Lineare Algebra I – Übungsblatt 02 Wintersemester 2024/25 Aufgabe 1. Sei G eine Menge mit zwei Elementen. Beweisen Sie, dass G genau zwei Gruppenstrukturen zulässt. Hinweis: Beweisen Sie, dass die Wahl des neutralen Elements die Gruppenstruktur bestimmt. Aufgabe 2. Sei (G, ·) eine Gruppe und H eine Teilmenge von G. Wir definieren eine Relation Beweisen Sie, dass R eine Äquivalenzrelation ist genau dann, wenn H ≠ ∅ und das Folgende gilt: Hinweis: Beweisen Sie zuerst, dass Aufgabe 3. 1. Für n ∈ N definieren wir eine Relation Rn = {(x, y) ∈ Z × Z | n dividiert x − y}. Beweisen Sie, dass Rn eine Äquivalenzrelation auf Z ist. 2. Für x ∈ Z bezeichne das Bild von x unter der kanonischen Projektion Z → Z/Rn. Beweisen Sie, dass Aufgabe 4. Geben Sie eine Bijektion zwischen N × N und N an. Hinweis: Verwenden Sie, dass jede natürliche Zahl (ungleich 0) ein Produkt aus einer ungeraden Zahl und einer Zweierpotenz ist.
FIT3175 Usability - S1 2025 Submission 1 - Data Gathering and User Analysis (25%, Group and Individual Work) This assessment task has 2 parts, each with multiple deliverables. ● Part 1: Questionnaire and Data Analysis (group) ● Part 2: Personas and User Stories (individual) Part 1: Questionnaire and Data Analysis (group, 13%) Before you start developing an application, you need to learn about potential users in order to better understand their behaviours and needs. For this project you will survey adults who would like to find and participate in online cooking classes. Develop a questionnaire and distribute it to some potential users in that group in order to gather data. Your group deliverables for this task are: 1. Questionnaire with 15 questions (no less, no more than 15) Think about what you want to learn about your potential users. ○ 5 questions that collect demographic information about your participants. ■ Do not collect any personally identifiable information (e.g., names, contact information). ○ 5 questions that collect information about participants' current experience and behaviour relating to technology. ■ This can include behavioural and psychographic questions to help you understand how participants' skills, habits and attitudes. ○ 5 questions that collect information about participants' current experience and behaviour relating to the project domain. ■ This can include questions relating to their knowledge, tasks and values relating to learning to cook. Use Google Forms to easily distribute your questionnaire to participants. Use a variety of question types and formats with consideration of the strengths and weaknesses of different question types in your question design. Distribute your questionnaire to a varied selection of participants - your questionnaire should not be distributed to university students only! Don't write questions that ask participants to suggest preferred app features or questions that ask participants to imagine/predict future outcomes. Your questionnaire (full question text and answer format) should be included near the beginning of your report. Only providing links to view the questionnaire online is not sufficient. 2. Questionnaire response analysis Collect 5-10 survey responses per group member, then analyse the collected data to discover useful insights about your potential users. Write a short report that explains your findings. ○ Describe decisions that you made with regard to your questionnaire distribution and participant selection methodology (up to 100 words). ○ Analyse the data collected from each question. Explain the intent of each question and what you learned from it (up to 900 words). ■ Some questions may reveal useful insights on their own. ■ Some questions may reveal more useful insights when cross-analysed with other questions. ■ Do the responses infer any patterns or have interesting outliers that may affect your future decisions? ■ Do you notice any problems with your questions that may limit the quality of the data collected? ○ When conducting a survey with a low number of participants, there will be some gaps in what you learn from the data. Identify a gap in your data and conduct further research using existing online resources to uncover at least 1 new insight about your users that was not found in your data. (up to 150 words). You must include your raw response data (spreadsheet) in your report's appendix. Only providing links to view the response data online is not sufficient. Part 2: Personas and User stories (individual, 12%) Based on the results of the group data collection and the chosen target group, develop a persona and user stories to represent them and identify new requirements. Though the tasks in this section should be completed individually, the personas should be discussed with your groupmates to avoid overlap/duplication across your individual deliverables. Ensure that each deliverable lists the name of the group member who created it. Your individual deliverables for this task are: 1. User persona X 1 Imagine a fictional person who embodies what you learned from your questionnaire analysis and further research. Develop 1 persona that describes this person. ○ Create your high-fidelity persona using an appropriate template. The template can be sourced from unit resources, online sources or your own design. ○ The persona must have identifiable connections with your questionnaire analysis and further research. ○ The persona must include information that evokes empathy with users. ○ Briefly explain how your persona was developed using 4 examples from your data (up to 200 words). A persona is a document that helps you empathise with users, not a document about app design. Don't mention your app or propose app specific features. 2. User stories X 2 Produce 2 user stories that are based on your persona and decide the priority of each story. ○ Your user stories must identify users’ needs and desired benefits using the format: "As , I want so that ". ○ The user stories must be different to each other, describing needs that are based on different aspects of the personas. ○ Assign a priority to each user story using the MoSCoW prioritisation method. ○ Briefly justify of how each story's priority was decided (up to 100 words) ■ Consider the story's impact on your persona. ■ Consider the potential impact on a wider range of users, relating to your survey data collection and further research. 3. New functional user requirements X 2 Propose 2 new functional user requirements in addition to the 3 already defined in the Project Brief. ○ Your user requirements should be written in the following user-centred format: "Users should be able to … " (refer to the Project Brief for examples). ○ The new requirements must be identifiably related to your user stories, and expressed concisely as high-level descriptions. Submission deliverables Compile all of your deliverables into a single PDF document for the group and upload it to the Moodle assignment submission activity. Your submission must contain the following: ● Title Page ● Table of Contents ● Data Collection Methodology (up to 100 words) ● Questionnaire with 15 questions (including full text and response format) ● Questionnaire Response Analysis (up to 900 words) ● Additional research (up to 150 words) ● 4 User Personas (1 per group member) ○ Identify 4 links to your data analysis and research (up to 200 words per member) ● 8 User Stories (2 per group member) ○ Prioritise using MoSCoW method, with justification (up to 100 words per member) ● 8 New Functional User Requirements (2 per group member) ● Appendix ○ Questionnaire response data (spreadsheet containing raw data) Deliverables should be professionally formatted - present then as if you were giving them to a potential client. The name of the report file should follow this format: FIT3175-Sub1-Applied#-Group (e.g. FIT3175Sub1-Applied01-TeamRocket). Submission Due: Friday 4th April, at 11:55pm.
CSE 6242 / CX 4242: Data and Visual Analytics | Georgia Tech | Spring 2025 HW 4: PageRank Algorithm, Random Forest, Scikit-learn Download the HW4 Skeleton before you begin Homework Overview Data analytics and machine learning both revolve around using computational models to capture relationships between variables and outcomes. In this assignment, you will code and fit a range of well-known models from scratch and learn to use a popular Python library for machine learning. In Q1, you will implement the famous PageRank algorithm from scratch. PageRank can be thought of as a model for a system in which a person is surfing the web by choosing uniformly at random a link to click on at each successive webpage they visit. Assuming this is how we surf the web, what is the probability that we are on a particular webpage at any given moment? The PageRank algorithm assigns values to each webpage according to this probability distribution. In Q2, you will implement Random Forests, a very common and widely successful classification model, from scratch. Random Forest classifiers also describe probability distributions—the conditional probability of a sample belonging to a particular class given some or all its features. Finally, in Q3, you will use the Python scikit-learn library to specify and fit a variety of supervised and unsupervised machine learning models. The maximum possible score for this homework is 100 points. Important Notes 1. Submit your work by the due date on the course schedule. a. Every assignment has a generous 48-hour grace period, allowing students to address unexpected minor issues without facing penalties. You may use it without asking. b. Before the grace period expires, you may resubmit as many times as needed. c. TA assistance is not guaranteed during the grace period. d. Submissions during the grace period will display as "late" but will not incur a penalty. e. We will not accept any submissions executed after the grace period ends. 2. Always use the most up-to-date assignment (version number at bottom right of this document). The latest version will be listed in Ed Discussion. 3. You may discuss ideas with other students at the "whiteboard" level (e.g. , how cross-validation works, use HashMap instead of an array) and review any relevant materials online. However, each student must write up and submit the student’s own answers. 4. All incidents of suspected dishonesty, plagiarism, or violations of the Georgia Tech Honor Codewill be subject to the institute’s Academic Integrity procedures, directly handled by the Office of Student Integrity (OSI) . Consequences can be severe, e.g., academic probation or dismissal, a 0 grade for assignments concerned, and prohibition from withdrawing from the class. Submission Notes 1. All questions are graded on the Gradescope platform, accessible through Canvas. 2. We will not accept submissions anywhere else outside of Gradescope. 3. Submit all required files as specified in each question. Make sure they are named correctly. 4. You may upload your code periodically to Gradescope to obtain feedback on your code. There are no hidden test cases. The score you see on Gradescope is what you will receive. 5. You must not use Gradescope as the primary way to test your code. It provides only a few test cases and error messages may not be as informative as local debuggers. Iteratively develop and test your code locally, write more test cases, and follow good coding practices . Use Gradescope mainly as a "final" check. 6. Gradescope cannot run code that contains syntax errors. If you get the “The autograder failed to execute correctly” error, verify: a. The code is free of syntax errors (by running locally) b. All methods have been implemented c. The correct file was submitted with the correct name d. No extra packages or files were imported 7. When many students use Gradescope simultaneously, it may slow down or fail. It can become even slower as the deadline approaches. You are responsible for submitting your work on time. 8. Each submission and its score will be recorded and saved by Gradescope. By default, your last submission is used for grading. To use a different submission, you MUST “activate” it (click the “Submission History” button at the bottom toolbar, then “Activate”). Q1 [20 pts] Implementation of PageRank Algorithm Technology PageRank Algorithm Graph Python >=3.7.x. You must use Python >=3.7.x for this question. Allowed Libraries Do not modify the import statements; everything you need to complete this question has been imported for you. You MUST not use other libraries for this assignment. Max runtime 5 minutes Deliverables [Gradescope] • Q1.ipynb [12 pts]: your modified implementation • simplified_pagerank_iter{n}.txt: 2 files (as given below) containing the top 10 node IDs (w.r.t. the PageRank values) and their PageRank values for n iterations via the provided run() helper function simplified_pagerank_iter10.txt [2 pts] simplified_pagerank_iter25.txt [2 pts] • personalized_pagerank_iter{n}.txt: 2 files (as given below) containing the top 10 node IDs (w.r.t the PageRank values) and their PageRank values for n iterations via the provided run() helper function personalized_pagerank_iter10.txt [2 pts] personalized_pagerank_iter25.txt [2 pts] Important: Remove all “testing” code that renders output, or Gradescope will crash. For instance, any additional print, display, and show statements used for debugging must be removed. In this question, you will implement the PageRank algorithm in Python for a large graph network dataset. The PageRank algorithm was first proposed to rank web pages in search results. The basic assumption is that more “important” web pages are referenced more often by other pages and thus are ranked higher. To estimate the importance of a page, the algorithm works by considering the number and “importance” of links pointing to the page. PageRank outputs a probability distribution over all web pages, representing the likelihood that a person randomly surfing the web (randomly clicking on links) would arrive at those pages. As mentioned in the lectures, the PageRank values are the entries in the dominant eigenvector of the modified adjacency matrix in which each column’s values adds up to 1 (i.e., “column normalized”), and this eigenvector can be calculated by the power iteration method that you will implement in this question. This method iterates through the graph’s edges multiple times to update the nodes’ PageRank values (“pr_values” in Q1.ipynb) in each iteration. We recommend that you review the lecture video for PageRank and personalized PageRank before working on your implementation. At 9 minutes and 41 seconds of the video, the full PageRank algorithm is expressed in a matrix-vector form. Equivalently, the PageRank value of node vj , at iteration t + 1, can also be expressed as (notation different from video’s): where • vj is node j • vi is any node i that has a directed edge pointing to node j • out degree(vi) is the number of links going out of node vi • PR t+1(vj) is the pagerank value of node j at iteration t + 1 • PR t(vi) is the pagerank value of node i at iteration t • d is the damping factor; set it to the common value of 0.85 that the surfer would continue to follow links • Pd(vj) is the probability of random jump that can be personalized based on use cases Tasks You will be using the “network.tsv” graph network dataset in the hw4-skeleton/Q1 folder, which contains about 1 million nodes and 3 million edges. Each row in that file represents a directed edge in the graph. The edge’s source node id is stored in the first column of the file, and the target node id is stored in the second column. Your code must NOT make any assumptions about the relative magnitude between the node ids of an edge. For example, suppose we find that the source node id is smaller than the target node id for most edges in a graph, we must NOT assume that this is always the case for all graphs (i.e., in other graphs, a source node id can be larger than a target node id). You will complete the code in Q1.ipynb (guidelines also provided in the file). 1. Calculate and store each node’s out-degree and the graph’s maximum node id in calculate_node_degree() a. A node’s out-degree is its number of outgoing edges. Store the out-degree in instance variable "node_degree". b. max_node_id refers to the highest node id in the graph. For example, suppose a graph contains the two edges (1,4) and (2,3), in the format of (source, target), the max_node_id here is 4. Store the maximum node id to instance variable max_node_id. 2. Implement run_pagerank() a. For simplified PageRank algorithm, where Pd( vj ) = 1/(max_node_id + 1) is provided as node_weights in the script. and you will submit the output for 10 and 25 iteration runs for a damping factor of 0.85. To verify, we are providing the sample output of 5 iterations for a simplified PageRank (simplified_pagerank_iter5_sample.txt). b. For personalized PageRank, the Pd() vector will be assigned values based on your 9- digit GTID (e.g., 987654321) and you will submit the output for 10 and 25 iteration runs for a damping factor of 0.85. 3. Compare output a. Generate output text files by running the last cell of Q1.ipynb. b. Note: When comparing your output for simplified_pagerank for 5 iterations with the given sample output, the absolute difference must be less than 5%. For example, absolute((SampleOutput - YourOutput) / SampleOutput) must be less than 0.05. Q2 [50 pts] Random Forest Classifier Technology Python >=3.7.x Allowed Libraries Do not modify the import statements; everything you need to complete this question has been imported for you. You MUST not use other libraries for this assignment. Max runtime 300 seconds Deliverables [Gradescope] • Q2.ipynb [45 pts]: your solution as a Jupyter notebook, developed by completing the provided skeleton code 10 points are awarded for 2 utility functions, 5 points for and 5 points for formation_gain()o 35 points are awarded for successfully implementing your random forest • Random Forest Reflection [5 pts]: multiple-choice question completed on Gradescope. Q2.1 - Random Forest Setup [45 pts] Note: You must use Python >=3.7.x for this question. You will implement a random forest classifier in Python via a Jupyter notebook. The performance of the classifier will be evaluated via the out-of-bag (OOB) error estimate using the provided dataset Wisconsin_breast_prognostic.csv, a comma-separated (csv) file in the Q2 folder. Features (Attributes) were computed from a digitized image of a fine needle aspirate (FNA) of a breast mass. They describe characteristics of the cell nuclei present in the image. You must not modify the dataset. Each row describes one patient (a data point, or data record) and each row includes 31 columns. The first 30 columns are attributes. The 31st (the last column) is the label, and you must NOT treat it as an attribute. The value one and zero in the last column indicates whether the cancer is malignant or benign, respectively. You will perform binary classification on the dataset to determine if a particular cancer is benign or malignant. Important: 1. Remove all “testing” code that renders output, or Gradescope will crash. For instance, any additional print, display, and show statements used for debugging must be removed. 