ENERGY 722, 2025 - Assignment 3 Wind Resources & Turbines Assignment objective: Show your understanding of the Wind Resources & Turbines Lectures. This assignment is expected to be undertaken completely independently. Due Date: 11.59pm, 28 April 2025, submitted online through Canvas. Lateness policy: If you cannot complete the assignment in time due to extenuating circumstances, please contact Michael MacDonald in advance of the deadline to arrange an extension. If an assignment is submitted late (without a prior extension) a penalty of 10% (of the total marks available) per 24 hours will be deducted. No assignments will be accepted more than 48 hours late without prior arrangement. Value: 20% of your final grade for the ENERGY722 course. Show your working where appropriate. You will be graded for lay-out and format (e.g., correct referencing, clear figures, appropriate number of significant figures given, clearly stated assumptions, etc.) as well as correct numerical results. Queries: Please direct questions on content to Michael: [email protected]; General questions to Bart: [email protected] Marking sheet: Total Available Marks Q1 4 Q2 5 Q3 5 Q4 4 Q5 10 Q6 6 Overall work, lay-out, presentation 4 Final mark 38 Question 1: [4 marks] Three profiles from different sites are given below (in the figure and table). By fitting the logarithmic velocity profile (assume K = 0.4), estimate the roughness lengths for the three sites. State what ground surfaces these roughness lengths likely represent. Question 2: [5 marks] Two possible sites for wind turbines are suggested: A. one, in a dense forest (z0 = 0.4 m) near a city where a mean wind speed of U10 = U(z = 10 m) = 7.1 m/s was measured, and which could support a wind turbine with a hub-height of 60 m and blade length of 26 m; and B. two, a remote, snow-covered open terrain (z_0=0.0019 m) with U_10=10.4 m/s which could only support a wind turbine with hub height of 44 m and blade length of 22 m. For both scenarios, compute the power available in the wind using the logarithmic velocity profile, using the wind velocity at the hub height and assuming it is constant over the entire swept area. State which of these two sites you think is preferable and explain why. You should consider potential features of the site (stating any assumptions) in addition to the potential power available. Question 3 [5 marks] The original Brooklyn Wind Turbine was constructed in 1993 and became an icon of Wellington. It was recently replaced in 2016 with an even larger wind turbine. Citing your source(s) state the name, class and size (hub height and blade length) of the two turbines. Why was this particular turbine class chosen? Next, find the annual energy output and compute the capacity factor of the original and new wind turbines. Briefly explain why the capacity factors might be different. Question 3 [5 marks] The small town of Ōpunake (near Mt Taranaki) wants to install a wind turbine near the town, to attract tourists and provide enough electricity for approximately one third of households/dwellings in the town. Stating your assumptions and references, provide an approximate estimate of the size (blade length) of the wind turbine required. You can neglect any vertical variation from any wind speed mapping data you use and simply assume an appropriate capacity factor and turbine efficiency. Question 4 [4 marks] You work for a small consultancy specialising in projects involving wind energy. Your company has been engaged to give some information to a power company on wind turbine sizing and power production for a possible wind turbine. The power company has narrowed down its choices to two possible wind turbine designs, both with a rated power of 810 kW, and a hub height of 60 m. The wind turbine is to be located near a collection of industrial buildings, with a roughness length Z0 = 0.2 m. Long term meteorological records for wind speed and direction at an open grassland terrain (Z0 = 0.002 m) near the proposed site are available from an anemometer mounted at a height of 20 m. They have been analysed, and it has been found that the distribution of wind speed (irrespective of direction) can be fitted by the Weibull distribution, with the parameters: A = 0.9, C = 11.0, k = 2.0. The Weibull distribution is given by (1) Differentiating the Weibull distribution results in the probability density function yields (2) Answer the following questions. Include working where appropriate; excel sheets or code scripts (e.g. Matlab/Python) can be uploaded to Canvas as separate files. a) Plot the probability density function for the wind speed at the hub height of the wind turbine. Show how you computed the appropriate value for C. b) An ENERCON E-48 turbine is proposed to be used on the site. Using the manufacturers data (see the pdf attached), compute the capacity factor and annual energy output (AEO) for this turbine. Assume the cut-out speed is 28 m/s. Show your working (e.g. an excel spreadsheet or Matlab/Python script). c) The second proposed turbine is the ENERCON E-53. Repeat your analysis from b) for the E-53 to compute the capacity factor and AEO. d) Explain why your answers for b) and c) are different, despite the two turbines having the same rated power. Question 6 [6 marks] Discuss the advantages and disadvantages between horizontal and vertical axis wind turbines, in less than a page (excluding references). Where possible, relate the discussion to concepts taught in lectures. Include situations/locations where you expect each turbine to be used, and why they are suited for those locations.
BUSOBA 2321 – Group Exercise 2025 Spring Semester Due Monday, April 21st at 11:59pm · File Name (1%) – Save your solution as “BusOBA 2321 – Group XXX” – inserting your 3-digit group number for the “XXX” · Cover Page (4%) – add all team members names and dot numbers as indicated. o List names in alphabetical order by last name o No more than 4 members to a group; your assigned group is available on Carmen. o If a member does not contribute, do not include their name on the cover sheet. o If a team member is unresponsive or inaccessible through Monday, April 14th, let your instructor know and that person will be dropped from your group. o Individual submissions will be accepted but will incur a 20% deduction from the grade earned, unless otherwise discussed with your professor. · There are 4 problems: a decision-making problem, a decision tree, an optimization and sensitivity analysis, and a network model. · Submit the worksheet via Carmen. o 1 submission per group using the provided template. · Your submission includes 9 total worksheets: o Cover sheet – 1 sheet o Decision making - 1 sheet o Decision tree – 2 sheets o Optimization/Sensitivity – 4 sheets § “Problem 3 Table” requires no work but must be included. o Transshipment – 1 sheet · Up to 20% will be deducted for “non-professional” reports – neatness and formatting count. · Incomplete assignments will receive a grade of zero. · Should the grader feel a poor effort was made the entire assignment will receive a zero. · If the assignment is submitted late all members will receive a reduction of 33% per day. · Solver MUST be complete (i.e., executable) for problem 3 and 4 in your final submission or you will receive a ZERO for each problem that is missing the solver details! If group members used Excel Online to share the excel workbook with group members or if a problem was copied from another workbook, the solver program may not transfer with the copied/shared files. Each group is responsible for checking its final submission to ensure that solver is properly filled out for each problem. Should solver be missing or not run for a problem the group will receive a zero for the problem. It is advised to complete the group exercise in Teams rather than trying to combine various files. · Some advice for completing the Group Exercise o The Group Exercise is designed to be COMPREHENSIVE – to include almost everything covered in the course. o The Group Exercise is designed to IMPROVE YOUR ABILITY TO USE THE COURSE MATERIAL, to solve problems, to apply simple logic and algebraic principles in the solution of business issues. o The Group Exercise provides all the information you require to solve the problem, but not always in a straightforward array of data – you may have to THINK THROUGH THE PROBLEM. o The Group Exercise includes somewhat complex problems which are designed to be completed through DISCUSSION AND COLLABORATION. o The Group Exercise is designed to PREPARE YOU FOR THE FINAL EXAM. o The Group Exercise is not designed as a DIVIDE AND CONQUER assignment – assigning individual group members to an individual problem, then assembling these individual efforts into a finished project will not be in any group member’s best interest. · Work together, work early. You will be given chances to work with your group during lecture and recitation, where instructors and TAs are available to help you. During these sessions, and during office hours, we will easily recognize those who have not put any work or thought into the assignment and we will defer helping you until we feel you have put work and thought into the project. · And, in case you missed our earlier subtle hints: Question 1 Decision Analysis The OSU Athletic Department is trying to sell tickets to their fanbase for the National Championship. The CFP committee has given OSU Athletic Department a ticket inventory of 45,000 tickets to sell on a variety of ticket platforms including StubHub, Ticketmaster, Vivid Seats, Seat Geek, OSU Facebook Groups, and GroupMe. The OSU Athletic Director, Owen, must create a payoff table to decide which ticket platforms to allocate the ticket inventory to maximize profitability. The ticket demand is affected by four different scenarios: · The first scenario involves quarterbacks for Ohio State and Notre Dame both suffering season ending injuries in the week leading up to the championship game. Since both starting QBs are injured, demand is low for the game on established platforms. · The second scenario includes Lou Holtz tweeting, “If Notre Dame doesn't win, it's because we want to preserve Ryan Day's job. I was originally going to be at the game in spirit, but now I'll be dragging my body along as well”. Some fans think Lou Holz was being rude and therefore do want to attend the game. · The third scenario involves the OSU Dance Team winning the UDA National Championship just days before the football national championship. This has boosted morale for Ohio State fans who want to see multiple national championships, so the game has moderately high demand. · Lastly, Notre Dame cornerbacks decided to verbally state they will be playing man coverage against OSU’s receiving core (Jeremiah Smith reposted). Both groups of fans are excited about the matchup, especially with the players talking smack before. Demand is high for the game. Conditions and Constraints: The OSU Athletic Department has provided four potential market scenarios, each influenced by factors such as consumer behavior, platform. costs, and OSU policy. · Processing Fee: o The website traffic will determine the processing fees implemented on each website. o IF the website traffic is moderate, there will be no fee. o IF the website traffic is high, the processing fee will be added as a percentage of sales price. · OSU Discount Policy: o OSU made a deal with Ticketmaster & StubHub to provide a $50 discount per ticket to encourage fans to go and support the team in certain scenarios. (Hint: Refer to Market Scenario Table) PLEASE FOLLOW INSTRUCTIONS ON THE EXCEL TEMPLATE FOR EACH PART!!! **Note** Many of these scenarios did occur in real life, for the context of the problem treat each scenario independent from one another. Market Scenarios: Scenario/conditions Injured QBs Lou Holtz UDA Champs Man-to-Man Website Traffic Moderate Moderate Moderate High OSU Discount Policy Yes Yes No No Ticket Demand per Market Scenario: Ticket Platforms Injured QBs Lou Holts UDA Champs Man-to-Man StubHub 3000 11000 16000 10000 Ticketmaster 2000 10000 9000 17000 Vivid Seats 1000 6500 11000 14000 Seat Geek 7000 12000 8500 7000 OSU Facebook Groups 3000 3500 4000 6000 Some Sketchy GroupMe 4000 3500 2000 1000 Ticket Website Cost to list Ticket Selling Price Ticket Inventory Listing Fee Processing Fee StubHub $125 $400 7000 $116,000 3% Ticketmaster $175 $580 12000 $350,000 4% Vivid Seats $110 $280 9000 $95,000 2% Seat Geek $135 $315 11000 $200,000 1% OSU Facebook Group $85 $225 3500 $0 0% Some Sketchy GroupMe $50 $150 2500 $0 0%
