Assignment Description 1. General Instruction: A. This assignment contributes 30% of course. B. Marks allocated: 100. C. Students must submit a copy (in PDF format) on the due date with the authentic and valid plagiarism report, the similarity should be below and/or equal to 15%. D. Number all pages. E. The answer must be in original, i.e. in your own words. F. An official cover page must be handed in with the written assignment. G. It should be concise and generally free from spelling mistakes and grammatical errors. H. APA referencing style is required. I. The assignment should type in the font of Time New Romans ONLY; the font size is 12pt; it should be 1.5 spacing line. 2. Case Study: CASE ONE Joanne supervised 36 professionals in 6 city libraries. To cut the costs of unnecessary overtime, she issued this one-sentence memo to her staff: When workloads increase to a level requiring hours in excess of an employee regular duty assignment, and when such work is estimated to require a full shift of eight (8) hours or more on two (2) or more consecutive days, even though unscheduled days intervene, an employee tour of duty shall be altered so as to include the hours when such work must be done, unless an adverse impact would result from such employee absence from his previously scheduled assignment. After the 36 copies were sent out, Joanne,s office received 26 phone calls asking what the memo meant. What the 10 people who didn,t call about the memo thought is uncertain. It took a week to clarify the new policy. CASE TWO Chris was simultaneously enrolled in a university writing course and working as a co-op student at the Widget Manufacturing plant. As part of his co-op work experience, Chris shadowed his supervisor/mentor on a safety inspection of the plant, and was asked to write up the results of the inspection in a compliance memo. In the same week, Chris,s writing instructor assigned the class to write a narrative essay based on some personal experience. Chris, trying to be efficient, thought that the plant visit experience could provide the basis for his essay assignment as well. He wrote the essay first, because he was used to writing essays and was pretty good at it. He had never even seen a compliance memo, much less written one, so was not as confident about that task. He began the essay like this: On June 1, 2018, I conducted a safety audit of the Widget Manufacturing plant in New City. The purpose of the audit was to ensure that all processes and activities in the plant adhere to safety and handling rules and policies outlined in the Workplace Safety Handbook and relevant government regulations. I was escorted on a 3-hour tour of the facility by … Chris finished the essay and submitted it to his writing instructor. He then revised the essay slightly, keeping the introduction the same, and submitted it to his co-op supervisor. He “aced” the essay, getting an A grade, but his supervisor told him that the report was unacceptable and would have to be rewritten — especially the beginning, which should have clearly indicated whether or not the plant was in compliance with safety regulations. Chris was aghast! He had never heard of putting the “conclusion” at the beginning. He missed the company softball game that Saturday so he could rewrite the report to the satisfaction of his supervisor. 3. Group Analytical Report Requirements: A. Clearly state the purpose of the report. Define the scope of the analysis, including the specific problem or question being addressed. Outline the objectives of the analysis and what the report aims to achieve. B. Summarize relevant theories, models, and research studies that provide context to the report. Critically evaluate the existing CASE STUDIES to identify gaps that your report aims to fill. C. Explain the research design and approach used in gathering and analyzing data. Describe the methods and tools used for data collection, ensuring to justify the choice of methods. Detail the analytical techniques applied to interpret the data. D. Present the data in a clear and organized manner, using tables, charts, and graphs as needed. Analyze and interpret the data in relation to the research objectives. Compare the findings with existing literature or benchmarks. E. Provide a concise summary of the key findings from the data analysis. Discuss the implications of these findings for the subject area, including any potential impacts or recommendations. F. Critically assess the results in the context of the research question or problem. Relate the findings back to the CASE STUDIES review, highlighting how they support or challenge existing theories. G. Summarize the key points made in the report. Offer any recommendations based on the analysis. Suggest areas for further research or limitations encountered during the study. H. Appendices: Include any additional material that supports the report but is too detailed for the main body (e.g., raw data, detailed calculations, supplementary information). I. Approximately 3,000 words, the report words limit cannot be more or/and less than 10%. 4. Group Collaboration Section A. Roles and Responsibilities: Detail the contributions of each group member. B. Coordination: Describe how the group coordinated and communicated during the project. C. Reflection: Include a reflection on the group,s collaborative process, highlighting challenges and successes.
MTH227 Research Project: Interstellar Parachute Design Challenge Future Aerospace Engineers Project Deadline: Wednesday of Week 13 Project Description Welcome, aerospace engineers! Your mission is to design a parachute system for a planetary exploration mission to Mars, Venus, or Titan. The key challenge lies in the unique atmo-spheric conditions of these celestial bodies (e.g., low density, different composition), which drastically affect fluid dynamic behavior. compared to Earth. This project requires you to apply core fluid mechanics principles to design a parachute that can operate effectively in a specified extraterrestrial environment. You are encouraged to think creatively and move beyond traditional designs. Your goal is to propose a conceptually sound design justified by fluid mechanics theory and analysis. Key Requirements Team Formation & Submission • Form. a team of three students. • Submit one research paper per team. • The paper must be no less than 5 pages, excluding references and appendices. • The deadline is Wednesday of Week 13. • In principle, all team members will receive the same score. Paper Structure Your paper must include the following sections in order: 1. Title: A concise reflection of the core content of your main research. 2. Author: The names and IDs of all three students. 3. Abstract: A concise summary of your mission, design, and key findings. 4. Introduction: Background on the target planet, a literature review, the engineering problem, and objectives. 5. Main Body: This should detail your design process, theoretical analysis, and calcu-lations. 6. Conclusion: Summary of your design’s advantages, limitations, and potential im-provements. 7. References: List all cited books, articles, and online resources. 8. AI Usage Statement: A declaration of how AI tools were used (see policy below). 9. Appendix (Optional): For code, detailed calculations, or simulation setups (e.g., CFD parameters). Note: CFD or other simulations are NOT required. You may choose to use them as a supplementary analysis tool, but they will NOT contribute to your score. AI can be used as a tutor to help you learn CFD software if you wish. AI Usage Policy • DO NOT use AI to generate the paper’s content. The writing must be your own. • You ARE ENCOURAGED to use AI for: – Brainstorming and generating initial ideas. – Conducting background research and summarizing literature. – Assisting with data analysis or explaining complex theoretical concepts. – Assisting with coding if you need. – Learning how to use software if you wish (e.g., CFD tools). • You MUST include an AI Usage Statement detailing which tools were used and for what purposes. Proper use of AI will not affect your score. • Here is an example of the statement:AI Usage Statement: We used DeepSeek for brainstorming and to improve our understanding of theoretical fluid dynamics concepts related to drag and stability. All content in this report was written and developed by our team. Grading Rubric Your project will be evaluated based on the following criteria: 1. Application of Fluid Mechanics Theory & Analysis (30%) Correct and deep application of concepts, theory and analysis methods. Quality of the theoretical analysis of your design. 2. Creativity & Critical Thinking in Design (20%) Originality and innovativeness of the proposed parachute design. Evidence of critical thinking in comparing design options and justifying choices. 3. Use of Mathematics & Physics in Modeling (20%) Effective use of mathematical tools and physical laws to calculate and predict the performance of your design. 4. Reliability, Persuasion, & Feasibility (15%) The overall credibility and logical flow of your argument. How well you convince the reader that your design is feasible and addresses the core challenges. 5. Clarity, Structure, & Readability (15%) The overall organization, clarity of writing, use of professional language, and quality of visual presentations (figures, graphs, diagrams). Getting Started • Find your partners and form. a research team of three members. • Choose your target planet and research its atmosphere. • Review key fluid mechanics principles related to drag and flow around bluff bodies. • Brainstorm wildly as a team, then refine your ideas into 2-3 promising concepts. • Start with simple calculations and build your analysis from there. We are excited to see your innovative designs for the final frontier! Good luck!