2. You may only use the modules and libraries provided at the top of the notebook file included in the skeleton for Q2 and modules from the Python Standard Library. Python wrappers (or modules) must NOT be used for this assignment. Pandas must NOT be used — while we understand that they are useful libraries to learn, completing this question is not critically dependent on their functionality. In addition, to make grading more manageable and to enable our TAs to provide better, more consistent support to our students, we have decided to restrict the libraries accordingly. Essential Reading Decision Trees. To complete this question, you will develop a good understanding of how decision trees work. We recommend that you review the lecture on the decision tree. Specifically, review how to construct decision trees using Entropy and Information Gain to select the splitting attribute and split point for the selected attribute. These slides from CMU(also mentioned in the lecture) provide an excellent example of how to construct a decision tree using Entropy and Information Gain. Note: there is a typo on page 10, containing the Entropy equation; ignore one negative sign (only one negative sign is needed). Random Forests. To refresh your memory about random forests, see Chapter 15 in theElements of Statistical Learningbook and the lecture on random forests. Here is a blog postthat introduces random forests in a fun way, in layman’s terms. Out-of-Bag Error Estimate. In random forests, it is not necessary to perform explicit cross- validation or use a separate test set for performance evaluation. Out-of-bag (OOB) error estimate has shown to be reasonably accurate and unbiased. Below, we summarize the key points about OOB in the original article by Breiman and Cutler. Each tree in the forest is constructed using a different bootstrap sample from the original data. Each bootstrap sample is constructed by randomly sampling from the original dataset with replacement (usually, a bootstrap sample has thesame sizeas the original dataset). Statistically, about one-third of the data records (or data points) are left out of the bootstrap sample and not used in the construction of the kth tree. For each data record that is not used in the construction of the kth tree, it can be classified by the kth tree. As a result, each record will have a “test set” classification by the subset of trees that treat the record as an out-of-bag sample. The majority vote for that record will be its predicted class. The proportion of times that a record’s predicted class is different from the true class, averaged over all such records, is the OOB error estimate. While splitting a tree node, make sure to randomly select a subset of attributes (e.g., square root of the number of attributes) and pick the best splitting attribute (and splitting point of that attribute) among these subsets of attributes. This randomization is the main difference between random forest and bagging decision trees. Starter Code We have prepared some Python starter code to help you load the data and evaluate your model. The starter file name is Q2.ipynb has three classes: ● Utililty: contains utility functions that help you build a decision tree ● DecisionTree: a decision tree class that you will use to build your random forest ● RandomForest: a random forest class What you will implement Below, we have summarized what you will implement to solve this question. Note that you must use information gain to perform. the splitting in the decision tree. The starter code has detailed comments on how to implement each function. 1. Utililty class: implement the functions to compute entropy, information gain, perform splitting, and find the best variable (attribute) and split-point. You can add additional methods for convenience. Note: Do not round the output or any of your functions. 2. DecisionTree class: implement the learn() method to build your decision tree using the utility functions above. 3. DecisionTree class: implement the classify() method to predict the label of a test record using your decision tree. 4. RandomForest class: implement the methods bootstrapping(), fitting(), voting() and user(). 5. get_random_seed(), get_forest_size(): implement the functions to return a random seed and forest size (number of decision trees) for your implementation. Important: 1. You must achieve a minimum accuracy of 90% for the random forest. If the accuracy is turning out to be low, try playing around with hyper-parameters. If it is extremely low, try revisiting best_split() and classify()methods. 2. Your code must take no more than 5 minutes to execute (which is a very long time, given the low program complexity). Otherwise, it may time out on Gradescope. Code that takes longer than 5 minutes to run likely means you need to correct inefficiencies (or incorrect logic) in your program. We suggest that you check the hyperparameter choices (e.g., tree depth, number of trees) and code logic when figuring out how to reduce the runtime. 3. The run() function is provided to test your random forest implementation; do NOT modify this function. 4. Note: In your implementation, use basicPython Listsrather than the more complex Numpy data structures to reduce the chances of version-specific library conflicts with the grading scripts. As you solve this question, consider the following design choices. Some may be more straightforward to determine, while some maybe not (hint: study lecture materials and essential reading above). For example: ● Which attributes to use when building a tree? ● How to determine the split point for an attribute? ● How many trees should the forest contain? ● You may implement your decision tree using the data structure of your choice (e.g., dictionary, list, class member variables). However, your implementation must still work within the DecisionTree class structure we have provided. ● Your decision tree will be initialized using DecisionTree(max_depth=10), in the RandomForest class in the jupyter notebook. ● When do you stop splitting leaf nodes? ● The depth found in the learn function is the depth of the current node/tree. You may want a check within the learn function that looks at the current depth and returns if the depth is greater than or equal to the max depth specified. Otherwise, it is possible that you continually split on nodes and create a messy tree. The max_depth parameter should be used as a stopping condition for when your tree should stop growing. Your decision tree will be instantiated with a depth of 0 (input to the learn() function in the jupyter notebook). To comply with this, make sure you implement the decision tree such that the root node starts at a depth of 0 and is built with increasing depth. Note that, as mentioned in the lecture, there are other approaches to implement random forests. For example, instead of information gain, other popular choices include the Gini index, random attribute selection (e.g., PERT - Perfect Random Tree Ensembles). We decided to ask everyone to use an information gain based approach in this question (instead of leaving it open-ended), because information gain is a useful machine learning concept to learn in general. Q2.2 - Random Forest Reflection [5 pts] On Gradescope, answer the following multiple-choice question. You can submit your answer only once. Clicking the “Save Answer” button on Gradescope WILL immediately submit your answer, making it final and unchangeable. Select all that apply; your answer must be completely correct to earn the points. No partial marks will be awarded if all correct options are NOT selected. What are the main advantages of using a random forest versus a single decision tree?
FINC 5001 – FOUNDATIONS IN FINANCE GROUP MAJOR ASSIGNMENT SEMESTER ONE 2025 Due: 11:59pm 12 May 2025 Assessment Weighting: 40 Marks Part A – Written Report (30 Marks) Your team acts as investment analysts at an investment bank, conducting an AI-assisted financial analysis of a publicly listed company. The report should blend AI-generated insights with human evaluation and independent financial reasoning. The report should be written in the style of a professional business report. Required: Select a non-financial list company on the Australian Securities Exchange (ASX) that has been listed on the exchange for at least 5 years (that is listed prior to March 2020). Using data for your selected company undertake the following analysis and prepare a written report presenting your analysis. You are encouraged to present the report partitioned in sections following the same format as given in the questions below. 1. AI Generated Investment Analysis (4 marks): Your group is required to use a generative AI tool (or multiple generative AI tools) to undertake a company analysis of your chosen company (be careful to balance your AI report with the need to undertake independent analysis in the latter parts of the report when generated your AI prompt). Be sure to specify the need for an investment recommendation (buy/hold/sell). Cut and paste the AI response into your report in italics. It is expected that the AI prompts needed will be an iterative process. Specify which AI tool/s you have used and provide all the prompts that were specified to the AI tool during this iterative process. 2. Company Overview and Industry Analysis (3 marks): In this section of the report your group will validate and critique the AI’s summary of the business model, market position, and competitive landscape using academic and market data. Evaluate the quality and thoroughness of the AI report using your own analysis. 3. Financial Performance and Risk Analysis (5 marks): In this section of the report your group will validate and critique the AI-generated figures— such as returns, beta, and volatility—with independently sourced data. Your group should identify any errors, outdated assumptions, or misinterpretations. 4. Valuation (8 marks): In this section of the report your group will independently recalculate key inputs such as growth rates, discount rates, and expected cash flows, and generate your own valuation and estimated share price (as at the time of writing the report). Provide your results and assumptions in the report in a clear and concise manner. 5. Investment Recommendation and AI reflection (10 marks): In this section of the report your group will compare the AI's generated investment recommendation (buy/sell/hold) with your own calculations. Was the generative AI analysis reliable? What types of errors or oversimplifications did you identify in the AI report? Should AI-generated financial insights be disclosed in professional settings? What are the ethical risks of AI-generated investment advice? Discuss with reference to suitable academic literature. Part B – Presentation (10 Marks) The main deliverable ofthis part ofthe assignment is a pre-recorded video presentation in which all members of the group need to participate. The video will present the findings of your written report and will contain your group recommendation (buy/hold/sell). At least 50% of the presentation time mut be spent on critiquing the AI-generated content. The presentation should last between 8-12 minutes and each group member needs to present for at least 2 minutes. A maximum of 7 slides should be included among which: 1. A slide with the names and SIDs ofthe group members (ensure that the order of the names aligns with the order of the presentation). 2. A list of references/sources used in the presentation. Submission Requirements The written report and video presentation (including the slides) should be submitted by 11:59pm (Sydney time) on Monday 12 May 2025. Submission links will be provided on Canvas for your PDF document, video file and Powerpoint presentation slides (as a .pptx file). Only one member (the group leader) should submit the relevant files on behalf of the whole group. Consistent with Business School practice, a late submission penalty will be applied if your submission is not received by the announced due date/time. Written Report Formatting and Presentation: 1. The number of pages allowed ranges from a minimum of 15 to a maximum of 20, with 1.5 line spacing and a font size of 12 Arial or Calibri. It should have normal-sized (2.54cm) margins on all sides. Please number the pages of your report. Marks will be reduced by 5 for each page you exceed the lower and the upper page limit. For example, your mark will be reduced by 10 if the report is of a length of 22 pages or 13 pages. You will be penalised for inappropriate formatting. 2. Text presented in tables and graphs do not need to follow this formatting requirement. However, these will still need to be professionally presented in the report. 3. Ensure you use proper academic referencing in supporting the ideas and discussion within your report. All reports must include a list of references in academic form using the APA 7th method. Further information on the APA referencing style. can be found here:https://libguides.library.usyd.edu.au/citation/apa7. Failing to reference your sources may be subject to further actions according to the University of Sydney Code of Conduct and will be dealt with by the School. https://www.sydney.edu.au/students/academic-dishonesty.html 4. Pay particular attention to presentation. A component of your mark will be based on presentation. Avoid overdoing formatting and ensure that the report is very clear, logical, and professional. Pay attention to grammar. Clear and logical presentation is a major challenge in report preparation. 5. Preparing a concise report poses a major challenge. Brevity and conciseness are key ingredients ofa highly successful report. Every part of the report should somehow add to the result; otherwise, it is superfluous and distracting. 6. Use headings in the report to separate key ideas. Using paragraphs will also assist with structuring ideas. 7. The report must be submitted as a PDF document. You must submit the report electronically via the Turnitin link on Canvas. Excel spreadsheets with all your calculations must be submitted as a .xlsx workbook. You must submit two files electronically via the link on Canvas. What is included in the 15–20-page limit? 1. Report body 2. Tables 3. Diagrams What is excluded from the 15–20-page limit? 1. Title page 2. Table of contents 3. Executive summary 4. Reference list 5. Appendices (For each set of data used in the report, present a screenshot of this data in the Appendix) Marking Rubric The marking rubric for the written report and the video presentation are available on canvas. Please pay careful attention to the marking rubric and ensure that you address all aspects in both your written report and your video presentation.
Final Projects – Guidelines LINC11 Winter 2025 April 3, 2025 Submission due: April 14th, 23:59 on Quercus 1 The Data to Consider You’ll be given the option to choose between one of several topics for the final project. Each of these topics will have some natural language data, and a question or set of questions surrounding it that relates to content we’ve discussed in this course. You’ll be given a brief write-up concerning the topic in question, and one or several papers and/or datasets bearing on this topic to discuss. So, for example, you might receive a paper on Mongolian case, along with a set of discussion questions about the paper and the data therein. You are permitted and encouraged to consider data and discussions outside of those given to you, including from other published work as well as linguistic judgements and data from yourself, your team-mates, or others you might know. However, you must properly cite all of the sources you use, and mention clearly where your data comes from. This is, however, not a field research project, and you should not be going out to collect additional data or formally consulting others. All the data you realistically need to complete this project will be available in the packages given to you. 2 What are we looking for? The final project is a group assignment. We want you to cooperate with others and share your ideas, importantly to learn from one another. However, you are also permitted to submit individually if you absolutely must. As a group project, we are therefore expecting to see the following three pieces: 1. A written report on the topic you choose 2. A group accountability document (just like in synthesis ex. 2) 3. A personal reflection statement on your role in the groupwork 2.1 Written Report As a group, you should submit a written report that addresses the questions posed to you in the Discussion Ques- tions document. These might ask you, for example, to consider an author’s analysis in light of what we’ve learned about the architecture of the grammar, or perhaps you might be asked to formulate your own hypotheses about some of the data. You’ll be asked to illustrate your points with figures and structural diagrams, in addition to other means, e.g. tables, written examples etc. The report should have a clear opening where the problems are outlined, several sections taking up your dis- cussion and/or solutions to the topic you’ve chosen, and concluding or summarizing remarks at the end. Your report must include a discussion of how you arrived at your conclusions and solutions. This is the real core of what we are assessing: your reasoning and analysis skills, taking into account what we’ve discussed this term in class. 2.2 Specifications and Submission Guidelines Your group submission must be completed by uploading a PDF document onto Quercus. Only one member from each group needs to upload a final submission file. Keep your report under seven (7) pages in length (single or double spaced) at an average of 12pt font. There are no strict formatting requirements, but please aim for readability -use simple fonts, keep margins to a reasonable size (2.5cm / 1 inch is ideal) and write with black text, using colour, bold, italics or other special formatting sparingly. You are not being assessed on formatting, but if any formatting choices impact readability, it could impact your grade. Figures and structures may be generated using a program (e.g. R syntax tree, LaTeX etc.), illustrated digitally by other means, or submitted as hand–drawn structures embedded as images in your text. Either way, readability and clarity of presentation of your points is essential. 3 Assessment Criteria These three criteria are equally–weighted aspects of your report. The final project is worth 25% of your final mark, and will be assessed on a point–based rubric taking into account the following assessment criteria: • Have you addressed all of the issues raised in the questions document? • Is the discussion thorough, and properly supported with references to the data, figures, etc.? • Is the writing clear and concise so as to properly convey your argumentation?
