MATH38032 Time Series Analysis 2024-25 Coursework (Deadline 6pm Friday 4th April) The data in jnj.txt are quarterly earnings per share of Johnson and Johnson from the first quarter of 1960 to the last of 1980. You can download the file from MATH38032 on Bb under Assessment and Feedback (menu on the left). 0 .710000 0 .630000 0 .850000 0 .440000 0 .610000 0 .690000 0 .920000 0 .550000 0 .720000 0 .770000 0 .920000 0 .600000 0 .830000 0 .800000 1 .000000 0 .770000 0 .920000 1 .000000 1 .240000 1 .000000 1 .160000 1 .300000 1 .450000 1 .250000 1 .260000 1 .380000 1 .860000 1 .560000 1 .530000 1 .590000 1 .830000 1 .860000 1 .530000 2 .070000 2 .340000 2 .250000 2 .160000 2 .430000 2 .700000 2 .250000 2 .790000 3.420000 3 .690000 3 .600000 3 .600000 4.320000 4.320000 4 .050000 4.860000 5 .040000 5 .040000 4.410000 5 .580000 5 .850000 6 .570000 5 .310000 6 .030000 6 .390000 6 .930000 5 .850000 6 .930000 7.740000 7.830000 6 .120000 7.740000 8 .910000 8 .280000 6 .840000 9 .540000 10 .260000 9 .540000 8.729999 11 .880000 12 .060000 12 .150000 8 .910000 14 .040000 12 .960000 14.850000 9 .990000 16 .200000 14 .670000 16 .020000 11 .610000 Fit an appropriate ARIMA model to the data. Do the following in R without using any additional package. 1. Read the data into R. No log transform here. [1] 2. Plot the data for 1960-80 and apply diferencing if necessary to remove trend and seasonal pattern. [3] 3. Produce sample acf and pacf plots of the diferenced data. [2] 4. Specify a tentative ARIMA model by examining the sample acf and pacf together. [3] 5. Estimate the parameters of the specified model. [2] 6. Examine the residuals of the fitted model, check correlation and Gaussianity of the residuals. [3] 7. Fit the same model to log quarterly earnings and report any improvement. [1] 8. Choose a model that is adequate for your (earnings or log earnings) data and see if the number of parameters can be reduced. [2] 9. Do 2.—4. above for the log quarterly earnings. [3] Submit a brief report (about 6 pages) on Bb by the deadline. This should be in .pdf format and include an introduction, description of data, results, analysis, and a summary or conclusion. While it is not necessary to list all the R code you used, there should be sufficient information for your results to be reproduced. The weighting of this coursework is 20%. The suggestion is to spend 4-6 hours including computer work and writing up, but excluding revision/catching up.
QBUS6600 Data Analytics for Business Capstone Semester 1, 2025 Assignment 1 (Individual Assignment) 1. Key Instructions Required submission: • Written report (in pdf, due date: Monday, March 31 by the end of the day). • Confidentiality Deep Poll online form (deadline for submission: Monday, March 17). Detailed submission instructions for the report will be posted on Canvas in Week 5. Weight: 30% of your final grade. Length: Your written report should have a maximum of 12 pages (single spaced, 11pt). Cover page, references, and appendix (if any) will not count towards the page limit. Please keep in mind that making good use of your audience’s time is an essential business skill: every sentence, table or figure should serve a purpose. 2. Problem Description Please read through the Project Outline document for your selected industry project, which you can find on the ‘Learn about our industry projects’ page in the Week 1 module on Canvas. Focus on the Problem Description section of the Project Outline, especially the first and third bullet points (EDA and Strategy), which are the most relevant bullet points for Assignment 1. You are not required to build a predictive model for Assignment 1. Both your analysis and your recommendations should be in line with the requirements/suggestions provided in the Project Outline. As a business analyst, you will conduct Exploratory Data Analysis (EDA) of the data corresponding to your industry project. You should aim to find or reveal all possible properties, characteristics, patterns, and statistics hidden in the data, supporting your findings with insightful plots and relevant statistical output. Use the results from your EDA to outline a preliminary strategy or provide preliminary recommendations to the UNICEF team corresponding to your selected industry project. You will have a chance to refine these recommendations in Assignment 2. 3. Written Report The purpose of the report is to describe, explain, and justify your findings to the UNICEF team corresponding to your selected industry report. You may assume that team members have training in business analytics, however, they are not experts in statistics or machine learning. The team’s time is important: please think about the most structured way to present your findings. Be concise and objective. Suggested outline for the main parts of the report (further details below): 1) Problem formulation. 2) Data processing. 3) Exploratory Data Analysis (EDA). 4) Conclusions and preliminary recommendations. You should consider breaking down the longer parts into smaller sections. 4. Marking Scheme formulation5%Data processing30%Exploratory DataAnalysis recommendations10%Writing and presentation ofthe report10%Total100%
CP2414 Assignment 2 Cryptography and Network Security Applications Introduction: This assignment has been divided into four (4) parts. You are to prepare a report for the CEO ofa mattress in a box company with regards to: 1. User authentication 2. Cloud Computing and blockchain for handling the Company's data 3. Network diagram 4. Citation and Referencing Deliverables: 1.A single Word document (.docx) – containing all parts. 2.Font - Calibri 11, Line Spacing 1.5 3.Use IEEE referencing, see https://libguides.jcu.edu.au/IEEE NOTE: The assignment template can be found at the end of this assignment sheets. Scenario: Your client, TheSleepyheads, was satisfied with the advice you provided them with last time. They have decided to hire you again. Having accrued a vast amount ofvaluable data, and with intent to licence the company’s data to others, the CEO, Ms Jessica Raye, has begun to take security more seriously. Note: You may only use information concerning TheSleepyheads in this assignment if it has been provided within this document. Company information must not be carried over from the previous assignment. About the company: TheSleepyheads is a growing mattress in a box company with, now, 3 branches. Some changes have been made to the company networks to accommodate this growth. The Perth branch is still the main branch for the company; however, there are smaller branches in Melbourne, and Christchurch. Each branch now has 5 departments with approximately 50 employees working in each department. The Perth branch now has a mail server, 2 file servers, 2 web servers, a DNS server, and 4 database servers. The smaller branches each now have a mail server, 2 database servers, and two file servers. To the best of Jessica’s knowledge, all of the company data, including all employees’ usernames and passwords for all branches, are being stored in plaintext form. Jessica is concerned that employees’ credentials may be accessed from someone outside of the company and be used to obtain company data. PartI Kerberos and User Authentication As the company grows, Jessica fears legitimate users may be impersonated to access company network resources. You, as a consultant, know that Kerberos would be the answer to Jessica’s requirement regarding user authentication. Your task for this part is to explain how Kerberos cryptography can be used for the user authentication purpose. The following aspects may be explained: • Why Kerberos should be chosen for this purpose? • Does Kerberos use symmetric or asymmetric cryptography? Explain. • How does Kerberos authenticate each client? You may discuss Kerberos Ticket-Granting Server (TGS) and Ticket Granting Ticket (TGT). • How does Kerberos tackle the problem of replay attacks? You must also: • Recommend a