDPR) National, ISO and European Data Protection principles and requirements Impact of GDPR on data handling and processing Ensuring compliance with GDPR in data science projects MODULES 8. REALISTIC CASE STUDIES Examples of real-world data integrity issues and debugging challenges Discussion of best practices and lessons learnt Prerequisite: Introduction to Data Science FOR ACTIVITIES IN THE “SUMMER” AND WINTER” SESSIONS ALL PARTICIPATING STUDENTS, ASSISTING/ADVISING INSTRUCTORS AND PROFESSORS MUST BE OFFICIALLY RECOGNISED; REQUIRES BOTH CIVILIAN ID AND STUDENT/FACULTY ID FOR CONFIRMATION OF INDIVIDUAL. THERE WILL ALSO BE USE OF IDENTIFICATIONS FOR ACTIVITIES FOR RESPECTIVE SESSION. SECURITY AND NON-PARTICIPATING ADMINISTRATION WILL ONLY IDENTIFY RESPECTIVE ACTIVITY BY IDENTIFICATION CODE. SECURITY AND NON-PARTICIPATING ADMINISTRATION MUST NEVER KNOW WHAT ACTIVITIES IDENTIFICATION CODES IDENTIFY: < Alpha, Alpha, Alpha, Alpha > - < # # # # # > - < session > - < yyyy > Activities repeated can be added to transcripts upon successful completion. Repeated activities later on can be given a designation such as Advance “Name” I, Advance “Name” II. As well, particular repeated activities serve to towards developing true comprehension, competency and professionalism..... BLOCKCHAIN DEVELOPMENT Conway, L. (2020). Blockchain Explained. Investopedia In this activity you will only be as good as how serious and dedicated you are. Between RDMS and blockchain will pursue comparative development and comparative hands-on labs. Namely, what is/was developed and done with RDMS will try to pursue blockchain development “parallelly”. Advantages and disadvantages will be highlighted. At designated times of the activity students to give live demonstrations concerning topics and projects of interest in development. NOTE: activity has no operation with cryptocurrencies. NOTE: at least intermediate level course in RDMS with SQL as prerequisite. EXPLORATORY DATA ANALYSIS AND MACHINE LEARNING TOOLS WITH PROFESSIONAL DATABASES Necessity with EDA: how to apply the following R packages to acquired data CADStat Tidymodels Tidyverse Time series R packages as well Note: no instructor will prepare nor data wrangle any data from the given sources for students. Areas of interest: -IGOs data -Census Bureau data -Bureau of Economic Analysis data -Financial Assets -Genomic Data -Ecological Data -Air Traffic Data -Astronomy Spectroscopy applications (light curve analysis, distance, speed, temperature composition, surface gravity, age, cosmology, etc., etc., etc.). Use of analytical and statistical models with data. Orbits development interstellar bodies (asteroids, comets, stars, etc.) Classifying comets NOTE: emphasis on no instructor preparing/wrangling any data from the give sources; students will become competent with the structure, logistics and accessibility involving astronomical databases for purposes of interest with data of interest. Many today (even PhDs) struggle with competent astronomical databases usage. Examples of databases: https://www.mpia.de/en/services/library/astronomical-databases http://tdc-www.harvard.edu/astro.data.html OPERATIONS & ANALYSING SATELLITE IMAGES IN GOOGLE EARTH ENGINE WITH BIGQUERY SQL and R: --- https://cloud.google.com/blog/products/data-analytics/analyzing-satellite-images-in-google-earth-engine-with-bigquery-sql --- https://vizzuality.github.io/sql2gee/gettingstarted.html --- https://www.css.cornell.edu/faculty/dgr2/_static/files/R_html/ex_rgee.html --- https://cran.r-project.org/web/packages/rgee/vignettes/rgee01.html --- https://www.r-bloggers.com/2022/05/how-to-connect-google-earth-engine-with-r-shiny/ --- https://csaybar.github.io/rgee-examples/ Note: it’s important to develop a strong understanding of GEE, its structural layout and typical operations before deep immersion.

PARALLEL PROGRAMMING FOR MACHINE LEARNING Note: an R and Python environment. This activity covers CPU programming (the classical processing unit) and GPU programming (on graphic cards). It is directed towards the goal of writing efficient programs which take advantage of the hardware architecture. First part of the activity is dedicated to computer architecture, and in particular everything that enables programmes to run in parallel and communicate. Activity is tasks oriented, so what was developed analytically there will always be “walk the walk” obligations for various aspects with competence and towards sustainability. Implementation and verification are crucial. Second part will be developing competence with knowledge and skills from first part to put into in practice. R (and Python) programming on CPU with several examples of efficient algorithm implementations versus the “status quo” (or conventional implementations), then counterpart cases with GPUs. Planning CUDA, threads, memory management Pointers, GPU/CPU interaction, using __inline__ and __globals__ PyTorch and R counterparts: extension implementation INTELLIGENCE AND INNOVATION INITIATIVE FOR DECISION MAKING WITH TRANSMISSION VECTORS Article of interest: Siraj, A. S. et al. (2018). Spatiotemporal Incidence of Zika and Associated Environmental Drivers for the 2015-2016 Epidemic in Colombia. Scientific Data, 5, 180073. Abstract of journal article: Despite a long history of mosquito-borne virus epidemics in the Americas, the impact of the Zika virus (ZIKV) epidemic of 2015–2016 was unexpected. The need for scientifically informed decision-making is driving research to understand the emergence and spread of ZIKV. To support that research, we assembled a data set of key covariates for modelling ZIKV transmission dynamics in Colombia, where ZIKV transmission was widespread and the government made incidence data publicly available. On a weekly basis between January 1, 2014 and October 1, 2016 at three administrative levels, we collated spatiotemporal Zika incidence data, nine environmental variables, and demographic data into a single downloadable database. These new datasets and those we identified, processed, and assembled at comparable spatial and temporal resolutions will save future researchers considerable time and effort in performing these data processing steps, enabling them to focus instead on extracting epidemiological insights from this important data set. Similar approaches could prove useful for filling data gaps to enable epidemiological analyses of future disease emergence events. Interest with ambiances of concern: Applying the assumption that a Zika vector is not encouraged in the ambiances of interest, instead such a journal article can be used to model disease vectors or infection vectors or infestation vectors in the ambiances of interest. Many other viruses (though likely not as formidable as ZIKA) are known to spread through mosquito activity, and there’s the constant threat of another mealybug infestation. The given journal will be analysed and used as a blueprint to build a data analysis solution to model a decision-making process for contagion or infestations of interest. However, students will be engaged in identifying economical means and open source tools as substitutes for the various products and proprietary tools applied in the journal article. Direct development of data acquisition tools like always will be required; test of such with trials will also be likely to establish credibility. Of consequence, some phases of development with be in the field (exposed to the elements). For the case of mealy bugs, such may or may not be more complicated since one must identify transmission resulting from human activity (negligence, ignorance, etc.). RStudio with Quarto can be incorporated with other alternative tools and sources as substitutes. The system developed likely will be integrated to an alarm system for computer and mobile devices. DISEASE SURVEILLANCE SYSTEM Sources of Interest --> 1. Haghiri, H., Rabiei, R., Hosseini, A., Moghaddasi, H., & Asadi, F. (2019). Notifiable Diseases Surveillance System with a Data Architecture Approach: A Systematic Review. Acta Informatica Medica: AIM: journal of the Society for Medical Informatics of Bosnia & Herzegovina: casopis Drustva za medicinsku informatiku BiH, 27(4), 268–277. 2A. JHU Applied Physics Laboratory – Inside ESSENCE: Providing early detection of epidemics – YouTube << https://www.youtube.com/watch?v=4AGPYmXcnZQ >> 2B. JHU Applied Physics Laboratory – EESENCE Early Notification of Epidemics – YouTube << https://www.youtube.com/watch?v=uxP6bGUhZ1c >> Based on 1 and 2 will like to profile ambiance counterpart, AND develop a prototype disease surveillance system w.r.t. ambiance(s) considered. However, concerning the first source one would like to determine whether there are alternatives to the “data architecture approach”, and if more predominant or popular. Nevertheless, the approach conveyed in the given journal article appears to be quite feasible to develop concerning APIs, algorithm instructions and so forth. Source (2) provides socially informative ideas but really isn’t much. Is ESSENCE based on the “data architecture approach”? It may also be the case that data constructed from sources may not be exactly to preference, hence one may have to write “data structure” instructions to acquire preference. How does one know they’re getting the right type of thing they want? First attempt at developing such a system may not go far into successful development as one would like, however, your level of progress will be a stepping stone to be better and advance further. As well, such activity “forces” one to do research and become knowledgeable or accessible to things never imagined before. It’s best that one keeps record of development in stages so they can backtrack and remain fresh with their own labour. Some of the links in the following sites may be helpful with ideas: << https://www.cdc.gov/csels/dhis/ >> << https://wonder.cdc.gov >> Consider as well the “Topics” and “A – Z Index” links in the latter.

BIG DATA TOOLS Apache (Hadoop, Hive, Spark, Spark SQL, Airflow, Kafka) Delta Lake The most challenging part of this activity may be having enterprises and assets relevant and integrable to accomplish anything meaningful and economic. For the specified Apache tools above it’s essential that a tangible, practical, fluid and constructive sequential process is developed towards real projects and the management. Then onwards to Delta Lake development. Note: students may also have access to tutorials to accommodate projects in this activity. Note: there may be alternatives to such particular tools concerning the specific uses.

DATA WAREHOUSING Real-world development and objectives Intelligence & Analysis Labs (administration and practical goals) Short term and long term objectives Projects and Administration

RDMS and NoSQL WITH PYTHON (COMING SOON) Concerns basic practical python routine fundamentals to convey ability and competence. Developing your routines. YUH GONNA READ A LOT ACCOMMODATED WITH TRIAL AND ERROR; DON’T GET DISCOURAGED. Python libraries of interest: SQLAlchemy PyMongo (or other NoSQL alternative) NumPy Pandas Matplotlib Seaborn Statsmodels Sci-kit learn Tensorflow PyTorch

PROJECT DEVELOPMENT WITH GITHUB AND/OR CREDIBLE COMPETITOR For this activity to be meaningful, multiple data science/engineering projects will be implemented in order for the environment and operations skills to sink in and be retained. The major concerns: Registration Network Participant Connection/Syncing Administrative Rights Throughout Projects Intellectual Property Rights Throughout Projects Project Development/Implementation Marketing

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plumpoctopus · 4 years

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Computational Finance and some needed engineering particulars (AE, ME, EE and COMPE)

From my experience with a highly oppressive and disadvantaging academic environment, frustration and pessimism can often lead to one pursuing competency and professionalism for a world that seems like a cult and unworthy. From my experience many Mathematics departments are often degenerate and corrupt towards serving the interest of its constituents. Many claim to reinforce structure, but in actual the tactics observed are plainly means to serve their employment goals, be mischievous and obnoxious towards nothing. In general, most of my studies reside out of pure mathematics, where I may reference at least 15 - 25 Journal articles and texts per week (out of physics, engineering, chemistry, geophysics, biology, social sciences, etc., etc.). Of consequence, at the end of the day, being a demigod or complacent in complex variables, mathematical proofs, discrete mathematics, abstract algebra, and matrix algebra is a waste of time. Most who lecture in computational finance from a mathematics department aren’t professionals in that environment. They try to bamboozle you with claims of regime discipline, when in all it gets you quite unfocused, unrefined, and incompetent in applied studies. Some are just devils and hexes incarnate. Concerning my interests, I despise mathematical swamps and leeches. People have goals, work, travel, clean, bathe and move...rather than mathematical frolic, prejudice, sabotage and oppression. From my experience I can almost say being a mathematician is not a real job (with the exception of some professors born around 1937 and so forth). Well, my interest in mathematics is computational finance, where I can say I am pretty much self-made in this area due to frustration and self-developing practicality. The following regimen serves to be economic concerning future certainty, cost effectiveness towards graduate school, professionalism and confidence. Note: about my blogs, reading is fundamental, and you will have to do so...quite a bit. The Computational Finance concentration requires the following courses: ---Mandatory Courses Introduction to Macroeconomics (check ECON); Money & Banking (check ECON); Enterprise Data Analysis I & II (check FIN); International Financial Statement Analysis I & II (check FIN); Corporate Finance (check FIN); Financial Accounting (check FIN) ---Required Elementary Skills Scientific Writing I & II; Calculus for Science & Eng I-III; Ordinary Differential Equations; Numerical Analysis; Probability & Statistics B; Mathematical Statistics ---Required Computational Skills Data Programming with Mathematica; Stochastic Models & Computation; Financial Time Series ---Required Portfolios and Capital Markets Courses Investments & Portfolios in Corporate Finance (check FIN); Asset Management ---Required Instruments and Derivatives courses Theory of Interest for Finance; Introduction to Derivatives for Financial Engineering; Derivatives Modelling and Pricing I & II; Fixed Income Securities; Commodities & Futures Trading Theory of Interest for Finance Deterministic treatment of fixed interest rate instruments in the interest of finance. You’re not in this course for mathematical wonder. Course focuses on students simply being competent with the features and behaviour of fixed instruments, because such instruments are serious business where time is quite limited. Typical Text: Kellison. S.G. Theory of Interest. McGraw-Hill/Irwin Computational Tools: Accepted Calculator RStudio + R packages Quandl, Quantmod, tvm, YieldCurve, jrvFinance, BondValuation, credule R packages serve to compliment analytical development. In other words, the packages will not make sense to you, or you will not be constructive with them if you don’t comprehend well what you’re trying to do. Financial Computation in Wolfram Documentation Centre FinancialData, TimeValue, EffectiveInterest, CashFlow, FinancialBond Take effort to investigate parameters and methods available in such Mathematica functions; you may be able to choose methods in functions. Mathematica functions serve to compliment analytical development. In other words, it will not make sense to you, or you will not be constructive with them if you don’t comprehend well what you’re trying to do. Grading: Homework 10% 3 Quizzes 30% 4 Exams 60 % Course Topics (and no other) --> Chapter 1. Measurement of Interest Chapter 5. Yield Rates Chapter 6. Amortization Schedules & Sinking Funds Chapter 7. Bonds and other Securities Chapter 8. Practical Applications Chapter 9. Durations, Immunization, Matching Assets & Liabilities Prerequisites: Calculus II Ordinary Differential Equations: Linear Algebra is not a Matrix Algebra course. Minimal use of manual matrix algebra will be confined to 2 by 2 matrices and nothing further (use of software and calculators for higher matrices, say time is precious). Rigorous instructions to be followed by ODE numerical solvers: https://reference.wolfram.com/language/ref/DSolve.html https://reference.wolfram.com/language/ref/NDSolve.html As well, pay attention to all links and directions in the given links above. Outline: 1. Introduction to Differential Equations (4 hours) Definitions and terminology Initial-value problems Differential equations as mathematical models 2. First-Order Differential Equations (11 hours) Solution curves without a solution; direction fields, autonomous first-order differential equations Separation of variables Linear equations Exact equations Solutions by substitutions Numerical methods; Euler's method, numerical solvers 3. Modelling with First-Order Differential Equations (6 hours) Linear models: exponential growth and decay, Newton's law of cooling, mixture problems, series circuits Non-linear models; logistic growth, chemical reactions Systems of differential equations; mixtures, predator-prey models 4. Higher-Order Differential Equations (15 hours) Linear differential equations: initial-value and boundary-value problems, homogenous equations, non-homogeneous equations Reduction of order Homogeneous linear equations with constant coefficients Undetermined coefficients; superposition approach, annihilator approach Variation of parameters Cauchy-Euler equation Solving systems on linear equations using elimination Non-linear differential equations 5. Modelling with Higher-Order Differential Equations (6 hours) Linear models with initial value problems: gravitational free fall with and without resistance; spring-mass systems with free undamped motion, free damped motion, and driven motion; series circuit analogue Linear models with boundary value problems Nonlinear models 6. Series Solutions of Linear Equations (6 hours) Review of power series Solutions about ordinary points Solutions about singular points 7. The Laplace Transform (10 hours) Definition of the Laplace transform Inverse transforms and transforms of derivatives Operational properties of the transform Translations on s-axis, translations on t-axis Derivatives of a transform, transforms of integrals Systems of linear differential equations Prerequisite: Calculus II. Numerical Analysis Accompanying mathematical analysis and the numerical models, most of the scientific computation will be projects and assignments; all modules will be accounted for, whether individually or bundled with other modules. Professor can provide strategy or logistics set up for scientific computation but nothing further. Code development is necessary for this field of mathematics to be constructive and rigorously applicable. This course serves to understand what's implemented that makes analytical development meaningful when applied, rather than choking or being disheartened by overwhelming theoretical mucus and bile; in the modern era computers are not considered a luxury, rather economic tools for time optimisation and accuracy to do great things. Numerical Analysis should not be thought of as development based solely about mathematicians; that’s just stupid, say, we would never get anywhere in science and engineering with mathematicians hoping recklessly about or doing their hopscotch in their department. Anyone culturally pushing post-apocalytic wastelands or pushing agrarian efforts as undercurrent mischievously upon students (sabotage or ego) should not be on any campus; they are never hated for obvious reasons. NOTE: will be extending all methods and algorithms in course to multivariate counterparts. Lecturing Texts --> Numerical Methods in Scientific Computing vol. 1, Dahlquist & Bjork, SIAM Numerical Analysis (second edition), Walter Gautschi, Springer. Note: primary text to be that of SIAM, while the Springer text to serve as reference. Projects Text --> Press, W. H., Teukolsky, S. A., Vetterling, W. T. and Flannery, B. P. (2007), Chapter 9. Root Finding and Nonlinear Sets of Equations. Numerical Recipes: The Art of Scientific Computing (3rd ed.). New York: Cambridge University Press Projects --> -Projects will be all numerical methods algorithms to develop, run and compare to default and specified methods (in Mathematica) computational environment for various examples. The given projects text employs a FORTRAN environment or C environment, but students must be able to develop Mathematica analogy. -Also, for particular topics students will be asked to compare their code results to earlier alternatives introduced, alongside results from default methods chosen by computational environment (Mathematica). Includes error and truncation development for all identified methods. -Some tasks will be independent development of more advance alternative algorithms; assume all priors to apply. -Students may also be asked to extend to multivariate cases. Exams --> The following are required (and single to multivariate for some cases) 1.Development of mathematical structuring and truncation error modelling 2.Designing (conceptual) code on test paper 3.Elementary approximation tasks on exams and assignments that can be done in short time on paper (convergence and truncation error as well to apply wherever relevant). Being reasonable: For all function approximation methods and algorithms in course, after development and truncation error modelling, students will be asked to apply limits, first order derivative analysis, and second order derivative analysis, namely, continuity, intermediate value theorem, root finding, asymptotes, slope, extrema (relative extrema and absolute extrema), concavity, and inflections. Such will be used to compare approximating functions to given “true functions”. Probing doesn’t getting simpler than basic calculus. Some theorems also to be demonstrated for particular problems. Concerning finite difference (for first and second order DE) Manually done example(s) concern ability to develop first and second order central approximations; Concerning chosen Runge Kutta (for first and second order DE) Manually done example(s) concern only developing 2-4 steps Determining appropriate RK method for various DE Compared to FD central manually done (for first and second order differential equations) Concerning interpolation Only 2 or 3 points will be considered Concerning root finding methods First will involve confirming continuity and differentiability Some methods may not warrant confirming differentiability Intermediate value theorem applied Manually implemented method on a small, decent interval Concerning orthogonalization of function Standard problems just to get the point across Concerning Fourier expansion and spectral method Convergence criteria via Dini’s test and Dirichlet BCs Dini continuity and Dini criterion Standard approximation problems versus Taylor approx. Spectral methods problems will be standard Concerning quadrature Functions will be basic and increments will be small Compare with Taylor/Maclaurin & Fourier expansion under integration 4.Additionally, on exams students will be provided algorithms for particular methods where they must recognise purpose and mathematically represent them. 5.Some cases may also concern correcting the code of labeled algorithm Grading --> Assignments 10% Projects 30% 4 Exams totaling 60% Modules (going from single to multivariate): I. Chapter 2 & 3 Number Systems, Series, Acceleration. The title for chapter 2 will be taken literally. The primary concern is competent error analysis for experiments and measurement observations. Also, will explore conventional algorithms that treat, involve or produce such. II. Chapter 1 (coding from modelling emphasized) Fixed Point Iteration, Newton-Raphson method (manually and by scientific computation). Note: Newton’s method will not just be treated bluntly, rather will be applied to acquire various parameter values in applications. III. Function Approximations and Primitive Numerical Solution of DEs --Taylor’s formula and power series (manually and by scientific computation). Remainder formula, truncation error and round off error. Will compare power series method to analytical solution methods for differential equations of interest. Loop for Taylor expansion (and error modelling). Expect numerical solutions of DEs as part of projects. --Chebyshev Polynomials (manually and by scientific computation) Remainder formula, truncation error and round off error. Will compare power series method to analytical solution methods for differential equations of interest. Conceptual loop design for Chebyshev expansion (and error modelling) All prior to contrast with Taylor counterpart. --Legendre Polynomials (manually and by scientific computation) Remainder formula, truncation error and round off error. Will compare power series method to analytical solution methods for differential equations of interest. Conceptual loop design for Legendre expansion (and error modelling) All prior to contrast with Taylor and Chebyshev counterparts. --Finite Difference Central Scheme (development, coding and comparison with Mathematica method specification). Truncation error and round off error. Will express Taylor’s formula in terms of FDCS and determine performance. Will compare to power series solution method regarding convergence and divergence from analytical solutions, truncation error and round off error. --Euler’s method, RK2, RK 3, RK 4: Develop approximation models, programming, execute, then compare geometrically with the general solutions; use of DSolve or NDSolve for cross reference, and then compare geometrically with FDCS and power series method for truncation error, convergence and divergence. Note: one must establish the advantages and disadvantages between power series method, FDCS and Runge Kutta. All such concerns (i) Linear homogeneous & non-homogeneous first order ODE (ii) Nonlinear homogeneous & non-homogeneous first order ODE (iii) Second order linear homogeneous & non-homogeneous ODE (iii) Second order nonlinear homogeneous & non-homogeneous ODE IV. Chapter 4 (Interpolation) Types of interpolation will also include error analysis. All subjects to be applicable to coding from modelling. Will pursue applications from the sciences and engineering for meaningfulness and practicality; much need to exhibit the practicality of Hermite interpolation. -Lagrange Interpolation -Cen, Z. and Xu, A. (2009). A Remainder Formula of Numerical Differentiation for the Generalised Lagrangian Interpolation. Journal of Computational and Applied Mathematics 230, 418 – 423. -Divided Differences -Newton Interpolation As well, prove: the limit of the Newton polynomial if all nodes coincide is a Taylor polynomial, because the divided differences become derivatives -Hermite Interpolation -Wanicharpichat, Wiwat. (2008). A Hermite’s Interpolation Formula with Generalised Quotient and Remainder Theorems. Scientiae Mathematicae Japonicae. 71. 2010-183. -Rectilinear motion with calculus as application of Hermite Interpolation? V. Root finding methods Review of Newton-Raphson method Secant method Dekker’s method Dekker, T. J. (1969), Finding a Zero by Means of Successive Linear Interpolation. In: Dejon, B. and Henrici, P. (eds.), Constructive Aspects of the Fundamental Theorem of Algebra, London: Wiley-Interscience Brent’s method Brent, R. P. (1973), "Chapter 4: An Algorithm with Guaranteed Convergence for Finding a Zero of a Function", Algorithms for Minimization without Derivatives, Englewood Cliffs, NJ: Prentice-Hall Chandrupatla’s method Chandrupatla, Tirupathi R. (1997). A New Hybrid Quadratic/Bisection Algorithm for Finding the Zero of a Nonlinear Function Without Using Derivatives. Advances in Engineering Software. 28 (3): 145–149 Note: students may be asked to also express methods in divided difference form towards code if such is applicable to method. VI. Chapter 4 (Approximation) Fourier Methods and FFT. Moderate theory where scientific computational activity is enforced; can be compared to Taylor and Maclaurin series with computation. VII. Orthogonalization of functions Seaborn, J. B. (2002). Orthogonal Functions. In: Mathematics for the Physical Sciences. Springer, New York, NY Gram-Schmidt (functions). Modified Gram-Schmidt (functions). Grand-Schmidt orthogonalization and its relation to Taylor expansion, Fourier expansion and possibly Chebyshev expansion. Will pursue developing functioning code for such. VIII. Fourier Modelling & Spectral Method Advance fast review of trigonometric integral identities and the associated complete orthogonal system. Advance fast review of periodic functions Definition of Fourier series Going from [-pi, pi] to [-L, L] via change of variables Complex Fourier series Applications Convergence criteria via Dini’s test, etc.; exemption functions examples Dini continuity and Dini Criterion Error analysis –> –A. C. R. Newbery. (1973). Error analysis for Fourier Series Evaluation. Mathematics of Computation, 27(123), 639-644. –Boudreaux-Bartels, G., Tufts, Dhir, Sadasiv, & Fischer. (1989). Analysis of errors in the computation of Fourier coefficients using the arithmetic Fourier transform (AFT) and summation by parts (SBP). International Conference on Acoustics, Speech, and Signal Processing, 1011-1014 vol.2. Spectral method concerning derivatives, smooth curves, and differential equations. Will be compare with power series method, FDCS and Runge Kutta concerning convergence (rate) and error. Will pursue developing functioning code for such and will be compared to methods from (III). IX. Chapter 5 (Quadrature) Concerns integration approximation schemes. Competent implementation of quality approximations is primary rather than only pure mathematical frolic and memorization of everything. Concerns formulas out of the following: Newton-Cotes quadrature rules (open and closed) Gaussian quadrature Clenshaw-Curtis quadrature Will include contrasts of convergence, error and instability. Exercises conventionally done in Calculus I-II will not be repeated; review independently from a calculus textbook of choice. Such will be followed by the task of building functioning code for various quadrature (likely with parameter setting ability). Also, use of well-defined Taylor/Maclaurin formulas to be applied towards integral approximations, to compare with quadrature from the three mentioned classifications; for integration intervals of interest will determine polynomials that behave well for compare and contrasts with quadrature. This means that for polynomial approximations: --Students must convey that critical points, relative extrema and concavities of polynomials are consistent with critical points, relative extrema and concavities of the actual function --For the Extreme value theorem polynomials must be consistent with real function on interval considered. Additionally, from module (VIII), established approximation functions from Fourier can be used for integration approximation towards compare and contrasts (appropriate amount of terms needed based on Fourier theory) with Taylor/Maclaurin --Students must convey that critical points, relative extrema and concavities of Fourier approximation and polynomials are consistent with critical points and relative extrema of the actual function --For the Extreme value theorem Fourier approximations and polynomials much be consistent with real function on interval considered. Prerequisites: Calculus II, ODE. Partial Differential Equations: Course is rather a constructive course of professionalism and practicality for relevance in the physical sciences, planetary sciences and engineering. Course will not be a Mathematician’s frolic. This is not a Harmonic Analysis course. Note: this course is not for you if you believe you will be transforming everything to systems of linear equations. You will be a disservice to yourself and others with such policy. An analogy, natural things aren’t simplistic. Say, you don’t find iron that’s pure because it’s found as iron ore, which takes so much energy to purify. Iron by itself isn’t much useful in most industries. Yet, if I ask you for 316L (or higher) surgical steel or aerospace grade steel, I don’t want pure iron. You will end up in jail if pure iron was used; would be beheaded in certain countries. Note: this course is neither a mathematical analysis course nor a harmonic analysis course nor a complex variables course. Note: throughout course it’s a good habit to observe what computational functions are available via a CAS such as Mathematica and means of practical implementation. Wolfram Documentation with the scoping of functions. Note: throughout course, to compliment any encountered “analytic” solutions, it’s a good habit to observe what numerical methods are applied to acquire solutions via a CAS such as Mathematica. Note: will be only concerned with realistic initial conditions and boundary conditions when the appropriate times arise, but such will not compromise the integrity and quality of any module and topic. Note: you are not here to be perfect; you “become such” when you know what the hell you’re doing and how to navigate through things concerning scientific progression and technology. Furthermore, in professional industries perfecting calligraphy with separation of variables and other things are not economic. You are here with the intension of being useful to yourself and to others in the future, rather than “evolving” (devolving) into a viral and tirelessly infuriating nuisance; I AM NOT KIDDING ABOUT SUCH. You can’t get to things like RANS by being a disgusting and premeditated carnage inducing [@#$%]. Perfect things on your own time. Note: course to run up to 18 weeks. Tools --> Mathematica OpenFOAM Grading --> 4 Exams: 60% Homework 15% Algorithm and Computational Assignments with OpenFOAM: 25% Homework & Assignments--> -There will be standard homework questions -It’s become customary to copy off numerical computational programming from various sources, hence for problems with numerical methods in the Mathematica and OpenFOAM environment I will emphasize problems where you are forced to account for different types of derivatives, various coefficient functions, various models of non-linearity and various non-homogeneous cases: A. Non-constant analytic functions B. Various Nonlinearity C. Higher order derivatives in independent variables D. Mixed derivatives involved (first and higher) E. PDEs containing first order derivatives, but not as lead F. Combinations among A through E In other words, your numerical methods development will not involve the custom elementary second order PDEs. You will also be responsible for determining what numerical methods are appropriate if assigned method performs poorly. Some tasks may inevitably concern finite element development to compare with software. -Some assignments will require students apply only real variables coordinate transformations concerning geometries of interest and solution; to then compare with rectangular coordinates. Accompanying the analytical development will be Mathematica findings and development of numerical computation to run and compare with Mathematica execution data. Algorithm and Computational Assignments with OpenFOAM --> OpenFOAM (when appropriate) at designated periods will be introduced with various types of immersion. Various heavy tasks with OpenFOAM will be assigned. Exams --> -Exams will be based on lecturing, homework & assignments -The Mathematica activities will also be relevant -Certain latter exams (within second to fourth exam) will include OpenFOAM activities when a certain amount of activities with algorithm and computational assignments with OpenFOAM have been encountered. WARNING MEMO: I don’t give exams for you to memorize structure and solutions for two hours then to forget. You will exhibit your value with your intellect, effort, and maturity. There’s value in your work and personal preparation. On exams you will be permitted a maximum of 1-2 loose leaf sheets of notes. This is not a con artist and social victimization course to benefit Asians and Whites in appearance. I don’t care for “status quo academic cultural appropriateness”. Your culture is your business; this is a practical and tangible PDE course for real goals. WARNING MEMO: if you’re in my course you must be registered throughout. If you are allowed to sit in my course, your existence has no influence on course instruction for other students. No student has influence on the grading rubric of other students. I am not the type having staged exams where I would stay “It was so easy”; repetitive coughs like one is getting off and disturbing the course progression. NOTE: if you have any issue with my warning memos withdraw immediately, and find your socioeconomic savages elsewhere. I don’t like hordes, thugs, parasites, sentient viruses, HIV tactics culture and cartels in academics. Course Outline --> 1. Models of Linear (homogeneous and non-homogeneous) and non-linear (homogeneous and non-homogeneous) PDE 2. Crucial concerns with choice of methods for dealing with PDE http://reference.wolfram.com/language/tutorial/NDSolveOverview.html NOTE: observing the options of methods for use (in Mathematica) compared to what Mathematica chooses to provide solutions. Don’t lose this skill. 3. Method of Characteristics ---Traﬃc wave models, quasi-linear equations Includes PDE representation by dot product of gradient and a vector field (with plots), and the following: https://reference.wolfram.com/language/tutorial/DSolveLinearAndQuasiLinearFirstOrderPDEs.html ---Inhomogeneous boundary conditions and equations ---Series Solutions 4. Second Order Linear PDE ---Significance of focus on second order PDEs ---Classiﬁcation of 2nd order PDEs (hyperbolic, parabolic and elliptic equations by discriminant with role of coefficient functions). --Wave and Heat equation derivation through physical backgrounds of problems ---Derivation of the (mechanical) wave equation ---Derivation of the electromagnetic wave ---Derivation of the heat equation ---General governing form for a second order non-homogenous model (diffusion and wave) where all derivatives are of order 2 or lower (and possibly mixed derivatives) are relevant with physical phenomena (viscosity, convection, advection, thermal conduction, radiation, external “forces”/influence, etc.), and feasible solutions. 5. Fast Solutions by Separation of Variables ---Fast solutions for ideal heat and wave equations by separation of variables NOTE: concerning Eigenvalue problems with separation of variables, I will go through the cases only once to identify the non-trivial cases w.r.t. meaningful boundary conditions. Sustainable applications ability is more economic than finesse. ---Determination of separability and solutions Linear PDE of arbitrary order Linear Non-homogenous PDE Combination of the former two 6. Further Studies for Separability ---Second order damped wave equation ---Nonlinear Wave Equations by Separation of Variables Zhdanov, R. Z. (1994). Separation of Variables in the Nonlinear Wave Equation. Journal of Physics A: Mathematical & General, Vol 27, N0. 9 Estevez, P. G. and Qu, C. Z. Separation of Variables in a Nonlinear Wave Equation with a Variable Wave Speed. Theoretical and Mathematical Physics(2002) 133: 1490. Hu, J. and Qu, C. Functionally Separable Solutions to Nonlinear Wave Equations by Group Foliation Method. J. Math. Anal. App. 330 (2007) 298 - 311 ---Heat equation with source or sink ---Jia, H. et al, Separation of Variables and Exact Solutions to Nonlinear Diffusion Equations with x - Dependent Convection and Absorption, Journal of Mathematical Analysis and Applications, Volume 339, Issue 2, 15 March 2008, Pages 982 – 995 ---Na. T. Y. and Tang, S. C. (1969). A Method for the Solution of Conducting Heat Transfer with Non-linear Heat Generation. Journal of Applied Mathematics and Mechanics. Volume 49, Issue 1 – 2, pages 45 – 52 ---Nonhomogeneous electromagnetic waves If non-separable (identify method of solution alternatives). Time varying charge density and time varying current; sinusoidal or periodic. Pulsed phenomena (relevant to charge density and current density) 7. Dispersion and Solitons ---Classical modelling of surface water waves ---Third order linear dispersion (separation of variables and meaningful boundary conditions) ---Korteweg–deVries equation (or Boussinesq equation) Assume that the traveling wave is localized, namely, the solution and its derivatives are small at large distances towards a model that has a squared hyperbolic secant function (of time and position). Model, solution (and simulation) of intersection of two solitons. 8. Energy Methods (Energy and uniqueness) ---Treatment for second order linear wave equation and second order linear heat equation. ---Treatment of energy methods for PDE that are nonlinear. Concerns applicable establishment rather than a swamp of real analysis and so forth: W. A. Strauss, The Energy Method in Nonlinear Partial Differential Equations, Notas Mat. No. 47, IMPA, Rio de Janeiro, Brasil Antontsev, S. N. and Shmarev, S. I. The Energy Method. Application to PDEs of Hydrodynamics with Nonstandard Growth. IOP Conf. Series: Journal of Physics: Conf. Series 894 (2017) 012001 A. SJGBERG, On the Korteweg de Vries equations: Existence and Uniqueness, J. Math. Anal. Appl. 29 (1970), 569-579. 9. Legendre Differential Equations and Bessel Differential Equations (Mathematica usage follows modelling towards meaningful quantities with computation and physical representations) ---Synopsis of the relevancy in phenomena ---Elliptic PDE in spherical and cylindrical coordinates; make use of practical boundary conditions. ---The applications of focus: A. For the spatially 2D heat equation finding the equilibrium solution (time-independence solution) if there were no sources; results in reduction to the Laplace equation in spatial 2D. Concerns rectangular body along with the four boundary conditions. Recognition of no initial conditions here. Observation of boundary conditions being linear but not homogeneous. Resolve. B. Newtonian gravitational potential and determination of associated gravity source body geometry (LDE) C. Magnetospheres (LDE) D. Puff of hot gas rising through still air (LDE): A. R. Paterson (1983). A First course in Fluid Dynamics. Cambridge University Press, Cambridge. E. Radial part of the modes of vibration of a circular drum (BDE) F. Heat conduction in a cylindrical object (BDE) G. Electromagnetic waves in cylindrical waveguide (BDE) H. Pressure amplitudes of inviscid rotational flows (BDE) Note: may treat the third subsection in module 6 and module 7 (total) for both spherical and cylindrical coordinates. 10. Fourier Methods of Solution (Mathematica usage follows modelling) Concerns treatment of chosen PDEs, being first or second order, being linear or non-linear with homogeneous or non-homogeneous property. Note: throughout this module students may be asked to reconcile solutions of particular PDEs with earlier methods. Note: this course is neither a mathematical analysis course nor a harmonic analysis course nor a complex variables course. ---Advance fast review of trigonometric integral identities and the associated complete orthogonal system. Advance fast review of periodic functions. ---Definition of Fourier series and computations ---Going from [-pi, pi] to [-L, L] via change of variables and computation. ---Complex Fourier series (CFS) i. Establishing CFS from trigonometric properties ii. Periodic functions and computations iii. Going from [-pi, pi] to [-L, L] via change of variables iv. Convergence criteria via Dini’s test and Dirichlet boundary conditions; with exemption functions examples. Calderon, C. P. On the Dini Test and Divergence of Fourier Series. Proceedings of the American Mathematical Society, Vol. 82, No. 3 (Jul., 1981), pp. 382-384 v. Dini continuity and Dini criterion. ---Fourier Transform (expansions and Integral transforms) ---Finite domain problems only in rectangular coordinates ---Inﬁnite domain problems with Fourier Transform ---The extent of Fourier method with linear AND nonlinear PDEs 11. Green’s Functions (must be completed and Mathematica usage follows thorough instruction modelling) Note: throughout this module students may be asked to reconcile solutions of particular PDEs with earlier methods. ---Idea and purpose. The logistical process. ---Series and integral expansions of Green's functions ---Heat equation boundary conditions (include non-homogeneous) Conventional Oblique Periodic and antiperiodic ---Green’s function for the wave equation (include non-homogeneous) ---Some idea of Green’s function and nonlinear PDEs. The following are two example guides, but there may be others: Khurshudyan, A. (2018). Nonlinear Implicit Green’s Functions for Numerical Approximation of Partial Differential Equations: Generalized Burgers’ Equation and Nonlinear Wave Equation with Damping. International Journal of Modern Physics C volume 29 number 7 Khurshudyan, A. (2018). New Green’s functions for some Nonlinear Oscillating Systems and Related PDEs. International Journal of Modern Physics C volume 29 number 4, 1850032 12. Finite Difference (representation and simulations) Review of module (2). Time spent on this subject concerns establishing numerical models and computational limits. Students will not be asked to manually estimate with finite difference. However, they will be expected to know how to set up numerical method algorithms w.r.t. PDEs given for any property thrown at them (namely, order, linearity, nonlinear, analytic coefficients, and mixed). ---First and higher order (besides 2nd order) partial derivatives (including mixed derivatives) representation for central difference scheme with consideration of order, linearity, nonlinearity, analytic coefficients and combinations. ---Crank-Nicolson (similar to elementary FD) 13. Navier Stokes (overview) What is it? Where did it come from? Why the infamous reputation? What matter-energy configurations/dynamics exhibit Navier-Stokes? Gorguis, A. (2012). A Reliable Approach to the Solution of Navier–Stokes Equations. Applied Mathematics Letters 25, pages 2015 – 2017. Identified is the use of the Hopf-Cole transformation. How practical or robust is the approach? Settings and conditions resulting in simplified forms of Navier-Stokes that can be solved. Prerequisites: ODE, Numerical Analysis, Calculus III Probability & Statistics B MEMO: course serves to be sustainable and future useful; not a sabotage excrement show with all sorts of weird support regions and weird dependence relations among random variables. Course doesn’t serve for pestilence to conjure mess just for the hell of it. Course Literature: Rose, C. and Smith, M. D. (2002). Mathematical Statistics with Mathematica. Springer-Varlag (updated edition may exist) Wolfram Documentation Centre Note: students will be guided to develop multivariate extensions when called upon. Reading will be fundamental concerning use of Mathematica. Outside sources are also feasible. Assessment: Homework 3-4 Lecture quizzes Lectures + R Immersion (with open notes/book) 3 Exams Labs COURSE OUTLINE --> 1. Descriptive Statistics -- Measures of Central Tendency -- Measures of Dispersion 2. Elementary Probability -- Axiomatic Approach -- Combinatorics Note: Selections, arrangements, combinations and such sort are not lifesaving tools, thus such problems will be quite limited. -- Probability Theorems Note: Drawing balls, picking cards, gender matching and such sort are not lifesaving tools, thus such applications problems to be limited to 2 sessions. 3. Discrete Probability Distributions -- Discrete random variables. Cumulative distribution and its properties for discrete random variables -- Expected value, variance and standard deviation -- Poisson Distribution -- Binomial Distribution -- Negative Binomial -- Poisson as approximation to binomial 4. Continuous Probability Distributions -- Continuous random variables. Cumulative distribution its properties for continuous random variables -- Expected value, variance and standard deviation -- Uniform Distribution -- Exponential Distribution and relation to Poisson distribution -- Normal Distribution; binomial distribution converging to normal distribution for large trials -- Normal distribution and Law of large numbers -- Central Limit Theorem -- Gamma Distribution and related distributions 5. Multivariate Probability Distributions (independent and dependent RVs) -- Multivariate Distributions -- Marginal and Conditional distributions -- Sums of Independent Random Variables -- Expected values for a function of random variables -- Bivariate Normal Distribution -- Conditional distributions and Expectations 6. Covariance and Correlation 7. Moment Generating Functions (optional) Meaningful use. If it’s not practical with realistic applications, don’t bother. Limit MGF determination exercises, table will be provided. COMPUTATIONAL LABS --> Most (not all) built-in or package functions encountered or learnt are mainly for establishing consistency. Instructors are only responsible for logistics development, whereas students will be responsible for actual code writing and implementation. Instructor will assign problems while students will be responsible for data modelling, computation and simulations. Students will have available guides and on-line sources to complete their assignments. For each module there will also be questions sets where students will be required to provide analytic writing that complements data analysis or plotting or computational or simulation activities. Note: students should be introduced to palettes and non-computational “italics” in Mathematica so they don’t need to waste paper. Wolfram Mathematica Documentation Center and probability with Mathematica texts can boost detailed labs and other interests. NOTE: labs will have analytical quizzes, where Mathematica is at your disposal to give values. 1. Elementary statistics Computation of probabilities, expectation, variance and standard deviation (univariate) from data sets. Students will be responsible for pursuing different types of real data sets to generating summary statistics. 2. Random variables and distributions Probability mass and density plotting for intervals and inequalities; includes cumulative distribution determination (discrete and continuous). Concerns Geometric, uniform, binomial, Poisson, normal, Gamma, Gamma related. Review of determination of respective expectation, variance and standard deviation (discrete and continuous) General Plots Histograms and mass/density Inequality or intervals Simulating random variables from experiments (analytical and with R). Simulate practical experiments (uniform, exponential, Poisson, binomial, normal). Learning to generate simulation (sample) data from from different distributions. Students will be responsible for pursuing different types of real data sets, providing histogram/frequency representation with comparative view of densities believed to model data. 3. P-P plots, and Q-Q plots Students will be responsible for pursuing different types of real data sets to apply. 4. Simulation insight into the Law of Large numbers and Central Limit Theorem versus the Law of Large numbers. Development of real experiments or circumstances. 5. Multivariate Distributions (independent and dependent RVs) Review of multivariate distributions and properties (discrete and continuous). Plotting PDFs and CDFs. Simulating pairs of jointly distributed random variables (monte carlo) Simulating joint density and accompanying histogram (monte carlo) Simulating probability conditions (monte carlo versus direct functions) 6. Conditional Probabilities & Conditional Expectations 7. Estimating probabilities and expectation with dependent random variables (like meeting a date to a movie problem). Simulation or computation insight into the Birthday Problem example (investigates the least number of people required if the probability exceeds one-half that two or more of them have the same birthday); other problems similar to such. 8. Extend (6) to dependent variants. 9. Learning to generate simulation (sample) data from bivariate distributions, having data geometrical display alongside marginal distributions and joiint distributions. Will also have real data counterpart. Commentary expected throughout. 10. Monte Carlo methods in practice -Estimate and simulate Buffon’s experiment. Estimating various quantities. Univariate and multivariate integrals by hit-or-miss Monte Carlo; where students must develop each monte carlo and estimate. Commentary expected throughout. -Univariate and multivariate integral evaluation by expectation via uniform random variables; where students must develop each monte carlo and estimate. Commentary expected throughout; to be compared to Hit-or-Miss approach. -First Year Net Profit Monte Carlo Identification of formula Uncertain Variables (Unit Cost, Sales, Price) Uncertain Functions (Net Profit) & Statistics The Flawed Average Model -Product demand forecast -Cobbs-Douglas production function and CES production function -Yee, W. (2019). Monte Carlo Simulations: The Intersection of Probabilistic and Deterministic. Towards Data Science. Critical question---concerning the prior article blog, what will be the new structure if one considers market segmentation in seating class where each class has a seat cap? -Value at Risk Comprehending the measure and structure Monte Carlo simulation Expected will be coding and simulation with customary functions versus package usage. -CVar and Expected Shortfall (ES) monte carlo Comprehending the measures and structures. How are CVar and ES approaches unique to simple VaR? Expected will be coding and simulation with customary functions versus package usage. 11. Covariance and Correlation A. Will decide upon densities to generate random sample sets, where each set has 20 – 25 elements. Based on earlier analytical modelling with covariance and correlation for discrete sets will programme covariance and correlation in R. correlation matrix for a high number of variables. B. Use of financial data, economic data, etc., etc. C. Generating scatter plots with data for visual information D. Correlation as the geometric mean of regressions E. Generating heat maps and interpretation Prerequisite: Multivariate Calculus (no exception) Data Programming with Mathematica: Course serves towards advance syntax for development and manipulation. Hence, this course may be difficult or repulsive to students not acquainted with Mathematica. Beneficial towards Quantitative/Computational Finance, Computer Science, Physics, Chemistry and Geophysics majors. Students may gain the most out this course when assigned projects with step assignments, then to investigate how their interests can apply to such, leading to mini projects of interest. One shouldn’t necessarily believe that instruction serves as highest potential with use of functions and development. Functions in the Wolfram Mathematica language are highly versatile in many applications and with other functions. Most individuals will not have an affinity for such, so interests and reading texts involving the use of Mathematica will amplify one’s imagination with the many uses. One should also realise that there are hundreds to thousands of functions in Mathematica catering for various purposes. One should start with their interests, develop, reinforce, then challenge themselves with new ideas. This course will have no environment that allows or encourages majority trends and intimidation. The only culture that should arise is what an individual pursues to accomplish. This course serves as no means to promote or elevate any polarizing social expectations with any type of group that is a majority in course. Students in life should not be hoodwinked by con artists conveying coding expertise in everything; again, there are thousands of functions in the Wolfram Language. Don’t subjugate oneself to gaudy or extravagant fodder shows from others. The foundation of this course serves to be the most constructive and economic towards retention, versatility and practicality. NOTE: it may be inevitable that you encounter things in advance without intent; such is natural due to demands with “data structures”, goals and related interests. NOTE: will be open exams. It’s not a competition about who can first assemble their guns and shoot the other in the head. You are your own best friend, and also your worse enemy. You don’t have to care about how Mathematica markets its product if you help yourself rather than being toxic or ring worm. Course grade constitution: I. Assigned tasks constituted by step assignments 25% Such will be activities where students research the wolfram language and acquire programming remedies. Often instructor will provide abstracts and conceptual framework for a task, where you must figure out programming to implement whatever. II. There will be exams based on the conventional constructive practical syntax stemming from lectured subjects, and resembling past assigned tasks. There may be problems where students will have to complete or correct code or determine whether code does what is conveyed about it. Students may be asked to extend code as well. Students will also be given a conceptual model, task or computation to design. Students can make use of Mathematica in exams for meaningfulness. There will be 4 - 5 exams for 40%. NOTE: will be open exams. It’s not a competition about who can first assemble their guns and shoot the other in the head. III. Mini interest projects (in Mathematica notebook) that apply given course instruction (and possibly with other past instruction). Students can incorporate past instruction and independent development in projects if feasible and practical. To have substance and meaningfulness students will inevitably also incorporate some things from Mathematica not lectured in course, however most development must be based on declared lecturing. Students can incorporate their mathematical and science level skills to serve themselves. For projects of interest students will develop logistical blocks and routines to accompany build and demonstration of their projects. Must have PDF copy print out as well. 3 individual projects 15% IV. Major final project. For projects of interest students will develop logistical blocks and routines to accompany build and demonstration of their projects. Must have PDF copy print out as well. Project will be individual 20%. Course is an environment of learning and encouragement rather than failure by imposing attempted conformity with interests. Note: due to the pursuits of interests, naturally, students to independently acquaint themselves with functions not encountered in instruction and assigned tasks. For one particular subject comparing multiple texts is an excellent means towards acquiring progression. When comparing texts, it may take up to ten times or more for you to realise that a particular method or orchestration in some text (staring at you) may be the most engaging to build on. Plan things out with conceptual development before jumping into a self-made “Jumanji”. Additionally, one must be able to apply structuring to various applications of interest. How does the structuring come into play from one circumstance to another? Learning and retention are not “one-stop” implementations. Challenge yourself with contrary development circumstances or with further interests. Course will be longer than usual courses. One shouldn’t necessarily believe that instruction serves as highest potential with use of functions. Functions in the Wolfram Mathematica language are highly versatile in many applications and with other functions. Most individuals will not have an affinity for such, so interests and reading texts involving the use of Mathematica will amplify one’s imagination with the many uses. One should also realise that there are hundreds to thousands of functions in Mathematica catering for various purposes. One should start with their interests, develop, reinforce, then challenge themselves with new ideas. Texts of consideration: -The Mathematica Book, by Stephen Wolfram -The Mathematica Guidebook for Programming, by Michael Trott -Mathematica: A Problem-Centred Approach, by Roozbeh Hazrat -Mathematica in Action, by Stan Wagon -Essentials of Mathematica by Nino Boccara -Mathematica Cookbook, by Sal Mangano NOTE: for each Mathematica function it’s quite important that you comprehend the scope of all parameter options. As well, you must know how make choice of method of interest. Read the damn documentation center sources well. NOTE: the Wolfram Data Repository will be accessible throughout. Other data sources can be applied as well to be self-reliant and versatile. NOTE: students should practice drawing up the logistics for computational schemes, rather than diving blindly into large tasks or projects; your logistics is your business, namely, will be doing actual programming. Don’t mess yourselves and the future students of this course; your antics can carry over to the future. Your lecturer, etc. should belong in this course, not because of some social excrement show, thug rent seeking and nonsense social toxicity. Course layout --> 1. Basic features of Mathematica notebook Brief survey of capabilities Interacting with the front end Basic concepts and first look at some important functions Documentation Constructs (enforced throughout course) -- > https://reference.wolfram.com/language/tutorial/DocumentationConstructs.html “Insert New Cell”, Palettes, features in “Help”, and Notebook Modification History. Note: other features of Mathematica are left to students’ interests; everything can’t be taught. 2. Calculus Operations & Plotting (single and multivariate) Note: rewiew analytical development before Mathematica development Point evaluation and function evaluation on sets polynomials, exponentials, logarithmic, trigonometric, abstract functions Include “list” or array generation Include developing scatter plots Basic plotting syntax and embellishments (includes plot styles) What’s the difference to scatter plots prior? Review equation for a line determination based on two points; includes identification of axes intercepts Interpolation (Mathematica logistics and implementation only) Axis labelling & curve labelling Plot types and embellishments (with prior) Manipulate function Plotting Data and Mixing several kinds of plots into a single graph Will make use of ListPlot, Show, GraphicsColumn and GraphicsGrid functions. Note: for some functions scaling may be an issue concerning display of characteristic features. As well, prior topics to be infused when practical. Calculus operations of functions Intersection points Root finding Differentiation Integration Note: in progression often such features and tools complement each other towards advance details. 3. Synthetic Data Consider the case where your profession may be in the field of marketing/revenue management, actuarial science, etc. where there isn’t luxury or access to data of interest. What can you do? Generating simulated data sets in order to explore modeling techniques or better understand data generating processes. The user defines the distributions of individual variables, specifies relationships between covariates and outcomes, and generates data based on these specifications. The final data sets can represent randomized control trials, repeated measure designs, cluster randomized trials, or naturally observed data processes. Other complexities that can be added include survival data, correlated data, factorial study designs, step wedge designs, and missing data processes. Adding data to an existing data table. Aside from generating new data sets (as in prior) from scratch, it’s often necessary to generate the data in multiple stages so that we would need to add data as we go along. For example we may have multi-level data with clusters that contain collections of individual observations. The data generation might begin with defining and generating cluster-level variables, followed by the definition and generation of the individual-level data; the individual-level data set would be adding to the cluster-level data set. 4. Import & manipulate data (.xls, .xlsx, .csv, .accd, .mde). APIs and API keys. 5. Database Usage (subject to 4) Cleaning/Wrangling Projects Methods for missing data (to pursue) Kang H. (2013). The Prevention and Handling of the Missing Data. Korean J Anesthesiol. 64(5): 402-6. Treating missing data in Mathematica Summary statistics generation 6. Creating data frames from prior data or prior data frames (subject to modules 3-5) 8. Data Frames Making a Grid of Output Data: Wolfram Documentation Center Make A Grid of Output Data Summary statistics generation Note: sets with high volume of raw data will need more ingenuity with labelling; it’s sensible to know the set’s length before pursuing such. Practical Operations on your data frames 9. Structured Data in Science and Engineering from Mathematica Operations with ElementData, ChemicalData, ParticleData, ParticleTable, ProteinData, FinancialData, etc, etc, etc. In the Wolfram language there’s also geophysical data, say “Earth sciences: Data & Computation”. Advance data acquisition and manipulation example: ETF=FinancialData[#, “Return”, {{2008, 2}, {2013, 2}, “Month”}] [[All, 2]] &/@ {“EWA”, “EWC”, “EWG”, “EWJ”, “EWU”, “SPY”, “EWS”} Note: in the example above the specified parameters (excluding the operators are unique to FinancialData. This ETF array defined can be operated on or manipulated in many more advanced ways. Case Study (just surveying mostly): Malacarne, R. L., Canonical Correlation Analysis, The Mathematica Journal, Volume 16, Jun 23 2014, 22 pages Data structured in above article is dependent on the FinancialData function. However, one can pursue similar array structuring with other data functions, files and external sources. Structuring data (frames) from the mentioned prior specific functions 10. Data Analysis Review For descriptive statistics Mangano’s text, Chapter 12, pages 455 - 504 (has good summary data forms). Will treat some of the topics, but with real data rather than synthetic data from RandomReal and RandomSample. Modules (3) through (8) may or may not come back to haunt. 11. Basic Regression immersion All will be highly strategic rather than a comprehensive environment. Mathematica tools for regression. Justifying variables for models. Choosing between OLS, WLS and GLS choice. Summary statistics and interpretation. 12. Basic Time Series immersion All will be highly strategic rather than a comprehensive environment. Mathematica tools for salient characteristics/decompositions. Model process for time series: selection, estimation, validation and diagnostics. Summary statistics. Forecasting and error. 13. Introductory Machine Learning Wolfram Documentation Center Machine Learning Note: cleaning, wrangling and data description will come back to haunt. For any chosen respective Mathematica ML function one should have a firm understanding what it does, its strengths and limitations. Programming Data Sets (for training, testing, validation); must be relativity large towards performance credibility. Data of consideration will be real data from various applications involving real systems, natural phenomena, processes, etc. If data of meteorology and oceanography are to to be applied, to be annual or seasonal in range and nothing shorter since atmospheric and oceanographic behaviours are highly dynamic in the short term concerning fluid dynamics and thermodynamics where oceanographic and atmospheric behaviours are often “coupled” or influence each each other. Means of improving accuracy. Assumption of no cognition bias in ML; it’s the programmer/researcher who is at fault involving what’s in their minds and possible neglect, augmented by whatever is being put out there. Will be restricted to the following areas: Wolfram Data Repository Supervised Learning Multivariate Regression review: variables choice, OLS/WLS, summary statistics interpretation. Validation. 2 other versatile and robust types Unsupervised learning Clustering Association Dimensionality Reduction 14. Hiding your code (applicable to prior and future instruction) Prerequisites: Ordinary Differential Equations, Numerical Analysis, Probability & Statistics B