ECO 320: Statistical Analysis Project Final Report Guidelines Fall 2025 Assignment: Statistical Analysis Project: Final Report Due Date: Thursday, December 11, by 11:59 PM (submitted on Brightspace) Purpose The purpose of this report is to bring together all the components of your semester-long project. This isn’t just a “final paper” to check a box. It’s your opportunity to be an economist or a data analyst. You’ll take a real-world economic dataset you chose, apply the statistical methods we’ve learned to answer a specific research question, and communicate your findings in a clear, professional report. This directly addresses our final learning objective, LO8: to use statistical software to conduct analysis and clearly communicate results using both technical and non-technical language. Beyond this course, this is exactly what analysts do. In any job, you’ll be asked to “figure something out from the data” and “present your findings.” This report is your first major practice run at that entire process. Skills This assignment is designed to help you apply several key skills that are essential in this field: • Applying: You will apply the statistical concepts from class (like descriptive statistics, confidence intervals, and hypothesis testing) to a real, and probably messy, dataset. • Analyzing: You will analyze your data to find patterns and evidence that help answer the research question you defined in your proposal. • Synthesizing: You will pull together multiple pieces (your initial question, the back- ground context, the data, your statistical results, and your interpretation) into a single, coherent story. • Evaluating: You will have to judge which statistical methods are the right ones for your specific data and question. • Communicating: You will practice translating complex statistical output into a simple, meaningful interpretation that a non-expert could understand. Knowledge This report will primarily draw on the content from the second half of our course. You’ll be expected to be familiar with: • Descriptive Statistics (LO1) to summarize your data. • Sampling Distributions and the Central Limit Theorem (LO5) as the foundation for your inferences. • Confidence Intervals (LO6) to estimate population parameters. • Hypothesis Testing (LO7) to make decisions about your research question. • You will also, of course, become more knowledgeable on the specific economic topic you chose to study! Tasks Your task is to submit a single, polished Final Report document as a group. This report should be a complete, standalone document that summarizes your entire project, from the initial question to the final conclusion. I’m not looking for a 50-page thesis. A good target is 5—10 double-spaced pages, including your tables and figures. Here is a recommended structure for your report: 1. Introduction: • State your research question, incorporating any feedback from your proposal. • Explain the context: why is this question interesting or important? • Briefly introduce your dataset. • End with a 1–2 sentence summary of your main finding and a “roadmap” for the rest of the report. 2. Data Description: • Where did your data come from? What are the key variables you used? • Provide a table of descriptive statistics (mean, median, standard deviation, count, etc.) for your key variables. • Include at least one relevant data visualization (like a histogram, scatterplot, or bar chart). 3. Statistical Methods: • Explain the statistical methods you used to answer your question. • Crucially: Don’t just name the test (e.g., “We used a t-test”). Justify it. (e.g., “To compare the mean income between two independent groups, a two-sample t-test was the appropriate method...”). • You must also include all steps you underwent to perform the statistical method. For example, if you ran a hypothesis test, you must state your null and alternative hypotheses, the test statistic, the p-value, and your decision rule, as well as the steps you underwent. 4. Results: • Present the results of your analysis. This is where you put the output from your analysis or software. • Use clearly labeled tables and figures to present your findings (e.g., “Table 1: Results of Hypothesis Test for...”). Report test statistics, p-values, confidence intervals, etc. 5. Interpretation & Discussion: • This is the most important part! What do your results mean? • Translate the “stat-speak” into plain English. For example, instead of just saying “we reject the null hypothesis,” explain what that means in the context of your research question. • Crucially: Clearly define the population you are making an inference about and the sample you are using. This context is essential for a valid interpretation. • Discuss any limitations of your study. (e.g., “Our sample size was small,” “the sample might not be random,” “there could be serial correlation,” “we only had data for one year,” “this is just a correlation,” etc.) • End with a clear conclusion that directly answers your research question. 6. Appendix: Tool Disclosure (Mandatory) • As stated in the syllabus, you must disclose all tools used. • Software: Please state what software you used (e.g., “All analysis was conducted in Microsoft Excel,” or “We used R for... and Excel for...”). • Code (If Used): Using programming languages like R or Python is not mandatory. Many successful projects can be completed using Excel. If you did use code, you must include it with your submission. • AI (If Used): You must disclose if and how you used AI tools (Copilot, Gemini, ChatGPT, etc.). Be specific about the role it played (e.g., “We used ChatGPT to help brainstorm our research question” or “We used Copilot to help debug a section of our R code”). You do not need to include your specific prompts. A Note on the Presentation: This written report is a separate, more detailed component than your presentation. While your presentation is for summarizing your key findings, this report is where you provide the full detail, justification, and complete analysis. Criteria for Success This Final Report is worth 7% of your total course grade. A successful report will be graded using a detailed rubric (which will be posted on Brightspace), but these are the main characteristics I am looking for: ✓ Clarity of Question: Is the research question focused, clear, and well-motivated? ✓ Appropriateness of Methods: Did you choose the correct statistical methods for your data and question? ✓ Accuracy of Analysis: Are your steps, calculations, software outputs, and technical descriptions correct? ✓ Depth of Interpretation: This is key. Do you move beyond just reporting numbers and provide a thoughtful interpretation of what they mean in their economic context? ✓ Incorporation of Feedback: Does the report reflect thoughtful consideration and incorporation of the feedback provided on the project proposal? ✓ Clarity of Communication: Is the report well-written & organized, and easy for someone in the class to understand? Are the tables and figures clear & properly labeled? ✓ Honesty & Disclosure: Did you fully and transparently disclose your use of software, code, and AI tools as required? Submission Guidelines Please submit a single compressed file containing the following items: 1. Your PDF Report 2. Your Dataset File (e.g., .csv, .xlsx) 3. Any Code used (if you used R, Python, etc.) • File Name: Please name the .zip file using your group number, formatted with two digits: ECO320 ProjectReport GroupXX. zip • Submission: One (1) group member should submit the single compressed file to the correct assignment folder on Brightspace.
Final Review Paper Assignment: write a review paper using the theory and framework studied during the course using at least one of the chapters from Principles of Photonics. For more information on how to write a scientific review paper, read this article (https://blog.addgene.org/how-to-write-a-scientific-review-article) . Generally, follow these instructions: 1. You will review the following peer-review paper in photonics related to topics covered during the course (e.g. optical material properties, polarization, coupling, modulation, etc.): Section 1A: Lemons, Randy, et al. "Integrated structured light architectures." Scientific Reports 11.1 (2021): 1-8. Section 1B: Tang, Jingyi, et al. "Laguerre-gaussian mode laser heater for microbunching instability suppression in free-electron lasers." Physical review letters 124.13 (2020): 134801. 2. Identify one or more elements of the paper that you’d like to review, discuss, and elaborate further using your own calculations beyond the content of the paper using the principles learned in class (e.g. polarization, light modulation, etc.), and organize your paper title, abstract, and body accordingly. Some ideas for modeling and calculating for the papers although you're free to choose your own: Section 1A: Can you calculate Data Points on the Poincaré Sphere and validate/invalidate the results presented? Can you reconstruct or model the complex wavefronts and match them with intensity profiles? Can you quantifiably study the effect of discretization in high-fidelity structure synthesis? Section 1B: Can you find and calculate alternative methods of producing donut-shaped intensity beams with fixed polarization? Are there any other non-Laguerre-Gauss modes you could study in this scientific application? Can you improve the laser heater beamline by changing other parameters of the laser, for example, wavelength? And what technology would you use for that? 2. Write a short (3-page minimum, plus references/citations) review paper to demonstrate your understanding of the concepts studied, and to practice your analytical skills and scientific writing. Use this template (universal-template.docx) (https://bruinlearn.ucla.edu/courses/214370/files/21857448) (https://bruinlearn.ucla.edu/courses/214370/files/21857448/download?download_frd=1) 3. The first-round review cycle will be carried out by uploading your 3-page PDF to Canvas, the second and final submission will be done via eScholarship (as noted in the next point). Note that only high-level stylistic and content feedback will be provided in this first review cycle. It is your responsibility to address the grading criteria and make sure that the editorial process is completed following the guidelines here. 4. When finished, upload the final version in PDF to the UCLA ECE Unit scholar repository (see screenshot and video), eScholarship (https://escholarship.org/uc/ucla_ece). Once the submission is confirmed, submit the URL link of your review paper in the corresponding Canvas assignment. This assignment will not be completed until the URL link has been submitted through Canvas. Grading criteria: 1. You demonstrate that you understand the concepts you are reviewing and their broader relevance in the science, engineering, and applications of photonics in the broader society. 2. You demonstrate that you can critically examine and explain the theory/data in a paper using concepts learned in class using your own formulae, calculations, or analytical methods 3. You use adequate paper review criteria and format, including structure, scientific writing, and citation style. To learn more about how to evaluate scientific literature and sources, apply the CRAP test (https://library.hccs.edu/evaluatingsources/test) . Examples and resources: Here's one review article (https://escholarship.org/content/qt28g8j92g/qt28g8j92g.pdf) you can use as an example. This article is longer than the assignment and contains more sections than you'll need so just take it as a general example but not as a template. For general tips on how to write a good, succinct scientific review paper, read this article (https://www.nature.com/articles/d41586-020-03422-x) in Nature. You can check the UCLA Undergraduate Science Journal (https://uclausj.weebly.com/) for more examples, resources, and support contact.