Project 2: Quantitative Trading Strategy Construction and Evaluation Introduction Effectiveness in Finance research and industry necessitates a facility with data aggregation, combination, selection, and manipulation. Building on the foundational skills acquired in Project 1, this project extends the focus to the construction, implementation, and evaluation of a quantitative trading strategy. In this project, students will integrate price data from multiple sources, compute stock returns, derive volatility measures, and construct equal-weighted portfolios sorted by total volatility. The objective is to investigate whether a volatility- based long-short strategy can generate statistically and economically significant returns. Beyond technical implementation, this project emphasises communication and presentation skills simulating the real-world task. Students will prepare a written report and deliver a group presentation to showcase their methodology, findings, and insights. By completing this project, students will: • Develop a structured approach to construct and test financial trading strategies; • Gain practical experience with data processing and portfolio analysis in Python; • Enhance their ability to communicate technical findings to a professional audience. This project offers a comprehensive, applied learning experience that reflects the expectations of roles in quantitative finance and investment analysis. The Source Files All required files are included in a zip archive with the following structure: |__ project2/ | | | |__ __init__.py | |__ config.py | |__ project_desc.pdf | |__ util.py | |__ zid_project2_characteristics.py | |__ zid_project2_main.py | |__ zid_project2_portfolio.py | |__ zid_project2_etl.py | | | |___data/ | | | example_prc.csv < This is a sample file provided for testing purposes only> | | | where • project2/ represents the main folder containing all the project files. • config.py, zid_project2_main.py, zid_project2_etl.py, and zid_project2_characteristics.py contains the functions you need to write for this project. These are the files you need to submit. • project_desc.pdf is the PDF version of this document. • data/: This is the sub-directory where you save data files for this project. You will find a sample file provided for testing purposes only. • config.py is the configuration module for this package. • util.py is the module that contains auxiliary functions. You should not modify this file. Instructions Important: This project is a group project. Do not exchange complete or partial codes with students from other groups. Please do not post any project related questions in public online forums, marks will be deducted if this rule is violated. Preparing the files for this project 1. Copy the project2 folder into the toolkit project folder. Afterwards, your toolkit folder will look like: toolkit/
SUMMER TERM EXAMINATIONS 2018 ECON1004: INTRODUCTION TO MATHEMATICS FOR ECONOMICS TIME ALLOWANCE: 2 HOURS Answer ALL FIVE questions in Section A and TWO questions from Section B. Each question in Section A carries 10 marks and each question in Section B carries 25 marks. In cases where a student answers more questions than requested by the examination rubric, the policy of the Economics Department is that the student’s first set of answers up to the required number will be the ones that count (not the best answers). All remaining answers will be ignored. SECTION A 1. Define the rank ofa matrix. Explain how to find the rank of (i) an echelon matrix, (ii) a general matrix. Find the rank of 2. Define the terms positive definite and positive semidefinite as applied to quadratic forms. Determine directly from the definitions whether the quadratic form. q(x1, x2, x3 ) = x1(2) + x2(2) + x3(2) - x2x3 is (i) positive definite, (ii) positive semidefinite but not positive definite, (iii) neither of these. 3. Suppose the production function of an economy is Q = F(K, L) where Q, K and L denote aggregate output, capital and labour respectively and F(K, L) is a smooth homogeneous function of degree s where s is a positive constant. Suppose further that K and L have the same constant proportionate rate of growth m. Use the chain rule and Euler’s theorem to find the rate of growth of output. 4. Find the gradient vector and the Hessian matrix of the function 3x2 - 6xy + y4 + y2 . Verify that (1,1,-1) is a critical point and determine whether it is a local maximum, local minimum or neither. 5. A consumer has a utility function U(x1, x2 ) = x1(3)x2 where xi denotes the consumption ofthe i-th commodity. If the price of the i-th commodity is pi and the consumer’s income is m, express the consumer's problem as a constrained maximisation problem. Write down the Lagrangian for the problem and obtain the first-order conditions. SECTION B 6. (a) Define the term echelon matrix and say what the 4 types of echelon matrix are. Hence show that the number of solutions ofthe simultaneous linear equations Ax = b is 0, 1 or infinity where A is an m×n matrix, x is a vector in R n and b is a vector in Rm . (b) Given that the equation ABx = d , where has a solution, find k. 7. (a) For the function f (x, y) = -3cx2 + 2cxy - y2 - 2x + 5y where c is a constant, find the gradient vector and the Hessian matrix. For what values of c is f (x, y) concave? When c=2, explain how you know that any critical point of f (x, y) must be a global maximum point. Hence find the global maximum. (b) Suppose the profit of a firm is given by the smooth concave function Π(x1, x2 ) where x1 and x2 denote the output levels of the two products which the firm manufactures. Write down conditions, in terms of the first-order partial derivatives of Π , sufficient for the profit to attain its global maximum value at (a, b) . In the particular case where Π(x1, x2 ) = -2x12 + 4x1x2 - 3x22 +10x1 -14x2 - 3 verify that Π is concave and find the profit-maximising output levels and the maximum profit. 8. Consider the production function Q = (K1/ 2 + L1/ 2)2 where Q, K and L denote output, capital and labour respectively. Show that the isoquants are negatively sloped and convex. Find the coordinates of the points where the isoquant, along which Q takes the value c, (c > 0) , meets the K and L axes. Find also the slope of this isoquant at each of these points. Sketch the isoquant diagram. When the prices of capital and labour are r and w respectively, find the conditional input demand functions and the total cost function. Find also the elasticity of substitution. 9. Consider the differential equation where a and b are constants with a ≠ 0 . Find the stationary solution, the complementary solution and the general solution. Find also the range of values ofa for which the stationary solution is stable. Now consider the following two difference equations: (i) Δyt + ayt = b , (ii) Dyt + ayt = b where Δyt = yt +1 — yt , Dyt = yt — yt—1 and a and b take the same values as in (*). For each difference equation, find the stationary solution, the complementary solution and the general solution. Find also the range of values of a for which the stationary solution is stable. For each of the following statements, say whether it is true or false, giving reasons for your answer: (a) If the stationary solution of the differential equation (*) is stable, then the stationary solution of at least one of the difference equations (i) and (ii) must be stable. (b) If the stationary solution of at least one of the difference equations (i) and (ii) is stable, then the stationary solution of the differential equation (*) must be stable. (c) There is a set of values of a for which the stationary solutions of the differential equation (*) and the difference equations (i) and (ii) are all stable.
ASSESSMENT GUIDE MGMT5050 Responsible Business Professionalism Term 1, 2025 Welcome to the course Dear student Welcome to MGMT5050 – Responsible Business Professionalism. This course may be unlike other courses you’ve taken at university. There are no tests or exams. There is no off-by-heart learning. There is no simple calculation to guarantee success. Instead, this course aims to transform. you as an individual, a student, and a developing professional through a deep focus on sustainability, ethics, leadership, and responsible professionalism. There are three main main components to the course: 1. Pre-class activities In preparation for each week’s learning, you’ll work through current, stimulating multimedia content accessible on Moodle. This will open your mind to new ways of thinking about the course’s topics. 2. Synthesis & Integration (S&I) session (replaces traditional lectures) In these weekly interactive sessions, your lecturers will share vital content to support your learning. We encourage you to attend, ask questions, and connect with your peers. 3. Learning in Practice (LiP) session (replaces traditional tutorials) In the LiPs, your tutor will guide you on a journey of self-growth, supporting your development of critical competencies to support you in the workplace and beyond. We are passionate about this course and can’t wait to take this learning journey with you. Submission guidelines The Assessment guide includes several icons. Here’s what each one means: Keep the following in mind when submitting your assessments: Turnitin Turnitin checks your work for originality and proper citation. It compares your submission with other students’ work, online content, and selected resources. If you need to submit via Turnitin, you’ll find the link on your Moodle course page. More details are available on the Turnitin student information site. Submitting your assignments • Ensure you submit the correct assessment using the right link on Moodle. After the deadline, no changes can be made. • Upload your work as a Word document (not PDF). • All times are in Australian Eastern Standard/Daylight Time (AEST). Viva Voce You might be asked to do a viva voce for any submitted assignment. This is an interview where you discuss your assignment to show your understanding and preparation. Late Submissions Late submissions lose 5% of the total mark per day. After five days past the due date, the submission will receive a zero grade. Papers are considered late if: • Assignments have been submitted in the wrong format. • An incorrect assignment has been submitted. This refers specifically to a paper from another course. If you submit a draft/incorrect version of the assignment, what is submitted by the deadline is what will be graded. Extensions Plan ahead to meet deadlines. Extensions are only given if Special Consideration is awarded. There will be no extensions for the 10 Minute Debriefs, Reflective Wikis or class participation. Special Consideration The Special Consideration process helps if unexpected events affect your ability to perform in an assessment. It applies when such events prevent completion or submission of work or significantly affect performance. Click this link to see a list of example circumstances. You can apply for Special Consideration via the central UNSW Special Consideration portal onmyUNSW(see My Student Profile > Special Consideration). Assessment 1: Memo Week 3: 1pm, Friday 7 March (AEST) 15% Written organisational memo: documenting the work and the process 750 words +/-10% plus reference list (the reference list is not included in this word count limit) Via Turnitin Description of assessment task You are a recent graduate working at TechNova, a global technology company renowned for its cutting-edge consumer electronics, including laptops, smartphones, and wearable devices. TechNova has long been recognised for its commitment to innovation and sustainability, having taken steps to reduce its environmental footprint by optimising energy efficiency in manufacturing, adopting recyclable packaging, and investing in renewable energy for its production facilities. However, you have noticed a growing issue that threatens to undermine TechNova’s sustainability efforts: electronic waste (e-waste). As the company continues to release new product lines at a rapid pace, older devices are quickly becoming obsolete. Many customers discard these products, contributing to the global e-waste crisis, which poses serious environmental and health risks. While competitors are finding innovative ways to tackle this, TechNova has yet to take substantial action to address this issue. You are concerned that this lack of action not only harms the environment but also risks damaging TechNova's reputation as a responsible company. You decide to write a memo to the CEO, outlining your concerns and proposing actionable solutions to address TechNova's e-waste problem while still maintaining its focus on innovation and growth. Given multiple pressures on your time, you decide to use GenAI to help you get started: Your memo should: • Outline your concerns, highlighting their importance, considering TechNova’s commitment to sustainability. • Discuss the significance of environmental sustainability in the technology industry and TechNova’s potential role in addressing the growing e-waste problem. • Make recommendations on how TechNova can remain a leader in sustainability while continuing to innovate and grow. • Incorporate the UN SDGs, reflecting TechNova’s commitment to responsible consumption and production. To support your thinking, look at thefollowing extractfrom the United Nations Institute for Training and Research’s (UNITAR) 2024 report: The Global E-waste Monitor 2024. You must reference this extract in your memo. (For your interest: clickherefor the full report) Assessment 1: Supporting information What is a memo? A memo is an internal professional document that you would give to your manager to advance an idea. It must be clear, factually correct, and supported by credible evidence. Click here for guidance on how to write a report. How to use GenAI in this task? 1. Create the base memo: Create a base memo using GenAI (e.g., ChatGPT, Co-Pilot, Claude). 