Stochastic Models & Computation For quality instruction and sustainable skill sets of value in Scientific Computation, the duration of the course of Stochastic Models & Computation to be longer than other courses of “traditional” semester duration, meeting at least two days per week, for a minimum of two and a half hours each day. There will be heavy emphasis on mathematical derivation, modelling accompanying scientific computation. Modules of the class must be thoroughly completed in full. Development of code concerns credibility towards professional endeavors in various industries of society. There will be written and coding assignments, accompanied by written and coding examinations (take home and/or in class). Instructors are mostly responsible for practical and fluid modelling, and conceptual development and logistical flow for code and computation, whereas students will be responsible for actual writing and implementation. Algorithms to be designed in class, and independently outside of class based on assignments and projects. On exams students are required to develop the mathematical structuring followed by design code on test paper. Course provides no formal engagement of Markov chains. Course serves towards students being fluid, tangible, practical, useful and having respect for the precious time of others and themselves. A Wolfram Mathematica environment course. Students’ potential aren’t confined to the ambiance tone or rhetoric. Course doesn’t assume students have an affinity or innate ability for such technical activities (aside from mathematical skill), however, active interest in applications and study outside of class sessions are the best means for a student to become comfortable with language structures or syntax schemes. There is no regression nor cap policy regarding the level of mathematical coding; prerequisites satisfaction for this course (Multivariate Calculus, Differential Equations, Probability & Statistics B, Numerical analysis). Exposure to elementary scientific computation in the four mentioned prerequisites classes will be an invaluable asset. Course aims to introduce and develop stochastics in the most natural way, i.e., simple logical experiments and relevance to physical science, rather than a synthetic, mundane and frustrating scheme of pure mathematics. NOTE: students should practice drawing up the logistics for computational schemes, rather than diving blindly into large tasks or projects; your logistics is your business, namely, will be doing actual programming. Don’t mess yourselves and the future students of this course; your antics can carry over to the future. Your lecturer, etc. should belong in this course, and not because of some social excrement show, thug rent seeking and nonsense social toxicity. Assignments & Projects: 30% Exam 1: 15% Exam 2: 15% Exam 3: 15% Final Exam: 25% NOTE: if you think you are going to turn this course into Markov chains fodder with matrix algebra, find another course immediately outside of the institution. I don’t care about you pretending that you understand stochastic models and computation with shows of matrix algebra. If you can’t develop, it doesn’t matter. I will not encourage bamboozles about modelling and algorithms as the successor to matrix perversions. If I ask you to model, simulate and compute, then just do that. I don’t care what upper triangular, lower triangular and adjoint[adjoint[adjoint] looks like. Outline--- 1. Simulations & Data Manipulation: ---Real Experiments Histograms, frequency simulations & measures of central tendency ---Probability Axioms review ---Simulating for a random variable of chosen sample size that contains a set of values with the correct relative frequencies such that a respective given proportion corresponds to a respective given value from the set. ---Simulating data when real data of interest are unavailable ---Introspection, queries and data wrangling Data import and extraction from various sources (financial, scientific, engineering, .com, .xls, .xlsx, .csv, APIs). Making data frames from acquired data ---Development of summary statistics from data (raw data and made data frames) ---Development of random variables, and corresponding probabilities to outcomes (upon data). Simulating random variables from real data sets manually with small data sets Histograms, density plots, q-q plots ---Use of ListPlot, DistributionFitTest, LocationTest, VarianceTest 2. Elementary Monte Carlo for ideal phenomena (with simulations): ---Monte Carlo method as any process that consumes random numbers ---Waiting and Poisson processes (rapid review) ---Consider phenomena or dynamics that are generally assumed to abide by the Waiting/Poisson process. Means of simulating data for a respective circumstance and determination of good sample sizes. ---Coin tosses and binomial processes (rapid review) ---What phenomena or dynamics are naturally normally distributed? What arguments allows for such? What is a good sample size? Means of simulating data for a respective circumstance and determination of good sample sizes. ---Hit-or-miss methodology (rapid review) Analytical development and primitive programming Compare with computation NIntegrate[f, {x, a, b}, Method--> “MonteCarlo”] ---Crude (or Mean-value) Monte Carlo Compare with computation NIntegrate[f, {x, a, b}, Method--> “MonteCarlo”] and primitive programming ---Comparison between Hit-or-Miss approach and Crude Monte Carlo by analysis of unbiasedness and minimal variance. ---Such estimations will be compared with built-in quadrature tools in Mathematica, and integration approximation via Maclaurin approximation. ---Review of monte carlo applications First year net profit Demand forecast Yee, W. Monte Carlo Simulations: The Intersection of Probabilistic and Deterministic. Towards Data Science (2019) ---Variance Reduction Methods A. Why do that? B. Control Variates C. Usefulness of Hastings-Metropolis and Importance Sampling Solely on integration (single and multivariate) D. After applying (B) and (C) for specific examples, compare with the options of monte carlo strategies from “Crude Monte Carlo and Quasi Monte Carlo Strategies” and “Global Adaptive Monte Carlo and Quasi Monte Carlo Strategies” in the Wolfram language. Involves estimate with developed code of Hit-or-Miss approach and Mean-value monte carlo. Substantial intervals to be chosen. Is it meaningful or practical for monte applications such as first year net profit, demand forecast and Yee’s article? ---Review and applications implementation of Value at Risk Comprehension of the extent or meaningfulness of valuations or measures concerning strong practical realistic applications. Monte Carlo method Are variance reduction methods relevant or practical? Expected shortfall and stressed expected shortfall monte carlo (applications intensive) ---Ted G. Eschenbach & Robert J. Gimpel (1990) Stochastic Sensitivity Analysis, The Engineering Economist, 35:4, 305-321 Are variance reduction methods significant or relevant? Will pursue multiple applications to computationally develop ---Monte Carlo for the World Cup Etienne Bernard, Predicting Who will the World Cup with Wolfram Language, Wolfram Blog, June 20, 2014. Etienne Bernard, World Cup Follow-Up: Update of Winning Probabilities and Betting Results, Wolfram Blog, June 26, 2014. For both priors can one grasp any sense of variance reduction? Is variance reduction relevant here? Will also apply to following World Cup events. 3. Boundary condition problems by stochastic algorithms: A. Walk on Spheres (WOS) B. Green’s Function First Passage (GFFP) Students to develop both loop algorithms and the Wolfram language analogy for chosen types of PDEs. Also involves determination of what type of PDEs are applicable in regard to the presence of linearity, non-linearity, homogeneity and non-homogeneity; can be combinations out of such. 4. Development of Stochastic Processes via probability densities and loops ---Going from deterministic DEs to stochastic DEs ---Solutions of such SDEs with meaningful interpretation of expectation and variance to be introduced as well (with geometric exhibitions). Probability distribution of the respective stochastic process (with proof). ---Mathematical argument for the use of loops to generate randomness (stochastic behavior) involving probability spaces. ---Modelling and simulation trajectories by loops via Gaussian densities (and perhaps other densities as well), and their applications. Note: loop algorithm development to be flanked by function development from the following text: Computational Financial Mathematics Using Mathematica, by Stojanovic, Chapter 2, pp 34 – 45. Concerning stochastic generators, students must comprehend generating components both in terms of loops and the Wolfram language, and how they function in the same manner. A. Brownian Motion (BM) (i) Origins in physics (ii) Drunkard’s Walk construction in a plane and constructing a simulation by means of a developing a binomial lattice (BL) model, say, repeated highly compact Bernoulli trials. Simulate for various parameter values where the Manipulate function can serve well. (iii) Solution of BM. Models for expectation and variance to be acquired as well. Probability distribution of the stochastic process (with proof). (iv) Random Walk modelling, and simulation by loop design involving Gaussian density. Brownian Motion with drift; developing BM simulation in Mathematica. What is noise and what is the cause? Simulate for various parameter values where the Manipulate function can serve well. B. Geometric Brownian Motion (GBM) (i) First, Informally, introduce the SDE for Geometric Brownian motion and its features that differentiates it from (A). (ii) For the exact form of GBM find the resulting expectation and variance of GBM. For GBM SDE establish the probability distribution (with proof). then simulate via use of loop and probability density. (iii) Simulate via use of loop and probability density; developing BM simulation in Mathematica. Simulate for various parameter values where the Manipulate function can serve well. (iv) BL from (Aii) as an approximation to GBM and convergence. Note: emphasis done without specific application of stocks. 5. Ito Calculus: Note: complementing theoretical modelling and development will be computational programming structuring based on the following text: Computational Financial Mathematics Using Mathematica, by Stojanovic, Chapter 2, pp 46– 55; students must also be able to establish the loop programming counterpart. A. Riemann-Stieltjes Integration B. Ito’s Lemma C. Ito Process (with simulations where the Manipulate function can serve well). Solution of this SDE to be derived; expectation and variance as well. D. Deriving Ito SDE from probabilities E. Show that BM and GBM can be treated by Ito’s formula. 6. Martingales and Martingale Representation Theorem: ---Definitions and models for practical use with Martingales ---Applications of the Martingale Representation Theorem ---Girsanov theorem with choice of trajectories due to likelihood under the martingale measure Q (density transformation from P to Q). Applying theorem to stochastic processes in (4) and (5). Realistic applications. 7. It’s also most practical and good to develop code with interactive parameters, namely, making use of the “Module” function and the “Manipulate” function on parameters for SDE. Additionally, for programming stochastic processes with loops one should consider the advantages and disadvantages of non-uniform time steps. An example: Bozoudis, M., “Geometric Brownian Motion with Nonuniform Time Grid”. Wolfram Demonstrations Project. 8. Stochastic Dynamic Models Allen, L. (2010). Chapter 8. Diffusion Processes and Stochastic Differential Equations, pp 359 - 408. In: An Introduction to Stochastic Processes with Applications to Biology. Philadelphia: CRC Press LLC. For the Kolmogorov backward equation and Kolmogorov forward equation make certain to establish the rationale for adjectives “forward” and “backward”. As well, to determine which of the two PDEs can best represent the following processes: scaled BM, scaled BM with drift, GBM, Ornstein-Uhlenbeck, Black-Scholes equation. 9. Applied Stochastic Modelling: ---Applications, modelling, derivation and simulation of specified SDE and their stochastic behaviours. Validating the extent of Martingale Representation & Girsanov theorem (if possible) A. Langevin modelling Focus here is acquiring the SDE through modelling stemming from physics and confirming the respective probability distribution. (i) The diffusion of pollutants through the atmosphere (ii) Stochastic resonance with the conventional dynamical system settings for the derivation and/or properties of Langevin model. (iii) The diffusion of “holes” or minute regions in which the electrical charge potential is positive through a semiconductor. (iv) Stochastic flux freezing B. Fokker-Planck modelling Idea and derivation of the Fokker-Planck equation by Laplace or other (if more convenient). What probability distribution satisfies the Fokker-Planck equation and how to confirm such? Establish the Fokker-Planck equation corresponding to the time dependence given by a Langevin equation; F-K governing the time evolution of the probability density of “Brownian” particles. Consider the underlying SDE from Langevin modelling and the governing probability distribution. Construct a geometrical exhibition where a simulation resides in the “X-t” plane with evolving P(X, t) providing a three-dimensional exhibition. Through time, how does the variance appear among the various distributions with respect to the “noise” of the simulation? Applications to develop: (i) Cosmic ray propagation. (ii) Noble, P. L., and Wheatland, M. S., Modelling the Sunspot Number Distribution with a Fokker-Planck Equation, The Astrophysical Journal, 732:5 (8pp), 2011 May 1 (iii) Pope, S. B., Simple Models of Turbulent Flows, Physics of Fluids 23, 011301 (2011). (iv) Scale‐dependent fractal dispersitivity introduced in the convective‐dispersive equation of transport in subsurface flow. C. Ornstein-Uhlenbeck (i) Informally introduce the SDE (being mean-reverting and what not). Relation between Ito and OU. Identify the condition(s) that distinguishes/relates it to the Langevin modelling, and establish Martingale representation. (ii) For probability distribution acquirement for the OU: Mahnke, Reinhard, et al., Physics of Stochastic Processes: How Randomness Acts in Time, John Wiley & Sons, 2009, pp 253-273. Relevance to the Fokker-Planck equation. 10. Parameter Estimation of Stochastic Differential Equations Will have limited analytical development based on the given articles, however, will only concern ourselves 2 or 3 methods that are easily retainable, fluid, practical and robust; we want competent and sustainable computational activity with real data in result. Hurn, A. S. and Lindsay, K. A. (1999). Estimating the Parameters of Stochastic Differential Equations. Mathematics and Computers in Simulation 48(4 – 6), pages 373 – 384 David A. McDonald & Leif K. Sandal (1999) Estimating the Parameters of Stochastic Differential Equations using a Criterion Function, Journal of Statistical Computation and Simulation, 64:3, 235-250 Nielsen, Jan & Madsen, Henrik & Young, Peter. (2000). Parameter Estimation in Stochastic Differential Equations; An Overview. Annual Reviews in Control, 24. 83-94. Bishwal, J. P. N. (2008). Parameter Estimation in Stochastic Differential Equations. Springer Weber, GW., Taylan, P., Görgülü, ZK., Rahman, H.A., Bahar, A. (2011). Parameter Estimation in Stochastic Differential Equations. In: Peixoto, M., Pinto, A., Rand, D. (eds) Dynamics, Games and Science II. Springer Proceedings in Mathematics, vol 2. Springer, Berlin, Heidelberg. The SDEs of concern: A. Brownian Motion B. Geometric Brownian Motion C. Ito process D. Ornstein-Uhlenbeck process ---Mathematica functions for SDEs Mathematica functions will be investigated concerning treatment of all prior SDEs and the various primitive tasks done for each SDE encountered It’s also practical good to have interactive parameters, namely, making use of the “Manipulate” function on parameters for the respective SDE Monte carlo statistics (within a confidence band or not) Mean path, Min and Max within confidence bands Includes monte carlo statistics (within a confidence band or not) Means to acquire distributions Will critique with acquired analytical manual skills learnt earlier Parameter Estimation 11. Feynman-Kac formula: A. Recall the heat equation and its Fourier solution form via separation of variables. Then acquire the Gaussian solution form. How does one relate the deterministic solution form to the Gaussian solution form? Why is there a connection between Brownian motion and the heat equation? B. Relation between parabolic (or elliptic) PDE and stochastic processes; important class of expectations of random processes can be computed by deterministic methods. Proof of relation via Ito’s Lemma. C. Establish relation between backward Kolmogorov PDE, forward Kolmogorov PDE, Feynman Kac formula and Fokker-Planck. 12. Stochastic approach to Quantum Mechanics (time permitting): Okamoto, H., Stochastic Formulation of Quantum Mechanics based on a Complex Langevin Equation, 1990 J. Phys. A: Math. Gen. 23 5535 Time permitting, this module will be discussion-based, through derivation only, hence, will have no influence on grade unless questionable conduct exists. Prerequisites: ODE, Numerical Analysis, Probability & Statistics B. Co-requisite: Mathematical Statistics. Mathematical Statistics: A major portion of the course will be focused on computational development with data and simulation for professional and constructive practice based on instructed analysis and modelling from lecturing. A computational environment is emphasized towards developing professionalism and integrity, else much would be useless or barely meaningful in modern society. Instructors are mostly responsible for conceptual development and flow for code and computation, whereas students will be responsible for actual writing and implementation. Mathematica primarily will be the CAS of interest. Course Literature: Rose, C. and Smith, M. D. (2002). Mathematical Statistics with Mathematica. Springer-Varlag (updated edition may exist) Wolfram Documentation Centre Apart from assigned texts and the designated journal articles, the following provides a very “fresh air” guide to some modules: https://www.itl.nist.gov/div898/handbook/ Note: students will be guided to develop multivariate extensions when called upon. Reading will be fundamental concerning use of Mathematica. Outside sources are also feasible. NOTE: for each Mathematica function it’s quite important that you comprehend the scope of all parameter options. As well, you must know how make choice of method of interest. Read the damn documentation center sources well. NOTE: in the Mathematica environment there is the Wolfram Data Repository available; not necessarily confined to it however. Homework and Projects 30%--> Standard problems Recital of chosen prerequisite labs Computational and simulation homework assignments and projects to be included with considerable weight in final grade, which accompanies handwritten homework problem sets to be turned in. Labs with Mathematica 40% --> Without experience and competence with a CAS concerning Statistics, an analytical framework is extremely limited. Such follows the relevant fast review of analytical structure. Furthermore, expect labs to have labs quizzes. Exams 40% --> Hand written tests cannot exceed 40% percent of final grade. There will be 4 exams, hence cramming will not be encouraged. Limited open notes. I don’t like setting up myself and students for embarrassment; you are not perfect with statistics, so expect exams to be primarily knowledge based and the calculus related fodder. Most of your development will come from homework and labs; it is what it is. COURSE OUTLINE --> 1. Generating summary statistics for raw data 2. Review of Probability Distributions and their properties (Uniform, Exponential, Poisson, Binomial, Normal) 3. Simulations: Identifying frequencies from real data & finding cumulative distribution Techniques for simulating random variables Will make use of real experiments Will use a CAS (Mathematica) 4. Distribution of data Import & extraction from sources (htm, .html, .xls, .xlsx, .csv, .com, APIs) Introspection, Import and Wrangling (APIs, addresses, file types) Elementary determination of distribution of data Summary Statistics (include skew and kurtosis) Density Plots P-P and Q-Q 5. Law of Large Numbers and the Central Limit Theorem Introduce the Central Limit Theorem (CLT) and Law of Large Numbers (LLN). Identify Poisson and Binomial data and respectively determine in a manner to confirm LLN and CLT. Routledge, R., Chebyshev’s Inequality, Encyclopaedia Britannica Is there too much reliance on assuming normal or Gaussian distribution? Towards Chebyshev’s inequality what amount of repetition (regarding LLN and CLT) of an experiment is adequate towards Chebyshev becoming relevant? Overview and goals of concentration inequalities (just a survey). 6. More Normal distribution analysis| Limpert, E. and Stahel, W. A. (2011). Problems with Using the Normal Distribution--and Ways to Improve Quality and Efficiency of Data Analysis. PloS one, 6(7), e21403. Ghasemi, A., and Zahediasl, S., Normality Tests for Statistical Analysis: A Guide for Non-Statisticians, Int J Endocrinol Metab v. 10(2); Spring 2012 7. Estimation and properties of estimators Method of maximum likelihood Method of moments. NOTE: practice examples for particular distributions manually done only serve towards establishing primitive mathematical mechanics with MLE and MoM. Realistically, very small sample size data yield highly erroneous estimations; one can’t acquire a smooth and appropriate density with small data sizes. Computational skills are critical to be relevant in any field at all. A. Binomial parameter estimation from sample data Small binomial sample for manual practice, then followed by large sample towards immersion with computational tool. Is your data well behaved towards binomial? Then what? B. Poisson modelling by use of real practical data Small Poisson sample for manual practice, then followed by large sample towards immersion with computational tool. For Poisson modelling with large sample choose ambiances with high activity. Is your data well behaved towards binomial? Then what? Examples: The number of gun related injuries per day, followed by per week, then by per month, then by per year. Such is a means to observe what specified durations fit the model well and what periods yield the highest activities for the respective duration. Patients arriving at emergency rooms per day, followed by per week, then by per month, then by per year). Such is a means to observe what specified durations fit the model well and what periods yield the highest activities for the respective duration. The number of bankruptcies that are filed in a week, followed by month, then by year. Such is a means to observe what specified durations fit the model well and what periods yield the highest activities for the respective duration. C. Normal, Maxwell-Boltzmann, Weibull Small sample concerning respective distribution for manual practice, then followed by large samples towards immersion with computational tool. D. Cramer-Rao inequality, Rao-Blackwell theorem 8. Confidence intervals (with relevance to module 6) Normal confidence intervals Standardization of variables. Why? Uniform confidence interval Poisson confidence interval Binomial confidence interval Lognormal confidence interval 9. The Chi-Square distribution The bottom line is to establish the flow of the uses competently with applications involving real raw data. The Chi-Square structure and its features Comprehending categorical and ordinal data. Probing real data sets. Includes means to converts character instances to numeric. Sensitivity of categories concerning traits of interest. Test for independence McHugh ML. (2013). The chi-square Test of Independence. Biochem Med (Zagreb). 23(2): 143-9. Using Fisher’s Exact Test as an alternative Test of homogeneity Test of variance Applications of the Chi-Square distribution with confidence intervals for the exponential lifetime mean. Why the emergence of Chi-Square? 10. T-Distribution & F-Distribution Often such distributions are introduced to intimidate and discourage students by means of memorization for paper tests. Realistically, such distributions barely exists in the real world. In this course understanding why and when to use, with applicability and practicality in a computational environment for such distributions is the only goal. Will not use bamboozle intellect with synthetic hypothetical parameters, rather, will make use of real raw data. Memorizing the mathematical models for the distributions will not be forced, rather use of computational tools with real raw data and practice for such. T- distribution Structure and Parameters of concern for the T-distribution Kim T.K. & Park J. H. (2019). More About the Basic Assumptions of T-test: Normality and Sample Size. Korean J Anesthesiol. 72(4): 331-335. Determinations with the T-distribution Sample size determination Population parameter estimation Confidence intervals F-distribution Structure and Parameters of the F-distribution Assumptions for the F-distribution Determine if the variances of two populations are equal by the F-distribution Note: consult with Mathematica resources. The bottom line is to establish the flow of the uses competently with real data. 11. Goodness-of-Fit Note: assumption generally by many is that hypothesis testing should be before goodness-of-fit. However, I don’t like jumping into things assuming normal distribution for every all. A contrary stance is dangerous. Comprehension and logistics for particular measures and values involved will be treated concerning their presence in active computational modelling. Primitive computations and analysis: Review module (4) Box Plots Skewness Kurtosis Statistical Tests Definition, Null hypothesis, one-sided & two-sided tests of hypothesis Types of test statistics Comprehending critical values for ideal distributions Significance levels Comparing critical values for real raw data sets Does your data distribution exonerate ideal models? Advance Distribution Determination Tests: Jarque–Bera tests of normality Ghasemi, A., and Zahediasl, S., Normality Tests for Statistical Analysis: A Guide for Non-Statisticians, Int J Endocrinol Metab v. 10(2); Spring 2012 Chi-square Goodness of fit test Kolmogorov-Smirnov test Anderson-Darling test Shipiro-Wilk Test A project based component of the module, to make use of various data that one suspects will follow the Poisson distribution concerning the following article < Brown, L. D., and Zhao, L. H., A Test for the Poisson Distribution, Sankhyā: The Indian Journal of Statistics, Series A, Vol. 64, No. 3 > Note: students will also be responsible applying other test distributions to identify possible better candidates for distribution fit. Olson, D. L. and Wu, D. (2013). The Impact of Distribution on Value-At-Risk Measures. Mathematical and Computer Modelling 58, 1670 – 1676 Note: students will also be responsible applying other test distributions to identify possible better candidates for distribution fit. MLE and/or MoM for parameter estimations based on assumed or determined distribution. Note: it’s customary to implement MLE and/or MoM manually for integrity, but in the real world data sets are extremely large. 12. Hypothesis testing (project based module for real world decision making) Note: I don’t like cult paraphrasing or degenerative attempts to minimalize ability. If you’re not here to be practical, then get out of my class. Lecturing primary concerns the competent development of logistics for computational activity in hypothesis testing. There is no “cue card” lecturing/problems involved, rather, what and when to use for meaningfulness in applications. Will recognise promptly the limitations of z- scores with normal distribution rather than being overwhelmed with fodder; cases where sample sets just aren’t normal at all is most realistic. I will not ask you to memorize formulas, rather knowing what they’re used for and how to implement them in a computational environment. A. Steps of Hypothesis Testing: I. State the two hypotheses so that only one can be right. II. Formulate an analysis plan, which outlines how the data will be evaluated. III. The third step is to carry out the plan and physically analyse the sample data. IV. The fourth and final step is to analyse the results and either reject the null hypothesis, or state that the null hypothesis is plausible, given the data. Based on such steps students will acquire real data out there to administer hypothesis testing. NOTE: modules (10) and (11) will be crucial. Question to consider: Are your hypotheses even practical? Topics of concern (all to be done): Testing the significance of the correlation coefficient Module (9) Regression models (interpretation of the summary statistics) Note: no use of T-tests and F-tests extensively. Else, if you want that you can go find various texts and work with faculty that actually likes you and your attributes with your personal time. If you do you use it, you must confirm it’s applicability sans any data transformation/manipulation. If assumptions for respective test is not met, then identify appropriate alternatives and apply. Students will develop projects with various real data. Then will implement the prior 3 topics of concern based on the given HT steps. Does your conclusions agree with your hypotheses based on the above topics? Not interested in being dictated to with applications not of interest to students, rather how HP can be of use; else it’s pointless. You’re not here for a math department’s biased and subjugating culture of Nurgle and Skeksis. Students will be divided into groups for them to choose real raw data to work on. Personal interest and understanding of such interests are often the best ways to grasp and implement towards competency and professionalism; you might end up liking this module at the end based on projects of interest. Functions or packages in R for hypothesis testing only concerns cross checking with code manually constructed and implemented with data; one must inevitably understand clearly what they’re trying to discriminate from in sample data. Projects will make use of R + RStudio. 13. Applying bivariate normal and other bivariate distributions Using two standard normal variables to build a general bivariate normal distribution; onwards to the five significant parameters where the random variables are expressed in terms of such. Confirm that the marginal distributions of such two random variables (in terms of the parameters) are normal. Recalling the form of correlation in terms of covariance. Change of variables and Jacobian leading to a bivariate form that’s inviting to data, and compact matrix form. Mardia test for multivariate normality. Goodarzi, E., Mirzaei, M., and Ziaei, M., Evaluation of Dam Overtopping Risk Based on Univariate and Bivariate Flood Frequency Analyses, Can. J. Civ. Eng. 39: 374–387 (2012) As well, find data to intimately develop after Yue, S., A Bivariate Gamma Distribution for use in Multivariate Flood Frequency Analysis, Hydrol. Process. 15, 1033–1045 (2001) As well, find data to intimately develop after 14. Covariance and Correlation Reviewing practical use of Covariance and Correlation Mukaka M. M. (2012). Statistics Corner: A Guide to Appropriate Use of Correlation Coefficient in Medical Research. Malawi Medical Journal: the Journal of Medical Association of Malawi, 24(3), 69–71 15. Correlation and Regression Include the following---> Bivariate regression models Multivariate regression Choosing variables based on data analysis to support regression models Heinze, G., Wallisch, C., & Dunkler, D. (2018). Variable Selection - A review and recommendations for the practicing statistician. Biometrical journal. Biometrische Zeitschrift, 60(3), 431–449 OLS assumption olsrr: Tools for Building OLS Regression Models; compare to Heinze et al MANDATORY: summary statistics that convey whether models are good or bad 16. Detection of Data Fabrication Using Statistical Tools NOTE: must be applied computational as well with real data out there to get the points across. Will use common labs in the natural and applied sciences as examples where students may tend to fabricate data. As well as trustworthy data sets from various sources. Hartgerink C, Wicherts J, van Assen M (2016) The Value of Statistical Tools to Detect Data Fabrication. Research Ideas and Outcomes 2: e8860. Hartgerink, C. H. J. et al. (2019). Detection of Data Fabrication Using Statistical Tools. Do statistical tools for data fabrication lead to misidentifying natural “black swans” or “elevated data cases” as fabricated data? LABS SYLLABUS (Mathematica) --> Note: students should be introduced to palettes and non-computational “italics” in Mathematica so they don’t need to waste paper. The following link for data analysis serves well: https://reference.wolfram.com/language/guide/StatisticalVisualization.html Functions of interest throughout labs naturally including conventional probability distributions, cumulative distribution and real data. NOTE: students must have strong self-interest concerning all possible parameters for the functions and functions in packages: -- ListPlot, DistributionFitTest, LearnDistribution, FindDistribution, DataDistribution, EstimatedDistribution, FindDstributionParameters, Moment, ParameterEstimator, Likelihood, LogLikelihood, HypothesisTestData, LocationTest, VarianceTest, IndependenceTest, PearsonChiSquareTest, KolmogorovSmirnovTest, AndersonDarlingTest, FisherRatioTest, TTest BinormalDistribution, FindFit, LinearModelFit, GeneralizedLinearModelFit, NonlinearModelFit, NonlinearRegress, LeastSquares, MatrixForm, Covariance, Correlation --Wolfram Language & System Documentation Center – Hypothesis Testing Package --Wolfram Language & System Documentation Center – Hypothesis Tests --Transpose data towards covariance, correlation, variance-covariance, etc. --Wolfram Language & System Documentation Center – Linear Regression Package Further guides: Wolfram Documentation Center Statistical Data Analysis Statistical Model Analysis NOTE: for each Mathematica function it’s quite important that you comprehend the scope of all parameter options. As well, you must know how make choice of method of interest. Read the damn documentation center sources well. Topics will be bundled for each lab. For each lab there will also be questions sets where students will be required to provide analytic writing/solutions that complements. Topics of concern –> ---Review of conventional probability distributions. Simulating random variables from phenomena. Frequency simulations. ---Data acquisition and modelling Data sources (.xls, .xlsx, .csv) Data Wrangling (.xls, .xlsx, .csv) Mathematica functions like FinancialData, etc. and Mathematica data sources <Astronomical Computation & Data, Earth Sciences: Data & Computation>. Reminder: use Wolfram Documention to scope the range of parameters for functions like FinancialData; other functions will have different parameters to consider. Generating summary statistics. Correlation matrix and heatmaps Distribution of a variable (revisiting module 4). Development of random variables and corresponding probabilities to outcomes from Mathematica sources and other external data sources. Univariate distribution among variable pairs ---Probability distributions with MLE During lecture instruction, manual modelling synthesis of estimators will be at least intermediate with respect to the given probability distribution models. High volume sample data: Binomial, Poisson, Gamma, Weibull, Normal. Previous to be applied to P-P plots and Q-Q plots. ---Method of moments (mean, variance, skewness, kurtosis) towards real high volume sample data, along with P-P plots, Q-Q plots, and comparing to MLE above; difficult moments to be provided. ---Review and computational repetition with modules 8, 9 & 10 for various data ---Goodness-of-fit with external raw data ---Simulating data from densities when real data is scarce or not acquirable. ---Olson, D. l. and Wu, D. The Impact of Distribution on Value-at-Risk Measures. Mathematical and Computer Modelling 58 (2013) 1670 - 1676 For such given article one will not only be confined to normality and logistic distributions, but will also introduce lognormal distribution. MLE may or may not be applied. Crucially, one must also be able to apply VaR to the true distribution of the data (compared to the three ideal distributions). More relevant real stock data will be applied. Will also pursue a scheme or currency exchange risk based on such three distributions. --Modules 10-12 conjoint ---Module 13 with external real data ---Fraile, R., and Garcia-Ortega, E., Notes and Correspondence, Fitting an Exponential Distribution, Journal of Applied Meteorology, Volume 44, 2005, pages 1620 – 1625. From what was described in this journal article, applied will be at least three sets of unique data each from different natural behaviours or phenomena. Will make use of (least squares) regression, MLE, and method of moments to compare (or comparison). How is there certainty that either of the three methods will be most accurate or appropriate? ---Lucas, C., C. and Soares, C. G., Bivariate Distributions of Significant Wave Height and Mean Wave Period of Combined Sea States, Ocean Engineering 106 (2015) 341–353 The data set in the journal article can be applied but will be updated. Will also pursue two to three other data sets from different ambiances. ---Tao, S. et al, Estimating Storm Surge Intensity with Poisson Bivariate Maximum Entropy Distributions Based on Copulas, Nat Hazards (2013) 68:791–807 Will pursue data that’s not of Qingdao, rather, of the Caribbean and other places of interest. ---Nelson, J. F. Multivariate Gamma-Poisson Models. Journal of the American Statistical Association, Vol. 80, No. 392 (Dec., 1985), pp. 828-834 The above article concerns analysis with confirmation of the probability and statistical models/tools applied. However, ambiances of interest to apply and data may be augmented with more recent times with associated data. Hence, conclusions may differ from article. Will also try to determine any robustness and adaptability of such “headliner” distribution, compared to ordinary Poisson distribution models and ordinary Gamma distribution models. NOTE: functions to be applied in Mathematica in labs will serve to complement manual development as assurance, and towards cases of abundant data and sources. Computational Mathematica functions will be applied. ---Correlation and Multivariate Regression (will be active with vast raw data) ---Detection of Data Fabrication Using Statistical Tools Hartgerink C, Wicherts J, van Assen M (2016) The Value of Statistical Tools to Detect Data Fabrication. Research Ideas and Outcomes 2: e8860. Al-Marzouki, S., Evans, S., Marshall, T., & Roberts, I. (2005). Are these Data Real? Statistical Methods for the Detection of Data Fabrication in Clinical Trials. BMJ, 331(7511), 267–143. Yamamoto, K., & Lennon, M. L. (2018). Understanding and Detecting Data Fabrication in Large-Scale Assessments. Quality Assurance in Education, 26(2), 196–212. Prerequisite: Probability and Statistics B (no exception). Introduction to Derivatives for Financial Engineering: This is an introductory course in computational finance. Major ideas and concepts underlying modern computational finance are explained and illustrated. Course covers financial markets (excluding bonds), options with strategies, the binomial model, and provides a soft but fluid elementary treatment of continuous time models and the Black-Scholes formula. Course stresses emphasis on crucial market intelligence, and the instruments mechanics many take for granted. NOTE: for quality, retention and sustainability in skills course will be 18 weeks, having 3 sessions per week with at least 2 hours per session. NOTE: without basic knowledge of assets derivatives will not be useful as one would like them to be. Without any understanding of assets’ markets, use of financial derivatives will not be constructive. NOTE: in all honesty, one’s first course in derivatives generally isn’t a strong read on what an individual is truly capable of; course isn’t like arithmetic nor algebraic solving, nor “tic-tac-toe”. NOTE: course is not a playground for a Mathematician’s toxicity. Course is an introduction into a professional environment, where the terms “art” or “skill” become more identifiable, instead of a “black hole” of mathematical perversion. If you’re somehow stressing real analysis or manual matrix algebra (for whatever reason) as being somehow primordial, you don’t belong in the business because you will never get anything done; a math office doing whatever is better suited then. Prerequisite stated will be the prerequisite. Co-requisite stated will be the co-requisite. NOTE: this course will never concern mathematicians becoming acquainted with tools so that they can teach as con artists based on parasitism and rent-seeking sewage going nowhere. NOTE: keep your notes, reinforce your intelligence and skills in the future; rust and doubt are easy to catch like the common cold. Objectives: i. Students will understand the basics of financial instruments such as stocks, forwards, futures, and options. ii. For each security, instrument or derivative encountered will learn to access and interpret market data, and the relevance of such data to our models. iii. Students will learn about arbitrage free pricing and hedging. iv. Students will be introduced to basic option strategies (basic and advance). v. Students will understand the role of risk neutral probability measure; the use of some elements of stochastic calculus in mathematical finance. vi. Student will understand the binomial model for stock prices and its use for pricing and hedging European and American type options. vii. Students will learn how to use mathematical software (Mathematica) to price and hedge financial instruments in discrete time models. viii. Students will learn the basics of continuous time models and Black-Scholes option pricing formula. ix. Students will learn how to use mathematical software (Mathematica) to price and hedge financial instruments in continuous time models. NOTE: students must understand this course is crucial towards any progression with derivatives. Course serves as a critical foundation. NOTE: computational programming/data projects and labs should not be taken for granted; they are not just burdening tasks. Performance in such will influence one’s future level of competence. Apart from instructors, students should independently research computational finance with Mathematica and practice. NOTE: keep your notes, reinforce your intelligence and skills in the future; rust and doubt are easy to catch like the common cold. Example texts: The Mathematics of Finance: Modelling and Hedging”, by Joseph Stampfli and Victor Goodman (2009), AMS. Hull, J. C. (2017). Options, Futures & Other Derivatives. Pearson. Grade Assessment --> Homework 10% Labs + Programming/Data Projects 30% Labs: concern modules 1-3, 6-13 Note: Programming/Data Projects concern modules 1, 2, 3, 11 Major Project: based on modules 1, 2, Picardo’s article and 11, students will build complex strategies. Relevance of bid/ask. May also be required to adjust strategies in the near future with arguments. 4 Exams 60% Such assessment serves to establish and enforce integrity in this course. Additionally, poor conduct in course can warrant 69% of total grade forfeited. NOTE: not all homework and projects will come from mentioned texts; many to come from the syllabus/course outline and the listed literature/articles. Course Outline --> 1. Financial Markets -Investopedia: Hayes, A. (2023). What are Capital Markets, And How Do They Work? -What drives markets? -Currencies: Floating Rate vs. Fixed Rate: What’s the Difference? – Investopedia The Foreign Exchange Spot Market Banton, C. and Scott, G. (2019). Investopedia- How are International Exchange Rates Set? Investopedia: Picardo, E. (2020). Understanding the Indirect Effects of Exchange Rates Influences on currency exchange rates Segal, T. (2021). Using Currency Relations to your Advantage, Investopedia Note: must also be able to provide credible arguments for causes -Stocks: Definition and structure Means of creation and recognition with commissions Market with exchanges, platforms & transaction process -It’s imperative that students are exposed to the logistics and computational development for mentioned methods from the following given links, comparing with each other and recognised market value. Some methods may concern “present” valuation while others concern “future” valuation. Chen, J. (2020). Dividend Discount Model (DDM) – Investopedia Kenton, W. (2020). Abnormal Earnings Valuation Model – Investopedia Capital Asset Pricing Model (CAPM) for stock valuation Multifactor models (extensions of CAPM) Joseph Nguyen (Investopedia) – How to Choose the Best Stock Valuation Method -Stock metrics and means of determination -For various stocks compare market value to the given prior valuation methods, and to stock metrics. Are such compare/contrasts adequate enough to determine overvalued or undervalued stock? -Acquiring and re-adjusting financial statements towards: liquidity ratios, coverage ratios, profitability ratios and efficiency ratios; historical behaviour. -Future outlook on stock markets and currencies (quantitative AND judgmental methods) Survey of Professional Forecasters & Biege Book Leading economic indicators: PMIs, yield curve, TED spread, Mutual funds liquidity Leading and Lagging Employment, Inflation Monetary Policy Rules, Tools Economic data to predict implementation of such Economic data to predict retraction of such Gov’t Budget Analysis Fiscal Indicators and Fiscal Policy Geopolitics -PESTEL/SWOT analysis for a particular equity? Serves as planning beyond the luxury of day trading. Results generally “complement critique” stock valuation (present and future), metrics and financial ratios. How will future outlook module prior influence your PESTEL/SWOT for a particular equity? Currency? Will have tangible with template usage for PESTEL and SWOT 2. Elementary Data Analysis (stocks, commodities, currencies) Financial tools via Wolfram Documentation Centre Financial Data and Economic Data Means of accessing data (with preferences in parameters) Statistical measures and summary statistics development Asset price as a random variable towards distribution Distribution fitting of asset data Financial tools via Wolfram Documentation Centre Financial Indicators (investigation of functions and their parameters) Financial Visualization (investigation of functions and their parameters) Currency conversion arrays Development of various professional output logistical schemes with prior intelligence and skills acquired; students given conceptual frameworks to develop. 3. Market/Systematic Measures & Behaviour -Beta coefficient versus standard deviation. Which is more practical? -Beta versus VaR and CVaR for systematic risk -Ahmed, S., Bu, Z., & Tsvetanov, D. (2019). Best of the Best: A Comparison of Factor Models. Journal of Financial and Quantitative Analysis, 54(4), 1713-1758 What advantages do factor models have over CAPM Portfolio construction with factor models -Market relationship between risk free bonds yields rates and stock indices Data Analysis for S&P/TSX Composite Index (with Canada gov’t bonds), S&P 500 (with treasuries), Russell 2000 (with U.K. gov’t bonds), STOXX Europe 600 (risk free European bonds). -The following subjects are not well treated or understood which lead to market participants in false positions or comforts. Concepts via Investopedia, and will also pursue active exploratory case studies. Treat them in the most logical and constructive sequential manner: Federal Call Marginal Call Margin Debt Liquidation Level Liquidation Margin 4. Arbitrage Lioudis, N. K. (2019). What is Arbitrage? - Investopedia Will treat practical problems concerning arbitrage. Is arbitrage a driving force in markets? Folger, J. (2019). Arbitrage versus Speculation: What’s the Difference? - Investopedia 5. Futures and Speculation O’ Hara, N. (2020). How to Use Index Futures – Investopedia Will also pursue a quantitative/computation examination with market data, and developing analysis. However, what is the horizon? REMINDER: news or information changes everything. 6. Forwards Definition, vendors, practical uses or goals Piecewise linear models and generating plots of put and calls (also with long and short, respectively). Continuously compounded models of put and calls, and generating plots (also with longs and shorts). Put-Call Parity 7. Financial Computation in Wolfram Documentation Centre (investigation of functions and their parameters) FinancialDerivative function for futures and forwards Observation of derivative types and the possible parameters Observe what method of evaluation is applicable, and choices you can make in computation (tree type, monte carlo method type, etc., etc.) 8. Minimum Variance Hedge Ratio To be used as an important factor in determining the optimal number of forwards/futures contracts to purchase to hedge a position. 9. Forwards for currencies Foreign exchange forwards (introduction, purpose and vendors) FX Spot–Forward Arbitrage (what are you looking for?) FX Forward Price Quotes and Forward Points (how are they useful?) Timing (establish relevance) Payoff models for currency forwards (developed from the prior subjects) Call (long and short) Put (long and short) Range forward contracts for forwards with payoff models 10. Options: Difference from forwards/futures European --> definition, vendors, practical uses or goals. Models and plots parallel to (6), namely, both piecewise and continuous. American --> definition, vendors, practical uses or goals. Which is usually more expensive, European Options or American Options? Models and plots parallel to (6), namely, both piecewise and continuous. Picking the right strike price: Picardo, E. (2020). Options Basics: How to Pick the Right Strike Price – Investopedia Comparing determined strike price to market value. Does it derive the same conclusions as comparing market value with stock valuation and stock metrics? Kenton, W. (2018). What is Moneyness? Investopedia Simon, H. (2020). What is Option Moneyness? Investopedia How is Picardo’s article relevant to the prior two articles? 11. Profit Potential of Options and Performance Evaluation Farley, A. (2020). Measure Profit Potential with Options Risk Graphs. Investopedia For the above literature included with applied shares and how they influence derivatives portfolios. For performance evaluation, intention will concern both arbitrary sets of options chosen AND index options similar to the following manner with applied shares and how derivatives influence: Bookstaber, R., & Clarke, R. (1984). Option Portfolio Strategies: Measurement and Evaluation. The Journal of Business, 57(4), 469-492. Can one draw the same conclusions when comparing Farley to Bookstaber & Clarke? 12. Using Options to Predict Stock market direction Seth, S. (2021). Using Options Data to Predict Stock Market Direction. Investopedia 13. Options Strategies & Hedging NOTE: for OPTIONS STRATEGIES will have proper development towards taking positions on assets concerning shares (or currency prices) and the amount of investment needed concerning surplus or hedge. -Farley, A. (2020). Factors that Determine Option Pricing. Investopedia -Downey, L. (2020). Essential Options Trading Guide. Investopedia -Put-Call parity and the conditions for its relevancy: Stoll, H. (1969). The Relationship Between Put and Call Option Prices. The Journal of Finance, 24(5), 801-824. Is put-call parity based on arbitrage? Construction of geometrical representation. Why not American options for put-call parity? -General options strategies Constructing mathematical models, the corresponding geometries, respective code development with plotting based on literature given. Will also include writing code for net payoffs involving option strategies having parameters of strike price(s), price(s) of calls and/or puts (including longs and shorts) towards characteristic plots. Mirzayev, E. (2019). Options Strategies: A Guide for Beginners. Investopedia. Out of the following: Bull Bear Covered Call Married put Box Spread Protective Collar Risk Reversal Straddle (long and short) Strangle (long and short) Butterfly (long and short) -How to develop a hedge concerning one’s belief about an asset; concerns one having a specified number of shares (for stocks) or capital (for currencies). Namely, it’s not just a matter of building strategies, but also quantity in portfolio invested and desire pursued. -Will have proper development towards taking positions/strategies on assets concerning applied shares (or currency prices with capital) related to expected surplus/speculation. Namely, it’s not just a matter of building strategies, but also quantity in portfolio invested and desire pursued. -More general cases concern option strategies for gains constituted by various options and how shares in stock (or capital in currency asset) influence profit requirements. -Ask price and bid price. How does such influence prior 3 topics? NOTE: students will build complex options strategies constituted by calls (long and short) and puts (long and short). Will have continuous compounding versions as well with complex strategies. -Range forward contracts with options (long and short) 14. Binomial Model: purpose and pricing a. Derivation b. European Options c. American Options -Will also include interpretation use of parameters. There will also be simulation code building and implementation for each options type. -Volatility is a major influence on stock price in the binomial option pricing model with future movements. Forewarning: your model (whether put or call) doesn’t dictate market volatility, say, volatility it’s quite indifferent to your strategy. -Also, from module (1), particularly Abnormal Earnings Valuation Model (AEVM), for various time increments in the future, is such stock valuation method a good benchmark for volatility? 15. Introduction to Continuous Time Models NOTE: following modelling and derivations there MUST be computational and simulation activities towards recognising practicality with each topic. -Stocks (and other assets) movement --> Why are asset prices considered stochastic? Market forces and volatility Volatility and its indifference to asset movement direction Concept may be best visualized with standard deviation for asset returns -Binomial or trinomial mechanism (drunkard’s stagger) as an ideal means of generating random walks, say p[left], p[straight], p[right]; yet even a drunk may have preference in direction due to whatever that stimulates the senses and mind (but a smooth path isn’t expected); likewise market movement direction is not p[up] = p[down] = p[no movement] due to the many market participants and information available. -Lognormal distribution preferred over the normal distribution (a historical returns perspective) Skew and Kurtosis For asset returns identifying which of the following are most characteristic and the applicability of lognormal--> Leptokurtic, mesokurtic and platykurtic distributions -Geometric Brown Motion & involved parameters compared to basic random walks. The role of standard deviation/variance in GBM. Why is the lognormal distribution identified with GBM? Observing the role of standard deviation in the lognormal distribution compared to its role in GBM. -The Black-Scholes-Merton model: assumes that stock prices follow a lognormal distribution based on the principle that asset prices cannot take a negative value; they are bounded by zero. -Derivation of Black-Scholes-Merton model Binomial model method (includes computational development in Mathematica exhibiting the “vast probability space” under appropriate conditions) By Expectation (includes computational development in Mathematica) -Conditions for the relevancy of the Black-Scholes-Merton model. -Computational pricing with Black-Scholes-Merton model: monte carlo building and implementation for put and call. -Valuation of Currency Options (extend prior with the two interest rates involved) -The Greeks: derivatives of the Black Scholes Merton model. Greeks construct the Blacks Scholes PDE. -Survey of numerical methods for Black-Scholes PDE Note: will not dive into numerical methods because the common “kindergarten” choices like finite difference generally gives poor performance. In addition, software like Mathematica and so forth often chooses a numerical method that’s most efficient. This course isn’t about plain mathematical frolic (or destructive impeding obnoxiousness and Ivy League punk cults). On the contrary, the Numerical Analysis course will treat FD well. -Review conditions for the relevancy of the Black-Scholes PDE. Why are these conditions ideal? -Foreshadowing for following advance courses, observe asset returns (stocks, currencies, commodities) for different time periods. What is the behavior of sigma (or standard deviation)? Does such behaviour overall vindicate the binomial pricing model or Black-Scholes-Merton model for behaviour at different time scales? What tools do you have right now to deal with such? 16. Financial Computation in Wolfram Documentation Centre (investigation of functions and their parameters). DON’T TAKE FOR GRANTED FinancialDerivative function for options Observation of derivative types and the possible parameters Observe what method of evaluation is applicable, and choices you can make in computation (tree type, monte carlo methods type, etc., etc.) Prerequisites: Corporate Finance, Probability & Statistics B Co-requisite: Stochastic Models & Computation.