SEMTM0031: Introduction to Financial Technology (INFT) Academic Year 2025-26. Main Coursework. Release date: Friday 14/11/2025 (via Blackboard) Due date: Tuesday 09/12/2025 (1pm via Blackboard) What to submit: 7-page PDF report and all code used to generate your results Marks available: 70 Individual assessment: You should work alone on this assessment. PDF report: You should submit your answers to all questions in a single PDF file, 7-page maximum length, font size 11. Suggested approximate length for each question: Q1: ~1 page, Q2: ~1 page, Q3: ~2 pages, Q4: ~2 pages. Page penalty: 5 points deducted for every page over 7. Code files: We should be able to run your code for all your work. For each question, submit a separate Jupyter notebook containing your code for that question and give it an easily identifiable name, e.g., qu1.ipynb, qu2.ipynb, etc. Also submit your BSE.py file and any other python files that you write. Finally, if you use any input price data to configure your experiments, also submit those data files. Use of AI: Minimal - You may only use tools such as spelling and grammar checkers in this assignment, and their use should be limited to corrections of your own work rather than substantial re-writes or extended contributions of code or text. See: https://www.bristol.ac.uk/students/support/academic-advice/using-artificial- intelligence/#categories Academic integrity guidelines - For more information on the use of AI and academic integrity guidelines, see: https://www.bristol.ac.uk/students/support/academic-advice/academic-integrity/ Late submissions penalties - Please refer to the 'Due Date' section for the assessment deadline, unless you have an approved extension. Late submissions will incur late penalties. From this academic year (2025/26), under Article 24.3 of the Regulations and Code of Practice for Taught Programmes, any work submitted more than 96 hours after the deadline (or your extended deadline) will not be marked and will count as a non-submission. If you have any issues or queries, please contact the School Office via [email protected]. Question 1: You want to address the claim, “ZIP traders generate more profit than ZIC traders in homogeneous and periodic BSE markets with static and symmetric demand and supply curves”. Using BSE, configure and run a series of experiments and perform a suitable statistical hypothesis test to address this claim. Provide a brief description and motivation of your choices. Present one figure to best summarise your experimental results and interpret and explain your findings. [15 marks] Question 2: In Vernon Smith’s seminal 1962 paper, he performed a series of trading experiments. Each experiment, human participants are divided into buyers and sellers. Buyers and sellers are allocated a card with a reservation price (maximum price to buy; or minimum price to sell) and then asked to trade. When no more trades take place, a new “period” begins. At the start of the new period, buyers and sellers are re-allocated a new reservation card and asked to trade again. The experiment repeats for P periods. Results from one of Smith’s experiments (“Chart 5”) is copied below. Using BSE, reproduce Smith’s Chart 5 experimental framework as closely as you can, but replace human participants with heterogeneous markets containing approximately equal numbers of ZIP, SHVR, and ZIC trading agents. Describe your experimental configuration. Then show two plots of demand and supply, before and after market shock, with equilibrium price indicated by horizontal dotted line. Finally, plot your trading results in the same style. as Smith, with “transaction prices” on the y-axis and “transaction number (per period)” on the x-axis and dotted lines indicating theoretical equilibrium price and the start/end of each period. Describe how your results compare with Smith’s results. You can re-run your market as many times as you like, but you should only show results from one representative run. [20 marks] Smith Chart 5: Reproduced from Vernon Smith (1962), An experimental study of competitive market behaviour, Journal of Political Economy, 70(2), pp. 111-137. (Available online: PDF). Question 3: BSE includes a Minimal Market Maker MMM01, which has three configuration parameters with default settings: n_past_trades=1, bid_percent=0.5, ask_delta=25. Your task is to systematically explore MMM01 parameter values to determine a set of robust values that maximise profits. To do this, you should test different vectors of parameter values by configuring a series of BSE experiments with various market conditions, perform enough IID runs to get useful data, and then perform. data analytics, visualisation, and hypothesis testing to draw valid conclusions. Finally, clearly state the three parameter values that you select as your best performing configuration – we will call this best configuration MMM01*. To achieve a high mark, you should carefully consider the market configurations that you will use to test MMM01 profitability: your configurations should include at least one market that incorporates real pricing data as input to offset supply and demand; and at least one market that does not incorporate real pricing data as input. You should also carefully select the length of simulations that you will run and the number of repeated IID trials, N. Finally, consider which other trader types you will include in the market. You should clearly state your configurations and provide a brief justification of why you have chosen these configurations. When presenting results, you should minimise the number of figures you present – i.e., only include figures that are necessary. [20 marks] Question 4: BSE also includes a Minimal Market Maker MMM02, which contains identical code to MMM01. (Code for Trader MMM02 is listed in BSE.py lines 2302-2512: the “respond” method is listed in BSE.py lines 2390-2467.) Your task is to edit the logic of MMM02 within BSE.py to improve its performance. You should describe your new MMM02 logic and rationale for including this logic. You should then perform a series of BSE experiments to compare the performance of MMM02 against MMM01* (where MMM01* is configured using the best parameter values that you discovered in Question 3). To do this you should perform. enough IID runs to get useful data, and then perform data analytics, visualisation, and hypothesis testing to draw valid conclusions. [15 marks]
Coursework Assessment This assessment takes the form. of a group (up to 6 students in each group) coursework research project. Groups will be assigned semi-randomly with LMO (see details in group choice assignment). The coursework project is the assessment for the ECO204 module with a weight of 30% of the final mark for the module and includes group mark the same for all group members (80% of individual CW mark) and individual peer assessment component (20% of individual CW mark). The objective of the project is to apply what you have learned in the module to solve a problem of economics, finance, or related areas. In particular, this can include following methods: • Linear algebra tools: systems of equations, matrix inverses. • Calculus tools: partial and total derivatives, gradients, implicit differentiation tools. • Optimization tools: constrained and unconstrained optimization of functions of several variables. • Dynamic tools: simple single ODEs and their equilibria The project should contain four parts (in brackets is the associated area of evaluation, as per recent marking descriptors): 1. The statement of the problem you address in economic or financial terms (20%),(AS) 2. The formulation of the problem in mathematical concepts (30%),(KU) 3. The analysis and solution of this mathematical problem (35%),(KU) 4. An economic interpretation of the solution (15%), (MQC) where the percentages in the parentheses indicate the proportion each part takes in the grading. The grading of the project will depend on the following factors: 1. The clearness of the statement and the significance of the problem. 2. The correctness of the mathematical formulation of the problem and its solution. 3. The correctness and depth of the economic interpretation of the solution. See the marking grid and marking descriptors for KU, AS, MQC respectively in separate files for further details. Each group should submit a report, with no less than 3000 no more than 5000 words, through LMO by 23:59, 15 December, 2025 (subject to further adjustments after assessment dates approval). You will find a separate assignment section for this purpose. Backup: If for some reason submission through LMO fails, students can send their coursework to the module leader via e-mail: [email protected] The typical coursework project should consist in taking a version of an economic model of those being discussed during module (or equivalent), solving it fully and analyzing the comparative statics with different parameter values. The main purpose of the CW task is to train in constructing and solving analytically the theoretical model. Students are encouraged to use any real world data to illustrate and support their findings, but the coursework with no theoretical model and only empirical research will be graded as unsatisfactory. Please refer to examples of successful courseworks for further guidance. You are also encouraged to discuss your coursework topic and methods with tutors and the module leader. Free-rider policy: If any group member after formation of groups fails to communicate with his/her group-mates and next fails to answer ML’s e-mail queries, he/she will be kicked off the group and will have to complete the CW project alone. If complaint on the free-rider arrives too late in the semester, group-mates may reflect the free-riding by selecting ‘0’ in peer-assessment part. Peer-assessment policy: Each group member is asked to assess the participation of all his/her group mates. This assessment is anonymous (not known to other group members). The resulting peer-component mark is average from marks received by the student from all other group members and weighs 20% of the final CW mark for each student. If a student receives ‘0’ from all his/her group-mates, there is a penalty automatically computed by the system for his/her final CW mark irrespective of the group mark. In particular, he is then considered free-rider and receives 0 for the CW project. Late submission policy: Each 24 hours after deadline the penalty is 10 points, late submissions more than 5 days late are not accepted by any channel. The list of exemplary models which can be used as a basis for the coursework can be found throughout the textbook examples and those discussed in lectures. List of exemplary topics and examples of successful coursework projects from previous years will be provided. Students are also encouraged to independently search the literature for prototype models.