commercial software program for user authentication; and • Explain and justify your recommendation clearly. Part II Cloud Computing and Blockchain for Handling the Company's Data As you were already informed, Jessica wants to keep her company’s valuable data secure. She told you that she has heard about Cloud Computing and blockchain, as a result, she wants to know if they could be used to keep the company’s data secure. For this part, you are required to: • Explain the possibility of employing Cloud Computing (CC) for the company to protect valuable data. • You have to recommend a kind/s of CC service/s to be used for the company’s data as well as how data may be sent to an authorised partner securely using the Cloud. You will have to justify why you recommend such CC service/s over the other services. • Explain blockchain in detail to Jessica. Furthermore, list and describe any drawbacks and advantages of employing blockchain in general. • You are to advise the possibility of using Blockchain to keep the company’s data secure and whether blockchain is suitable for this purpose. Explain any drawbacks and advantages of employing blockchain within the company. • You will have to explicitly make a recommendation and justification on employing blockchain for storing the company’s data. Part III Network Diagram employing Kerberos and Cloud Computing for Perth Branch Employing Kerberos for user authentication and Cloud Computing can be an effective means of protecting the company’s valuable data. As such, you are required to design a network diagram for the Perth branch of the company. To do this, you will need to consider the existing devices (see “About the company” – Perth branch ONLY), user authentication software you recommended in Part I, and Cloud Computing service/s you recommended in Part II. You are required to: 1. Draw your proposed network diagram, including: a. User authentication software b. Cloud Computing service integrated to the Perth branch network c. Existing devices (e.g. servers, workstations, router, switches) 2. Explain and justify the proposed network diagram with respect to the placement and purpose of each piece of hardware/software, user authentication software and CC service. Part IV. References • Use correct IEEE referencing style, see https://libguides.jcu.edu.au/IEEE Assignment Guide/Template: To get the highest marks possible, you should READ THE RUBRIC and follow the template below: Part I User authentication • Make a recommendation on Kerberos cryptography o Explain all aspects asked about Kerberos. o Recommendation and justification on a software off the shelf for user authentication. Part II Cloud Computing and Blockchain for Handling the Company's Data • Explain the possibility of employing CC for the company’s valuable data. o Provide recommendation and justification on employing CC (which model you’ve recommended and why). • Explain the possibility of employing Blockchain for the company’s valuable data. o Explain blockchain, list and describe any advantages and disadvantages using blockchain in general (with any other applications). o Explain any drawbacks and advantages of employing Blockchain within the company o Provide recommendation and justification on employing blockchain for storing the company’s data. Part III Network Diagram employing Kerberos and Cloud Computing for Perth Branch • Diagram • Explanation and justification of the proposed configuration. Part IV Use Correct IEEE Referencing Style • includes in-text citation • References at the end of the document using IEEE referencing Style.
Assessment Proforma 2024–25 Key Information Module Code CMT304 Module Title Programming Paradigms Assessment Title Functional Programming Assessment Number Part 2 of the 4-part portfolio coursework Assessment Weighting 25% of the portfolio coursework Assessment Limits Hand-out: 22nd of November 2024 Hand-in: 10th of April 2025, 9:30am Feedback expected by: 13th of May 2025 Limits are per task as set in the instructions The Assessment Calendar can be found under ‘Assessment & Feedback’ in the COMSC–ORG– SCHOOL organisation on Learning Central. This is the single point of truth for (a) the hand out date and time, (b) the hand in date and time, and (c) the feedback return date for all assessments. 1 Learning Outcomes The learning outcomes for this assessment are • Explain the conceptual foundations, evaluate and apply various programming paradigms, such as logic, functional, scripting, filter-based programming, pattern matching and quantum com- puting, to solve practical problems. • Discuss and contrast the issues, features, design and concepts of a range of programming paradigms and languages to be able to select a suitable programming paradigm to solve a problem. 2 Submission Instructions The coversheet can be found under ‘Assessment & Feedback’ in the COMSC–ORG–SCHOOL or- ganisation on Learning Central. All files should be submitted via Learning Central. The submission page can be found under ‘As- sessment & Feedback’ in the CMT304 module on Learning Central. Your submission should consist of these files: Description Type Name Coversheet Compulsory One PDF ( . pdf) file coversheet. pdf Task 1 Compulsory One Haskell ( . hs) source file task1 . hs Task 2 Compulsory One PDF ( . pdf) file task2. pdf If you are unable to submit your work due to technical difficulties, please submit your work via e- mail to [email protected] and notify the module leader (and ideally the setter, if different). Any code will be tested on a Linux system equivalent to COMSC’s Linux lab machines and must run there. 3 Assessment Description Consider the problem of solving a 2 × 2 Sudoku puzzle. It is played on a grid consisting of 4× 4 cells subdivided into four 2 × 2 squares as shown in the figure below. Some of the cells are empty, some of them are filled with digits from 1 through 4. The aim is to fill in the empty cells such that every row, every column, and every 2 × 2 square contains the digits 1, 2, 3, 4. Task 1: Write an efficient Haskell function sudoku p that can solve this problem. Its input is a matrix, represented as a list of rows, where each row is a list of the numbers in the row. The numbers are either 1, 2, 3, 4 if the field is filled or 0 if the field is empty. The output of the function should be one solution to the problem, in the same matrix format with the 0 values replaced by a number 1 to 4 or an error if the input has no solution. For example, for the above grid, the input is p = [[3,4,0,0], [2,0,3,0], [0,3,0,2], [0,0,1,3]] and one solution is [[3,4,2,1], [2,1,3,4], [1,3,4,2], [4,2,1,3]] . Make sure you clearly document your approach and how to use your function in the comments. Note, there are multiple, more or less efficient algorithms to solve this problem – make sure you clearly document your approach. Also note, you must write a function, not a full program (so no main, etc.) and it must have the above name with one argument. Make sure your Haskell code can be compiled/interpreted without errors. You must write your own code to solve this problem and not just call a library function, or copy code from some other source (you only get marks for your own work). You may of course use functions from the standard libraries listed in the Haskell 2010 language report. Task 2: Write a report of up to 400 words (this is an upper limit, not a target) as described below: (a) Discuss one feature of the functional programming paradigm that is useful to solve this prob- lem and compare it to another paradigm of your choice that does not have this feature. (b) Discuss one feature of the functional programming paradigm that makes it difficult to solve this problem and compare it to another paradigm of your choice that would make it simpler. Clearly indicate which of the two points above you address. Make sure you discuss only one feature per point above; only the first feature you discuss for each point will be considered.