Derivatives Modelling and Pricing I Course emphasizes high amounts of computational activity succeeding “comprehensive modelling”; a means to understand the reasoning or purpose of specifying parameters and use of particular industry simulations. A major part of this course will be focused on quantifying or modelling volatility towards understanding the relevance of stochastic control, rather than reckless focus on mean reversion being a characteristic which may not be observed at end of maturity. Course will make use of various texts and journal articles. Many of the tasks stated in the syllabus will be the responsibility of the students. I don’t care for mathematicians with their perversions and indulgences. They usually have an office with all the time in the world to do whatever it is they do. Many theoretical mathematical ghouls can belch out and express all sorts of theoretical complications, but are like “fish out water in the real world”. NOTE: an 18 weeks course with 2-3 sessions per week. NOTE: course is not a playground for a Mathematician’s toxicity. Course is an introduction into a professional environment, where the term “art” becomes more identifiable, instead of a “black hole” of mathematical perversion. If you’re somehow stressing real analysis or linear algebra as being somehow primordial, you don’t belong in the business because you will never get anything done; a math office doing whatever is better suited then. Prerequisites stated will be the prerequisites. NOTE: this course will never concern such mathematicians becoming acquainted with tools so that they can teach as con artists based on parasitism. NOTE: it’s very crucial that students take personal interest to remain fresh and competent with their knowledge and skills from prerequisites, aside from mandatory activities in this course. Will be the make-or-break life choice in the profession. Textbooks in unison considered --> Options, Futures & Other Derivatives, by Hull and Basu Computational Financial Mathematics Using Mathematica (Stojanovic) Economic and Financial Modelling with Mathematica (Varian) Option Valuation Under Stochastic Volatility: With Mathematica Code (Alan. L. Lewis) Option Valuation Under Stochastic Volatility II: With Mathematica Code (Alan. L. Lewis) Glasserman, P, 2003, Monte Carlo Methods in Financial Engineering, Cambridge University Press, Cambridge. Journal articles --> Journal articles and documents mention to be used Assessment --> Homework 25% Prerequisite refresher tasks (HW, labs tasks, projects) 0.4 From prerequisite modules 1 – 3, 8, 10 – 15, to be synchronized with course progress Students will get feedback on their fumbles and errors Current course problems 0.6 Computational assignments 35% 4 exams 40% NOTE: exams to reflect homework and computational assignments. NOTE: for computational assignments much will stem from modules. I will not teach you computation and code because prerequisites convey that you are capable of expected tasks with integrity. I will go over the mechanics of the computational assignment, but I will not teach you code because the texts and external sources will provide strong guides; it’s up to you to understand what you’re doing and how to professionally make use and advance in computation. I expect professional commentary, computational layout in a research format (with references because conventionally you are learning to code from somewhere. Don’t make the mistake of being a condescending, toxic and sabotaging entity from a theoretical mathematics department, because they don’t get screwed or fired from occupations they don’t have. Outline --> 1. Fast Review and stock data modelling ---Review of normal distribution and lognormal distribution properties (expectation, moments, variance, cumulative distribution). ---Stock as the underlying asset modelled by Geometric Brownian Motion. Expectation and solution of this SDE. Girsanov theorem relevancy. ---Geometric Brownian Motion simulation (Use of Wolfram Mathematica for monte carlo statistics. Mean path and confidence bands, parameter fitting). Recall the proof of the lognormal distribution being the distribution of geometric brownian motion. Construct a geometrical exhibition where a simulation resides in the “X-t” plane with evolving P(X, t) providing a three-dimensional exhibition. Through time, how does the variance appear among the various distributions through time with respect to the “noise” of the simulation? ---Then develop prior with real market data (stock, currency, commodity) ---http://jonathankinlay.com/2019/10/stochastic-calculus-mathematica/ NOTE: ignore Shreve’s cliff sludge slide textbook and leverage upon the Mathematica development ---Comparing the mean reversion model (having expectation likely yielding an exponential form with initial stock price as coefficient) to the day trade, to 5 days, to one week, to two weeks, to a month, to a year; observe whether there’s any eventual convergence. Is mean reversion a constructive goal even for long term investing? Compare expectation of GBM SDE to mean reversion, and also to the day trade, to 5 days, to one week, to two weeks, to a month, to a year respectively. 2. Empirical observations of elementary deviation for specified time periods (scientific computation instruction accompanies the mathematical layout). ---Historical volatility simply as the standard deviation involving asset data (importation and manipulation). ---Comparing historical volatility of chosen time periods ---Why historical volatility is generally uncharacteristic of realistic instantaneous stock behaviour (concepts of economic factors, political agitation, information, black swans, market participants). 3. Recalling primitive features and common strategies with European style options: ---“Risk-free rate”, SOFR, SONIA, EURIBOR ---Fast review of the definition of the European options ---European options and put-call parity. ---Strategies with European options towards underlying assets: hedges, straddles, strangles, spread, butterflies and risk reversals with respective programming assignments. For complex options strategies will have proper development towards taking positions on assets concerning shares (or currency prices), and the amount of investment needed concerning surplus or hedge. Namely, it’s not just a matter of building strategies, but also quantity in portfolio invested and desire pursued for whatever goals in mind. First typical scenario concerns one having a specified number of shares in a particular, and how to develop a hedge concerning one’s uncertainty with asset of concern. More general cases concern option strategies constituted by various options and how shares in stock (or currency asset) influence profit requirements. 4. Binomial Option Pricing & Black Scholes Merton: ---Shares and subliminal delta-hedging relating to arbitrage and risk-neutral probabilities. ---Determination of tree parameters The following excerpt can be very beneficial: J. C. Hull and S. Basu, Options, Futures and Other Derivatives. Pearson, 2016, pp 479-480. ---Binomial model and lattices of two and three steps for European options ---Simulations for binomial option pricing for at least four steps (manual programming and/or built-in function tool). ---Binomial model with large nodes exhibiting stochastic trajectories for European options. ---Reminding note: First, with the assumption of risk-neutral world, expected return from the asset is the risk-free interest rate; to recognise that such condition is ideal, and interest rates change. Secondly, from earlier modules, observing that statistical volatility changes over time, unlike the case of volatility as a fixed parameter; in the future, volatility has various descriptions, being either realised, implied, local or stochastic, where the parameter fix comes from choice out of the first three. Third, the binomial process to generally appease diffusion. From consequence of the three conditions, observed is appeasement to the ideal Black-Scholes-Merton ambiance (or geometric Brownian motion process). Note: time segmentation choice(s) for a particular option may or may not have significant influence on price. --Volatility is a major influential parameter on stock price in the binomial option pricing model; also recall methods of stock valuation, particularly AEVM. For various time increments in the future, is comparing both sensible at all? If so, is it a robust compare/contrast for drawing any conclusions? ---Deriving Black-Scholes-Merton model via binomial model by large nodes. ---Conditions for BSM model: market efficiency, European style, sans commissions, uniform interest rates and volatility, and assumption of log-normal stock returns. ---BSM monte carlo computations ---Valuation of Currency Options (extend prior) ---Black-Scholes-Merton formula as an expectation (prove) and pricing computations (put and call). Reviewing the limits of the Black-Scholes-Merton formula (applicable options and fixed parameters) 5. American Options: ---American option and path dependence ---No Put-Call Parity ---Boundary conditions and conditions on stock price ---Change of variables for the payoff function ---Binomial model with control variate technique. Lattices of two and three steps for the American options and pricing. ---Simulations for binomial option pricing for at least four steps (manual programming and/or built in function tool). Does it make sense to use American options as opposed to European options in complex options strategies? ---American form of currency options and valuation? 6. Black-Scholes PDE: ---Review of boundary conditions for European option ---Review of boundary conditions for American option ---Use of the Greeks (overview of all Greeks) ---Greeks constructing the Black-Scholes PDE. 7. Crank-Nicolson method for the BS PDE (quite limited time spent on model): ---Recognising appropriate boundary conditions to implement (for European and American options). ---Crank-Nicolson algorithm derived ---Recognising the advantages and disadvantages between the binomial model, Black-Scholes-Merton model and the Crank-Nicolson method. Note: despite the unconditional stability of Crank-Nicolson, it may not provide the best precision. In Mathematica with the NDSolve function or package choice of numerical method (Finite Difference, FEM, Method of Lines, etc.); else, Mathematica generally chooses the best choice. 8. Least squares monte carlo and Longstaff-Schwartz method for American options (analysis, algorithm structure, algorithm development & tests versus Mathematica function FinancialDerivative and R packages 9. Pricing beyond the Black-Scholes-Merton Model, & Empirical Statistics ---Studies exhibiting asset’s log-return distribution being non-Gaussian plaguing the Black-Scholes-Merton model with many problems. ---Distribution fitting and mean reversion exercises for stock. Acquire stock data from a particular year for two or three different tickers. Respectively, for each ticker, choose a conventional trading day, 5-day trading week, a month and given year to acquire the distributions of (log) returns; make appropriate parameters fitting for respective distribution (Lognormal, Meixner, Variance Gamma). P-P plots or Q-Q plots can apply for additional convincing. ---Alternative comparative view of fit among the candidate distributions with respect to stock data: construct a geometrical exhibition where stock simulation resides in the “X-t” plane with evolving P(X, t) candidates (colour coordinated) providing a three-dimensional exhibition. Observe the respective evolving variance for each distribution and how well such corresponds with the stock data in the “X-t” plane. Observe tails as well. Note: log returns model may not be appropriate. ---For completeness, apply distribution fitting (lognormal, Meixner, and Variance Gamma) and mean reversion (expectation) concerning conventional trading day, 5-day trading week, a month and given year in similar fashion for chosen equity, currencies and commodities. Compare the mean reversion of the Meixner distribution and the VG distribution to such durations of the chosen commodities and currencies. Then, reapply alternative comparative view of fit among the candidate distributions with respect to chosen commodities and currencies. ---Heavy tails and high peaks (leptokurtic): (i) Madan, D. P., Carr, P. P., and Chang, E. C., The Variance Gamma Process and Option Pricing, European Finance Review 2: 79–105, 1998 Daal, E. A., & Madan, D. B. (2005). An Empirical Examination of the Variance‐Gamma Model for Foreign Currency Options. The Journal of Business, 78(6), 2121–2152 (ii) Nannavecchia, Antonella. (2015). The Meixner Process for Financial Data, Megatrend revija. 12. 33-44. 10.5937/MegRev1502033N. Develop option price model for Meixner similar to VG process option pricing in (i). Pursue compare/contrast with pricing. ---Computationally exhibit the VG, Meixner & BSM pricing models in Mathematica; one can have interactive change of parameters with use of “Manipulate” function. ---Possible Greeks for the VG and Meixner pricing compared to BSM Greeks? 10. Volatility as an underestimated parameter: Ackert, L. F., Kluger, B. D. and Qi, L. Implied volatility and Investor Beliefs in Experimental Asset Markets. Journal of Financial Markets 43 (2019) 121 - 136 ---Analyse article then apply market data from unique ambiances towards conclusions. ---Essential use of Implied Volatility ---Bull & bear markets, smile, term structure (concepts) ---Modelling the implied volatility term structure (then simulate) ---Modelling the implied volatility smile (then simulate) ---Newton-Raphson method with programming and pursuit of implied volatility surface for European options. Note: unique assets often don’t behave in similar fashion, so those of interest must be considered. Acquiring the volatility smile and term structure; understand if the set of options in use are out-of-money, in-the-money, or at-the-money, (moneyness issue), etc. ---Stock market index implied volatility Provides a measure of market risk and investors' sentiments for the market, but isn’t necessarily a predictor for a unique asset’s performance. Each geographical ambiance often has a VIX analogy. Examples: (a) The CBOE VIX Formula (b) Euro Stoxx 50 Volatility (VSTOXX) ---Comparison/contrast between Implied and Historical volatility for the determination of overvalued and undervalued options. Note: such is not a predictor of asset behaviour---keep in mind when reviewed on multiple occasions. ---Determining implied risk-neutral distributions from volatility smiles (Hull and Basu 2016, 475-477) (a) Express the price of a European call (or put) with exercise price and time-to-maturity as the discounted sum of all expected future payoffs in terms of implied risk-neutral distribution. (b) For a stock of concern set up various options strategies based on one’s believes on future stock prices, and similar to such in the mentioned situated text (Hull and Basu 2016, 475-477) acquire the relevant prices and implied volatilities data, then determine the implied risk-neutral distributions from volatility smiles. Then, determine the price of a European call (or put) with exercise price and time-to-maturity as the discounted sum of all expected future payoffs in terms of implied risk-neutral distribution. (c) Recall module (9) with the various distributions. For the chosen stock, fit such distributions and compare with the acquired implied risk-neutral distribution. How similar is the acquired implied risk-neutral distribution in (b) to any of the distributions? Apart from geometrical observation one can compare computed probabilities for stock prices among the distributions. What can one deduce? (d) Knight, JL, & Satchell, S. 2007, Forecasting Volatility in the Financial Markets, Elsevier Science & Technology, Oxford. Section 9.5, pages 205 to 208. Compare such model to that of (b) and with computation; appropriate weights and other parameters must be determined for the model stemming from the latter text. ---The GARCH (1, 1) model Hull, J. C. and Basu B. (2016). Estimating Volatilities and Correlations. In: Options, Futures and Other Derivatives. Pearson. Pages 554 – 564. Determination of parameters will not be taken lightly, and will also compare individual assets to market indices such as the S&P 500, Russell 2000, Euro STOXX 600 or TSX Composite; latter (indexes) could be done as well to compare to individual chosen stock. How does “future volatility” compare to implied volatility via Newton-Raphson method, and which is more practical? ---Sheraz, M. and Preda, V. Implied Volatility in Black-Scholes Model with GARCH Volatility. Procedia Economics and Finance 8 (2014) 658 – 663 Concerning options pricing how does such journal article compare with the modelling of Hull (and Basu)? Make use of various market data sets. ---Y. Zhuang and M. Wang, "Comparison of Several Implied Volatility Models," 2017. 16th International Symposium on Distributed Computing and Applications to Business, Engineering and Science (DCABES), Anyang, 2017, pp. 49-52 ---Recall Abnormal Earnings Valuation Model (AEVM) and factor models for future stock valuation. For various time increments in the future, are such valuation methods good benchmarks for volatility? Can they be used as future volatility predictors? Compare with all prior implied volatility models/methods for assets of interest. ---Optimal Delta Hedging for Options (A). The Greek measure vega Practical use of vega Finite Difference Monte Carlo Making vega relevant to market data. What can you do with it that’s more meaningful than ordinary delta? (B). Analyse the following journal article and will apply to real data from the market: Hull, J. and white, A. (2017). Optimal Delta Hedging for Options. Journal of Banking and Finance, Vol. 82, pp 180-190. Pursue such with Russell 2000, Euro STOXX 600 and TSX Composite Interested also in individual assets to compare with such indices. Understand the role of hedging against volatility versus options strategies for profit. Recall that volatility doesn’t show market direction, however, many option strategies require volatility for gains. Why does one attempt to hedge against volatility? 11. Towards pricing of European and American options compare binomial, BSM, Meixner and VG involving realised volatility, implied volatility from Newton-Raphson method, and implied volatility from GARCH approach. 12. Implementing Elementary Stochastic Calculus for Finance: ---Relevance/Motivation with Riemann-Stieljes integration. ---From Brownian motion leading to Ito integration. ---Ito Calculus (propositions) ---Idealistic lognormal models as solutions of stochastic differential equations by proof; include simulations in Wolfram and distribution fitting for the paths. Brownian motion with drift and deviation towards Geometric Brownian Motion. Understanding it’s restrictive use for modelling stock prices: (A) Assumption of constant volatility (B) Assumption of constant interest rate (C) Assumption of no jumps ---Ito process leading to derivation of the Black-Scholes PDE. (A) Assumption of constant volatility (B) Assumption of constant interest rate (C) Assumption of no jumps ---Martingale approach for European and American options (with computation construction in Mathematica). Compare computational results to binomial pricing, finite difference schemes and such from module (11) for the various volatility types. ---Hedging strategies with the martingale approach previous and recovering the BS PDE (make appropriate setting for respective boundary conditions). What are you hedging against? Note: martingale approach problem exercises can be broad, but practicality and relevance in industry are priority over broad mathematical mischief. ---The heat equation from the BS PDE and the Gaussian solution via Fourier transform relevant to idealistic lognormals, and its (limited) practicality. ---Feyman-Kac formula and its solution (with proof) as a model for options pricing. How practical is it? (A) How similar is such a proof to that of the martingale approach? (B) Using model for computation in Mathematica. Compare computational results to martingale approach, binomial pricing, finite difference schemes and BSM. (C) Relating-Feynman Kac to the BS PDE ---Variance Swap Strategy, structure and parameters. Pricing and valuation with practicality for the industry. Is vega helpful or related constructively? 13. Choice and change of Numeraire (application to foreign exchange rates with computational verification for meaningfulness) ---Notion of numeraire (relevant to currency exchange). Underlying concept: “my foreign currency account grew by a certain percent but the foreign exchange rate dropped by a certain percent”. ---To perform a fair pricing, one has to determine a probability measure (for example on the foreign market), under which the transformed (or forward, or deflated) process will be a martingale. Defining the associated forward measure, and providing an expectation form. ---Proof of likelihood ratio by expectation ---Pricing using change of numeraire and realistic computational development ---Identifying the (tangible) model form of the numeraire from a specified “overseas investment opportunity”: foreign money market account valued on the local (or domestic) market, and its discounted value on the local market. ---Identifying a relation between both risk-free rates (cost of carrying), the exchange rate process (with its solution form, and the corresponding discounted value of the foreign money market account on the local market). 14. Multi Asset Options Note: module (10) may bare its influence here as well ---Garman-Kohlhagen formula <Garman, M. B. and Kohlhagen, S. W. "Foreign Currency Option Values." J. International Money and Finance 2, 231-237, 1983 (A) Garman-Kohlagen formula with European options; pursuing monte carlo development and implementation. (B) Put-call parity and Garman-Kohlhagen formula with proof for European options. (C) Garman-Kohlagen formula with American options; pursuing monte carlo development and implementation. (D) Project—Confirm whether all of module (14) still has relevance (mathematical representations) with the Garman-Kohlhagen formula. Establish whether the Martingale approach and Feynman-Kac approach are still relevant; monte carlo. (E) Project—analyse the following journal article and pursue financial data to support or disprove such <Kung, J. J., A Continuous-Time Model for Valuing Foreign Exchange Options. Hindawi Publishing Corporation Abstract and Applied Analysis. Volume 2013, Article ID 635746, 10 pages ---Rainbow option and payoff scenarios (A) Project: Ouwehand, P. and West, G., Pricing Rainbow Options, WILMOTT Magazine ---Spread option (not the same as an options spread) (A) crack, crush, spark and calendar spreads. (B) Project—Research Kirk’s formula and the Bjerksund-Stensland formula. Provide at least two realistic applications. 15. Stochastic Volatility: Implied volatility smile used with Black-Scholes formula tends to systematically misprice out-of-the-money and in-the-money options if the volatility implied from the at-the-money option has been used; SV option pricing models such as the Heston model were developed to capture the “smile” effect. --Heston Model Heston, S. (1993) A Closed-form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options. Review of Financial Studies, 6(2), 327; given course literature as well. Heston model and Feller condition, and identifying the relevancy of Girsanov theorem. Use of Wolfram Mathematica for simulations, mean path and confidence bands. Monte carlo statistics. Mean path and confidence bands. Recalling the leverage effect; the Weiner processes in the Heston model should be correlated Probability Distribution of returns in the Heston Model i. Dragulescu, A. A. and Yakovenko, V. M. (2002). Probability Distribution of Returns in the Heston Model with Stochastic Volatility, Quantitative Finance Volume 2, pp 443 – 453. There will also be activities with real data. One may not be only interested in stock indices, say, to also pursue individual stocks of interest. ii. Silva, A. C. and Yakovenko, V. M. (2003) Comparison Between the Probability Distribution of Returns in the Heston Model and Empirical Data for Stock Indexes. Physica A 324 (2003) 303 – 310. There will also be activities with real data. One may not be only interested in stock indices, say, to also pursue individual stocks of interest. iii. Ralf Remer 1 & Reinhard Mahnke (2004) Application of the Heston and Hull–White Models to German Dax Data, Quantitative Finance, 4:6, pages 685 - 693 There will also be activities with real data. One may not be only interested in stock indices, say, to also pursue individual stocks of interest. ---Calibrations & Simulation of Heston Model--> i. Mikhailov, S., Nogel, U. Heston’s Stochastic Volatility Model Implementation, Calibrations and Some Extensions, WILMOTT Magazine, pages 74 - 79: ii. Mrázek, M., & Pospíšil, J. (2017). Calibration and Simulation of Heston Model, Open Mathematics, 15(1), 679-704. Computational competency to be emphasized rather than just writing down formulas. The following may prove quite useful --> iii. Wang, X. et al (2017), Parameter Estimations of Heston Model Based on Consistent Extended Kalman Filter, IFAC PapersOnLine 50-1, pages 14100–14105. Computational competency emphasized rather than just writing down formulas. ---America Options under Stochastic Volatility Note: parameters are expected to be market related towards pricing pursuits. i. Ikonen, S., & Toivanen, J. (2008). Efficient Numerical Methods for Pricing American Options Under Stochastic Volatility. Numerical Methods for Partial Differential Equations, 24(1), 104 - 126. ii. Chockalingam, A., & Muthuraman, K. (2011). American Options Under Stochastic Volatility. Operations Research, 59(4), 793-809. iii. One should compare pricing American options with basic Black-Scholes Merton monte carlo, Binomial model (with realised volatility and implied volatility), Meixner process (with realised volatility and implied volatility), and the VG process (with realised volatility and implied volatility) to (i) and (ii). ---Implied volatility versus versus stochastic volatility...and purpose. Note: the long variance parameter, or long run average price variance in the Heston model is probably to make use of either implied or local volatility in some means. Preserve the purpose of comparing historical volatility and implied volatility earlier on. Note: such is not a predictor of asset behaviour---keep in mind when reviewed on multiple occasions. The purpose of comparison between stochastic volatility and implied volatility. Prerequisites: Stochastic Models & Computation, Introduction to Options & Futures for Financial Engineering, PDE. Derivatives Modelling and Pricing II Note: Derivatives Modelling I is only a beginner’s course in computational/quantitative finance towards competency and professionalism. Overall, it’s the obligation of the student to reinforce their knowledge and skills from that course; all advance review modules from Derivatives Modelling and Pricing I will have limited duration. All modules in this course will be completed thoroughly and fluidly. Course will make use of various texts and journal articles. I don’t care for mathematicians with their perversions and indulgences. They usually have an office with all the time in the world to do whatever it is they do. Many theoretical mathematical ghouls can belch out and express all sorts of theoretical complications, but are like “fish out water in the real world”. NOTE: this course will never concern such mathematicians becoming acquainted with tools so that they can teach as con artists based on parasitism. NOTE: an 18 weeks course with 2-3 sessions per week. -Textbooks in unison considered: Options, Futures & Other Derivatives, by Hull and Basu Computational Financial Mathematics Using Mathematica (Stojanovic) Economic and Financial Modelling with Mathematica (Varian) Option Valuation Under Stochastic Volatility I: With Mathematica Code (Alan. L. Lewis) Option Valuation Under Stochastic Volatility II: With Mathematica Code (Alan. L. Lewis) Glasserman, P, 2003, Monte Carlo Methods in Financial Engineering, Cambridge University Press, Cambridge. -Journal articles and documents mentioned to be used Assessment --> Homework 25% Prerequisite refreshers problem sets Prerequisite modules/topics/assignments/projects Students will get feedback on their fumbles and errors Current course problems/assignments/projects Computational assignments 35% 4 exams 40% NOTE: exams will reflect homework and computational assignments. NOTE: for computational assignments much will stem from modules. I will not teach you computation and code because prerequisites convey that you are capable of expected tasks with integrity. I will go over the mechanics of the computational assignment, but I will not teach you code because the texts and external sources will provide strong guides; it’s up to you to understand what you’re doing and how to professionally make use and advance in computation. I expect professional commentary, computational layout in a research format (with references because conventionally you are learning to code from somewhere. Don’t make the mistake of being a condescending, toxic and sabotaging entity from a theoretical mathematics department, because they don’t get screwed or fired from occupations they don’t have. Course Outline --> 1. European and American options ---Advance review of model and boundary conditions of European options ---Advance review of modules (3) - (5) from prerequisite 2. Trinomial Model ---Extend model set up to trinomial ambiance (includes extending determination of tree parameters) for European options ---Trinomial model and lattices of two and three steps for European options pricing. ---Simulations for trinomial option pricing for at least four steps (manual programming and/or built in function tool). Compare computational results to binomial pricing, finite difference schemes and monte carlo. ---Trinomial computational algorithm for large nodes exhibiting stochastic trajectories for European options. ---Note: Trinomial model generally to produce more accurate results than the binomial when fewer steps are modelled, say, stability and accuracy with exotic options despite step size (general mention); can be more useful than binomial model for American options. ---Black-Scholes-Merton model via trinomial model by large nodes Note: First, with the assumption of risk-neutral world, expected return from the asset is the “risk-free” interest rate; however, such condition is ideal, and interest rates change. Secondly, from prerequisite, observing that statistical volatility changes over time; volatility has various descriptions, being either realised, implied, local or stochastic, where the preference for the parameter comes from choice out of the mentioned types of volatility. Third, the trinomial process to generally appease diffusion. From consequence of the three conditions, observed is appeasement to the ideal Black-Scholes-Merton ambiance (or geometric brownian motion). Deriving the Black-Scholes-Merton model via trinomial model by large nodes. 3. American options: ---Trinomial model (with control variate technique if warranted) and lattices of two and three steps for American options. Pricing. ---Simulations for trinomial option pricing for at least four steps (manual programming and/or built in function tool). Compare computational results to binomial pricing, finite difference schemes and direct monte carlo. ---Trinomial computational algorithm for large nodes exhibiting stochastic trajectories for American options. Note: students may asked pricing problems where they compare binomial with trinomial. 4. Advance review of modules (8) - (11) from prerequisite; include trinomial model with (11). 5. Advance review of module (12) from prerequisite After computational programming development for the trinomial model compare with results with martingale pricing, Feynman-Kac and binomial pricing. 6. Advance review of modules (12) - (14) from prerequisite 7. Local Volatility ---It’s purpose with options data and underlying asset. ---Relevance to exotic options ---Instantaneous volatility model ---Local volatility model ---How does the local volatility surface compare with the implied volatility surface generated by GBM (with implied volatility use)? ---Dupire volatility. Dupire formula permits the deduction of the “volatility function” in a local volatility model from quoted put or call options in the market. A. Parabolic PDE environment with Dupire’s Formula Mark, H. A. Davis. The Dupire Formula: < https://www.csie.ntu.edu.tw/~d00922011/python/cases/LocalVol/DUPIRE_FORMULA.PDF > Note: don’t take the given data modelling instructions lightly B. Local volatility being the conditional expectation of the instantaneous variance for the final underlying (derive). C. Instability of the Dupire model. A real market will only have a finite number of (liquid) option prices, where price is a result of volatility; eventual goal is the implied volatility to be incorporated into the local volatility formula. Direct interpolation of market prices can be difficult. Note: unique assets often don’t behave in similar fashion, so those of interest must be considered. (i) Market often quotes vanilla options in terms of implied volatility instead of call price (Black-Scholes-Merton). Then it’s often convenient to describe local volatility in terms of implied volatility rather than option prices. Apply the related chain rules for partial derivative of market price w.r.t. maturity, second order partial derivative w.r.t. strike price; find the terms in the chain rules, and insert the necessary found terms into the Dupire formula. Of consequence, local volatility is then expressed in terms of market observables (makes extensive usage of implied volatility surface); again unique assets often don’t behave in similar fashion, so those of interest must be considered. The resulting “improved” formula should revert to the Black-Scholes “no-smile” if one considers the case where the implied volatility is constant over strike and time; be realistic and practical. (ii) An alternative to (i): FOCUS ON pp 61-62 of, Kotzé, Oosthuizen, and Pindza, Implied and Local Volatility Surfaces for South African Index and Foreign Exchange Options, J. Risk and Financial Management. 2015, 8, 43-82. Then apply the New VIX formula to model; again unique assets often don’t behave in similar fashion, so those of interest must be considered. (iii) Constructing a local volatility surface based on implied volatility (includes actual computational work) 1. Assemble the data, consisting of a matrix of quoted option prices {C(Ti, Ki j ), i = 1, . . . , N, j = 1, . . . , M(i)} together with the yield curve (to determine r(t)) and dividend information (to determine q(t)). 2. Interpolate and extrapolate these prices (or, more likely, Black-Scholes implied volatilities) to create a smooth volatility surface C. 3. Calculate σ(T, F) from (3.1) and compute ˜σ(T, S) 4. The price model is S_t given by dS_t = μ(t)S_tdt + ˜σ(t, S_t)S_tdW_t 5. Now we can calculate the prices of other options by finite-difference methods or Monte Carlo 6. What can you do with your model? Recall, that if parameters are not constant, binomial option pricing and Black-Scholes-Merton are useless. Review the developed pricing formulas from Meixner and Variance Gamma (realised, implied). Implied volatility is often applied to exotic options, hence how will one go about the pricing of exotic options with local volatility? Note: preserve the purpose of comparing historical volatility and implied volatility earlier on. Note: such is not a predictor of asset behaviour---keep in mind when reviewed on multiple occasions. The purpose of comparison between local volatility and implied volatility. 8. Bermudian options: ---Strategy, model, boundary conditions, pricing --Will local volatility be more practical than implied volatility with pricing? 9. American barrier options: ---Strategy, model, boundary conditions and strategy. ---Implied volatility vs local volatility with pricing ---Put-Call parity for “down-and-out” call option & “up-and-out” put option. ---Trinomial model for American Barrier, pricing and simulations (similar procedure as done before, however, without need for exhibition of stochastic trajectories for large nodes). ---Development of trinomial computational algorithm. Compare with Mathematica’s FinancialDerivative function and R packages ---Decomposition technique (separating European option value from early exercise premium) involving integral form; also computationally developed in Mathematica. Compare with bit trinomial function and pricing alternatives of by the FinancialDerivative function and R packages ---Feynmac-Kac localised for barrier options ---How does local volatility influence Feynmac-Kac compared to implied volatility? 10. Advance review of Module 15 from prerequisite Computational competency is demanded (modelling and CAS tool). ---When is stochastic volatility most advantageous compared to implied volatility and local volatility? Note: preserve the purpose of comparing historical volatility and implied volatility earlier on. Note: such is not a predictor of asset behaviour---keep in mind when reviewed on multiple occasions. The purpose of comparison between stochastic volatility, local volatility and implied volatility. 11. Asian options ---Strategy: Asian options are very useful for assets of high volatility, means against manipulation, say commodities w.r.t currency denominations (and possibly stock). Are cheaper than European options, but course to focus on American-style of Asian options. ---Structure of American-style of Asian options ---Probabilistic model for pricing of American-Style of Asian options, and boundary conditions; consideration of continuous geometric average; continuous arithmetic average; weighted arithmetic average before expiration date. ---It’s important that one understands the logistics and implementation of volatility in (American-style of) Asian options. The assumption is that averaging reduces volatility risk, however the type of volatility implemented in options pricing should be considered carefully (implied vs, stochastic vs local). Guides of possible interest: Rogers, L.C.G. and Shi, Z. (1995), The Value of an Asian Option, Journal of Applied Probability, 32 (4): 1077–1088, T. Bokes, “Valuation of the American-style of Asian options by a solution to an Integral Equation”, Acta Universitatis Matthiae Belii, ser. Mathematics 16 (2010), 17-23. Not focused on dividends. Devreese J. P. A., Lemmens D. and Tempere J. (2010), "Path Integral Approach to Asian Options in the Black-Scholes model", Physica A, 389 (4): 780–788 Dingeç, Kemal Dinçer, and Wolfgang Hörmann. “Control Variates and Conditional Monte Carlo for Basket and Asian Options.” Insurance Mathematics and Economics, vol. 52, no. 3, 2013, pp. 421–434. Lapeyre, Bernard, et al. “Competitive Monte Carlo Methods for the Pricing of Asian Options.” The Journal of Computational Finance, vol. 5, no. 1, 2001, pp. 39–57. Kubendran, N, et al. “Quasi-Monte Carlo Approach to Asian Options Pricing.” Asia Pacific Journal of Management Research and Innovation, vol. 10, no. 1, 2014, pp. 67–78. Boughamoura, W., & Trabelsi, F. (2011). Variance Reduction with Control Variate for Pricing Asian Options in a Geometric Levy Model. IAENG International Journal of Applied Mathematics, 41(4), 320-329. 12. Assets with the possibility of negative price values (general knowledge) Oil prices and interest rates have known to crash below zero. What kind of distributions can characterise such market behaviour? Is Black-Scholes relevant? Are the options models and pricing different for such circumstances? Prerequisite: Derivatives Modelling & Pricing I Financial Time Series The main objective of this course is to develop the skills needed to do empirical research in fields operating with time series data sets. The course aims to provide students with techniques and receipts for estimation and assessment of quality of economic models with time series data. Special attention will be placed on limitations and pitfalls of different methods and their potential fixes. The course will also emphasize recent developments in Time Series Analysis and will present some open questions and areas of ongoing research. Programming and computation skills further developed in course environment and independently will likely vary among students. Students musts hone their skills in programming and computation that best serves them towards successful completion of course. NOTE: basic time series modelling and forecasting applications are -Commodities (must have numeraire to compare with or reference to) -Currencies (must have numeraire to compare with or reference to). -Stocks -Will also concern ourselves with treating stock movement, different types of volatility (for stock, currency, commodities). -Interest Rates -Inflation -Applying time series to the Nelson-Siegel-Svensson model -Course will have other various realistic applications not mentioned in syllabus. NOTE: one will not just copy time series models, rather, they must analyse and comprehend model design concerning variables and parameters for the respective application or field or industry. Such implies investigating how functions in Mathematica will be applied, and developing means to accomplish goals. NOTE: in the Mathematica environment there is the Wolfram Data Repository available; not necessarily confined to it however. NOTE: Journal articles are application guides for interactive skills with data, modelling, computation and forecasting. One will not just assume that everything in journal articles to be perfect with modelling development, critique, and training & test data. Assignments will have written detailed analysis and modelling, accommodated by computational development in Mathematica notebook (with pdf format printouts). NOTE: students must have strong self-interest concerning all possible parameters for functions encountered in Mathematica The following links for time series processing serve well Wolfram Documentation Centre Time Series Processing Time Series Processes Data Transforms and Smoothing Augmented with the following functions: ListLinePlot DateListPlot Moment HypothesisTestData DistributionFitTest EstimatedDistribution AutocorrelationTest NOTE: for all Mathematica functions, students should take time to observe the range of “parameters” for each function. Just as what was done for Mathematica functions encountered in Mathematical Statistics (which WILL also be useful in this course). NOTE: for each Mathematica function it’s quite important that you comprehend the scope of all parameter options. As well, you must know how make choice of method of interest. Read the damn documentation center sources well. Wolfram Demonstrations may also provide other rewarding guides. AGAIN: for all Mathematica functions, students should take time to observe the range of “parameters” for each function. Just as what was done for Mathematica functions encountered in Mathematical Statistics (which WILL also be useful in this course). NOTE: don’t take your skills from prerequisites lightly. Your knowledge and skills are more powerful than you might imagine when it comes to pre-analysis of data…so you will not slip off an “arrogance cliff” people have waiting for you. Trust yourself and what you’ve accomplished prior. Concerns modelling, computation, simulation and forecasting. Additionally, resources serve towards being capable with large data, and consistency determination, say comparing theoretical model development with Mathematica tools for model selection, data training, forecasting, etc., etc. Mathematica functions in use don’t replace instruction, rather, they serve to be at least competent with real data and growth in real world professionalism. Mathematica skills involving functions learnt and retained from mathematical statistics and computational finance will be invaluable and essential. Cater for multivariate time series as well in similar fashion (comparing theoretical model development with Mathematica tools for model selection, data training, testing validation, etc.). It’s imperative that students remain active with data acquisition and screening from general sources; includes checking whether data is organised appropriately, fraud and how to resolve organisation issues. This should be treated as an obligation with purpose towards a future where one knows how to apply times series for constructive business and professionalism, rather than toxic “all-over-the place" mathematical frolic and obnoxious, trivial excrement. Analytical text --> TBA Computational texts and sources --> Economic and Financial Modelling with Mathematica, by Hal R. Varian, Springer, 1993. Time Series Processing in Wolfram Documentation Center NOTE: students are welcomed to incorporate R skills as well. Grading Options (chosen by me): 25% Assignments + 25% for better of 2 Midterms + 50% Final 30% Assignments + 70% Final Will be individual student based; such is a means in preserving an existence of justice regardless of a respective student’s culture concerning the future (assuming ethical instruction and grading). For exams --> In a room with disabled WIFI, disabled LAN with an environment that rejects hot-spots you will use your computers or room computers with Mathematica ability. At midnight, say, you will be given various data files where you must know how to ACTIVELY apply them towards time series pursuits. Questionnaires will be handed out where task is to complete what’s on such questionnaires. To complete questions you will rely on your statistics and time series knowledge. You are allowed to bring 2-3 loose leaf size sheets of aid to exams. If you make contact with any student during test with any electronic device means, such will warrant an automatic F grade on final without second thought. Exams will be comprehensive. NOTE: through each module summary statistics for time series will be developed/applied and analysed. Done numerous times throughout each module. Course Outline --> 1. INTRODUCTION (module with have practical purpose for tangible applications) Role of time series in the finance markets. Objective of course. Distribution of returns or data, empirical properties. Covariance, Dependence and Stationarity. Time series representation of data Difference equations modelling, lag operators, and conditional expectation Simple Stationary Models Autoregressive Processes Moving Average Processes Decomposition: Additive and Multiplicative Seasonal tests Non-parametric test HAC Non-Parametric Tests of Mean of Differences Time Trend tests Trend tests Buys-Ballot Plots Friedman’s Non-parametric test F-Test Stationarity tests Augmented Dickey-Fuller test Kwiatkowski-Phillips-Schmidt-Shin test Linearity and logarithmic structure Forecasting and Forecasting Errors for earlier encountered time series MAE, MAPE and RMSE 2. BOX-JENKINGS METHODOLOGY NOTE: legacy literature (but logistics toward Mathematica/R usability is the prime directive in this module) -- Box, G.E.P. & Jenkins, G.M. (1976). Time Series analysis: Forecasting and Control. Second edition. Holden-Day Press, San Francisco. 3. ARMA MODELS Basic Properties Relevance of tests (seasonal, trend, stationarity) ARMA(p, q) models: generation, estimation, validation/diagnostics Autocorrelation and Partial Autocorrelation Functions Forecasting and Forecasting Errors for earlier encountered time series MAE, MAPE and RMSE 4. BOX-JENKINS METHOD WITH ARMA Approach Relevance of tests (seasonal, trend, stationarity) Model identification & Model selection Parameter(s) estimation (via MLE or Non-linear least squares) Model checking (includes Ljung-Box test, Box-Pierce text and/or plotting autocorrelation and partial autocorrelation of the residuals are helpful to identify misspecification) Training and test data, validation Forecast errors (use of MAE, MAPE and RMSE) 5. ARIMA MODELS Like modules 3 & 4, but emphasis on the significance & relevance of the “I” in ARIMA. 5. NON-STATIONARY AND SEASONAL MODELS Unit Roots -- recognising its decomposition into stationary series and a random walk; implication of non-stationary but not the reverse; types of practical unit roots tests; trend-stationary versus difference stationary; unit root tests are a tool for assessing the presence of a stochastic trend in an observed series. Seasonal Models Seasonal Autoregressive Integrated Moving Average (SARIMA) Hipel, K. W. and McLeod. A. I. (1994). Chapter 12: Seasonal Autoregressive Integrated Moving Average Models. Time Series Modelling of Water Resources and Environmental Systems. Elsevier, pages 419 - 462 Pursuit of applications in finance Forecasting and Forecasting Errors for earlier encountered time series MAE, MAPE and RMSE 6. DETERMINISTIC TREND VERSUS STOCHASTIC TREND Diebold, F. X. and Senhadji, A. S. Deterministic vs. Stochastic Trend in U.S. GNP, Yet Again. NBER Working Paper 5481, March 1996 What types of other data or assets are best suited for such modelling and analysis? 7. STATE-SPACE MODELS (SSM) NOTE: will only focus on SSM as an alternative to Box-Jenkins (BJ) Advantages and disadvantages to BJ State-Space Formulation Structural Models AR, MA, ARMA and ARIMA models in state-space form Develop the counterpart process for Box-Jenkins Verify the concern of Commandeur & Koopman with real data against BJ. Forecasting and Forecasting Errors for earlier encountered time series MAE, MAPE and RMSE Versus BJ approach Filtering and Smoothing: The Kalman Filter and EM Algorithm 8. ARCH MODELS Valid settings for introduction and practicality in applications MUST: efficient counterpart process to module 4 or 5. Incorporate methods for forecast errors wherever appropriate. A methodology to test for the lag length of ARCH errors using the Lagrange multiplier tests (three steps) --> Engle, Robert F. (1982). Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation. Econometrica. 50 (4): 987–1007 Training and test data, validation Forecasting and Forecasting Errors for earlier encountered time series MAE, MAPE and RMSE Veiga Á., Medeiros M.C., Fernandes C. (1998) State Space Arch: Forecasting Volatility with a Stochastic Coefficient Model. In: Refenes AP.N., Burgess A.N., Moody J.E. (eds) Decision Technologies for Computational Finance. Advances in Computational Management Science, vol 2. Springer, Boston, MA, pages 267- 274. Forecasting and Forecasting Errors for earlier encountered time series MAE, MAPE and RMSE What kind of volatility are we forecasting? 9. GARCH MODELS NOTE: all that was treated for ARCH will extend to GARCH with the error variance. Incorporate methods for forecast errors wherever appropriate Applications --> -Bollerslev, T. (1986). Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics. 31 (3): 307 – 327. -The lag length p of a GARCH(p, q) process established in three steps D. Ruppert. Statistics and Data Analysis for Financial Engineering. In: Chapter 18 (GARCH Models). Springer Texts in Statistics. 2011 -Hull, J. C. and Basu B. (2016). Estimating Volatilities and Correlations. In: Options, Futures and Other Derivatives. Pearson. Pages 554 – 564. Determination of parameters will not be taken lightly, and preference will be individual assets rather than a market index such as the S&P 500; market indices to be done after. How does “future volatility” development compare to implied volatility via Newton-Raphson method, and which is more practical? -Hull, J. C. and Basu B. (2016). Estimating Volatilities and Correlations. In: Options, Futures and Other Derivatives. Pearson. Pages 564 – 566. -D. B. Nugroho et al 2019. Empirical performance of GARCH, GARCH-M, GJR-GARCH and logGARCH Models for Returns Volatility. J. Phys.: Conf. Ser. 1307 012003 What kind of volatility is being considered? Will be in an applications environment with more modern data. -Comparison of GARCH (1,1), EGARCH, GJR-GARCH, TGARCH for implied volatility. Will be in an applications environment with data. -Lingling Luo, Sattayatham Pairote & Ratthachat Chatpatanasiri (2017) GARCH-type Forecasting Models for Volatility of Stock Market and MCS Test, Communications in Statistics - Simulation and Computation, 46:7, 5303-5312 -Guillermo Ferreira, Jean P. Navarrete, Francisco J. Rodríguez-Cortés & Jorge Mateu (2017) Estimation and Prediction of Time-Varying GARCH models through a State-Space Representation: A Computational Approach, Journal of Statistical Computation and Simulation, 87: 12, 2430-2449 10. STOCHASTIC VOLATILITY Jacquier, E., Polson, N. G., & Rossi, P. E. (2002). Bayesian Analysis of Stochastic Volatility Models. Journal of Business & Economic Statistics, 20(1), pages 69–87. GARCH models vs Stochastic Volatility models vs Heston model Kastner, G. Dealing with Stochastic Volatility in Time Series Using the R Package stochvol. CRAN R Omari, C. O., Mwita, P. N. and Waititu, A. G. (2017). Modelling USD/KES Exchange Rate Volatility using GARCH Models. IOSR Journal of Economics and Finance. Volume 8, Issue 1 Compare one’s conclusions of decent model(s) to that of the journal article, say, replicate with more modern data comparing article’s models to yours. Note: the applied exchange may be substituted for others, and as well, identify how the observation period range can considerably alter findings; one market year behaviour can be totally different to another. Pursue also with stochastic volatility models and Heston model for compare and contrast. 11. PARTICULAR APPLICATIONS IN FINANCE NOTE: there must be integrity with model identification, selection, parameter(s) estimation and diagnostics. --Asymmetric news Engle, R. F. and Ng, V. (1993). Measuring and Testing the Impact of News on Volatility, Journal of Finance 48(5), 1749 - 1778. --Mean-Variance Portfolio Optimization Soeryana, E., et al, (2017). Mean-Variance Portfolio Optimization by using Time Series Approaches based on the Logarithmic Utility Function, IOP Conf. Series: Materials Science and Engineering 166 (2017) 012003; versus conventional method for mean-variance portfolio optimization. --French, J. (2017). The Time Traveller’s CAPM. Investment Analysts Journal, 46: 2, 81-96 Note: may be interested in multi-factor models as well. 12. MULTIVARIATE TIME SERIES (model selection, estimation, validation, forecasting, training-test data, validation and forecast error methods when necessary) Vector Autoregression (well-rounded and applied computational relevant) State Space Representation of VAR Treatment should be tangible, practical and computationally accessible as in the manner done with other modules (modelling, estimation, validation, error). Further Multivariate Models Moosa I.A. (2000) Multivariate Time Series Models. In: Exchange Rate Forecasting: Techniques and Applications. Finance and Capital Markets Series, Palgrave Macmillan, London. Raddant, Matthias & Wagner, Friedrich. (2016). Multivariate GARCH for a Large Number of Stocks. Kiel Working Paper, No. 2049 Forecasting the Yield Curve Moench, E. (2005). Forecasting the Yield Curve in a Data-Rich Environment: A No-Arbitrage Factor-Augmented VAR Approach, ECB Working Paper No. 544 Prerequisites: Mathematical Statistics, and Derivatives Modelling & Pricing I to retain registration in course. Commodities & Futures Trading -Despite heavy use of technical analysis with commodities, factors that drive markets are supply and demand; economic view, weather, pestilence, political issues and shocks are ever prevalent. -Commodities often demand much more “field experience” because there are unique mechanisms and parameters not identifiable with other assets (such as stock and bonds which having no relevance to delivery and other things). As well, some commodities are perishable which makes things much more interesting. Many tend to overestimate their knowledge and skills with commodities markets. -This course will mainly focus on hard commodities (energy products and metals) -For a fledgling, this course serves to be constructive, practical, reasonable and fluid for a beginner. Course serves to be a foundation that’s integrable with real markets, rather than creating a runaway trainwreck for students new to (hard) commodities. The mechanics, strategies and applied tools for the commodities market can be devastating to an individual when taken for granted. Comprehension, fundamentals and skills to be reinforced and remain fresh. -For constructive use of derivatives, comprehension of markets is vital; opportunities and risk must be well managed. Can technical analysis alone account for market forces and agents? -Course should never be used as a general beginner derivatives course; the later it is taken, more likely the greater benefit with future re-acquaintance. -An 18 weeks course, having at least 2 hours per lecturing session for 2 days per week. -Lab hours are unique to lecturing hours. Some labs will require multiple days to complete. Each lab session requires 2 hours. Course Assessment --> --Homework: 15% --3 Quizzes: 15% --4 Exams: 40% --Labs + Trading experience: 30% Texts in unison example: Peterson, P. E. (2018). Commodity Derivatives: A Guide for Future Practitioners. Routledge. 280 pages Kolb, R. & Overdahl, J. Understanding Futures Markets, Blackwell Pub Crucial links for data (databases)--> --FAO --OECD --WASDE --CME --UN Comtrade Database --Commodities Futures Trading Commission databases (ambiance analogy) --Financial markets data sources --Quandl Necessary Tools --> Mathematica FACTSim Labs and Trading experience --> Note: each lab stage likely will have multiple sessions Labs stages: 1. Data acquisition and data analysis with Mathematica Summary statistics Distribution modelling and fitting of stocks and indices Regressions and time series models Mathematica Financial Data Mathematica Financial Visualization 2. Applied fundamental analysis based on scarcity elements 3. More empirical analysis of scarcity elements and computational development of the literature of Westcott & Hoffman 4. More active logistics with FACTSim Will build on activities from first lecture topic. Hence, it’s assumed students were keeping good logistical notes and have dedicated personal time to becoming quite comfortable and competent with FACTSim. 5. Technical Analysis (TA) & Time Series Limited constituents for TA but highly robust methods Time Series Modeling of Cash and Futures Commodity Prices Salient Characteristics: Additive/Multiplicative Decomposition Futures prices prediction and error After analytical structuring will incorporate both Mathematica and FACTSim for meaningfulness. 6. More and More FACTSim and Mathematica 7. Hedging activities. Minimum variance Hedge Ratio based on regression (and possibly other hedge ratios). Reminder: hedging is not speculation. 8. Advance review of some skills (modelling and computation) from at least Derivatives Modelling & Pricing I with focus on commodities; commodities options pricing methods; volatility types and their application to commodities derivatives. 9. Options on futures Course Outline --> 1. FACTSim - online simulation trading introduction (used throughout course). 2. Trading Methods & Strategies: Fundamental Analysis & Technical Analysis --Commodities Influences on commodities prices Benchmarks/markers for commodities. Why do they differ among a particular commodity such as oil? Which benchmark/marker concerns you, say delivery/procurement versus taking advantage of market dynamics without possessing the asset? Balasubramaniam, K. (2020). Who sets the Price of Commodities? – Investopedia Future outlook on commodities (judgmental AND quantitative methods) Lioudis, N. K. (2020). Commodities Trading: An Overview – Investopedia --Scarcity Elements in play for scarcity: resources, production, supply, production costs, demand, stocks-to-use ratio Ability to develop price road maps based on the scarcity elements Peculiar case with oil: Englund, W. (202). Oil Drops Below $0, Signaling Extreme Collapse in Demand. But, You’re Still Going to Have to Pay for Gas. Washington Post Further Awkward Cases Vasquez, J. and Pakiam, R. Gold Prices Plunge by Most Intraday since June 2013, Bloomberg Bloomberg, Gold Joins the Virus Sell-Off With Biggest Slide Since 2013 --Technical Analysis Predominant measures and tools to capture market sentiment (limited constituents but highly robust methods). NOTE: will have considerable analysis and hands-on immersion into predominant measures and tools of technical analysis. Is the use of historical volatility constructive and sensible for commodities? What kind(s) of volatility are most meaningful? NOTE: will have considerable analysis and hands-on immersion into predominant measures for volatility 3. Market Factors and Gov’t Programmes Westcott, P. C. and Linwood A. Hoffman. (1999). Price Determination for Corn and Wheat: The Role of Market Factors and Government Programmes. Market and Trade Economics Division, Economic Research Service, U.S. Department of Agriculture. Technical Bulletin No. 1878: www.ers.usda.gov/webdocs/publications/47264/51097_tb1878.pdf Note: extendable for other soft commodities. Also, to then situate to more modern time periods. 4. Pricing Methods Critically, comprehension of the motivations/causalities for positions, and comprehension of instruments relevant to appropriately apply. Modules 2 and 3 will come back to haunt. Fixed Price Floor Price Ceiling Price Floating Price 5. Correlating Markets Understanding what “correlation” means to apply it appropriately. What is the most appropriate correlation model? Markets/Industries of interest towards hard commodities prices. Analytical Development Computational development and implementation 6. Peculiar asset dynamic due to market agents Vasquez, J. and Pakiam, R. Gold Prices Plunge by Most Intraday Since June 2013, Bloomberg Bloomberg, Gold Joins the Virus Sell-Off with Biggest Slide Since 2013, Bloomberg Concerning (5) for the markets that are conventionally highly correlated with gold (posititive or negative), does such remain the same for the described events in both articles? Provide rationale concerning the observed correlation. 7. Asset Price Bubbles Robert Jarrow (2016) Testing for Asset Price Bubbles: three new approaches, Quantitative Finance Letters, 4:1, 4-9 Will like to develop at least two out of three for compare/contrast with past events concerning prediction accuracy 8. Futures Review of futures contracts and futures markets O’ Hara, N. (2020). How to Use Index Futures – Investopedia Will also pursue a quantitative/computation examination with market data. However, what is the horizon? REMINDER: “forces of nature” and news/information change everything. 9. Buying and selling futures (strategies and mechanics) 10. Cash vs. futures prices Arbitrage Speculation 11. Time Series --Outlining the relevant time series to apply (review your comprehension, computational logistics and implementation independently) --Time Series Modeling of Cash and Futures Commodity Prices --Futures prices prediction/forecasting --Is your Fundamental Analysis and Technical Analysis harmonic with your time series prediction/forecast? If not, what’s going on? 12. Forecasting Markets Note: adjust with data of interest, incorporating more modern data if more meaningful with markets. May have to observe different phases of the business cycle to acquire a robust conclusion. Emmons, W. R. and Yeager, T. J. (2002). The Futures Market as a Forecasting Tool: An Imperfect Crystal Ball. Federal Reserve Bank of St. Louis Reichsfeld, D. A. and Shaun K. Roache, S. K. (2011). Do Commodity Futures Help Forecast Spot Prices? IMF Working Paper. WP/11/254 12. Spreading with futures Smith, T. (2022). Futures Spread. Investopedia CME Group Futures Spread Overview: https://www.cmegroup.com/education/courses/understanding-futures-spreads/futures-spread-overview.html Understanding Futures Spreads: https://www.cmegroup.com/education/courses/understanding-futures-spreads.html 13. Hedging with futures - fundamentals, strategies, exercises 14. Application of Minimum Variance Hedge Ratio 15. Review of options Expect similar tasks from prior derivatives courses, but catering for commodities 16. Options on futures Concepts and practical models for markets 17. Speculating, spreading, and hedging with options on futures Apart from the interest rate, must determine appropriately the other parameters that make the options practical in use. Prerequisites: Advance course in financial derivatives, Financial Time Series. Fixed Income Securities: In the market of fixed income securities elements such as interest, yield and credit/default are considered primary concerns. However, such three elements are commonly influenced by microeconomic market agents, where these market agents reside within the macroeconomic function. As well, derivatives are often applied to fixed income securities for hedging or speculation, where the related transactions data can also move the herd. Hence, fixed income instruments aren’t overall fixed, but rather cash flow or rate of return being variable. Course aims to give a well-rounded introduction to the market and tools relevant to fixed income instruments, rather than having a boring and misleading view from a mathematician’s Neverland run-a-mock, or mundane actuarial annuity focus. Data importation and manipulation will be extensive in this course. Course is designed for students to retain meaningful market skills and to encourage further skills, rather than brute force memorization for momentary examinations renown in a Midwood area college. Concerning computational algorithms or packages, instructors will mostly provide guide analysis and logistics, while students are responsible for actual computational development for study, assignments and projects. Computation assignments must be accompanied by quantitative analytical design and reasoning with fitted parameters. Students to also be tested on models of computational algorithms. FUTHERMORE: MANUAL DEVELOPMENT (PEN AND PAPER) HAS ITS LIMITATONS WHEN DEALING WITH PROPERTIES OF BONDS. IN THE PROFESSIONAL INDUSTRY YOU DON’T HAVE TIME FOR EVERYTHING WITH PAPER AND PEN WITH MATHEMATICAL PERVERSION. YOU WILL MAKE USE OF YOUR SKILLS ACQUIRED FROM PREREQUISTES R (knowledge and skills will be invaluable (from Microeconomics I; Macroeconomics I & II; Corporate Finance; Theory of Interest; Investments & Portfolios in Corporate Finance) As well the packages to incorporate: fImport, Quandl, Quantmod, tvm, YieldCurve, jrvFinance, BondValuation, credule, FinCal, fPortfolio, LDPD, NMOF, pa, Performance Analytics, PortfolioAnalytics, RQuantLib Note: some of the above packages have been introduced in the prerequisite courses. The other packages have been introduced in the course that is Investments & Portfolios in Corporate Finance Note: packages are no good sans analytical development Note: you may also be writing monte carlo and binomial/trinomial tree code to be compared to packages when the times arise. MATHEMATICA (tools and skills from Numerical Analysis, Data Programming with Mathematica, Probability & Statistics, Stochastic Modelling & Computation, Mathematical Statistics, Intro to Options & Future for FE, Derivatives Modelling & Pricing I, Financial Time Series). As well, functions of use to incorporate: FinancialData, TimeValue, EffectiveInterest, CashFlow, FinancialBond, FinancialDerivative, InflationAdjust. Includes time series functions encountered in Financial Times Series course. Take effort to investigate parameters and methods available in such Mathematica functions; you may be able to choose methods and various parameter setting in the functions. THIS IS NOT A 25 - 26 SESSIONS COURSE. YOU WILL NEED MORE THAN THAT TO DEVELOP NAVIGATION SENSE AND GOOD PRODUCTIVITY (up to 9 more). COURSE TO ALSO INCORPORATE LABS (review topics then carrying out lab goals). LABS WILL BE BOTH ANALYTICAL, COMPUTATIONAL AND DATA DRIVEN. COURSE IS NOT TO SERVE THOSE OF PURE MATHEMATICAL FLATTERY. YOU ARE DEALING WITH A MARKET OF ACTIONS AND CONSEQUENCES, NOT CARTEL RENT SEEKING AND ANTISOCIAL BEHAVIOUR WITH DEVILS. NOTE: for mentioned journal articles there will be attempt to develop computation/simulation environments (that will also incorporate real data). Course Evaluation --> 2 exams (50% of grade) HW + Labs + Computational Assignments + Projects (45% of grade) Attendance 5% Course Outline --> 1. Properties of Fixed Income Securities (RAPID REVIEW) THERE IS MUCH TO DO BEYOND THIS MODULE; FINNESSING WITH DETERMINISTIC INTEREST MODELS WILL BE LIKE CHEMICAL COMBUSTION ROCKET FUEL TO A ION PROPULSION MOTOR. NAMELY, THE SPECIFIC IMPULSE ISSUE. HOW FAR CAN YOU GO WITH THE FORMER? --Types of interest rates --Measuring interest rates --Bond Market Entry (corporate & gov’t bonds) Market participants & Financial objective (risk free versus risky) Procedures and logistics for bond issuance Sanctioned agencies, government agencies and processing Transactions costs throughout the process Role of credit in market entry. What purpose does the credit market serve? ---Basic properties of fixed instruments A. Discrete compounding for Cash flow, NPV & FV. Continuous compounding for NPV & FV and the calculus for such. Show series convergence to exponential prematurely B. Coupons subject to all in (A) C. Value of a zero bond, subject to all in (A) D. Value of a bond paying a coupon interest and the principal at maturity subject to all in (A) E. IRR with numerical methods, subject to all in (A) & (D) F. Accrued Interest & Effective Interest Rate, subject to all in (A) & (D) G. YTM (for both zeros & D); subject to all in (A) and (D) H. Bond yield versus price I. Memorizing formulas is generally not required throughout, however, understanding how and when to use them is my only concern; you have much to cover in this course. Exercises and homework for relating/connecting formulas with each other for various pursuits rather than plain substituting in values for parameters. Relations among Cash Flow, NPV, FV, IRR, effective interest rate, YTM and YTC. Formulas and such examples to be introduced in the most constructive and time efficient manner; expect (A) through (G) to consistently resonate. J. How do banks determine what interest rates to provide to consumers? What tangible and practical models exist that reflect market risks, credit risk and macroeconomics? How does it behave compared to the feds fund rate and SOFR (or EURIBOR or whatever)? K. Overview of variable interest and its implication on NPV, FV, valuation and accrued interest Subject to (A) through (D) NOTE: in succeeding modules for the case of corporate bonds will not blindly assume without coupon interest. 2. Tools for Fixed Income Securities ---Market relationship between bond prices and interest rates Luthi, B. (Author) and Kindness, D. (Reviewer), 2020. Why Do Bond Prices Go Down When Interest Rates Rise? The Balance Lioudis, N. K. (2020). Inverse Relationship Between Interest Rates and Bond Prices. Investopedia Interest rate risk — When Interest rates Go up, Prices of Fixed-rate Bonds Fall. Investor Bulletin, SEC: https://www.sec.gov/files/ib_interestraterisk.pdf Note: with historical data students must verify the (negative) correlation, and exhibit an inverse model for various classes of bonds (risk levels and maturity). ---Analysis of market yield variations Will gather yield/interest rate data for different time scales for various bonds (gov’t and corporate) and pursue modelling. Distributions based on data compared to stereotypical analytical density models; analytical density models of concern are the Hull-White model, Ornstein-Uhlenbeck model, Black-Derman-Toy model, and Black–Karasinski model ---Forecasting Interest Rates based on monetary rules Monetary policy rules towards to the feds funds rate; observation of the different types based on historical action of the Fed with economic conditions: https://www.federalreserve.gov/monetarypolicy/policy-rules-and-how-policymakers-use-them.htm Comprehending effects of Fed action for debt/credit markets ---Forecasting Interest Rates by other methods Duffee, Gregory, 2013. Chapter 7, Forecasting Interest Rates, “Handbook of Economic Forecasting. In: G. Elliott, C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, Edition 1, volume 2, pages 385-426, Elsevier. ---Classical Durations (with respective advantages and disadvantages) A. Macaulay B. Modified ---Effective Duration ---Exponential Duration Livingston, M. and Zhou, L. (2005) Exponential Duration: a More Accurate Estimation of Interest Rate Risk, Journal of Financial Research, 28, 343–61 ---Discrete Duration Include exponential duration along in a comparative analysis with Macaulay, Modified and Exponential duration: Bajo, E., Barbi, M. & Hillier, D. (2013). Interest Rate Risk Estimation: A New Duration-Based Approach. Applied Economics, 45(19), pages 2697 - 2704 ---Convexity Analysis based on the types of durations encountered prior) ---Immunizations (with respective purpose and advantages) A. Cash Flow matching Include the following development: Funding with bonds of different maturities with LP Corporate debt defeasance B. Duration Matching C. Interest Rate Swaps ---Tchuindjo, L. (2007). An Accurate Formula for Bond-Portfolio Stress Testing. The Journal of Risk Finance, Vol. 9, No. 3, 2008, pp. 262-277 ---PCA in Interest Rate Risk Management NOTE: Establish the circumstances for PCA usage being more constructive or practical versus basic durations and immunizations. NOTE: module will be highly data driven and computational. Hagenbjörk, J. & Blomvall, J. (2019). Simulation and Evaluation of the Distribution of Interest Rate Risk. Comput Manag Sci 16, 297–327 Pelata, M., Giannopoulos, P. & Haworth, H. (2012). PCA Unleashed: Interest Rate Strategy - The application of PCA across European Rates Markets. Credit Suisse ---Yield Spread Apart from such determination percentage, is that percentage directly cash interpretable concerning difference? Say, the principle of a respective bond and YTM are often unique to another bond. Consider a means to compare performance between two industries based on yield spread movements. How can one accomplish such? 3. Risk free assets, AA rank, lower grade foreign gov’t bonds, and attempt on forecasting economic weather. ---Structures of Instruments’ (“T-bills”, zero coupon strips, and nominal coupon bonds) ---Acquisition Market agents for auction process versus direct purchase Effect of availability on premiums from auctions. How aggressive are auctioneers with acquisitions? Auction process based on yield to maturity, interest coupon rate, and the discount (or premium) on a treasury security. Competitive and non-competitive bids; purchasing at a discount versus purchase at a premium. ---The Yield curve. Logistics & computational algorithms for observation. A. The Nelson–Siegel–Svensson model: interpreting its components B. Estimation via Nelson–Siegel–Svensson (NSS) model via market data incorporation and use of times series towards betas of the model. C. Estimation via a chosen spline technique D. Reason why geometry of yield curved is conventionally upward sloping involving risk and higher interest rates for long-term investments. E. Case of inverted curve as a sign of possible recession and weak credit outlook. How accurate are such? Use of historical data and confirmation. For which countries is the yield more accurate with economic outlook, and why so? F. Review forecasting interest rate from the two sub-modules in (2) to compare with (B) though (C). 4. Foreign securities and foreign cash in a central bank’s portfolio ---For transactions with foreign currencies, what is the influence on government securities and vice versa? How do currency crashes or downturn influence associated gov’t securities? 5. Measures for US risk free assets. Instructor must develop comprehension and exhibit modelling to students, and how to competently read and analyse market data: ---Definitions and use of TYVIX MOVE (Merrill Lynch option volatility Estimate) Index Note: for such measures there are likely analogies to such for a respective ambiance of interest (AAA to A-). Else, pursue development of programming if possible. 6. Collateral Trust Bonds and the Eurobond (not being Eurobonds of the EU Central bank) Hayes, A. (2021). Collateral Trust Bonds. Investopedia Seth, S. How Does a Eurobond Work. Investopedia How to measure currency exposure for such prior? Remedies for unfavourable exposure. Can Eurobonds also be collateral trust bonds? 7. Bond Betas Idea and model(s) Nektarios Aslanidis, Charlotte Christiansen, Andrea Cipollini, (2019), Predicting Bond Betas Using Macro-Finance Variables, Finance Research Letters, Volume 29, Pages 193-199 João F. Caldeira, Guilherme V. Moura, André A.P. Santos, (2016), Bond Portfolio Optimisation using Dynamic Factor Models, Journal of Empirical Finance, Volume 37, Pages 128-158 8. Debt Ratings Data Fitch, S&P, Moody’s, IMF, World Bank and CariCris; such firms possess both foreign government ratings risk indicators, as well as for foreign private firms. Instructor must exhibit to students how to competently read and analyse such data. Speculate on what models are applied to determine such ratings. IMF excerpt, Chapter 3, “The Uses and Abuses of Sovereign Credit Ratings”. 9. Default Probabilities for Fixed Income Securities Develop computational models and compare with results of the ratings firms mentioned in (8). Iqbal, N., & Ali, S.A. (2012). Estimation of Probability of Defaults (PD) for Low-Default Portfolios: An Actuarial Approach. 2012 Enterprise Risk Management Symposium, April 18-20, 2012 Pluto, Katja & Tasche, Dirk. (2011). Estimating Probabilities of Default for Low Default Portfolios. In: Chapter 5, Engelmann, B., & Rauhmeier, R. (2011). The Basel II Risk Parameters: Estimation, Validation, Stress Testing - with Applications to Loan Risk Management. Berlin, Heidelberg: Springer Berlin Heidelberg, Pages 75 - 101 10. Using Equity Prices to Estimate Default Probabilities Merton. R. C. (1974). On the Pricing of Corporate Debt: The Risk Structure of Interest Rates. Journal of Finance, 29: 449 – 70 Hull, J. C. and Basu, S. Using Equity Prices to Estimate Default Probabilities. In: Options, Futures and Other Derivatives. Pearson. 2016, pages 582 – 584 Note: for both prior literature one should realise that the parameters involved are generally not handed to them, rather, they must accurately acquire them from sources or through the data modelling. There will be practical exercises, and treatment for general bonds (besides zero coupon bonds) as well. Will be directly immersed with determining a company’s assets and liabilities as inputs. Only for cross reference: Moody’s KMV provides a service that transforms a default probability produced by Merton’s model into real-world default probability (which it refers to as an expected default frequency, or EDF); students should understand such a transformation model. Extend Merton’s model to the KMV model Altman Z with default risk Compare amongst each other: Merton, KMV, Altman Z, (8) and (9). 11. Credit Spread -Instructor must exhibit to students how to competently read and analyse data out of the most practical sources. Credit spreads are larger for debt issued by emerging markets and lower-rated corporations than by government agencies and corporations of wealthier nations. Why? Spreads are larger for bonds with longer maturities. Why? One can also develop credit spreads for countries apart from U.S. government bonds considered. Compensation for credit risk. Haubrich, J. G. and Thomson, J. B. (2007). Credit Spreads and Subordinated Debt. Economic Commentary, Federal Reserve Bank of Cleveland. Note: Focus on “Extracting Useful Information” section concerning the abilities of reduced-form method of pricing risky bonds Robert Jarrow, and Stuart Turnbull. 1995. “Pricing Derivatives on Financial Securities Subject to Credit Risk,” Journal of Finance, volume 50, pages 53–86. Darrell Duffie, and Ken Singleton. 1999. “Modeling Term Structures of Defaultable Bonds,” Review of Financial Studies, volume 12, pages 687–720. Do corporate bonds typically underperform? As well, make use of (8), (9) and (10) towards the credit spread formula and compare with market data. 12. The TED spread Concept. Instructor must exhibit to students how to competently read and analyse market data observed: ---Credit risk and default risk observation ---Trade construction methodology ---Perturbation values, observation of hedge ratios (with any formula) ---Liquidity-related factors Note: for such measures there are likely analogies to such for a respective ambiance of interest to create a “foreign TED spread”. Else, construct them. Also, with the replacement of LIBOR apply appropriate substitution. 13. Default Correlations Determining default correlations or the probabilities of default by more than one firm is vital in credit analysis, risk management and so forth. Does anything from modules (8) through (11) apply? The following articles provide resolutions to treating default correlations. Adopt the most tangible and practical means w.r.t. time consumption; will likely rely heavily on a CAS (requiring user to be highly competent). There will be computational tasks given: A. Merton’s Model Approach Erlenmaier, U. and Gersbach, H. (2014). Default Correlations in the Merton Model, Review of Finance, 18(5), Pages 1775–1809 Note: may try to extend Merton’s model to the KMV model for such. B. First-Passage-Time Models Approach Zhou, C. An Analysis of Default Correlations & Multiple Defaults. Rev. Financ. Stud. 2001, 14, 555–576. Valužis, M. On the Probabilities of Correlated Defaults: A First Passage Time Approach. Nonlinear Anal. Model. Control 2008, 13, 117–133. Metzler, A. On the First Passage Problem for Correlated Brownian Motion, Stat. Probab. Lett. 2010, 80, 277–284 Li, W. Probability of Default & Default Correlations. J. Risk Financial Manag. 2016, 9, 7 C. Multi-Factor Models Approach 14. Swaps ---Bond Swap Chen, J. (2020). Bond Swap. Investopedia Adams. K. (2019). The Advantages of Bond Swapping. Investopedia Boardman, C., & Celec, S. (1980). Bond Swaps And The Application Of Duration. Business Economics, 15(4), 49-54. ---Interest Rate Swap Kuepper, J. and Scott, G. (2020). Interest Rate Swap. Investopedia Determining SOFR/swap zero rates beyond 12 months (apply whatever rate for ambiance of interest) Mirzayev, E. (2021). How to Value Interest Rate Swaps. Investopedia Note: generally there’s valuation in terms of bond prices, and valuation in terms of FRAs. ---Bilateral Netting ---Swap Spreads and use with economic analysis 15. Credit Default Swaps Kuepper, J. & Scott, G. (2020). Credit Default Swap (CDS) Definition, Investopedia ---Sources of market data: data on an annual and semi-annual basis is available from the International Swaps and Derivatives Association (ISDA); data also available from the Bank for International Settlements (BIS); the Depository Trust & Clearing Corporation (DTCC) through its global repository Trade Information Warehouse (TIW) provides weekly data, but the publicly available information goes back only one year. Daily, intraday and real time data is available from S&P Capital IQ via their acquisition of Credit Market Analysis. The numbers provided by each source do not always match because each provider uses different sampling methods. What are such sampling methods about? �� Instructor must exhibit to students how to competently acquire, read and analyse data out of the most practical sources mentioned, and what ways they are relevant to instruments, models, etc. ---Uses: speculation, hedging and arbitrage. Constructive and practical examples to be entertained, respectively. ---Settlement: physical or cash where constructive and practical examples to be entertained, respectively. Auctions. ---What is the Z-spread and its relevance to CDS? Why Z for spread? Are there more realistic models than Z? Pursue and compare. ---Pricing and Valuation: the probability model and the no-arbitrage model. Constructive and practical examples to be entertained and results compared among models: Hull, J. C. and White, A. D. (2000). Valuing Credit Default Swaps I. The Journal of Derivatives, 8 (1) 29 – 40 Hull, J. C. and White, A. D. (2000). Valuing Credit Default Swaps II. The Journal of Derivatives, 8 (3), 12 – 21 Note: if one can’t develop computational logistics towards implementation, then there’s not much value in it. Hence computational logistics towards implementation in a CAS is a necessity, accompanied by use of R package credule. Nevertheless, computations must reflect market data. ---Systematic risk concerns with CDS ---Chan-Lau, J. (2003). Anticipating Credit Events using Credit Default Swaps, with An application to Sovereign Debt Crises. IMF Working Paper, WP/03/106. Note: will have active assignments for development. 16. Influence of Inflation on Fixed Instruments ---Towards comprehension Concept of inflation and types of measures Interest rates respond to inflation: when prices in an economy rise, the central bank typically raises its target rate to cool down an overheating economy. Inflation also erodes the real value of a bond's face value, which is a particular concern for longer maturity debts. ---Correlation investigation between inflation, interest rates and bod prices for different years. Namely, correlation matrix along with heatmap development. Time lagged cross correlation (TLCC) & windowed TLCC Dynamic Time Warping (DTW) Instantaneous Phase Synchrony ---Long-term interest rates on the other hand, market forces (supply and demand) determine equilibrium pricing for long-term bonds, which set long-term interest rates. If the bond market believes that the central banks “market committee” has set the fed funds rate too low, expectations of future inflation increase, which means long-term interest rates increase relative to short-term interest rates – the yield curve steepens; for belief that the fed funds rate is set too high, the opposite happens, and long-term interest rates decrease relative to short-term interest rates – the yield curve flattens. ---The Timing of a Bond's Cash Flows and Interest Rates If market participants believe that there is higher inflation on the horizon, interest rates and bond yields will rise (and prices will decrease) to compensate for the loss of the purchasing power of future cash flows. Bonds with the longest cash flows will see their yields rise and prices fall the most. This should be intuitive if you think about a present value calculation – when you change the discount rate used on a stream of future cash flows, the longer until a cash flow is received, the more its present value is affected. The bond market has a measure of price change relative to interest rate changes; this important bond metric is known as duration (with identification of the most appropriate type and convexity). ---Brenner, M., & Landskroner, Y. (1983). Inflation Uncertainties and Returns on Bonds, Economica, 50 (200), 463-468 --> It’s important that more highly modern data is applied to model(s) to convey points. As well, the other journal articles in reference (excluding Fama 1976) may prove quite valuable, however, more highly modern data is to be applied. As well, one may compare different time periods to draw on anything conclusive. Guide assist(s) may be precursor(s) to project. ---Inflation forecasting methods Meyer, B. H. and Pasaogullari, M. (2010). Simple Ways to Forecast Inflation: What Works Best? Federal Reserve Bank of Cleveland Economic Commentary, Number 2010-17 Note: will reflect knowledge and skills form prerequisites (Mathematical Statistics and Financial Time Series). Will have comparative analysis of methods in terms of training, testing, validation and forecasting error. ---Build an inflation premium into the interest rate or required rate of return demanded for an investment based on expected inflation. Will multifactor models do that? Identify whatever means and implement regardless of answer. 17. Inflation-Indexed bonds (ILBs) A. Preliminary guides for ILBs --> Chen, J. (2019). Index-Linked Bond. Investopedia Segal, T. (2020). Hedge Your Bets with Inflation-Index Bonds. Investopedia Campbell, John Y. and Shiller, Robert J. and Viceira, Luis M., Understanding Inflation-Indexed Bond Markets (May 18, 2009). Cowles Foundation Discussion Paper No. 1696 Deacon, M., Derry, A. and Mirfendereski, D. (2004). Inflation-Indexed Securities: Bonds Swaps and Other Derivatives. Wiley B. TIPS Yield Curve Gürkaynak, Refet S., Brian Sack, and Jonathan H. Wright. 2010. The TIPS Yield Curve and Inflation Compensation. American Economic Journal: Macroeconomics, 2 (1): 70-92 Note: also consider other risk-free assets besides American C. Pricing Where would one find quotes or read incoming (real time data) for ILBs? An index-linked bond is also known as a real return bond in Canada; Treasury Inflation-Protected Securities (TIPS) in the U.S.; linker in the U.K. Directives are: -To establish the modelling of inflation protection; desire to observe explicitly how ILBs work -Strong literature Béatrice de Séverac, José Fonseca. Pricing Inflation-Linked Bonds and Hedging Bond Portfolios: A Comparative Analysis Applied to French OAT Indexed Bonds. The 14th Paris December Finance Meeting EUROFIDAI - AFFI - ESSEC, Dec 2016, Coimbra, Portugal: https://www.eurofidai.org/sites/default/files/pdf/parismeeting/2016/Severac_2016.pdf Jarrow, Robert A. and Yildirim, Yildiray. (2003). Pricing Treasury Inflation Protected Securities and Related Derivatives Using an HJM Model. Journal of Financial and Quantitative Analysis (JFQA), Vol. 38, No. 2, pp. 337-359 Paolo Falbo, Francesco M. Paris (1960–2005) & Cristian Pelizzari (2010), Pricing Inflation-Linked Bonds, Quantitative Finance, 10:3, 279-293 Deacon, M., Derry, A. and Mirfendereski, D. (2004). Inflation-Indexed Securities: Bonds Swaps and Other Derivatives. Wiley -Pricing methods relevant to market data Note: some programming/coding will be necessary to associate data. However, since students have successfully completed the stated prerequisites (below) such shouldn’t be overwhelmingly daunting. It’s great to be able to compare pricing methods with market data alongside. D. Empirical analysis Will also be interested in data analysis for different time periods with different ambiances for considerable inflation and deflation concerning yield (alongside CPIs or other measures of inflation). The following journal article to serve as complimenting data analysis activity --> Kajuth, F., & Watzka, S. (2011). Inflation Expectations from Index-Linked Bonds: Correcting for Liquidity and Inflation Risk Premia. Quarterly Review of Economics and Finance, 51(3), 225-235 18. Ratios and Market Risk (to develop) Pilotte, E., & Sterbenz, F. (2006). Sharpe and Treynor Ratios on Treasury Bonds. The Journal of Business, 79(1), 149-180. Bid-Ask spread as a measure of liquidity Harvey, J. et al. (2016). Stress Testing a Securities Portfolio with Spread Risk and Loss Recognition. Moody’s Analytics Rohan Arora, Guillaume Bédard-Pagé, Guillaume Ouellet Leblanc and Ryan Shotlander (2019). Bond Funds and Fixed-Income Market Liquidity: A Stress-Testing Approach. Bank of Canada, Technical Report No. 115 / Rapport Technique no 115 19. Hedging a Portfolio of Corporate Bonds Note: hedging concerns mitigating risks or loss, not making money; understand what you’re trying to counter; it’s not because it sounds sexy. Toulson D., Toulson S. & Ndumu A. (2000). Hedging a Portfolio of Corporate Bonds Using PCA/EGARCH Yield Curve Analysis. In: Dunis C.L. (eds) Advances in Quantitative Asset Management. Studies in Computational Finance, vol 1. Springer For this to sink in one has to be computationally active with. First, must be comprehension of the goal of applied hedging, then the analysis of development, followed by logistics for computation, then computational/data implementation. Note: also consider what assets typically counter corporate bonds downturns. 20. Callable Bonds Note: will concern ourselves with tangible and practical modelling development accompanied by computational development in CAS. Chen, J. and Scott, G. (2020). Callable Bond. Investopedia The model of callabable bonds Pricing of Callable Bonds Cayon Fallon, Edgardo and Sarmiento-Sabogal, Julio, A Methodological Approach for the Valuation of Callable Bonds in Emerging Markets: The TGI Example (2010). Cuadernos de Administración, 23(40): pages 271 - 294 Concerning variations in interest rate, is the binomial pricing model a superior tool to the Black-Scholes type model? The Salomon Brothers Approach Fernandez, F.R. (2005). Valuation of Callable Bonds: The Salomon Brothers Approach. Debon, Maxime et al. On the Pricing and Early Call of American and Bermudan Callable Bonds (March 1, 2012). 29th International Conference of the French Finance Association (AFFI) 2012 NOTE: may also need to treat Puttable Bonds Yield-To-Worst (YTW) 21. Convertible Bonds Lioudis, N. (2021). An Introduction to Convertible Bonds. Investopedia An investor must understand the possible economic/financial circumstances to cause trigger; structure of bonds must be designed to easily satisfy the initiation parameters in the future concerning advantageous stance. Previous modules can be used for bond model design preferences. Instrument structure, parameters & initiation. Relevance of shares towards conversion. NOTE: students will be given assignments sets concerning zeros, coupons, principal + coupon, stocks (for zeros, coupons and principal + coupon ) Economic circumstances that can lead to respective option initiation. Establish parameters for triggers based on bond features and consequential parameters for the triggered options. Comparative time series data between CoCo price and corporate share price with summary statistics. Developing comparative distributions, volatility analysis. Constructing payoff models and the associated geometrical representations Pricing (different methods and monte carlo) Pricing from distributions observed from market behaviour The following two guides will be applied to establish a sturdy, tangible and practical environment for such hybrid instruments: Spiegeleer, J., Schoutens, W. & Cynthia Van Hulle. (2014). Chapt 12. Pricing Contingent Debt. Pages 311 – 346. In: Pricing Contingent Convertibles: A Derivatives Approach. John Wiley & Sons Ltd. Schoutens, W., Jabre, P. and Spiegeleer, J. (2011). The Handbook of Convertible Bonds: Pricing Strategies and Risk Management. Wiley. Effective duration for convertible bonds (active with various problems) Prerequisites: Theory of Interest for Finance; Corporate Finance (check FIN); Derivatives Modelling & Pricing I, Financial Time Series Asset Management This course serves towards the pandemonium of financial markets, where for topics in the course one’s skills or talent are generally developed by personal investment in developing models and strategies. Course functions as a social ambiance with many obligations as group efforts. Students however should know the limits to exposure of their skills or talent with others, namely, sans self-exploitation in a employee environment. Towards group projects assigned professors/instructors to provide objectives, mechanisms and logistics for research or tasks. Professors/instructors to provide process guidance and review of progressing projects. Computational developments to be supported by reports with the official participants of the respective project. NOTE: review R packages from your prerequisites. People tend to heavily underestimate what they have. Caution: plan, so logistics and implementations are tangible, fluid and cost/time effective. Attendance 15% --> There is virtually no chance of you passing this without good attendance and strong participation. Exams are not walk ins upon expected problem sets. Poor or destructive behaviour can warrant an amplification of 69% forfeited from final course grade. Data & computational group project assignments 85% --> Data & computational project assignments follow conceptual and model setup by instructor. It’s likely inevitable that, financial statements, Quandl, UPENN WRDS with various datasets and the CRSP/Compustat Merged Database (CCM) will be used along with other data sources and tools. Some of the topics in course outline will be the assignments. Each numeric module warrants a heavy project. Course Outline --> 1. Foreign Exchange Features: ---Linking the Money Market to the Foreign Exchange Market ---Exchange Rate Overshooting & Volatility ---Relation between forward exchange rate & current spot exchange rate 2. Industry methods of forecasting currency exchange rates and instruments ---Levich, R. M. (1998). Chapter 6. Determination of Spot Exchange Rates. In: International Financial Markets – Prices & Policies. Irwin/McGraw-Hill ---Econometric models: Cheung, Y. et al. (2017). Exchange Rate Prediction Redux: New Models, New Data, New Currencies. ECB Working Paper 2018 Note: replicative econometric research needs to be done. Verify with applied data, then investigate for more modern data. ---Strength of economic growth Yoichi Tsuchiya, 2012. " Is the Purchasing Manager’s Index Useful for Assessing Economy’s strength? A Directional Analysis. Economics Bulletin, AcessEcon, vol. 32 (2), pages 1302 - 1311 (likely applicable towards other ambiances) Note: as well, black swans, political contagion and geopolitical perturbations are difficult to quantify. ---Does strength of economy findings (from PMI index) always correlate well with results stemming from models chosen out of Cheung et al (2017) ECB Working Paper Series? ---Fixed exchange rates and pegged exchange rates Investopedia – Floating Rate vs. Fixed Exchange Rate: What’s the Difference Richard Lee – Investopedia. Pegged Exchange Rates: The Pros & Cons Caroline Banton (Investopedia). How are International Exchange rates Sets ---Questioning the reverence for currency pegs project Apart from the trade being a common reason for currency pegs, develop empirical research towards determining whether respective policy served well or not. Particular interest towards temporary pegs, say, observation pre-peg, peg period and post peg. Apart from needing to hold large reserves of counterpart currency (observe evolution), incorporate economic statistics/data that will serve well in research, accompanied by A. Purchasing of gov't bonds versus selloffs B. Current Account Deficit/Surplus C. National Depth to GDP ratio -Hennerich, H. Debt-to-GDP Ratio: How High Is Too High? It Depends, Federal Reserve Bank of St. Louis -Caner, Mehmet; Grennes, Thomas; Koehler-Geib, Fritzi. (2010). "Finding the Tipping Point -- When Sovereign Debt Turns Bad". Policy Research working paper; no. WPS 5391. World Bank. Note: may have to extend with more modern data -How to model with intelligence gathered from (i) and (ii) D. Money Supply E. Observe whether nation that created peg is actually disciplined with holding of large reserves of counterpart currency. If not, how fast are reserves burnt and why so? Can a reserve holding threshold or quantity be determined towards the peg? F. Possible trade tensions with other countries Trade balance among countries in trade conflict Project for students --> Students (likely in groups) will be given different pegs to the US dollar and the Euro, to develop highly sensitive forecast models (2 - 3) for the case of a floating rate (which incorporates market and economic data for chosen periods) within the peg life period, to compare with fixed rate and determine the level of convergence or divergence to such fixed rate over time. Note: in the pre-peg phase real currency market data will be applied to train/test forecast model(s), but also models can be supplied evolving economic data throughout peg phase. ---Currency Exposure PART A: What commodities and other assets are highly correlated (+ and -) with currencies? Events of interest: phases in the business cycle, and shocks. Strategies. PART B: known means of determining currency exposure (develop) Hekman, C. R. (1983). Measuring Foreign Exchange Exposure: A Practical Theory and Its Application. Financial Analysts Journal, 39 Adler, M., & Dumas, B. (1984). Exposure to Currency Risk: Definition and Measurement. Financial Management, 13(2), 41-50. Lane, P., & Shambaugh, J. (2010). Financial Exchange Rates and International Currency Exposures. The American Economic Review, 100(1), 518-540. PART C: for the following journal article below will like to incorporate more modern data and treat other industries as well (for industries segmentation purposes) Khoo, A. Estimation of Foreign Currency Exposure: An Application to Mining Companies in Australia. Journal of International Money and Finance. Volume 13, Issue, June 1994, Pages 342 – 363 ---Value-at-Risk Estimation of foreign exchange risk The following guides serves well towards development of VaR : Papaioannou, M. (2006). Exchange Rate Risk Measurement and Management: Issues and Approaches for Firms. International Monetary Fund WP/06/255 Bredin, Don & Hyde, Stuart. (2002). Forex Risk: Measurement and Evaluation using Value-at-Risk. Research Technical Papers 6/RT/02, Central Bank Ireland Swami, O. S., Pandey, S. K. and Pancholy, P. (2016). Value-at-Risk Estimation of foreign Exchange Rate Risk in India. Asia-Pacific Journal of Management Research and Innovation. 12(1): 1 – 10 ---Range forwards (long and short) ---Currency Crisis Radcliffe, B. (2019). What is a Currency Crisis? Investopedia Identify models and techniques applied in the following literature. Can expect much data analysis, possible sensitivity analysis and econometric/time series tools incorporated. Past events investigation. Modern data as well. Investigations will be highly data driven in computational environment. Kaminsky, G., Lizondo, S. and Reinhart, C. M. (1997). Leading Indicators of Currency Crises. Policy Research Working Paper 1852, The World Bank Berg, A. and Pattillo, C. (1999). Predicting Currency Crises: The indicators approach and an alternative, Journal of International Money and Finance, Volume 18, Issue 4, Pages 561-586 Probit model Vlaar, P. J. G. Early Warning Systems for Currency Crises. Bank of International Settlements 3. Global Currencies ---Benchmark currencies (CHF, EUR, GBP, JPY and USD). Identifying trends in the following: Evidence of global liquidity BIS global liquidity indicators: methodology https://www.bis.org/statistics/gli/gli_methodology.pdf Government budget deficit Other Fiscal Indicators Gov’t Credit Balance of Trade Debt to (real) GDP Inflation You may also rank currencies with PCA ---Currencies of high potential as candidates or substitutes (CAN, AUS, SGD) for benchmark currencies; use the trends in the above and observe how each prospect currency stacks up with the benchmark currencies. With the same timeline apply PPP with the benchmark currencies; goods chosen must be essentials that are monetized. You may also rank candidates among the premiers in PCA. ---For different regions will make use of empirical and computational tools/skills to decide which currency can be a benchmark currency for the respective region. ---Speculate on a respective prospect currency whether the sovereign authority prefers a low value with the benchmark currencies in the interest of trade, etc., and its value with (chosen) emerging markets or developing countries. How is inflation treated? Note: case of Japan’s currency is an interesting one being a benchmark currency. ---Currency baskets Uses of currency baskets: Ganti, A. (2021). Currency Basket. Investopedia The U.S. Dollar Index (USDX), Special Drawing Rights (SDR). ---Building a currency basket Development assist: Edison, H. J. and Vardal, E. (1985). Optimal Currency Basket in a World of Generalized Floating an Application to the Nordic Countries. International Finance Discussion Papers (IFDP). No.266 Edison, H. J. and Vårdal, E. (1990). Optimal Currency Baskets for Small, Developed Economies. The Scandinavian Journal of Economics, 92(4), pages 559–571 Han, H. (2000). Choice of Currency Basket Weights and Its Implications on Trade Balance, International Review of Economics and Finance 9, 323–350 Daniels, J. P., Toumanoff, P. G., and von der Ruhr, M. (2001). Optimal Currency Basket Pegs for Developing and Emerging Economies, Journal of Economic Integration 16(1); 128-145 Jyh-Dean Hwang (2015). On the Correct Model Specification for Estimating the Structure of a Currency Basket, Applied Economics Letters, 22:10, 783-787 Projects of interest: Build a currency basket model for USDX. Does it conform to the given US Dollar Index formula? Regardless, confirm the accuracy over various years by comparing alongside historical valuation data. Except for a given formula to compare with, what was done for for the USDX will also be done for the SDR. Note: historical data SDR valuation data for contrast can be found on IMF website. Modelling and Forecasting of USDX volatility with ARIMA, GARCH and ARIMA-GARCH models. AIC, AICC, BIC, HQIC for model selection; followed by forecasting and error. Build a currency basket of the EC, CC, Latina America, Africa and Asian regions A basket of currencies may be used by monetary authorities to set the value of their currency. Compare wih actual realised policy. 4. Holding Cash. Inflation, Government Bonds and Commodities A. Two sound foundational guides (replication and extension with new data) –> Nason, R. S. and Patel, P. C. (2016). Is Cash king? Market Performance and Cash During a Recession. Journal of Business Research 69, 4242–4248 You, J., Lin, L. and Huang, J. (2020). When is Cash King? International Evidence on the Value of Cash Across the Business Cycle. Rev Quant Finan Acc 54, 1101–1131 B. In addition, with recession periods it may be sensible to compare yields from risk free assets and commodities (specifically gold) and draw conclusions. C. Inflation --> (i). Consumer Price Index (CPI) Relevance to the investor Basket model, sources for data and forecasting skills (ii) Meyer, B. H. and Pasaogullari, M. (2010). Simple Ways to Forecast Inflation: What Works Best? Federal Reserve Bank of Cleveland Economic Commentary, Number 2010-17 (iii). Research Federal Reserve Bank of St. Louis. (2019). Is Gold a Good Hedge Against Inflation? The FRED Blog Note: students are expected to have skills to independently generate their own geometrical exhibitions. Augment with modern data. Distribution fitting will also be appreciated. Bloomenthal, A. (2020). The Better Inflation Hedge: Gold or Treasuries? Investopedia Alexander P. Attié and Shaun K. Roache. (2009). Inflation Hedging for Long-Term Investors. IMF Working Paper WP/09/90 Ambiances and modern data D. Commodities in Hedging portfolios Banton, C. (2020). Commodities: The Portfolio Hedge. Investopedia What models are practical towards weight in portfolio? 5. Gov’t bonds and the economy Choe, S. and Veiga, A. (2021). EXPLAINER: Why Rising Rates are Unsettling Wall Street. AP News Duguid, K. (2021). Explainer: What Rising Bond Yields Mean for Markets. Reuters A. The given literature to be analysed B. Development of data analysis for modelling dynamic Different economic periods for different years C. What does your developed (Svennson) yield curve show? Such different economic periods for the different years D. Choose at least five other ambiances (developed and developing) for (A) through (C) E. Is the effect of rising bond rates always reflected on individual stocks? 6. Economic Indicators that help predict market trends -Unemployment -Inflation (leading and lagging) -Yield Curve YieldCurve R package Enrico Schumann. Fitting the Nelson–Siegel–Svensson model with Differential Evolution. CRAN R Janpu Hou. (2017). The Yield Curve – Example of Correlation. RPubs -Monetary policy rules with data for possible future central bank action -PMIs Investopedia - Purchasing Manager’s Index (PMI) Picardo, E. (2019). The Importance of the Purchasing Manager’s Index - Investopedia -“Beige Book” -Observation of Gov’t Budget Analysis for expenditure and cuts Sectors and Industries relevance -Economic data towards prediction of monetary rules implementation -Fiscal Indicators -Fiscal Policy -Is an increase in household debt in relation to a country's (real) GDP in at least the short to medium term a strong predictor of a weakening economy? -TED Spread (developed countries counterpart) -OECD System of Composite Leading Indicators -Global PMI Project for development: Vermeulen, P. (2012). Quantifying the Qualitative Responses of the Output Purchasing Managers Index in the US and the Euro Area. European Central Bank. Working Paper Series No 1417 February 2012. “ The survey based monthly US ISM production index and Eurozone manufacturing PMI output index provide early information on industrial output growth before the release of the official industrial production index” (Vermeulen 2012). Will try to compare the consistency between such indices and the computational methodology found in the following article with time periods of interest (and compare with) --> Joseph, A., Larrain, M. and Turner, C. Forecasting Purchasing Managers’ Index with Compressed Interest Rates and Past Values. Procedia Computer Science 6 (2011) 213–218 7. Advanced stock analysis ---Initial Public Offering (IPO) Model to implement ---Case of a new IPO (analysis of S1 documentation) ---Meaning of given shares ---Speed reading SEC filings ---Value of common stock Ahmed, S., Bu, Z., & Tsvetanov, D. (2019). Best of the Best: A Comparison of Factor Models. Journal of Financial and Quantitative Analysis, 54(4), 1713-1758 Chen, J. and Scott, G. (2020). Dividend Discount Model (DDM). Investopedia Chen, J. (2021). Multistage Dividend Discount Model, Investopedia Joseph Nguyen (Investopedia) – How to Choose the Best Stock Valuation Method Kenton, W. (2020). Abnormal Earnings Valuation Model (AEVM). Investopedia Capital Asset Pricing Model (CAPM) or Multi-Factor Models It’s imperative that students are exposed to the relevance, logistics and computational development for mentioned methods from the prior three given literature, comparing with each other and recognised market value. NOTE: there are methods for prices “today” and those to predict “future” prices. For various stocks compare market value to present valuation, future valuation with stock metrics. Are assets overvalued or undervalued? ---Market relationship between risk free bonds yields rates and stock indices Data Analysis for S&P/TSX Composite Index (with Canada gov’t bonds), S&P 500 (with treasuries), Russell 2000 (with U.K. gov’t bonds), STOXX Europe 600 (with risk free assets in Europe). ---Defensive stocks Chen, J. (2020). Defensive Stock. Investopedia With market data how can we vindicate the adjective “defensive” or “non-cyclical”? Note: defensive stocks don’t necessarily imply optimal gains. Note: a student project will be to analyse how volatile defensive stocks are against poor PMI releases, downturn yield curve and inflation. Will choose multiple successive years and monthly (or whatever) reports. ---Develop the following for various firms in regions of interest: Mohammed Issah & Samuel Antwi | David McMillan (Reviewing Editor) (2017) Role of Macroeconomic Variables on firms’ Performance: Evidence from the UK, Cogent Economics & Finance, 5:1 ---Creating a rubric chart involving the following nine a. Economic Indicators Predict Market Trends (review module 6) b. PESTEL & SWOT Analysis c. Pinkasovitch, A. (2019). Analysing Stocks with Porter’s Five Forces. Investopedia d. Investopedia (2018). The 4 Basic Elements of Stock Value e. Chosen stock valuation methods from earlier f. Stock Metrics Ratios (P/E, PEG, P/B, D/E, Price-to-Sales) EBITDA, NIAT, ATOI, NOPAT, NOPLAT, Operating Cash Flow, EVA FCF, Payout, ROE, ROA, beta benchmarking, portfolio beta g. Ratios (Liquidity, Coverage, Profitability, Efficiency): Different ratios can provide some insight on investors’ appetite for respective equity. One can observe the historical performance in such ratios h. Beneish Model, Modified Jones Model, Dechow F Score, Altman Z Model i. Off-balance sheet concerns ---Market Sector Indices: One can find or develop market capitalization weighted index for a respect sector (will identify the modelling and logistics) to compare with high-volume indices. Consider an index for each sector. Sector indices will be compared among each other and with high-volume indices. Summarizing the performance of stocks grouped by specific market sectors; allows investors to benchmark the performance of a particular stock market sector or industry. Comparing the performances of particular stock to its associated market sector (in conjunction with prior rubric analysis towards particular stock considered). 8. Asset investment risk measures (equity, debt and mixture of such two). Primary goal is to develop quantitative/computational models applicable to assets in markets and portfolios; meaningful “risk valuation”. As well, students must understand what they’re trying to measure. In general, cause of personal choices in equity and securities depends on firm (or individual). The mentioned risk measures generally have no rationale from economics, rather they are overall statistical towards performance. Methodologies for choices in equity are treated in other modules of the course. ---Securities exchange and trade commissions filings/registrations (investment types and operations) ---Special Purpose Vehicle/Entity (SPV/SPE): purpose and tactics ---Beta (measure of systematic risk) of a security or portfolio in comparison to the market as a whole. ---VaR, Expected Shortfall monte carlo (computational) and Stressed Expected Shortfall (computational). ---There are very case sensitive portfolio constitutions to consider. An elementary case could be a portfolio consisting solely of N different stocks (assuming diversification in different industries); a more general case, a portfolio consisting of unique stocks securities and stocks with different maturities. Skills in manipulation of arrays by computational tools are necessary. ---Jensen Index ---K-ratio ---Sortino Ratio ---Treynor Ratio ---Return Over Maximum Drawn Down (RoMaD) 9. Expense ratio and index fund development ---Actively Managed Funds Note: catering for different types of asset allocation Modules (6), (7) and (8) to be undercurrent. Comparative development: mean-variance, multi-factor models, PCA Market efficiency, Risks, Empirical performance and Transaction costs ---Index fund development A. Economy assessment & assessment of industries. Modules (6), (7) and (8) to be undercurrent B. Sampling from the index in accordance with its overall makeup and construction for different sectors; use some discretion as to how many you want to include in each sector class. Comparative development: mean-variance, multi-factor models, PCA seldom case of increasing or decreasing the number of stocks (or shares of stock) you hold in each sector. C. Weighted average market capitalization D. Establish your benchmark(s) E. Individual trade costs & investment capital. Create yours or not? Linear Programming may just be only one means of “basketing”, but that MUST be subjugated to all prior. A project will be developing your own index funds. In groups students will develop at least three index funds, each from a different sovereign environment. Must also demonstrate how to track and evaluate. 10. Liquidity in Investment Funds The following papers can serve as guides towards logistics and means towards developing a tangible computational toolkit for liquidity; measuring it and stress testing. Professor will orchestrate analysis and conceptual groundwork of computational structure. Students are to develop computational code toolkit and apply real market instruments. May also be applicable to ETFs. ---Measuring Liquidity Profile of Mutual Funds Hussain, A. (2022). Mutual Fund Liquidity Ratio. Investopedia Aramonte, S., Scotti, C. and Zer, I. (2019). Measuring the Liquidity Profile of Mutual Funds. Finance and Economics Discussion Series Divisions of Research & Statistics and Monetary Affairs Federal Reserve Board, Washington, D.C. US Federal Reserve Students may be given questions based on established data concerning constituents of respective fund where they must compute liquidity. Students may be asked to develop a mutual fund constituted by a broad range of securities, stocks, cash, derivatives, etc., that suffices a liquidity measure threshold, having other systematic risks in mind. ---Measuring Mutual Fund Risk Banton, C. (2020). 5 Ways to Measure Mutual Fund Risk. Investopedia PURSUE ---Performance measures for Mutual Funds Jensen, Standard Deviation, Sharpe, Sortino, Treynor Compare a fund’s performance against its benchmark index Up-Market Capture Ratio, Down-Market Capture Ratio Performance relative to risk taken Performance Attribution 11. Liquidity stress testing for Investment Funds Note: project based and not only based on bonds and fixed- income --> Arora, R. et al. Bond Funds and Fixed-Income Market Liquidity: A Stress-Testing Approach. Technical Report No. 115, Bank of Canada 2019 Bouveret, A. (2017). Liquidity Stress Tests for Investment Funds: A Practical Guide. IMF Working Paper No. 17/226 12. Fund Analysis and Building Project: The R environment will be available and recommended to be put to much use for the following projects. ---Student groups will be given "funds” with stocks, bonds (gov’t and corp) and currencies where each group is given a different make up, but same number of stocks, bonds and currencies. Student groups will investigate particular stocks, bonds and currencies. NOTE: constituents of “funds” will be assessed by tool/skills acquired from prerequisites, and (critically) prior modules. You will also compose your process in writing with spread involving mathematical palette to accompany. Determination of which constituents and recommendation of researched assets for possible replacement to constitute an aggressive portfolio, defensive portfolio, income portfolio, speculative portfolio, hybrid portfolio, respectively. ---A fund manager with 200 stocks (or bonds, notes, bills) in portfolio. To analyse these securities quantitatively a manager will require a co-relational matrix of the size 200 by 200, which makes the problem very complex. However, PCA can extract 10 Principal Components which best represent the variance in the securities best, reducing the complexity of problem while still explaining the movement of all 200 stocks (or bonds, notes, bills). Kaiser rule? ---Making use of the R Packages ESG A. Logistical scheme for economic scenario generator concerning stocks, bonds (gov’t and corp), currencies, commodities and derivatives. B. Apply the package to the considered assets and derivatives ---More Portfolio Rebalancing Will be given various (high volatility) assets types in a portfolio (stocks, meme stocks, bonds, notes, bills, currencies) at given past date leading to a future date, to apply methods 13. Market (in)efficiency & elementary derivatives Generally concerns stocks, currencies and commodities as assets of consideration. Derivatives are neither means of stock analysis as in past modules, however, such modules can influence one’s mindset for transactions with long term options derivatives. ---Concept of arbitrage and no-arbitrage ---Conditions for surplus/deficit or market correction: The following subjects are not well treated which lead to market participants in false positions or comforts. Treat the following notions in the most logical/constructive sequential manner --> Margin Debt Marginal Call Liquidation Level Federal Call Liquidation Margin Will have active market case studies to comprehend how they are situated and resolutions to accompany. Vasquez, J. and Pakiam, R. Gold Prices Plunge by Most Intraday since June 2013, Bloomberg Bloomberg, Gold Joins the Virus Sell-Off With Biggest Slide Since 2013 ---Making sense of Hedge Funds in the Commodities Market For a hedge fund with ventures in commodities what are the “common strategies” applied concerning speculation or hedging, or even towards taxes reduction? An example: Wallace. J. (2020). Hedge funds that Cashed in When Oil Prices Cratered. The Wall Street Journal. Then, consider the following article: Scanlan, D. (2020). How One Hedge Fund Made Money Amid Singapore Hub Meltdown. Bloomberg. Does the finance or economics add up with such articles? What particular economic circumstance or scenario would make stock piles high in demand towards a profit? What are the unique principles in this latter strategy compared to “common strategies”? ---O’hara, N. (2020). How to use Index futures. Investopedia ---Applications of minimum variance hedge ---European Options ---Relating shares to options strategies ---European currency options (structure, & basic strategies) ---Range forwards contracts with options (long and short) ---Pricing/Valuation of European stock options and currency options 14. Elementary volatility measures for options (primarily for stock as the asset): ---Historical volatility ---Indices of future volatility that provide a measure of market risk and investors' sentiments. ---An essential role of implied volatility: bull & bear markets. However, for options on stock, currencies and commodities each unique asset has unique volatility to consider. Particular past modules for stock analysis and currencies analysis must be well understood for strategy and planning with assets; company A does not necessarily equate to company B with market. ---Comparison between Implied and Historical volatility for the determination of overvalued and undervalued options; such comparison conclusion is never a substitute for stock analysis. 15. Measuring the market’s risk A. Wanting to know the daily VaR and CVaR of the market at a 99.9% confidence level (S&P 500, Russell 200, TSX Composite, STOXX Europe 600). B. Measuring the market’s risk expectations for an extreme event, often called a “tail event” or a “black swan,” which is a drop of at least three standard deviations. For integrity and professionalism, one must understand some level of modelling (distributions, fat tails, etc.) in a setting with implied volatility. Means to calculate the cost of protecting against such a drop, providing important insight into investors’ expectations. It’s features: (i) Using instantaneous implied volatility to calculate standard deviation of returns (will be actually done). (ii) Responding to current market conditions rather than relying on historical data. (iii) Extending to a portfolio of stocks. Pursue w.r.t. implied volatility Note: if there’s analogy for commodities then so be it. Will also like prior developed measure to be compared to the following journal article concerning past extreme events. Do they complement each other well? Samer, A. A. (2010). Stock Return Dynamics Around U.S. Stock Market Crises & Inverted Smiles. Journal of New Business Ideas & Trends. Volume 8, Issue 2 16. Attitudes of market participants Your individual culture may seem to be that of a “bozo” when it comes to financial markets. One must definitively identify practical stimuli for market behaviour. A. Some articles for analysis: Imbert, F. and Huang, E. (2020). Stocks Rise to Start the Week as Amazon and Apple lead Tech Higher, Gold Hits Record. CNBC Why is gold rising when stocks are soaring? Krugman, P. Stocks are Soaring. So is Misery. The New York Times Is the market behaviour of S&P 500, Russell 2000, Dow Jones and Nasdaq parallel to other ambiances (STOXX, TSX, etc.)? What are the drivers (Pied Piper) of such stock behaviour? Reasoning. B. Articles and development in (A) will be applied as the setting for the following: The degree to which funds are flowing in and out of various fixed income mutual funds and ETFs can also help gauge sentiment, particularly towards means of caution. 17. Market Efficiency (ME) & Asset Price Bubbles (APB) PART A (ME) Godfrey, K. R. L. (2017). Towards a Model-Free Measure of Market Efficiency Pacific – Basin Finance Journal, volume 44, pages 97 – 112 Tran, Vu. & Leirvik, T. (2019). A Simple but Powerful Measure of Market Efficiency. Finance Research Letters, Elsevier, 29(C), pages 141 – 151 PART B (APB) Note: when dealing with stocks will not focus only on the S&P 500 but also other indices such as the Russell 2000. Other developed countries as well, and also STOXX Europe 600 Phillips, P. C. B. and Shi, S. (2020). Chapter 2. Real-Time monitoring of asset Markets: Bubbles and Crises. Pages 61 – 80. In: Vinod, H. D. and Rao, C. R. Handbook of Statistics volume 42. Financial, Macro and Micro Econometrics Using R. North Holland. Cowles foundation Discussion Paper No.2152 version: https://cowles.yale.edu/sites/default/files/files/pub/d21/d2152.pdf It’s important that one becomes actively acquainted with R package psymonitor with various data of different times. Analyse and replicate. There’s also possibility of investigation with new data. Then can proceed with other ambiances of interest. R vignettes: Phillips, P. C. B., Shi, S. and Caspi, I. (2018). Real-Time Monitoring of Bubbles: The S&P 500. CRAN R < https://cran.r-project.org/web/packages/psymonitor/vignettes/illustrationSNP.html > Phillips, P. C. B. (2018). Real-Time Monitoring of Crisis: The European Sovereign Sector. CRAN R < https://cran.r-project.org/web/packages/psymonitor/vignettes/illustrationBONDS.html How well does it stack up against methods out of the following? Gurkaynak, R. S. (2005). Econometric Tests of Asset Price Bubbles: Taking Stock. Federal Reserve Board Robert Jarrow (2016). Testing for Asset Price Bubbles: Three New Approaches, Quantitative Finance Letters, 4:1, 4-9 Prerequisites: Macroeconomics I; International Financial Statement Analysis I & II; Corporate Finance; Investment & Portfolios in Corporate Finance