INST0092 Mathematics and Statistics in Information Studies Conducting statistical analysis and reporting findings on immigration to the UK This assignment counts as 100% of the total course assessment. Scenario You are working as a data analyst for a governmental body working on UK's migration. As part of a larger project, which aims to produce accurate forecasts on immigration to the UK, you have been asked to analyse historical data on immigration to the UK of British, European (i.e. from a country that is part of the European Union, noted as EU) and Non-European (Non-EU) citizens. The main aim of the brief is to conduct a list of data analysis tasks on historical data and present findings in a 2,500-word report to be circulated amongst senior stakeholders. Dataset The dataset can be found on Moodle in the Assessment section titled “Immigration Figures in the UK.xslx” in the tab “Assessment Dataset”. The source of the dataset is the House of Commons and the Office for National Statistics (ONS) and it was downloaded through Statista, which you can access using your UCL account: House of Commons, & Office for National Statistics (UK). (May 22, 2025). Number of immigrants entering the United Kingdom from 4th quarter 1991 to 4th quarter 2024, by citizenship (in 1,000s) [Graph]. In Statista. Retrieved August 13, 2025, from https://www-statista-com.libproxy.ucl.ac.uk/statistics/284038/immigration-figures-uk-by-citizenship/ Tasks The list of tasks that you must complete as part of this assessment is as follows. 1. Provide an analysis of the levels of immigration to the UK by citizenship and overall using descriptive statistics and using only formulas on Microsoft Excel. 2. Evaluate your calculations (i.e. ensure they are correct) using Microsoft Excel's Data Analysis toolkit. Presented statistics should be described in the report, for a general audience. Any salient results must be highlighted. 3. Senior stakeholders are assuming that non-EU immigrants make on average over 40% of total immigrants to the UK (EU, Non-EU and UK) every year. You must test this claim. On your report, present the test performed and its findings, highlighting any salient results. 4. Your report must include visuals demonstrating how immigration to the UK is trending. You should demonstrate trends for each citizenship group and overall, using appropriate plots and statistics which are clear, readable and address the task. For any models that you develop present and interpret the results on your report. Based on the visualisations you produce and your calculations, to what extent can these models be trusted in your opinion? 5. Your report must also feature future projections. These must be supported by appropriate visualisations. Any assumptions made must be disclosed, the accuracy of those projections must also be reported. Consider including in your report potential measures that would help improve the accuracy of the projections. Report Structure Ensure that your report follows this structure: · It begins with an “Executive Summary”, that summarises in less than a page, the key findings of your work. · Executive Summary is followed by the “Introduction” that introduces the reader to the report, including the broader context (i.e. what is this report about and who is it for) and practicalities of the work (e.g. the dataset utilised, the report’s structure, or details about the accompanying Excel file). · The main body of the report includes a section for each one of the tasks, titled appropriately (e.g. “Dataset Summary”, not “Task 1”). · The report concludes with the “Conclusion” that summarises in 2-3 sentences the work that was performed and then highlights pathways forward, answering for example questions such as “How could this work be continued? What is worth exploring next?”. References and Captions For all visual components make sure you include a properly numbered 'Figure Caption' below each one, which includes enough context that the figure and caption make sense on their own. Any references should be provided using footnotes according to the Chicago Manual of Style, and you should include a properly formatted works cited page. Deliverables The coursework is comprised by 2 deliverables: 1. A Microsoft Excel spreadsheet: The Microsoft Excel file containing all the calculations as these are required in the Tasks listed above. It would be useful to use clear structure (e.g. employing different tabs), appropriate formatting and whenever necessary to include brief descriptions to support the work conducted. 2. Findings Report: A written report 2,500 words long (maximum) that follows the structure noted above (in the “Report Structure” section) and features the work described in the “Tasks” section. The report must be professionally presented, as it is meant to be circulated with the senior governmental stakeholders and policy makers. Submission Details Two separate files must be submitted: 1. The Microsoft Excel spreadsheet (.xlsx) file The file name should consist of Student Number (SRN) + module code e.g. "12345678-INST0092.xlsx". 2. The written report in PDF format (.pdf) The file name should consist of Student Number (SRN) + module code e.g. "12345678-INST0092.pdf". The first page of the written report must provide: (1) our student number (SRN); (2) The module code and title; (3) The lecturer's name. Generative AI This assessment is “Category 2. GenAI tools can be used in an assistive role”. You are allowed to use AI tools to improve your writing, or to help you with your learning (e.g. to help explain parts of the textbook, or of the theory and examples covered in class). It is critical that this assessment is your own, original, piece of work, consisting of your own technical work (calculations) and critical reflection (report). Your report must include a statement at the end of the paper outlining how you have used generative AI or other writing aids (if at all). This statement is not included in the word count. Word count The following do not count towards the word-count: · Text on tables and visualisations · List of references · Acknowledgement of any use of AI Your submission MUST comply with the UCL regulations about plagiarism which are available from the UCL website at https://www.ucl.ac.uk/students/exams-and-assessments/plagiarism Marking Rubric Assessment Criteria A 70%+ B 60-69% C 50-59% D 40-49% Below 40% Implementation & Presentation of Descriptive Statistics (20%) An excellent implementation and presentation of descriptive statistics on the spreadsheet and the report, providing an excellent summary of the dataset. Implementation and presentation of descriptive statistics is good, providing a complete summary of the dataset. Implementation and presentation of descriptive statistics is satisfactory, providing a partial summary of the dataset. Implementation and presentation of descriptive statistics is basic, providing a limited summary of the dataset. Descriptive statistics are poor or missing. Implementation & Presentation of Statistical Test on the Percentage of Non-EU immigrants (25%) The statistical test provided is excellent in its implementation and presentation, addressing the question concerning the percentage of non-EU immigrants to an excellent degree. The statistical test provided is good in its implementation and presentation, addressing the question concerning the percentage of non-EU immigrants to a good degree. The statistical test provided is satisfactory in its implementation and presentation, partially addressing the question concerning the percentage of non-EU immigrants. The statistical test provided is basic in its implementation and presentation, providing a limited response to the question concerning the percentage of non-EU immigrants. The statistical test concerning the percentage of non-EU immigrants is poor or missing. Implementation & Presentation of Immigration Trends Analyses (25%) The implementation, presentation and evaluation of immigration trends analyses are excellent, featuring all necessary models, visualisations, and critical reflection. The implementation, presentation and evaluation of immigration trends analyses is good, covering models, visualisations, and critical reflection to a good extent. The implementation, presentation and evaluation of immigration trends analyses is satisfactory, providing some models, visualisations, and critical reflection. The implementation, presentation and evaluation of immigration trends analyses is basic, providing limited models, visualisations, and critical reflection. The implementation, presentation and evaluation of immigration trends analyses is poor, or missing. Calculation and Presentation of Immigration Projections (25%) Immigration projections and their visualisations are excellent accompanied by exemplary critical reflection on accuracy and measures for improvement. Immigration projections and their visualisations are good accompanied by critical reflection on accuracy and measures for improvement. Immigration projections and their visualisations are satisfactory accompanied by some critical reflection on accuracy and measures for improvement. Immigration projections and their visualisations are basic accompanied by limited critical reflection on accuracy and measures for improvement. Immigration projections and their visualisations and critical reflection are poor or missing. Quality of the Spreadsheet & the Report (5%) The spreadsheet containing the calculations is excellent in its presentation, featuring a clear and easy to navigate structure and helpful comments. The report is exemplary, very well structured and professionally presented. Figures are captioned and relevant external references are provided and correctly cited in-text as well as in a separate list of references. The spreadsheet containing the calculations is good in its presentation, well-structured with some helpful comments. The report is good, well-structured and presented. Figures are captioned and some relevant external references are provided and cited in-text as well as in a separate list of references. The spreadsheet containing the calculations and the report are satisfactory in their presentation, structure and formatting. The spreadsheet containing the calculations and the report are basic in their presentation with limitations concerning their structure and formatting. The spreadsheet containing the calculations and the report are poor in their presentation.