Individual Project Date: February 19th, 2025 Students are required to conduct data analytics on price movements ofa stock and write a report of 800 to 1000 words and submit in the 10th week. Total score is 15. Only Excel/Word file is accepted. Submission via Verguide and Moodle are both accepted. Chose a stock from S&P 500 index and provide reasons for choosing this specific stock. Download the prices ofthe stocks, T-bill rate and the S&P500 from the websites, e.g. Yahoo Finance, which we will use as the market index portfolio. a) Use the data and Excel’s regression function to compute the stock’s excess return in each month as well as its alpha, beta, and residual standard deviation, σ(e), over the entire period. b) Fill the following table. What was the sharp ratio of the S&P500 and the stock over the entire period? c) What was the stock’s information ratio over the period? d) If someone whose risky portfolio is currently invested in an index portfolio such as the S&P500 wishes to take a position in the stock based on the estimates from parts (a)-(c), what would be the optimal fraction of the risky portfolio to invest in the stock? Use the equation 6.16 and 6.17. (6.16) (6.17) e) Visualize the price movement of the stocks by graph or charts and analyse price movements over time. Look for trends, seasonal patterns, or cycles in the data. Due date: 5:o00PM, March 26th, 2025
2nd SEMESTER 2024/25 BA Accounting ACC202 Accounting Theory Group Coursework (weighing 35% of overall module mark) ACC202 Accounting Theory (S2, AY2024/25) Group Coursework Instructions (35% of Total Module Mark) A. The Task: You are expected to work with your group members to evaluate the accounting quality of a public company listed on LSE (London Stock Exchange). The task includes the following five steps: Step 1: Look for group members and sign up for a group on LM You are required to identify your own group members and sign up for a group on LM by the specified deadline. Notes: • Each group can consist of up to 6 students. • If you cannot find any other students to work with, or if you prefer to work independently, please consult with the examiner. Step 2: Choose a company for your group coursework Please decide which company you would like to select (the list of companies can be found on LM), and send your choice to the examiner for his approval (email: [email protected]) by the specified deadline. In your email, please include the required details (Group ID number, Company name, and ICB Super-Sector), filling out the table below accordingly. Notes: • Do not select any companies that have been discussed (or will be discussed) in our ACC202 lectures/tutorials. • Each group must select a unique company, different from the choices of other groups. If your chosen company has already been selected by another group, you will then be required to make a second choice. Step 3: Complete the accounting analysis (i.e., presentation PPT document submission and on-site group oral presentation) Evaluate the accounting quality (i.e., earnings quality) of the company in the most recent three full financial years. You may like to follow those examples discussed in the lectures/tutorials. The analysis may be structured as follows: and/or the challenges it faces within the competitive la elievemayinfluencethecompany’saccountingquality[example: Euro Disney], such as:RegulatoryrequirementsorotherinstitutionalfactorsOrmanagersincentivesPart three:Examine2-4accountingitemsfromthefollowinglist.Youneedtoinvestigatetheunusualand/orunexplainedchangesofthoseacc ,beforereachingaconclusion[example: • Angle PLC]Credit sales policy and accounts receivables[example: • • 08); IAG; IHG]R&Dexpenditures,and/orintangibleassets:amortisationandimpairmentloss[example: M&S; Toyota; LG; IHG]Non-recurring items (assetsales, restructuring/acquisition orotherexpensese.g., litigation or oil spill etc.)[example: • R&D partnerships and related party transaYourchosenitemsshouldbecriticaltothecompanyanditsin should contain a certain level ofaccountingflexi .FactorsAccountingitemone…….1Typeofaction2Consistency with GAAP3Directionoftheeffectonearnings4Materiality5Periodofeffect6Purpose in mind
EENG20005 Coursework Script Part 4 DC machines Summary Build analytical models of DC machines and evaluating its steady-state and transient-state characteristics. Learning outcomes 1. Learning how to use Simulink to model a Brushed Permanent Magnet (PM) DC machine and predict its performance. 2. Learning how to model field-wound DC machines and simulate its performance. 3. Analyse, compare, and evaluate the characteristics and output performance of the DC machines. Tools MATLAB 2024a and Simulink. Learning materials 1. An incomplete Simulink model draft. 2. A guidebook for MATLAB - “Matlab_primer”. 