FOR ACTIVITIES IN THE “SUMMER” AND WINTER” SESSIONS ALL PARTICIPATING STUDENTS, ASSISTING/ADVISING INSTRUCTORS AND PROFESSORS MUST BE OFFICIALLY RECOGNISED; REQUIRES BOTH CIVILIAN ID AND STUDENT/FACULTY ID FOR CONFIRMATION OF INDIVIDUAL. THERE WILL ALSO BE USE OF IDENTIFICATIONS FOR ACTIVITIES FOR RESPECTIVE SESSION. SECURITY AND NON-PARTICIPATING ADMINISTRATION WILL ONLY IDENTIFY RESPECTIVE ACTIVITY BY IDENTIFICATION CODE. SECURITY AND NON-PARTICIPATING ADMINISTRATION MUST NEVER KNOW WHAT ACTIVITIES IDENTIFICATION CODES IDENTIFY: < Alpha, Alpha, Alpha, Alpha > - < # # # # # > - < session > - < yyyy > Such computational finance activities will also warrant criminal background check (CBC) in order to participate. Severely threshold may vary depending on administration. Administrators will provide dated letters of confirmation of thorough CBC to student affairs and other appropriate administration. Such also may include screening that’s parallel to customs & immigration processing where certain levels of criminal history warrants rejection. Email and physical letters with data. Such CBC protocol will not explicitly identify any particular titles or descriptions of any activity, rather, will only convey code as above. Activities repeated can be added to transcripts upon successful completion. Repeated activities later on can be given a designation such as Advance “Name” I, Advance “Name” II. As well, particular repeated activities serve to towards developing true comprehension, competency and professionalism. It may be the case some activities can be grouped and given a major title together; however, detailed descriptions will be required. QUANTITATIVE SWOT PART A Review of framework and logistics for SWOT (PESTLE --> SWOT) PART B Implementation PART C Chang, H. and Huang, W. (2006). Application of a Quantification SWOT Analytical Method. Mathematical and Computer Modelling 43, pages 158–169 Note: no professional has time to sit down and do matrices manually like rowdy pigs in a pen. Note: Excel, Mathematica and R will be available FUNDAMENTAL ANALYSIS & TECHNICAL ANALYSIS NOTE: all students participating in activity must sign a dated compliance form declaring that “festivity” makes no use of real capital, real financial assets and real derivatives in transactions towards real existing profit. Use of tools for real profit by students is independent of the “festivity”, and students take full responsibility for their own actions. Note: one needs at least a background in Corporate Finance and Probability & Statistics to participate. A. Basic Data Gathering Acquiring financial statements (balance sheet, income, cash flow). In the Mathematica environment acquiring financial data for market assets: intraday, closing price, comprehension of dynamics. B. Comprehensive Fundamental Analysis for Stocks Will be assigned at least 15-20 stocks. Creating “dashboard fill-ins for firms in columns” based on the following features is good preparation: Speed reading SEC filings Financial statements (GAAP vs. non-GAAP) Coverage ratios, liquidity ratios, profitability ratios, efficiency ratios Include historical performance Beneish, Dechow, Modified Jones, Altman Economic data (leading) and forecasts Current Account Benchmarks Gov’t Budget Analysis, Fiscal Policy, Fiscal Indicators, Fed Policy PESTEL, SWOT Stock Valuation (present and future) Stock Metrics P/E, PEG, P/B, D/E, Price-to-Sales FCF, Payout, ROE, Beta Beta coefficients and market risk ratios/measures Notions of shares and share acquisition value; bids and asks, say what you can afford B. Mathematica Development Financial Tools Wolfram Documentation Centre – Financial and Economic Data Wolfram Documentation Centre – Financial Indicators Wolfram Documentation Centre – Financial Visualization Note: students should research the available functions and range of possible parameters before diving head first Note: it takes heavy interest and much immersion to become credible with financial tools. C. Technical Analysis for stocks Basics of Technical Analysis – Investopedia (subsections 1 through 12). Some clear ideas of trading strategies-- Introduction to Technical Analysis Price Patterns - Investopedia How to Build a Trading Indicator - Investopedia 7 Technical Indicators to Build a Trading Toolkit - Investopedia D. Direct Tools at disposal (mostly independent of financial institutions): Investopedia Stock Simulator CME Group simulators Ninja Trader Thinkorswim TD Ameritrade London Stock Exchange Virtual Portfolio London Stock Exchange Trading Simulator TMX Capital Markets Learning Centre < https://www.tmx-edu.com > FACTSim Virtual Stock Exchange The fundamental analysis versus Technical Analysis development. E. Blotters Haynes, A. (2022). Blotter. Investopedia F. Transaction thresholds (appropriate order) Marginal Call, Margin Debt, Liquidation Level, Liquidation Margin, Federal Call ANALYSIS OF CURRENCIES MARKETS NOTE: all students participating in activity must sign a dated compliance form declaring that “festivity” makes no use of real capital, real financial assets and real derivatives in transactions towards real existing profit. Use of tools for real profit by students is independent of the “festivity”, and students take full responsibility for their own actions. Note: one needs at least a background in Corporate Finance and Probability & Statistics to participate. A. Currency forecasting methods Note: serves best for speculation and long-term investments Tools and Analysis to Implement --> Economic indicators (leading) Analysis of PMIs Econometrics and times series Current Account Benchmarks Fiscal Policies, Budget Analysis, Fiscal Indicators PESTEL and SWOT Conditions for monetary policy to anticipate Fed policy & effect on markets Use of currency baskets Currency crisis prediction/forecasting Berg, A. and Pattillo, (1998). Are Currency Crises Predictable? A Test. IMF WP/98/154 Berg, A., & Pattillo, C.A. (1999). Predicting currency crises:: The indicators approach and an alternative. Journal of International Money and Finance, 18, 561-586. Peltonen, T. A. (2006). Are Emerging Market Currency Crises Predictable? A Test. ECB Working Paper Series NO. 571 Inoue, A., & Rossi, B. (2008). Monitoring and Forecasting Currency Crises. Journal of Money, Credit and Banking, 40(2/3), 523–534. Xu, L., Kinkyo, T., & Hamori, S. (2018). Predicting Currency Crises: A Novel Approach Combining Random Forests and Wavelet Transform. Journal of Risk and Financial Management, 11(4), 86. MDPI AG. Keep in mind that perturbations such as demand-supply instability (in both the money markets and trade), trade conflicts, geopolitical conflicts, pestilence and epidemics/pandemics can take their toll. B. Basic Data Gathering In the Mathematica environment acquiring financial data for market assets: intraday, closing price, or specified time intervals. Mathematica Development Financial Tools Wolfram Documentation Centre – Financial and Economic Data Wolfram Documentation Centre – Financial Indicators Wolfram Documentation Centre – Financial Visualization Note: students should research the available functions and range of possible parameters before diving head first C. Foreign Exchange Literature Note: for students I don’t expect day trading to be a realistic norm due to obligations, liabilities and aspirations in life. Nevertheless, the tools and logistics will be treated. Mitchell, C. Forex (FX). Investopedia Chen, J. and Scott, G. Foreign Exchange (Forex). Investopedia Chen, J. and Scott, G. Forex Trading: A Beginner’s Guide. Investopedia Lee, R. The Top 8 Most Tradable Currencies. Investopedia Author, S. Top 6 Most Tradable Currency Pairs. Investopedia Segal, T. and Perez, Y. (2021). What is the Best Method of Analysis for Forex Trading? Investopedia Anthony, G. Three Strategies to Mitigate Currency Risk. Investopedia Take advantage of numerous icon subjects on left side of website Note: students are not restricted to currencies of developed countries. Often countries that serve as high output in manufacturing and customer services have currencies highly immersed in markets. --Simulation Tools at disposal: Investopedia Stock Simulator CME Group simulators Ninja Trader London Stock Exchange Virtual Portfolio London Stock Exchange Trading Simulator TMX Capital Markets Learning Centre < https://www.tmx-edu.com > FACTSim Virtual Stock Exchange D. Blotters Haynes, A. (2022). Blotter. Investopedia DERIVATIVES TRADING ACTIVITY “SUMMER” AND “WINTER” SESSIONS (or whenever capable) FORMALITY --> -Assumption that at least the Introduction to Derivatives for Financial Engineering course was successfully completed. -The prior two activities need to be competently accomplished with competent practice to markets. -With all markets trading tools to have record keeping (logs and accounting). At the end of the activity a student is to develop a unified financial report (including accounting statement) with their analysis and “logic confession” of financial actions implemented. May require printout of activities for designated period intervals. NOTE: all students participating in activity must sign a dated compliance form declaring that “festivity” makes no use of real capital, real financial assets and real derivatives in transactions towards real existing profit. Use of tools for real profit by students is independent of the “festivity”, and students take full responsibility for their own actions. Note: minimum requirement to participate is an introductory course in options and futures. NOTE: not all assets, derivatives and funds types will be treated at the same time. There will be designated periods for chosen (may be one at a time or some grouped to particular time periods). Particular projects of interest being stationary: --Will analyse the logistics for market participation with stocks, derivatives products, daily trading and investment with services provided by market firms and financial institutions. Technical terminologies and entities will be identified with their rolls. --Examples of simulation tools at disposal: Investopedia Stock Simulator CME Group simulators Ninja Trader Thinkorswim TD Ameritrade London Stock Exchange Virtual Portfolio London Stock Exchange Trading Simulator TMX Capital Markets Learning Centre < https://www.tmx-edu.com > FACTSim Virtual Stock Exchange --Blotters Haynes, A. (2022). Blotter. Investopedia Note: Mathematica and R to accompany. Towards immersion, simulation, retention and competency with real trading tools there will be designated time outside of any computational finance course; activity has no influence on any course in derivatives, computational finance or portfolio management. Tools primarily concern trading comprehension and experience with stocks, currencies, forwards, options (European, American, etc). Students should take advantage of knowledge and skills acquired in any course in derivatives, computational finance and portfolio management, to constructively implement such knowledge and skills beyond plain mathematical snot finesse; preparation with such knowledge and skills towards trading times is crucial to be competent and successful. Before actual independent (group) immersion there will be debriefing for assets and derivatives with sources towards developing strategies. There will also be demonstration(s) of tool(s) to be applied with walk-through(s). Students must take advantage of any time available to practice. Note: trading tools may or may not provide (temporary) transactions logs. Students must sign a term of agreement form for such. Students must keep a log journal for the assessment of commodities based on fundamental analysis and technical analysis with the corresponding actions applied. Hopefully the simulators provide long term actions log record to validate students’ log statements. COMPONENTS OF ACTIVITY --> ---Based on knowledge and skills form prerequisite activities and the Introduction to Derivatives for Financial Engineering course (bring knowledge, notes, files, etc.), will begin making use of trading simulators concerning stocks and currencies. ---Futures (mainly towards currencies and commodities here) --> Pre-market trading, insight and index arbitrage: O’Hara, N. (2020). How to Use Index Futures. Investopedia Overall pre-marketing views are suppressed due to supply, demand, fundamental analysis, acting agents, economic data and political perturbation. ---Investopedia - Minimum Variance Hedge Ratio (stocks and commodities) To be used as an important factor in determining the optimal number of futures contracts to purchase to hedge a position. Will also have applications with regression. Will be applied to commodities and equity. Students will track futures derivatives in the market associated to various asset classes. Will be hedges against assets and other futures. Students will provide analysis based on results of respective strategy (includes possible loss or not) and associated market behaviour. ---Review options (European, American, etc., etc.) Call puts and positions (long and short) Mathematica and R will be used to assist with modelling, computations, and comparing students’ parameters determination or forecasts with parameters given in trading markets; modelling and computational work must be shown for credibility. ---Remember the options market Positions of options in the market “At-the-money” “In-the-money” “Out-the-money” Such terms are often thrown carelessly about without really comprehending the relevance to their portfolio or the economics. Will review the relevance of volatility term structure and volatility smiles in addition to making sense of such 3 positions. Students will be assigned various types of options and must determine their position based on analysis of market data. Can one orchestrate means to have the volatility term structure and volatility smiles reflect real data and real time data? Does the observation of the volatility term structure and volatility smiles have considerable affect on transactions with options? If so, is it just a trend effect or the conventional flow of things? Can one develop options strategies solely based on the volatility term structure and volatility smiles? ---Options strategies Bull (long and short) Bear (long and short) Straddle Strangle Spread (bull, bear, butterfly) Risk reversal Note: valuation of currency options. Long range forward contracts are applicable in activity concerning currencies. ---Options Trading (for stocks and currencies) --> Students will track currencies, stocks (and commodities) in the market based on knowledge and skills from prerequisite activities or from experience from relevant courses. They will provide analysis towards respective strategy; concerns taking advantage of predicted behaviour of assets, or hedging strategies. Incorporated will be options strategies, hedges and portfolio management. For the case of trading European options the expiration dates will be quite short towards acquiring meaningfulness with trading. Students must keep chronological logs for options strategies or hedges with capital diversified (pricing, shares, dividends and what not), including reasoning for related views of assets in question. For each action student must comprehend and record the amount of capital applied (in shares, pricing, etc.). Accounting for investments and outcomes chronologically is essential. Note: in general, one doesn’t have to “buy” or “sell” asset to apply derivatives, rather, the asset (stock, commodity, currency or bond) will drive the derivative. Use of options will not be only for hedging. Hedging only serves to counter possible risk, else, otherwise applied you’re loosing money for no sensible reason. ASSISTING LITERATURE AND RECANTS (may serve well throughout) --> A. Investopedia – Hedge B. Some advance options risk measures 1. A strong guide to build practice on: Summa, J. (2020). Option Greeks: 4 Factors for Measuring Risks – Investopedia Such article provides a strong base to develop practicality with the Greeks. Can provide a good foundation with real market data. Build many cases. C. For assets, volatility is generally not constant, so why use delta and gamma hedging? D. How does one realistically hedge against volatility with vega? E. Model for the Minimum Variance Delta Apart from the S&P 500 in the journal article below, to apply model to other indices data and observe model variation based on data applied compared to the S&P 500. Model’s evolution will also be observed among different indices with updating data. Will apply high volume markets to observe meaningful dynamics. Examples besides S&P 500; Russell 3000, NASDAQ Composite, S&P/TSX Composite, FTSE 100, DAX Performance, etc. Hull, J., and White, A., Optimal Delta Hedging for Portfolios, Journal of Banking and Finance 82 (2017) 180-190 http://www-2.rotman.utoronto.ca/~hull/downloadablepublications/Optimal%20Delta%20Hedging.pdf Will pay attention to the unique presence of the Black-Scholes delta (as it is normally calculated), the Black-Scholes vega (partial derivative with respect to implied volatility), and the change in expected value of the implied volatility with to asset movement. Is using vega a means to make money? What is it used for? HARD COMMODITIES TRADING (needs amending) Note: activity will make use of computational tools alongside simulators without use of real capital assets. One choice of market simulator alongside Mathematica or Rstudio is FACTSim. Use of real capital assets if ever occurring during activity is of the students own doing ad not of the bridge programme. Students must sign a term of agreement form for such. Students must keep a log journal for the assessment of commodities based on fundamental analysis and technical analysis with the corresponding actions applied. Hopefully the simulators provide long term transactions record to validate students’ log statements. Activity is open to students in mathematics and business. Will make use of financial markets data sources concerning commodities, commodities derivatives. Will also make use of FACTSim (or possibly other simulator tool). Literature assists: 1. Lioudis, N. K. Commodities Trading: An Overview. Investopedia 2. CME Group. Fundamental Analysis – Futures Supply & Demand 3. Stocks-to-Use ratio 4. Investopedia – Using index futures to predict the future 5. Bajpai, P. (2021). Commodities Investing: Top Technical Indicators - Investopedia For the technical indicators mentioned the concern is their use with identifying properties that make trading as profitable as possible. The will be hands-on activities with technical indicators through use of Mathematica and RStudio. 6. Before actual independent (group) immersion there will be debriefing for the markets of concern with sources towards developing strategies. There will also be demonstration(s) the of tool(s) to be applied with walk-through(s). Students must take advantage of any time available to practice. One goal is to have an investigative view of performance between proper use of fundamental analysis and technical analysis. There will be multiple trials with different types of commodities; hopefully market behaviour is reasonably dynamic to have definitive data. STOCK SELECTION MODELS A. For assets being 50 or more in stocks, such can be troublesome to review with quality. Steps for index fund development that are quite common --> ---Choices of industries based on economic outlook, economic indicators, monetary policy and fiscal policy ---Index fund development A. Investopedia Pinkasovitch, A. and Catalano, T. J. (2021). How to Pick a Stock: Basic Best Practices for New Investors Taylor, B. (2020). Investment strategies to Learn Before Trading B. Fiscal Indicators and relevance to economy. Fiscal Analysis C. Leading economic indicators Establish your benchmark(s) D. Stock metrics and financial ratios (coverage, liquidity, profitability, efficiency); trend in latter for each ratio considered E. Risks and proper diversification. F. Sampling from the index in accordance with its overall makeup and construction for different sectors; use some discretion as to how many you want to include in each sector class. Seldom case of increasing or decreasing the number of stocks (or shares of stock) you hold in each sector. G. Weighted average market capitalization H. Individual trade costs & investment capital. Create your own or not? Integer Programming may just be only one means of “basketing”, but that MUST be subjugated to all prior. B. However, again, 50 or more stocks in a fund can prove difficult. The following articles provide computational structure for stocks selection --> --Schadler, F. P. and Eakins, S. G. (2001). A Stock Selection Model Using MorningStar’s Style Box. Financial Services Review, volume 10, Issues 1 – 4, pages 129 – 144 --Yu, H., Chen, R. and Zhang, g. A SVM Stock Selection Model within PCA, Procedia Computer Science 31 (2004) 406 – 412 --Guerard Jr, J. B., Markowitz, H. and Xu, G. (2015). Earnings Forecasting in Global Stock Selection Model and Efficient Portfolio Construction and Management. International Journal of Forecasting, volume 31, Issue 2, , pages 550 – 560 --Cowell F. (2002) Optimized Stock Selection Models. In: Practical Quantitative Investment Management with Derivatives. Finance and Capital Markets Series. Quantitative Stock Selection. Palgrave Macmillan, London --Harvey, C. R. Quantitative Stock Selection. Global Asset Allocation & Stock Selection < https://faculty.fuqua.duke.edu/~charvey/Teaching/IntesaBci_2001/stockselection.pdf > C. For such articles a major goal will be confirming how compatible or harmonic each article structure is with part (A). Nevertheless, research would be incomplete if they are not tested, say, whether in tune with part (A) or not. As well, are such methods applicable to currencies and bonds. If not, determine what amendments must be applied? NOTE: a gauge in performance can be constructing an aggressive portfolio and a “excessively defensive” portfolio, both measurable/comparable to your fund. ECONOMIC SCENARIO GENERATOR Activity concerns identifying the purpose of an economic scenario generator and developing fluid and tangible logistics towards accomplishing goals. Literature guides --> Wilkie, A.D. (1986) A stochastic investment model for actuarial use. Transactions of the Faculty of Actuaries, 39, 341–403. Wilkie, A.D. (1995) More on a Stochastic Asset Model for Actuarial Use. British Actuarial Journal, 1(5), 777–964 Huber, P. (1997) A Review of Wilkie’s Stochastic Asset Model. British Actuarial Journal, 3(1), 181–210. Bégin, J.-F. (2019) Economic Scenario Generator and Parameter uncertainty: A Bayesian approach. ASTIN Bulletin, 49(2), 335–372. Pedersen. H. et al (2016). Economic Scenario Generators: A Practical Guide. Society of Actuaries: https://www.soa.org/Files/Research/Projects/research-2016-economic-scenario-generators.pdf Conning, “A User’s Guide to Economic Scenario Generation in Property/Casualty Insurance.” Casualty Actuarial Society, CAS Research Papers, 14 Oct. 2020 PART A Concerns assets and financial instruments tied to markets. Will develop multiple portfolios, each constituted by stocks, corporate bonds, gov’t bonds (domestic and foreign), and currencies based on mean-variance, factor models and PCA, respectively, in the R environment. Each portfolio may have 25 - 50 elements to be realistic. PART B From the given literature there will be analysis followed by logistics for R implementation. Identifying what types of R tools, R programming and R packages will be needed for its development. When apply appply or R skills. Circumstances may be a single issue, or most often the coupling of multiple issues PART C Will then make use of the ESG R package ansd compare to (B). A “pivoting” task will be determining our ability range (part B) and with ESG R package compared to Conning’s GEMS® Economic Scenario Generator proprietary software and the given literature guides. Side-side-by-side development would be nice but will not want to exhaust our “change purses”. NOTE: development in Mathematica for self-development is also possible. REAL-TIME MONITORING OF ASSETS MARKETS: BUBBLES & CRISES PART A --> To have strong engagement in this activity one must have solid skills in computational mathematical statistics. I will not tolerate students without strong computational mathematical statistics backgrounds. This is not a screw-job festivity at any time. The given articles or texts describe means to develop real-time monitoring of bubbles. It’s crucial that one comprehends what they’re really doing. Phillips, P. C. B. and Shi, S. (2020). Chapter 2. Real-Time monitoring of asset Markets: Bubbles and Crises. Pages 61 – 80. In: Vinod, H. D. and Rao, C. R. Handbook of Statistics volume 42. Financial, Macro and Micro Econometrics Using R. North Holland. Cowles foundation Discussion Paper No.2152 version: https://cowles.yale.edu/sites/default/files/files/pub/d21/d2152.pdf Supporting papers: --Phillips, P. C. B., Shi, S. and Yu, J. (2015). Testing for Multiple Bubbles: Historical Episodes of Exuberance and Collapse in the S&P500. International Economic Review, volume 56, number 4. http://korora.econ.yale.edu/phillips/pubs/art/p1498.pdf --Phillips, P. C. B., Shi, S. and Yu, J. (2015). Testing for Multiple Bubbles: Limit Theory of Real-Time Detectors. International Economic Review. Volume 56, Issue 4. Pages 1079 – 1134 https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID2327633_code331494.pdf?abstractid=2327633&mirid=1 --Phillips, P. C. B. and Shi, S. (2017). Detecting Financial Collapse and Ballooning Sovereign Risk. Oxford Bulletin of Economics and Statistics. Volume 81, Issue 6 Cowles foundation Discussion Paper No.3010 version: < https://cowles.yale.edu/sites/default/files/files/pub/d30/d3010.pdf PART B --> Overall, computational development was devoted to the R environment by the authors, with the R package psymonitor. Will investigate how such given package applies to the literature in part A. Then will also apply our comprehension and skills to best of ability towards development in Mathematica; a means to acquire a “wholesome” idea of the R package. The operational or computational rundown of the R package is described by the following two vignettes: i. Phillips, P. C. B., Shi, S. and Caspi, I. (2018). Real-Time Monitoring of Bubbles: The S&P500. CRAN R https://cran.r-project.org/web/packages/psymonitor/vignettes/illustrationSNP.html ii. Phillips, P. C. B. (2018). Real-Time Monitoring of Crisis: The European Sovereign Sector. CRAN R. https://cran.r-project.org/web/packages/psymonitor/vignettes/illustrationBONDS.html PART C In both R and Mathematica will investigate different assets in various countries for different time periods. PART D Analyse and replicate the following: Samer, A. A. (2010). Stock Return Dynamics Around U.S. Stock Market Crises & Inverted Smiles. Journal of New Business Ideas & Trends. Volume 8, Issue 2 Will then compare our findings to what was developed in part C for such assets in various countries for different time periods. PART E How well does it stack up against methods out of the following? Robert Jarrow (2016) Testing for asset price bubbles: three new approaches, Quantitative Finance Letters, 4:1, 4-9 Note: develop and compare with Phillips, P. C. B. and Shi, S. (2020) for various past events? LIQUIDITY IN THE FOREIGN EXCHANGE MARKET Develop the given journal. Make currency pairs out of the following set (US, EUD, CAD, CHF, JPY, AUS, NZD). After successful completion, pursue data modern time periods following. One can also pursue currency pairs with your ambiance currency. Mancini, L., Ranaldo, A., and Wrampelmeyer, J. (2013). Liquidity in the Foreign Exchange Market: Measurement, Commonality, and Risk Premiums. The Journal of Finance, 68(5), 1805-1841. THE LIQUIDITY OF CORPORATE AND GOVERNMENT BONDS: DRIVERS AND SENSITIVITY TO DIFFERENT MARKET CONDITIONS Clara Galliani, Giovanni Petrella, and Andrea Resti (2014). The Liquidity of Corporate and Government Bonds: Drivers and Sensitivity to Different Market Conditions. JRC Technical Reports, European Commission Joint Research Centre Institute for the Protection and Security of the Citizen http://publications.europa.eu/resource/cellar/3f1e38ea-746f-4e70-b50a-6e9590cfa781.0001.01/DOC_1 Will like to analyse this literature and confirm its findings by replication. Then, to incorporate modern data. Then, will pursue ambiances of interest. Two issues to be resolved: -Data sources for government bonds data and corporate bonds data given may not be economic, hence must find alternative sources. -Quantile regression is not as mainstream as OLS regression, but there are considerable advantages for particular circumstances.