CSCS001 Strategic Communication in Society Semester Sem. 1, 2025 Assessment Item Name Contemporary Issues Editorial Weighting 30% Due Date Week 7 Assessment item description A description of the assessment item is as follows: For this assessment, you will write an editorial exploring whether the internet functions as a new Public Sphere. Your editorial should present a well-reasoned argument, applying at least two media effects theories (both strong and limited effects) to analyse the role of media in shaping public discourse on a contemporary social issue. Unlike a traditional essay, an editorial is persuasive and opinion-driven, making a clear argument supported by evidence. You must reference course materials, use real-world examples from news and social media, and include screenshots and direct quotes to support your points. The objective of this assessment is to critically evaluate the ways that the media has affected and delivered key messages relating to a current social issue. You will use this analysis to decide whether the Internet is becoming a new Public Sphere. Subject learning outcomes (SLOs) & Language learning outcomes (LLOs) On successful completion of this assessment item, students should achieve the following outcomes: SLO1 Recognize, analyse and incorporate the social, economic, political and professional contexts for public communication practice SLO2 Identify current controversies in the literature SLO3 Critically reflect on practice SLO6 Write clearly and effectively for identified tasks and publics LLO4 Effectively write an academic text Assessment item brief For this assessment item you are required to produce the following: CONTEXT This Assessment is designed to help you with the process of writing by asking you to author an editorial about a contemporary social issue, analysing the effects the media have had upon it, to decide whether internet technologies are producing a new Public Sphere You will have submitted the Draft Editorial Outline in Week 4 and you should use the feedback and suggestions for improvement in your final Essay submission. Public Communication professionals need to be able to create effective communications strategies to achieve their goals: a key to devising these strategies is the ability to research, analyze and plan effectively. To do this requires the skills of critical analysis that come from theoretical roots, as well as devise effective solutions – essay writing helps you to develop these skills SUPPORT You will have documented your research in your Research & Reading Portfolio, with feedback along the way from your teacher, and your teacher will give you feedback and suggestions for improvement on your Draft Essay Outline. You will have time in class to undertake peer review activities and ask specific questions of your teacher. You should also consider investigating the HELPS resources at UTS College for assistance and tips on all aspects of academic study skills, including research and essay writing. TASK INSTRUCTIONS You must answer the following question: Is the Internet a new Public Sphere? You must answer the following question: Is the Internet a new Public Sphere? To do this, follow these steps: 1. Choose a contemporary social issue that has been significantly shaped by digital media. 2. Analyze media coverage using at least two media effects theories—one representing strong media effects and another representing limited media effects. 3. Gather evidence from news websites, social media platforms, and other online sources. 4. Include screenshots and direct quotes from news articles, tweets, Facebook posts, or other digital content to illustrate your argument. 5. Support your claims with references to at least nine academic sources, including course materials. 6. Structure your editorial with a compelling introduction, clear argumentation, and a persuasive conclusion. Using this research, you should construct an argument that answers the question. To provide more detail to the question: Does the media treatment and influence on your chosen issue show that the Internet is/is not a new Public Sphere? Final Reminder: Your editorial should present a clear opinion backed by evidence. Be persuasive, think critically, and integrate real-world examples to strengthen your argument. Assessment item submission requirements For this assessment item you are required to submit the following: · Length: 1,000-1,250 words, double-spaced. · Structure: Editorial format (headline, subheadings, engaging tone, persuasive argumentation). See week 3 Between Tutorials for details. · Sources: Minimum of 9 academic references (APA 7th edition) + real-world media examples. · Media Integration: At least 3 screenshots of relevant media content (news headlines, social media posts, etc.). · Submission: Online via Canvas · Format: PDF or Word Document ·
ECOM1000 – Business Report and Excel Prescriptive Model Semester 1, 2025 Analytics for Decision Making Business Report – Semester 1, 2025 This business report aims to explore a prescriptive analytics model designed to guide investment decisions through the optimal allocation of stocks within a portfolio. The primary objective is to evaluate and compare two portfolios, determining the ideal weighting of assets by assessing the risk-reward trade-off using the Sharpe Ratio, as outlined in Harry Markowitz's Modern Portfolio Theory (MPT). Consider the following scenario: Imagine you have $150,000 to invest in the US stock market. After conducting extensive research and evaluating the long-term potential of various companies, you've narrowed down your options to two possible portfolios, each consisting of four stocks. Your task is to determine whether Portfolio A or B offers the better investment opportunity. The specific stocks under consideration for each portfolio are detailed below. · Portfolio A: Ticker Company Name Industry Sector T AT&T Telecommunications DUK Duke Energy Utilities KO Coca-Cola Co. Beverage AWK American Water Works Utilities · Portfolio B: Ticker Company Name Industry Sector BAC Bank of America Financials META. Meta. (Facebook) Technology PFE Pfizer Pharmaceuticals DIS Walt Disney Company Entertainment Using the principles of Modern Portfolio Theory (MPT), as outlined in the MPT – Basic Concepts and MPT - Excel Model videos on the Assessments>Assessment 2 - Business Report and Prescriptive Model folder on Blackboard, your task is to evaluate two portfolios that were shortlisted. You are to determine which portfolio offers the most favourable investment opportunity by evaluating the risk-return trade-offs by calculating Sharpe Ratios for each portfolio and providing a well-supported recommendation. Specify the exact allocation of USD 150,000 among the four stocks within the selected portfolio, ensuring that each stock receives between 10% and 50% of the total investment to maintain diversification and prevent over-concentration in a single stock. Assessment Requirements The group needs to address the following points as part of the written report and Excel file: MPT Prescriptive Model – Portfolio Optimization 1. Provide a summary of the steps to create the Prescriptive Model in Excel. 2. Based on the Sharpe Ratio calculations and optimization in your Excel file, which portfolio (A or B) is better for investment? Using the Excel Solver tool, what is the optimal percentage allocation for each stock in the selected portfolio? Provide a possible explanation of the results. Elaborate your answer in 1 to 3 paragraphs. 3. If you invest the entire $150,000, what would be the dollar allocation for each stock in the chosen portfolio? ChatGPT Analysis (Written Report Only) 4. Prompt ChatGPT to evaluate which portfolio—A (T, DUK, KO, AWK) or B (BAC, META, PFE, DIS)—is better based on Modern Portfolio Theory (MPT) and Sharpe Ratio concepts. What was the exact prompt you used? Summarize ChatGPT's response. Did ChatGPT's recommendation align with your conclusions based on your calculations? Provide a detailed explanation in 1 or 2 paragraphs. 5. Enhance your prompt by asking ChatGPT (or GPT extensions) to calculate the Sharpe Ratio and the Portfolio's Expected Return using historical monthly returns from the past five years, risk free rate of 4.45% (considered in your analysis), and the requirements for minimum and maximum allocation of each stock. What prompt did you use for this request? Do you agree with ChatGPT's response? Were there any limitations noted when using the AI tool? Elaborate on your response in a few paragraphs. Extra Tasks (Excel File Only) Add two additional sheets to your Excel file, labelled "Portfolio A – Extra Tasks" and "Portfolio B – Extra Tasks" and address the following points: 1. Use conditional formatting to highlight when monthly returns were greater than 10% (use green colour) and lower than -10% (use red colour). 2. Using the monthly returns dataset, calculate the cumulative monthly returns of each stock as the growth of $1 (starting on 07/2019) in a tabular format and create 2 time series graphs showing the monthly prices and the growth of $1 invested for the stocks in Portfolios A and B. Ensure both graphs are consistently and appropriately formatted. 3. Using the historical monthly returns of the portfolio stocks, calculate the correlation coefficients between all pairs of stocks. Present the results in a matrix format. Visualize the results with a colour scale (Green - Yellow). General Information and Late Submission 1. This is a group assignment, and your assigned group will be announced in Week 3. Each group will consist of 3 students and will be identified by a group number. Groups will include a mix of students from different campuses (e.g., Bentley, Mauritius, Malaysia, and Singapore). One of the objectives of this assessment is to provide an opportunity for cross-cultural collaboration among students, allowing them to learn from diverse perspectives and enhance their teamwork skills in a global context. To facilitate collaboration, it is recommended that groups utilize Microsoft Teams, provided by Curtin University, and schedule regular meetings (at least 3) to meet the assignment requirements. Groups can choose to have their meetings in person or use an online collaboration/meeting software. It is the group's responsibility to coordinate these meetings and distribute tasks among members appropriately. Microsoft Teams Help and Guide for Curtin Students 2. Three components must be submitted for your group's business report: a written report, an Excel working file, and the Group Sign-up Form. Please use the following format and naming conventions for your files: "GroupID_Report.pdf, "GroupID_MPT_Model.xlsx, and "GroupID_Signup_Form.pdf". 3. Use the ECOM1000 Group Sign-up Form.docx template located in the Assessments > Assessment 2 - Business Report and Excel Prescriptive Model folder on Blackboard to complete the Group Sign-up Form. Each group member must acknowledge their participation by e-signing this document, including a signature for their attendance at each of the required meetings. 4. Submit the group written report via the Turnitin Assignment submission point to facilitate plagiarism checking. For additional information on Turnitin, please visit the university website: Link to Student information about Turnitin. Follow the report structure proposed in the Student's Exemplar Word document (Assessments > Assessment 2 - Business Report and Excel Prescriptive Model). Include the Group ID and the last names of all group members in the report's header, formatted as follows: Group #: LastName1, LastName2, and LastName3. Please convert your report to a PDF before uploading it to the Turnitin link on Blackboard and use the following naming format: 'GroupID_Report.pdf'. 5. The submission point for the Group written report, working Excel file, and Group Sign-up Form. on Blackboard can be found under Assessments > Assessment 2 - Business Report and Excel Prescriptive Model > Group #. 6. Please be aware that penalties for late submissions are outlined in your Unit Outline for this unit. Note that penalties are calculated based on the total marks for the assessment. For instance, a 5% penalty for submitting up to 24 hours late means a deduction of 5% from the total 40 marks, which is 2 marks. A 10% penalty per additional day will result in a further deduction of 4 marks per day. These penalties are applied to the total marks, not to your final score. Further Instructions 1. This report focuses primarily on Lecture 5 – Measures of Association but will also require Excel skills developed throughout the semester. To complete this assignment, it is essential to watch the MPT – Basic Concepts and MPT - Excel Model videos, which provides additional theoretical insights and Excel features relevant to the task. It also includes clear instructions on completing your Excel MPT Model file for submission. 2. Follow the assessment tutorial video guidelines to prepare your Excel working file: a. Extract the stock's historical price data using the STOCKHISTORY function. b. Calculate the Portfolio's Risk and Expected Return (annualized to align with the risk-free asset) based on the 5-year historical returns for each stock. Use historical monthly closing price data from July 2019 to July 2024. c. Determine the Covariance Matrix and use it to calculate Portfolio Risk. Use the MMULT and TRANSPOSE matrix functions. d. Assume the US 10-year Government Bond rate as of July 2024, 4.45% per annum, as your Risk-Free Asset. e. Calculate the Sharpe Ratio considering a specific weight allocation (e.g., equally-weighted portfolio). Next, optimize the portfolio's Sharpe Ratio (Excel Solver tool) by adjusting the stocks' proportion. f. Determine the portfolio with the highest optimal Sharpe Ratio and allocate USD 150,000 among the four stocks in that portfolio. Requirement: ensure that each stock receives an allocation between 10% and 50% of the total investment to maintain diversification and prevent over-concentration in a single stock. 3. Ensure your Excel file is well-organized, with a clear and easy-to-follow layout. Refer to the tutorial video for guidance on effectively structuring your model presentation in Excel. 4. The Business Report should follow this structure: Introduction, Prescriptive Model - Portfolio Optimization, Chat-GPT Analysis (expand on the answers to the 5 tasks/questions), and Conclusion (summarize your findings and address any limitations). Ensure that your answers to Questions 1-3 reference your work in Excel. Follow the report structure proposed in the Student's Exemplar Word document (Assessments > Assessment 2 - Business Report and Excel Prescriptive Model). 5. The report, including tables and calculations, must be at most 3,500 words. The text should be formatted with the following settings: 1.5 line spacing, Arial font, 12 font size, 2.5 cm margins on the left, right, top, and bottom. Adherence to these formatting guidelines is mandatory. Any work exceeding the 3,500-word limit will not be marked. The word count begins with the first word on page 1 and includes all content in the report, including tables and references. 6. Assessment Rubric: Please refer to the marking rubric, which will be provided later in the semester, for a detailed breakdown of the 40 marks allocated for your Business Report PDF and Excel submissions. As a preview, 10 marks will be awarded for the reports' formatting, introduction, and conclusion, and 17 marks will be assigned for the Excel working file. Finally, 13 marks for accurate analysis and responses to the assignment questions.
MODULAR PROGRAMME COURSEWORK ASSESSMENT SPECIFICATION Module Details Module Code UFMFP9-15-3 Run 2024/25 Module Title MECHANICS OF MATERIALS Mechanics of Materials Coursework: You are asked to design a door handle in an aircraft, as shown in Figure 1. The loads and major dimensions are provided in Table 1. You, as a designer, are free to choose the other geometric parameters freely considering that design requirements for safety factors are satisfied. The bracket is mounted on the locking mechanism by the help of a flange. There is a fillet of radius r at the transition from the hollow shaft to the flange. Figure 1 Door handle geometry Parameterised geometric data choices are given in Table 1. Question 1 (10 marks) By doing a literature survey and/or consulting materials databases, choose a type of aircraft grade aluminium alloy for the material to be used in the design. Question 2 (20 marks) The bracket is expected to withstand a force of F without yielding. Size your design to provide a reasonable Factor of Safety for static yielding. Please refer to the techniques taught in the year 2 modules: “Structural Mechanics” . You should find the stresses at the most critical location with respect to the coordinate system shown. Then find the Principal Stresses, Maximum Shear Stress, von Mises Stress and the planes on which Principle Stresses and Maximum Shear Stress are acting. Show these planes by drawing a schematic at the critical location. Use a suitable static failure criterion! Question 3 (10 marks) Find the vertical and horizontal deflection of the end of the handle under the applied load using an energy method of your choice. Size your handle so that the static deflection in y- direction should not exceed 2 mm. Question 4 (30 marks) The service load consists of the locking and unlocking force applied to the end of the handle. So for fatigue life calculations, the bracket can be considered to be subjected to a sinusoidal force with Fmax = F and Fmin = -F . Resize your design so that you can provide a reasonable factor of safety for infinite life in fatigue. (By doing a literature survey and/or consulting materials databases, try to find the actual S-N diagram of the aluminium alloy you have chosen. If you cannot, it is also fine to use approximated values derived from the UTS, as done in the lectorials) If the bracket is subjected to a sinusoidal force function with Fmax = 2F and Fmin = 0 what will be the safety factor for infinite life in fatigue? Question 5 (10 marks) Given the fact that the alloy used is a ductile material, find the orientation of the plane at which crack initiates and progresses with respect to the coordinate system shown. Find the dimensions of the crack that will lead to a catastrophic failure. Question 6 (10 marks) Considering that the data retrieved from literature or provided by the manufacturer may not be reliable, you decided to test the specimen in the laboratory yourself. Find the relevant standards for obtaining the relevant material data for your design, provide a brief description of the specimens and procedures in your report. [15 marks] Miscellaneous (10 marks) ● Conduct of presentation (including clarity of slides, time, delivery…) ● Extent of individual effort ● Evidence of teamwork Table 1. Parametric data for design problem. Group Number F a b (N) (mm) (mm) 1000 100 100 1100 90 110 1200 80 120 1300 70 130 1400 60 140 1500 50 150 1600 60 140 1700 70 130 1800 80 120 1900 90 110 2000 100 100 925 115 135 975 105 125 1025 95 115 1075 85 105 1125 75 95 1175 85 105 1225 95 115 1275 105 125 1325 115 135 1375 125 145 1425 135 155 1475 145 165 1525 155 175 1575 165 185 1000 100 100 1100 90 110 1200 80 120 1300 70 130 1400 60 140 Your submission should contain two files: a written “report” in .pdf format and a spreadsheet in .xlsx format. The report should contain a maximum of 10 pages and should contain the formulae used, calculations, relevant graphs and charts. It should also include a summary table in a specified format for geometric dimensions, loads, stresses, stress concentration factors, stress intensity factors, and safety factors at each of the stages of the design. 10 pages is quite short, and you do not need to obey all the rules of technical writing. Feel free to use bullet points instead of full sentences for instance. This being said, it is always a good idea to number headings, and number and caption figures and tables. In doubt, check with the module leader. The preferred channel of communication for this is the Forum on blackboard. A template Excel Sheet is provided with this brief, please fill it with required data and formulae and submit it in addition to your report. Remember that you are iterating your design. Therefore your dimensions and the corresponding factors of safety will vary. It is recommended that you create different worksheets (within the same file) for the different stages and make your chosen data very clear. You can use Matlab instead if you prefer, but make sure your code is very well documented. You might want to complement your Matlab code with a table anyway, as a synthetic way to display your chosen parameters, and the resulting FOSs. The most convenient way to submit is to zip your .pdf and your .xlsx files, and to submit this zip file. The report and spreadsheet are not assessed directly, but through a 30 minutes presentation and question viva style session. In the first 10 minutes, you are expected to present you methods and results, ideally using slides based on your report. This will be followed by 20 minutes of questions. Be prepared to explain how your spreadsheet works!