3. Tutorial – introduction of Simulink and modelling support. Case 4A Simulink modelling of brushed Permanent Magnet DC machines You will be modelling a permanent magnet DC machine using equivalent circuit diagrams and Simulink models and simulating its performance. Fig 3 shows the draft Simulink model that has been provided for you to begin modelling as you progress through the tasks. (a) Brushed PM DC machines model overview. (b) Brushed PM DC machines incomplete model draft. Fig. 3: An incomplete Simulink model draft. Task 4.1 Draw the equivalent circuit diagram of a brushed Permanent Magnet (PM) DC machine for both steady-state and dynamic-state, and in both cases work out the voltage equations. Briefly describe each component in both equivalent circuits. Discuss the differences between the two circuits. Task 4.2 Derive both the steady-state and dynamic-state torque equations for the same brushed Permanent Magnet (PM) DC machine. Describe each component in the torque equation and briefly explain its physical meaning. Task 4.3 Calculate the no load speed (in revolutions per minute, rev/min or RPM) and stall torque (in Nm) for a permanent magnet DC machine connected to a 50V battery as supply, with the following parameters: Armature Resistance, Ra = 1Ω Armature Inductance, La = 2.5 mH Electro-mechanical Conversion Constant, ke = 2.5 × 10 2 VS rad 1(or Nm A 1) Rotor mass moment of inertia, J = 0.005 kg m2 Rotor viscous friction constant, B = 0.02 Nm S You can do these calculations by hand or through MATLAB code. Task 4.4 Using the incomplete Simulink model provided, build the brushed Permanent Magnet (PM) DC machine. Calculate all the key parameters in the dynamic-state equations of the brushed Permanent Magnet (PM) DC machine by using the parameters given in Task 4.3. In your report, present screenshots or images of your model, distinctly showing the top-level model, the voltage-current control loop, and the torque-speed control loop (You can refer to Fig. 3 of this document as an example). Briefly discuss how these loops work and the relationships between different variables, such as speed, current, torque, voltage, etc. Task 4.5 Using the Simulink model built in Task 4.4, simulate the no-load speed and present your simulation result in your report. For this simulation, set the run-time to 20 seconds. Does the no-load speed operating point from task 4.3 correspond to the simulation results? If not, why? Task 4.6 Using the Simulink model built in Task 4.4, add a varying mechanical load torque that opposes the electro-magnetic torque to simulate the motor having to do some mechanical work. The varying load torque will be a square wave varying from 0 to 0.2Nmwith a time period of 4 seconds. Provide a screenshot of your modified Simulink model. Run your modified Simulink model, and plot the speed and current. Discuss and explain the simulation results; for example, you could discuss the angular speed (ω) curve, the armature current (Ia), and the electromagnetic torque (Tem )) Think of the following questions and discuss your results accordingly: 1. What does the current (Ia) curve look like and why? Discuss how and why its shape changes. 2. What does the angular speed (ω) curve look like and why? Explain the factors impacting the angular speed (ω) and how it changes during the start-up period (dynamic state). Case 4B Simulink modelling of Wound Field DC machines You will be modelling a wound-field DC machine using equivalent circuit diagrams and Simulink models and simulating its performance. Task 4.7 Derive the dynamic equations for a brushed DC machine that has a wound field (rather than a permanent magnet field). Use M as the parameter that is equivalent to the mutual coupling and iF to represent the field current. Use the other parameters such as resistances, mass moments of inertias, coefficient of viscous friction, etc. Please note that these parameters should be consistent with Task 4.1 and Task 4.2). Assume that the machine rotor is infinitely stiff (i.e., no need to model torsional stiffness) and that there is no load torque. Task 4.8 Calculate the value of the mutual coupling parameter (M) required to achieve a performance same as that of the machine in Task 4.3 (shown below) when the field current is 10A. The DC machine is connected to a 50V battery supply. 1- Armature Resistance, Ra = 1Ω 2- Armature Inductance, La = 2.5 mH 3- Electro-mechanical Conversion Constant, ke = 2.5 × 10 2vS rad 1(orNm A 1) 4- Rotor mass moment of inertia, J = 0.005 kg m2 5- Rotor viscous friction coefficient, B = 0.02 Nm S rad 1 Task 4.9 Use the equations from Task 4.7 to convert your PM brushed DC machine Simulink model into a wound field brushed DC machine model. Provide screenshots of your Simulink model. Task 4.10 Use the equations from Task 4.7 to predict how the no-load speed will change if you reduce the field current to 5A in the steady state. Calculate the new stall torque with this configuration. Validate this using your Simulink model and discuss your results. Case 4C Case Study of a Wound Field DC machine. In this case, you will be using both Simulink modelling and simulation techniques and theoretical calculation to study and evaluate a wound field DC machine. A separately excited DC motor delivers rated torque at a rated speed of 600 rpm and has the parameters indicated below: - Rated output power = 1500 kW. - Rated Supply Voltage (for both wound-field and armature) = 600 V. - Rated Armature Current = 2650 A. - Rated Field Current = 83 A. - Armature Resistance = 0.003645Ω . - Armature Inductance = 0.1 mH. - Rotor Co-efficient of Viscous Friction = 15 Nm s rad-1. Tasks 4.11 to 4.15 are related to this. Task 4.11 Case Description: Determine the machine’s torque constant and hence derive the mutual inductance of the machine at rated conditions. You can do this either by hand calculations or through MATLAB code. Task 4.12 Calculate the machine’s efficiency at rated conditions. You can do this either by hand calculations or through MATLAB code. Task 4.13 (Advanced Task) Plot a steady-state torque speed curve/envelope for this machine up to 1500 rpm. For this, use a MATLAB code instead of a Simulink model. Discuss your results. Task 4.14 (Advanced Task) Plot an efficiency curve for the machine when it is supplying maximum torque at each speed over the speed range given in Task 4.13. For this, use a MATLAB code instead of a Simulink model. Discuss your results.