Some remaining course description for Engineering ELECTRICAL ENGINEERING PARTICULARS --> Optoelectronics This course introduces students to a broad range of modern optoelectronic applications and devices. It starts with a review of physical and geometrical optics, followed by an introduction into fiber optics, lasers and LEDs, photodetectors, and photovoltaic devices. Core course for students who choose to specialize in electrical engineering, elective for others. Offered annually. Typical Text: S.O. Kasap (2013), Optoelectronics & Photonics: Principles & Practices -Light propagation in homogeneous media. Frequency Dispersion -Group velocity and Poynting’s vector -Snell’s law, reflection, transmission, total internal reflection, antireflection coatings -Interference, resonators, diffraction -Phenomena of absorption. Spatial and temporal coherence. -Optical fibers, light coupling to optical fibers -Dispersion in single-mode fibers. Bit error rate, dispersion, optical and electric bandwidth. -Attenuation in optical fibers. Fabrication methods. -Basic semiconductor physics, p-n junction -Interaction of light with semiconductor materials in a p-n junction configuration. The distinction between direct and indirect compound semiconductors materials is noted. -Electroluminescence, and stimulated emission. -Light emitting diodes -Gas and semiconductor lasers -Photodetectors -Image sensors, solar cells -Light polarization, anisotropic materials -Pockels cell, acousto-optics, Mach-Zehnder interferometer -Liquid crystal displays Labs --> Labs to feature Cover Page Abstract Introduction: It includes the following information Experimental procedure Experimental data and plots Results Discussion Conclusion References Figure Captions (experimental setups, circuits, curves, etc.) OPTICAL EMITTER LABS: Light-emitting diodes: Red, green and blue (I-V, I-P) Light-emitting diodes: Red, green and blue (Spectrum) Laser diodes: Red, green and blue (I-V, I-P) Laser diodes: Red, green and blue (Spectrum) OPTICAL ABSORBER LABS: Photoconductor - Optoelectronic effect for light detection Photodiode: PIN photodetector Photodiode: Solar cell (photovoltaic effect for power generation) APPLICATION LABS: -LED digital display and Liquid crystal digital display -Optical transmitter receiver: Optical output by free space transmission of optical signal -Optical transmitter receiver: Audio output by free space transmission of optical signal -Quadrant photodiode Prerequisites: Calculus III, General Physics II, Modern Physics Power System Analysis I This course will introduce analysis and operation of power systems. The topics covered in this course include per unit systems, circuit and fault analysis, load flow analysis and advanced topics such as voltage stability, economic dispatch, and state estimation. Specifically, vector/matrix handling skills will be dealt with in a logistical (economic) manner so students can carry out circuit analysis for power grid. Further, computing techniques on solving nonlinear algebraic equations and optimization problems will be integrated into this course. The course will lay a solid foundation for students with power grid analysis knowledge and skills and help their future career in power utilities industry. Students will be trained to use programming/computing tools such as SystemModeler to conduct large-grid computing and analysis. Tools --> Mathematica + SystemModeler A SPICE simulator PSAT: Power System Analysis Toolbox + GNU/Octave MATPOWER + GNU/Octave NASA NPSS Electrical Power Systems Analysis Toolbox Tutorial sessions--> 1. Mathematica/SystemModeler programming using vectors and matrices; How to make plots 2. Mathematica/SystemModeler Programming on iteration loops and load flow computing Labs --> For designated common systems of economic supply, to analyse and design power systems. Development of models and tools for investigating system behaviour, and design processes. Optimal generation dispatch will be developed. Grading --> Homework Labs 3 Exams 1. Circuit analysis basics: a. Phasors for ac signals (what if there are harmonics?) b. KCL, KVL, Ybus matrix and Z matrix c. Power computation: Instantaneous power, active power and reactive power in single phase ac systems and three-phase ac systems 2. Per unit systems a. How to “get rid of” transformers so that a power grid looks like a circuit with voltage sources and passive components such as R, L, C 3. Power system protection and fault analysis a. Z matrix-based three-phase fault analysis b. Other fault analysis based on symmetric components 4. Transmission line modeling and steady-state operation – the basic power and voltage phasor relationship. 5. Load flow analysis a. Problem formulation b. Nonlinear algebraic equations solving techniques (Gaussian, Newton-Raphson) c. Scope of the methods or when the NR method does not work well 6. Advanced topics (optional) a. Voltage stability or Maximum loading b. Economic Dispatch c. State Estimation & Maximum Likelihood Estimation Prerequisites: Circuit Analysis II, Signals & Systems, Power Electronics Power System Analysis II Necessary advance treatment towards competency and professionalism Prerequisites: Power System Analysis I Electromagnetic Waves & Antennas Antennas, wave propagation, wireless communication systems, electromagnetic radiation. The student learns the fundamental solutions of time-varying Maxwell's equations, and applies them to design antennas. The student understands radio wave propagation phenomena in modern communication systems, and fundamentals of electromagnetic radiation with application to antenna theory and design. -Use of electromagnetics, physics, and mathematics to understand fundamentals of antennas. Contribution of Course to Meeting the Professional Component Mathematics: 40%, Physics: 40% , Software tools: 20% Computer Usage: Computer language programme (Mathematica, Matlab, C++, Fortran, etc.) to be used to verify some concepts derived in class and in homework problems. Will also reacquaint ourselves with software tools used in electromagnetics I & II. Typical Text: TBA References: http://eceweb1.rutgers.edu/~orfanidi/ewa/ Field and Wave Electromagnetics, by Cheng, Addison Wesley Antenna Theory: Analysis and Design, third edition, by Balanis, Wiley Topics --> --Electromagnetic spectrum, Maxwell's equations, constitutive relations, Poynting’s theorem, time-harmonic fields (3 hrs) --Plane wave solution, dispersion relation, polarization, waves in materials, boundary conditions, reflection and transmission at media interfaces, Fresnel coefficients, Brewster's angle, total internal reflection (12 hrs) --Solution to radiation problems, antenna parameters, wire antennas, aperture theory, horns and reflector antennas, phased arrays, traveling-wave antennas, broadband antennas, log-periodic antennas, Yagi-Uda antennas, loop antennas, helical antennas, microstrip antennas (20 hrs) --Friis transmission formula, receiving properties of antennas, impact of antenna performance in communication links, Friis transmission formula, basic radar principles, numerical techniques for wave propagation and antenna design (5 hrs) Prerequisite: Electromagnetics II Antenna Theory General theory of conduction current antennas; linear antennas including dipoles and monopoles; antenna equivalent impedance; design of AM, FM, TV and shortwave broadcast antennas of one or more elements including ground and mutual impedance effects; matching techniques including lumped, shunt, and series elements, transmission lines and conjugate matching; receiving antennas; antennas used for mobile communication systems and their radiation characteristics; antenna arrays and their design; wave propagation including propagation via ionosphere or troposphere; loop antennas and Yagi-Uda arrays; antenna synthesis for specified radiation patterns. UHF and microwave antennas including corner reflector antennas, helical antennas, theory of aperture antennas including rectangular and circular apertures; broadband log-periodic antennas; microstrip antennas and phased arrays including applications for wireless communication systems; slot antennas, turnstile, horn and parabolic radiators; considerations for radar antennas and communication links. Antenna ranges and measurement techniques. Teaching and Learning Methods --> Class meeting time will used for deriving core concepts (in real time on the board), working through problems, and exploring interactive demonstrations developed in Mathematica. Students are encouraged to bring laptop computers to class to interact with the downloadable demonstrations while in class. The majority of learning will occur as students work out the assigned problem sets, out of class, and a few student chosen problems, in class. Students are encouraged to work together on these. Because significant time will be spent working out problems in class, students will be expected to read and understand some material without the benefit of lecture. Assignments --> There will be about six or seven problem sets. You may work together on these, but every student is responsible for being able to explain their submitted work. Please consider the importance of aesthetics and clarity when submitting your work. Typeset solutions will be greatly appreciated. Also, work the problems analytically to a reasonable conclusion before plugging in the numbers. Computational systems, such as Mathematica (or whatever) are recommended for numerical, or symbolic, evaluation. (Calculators are not really useful for reliable evaluation and debugging of complex evaluations.) Exams --> There will be two exams, a midterm exam and a final exam. These exams will take place in class, and will be “open book” - any printed resource may be used. In this course, students will obtain: 1. Understanding of antenna fundamentals 2. Ability to design, and analyse the performance of, common antenna types. Typical Texts: Antenna Theory and Design (3rd Edition), by Warren L Stutzman and Gary A. Thiele. References: Antenna Theory and Design, second edition, Stutzman and Thiele, Wiley Antennas for All applications, third edition, Kraus and Marhefka, McGraw-Hill, Assessment --> Assigned problem sets 35% In Class problems 15% Midterm exam 20% Final exam 30% Tentative Schedule --> Introduction Chapter 1 2 lectures Antenna Fundamentals Chapter 2 5 lectures Simple Radiating Systems Chapter 3 3 lectures System Applications for Antennas Chapter 4 3 lectures Line Sources Chapter 5 3 lectures Wire Antennas Chapter 6 4 lectures Broadband Antennas Chapter 7 3 lectures Array Antennas Chapter 8 3 lectures Aperture Antennas Chapter 9 3 lectures Prerequisite: Electromagnetics II RF & Microwave Circuits for Wireless Communications I This course is an introduction to RF and microwave circuit design and analysis techniques, with particular emphasis on applications for modern wireless communication and sensing systems. An integrated laboratory experience provides hands-on exposure to specialized high-frequency measurement techniques. Students will develop an enhanced understanding of circuit design and analysis principles as applied to modern RF & microwave circuits, as well as gain familiarity with design techniques for both hand analysis and computer-aided design. A design project will be designed, built, and tested using the computer-aided techniques and instrumentation in the lab. Typical Text: David M. Pozar, Microwave Engineering, John Wiley & Sons Supplementary reading: Guillermo Gonzalez, Microwave Transistor Amplifiers, Prentice-Hall Additional Necessities: WHITE PAPERS/TECHNICAL PAPERS SPICE Tools --> Skills and competence from prerequisites Skills with one out of the following Cadence Keysight Ansys ADS Grading: Homework 20% Mid-term exam 25% Laboratory (includes design project) 25% Final exam 30 % Course Outline --> --Review of electromagnetics; Maxwell's equations, plane wave solutions, transmission lines. Introduction to ADS or ANSYS microwave CAD software or whatever --Types of transmission lines and their properties; coaxial lines, rectangular waveguides, microstrip. --Network analysis; scattering matrix, transmission matrix formulations. Flow graphs, Mason's rule. --Matching networks: lumped element designs and limitations, single and double-stub tuned designs. Quarter-wavelength transformers, multisection matching transformers. --Active microwave circuit design, characteristics of microwave diodes and transistors. Linear and nonlinear behaviour and models. --Amplifier design; gain and stability, design for noise figure. --Noise in microwave circuits; dynamic range and noise sources, equivalent noise temperature, system noise figure considerations. Homework --> Homework will be assigned and collected (approximately) weekly Examinations--> There will be 1 in-class midterm examination, and cumulative final exam Laboratory and Design Project: (approx. 11 laboratory sessions) --> 1. High frequency performance of circuit components 2. Measurement basics; reflectometry, spectrum analysis 3. Scalar network analyser measurements 4. Vector network analyser operation and error correction 5. Scattering parameter measurements of active devices 6. Matching network design, fabrication, and characterization 7. Project design, characterization, and analysis 8. Nonlinear and noise characterization of active circuits Prerequisites: Antenna Theory RF & Microwave Circuits for Wireless Communications II This course builds upon the knowledge gained from prerequisites. Here there is a greater emphasis on designs involving active components. Linear and power amplifiers and oscillators are considered, as well as stability, gain, and their associated design circles. The course uses computer-aided design techniques and students fabricate and test circuits of their own design. Aims--> Learn about active devices and use them to design amplifiers, and oscillators which will be fabricated and tested during the two lab weeks. Objectives --> --Understand Active Devices and be able to design amplifiers, and oscillators. --Appreciate the design trade-offs for power, noise figure, gain, match, and stability. --Understand the importance of DC biasing amplifiers and its affect on RF matching and performance. --Acquire a basic understanding of how active circuits are used in systems. Tools --> Skills and competence from prerequisites Skills with one out of the following Cadence Keysight Ansys ADS Additional Necessities: TECHNICAL PAPERS & WHITE PAPERS SPICE Lectures are followed by homeworks to reinforce the material. Students will design amplifiers and a voltage controlled oscillator circuit which will be fabricated and tested during the two lab weeks; fabrication will done by a firm to ship back (hopefully in time). Assessment --> Chosen Advance Lab recitals related to prerequisite 25% Homework and Labs 35% Best of Midterm or Final 40% Note: advance lab recitals related to prerequisite will be administered during appropriate times in this course. Syllabus --> Active Devices, FETs, Gain, etc. Active Devices, Matching and Models General Purpose Amplifier Low Noise Amplifier Power Amp (Cripps) ADS Non Linear--Simulate PWA Oscillators Lab 1 - Low Noise and Power Amp Meas (independent of advance lab recitals) Broadband Amplifier Techniques (Feedback) Lab 2 – Oscillators (independent of advance lab recitals) Antennas, Systems MidTerm Amplifier Operation (Class A/AB/C/F?) Final Prerequisites: RF & Microwave Circuits for Wireless Communications I Analogue & Digital Communications Systems Analogue modulation methods including AM, DSBSC-AM, SSB, and QAM; effects of noise in analog modulation systems. Digital communication methods for the infinite bandwidth additive white Gaussian noise channel: PAM, QAM, PSK, FSK modulation; optimum receivers using the MAP principle; phase- locked loops; error probabilities. Digital communication over bandlimited channels: intersymbol interference and Nyquist's criterion, adaptive equalizers, symbol clock and carrier recovery systems, trellis coding. Spread spectrum systems: direct sequence modulation and frequency hopping. Typical Text: Modern Digital and Analog Communication Systems, 4th edition, by B. P. Lathi and Zhi Ding, published by Oxford University Press Reference: Samuel O. Agbo and Matthew O. Sadiku, Principles of Modern Communication Systems, Cambridge University Press, Cambridge Communication Systems by Simon Haykin, 5th Edition, published by John Wiley and Sons, 2009, ISBN 0-471-17869-1 In the first part, we begin with an overview of communication systems. A quick review Fourier Transforms will be given followed by a review of stationary and ergodic random processes. Power spectral density and complex-envelope representation of signals will be covered. Analog communication techniques including amplitude modulation (AM) and frequency modulation (FM) will be covered. The effect of noise of the performance of analog communication systems will be reviewed. In the second part, the transition from analog to digital communication systems will be discussed first. The sampling theorem and the effect of quantization will be discussed. Digital communications for both bandwidth-limited and power-limited AWGN channels will be discussed. Modulation techniques such as BPSK, QPSK, MPSK, MQAM , MSK and GMSK will be covered. In the third part, we cover the performance of communication systems in the presence of ISI. ZF, DFE and adaptive equalization techniques will be discussed. Spread Spectrum communication systems will be introduced and Multiple Access techniques (FDMA, TDMA and CDMA) will be described that allow multiple users to share communications resources. The performance of communication systems over fading channels will be covered. Time permitting, multiple-input multiple output (MIMO) communication systems will be introduced. The fourth part of the course will consider the information theoretic bounds for source coding and channel capacity. Huffman and Lempel-Ziv source coding will be covered. Error-control coding for power-limited channels will be covered with examples of commonly used block and convolutional codes. Grading --> Homework Labs 3 Exams Homework --> Homework will give students much opportunity to reason, develop and practice analytical modelling, and practice there plotting, coding and simulation skills. To build on labs and lectures. Exams --> Exams will be open notes, but you must have: -The ability to distinguish between rubbish (includes code) and what’s meaningful. -Identify facts and misconceptions -Identifying right models & representations, and deducing requirements. Tentative Schedule --> Introduction, Overview, Communications System Elements, Service Requirements. Review of Random Processes, Fourier Transform, Signals and Systems and Hilbert Transform. Continuous Wave (Analog) Modulation, AM and FM Modulation and Demodulation, Noise and Impairments, Examples of Voice and TV Transmission. Nyquist Sampling Theorem, Information Sources, Pulse Code Modulation (PCM), Delta Modulation, Quantizing Noise, Digitization of Video and MPEG. Baseband Pulse Modulation, Digital Transmission over the AWGN Channel, Modulation for Power or Bandwidth-Limited Channels, Matched Filters, Likelihood Receivers, PAM for Bandwidth Limited Channels. Passband Digital Transmission via Carrier Modulation, BPSK, QPSK, MSK, GMSK, QAM, Power Density Spectra and Probability of Bit Error, Nyquist Filtering, Demodulator Implementation, Sources of Impairment and Bit Error Rate (BER). The 8-VSB digital TV transmission format. Mid-Term Exam Performance of Communication systems in presence of ISI. ZF, DFE and adaptive equalization. Multi-User Communications, Multiple Access Techniques, FDMA, TDMA, CDMA, Spread Spectrum Communications, Dynamic Spectrum Access, Communication over fading channels. Satellite Communications Applications, System Elements, Performance Predictions, Link Budget Examples. Fundamental Limits in Information Theory, Source Coding, Information Capacity, Data Compression. Error Control Coding for Power Limited Channels, Linear Block Codes, Cyclic Codes, Convolutional Coding/Viterbi Decoding. Final Exam Lab Areas (list not necessarily in appropriate order) --> Each area often concerns various methods. However, our concern is for those that are highly applicable to “modern” communication systems and gives quality. NOTE: labs build on lectures. BEWARE: hardware usage is not limited to Spectrum Analyzer and/or Oscilloscope and ICs. Will also make use of SPICE simulators. Various advance circuits, plots and simulation programming are involved as minimum expectation, say, there will be much more than that. In all cases your intelligence and skills from Signals & Systems prerequisite (including coding) will be vital to success. -Introduction to Signal -to-Noise ratio -Using the Spectrum Analyzer and/or Oscilloscope -Amplitude Modulation -FM Modulation -Phase Lock Loops -Multiplexing -Manchester Coding -Pulse Code Modulation and coding -Phase Shift Keying -BPSK and QPSK Modulation -Spread Spectrum Prerequisite: Signals & Systems, Probability & Statistics B Modern Digital Communications (incomplete) Review of modulation and coding. Trellis coded modulation. Digital signaling over fading multipath channels. Spread spectrum signals for digital communications. Multiple access systems, time division multiple access, code-division multiple access, frequency-division multiple access. OFDM communications systems. Typical Text: Digital Communications, by John G. Proakis and Salehi, McGraw-Hill References: Biglieri, E. et al. Introduction to Trellis-Coded Modulation with Applications. Macmillan Publishing Company Communication System Engineering by John Proakis and M. Salehi, Prentice Hall Error-Correction Coding for Digital Communications by G. C. Clark, Jr. and J. B. Cain. Plenum Press, 1981. Error Control Coding: Fundamentals and Applications by S. Lin and D. J. Costello. Prentice-Hall, 1983. Digital Communications. B. Sklar, Prentice-Hall, Course Outline --> Review of Modulation and Coding Theory i. Review of the main components of a Digital Communication System ii. Review of Block Codes - Convolutional codes iii. Lattices Trellis Coded Modulation (TCM) i. Introduction and Fundamentals ii. Trellis Representation iii. Set Partitioning iv. Examples of TCM schemes v. Decoding TCM vi. Performance Evaluation in AWGN channel vii. Upper Bound to Error Probability viii. Lower Bound to Error Probability ix. Examples x. Computation of dfree Digital Signaling over Fading Multipath Channels i. Characterization of Fading Multipath Channels ii. The Effect of Signal Characteristics on the Choice of a Channel Model iii. Diversity Techniques for Fading Multipath Channels iv. Digital Signaling over a Frequency-Selective, Slowly Fading Channel v. Binary and M-ary Signaling over a Frequency-Nonselective, Slowly Fading Channel vi. Coded Waveforms for Fading Channel vii. Probability of Error. Hard and Soft Decision viii. Performance of Convolutional Codes ix. Constant Weight and Concatenated Codes x. Analysis and Performance of TCM for Fading Channels Spread Spectrum Signals for Digital Communications i. Model of a Spread Spectrum Communications System ii. Direct Sequence Spread spectrum Signals iii. Rake Receivers iv. Multi-user Detection v. Frequency Hopped Spread Spectrum Signals vi. Other types of Spread Spectrum Signals vii. Spread Spectrum in multipath channels Multiuser Communications i. Multiple Access Techniques (CDMA, TDMA, FDMA, SDMA, PDMA) ii. Capacity of Multiple Access Systems. Multichannel and Multicarrier System i. Multichannel Digital Communications in AWGN ii. Multicarrier Communications OFDM i. Introduction ii. Transmitter and Receiver Structure iii. Performance Analysis Lab Projects --> Labs will be somewhat similar to what was encountered in the prerequisite course, however, it will cater to the topics in this course with emphasis on the MODERN-DIGITAL adjective, and suiting to scale, technology and abundance usage. Homework --> Homework will give students much opportunity to reason, develop and practice analytical modelling, and practice there plotting, coding and simulation skills. To build on lectures and labs. Exams --> There will be 3 exams will be open notes, but you must have -The ability to distinguish between rubbish (includes code) and what’s meaningful, -Identify facts and misconceptions -Identifying right models & representations, and deducing requirements. Assessment --> Homework 15%. Lab Projects 25% 3 Exams 60 % The following articles may prove useful for lectures, homework & labs --> -Beltran, J. R. and de Leon, J. P. Estimation of the instantaneous amplitude and the instantaneous frequency of audio signals using complex wavelets. Signal Processing 90 (2010) 3093–3109 -Petrović, P., Damljanović, N. New Procedure for Harmonics Estimation Based on Hilbert Transformation. Electr Eng 99, 313–323 (2017) -K. Kucuk, "Design and implementation of a real-time ERP-OFDM SDR receiver on the USRP2 platform," 2016 Sixth International Conference on Digital Information and Communication Technology and its Applications (DICTAP), Konya, 2016, pp. 24-29. -M. J. Leferman, A. M. Wyglinski. “Taming Software-Defined Radio: A Graphical User Interface for Digital Communication System Prototyping.” DSP-FPGA.com – The Journal of Embedded Signal Processing, January 2010. -H. Arslan. “A Wireless Communication Systems Laboratory Course.” Proceedings of the 2nd International Conference on Engineering Education & Training, April 9-11, 2007, Kuwait. -C. B. Dietrich et al. “Implementation and Evaluation of Laboratory/Tutorial Exercises for Software Defined Radio Education.” Proceedings of the 2010 ASEE Southeast Section Conference, 2010. -H. Arslan. “Teaching SDR through a laboratory-based course with modern measurement and test instruments.” Proceedings of the SDR Forum Technical Conference, November 2007. -S. Bilen. “Implementing a Hands-on Course in Software-defined Radio,” Proceedings of the 2006 ASEE Annual Conference, June 2006. -S. Katz. “Using Software Defined Radio (SDR) to Demonstrate Concepts in Communications and Signal Processing Courses”, Proceedings of the 2009 ASEE Annual Conference, June 2009. -Szelest, M., Uzdrzychowski, W., & Grzechca, D. (2012). GNU radio and USRP2 as a universal platform for verification of wireless communication devices used in automotive applications. Proceedings of the 19th International Conference Mixed Design of Integrated Circuits and Systems - MIXDES 2012, 436-440. Prerequisite: Analogue & Digital Communication Systems Optical Communications & Photonics A comprehensive description of the technology of fiber optical communication system. A balanced discussion between component operation and system design consideration. Performance parameters and fabrication problems, lasers, LED modulation and detector responses. Link budget analysis. Advantages of fiber optics, recent developments and applications.Typical Text: Gerd Keiser, Optical Fiber Communications, third edition, McGraw Hill, 2000 References: Fiber Optics : principles and practices, by Abdul Al-Azzawi, CRC press Fiber Optic Communications, Joseph Palais, Prentice Hall Software Tools --> Mathematica, Optiwave (OptiSystem, OptiBPM & OptiFiber and software instruction manuals), Lumerical Interconnect After completing this course the students should be able to: -Understand fiber optic concept to information transmission. -Identify the elements of an optical fiber transmission link. -Understand optical fiber structure, wave guiding, and fabrication -Understand, compute and simulate the modes in slab waveguide, step index fiber and graded index fiber. -Calculate and simulate the attenuation and signal degradation due to intermodal and intramodal distortion. -Understand the structure, the performance and the signal analysis of optical sources. -Understand the structure, the performance and signal analysis of optical detectors. -Calculate power coupling losses due to connectors, splices, source output pattern and fiber numerical aperture. -Design optimum single mode and multimode fiber link. -Design and analyze optical receivers. Topic Outline --> The evolution of fiber optic systems Optical fiber modes and configurations Mode Theory and waveguide equations Single-Mode and graded-index fiber structure Signal degradation in optical fibers Optical Sources Photo detectors Optical Receiver Performance and Operation Optical Measurements Prerequisite: Analogue & Digital Communications; Modern Digital Communications; Electromagnetics II Co-requisite: Optical Communications & Photonics Lab Optical Communications & Photonics Lab This lab course accompanying its co-requisite covers fiber optic communication design, measurements and simulations. This includes numerical aperture, fiber attenuation, power distribution in single mode fibers, mode distribution in multimode fibers, fiber coupling efficiency and Connectors/ splices losses. Also, design, construction and simulation of WDM communication system components are covered. Individual and group projects are assigned to students in the Lab. Typical Text: Optical Fiber Communications by John Senior, Prentice Hall References: Fiber Optic Communications, by Joseph Palais, fifth edition, Prentice Hall, 2004 Fiber Optics: Principles and Practices, by Abdul Al-Azzawi, CRC press Software Tools --> Mathematica, Optiwave (OptiSystem, OptiBPM & OptiFiber and software instruction manuals), Lumerical Interconnect After completing this course the students should be able to: 1. Align light waves into small optical components with high precision 2. Use modern hardware/software design tools to develop modern communication systems 3. Calculate and simulate the attenuation and signal degradation due to intermodal and intramodal distortion. 4. Calculate power coupling losses due to connectors, splices, source output pattern and fiber numerical aperture 5. Understand, compute and simulate the modes in step index fiber and graded index fiber. 6. Design, implement and test WDM communication system using its basic components 7. Participate in team projects including design, inspection and optimization 8. Understand the reliability issues of the highly delicate optical devices Topic Outline --> Introduction to fiber optics Measurements Introduction to OptiSystem, OptiBPM, and OptiFiber Fiber Numerical Aperture Measurements Fiber Attenuation and Dispersion Measurement Single Mode Fiber Characteristic Mode Distribution in Multimode Fiber (includes higher order modes) Fiber Coupling Efficiency to Optical Components Connectors/Splices Construction and Loss measurements Analogue and Digital Construction of MUX and DEMUX for WDM systems Design of Fiber Optic WDM link Prerequisite: Analogue & Digital Communications; Modern Digital Communications; Electromagnetics II Co-requisite: Optical Communications & Photonics Image & Video Processing Broad and technical treatment of the fundamentals in image and Video processing. General Pursuits --> 1. Understand the fundamentals of image and video signal processing and associated techniques. 2. Understand how to solve practical problems with some basic image and video signal processing techniques. 3. Have the ability to design and implement simple systems for realizing some multimedia applications with some basic image and video signal processing techniques. References: Y. Wang, J. Osterman, Y.-Q. Zhang, Video Processing and Communications, Prentice Hall M. Ghanbari, Video Coding - an introduction to standard codecs, IEE Telecommunications Series A. M. Tekalp, Digital Video Processing, Prentice–Hall Gomes J. and Velho L. (2015). From Fourier Analysis to Wavelets. IMPA Monographs, vol 3. Springer, Cham D. Dudgeon and R. Mersereau, Multidimensional Digital Signal Processing, Prentice-Hall R. Gonzalez and R. Woods, Digital Image Processing, 2nd Ed., Prentice-Hall R. C. Gonzalez and R.E. Woods, Digital Image Processing, 2nd ed., Prentice Hall, Ken C. Pohlmann, Principles of Digital Audio, 4th ed., McGraw-Hill. Technology Tools: CVIP tools (Open Source) video processing software Mathematica Image Processing & Analysis Video Processing C programming (OpenCV, CUDA) GPUImage There will be numerical comparative development among various mentioned tools. Programming --> Despite the given requirement course in C in declarations of prerequisites. Much much more will be expected of you based on academic seasoning with obligations in programming, and being that this course only concerns the Networks concentration in C++. Will show no mercy to those weak or limited to a second term course in C++. Assignments --> Assignments will be constituted by Testing knowledge and skills from prerequisites Standard problems Media evaluation and suggested techniques Mathematical/Statistical basis of strategies and techniques Coding and programming assignments building on lectures and labs Labs --> Labs will require a minimum of 3 hours per session, but will not exceed 4. The term “lab” will not be an understatement. Some activities in lab will go beyond lectures concerning techniques, algorithms and programming. When treating videos will like interactive activities for the following: VHS DVD Videoconferencing Videophone Live social media Exams --> Exams will call you out with prerequisites, lectures, assignments and labs Assessment --> Lab 30% Assignments 20% Exam 1 15% Exam 2 15% Final 20% Lecture Topic Outline --> WEEK 1 Image Formation and Representation: 3D to 2D projection, photometric image formation, trichromatic colour representation, video format (SD, HD, UHD, HDR). Contrast enhancement (concept of histogram, nonlinear mapping, histogram equalization) WEEK 2 Review of 1D Fourier transform and convolution. Concept of spatial frequency. Continuous and Discrete Space 2D Fourier transform. 2D convolution and its interpretation in frequency domain. Implementation of 2D convolution. Separable filters. Frequency response. Linear filtering (2D convolution) for noise removal, image sharpening, and edge detection. Gaussian filters, DOG and LOG filters as image gradient operators WEEK 3 Image sampling and resizing. Design of interpolation filters. Multiresolution representation: Pyramid and wavelets. WEEK 4 Sparsity and dictionary-based image processing: Image representation using orthonormal transform/dictionary. Sparsity assumption. General formulation of image enhancement as an optimization problem, L0 vs. L1 vs. L2 prior, Basic optimization techniques. Applications in deblurring, denoising, inpainting, compressive sensing, superresolution, dictionary learning (PCA and KSVD). WEEK 5 Feature detection (SIFT), feature descriptors and matching, and feature based global mapping estimation (Robust least squares and RANSAC). WEEK 6 Geometric transformation. Image warping. Image morphing. Panoramic view stitching. Video stabilization. WEEK 8 Image segmentation: region growing, split and merge, Otsu’s method, K-means, GMM clustering. WEEK 9 Dense motion/displacement estimation: optical flow equation, optical flow estimation; block matching, multi-resolution estimation. Deformable registration (medical applications) WEEK 10 Moving object detection (background/foreground separation) (Gaussian mixture model, RPCA). Simultaneous estimation of camera motion and moving objects. Object tracking. Video shot segmentation. WEEK 11 Stereo and Multiview video: depth from disparity, disparity estimation, view synthesis. Depth camera (Kinect). 360 video camera and view stitching. Light field imaging. WEEK 12 Fundamentals of source coding: characterization of random sources by entropy, binary encoding, scalar quantization, vector quantization. WEEK 13 Transform coding: Image representation using unitary transforms (orthogonal bases), Transform coding, JPEG image compression standard, Image representation using wavelet transform; concept of layered coding, JPEG2000 image compression standard WEEK 14 Video coding: block-based motion compensated prediction and interpolation, adaptive spatial prediction, block-based hybrid video coding, rate-distortion optimized mode selection, rate control, Group of pictures (GoP) structure, trade-off between coding efficiency, delay, and complexity. Overview of video coding standards (AVC/H.264, HEVC/H.265); Layered video coding: general concept and H.264/SVC. Multiview video compression. Error resilience issues. Adaptive Video Streaming (DASH). WEEK 15 Wrapping up unsettled topics with video processing WEEK 16 Final (may be 2 days required) Prerequisites: Signal & Systems, Practical Programming in C for Engineering I & II, Image & Audio Processing, Mathematical Statistics Wireless Networks Wireless networks have an increasingly important role in the world of communications. This course provides an introduction to various current and next generation wireless networking technologies, and undertakes a detailed exploration of fundamental architectural and design principles used at all layers. Related protocols and their performance are studied using formal analytical tools and realistic simulations. A course that focuses on higher layer protocol design and analysis for wireless networks. Course provides students a detailed introduction to the design and analysis of protocols for power control, medium access, routing, and congestion control that form the fundamental basis for a wide range of wireless data networks, from cellular networks, to mobile ad-hoc network, to sensor networks. The specific objectives of the course are to help the students: 1. Understand the architecture and applications of current and next generation wireless networks: Cellular, WLANs, sensor networks, mobile ad-hoc networks and intermittently connected mobile networks. 2. Get a basic introduction to the key concepts and techniques underlying modern physical layer wireless and mobile communications: radio propagation modelling; performance of digital modulation schemes and coding techniques in fading environments; CDMA and OFDM; diversity and MIMO. (These topics are all explored in much greater detail in EE 535, the goal here is to provide a sufficient survey of this topics so that the higher layer protocols are well grounded and motivated.) 3. Learn how to design and analyse various medium access and resource allocation techniques such as power control for fixed-rate and rate-adaptive systems, Aloha and CSMA based randomized medium access, scheduling for TDMA/FDMA/CDMA-based wireless networks. 4. Learn how to design and analyse network layer routing protocols, along with key component mechanisms, such as link metric estimation and neighbourhood table management for proactive and reactive routing protocols, opportunistic routing, backpressure routing, network coding, cooperative routing, routing with mobility and intermittent contacts. 5. Learn to design and analyse transport layer protocols, with an emphasis on congestion control, including TCP over wireless, congestion sharing mechanisms, explicit and precise rate control, utility optimization-based approaches, and backpressure-based utility optimization. 6. Learn how to evaluate MAC and network protocols using network simulation software tools such as NS-2 or Qualnet. Typical Text: Wireless Communications, Andrea Goldsmith, Cambridge University Press Additional Materials: Some of the course material will be drawn from research papers (IEEE and so forth), industry white papers and Internet RFCs. Grading --> 1. Assignments, 20% of the grade, will consist of prerequisites refreshers and current level tasks: Modern Digital Communications Similar to programming labs and projects encountered Includes analytical tasks Incudes strong SPICE, Mathematica and C use Computer Networks for Engineers Similar to programming labs and projects encountered Includes analytical tasks Incudes strong C use There will be 5 course level assignments. 20% of the grade. 2. Projects: there will also be 3 simulation projects. Together count for 15% of the grade. These projects are to be worked on and submitted by pairs of students working together. 3. Midterm Exam: this exam will count for 20% of the grade. 4. Final Exam: this exam will count for 25% of the grade. 5. Research Project will count for 20% of the grade Research Project--> The course project is intended for students to carry out small research projects in teams of two or three. It has four components: -A proposal: which describes your problem, why it is important, your plan for tackling the problem, and how you are going to evaluate the solution. It should be no more than 3 pages. (Due: on given date) -A progress report: which explains your approach, related/prior work, any preliminary results you might have obtained. (Due: on given date) -A final report: conference-style paper describing the project and its key contributions/findings. (Due: on given date) -A presentation: conference-style presentation during the penultimate week of classes. (Due of given date) Topic Outline --> WEEK 1 Introduction to wireless network architectures: cellular networks, wireless local area networks, multi-hop networks WEEK 2 Radio propagation models, Narrowband digital modulation and Coding under wireless fading environments. Assignment 1 on network architecture and phy-layer. WEEK 3 Basics of CDMA and OFDM, Diversity and MIMO, Equalization. Project 1 assigned: Simulation of coding and modulation on a single link. WEEK 4 Power allocation for rate-adaptive parallel channels (Waterfilling); power control for fixed-rate independent channels (Centralized linear solution; Foschini-Miljanic distributed algorithm) WEEK 5 Randomized medium access 1: Unslotted and Slotted Aloha. System throughput analysis and two-user saturation rate region analysis WEEK 6 Randomized medium access 2: CSMA. System throughput analysis and two-user rate region analysis for p-persistent CSMA. Bianchi’s Markov chain analysis of throughput for the IEEE 802.11 CSMA protocol. Other window adaptation mechanisms. Assignment 2 on power allocation/control and randomized medium access. WEEK 7 Graph colouring and its application to channel allocation in (TDMA/FDMA/CDMA-based) wireless networks under the protocol model. Mid-term Exam WEEK 8 Integer Linear Programming formulation of channel allocation for both protocol and SINR interference models. Extensions to other objective functions such as non-homogeneous channel preferences, throughput maximization and fairness. Introduction to wireless network simulator (NS-2/QualNet). Project 2 assigned (simulation of IEEE 802.11 MAC). Assignment 3 on Graph Colouring and ILP WEEK 9 Introduction to multi-hop wireless network routing. The AODV and OLSR protocols for mobile ad-hoc networks. Link estimation and neighbour management. WEEK 10 Geographic routing: greedy routing and different solutions for avoiding routing holes. Routing in intermittently connected mobile networks. WEEK 11 Theory and Practice of Dynamic Backpressure Routing. Theory: Lyapunov drift minimization yielding the centralized maximum weight independent set matching solution. Practice: the BCP protocol for sensor networks. Assignment 4 on Wireless Routing. WEEK 12 Opportunistic routing and Cooperative Routing: ExOR, Flash flooding, Barrage relay. Project 3 assigned (Simulation of MANET routing protocol). WEEK 13 TCP over wireless networks. Congestion sharing (IFRC, WCAP). Centralized and distributed explicit and precise rate control (RCRT, WRCP). WEEK 14 Optimization-based rate control with Lagrange duality and with queue backpressure. Assignment 5 on Wireless Congestion Control. WEEK 15 Wrap up and course review. Discussion of emerging industry standards such as 4G Cellular or 5G cellular, IEEE 802.11p, and/or guest talk by visitor from industry/academia working on wireless networks. WEEK 16 Research Project Presentations EXAM WEEK Prerequisites: Signal & Systems; Probability & Statistics B; Analog & Digital Communications Systems; Modern Digital Communications; Computer Networks for Engineers Electrification of Transportation I This course presents fundamentals in hybrid electric, hybrid hydraulic and electric vehicle engineering with specific applications to commercial vehicles and so forth. The course focuses on mechatronic system and component design of HEV based on the requirements to power flow management, power conversion and thus to vehicle dynamics and energy/fuel efficiency. Mechanical drivetrain engineering problems are considered in conjunction with electric drive design and then mechatronic wheel-electric drive, suspension and locomotion System design are presented. The course discusses design of batteries and energy storages and vehicle power electronics and also introduces plug-in hybrid electric vehicles. Additionally, to regular lectures, the course provides (i) hands-on experience in testing vehicles on the 4x4 vehicle (or other) chassis dynamometer with individual wheel control, (ii) laboratory works (iii) computer workshops on simulating vehicles and wheel-electric drive control and (iv) practical knowledge in testing and controlling dynamics of electric unmanned ground vehicles. Concerning the technical activities of course, any less you really don’t want to learn or don’t want to have a solid introduction in EV and HEV. Texts: TBA Assessment: Homework Quizzes Labs Major Group Projects LAB Tools --> CAD Mathematica SystemModeler Modelica/Modelica Libraries SPICE Motors and motor control Mechanical drive components and wheels Sensors and various DAQs Microcontrollers (possibly) Battery Supply and battery mangement systems Power Electronics Multimeters and Oscilloscopes Frame construction tools NOTE: having some level of detailed realistic observation of hybrids or electric vehicles can often prove difficult. However, some government agencies can provide some transparency with such. An example: T. A. Burress et al. (2011). Evaluation of the 2010 Toyota Prius Hybrid Synergy Drive System. Oak Ridge National Laboratory. Managed by UT-Battelle, LLC for the U.S. Department of Energy, Under Contract DE-AC05-00OR22725. ORNL/TM-2010/253 --> https://info.ornl.gov/sites/publications/files/Pub26762.pdf NEVERTHELESS: will try to acquire discarded “first generation” EV and HEV in shop for physiology and systems investigation. Homework --> Concerns standard problems and reinforcing knowledge and skills from prerequisites Labs --> NOTE: certain labs will be compliment by hands-on development in with physical components. Includes experimental means of analysing characteristics, properties, and behaviours in function. Labs (not necessarily in given order): “Camp fire story”: Swart, G. (2016). Learning Systems Engineering Lessons from an Electric Vehicle Development. Incose International Symposium, Volume 26, Issue 1, pages 2055 – 2069 Vehicle dynamics and simulation Mechanical drive components modelling and simulation (includes incorporation of flywheel eventually) Powerflow and management (includes incorporation of flywheel eventually) O. Hegazy, R. Barrero, J. Van Mierlo, P. Lataire, N. Omar and T. Coosemans, "An Advanced Power Electronics Interface for Electric Vehicles Applications," in IEEE Transactions on Power Electronics, vol. 28, no. 12, pp. 5508-5521, Dec. 2013 Article may be in conflict with prior and a generl model, but noteworthy: H. Ma, Y. Tan, L. Du, X. Han and J. Ji, "An Integrated Design of Power Converters for Electric Vehicles, 2017 IEEE 26th International Symposium on Industrial Electronics (ISIE), Edinburgh, 2017, pp. 600-605 Battery Cells Management System Battery Cells containment and shielding methods Build a drivetrain model and simulation Modelling vehicle suspension design via system-level simulation Steering system M. Bertoluzzo et al., A Distributed Driving and Steering System for Electric Vehicles Using Rotary-Linear Motors, SPEEDAM 2010, Pisa, 2010, pp. 1156-1159 Chen Y., Lu Z., Zhang D. (2009) Study on Steering Control Strategy of Electric Vehicles Driven by Hub-Motors. In: Yu W., He H., Zhang N. (eds) Advances in Neural Networks – ISNN 2009. ISNN 2009. Lecture Notes in Computer Science, vol 5552. Springer, Berlin, Heidelberg. Chassis design and analysis Designed to accommodate all systems Consequential weight distribution and scuring Consequential structural integrity Integrating and connecting all systems to chassis to function competently Systems integration (competently) Consideration of all prior labs in unison model and simulation NOTE: generally, labs will not be in tune with lecturing, rather the labs will be reinforcement/advancement of prerequisite skills. Contrary stance will have things quite chaotic or unprofessional in end result. Such labs will be crucial to major group projects Major Group Projects --> 1. Profiling motors, power supply preferences, analysis and implementation of control 2. Drive System (engine, transmission, drive shafts, differentials, differentials, and final drive) 3. Drive System where each wheel has independent motors and control For major group projects much will depend on lectures (with activities), lab development, personal ambition, cooperation and discipline. Will require highly detailed and clear planning to develop at least competent projects. Apart from lectures and labs knowledge and skills from prerequisites will be vital. Students concerns with whatever vehicle designs will accommodate components where configurations/integration yields minimal burden on power train, but also having excellent structural integrity. NOTE: there may be additional modelling, simulation and experimental activities unique to labs and major group projects from lecturing. Prerequisites skills will be invaluable towards keeping pace (timely comprehension, digestion and retention) WEEK 1 1. Hybrid and Electric Vehicles (HEV): History Overview and Modern Applications 1.1. Ground vehicles with mechanical powertrain and reasons for HEV development 1.2. HEV configurations and ground vehicle applications 1.3. Advantages and challenges in HEV design 1.4. Course objectives WEEK 2 2. Power Flow and Power Management Strategies in HEV 2.1. Mechanical power: generation, storage and transmission to the wheels 2.2. Electric power: generation, storage and conversion to mechanical power 2.3. Hydraulic power: generation, storage and conversion to mechanical power 2.4. Energy storage/conversion and thermodynamic relations WEEK 3 – 4 3. Vehicle Dynamics Fundamentals for HEV Modelling and Computer Simulation(Mathematica/SystemModeler) 3.1. Various strategies for improving vehicle energy/fuel efficiency 3.2. Vehicle chassis mathematical model in various operation conditions (steady motion, acceleration, regenerating braking, coasting, moving up and down a hill) 3.3. Series HE powertrain mathematical model 3.4. Computer model of the HEV 3. Vehicle Dynamics Fundamentals for HEV Modelling and Computer Simulation (Mathematica/SystemModeler) - continuation 3.5. Computer Workshop. Fuel efficiency evaluation of a series HEV in city and high-waycycles: study and analyse two strategies for ICE/Battery power split 4. Vehicle Testing Laboratory Works 4.1. 4x4 Vehicle Chassis Dynamometer: Power Curve Test WEEK 5 4. Vehicle Testing Laboratory Works - continuation 4.2. 4x4 Vehicle Chassis Dynamometer: Programmed Force Test 5. Mechanical Drivetrain Engineering 5.1. Driving axle designs and characteristics 5.2. Automatic transmission designs and characteristics WEEK 6 5. Mechanical Drivetrain Engineering - continuation 5.3. Planetary gear sets in transmission designs 5.4. Vehicle applications at different modes of operation WEEK 7 6. Electric Drives 6.1. DC-Brushed and brushless drives: principles of design, operation, math modelling and Control Shunt Drives Series Drives Compound Drives WEEK 8 6. Electric Drives - continuation 6.2. Thermal analysis of electric drives in various vehicle applications WEEK 9 7. Wheel-Electric Drive, Suspension System Design 7.1. Gear trains in wheel-electric drives 7.2. Mechatronic design of wheel-electric drives 7.3. Suspension design for wheel-electric drives WEEK 10 7. Wheel-Electric Drive, Suspension System Design - continuation 7.4. Wheel/Tire-terrain interactive dynamics 7.5. Inverse dynamics-based control 7.6. Computer Workshop. Inverse dynamics-based control of a tire-surface interactive dynamics (Mathematica/SystemModeler) WEEK 11 Midterm Examination (one session) 8. Batteries and Energy Storages 8.1. Battery characterization, math modelling and designs 8.2. Battery sizing for various vehicle applications WEEK 12 8. Batteries and Energy Storages – continuation 8.3. Battery monitoring and charging control 8.4. Combination of batteries and ultracapacitors 8.5. Fuel cells: principles of operation, design, modelling 8.6. Fuel cell storage system 8.7. Strategy for controlling hybrid fuel cell system WEEK 13 8. Batteries and Energy Storages – continuation 8.8. Flywheel energy storage characterization May seek additional intelligence from journal articles for structure with components and further modelling and characteristics suited for an EV. Assisting example: A. Buchroithner, H. Wegleiter and B. Schweighofer, "Flywheel Energy Storage Systems Compared to Competing Technologies for Grid Load Mitigation in EV Fast-Charging Applications," 2018 IEEE 27th International Symposium on Industrial Electronics (ISIE), Cairns, QLD, 2018, pp. 508-514 WEEK 14 9. Power Electronics in Hybrid Electric Vehicles 9.1. Rectifiers 9.2. Buck convertor 9.3. Voltage source inverter 9.4. Current source inverter 9.5. DC-DC convertor 10. Plug-in Hybrid Electric Vehicles 10.1. PEV configurations 10.2. Power management problems XX.X. Filters? From batteries to [...] to motors 10.3. Component sizing WEEK 15 11. Electric Unmanned Ground Vehicle: Computer Modelling and Physical Tests 11.1. Autonomous wheel power management for vehicle dynamics control Prerequisites: Practical Programming in C for Engineering I & II, Machine Design I & II, Systems Modelling I & II, Mechatronics I & II, Modelling & Simulation Lab, Electric drives I & II. Power Electronics, Modelling & Control of Power Electronics, Power Electronics for Electric Drive Vehicles