Fundamentals of Conceptual and Numerical Groundwater Modelling: CEG8527 Coursework 2024/25 Overview You are an independent hydrogeological consultant undertaking an assessment on behalf of a housing developer. You have been engaged to determine whether there is sufficient groundwater in the area to supply a new housing development. You will need to generate a conceptual model, implement a numerical model to assess feasibility, and present a report of your findings to the developer. You have been provided with; • A numerical model for the Stringside surface water catchment (Norfolk, UK) in which the planned groundwater abstraction is to be located. • A river flow time series for the Stringside catchment outfall at Whitebridge (NRFA 33029). • Groundwater levels from an observational borehole at Great Thorn Farm (SHETRAN grid square 133). • The location of a proposed water supply borehole at Lat/Lon = 52.636148, 0.607272 Assignment Task 1 - Create a Hydrogeological Conceptual Model (40 marks) Approximately 5 pages long including figures The conceptual model should include (but is not limited to); 1. Geology overview - including any superficial and bedrock geology. 2. Hydrology overview - including river flow, baseflow, recharge, and rainfall. 3. Aquifer characteristics - including key parameters and information on flow direction/water quality. 4. Summary of what the information tells you about the hydrogeological setting. The conceptual model should begin with a glossary of key terms and any acronyms used in the report and use a range of literature to derive the conceptual model. Include appropriately labelled figures and plots where necessary. State any data gaps and propose ways to address those. Task 2 - Multicriteria Calibration (20 Marks) approximately 3 pages You have been provided with a SHETRAN model for the catchment. Perform. a multi-criteria calibration considering two of the SHETRAN model parameters: the saturated hydraulic conductivity of the chalk layer and its saturated porosity. Assume the chalk aquifer is homogenous and isotropic. Steps to complete; 1. Prepare (and present) a calibration plan. 2. Determine appropriate calibration metrics (objective functions) for the river flow and water level data and interpretation within a multi-criteria calibration strategy and physically plausible parameter limits and parameter sampling strategies. 3. Perform. ~10 calibration runs. 4. Choose the best simulation based on years 2-5 of the simulation (1981-1984). 5. Run your best model for a 20-year period to provide a baseline against which the impacts of abstraction may be assessed. 6. Justify of your choice of “best model” in the context of providing a baseline against which abstraction impacts can be assessed. Task 3 - Groundwater Abstraction Assessment (20 Marks) approximately 4 pages The developer proposes a borehole (located Element 112 in the SHETRAN model) to supply water to the new housing development for 100,000 people. The development itself will be located outside the catchment. It is expected that water consumption will be 130 litres/day per person. It is possible that the abstraction will not meet the needs the total number of residents. 1. Estimate groundwater recharge and choose an appropriate abstraction rate for supply to the new development based on sustainable hydrological considerations. 2. Adjust the SHETRAN model appropriately to include the chosen abstraction rate and perform a 20-year impact assessment simulation (1980-1999 inclusive; 1980 is the spin-up year). 3. Discuss and quantify the hydrological impacts of the abstraction on the water table and surface hydrology considering both wet and dry years. 4. State in the report if you recommend that the development can be totally, partially, or not supplied from the borehole. Task 4 – Discussion, Conclusions, Limitations and Further Work (20 Marks) approximately 2 pages You should provide a summary of your findings from the hydrogeological assessment process including your final recommendation to the housing developer. This should include a discussion of sources of uncertainty in both the conceptual and numerical modelling you have completed. You should critically assess the limitations of your approach and provide a considered review of how you could improve the assessment, including characterisation of geology, additional datasets and modelling enhancements. Marking criteria and submission details To pass this assessment you must be able to demonstrate that you can: • apply, interpret and critically evaluate hydrogeological data; • create, evaluate and update conceptual groundwater models; • understand the process for numerical groundwater modelling, and describe and implement numerical modelling software and techniques for water resource management; • use numerical models to test understanding of groundwater systems. The standard faculty marking criteria as provided on Canvas will be applied, with marks assigned to the sections as indicated. Presentation and accurate citation will be considered as part of the marking process. The maximum length of the submission is 14 pages (assuming single spacing, 11pt text, not including title information and references). You do not have to include screen shots or lengthy descriptions of the modelling process as you will principally be marked for demonstrating understanding and interpretation of the outputs. Submission: 2pm on Monday 28th April. Modelling resources SHETRANexe.zip: the SHETRAN executable code. SHETRANmodel.zip: the SHETRAN model of the Stringside catchment. SHETran-Results-Viewer-1.6.3.zip: Graphical interface to view SHETRAN model results. Shetran Viewer Guide.ppt: Guide to the graphical user interface CalibrationDatasets.xls: observed river flow and water table elevations, plus corresponding simulation data from an uncalibrated SHETRAN model. CR04236N.pdf: Ander, E.L.; Shand, P.; Griffiths, Kate; Lawrence, A.; Hart, P.; Pawley, J.. 2004 Baseline report series. 13, the Great Ouse chalk aquifer, East Anglia. Environment Agency, 48pp. (CR/04/236N) Table 1 Summary ofSHETRAN simulations Task Activity Time period 2 Calibration runs (approximately 10 runs) The first year of the simulation (1980) is the model spin-up period and should not be used in assessing model performance. Compute model performance metrics on years 2 – 5 (1981-84, inclusive). Baseline run Run the selected best simulation for a 20-year period (1980-1999, inclusive). 3 Impact assessment run Run the best simulation, with your chosen abstraction rate, for the same 20-year period as the baseline. Comparisons should exclude the spin-up year (1980).
Operating Systems COMP 310 – ECSE 427 Assignment #2: Multi-Process Scheduling Due: February 28, 2025 at 23:59 1. Assignment Description This is the second of a series of three assignments that build upon each other. In this assignment, you will extend the simulated OS to support running concurrent processes. This assignment can become longer than Assignment 1 if your solution duplicates a lot of code, so plan your solution in advance to be well-factored and don’t hesitate to ask questions on Discord if you get stuck. 1.1 Starter files description: You have three options: • [Recommended] Use your solution to Assignment 1 as starter code for this assignment. If your solution passes the Assignment 1 testcases, it is solid enough to use as a basis for the second assignment. • Use the official solution to Assignment 1 provided by the OS team as starter code. The solution will be released on approximately February 19, so you will have to wait to start programming. You can use this time to go over the assignment instructions carefully and sketch your solution. To obtain a local copy of this documentation, you can get the files from our git repository, assuming you’ve added our remote when you completed A1: $ git fetch staff $ git checkout main $ git merge staff/main # This file is at A2/Assignment_2_Winter2025.{docx,pdf} 1.2 Your tasks: Your tasks for this assignment are as follows: • Implement the scheduling infrastructure. • Extend the existing OS Shell syntax to create concurrent processes. • Implement different scheduling policies for these concurrent processes. On a high level, in this assignment you will run concurrent processes via the exec command, and you will explore different scheduling strategies and concurrency control. Exec can take up to three files as arguments. The files are scripts which will run as concurrent processes. For each exec argument (i.e., each script), you will need to load the full script code into your shell memory. For this assignment, you can assume that the scripts will be short enough to fully fit into the shell memory this will change in Assignment 3. To complete this assignment, you will need to implement several data structures to manage code execution for scripts as the scheduIer transitions processes in and out of the“running”state. These data structures should be defined in their own header and implementation files. Once the infrastructure is established, you will implement the following scheduling policies: FCFS, SJF, and RR. You are encouraged to add new files to the project and modify the Makefile as needed, as your Makefile will be used for evaluation. More details on the behavior of your scheduler follow in the rest of this section. Even though we will make some recommendations, you have full freedom for the implementation. In particular: • Unless we explicitly mention how to handle a corner case in the assignment, you are free to handle corner cases as you wish, without getting penalized. • You are free to craft your own error messages (please keep it polite). • Just make sure that your output is the same as the expected output we provide in the test cases. • Some of the test cases in the assignment have both a *_result. txt and a *_result2. txt expected result. This is because we didn't tell you how to break ties when adding processes to your queue, and depending on which way you break ties you may get different results. You only have to match one, not both. • Formatting issues such as tabs instead of spaces, new lines, etc. in the output will not be penalized. Let’s start programming! 1.2.1. Implement the scheduling infrastructure We start by building the basic scheduling infrastructure. For this intermediate step, you will modify the source command to use the scheduler and run SCRIPT as a process. Note that, even if this step is completed successfully, you will see no difference in output compared to the source command in Assignment 1. However, this step is crucial, as it sets up the scaffolding for the exec command in the following section. As a reminder from Assignment 1, the source API is: source SCRIPT. Executes the commands in the file SCRIPT source assumes that a file exists with the provided path, absolute or relative to the current directory. It opens that text file and then sends each line one at a time to the interpreter. The interpreter treats each line of text as a command. At the end of the script, the file is closed, and the command line prompt is displayed once more. While the script. executes, the command line prompt is not displayed. If an error occurs while executing the script. due a command syntax error, then the error is displayed, and the script continues executing. You will need to do the following to run the SCRIPT as a process: 1. Code loading. Instead of loading and executing each line of the SCRIPT one by one, you will load the entire source code of the SCRIPT file into the OS Shell memory. It is up to you to decide how to encode each line in the Shell memory. o Hint: We highly recommend defining a new data structure in shellmemory.c for storing program lines, separate from the variable memory. Each program line would be a string. o Hint: While you could store the program lines in the PCB, or have a per-process structure in shellmemory.c, that approach would not work for Assignment 3 where the programs will share their code lines. Therefore, we recommend using a structure shared by all processes. This will require an allocator to allocate space in the structure, but it can be very simple. o Hint: Alternatively, you may wish to ignore the looming future of A3 for now, and keep the program code separated from each other. That is a perfectly valid approach. 2. PCB. Create a data-structure to hold the SCRIPT. PCB. PCB could be a struct. In the PCB, at a minimum, you need to keep track of: o The process PID. Make sure each process has a unique PID. o The spot in the Shell memory where you loaded the SCRIPT instructions. For instance, if you loaded the instructions contiguously in a shared data structure in shellmemory.c (highly recommended), you can keep track of the start position and length of the script. o The current instruction to execute. If following the recommendation, this is probably an index into an array of program lines (i.e., serving the role of a program counter). 3. Ready Queue. Create a data structure for the ready queue. The ready queue contains the PCBs of all the processes currently executing (in this case, there will be a single process). One way to implement the ready queue is to add a next pointer in the PCB (which points to the next PCB in the ready queue), and then your queue structure will have a pointer that tracks the head of the ready queue. o Note: you will only ever need one queue at a time, so it is OK to have a single global queue. However, keeping separate queues for different scheduling policies, or for other purposes, can lead to nice solutions, so you may want a complete queue interface with create/destroy functions. It is up to you. 4. Scheduler logic. If steps 1—3 were done correctly, we are now in good shape to execute SCRIPT through the scheduler. o The PCB for SCRIPT is added at the tail of the ready queue. Note that since the source command only executes one script. at a time, SCRIPT is the only process in the ready queue (i.e., it is both the tail and the head of the queue). This will change in Section 1.2.2 for the exec command. o The scheduler runs the process at the head of the ready queue (specifically the highest priority process, in case your queue is not sorted by priority), by sending the process’current instruction to the interpreter. o The scheduler switches processes in and out of the ready queue, according to the scheduling policy. For now, the scheduling policy is FCFS, as seen in class. o When a process is done executing, it is cleaned up (see step 5 below) and the next process in the ready queue starts executing. 5. Clean-up. Finally, after the SCRIPT terminates, you need to remove the SCRIPT source code from the Shell memory. Assumptions • The shell memory is large enough to hold three scripts and still have some extra space. In our reference solution, the shell memory can hold 1000 lines (and is shared by all processes); so, no more than 1000 lines of code will be loaded at the same time. If you implemented your shell from scratch, please use the same limit. • You can also assume that each command (i.e., line) in the scripts will not be larger than 100 characters. If everything is correct so far, your source command should have the same behavior. as in Assignment 1. You can use the existing unit tests from Assignment 1 to make sure your code works correctly. 1.2.2. Extend the OS Shell with the exec command We are now ready to add concurrent process execution in our shell. In this section, we will extend the OS Shell interface with the exec command: exec prog1 prog2 prog3 POLICY Executes up to 3 concurrent programs, according to a given scheduling policy • For now, exec takes up to four arguments. The two calls below are also valid calls of exec: o exec prog1 POLICY o exec prog1 prog2 POLICY • POLICY is (for now) always the last parameter of exec. • POLICY can take the following four values: FCFS, SJF, RR, or AGING. If other arguments are given, the shell outputs an error message, and exec terminates, returning the command prompt to the user. o Recommendation: the policies are different in two ways: when they interrupt the processes, and how they choose which process to run. You will have the easiest time if you structure your code around these two differences. Have only one (a bit tricky) or two (we found this easier) loops executing program code. If using two loops, one is for policies that are non-preemptive, and the other is for preemptive policies. Use configurable variables to decide when to preempt processes, and to decide which policy’s enqueue/dequeue functions should be used. (The reference solution sets the enqueue/dequeue functions using variables with function pointers. However, that is not required, and there are plenty of other reasonable ways to do this.) o If it would take more than a few minutes to add a new scheduling policy to your code, the structure is probably not very good, and this will cause headaches later in the assignment. Exec behavior for single-process. The behavior. of exec prog1 POLICY is the same as the behavior. of source prog1, regardless of the policy value. Note: this is not a special case - a correctly implemented exec should have this property. Use this comparison as a sanity check. Exec behavior. for multi-process. Exec runs multiple processes concurrently as follows: • The entire source code of each process is loaded into the shell memory, as in 1.2.1.1. • PCBs are created for each process. • PCBs are added to the ready queue, according to the scheduling policy. For now, implement only the FCFS policy. • When processes finish executing, they are removed from the ready queue and their code is cleaned up from the shell memory. • Each exec argument is the name of a different script. filename. If two exec arguments are identical, the shell has to display an error (of your choice) and exec must terminate, returning the command prompt to the user (or keep running the remaining instructions, if in batch mode). • If there is a code loading error (e.g., running out of space in the shell memory, or file does not exist), then none of the programs should run. The shell should display an error, and then display the prompt again. The user will have to input the exec command again. • For now, when exec completes, the ready queue should be empty and any space used by the program lines should be reset, so that another exec command can be used independently of the first. If the “background”mode is used (see 1.2.5), this might not be true, as there may still be other processes in the queue that were added by different exec commands. Example execution prog1 code prog2 code prog3 code echo helloP1 set x 10 echo $x echo byeP1 echo helloP2 set y 20 echo $y print y echo byeP2 echo helloP3 set z 30 echo byeP3 Execution: $ exec prog1 prog2 prog3 FCFS helloP1 10 byeP1 helloP2 20 20 byeP2 helloP3 byeP3 $ //exec ends and returns command prompt to user Assumptions • For simplicity, we are simulating a single core CPU. Do not use real threads to run the different programs as this will almost certainly result in out-of-order output. • You can assume that a program containing an exec call does not include other nested exec calls, except that the“background script”(see section 1.2.5) might contain more exec calls. There is more information about how to handle this in that part of the description. 