2. Add your own input: Apply your own critical thinking to the AI-generated text and make necessary enhancements. Use track changes in the text to show any changes that you’ve made to the text. Use comments to explain your additions/deletions/refinements. o Carefully fact-check the AI-generated content. Any incorrect or discriminatory content will be considered unsatisfactory. o Memos that rely solely on AI-generated content without significant personal input will be deemed unsatisfactory. You are expected to change, rewrite or adjust at least 50% of the memo’s content. 3. Ensure Academic Integrity Disclose your prompt: o Include the prompt you used to generate the base memo at the beginning of your memo. Referencing o Use the Harvard referencing system to acknowledge sources used. o Ensure all citations are accurate and credible. o Using false citations will trigger an integrity investigation, which may result in your submission being escalated to the Conduct and Integrity Office (CIO). AI-Generated Content: o Cite your use of GenAI. Click here to access theUNSW guide for referencing AI Use o Any work detected as GenAI, if used incorrectly, inappropriately, or without proper citation, will be investigated. This may lead to your submission being escalated to the CIO. AI Usage Report: o Turnitin will generate an AI usage report for your submission. o This report will not be available to students but will be visible to your marker. Other task requirements: Use of Course Materials: • You should ONLY use the extract from the UNITAR (2024) report linked above and materials from Weeks 1 and 2 of this course. This includes the S&I lectures, LiP workshops, and materials from the Pre-Learning Modules available on Moodle. Originality and Language Requirements: • Your work must be written in your own words. Do not write your paper in another language and then translate it into English. This will be considered computer-generated work and may be escalated to the Conduct and Integrity Office. Format requirements • 12-point font, Arial or Times New Roman • Harvard referenced • 1.5 line spaced • Left justified • Must be uploaded in a Word document with track changes shown and comments to the document to show your thinking and progress of work. Submission instructions Submit via the Turnitin submission link under the Assessment Hub on Moodle. Supporting resources and links Writing and academic support We recognise that writing can be challenging, and we’re hereto support you. In MGMT5050 we offer access to Studiosity within the course as part of this first assignment. Studiosity is the official online writing support service for UNSW, offering detailed and personalised feedback on your work. It is accessible online from anywhere, and it provides both real-time and on-demand support. You can access this additional help through the Assessment Hub on the course Moodle site. Additional academic support If you need additional help with writing, referencing, speaking, or presenting, the Business School offers online academic writing and communication modules, communication workshops, and additional online resources. Click here to read more about the Business School’s learning support and tools. You can also book a free one-to-one consultation through the Business School to support your learning. Click here to find out more. Assessment 2: Report Week 7: 1pm, Friday 4 April (AEST) 30% Written report, components task 1700 words +/- 10% plus reference list (i.e., the reference list is not included in this word count limit) Via Turnitin Description of assessment task As a Master’s graduate, you will be expected to produce professional reports in the workplace. This assessment allows you to apply key tools and concepts while demonstrating the skills you’ve developed in the first half of the course. Rather than submitting a full report, you will complete a series of report components, helping you understand and practice the report-writing process. Meta (formerly Facebook Inc.) is one of the largest technology companies in the world. It owns Facebook, Instagram, WhatsApp, and other platforms. Its2024 Sustainability Reportacknowledges that “our size and global reach give us the opportunity — and the responsibility — to drive sustainable change across our industry” . However, it faces serious sustainability and ethical problems that affect its reputation and the world. You must choose ONE of the following critical issues to focus on in your report: 1. Energy use and environmental footprint o Meta’s data centres and infrastructure consume massive amounts of energy to power its platforms. While the company has committed to renewable energy, concerns persist about the carbon footprint of its expanding operations, especially as demand for VR, AI, and data storage grows 2. Misinformation and social polarisation o Meta’s platforms, particularly Facebook and Instagram, have been criticised for spreading misinformation, fostering “echo chambers,” and amplifying political and social polarisation. 3. Privacy, Data Use, and Trust o Meta’s handling of user data, including privacy breaches and the ethical implications of targeted advertising, continues to spark debate about transparency, trust, and protecting personal information across its platform. Using your chosen critical issue, produce the following five report components. Part A: 5W framework (150-200 words) Use the 5W framework (Who, What, Where, When, Why) to summarise your chosen issue. Address each of these directly and structure this as a short, well-organised narrative (not dot points). • Write in the 3rd person (e.g., “Meta. faces this issue…” rather than “I think…”). • Support your points with in-text citations. Part B: PESTEL analysis & summary (250-300 words + PESTEL grid) • Create a PESTEL grid: Conduct a PESTEL analysis (Political, Economic, Social, Technological, Environmental, and Legal factors) in a 6-box grid format. Use dot points to keep ideas concise. (The PESTEL grid is not counted in the wordcount). • Summarise your findings: based on the grid, write a short narrative summary explaining how these factors impact Meta. and the chosen issue. Write in the 3rd person. • Clearly connect PESTEL insights to the critical issue and include citations. Part C: Ethical analysis (±750 words) Use your PESTEL analysis to identify 2 or 3 key concerns related to your chosen issue. These concerns should notably impact stakeholders, society, or the environment and require ethical consideration. Explore each concern in detail by answering: o What is the concern? Describe the problem and use evidence (e.g. examples/data) to show its impact. o Why does it matter? Explain why Meta should care. o How does it relate to ethical and sustainability principles? Link the concern to relevant SDGs. Apply an ethical framework (e.g., utilitarianism, deontology) to explain its ethical importance. Use other course concepts/theories like stakeholder theory, ESG, or CSR to strengthen your argument. Explain the consequences: Show how ignoring the issue could harm Meta’s success or sustainability goals. Write clearly and professionally in 3rd person and include in-text citations. Part D: Recommendations (±250 words) Based on your ethical analysis, propose 2 or 3 actionable recommendations for Meta. For each recommendation: • Identify potential risks of implementing this recommendation • Suggest risk management strategies to minimise these risks. • Write in the 3rd person and provide supporting citations. Part E: Reflection (±250 words, 1st person writing) Reflect on your learning experience while completing this task. Some questions you could consider are: • How did this task shape or challenge your understanding of sustainability, ethics, and Meta's role in these areas? • What assumptions did you initially have about your chosen issue, and did they change as you conducted your research? • If you were to redo this assessment, what would you approach differently, and why? • Which specific skills did you strengthen through this process? Write this section in the 1st person (e.g. “I learnt…”). Do not use GenAI (like ChatGPT/CoPilot) for this section. It must reflect your personal learning journey. Finally, include an end-text Reference List (using Harvard referencing style) • If you have used GenAI, remember toacknowledge it on your Reference List. If you use GenAI to generate initial ideas or outlines, include your prompt(s) at the end of your report. Assessment 2: Supporting information How to research for this assessment? You are required to undertake academic research to complete this case study report, finding at least 3 additional journal articles to support your work. Use available resources through the UNSW Library catalogues, databases and collections, or other appropriate sources. You can link your UNSW account to Google Scholar, enabling easy access. If you are uncertain how to conduct a library search, please reach out to: https://www.library.unsw.edu.au/research/support-for-your-research Or https://www.library.unsw.edu.au/about-unsw-library/contact-us Your three additional journal articles must come from the following journals: Academy of Management Journal Academy of Management Perspectives Academy of Management Review Business Horizons Organization Science Organizational Dynamics Organization Studies Journal of Management On the Reference List, put the articles you’ve used from the list above in bold. You may also use other credible sources in your research. For example: • Materials used in the course. • Articles from other peer-reviewed academic journals. • Popular media articles from credible sites. • Corporate/organisational reports • NOTE: Conference proceeding papers are not appropriate sources for this assessment. Do not use them. How to use GenAI in this task? Permitted Use: You may use GenAI tools, software, or services to help you generate initial ideas or outlines. If you use GenAI, include your prompt(s) at the end of your report. Requirement for original work: The ideas or content generated by AI must be thoroughly developed or reworked by you. • Your final submission should reflect your own work, not what was originally produced by the AI tool. • In this assessment, we are not looking for perfect English use. Instead, we will assess your ability to insightfully and originally apply the course material to the critical issue you have chosen. We want to read your ideas in your voice. Do not use Grammarly/GrammarlyGO to replace your original text. Language requirement: Do not write your paper in another language and then translate it into English. This will be considered computer- generated work and may be escalated to the Conduct and Integrity Office (CIO). Record Keeping: Keep copies of all iterations of your work to provide to your Course Authority if there are any questions regarding the originality of your submission. Addressing Concerns: If your Convenor believes that your submission includes AI-generated text or media that has not been adequately modified, you may be asked to explain your work. Academic Integrity: If you cannot satisfactorily demonstrate your understanding of your submission, you may be referred to the UNSW Conduct & Integrity Office for an investigation into potential academic misconduct, which could lead to penalties. How to show academic integrity in Assessment 2? • Include in-text citations and a Reference List using the Harvard Referencing system. • On the Reference List, bold the articles you’ve used from the journals on the required journal list above. • Cite and acknowledge any use of GenAI, including ChatGPT, Copilot, Quillbot, GrammarlyGo, Baidu Education and BARD. • Any false citations and/or work detected as unethical, inappropriate or incorrect use of GenAI will be investigated. Violations may lead to your submission being escalated to the CIO. Format requirements • 12-point font, Arial or Times New Roman • Harvard referenced • 1.5 line spaced • Left justified • Must be uploaded in a Word document Submission instructions Submission must be made via the Turnitin submission link under the Assessment Hub on Moodle. Supporting resources and links Writing and academic support Studiosity is the official online writing support service for UNSW, which is aimed at providing detailed and personalised evaluation and feedback of your written work. It is accessible online from anywhere and it provides both real-time and on-demand support. For assignment 2, click here to access the service as this is provided outside of the course: Additional academic support If you need additional help with writing, referencing, speaking, or presenting, the Business School offers online academic writing and communication modules, communication workshops, and additional online resources. Click hereto read more about the Business School’s learning support and tools. You can also book a free one-to-one consultation through the Business School to support your learning. Clickhereto find out more