DAT 5566: Big Data and Cloud Computing Fall 2025, Mini B Lab #3 INSTRUCTIONS 1. This is a group assignment to be completed during the lab. 2. ONLY utilize the codes we practice. 3. Due on Canvas. 4. Submit on Canvas. ASSIGNMENT In this assignment, we are going to work with a dataset called CarSale.csv located on our server. The data has several columns, as explored in the previous assignments. Answer questions on Canvas. No need to submit the codes. Questions Part 1- Linux command practices 1- Take a look at the data. Is there any car that is reported more than once? You need to answer. For this, we look at VIN of the car. Look at 2 rows to make sure there is no duplicated car. 2- Find the 5 cars that sit on the market for longest time. Report the days on market, make_name, and model_name. Make sure to have the appropriate header names too. 3- Let’s find the average price for all rows using AWK. 4- Let’s make the previous question more complex. Then let’s find the average price, and number of cars per year using AWK. In addition, add a header for your results. Do a sort according to years in ascending format. 5- Let’s make a smaller data by selecting only columns 1,2,4,12,13,15,18,19, and 23. Also consider only cars of years 2000 and beyond. Part 2- Importing data into Hive/Impala 6- Creating table and uploading file into the table: a. Upload the merged file into HDFS. Then create a table in Hive called your IDS_carsale. For example, in a group with two teammates with SIDS as 111111 and 222222, the table name is going to be 111111_222222_carsale. This table is going to include carsale data, then, make it corresponding to the data. b. Upload the merged file into the created table. Part 3- Query with Hive/Impala 7- Find the maximum, minimum, and average days on market per body type. Do not list null body types. 8- Find the average price and number of cars, per color, per condition (new or not). List only rows with more than 100 cars. Which combination is the most available ones? 9- Find the number of cars, average and maximum price per car maker, car model, and condition (new, used). If the car is new, tag it as “New”, otherwise as “Used”. Report only rows with more than 250 cars. Part 4- Clean up the assignment 1- Remove the table that you created. 2- Remove both car sales files on home directory.
DAT5567 – Prescriptive Analytics Fall 2025 Module 5: Linear Optimization with Integer Variables Lab Problem Set Required Problems: 1-3 Please upload to Canvas both the .ipynbfile as well as an .html or .pdf rendering of that file with the solution output displayed. You can solve the problems in a single notebook or in separate notebooks (but please label them clearly). You are not required to provide the mathematical formulation (but are strongly encouraged to have it handy before you start writing your code). Additional optional problems: 4-5 Problems labelled with an asterisk (*) are more challenging Problem 1 (Fixed Cost) Radford Castings can produce brake shoes on six different machines. The following table summarizes the manufacturing costs associated with producing the brake shoes on each machine along with the available capacity on each machine. If the company has received an order for 1,800 brake shoes, how should it schedule these machines? a. Formulate a (mixed-) integer linear optimization model for this problem. b. Construct a PuLP model for this problem and solve it. c. What is the optimal solution? Problem 2 (Set-covering) Health Care Systems of Florida (HCSF) is planning to build a number of new emergency-care clinics in central Florida. HCSF management has divided a map of the area into seven regions. They want to locate the emergency centers so that all seven regions will be conveniently served by at least one facility. Five possible sites are available for constructing the new facilities. The regions that can be served conveniently by each site are indicated by X in the following table: a. Formulate a (mixed-) integer linear optimization model to determine which sites should be selected so as to provide convenient service to all locations in the least costly manner. b. Construct a PuLP model for this problem and solve it. c. What is the optimal solution? Problem 3 (Minimum Order) Clampett Oil purchases crude oil products from suppliers in Texas (TX), Oklahoma (OK), Pennsylvania (PA), and Alabama (AL), from which it refines four end-products: gasoline, kerosene, heating oil, and asphalt. Because of differences in the quality and chemical characteristics of the oil from the different suppliers, the amount of each end product that can be refined from a barrel of crude oil varies depending on the source of the crude. Additionally, the amount of crude available from each source varies, as does the cost of a barrel of crude from each supplier. These values are summarized below. For example, the first line of this table indicates that a barrel of crude oil from Texas can be refined into 2 barrels of gasoline, 2.8 barrels of kerosene, 1.7 barrels of heating oil, or 2.4 barrels of asphalt. Each supplier requires a minimum purchase of at least 500 barrels. The company owns a tanker truck that picks up whatever crude oil it purchases. This truck can hold 2,000 barrels of crude. The cost of sending the truck to pick up oil from the various locations is shown in the column labeled “Trucking Cost.” The company s plans for its next production cycle specify 750 barrels of gasoline, 800 barrels of kerosene, 1,000 barrels of heating oil, and 300 barrels of asphalt to be produced. a. Formulate a (mixed-) integer linear optimization model that can be solved to determine the purchasing plan that will allow the company to implement its production plan at the least cost. b. Construct a PuLP model for this problem and solve it. c. What is the optimal solution? Problem 4 (Trasportation) Tropicsun is a leading grower and distributor of fresh citrus products with three large citrus groves scattered around central Florida in the cities of Mt. Dora, Eustis, and Clermont. Tropicsun currently has 275,000 bushels of citrus at the grove in Mt. Dora, 400,000 bushels at the grove in Eustis, and 300,000 at the grove in Clermont. Tropicsun has citrus processing plants in Ocala, Orlando, and Leesburg with processing capacities to handle 200,000, 600,000, and 225,000 bushels, respectively. Tropicsun contracts with a local trucking company to transport its fruit from the groves to the processing plants. The trucking company charges a flat rate of $8 per mile regardless of how many bushels of fruit are transported. The following table summarizes the distances (in miles) between each grove and processing plant: Tropicsun wants to determine how many bushels to ship from each grove to each processing plant to minimize the total transportation cost. a. Formulate a (mixed-) integer linear optimization model for this problem b. Create a PuLP model for this problem and solve it. c. What is the optimal solution? Problem 5* Universal Technologies, Inc. has identified two qualified vendors with the capability to supply some of its electronic components. For the coming year, Universal has estimated its volume requirements for these components and obtained price-break schedules from each vendor. (These are summarized as “all-units” price discounts in the table below.) All-units price discounts work as follows. Take Vendor A and Product 3 for example. If 1,400 units are purchased from Vendor A, each of the 1,400 units costs $56 each, and the total cost is $56*1,400=$78,400. Universal s engineers have also estimated each vendor s maximum capacity for producing these components, based on available information about equipment in use and labor policies in effect. Finally, because of its limited history with Vendor A, Universal has adopted a policy that permits no more than 60% of its total unit purchases on these components to come from Vendor A. a. Formulate a (mixed-) integer linear optimization model that finds the minimum-cost plan for Universal. b. Construct a PuLP model for this problem and solve it. c. What is the optimal solution? d. Suppose that Vendor A provides a new price-discount schedule for component 3. This one is an “incremental” discount, as opposed to an “all-units” discount, as follows. Unit price = $60 on all units up to 1000 Unit price = $56 on the next 1000 units Unit price = $51 on the next 500 units With the change in pricing at Vendor A, what is the minimum purchasing cost for Universal, and what is the impact on the optimal purchase plan (compared to Part (c))?