DTS405TC Image Processing and Computer Vision Individual Coursework 2 Due: 7th April 2025 Weight: 50% Maximum score: 100 points Learning Outcomes Assessed • C. Demonstrate expert knowledge to offer critical insight into the current state-of-the-art image processing and computer vision technologies. • D. Expertly analyse real-world IP/CV problems and critically appraise the development of appropriate algorithms used for implementing IP and CV. Coding Policy • Programming Language: All code must be written in Python, with a version of 3.6 or higher. Students are required to use Jupyter Notebook for their implementation, and the main file must be an ’ .ipynb’ file that includes all outputs (such as printed results, graphs, etc). • Code Structure: The code must be well-structured, readable, and properly documented. Comments should be included for each function and section, explaining its purpose and functionality. • Libraries and Tools: The method must be implemented manually, without relying on pre-built computer vision functions or existing open-source lane detection repositories. However, you are permitted to use fundamental functions from libraries such as OpenCV, Scikit-Learn, TensorFlow, PyTorch, Keras, and XGBoost. If you wish to use any other library, please seek approval from the module leader in advance. • Code Validation: Ensure the code is fully executable without errors. All notebooks must be submitted with outputs included (e.g., model training results, visualizations, evaluations), allowing the marker to verify the results without rerunning the notebook. Submission Policy 1. Submission Format • Each team must submit a single zip file containing: (a) The final report in PDF format. (b) Afolder labeled code that contains all individual model implementations, data preprocessing scripts, and evaluation scripts. Each individual’s work should be in a separate Jupyter Notebook ( .ipynb) file. (c) A README file explaining how to run the code, specifying any dependencies (libraries) and installation instructions. 2. File Naming • The file and folders should be named in the format: TeamName_Coursework.zip. Each individual’s code must be in a separate folder, e.g., TeamName_JohnDoe_StudentID_Model .zip. Late Policy 5% of the total marks available for the assessment shall be deducted from the assessment mark for each working day after the submission date, up to a maximum of five working days. Avoid Plagiarism • Do not submit work from other teams. • Do not share code/work to students other than your own team members. • Do not read code/work from other teams, discussions between teams should be limited to high level only. • Do not use open-source code. Overview This coursework involves implementing a lane detection system for autonomous vehicles using deep learning and computer vision techniques. You will develop, test, and analyze methods to detect lane boundaries, focusing on performance metrics and visualisation. 1. Tasks • Detects lane boundaries from an image using deep learning • Visualize the lane detection. 2. Datasets Two datasets will be used in this coursework. (a) Carla driving Dataset: this dataset is for training, evaluation and visualisation. The data set consists of images that were generated with the Carla driving simulator. The training images are images captured by a dashcam that is installed in the simulated vehicle. The label images are segmentation masks. A label image classifies each pixel as the left lane boundary, the right lane boundary or neither of those. The task connected to this dataset is to train a model that can accurately predict the segmentation masks for the validation data set. (b) CULane Dataset: this dataset is for evaluation only. CULaneis a large scale challenging dataset for academic research on traffic lane detection. It is collected by cameras mounted on six different vehicles driven by different drivers in Beijing. More than 55 hours of videos were collected and 133,235 frames were extracted. Data examples are shown above. The CULane dataset include traing set, validation set and test set. In this coursework, we only use 34680 images in test set. The test set is divided into normal and 8 challenging categories, which correspond to the 9 examples below. 3. Evaluations • Evaluation in Carla Driving Dataset: The metric is the Dice Score, which also known as the Dice Similarity Coefficient, is a measure of the similarity between two sets of data, usually represented as binary arrays. In the context of image segmentation, for example, the Dice score can be used to evaluate the similarity between a predicted segmentation mask and the ground truth segmentation mask. The Dice score ranges from 0, indicating no overlap, to 1, indicating perfect overlap. • Evaluation in Carla Driving Dataset: it is more complicated. For the CULane dataset, it is to evaluate F1, Accuracy and Recall. Each channel is treated as a 30-pixel-wide lane, using intersecting unions (IoU) to calculate predictions and ground truths. Where the predicted IoU is greater than the 0.5 threshold, it is marked as True Positives (TP). The evaluation function is defined as: 4. Visualisation After the Lane segmentation, there are some things to visualize the results. (a) Hough Transform.: Use Hough transform. to find a lane line from segmented images. (b) Draw Lines [Mark Lane Lines with different Colour] 1 Method Development & Implementation (30%) 1. Method Development & Implementation • You must individually develop and implement a computer vision method to successfully segment the lane pixel out. • The method must be implemented manually, without relying on pre-built computer vision functions or existing open-source lane detection repositories. However, you are permitted to use fundamental functions from libraries such as OpenCV, Scikit-Learn, TensorFlow, PyTorch, Keras, and XGBoost. If you wish to use any other library, please seek approval from the module leader in advance. • The implementation should include the core components of the methods, such as the structure, training process, and optimization method, all designed and coded independently by the student. 2. Training & Reporting • Ensure that your method is trained, validated, and tested on the Carla Driving Dataset. • Include relevant code snippets and detailed explanations of your implementation in your report. • You must clearly indicate in your report and code which method you implemented. 2 Result Analysis and Evaluation (20%) 1. Evaluation Metrics • You must identify and apply appropriate evaluation metrics to assess the performance of the implemented method. • Evaluate the method using a variety of criteria, such as predictive accuracy, computational efficiency, model complexity, and memory consumption. 2. Interpretation and Discussion • Provide a thorough analysis of the results, interpreting what the evaluation metrics reveal about each method’s performance. • Discuss the implications of the trade-offs observed, offering insights into why your method may excel in specific areas but underperform. in others. • Draw conclusions about the overall effectiveness of your method, supported by a critical analysis of the results. • Reflect on the limitations of the evaluation process and suggest potential areas for further improvement or research. 3 Visualisation (20%) 1. Hough Transform • Solving a problem how to detect multiple lines in an image. • Apply Hough transform. correctly • The Hough Transform detects straight lines by converting them into a parameter space representation. • It identifies intersections in this space to determine dominant lines in the image. • Lane Line Fitting: The detected lines are then mapped back onto the original image, effectively fitting lane lines to the detected edges. This process allows for the identification of lane boundaries, which is crucial for applications such as autonomous driving 2. Draw Lines (Mark Lane Lines with different Colour) • Classify detected lines as left or right lanes based on slope. • Fit a separate line for left and right lanes. • Draw the lane lines on the image. • Overlaying the Lines on the Original Image: to blend the lane lines smoothly with the original image 4 Report Writing (30%) 1. Organization and Clarity • Structure thereport in a clear and logical manner, ensuring that each section flows naturally to the next. • Use straightforward language and explanations to make complex ideas accessible. 2. Accuracy and Detail • Provide precise and detailed descriptions ofthe models, methods, and results. • Ensure technical content is correct and well-supported by evidence or references. • Include relevant code snippets, figures, tables, and other supplementary materials that enhance understanding. • Ensure that all supplementary materials are clearly labeled and appropriately referenced within the report. 3. Formatting and Word Limit • Format the report professionally with consistent use of headings, fonts, and styles. • Ensure that all sections are written succinctly while covering all necessary details. • The report should be concise and should not exceed 2500 words.