Assignment 1 CSSE3100/7100 Reasoning about Programs Due: 4pm on 1 April, 2025 The aim of this assignment is to consolidate your understanding of the course's material on weakest precondition reasoning. It is worth 15% of your final mark for the course. Submission instructions: Upload a single Dafny file (A1.dfy) to Gradescope with your solutions to Q1-Q3 formatted as per the formatting instructions below. Q1 Prove the following justifying each line of your proof with a law from Appendix A of Programming from Specifications. (A ==> B) && (!A ==> B) = B (2 marks) Q2 The following program is the third suggested fix for the Zune bug (discussed in Week 1) that appeared online in 2009. At the time, one commentator said "Trying to verify correctness by pure reason—as opposed to trial-and-error testing—looks almost hopeless." Use weakest precondition reasoning to show that the code below is partially correct. method CalculateYear(d: nat) returns (year: nat) requires d > 0 ensures year == Year(d, 1980) { year:= 1980; var days := d; while days > 365 invariant days >= 0 && Year(days, year) == Year(d, 1980) { if IsLeapYear(year) { if days > 366 { days := days - 366; year := year+1; } else { days := days - 366; } } else { days := days - 365; year:= year + 1; } } } where predicate IsLeapYear(y: nat) { y%4 == 0 && (y%100 == 0 ==> y%400==0) } and Copyright Notice © This content is protected and may not be shared, uploaded or distributed. The School of EECS at the University of Queensland holds the copyright for this material. Students are not permitted to share these materials on sites external to the University of Queensland. ghost function Year(d: nat, y: nat):nat { if d > DaysInYear(y) then Year(d - DaysInYear(y), y+1) else y } ghost function DaysInYear(y: nat): nat{ if IsLeapYear(y) then 366 else 365 } (9 marks) Q3 The original Zune bug was due to the program not terminating. Additionally prove that the above program is totally correct using weakest precondition reasoning. You will need to decide on an appropriate termination metric to do this. (4 marks) Formatting instructions The proofs are to be completed in the template file A1.dfy provided on Blackboard. The template enables checking of the syntax of your predicates to avoid you making typos or misusing predicate operators. It also enables us to (partially) auto-grade your submission. For this latter reason, it is important that you carefully follow the instructions below. The file includes three methods, one for each question above. The method Q1 has inputs A and B corresponding to the predicates of Q1, and a single declaration of a local Boolean variable PS (for proof state). The proof should be written as a series of assignments to PS. For example, the proof of Exercise 1.5(c) (shown below on the left) should be written as shown on the right below. X && Y ==> Z PS := X && Y ==> Z; !(X&&Y)||Z (A.22) PS := !(X&&Y)||Z; // A.22 (!X||!Y)||Z (A.18) PS := (!X||!Y)||Z; // A.18 !X || (!Y || Z) (A.5) PS := !X || (!Y || Z); // A.5 X==>!Y||Z (A.22) PS := X==>!Y||Z; // A.22 Note that justification in terms of laws from Programming from Specifications should be included as comments. The method CalculateYear includes the code from Q2 with two additional local Boolean variables WP and WP_s. The proof should again be written as a series of assignments to WP and WP_s. WP (for weakest precondition) should be used for all predicates in the proof excepting those where a strengthening has occurred. WP_s should be used only when a strengthening has occurred, i.e., the predicate assigned to WP_s should be strictly stronger than the predicate below it. For example, the snippet of the final proof in Week 4's lecture slides (shown on the left below) should be written as shown below on the right. {s == n*(n – 1)/2 && n != 33} (strengthen with n!=33) {s == n*(n – 1)/2} (arithmetic) {s + n == n*(n – 1)/2 + n} s := s + n; {s == n*(n – 1)/2 + n} WP_s := s == n*(n – 1)/2 && n != 33; // strengthen with n!=33 WP := s == n*(n – 1)/2; // arithmetic WP := s + n == n*(n – 1)/2 + n; s := s + n; WP := s == n*(n – 1)/2 + n; Note that justification must be provided for all predicate simplifications. These need to be sufficient for a peer, e.g., someone else doing this course, to understand the step. If you refer to a function in your justification, make sure you state the property of the function you are using. For basic arithmetic, the justification can just be "arithmetic" (as above). The justification can be on the same line as the predicate or, when this would make the overall line too long, on the line following the predicate. If you use the rule proved in Q1, you may include "Q1" as justification. You also need to justify why the result of your weakest precondition calculation means the method is partially correct. Add this justification as a comment immediately above the top- most line of your proof. The method Q3 includes the code from Q2 with a ghost variable m to record the value of the termination metric (similar to the ghost variable d in the lecture slides) and two additional Boolean variables WP and WP_s. The proof is to be written following the rules given above for the method CalculateYear. The proof should begin with just the predicate required for proving termination (d > D in the lecture slides) and introduce additional predicates by strengthening if required. You need to justify why the result of your weakest precondition calculation means the method terminates. Add this justification as a comment above the top-most line of your proof. Marking For each question, you will be awarded full marks for a correct proof (formatted as described above) with each step (apart from application of wp rules) sufficiently justified. You will lose marks for incorrect proof steps or missing justification as detailed below. Q1 You will lose 0.5 marks for each incorrect proof step (capped at 1 marks), and 0.5 marks for each case of insufficient or incorrect justification (capped at 1 marks). Q2 You will lose 0.5 marks for each incorrect proof step (capped at 6.5 marks), and 0.5 marks for each case of insufficient or incorrect justification (capped at 2.5 marks). Q3 You will lose 0.5 marks for each incorrect proof step (capped at 3 marks), and 0.5 marks for each case of insufficient or incorrect justification (capped at 1 marks). For each question, additional marks (up to the total marks for the question) may be taken off for work regarded as having little or no academic merit.
218.321 Construction Estimation & Risk Semester 1, 2025 Assignment 1 GENERAL INSTRUCTIONS: 1. This is a group assignment with no more than THREE members in each group. If you choose to work alone, you may do so, but there will be no concession or difference in the final output standards expected. 2. Total marks for this assignment: 100 marks, total course weightage and contribution of the assessment component: 40% 3. Submission date: Wednesday, 30 April 2025, no later than 11:50 pm 4. Online submission on Stream: COMPULSORY. NO HARD COPY SUBMISSION IS REQUIRED 5. Late assignments will be penalised as per the course guide and the school’s policy. 6. You must include your names OR IDs, the course number, the course title and the names of the course teaching team on the cover page. 7. ONLY one student from each group must submit the assignment on stream. General Comments: • Students should form. teams and name the team members using the team choice tool on Stream by 5pm, Wednesday, 31st March 2025. If you want to do this assignment individually, you also need to form your own team in Stream. Please go to Stream/Assessment /Group Choice for Assignment. 1) Every member of each group needs to fill a survey for the peer-to-peer evaluation in Stream by: 1st May, 2025. Your evaluation will be kept anonymous. Submission Instructions: • All calculations of Task 1 and Task 2 need to be provided in an Excel Spreadsheet. • Task 3’s report can be uploaded in word/pdf file. • Please submit your files to: Stream/Assessment/Assignment 1 • Ensure the files are named correctly. o Report_Group ID o Appendix_Group ID Learning outcomes cover: • Apply advanced estimating techniques to prepare cost estimates for bill preparation, tendering, and cost planning • Evaluate design solutions with respect to the cost plans Task 1 (20 Marks): Cost Planning Scenario: A client has approached your project management consultancy with a request to prepare a detailed cost plan for a new school development in an emerging area of Auckland. This new educational facility aims to serve 500 students and includes various functional spaces such as classrooms, administrative offices, and technology laboratories. The client is committed to sustainability and expects the project to achieve an “Excellent” Green Star rating. Table 1: Project summary Site Area Description of the proposed building facilities. Green star Excellent. Approximately 4,000 m2 Approximately 1,000 m2 Approximately 1,000 m2YearQuarterIndex2022Q317992022Q418252023Q118482023Q218382023Q318412023Q418472024Q119102024Q218552024Q319212024Q419372025Q11941
SUMMER TERM EXAMINATIONS 2017 ECON1004: INTRODUCTION TO MATHEMATICS FOR ECONOMICS TIME ALLOWANCE: 2 HOURS Answer ALL FIVE questions in Section A and TWO questions from Section B. Each question in Section A carries 10 marks and each question in Section B carries 25 marks. In cases where a student answers more questions than requested by the examination rubric, the policy of the Economics Department is that the student’s first set of answers up to the required number will be the ones that count (not the best answers). All remaining answers will be ignored. SECTION A 1. State a criterion in terms of the determinant for a square matrix to have an inverse. Find the values ofa for which the matrix has an inverse. 2. Let Verify that any two of the three 3-vectors u,v,w are orthogonal. Find scalars λ, μ,v such that [λu μv vw] is an orthogonal matrix. 3. Suppose z = x ln(1+ xy) . Use the small increments formula to find an approximation to the change in z when x changes from 1 to 1+ Δx andy changes from 1 to 1+ Δy where Δx and Δy are small. Now suppose you are additionally given x = 1 + t, y = t 2 . Use the chain rule to find dz / dt when t = 1. 4. Show that the function x2 - 2xy + 5y2 -10x + 2y is convex. Find its global minimum value. 5. Find the general solution of the differential equation Also find the solutions which satisfy y=1 when t=0 and y=0 when t=1 and sketch them on the same axes. SECTION B 6. (a) Define the terms linear combination, linear dependence and linear independence as applied to vectors. Suppose a,b and c are three vectors in Rn . Show that a,b and c are linearly dependent if and only if there exist scalars α,β and γ, not all zero, such that αa+βb+γc=0 . State the generalisation of this result to the case ofk vectors in Rn . (b) Define the term echelon matrix and say what the 4 types of echelon matrix are. Hence show that the number of solutions ofthe simultaneous linear equations Ax = b is 0, 1 or infinity where A is an m×n matrix, x is a vector in R n and b is a vector in Rm . (c) Use the results in (a) and (b) to show that ifwe have a set of more than n vectors in Rn , these vectors must be linearly dependent. 7. (a) Suppose the production function of an economy is Q = F(K, L) where Q, K and L denote aggregate output, capital and labour respectively. Explain what is meant by saying (i) F(K,L) displays diminishing returns to each factor, (ii) F(K,L) displays increasing returns to scale. Now consider the special case F(K, L) = KαLβ (α, β > 0) . Find a condition in terms of α and β for the production function to exhibit decreasing returns to scale. Show that if this production function exhibits decreasing returns to scale then it also exhibits diminishing returns to each input. State, with reasons, whether the converse is true. (b) Now suppose the production function is G(K, L, t) = ertKαLβ (α, β, r > 0) and K and L have constant rates of growth m and n respectively. Find the rate of growth of output. 8. Explain what is meant by a homogeneous function of 2 variables of degree h. Show that the partial derivatives of such a function are homogeneous of degree h-1 . Show that the utility function U(x, y) = xαyβ , where α and β are positive constants, is homogeneous and state the degree of homogeneity, h. Verify that the two marginal utilities are homogeneous of degree h-1 . For this utility function, show that the slope of the indifference curves is constant along the line y = cx where c is a positive constant. Draw a diagram to illustrate this result. Now show the same result is true when the utility function is a general homogeneous function of 2 variables. 9. A consumer has a utility function where xi denotes the consumption of the i-th commodity. Show that each indifference curve is negatively sloped, convex and has two asymptotes. Find the equations of the asymptotes corresponding to the indifference curve U = c (c > 0) . Sketch the indifference curve diagram. If the price of the i-th commodity is pi and the consumer’s income is m, express the consumer's problem as a constrained maximisation problem. Find the demand functions, explaining carefully each step of your argument.