1.2.3. Adding Scheduling Policies Extend the scheduler to support the Shortest Job First (SJF) and Round Robin (RR) policies, as seen in class. • For SJF, use the number of lines of code in each program to estimate the job length. • For RR, schedulers typically use a timer to determine when the turn of a process ended. In this assignment, we will use a fixed number of instructions as a time slice. Each process gets to run 2 instructions before getting switched out. Example execution (prog1, prog2, prog3 code is the same as in Section 1.2.2) Example SJF Example RR $ exec prog1 prog2 prog3 SJF $ exec prog1 prog2 prog3 RR helloP3 helloP1 byeP3 helloP2 helloP1 helloP3 10 10 byeP1 byeP1 helloP2 20 20 20 20 byeP3 byeP2 byeP2 $ $ 1.2.4. SJF with job Aging One of the important issues with SJF is that short jobs continuously preempt long jobs, leading to starvation. Aging is a common technique that addresses this issue. In this final exercise, you will implement a simple aging mechanism to promote longer running jobs to the head of the ready queue. The aging mechanism works as follows: • Instead of sorting jobs by estimated job length, we will sort them by a“job length score”. You can keep track of the job length score in the PCB. • In the beginning of the exec command, the“job length score”of each job is equal to their job length (i.e., the number of lines of code in the script) like in Section 1.2.3. • The scheduler will re-assess the ready queue every time slice. For this policy, we will use a time slice of 1 instruction. o After a given time-slice, the scheduler“ages”all the jobs that are in the ready queue, but not the job that was executing during that time slice. (You may find it easiest to remove jobs from the queue while they are executing via a dequeue operation, and enqueue them back to the queue only after their time slice and any aging step is complete. This goes for all policies.) o The aging process decreases a job’s“job length score”by 1. The job length score cannot be lower than 0. o If after the aging procedure there is a job in the queue with a score that is lower than the score of the job that just ran, then the job with the lower score will run next. Ultimately, this is up to you, but you should keep the queue sorted by job length score when using this policy. The easiest way to do this is for your enqueue function to behave like the “insert”part of insertion sort. That way, after each aging step, when you enqueue the job that just ran back to the queue, it will be inserted in the right place. The other jobs will necessarily be sorted, because they were sorted before and all of their scores decreased by 1 (or are 0). o If after the aging procedure the current head of the ready queue is still the job with the lowest (or tied for lowest)“job length score”, then the current job will continue to run for the next time slice. prog1 code prog2 code prog3 code echo helloP1 set x 10 echo $x echo byeP1 echo helloP2 set y 20 echo $y print y echo byeP2 echo helloP3 set z 30 echo byeP3 Execution of SJF with aging and a time slice of 1 instruction; the state of the ready queue shown in comments: $ exec prog1 prog2 prog3 AGING helloP3 // (P3, 3), (P1, 4), (P2, 5) → aging (P3, 3), (P1, 3), (P2, 4) → no promotion //Nothing printed for set z 30 // (P3, 3), (P1, 3), (P2, 4) →aging (P3, 3), (P1, 2), (P2, 3) →promote P1 helloP1 // (P1, 2), (P2, 3), (P3, 3) →aging (P1, 2), (P2, 2), (P3, 2) →no promotion //Nothing printed for set x 10 // (P1, 2), (P2, 2), (P3, 2) →aging (P1, 2), (P2, 1), (P3, 1) →promote P2 helloP2 // (P2, 1), (P3, 1), (P1, 2) →aging (P2, 1), (P3, 0), (P1, 1) →promote P3 byeP3 // (P3, 0), (P1, 1), (P2, 1) →aging (P3, 0), (P1, 0), (P2, 0), →promote P1 10 // (P1, 0), (P2, 0), no more aging possible byeP1 // (P1, 0), (P2, 0), no more aging possible //Nothing printed for set y 20 // (P2, 0), no more aging possible 20 // (P2, 0), no more aging possible 20 // (P2, 0), no more aging possible byeP2 // (P2, 0), no more aging possible $ 1.2.5. Background Mode In this final exercise, you will approximate the behavior of a bash shell when the `&` modifier is placed after a command. (If you are not familiar, experiment with commands like sleep 10 && echo “done!” vs sleep 10 && echo done &.) Part 1. RR policy with extended time slice. Add a new RR30 policy, where each process gets to run for 30 instructions before it is switched out. The rest of the implementation is identical to the RR policy described in Section 1.2.3. If your code is well- structured, this part should take only a few minutes. (Adding this to the reference solution touched only 8 lines of code.) Part 2. Execution in the background. We will now add the # option to the exec command: exec prog1 [prog2 prog3] POLICY [#] • The semantics of exec are the same as described in 1.2.2. • # is an optional parameter that indicates execution in the background (similar to the & command in the Linux terminal). If exec is run with #, control will appear to return to the batch script, and the batch script will appear to continue running with the scheduler; it will be swapped out with the other programs given to exec. • This is achieved by converting the rest of the Shell input into a program and running it, as you are running programs in the exec command. That is, read the rest of the user input as if it were another program prog0, and then schedule it as such. Call this the“batch script process.”The batch script process begins with the first line after the exec that used #. • All the programs, including the batch script process, are run according to POLICY. • Regardless of the scheduling policy, the batch script process must run first. This gives the batch script process a chance to invoke additional exec commands before other programs run (and possibly finish, which would complicate your code line allocation). Once the batch script has been given a time slice and preempted, it will be scheduled normally after that. In other words, this condition only affects the first time that the batch script. process is scheduled. • While none of the test programs invoke the exec command, the batch script process might. This is the only way that exec commands will be invoked while your scheduler is in-use. This is sort of a weird“exec recursion,”and requires special care. When this happens, you should enqueue the newly exec’d programs onto the same queue that is being used for the exec command that used #. For example, see test case T_RR30_2.txt. Notice that P_quit runs before any of the programs in the first exec command are given a second timeslice. Example execution Commands (prog1, prog2, prog3 same as in Section 1.2.2; RR policy is the same as in Section 1.2.3) exec prog1 RR exec prog1 RR # echo progDONE echo progDONE echo progDONE2 echo progDONE2 echo progDONE3 echo progDONE3 Execution helloP1 progDONE 10 progDONE2 // batch script. has priority byeP1 helloP1 // Only 1 line printout, as the set command does not have an output progDONE progDONE3 progDONE2 10 progDONE3 byeP1 Assumptions • You can assume that only one exec command will be run with the # option in each testcase. • You can assume that the # option will only be used in batch mode. It is difficult to test in interactive mode, so we recommend doing your own testing with batch mode as well. • You can assume that if an exec command with the # option is launched with a POLICY P, then all following exec commands will use the same POLICY P. More generally, we will not be testing different policies in the same testcase. 2. TESTCASES We provide 20 testcases and expected outputs in the starter code repository. Please run the testcases to ensure your code runs as expected, and make sure you get the same results as the automatic tests. IMPORTANT: The grading infrastructure uses batch mode, so make sure your program produces the expected outputs when testcases run in batch mode. You can assume that the grading infrastructure will run one test at a time in batch mode, and that there is a fresh recompilation between two testcases. 3. WHAT TO HAND IN The assignment is due on February 28, 2025 at 23:59. As is the late policy, you have up to 4 late days to use across the entire term, but you must fill out the late submission form on MyCourses before the deadline if you wish to use late days. Your final grade will be determined by running the code in the GitLab repository that is crawled by our grading infrastructure. We will take into account the most recent commit that happened before the deadline, adjusted by any late days requested, on the main branch of your fork. In addition to the code, please include a README mentioning the author name(s) and McGill ID(s), any comments the author(s) would like the TA to see, and mention whether the code uses the starter code provided by the OS team or not. The project must compile on the mimi server by running make clean; make mysh The project must run in batch mode, i.e. ./mysh
ECOM1000 – Analytics for Decision Making Business Report – Assessment 2 Prescriptive Analytics Model – Optimization of Portfolio via MPT Semester 1 - 2025 1. Introduction · Explain the purpose of the report and introduce the theoretical model (e.g., Modern Portfolio Theory, MPT) that will be used for the analysis. · State the study’s objective and include tables highlighting the differences between the analysed portfolios. · Briefly explain how your group planned and worked together, including how meetings were scheduled and conducted (e.g., face-to-face, online via Teams). · Include a brief paragraph from each student introducing a group member, highlighting their background, including work experience, field of study, and cultural identity. Suggestion: 600 – 800 words 2. Prescriptive Model – Portfolio Optimization In this section, we will begin addressing the tasks and questions outlined in the Assessment Requirements. 2.1 Modern Portfolio Theory – Prescriptive Model 1. Provide a summary of the steps to create the Prescriptive Model in Excel. Elaborate a short description of each step. The following steps outline constructing a prescriptive model designed to optimize portfolio allocation based on Modern Portfolio Theory (MPT). This process incorporates key Excel functions and tools, including historical data analysis, risk-return calculations, and optimization techniques, to determine… Suggestion: 500 – 700 words 2. Based on the Sharpe Ratio calculations and optimization in your Excel file, which portfolio (A or B) is better for investment? Using the Excel Solver tool, what is the optimal percentage allocation for each stock in the selected portfolio? Provide a possible explanation of the results. Elaborate your answer in 1 to 3 short paragraphs. The optimal portfolio allocation and Sharpe Ratio for portfolio A and B is as follows: · Sharpe Ratio: Portfolio A Portfolio B Portfolio A Optimal Allocation (%) T DUK KO AWK Portfolio B Optimal Allocation (%) BAC META. PFE DIS Based on the Modern Portfolio Theory (MPT) prescriptive model results and the Sharpe Ratio calculations performed in Excel, Portfolio… Suggestion: 200 – 400 words 3. If you invest the entire $150,000, what would be the dollar allocation for each stock in the chosen portfolio? Present the optimal allocation for Portfolio A in a table format, showing each stock's percentage and dollar investment. Suggestion: 40 – 70 words 2.2 ChatGPT Analysis 4. Prompt ChatGPT to evaluate which portfolio—A (T, DUK, KO, AWK) or B (BAC, META, PFE, DIS)—is better based on Modern Portfolio Theory (MPT) and Sharpe Ratio concepts. What was the exact prompt you used? Summarize ChatGPT's response. To address this task, we developed the following prompt to ChatGPT: Prompt: ChatGPT Answer: Suggestion: 250 – 350 words Did ChatGPT's recommendation align with your conclusions based on your calculations? Provide a detailed explanation in 1 or 2 paragraphs. Suggestion: 100 – 150 words 3. Enhance your prompt by asking ChatGPT (or GPT extensions) to calculate the Sharpe Ratio and the Portfolio's Expected Return using historical monthly returns from the past five years (July 2019 – July 2024), risk free rate of 4.45%, and the requirements for minimum and maximum allocation of each stock. What prompt did you use for this request? To address this task, we developed the following prompt to ChatGPT: Prompt: ChatGPT Answer: Suggestion: 250 – 350 words Do you agree with ChatGPT's response? Were there any limitations noted when using the AI tool? Elaborate on your response in a few paragraphs. Suggestion: 200 – 300 words 3. Conclusion · Summarise your findings and address any limitations. Suggestion: 200 – 300 words
Thesis Title: Atomically Engineered, Self-Healing 2D Semiconductor Platforms for Reversible Logic and Ultra-Low Energy Computation 1. Overview & Motivation As silicon-based logic approaches its physical and thermodynamic limits, the next generation of computation requires radically new materials and device paradigms. This project proposes to explore a novel class of atomically thin, defect-tolerant semiconductors capable of reversible logic switching with minimal energy dissipation, potentially below the Landauer limit. In addition, these materials will be engineered to exhibit self-healing behaviour, a property that could drastically enhance reliability and lifetime in advanced computing systems. 2. Objectives 1. Identify and simulate promising 2D semiconductor materials (e.g., MoS₂, Janus structures, phosphorene) with: a. Tunable bandgaps b. Low defect formation energies c. Reversible electronic or valleytronic behavior 2. Investigate atomic level defect dynamics and healing mechanisms under external stimuli (e.g., thermal, optical, electric field). 3. Design and prototype a reversible logic gate (e.g., Fredkin or Toffoli-type) using the selected material platform. 4. Characterize energy dissipation per logic operation, aiming for sub-kT·ln(2) switching energy. 5. Demonstrate partial or full recovery of logic function after induced damage, confirming self-healing behavior. 3. Methodology 1. Computational Screening: DFT based calculations and AI-guided materials discovery for candidate semiconductors with desired quantum and defect-tolerant properties. 2. Material Synthesis: Fabrication of atomically thin layers using CVD or exfoliation, with dopants or strain to enable dynamic lattice behavior. 3. Device Fabrication: Nanofabrication of test structures (logic elements, transistor analogs). 4. Characterization Tools: a. In situ TEM and STM for defect tracking b. Electrical transport + AFM for logic switching and defect recovery c. Pump-probe spectroscopy for quantum coherence or valley dynamics 5. Theoretical Modeling: Thermodynamic modeling of entropy and information retention in logic operations. 4. Expected Contributions 1. A demonstrable step toward reversible computing using solid-state materials. 2. Experimental validation of self-healing in 2D semiconductors, potentially applicable to next-gen AI hardware, neuromorphic systems, or ultra-resilient space electronics. 3. A scalable framework for ultra-low-power logic that challenges classical limits. 5. Stretch Goals 1. Incorporation of photonic or valleytronic read/write mechanisms 2. Coupling with AI-driven feedback for dynamic material repair prediction 6. Relevance This topic sits at the convergence of materials innovation, energy-efficient computing, and quantum-adjacent device physics. If successful, it may open new pathways toward computing architectures that are: 1. More sustainable 2. Fundamentally reversible 3. Resilient and adaptive at the atomic level 7. Literature Snapshot The proposed work is inspired by and builds upon recent advances in the fields of 2D materials, reversible computing, and defect engineering. Below are several cornerstone papers and reviews that provide both theoretical and experimental backing for the key concepts: Reversible Computing & Sub Landauer Switching 1. Frank, M. P. (2005). Introduction to Reversible Computing: Motivation, Progress, and Challenges. Proceedings of the International Workshop on Physics and Computation. · Introduces the thermodynamic basis of reversible computing and frames it as the future of ultra-efficient logic. 2. Younis, S. et al. (2021). Adiabatic logic: A step toward energy-efficient computing beyond Moore’s Law. Nature Electronics, 4, 472–479. · Describes recent physical implementations of low-energy logic switching using adiabatic designs. 2D Semiconductors for Logic Applications 1. Chhowalla, M. et al. (2016). The chemistry of two-dimensional layered transition metal dichalcogenide nanosheets. Nature Chemistry, 8, 191–201. · A comprehensive overview of the properties, synthesis, and applications of 2D TMDs such as MoS₂, WS₂, etc. 2. Manzeli, S. et al. (2017). 2D transition metal dichalcogenides. Nature Reviews Materials, 2, 17033. · Focuses on electrical properties, valleytronics potential, and device applications of 2D semiconductors. Defect Dynamics & Self Healing in Nanomaterials 1. Zhang, X. et al. (2022). Defect-tolerant and self-healing semiconductors: Towards resilient optoelectronics. Nature Materials, 21, 1093–1101. · Discusses how self-healing occurs in layered materials and how to harness it for durable devices. 2. Komsa, H. P. et al. (2012). Two-dimensional transition metal dichalcogenides under electron irradiation: Defect production and doping. Physical Review Letters, 109, 035503. · Simulates and observes defect creation and migration in 2D TMDs — vital for understanding healing pathways. Quantum Coherence & Valleytronics in 2D Materials 1. Mak, K. F., Shan, J. (2016). Photonics and optoelectronics of 2D semiconductor transition metal dichalcogenides. Nature Photonics, 10, 216–226. · Reviews quantum optical properties of 2D TMDs, critical for understanding potential logic switching methods. 2. Vitale, S. A. et al. (2018). Valleytronics: Opportunities, challenges, and paths forward. Small, 14(30), 1801483. · Explores valley degree of freedom in 2D materials and its role in encoding and preserving information. AI-Driven Materials Discovery 1. Jha, D. et al. (2019). ElemNet: Deep learning the chemistry of materials from only elemental composition. Scientific Reports, 8, 17593. · Demonstrates how deep learning can rapidly screen materials with target properties — useful for narrowing candidates for this thesis.