UPD202 2nd SEMESTER 2024/25 COURSEWORK BA URBAN PLANNING AND DESIGN – Year 3 RURAL PLANNING Coursework 1: Rural Planning Essay Assignment This coursework is an essay to be completed by individual students. It assesses the learning outcomes A, B, and C, as specified in the Module Specification and Handbook. Students are asked to (1) discuss how rural areas are defined in theory, (2) Choose one country from China, the United Kingdom, and the United States to examine how rural areas are defined in practice, and (3) examine how practical definitions affect rural planning from sustainable development perspective. The discussion should draw on the module learning materials provided and broader literature sources. Task You are expected to: - read the required and recommended reading materials as listed in the Module Handbook and copies provided for the preparation of weekly lectures, - search and assess the relevant literature from peer-reviewed international journals, - analyse theoretical debate in defining rural areas. - identify and discuss different practical definitions of rural areas in your chosen country. - analyse functional changes in rural areas and the scope of rural planning in your chosen country. - discuss how rural planning in the country you choose deals with sustainable development challenges, and - make the format of citations and references right. Marking Criteria Theme Description Quality of articulation and justification of the topic (20%) Demonstrate knowledge and understanding of the topic and ability to introduce the topic and the aim of the work briefly Quality of analysis (40%) Demonstrate skills in conducting critical, coherent, and sound analysis and synthesis of the existing literature Quality of presentation (30%) Demonstrate good writing skills in English on the topic and organise and structure the discussion and arguments clearly and logically. Sources/referencing (10%) All sources cited in the assignment are listed consistently in the references list Rating Point Class Mark (%) 5 First class 100 - 90 to 99 Outstanding 80 to 89 Excellent 70 to 79 Very good 4 Upper second class (2.1) 60 to 69 Comprehensive 3 Lower second class (2.2) 50 to 59 Competent 2 Third class 40 to 49 Adequate 1 Narrow fail 35 to 39 Compensable fail 0 Fail 20 to 34 Deficient 0 to 19 Extremely weak
CPS188 : Term Project : Winter 2025 Introduction: This project is conceived as a team project. It is required that the project be worked on in teams of two to four students (no more, no less, no exceptions). Group members can be from different lab sections but must be from the same professor (Dr. Hamelin: sections 01-10; Dr. Woungang: sections 11-15; Dr. Mustafiz: sections 16-18; Dr. Davoudpour: sections 19-23). Only one submission per group will be permitted so make sure the cover page clearly indicates the members of the group. Groups are managed by the D2L Group Formation Tool. Start working on the project early! Past experiences have found that the end of semesters can be hectic and communications between group members might become more difficult. Description: In this project you will make calculations, graphs and conclusions based on real data. You will find the actual data file here that contains actual data collected by the NOAA during the 2023-2024 winter about the Great Lakes average ice concentration. Values are in %. https://apps.glerl.noaa.gov/coastwatch/webdata/statistic/ice/dat/g2023_2024_ice.dat Days are numbered between 001 to 365, 001 being January 1st and December 31st being 365. Note that for plotting it might be better to convert the days into indexes to avoid gaps in the lines and make the plots more attractive. The file format is CSV (comma spaced values). It is up to you to import the data from the file into your C program. This operation must be done within your C program. Do not copy and enter data by hand! The data in the file is in string format so some numerical values will have to be converted. You are to make a report showing tables, graphs and conclusions based on data using C programming and GNUPlot functionalities. Required elements: The entire project must be presented as one single program (including the parts that generate the output file for the graphs) . Divide your code into sections, one for each question. Add comments in your program to identify which question is answered in that section. Make sure your C and GNUPlot codes are well documented (comments) and well presented (style. and indentation). All computations and determinations are to be done in C using the imported data file. For the graphs, all the labels, legends and titles must be generated by the GNUPlot script. Nothing can be done by hand. The submission package will include the following files: ● The project report in PDF format including the CPS 188 Term Project - Standardized Cover Page. ● A .zip file containing the assets of the project (the .c file of your program and all the GNUPlot scripts (use .gnu or .gp as the file extension). The problems to solve: 1. Calculate the yearly average ice concentration percentage for each of the lakes, and the yearly average for all six lakes put together (GL Total). One 2023 average and one 2024 average for each of the lakes plus the GL total column. So 14 averages in all. 2. Indicate which lake has the highest ice concentration percentage and which lake has the lowest ice concentration percentage, based on the average ice concentration calculated in step #1. 3. Indicate the day and year and the ice concentration percentage with the highest percentage for each of the lakes. In the case ofa tie, mention all the dates. 4. Which day, which year and which lake has the highest ice concentration percentage found in the data file. One single answer unless there are ties, in that case mention all. 5. Make a graph of the ice concentration percentage of each daily average (x=day, y=ice %). Make one graph per lake to show the ice coverage trends. Label the axes clearly and add titles to all your graphs. Use script commands to generate the labels and titles for all graphs. You need 6 plots and figures here. 6. Make a single graph of the ice concentration percentages (x=day, y=ice %) that shows all 6 lines on one graph. Each lake will have a different colour and line type. Title your graph, label your axes, and have a legend. 7. Re-do question 1 (the 7 yearly averages) but with data from 2022-2023 and 2021-2022 instead. Make a table of the averages side by side to illustrate the three yearly results. Any notable differences? Can you advance a conclusion why there is a difference (or not)? 2022-2023: https://apps.glerl.noaa.gov/coastwatch/webdata/statistic/ice/dat/g2022_2023_ice.dat 2021-2022: https://apps.glerl.noaa.gov/coastwatch/webdata/statistic/ice/dat/g2021_2022_ice.dat 8. Make a graph of the ice concentration percentage of each daily average (x=day, y=ice %) (like question 5). Make one graph per lake to show the monthly coverage trends using the three data files. Label the axes clearly and add titles to all your graphs. Use script. commands to generate the labels and titles for all graphs. You make 6 plots and figures here and each plot has 3 lines (2021-2022, 2022-2023, 2023-2024).
Algorithms and Data Structures I Lab 9: Kth Smallest Item Background Statisticians often calculate the median of a collection of numbers to inform themselves about the range of data they’re working with. One way to find the median of a data set is to sort the data and find the item in the middle. We can even take it a step further and return the item at index k - 1 to represent the kth smallest item. To get the median, we can set k = data .length / 2 and run our algorithm. This lab will use our knowledge of quicksort to find the kth smallest value in an array. Exercise Your job is to implement the kthSmallest method in Lab9.java. The kthSmallest method takes in an unsorted int[] called a and a positive int called k. Your method must return the kth smallest value in the array. For example, consider an array of ints: int[] numbers = {10, 6, 4, 3, 6, 9, 5}. If we wanted the smallest item in the array, we could call kthSmallest(numbers, 1), which should return 3. If we wanted the second smallest number, we could call kthSmallest(numbers, 2), which should return 4. To efficiently find the kth smallest item in an array, we can use the partition method from Quicksort. After choosing a pivot and partitioning the array into two subarrays (Smaller and Larger), the following points are true: - If the smaller partition contains exactly k - 1 entries, the kth smallest item is the pivot value (Hint: this is the base case) - If the smaller partition contains k or more entries, it must contain the kth smallest entry. - If the smaller partition contains fewer than k - 1 entries, the kth smallest entry is in the larger partition. There are many ways to correctly implement this program, but few ways to do it efficiently. The autograder will time your program and will reward more points the faster the program can run. In order to receive full credit, your program must utilize an algorithm that is faster than the naive approach. Deliverables You are responsible for submitting Lab9.java with an implemented kthSmallest method. Grading Your program will be autograded based on this rubric: Criteria Points Correctly identify the kth smallest item in an array of 4 integers 1.0 Correctly identify the kth smallest item in an array of 100 integers 0.25 Correctly identify the kth smallest item in an array of 1,000,000 integers within 1,000ms 0.25 Correctly identify the kth smallest item in an array of 1,000,000 integers within 500ms 0.25 Correctly identify the kth smallest item in an array of 1,000,000 integers within 300ms 0.25 Note: If the autograder fails to complete all 5 test cases within 10 minutes, you will receive a 0/2. If all else fails, sort the array using a sorting algorithm from class and then find the kth smallest item. Additionally, your computer might run faster than the autograder. For example, my efficient submission was able to sort in < 50ms locally but took over 200ms when submitted to gradescope. Check your submission with gradescope early to make sure you aren’t going to lose points! Hint: Having trouble implementing the algorithm? Take a look at Sorting2.java on Canvas!