GE1205 Green Economics Term Project Guideline (30%) The Aims: 1. To describe and discuss current environmental problems/issues in Hong Kong, Mainland China, or the world that you are interested in it. (Discovery) 2. To apply economic concepts and theories to analyse the environmental problems. (Enriched) 3. Evaluate government policy implemented on the environmental problems you discovered. (Enriched) Your Tasks: 1. Your group needs to find out a current environmental problem/issue in Hong Kong, Mainland China, or the world that you are interested in it. 2. Collect news and necessary data related to the environmental economic problem or issues. 3. Describe the environmental problem/issue you have selected. 4. Use the economic concepts and theories you have learnt to analyse the environmental problem/issue. 5. Give your opinions, comments, and suggestions to the environmental problem/issue. Assessment (30%): 1. Written Report (20%) 2. Presentation (10%) Length: The report should be typed using single-sided, double-spacing, 12-point font, and include page numbers. Do not exceed 12 pages. Tables, diagrams, and Appendix are excluded from the page limit. Deadline: The deadline of the written project is (Wednesday, 23rd April 2025). Please submit one software copy (in PDF) through Canvas by the deadline. Late submission receives zero marks. Presentation: Each group will be given around 20 minutes to present in week 11 to week 13 through Zoom. Note that week 10 is project preparation week and no class will be held in week 10.
MATE7016: Materials for Energy Conversion and Storage Introduction. (3 marks) In the introduction or background, student should clearly write the purpose of the experiment, the real-life applications of Li-ion batteries, how Li-ion batteries works, equations (if needed), challenges faced by commercial Li-ion batteries, how advanced Li- ion battery anodes may solve these problems (350 words). Methods. (4 marks) Student should briefly write the steps involved in the scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDS) characterisations, manufacturing of the Li-ion coin cells, and the electrochemical measurements (with parameters) of the coin cells. Include the purpose of using these methods whenever appropriate. (Passive form) (300 words). Results. (4 marks) The loading weight* of the two electrodes shall be calculated. Students need to include the following figures obtained from the experiment for the two electrodes: 1a) SEM image of the graphite electrode, 1b) SEM image of the Cu6 Sn5 electrode, 1c) EDS mapping of graphite electrode, 1d) EDS mapping of Cu6 Sn5 electrode along with Table 1) EDS quantitative analysis results. Students shall also plot the results generated in the electrochemical characterisation: 2a) voltage (V) vs. capacity (mAh); 2b) voltage (V) vs. gravimetric capacity (mAh g-1). The plots can be generated using excel or origin software. Example: Analysis and Discussion. (4 marks) Students should discuss the morphologies and particle sizes of the two electrodes as observed in Figure 1a and b. The chemical compositions of each electrode shall be determined by the EDS results in Figure 1c and d and Table 1. Students need to carefully identify the discharge voltage plateaus of each electrode from figure 2a, and evaluate the data with existing literature. From Figure 2b, students should report the specific gravimetric of the two electrodes, and compare these values with existing literature. Conclusion. (2 marks) Brief description of the purpose of the experiment, findings, and analysis. Need to write any shortcomings of the experiments and potential application of this experiment for research and industry. References. (1 mark) Relevant references, cited in the correct format in the text and reference list. Written communication. (2 marks) Clear, concise and logical writing style. *Loading weight is the weight of the active material deposited onto the Cu current collector. In the case of Cu6 Sn5, the loading weight is the difference between the mass of the electrode and the mass of the bare Cu foil; while in the case of the Gr electrode, only 90% of this mass is Gr and so the loading weight of Gr shall be calculated accordingly.
Nutritional Epidemiology Module assignment Instructions The Module assignment is as detailed below. Please submit a single Word file or PDF that addresses all components of the assignment. The entire task should be completed individually (it is not intended to be a group exercise). An approximate proportion of scoring/grading (of 100%) is supplied for each question or task, e.g. (5%). Any numeric information or figure must not be submitted in an artificial intelligence (AI) tool. Your answers are expected to consist of up to 1500 words in total and to be submitted in a single file. Selected publications that are relevant to this assignment are available as PDFs. Each file name starts with the first author’s name. Some publications are essential to enabling responses to the questions posed in the assignment. Not all publications are directly relevant, but uploaded partly as resources to learn. Assignment Research setting: In an ongoing prospective cohort study in the UK, participants were recruited from the general practice (family doctor) registries. At its baseline (1993-1997), 24,857 participants underwent dietary assessment with a food-frequency questionnaire and many other measurements. Then, they were followed up over years for further assessment and for identification of deaths and disease onset. Recently, a research group has conducted an epidemiological analysis to address the following hypotheses: (i) Dementia incidence would vary by the degree of adherence to a plant-based dietary pattern. Greater adherence is associated with lower dementia incidence when the plant-based dietary pattern is characterised by high consumption of healthy plant-based foods or beverages. (ii) Dementia incidence would vary by the degree of adherence to a plant-based dietary pattern. Greater adherence is associated with higher dementia incidence when the plant-based dietary pattern is characterised by high consumption of unhealthy plant-based foods or beverages. The investigators calculated dietary pattern scores of the current UK study participants (n=24,857) so that the scores reflected the degrees of adherence to two types of the plant-based diet patterns according to the approach previously taken by other researchers, e.g. Satija et al. (Satija et al., Healthful and Unhealthful Plant-Based Diets and the Risk of Coronary Heart Disease in U.S. Adults, J Am Coll Cardiol, 2017;70(4):411-422 doi: 10.1016/j.jacc.2017.05.047). The two scores were named healthy plant-based diet index (“healthy PDI”) for the diet high in healthy plant-based foods and unhealthy plant-based diet index (“unhealthy PDI”) for the diet high in unhealthy plant-based foods. In the current UK study, dementia cases from the baseline to the end of follow-up (31 March 2022) were ascertained by record linkage with death certificates and hospital records and, using diagnostic records of International Classification of Diseases (ICD) codes for dementia: A81.0, F01, F01.0-F01.3, F01.8, F01.9, F02, F02.0-F024, F02.8, F03, F04, F05.1, F10.7, G31.0, G31.8, and I67.3. Other data collection methods for covariates are available in numerous publications, such as Tong et al., (Prospective association of the Mediterranean diet with cardiovascular disease incidence and mortality and its population impact in a non-Mediterranean population: the EPIC-Norfolk study, BMC Med, 2016;14(1):135 (doi: 10.1186/s12916-016-0677-4)). Briefly, socioeconomic factors, behavioural factors, medication use, and disease histories of participants and their family members were assessed with self-administered questionnaires. Anthropometric variables were obtained by trained research staff. The investigators conducted descriptive analyses to characterise the study participants and multivariable-adjusted Cox proportional hazard regression analysis to characterise the association of each of healthy and unhealthy PDIs at baseline (1993-1997) with incidence of dementia ascertained by 2022. Some of the results are presented below. Assignment questions: Q1-1. Provide the PICO for each of the two hypotheses (PICO: Population, Intervention hypothesised, Comparison undertaken, and Outcome assessed) (3%). Q2. Table S1 presents food grouping in the UK study. The food groups and their scoring were conducted in a consistent way (as done by Satija et al.). Certain plant-based food groups received positive scores while others were scored negatively. Q2-1. Identify one food group or food item that is classified as healthy or unhealthy plant-based item and could be controversial in its scoring in the context of different countries, populations or population sub-groups. Then, please explain why the classification could be controversial and how the specific item could be classified differently. (5%) Q3. Assume you are the investigator analysing the data from the UK study and decide to add one more component or split one food group into two (in Table S1). Q3-1. Please nominate one dietary component you may include by adding it or splitting one component in the two PDIs (i.e. healthy and unhealthy PDIs). (6%) Q3-2. Suppose you calculate each PDI after the modification (adding one component), according to the approach taken by Satija et al. What is the possible range of each PDI score? (4%) Q4. Table 1 shows descriptive statistics by the healthy PDI. Q4-1. According to the results in Table 1, select two covariates and discuss how each could cause confounding in the longitudinal analysis relating the healthy PDI to dementia incidence. Clarify the direction of confounding. (6%) Q4-2. Covariates that indicate a crude correlation with the healthy PDI score do not necessarily act as confounders in the association of the PDI with dementia incidence. Describe two reasons for it. (6%) Q5. Table 1 includes the descriptive statistics for trans fat intake. Suppose that Trans fat was consumed from plant-based foods. While it could be a part of any of the PDI, the investigators adjusted for the variable in the longitudinal analysis of the UK study dataset (as described in the footnote of Table 2 shown below). Q5-1. The statistical adjustment was also made by Satija et al. Discuss why Satija et al. conducted the adjustment to examine the association independent of trans fat intake or separate out the potential effect of trans fat intake. (5%) Q5-2. Discuss whether the same adjustment should be made in the UK study analysis and provide the rationale. (5%) Q6. The investigators conducted Cox proportional hazard regression analyses and presented the results in Table 2 (for the UK study). Q6-1. In this study, the investigators were interested in the diet-dementia association independent of obesity, even if obesity could be a mediator. They reasoned that obesity could be a confounder because it can cause measurement errors in self-reported dietary intakes systematically and may increase dementia incidence independently. Suppose that obesity caused under-reporting of all of the unhealthy plant-based items and animal-based items. Discuss which direction of confounding bias this measurement error would cause for an association of the unhealthy PDI with dementia incidence. (6%) Q6-2. Using the numeric information in Table 2, describe, in two ways, the main result that is most relevant to the study hypothesis about a healthy plant-based diet: one, under the assumption of causality as if the estimate was obtained from a perfect trial (or a meta-analysis of trials); and the other, without any assumption of causality. (8%) Q6-3. The investigators statistically adjusted for total energy intake. State at least three aims of the statistical adjustment for total energy intake in this study: through the adjustment, what specific bias did the investigators attempt to minimise in this particular study or what study-specific aim did the investigators attempt to achieve? If necessary, refer to the course materials and the published information on energy adjustment in nutritional epidemiology, such as Willett et al., Adjustment for total energy intake in epidemiologic studies, Am J Clin Nutr, 1997;65(4):1220S-1228S. (8%)