AD 616: Enterprise Risk Analytics Assignment 5 What to submit? Please submit (i) a Word file explaining in detail your answers to each question (you can use screenshots of the Python to explain your answers) AND (ii) an ipynb file with a separation for each question. For each question, make sure you develop the model and present the simulation results – the ipynb file should be self-explanatory. The assessment of your work will include both the accuracy and the clarity of your Word file and the Python Code. Question 1: Bayesian Investment Decision Problem: Real estate decision with a consultant Hint: You do not need Python code to answer this question A real estate speculator is considering buying property at a resort island for $400 thousand. The local government is considering a proposal to rezone the property for commercial use, which has the potential to increase its value drastically. Once the government makes its decision, the speculator would lose the chance to purchase the property. As it stands, there’s a 30% chance the property will be rezoned. If it were rezoned, there’d be a 20% chance the speculator can incite a bidding war over the property and sell it for $3 million; there’d be a 40% chance he could interest a developer in the property and sell it for $1.8 million, and even if neither possibility played out, he could still sell it for $700 thousand. If the property isn’t rezoned, there’s a 25% chance he could resell it and recoup $300 thousand, but failing that, he would be stuck with a useless property, which would increase his liability by an additional $100 thousand. The real estate developer discusses his options with a trusted consultant, who offers to look into the political situation on the island for a flat fee of 50 thousand dollars. The consultant has a good reputation; she has a 90% probability of correctly identifying that a property is going to be rezoned, and a 70% probability of correctly identifying that the motion to rezone a property will fail. While he’s considering her offer, she mentions another possibility: if he’s willing to pay her an additional $75 thousand (for a total of $125 thousand), she’ll use that money to make some generous campaign contributions to some of the island’s key government officials in exchange for future considerations. She estimates, with this strategy, the chance the property would be rezoned after the speculator’s purchase would increase to 60%, but there would be a 5% chance one of the island’s less enterprising functionaries would catch wind of her efforts. In this instance, the speculator would end up losing the amount he paid her, eating the cost of the property, and paying an additional $1.5 million in fines. Question 1 tasks: 1. (1pt) What is the expected value (EV) of buying the property outright without hiring the consultant? 2. (2pts) What is the EV if the speculator only hires the consultant for 50K (report only)? Assume the speculator will only buy when the report is positive. 3. (2 pts) What is the EV if the speculator hires the consultant for both reporting and campaigns (125K)? Which option should the speculator choose? Question 2, Markov Chain Monte Carlo: Imagine you are working for a financial analytics firm and are tasked with assessing the expected return of a volatile stock. The stock's return is believed to follow a normal distribution with unknown mean μ and known standard deviation σ = 2% (i.e., 0.02). You are given the following historical monthly return data (in decimal format): 0.021, 0.017, -0.005, 0.023, 0.019, 0.025, -0.003, 0.020, 0.018, 0.021 You are to construct a Bayesian model to infer the posterior distribution of the unknown mean return μ. Assume the following prior: μ ~ Normal(0, 0.01) 1. (1 pt) Write the unnormalized log-posterior function for μ, given the data and assumptions. Hint: The formula for the unnormalized log-posterior is 2. (2 pts) Implement the Metropolis-Hastings algorithm to sample from the posterior distribution of μ, using a normal proposal Run the sampler for 10,000 iterations with τ=0.00, starting at μ=0. 3. (1 pt) Plot the histogram of the samples and report the posterior mean and 95% credible interval for μ. 4. (1 pt) Comment on how prior beliefs influence the posterior. What happens if you use a wider prior
OLET1201 Business Entrepreneurship: Business Models Description Your task is to analyse a business model case through the concepts and methods covered in OLET1201 learning materials (in-class, and in the relevant readings), supported by relevant sources of information (e.g., venture reports, news articles, and other reputable sources). To do so, you will choose a case of an established company, research about its early beginnings, and discuss the changes applied to its business model over time. The analysis must include: ● A brief introduction (1 paragraph) that compares and contrasts the venture from when it started to it's current form. today. ● A clear explanation of how the venture's Business Model Canvas has changed over time. ● An elaboration of the problems or opportunities that may have prompted such changes. ● A reflection on how design and design thinking methods may have facilitated the venture's transformation. Overall, the analysis should uncover the key components and assumptions of your chosen venture's business model, utilising the Business Model Canvas to do so. Wordcount: 1500 words (+/-10%); (excluding references)
MATH2040/6131 Financial Mathematics Assignment 2025/26 This Assignment counts as 20% of your overall mark for this module. Completed work should be submitted on Blackboard before 23:59 on Monday 15 December 2025. This deadline is strict and the standard University penalty for late submission of work will apply. To submit your work, go to the Assignments tab in the Blackboard page, where you will find an assignment called Coursework submission 2025/26. Please submit the following two files: • A report in a file named report-ID.pdf, where ID is your student ID number; • An Excel spreadsheet in a file named spreadsheet-ID.xls, where ID is your student ID number. Note that all your results, explanations, and discussion must be presented in your report, and all calculations and simulations must be done in your Excel spreadsheet, without use of Macros/VBA. Therefore please avoid using expressions such as “Please see the spreadsheet” in the report. The strict page limit of the report is 4 A4 pages, and a font size of no smaller than 11pt should be used. The report should be written in a coherent manner, with careful explanation, and should be self contained and well presented. [It may help to think of yourself as a graduate trainee, with the report to be submitted to your line manager.] The spreadsheet should be clearly set out, with the calculations and simulations relating to different parts of the questions clearly identified. Your work should be entirely your own, and in accordance with the University Academic Integrity Guidance. 1. An electricity generation company is considering an investment project involving the construction, operation, and eventual decommissioning of a coal-fired power station. Construction is expected to take three years, and to cost £420 million, payable in equal instalments at the start of each year. Once constructed, the power station is expected to enjoy 40 years of operational life, to produce an annual output of 3 billion kWh of energy, and to incur an annual operating cost of £120 million, both of these annual figures being spread uniformly throughout the year. At the end of its operational life, it will be necessary to decommission the power station, a process that is expected to take two years and to cost £100 million, payable in equal instalments at the start of each year. The company has no spare funds to finance the project, but may borrow the construction costs from its bankers, who charge an effective annual rate of interest of 5% on borrowings and pay an effective annual rate of interest of 3 1 2% on deposits. (a) Determine the minimum price (in pence per kWh) at which electricity must be sold if this project is to just break even, and find the length of time that must elapse before the company will have repaid its bank indebtedness at this minimum price, assuming that borrowings may be reduced by repayment at any time. [15] (b) If the price at which electricity may be sold is twice that found in part (a), find the accumulated profit achieved by the company on this investment project at the end of the project term. [5] (c) The above model for the project involves various assumptions and expectations. Identify, discuss, and investigate these, using a spreadsheet to explore the impact of changing these aspects in order to make the model more realistic and/or to test its robustness to such changes, and take note of the corresponding risks. [30] [Total 50] Note: You may find Example 5.5 in the lecture notes helpful for part (a). 2. An equity fund manager at an investment firm models the future performance of the fund, as follows: it is assumed that, in each year, t, the corresponding annual effective yield, it , is independent of that in any other year, and is such that the corresponding accumulation factor, 1 + it , is lognormally distributed, with (constant) parameters µ and σ2 , so that log(1 + it) ∼ N(µ, σ2). The mean and variance of it are assumed to be j = 0.09 and s2 = (0.05)2 , respectively. [Here, log means the natural logarithm.] The fund offers investors a choice of two three-year investment products, with the following cashflows: • A single investment of £1 million made at the start of the three-year period. The accumulated value, X, of this single investment is returned to the investor at the end of the three-year period. • An annual investment of £1 million made at the start of each of the three years. The accumu-lated value, Y , of this total investment is returned to the investor at the end of the three-year period. (a) Calculate the mean and standard deviation of X. [2] (b) Calculate the mean and standard deviation of Y . [4] (c) Calculate the values of µ and σ 2 . [2] (d) Calculate the 95% confidence limits for X. [4] (e) Using simulation, estimate the mean, the standard deviation, and the 95% confidence limits for X, and compare with your exact results obtained in parts (a) and (d). [Use 10,000 simulations of X.] [8] (f) Using simulation, estimate the mean, the standard deviation, and the 95% confidence limits for Y . [Use 10,000 simulations of Y .] [8] Another fund manager at the investment firm has questioned the validity of the modelling assumption that the annual effective yield, it , in year t is independent of that in that in any other year. He has suggested that the model be generalised to allow for a degree of dependence between the annual effective yields in successive years, by letting log(1 + it) ∼ N(µt , σ2), where µ1 = µ and µt = µ + k [log(1 + it−1) − µ] for t ≥ 2. Here, the parameter k satisfies 0 ≤ k ≤ 1 and controls the degree of dependence, the case k = 0 corresponding to the assumption of independence used by the first fund manager. (g) Using simulation, estimate the mean, the standard deviation, and the 95% confidence limits for X under this generalised model, for both k = 1/2 and k = 1. [Use 10,000 simulations of X.] [6] (h) Using simulation, estimate the mean, the standard deviation, and the 95% confidence limits for Y under this generalised model, for both k = 1/2 and k = 1. [Use 10,000 simulations of Y .] [6] (i) Discuss all of your results. [10] [Total 50] Note: Use a fixed seed for your simulations, and state the seed you use, so that the random numbers generated are reproducible.