IMSE3107 Systems Modelling and Simulation Assignment 2 Objective The objective of this assignment is to assess the ability of the students to build Excel and FlexSim simulation models to solve typical industrial or logistics engineering application problems. Problem 1 (20 marks) An operation of a company relies on a machine which has 3 different bearings with identical distribution of the lifetime as shown in Table 1. The machine will fail to operate if any one of the bearings fails. In case of machine failure, a mechanic is called to repair the machine and the delay time for the mechanic to arrive is random with a distribution shown on Table 2. The time for a mechanic to repair the machine depends on the total number of bearings that need tobe replaced. The mechanic can replace one bearing at a time, taking 20 minutes for each, or that the total time for replacing all bearings at once is fixed at 38 minutes. Table 3 lists all the costs associated with the maintenance of the machine. Table 1 Table 2 ofmechanicHK$1500 per hourLane123456Destination CodeICNSINBKKTYOMNLJKTAirportIncheonSingaporeBangkokTokyoManilaJakartaCountrySouthKoreaSingaporeThailandJapanPhilippinesIndonesia% of parcels5%10%15%20%25%25%Staging Area123456Lift speed=2ms -1Acceleration=3 ms -2Dimension: length=2.38 mwidth=1.37 m,height=2.50 m
Assignment Remit Programme Title MSc Management Module Title Sustainable and Responsible Business Practices Module Code 38013 Assignment Title Assignment 2: Group Video Presentation and Individual Written Reflection Level LM Weighting 30% (split 80/20 between the video presentation and reflective exercise) Deadline Date & Time 27th March 2025 12pm Feedback Post Date 15th April 2025 Assignment Format Other Assignment Length 5-minute group video presentation (80%) 500-word individual written reflection (20%) Submission Format Online Team Module Learning Outcomes: This assignment is designed to assess the following module learning outcomes. Your submission will be marked using the Grading Criteria given in the section below. LO 3: Connect theory and practice to identify the challenges and opportunities raised by key sustainable and responsible business issues and develop solutions to address these issues in various organisational contexts. LO 4: Critically evaluate the business and moral case for diversity management in various contexts using theory and empirical evidence and draw on implications for the promotion of equality, diversity and inclusion within organisations. LO 5. Undertake reflective and reflexive practice, and assess your own values and position with regards to sustainable and responsible management Assignment: This assignment has two components: 1. Part A: A 5-minute group video presentation 2. Part B: A 500-word individual written reflection This assignment is designed to connect global sustainability challenges related to equality, diversity, and inclusion (EDI) with a specific organizational context. You will apply responsible business tools and frameworks to develop solutions for these challenges. The group video presentation encourages you to develop collaboration, communication, and presentation skills, while the individual reflection supports reflexive practice, self-expression, and lifelong learning for personal and professional growth. Assignment Scenario: Imagine that your group started a food van business two years ago, operating in Birmingham's city centre and catering to lunchtime customers. Your business focuses on one type of cuisine (e.g., British, Chinese, Indian, Middle Eastern, African, Latin American, or any other you prefer) and values sustainability and EDI. Recently, you secured a contract to provide food for the upcoming Commonwealth Games, which requires expanding your business operations, including: • Adding two more food vans. • Hiring additional employees. • Adjusting your food offerings to meet diverse customer expectations. Your task is to create a business plan that aligns these changes with your chosen EDI- focused SDG. Assignment Tasks Part A: 5-Minute Group Video Presentation As a group, complete the following steps: 1. Choose an EDI-Related SDG Select one of the following Sustainable Development Goals (SDGs) and its associated targets: o SDG 5: Gender Equality o SDG 10: Reduced Inequalities o SDG 16: Peace, Justice, and Strong Institutions 2. Preparation Familiarize yourself with the course material related to EDI and any other material you may find relevant. The focus should be on critical analysis i.e., make sure you understand the concepts, ideas, and theories related to EDI and various ways to promote it within organisations and can explain how you will use these within your business. 3. Develop a Business Plan for Expansion Create a comprehensive plan for expanding your business (adding two food vans, hiring employees, and adjusting food offerings) in a way that aligns with your chosen SDG and your business’s sustainability and EDI values. Your plan should include the following components: o Staffing Strategy: How you will hire and manage a diverse workforce while promoting EDI values. o Operational Adjustments: Changes to your food offerings or service model to cater to the diverse audience of the Commonwealth Games. o Sustainability Practices: Integration of responsible business practices, such as using local suppliers, reducing waste, or employing energy-efficient operations. 4. Critically Analyse Your Plan Analyse how well your proposed expansion aligns with the chosen SDG and your business’s EDI values. Identify opportunities and challenges, and provide actionable solutions, supported by relevant theories, concepts, and frameworks from the module. 5. Create and Record the Presentation Develop a video presentation that includes: o Your chosen SDG and its relevance to your business values. o Key actions in your business plan to align your expansion with EDI principles and your chosen SDG. o A critical analysis of opportunities and challenges in embedding EDI and sustainability in your business practices. Presentation Tips: • Keep your video to 5 minutes. • Include visuals that are clear and concise (avoid long text blocks). • Each group member must actively participate. • Follow the practical video creation guidance on Canvas. Note: Design your presentation and record it following the practical guidance available on Canvas. Your presentation should include a view of the presenter(s) as well as your visual aid. Each group member should be an active participant in the presentation (creating and/or delivery). Think about how best to structure your presentation and make sure you rehearse your delivery and timings. Make sure to meet the assignment marking criteria for Part A as presented below. Submission Requirement: Attach three completed Group Meeting Record Forms as an appendix to Part A (see below for more details) . Part B: 500-Word Individual Written Reflection Individually, write a reflection on your experience completing Part A. Address the following: 1. Group Collaboration: Reflect on your experience working in a group to create the video presentation. 2. Strengths and Areas for Improvement: Evaluate what went well, what could have been improved, and how your thoughts, feelings, and values influenced your actions. 3. Learning and Professional Development: o How has this experience shaped your understanding of sustainable and responsible business practices? o Have your professional values evolved since completing Assignment 1? o What insights have you gained from working with your colleagues? 4. Future Applications: Explain how you plan to apply these insights in your personal and professional life.