Macroeconomics 137 Problem set 2 Question 1 1. Go to FRED. Download the data for Effective Federal Funds rate (FEDFUNDS), Industrial Production (INDPRO), Consumer Price Index (CPIAUCSL), Unemployment rate (UNRATE), and yield curve (T10Y2Y). Download all of these as monthly series. Use data from January 1994 to December 2007. 2. Plot these series on separate graphs. Correctly label the x-axis and y-axis for each graph. 3. Using local projections, estimate impulse responses for log (Industrial Production), log (CPI), unem- ployment rate, and yield curve to a 100 basis point change in federal funds rate. You will run thee following regression to recover βh for each horizon h: yt+h - yt- 1 = α + βh ∆it + γhyt- 1 + ϵt+h where y is the variable whose impulse response you are estimating, h is the horizon at which you are estimating the response, ∆it is the month on month change in Federal Funds rate, and yt- 1 is the lag of the dependent variable. Plot the βh coefficients for horizons 0 to horizon 24 against horizons on x-axes for the four dependent variables. 4. Explain the estimated responses. Do these align with what you’d expect based on the Evidence on effects of monetary policy that we discussed in the class? 5. Explain a problem with this estimation strategy. (i.e. why these estimates are not causal).
Paper Assignment Econ 5140, Spring 2025 Over the course of the semester, you will conduct independent statistical analysis on a topic of your choosing, which will culminate in a write-up to be handed in on 4/22. The objective of this project is for you to see how the concepts discussed in lecture can be applied to a real dataset of interest to you. This analysis must be novel and cannot borrow any work you have done for another class or project. Think of the end product as being the type of long-form. analysis that could be posted as an article on a quantitative blog. It will involve rigorous econometrics and thoughtful analysis, but it is less substantial than an academic paper. Schedule: This project will be developed over the course of the semester according to the schedule below. I will give you some feedback as the schedule unfolds, but please reach out to me if you would like to discuss what you are doing in more depth. This is especially true in the last couple weeks of the semester, when you will be pulling the paper together. 1. 2/4 (as part of Problem Set 2): Propose 3 datasets that you think might be interesting to study. A long list of publicly available datasets are available at the end of this document; this can be a very helpful place to look. 2. 2/18 (as part of Problem Set 3): Choose a dataset and propose a research question that the variables in the dataset could help you to answer. 3. 3/14 (as part of Problem Set 4): Provide summary statistics (number of observations, mean, variance, median, minimum, maximum) of at least 3 variables in the dataset. 4. 3/28 (as part of Problem Set 5): Show results from at least 2 regressions in your dataset, including both coefficients and standard errors. 5. 4/11 or 4/15: Make a 15-20 minute presentation to the class showing current state of analysis. 6. 4/22: Final write-up due. Final Write-up: (Steps 1-4 above will be discussed in greater detail in their corresponding Problem Sets.) The final write-up (step #5 due on 4/16) should be roughly 2,000-2,500 words, excluding tables and figures. Tables and figures should be formatted in a professional manner; sample tables are provided on Canvas. It should include the following components: 1. A discussion of a research question or hypothesis. For instance, “Do the returns to education (in terms of salary) differ for people with different IQs?” You should discuss why this issue is interesting and/or important, and how knowing the answer could guide how individuals, organizations, or policymakers might make decisions. (~250 words) 2. A description of the dataset. This should include the time period covered, the number of observations, the variables included, how the data was collected, and anything else noteworthy about the dataset. (~125 words) 3. Summary statistics describing all variables to be used in the analysis. These should be “publication quality” tables showing (at least) number of observations, mean, variance, median, minimum, and maximum. If there are two variables of primary interest, it may be helpful to show a scatterplot. (~125 words) 4. An explanation of the empirical methodology. What will be the lefthand side variable in your regressions, and what will be the key righthand side variable(s)? Do you have to do any data transformations (e.g. take logs of variables)? Why do the regressions you propose help to answer the research question you proposed above? How will you interpret the coefficients that Stata spits out? What key hypothesis test(s) will you conduct? (~250-500 words) 5. Discussion of results from at least three regressions. (~500 words) a. A “baseline” regression of y on x1 (and potentially other regressors x2, etc.) b. A “flexible” regression that allows x1 to enter non-linearly (e.g. quadratic, non-parametric) c. A version that adds an additional regressor to the baseline (you can also add it to the flexible version if you think it makes sense) You should discuss how the implications of your regression results for your hypothesis, including sign (positive, negative), magnitude, and statistical significance. If you feel you got a clear answer to your question, what was it? If the answer is still unclear, why is that? Be sure to discuss how adding the regressor (in regression c) affected the coefficient and the standard error on your main x1. Also discuss whether you think the baseline or the flexible version is more useful. This is the main section of the report, and it will be different for each person; the questions above are not an exhaustive list. Think hard about what your results say (and don’t say) and discuss that here. 6. Literature review; described further below. (~250-500 words) 7. Conclusion. What was your empirical analysis able to teach you? What are its shortcomings? What are some new questions it brings up? If you had more time and/or better data, how would you try to improve the analysis? (~250-500 words) Evaluation: Your paper will be evaluated along the following dimensions: ● Did you employ the tools from the course in a proper and sensible way? Concretely, do the regressions that you ran on your dataset constitute a reasonable approach to answering your research question? ● Did you interpret the results of your regression analysis in a reasonable way? ● Did you explain the results in a clear, transparent way? I will not explicitly grade you on the quality of your English prose, but papers will receive higher grades if they are able to explain the ideas in a way that is easy for a reader to follow. The writing should be formal (e.g. avoid contractions like “won’t”) and should include economic/econometric terms whenever relevant. ○ Note: Think of the “target audience” as your Econ 2560 classmates. You do not need to try to explain your ideas in a way that the “(wo)man on the street” could understand – you can assume an understanding of econometrics from your readers. However, you should write as an independent project that is separate from the components you handed in during the semester. Literature Review: You must provide a literature review of prior work relevant to your research question. This literature review will help you conceptualize and operationalize your research question. This literature review must be comprised of at least three sources. For most projects, these citations should come from academic journals. However, if your project is about a topic that is not closely studied by academics (e.g. some sports topics), then we can discuss suitable alternatives. These three (or more) sources can be searched via academic journals’ electronic portals such as, for example, “JStor” (http://www.jstor.org/), “EconLit” (http://www.aeaweb.org/econlit/), as well as other electronic resources accessible via the NU Libraries (http://library.northeastern.edu/find). Other useful academic sources are, among others, the “Journal of Economic Perspectives” (http://www.aeaweb.org/jep/), the “Journal of Economic Literature” (http://www.aeaweb.org/jel/index.php), the “Handbook of Economics” series (http://www.elsevier.com/books/book-series/handbooks-in-economics), and the “New Palgrave Dictionary of Economics” (http://www.dictionaryofeconomics.com/dictionary). Each of these resources is available to you, free of charge, via the Northeastern library website (http://library.northeastern.edu/find). If you are in doubt on how to use any of these resources to locate academic articles relevant to your research topic, I highly recommend you consult a librarian at the Northeastern library. For each of the formal sources you select for your literature review, you should provide a brief and to-the-point summary of the article. Then, you must discuss how your findings relate to the literature you are citing to. Do your findings contradict anything the other papers found? If so, why might this be (e.g. different setting? different econometric approach)? Do your findings extend the conclusions of the prior literature (e.g. “the prior literature finds a positive effect of education on earnings, but I find this is mostly driven by men”)? Exactly what this section should contain is case-specific, but the above questions are good starting points for how you should think about what to include. Note that you must then cite this article in your bibliography (at a separate page in the end of your paper): Ehrlich, Isaac. 1996. “Crime, Punishment, and the Market for Offenses.” Journal of Economic Perspectives. 10(1). Pp. 43-67. List of selected surveys conducted by U.S. government agencies ● Academic Libraries Survey ● Advance Monthly Retail Sales Survey ● Airline Origin and Destination Survey ● American Community Survey ● American Housing Survey ● American Time Use Survey ● American Travel Survey ● Annual Capital Expenditures Survey ● Annual Parole Survey ● Annual Parole Survey & Annual Probation Survey ● Annual Public Employment Survey ● Annual Retail Trade Survey ● Annual Survey of Government Finances ● Annual Survey of Jails ● Annual Survey of Manufactures ● Annual Survey of State and Local Government Finances ● Annual Wholesale Trade Survey ● Baccalaureate and Beyond Survey ● Beach Sanitary Survey ● Beginning Postsecondary Students Longitudinal Study Survey ● Beginning Teacher Longitudinal Study Survey ● Building Permits Survey ● Business and Professional Classification Survey ● Business R&D and Innovation Survey ● Business Research and Development and Innovation Survey ● City-Level Survey of Crime Victimization and Citizen Attitudes ● Civil Justice Survey of State Courts ● Clean Watershed Needs Survey ● Commodity Flow Survey ● Community Water System Survey ● Consumer Expenditure Survey ● Coral Condition Survey ● Criminal Justice Expenditure and Employment Survey ● Current Population Survey ● Customer Service and Satisfaction Survey (by U.S. HUD) ● Early Childhood Longitudinal Study Survey ● Health and Diet Survey (FDA) ● High School and Beyond Survey ● Housing Vacancy Survey ● Information and Communication Technology Survey ● Justice Assistance Data Survey ● Local Government School System Finance Survey ● Mammography Facility Survey ● Manufacturers' Shipments, Inventories, and Orders Survey ● Manufacturing Energy Consumption Survey ● Manufacturing Technology Surveys ● Medical Expenditure Panel Survey ● Medical Expenditure Survey ● Monthly Retail Trade Survey ● Multi-Agency Radiation Survey ● National Aquatic Resource Survey ● National Assessment of Education Progress Survey ● National Assessments of Adult Literacy Survey ● National Asthma Survey ● National Beneficiary Survey ● National Cancer Patient Experience Survey ● National Compensation Survey ● National Computer Security Survey ● National Crime Victimization Survey ● National Employer Survey ● National Family of Family Growth ● National Former Prisoner Survey ● National Health and Nutrition Examination Survey ● National Home and Hospice Care Survey ● National Home Health Aide Survey ● National Hospital Discharge Survey ● National Household Education Survey ● National Household Travel Survey ● National Immunization Survey ● National Inmate Survey ● National Longitudinal Survey of Young Men and Older Men ● National Longitudinal Survey of Young Women and Mature Women ● National Longitudinal Survey of Youth ● National Maternal and Infant Health Survey ● National Mortality Followback Survey ● National Nursing Home Survey ● National Postsecondary Student Aid Study Survey ● National Public Education Financial Survey ● National Rivers and Streams Assessment Survey ● National Study of Postsecondary Faculty Survey ● National Survey of Ambulatory Surgery Survey ● National Survey of Children with Special Health Care Needs ● National Survey of Children's Health ● National Survey of DNA Crime Laboratories ● National Survey of Fishing, Hunting, and Wildlife-Associated Recreation ● National Survey of Indigent Defense Systems ● National Survey of Recent College Graduates ● National Survey of Residential Care Facilities ● National Survey of Youth in Custody ● National Survey on Drug Use and Health ● National Wetland Condition Assessment Survey ● Nationwide Personal Transportation Survey ● New York City Housing and Vacancy Survey ● Occupational Employment Statistics Survey ● Origin and Destination Survey ● Police-Public Contact Survey ● Property Owners and Managers Survey ● Public Libraries Survey ● Quarterly Public Employee-Retirement Systems Survey ● Quarterly Survey of Plant Capacity Utilization ● Quarterly Tax Survey ● Recidivism Survey of Felons on Probation ● Report of Organization Survey ● Residential Finance Survey ● Service Annual Survey ● State and Local Government Public-Employee Retirement System Survey ● State Government Tax Collections Survey ● State Library Agencies Survey ● Survey of Adults on Probation ● Survey of Business Owners ● Survey of Campus Law Enforcement Agencies ● Survey of Construction ● Survey of Doctorate Recipients ● Survey of Income and Program Participation ● Survey of Industrial Research and Development ● Survey of Inmates in Federal Correctional Facilities ● Survey of Inmates in Local Jails ● Survey of Law Enforcement Gang Units ● Survey of Market Absorption ● Survey of New Manufactured (Mobile) Homes ● Survey of Pollution Abatement Costs and Expenditures ● Survey of Program Dynamics ● Survey of Research and Development Expenditures at Universities and Colleges ● Survey of Science and Engineering Research Facilities ● Survey of Sexual Violence ● Survey of State Procedures Related to Firearm Sales ● Survey of State Research and Development Expenditures ● Survey on Sexual Violence ● Teacher Compensation Survey ● University Transportation Survey ● Vehicle Inventory and Use Survey ● Women- and Minority-Owned Business Survey
Management School - Undergraduate Coursework Specification 2022-23 Module Code: MGT253 Coursework Codes: X,W Module Title: Principles of Operations Management Date Available: 14th of February 2024 Submission details: 2nd of May 2025 Your submission consists of two files: a MS Excel spreadsheet with the results of your simulation; and a MS Word file with your report. Electronic submission only through Blackboard. There will be two submission points, one for the MS Excel file and the other one for your report. You can submit your assignment multiple times to the submission link on the module Blackboard site. Each time you submit you will receive a Similarity Report. You can check this and improve your referencing before the final deadline. After 3 submissions you will need to wait 24hrs before you receive a new report. Please note: each new submission replaces any previous submission. It is not possible to retrieve a previous submission. Your final submission must be made before the deadline to avoid late penalties. You should note that the time of submission is taken from once the document has been successfully uploaded and confirmed - this may take more than five minutes during busy periods. Late penalties will be applied to any work submitted from 12.01pm on the 2nd of May onwards. Details of how to calculate a late penalty can be found in your programme Handbook. It is your responsibility to ensure the correct document/file has uploaded successfully. When submitting students must: 1. "Include a completed cover sheet (available from Blackboard called “Individual Coversheet MGT253 with screenshots”) which must include the required mySkills. Only for the simulation report (MS Word document). Remember it is compulsory for SUMS students to do at least one mySkills Assessment per year, and at least three development experiences. The coversheet provides evidence that you have done this. SUMS requires a penalty of 5 marks to be applied for students who do not comply with all these requirements. Please make sure that your coversheet includes your screenshots as required. 2. Use ‘StudentNumber-MGTXXX-X’ (e.g. 18203206-MGT253-X) as the Excel file name and also as the Assignment Title in Turnitin. 3. Use ‘StudentNumber-MGTXXX-W’ (e.g. 18203206-MGT253-W) as the MS Word document name and also as the Assignment Title in Turnitin. IMPORTANT NOTICE ABOUT THE USE OF AI: Please beware that the use of AI/GenAI is ONLY ALLOWED for the Improvement of English Grammar, vocabulary, or spelling. If this is done, you must acknowledge it using the Acknowledge/Describe/Evidence that is available in Blackboard. You are only expected to provide one example of the use of AI as a grammar, style, or spell check tool. Any other use of AI is strictly forbidden and will be penalised according to Sheffield University rules. For further information please refer to https://students.sheffield.ac.uk/digital-learning/ai Contribution to Final Mark for Module: 30% Maximum Word Length: 1500 words The word count is for the main body of the text and ignores the reference list and appendices. If you exceed the word length you will be penalised. For details see the Management School Handbooks. Please note that SUMS does not have a word count tolerance - it is a stated maximum as outlined above. Requirements: The Theory of Constraints, introduced and popularised by the book The Goal. A Process of Ongoing Improvement. by Eliyahu Goldratt and Jeff Cox, is a body of knowledge that deals with all the obstacles that limit or constraint the organisation’s ability to achieve its goals. In this work you will use a spreadsheet to conduct a simulation to represent and evaluate the impact of bottlenecks in an industrial setting. This work will be explained and the methodology, inspired by Goldratt’s book, will be explained and developed during tutorial sessions 1 to 3 (weeks 25 [3], 26 [5], and 29 [7], and 26 [4], 28[6], and 30 [8], depending on your tutorial group) and must be finished and submitted as an individual work by the end of Week 9 (2nd of May 2025). The submission consists ofthe MS Excel file containing the simulation exercise, and a short essay answering the questions indicated in the statement of the problem. The essay should also include: A short description of the experiment. A thorough reflection about the impact of bottlenecks on a company’s processes. You should show that you clearly understand what a bottleneck is in an industrial process, and how can a manager avoid and/or correct them. Your reflection should link what you observed in the simulation experiment with real life situations in industrial and service settings. The report must include some graphic support and tables. Avoid copy and pasting your Excel spreadsheets, these will be revised and assessed together with the report. Your tables and graphics must be designed specifically for your report. Think carefully which is the information you want to summarise and report using graphic support. Please remember that this essay is NOT expected to have the shape of an academic essay, but an executive report presented to a company’s board. Therefore, you are not expected to include academic references, as you will not do in a business environment. Further details of the exercise are provided in a document that will be published together with this specification form.
The Impact of Economic Growth, Population, and Infrastructure Development on Electricity Consumption in Chinese Cities: A Comparative Analysis of Coastal and Inland Regions Research Questions My final project examines the relationship between economic growth, population dynamics, and infrastructure development in driving electricity consumption in China, comparing two developed coastal cities (Shanghai & Ningbo) with two developing inland provincial capitals (Chengdu & Zhengzhou). The key research questions include: 1. Is economic growth (GDP) the primary driver of electricity demand across cities with different development levels? 2. How does population influence electricity consumption? Is total population more relevant, or does population density play a more significant role? 3. How does road infrastructure expansion impact electricity demand? Does this relationship differ between coastal and inland cities? 4. Do more developed cities exhibit lower electricity consumption growth compared to developing cities? Data and Methodology Data Sources I will use a panel dataset covering the selected cities over the past 20 years, including: • Electricity consumption (dependent variable) • GDP • Population size and density • Road infrastructure (total road length) Statistical Techniques Granger Causality Tests (1) To examine whether GDP, population, and road infrastructure cause electricity consumption changes or if there is a reverse causality effect. (2) If GDP Granger-causes electricity consumption, it supports the hypothesis that economic growth drives energy demand. (3) If electricity consumption Granger-causes GDP, it suggests that energy availability and consumption play a key role in economic growth. Vector Autoregression (VAR) Model (1) To analyze dynamic relationships and interdependencies between GDP, population, road infrastructure, and electricity consumption over time. (2) Helps identify how shocks in one variable (e.g., infrastructure investment) impact electricity demand in the short and long run. Panel Data Regression (Fixed & Random Effects Models) (1) To estimate the long-term relationship between electricity consumption and its key drivers while controlling for city-specific factors. Subsample Comparison & Interaction Terms (1) To assess whether electricity demand elasticity differs between coastal and inland cities. Expected Findings (1) If GDP Granger-causes electricity consumption, this would confirm that economic growth drives energy demand. However, if electricity consumption Granger-causes GDP, it suggests energy availability plays a vital role in economic development. (2) If population size is significant, but density has a stronger effect, it implies that urbanization and concentrated energy use patterns play a crucial role. (3) If road infrastructure significantly impacts electricity demand, particularly in inland cities, it could indicate that infrastructure investment facilitates industrial expansion, commercial activity, and residential energy demand. (4) If electricity consumption stabilizes in coastal cities but continues growing in inland cities, it would suggest an "electricity demand turning point," where more developed economies transition to lower energy-intensity industries. Policy Implications • Coastal cities may focus on energy efficiency measures and transitioning towards lower electricity-intensity industries. • Inland cities may require continued investment in energy infrastructure to support economic growth. • Understanding the causal relationship between economic factors and energy demand will help guide sustainable urbanization strategies in China.