Electrification of Transportation II 1. Maintenance and Safety of EV Knowledge, practices and skills from prerequisite and course will be mandatory in application. Will have similar development process as described in prerequisite. 2. Advance repetition and expansion are basic needs Advance redevelopment of prerequisite term project 3. Hydrogen generator (electrolysis) Analysis of hydrogen extraction from water (green hydrogen) Some electrochemistry for determination of production rate Expected production (and means to confirm) Will then develop hydrogen extraction system in lab Note: must well designed and developed with components (no crummy contraptions) Will be applying 13 – 40 gallons of water Will make use of solar power for process Development of safe storage for hydrogen Will be designing a hydrogen fuel cell powertrain May have to dig deep with the Modelica libraries or SystemModeler to simulate such a system Modelling & simulation of components integrated Design of various controllers as well, wherever warranted Power systems analysis General components in a hydrogen system Battery (auxiliary): In an electric drive vehicle, the auxiliary battery provides electricity to start the car before the traction battery is engaged and also powers vehicle accessories. Battery pack: This battery stores energy generated from regenerative braking and provides supplemental power to the electric traction motor. DC/DC converter: This device converts higher-voltage DC power from the traction battery pack to the lower-voltage DC power needed to run vehicle accessories and recharge the auxiliary battery. Electric traction motor (FCEV): Using power from the fuel cell and the traction battery pack, this motor drives the vehicle's wheels. Some vehicles use motor generators that perform both the drive and regeneration functions. Fuel cell stack: An assembly of individual membrane electrodes that use hydrogen and oxygen to produce electricity. Fuel filler: A nozzle from a fuel dispenser attaches to the receptacle on the vehicle to fill the tank. Fuel tank (hydrogen): Stores hydrogen gas onboard the vehicle until it's needed by the fuel cell. Power electronics controller (FCEV): This unit manages the flow of electrical energy delivered by the fuel cell and the traction battery, controlling the speed of the electric traction motor and the torque it produces. Thermal system (cooling) - (FCEV): This system maintains a proper operating temperature range of the fuel cell, electric motor, power electronics, and other components. Transmission (electric): The transmission transfers mechanical power from the electric traction motor to drive the wheels. Lab development of operating hydrogen fuel cell powertrain Validation Assembly Voltage, current, Power, RPM, efficiency, energy lifespan, practicality Multimeters, oscilloscopes, heat sensors, DAQs Various sensors and data processing will be employed to compare with simulation data. Prerequisite: Electrification of Transportation I Silicon Integrated Photonics Electromagnetic waves, silicon photonics, optical waveguides, waveguide couplers, waveguide filters, photonic electro-optical devices, silicon photonic modulators, germanium photodetectors, optical communications systems. Resonating Texts: L. Coldren, S. Corzine, M.L. Mashanovitch , Diode Lasers and Photonic Integrated Circuits, Wiley S. L. Chuang, Physics of Photonic Devices, 2nd edition B. E. A. Saleh & M. C. Teich, Fundamentals of Photonics, Wiley Tools --> Synopsys applications Photon Design Lumerical SPICE Assessment --> Homework and participation 15% Labs 25% Exam I 20% Exam II 20% Final Exam 20% Labs--> Course would be quite difficult to relate to without some level of interactive activity. I also can’t just show you pictures of devices or sketches and expect you to find much meaning in that, or keep interest. The described tools to be applied to chosen lab topics. Labs will make use of the given tools. Course Topics --> 1. Introduction and review (4 hours) Optical communications: short-reach, long-haul, and data centres communications. Economic drivers towards photonic integration. Interaction of optical waves with dielectric and metal interfaces. Boundary conditions, total internal reflection. Review of silicon PN-and PIN-junctions. Junction diode static and transient characteristics. 2. Fundamentals of Si photonics (8 hours) Symmetric dielectric waveguides. Asymmetric dielectric waveguides. Rectangular waveguides. Computational methods for integrated photonics. Marcatilli’s and effective index methods. Propagation matrix, finite difference time domain, eigenmode expansion. Design and fabrication of silicon waveguide structures. Waveguide loss, scattering, absorption, radiation. Adiabatic mode converters. Dispersion in optical waveguides, group delay, dispersion engineering. 3. Passive devices (8 hours) Coupling to waveguide: edge, grating, evanescent coupling, spot-size converters. Packaging solutions and economic/functional/power constraints. Coupled mode theory. Coupled optical waveguides. Power splitters. Mach-Zehnder interferometer. Cascaded MZI optical filters. Star couplers. Wavelength division multiplexing. Optical ring resonators. Add-drop multiplexers. Waveguide Bragg gratings. Polarization dependence and management. Waveguide polarization splitters and rotators. Optical isolation. Wavelength multiplexers figures of merit 4. Transmitter active devices (10 hours) Electro-optical effects in silicon. Thermal phase shifter, thermo-optic switch. Carrier-induced electro-optical effects. Carrier-Injection phase shifter. PN-junction carrier distribution, optical phase response, small signal response. Forward biased PIN junction variable optical attenuator. Micro-ring modulators and switches, small-signal response, ring modulator design. Carrier depletion phase shifter. PN-junction carrier distribution, optical phase response, small signal response. Traveling wave design of reverse-biased electro-optic modulator. Modulators for advanced modulation formats. Transmitter figures of merit. 5. Receiver active devices (4 hours) Germanium photodetectors. Fabrication approaches. III-V integration with silicon photonics. Integrated photodetectors, lasers and amplifiers. Receiver figures of merit 6. Photonic systems (3 hours) Introduction to photonic systems for short-reach and long-haul optical communications. Modulation formats, receiver and transmitter characteristics, optical link budget, BER and penalties. Introduction to data centre optical networks. Optical switching. Optical switches. 7. Emerging Applications (5 hours) Si photonics in quantum computing, neuromorphic computing, and biological sensing. Comparison of technological advantages and business models. State of silicon photonics industry. Skills and competencies Prerequisites: Signals & Systems, Electromagnetics II; Modern Physics; Solid State Devices III Silicon Photonics Design Lab Course is a rare opportunity where one can’t afford to be unconstructive. Due to economic constraints this course will be the closest thing to an industrial development lab; a virtual version of real development in a facility. It will be unfortunate if impedance, sabotage and pestilence gets into this course; essentially all that work leading up to this course will not be vindicated then. Text for lectures and labs: Chrostowski, L. and Hochberg, M. (2015). Silicon Photonics Design: From Devices to Systems. Cambridge University Press, 437 pages Course will follow the contents of the given text in such given order Tools --> Synopsys {RSoft Component Design + OptSim Circuit + Optodesigner} Photon Design Lumerical SPICE Labs --> Labs will be highly dependent on the mentioned above tools with structure from lab lectures. Development with such tools will be a sequential build up towards system design based on intentions of use. Exams --> Any type of testing will be a challenge to develop if there’s merit for such in this course. Likely there will be none because most of the academics come from prerequisites or co-requisite. For this course in particular you need all the time you can get, so time consuming exams aren’t likely. I will assume you have the maturity with past knowledge and skills to be sensible to appreciate the experience of this course. You have reached this level because you want to be here and do something meaningful and economic towards your future. This field in no way imaginable stops at the undergraduate level; there’s no other option. Prerequisites: Modern Physics; Optoelectronics; Solid State Devices III Semiconductor Quantum Structures & Photonic Devices This course serves to develop a fundamental understanding of the basic physics and practical operation of semiconductor optoelectronic devices, with emphasis on devices based on quantum structures. Design principles based on band-structure engineering will be highlighted. Optical properties of semiconductors: interband optical transitions; excitons. Low dimensional structures: quantum wells, superlattices, quantum wires, quantum dots, and their optical properties; intersubband transitions. Lasers: double-heterojunction, quantum-well, quantum-dot, and quantum-cascade lasers; high-speed laser dynamics. Electro-optical properties of bulk and low-dimensional semiconductors; electroabsorption modulators. Detectors: photoconductors and photodiodes; quantum-well infrared photodetectors Typical Text: Physics of Photonic Devices, S.L. Chuang, Wiley References: Electronic and Optoelectronic Properties of Semiconductor Structures, J. Singh, Cambridge Diode Lasers and Photonic Integrated Circuits, L.A. Coldren, S.W. Corzine & M. L. Mashanovitch, Wiley Tools --> -SPICE -Purdue gekco (nanoHUN, OMEN, NEMO 1D, NEMO 3D, NEMO5) -nextnano -Semiconductor Quantum Dot Computer Aided Engineering (CAE) Simulation Tool – Wei Li et al -KdotPsoft Bose, S. et al (2017). KdotPsoft: Modelling and Simulation of Semiconductors and Device Physics. 9th International Conference on Materials for Advanced Technologies (ICMAT 2017). Procedia Engineering 215, 36 – 40 Tanaka, R. Y. et al (2007). Software Tools for the Design and Analysis of Quantum Well, Quantum Wire and Quantum Dot Devices. 2007 SBMO/IEEE MTT-S International Microwave & Optoelectronics Conference (IMOC 2007) Concerning software clouds mentioned in tools one will like to get access and make use of at least 2 for cross evaluation, or it may be the case that one software has particular strengths or attributes while another has unique valuable properties. As well, supporting journal articles explaining their physics, engineering and mathematical structure would be much appreciated. NOTE: finding journals supporting a particular software doesn’t mean it is better than others; often conferences and research are inaccessible to “certain folk”. Emphasis on use of such tools gives the course more sense of purpose, rather than a view of “chucking extravagant fodder” towards no real purpose. Assessment --> Homework 15% 2 Exams 30% Labs 15% Final exam 25% Project 15% Homework --> Assignments will call you out with course prerequisites, as well as standard problems for course. Mathematica and so forth can serve only as cross evaluation for consistency with your work. Assignments to be done with word processor making use of the mathematical palette in writing; accompanied by Mathematica development when needed. Use of Tools --> During lectures there will be time periods designated for incorporation of tools to increase value in lectures. Labs--> Course would be quite difficult to relate to without some level of interactive activity. I also can’t just show you pictures of devices or draw sketches and expect you to find much meaning in that, or keep interest. The described tools to be applied to chosen lab topics. Labs will make use of the given tools. Exams --> Exams will harshly reflect homework assignments. Yet, don’t expect a culture solely of problems to be memorized. Will also test your fundamentals and conviction concerning your intelligence, and also why you do or don’t use it. Student Project --> Project concerns development towards constructive and/or serviceable applications. Use of tools are mandatory in order to develop anything with substance. Mathematica usage also welcomed. Again, project is 20 % of your grade. Make it really happen, else you are penalizing yourself with 20%. Topic Outline --> 1. Electronic band structures (Week 1 – Week 3) Review of relevant concepts of quantum mechanics and semiconductor physics; k∙p method; key results of Luttinger-Kohn’s theory; effective mass approximation; band structures of compound semiconductors; strain effects. 2. Optical properties of bulk semiconductors (Week 3 – Week 5) Interband optical transitions; absorption and gain; spontaneous and stimulated emission; carrier-induced refractive index; exciton absorption. 3. SQS & their optical properties (Week 6 – Week 8) Electronic structures of quantum wells, superlattices, quantum wires and quantum dots; interband optical transitions and exciton effects in low-dimensional systems; intersubband optical transitions; polarization selection rules. Midterm 4. Semiconductor lasers (Week 9 – Week 11) Double-heterojunction lasers; quantum-well and strained-layer quantum-well lasers; quantum-dot lasers; intersubband (quantum-cascade) lasers: light current characteristics; laser dynamics and direct modulation characteristics; linewidth enhancement factor. 5. Modulators (Week 12 – Week 13) Franz-Keldysh effect; quantum-confined Stark effect; electroabsorption modulators; interferometric modulators; all-optical switches. 6. Photodetectors (Week 13 – Week 14) Photoconductors; p-i-n and avalanche photodiodes; quantum-well infrared photodetectors (QWIPs). 7. Tying up loose ends (Week 15) 8. Final (Week 16) Prerequisites: Modern Physics, Solid State Devices III, Optoelectronics, Methods of Mathematical Physics, Quantum Mechanics I Satellite Communications Increasingly, satellites are also being used for data relay and personal communication systems. The principles of radio communications have wider application, but the unique attributes of orbiting satellites and the techniques used for communication via these satellites requires a specialized course. This course gives students a broad treatment of the diverse (sub)systems that make up a complete satellite communication system. Theory, practice and design of satellite communications. Orbits and launchers, spacecraft, link budgets, modulation, coding, multiple access techniques, propagation effects, and earth terminals. NOTE: course will require at least 44 hours of lecturing. Additionally, there will be specialized labs to treat particular topics and technical tools. Guiding Texts: Pratt, T., Bostain, C. W. & Allnutt, J. E. (2002). Satellite Communications, Wiley Gordon, G. D. & W. Morgan, W. L. (1993). Principles of Communications Satellites, Wiley-Interscience Necessary Supplementary Texts: Wertz, J.R. and W.J. Larson, eds. Space Mission Analysis and Design. 3rd ed. Microcosm Press, 1999. NASA Cost Estimating Handbook Tools --> Modelica Mathematica & SystemModeler SPICE Nasa Open Source Software (type search “satellite” and so forth) < https://software.nasa.gov > < https://opensource.gsfc.nasa.gov > < code.nasa.gov > ONSET: the Online NASA Software Estimating Tools Analogy Software Cost Tool (ASCoT) CubeSat Or Microsat Probabilistic and Analogies Cost Tool (COMPACT) AGI Systems Toolkit (hopefully NASA software can be substitutes) Cost Estimation Toolkit (CET) Software Package CAD Homework --> Will be problem sets from different sources Modelling & Simulation projects --> -Will take projects from the following article and augment them: Aburdene, M. F. and Nepal, K. AC- 2100 – 657: Satellite Communications, Data Communications, and simulation. ASEE 2011 March 1st https://peer.asee.org/satellite-communications-data-communications-and-simulation.pdf -Satellite subsystems development subject to satellite’s purpose (6) Modelic and SystemModeler environment -Integrated satellite communications systems Modelic and SystemModeler environment Sequential Projects (supplementary texts) --> Will require the coding of software modules. We intend for these modules to be useful in future subjects or satellite system design work beyond your studies. The point of analysing the other teams' work and receiving comments on your own is to help you build useful and effective tools. The modules should mathematically capture the relationships between the discipline's inputs and outputs and in general relate subsystem performance and cost to the subsystem's requirements. When used in an integrated concurrent engineering context, you will be asked to determine how the subsystem performance or cost will change as a result of changes in the requirements. The module must be complex enough to capture the important relationships yet simple enough to provide outputs that make sense. You should ensure that your modules are appropriately documented with explicit definitions of input and output so that you and others will understand its structure. You are likely to use this program again in the future or may need to use part of it in developing the solution to another problem. You might have to update it or correct errors. In any case, the faculty and the review team will grade it. Documentation is essential so that we can understand and give proper credit for your work. Good documentation would include: Programmer's name A concise requirements specification Descriptions of problem inputs, expected outputs, constraints and applicable formula A pseudo-code or flowchart for its algorithm (optional) A source program listing A hardcopy of a sample test run of the program A user's guide explaining to non-programmer users how the program should be used (optional) Additional projects --> 1. I will ask you to design code in C/sensor instrumentation language towards microcontroller-sensor integration for subsystems. Some components in the following literature will be simulated followed by physical development: Geostationary Operational Environmental Satellite – R Series. NOAA – NASA. Pursuant to Contract NNG09HR00C. Revision A, 2019 CDRL PM – 14:-> https://www.goes-r.gov/downloads/resources/documents/GOES-RSeriesDataBook.pdf 2. The following article to serve as guidance Katona, Z. et al (2020). A Flexible LEO Satellite Modem with Ka-band RF Frontend for a Data Relay Satellite System. International Journal of Satellite Communications and Networking, Volume 38 Issue 3, pages 301 – 313 Will require your intelligence and skills from the following courses: Signals & Systems Analogue & Digital Communications Systems Modern Digital Communications Grading --> Homework Modelling & Simulation Projects Sequential Projects Additional Projects Course Outline --> 1.Orbital Mechanics 2. Reference frames for satellites and Earth with relevance to communications and manoeuvres. Look angle determination, orbital effects in communications system performance 3.Spacecraft Subsystems 4.Evaluate spacecraft subsystem performance and trades 5.Select appropriate launch systems and understand their effects on satellite and payload design and performance 6.Link Budgets, C/N Calculation 7.Analogue Modulation techniques, S/N calculation 8.Digital Modulation, Transmission, Reception, Multiplexing, BER and SER calculation 9.Multiple Access Techniques: FDMA, TDMA, CDMA, RA 10.Coding and Error control 11.Propagation Effects 12.Estimate space system costs 13.Trade subsystem performance requirements to optimize higher-level system performance, cost, or weight 14. Case Studies: DBS-TV, GPS, LEO, VASAT networks, etc. etc. Prerequisites: Signals & Systems, Analogue & Digital Communications Systems; Modern Digital Communications; Modelling & Simulation Lab; Mathematical Statistics, Practical Programming in C for Engineering I & II Hands-on Satellite Design This course is designed for students with strong development in engineering towards applicable and practical insight into space technologies. With the practical approach applied, students experience working on a challenging project in an interdisciplinary team. Students will know the parts of a space system and understand their correlations, and will be able to plan and conduct a space mission. Practically, students will be capable of designing a part of a space system with regard to mechanics, electronics and programming. During project work units, parts of the satellite will be designed with supervision in smaller groups. Satellite designs to emulate --> CubeSat, CanSat, BeeSat During project work units, parts of the chosen satellite will be designed with supervision in smaller groups. Will also pursue means to test under real conditions. Satellite will perform several measuring tasks. In this course, a satellite is designed, built and tested in the field during a rocket launch. Therefore, all basics of topics related to exciting area of space technologies is imparted and practical skills for the development of the satellite are trained. The theoretical units are supplemented by practical exercises. Parts of the satellite are developed in intensely supervised small groups. During a launch campaign, the satellite will be tested under real conditions. Literature Resources --> Handbook of Space Technology, W. Ley Santoni, F., et al. (2014). An Innovative Deployable Solar Panel System for Cubesats. Acta Astronautica. 95. 210–217. Make: Electronics, C. Platt Arduino Cookbook, M. Margolis C programming for Engineers Macro Coding Assists --> NASA Open Source Software https://code.nasa.gov NASA Software Catalogue https://software.nasa.gov https://opensource.gsfc.nasa.gov code.nasa.gov > ONSET: the Online NASA Software Estimating Tools Analogy Software Cost Tool (ASCoT) CubeSat Or Microsat Probabilistic and Analogies Cost Tool (COMPACT) SPENVIS (with data files incorporated) Modelica Wolfram SystemModeler Physical Design --> CAD (computer-aided design) NOTE: it’s recommended that students use their own laptops for the hands-on project. NOTE: machining and additive manufacturing may be inevitable Assessment --> The assessment is based on the project which is conducted throughout the whole duration of the course. The students work in small teams where team marks as well as individual marks will be given. The final grade of each individual student is composed of the following components: - Short tests - Design of systems - Possible simulations - Construction and testing of systems - Project presentation and answering to critical questions in front of a review board - Flight performance of the team’s system during the launch campaign Development Areas --> Astronautics Mission Planning & Design (extensive and resonates throughout) Electronics Design Programming (extensive and resonates throughout) CAD Design Satellite Subsystems Fit check Soldering Integration dry run Assessment Presentation Launch Prerequisites: Practical Programming in C for Engineering I & II, Satellite Communications Electromagnetic Scattering from Random Media & Rough Surfaces Classical models for scattering from statistically described media such as “random media” or “randomly rough” surfaces. Models stem from a combination of approximate methods for electromagnetic scattering and classical statistical techniques to give insight into the behaviour of electromagnetic waves propagating in sophisticated media. Concerned with the theories of independent scattering, radiative transfer, analytical wave theory, and the Kirchhoff and small perturbation methods for rough surface scattering in the course. Comprehension of these theories is crucial for the design of sensors and algorithms for microwave remote sensing of the Earth, and also for clutter reduction tools in statistical signal processing of radar data. Comprehending the limitations of these theories is crucial, due to approximate descriptions of the physical environment and the scattering process. Texts in unison: Ishimaru (1997). Wave Propagation & Scattering in Random Media, IEEE Press L. Tsang, J.A. Kong, and R.T. Shin (1985). Theory of Microwave Remote Sensing, John Wiley & Sons Invaluable References: IEEE journal articles and publishing OSA Publishing Tsang, L. et al. (2001). Scattering of Electromagnetic Waves: Numerical Simulations. Wiley-Interscience, 736 pages Grading: 4 – 5 HW sets 15% 4 – 5 Quizzes 15% Computer Project 20% Midterm 25% Final 25% Quizzes --> Will reflect lecturing and homework Exams --> Will reflect homework, lecturing and quizzes Computer Project --> Each student is required to complete a project comparing a more “exact” numerical scattering problem solution with the results of one of the course approximate theories, and discussing the results and implications of this study in a written report. A standard project will be suggested and developed as the course progresses, but some students may wish to pursue their own projects and should arrange their topic with the instructor. Prerequisites: Numerical Analysis; Partial Differential Equations (CHECK Computational Finance); Electromagnetics I & II; Electromagnetic Waves & Antennas; Mathematical Statistics AEROSPACE ENGINEERING PARTICULARS --> Aircraft Design This is a project course in which students complete the preliminary design of an airplane of their choice. The design process involves defining the mission requirements, weight sizing, performance sizing, fuselage design, wing, high-lift system and lateral controls design, landing gear design, weight and balance, stability and control, drag polars, and final drawings. In their final report students also discuss environmental, economic and safety considerations for their airplane. Required Literature --> Raymer, D. (2018). Aircraft Design: A Conceptual Approach. AIAA Snorri Gudmundsson. (2013). General Aviation Aircraft Design. Butterworth-Heinemann Required Weight Optimisation Literature --> Wells, D. P. and McCullers, L. A. (2017). The Flight Optimization System Weights Estimation Method. NASA/TM–2017–219627/Volume I Riboldi, C.E.D. & Gualdoni, F. (2016). An Integrated Approach to the Preliminary Weight Sizing of Small Electric Aircraft. Aerospace Science and Technology, 58, 134–149. Tools applied in course --> < DATCOM, XFLR5, Athena Vortex Lattice (AVL), XFOIL, OpenVSP, Cart3d, VSPAERO, Open VOGEL, AVL > < Ansys, Nastran + Patran > Course Assessment --> Homework 10% 5 Quizzes 15% Intensive Design/Simulation Projects 20% 3-4 Project Development Phases Reports 30% Final Report 25% Development Outcomes --> 1. Describe the pros and cons of unconventional aircraft configurations such as canards, 3-surface, sweptforward wings, flying wings, tailless, V/STOL, stealth, etc. 2. Perform weight and performance sizing of a gas-powered and electric airplanes, including pertinent Title 14 of the U.S. Code of Federal Regulations (14 CFR Parts 23/25) and European standards (EASA CS23/25) 3. Design the fuselage, the wing, the empennage, and the landing gear of an airplane. 4. Perform weight and balance analysis of an airplane. 5. Perform a stability and control analysis of an airplane. 6. Compute the drag polars of an airplane. 7. Produce final drawings of an airplane. 8. Discuss environmental and safety issues related to your airplane. 9. Value-driven design, cost modelling, systems engineering aspects Basic life cycle cost analysis. A systems-level view of aircraft design. 10. Communicate the results of their design in a comprehensive, well written final report, following APA guidelines. Must include the following technical features in report: Explanation of values/parameters In the word processor expressed formulae by use of mathematical palette CAD and structural analysis development Tables, Charts and graphs (based on Mathematica, Excel, R, etc.) Referencing all software and sources Homework --> Homework should be taken seriously, otherwise, performance on quizzes will be highly predictable. After a certain amount of homework is provided, collected and returned, immediately a quizz to follow. No late homeworks will be accepted. Quizzes --> 5 Quizzes at most concern intelligence towards social interaction in the field of aerospace engineering. Concerns analysis for given data or conditions towards determination of formulae required and computation. Decision making problems are also possible. Intensive Design/Simulation Projects --> Will be in a lab environment. Each lab will be procured a designated amount of official time depending on level of intensity/difficulty. NOTE: getting assistance is not a bad thing, however, being self-reliant in the long run is the ultimate success. -Wing design using Ansys (or whatever CAD) -Wing structural analysis -Tail Analysis -Fuselage shell analysis -Fuselage stress analysis -Landing gear design using Ansys (or whatever CAD) -Landing gear structural analysis -Setting up the parametric CAD model of an aircraft, from 2d sketches to 3d whole aircraft models. Note: students should expect to be randomly called upon to demonstrate various construction or setup features without reservation. Project Development Phases Reports --> NOTE: getting assistance is not a bad thing, however, being self-reliant in the long run is the ultimate success. There will be 3-4 mandatory project development phases reports serving to build susbstance, integrity and sustainabilty towards final reports and future endeavors in aerspace engineering. Late submission will be penalized severely; there will also be reduction in final report grade. Final Report --> Students will communicate the results of their design in a comprehensive, well written final report, following APA guidelines. Must include the following technical features in report: Explanation of values/parameters In the word processor expressed formulae by use of mathematical palette CAD and structural analysis development Tables, Charts and graphs (based on Mathematica, Excel, R, etc.) Referencing all software and sources Prerequisite: Aircraft Theory Aerodynamics Aerodynamics of aerofoils and wings in subsonic, transonic and supersonic flight. Laminar and turbulent boundary layers and effects of viscosity on aerodynamic performance. Students will: Aerodynamics of aerofoils and wings in subsonic, transonic and supersonic flight. Laminar and turbulent boundary layers and effects of viscosity on aerodynamic performance. 1. Learn how lift, drag and pitching moment are generated 2. Learn airfoil and wing geometric parameters and aerodynamic performance characteristics (Cp, Cl , Cm, Cd, Drag Polar) 3. Learn similarity parameters, physical characteristics and aerodynamics trends associated with continuum flow regimes (Subsonic, Transonic, Supersonic, Hypersonic, Steady, Unsteady, Viscous, Inviscid) 4. Learn how the Potential Flow approach can be used to predict incompressible and compressible aerodynamics 5. Learn the boundary-layer concept for modeling the effects of viscosity 6. Be introduced to Non Continuum Flows / Non Newtonian Fluids 7. Be introduced to the Computational Fluid Dynamics (CFD) approach Students will be able to: 1. Use analytical methods to estimate lift and drag (including viscous effects) on aerofoils, wings and bodies of revolution in subsonic and supersonic flight. Thin Aerofoil Theory, Finite Wing Theory, compressibility corrections, transonics, sweep effects, area rule, supersonic linearized theory, shock expansion wave method, Newtonian Theory, flat plate boundary layer results in laminar/turbulent flow 2. Use numerical methods to calculate aerodynamic loads and moments (including viscous effects) on 2-D and 3-D bodies in in incompressible and compressible flow Panel methods and integral boundary layer methods 3. Describe physical characteristics (including momentum and thermal) of laminar and turbulent boundary layers, transition and separation. NOTE: course doesn’t concern teaching Fluid Mechanics; course in fluid mechanics is prerequisite. Tools of consideration --> << DATCOM, XFLR5, Athena Vortex Lattice (AVL), XFOIL, OpenVSP, VSPAERO, Open VOGEL, AVL >> << OpenFoam, Cart3D >> << ANSYS: FLUENT, CFX >> Grading --> Problem Sets 3 - 4 Exams Labs Labs will be an environment of theory towards simulations. Will make make use of software from “tools of consideration” to follow recognised theory. Include various aerofoil designs and the responses. As well will encounter various aircraft designs with various types of aerofoils in structures. Some may apply models that are different to other software; determination which is most appropriate with consideration of the existing environment (subsonic, transonic, supersonic and hypersonic). Labs will reflect all topics. Course Outline: 1) Aerodynamics Intro and Course Overview (1 hour) 2) Fluid Motion Basics (1 hour) Streamlines, pathlines, steady vs. unsteady, rotation and vorticity, boundary layer 3) Viscous Flow (21 hours) Incompressible (16 hours): Simple solutions to the Navier-Stokes equations, boundary layer equations: exact solutions, Blasius solution, pressure gradient effects Physics of turbulence and its effects, turbulent flat plate solutions, factors affecting transition Momentum Integral Method, Thwaites Method, Head’s Method, Squire-Young formula for drag, empirical methods for transition estimate, Michel’s Criteria Overview of Non-Newtonian fluid effects on skin friction Compressible (5 hours): Compressibility corrections to boundary layer equations, prediction of skin friction and heat transfer 4) Potential Flow (2 hours) Derivation of Velocity Potential Equations for Compressible and Incompressible Flows 5) Low Speed Aerodynamics (15 hours) Elementary solutions for incompressible Potential Flow: uniform flow, source/sink, doublet, vortex (1 hour) Flow around 2-D cylinder, concept of circulation, Kutta-Joukowsky Theorem, drag in separated flow, Cp distribution (3 hours) Aerofoils (6 hours): Thin Aerofoil Theory, Kutta Condition, Cl, Cm, lift curve slope, centre of pressure, aerodynamic centre Overview of panel methods, numerical tools for prediction of skin friction drag around aerofoils 6) Wings (5 hours): Physical characteristics, trailing vortices, vortex sheet, starting vortex, downwash, induced drag, effect of aspect ratio Prandtl's lifting line theory and numerical tools Induced drag, elliptical lift distribution, span efficiency factor, drag polars including viscous effects Vortex dominated flows and leading edge vortices 7) High Speed Aerodynamics (15 hours) 8) Derivation of Linearized Potential Flow Equation, small disturbance approximations (1 hour) Subsonic Flow over Aerofoils (3 hours) Prandtl-Glauert Rule, compressibility corrections and effects on lift, drag and Cp distribution Subsonic Flow over Wings and Bodies (3 hours) Modifications to lifting line analysis to include compressibility effects, Potential Flow over Body of Revolution using Gothert's Rule, closed form expressions for Cp and Cd Transonic Effects on aerofoils, Wings and Bodies of Revolution (4 hours) Transonic flow effects on Cl, Cd, Cm and Cp, finding Critical Mach Number of aerofoils and bodies of revolution, Wave drag, Drag divergence; elimination of drag rise by sweep, area rule, supercritical aerofoils. Supersonic and Hypersonic Flow Prediction (4 hours) Determination of lift and drag using linearized supersonic flow, shock-expansion wave theory, Newtonian Theory, Modified Newtonian Theory 9) Computational Fluid Dynamics (2 hours) Overview of Reynolds Averaged Navier-Stokes (RANS) approach and capabilities Understanding and exposure to numerical flow analysis process: grid generation, flow solution, post processing Prerequisite: Fluid Mechanics Compressible Flow Fundamentals of compressible fluid dynamics and application to external and internal flows. Channel flow, extensions, and analysis of multi-dimensional flows in aircraft geometry, nozzles, diffusers, and inlets. Effects of friction and heat transfer. Forces, moments, and loss generation resulting from compressible fluid flow interactions with aerodynamic shapes in subsonic, supersonic, transonic, and hypersonic flight, shock waves, and vortices. Disturbance behaviour in unsteady compressible flow. Typical texts (in unison) --> John D. Anderson Jr., Modern Compressible Flow NACA TR1135, Equations, Tables and Charts for Compressible Flow, 1953 Tools --> OpenFOAM Cart3d Mathematica (search for topics of interest) Wolfram Community Wolfram Demonstrations Nasa software catalogue (https://software.nasa.gov/software) vuCalc Grading --> Homework +Simulation Exercises 15% 3 Tests 45% Final Exam 20% Group Project 20% Group Project --> Simulation of Aerodynamics and Heating w.r.t. detailed aircraft design Subsonic Transonic Supersonic Hypersonic A. Finite Element Analysis of the assigned 1-2 aircraft designs to each group. B. Expected are recognition and appropriate settings for governing models relevant to aerodynamics, compressible flow and heating. C. As well, identification of the applied simulation tools and the logistics with the incorporation of such simulation tools. D. AGAIN, groups will be assigned 1-2 aircraft designs to situate the simulation. Will your results or findings from (A) identify sustainability in structural integrity with simulation findings with consideration of structural materials proposed? Note: meshes may or may not be relevant/ Topic Outline --> I. Introduction to Compressible Flow (1.1, 1.2, 1.3, 1.5, 1.6, 1.7) II. Review of Thermodynamics (1.4) III. Integral Form of the Conservation Equations (2.1-2.9) IV. One-Dimensional Steady Flow with Area Variations (Ch. 3 and 5, omit 3.8, 3.9, 5.5, 5.6) V. One-Dimensional Steady Flow with Area Variations (Ch. 3 and 5, omit 3.8, 3.9, 5.5, 5.6) Isentropic Flow: Conservation Equations (3.2, 5.2) Stagnation and Critical Quantities (3.4, 3.5) Area-Velocity Relation (5.3) Applications (5.4) Normal Shock Waves: Conservation Equations (3.6) Rankine-Hugoniot Relations (3.7) Applications (5.4) VI. One-Dimensional Unsteady Flow (7.1, 7.2, 7.3, 7.8) Unsteady Normal Shock Waves (7.1, 7.2, 7.3) Unsteady Isentropic Expansions Shock-Tube Relations (7.8) VII. One-Dimensional Flow with Heat Addition (3.8) VIII. Two-Dimensional Steady Flow (Ch. 4, omit 4.4, 4.5, 4.8, 4.13) Isentropic Flow: Isentropic compressions and expansions (4.1, 4.2) Prandtl Meyer Function (4.14) Oblique Shock Waves: Connection to Normal Shock Waves (4.3) Shock Reflections and Interactions (4.7, 4.9-4.12) Wave Interactions in Diffusers and Jets (5.4-5.6) Lift and Drag in Supersonic Flow Airfoils (4.15) Other Applications Conical Shock Waves (4.4, 10.1-10.3) Differential Forms of the Conservation Equations (6.1-6.9) Solution of the Differential Forms Method of Characteristics (11.2-11.7) Equations of Characteristic Lines (11.3, 11.4) �� Applications (constant Mach No. turns, nozzle design) (11.7) Linearized Theory (9.1-9.12 ) Hypersonic Wind Tunnel Development (time permitting) Sivells, J. C. (1978). A Computer Programme for the Aerodynamic Design of Axisymmetric and Planar Nozzles for Supersonic and Hypersonic Wind Tunnels. Report #: AEDC-TR-78-63 Hu, J. & Rizzi, A. (1995). Turbulent Flow in Supersonic and Hypersonic Nozzles, AIAA Journal Vol. 33, No. 9 Shope, F. L. (2005). Design Optimization of Hypersonic Test Facility Nozzle Contours Using Splined Corrections. AFRL/AFOSR. Performing Organisation Report #: AEDC-TR-04-2 Wang, Y. & Jiang, Z. (2022). Theories and Methods for Designing Hypersonic High-Enthalpy Flow Nozzles. Chinese Journal of Aeronautics, 35(1), pp 318-339 For prior journal article, the highlighted methods and their nature: Method of Characteristics (MOC) The graphic design method The Sivells method The theory for boundary correction CFD-based design optimization methods Prerequisites: Aerodynamics Aircraft Flight Dynamics I Three-dimensional rigid body dynamics, aircraft equations of motion, static and dynamic stability, flight control design, introduction to aeroelastic phenomena. NOTE: this a is not a fanatic garbage matrix algebra course of the mathematics department. Without model development and analysis all is pointless; you’re in the role of an engineer, not a wonderland ideologist. No one professionally in engineering has time to prove to anybody on a board that they’re gurus with trivial systems of equations. Basic operations with matrices is expected, but if you can recite your elementary multiplication tables (2-3) before completing matrix operations, then it’s not worth the time. If you believe matrix algebra will dictate this course, you will be utterly embarrassed by an engineer with their arsenal. This is course not a math-rat’s nest at the expense of others. Learning Outcomes --> 1) Kinematics and Dynamics of a 3D Rigid Body 2) Formulation and Numerical Solution of Flight Dynamics Equations of Motion 3) Concepts of Static and Dynamic Stability of Aerospace Systems 4) Location of the Elastic axis vs Aerodynamic Centre 5) Concepts of Divergence and Stability with a Single DOF Model 6) Sweep Effects 7) Concept of Flutter with a Pitch/Plunge model 8) Relevant Applications to Aerospace Systems Lab Tools --> Aircraft Dynamics Library Fritzson, P. and Idebrant, A. (2004). Aircraft - A Modelica Library for Aircraft- Dynamics Simulation FlightGear Flight Simulator Supports flight dynamics models like supports LaRCsim, UIUC, YASim and integration with various CAS tools Permits access to control and simulation data Course Outline --> I. Introduction Review Aerodynamic Nomenclature II. Aircraft Static Stability and Control Definitions Longitudinal Static Stability Longitudinal Control Directional Stability and Control Roll Stability and Roll Control III. Introduction to Static Aeroelastic Phenomena Divergence analysis using a Spring restrained Aerofoil Model Location of Elastic Axis versus Aerodynamic Centre Torsional Divergence Sweep Effects Aileron Reversal IV. Aircraft Equations of Motion Review Coordinate Systems and transformations Derivatives in Rotating Frames Translational Equations Rotational Equations Effect of spinning rotors V. Linearization Small Disturbance Theory Aerodynamic Force and Moment Derivatives Lateral-Directional Equations of Motion Equations of Motion in a Non-uniform Atmosphere VI. Aircraft Longitudinal Dynamics Review of modal analysis Longitudinal Motion Approximations Influence of Stability Derivatives Transfer Functions Flying Qualities VII. Aircraft Lateral Dynamics Lateral-Directional Equations Dutch Roll, Roll and Spiral Modes Modal Analysis Approximate Models Transfer Functions Flying Qualities VIII. Introduction to Dynamic Aeroelastic Phenomena Lift Deficiency Function Flutter Analysis using a 2DOF Pitch-Plunge Model Wing Flutter IX. Aircraft Flight Control System Design Prerequisites: Aircraft Theory & Design, Aerodynamics, Systems Modelling II, Feedback Control Aircraft Flight Dynamics II Advance treatment is necessary for retention, competency, professionalism and readiness towards future endeavours. You are only benefitting yourselves. NOTE: flight dynamics modelling and dynamic stability analysis for various aircraft will be emphasized. Lab Tools --> Aircraft Dynamics Library Fritzson, P. and Idebrant, A. (2004). Aircraft - A Modelica Library for Aircraft- Dynamics Simulation FlightGear Flight Simulator Supports flight dynamics models like supports LaRCsim, UIUC, YASim and integration with various CAS tools Permits access to control and simulation data Prerequisites: Aircraft Flight Dynamics I Advance Flight Mechanics: Develop conceptual understanding and technical insight into flight dynamics and flight control systems; exposure to advanced flight control concepts. Linear and nonlinear control of aircraft and spacecraft. Advanced aircraft and spacecraft modelling and control issues. B.L. Stevens and F. L. Lewis, Aircraft Control and Simulation, 2nd Edition, John Wiley & Sons, Inc., 2003. R.M. Murray, Z.Li, and S.S. Sastry, A Mathematical Introduction to Robotic Manipulation, CRC Press, 1994. D. McLean, Automatic Flight Control Systems, Prentice-Hall, 1990 A.E. Bryson, Control of Spacecraft and Aircraft, Princeton Univ. Press, 1994. Homework --> Homework problem sets will be distributed throughout the semester. Mathematica/SystemModeler or other simulator will be needed for some homework problems. Some homework questions may not have a single solution and may depend on your design choice. You are required to set a team of at least 2 but not more than 3 students for homework assignments. Each team is required to submit one homework solution and every student in a team will get the same score. Due dates will be specified on each homework assignment. Late submission of homework assignments will be penalized. Delay of submission of a homework set will cost 5% per day. For example, if you submit your homework 4 days late, then your homework score will be multiplied by 0.8. You cannot delay your homework submission beyond the last class day of the semester. You should submit your homework to the class website in “Blackboard”. Homework submission should be typed; no hand-written homework submission will be accepted. If your solution involves simulation and/or programming, the simulation model and/or source code also have to be submitted. Each team will be required to present in class their homework solution. Each team should be ready for presentation upon their homework submission. Homework presentation will be considered and graded as another homework assignment. Projects --> Choose a significant topic related to flight dynamics and/or flight control; typical topics include, but are not limited to, the following: • Mass-varying aircraft, rocket and spacecraft systems • Aircraft dynamics and control in wind and turbulence • Formation flight and control • Automated aerial refuelling • Handling qualities of remotely piloted aircraft • Thrust vectoring control for tailless military aircraft • Airship/Blimp dynamics and control • Landing on aircraft carrier • Control of coordinated aircraft turns • High angle of attack rolling manoeuvres • Multiple engine control for a damaged commercial aircraft • Integrated propulsion and flight control • Control of bank to turn missiles • Pilot induced oscillations • Rotorcraft flight control • Quadrotor flight modelling and control • Air traffic control conflict prediction and resolution • Rapid spacecraft slewing • Gravity gradient effects on spacecraft attitude control • Spacecraft attitude control using magnetic torquers • Attitude control using pulse-width-modulated thrusters A decision of the project topic is on whatever given date (you should discuss the topic with the instructor before making your decision final). A two-page topic proposal is due in class whatever given date. You should submit your proposal to the class website in Blackboard. In the proposal, you should clearly state the problem, why it is important, what has been reported in the literature, what specific topic you propose to address, how you propose to address it and what will be the deliverables of the project. In the case when your proposal is not accepted, you need to submit another proposal. Every other week, you must report to me the status of your project progress. The final report is due on whatever given date. Your final report should provide a summary of your results and conclusions, and be in the format of AIAA conference papers. You can download conference paper template from AIAA website. Your report should not be longer than 10 pages. Within the last two weeks of the semester, you should come to class to give a 15-20-minute presentation on your term project. The schedule of the presentations will be determined by the instructor. Your project will be evaluated on the basis of its compliance with your Sep-12 proposal, the quality of the technical development, its engineering merit, and the quality of the report and the presentation. I will use the following rubric in evaluating your project work. Project Proposal: 10 points Research Quality: 60 points Project Report: 20 points Project Presentation: 10 points. Attendance: Students are required to attend class and must notify the instructor if missing a class is necessary. Tools --> Mathematica + SystemModeler Modelica (https://www.modelica.org/libraries ) Aircraft Dynamics Library Fritzson, P. and Idebrant, A. (2004). Aircraft - A Modelica Library for Aircraft- Dynamics Simulation FlightGear Flight Simulator Supports flight dynamics models like supports LaRCsim, UIUC, YASim and integration with various CAS tools Permits access to control and simulation data Grading --> Attendance 15% Homework 35% Project 50% Course Outline --> • Rigid body motion Orientation Inertial coordinates and body coordinates Rotation matrix and orientation parameterizations Euler angles Axis-angle variables Quaternions Properties of rotation matrices Rotational kinematics Translational kinematics Newton-Euler equations Rotational dynamics Translational dynamics Expressing equations of motion in various coordinate frames • Aircraft equations of motion Aircraft rotational and translational kinematic models Aircraft rotational and translational dynamic models Required model data Aircraft data Aerodynamic data Nonlinear terms Nonlinear approximate models Trimmed flight maneuvers Linearized approximate models Expressing aircraft equations of motion in various coordinate frames Advanced aircraft modeling issues Wind models including wind shear Flexible aircraft and aeroelastic effects • Aircraft control Flight control variables State variables Aero control surfaces and throttle control Output variables Flight control performance measures Handling qualities Structural loads Flight control problems Longitudinal control Cruise Climb rate Airspeed Lateral control Bank angle Coordinated turns Control design methodologies LQG linear control (remember, your are designing aircraft for the real world to perform great, and not for a mathematician’s perversion, so know your priorities) Robust linear control (remember, your are designing aircraft for the real world to perform great, and not for a mathematician’s perversion, so know your priorities) Gain scheduling Time scale methods Feedback linearization and dynamic inversion Advanced aircraft flight control issues Control surface dynamics and limits Aggressive maneuvers (not trimmed flight) Thrust vectoring High angles of attack Tailless aircraft Integrated propulsion and flight control Control configured aircraft Control mixing logic Reconfigurable aircraft • Spacecraft control (possibly but if time left) Spacecraft control models: thrusters, reaction wheels, CMGs Flight control objectives Velocity stabilization Attitude stabilization and tracking problems Spin stabilization Control design methodologies Robust control Lyapunov methods Feedback linearization and dynamic inversion Advanced spacecraft attitude control issues Momentum management Control of flexible spacecraft Dual spin spacecraft Control of spacecraft with articulated appendages Prerequisites: Aircraft Flight Dynamics II, Systems Modelling II, Automatic Control, Modeling & Simulation Lab