(CPT301/25-26/S1) Notes: ◼ To obtain full marks for each question, relevant and clear steps should be included in the answers. ◼ Partial marks may be awarded depending on the degree of completeness and clarity. Section I: Short Answer Questions Question A: Basic Logic [20 marks] a) The following temporal logic formulas are not simple enough. Each formula could be replaced with a concise version that presents the same property. Please refine these formulas and justify your answer. (“concise” means “small” or “have few symbols”) i. (□◊r) U (p U q) [2 marks] ii. ¬◊¬(p S q) [2 marks] b) Prove the validity of the logic expression below using both Truth Table and Natural Deduction: ((p → q)) ├ (r∨p) → (r∨q) [7 marks] c) Is the following temporal logic property valid? Here, p and q are arbitrary state formulas. (◊□q∨◊□(¬p)) ⇒ ◊□(p→□q) [4 marks] d) Let p be a Boolean variable of a system. The property is described as follows: In a sequence q0, q1, q2, q3, … of states, t holds in even states q0, q2, q4, … and has arbitrary values in the other states. Construct Büchi automata according to the following requirements: i. Accepting exactly all behaviors that do NOT satisfy the above property. [2 marks] ii. Accepting exactly all behaviors that have no suffix that satisfies the property. In other words, for any suffix qn, qn+1, qn+2, qn+3 … it should NOT be the case that p is true in all of the states qn, qn+2, qn+4, … [3 marks] Please justify your answer. Question B: Z Specification [25 marks] Define types STATE ::= Alive | Dead and CELL = ℤ × ℤ. CW game can be represented as an infinite two-dimensional grid where each cell is either alive or dead. Formally, this can be modeled as a function CWState : CELL → STATE where CELL denotes the set of all grid positions (for example, Z 2 ), and STATE is the set {Alive,Dead}. a) Define a schema CWState that contains exactly one schema variable, CWState. [2 marks] The schema’s state predicate must ensure that every possible value of boardState corresponds to a valid board configuration. b) Write the schemas ∆CWState and ΞCWState in full. [4 marks] c) Write a schema InitCW which inputs a variable piece? : CELL → STATE , and sets the board up according to piece? . [4 marks] d) The cell (x , y) is adjacent to the cell (xt , yt ) when they share an edge or a corner. For instance, the grey squares below are adjacent to the black square: Write a predicate adjacent on CELL×CELL such that adjacent ((x , y ), (x t , yt )) is true precisely when (x , y ) and (x t , yt ) are adjacent. [4 marks] e) Specify ln : CELL → (CELL → STATE ) → ℕ which returns the number of Alive neighbours of a cell under a given board s : CELL → STATE. Use adjacent to count only neighbours of c. [2 marks] f) Using ln, define a total function nextCell : CELL × (CELL → STATE) → STATE that encodes exactly these transitions: An Alive cell with fewer than 2 Alive neighbours becomes Dead. An Alive cell with 2 or 3 Alive neighbours stays Alive. An Alive cell with more than 3 Alive neighbours becomes Dead. A Dead cell with exactly 3 Alive neighbours becomes Alive. Write a schema CWTransition specifying the transitions of the board. [6 marks] g) Write a schema Tick that relates the board before and after one clock tick by pointwise application of nextCell. Use a change schema and make the post-state equal to the cellwise update. [3 marks] Question C: Temporal Specification [15 marks] a) This question concerns the representation of natural language descriptions in temporal logic. Consider the following transition system T and the list of LTL formulae φ1, . . . , φ4. φ1 :□(a ⇒ ◊c) [2 marks] φ2 : ◊(b ⇒ ¬a) [2 marks] φ3 : ◊□ (b∧c) [2 marks] φ4 : (a∨b∨c) U c [2 marks] For each formula φi, i : 1 ≤ i ≤ 4, check whether T |= φi holds or not. Justify your answer for each formula. b) Write a temporal logic formula that precisely captures the semantics of the following program fragment. The formula should describe the evolution of the variables a and b over the next one or two steps, depending on the branch taken. Necessary explanations are required. ( || means nondeterministic choice: the system may execute either a := 2*a or b := 2*b, but not both.) [7 marks] if (a > b) then a := a - b; b := b + 1; elseif (a < b) then b := b - a; a := a + 1; else ( a := 2*a || b := 2*b ) // nondeterministic choice, one step End Section II: Short Report [40 marks] Question D: Model Checking Model: Use the provided Promela system with processes P, Q, shared x,y,b, and rendezvous channel t. See the following given Promela code. byte x = 0; byte y = 0; bool b = false; chan t = [0] of { bit }; active proctype P() { do :: x < 20 -> atomic { x = 20; b = true } :: x >= 0 -> if :: x < 30 -> x++ :: else -> x = 10 fi :: t?1 -> y++ od } active proctype Q() { do :: (x >= 10 && b) -> t!1 :: (x < 10) -> atomic { x = 0; b = false } :: else -> skip od } Report 1. Behavior. overview: Describe plausible executions and outcomes (e.g., unlatched vs. latched regimes; effects on x, y, b) with 1–2 short execution sketches. 2. Property set: Specify ≥3 safety and ≥3 liveness properties relevant to this model. Provide the exact formulas you verify. 3. Verification experiments: Show command lines and results. For each property, report Hold / Fail / Inconclusive with brief evidence (stats; short annotated counterexample for failures). 4. Impact of model variants (≥2): Propose two minimal changes (e.g., channel capacity, adjusting/removing atomic, guard tweaks, progress/fairness modeling). Predict effects, re-verify, and compare results concisely (before/after table + root-cause note). 5. Word limit: ≤1000 words. Note: The use of generative artificial intelligence tools is not permitted in the preparation of this report. All text, analysis, and arguments must be produced independently by the student without AI assistance. Presentation (Scheduled for Week 13). • 8 minutes to present your approach and findings. • 5 minutes for Q&A. Marking Scheme Report [20 marks] R1. Property design & correctness [8 marks] • 0–3: Fewer than 3 safety or 3 liveness; major logic mistakes or poor relevance. • 4–5: Meets minimum; mostly well-formed temporal logic; some mismatch/redundancy. • 6–7: Clear, relevant, non-trivial set; good coverage of key behaviors; sound justification. • 8: Precise, minimal, insightful portfolio; captures edge cases; excellent rationale. R2. Verification experiments & rigor [6 marks] • 0–2: Minimal setup; unclear commands/options; sparse evidence. • 3–4: Commands shown; at least one option varied; basic stats reported. • 5: Multiple options compared; reproducible workflow; coherent methodology. • 6: Systematic exploration; well-organized, easily reproducible; clear justification of choices. R3. Evidence & counterexample analysis [2 marks] • 0: Results stated without explanation; trails missing/uninterpreted. • 1: At least one failing property with a correct, concise trail explanation. • 2: Clear, minimal trails for all failures; explains enabling guards/interleavings and why they repeat. R4. Impact of model variants — [4 marks] • 0–1: No variants or purely speculative discussion. • 2-3: One variant tested well or two variants lightly tested; partial before/after evidence. • 4: ≥2 variants tested with before/after tables and concise root-cause analysis of differences. Presentation [20 marks] P1. Understanding [8 marks] • 0–3: Disorganized; unclear model behavior; confuses safety vs. liveness. • 4–5: Mostly clear storyline; basic grasp of regimes and properties. • 6–7: Cohesive, accurate narrative tying model, properties, and results. • 8: Crisp, insightful synthesis; highlights key subtleties (e.g., scheduling/fairness) accessibly. P2. Live demo / walkthrough of verification [6 marks] • 0–2: No demo or non-reproducible steps; superficial. • 3–4: Basic run shown (commands/results); limited option variation. • 5: Competent walkthrough with options and interpreting outputs. • 6: Polished, reproducible demo; anticipates pitfalls; connects outputs to properties and traces. P3. Slides/visuals & time management [2 marks] • 0–1: Cluttered slides; over/under time. • 1–2: Clean visuals (tables/flows/trails screenshots); well-paced within allotted time. P4. Q&A [4 marks] • 0: Unable to address questions. • 1-2: Addresses basics; minor inaccuracies. • 3-4: Accurate, confident answers; can reason about “what-if” changes.