BAFI1045 - Equity Portfolio Management Assessment Assessment Task 3: Equity Portfolio Management Report Marks/Weighting: 40 marks, accounting for 40% of the total grade for this course Assignment Due Date: Sunday of Week 14, 20th April 2025, 5 pm, Singapore time Word Limit: Maximum 3,500 words (excluding ToC, Appendix and References) Submission: The assignment will be submitted via Canvas, Turnitin Rubric/Marking criteria: A marking rubric is provided on Canvas. The assessment is submitted as an individual assignment You will be given funds to invest in the share market. You are required to construct two $1,000,000 equity investment portfolios: 1. A passive portfolio replicating the return of The Straits Times Index (STI) 2. An active portfolio to achieve your investment objective of outperforming the index You will then prepare a report in which you can explain your investment strategy for constructing a passive and an active portfolio and then evaluate the investment performance of each in terms of absolute and relative return, risk and attribution effects to explain the differences in performance of each portfolio. You will be given ten companies selected from the STI index that tracks the performance of the top 30 companies listed on the Singapore Stock Exchange to create an active portfolio. This assessment replicates the tasks that would be undertaken by portfolio managers in a real-world investment company. For the passive portfolio, your task will be to replicate, as closely as possible, the risk and return characteristics of the Straits Times Index (STI) benchmark index. For your active portfolio, your task will be to select stocks and sectors from ten stocks selected from companies in the STI Index, which will result in your portfolio achieving a higher return than the index. Your task is not necessarily to produce a positive return. If the markets fall in value, then your passive portfolio should fall in value by a similar degree. Your active portfolio should aim to outperform. the return on the index: if the index falls, your portfolio should fall by a lesser amount; if the index rises, then your portfolio should rise by a higher amount. The final submission should fulfil the following minimum requirements For Passive portfolio · calculate the number of shares required for your passive portfolio to replicate the composition of the STI index For Active portfolio Assess all ten companies and sectors from the stocks shared with you · analyse the outlook for each company’s industry · analyse the macroeconomic environment at the global and domestic level · identify the firms and sectors that you consider will outperform. relative to the index and build your active portfolio to reflect your predictions · analyse and comment on three financial ratios of each company over the previous five years. Examples of ratios that can be used- · Return on Equity · PEG Ratio · Net Profit Margin · Earnings Growth · Debt to Equity Evaluate your findings and select six companies for your active portfolio · after assessing the ten companies, select six to be included in your active portfolio · describe the reasons for your selections (around 5 bullet points for each stock) · also, describe the reasons why you have not chosen the other four firms (around 5 bullet points for each stock) · assign portfolio weights for each of your companies and discuss why you have chosen the weights in comparison to the weight of each stock in the index · calculate the number of shares required for each company to create a portfolio with the initial weights you have selected for your active portfolio è why are some companies overweight in your portfolio, and why are others underweight as compared to the index? è what do these active weights mean for your portfolio’s potential performance relative to the index? Build your portfolios · create these two portfolios in LSEG Workspace, ensuring that all dates and numbers of shares are correct Portfolio Creation Dates Passive and Active · Start Date: Monday, March 17th, 2025 Portfolio Names in Workspace · Passive: Student number Replication (Ex. s3254663 Replication) · Active: Student number Active (Ex. s3254663 Active) Benchmark Portfolio · Straits Times Index (STI) Portfolio Analysis period for both portfolios · Start Date: Monday, March 17th, 2025 · End Date: Friday, April 11th, 2025 Observe your portfolios’ performances over the analysis period · as the share prices change over the evaluation period, you will be able to watch how the returns on the index, your active portfolio and your passive portfolio react For each portfolio · explain the reasoning for your stock selection and weighting relative to the index · attach screenshots of your portfolios created in Workspace · report your results for each portfolio · provide comments on the total return/risk and active return/risk of your portfolios · discuss the sectors and securities’ active weights in your portfolio · analyse the active return of your portfolios with reference to the allocation and selection effects · What was the overall performance of the active portfolio, your passive portfolio and the benchmark index? · describe any major market events that contributed to the return performance of the benchmark or your portfolios · have you achieved (or not achieved) the goal for your passive/active portfolio Finally, which of the two portfolios will you recommend and why? Data for your report from Workspace Workspace calculates the portfolio statistics you will require for your report. The information you will need can be found as listed below. Information Workspace Location Total and Active Return Balanced Summary – Contribution Contribution to Return Equity Summary – Performance/Contribution Contribution to Portfolio Weight Equity Summary – Allocation Allocation and Selection Effects Brinson Single Currency Contribution to Total Risk Ex-ante Multi-factor Risk – Portfolio Summary Contribution to Active Risk Ex-ante Multi-factor Risk – Active Summary Performance Ratios (Sharpe, Treynor) Return Statistics You will need to select six stocks for your active portfolio from the following ten stocks that are constituents of the STI Index: Code Company Sector / Industry Group U14 Uol Group Limited Real Estate / Real Estate Management and Development C09 City Developments Limited Real Estate / Real Estate Management and Development BUOU Frasers Logistics & Commercial Trust Real Estate / Industrial REITs M44U Mapletree Logistics Trust Real Estate, Commercial REITs G13 Genting Singapore Consumer Discretionary / Consumer Services C07 Jardine Cycle & Carriage Ltd Consumer Discretionary / Retailing Y92 Thai Beverage Public Co Ltd Consumer Staples / Food, Beverage & Tobacco J36 Jardine Matheson Hldgs Ltd Industrials / Capital Goods S58 Sats Ltd Industrials / Transportation Infrastructure C6L Singapore Airlines Industrials / Transportation
ECON343 Advanced Macroeconomics Research Report Instructions This report contributes to 30% of the final mark for this module. Please read this document and the research report template carefully before completing your report. 1 Instructions Use the Matlab code provided to simulate a real business cycle model. Instructions on how to set up Matlab and run the code is provided below in section 2. Complete a research report of no more than 1,000 words. Your report should address the following three tasks: 1. Run the code to get the plot for the impulse response functions (IRFs). Interpret the economic intuitions of the plot. 2. Line 7 of the code rbc.mod declares 6 key parameters of the model after the com-mand parameters. The parameter names are separated by a space. Line 32 − 46 of the code define the 8 endogenous equations that characterise this RBC model. (i) Use these hints to identify which parameter is the Frisch elasticity of labour supply in the code. (ii) Change the value of this parameter to another reasonable value. Justify your choice of the parameter value. [Hint: You may with to consult the empirical literature to find the reasonable values of this parameter.] (iii) Re-run the code to plot the IRFs under this different paramter value. Compare this plot with the plot you get from task 2 above, and explain the intuition of the difference. 3. The output of the code in the Command Window contains the THEORETICAL MOMENTS of the endogenous variables. Identify the standard deviation of the endogenous variables that you think are mostly affected by the value of the Frisch elasticity of labour supply. Compare those values produced by your exercises in Task 1 and 2 above with the business cycle evidence (such as in King and Rebelo (1999)). Given your finding in this and all above exercises, critically evaluate empirical relevance of the Real Business Cycle model. A separate report template provides further guidance on completing the report. 2 How to Run the Code The code needs to be run in Matlab. In addition, you will need to install Dynare in Matlab to run the code. Dynare is an extension package for Matlab. The package is widely used by academic researchers and central banks for solving and simulating a wide range of macroeconomic models. 2.1 Setting up Matlab and Dynare 1. Register a Mathworks account and associate your account with the University li-cense for Matlab. The instruction on how to do this is here. 2. Download Matlab here. You may need to sign in your Mathworks account to download the package. You can download any version ranging from R2018b to R2024b. 3. Install Matlab by following the instructions of the installer. 4. Download Dynare 6.3 here. Follow the instructions of the installer to install Dynare. For any questions related to installation, consult section 2.2 of the Dynare docu-mentation here. 5. Open Matlab. You need to add the ‘matlab’ subdirectory of your Dynare instal-lation to MATLAB path. You can do this by following the instructions in section 2.4.1 of the Dynare documentation here. There are two methods mentioned in the instructions. If you are following the first method by typing the command, the command window mentioned in the instructions is marked green in the figure be-low. Alternatively, if you are following the second method via the menu entries, the ‘Set Path’ button mentioned in the instructions is marked red in the figure below. Now you have finished the set-up! 2.2 Running the Code To run the code rbc.mod: 1. Open the code in Matlab by clicking Open in the top left corner (marked in red in the figure below). 2. Find the folder where you save the downloaded code. Make sure that you select All Files (marked in red in the figure below) so that you can see the code rbc.mod. 3. Choose the code file and click Open. You will be able to see the script. of the code in Editor (marked in green in the figure below). 4. Check that you ‘current folder’ is the folder where you save rbc.mod at. The way to check this is to check that the directory matches the directory of the code (marked in violet in the figure above), and that rbc.mod appears in the current folder on the left (marked in orange in the figure above). 5. If you current folder is incorrect, you can change this by clicking the small button with a downward green arrow to the left of the directory (marked in blue in the figure above) 6. Once everything is correct, type dynare rbc.mod in the command window. The running should be within seconds. You get some output in the command window and a plot of the IRFs for the 8 endogenous variables to a positive productivity shock as shown in the figure below. You can save this figure by clicking the classic blue save button on the top left of the plot window. Please make sure that you save into a format that can be inserted into your research report (e.g. .jpg, .png, etc.). 7. You can change the values of the key parameters of your choice in line 12-17 of the code. Then you can re-run the code by simply typing dynare rbc.mod again in the command window. The new set of output corresponds to the new set of parameter values. 3 Additional Information on the Model In this model, we assume that the production function is in Cobb-Douglas form. Meanwhile, the households’ utility function is in the following form. 4 How to Submit The report must be submitted online through Canvas. The submission link for this is available on Canvas. The deadline for submitting research report is 14:00 on Wednes-day 7th May. If you have any issues of submitting it on Canvas, please email your report to me ([email protected]) before the deadline. 5 Further Information Regarding Dynare Codes The code is illustrated with comments (initiated by double backward-slashes //) to help you understand what each line of code is roughly doing. For more information on the structure and specific commands of Dynare codes, you can consult here. Note that this is not necessary for completing this research report.