Propulsion Systems II: Turbomachinery and combustor design, compressor-turbine matching and off-design engine performance. Introduction to advanced propulsion architectures including scramjets, pressure gain combustion, and electric/hybrid-electric. Typical Texts: Mechanics and Thermodynamics of Propulsion, Philip Hill and Carl Peterson, Addison Wesley Aircraft Propulsion, S. Farokhi, Wiley, 2009. Additional sources: Gas Turbine Combustion, A. Lefebvre and D. Ballal, CRC Press, 2010 Heiser and Pratt. Hypersonic Airbreathing Propulsion. AIAA. 1994. Escher, W. J. D. The Synerjet Engine: Airbreathing/Rocket Combined-Cycle Propulsion for Tomorrow’s Space Transports. SAE International. 1997. COURSE OBJECTIVES --> 1. Familiarize students with the preliminary design and analysis of turbomachinery components found in conventional aircraft engines: compressors and turbines. 2. Explore the concept and procedures for compressor-turbine (gas generator) matching and provide understanding of off-design performance of an engine based on compressor and turbine maps. 3. Familiarize students with the preliminary design and analysis of main combustor found in conventional aircraft engines. 4. Introduce students to advanced propulsion architectures for hypersonic aircraft, and for enhanced cycle efficiency or reduced fuel-consumption in subsonic or transonic aircraft. LEARNING OUTCOMES --> Students will be able to: 1. Provide preliminary design parameters for compressors and turbines and characterize their performance based on a mean line approach. 2. Evaluate the operation and performance of a jet engine based on compressor and turbine maps for different operating conditions. 3. Provide preliminary design parameters and define key design issues, constraints and architectures for main combustors in jet engines. 4. Describe the advantages and drawbacks of various advanced propulsion architectures. TOOLS --> < NASA WATE, pyCycle, Modelica libraries, Modelon Jet Propulsion Library < ICT- Thermodynamic code > < STANJAN > < Autodesk Fusion 360, CATIA > < ANSYS BladeModeler > < other ANSYS solutions > < OpenFoam > ASSESSMENT --> Problem Sets 20% Labs 40% 4 Exams 40% Problem sets --> A mixture of prerequisite review (range i to iv) AND of current course level Labs --> There will be various tasks: -Recital of chosen labs from prerequisite -Extensive use of constituents in TOOLS for course level. Propulsion systems simulations; students should be able to relate analytical modelling with propulsion systems simulations. Ability to relate analytical modelling with curve fittings and mappings. Exams --> Will reflect problem sets and current course lectures TOPIC OUTLINE --> 1. Aircraft Propulsion Review (2 hours) Engine Architectures Performance Characteristics 2. Turbomachinery Design and Analysis (13 hours) Axial architectures, Euler equations & cascade nomenclature (2) Mean line design of compressors & compressor performance (5.5) Cascade flow angles and velocity triangles Single-stage compressor characteristics Blade design considerations Multistage compressors Mean line design of turbines and turbine performance (3.5) Overview, Euler equations and maps Degree of reaction Stage inlet swirl, solidity, losses and other design requirements Blade and disk stresses Compressor and turbine design point procedures (2) 3. Engine Off-Design Performance (6 hours) Gas turbine matching requirements and map scaling (1) Gas generator matching for off-design performance (2) Engine off-design performance (1½) Engine transient response (½) 4. Combustor Design (10 hours) Overview: requirements and rationale for typical features (2) Inlet diffuser sizing & losses, combustor length scaling (1) Fuel atomization and evaporation (2) Ignition (1) Aerodynamics and swirl (2) Controlling emissions (0.5) Heat transfer and liner cooling (1.5) 5. Advanced Propulsion Architectures and Modelling (14½ hours) Scramjets (5) Detonation Engines (6) Oblique (ODE) Rotation (RDE) Electric and hybrid electric propulsion (3½ ) NOTE: for ODE and RDE the concepts are often too difficult to comprehend because the engine/engineering features and dynamic are vague in delivery by many literature. Major goals are to provide: --A transparent and fluid description of the engineering features and engine structure. Hopefully hghly detailed models in literature displays exist. --Good detailed physics < Oxygen-Fuel considerations, Fluid processes, Combustion processes, Thermal processes > that well describe mechanisms and processes, that lead to practical mathematical models and means of solution(s) and detonation dynamic/control --Development of CDF models and simulations w.r.t. to the geometrical specifications to validate the harnessing and effciency of detonative combustion. The following may be some decent literature for ODE (but may not capture all details) --> Pratt, D. T.; Humphrey, J. W.; Glenn, D. E. (1991). "Morphology of Standing Oblique Detonation Waves". Journal of Propulsion and Power. 7 (5): 837–45. M. Valorani, M. Di Giacinto, C. Buongiorno, (2001), Performance Prediction for Oblique Detonation Wave Engines (ODWE), Acta Astronautica, Volume 48, Issue 4, Pages 211-228 Honghui Teng, Yining Zhang, Zonglin Jiang,(2014), Numerical Investigation on the Induction Zone Structure of the Oblique Detonation Waves, Computers & Fluids, Volume 95, Pages 127-131 Kazuya Iwata, Shinji Nakaya, Mitsuhiro Tsue, (2017), Wedge-Stabilized Oblique Detonation in an Inhomogeneous Hydrogen–Air Mixture, Proceedings of the Combustion Institute, Volume 36, Issue 2, Pages 2761-2769 Rosato, D. A. et al (2021). Stabilized Detonation for Hypersonic Propulsion. Proceedings of the National Academy of Sciences, 118 (20) e2102244118 The following may be some decent literature for RDE (but may not capture all details) --> Schwer, D. and Kailasanath, K. (2013). Fluid Dynamics of Rotating Detonation Engines with Hydrogen and Hydrocarbon Fuels, Proceedings of the Combustion Institute, Volume 34, Issue 2, Pages 1991-1998 Eric M. Braun, E. M. et al (2013). Airbreathing Rotating Detonation Wave Engine Cycle Analysis, Aerospace Science and Technology, Volume 27, Issue 1, Pages 201-208 Tsuboi, N. et al (2015). Numerical Estimation of the Thrust Performance on a Rotating Detonation Engine for a Hydrogen–Oxygen Mixture, Proceedings of the Combustion Institute, Volume 35, Issue 2, Pages 2005-2013 Sousa, J., Braun, J. and Paniagua, G. (2017). Development of a Fast Evaluation Tool for Rotating Detonation Combustors, Applied Mathematical Modelling, Volume 52, Pages 42-52 Huff, R., Polanka, M.D., McClearn, M.J., Schauer, F.R., Fotia, M.L., & Hoke, J.L. (2019). Design and Operation of a Radial Rotating Detonation Engine. Journal of Propulsion and Power. Ma, J. Z. et al (2019). Experimental Investigation on Delay Time Phenomenon in Rotating Detonation Engine, Aerospace Science and Technology, Volume 88, Pages 395-404 Koch, J. and Kutz, J. N. (2020). Modelling Thermodynamic Trends of Rotating Detonation Engines. Physics of Fluids 32, 126102 Koch, J., Kurosaka, M., Knowlen, C. and Kutz, J. N. (2020). Mode-Locked Rotating detonation Waves: Experiments and a Model Equation. Phys. Rev. E 101, 013106 Prerequisite: Propulsion Systems I Rocket Propulsion Analysis and design of a broad range of space vehicle propulsion options including solid, hybrid, liquid, combined-cycle, and advanced propulsion systems The objectives of this course are to introduce the student to the basics of propulsion system analysis and performance prediction for a wide range of space vehicle propulsion options. Emphasis will be placed on propulsion system selection and application of propulsion analysis to vehicle-level design. Specifically, the goals are to: a) Teach the student basic performance prediction methods for liquid and solid rocket engines. b) Familiarize the student with a variety of space vehicle propulsion options and components and the advantages and utility of each. c) Expose the student to the terms and methods used in the rocket propulsion field. Typical Text --> Brown, Charles. Spacecraft Propulsion. AIAA. 1995 References --> Hill and Peterson. Mechanics and Thermodynamics of Propulsion. Addison-Wesley. 1992. Huzel and Huang. Modern Engineering for Design of Liquid-Propellant Rocket Engines. AIAA. 1992. de Laco Veris A. (2021) Fundamental Concepts on Liquid-Propellant Rocket Engines. In: Fundamental Concepts of Liquid-Propellant Rocket Engines. Springer Aerospace Technology. Springer, Cham. Computer Usage --> Students will be required to access a personal computer or workstation to complete computing project assignments. Suitable computers can be found in the school and Institutes computing laboratories and in research laboratories. In addition, in-class instruction will rely on classroom computers and projection equipment. Tools --> < ICT-Thermodynamic code > < NASA CEA, GUIPEP + PROPEP, Burnsim > < STANJAN > < OpenFOAM, Cart3d > < Nasa software catalogue (https://software.nasa.gov/software) > < OpenRocket Simulator, ROCETS from NASA software catalog > < SystemModeler, Modelica > Projects --> There will be five assigned computer projects. In some cases, the assignments can be completed on a spreadsheet. 1. Assuming a supersonic rocket nozzle. Use isentropic flow equations to determine the internal pressure along the inside of a given nozzle vs. nozzle length. Create plots to show that thrust is maximized for an ideally expanded nozzle. 2. Modelling and simulation of a supersonic convergent-divergent nozzle -Expected to have involved at least: Development of supersonic convergent-divergent nozzle in CAD to apply to CFD -Isentropic equations (with consideration of phases in mixture, condensed phases and so forth). Integration of nozzle geometrical parameters in the isentropc equations is essential. -Continuity model and conservation/flow model Can one determine if findings in (1) is consistent with supersonic convergent-divergent nozzle simulation prior, assuming that the geometrical parameters from (1) is equivalent to CAD model prior? 3. For a given tubular solid rocket motor configuration, write a program to calculate internal pressure and regression rate vs. time. Create plots of overall motor thrust and Isp vs. time. 4. Using simple rocket engine performance equations, determine the effect of chamber (inlet) pressure on the thrust and Isp of a nitrogen cold gas thruster. Create a graph of Isp, thrust, and Cf vs. pressure. 5. Given pump and turbine efficiencies, create a simple cycle balance model for a given liquid engine. Create plots of thrust, Isp, turbine work, NPSH, and pump rpm vs. throttle setting. 6. For a given ascent flight path of an RBCC-powered launch vehicle, calculate the thrust coefficient and the Isp produced by the combined-cycle engine. Plot the results vs. flight Mach number NOTE: projects are subject to change each term. Labs --> Labs are different from computer projects. Some instruction in labs may be more intricate and technical than lectures. Analytical modelling will be precursor to software usage or code development. --Modelling rocket trajectory (single and multistage) with relevant air resistance --Rocket aerodynamics modelling. Rocket aerodynamics simulation --Characteristics of concern: density, melting point, boiling point, auto-ignition temperature, adiabatic flame temperature, mass fraction of condensed-phase products, exhaust products, effective molecular weight of exhaust products. Models governing the characteristics of propellants. Followed by software use to acquire profiles. --M. El-Naggar et al (2020). Experimental Investigation of Star Grains in Dual Thrust Solid Propellant Motors. IOP Conference Series: Materials Science and Engineering 973 012001 The primary goals are developing Figure 19, Figure 20, and making sense of Figure 30 --Students to be given instruction to develop profiles of chosen solid propellant rockets concerning Rocket motor structure (with convergent-divergent specifications) Physical design (static stability, aerodynamics) Propellant characteristics subject to rocket motor size Simulating rocket trajectory Note: analytic modelling will be precursor to profile development with multiple software. Grading --> Homework 10% 5 Computer Projects 25% 5 Labs 25% 4 Exams 40% Course Outline --> 1. Introduction (1 hr.) - course overview, syllabus, grading, etc. 2. Rocket Engine Basics (6 hrs.) - calculation of rocket thrust via momentum equation - thrust model based on rocket motor geometry parameters ( https://www.grc.nasa.gov/WWW/K-12/rocket/rktthsum.html ) and propellant characterstics (two-phase flow if general) - definition of Isp (condensed formula, and expression in terms of prior), thrust coefficient (Cf), characteristic velocity (c*), and expansion ratio - ideal expansion, over/under expansion - computer project 1 - typical nozzle designs (cone, bell, plug) - sources of losses (frozen vs. equilibrium flow, divergence, etc.) 3. Rocket Nozzle Flow (6 - 8 hours) Greatrix, D., R., Rocket Nozzle Flow. Powered Flight: The Engineering of Aerospace Propulsion, Springer, pages 303 - 315 Majdalani, J., and Maicke, B., A. (2013). Direct Calculation of the Average Local Mach Number in Converging–Diverging Nozzles, Aerospace Science and Technology 24, 111–115 Xu, J., and Zhao, C. (2007). Two-Dimensional Numerical Simulations of Shock Waves in Micro Convergent–Divergent Nozzles, International Journal of Heat and Mass Transfer 50, 2434–2438 4. ICT- Thermodynamic code (6 - 8 hrs.) NOTE: focus will be towards situating solid propellants, hybrid propellants, liquid bi-propellants, hydrazine and hydrogen peroxide, respectively -Will like explicit observation of the formulas and how they are related to each Mass action and mass balance expressions to calculate thermal equilibria Chemical equilibria Analytical recognition of models/formulas for thermodynamic and thermochemical parameters for: Condensation Chemical processes with regard to combustion Pyrolysis Gasification/vaporization -Calculation for the heat of explosion -Determination of the parameters for gas detonations -Means of sftware development with logistics. Development of code and implementation to compare with STANJAN and NASA CEA (for solid propellants, hybrid propellants, liquid bi-propellants, hydrazine and hydrogen peroxide). 5. Solid Rocket Motors (8 hrs.) - propellant types (characteristics -- trades) - effect of grain cross section shape (thrust shaping) - propellant burninglaw (regression vs. pressure) - computer project 2 - Richard Nakka. Solid Rocket Motor Theory. Richard Nakka’s Experimental Rocketry Website < https://www.nakka-rocketry.net/th_pres.html > < http://www.nakka-rocketry.net/th_nozz.html > - from the first source prior the rate of change of chamber pressure model, namely equation 10 or 13, to verifying it’s solution to be equation 14 with consideration of various gases (specific heat ratio). Furthermore, there’s the following dilemma of two-phase flow: https://www.nakka-rocketry.net/th_2phf.html Hence, means to amend equation 14 from first source to be pursued. - Revisiting specific impulse. Will find a sensitive model for specific impulse, based on incorporation of motor geometry parameters: https://www.grc.nasa.gov/WWW/K-12/rocket/rktthsum.html and propellant characterstics (two-phase flow if general) - Adiabatic flame temperature (AFT) Determination for various propellants - STANJAN for AFT 6. Hybrid Rocket Propulsion (6 - 8 hrs.) - common propellant combinations and configuration - system performance characteristics (advantages -- trades) - combustion theory Some references: Chiaverini, M. J. (2000). Fundamentals of Hybrid Rocket Combustion and Propulsion. American Institute of Aeronautics and Astronautics. Chelaru, T., & Mingireanu, F. (2011). Hybrid rocket engine, theoretical model and experiment. Acta Astronautica, 68(11), 1891-1902. - Netzer, D. W. et al (1972). Hybrid Rocket Internal Ballistics. Chemical Propulsion Information Agency. John Hopkins University. AD-754 769 < https://apps.dtic.mil/dtic/tr/fulltext/u2/754769.pdf > - Recallng the Isp sensitive model developed in module 5. Despite the equivalent inputs for both solid and hybrid cases, why is Hybrid Isp greater than Solid Isp? - For hybrid propellants will the adiabatic flame temperature (AFT) formula be different to solid propellants? Can STANJAN still work? 7. Monopropellant Thrusters (4 hrs.) - overview of small pressure-fed thrusters - cold gas (N2) thrusters - computer project 3 - resisto-jet thrusters - hydrazine/catalyst thrusters - hydrogen peroxide thrusters Cervone, A. et al (2006). Development of Hydrogen Peroxide Monopropellant Rockets. 42nd AIAA/ASME/SAE/ASEE Joint Propulsion conference & Exhibit: < https://www.esa.int/gsp/ACT/doc/PRO/ACT-RPR-PRO-JPC2006-HP%20Rockets%202006-5239.pdf > Jung, S. et al (2021). Scaling of Catalyst Bed for Hydrogen Peroxide Monopropellant Thrusters using Catalytic Decomposition Modelling. Acta Astronautica 187, pp 167 – 180 - Acceptable purity of hydrogen peroxide is what percentage. Why? Chemistry to validate. - A task will concern given compounds to determine whether they are good or poor catalysts or non-reactive with hydrazine and hydrgen peroxide 8. Bipropellant Liquid Rocket Engines (11 hrs.) - thermodynamics of liquid rocket engines - common propellant combinations (storable, cryogenic c*) - engine cycles (gas generator, staged combustion, expander, etc.) - turbomachinery design (pumps, turbines, impellers, etc.) - computer project 4 - modelling and control (control valvels pumps, turbines, impellers, etc.) - other engine components (ignitors, GG, cooling loops, etc.) - why is Liquid Isp greater than Hybrid Isp? Can such be proven based on ICT-Theromodynamic Code, rocket motor parameters and propellant characteristics? - historical examples and state-of-the-art - Based on prior feature topics in this module will try to simulate a Bipropellant liquid rocket engine to best of ability. First, the ICT-Thermodynamic code will be applied. Can we compare findings to NASA CEA and so forth? Second, the components: tanks, pipes, valves (turbo)pumps, injectors, ingitors, etc., etc. Will try to pull this off with SystemModeler, Modelica, COCO (+ ChemSep), DWSIM (+ ChemSep), ESMO simulator, STANJAN. Note: if you can set pumps to necessary operational specifications you can imitate turbo-pumps behaviour. Note: turbopumps have to precisely and efficiently pump the intially separated two fluids of different propellants in precise ratios at very high volumetric flow rates, often cryogenic temperatures; highly volatile properties while combusting in combustion chamber. Will pursue modelling and controller development for all essential components mentioned, w.r.t. to the necessary operational specifications. Will also entertain tuning issues, etc., etc. Our simulations will inevitably diverge a bit from the two following guides: C. L. L. Wei, X. Gang, D. Jing, Z. Haiming, Y. Hao, "Modeling and Simulation of Liquid Propellant Rocket Engine Transient Performance Using Modelica," presented at the Proceedings of the 11th International Modelica Conference, Versailles, France, September 21-23, 2015. Naderi, M., Liang, G. and Karimi, H. (2017). Modular Simulation Software Development for Liquid Propellant Rocket Engines based on MATLAB Simulink. MATEC Web of Conferences 114, 02010. Check references in article. The hardest part (if needed) may be integrating a well-designed nozzle with convergent-divergent supersonic effects involving Mach value dynamics (if necessary). Or somehow making the explicit formulas (involving the propellant and rocket motor parameters) relevant in the simulation, to lead to accurate thrust. If given articles are not transparent about such, then, one can pursue means of harmonically integrating the dynamics of the simulated liquid systems described in prior articles with the supersonic convergent-divergent nozzle simulation from project 2. Curves of controllers or characteristic curves (or signals or whatever) all should sync well. Again: we’re not in the business of looking like copycats with MATLAB code, so another software like SystemModeler/Modelica would be appreciated. As well, various types of sensors may not be implemented in our simulations, yet, one will have to consider their incorporation to know pre-conditions for launch approval, and conditions during different stages in launch. Propellant temperatures requirements for high performance Pressure readings for fuel tanks (and possibly for various terminals and passages) Combustion chamber data. Hence, to develop a scheme involving the different types of sensors, how they are oriented within the rocket, processing systems for sensors, power sources for sensing and processing, and a telemetry scheme. Concerns for throttle-downs and throttle-ups autonomously. How are such executed, and what systems apply to conduct such? 9. Combined-Cycle Propulsion (6 hrs.) - thermodynamics of high-speed airbreathing propulsion - review of ramjet and scramjet propulsion - rocket-based combined-cycle propulsion (RBCC) Czysz, P. A. and little, M. J. (1993). Rocket-Based Combined-Cycle Propulsion (RBCC) – a Propulsion system for the 21st Century. 5th International Aerospace Planes and Hypersonics Technologies Conference - computer project 5 10. Advanced Propulsion (4 - 6 hrs.) - Daedalus, solar sails, etc. - Electric/ion propulsion (electric or nuclear) - Rotating detonation engines - Nuclear thermal rockets Prerequisites: Numerical Analysis, Heat Transfer, Compressible Flow MECHANICAL ENGINEERING PARTICULARS --> Fluid Machinery There is a vast and in-depth discipline involved in fluid machinery, rather than the belief that such study and skills are “Jurassic” and fully determined from an old era. Will establish high consistency among texts. Note: course will not be focused soley on liquids. Note: prerequisites are prerequisites...so keep that in mind. As well, I don’t expect you to be infants with some of the mentioned tools and technologies. This is engineering, neither brat city nor shielded and pampered candy@55e5. Furthermore, throughout the advancement of the other realms of engineering (aerospace, civil, industrial, electrical, computer, etc.) development would not be possible without a foundation or facility of mechanical engineering. And yes, even computer engineering, say, for example, you need to drive off heat somehow (which may be a soft example). As well, some aspects of this course also translate to liquid rocket engine design and development (being premier at this time). NOTE: course will not apply a single text. Example References --> Xu. J. et al. (2009). Fluid Machinery and Fluid Mechanics. 4th International Symposium (4th ISFMFE). Springer-Verlag Berlin Heidelberg Dixon, S. L. and Hall, C. (2013). Fluid Mechanics and Thermodynamics of Machinery. Butterworth-Heinemann Kim, KY. And Samad, A. and Benini, E. (2019). Design Optimization of Fluid Machinery: Applying Computational Fluid Dynamics and Numerical Optimization. Wiley. Rogers, G. F. C. et al. (2017). H. Cohen, P.V. Straznicky, and A.C. Nix, Gas Turbine Theory, Pearson Education. D. Japikse and N.C. Baines (1997). Introduction to Turbomachinery, Concepts-NREC Inc./Oxford University Press. Nguyen-Schäfer, H. (2012). Rotordynamics of Automotive Turbochargers. Springer-Verlag Berlin Heidelberg Tools --> Open Source << OpenProp >> << CAESES, Onshape, Salome (+ Netgen + Gmsh), Open Cascade - Technology, FreeCAD >> << OpenFoam, Cart3d >> << there exists open source FEA tools as well >> Proprietary << Autodesk Fusion 360, CATIA, ANSYS SpaceClaim >> << ANSYS (FLUENT, CFX, BladeModeler) >> << Patran + Nastran, Ansys >> Critical Development --> 1. Design approaches for various types of props 2. Design approaches and applications in the areas of pumps, turbines, compressors, and other fluid machinery systems to be clearly explained. 3. Methods and correlations which can be used in preliminary aerodynamic design (for general fluid machinery). 4. Mechanical design aspects (centrifugal stress, creep, durability, vibrations, etc.) 5. Numerical Methods and Numerical Simulations 6. Verification and Validation Techniques Labs --> Labs will be based on the Critical Development description prior, and Tools mentioned earlier. Physocs, mathematics and engineering concepts will be supportive of development in a tangible, fluid, constructive and sustainable manner. Meaningful to engineering development. Grading --> Homework Labs 3-4 Exams Course Topics --> WEEK 1 – 2 Introduction. Types of turbomachines. Dimensional analysis and similarity: application to incompressible and compressible flow machines. WEEK 3 Operating points. Selection of turbomachine type and size: specific speed and specific size. Cavitation: net positive suction head, suction specific speed, Thoma cavitation parameter. WEEK 4 – 5 Energy transfer between fluid and rotor: steady flow energy equation. Angular momentum equation. Euler pump and turbine equation. Degree of reaction; velocity triangles. Stage design parameters: work and flow coefficient. WEEK 6 Axial-flow compressors, fans and pumps: description; advantages and disadvantages; analysis and design considerations. Cascade methods: Howell’s correlations; North American practice. European Practice. WEEK 7 Blade-element methods. Loss mechanisms. Off-design performance: surge and stall. Multistage axial-flow compressors: stage stacking. WEEK 8 – 9 Axial-flow turbines: description. Stage characteristics. Design and analysis: cascade methods. WEEK 10 Centrifugal compressors, fans and pumps: description; advantages and disadvantages; analysis and design considerations. Head-capacity relations. WEEK 11 Slip and losses. Surge. Diffuser and volute design considerations. WEEK 12 - 13 Turbomachinery design for gas turbine engines: stages of the design process; analytical tools. Current design issues. Turbopumps for liquid propellant rocket engines (good literature for strong and well rounded development will be provided). Includes CFD runs. WEEK 14 - 16 Review and/or reinforcing past topics and labs Prerequisites: Numerical Analysis, Practical Programming in C for Engineering II, Fluid Mechanics. Finite Element Methods This course will train you to analyse real world structural mechanics problems using the finite element method. You will be introduced to the mathematical basis of finite element analysis, on which nearly all structural analysis software is built. You will learn how to apply commercially available finite element software to solve real-world engineering problems. The course will cater to the specific challenges of engineers across all mechanical disciplines (Aerospace, Manufacturing, Mechanical, Mechatronic, Automotive and Naval). The primary aim of this course is to train you to solve complex engineering structural mechanics problems with finite element analysis. The course will provide deep insight into the operation of finite element analysis software by teaching you the underlying computational methods involved. You will be taught to execute a detailed finite element study including planning, modelling, meshing, solving, evaluating results and validating against real world data. At the conclusion of this course, students should be able to: 1. Apply fundamental finite element analysis techniques to solve simple engineering problems 2. Explain the underlying mathematics behind finite element analysis software solvers 3. Plan and execute appropriate finite element analyses to solve a range of solid mechanics and other engineering problems. 4. Perform a detailed finite element study to investigate a real-world engineering problem This course includes two face-to-face teaching methods: 1. Lectures to introduce fundamental finite element analysis concepts 2. Software laboratories to apply fundamental concepts in common finite element analysis packages Aerospace Engineering employers request that the students are familiar with Patran/Nastran whereas ANSYS is more appropriate for Mechanical Engineers. The school supports both ME andAE packages and will for the foreseeable future. For Aerospace Engineering students, tools such as OpenVSP (and others) will serve well for 3D pre-development towards FEA; bring your A game in such if you want to thrive here with aerospace interests (no pre-setups). As weell, you will be expected to develop aircraft components for FEA. Typical Texts --> Cook, R. D., Malkus, D. S., Plesha, M. E., Witt, R. J. (2002). Concepts and Applications of Finite Element Analysis, 4 th Ed, John Wiley & Sons Chandrupatla, T. R., Belegundu, A. D. (2011) Introduction to Finite Elements in Engineering, 4th Ed, Prentice Hall (Pearson) All submissions are expected to be neat and clearly set out. Calculations, where they are necessary, should be shown professionally in any report; scans of hand calculations will not be accepted. The submission of online material should follow the instructions given on the appropriate Moodle page. Late submissions will receive zero marks but should still be submitted. It is always worth submitting late assessment tasks when possible. Completion of the work, even late, may be taken into account in cases of special consideration. In addition to any criteria specified in the assignment hand-outs, the following criteria will be used to grade assignments: Reports --> For reports: Identification of key facts and the integration of those facts in a logical development. Clarity of communication: this includes development of a clear and orderly structure and the highlighting of core arguments. Sentences in clear and plain English: this includes correct grammar, spelling and punctuation. Correct referencing of source materials. For numerical calculations: Accuracy of numerical answers. Use of diagrams, where appropriate, to support or illustrate the calculations. Use of graphs, were appropriate, to support or illustrate the calculations. Use of tables, where appropriate, to support or shorten the calculations. Neatness. Assignment 1 –> FE Fundamentals Finite Element Analysis is numerically intensive and is exclusively solved by powerful computers for all real engineering problems. Modern software packages hide the majority of complex tasks from the user. Unfortunately, this level of automation can lead to the false belief that FEA is an infallible tool. It is important that you as an engineer understand the computations being conducted on your behalf in order to understand their limitations and possible errors that can appear in your analyses. This assignment will teach you the fundamentals of the Finite Element Method through hand calculations and simple programming. Assignment 2 –> Good FE Practice Proper planning, execution and reporting of analyses are crucial skills for any engineering graduate. When using FE analysis techniques to solve and report on a problem, there are countless opportunities to exercise poor technique. At best, poor technique detracts from the quality of the solution and at worst leads to dangerous or negligent results. During this assignment you will study a very simple engineering problem using FEM but will learn best practice techniques to ensure you produce high quality results and write an excellent report. Major Project --> A flexible major project will be given to you at the beginning of semester and will form the largest component of the assessment for the course. The topic of the project will be up to you to decide, but must represent a current FE simulation challenge in the scientific literature or from a relevant engineering discipline. The assessment will be broken into pieces to ensure that adequate progress is being made throughout the semester: Topic selection guidance and approval (Friday Week 5) A topic title and 200 word outline will be submitted to the demonstrators for approval by Week 5. Must be submitted and passed to progress Draft findings (Friday Week 9) A small report will be submitted by Week 9 with preliminary findings, which will be peer assessed. The peer-assessment process will be worth 10 of the 50 marks for the major project. Exam Question (During mid-session) One question of the mid-session exam will be devoted to your major project. This question will assess the depth of your understanding of the FE method you are applying for your major project. FE Fundamentals Exam --> A mid-session exam will use a combination of short answer questions, derivations and long form calculations to test your understanding and application of FE fundamentals. Drading --> Assignment 1 – FE Fundamentals 10% Assignment 2 – Good FE Practice 10% Major Project 50% FE Fundamentals Exam 30% Topic Outline: WEEK 1 – Introduction to FEM --> Introduction to FEA; Discretisation; FE Terminology; Stiffness Matrices for Bars, Trusses and Beams; Element Library Introduction. WEEK 2 – Numerical solution Procedure --> Applying Loads and Boundary Conditions; Assembly; Solving for Nodal Displacements; Constitutive Laws; Interpolation of Stress and Strain Week 3 – The Element Library --> 2D Triangles and Quads; Shells; 3D Tets and Hexes; Solid Shells; Isoparametric Elements; Quadratic and Higher Order Elements; Benefits and Limitations of Different Element Types Week 4 – Good Fe Practice --> A General FE Problem Solving Approach; Modelling Assumptions; Meshing Strategy; Convergence; Validation; Sources of Error in FE; Computational Resources; Interfacing with CAD; FE Reporting WEEK 5 – Buckling and Nonlinear Analysis --> Eigenvalue Solutions; Linear Buckling; Material Non-linearity; Geometric Non-linearity and Buckling; Iteration Schema and Incremental Analysis; Contact WEEK 6 – Vibration and Transient Analyses --> Modal Analysis; Harmonic Analysis; Other Vibration Solutions; Transient Solutions and their Applications; Choice of Time Discretisation WEEK 7 – Mechanisms and Rigid Dynamics; Modelling Composites; Thermal Analyses; Fluid Structure Interaction; Magnetostatics; Soil Modelling WEEK 8 – 10 Clearing things. Up Wrap Up, etc. AE Prerequsites: Calculus III, Numerical Analysis, General Physics I & II, Mechanics of Materials Lab, Aircraft Theory, Aircraft Design ME Prerequisites: Calculus III, Numerical Analysis, General Physics I & II, Machine Design I & II, Mechanics of Materials Lab Powertrain Design Design of powertrain systems including piston ring assembly, combustion and induction systems, and transmissions. Performance emission trade-offs with emphasis on emission control. Detailed design study required Typical Text: Introduction to Internal Combustion Engines, Third Edition, Society of Automotive Engineers Reference: Willard W. Pulkrabek, Engineering Fundamentals of the Internal Combustion Engine, 2nd Edition, Pearson Prentice Hall Topic Outline --> 1. Valvetrain Systems 2. Induction Systems 3. Combustion Chamber Design 4. Induction & Exhaust System Design 5. Flow Losses in Internal Flow Systems 6. Turbo/Super-Charging 7. Sound & Noise in Intake/Exhaust Systems Labs --> * Mathematics, physics and engineering principles will support such lab activities. Students are responsible for proper referencing and identification with such three components, and relevant to observed data as well. *Observation of random actual powertrains, where students will be responsble for various analyses/predictions based on features. There will be 5 – 8 labs with the following analysis software tools for design, operating parameters, quantitative modelling of physical measures, critical modelling, operations analysis, operational curves, etc: ANSYS NASA WATE OpenWam SystemModeler Modelica Libraries (https://www.modelica.org/libraries ) Course Major Objectives --> -Knowledge of basic engine operating principles and definition of performance parameters. -Detailed understanding of engine valvetrain design and valve timing effects on performance, fuel efficiency, and emissions trade-offs. Variable Valve Timing (VVT) schemes. -Intake and Exhaust System Tuning Methods for commercial and racing applications; Helmholtz Resonator Theory. Effects of engine design parameters and operating conditions on performance and fuel efficiency. -Quasi-One-Dimensional Modelling theory and application. – learn and apply a commercial CAE code to optimize IC engine tuning and cam phasing. -Develop written and oral technical presentation skills through homework and team semester projects involving application of practical CAE analysis tools. -Understanding of Variable Induction (VIS) and Exhaust (VES) System Design Alternatives -Knowledge of flow losses in engine intake and exhaust systems; Basic definitions and design parameters of importance. Develop ability to calculate pressure drop across real world intake and exhaust systems. -Modelling combustion and heat transfer. Knock and octane effects. -Basics and Modelling of Turbo- and Super-Chargers -Knowledge of induction and exhaust noise generation; Basic definitions of sound. Resonator and Muffler designs. Prerequisites: Internal Combustion Systems Powertrain Control Systems Course covers essential aspects of electronic engine control followed by recent control problems arising in direct injection, variable valve timing, active boosting, and flexible-fuel combustion. The course includes models and feedback control design of spark ignition (gasoline), compression ignition (diesel), and thermal ignition (HCCI) engines. We will practice system identification, averaging, feedforward, feedback, multivariable control, and estimation. Course demands a 17-week schedule for this engineering course. * Basic ordinary differential equations (ODE) and control requirements are necessary. ** Mathematica and SystemModeler experience would be nice ***Modelica Libraries References --> Introduction to Modelling and Control of Internal Combustion Engine Systems" by L. Guzzella and C.H. Onder, Springer-Verlag Modelling and Control of Engines and Drivelines (Automotive Series)" by Lars Eriksson and Lars Nielsen Modelica articles --> Batteh, J. J., Tiller, M. and Newman, C. E. (2003). Simulation of Engine Systems in Modelica., Proceedings of the Third International Modelica Conference Newman, C. E. Batteh, J. J. and Tiller, M. (2002). Sparked-Ignited-Engine Cycle Simulation in Modelica . Proceedings of the Second International Modelica Conference, Proceedings, pp. 133 – 142 Note: There’s also compression ignition (certain Modelica libraries) The following is a list of the Math and Controls skills that will be employed a lot in the class and you should know --> 1. Ordinary Differential equations 2. Linearization 3. Laplace and transfer functions (poles, zeros, DC gain) 4. Frequency Domain Representation of systems and signals: bandwidth, roll-off rate, DCgain, natural, damped frequencies 5. Stability, characteristic equation, eigenvalues 6. Time responses, overshoot, undershoot, settling time, damping ratio, time constant, rise time ... 7. States, state-space representation 8. Basics of PID controllers, Root locus Tools --> Mathematica SystemModeler Modelica Libraries (https://www.modelica.org/libraries ) ANSYS OpenWam Homework --> Assignments will be standard problems and exercises. Homework also serves to make one strengthen or reinforce their skills with simulation tools (voluntarily). Labs --> Labs serve to reinforce lectures and homework assignments. Will involve high amounts of system modelling, control. Following such analytical development will be simulation and reconciling analytical development with simulations. There will be 1 preliminary lab concerning introduction and setting up tools. There will be 5 labs based on the major topics (and subtopics) in chapter 3. Exams --> Exams will be based mostly on lectures and homework. Exams will be open notes with calculator and what not. There will be three exams Powertrain Control Module Field Activity & Report --> If you don’t experience this intimately now who knows if you ever will in the future. Concerns a bit of time spent at a modern mechanic facility (hopefully one lets us in). Concerns mainly analysing PCM design and makeup, inspection and (reprogramming) the PCM. All will be interactive. Notes and data accumulation will be invaluable. Students must develop reports on how their course learning applies to the role of the PCM. Engineering, mathematics and control will be held in regards in reports; your notes and data must establish tangibility with engineering, mathematics and control. What powertrain control development with designated tools from lab can be related to PCM activity? NOTE: students must keep fresh with their knowledge and skills from prerequisites. Assessment --> Homework 10% Labs 25% 3 Exams 45% Powertrain Control Module Field Activity & Report 20% Topic Outline --> Chapter 1: Background and Motivation Chapter 2: Control Oriented Modelling – Manifold Filling Dynamics The Basics: Ideal Gas Law, Mass Conservation, Energy Conservation The Assumptions: Space-averaging and Cycle-averaging The Fidelity: Detailed and Mean-Value Models Event-averaging in time- and crank angle-domain Regression and mapping data Linearization Chapter 3: Basic Internal Combustion Engine Control Functionalities Air-to-Fuel Ratio Control The Fast Response: Feedforward Control with Air Charge Estimation The Accurate Response: Feedback with Oxygen Sensors (Linear and switching sensor) The Balanced response: Cylinder-to-cylinder Maldistribution (Lifting Control technique) Idle Speed Control The Three Devils: Unmeasured Disturbance, Actuator Authority, and Model Uncertainty The Three Tools: Feedforward and Feedback Spark Compensation—sequential loop closing Spark Timing Control The Easy Way: The Look-Up Table The Right Way: Feedback with Knock Sensor The Amazing Way: Combustion sensing, Estimation and HCCI control Exhaust Gas Recirculation External EGR Control Internal EGR Control Control of Variable Camshaft Timing and Variable Valve Timing Boosting The standard: Control of Wastegate The challenge: Coordinated control of VGT and EGR The fun: Optimal Control of Electrically Assisted Turbocharging Chapter 4: Control of Advanced Combustion Engines Lean Combustion & Exhaust Aftertreatment Control Ethanol-Gasoline Flex Fuel Vehicles (FFV) Low Temperature Combustion Control (HCCI, PCCI, PCI) On-board Diagnosis Chapter 5: Drive Cycles for Fuel Efficiency Estimation Powertrain Control Module Field Activity & Report Inspection (re)Programming Prerequisites: Systems Modelling I & II, Feedback Control, Modelling & Simulation Lab, Internal Combustion Systems, Powertrain Design Automated & Automatic Drivetrain Students will learn to analyze codes, diagnose problems, rebuild, repair and properly maintain Allison Automatic and other automated shift truck drivetrains in a professional setting. RATIONALE: Medium and heavy duty truck drivetrain systems used in transportation vehicles have many different designs and thus learning to diagnose and repair problems within these systems has always been an important part of Diesel service. However, with the advancement of integrated onboard electrically and electronically automated drivetrain systems, a new era of Drivetrain Technology service has arrived. A Diesel technician’s required skill set must include traditional repair of HD Truck drivetrains as well as an introduction to the latest technology in automatic and automated drivetrain systems and their repair. This course having active engagement in the perspective of a technician’s comprehensive repertoire for advanced automated and automatic drivetrain systems as well as their control system, diagnostic analysis and service. VERSATILITY IN EDUCATION: The majority of vehicles on the road are passenger vehicles, hence some level of expertise in this segmentation will prove invaluable. Course doesn’t concern pursuing a technician career, however, a (mechanical) engineer needs to be relevant with productive or industrial skills; this is the same as saying “don’t make computer scientist out to be a computer engineer”. Assessment --> 20% homework and assignments grade average 30% quiz, test and exam grade average 30% shop/safety & lab grade from rubric 20% attendance grade from the following rubric A 5% perfect attendance bonus may be awarded to the attendance rubric score dependent upon lab rubric scores. Assignments --> Unique to standard homework, at certain phases of course students will be responsible for developing assigned simulation concerns in SystemModeler and what not. Accompanying such will be mathematics and control related to the physics and engineering. Will make use of texts and handbooks in tools categorization and texts from academic texts categorization. Quiz, Test and Exam --> Quizzes, tests and so forth will have TWO INDEPENDENT components. One being analysis skills based on the “technician/mechanic” perspective. The other being independent engineering academic interests. Course may require up to 18 weeks. Course Objectives --> 1. Work safely in the shop/lab without harm to oneself or other students. 2. Gain the skill of tool usage through the hands on use of the student’s tools and equipment/tools supplied by the college. 3. Perform heavy duty truck automated clutch adjustment, disassembly, inspection, and assembly. 4. Identify internal/external and integrated parts for automated clutches, transmissions, driveline and differentials. 5. Properly diagnose component fault codes and component failures for both automated and automatic transmissions. 6. Explain the function and theory of automated clutches, transmissions, drivelines, driveaxles and differentials. 7. Gain technical skills by disassembling, inspecting, and assembling automatic transmissions, driveline and driveaxles. 8. Properly diagnose component failures by performing 3 and 7 above. 9. Use industry specialty tools in 3 and 7 above. 10. Diagnose electrical and electronic failures or fault codes in direct drive automated transmissions. 11. Properly use EST’s to diagnose and analyze electronic and mechanical failures for 10 above. 12. List and master use of proper terminology for automated clutches/transmissions. 13. List and master use of proper terminology for electronic and hydromechanical automatic transmissions Tools --> Automotive Technician/Mechanic Facility and its tools A modern technician’s handbook with emphasis on automated & automatic drivetrains, power transmissions and drivetrains. Heavy Duty Truck Systems (Fifth Edition), Authors: Bennett and Norman Mathematica and SymstemModeler Modelica packages Academic Texts --> Naunheimer, H. et al. (2011). Automotive Transmissions. Springer-Verlag Berlin Heidelberg Chen H., Gao B. (2014) Introduction. In: Nonlinear Estimation and Control of Automotive Drivetrains. Springer, Berlin, Heidelberg Fischer, R. et al. (2015). The Automotive Transmission Book. Springer International Publishing Petuya, V., Pinto, C. and Lovasz, E. (2014). New Advances in Mechanisms, Transmissions and Applications. Springer Netherlands Dobre, G. (2013). Power Transmissions. Springer Netherlands Major activities that will occur during class time --> - Disassembly, inspection and proper assembly of clutches, transmissions, driveline and differentials. - Hands on learning with Truck/car clutches, transmissions, driveline and differentials. - Businesses with power train equipment NOTE: discipline, organisation, planning and logistics are essential in the automotive industry. Concerns --> Personal Protective Equipment Motivation, Attitude & Desire Oral Communications House Keeping Workmanship Teamwork Talent, Aptitude & Confidence Tool Usage Safety Conduct (Habits) Time management NOTE: Attendance, punctuality and conduct will be brutally influential on students’ grading assessment TOPICAL UNIT OUTLINE--> I. Shop and Personal Safety A. Housekeeping (atmosphere-ventilation) B. Body coverings and personal protective equipment C. Lifting and carrying procedures D. Safety and computer record keeping E. Fire safety and proper extinguishing F. Hazardous materials laws and personal protection (employer/employee responsibilities) II. Tools and Fasteners A. Hand tools – techniques and professional ownership B. Power tools – Air and Electric C. Precision tool accurate reading, techniques and care D. Service and diagnostic literature E. Fasteners – grade, size and systems F. Advantage and Disadvantages G. Thread care and chemicals III. Torque Converters A. Torque converter construction B. Principles of operation C. “Technician” procedures for torque converter service D. Maintenance and service of torque converters E. Build customer relationships for troubleshooting F. Perform preventive maintenance G. Technician overhaul procedural guidelines IV. Automatic Transmissions and Their Service A. Planetary gearing and gear train configurations B. Technician procedures for transmission service C. Technician procedures for transmission overhaul D. Transmission hydraulic component service and replacement E. Governor trouble shooting and repair F. Clutch failure analysis G. Build customer relationships for troubleshooting H. Perform preventive transmission maintenance I. Technician overhaul procedural guidelines V. Electronic Automatic Transmissions A. CEC transmissions & gear train configurations B. Technician procedures for transmission service C. Modular component service and replacement D. Electronic trouble shooting and repair E. Modular failure analysis F. Introduce Cat CX and Voith DIWA (or whatever alternatives) G. Perform preventive transmission maintenance H. “Technician” overhaul procedural guidelines VI. Electronically Automated Standard Transmissions A. Autoshift/Ultrashift automated transmission id B. Geartrain configurations C. Technician procedures for transmission fault service D. Procedures for automated component replacement E. Autoshift housing trouble shooting and repair F. Perform preventive transmission maintenance G. Technician overhaul procedural guidelines Programme course content requirements may vary by regional employment needs. Therefore, flexibility will be incorporated concerning tasks by assigning each task a priority number. The priority number indicates the minimum percentage of those tasks, a student should accomplish in their course work in order to advance to the next area. Priority number has nothing to do with one’s sociocultural background or socioeconomic beliefs. Prerequisites: Mechanics of Materials Lab, Machine Design I & II, Systems Modelling I & II, Feedback Control, Modelling & Simulation Lab. Co-requisite or Prerequisite: Powertrain Design Mechanical Design Process The scope of this course covers four components, namely, market analysis, product definition, conceptual design, product design and evaluation. To make the learning process more effective and efficient, the course structure is designed to include the following modules. Part 1: Introduction to Design – Get to Know Design The goal of this module is to introduce basic concepts of design, product and process in the context of engineering design. • What is design? What is not design? What does it take to do design? • What is a product? What are possible and meaningful features of a product? • What are general processes of problem solving, decision making, and inventing? And how do they relate to design? • What is design process? What are different phases and different kind of processes? Part 2: Product Planning – Identify and Define Competitive Products Product planning is a part of the design process that deals with generating competitive product definitions based on company goals and market analysis. • What are company’s goals, skills and capabilities? • What is market? What is market situation? What product do you plan to make? • What are market needs? What do people need, want, and desire? • Who are your competitors? How well are they doing in satisfying market needs? • What are your targets and plans in competing with others? Part 3: Conceptual Design – Generate Creative & Marketable Product Concepts Conceptual design is at the heart of engineering design process that determines what your product should be. • What are main functions and auxiliary functions of the product to be designed • How do these functions relate to each other? • What are possible ways or means to achieve the functions identified? What are desirable ones and best ones? • How can one become more creative and what are practicable creative design methods? • How should one compose a product concept based on the possible partial solutions? • How should one evaluate and select from possible product concepts? Part 4: Product/Embodiment Design – Develop Effective & Efficient Physical Realizations Product design, also called embodiment design, is the process to create concrete physical realizations for the design concepts generated at the conceptual design stage. • What are the rules, principles, and guidelines that should be followed in realizing design solutions? • How should one deal with various constraints? • What are the structural, material, manufacturing, and assembling factors that need to be considered during product design? • How can one predict the performance of the product and estimate the cost breakdowns? NOTE: skills from prerequisites will be highly rewarding when used constructively, tangibly and practically to augment projects. Such skills from prerequisites in profession gives one control and management in design and development processes. Classroom Lectures --> Students are required to complete reading assignments, indicated in the schedule page, before each lecture. Usually the weekly 3-hour classroom lecture is divided into two parts. During the first 75 minutes, the instructor will present and discuss the contents outlined in the schedule page. In the second 75 minutes, students will work in groups to discuss the topics lectured and discussed by the instructor and practice design methods by solving small design problems (in the first several weeks) or their project design problems (as the course progresses). Active participation in classroom discussion is strongly required for all students. Textbook: David Ullman," The Mechanical Design Process", 5th Edition References: Pahl, G. & Beitz, “W. Engineering Design - A Systematic Approach", Springer Suh, N.P.: "Axiomatic Design - Advances and Applications", Oxford University Press Terninko, J. “Step-by-Step QFD – Customer-Driven Product Design”, 2nd Ed., St. Lucie Press, A CRC Press Company. Assessment --> Homework 20% 10-11 Quizzes 15% 2 Mini-Design Projects 15% Midterm 20% Term Project 30% Homework --> For the first half of the course, there will be weekly homework assignments. Each homework assignment has 2-3 short questions and/or one small design problem intended to help students: (1) assimilate the reading material and organize their thoughts about it, (2) digest key concepts learned from the lectures. Thoughtfulness, clarity, conciseness and incisiveness are required. Quizzes --> Quizzes will be given at determined periods. Quizzes may cover the materials in each lecture, required readings, and class presentations. Mid-term Exam --> After the “Part 3: Conceptual Design” module is completed, there will be a mid-term exam. The exam will be open-book and open-note. Questions of the exam will be similar to, but more comprehensive than, the homework questions, quizzes and design problems. Students will be asked to answer questions and solve small design problems. Mini-Design Projects --> Two mini design projects will be given. Each will be completed over the course of 1 to 2 weeks, and give the student an opportunity to design and build a small machine. One design project will occur during the first week, and the second will occur in the second to last week. The students shall implement the design methods learned in class on the second mini-design project. Term Design Project --> This course is Project-Based. The term project will be carried out throughout the course by student teams of 5-6 members. Each team will propose a design project, or bid for one, and develop a specific design solution for their design project problem. By doing the project, students will digest and apply the theory and methods learned from the class, enhance their creativity, and develop the experience of solving close-to-real engineering design problems. Students should form project teams after the very first lecture. Project Teams will give multiple project briefings to the whole class, and will submit two project progress reports and a final project report. Project Briefings (multiple) Project Reports (two) Final Project Report Prerequisites: Machine Design I & II, Systems Modelling I & II, Modelling & Simulation Lab Mechanical Design In this course, products are not just defined as consumer goods, but rather any end results an engineer creates in the course of their work. Products may be internal or external to a company or organisation. This course will focus on physical products. The approaches for developing products can be placed in two categories: Those from engineering design theory and methodology and practical engineering application, or engineering judgement. Executing the Axiomatic Design method. A useful method when beginning with an abstract problem statement and having an organised process to drive towards a solution. Executing the TRIZ design method. A useful method for solving conflicts in a design. Developing engineering judgement by providing practical advice from experienced engineers, both via the instructor, text, and class. Engineering judgement will be developed from conceptual design, to detail design, to design for manufacture. To internalize this advice, this class will consist of hands on applications. Mechanical engineering design, like many other engineering applications has no single “right” answer. In fact, any one person, include the instructor, only knows a small percentage of mechanical design techniques and procedures. As such, the students will be expected to actively participate and provide advice and lessons learned from their personal experiences. Course is segmented into two main sections, conceptual design and detail design. The portion of the course covering conceptual design occurs during the first half of the class, prior to the midterm, and the portion on detail design occurs in the second half. Throughout these two sections, the course can be further divided into three main themes. These are mixed throughout the course: Engineering Design Theory -- course will specifically cover the Axiomatic and TRIZ design methods in detail. Prerequisite covers additional design methods, including design thinking, and Systematic Design should that be of interest. Practical Engineering Applications –developing “engineering judgement”, or “best practices” or “Good Engineering Practice (GEP)”. Hands-on practice is implemented to assimilate this “engineering judgement”, although it is expected the material covered in the course will become of true value when working in industry. Hands-on Practice -- experiential practice is essential for internalizing the course concepts. Therefore, there will be a number of exercises throughout the class in the form of homework, group projects, individual projects and in class exercises. CRITICAL NOTE: the patents process will also be emphasized. CRITICAL NOTE: this class will be very challenging from an aspect of achieving quality designs, which is time consuming. Therefore, I recommend students expect that this course will take more time in preparation than other 3 hour courses. (Assume minimum of the full 9 hours/week). Compared to many other courses, this course will require greater “work ethic” than “book smarts” to be successful. Textbook: James Skakoon," The Elements of Mechanical Design", ASME Press 2008 Resources: Budynas, Richard G., J K. Nisbett, and Joseph E. Shigley. “Shigley's mechanical engineering design”. 10th Edition New York, NY: McGraw-Hill Education, 2015. Print. Kamarudin, K. M., Ridgway, K. and Hassan, M. R. Modelling the Conceptual Design Process with Hybridization of TRIZ Methodology and Systematic Design Approach. Procedia Engineering 131 ( 2015 ) 1064 – 1072 What to make of it? Texts from recent prerequisite may become quite useful CRITICAL NOTE: skills from all past prerequisites leading up can be highly valuable when applied constructively (tangible, practical and fluid application). Expect various types of simulators (for different levels in systems), CAD, FEA, CFD, etc., etc. Assessment: In-Class Exercises Homework Quizzes Labs Exams Two minor group projects Mid-term (Individual) Project Term (Team) Design Project In-Class Exercises -- A variety of in-class exercises will occur to assist students in understanding and assimilating the material. Students will be divided into groups for these exercises, with several groups consisting of students physically present, and other consisting of the DEN students 4 completing the exercises electronically. Groups for in-class exercises will be assigned at the beginning of the semester, and remain the same throughout the semester Homework -- This course will contain regular homework assignments. Homework exercises will be designed to accomplish work that will go into your midterm and final projects. Quizzes -- Quizzes may cover the material in each lecture, required readings, and class presentations. The ability to take the quiz will automatically be removed before each class session, as answers to the quizzes will be discussed in class. Quizzes are open book, open note, open friend, open Google and online. Labs --> 1.Take-Apart Labs You will work in groups to disassemble mechanical devices/assemblies, take measurements, answer questions, and reassemble the device/assembly to its original state. Tools will be provided, but you must bring your own safety glasses or you will be barred entry and have to make the lab up with a penalty. You must follow shop safety rules - long hair must be tied back, no open toed shoes, etc. Lathe disassembly HTMS and matrices Bearing alignment Transmission IC engine 2.Design Labs Such labs will concern shaft, spindle, X-slide, assembly, complex integrated mechanical/electromechanical systems (CIMEMS). Each labs will be 2 – 3 weeks apart; 6 of such labs in total (latter 2 labs concern CIMEMS). Will have 15 minute presentations followed by a 30 minute discussion/design review during every meeting. A projector will be available. Everyone must present their part of the project (even if there is no progress) and everyone must participate in the questions/discussion. Participation factors into the group grade that you will receive at the end of the term. Your team should (a) first tell us the purpose of the meeting, (b) then immediately show your Gantt chart and tell us if you are on/behind schedule, followed by other items as you feel appropriate such as (c) details of the work to date, (d) calculations, (e) risks, questions or items for discussion, etc., etc. Remember to have back up slides in the event that the questions/discussions delve deeper into the details. Exams -- An online midterm and final will occur in place of two of the quizzes. Exams may cover the material in each lecture, required readings, material on prior quizzes, and class presentations. Minor Group Projects -- Two minor group projects will occur in the first half of the class. The projects will focus on putting together small presentations of information. Mid-term (Individual) Project -- This class emphasizes the importance of learning by doing. The best way to understand the methods is to practice. Each individual student will work on an individual design project, to begin the product development process. At the midterm, each student will submit a report and a presentation on their work. Exams are open book, open note, open friend, open Google and online. Term (Team) Design Project -- This class emphasizes the importance of learning by doing. The best way to understand the methods is to practice. The term project will begin at the midterm, and continue through the end of the class. The goal is to develop a conceptual product by the end of the course. Teams may have a minimum of 2 members, and a maximum of 8 members. CRITICAL NOTE: Use of the machine shop must be scheduled in advance. Time on the CMM, waterjet or any CNC machine must be scheduled in person with the Shop Manager. For all other machines, a sign-up sheet is located in the machine shop. Only members from two teams may be in the machine shop at one time. The only exception is when a 3rd team needs to use the waterjet or CMM. No exceptions will be allowed, please DO NOT ask the Shop Manager to make exception. If you do, your grade will be affected. You may only sign up for times during your lab time or for appropriate designated periods. Prerequisite: Machine Design Process Precision Machine Design and Instrumentation This inter-disciplinary course teaches the student how to design, instrument, and control high-precision, computer-controlled automation equipment, using concrete examples drawn from the photonics, biotech, and semi-conductor industries. Topics covered include design strategy, high-precision mechanical components, sensors and measurement, servo control, design for controllability, control software development, controller hardware, as well as automated error detection and recovery. Students will work in teams, both in-classroom and out-of-classroom, to integrate and apply the material covered in class to a term-long multi-part design project in Pro-Engineer, Solid Works, or other comparable CAD system, culminating in a group presentation at the end of the semester. Course Goals: 1. Equip engineering students with the knowledge and experience to design instrumented, computer controlled machinery. 2. Teach students how to financially justify and successfully execute a machine development project. 3. Give students interdisciplinary hands-on experience in the design of electromechanical systems. Course Outcomes -- As an outcome of completing this course, students will: A) Have the tools necessary to design and instrument computer-controlled machinery. B) Understand basic actuator technologies. C) Understand basic sensing technologies. D) Understand basic machine control strategies. E) Understand basic transmission elements. F) Be able to size and select proper actuators, sensors, and controller hardware. G) Have the knowledge to financially justify, plan and execute a machine development project. Lecture hours: 4 per week (2 days per week) Lab hours: 3 per week (1 day per week) Textbooks: Precision Machine Design, by Alexander Slocum, Prentice Hall Reference Books: Handbook of Modern Sensors: Physics, Designs, and Applications; Jacob Fraden, Springer-Verlag Machinery’s Handbook, Industrial Press The Mechatronics Handbook, by Robert Bishop, Ed., CRC Press Lab Tools: CAD CAE SystemModeler/Modelica libraries Anysys or Nastran/Patran Assessment: Term Project: 70% Homework: 15% Class Participation: 15% Syllabus --> In addition to the fundamental principles of operation, these topics will be brought to life though selected case studies in the development of automation equipment. 1. Machine Design and Instrumentation Strategy 1 Wk Examples of Precision Automation Equipment (slides & videos) Design: Science or Art? Design Strategies Project Phases Functional Requirements and Design Parameters 2. Design Team Formation and Projects Assignment 0.5 Wk 3. Financial Justification and Project Planning 0.5 Wk Presentation and Justification to Management ProForma Analysis Return on Investment Project Scheduling 4. Actuators 1.5 Wks Rotary Motors Linear Motors AC/DC Stepper Motors Hydraulic/Pneumatic Actuators Solenoids and Voice Coils Piezoelectric Actuators 5. Transmission Elements 1.5 wks Gears Lead/Ball Screws Rack & Pinion Belts/Chains Mechanical Linkages Backlash, Stiction, Friction 6. Joints and Bearings 1.0 Wk Rotary Pin Joints Rotary Bearings Bushings Linear Bearings 7. Preliminary Design Review Presentations 1.0 Wk 8. Sensors 2.0 Wks Incremental and Absolute Encoders Tachometers Accelerometers Strain Gauges Force Sensors Flow Sensors Temperature Sensors 9. Servo Control and Design for Controllability 1.0 Wk System Modelling Closed Loop Control PID System Response Actuator/Sensor Location 10. Computer Control Software and Hardware 2.0 Wks C / C++ / Visual Basic Graphical Programming Interface Field Bus Motion Controllers Input/Output Devices 11. Vision and Image Processing 0.5 Wk Cameras and Lenses Image Processing Strategies 12. User Interface, Error Detection and Recovery 0.5 Wk Operator/Administrator Mode Real-time Fault Monitoring Recovery 13. Critical Design Review Presentations 1.0 Wk Prerequisites: Machine Design I & II; Systems Modelling I & II, Modelling & Simulation Lab, Machine Design Process Co-requisite: Mechanical Design Digital Fabrication Course is highly logistical with emphasis on creating competency in the process of “product” fabrication/construction. Course will guide students through the process of using rapid prototyping, CAD/CAM software, CAD/CAM devices, other engineering software and machining tools. In a studio/lab environment. Course will be three weeks longer than traditional courses for BOTH labs and instruction. Course will have actual development of term projects. There will be a hands-on term project. Course will have no exams. Ability will stem from prerequisites skills, maturity, passion for success, personal ingenuity, personal innovation, and consideration for others towards authentic accomplishment. Labs --> Labs will be based on prerequisites skills AND course topics involving active development. Term Project --> Such will be development throughout the whole term; must convey competent project development for particular phases (at least 3). Labs and mostly prerequisites skills will aid students in term project development. Term project will require a presentation, where student must demonstrate some level of active development in presentation. Level of term project will depend on resources available and authenticity/talent of individuals. NOTE: students must plan well and coordinate well with instructors and lab managers. Course Software & Literature Tools --> CAD/CAM Ansys/Catia/Open Source CAD/CAM devices in a studio environment Structural Analysis Ansys, Patran/Nastran Rhinoceros 3d + Grasshopper (or alternative) SystemModeler/Modelica Cart3d and OpenFOAM (if needed) Materials Science manuals or databases Mechanical Thermal Chemical Toxicity Sustainable form Under thermal/chemical processes Electric Permittivity Magnetic (permeability, susceptibility) Electromagnetic interference (internally, externally) Course equipment available --> CNC Mill, lathe, turning, router 3D printers Classical manual machining machines are not excluded Metrology equipment (includes mechanical/digital spirit levels) NOTE: safety and operations walk-through for each equipment before use. Course assessment --> Labs 60% Term Project 40% Course Topics --> -Overview of digital manufacturing processes What makes a manufacturing process “digital” The “10” disruptive principles of digital manufacturing processes -Parametric Modelling (preview) -Industrial Materials (Metals & Alloys, Polymers) Mechanical properties Structural analysis/integrity Insulation properties (types) Causes of material degradation Physical thresholds Thermal limitations Chemical Post processing Empirical and data-driven models -Additive Manufacturing Processes Engineering polymers, metals, ceramics -CNC -2D Cutting -Programmable Assembly Digital Assembly Digital Bending -Fundamentals of geometric representations for digital manufacturing Solid representations Boundary representations Function representations Voxel representations -Parametric Modelling -Algorithmic design for digital manufacturing Vibrational Geometry Generative models Topology optimization -Machine Control Gantry positioning approaches STL/AMF Slicing -Broader impacts Safety, Liability and intellectual property Environmental impact On-demand fabrication models and mass customization Prerequisites: Machine Design I & II, Computer-Aided Design & Visualization I & II, Mechanics of Materials Lab, Manufacturing Processes, Systems Modelling I & II, Mechatronics I & II, Modelling & Simulation Lab Computer-Aided Design & Visualization I Introduction to 3-D solid modelling, parts, drawings, assemblies, multi-body parts, sketch editing, sheet metal, weldments, surface and mold tools. Note: for integrity and fluidity I will make effort to have exercises that are dependent on prior activities Laboratory Schedule: two 3-hour lab sessions per week for one semester. Assessment --> Lab Assignments 40% Homework 0% Personal investment 4 – 5 Exams 60% Lab Tools: SolidWorks (or open source or AutoCAD with appropriate texts) Lab Assignments --> --Generally, you will not be allowed internet access of any kind before or during during class --You will not be permitted to use flash drives or any data transferring devices --Development of standard geometries and bodies --I will give you various items pre-developed where you are required to extend them based on given instructions --Will ask you to investigate and summarize “investigation/exploratory” tasks. Homework --> Homework assignments concerns maturity and self-interest to better yourselves. If you are interested or have difficulties with chosen task you are welcome to pitch your case during course; limited amounts allowed so make them count meaningfully. Exams --> Exams will have the nature of lab assignments. Additionally, it will be case there is four different courses exams for a class where students will be assigned seats randomly. Write ups and develpment....then go home! Course Texts --> Reyes, A. Beginner’s Guide to SolidWorks 2015 - Part I, Schroff Dev. Corp. Reyes, A. Beginner’s Guide to SolidWorks 2015 - Part II, Schroff Dev. Corp. Course Topics --> 1. Fundamentals of CAD part modelling; conventions and techniques. 2. Creation of engineering drawings from CAD models. 3. Techniques for creating assembly models from parts models in CAD. 4. Creating exploded and assembly drawings from assembly models in CAD. 5. Projections – creation of orthographic, isometric, and oblique projection drawings from part and assembly models using solid modelling CAD systems. 6. Fundamental surface modelling techniques. 7. Application of dimensioning tolerancing techniques and to CAD models, drawings and assemblies. 8. Fundamentals of engineering design and its expression as a design in CAD Prerequisite: sophomore standing Post-requisite: Computer-Aided Design & Visualization II. If you don’t register for the post-requisite in the following semester this course (even if you get an A+ it will be wiped out from your record). Computer-Aided Design & Visualization II Advanced techniques, including the use of a customized system. Presentation of advanced drawing applications, such as three-dimensional solids modeling and linking graphic entities to external non-graphic data. Emphasis on the productivity of CAD software through development of computer-aided drafting programs with emphasis on database design, access techniques, and structure methods with particular application in engineering graphics. Exploration of the use of system customization for drawing production enhancement and the principles of data manipulation. Presentation of advanced applications, such as three-dimensional objects creation and linking graphic entities to external non-graphic data. Course Schedule --> 2 hours lecture, 2 hours lab per week Lab Tools --> SolidWorks (or open source or AutoCAD with appropriate texts) Grades will be assigned according to the following criteria --> DAILY WORK 50% UNIT EXAMS 20% FINAL PROJECT 20% FINAL EXAM 10% Note: labs and exams will have the same rules as prerequisite Course Goals --> Build on skills already mastered Study the SolidWorks interface 3D modelling, basic functionality Assembly basics SolidWorks toolbox Basics Understand design tables Study revolve features Analyse sweep features Loft features Visualization techniques simulationXpress Projects, Assignments, Portfolios, Service Learning, Internships, etc. --> Create 3D models, using basic & advanced rendering skills Manipulate 3D models, by applying editing commands Create complete final project with real life simulation applied Prerequisite: Computer-Aided Design & Visualization I COMPUTER ENGINEERING PARTICULARS -->