DTS305TC Natural Language Processing Coursework 2 (Individual Assessment) Due: 5:00 pm China time (UTC+8 Beijing) on Fri. 19. Dec. 2025 Weighting: 60% Maximum score: 100 marks (100% individual report) Assessed learning outcomes: C. Implement deep learning models and evaluate them based on performance metrics. D. Develop skills of using NLP models and techniques in real-world applications. Overview Document classification is a core NLP task that involves automatically categorizing written content into a predefined set of classes or categories. This process is crucial for managing the vast amounts of textual data generated daily across various domains, including news, legal documents, medical records, and online content. The key aspects of document classification include: Text Representation, Feature Extraction, Model Selection, Deep Learning Approaches, Performance Evaluation, and so on. This task faces challenges such as handling imbalanced datasets, dealing with the nuances of human language including sarcasm and context, and adapting to domain-specific vocabularies and terminologies. Tasks You are required to use the slides and Internet resources to learn the detailed knowledge of document classification problems, and use the Python programming language to complete one document classification report. 1. Background Knowledge (10 Marks) Write the following content in text form. in the report. (1) Please provide 3 real-life application scenarios that require document classification methods. (6 Marks) (2) Please analyze why document classification methods, rather than other natural language processing methods (information retrieval, document clustering), are the most suitable for these 3 application scenarios. (4 Marks) 2. Algorithm Design (20 Marks) Write the following content in text form. in the report. (1) Provide two basic processes for a document classification system. (5 Marks/system x 2=10 Marks) (2) Provide pseudocode for the algorithms (one machine learning and one deep learning) used in the document classification system in 2(1). (5 Marks/algorithm x 2=10 Marks) 3. System Implementation (40 Marks) Use Python to implement the system described in Section 2 with the following functions: (1) Main function: control the startup and flow of the entire document classification system. (5 Marks) (2) User input function: allow continuous user input of text for classification via the console. (5 Marks) (3) Database input function: read a local text library from a document folder. (5 Marks) (4) Text preprocessing function: preprocess the read documents and use 80% as training samples and 20% as validation samples. (5 Marks) (5) Classification algorithm 1: train Model 1 on the training samples using classification algorithm 1. (5 Marks) (6) Classification algorithm 2: train Model 2 on the training samples using classification algorithm 2. (5 Marks) (7) Classification algorithm performance: output the model metrics of Model 1 and Model 2 on the validation samples. (5 Marks) (8) Output function: output the classification results of Model 1 and Model 2 for user input. (5 Marks) 4. Results Analysis (20 Marks) Test your system and record the results; write the following content in text form. in the report. (1) Test the developed document classification system using ten new text examples with your own labels. (5 Marks) (2) Use recall to analyze the two different classification algorithm results (algorithm 1 and algorithm 2). (5 Marks) (3) Use precision to analyze the two different classification algorithm results (algorithm 1 and algorithm 2). (5 Marks) (4) Use F1 to analyze the two different classification algorithm results (algorithm 1 and algorithm 2). (5 Marks) 5. Conclusion (10 Marks) Write the following content in text form. in the report. (1) Describe how your designed and implemented document classification system addresses the three application scenarios in Section 1. (5 Marks) (2) Report quality, including report format, code quality, and references. (5 Marks) Submission You must submit the following files: l A PDF file named Student_ID.pdf containing a cover letter with your ID and name. l A ZIP file named Student_ID.zip containing your program implementation and output files (e.g., dataset, DCS.py, precision.csv, recall.csv, F1.csv).
Syllabus (2025-2026 Fall) GESB 1013 - Everyday Statistics Course Description People nowadays are being connected globally in various ways, and statistics plays a role in giving basic international comparison. The first part of this course introduces some basic ideas in social and economic statistics for cross-national comparison. However, statistics is always considered as a hurdle for those not strong in mathematics. The second part introduces statistics which emphasizes intuitive thinking in daily life instead of technical mathematical jargon. This will equip students with minimal statistical literacy to cope with the data saturated society with confidence, and more advanced statistics courses in future studies. Emphasis is on statistical interpretation rather than analysis. Course Intended Learning Outcomes (CILOs) CILO-1. Students will grasp the basic ideas in international statistical comparison. CILO-2. Students will interpret international comparison statistics and make implications towards cross-cultural comparison. CILO-3. Students will understand basic statistical ideas intuitively without going through technical procedures in mathematics. CILO-4. Students will interpret intuitive statistical concepts such as variability, standard distributions, correlation and relation, sampling etc. CILO-5. Students will understand and interpret statistics published by different public and private bodies. Further, based on these knowledges, students can relate these statistics in their daily life, and hence participate in some exhibitions and competitions related to statistics generally available in the society.
Introduction to Publishing Studies (ENG4123) Research Project 2: InDesign Tutorials (10%) Assessment Overview Task: Students should complete the 10 Adobe InDesign tutorial assignments, each of which requires the submission of a file on iSpace. The requirements for each submission are detailed on the final slide of each tutorial. These tutorial assignments are assessed on a pass-or-fail basis, with 1% of the total course grade allocated for each passing tutorial submission. Tutorial assignments that are not submitted or that do not meet the requirements to pass will be awarded 0. Time will be allocated in class each week for students to work with the InDesign software in the ELLS computing lab. Therefore, students are not required to purchase the software for use on their own computers (although they are free to do so if they wish). Tutorial videos are available for students to watch on their own devices outside of class hours through the Udemy online platform. Although it would be advantageous to complete the tutorials as early as possible in the semester, students are free to work through the tutorials at their own pace. For example, a student may complete all of the tutorials in the first month of the course, or choose to complete only one tutorial each week. Therefore, students are required to plan their time throughout the semester to ensure that all of the tutorials are completed before the final deadline. Weighting: This assessment is weighted at 10% of the total course score (1% is awarded for every passing tutorial). Deadline: InDesign tutorials can be submitted anytime during the semester. However, the final deadline (after which no submissions will be accepted) is Week 12, Thursday 4th December, 10am. Late Submissions: No late submissions will be accepted for this assessment. Grades & Feedback: Grades will be available on iSpace within two weeks of the submission deadline.
GECC4130 Senior Seminar Reflective Essay Guidelines Write an 800 words reflective essay on your growth, changes and inspiration in KSAV, and team collaboration through the learning experiences. Your essay should include the following sections. 1 An introductory paragraph briefly provides the main idea of your work, the team settings and your role in the project, in order that reader of the essay can make sense of the claims, situations and idea you are going to elaborate. You may state your main reflection claims in this paragraph. 2 A section that describes your growth or changes in Knowledge,Skills and Attitude &Value (KSAV) through the learning experiences of the project. You may focus on some orall KSAV areas, reflect on the interdisciplinary elements of your study and how has the study has inspired you or widened your horizon, e.g.the scope or state-of-the- art of the topic, possible stakeholders involved in the topic, approaches to problem solving, strategies and perspectives of analysis, adaptability and resilience to differences,challenges and unseen context. 3 A section that describes your growth and changes in team collaboration through the learning experiences of the project.(You may look up the delicate difference between“collaboration” and"teamwork".) With respect to the team relationships throughout your project work, how effective was the communication among members,how did the team achieve a common goal through collaboration. Under the aspect of collaboration, did you encountered any challenges and difficulties and how did you solve them;will you adopt the same solution in future;what role had you played;any insight gained or lesson learned through this group project experience. If you could put the clock back, would you play the same role, use the same communication channels, use the same tone and language, adopt the same solutions to the problems encountered? 4 A section on what you see as the positives and negatives in the following areas through the learning experience of the project: i) Conducting a study or performing a task which is out of your major academic discipline / your strengths/your interest ii) Work with individuals with different backgrounds and personalities What kind(s)of soft skills would you identify as crucial and significant in working with teammates of diverse backgrounds,personalities,generations and cultures?(You may look up wordings like “personal soft skills”or“social soft skills”.)
1210W Art and Ritual in Asia Research Project The primary goal for this course is to investigate the role of art in the “ritual” context, and how its existence as an object with a purpose beyond the aesthetic affected the choices made by the creators of the object (artist, ritualist, patron). Thus, the research assignment for this class is to choose an object or substance which has both aesthetic and ritual uses in Asia and describe how it “works” in one or both aspects. Why choose to make an incense burner in the shape of a mountain? How did concerns about the well-being of the ancestor spirits shape the spaces used to contain their physical remains? Why inscribe the palms of Buddhist sculptures with flowers and wheels? Does a stand of bamboo outside of a teahouse transform. the experience of the tea being consumed within it into something beyond the quotidian desire for a pick-me-up? The subject you choose, therefore, is relatively open, but it must have a tangible ritual component. That is, you must *describe* something—a vessel, a sculpture, a temple—and discuss how the ritual use helped determine its shape. Then you should research the cultural and material context of that thing. What is it? What is it made from? In what environment is it most commonly found? How was it acquired/used by different types of people? Step 1: Choose a topic or object of interest. This is an initial exploration of your topic and a test for feasibility. Can you find enough secondary information to write a 1750-2500 word research paper on the object? Step 2: Develop annotated bibliography of at least 7 peer-reviewed sources. The development of the annotated bibliography often results in a revision of your initial thesis. This is good! Revise appropriately according to the new information you have learned from sources. Then construct a bibliography in proper CMOS 18 style. Add a paragraph (3-4 sentences) after each entry explaining how it will support your argument. Step 3: Prepare a “thesis paragraph.” After you have received feedback regarding your annotated bibliography, write a 4-6 sentence proposal, including an argumentative thesis statement which provides a tentative outline out your paper. Step 4: Complete a draft of your paper. This should be a full edited text with footnotes. You should include an image of your primary object of focus, but you do not need to include a full bibliography with this draft. This draft will undergo a review by your class peers, as well as myself. Step 5: Revise your final paper based on the peer review and my comments, and polish it according to the “art history paper guidelines” found on Brightspace, including: · Title page · Paginated research paper with footnotes following research paper formatting guidelines · Figures (images of your object and comparisons) · Bibliography of sources used, formatted in proper Chicago, Notes-and-Bibliography, Style. (CMOS 18) · Pdf (or folder) including screenshots/photos of specific citation pages