Session: 2023/24 Faculty: Business and Law Programme/Course: Level: 6 Module Title and Code: Business Finance – ACFI3203 2023 520 Date: 7 August 2024 Duration: 3 hours Exam period August 2024 The examination window will follow a 24 hour model which will start and finish at 9.00am BST. You are reminded that the examination must be completed and submitted within the 24 hour examination window. Statement of Own Work By submitting your examination answer, you are confirming that your effort is an individual effort, entirely your own work and that you have not engaged in bad academic practice and/or an academic offence. All students should note that any examination is liable to be subject to similarity testing, which may include being run through Turnitin software. All of your individual workings must be shown in your answers in order that the work can be substantiated as your own. Should there be any doubt as to the authenticity and/or integrity of your submitted answers then the University reserves the right to conduct a one-to-one viva examination with you in order to substantiate your knowledge and the answers submitted. All students should note that it is your responsibility to upload your answer sheet through the TurnitIn portal within the duration. Students who fail to submit through TurnitIn, or within the exam duration, will be awarded 0% for this assessment. Student Guidance on Taking Remote Examinations Students are reminded that guidance on taking online examinations is available on the Examinations web page. If you find what you perceive to be an error in any of the questions, please state your assumptions and continue with your answer. Please provide your answers and all your workings in this word document. Answer below the question you are attempting. Remember to save regularly. No photos, pictures, jpeg or images are allowed in your script. These will not be marked. Copy and paste excel into your word document via “keep source formatting” or “use destination style”. You must submit your script. within Quiz window / tab section before the 3 hours have passed, via the “Add file” button, bottom left side of window, upload your saved document. Then click on “Submit Quiz”. The next page is a confirmation page, check that it confirms that you have answered the question, if you have clicked on “Submit Quiz”. That completes your submission via Quizzes section. Following that, please submit your script. via the Turnitin link in Assignments on the ribbon at the top of the module shell, on the home page of the module. Follow the instructions. Upload your saved document there. Your script. needs to be submitted in 2 (two) places. Examination Rubric: Instructions to and information for candidates There are three (3) sections in this assessment. You must answer all questions in Section A, and ONE (1) question in Sections B and C. (ie ONE (1) from Section B and ONE (1) from Section C.) Section A (Question 1) is worth 10 marks and Sections B (Questions 2 & 3) and C (Questions 4 & 5) are worth 45 marks each. Formulae sheet and tables are provided at the end of this paper SECTION A – SHORT FORM. QUESTION Answer all questions in this section QUESTION 1: DIVIDEND POLICY A company's dividend policy is a crucial decision that affects its relationship with shareholders and its financial performance. In this question, you are required to critically explain three different dividend policies that a company can adopt and provide a detailed explanation of each, including their advantages and disadvantages. (10 marks) SECTION A TOTAL 10 MARKS Section B Choose ONE (1) question only from this section. (ie Question 2 OR Question 3) QUESTION 2: NPV (Net Present Value) BMW, a renowned global automobile manufacturer, is contemplating a substantial multi-million-pound investment in the expansion of the Oxford Mini plant in the United Kingdom. This expansion aims to secure the production of a new line of electric cars and promises to create a substantial number of highly skilled jobs within the UK. The initial market research conducted by BMW, which cost £500,000, suggested that this investment holds significant promise, particularly in light of the UK government's commitment to net-zero policies. To proceed with the project a £800,000 investment in new machinery would be needed. The machinery would have an expected life of 5 years, and a residual value of £50,000. The revenue is forecast to be £350,000 p.a. in real terms, and costs are forecast to be £60,000 p.a. in real terms. Inflation is forecast to be 6% p.a. over the next few years and the firm’s real cost of capital is 11% p.a. Tax depreciation allowances will be claimed at 25% on a reducing balance basis, up until the year of disposal, when a balancing allowance will arise. The tax rate is 33%, and tax is payable the year after that profit is earned. Required: a) Use the Net Present Value method to assess whether the new product should be undertaken and give a recommendation (25 marks) b) Calculate the Modified Internal Rate of Return for the product launch and give a recommendation (9 marks) c) Identify and analyse potential risks and uncertainties associated with using the NPV, IRR and MIRR investment decision making metrics. Discuss the differences between those three methods as well as their advantages and disadvantages. (11 marks) TOTAL: 45 MARKS Choose ONE (1) question from this section (ie Question 2 OR Question 3) QUESTION 3: VALUATION Amazon, a prominent American technology company specialising in online sales, is embarking on a strategic journey aimed at the hostile takeover of Aliexpress, an e-commerce marketplace owned by Alibaba. This aggressive move is driven by a compelling vision: the fusion of business development strategies and direct distribution channels originating from China. Amazon has received advice from its investment banker, asserting that such an integration has the potential to fuel annual growth and accelerate the expansion of their clothing and accessories brand. This case study delves into the complex dynamics surrounding Amazon's proposed hostile takeover of Aliexpress, scrutinizing the rationale, implications, and strategic considerations underlying this monumental endeavour. Below is the financial data from Aliexpress for the evaluation of Amazon's hostile takeover bid. Please use this data to answer the questions presented under the respective requirements. Aliexpress Statement of Financial Position: $000 Non current assets (Note 1) 1,750 Current assets (Note 2) 500 Total assets 2,250 Share capital 100 Reserves 1,150 Equity 1,250 Loan 700 Current liabilities 300 Total equity and liabilities 2,250 Note 1: The freehold property has not been revalued for several years and after an extensive revaluation process the current price has increased the value by $800,000, this is not reflected in the extract above. Note 2: Receivables contain an amount of $300,000 from a large customer which has just gone into liquidation. Extracts from AliExpress Income statement $’000 BASE Revenue 550 Cost of Sales -70 Gross profit 480 Operating expenses -45 Profit from operations 435 Finance costs -60 Profit before tax 375 Taxation (30%) -113 Profit after tax 262 Other information · Selling prices are expected to remain constant · Sales volumes are expected to rise at 7% pa for the next 3 years and then stay constant thereafter. · Assume that cost of sales is a completely variable cost, and that other operating expenses are expected to stay constant. · The discount factor is 9% · Company has just paid a dividend of $75,000. · Dividends are growing at 4% per annum. · The P/E ratio is 4 · Aliexpress currently has 100,000 shares in issue Requirements: a) In the context of Amazon's proposed hostile takeover of Aliexpress, you are required to employ four distinct valuation methods to assess both the minimum and maximum price bid that Amazon should consider for the shares of Aliexpress. Your report should include a calculation of a range of bid prices using: · Net Asset valuation · P/E Ratio Valuation · Dividend Valuation Model · Free Cash Flow Valuation Please provide detailed calculations using the financial data provided. (20 marks) b) Critically evaluate the results obtained from each valuation method, explain advantages and disadvantages of the valuation methods.and provide well-reasoned justifications for your minimum and maximum price bid recommendations. Clearly state any assumptions. (10 marks) c) Critically examine the advantages and disadvantages of merges and acquisitions. Evaluate the potential benefits and drawbacks for shareholders. (15 marks) TOTAL: 45 MARKS Section C Choose ONE (1) question only from this section. (ie Question 4 OR Question 5) QUESTION 4: PORTFOLIO THEORY Jaguar Land Rover UK, a publicly-traded company in the manufacturing sector, is considering two investment opportunities in a new production facility. The company's management is deliberating whether to proceed with the investments, which have the returns and probabilities below: Rate of Returns Probability Y Z 0.1 15% 6% 0.5 22% 15% 0.4 -2% 20% Requirements: a) Calculate the Expected Returns for each of the projects presented above (Y and Z) (4 marks) b) What is the risk measured as standard deviation for each of the projects (Y and Z)? (8 marks) c) Calculate the coefficient of variation for each of the projects (Y and Z). Is Y comparatively a less risky investment? (10 marks) d) If the financial analysts v to invest equal amounts in project Y (50%) and Z (50%), would it reduce risk? Explain and calculate the portfolio risk. (8 marks) e) Critically discuss the limitations and assumptions of CAPM in the context of making investment decisions. (15 marks) TOTAL: 45 MARKS Choose ONE (1) question only from this section. (ie Question 4 OR Question 5) QUESTION 5: Mergers and Acquisitions (M&A) Pfizer, a global pharmaceutical giant, and Seagen, a biotechnology company specializing in cancer treatments, are contemplating a merger and acquisition (M&A) deal to expand their market presence and increase their competitive advantage in the pharmaceutical industry. The Chief Executive Directors of both companies have submitted the data below for your consideration: Pfizer Seagen Earnings per Share (recent) $ 12.17 6.45 Dividends per share (recent)$ 17.29 3.35 Number of shares 3m 1m Share price $ 33.17 19.18 Dividend growth of Seagen is expected to be 6%, expected cost of equity capital is 13%, to be apply to the entities before and after merger, economies of scale will mean that Seagen / the combined entity’s dividends grow at 9%, the transaction costs involved will be $4,000,000. Required: a) You are required to calculate what value could be created from a merger? (10 marks) b) If Pfizer paid $130 cash for each of Seagen’s shares what value would be available for each group of shareholders? (6 marks) c) If Pfizer gave one of its shares for every five shares of Seagen’s what value would be available for each group of shareholders? (10 marks) d) Given the possible deal structures calculated above, discuss the optimal deal structure, consideration should be given to advantages and disadvantages, assumptions made and refinements that should be proposed. (19 marks) TOTAL: 45 MARKS
FIN208 – Fundamentals of Financial Technology Coursework 2: Problem-Based Case Study (Individual Project) The individual project represents 85% of the final mark for this module. It consists of a written report (85%). The submission deadline is May 23, 2025 (Week 14, Friday) by 5pm. A submission link will be provided on the LM Core one week before the deadline. University policies on late submission penalty and academic integrity will be followed. Task Description: As discussed in this module, several financial areas, e.g., banking, payment, insurance, investment, lending, and regulation, have been reshaped by the key technologies, e.g., AI, ML, API, cloud computing, and blockchain. Please select one financial area which has been covered in this module. Within the selected financial area, identify the major problem(s) or challenge(s) faced by stakeholders, and then critically evaluate the real- world FinTech solution(s) to these problem(s) or challenge(s). The FinTech solution(s) could be a firm’s FinTech product(s), such as Alibaba’s Alipay, or FinTech firm(s) themselves, such as ZhongAn Online P&C Insurance. However, they cannot be hypothetical or imaginary. The written report could cover the following points, but are not limited to these points: • Provide background information on your selected financial area. • Clearly identify the problem(s)/challenge(s) faced by stakeholders in the area. • Clearly identify the FinTech solution(s) you intend to discuss. • Critically evaluate the innovative technologies related to the FinTech solution(s). • Critically discuss the risks and ethical issues related to the FinTech solution(s). • Critically reflect on the disruptive impacts of generative AI (e.g., DeepSeek, Qwen, ChatGPT, Claude) on FinTech innovations within your selected financial area. Other requirements: • Reference: o Use of APA or Harvard Referencing, both citation and reference o Minimum of five (5) credible references, e.g., peer-reviewed journals, industry reports, textbooks, newspapers, magazines, etc. o No references from Wikipedia, UKEssays, students’ papers, or other unreliable information sources • Submission package: o Report: 2500 words+/-20% excluding tables, figures, references, and appendix. Name the report by using your student ID and family name, e.g., 20123456_Wang. Save the report as a Word document. o GenAI statement: Save it as a Word file containing a brief description of how Generative AI is used and a list of the key prompts.
Assignment Remit Programme Title MSc Management Module Title Digital Business & Business Analytics Module Code 37989 Assignment Title Individual Assignment Level PG - 20 credit module Weighting 70% Hand Out Date 16/01/2025 Due Date & Time 05/08/2025 12pm Feedback Post Date 02/06/2025 Assignment Format Report Assignment Length 2500 words excluding supporting materials and references Submission Format Online Individual Assignment Remit This assignment involves a practical task. You are asked to source a set of data, clean , manipulate, and use it to produce insights that would be useful to a specific audience or for a defined purpose. You need to produce a report of the process undertaken and the tools you have used for collecting, processing, and analysing data. For this assignment, each student is required to: 1. Select an Appropriate Dataset. Begin by carefully selecting a dataset to apply for this assignment. Your selection can be from any sources so long as there are no copyright restrictions that limit the use of the data. The dataset(s) you select should be those that you think are interesting to a particular group of people. You can find your own sources and take some guidance from lecture material. Other sources of useful datasets might be: - Google Dataset Search -https://datasetsearch.research.google.com - Data.gov.uk - https://data.gov - UK Data Service - https://ukdataservice.ac.uk - World Bank DataBank - https://databank.worldbank.org - OECD Data Explorer -https://data-explorer.oecd.org/ - Eurostat Database -https://ec.europa.eu/eurostat/web/main/data/database - Etc. You can scrape data from public websites where this is appropriate - but we are looking for rather large datasets (more than 500 observations/records with more than 6-7 variables/features) as a key element of your Data Story—not just a few numbers. NB- Avoid redundancy by ensuring that the chosen dataset differs from the one utilized in your work group assignment. In other words, refrain from using the same dataset for both Individual and Group Work Assignments. 2. Identify the Target Audience. Clearly define the target audience for your visualizations. Explain why this audience would be interested in the data and how they are expected to use it once provided. 3. Prepare the Dataset. The dataset you find may need restructuring, cleaning and editing to improve its quality and suitability for your purpose. You may use any tool to clean the data, including (but not necessarily limited to) Python, Excel or the data cleaning tools embedded in Tableau software. 4. Perform Exploratory Data Analysis (EDA) to understand and summarize the key characteristics of a dataset, identify patterns or anomalies, and prepare the data for modelling. Use Excel or Tableau (or both) to explore the data. Your EDA should include a range of visualizations, such as: • Histograms to examine distributions of numeric variables. • Boxplots to detect outliers and understand the spread of data. • Scatterplots to explore relationships between pairs of variables. • Bar charts, line charts, or PivotCharts to analyze trends or compare categories. • Summary tables to present counts or percentages of each categorical variables, and descriptive statistics like mean, median, mode, and standard deviation for numerical variables. • Other relevant visual tools based on the characteristics of your dataset. The primary objectives of your EDA are to: • Gain a good understanding of the variables, including the main characteristics of each variable (e.g., distributions, central tendencies, and variability). • Identify patterns, trends, and relationships between variables. • Detect missing values, outliers, or anomalies in the data and propose strategies to handle them. 5. Select and build appropriate data modelling. The choice of model depends on the nature of the business problem , the goals of the analysis, and the structure of your dataset. This may involve: Regression model: • Purpose: Analyse and predict numerical dependent/outcome variable based on independent variables/predictors. • Examples: Predicting sales revenue, customer lifetime value, or housing prices. • Approach: o Select appropriate regression techniques such as multiple linear regression or non-linear regression models o Evaluate the model's performance using metrics like R-squared and interpret coefficients. Times-series model: • Purpose: Understand and model patterns, trends, and temporal dependencies in time-ordered data. • Examples: Forecasting sales, stock prices, demands, or website traffic trends. • Approach: o Decompose the time series into trend, seasonality, and residual components. o Apply models like Moving Average, Exponential Smoothing, and Regression-based forecasting. o Evaluate predictions using metrics like Mean squared error (MSE) or Mean Absolute Percentage Error (MAPE). Classification model: • Purpose: Analyse and predict categorical dependent/outcome variable based on independent variables/predictors. • Examples: Fraud detection, customer risk classification, or churn behaviour. • Approach: o Use classification algorithms such as k-Nearest Neighbours, logistic regression or decision trees. o Evaluate model performance with metrics like accuracy. Unsupervised model: • Purpose: Identify natural groupings or patterns within the data without predefined labels. • Examples: Market/Customer segmentation, grouping similar products, market-basket analysis or text mining. • Approach: o Use unsupervised algorithms like K-Means, hierarchical clustering, sentiment analysis. o Evaluate cluster validity using metrics such as silhouette score or Elbow method o Visualize clusters using scatter plots, dendrograms, or silhouette plots. Structure of your data analytics report (2,500 words maximum): Chapter 1- Business Understanding: • Detail who the target audience is and the purpose for which they might use the data analytics results. Chapter 2- Data Understanding: • Explain why you chose the dataset(s) you did. You must provide a link to the dataset(s) used. • Describe the data: its size in terms of number of records (observations) and variables (features). Provide data dictionary, including the variable names, formats (e.g., numeric, categorical), descriptions, and examples of data values. Note: Ensure the dataset is different from the one used in your group assignment to avoid redundancy. Chapter 3- Data Preparation: • Explain the process you used to clean, edit or constructing the data. If you discarded any data say why this was done. • If you merged or integrate datasets, explain how and why you did this. • Describe what problems you encountered and how you overcame them. Chapter 4- Exploratory Data Analysis: • Use the methods of descriptive statistics and visualisation (such as crosstabulation, histogram, bar charts, line charts, scatterplots, heat maps, PivotCharts, etc) to explore the data. • Explain and interpret the results of the visualisations, highlighting trends, patterns, relationships, or anomalies. Discuss the implications of these findings in the context of the business or problem at hand. Chapter 5- Modelling: • Depends on the business problem and dataset, apply regression, times series analysis, classification or clustering techniques to build business analytics model(s). • Explain and interpret the results of the model(s) in relation to the business objectives. • If applicable, include comparisons of multiple models to identify the best- performing approach. Submission guidance: 1. Ensure each chapter flows logically and builds upon the previous one and keep the report concise, focusing on key insights and actionable findings. 2. Include the screengrabs of data visualisations in your word submission to help give the word document context. 3. Provide links to the source dataset(s) you used - otherwise we cannot audit the validity of your data, and you will drop marks. 4. Your report should be submitted in the form. of a Word document, use minimum 12pt font, and at least 1.2 line spacing. Module Learning Outcomes: This assignment tests the following module learning outcomes: • Collect, analyse and interpret data analytics to make informed business decisions. • Appraise how digital business and data analytics can be used to generate actionable insights for managers and decision-makers. • Communicating, presenting and disseminating analysis of the data.