Embedded Systems & Control I Embedded Systems are everywhere. From phones, cameras, TVs, etc. you are interacting with an embedded system. Embedded systems are also found in cars, airplanes, and robots. They far outnumber traditional computers (which also contain embedded processors). Learning to design and program embedded systems is a critical skill that is necessary for many industry and scientific occupations. In this course you will learn the basics of designing, interfacing, configuring, and programming embedded systems. We will likely make use of the Arduino platform, which is an inexpensive, popular embedded system used by hobbyists, researchers, and in industry, to implement the techniques learned in class. By the end of the course you will have mastered the basics of embedded system design and programming. This course will help to prepare you for cutting edge careers in industry and research. Typical Text (in unison): Wayne Wolf, Computers as Components, Second Edition: Principles of Embedded Computing System Design, 2nd ed. Morgan Kaufmann, 2008 Russell, D. (2010). Introduction to Embedded Systems: Using ANSI C and the Arduino Development Environment. Morgan and Claypool Publishers Further Embedded Systems reference: Edward Lee and Sanjit Seshia, Introduction to Embedded Systems, A Cyber-Physical Systems Approach, 2011. C language References: Purdum, J. (2012). Beginning C for Arduino: Learn Programming for the Arduino and Compatible Microcontrollers, Springer Michael Griffiths, M. (2018). Practical Arduino C. Independently Published (LULU) Bayle, J. (2013). C Programming for Arduino. Packt Publishing Course Platform --> Each student will be given, and be responsible for, an Arduino embedded system platform and associated hardware. You will be responsible for taking care of these throughout the semester and you may be charged for damage or loss of these. Tools --> Arduino Uno R3 Atmega 328 Simulator (when relevant) Materials --> Arduino Uno R3 data sheet Atmega 328 data sheet Analogue to digital Converter with Embedded Systems tutorial STMicroelectronics or (other) 3-axis accelerometer and 3-axis magnetometer data sheet/manual Homework --> There will be a number of homeworks assigned throughout the semester. These will typically have both questions and programming components. Most often these will require demonstrating the final operation to the instructor before the assignment is due during one of their regularly scheduled office hours, so please plan accordingly. These are individual assignments. It is ok to discuss concepts behind the problems in the homeworks with classmates, however, you cannot do them together. If you do discuss problems with classmates or other people, you must acknowledge this on the assignment (this will not lead to any grade reduction). As a metric for what level of discussion is allowed, it is ok to meet and talk over coffee or tea about the assignment. It is not ok to show someone your solution or to work on the details of the problems together. In addition, you should not take notes while discussing the problems. If in doubt, ask the instructor or TA questions about assignments. In Class Labs --> There will be a number of small group assignments that will be done during class times. Some labs may have small components that must be performed individually before the start of lab. Groups will be randomly assigned at the start of class. Your group will be graded based on what you are able to successfully accomplish during class. Homework assignments will often build on these mini-labs. If you are not in class or are not properly prepared for the lab, you will receive a zero for that lab. Projects --> There will be two small projects in this class that will build on and combine the components you develop in your homeworks. The projects will involve an in-class competition where you compete with your classmates to accomplish a task. In addition, there will be an associated project report. The first project/competition will be due in the middle of the semester. The second project/competition will be due the last week of classes. Additional details will be announced in class. Topics Covered --> Embedded System Organization: Major components in a typical embedded system, operating requirement, modes of operation, hardware/software codesigns, hardware-software trade-offs. Microcontroller Programming: Basic structures of microcontrollers, basic features, memory interfacing, digital I/O, timers, analogue interfaces, interrupt services, programming in high-level languages and assembly languages, basic data types, operators, constructs, data structures, compiler directives, power management. I/O Interfacing Concepts: Input devices, output devices, memory mapping, bus structures, peripheral and external communication interfaces. Operating System: Design and organization of embedded and real-time operating systems, scheduling, power management, communication, debugging. Grading --> Homework 20% In-Class Labs & Participation 20% Quiz 1 15% Quiz 2 15% Project 1 15% Project 2 15% Topic Outline --> Week 1. Course intro, c programming Week 2. Embedded system design, Arduino intro, basic circuit diagrams Week 3. Instruction sets, registers and mem access, digital I/O. Lab: LEDs & buttons Week 4. Timers, debugging. Lab: Timers and I/O Week 5. Pulse width modulation (PWM). Lab: Servos Week 6. CPU bus, comm protocols (UART, SPI, I2C) Week 7. Analog input. Lab: Analog sensors Week 8. Power management, program optimization. Project 1 Competition or completion Week 9. Interrupts. Lab: Encoders Week 10. Embedded algorithms, feedback control. Lab; Feedback Control Week 11. Embedded algorithms, feedback control. Lab: Feedback/Automatic Control Week 12. Embedded operating systems. Lab: Schedulers Week 13. Peripherals, sensors. Lab: i2c Week 14. Embedded systems applications Week 15. Embedded systems applications Week 16. Final Project Competition Prerequisites: Practical Programming in C for Engineering II, Assembly Language I Embedded Systems & Control II In this course you will build an omni-directional hovercraft robot and develop the low-level controllers and sensor interfaces on the embedded system that control the robot. In this course you will learn the theory and practice of interfacing, configuring, and programming embedded systems through the creation of this robot platform. Project may change for future terms. At a low-level, you will learn about embedded system design, using digital and analogue interfaces, controlling motors, communicating over various protocols, and interfacing with sensors. At a higher-level you will learn about implementing, optimizing, and debugging embedded algorithms to control the hovercraft's actions. In addition, you will learn about networking, embedded operating systems, and power management. The hovercraft platform can control a variety of motors, transport reasonable payloads, and has numerous sensors including gyros and magnetometers. For the final project, you will extend the robot with new sensors and develop algorithms that take advantage of these enhanced capabilities, and by the end of the course you will have a deep understanding of the design, programming, and interfacing of embedded systems. This will prepare you for cutting edge careers in industry and research. Typical Text (in unison): Wayne Wolf, Computers as Components, Second Edition: Principles of Embedded Computing System Design, 2nd ed. Morgan Kaufmann, 2008 Russell, D. (2010). Introduction to Embedded Systems: Using ANSI C and the Arduino Development Environment. Morgan and Claypool Publishers Further Embedded Systems reference: Edward Lee and Sanjit Seshia, Introduction to Embedded Systems, A Cyber-Physical Systems Approach, 2011. C language References: Purdum, J. (2012). Beginning C for Arduino: Learn Programming for the Arduino and Compatible Microcontrollers, Springer Michael Griffiths, M. (2018). Practical Arduino C. Independently Published (LULU) Bayle, J. (2013). C Programming for Arduino. Packt Publishing Course Platform --> Each student will be given, and be responsible for, an Arduino embedded system platform and associated hardware. You will be responsible for taking care of these throughout the semester and you may be charged for damage or loss of these. Tools --> Arduino Uno R3 Atmega 328 and Atmega 1284p ESP32 chips Simulator (when relevant) Materials --> Arduino Uno R3 data sheet Atmega 328 data sheet Atmega 1284p data sheet Hoverboard schematic (https://cse.unl.edu/~carrick/courses/2011/436/hoverboard2011v1.pdf ) ESP32 chips data sheet Analogue to digital Converter with Embedded Systems tutorial STMicroelectronics or (other) 3-axis accelerometer and 3-axis magnetometer data sheet/manual Topics Covered --> Topics covered will include basic circuit and schematic reading skills, datasheet reading skills, embedded C programming, embedded system design, embedded software design, register and memory access, digital I/O, bus communication, serial communication interfaces, PWM, analog to digital converters, interrupts, debugging embedded systems, designing embedded algorithms, sensors, sensor fusion, program optimization, networking, process scheduling, multitasking, operating system design and organization, power management, and more! See the course website for a detailed course schedule. Grading --> 15% Class and Lab Participation 15% Homework 40% Labs 30% Final Project Homework --> There will be at least two homeworks over the course of the semester. These are individual assignments. It is ok to discuss concepts behind the problems in the homeworks with classmates, however, you cannot do them together. If you do discuss problems with classmates or other people, you must acknowledge this on the assignment (this will not lead to any grade reduction). As a metric for what level of discussion is allowed, it is ok to meet and talk over coffee or tea about the assignment. It is not ok to show someone your solution or to work on the details of the problems together. In general any discussions should be limited to discussion and you should not be taking significant notes on the problems. If in doubt, ask me questions about assignments. Homeworks are due via email before the start of class on the day that they are due. Note that late homeworks are not accepted. Labs --> There will be four labs, each worth 10% of your final grade, during the semester. Each lab group only needs to submit one lab report. The lab report should be well written with complete sentences and paragraphs and be readable on its own. It must contain an introduction, discussion, conclusion, as well as the answers to specific questions asked. Supporting materials such as pictures, code examples, etc. are encouraged. Each lab group will appoint a group member at the start of each lab that will be primarily responsible for collecting and organizing the lab report. Each person must do this for at least one lab during the semester. Everyone in the group must still contribute fully to doing and writing the lab, the person in charge of the lab just has the added responsibility of organizing and submitting the lab writeup. Labs are due via email (or whatever) before the start of class on the day that they are due. Late labs will receive a 10 – point deduction for each 24 hours they are late. That means that if you turn it in after class, instead of before, your group will start with a 90% as the highest possible grade. Lab groups will be assigned at the start of the semester and will remain the same throughout the semester for the labs and final project. If you are experiencing any problems with the dynamics of your group, please let me know early so that we can address them quickly before they get out of hand. Final Project --> The final group project will consist of picking, interfacing, and designing algorithms to utilize a new sensor on the hovercraft. Some potential ideas are Accelerator: compensate for bumps, learn thruster configurations Range finders: Wall following, obstacle avoidance Bump sensors: obstacle avoidance, Roomba-like behaviour Gripper: transport objects Camera: follow objects IR Comms/range finder: multi vehicle communication/ranging/localization Overall the final project is worth 30% of your grade. The breakdown of the grading for the project is roughly: Proposal 5% Pre-presentation 5% Presentation 10% Project Report 10% The proposal is a short paper (2-4 pages) describing the sensor you plan to interface to the hovercraft and the algorithms sensor enables that you plan to implement. The project report is a final report describing your project and outcome. The presentation will show your system, sensor, and algorithms in action to the class and invitees. A short pre-presentation before the final presentation will also be given to ensure system functionality before the final presentation. Further details on the final project will be given in class. Class and Lab Participation --> Participation and lab is critical in this class and counts for 15% of your grade. You are expected to be prepared for class and lab, do assigned readings, and ask questions during class and lab. Simply coming to class and lab is not sufficient for obtaining full marks for participation; you should actively participate in discussions. It is acceptable to use computers to read papers and take notes. However, I expect that their use will not be a distraction. Texting, tweeting, facebooking, etc. can wait until after class. Do not use your cell phone during class. It is obvious and is a distraction not only for you, but for me and your classmates as well. Topic Outline --> Week 1. Intro, embedded system design, registers, memory access, datasheets Week 2 & 3. Embedded C programming, digital I/O, basic circuit elements, circuit diagrams Week 4. Bus and serial protocols (UART, I2C, SPI) Week 5. Debugging, pulse width modulation (PWM) Week 6. Interrupts, analog to digital converters (A2D) Week 7. Communication and networking (I2C, SPI, radio) Week 8. Sensors Week 9. Embedded algorithms (e.g. sensor fusion) Week10. Program Optimization Techniques Week 11. Process scheduling and multitasking Week 12. Operating system design and organization Week 13. TBD Week 14. TBD Week 15 & 16. Supercomputing-computer clusters Note: will likely make use of GitHub repositories and analyse code before use Week 17. Final Project Presentation Labs --> Lab 1a: Hovercraft Construction https://cse.unl.edu/~carrick/courses/2011/436/lab1/lab1.html Lab 1b: Intro to Hoverboard Programming https://cse.unl.edu/~carrick/courses/2011/436/lab1b/lab1b.html https://cse.unl.edu/~carrick/courses/2011/436/lab1b/lab1b.zip Lab 2: Communication, Debugging, Thruster Control, and Sensor Reading https://cse.unl.edu/~carrick/courses/2011/436/lab2/lab2.html https://cse.unl.edu/~carrick/courses/2011/436/lab2/lab2.tgz Lab 3: Interrupts, Communication, and Sensor Fusion https://cse.unl.edu/~carrick/courses/2011/436/lab3/lab3.html https://cse.unl.edu/~carrick/courses/2011/436/lab3/lab3.tgz Lab 4: PID, Serial Console, Scheduler https://cse.unl.edu/~carrick/courses/2011/436/lab4/lab4.html https://cse.unl.edu/~carrick/courses/2011/436/lab4/lab4.tgz Lab 5 (may take up to 2 weeks): Supercomputing-computer clusters Prerequisites: Embedded Systems & Control I Microprocessors I Course provides an introduction to microprocessors. It uses assembly language to develop a foundation on the hardware, which executes a program. Memory and I/O interface design and programming. Study of microprocessor and its basic support components, including CPU architecture, memory interfaces and management, coprocessor interfaces, bus concepts, serial I/O devices, and interrupt control devices. Laboratories directly related to microprocessor functions and its interfaces. Typical Text: Walter Tribel, "The 80386, 80486, and Pentium Processors: Hardware, Software, and Interfacing", Prentice Hall References: Myke Predko, "Programming and Customizing PICmicro Microcontrollers" 2nd Ed, McGrawHill LABS --> Students should really make most of lab activities because this is where you would gain some of the most tangible and practical skills in the course. No one can thrive with microprocessors solely on theory; contrary attitudes are equivalent to relating the size of one’s cranium to their lifestyle. Labs in this course are by no means on the level of the Microprocessors I Lab course. Don’t fool or screw yourselves. Course Objectives--> 1. Microprocessors and Microcomputers - Ch 1. Describe evolution of reprogrammable computer systems. Describe general architecture of a microcomputer system Describe Intel microprocessors, benchmarking 2. Real-Mode Software Architecture of the 80386DX Microprocessors - Ch 2. Describe the internal architecture of 80386DX. Describe real-mode software architecture. Describe real-mode memory space and data organization. Draw data alignment in memory. Convert 2's complement integer format among hexadecimal, decimal & binary. State the generation of a real-mode memory address. State the operation of stack. Describe real-mode I/O address space. 3. Real-Mode Assembly Language Programming Methodology - Chapter 3. Describe the concept of software. Describe the steps of assembly language program development. Describe the evolution of 8086 family instruction set. Describe the addressing modes of 80386DX. 4. Assembly Language Coding and Debugging - Chapter 4. Convert assembly language instructions to machine code. Use "DEBUG" program to debug. 5. Real-mode 80386DX Programming I - Chapter 5. Use data transfer instructions. Use arithmetic instructions. Use logic instructions. Use shift instructions. Use rotate instructions. Use bit test and bit scan instructions. 6. Real-mode 80386DX Programming II - Chapter 6. Use flag-control instructions. Use compare and set instructions. Use jump instructions. Use subroutine instructions. Use loop instructions. Use string instructions. 7. Program Development with MS-MASM - Chapter 7. (Not covered in class) Describe statement syntax. State pseudo operations. 8. Protected-mode Software Architecture of 80386DX - Chapter 8. Describe protected-mode register model. Describe protected-mode memory management and address translation. State descriptor and page table entries. State multitasking and protection. 9. Memory and I/O Interfaces of the 80386DX Microprocessors - Chapters 9. Describe system clock and bus cycles. Construct hardware organization of memory address space. Describe memory interface circuitry State types of I/O. 10. Memory Devices, Circuits and Subsystem Design - Chapter 10. Describe program and data-storage memory. Explain read only memory (ROM). State random access memory (RAM). Describe parity checking and related circuit. 11. PIC Microcontroller Understand the differences between microcontroller and microprocessor State the instruction and data memory organization Know the instruction set of PIC Be able to program the PIC to complete a specific task Know how to inteface PIC to peripheral circuits Design and debug microcontroller based circuits Grading --> Homework 10% Laboratory 30% 2 Exams 30% Final 30% Course Outline --> Week 1 Microprocessors and Microcomputers 80386DX internal architecture, data organization Week 2 Registers, memory segmentation Address generation, stack, I/O addr space Assembly language program development Week 3 Addressing mode I Addressing mode II Assembly language coding and debugging Week 4 Data transfer and arithmetic instructions Logic and shift instructions Rotate and bit instructions Week 5 Flag and compare instructions Jump and subroutine instructions Loop and string instructions Week 6 Pre-exam Review Exam 1 Protected mode registers (GDTR, IDTR) Week 7 LDTR and TR CR and SSR Virtual address, segmentation of virtual space Week 8 Address translation in segmented MM Page table and vir-to-phy addr translation Page table and vir-to-phy addr translation Week 9 Interfaces of 80386DX System clock, bus cycle and memory organization Interface circuitry, PLA and I/O Week 10 Interface circuitry, PLA and I/O ROM, static RAM Exam 2 Week 11 PIC overview PIC: Data Memory PIC Instruction Set I Week 12 PIC Instruction Set II PIC Programming Examples I Week 13 PIC Programming Examples II PIC Programming Examples III Week 14 Peripherals I Peripherals II Laboratory Day Week 15 Putting it together Course Review LAB EXPECTATIONS --> Five labs will be conducted and evaluated including both assembly language programming and hardware interfacing. Please check back for the posting of detailed lab specifications. Report format: Your report needs to follow the format below. Cover page including Lab number and title, Student Name, Partner's Name, and Date of report. Lab Purpose: It is usually the objective of the lab. Lab Content: Answer the questions in lab specification. Describe what you do in the lab, e.g. what commands did you practiced. It has to be at least one page with 11pt font size. Try to organize and summarize the lab in itemized lists. Difficulties: state what difficulties you encountered in the lab and how you managed to solve it. If not, what have you tried? Conclusion and Suggestions Lab assignments: To be posted on schedule page Lab Outline --> Lab 1: DOS commands and DEBUG software Learn how to: 1. Boot up DOS, edit a file, save a file, copy a file, move a file, delete a file. 2. Run/quit DEBUG software, show/modify register content, show/modify flags, dump memory contents, assemble and debug programs. Lab 2: Assembling and executing instructions with DEBUG software Learn how to: 1. Assemble instructions into the memory of PC. 2. Execute an instruction to determine the operation it performs. 3. Verify the operation of data transfer and arithmetic instructions. Lab 3: Assembly Language Programming Learn the development of an assembly language program. Students will be held accountable with prerequisites. Lab 4: PIC Microcontroller Programming with PICkit 1 Kit Learn how to use PICKIT 1 Flash Starter Kit to compile and upload program to PIC microcontroller. Learn PIC microcontroller assembly language programming. Lab 5: Stepper Motor Control using PIC16F684 Microcontroller Program a PIC microcontroller to control a bipolar stepper motor. Prerequisites: Digital Design II, Solid State Devices I, Assembly Language II Microprocessors II This course deals with advanced concepts in the programming and the interfacing of microprocessors/microcontrollers to the outside world as demonstrated by a variety of application examples. It covers the advanced architecture of modern processors and the many I/O peripherals now commonly found on-board the device. Detailed studies of computer I/O and interrupt techniques as applied to analogue-to-digital, digital-to-analogue, timers, parallel and serial interfaces are included. Laboratory activities provide the student with experience in developing the hardware and software required to incorporate microprocessors into systems that solve real-world interfacing problems. On successful completion of the course, the student should be able to: A. describe advanced microprocessor architecture and programming B. describe the difference between a microprocessor and a microcontroller C. design, develop, and validate microprocessor-based system software D. demonstrate increased proficiency in software programming E. develop and analyse schematics / logic diagrams for microprocessor-based systems F. determine and optimize a design for an input/output (I/O) device G. explain the operation and application of computer interrupts H. design and validate a parallel I/O interface I. choose an analogue-to-digital converter (ADC) based on relevant specifications J. choose a digital-to-analogue converter (DAC) based on relevant specifications K. design real-world interfaces incorporating ADCs and DACs L. describe the operation and application of serial communication interfaces M. describe the operation and application of serial peripheral interfaces and devices N. describe the operation and application of computer timer devices O. design for and interface to I/O devices incorporating ADCs, DACs, timer and serial methods P. synthesize and develop microprocessor interfaces for various I/O devices in general R. work in teams S. produce written documents and to give oral presentations T. construct circuits, use test equipment and use technical problem solving skills. Typical Texts: TBA Tools: An environment will be provided where students can actively build and test programming, and interface. Students will also be guided on how to practice their programming with testing and interfacing outside of course. Assessment --> 4 Exams 40% Labs 30% Lab --> An environment will be provided where students can actively build and test programming. Students will make use of their lecture notes and lab instruction towards programming activities. There will be practice programming assignments for students to take on outside of class for their own benefit. Students must be seriously honest with themselves about assignments; copying the work of others is readily a means of disaster. Simply put, if you don’t know it, then there‘s virtually no way to pass this course. COURSE OUTLINE --> A. Introduction 1. orientation 2. course overview B. Overview/review of Microcontroller Architecture 1. register set design and usage 2. addressing modes and applications 3. instruction set and timing 4. memory and peripheral mapping 5. hardware implementation and I/O support 6. analysis of application examples a. recursion and stack usage b. traffic light controller C. Input/Output Architecture 1. logic families & specifications 2. binary input ports 3. Schmitt triggered inputs 4. binary output ports 5. tri-state logic 6. bidirectional ports 7. software I/O control techniques a. polling / programmed b. interrupt-driven c. direct memory access d. multiplexed I/O D. Digital Interfacing 1. binary input devices a. mechanical switch inputs b. contact debouncing c. mechanical switch devices (thermostats, thermal fuses, mercury switches, magnetic reed) d. solid-state switch devices (optical, magnetic) e. pseudo-binary inputs f. keypads 2. binary output devices a. LEDs b. relays / solenoids c. analogue switches 3. parallel I/O a. I/O synchronization b. time multiplexed LED display c. parallel printer interface standard d. LCD modules 4. digital I/O expansion E. Analog Interfacing 1. digital to analogue converters a. DAC operation b. DAC specifications c. DAC types d. DAC interfacing e. DAC applications 2. analogue to digital converters a. ADC operation b. ADC specifications c. ADC types d. ADC interfacing 3. sensors a. temperature b. pressure c. motion / accelerometers d. sound e. chemical F. Time-based I/O 1. hardware timers and real-time interrupts 2. output compare operations 3. input capture operations 4. applications and implementation a. time keeping / software scheduling b. pulse accumulation c. voltage controlled oscillators (VCO) d. pulse-width modulation (PWM) e. DC motor control f. stepper motor control G. Data Communications 1. legacy serial I/O a. serial interface components b. serial data transmission c. serial communication standards d. serial interface implementation 2. special purpose devices a. magnetic stripe readers 3. protocol-based serial I/O a. CAN b. SPI c. IIC d. USB e. Zigbee Prerequisite: Microprocessors I Microprocessor Lab I In this laboratory, students get the opportunity to apply the theoretical knowledge they acquired in their previous microprocessor courses to real hardware and software. The course uses a Coldfire (68k based) or other microcontroller demo board as a development platform and commercial development tools so students can experience modern design techniques. Some of the labs focus strictly on software while others deal with the problems of operating and interfacing microprocessor hardware. The students write code in assembly language to develop a strong understanding of microprocessor fundamental operations. Specific Course Learning Outcomes (CLO) --> The students are able to 1. understand and apply the fundamentals of assembly level programming of microprocessors 2. work with standard microprocessor interfaces including GPIO, serial ports, digital-to-analogue converters and analogue-to-digital converters 3. troubleshoot interactions between software and hardware 4. analyse abstract problems and apply a combination of hardware and software to address the problem 5. use standard test and measurement equipment to evaluate digital interfaces Typical Text: Text from prerequisite and other sources Materials: Lab Manual for use will be declared Tools: An environment will be provided where students can actively build and test programming, and interface. Students will also be guided on how to practice their programming with testing and interfacing outside of course. Experiments --> Exp. 1 – Get Acquainted with the Project Kit (No lab report) • Learn to operate board used in the class • Learn to assemble and execute code Exp. 2 – Developing Software for the SBC (No lab report) Part 1: Find ‘X’ program Part 2: Move a string in RAM program Part 3: Adding numbers entered from the keyboard Exp. 3 – An Event Driven Annunciator System (Lab report required for 3-person group) • Demonstrate annunciator state machine program specified by lab manual Exp. 4 – Testing and Simulating Some IC’s (No lab report) Part 1: Quad logic gate (NAND, AND, OR) chip tester Part 2: Simulation of D and JK flip-flop in software Exp. 5 – Testing the Serial Port (Lab report required) • Clock Tolerance for the UART • Observation of the Serial Waveform Exp. 6 – DAC (Digital to Analog Converter) Interface with the Microprocessor (Lab report required) Exp. 7 – ADC (Analog to Digital Converter) with Accelerometer Lab Reports --> Lab reports are required for certain labs as indicated. Each lab report should have a primary author that is responsible for writing the report for the entire group. Each group partner is responsible for one report in the semester. The grade given for the report will count toward the primary author’s grade. Assessment --> Exp. 1 – 0.0 Exp. 2 – 0.1 Exp. 3 – 0.1 Exp. 4 – 0.15 Exp. 5 – 0.1 Exp. 6 – 0.15 Exp. 7 – 0.1 Lab reports – 0.2 Attendance – 0.1 Prerequisite: Microprocessors I Microprocessor Lab II The main objective of this lab course is to gain the practical hands on experience of programming the 8086 microprocessor and 8051 microcontroller and also to gain knowledge on interfacing of different peripherals to microprocessor; other microcontrollers and processors may be possible. Microprocessor technology is an exciting, challenging and growing field which will pervade industry for decades to come. To meet the challenges of this growing technology, one has also to be conversant with the programming aspects of the microprocessor and microcontroller. This practical course of microprocessor and microcontrollers presents an integrated approach to hardware and software in the context of a chosen microprocessor and chosen microcontroller. Typical Texts: Advanced Microprocessors and Peripherals, A.K. Ray and K.M. Bhurchandi, TMH Microprocessors and Interfacing, Douglas V. Hall , II Edn ,TMH. The 8086/ 8088 Family, John Uffenbeck , PHI 8051 Microcontroller, Kenneth J. Ayala, Penram International References: Microcomputer systems: The 8086/8088 Family, Architecture, Programming and Design, Yu Cheng Liu and Glenn A Gibson, II Edn, PHI Microprocessors, Interfacing and Applications, Ramsingh and B.P. Singh, New Age Publishers The Intel Microprocessors 8086/8088, 80186/80188, 80286, 80386, 80486, Pentium, and Pentium Pro Processor, Architecture, Programming and Interfacing, Barry b. Brey, IV Edn, PHI. Microprocessors Principles and Applications, Gillmore, II Edn, TMH. Tools: An environment will be provided where students can actively build and test programming, and interface. Students will also be guided on how to practice their programming with testing and interfacing outside of course. List of experiments --> The following Programs/experiments are to be written for assembler and execute the same with 8086 and 8051 kits: 1. Programs for 16-bit arithmetic operations of 8086 (using various addressing modes) To perform 16 bit addition, subtraction, multiplication and division in different addressing modes. Prerequisite: Assembly language programming, TASM commands, Architecture of 8086, Arithmetic Instructions of 8086 -Write Program to perform 16 bit addition in different addressing modes and execution. -Write Program to perform 16-bit subtraction in different addressing modes and execution. -Write Program to perform 16-bit multiplication in different addressing modes and execution. -Write Program to perform 16-bit division in different addressing modes and execution Applications: ALU Designing 2. Program for sorting an array for 8086 To understand the Branch Instructions and to sort the numbers in ascending and descending order. Prerequisite: Assembly language programming, TASM commands, Architecture of 8086, Arithmetic Instructions of 8086, Branch Instructions of 8086 -Write a program to sort the given array in ascending order and execution. -Write a program to sort the given array in descending order and execution. Application: Data processing and acquisition applications. 3 Program for searching for a number or character in a string for 8086 To understand how to search for a number or character in a string. Prerequisite: Assembly language programming, TASM commands, Architecture of 8086, Instruction set of 8086 -Write a program to search for a number or character in a string and display a message to indicate whether the number is found or not. Applications: Data acquisition and processing. Password Verification. 4 Program for string manipulations for 8086 To understand how to use the string manipulation instructions. Prerequisite: Assembly language programming, TASM commands, Architecture of 8086, String manipulation instructions of 8086. - Write a program to move the string from one location to another and execution. -Write a program to reverse the string and execution. Applications: Data acquisition and processing 5 Program for digital clock design using 8086 To understand how to design digital clock design using 8086. Prerequisite: Assembly language programming, TASM commands, Architecture of 8086, Instruction set of 8086. -Write a program to design a digital clock displaying Hours, Minutes and seconds 6 Interfacing ADC and DAC to 8086 Applications: Timer for different applications. To generate delays. To understand how to Interface ADC and DAC to 8086. Prerequisite: Assembly language programming, TASM commands, Knowledge of ADC and DAC, Architecture of 8086, Architecture and control words of 8255, Instruction set of 8086 -Write a program to read Analog input and Display digital value. -Write a program to accept Digital input and Display various wave forms viz. Sine, Triangle, and square Applications: Interfacing of analogue peripherals. Data acquisition and processing 7. Parallel communication between two microprocessors using 8255 To understand how to establish parallel communication between two microprocessors using 8255. Prerequisite: Assembly language programming, TASM commands, Architecture of 8086, Architecture and control word of 8255, Instruction set of 8086. -Write a program to transmit parallel data from microprocessor through port of 8255 and read the same in to another microprocessor. Applications: Data transfer between processors 8. Serial communication between two microprocessor kits using 8251 To understand how to establish serial communication between two microprocessors using 8251. Prerequisite: Assembly language programming, TASM commands, Architecture of 8086, Architecture and control word of 8251, Instruction set of 8086. -Write a program to transmit serial data from microprocessor through 8251 and read the same into another microprocessor. Application: Data communication 9. Interfacing to 8086 and programming got control stepper motor To understand Interfacing and control of stepper motor to 8086 through 8255. Prerequisite: Assembly language programming, TASM commands, Architecture of 8086, Architecture and control word of 8255, knowledge of stepper motor, Instruction set of 8086. -Writing programs to rotate the stepper motor clock -wise/ anti-clockwise and execution. Applications: Robots. Automation. 10. Programming using arithmetic, logical and bit manipulation instructions of 8051 To understand arithmetic, logical and bit manipulation instructions of 8051. Prerequisite: Assembly language programming, Keil software, Architecture of 8051, Instructions of 8051. -Writing programs to perform addition, subtraction, multiplication, division and execution. -Writing programs to perform logical AND, OR, XOR and execution . -Writing programs to perform Shifting operations, swapping and execution Application: ALU designing 11. Program and verify Timer/ counter in 8051 To verify the timer operation and counter operation in 8051. Prerequisite: Assembly language programming, Keil software usage, Timer/counter registers and modes in 8051, Instructions of 8051. -Write the program to verify the operation of timer in different mode and execution. Write the program to verify the operation of counter in different mode and execution. Application: To generate delays. External events counter. 12. Program and verify interrupt handling in 8051 To understand internal and external interrupt handling in 8051. Prerequisite: Assembly language programming, Keil software usage, Interrupt structure of 8051 microcontroller, Instructions of 8051. -Writing programs to verify interrupts handling in 8051 and execution. Application: Peripheral interfacing 13. UART operation in 8051 To understand UART operation in 8051. Prerequisite: Assembly language programming, Keil software usage, UART operating modes, Instructions of 8051. -Writing a program to serially transmit the data using UART. -Writing program to serially receive the data using UART. Application: Data transfer 14. Communication between 8051 kit and PC To establish Communication between 8051 kit and PC. Prerequisite: Assembly language programming, Keil software usage, Architecture of 8051, Instruction set of 8051 - Writing a program to establish Communication between 8051 kit and PC Application: Data transfer 15. Interfacing LCD to 8051 To understand Interfacing LCD to 8051 Prerequisite: Assembly language programming, Keil software usage, Architecture of 8051, Basics operation of LCD, Instruction set of 8051. -Explanation of LCD display commands -Writing program to interface LCD and execution. Application: Displays 16. Interfacing Matrix / Keyboard to 8051 To understand the Interfacing Matrix / Keyboard to 8051. Prerequisite: Assembly language programming, Keil software usage, Architecture of 8051, Basics operation keyboard, Instruction set of 805. -Explanation of keyboard operation. -Writing program to interface keyboard and execution. Application: Keyboard as an input device 17. Data Transfer from peripheral to memory through DMA controller 8237 / 8257 To understand how Data is transferred from peripheral to memory through DMA controller 8237 / 8257 Prerequisite: Assembly language programming, Architecture of 8237/8257. -Interfacing of a peripheral to memory through DMA and writing program for data transfer. Application: Direct memory Access Prerequisites: Microprocessors I, Microprocessor I Lab, Microprocessors II. Assembly Language I or Assembly Language II CMOS VLSI Design Analysis and design of digital MOS VLSI circuits including area, delay and power minimization. Laboratory assignments including design, layout, extraction, simulation and automatic synthesis. Typical Text: Kang and Leblebici, CMOS Digital Integrated Circuits, McGraw-Hill Topics --> -Introduction to CMOS Circuits; MOS Transistor Theory, stick diagrams, transmissions gates latches -CMOS Processing Technology and Fabrication, CMOS Design Rules -CMOS Physical Design – Euler Paths, Interconnections, Layout Strategies -MOS Transistor Theory – IV Characteristics, Capacitance, Threshold Voltage, Scaling, Inverter Characteristics, transmission Gates Characteristics -Inverter Fall Time/Delay, Inverter Optimisation, Sequential Circuits, Interconnect Delay, Interconnect Resistance, Capacitance, Superbuffer Design -Power Consumption -Dynamic Circuits, Dynamic Storage, Domino Logic, Memory Design Course Will also treat design constraints trade-offs, including economic constraints, to produce engineers capable of design VLSI Cells, to provide design techniques that can be applied as technology evolves, to provide capability for lifelong learning as technology changes. All prior objectives will serve as foundations for 1. Digital Logic Design 2. Circuit Design 3. Physical Design 4. Fabrication NOTE: DO NOT TAKE SUCH FOUR PHASES LIKELY; REMEMBER THE LISTED TOPICS THAT WILL BE INVOLVED THROUGHOUT. TAKE INTO ACCOUNTED ALSO THE DESIGNATED TEXT. PREREQUISITE SUBJECTS GENERALLY WILL NOT BE TAUGHT, RATHER YOU ARE EXPECTED TO HAVE INTELLIGENCE AND SKILLS IN THEM WHEN ENROLING IN THIS COURSE. CONSIDERING A 15 WEEK SCHEDULE FOR AT LEAST 2 – 3 TIMES PER WEEK, SUCH FOUR OBJECTIVES ARE HIGHLY CONDENSED. Laboratory Projects --> There will be 3 design projects, each of which builds on the other, culminating in a project, the objective of which is to minimize the cost-delay product. The minimum design wins the course design contest and receives a gift certificate. Students will need to spend much time in lab and apply independent development. In general, to be in the computer engineering you have to really be into it to get anything out of it and be able to apply. Tools --> Naturally expects some may expect usage of ANSYS solutions. That’s good and all, BUT THERE ARE VARIOUS SOFTWARE LISTED IN THE GOODY BAG POST THAT WILL PROVE TREMENDOUSLY BENEFICIAL, AND WILL NOT BREAK YOUR ARMS AND LEGS TO FIT THE BILL, BEING IN COMPUTER ENGINEERING THAT’S HIGHLY INDUSTRIAL AND EXCLUSIVE. Prerequisite: Solid State Devices III, Practical Programming in C for Engineering I & II, Digital Design I & II, Department Permission, Instructor Permission VLSI Testing & Validation Upon completion of this course, students will be able to effectively test VLSI systems using existing test methodologies, equipment, and tools. Typical texts: M. L. Bushnell and V. D. Agrawal, Essentials of Electronic Testing for Digital, Memory, and Mixed-Signal VLSI Circuits, Kluwer Academic Publishers M. Abramovici, M. A. Breuer, and A. D. Friedman, Digital Systems Testing and Testable Design, Computer Science Press L. T. Wang, C. W. Wu, and X. Wen, VLSI Test Principles and Architectures, Morgan Kaufmann Tools --> VLSI test tools will be used for assignments and projects. Naturally expects some may expect usage of ANSYS solutions. That’s good and all, BUT THERE ARE VARIOUS SOFTWARE LISTED IN THE GOODY BAG POST THAT WILL PROVE TREMENDOUSLY BENEFICIAL, AND WILL NOT BREAK YOUR ARMS AND LEGS TO FIT THE BILL, BEING IN COMPUTER ENGINEERING THAT’S HIGHLY INDUSTRIAL AND EXCLUSIVE. Topics --> 1. Fault modelling 2. Automatic test pattern generation 3. Fault simulation 4. Testability measurements 5. Design for testability and scan test 6. Boundary scan testing 7. Built-in self-testing 8. Memory testing 9. Case studies using CPU testing papers 10. Other most up-to-date research topics. This course includes extensive lab experiments and hands-on usage of VLSI test equipment and tools as an integral part of the course. Lab sessions will be scheduled each week and as necessary. Homework --> Homework assignments using test pattern generator software and testing VLSI circuits using VLSI test equipment (pattern generators, logic analysers, etc.). These assignments cover combinational and sequential test generation, scan-paths, boundary scan, and testing an existing VLSI chip for detection and location of faults. Exams --> Details on exams will be explained on first day Cheating Policy --> Cheating in test - will be graded F in this course. Copying assignment – the grade will be divided by the number of people sharing the code. Assessment --> Assignments + Projects: 40% 3 Exams: 60% Prerequisite: CMOS VLSI Design Analog Circuit Design I This course will teach the fundamentals of CMOS and BICMOS analog circuit design techniques used in today’s advanced mixed-signal integrated-circuit applications. Topics to be covered include device/process background, IC passives, analog amplifiers, current mirrors, op-amp design, noise fundamentals, RF design basics, switched capacitor circuits, comparators, A/D and D/A converters, and other analog circuitry used in today's mixed-signal ICs. The course will include a laboratory component involving hands-on measurements with high frequency instruments in the “RF Lab”, as well as the design, layout, and simulation of RF/analog integrated circuits using IBM 8HP device models (or other). Typical Texts: Carusone, Johns, and Martin, Analog Integrated Circuit Design, Wiley Lee, The Design of CMOS Radio-Frequency Integrated Circuits, Cambridge References: Gray, H. & Lewis, M. Analysis & Design of Analog Integrated Circuits, Wiley Razavi, Design of Analog CMOS Integrated Circuits, McGraw-Hill Allen and Holberg, CMOS Analog Circuit Design, Oxford Univ Press Horenstein, Microelectronic Circuits and Devices, Prentice-Hall Tools: Cadence SpectreRF and Ansys Totem are well known. However, from the goody bag post there are alternatives to avoid the financial challenge. The course involves the use of a coordinated set of lectures, labs, homework, and exams to teach analog/RF/mixed-signal integrated circuit design based on today’s CMOS and BICMOS technologies. The four simulation labs are designed to introduce the student to the Cadence SpectreRF CAD design tools (or other), starting with circuit simulation from the schematic, then physical layout, design rule and logic-versus-schematic checking, and finally circuit simulation using extracted models based on the layout. Tutorials will be utilized to help students learn the use of whatever tools applied. An experimental lab will be included using the RF equipment to measure S-parameters and other RF characteristics of a high frequency amplifier. Technical Papers & White Papers from companies to analyse and simulate Grading --> Homework 10% Labs 35% Exam 25% Final Project 30% Topic Outline --> WEEK 1 SiGe BICMOS Technology: fabrication, layout, design rules (CJ&M Ch 2, 8HP Manual) Compact analog/RF circuit models for BICMOS devices (Lee Ch 5, CJ&M Ch1 & 8) WEEK 2 Review MOS device physics and SiGe NPN device physics (Lee Ch 5) Cadence SpectreRF (or alternative) & 8HP Tutorial (2hr 15 min): software and hardware manuals Passive IC components: capacitor, resistor, inductor, transformer (Lee Ch 4) WEEK 3 Passive RLC Networks, Matching Networks (Lee Ch 3) Matching Networks (continued) (Lee Ch 3) 8HP Layout Tutorial (3 hr): 8HP Design Kit WEEK 4 Current mirrors and amplifier fundamentals (CJ&M Ch 3) Frequency response of amplifier circuits (CJ&M Ch 4) WEEK 5 Feedback amplifiers (CJ&M Ch 5) CMOS Op-amp design (CJ&M Ch 6) WEEK 6 CMOS Op-amp design (continued), Opamp compensation (CJ&M Ch 6) Op-amp design (continued), Wide-swing current mirrors (CJ&M Ch 6) WEEK 7 Distributed systems, transmission lines (Lee Ch 6) Smith chart, S-parameters (Lee Ch 7) WEEK 8 Noise in Semiconductor Devices (Lee Ch 11) Noise in Semiconductor Devices (cont) , review for Mid-Term (Lee Ch 11) Midterm Exam WEEK 9 Estimating bandwidth, risetime, and delay (Lee Ch 8) High frequency amplifier design (shunt peaking, shunt-series) (Lee Ch 9) WEEK 10 High freq amp design (tuned amplifiers, cascading) (Lee Ch 9) Comparators (CJ&M Ch 10) WEEK 11 Sample and Hold circuits (CJ&M Ch 11) Switched capacitor circuits (CJ&M Ch 14) WEEK 12 Data converter fundamentals (CJ&M Ch 15) Analog-to-digital converters (ADC) (CJ&M Ch 17) WEEK 13 – 14 Analog-to-digital converters (continued) (CJ&M Ch 17) Digital-to-analog converters (DAC) (CJ&M Ch 16) Homework --> 1. CMOS and Bipolar Devices and Fabrication (given 8 days to complete) 2. CMOS and Bipolar Small Signal Models and Biasing (given 16 days to complete) 3. IC Passives, Matching Networks, Amplifier Fundamentals (given 21 days to complete) 4. Operational Amplifier Design, Transmission Lines (given 15 days to complete) Labs --> 1a CMOS & NPN Bipolar Device Characteristics (schematic): dc, small-signal ac, fT (given 12 days to complete) 1b. CMOS & NPN Bipolar Device Characteristics (layout): dc, small-signal ac, fT (given 12 days to complete) 2. Analog Design: Current Mirror Op-amps in CMOS and BiCMOS (given 16 -17 days to complete) 3. Experimental Lab: S-parameter Measurements of cable, load, & MMIC amplifier (given 23 days to complete) 4. RF Design: High Frequency Amplifier (matching, tuning, S-parameters) (given 22 days to complete) Project --> Final Project: Design of an A/D Converter. Assigned date will be given (at some lower point of the term that will need the knowledge and skills developed) (given 15 days to complete) Prerequisites: Solid State Devices III, CMOS VLSI Design Analog Circuit Design II This course will teach the fundamentals of CMOS and SiGe BICMOS RF and analogue circuit design techniques used in today’s advanced mixed-signal integrated-circuit applications, such as a single chip radio. Topics to be covered include RF chip design, oscillators, mixers, RF low noise amplifiers, demodulators, phase-locked loops, RF power amplifiers, low power techniques, receiver and transmitter architectures, filters, and mixed-signal circuitry typical of modern telecommunications technology. Typical Texts: T. H. Lee, The Design of CMOS Radio-Freq Integrated Ckts, Cambridge C. Coleman, An Introduction to Radio Frequency Engineering, Cambridge Carusone, Johns, and Martin, Analog Integrated Circuit Design, Wiley References: B. Razavi, Design of Analog CMOS Integrated Circuits, McGraw-Hill Barry Gilbert, et al., Trade-offs in Analog Circuit Design, IEEE Press Gray, Hurst, Lewis, & Meyer, Analysis and Design of Analog Intgrt Ckts, Wiley The course involves the use of a coordinated set of lectures, labs, homework, and exams to teach RF/mixed-signal integrated circuit design based on today’s CMOS and BICMOS technologies. Design & simulation labs utilize the Cadence Spectre/RF CAD design tools (or other) to allow the student to practice RFIC design concepts in the 1-10 GHz frequency range using the IBM 0.13µm 8HP BiCMOS design kit and models. An experimental lab is also included using RF instruments to characterise high frequency behaviour in RFIC circuit components. Course will require an additional 2 weeks to complete with quality. Tools: Cadence SpectreRF and Ansys Totem are well known. However, from the goody bag post there are alternatives to avoid the financial challenge. The course involves the use of a coordinated set of lectures, labs, homework, and exams to teach analog/RF/mixed-signal integrated circuit design based on today’s CMOS and BICMOS technologies. The four simulation labs are designed to introduce the student to the Cadence SpectreRF CAD design tools (or other), starting with circuit simulation from the schematic, then physical layout, design rule and logic-versus-schematic checking, and finally circuit simulation using extracted models based on the layout. Tutorials will be utilized to help students learn the use of whatever tools applied. Technical Papers & White Papers from companies to analyse and simulate Grading --> Homework 10% Labs 35% Mid-term Exam 25% Final Project and Reading 30% Topics --> WEEK 1 Wireless Communication Principles Lee, Ch 2 WEEK 2 Review SiGe BICMOS Technology: process, device, and models 8HP Manual, J&M Ch1 WEEK 3 Noise in Semiconductor Devices (review) Lee, Ch 11 Tutorial in Lab (set up 8HP libraries & go over RF examples) 2hr -2hr 40 min WEEK 4 Extra Class: review background EC580 material WEEK 5 Low Noise Amplifier (LNA) Design Lee, Ch 12 LNA Design (cont), review of 8HP chip design and layout Lee, Ch 12, 8HP Manual WEEK 6 Mixers Lee, Ch 13 Modulators & Demodulators, Gilbert quadrature mixer Coleman Ch4, Literature WEEK 7 – 8 Biasing, Band Gap Reference Circuits Lee Ch 10 Feedback systems, root-locus techniques, stability Lee Ch 14 WEEK 9 RF power amplifier design Lee Ch 15, Coleman Ch 7 Modulation of RF power amplifiers Lee, Ch 15 WEEK 10 RF power amplifier design examples Lee, Ch 15 WEEK 11 Oscillators Lee, Ch 17 WEEK 12 Phase-Locked Loops Lee, Ch 16 Midterm Exam WEEK 13 – 14 Synthesizers Lee, Ch 17 Phase Noise Lee, Ch 18 WEEK 15 Continuous-time filters: Gm-C filters, BIP/CMOS transconductors J&M, Ch 15 RF Architectures: superheterodyne, direct conversion, transmitters Lee Ch19, Coleman Ch12 WEEK 16 Chip Design Examples (GPS Receiver Chip) Lee, Ch 19 Chip Design Examples (5-GHz WLAN Receiver) Lee, Ch 19 Chip Design Examples (802.11a Direct Conversion WLAN XCVR) Lee, Ch 19 WEEK 17 Antennas Coleman, Ch 10 Homework --> 1. Wireless Communications Theory (will be given 12 days to complete) 2. Low Noise Amplifiers, Mixers, Modulators (will be given 19 days to complete) 3. Band-Gap Circuits, Feedback, Stability (will be given 14 days to complete) 4. RF Power Amplifiers, Oscillators, Phase-locked Loops (will be given 21 days to completed) 5. Reading from IEEE JSSC literature (will be given 21 days to complete) Labs --> 1. Experimental Lab: use of Agilent Spectrum Analyzer to characterize a mixer (will be given 19 days to complete) 2. Design Lab: Low Noise Amplifier (will be given 16 – 23 days to complete) 3. Design Lab: Mixer Circuit (will be given 24 days to complete) 4. Design Lab: AM Receiver Front-End (LNA, Mixer, Local Osc, IF filter, detector) (will be given 26 days to complete) 5. Project: Design of a Direct-Conversion Transmitter. Assigned date will be given (at some lower point of the term that will need the knowledge and skills developed) (will be given 21 days to complete) Prerequisite: Analog Circuit Design I Mixed Signal Circuits Course will introduce design and analysis of mixed-signal integrated circuits. Topics include: Sampling and quantization, Sampling Circuits, Switched Capacitor circuits and filter, Comparators, Offset compensation, DACs/ADCs (flash, delta-sigma, pipeline, SAR), Oversampling, INL/DNL, FOM. The course will include two mini-projects towards the end using analysis and design techniques learned in the course. Students to provide written report with explanations to their design choices either with equations or simulation analysis/insight along with performance results. Students concern --> -Some main problems that designers who have to integrate analogue and digital circuits on the same PCB face are: Preventing digital switch noise from contaminating the analogue signal. Interfacing the wide range of analogue input voltages to the digital circuit. Generating analogue out puts from digital signals isn’t usually a problem, however, digital inputs from analogue signals is. -Apply principles of hierarchical mixed signal CMOS VLSI, from the transistor up to the system level, to the understanding of CMOS circuits and systems that are suitable for CMOS fabrication. -Design simulated experiments using Cadence (or other) to verify the integrity of a CMOS circuit. -Design mixed signal circuits in CMOS. -The language C with HDL code generation. Simulations. Examples and case studies to exhibit verification using top-down design including (i) ADC design using executable specifications (and/or DAC if relevant) (ii) Verifying SPICE and HDL models using top-down design (iii) Device testing using instrument control and test vector generation from top-down models. -PLL and SerDes treatment likely. -Apply their course knowledge and the Cadence (or other) VLSI CAD tools in a team-based design project that involves much the same design flow they would encounter in a semiconductor design and fabrication flow. Project is presented in a formal report due at the end of the semester. Textbook: TBA Resources: M. Anderson, J. Wernehag, A. Axholt and H. Sjoland, "Teaching top down design of analog/mixed signal ICs through design projects," 2007 37th Annual Frontiers In Education Conference - Global Engineering: Knowledge Without Borders, Opportunities Without Passports, Milwaukee, WI, 2007, pp. T1C-1-T1C-4 Sommer, R. et al. (2002). From System Specification to Layout: Seamless Top-down Design Methods for Analog and Mixed-Signal Applications. Proceedings 2002 Design, Automation and Test in Europe Conference and Exhibition, 884-891. Gielen G. (2000) System-Level Design Issues for Mixed-Signal ICs and Telecom Frontends. In: van de Plassche R.J., Huijsing J.H., Sansen W. (eds) Analog Circuit Design. Springer Tools --> Software to apply in this course can be found in “Goody Bag” post Technical Papers and White papers --> Course will make use of various technical papers and white papers from different companies. At various times students will be tasked with analysing and verifying (multiple) topics in a specified task. Will have analytical structuring and software to simulate and verify. This will be unique to standard assignments done in course. Lab seminars --> Lab seminars concern primarily motivation and insight into technical topics actively. Students will be expected to have sustain their skills from prerequisites. Seminars are not tutorials for prerequisites. Will rely heavily on Q&A and issues that professor/instructor needs to address. Laptops are mandatory. Idle use or activities with laptops not related to course will lead to severe consequences. Toxic or poor behaviour in seminars will lead to severe consequences. There will be penalties upon your midterm and projects. Tread at your own risk because I will neither provide nor inform you of any quantitative model for punishment. In some cases, consequences can lead to 69% forfeit of your final grade. Grading --> Homework Assignments [30%] Lab Seminars [10%] Midterm [25%] Projects [35%] Weekly Outline --> -Introduction -Ideal Sampling & Quantization -Static & Spectral Performance Metrics -Sampling Circuits -Switched Capacitor Circuits -Comparators, DACs -SAR ADCs -Flash ADCs -Pipeline ADCs -Time Interleaving, Oversampling -Oversampling, Decimation Filters -Other Converter Topologies -High Accuracy Converters -FOM -Wrap-up Prerequisites: Digital Design I & II; Solid State Device I-III, CMOS VLSI Design; VLSI Testing & Validation; Analog Circuit Design I & II Digital Systems Design Goals and Objectives--> How to go about designing complex, high speed digital systems (not just circuits)? How to use some of the modern CAD tools to help with the design? How to implement such designs using programmable logic (e.g. FPGAs)? How to read data sheets and make sense of them? How do digital building blocks (such as memory chips, processing elements, arithmetic circuits etc.) work? How to interface to processors and computers (from hardware point of view)? How to deal with testing of complex systems? Have fun! Reasonable Texts: Digital Design Principles and Practices", 4th Edition (Sept 2005), John F. Wakerly, Prentice Hall. Contemporary Logic Design”, Gaetano Boriello, Randy H. Katz, August 2004, Prentice Hall High-Speed Digital Design - A handbook of black magic", Howard G. Johnson, Prentice Hall FPGA-based System Design”, Wayne Wolf, Prentice Hall Verilator and Altera Quartus to be made available for demonstrations in lectures and use n labs. Best way to learn DSD is to do it. There will be 8 lab exercises using DE2 Board (from Altera) or other to learn the system. Design of a cordic based processor to add ripple effect on an image. Work in pairs – one deliverable between the pair. Deliverables: Working design and demonstrator Design document (effectively a no-nonsense report) Quartus-II software has a web-edition that can be downloaded (free) from Altera website after you register. Software also available on all Level 5 & Level 1 machines DE2 Boards or whatever to be available in particular lab facilities The course syllabus is divided into five main sections: 1. Programmable Logic 2. Arithmetic Circuits 3. Data Encoding & communication 4. Architectures 5. Testing Programmable Logic --> Technologies behind programmable logic Programmable Logic architectures in general Complex Programmable Logic Devices (CPLDs) Field Programmable Gate Arrays (FPGAs) Recent advances in FPGAs Designing with FPGAs Design Flow, Design Tools, Design Libraries Future of programmable logic Arithmetic Circuits --> Adders architectures Multipliers circuits Floating point arithmetic circuits Other computational building blocks Data Encoding and Communication --> Logic interface standards Clocking for high speed digital design Metastability issues Clock synchronisation Data encode and error correction On-chip and On-board communication Architectures --> Parallel vs Serial Systolic and other array architectures Distributed arithmetic Cordic based architecture Testing --> Modern packaging Board testing issues JTAG Boundary Scan Prerequisites: Senior Standng, Department Permission, Instructor Permission System-on-Chip (SoC) Design Setting, design, programming, optimisation, and application of modern System-on-a-Chip (SoC) architectures. Interactive coverage of the scale of computer engineering within the context of SoC platforms from gates to application software, including on-chip memories and communication networks, I/O interfacing, RTL design of accelerators, processors, concurrency, firmware and OS/infrastructure software. Formulating parallel decompositions, hardware and software solutions, hardware/software trade-offs, and hardware/software codesign. Attention to real-time requirements. Goals of Course --> --Design, optimise, and programme a modern System-on-a-Chip. --Task Development: (i) Analysis a computational task, (ii) characterising its computational requirements, (iii) identify performance bottlenecks, (iv) identify, explore, and evaluate a rich design space of solutions, and (v) select and implement a design that meets engineering requirements. --Decompose the task into parallel components that cooperate to solve the problem. --Characterise and develop real-time solutions. --Implement both hardware and software solutions, formulate hardware/software trade-offs, and perform hardware/software codesign. --Comprehend the system on a chip from gates to application software, including on-chip memories and communication networks, I/O interfacing, RTL design of accelerators, processors, firmware and OS/infrastructure software. --Comprehend and estimate key design metrics and requirements including area, latency, throughput, energy, power, predictability, and reliability Documentation --> XILINX (just a example) Vitis Unified Software Platform Documentation The Zynq Book Zynq UltraScale+ MPSoC overvew and referencemanual Data Sheets Ultra96 Board dcumentation Vivado Design Suite User Guide Parallel Programming for FPGAs literature Early Readings --> Suggestions and literature will be given before each lecture Writeups --> Writeups must be done in electronic form and submitted through designated portal. Use CAD or drawing tools where appropriate. A guideline will be given. The specific homework assignments will specify what portion of the writeup can be performed jointly and what part should be individual. Portions of the project milestones and final will be per group. Look for specific instructions associated with the project. Collaboration --> Students are allowed and encouraged to help each other with the Xilinx tools (SDSoC, SDK, Vivado, Vivado HLS, Windows, Linux) used for the course, but are disallowed from developing collaborative design solutions (C-code, pragmas, design and analysis) outside of identified project groups. Each team must develop its own design solution; collaborating across teams is a violation of the collaboration policy. Within a project group, the assignment will specify what part should be done as a group and what part should be done individually. Tools---We know the tools are complex and the documentation often dense or inadequate, and we won't be surprised if they are buggy. It will likely be necessary to collaborate as a class on figuring out how to best use the tools for the term. We encourage students to help each other and share what they learned. We will award bonus points for student-developed instructions and tutorials on how to solve common tasks that arise for the tools. Design Solutions---Each team (or individual where specified) should develop their own solutions to the design problem and their own implementations. You are taking this class to develop these skills, and we believe you need to work out the solutions on your own to master the skills. You cannot share code, diagrams, specific pragma settings, plots, analysis, metrics, or other results. You cannot share problem decompositions. HLS Pragmas---HLS Pragmas sit at the border between where collaboration is allowed and not allowed. You are allowed to help make each other aware of the existence of pragmas and the syntax for pragmas. You are not allowed to tell each other what pragma values and settings best solves the problem---you should be reasoning through what the settings mean and how they impact the code mapping, and you should be performing your own experiments in your project teams. You are allowed to say where a pragmas goes syntatically (e.g., relative to function header, relative to loop header), but are not allowed to suggest which function or loop would benefit from a specific pragma. Project --> There will be a substantial project running throughout term. Students work in groups. Platform will be an SoC-FPGA (e.g., Xilinx Zynq or Intel/Altera Arria or whatever else), permitting the provisioning of soft-core processors, accelerators, and memory in addition to the use of the embedded SoC logic. Beginning with a significant task (an example would be audio/video acquisition, processing, compression, networking). Course begins by running the task on single processor and identifying resource requirements. Then, it will deal with I/O for task. It then migrates the task to multiple processors to accelerate. Following, it develops custom accelerators for task and integrate with networked processor. The final half of the course is an open-ended optimisation project using the techniques and design options introduced in the course. Topics --> Architectural building blocks and heterogeneous architecture, Hardware-Software Codesign, Embedded Software, Interfacing, Computational requirements and system analysis, Concurrency, Real Time, Design-space formulation and exploration, Costs and metrics (energy, area, runtime, reliability, predictability), Quantitative design and analysis. Assessment --> Engagement [10%] Weekly Assignments [15%] Quizzes [10%] Midterm [10%] Final [15%] Design Project [40%] Outline --> Overview, scope, methodology Metrics and bottlenecks Memory Computational models Data parallel microarchitectures (SIMD, Vector, GPU) Thread-level Parallelism and virtualization Real-time, reactive Spatial computations, basic mapping from high-level Fine-grained parallelism microarchitectures (FSMD, VLIW) High-level synthesis (C-to-gates, resource selection and provisioning) Verification On-chip networking / Network-on-Chip VLSI technology and scaling Defect and fault tolerance Prerequisites: Working knowledge of C and/or C++ (including software development and debugging); Embedded Systems & Control I & II

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