BUSM1228 People Analytics Recommended structure - Assessment 2 (1500 words) Section What to include Suggested word count Cover and Title page 1. Title. 2. Student name and ID. 3. Due date. 4. Word count: 1,500 Not included. Executive summary 1. Outline the purpose of the report. 2. Discuss research method (e.g. examination of data, secondary sources, quality of journal articles, models/frameworks, etc.). 3. Explain findings, recommendations and conclusions. Not included. Table of contents Use the Microsoft word tool to develop a professional table of contents, which provides a specific overview of the structure and contents of the report. Not included. Introduction 1. Outline the aim of the report. 2. Mention the reasons of developing two analytical research questions. 3. Summarise what you intend to talk about in your plan (overview or outline of the plan). First…,Second … , Third,…Finally, … 100 words Body Use Headings and Subheadings 1. Analytical Research Questions Develop and explain two analytical research questions by analysing the dataset and data dictionary. Analytical Research question 1 (similar for question 2) Develop analytics research questions 1 and 2 based on quantitative data analysis. Explain reasons behind the choice of each question. Use journal articles (e.g., empirical research) to support the critical discussion. Follow a coherent and cohesive structure in each paragraph (6-7 sentences approx.). This is applicable for the following sections. 2. People analytics outputs Draw PA outputs and use digital objects (e.g., Power BI, excel) to create visualisation elements (e.g., graphs, tables, charts, etc.). Briefly explain PA outputs. PA outputs (similar for PA output 2, 3, 4, etc.). It could be more than 2 outputs. It is important to link to the analytical research questions. 200 words 200 words 3. Storytelling Apply storytelling skills based on the PA outputs to develop people analytics insights. Use journal articles (e.g., empirical research) to support the critical discussion. Storytelling 1 (similar to other storytelling) Tell a story about why it is a critical insight and what might have happened or will happen to the organisation based on the PA insights and inputs. 4. Recommendations Provide insightful recommendations to the executive team for further implementation. Recommendation 1 (similar for other recommendations) Make a clear connection between recommendations and analytical research questions. The recommendations should be based on theoretical and empirical research helping the organisation overcome the business problems identified through people analytics. 450 words 450 words Conclusion *Summarise key points of the report. *Explain your critical reflection from Assessments 1 and *You can use first person to share your insights. 100 words References 1. Ensure you have your reference list here and ensure it adheres to RMIT Harvard style. referencing. You need to use Easy Cite referencing tool-RMIT University Library 2. Ensure you have your references in alphabetical order and please ensure that all the references appearing in your report, also appear in your reference list and vice versa. 3. Ensure you properly use in-text references throughout the report. Not included.
ECOM097 Portfolio Construction Final Portfolio Report General Guidelines Aim: To broaden students’ knowledge of portfolio construction, monitoring and evaluation, including performance and risk attribution using a “real world” case study. Structure: The assignment will be completed individually at home; it is worth 80% of your final mark and it needs to be submitted in May 2024 (during the Final Exam Session) Final Report Assessment criteria: Written Report: min 3,000 words (max 3,500 words) (the exact deadline in May will be specified in the final assignment) Stage 1: You will be expected to create your own portfolio, which is different from the initial strategic allocation provided and incorporates three of your own trade ideas. These trade ideas can be introduced in response to the client’s objectives and constraints and/or recent market developments. This stage needs to be completed by the end of February with the new asset allocation sent to the TA (Konstantina Mari) via Submission Link on QM Plus, using the template provided on QM Plus. Stage 2: You will then need to monitor your portfolio from the end of February till the end of March so that it remains within prescribed volatility bands and does not violate minimum tracking error constraint by the month end in February and March. If it breaches these constraints at the end of February or at the end of March, the adjustment needs to be made before the final written report is submitted in May. You will not be penalised for the breach itself but you will have to propose a remedial action to bring your portfolio back within pre-agreed parameters. Important: if no constraints are breached, you are not allowed to make ANY adjustments to the portfolio you submitted to the TA in Stage 1. Adjustments can be made if and only if any of the constraints are breached. Stage 3: A Final Report, including the performance attribution analysis of the dynamic asset allocation decisions relative to the initial SAA and the rationale for the proposed adjustments, is submitted in May Note: Presentation matters! While the assignment itself carries a maximum mark of 100, up to 10 bonus marks may be awarded for exceptionally good-looking reports. For example, additional bonus marks could be awarded to students who - Structure their report well, with each section clearly marked or - Present summary of key client objectives and constraints in a clear and concise way or - Format tables/charts in such a way that immediately draws readers’ attention to the key data/information etc. The written report should contain the following elements: - Clear and concise summary of key client objectives and constraints and a description of their initial strategic asset allocation (SAA) - Investment rationales for three dynamic deviations or off-benchmark bets from the initial SAA; Note: if any further changes to the portfolio had to be made after the initial adjustment because of any breaches (e.g. after the end of February), these too need to be documented and justified - Risk Report outlining how the portfolio satisfied its volatility and tracking error constraints by month-end and/or if any changes had to be made - Performance Attribution Report assessing the impact of dynamic asset allocation decisions - Final Recommendation outlining whether the student believes the asset allocation should be maintained going forward (beyond May 2023) or whether any changes need to be made on the back of the assessment of the portfolio live history since the end of February or changes in client’s circumstances Constraints: - minimum tracking error constraint which will be assessed by looking at the backtested relative returns of the proposed portfolio versus the given strategic asset allocation - volatility range which will be assessed by the annualised standard deviation of backtested returns - minimum and maximum constraints on specific assets (as per client’s unique preferences)
CSCI4041 HW5 Part B - Graph Algorithms (Programming Problem) Problem H5.4: Route Mapping (40 points + 5 points possible extra credit) Figure 1 - Route mapping using a drone visualization. Instructions: You are to implement several graph algorithms and test them on a drone visualization system. Submission: Submit the search algorithms .py file to the Homework 5 - Part B Grade- scope assignment. Setup: • Download the support code from Canvas: hw5-support-code.zip • Install python dependencies: — pip3 install flask — pip3 install flask cors • Run the application — Use a terminal to cd to visualization code directory and run the visualization: * python3 app.py — Navigate to http://127.0.0.1:5000 Drone Visualization The drone visualization allows you to move a robot across the UMN. As soon as the robot moves, the drone will attempt to find the robot and move to its location. Figure 2 shows how to move the robot, Figure 3 shows a control panel where you can choose whether to view the robot or drone. You can also choose the algorithm you would like to use to move towards the robot. Three simple algorithms already exist to help you get started: • Point to Point: Moves the drone directly from one point to another. • Fly: Uses a parabolic arc to fly from one point to another. • Random Graph: Flies to a random point on the map and then follows a graph to the robot. Figure 3 shows this algorithm in action. Figure 2 - Click to move the robot and route the drone. Figure 3 - Interface for choosing the algorithms for the drone to use to find the robot. Figure 4 - The drone follows a path on a graph to find the robot. Task / Rubric The search algorithms .py file has a simple graph implementation and a set of graph al- gorithms for you to implement. You will do all your work in the search algorithms .py file. You should not need to touch the visualization code. Your task is to implement a subset of the following algorithms to reach 40 points (5 points extra credit possible): • Breadth First Search – (10 points) - breadth first(start, dest) - Breadth First Search. – (5 points) - breadth first hub(start, dest) - Every node with 5 or more neigh- bors is considered a hub. Calculate the top three hubs that are closest to both the start and destination using Euclidean distance. Use the breadth first algorithm to visit each hub before reaching the destination (visit hubs in order of decreasing distance from the destination - furthest to closest). • Depth First Search – (10 points) - depth first(start, dest) - Depth First Search. – (5 points) - depth first best(start, dest) - Perform the depth first search, but when choosing an edge to follow, always choose the edge that leads to a node that is closest to the goal (e.g. has the shortest Euclidean Distance). • Bellman Ford – (10 points) - bellman ford(start, dest) - Bellman Ford Algorithm. – (5 points) - bellman ford negative(start, dest) (5 points) - When calculating the weights of neighbors, if the neighbor node name ends with a 0, then it has a negative weight. Use Bellman Ford to find the path to the destination. If no path is found, use point to point navigation. • Dijkstra / A* – (10 points) - dijkstra(start, dest) - Dijkstra’s Algorithm. – (5 points) - astar(start, dest) - A* algorithm using Euclidean Distance as the heuristic. • Minimum Spanning Tree – (10 points) - min spanning tree(start, dest) - Calculate and follow the path on a minimum spanning tree to the destination. For each algorithm, you will take in a start point (3D point) and a destination point (3D point) to write an algorithm that returns a path (list of 3D points) on a graph for the drone to follow. You may calculate the weight of each edge using the Euclidian distance between nodes. Please look at the random graph(start, dest) function to understand how to use the graph. You can create a graph with the following line of code: graph = MapGraph(‘graph.json’). You may add / edit any structure within the search algorithms.py file including the MapGraph class Note: The start and destination points passed in are 3D points, not nodes in the graph. Therefore, for each search algorithm, you will first need to find the closest start and destination nodes in the graph. You can use the following method: graph.find closest vertex(point).