COMM1140 Financial Management - Term 1, 2025 Group Assignment Instructions: The group assignment is worth 25% of the total assessment for this course. In your week 4 tutorials, your tutor will randomly divide you into groups. Each group will be allocated one of the below companies, which you must use to complete the task below (hereafter, ‘assigned company’). The 2024 annual report of your assigned company must be used to complete this assessment. For comparative purposes, you may also use other relevant annual reports or public information. 1. Nine Entertainment 2. Seven Network (Seven West Media) 3. The Reject Shop 4. Kogan 5. Temple and Webster Group Assignment: All Australian businesses are currently facing uncertain trading conditions. High inflation and labour shortages have created sudden cost pressures and forced businesses to pass on cost increases to their customers. Additionally, rising interest rates pose a growing risk to businesses that have accumulated high levels of debt and increase the likelihood of a global recession occurring in the next 12 months. You are a UNSW Commerce graduate in 2022 who quickly found employment in Felicity Trust, a financial services company that specialises in providing loans to large Australian businesses. Your manager has asked you to prepare a presentation to help Felicity Trust decide whether it should continue lending money to your assigned company. This is the first task your manager has asked you to complete independently, and you want to ensure that you impress! Luckily, you took notes when the task was assigned to you, which should be strictly followed to complete this task. NOTE: Please also carefully read the marking criteria (rubric) for this assignment (provided in a separate document) which provides you with further details about what is expected. The notes are as follows: Question 1: Present a description of the business and the nature of its operations. This should focus on providing a short explanation of the business’s history, how it generates revenue, and who forms its customer base (5 Marks); Question 2: Present a financial statement analysis of the financial performance and financial position of the company (35 Marks); Question 3: Identify one risk from reading the reports prepared by key management personnel (i.e., Board Chair and/or CEO) in the 2024 annual report that may impact the company’s future financial performance and/or financial position. You should explain clearly how the risk you identify could affect the ratios discussed in Question 2 above (10 Marks); Question 4: Using two Firm Multiples and two Equity Multiples of three similar companies to your assigned company (30 Marks): a) Compare your allocated company with three similar companies and determine which one is the most similar. For the company that is most similar, provide supporting evidence and references of the comparison and state any assumptions (if any) you are making for this comparison. (10 marks) b) Calculate a range and mid-point (average) valuation of your allocated company’s outstanding equity (both the market capitalisation value and market share price) based on the 3 similar companies. Provide evidence of data collected with proper referencing and calculations to substantiate your valuation. (10 marks) c) Based on the comparison in part (a), explain from part (b) the reasons for the width of the range in valuation and why you think the mid-point valuation is accurate or not. Provide evidence and the sources of the evidence that support your explanation. Based on this explanation, give a simple but educated guess about the percentage you would adjust up or down the mid-point valuation to something more reasonable. What would that new mid- point valuation be? (10 marks) Question 5: Present a short description of whether you would recommend Felicity Trust to continue providing loans to your assigned company in the short term. You should clearly describe how and why you came to this decision. (5 marks) Submission Requirements Three separate submissions are required as part of this assignment, as outlined below. 1. Group Contract All groups must complete a group contract that sets expectations as to how the assignment will be completed. The total maximum grade for the group contract is 2 marks. Submission Requirements: One member of each group should email a completed group contract to your tutor by 5pm on Monday, March 24th (Week 6). All group members should be cc’d on the email. Late submissions will be subject to the penalties outlined below. 2. Video Submission To answer Questions 1-4, you should prepare a 15 minute pre-recorded video presentation, clearly following the submission requirements set out below. An additional 5 marks are available for the following: a. Structure of the presentation, professionalism and timing. (2.5 Marks) b. Use of Visual Aids. (2.5 Marks) The total maximum grade for the video submission is 85 marks. Submission Requirements: One member of each group will be required to submit your pre-recorded 15 minute video presentation via the dedicated submission link on Moodle by 5pm on Wednesday, April 16th (Week 9). Late submissions will be subject to the penalties outlined below. 3. Tutorial Presentation To answer Question 5, you must prepare and present a 3 minute presentation in your Week 10 tutorial, clearly following the submission requirements set out below. An additional 8 marks are available for the following: a. Structure of the presentation, professionalism and timing (2 Marks) b. Quality of responses during your presentation and your questions when critiquing an allocated peer group (6 marks) The total maximum grade for the tutorial presentation is 13 marks. Submission Requirements: Each group is required to designate one group member who will be responsible for emailing your presentation to your tutor before your tutorial in week 10. You must include a cover sheet with this submission, which lists the names and Z-ids of all members of the group. This cover sheet can be found on the COMM1140 Moodle site. The designated group member must submit this file on behalf of the entire group. Late Submission Policy Late submission will incur a penalty of 5% per day or part thereof (including weekends) from the due date and time. An assessment will not be accepted after 5 days (120 hours) of the original deadline unless special consideration has been approved. Submission Expectations - Video Presentation 1. To answer Questions 2, 3 and 4, you may only use the ratios provided in the “COMM1140 Ratio List” document (available in the “Group Assignment” Section on Moodle). 2. You must show a copy of the ratios you use to analyse the financial position and financial performance of the company allocated to your group for Question 2. Tables should be embedded in your presentation that show all ratios used to interpret the financial performance and financial position of your assigned company and its peers over the timeframe selected for your analysis (i.e., 2 years or more). We recommend that ratios be presented in table format using the categories discussed in the lecture (profitability, efficiency, liquidity, financial structure). Past students have found the IBISWorld database a useful source of industry averages (as used in your tutorial homework for week 4). 3. Question 4 is about multiples valuation. Start with a brief overview of the method applied, then walk your audience through how you used that method to value the firm. Be sure to explain any assumptions you made and how they might impact your valuation. You need to explain the rationale for choosing your comparable firms. Gather data on the firm you are valuing as well as the firm's competitors. There are several sub-methods for multiples valuation within firm multiples and equity multiples. Choose 4 sub-methods (2 from each valuation method) that are most appropriate for your analysis. Discuss if there are any discrepancies between the valuations. 4. You must also show a copy of the calculations you conducted to answer Question 4 during your presentation. 5. We recommend that groups use data visualisations to support your answer to question two and question four (or any other question you feel appropriate). A video on data visualisation has been provided on Moodle to help you in designing your presentation slides. See the “Support” section of the “Group Assignment” Section on Moodle. 6. We recommend splitting your 15 minutes based on the overall weight of each question. For instance, question two is worth 35/85 marks (approximately 41% of the total marks). This means you should spend about 41% of the 15 minutes on this question, or approximately 6 minutes (6/15 = 0.4). 7. You do not need to include a response to Question 5 in your video submission. This question will be answered in your in class presentation in you Week 10 tutorial. Submission Expectations - In Tutorial Presentation (in your Week 10 tutorial) 1. Your in-tutorial presentation should focus on responding to Question 5. Question 5 asks you to provide a recommendation to your manager and reference evidence for your decision based on information contained in earlier sections of your presentation. There is no ‘correct’ answer here – students can provide valid arguments of “yes, extend the loan” or “No, do not extend the loan” for each company. We are interested in the rationale used to support your decision. You should be clear in your 3 minute pitch to your manager why you came to this decision. We recommend that you provide 3 to 4 reasons to support your recommendation. 2. Following your presentation, a 5 minute Q&A will take place where you will respond to questions from your tutor/peers on your assignment and how you came to your final decision. Each group will be allocated a peer group to which they must pose questions during the Q&A component of that group’s presentation. Peer groups will be allocated in your week 9 tutorial. The questions should focus on extracting the information from the group you need as the manager to understand whether or not the loan facility should be extended. Other guidance: 1. The assignment primarily covers content discussed in the lectures in weeks 4 and 5. You should be able to begin answering questions 1-3 after the week 4 lecture/tutorial and question 4 after the week 5 lecture/tutorial. 2. A marking rubric is provided on Moodle. You could be asked to complete this task in a graduate role in business. Often, for these tasks in the real world, you do not have a sample to work off; your manager simply gives you the task, and you must respond! The idea of this task is to prepare you for such a scenario that you will encounter in the future. If you have questions, please post them in the Q&A forum on Moodle. 3. We encourage groups to spend time preparing their presentation slides – both for your 15- minute video presentation and in-tutorial presentation. Try not to overload your slides with information – this is a common mistake we see each term. Please do ensure, however, that the information you include in your slides communicates the key messages you want to highlight in response to each question. 4. Working in a group can be a challenging process. We encourage groups to work through any challenges that they encounter as a team. The COMM1140 teaching team should only be contacted as a last resort to resolve group conflict. 5. To ensure that you reflect on your contribution and the contribution of your group members, we will ask you to respond to a short Peer Evaluation Survey on Moodle in week 10. If you feel member(s) of your group have not contributed to the assignment, you can express your concerns in the survey. The COMM1140 teaching team will review the student responses, and students found not to contribute to the group assignment may receive a reduced grade. COMM1140 Group Assignment - FAQs FAQs about formatting and general questions regarding the video submission 1. What is the preferred formatting for the pre-recorded video submission? • We recommend that you use Zoom to record your presentation. All group members could be on the call, and we do recommend that the group member speaking at any one time is shown on camera. Others can be off-camera when they are not speaking if they wish. This would be expected in a professional environment. • Alternatively, you can also record your presentation using PowerPoint. 2. What sort of referencing is expected of us? • As it’s a presentation, we don't have specific referencing requirements. You can include a reference list at the end of your slide deck if you wish. 3. Do we show our faces? (i.e. is it a video presentation?) • We recommend that the speaker show their face during the video presentation while they are speaking - similar to how we record the Zoom lectures. 4. Which site should we use the data from for consistency? • You are free to source data from any reliable database. However, using Yahoo Finance for Q4 & IBISWorld for industry averages in Q2 might be more convenient as comprehensive instructions are provided in the tutorial. 5. Is there any leeway on the duration of the recording? For example, +_ 10% length or is 15 minutes just a rough guideline? What is the maximum duration I am allowed to record our presentation? • +/- 30 seconds is considered acceptable. Anything outside of this range will be penalized 1 mark, and excess content will not be graded (beyond 15 minutes 30 seconds). 6. Can a 15-minute video be recorded by one team member? Will other team members who did not participate in the recording be penalised for this? • We recommend all group members be involved in the recording of the video. It's okay if one group member has recorded the video once all group members were involved in the assignment. 7. Does our video recording have to be in one take or can each group member film their part individually and we cut it together? • You can record it individually and make necessary edits afterwards. 8. Does talking speed matter in the video? • Generally, students should seek to speak at a similar pace. There are marks for professionalism, and this would fall into this category. 9. Does the cover sheet have to feature in the video, or can it just be the first slide in the slide deck submission? • Please submit the cover sheet as the first page of the PDF containing your presentation slides for your 15-minute video. The cover sheet does not need to be featured in the video. FAQs about Question 2 of the Group Assignment 1. Should we use Yahoo Finance or the company's annual report to find data to use in ratio calculations? • We recommend the annual report. You should only use data from Yahoo Finance if you can confirm the same formula was used in calculating the ratio. For instance, do Yahoo Finance use NOPAT or PAT for ROE? 2. In the marking rubric for question 2 it is mentioned that we are expected to use the historical data of a peer firm for 3 years or more, or we can alternatively use the industry averages. However, the industry average is only available for the financial year of 2024. If we decide to use the industry average approach, are we expected to show the data for one year? • If you can't find the industry average for a 3-year period, it’s a better approach to compare your company's performance to a peer. In general, it is always good to do both cross-sectional analysis (i.e. compare with the industry average in 2024) and time series analysis (3–5-year trend). 3. We couldn't find the item 'credit sales' from the annual report, would you be able to advise us on what we should do? • Credit sales information is typically internal and unlikely to be found in the annual report. That's why databases commonly use total revenue instead of credit sales revenue to calculate the receivable turnover ratio. We recommend you do the same for your assignment. If receivables are not significant for the company, you might want to consider other ratios. It's not necessary to calculate every single ratio covered in the course. Focus on selecting the most relevant and important ratios for the company you're analysing. 4. Can all the profitability, activity (turnover), liquidity, and solvency ratios be used to examine financial performance AND position? • You should follow the guidance in the grading criteria which suggests you select three or more profitability ratios and relevant activity ratios. For some companies, you won't be able to calculate activity ratios as the information is not disclosed in the annual report. • Overall, you need to identify ratios relevant to your company in each category. 5. Is it mandatory to complete an analysis of DuPont? • It's not mandatory to do DuPont. 6. For calculating things such as the cash ratio and A/P turnover, would I include cash equivalents and other payables respectively as well in the calculation or only use the value for cash and accounts payable itself? • The cash ratio is not super helpful so we would suggest it could be excluded from your analysis. Focus on the current ratio and quick ratio instead. You should just include accounts payable listed as a current liability for the accounts payable turnover calculation. 7. According to IBIS World my group’s assigned company does not have account receivables yet the company’s financial statement has the value for ‘trade and other receivables’. In terms of calculating receivable turnover, is using ‘trade and other receivables’ value applicable? • Trade receivable is accounts receivable. Use the financial statement information to calculate ratios. IBISWorld is for industry averages only. 8. One of the marking criteria guidelines states we need tables to show the working out of the profitability ratios for 4/5 marks. Do we need to show this working out for our company as well as our competitors or is it just for our company? • You don't need to show workings, but we recommend you include a cell that shows the formula you used. The other cells can include the outcome of your calculations per year (i.e., 5%, 6%, 7% etc). You also need to complete and show these calculations for a competitor or find the market average. One company is sufficient as a comparison for the assignment. FAQS about Question 4 of the Group Assignment 1. For question 4a) is it possible to compare businesses that are similar but are in somewhat different industries? Like The Reject Shop as a retail discount store in comparison to a business operating as a retail department store? • Yes, this is ok once you provide a brief justification for your comparison. 2. Is it possible that the most similar company be an international company? • Of course you can use international companies. Comparable firms do not have to come from the same country. If you use ratios/multiples, then currencies don't matter. 3. Our group is doing 'The Reject Shop' and found the 3 companies we are going to compare with. However, those companies are under a bigger group like Kmart is under Wesfarmers, but when calculating Market cap, total assets, etc is there a way to get information just for Kmart or do we just do it under the Wesfarmers company (but this will include the total for every other shop under this group like Coles, Bunnings etc). • Selecting Kmart, which is a subsidiary of Wesfarmers, presents a challenge in isolating its financial data. We recommend checking the "Segment Reporting" section in the notes to the financial statements within the annual report. • If Kmart is a significant division of Wesfarmers, you should find the necessary details there. However, if this information is not available, your group might need to consider another comparable firm. Keep in mind that comparable firms are not restricted to the same country, but please focus on public companies, as information on private firms is harder to obtain. • You should discuss with your group to determine which companies are comparable. • Finding truly comparable firms is challenging, so try to match as many business and financial characteristics as you can. If no other comparable firms are similar in size and you're confident about your selection, proceed with the valuation. But be prepared to adjust the final valuation result to reflect any size discrepancies. 4. Regarding the market cap, do we have to show how we have acquired the data, or can we just use the data straight for the market cap and EV provided on Yahoo? • For the market cap of the assigned company, you need to derive it. Once you get the share price, multiply it by the number of shares outstanding. • For comparable firms, you can obtain the market cap from Yahoo Finance. 5. Once you find the company your selected company is the most similar to. Do you eliminate the valuation range values of the other 2 companies. Or is it possible to only eliminate the value of one of the companies. For example, company 3 is the most similar to your selected company but company 2 is the most similar according to size hence we chose to keep the range between those 2. And get rid of the other one completely. • You should keep all comparable companies so you can derive the valuation range. If you use only one company, then you won't be able to get a "range". • In part c, you can refine your valuation. For example, if only 2 out of 3 companies are truly similar, then you can redo the analysis with those 2 firms to get a more reasonable range. 6. We calculated a negative implied share price for Q4b) and we are not sure if we should include this in our range or ignore it and just talk about the negative share price theoretically. • You may want to double-check the numbers and calculations. • If you are 100% sure it's negative, check the quality of your comparables and multiples. • A negative share price doesn't make sense. 7. My group was planning on calculating the firm and equity multiples for the past 3 years. Given that Yahoo Finance doesn't provide historical statistics for many of these key values, should we be looking solely at the ratios for the most recent financial year instead of the past 3? • You are not required to calculate firm & equity multiples for the past 3 years. The valuation of the target company is current and hence information should be current or forward, not backward. You should follow the tutorial activity in week 5. 8. The instructions say to 'give a simple but educated guess about the percentage you would adjust up or down the mid-point valuation to something more reasonable'. How would we adjust the mid-point valuation, and how would we know what a more reasonable number looks like? • You can examine the stock performance over the past 52 weeks to assess the volatility and evaluate the reasonableness of your valuation range. • Additionally, consider the percentage of revenue generated by your target company in comparison with peer firms. • For example, if 100% of the target company's revenue comes from Business A, whereas only 80% of the peer firms' revenue is derived from this business, you might consider adjusting your valuation by a corresponding percentage (e.g. 20%). • Remember, this is just an illustrative scenario. Apply creativity and logical reasoning to your adjustments. • If you believe the range in 4b is already reasonable and no need to adjust further, then you provide reasons why you believe so. In this case, there is no need to provide a new range/mid- point.