DTS406TC Natural Language Processing Coursework 2 (Individual Assessment) Due: 5:00 pm China time (UTC+8 Beijing) on April 6, 2025 Weight: 60% Maximum score: 100 marks (100 individual marks) Assessed learning outcomes: C Implement and evaluate different NLP algorithms and models based on performance metrics and real-world application requirements D Critically review advanced topics in NLP , such as prompt learning, language generation , and natural language understanding E Demonstrate a strong capability for undertaking individual research on NLP problems Overview Question Answer System is defined as given a question, the system is able to correctly seek or generate the corresponding answer. The common question answer systems include Reddit, Yahoo Answer, Quora, Zhihu and so on. The Question Answer System assists the users to quickly receive the answer regarding the question that the user posts. On the other hand, NLP technologies are widely applied in the medical, legal, and financial domain. Equipped with the cutting-edge NLP algorithms, many problems are well addressed in these domains. Part One 1. Literature Review on Question Answer System (20 Marks) a) Overview of the Question Answer System and its applications. Please provide three examples of real-life applications of the Question Answer System. (6 Marks) b) Please list three key challenges in the Question Answer System. (6 Marks) c) Please elaborate on two BERT-style. and two ChatGPT-style. approaches to the Question Answer System. Meanwhile, discuss the advantages and disadvantages of each approach. (8 Marks) 2. Data Collection (12 Marks) Collect two datasets of User-Generated Content (UGC) from platforms such as Reddit or Yahoo Answer, focusing on the Question Answer System in different scenarios. Each dataset should contain a minimum of 3,000 instances. Preprocess the datasets by performing tasks like stopword removal and tokenization. Finally, conduct a statistical analysis of the two datasets(e.g., the word distribution of the corpus). Notice that some UGC data may be downloaded from Kaggle if there are API restrictions preventing direct downloads from social platforms. (6 Marks/dataset x 2=12 Marks) 3. Algorithm Description and Implementation (32 Marks) a) Choose two approaches for the answer generation in the Question Answer System on each collected UGC dataset: one using a BERT-style approach and the other employing a ChatGPT-style approach. You can directly adopt open-sourced LLMs like Llama and Qwen from Hugging Face. However, to use closed-source LLMs like ChatGPT, you'll need to register and access them via the API. Note that one dataset is designed for answer selection, where a BERT-style. approach will be applied. The other dataset is for answer generation, where a ChatGPT-style approach will be used. Please provide the pseudo-code. (3 Marks/algorithm x 2= 6 Marks) b) The BERT-style approach should be incorporated with Contrastive Learning(CL), and the ChatGPT-style. approach should be incorporated with Retrieval Augment Generation(RAG). Please provide the pseudo-code. (3 Marks/algorithm x 2= 6 Marks) c) Develop a Question Answer System for each approach using Python. The implementation pipeline should include the following components: feature engineering (3 Marks), algorithm implementation (6 Marks, with CL for the BERT-style approach and RAG for the ChatGPT-style approach), and metrics computation (1 Marks). (10Marks/algorithm x 2 = 20 Marks) 4. Results Analysis (12 Marks) a) Provide the results for each approach applied to the two UGC datasets. Select and apply two relevant metrics (e.g., precision and recall) to assess the performance of the implemented models for the answer selection task, and two relevant metrics (e.g., bleu and rouge) to assess the performance of the implemented models for the answer generation task, with each metric worth 2 Marks. (8 Marks) b) Explain the reasons behind the model performance on each dataset for each approach. (2 Marks/algorithm+dataset x 2 = 4 Marks) Part Two 1. Conduct a survey on one of the NLP domains: Medical, Legal, or Financial. (18 Marks) a) Provide an overview of the chosen domain. Meanwhile, provide three real-life scenarios of the chosen domain. For example, if you select the medical NLP domain, you could outline the problems within this area, such as detecting depression from social data, mining medical records, and generating doctor recommendations from medical forums. Additionally, you could provide a list of commonly used datasets in medical NLP. (6 Marks) b) Identify and list three key challenges within the domain. (6 Marks) c) Select one challenge and propose a novel approach to address it. Provide a detailed description of the approach, which will be assessed based on its novelty and correctness. (6 Marks) Part Three 1. Report Writing (6 Marks) This coursework evaluates your understanding the challenges of the problem and the correctness of the proposed algorithms. It also tests your professional skills in terminology usage, presentation of algorithms and experimental results, as well as the logical manner of the proposal. (6 Marks) Submission You must submit a single zip file. The zip file is named "StudentID_Coursework.zip". It includes: a cover letter with your information and the final PDF report. A folder labeled "algorithms" contains all the model implementations, data preprocessing scripts, and evaluation scripts. A folder labeled "data" contains all the datasets and the experimental results in the CSV format.
Assessment Brief – Academic Year 2024/25 Module Code: ARTD2109 Assessment Type: 100% CREATIVE DESIGN PROJECT: a creative design project/portfolio including a 1000 word written element; supporting appendices with creative outcomes, rationales and frameworks plus 4 self-styled images/photographs and a relevant 30 second promotional film. Module Title: CREATIVE STRATEGY Weighting: 30 CATS/CREDITS ASSESSMENT BRIEF DETAILS: The learning outcomes of this module are defined in the module profile, which can be found on Blackboard and are detailed below. Please constantly refer to these learning outcomes as they are what you are assessed against. For more information on formative feedback for this module, see the section above. Please also familiarise yourself with the following guidelines and regulations- these are an important part of the assessment process: Referencing Guidelines: http://library.soton.ac.uk/sash/referencing Academic Integrity Regulations: http://www.calendar.soton.ac.uk/sectionIV/academic-integrity-regs.html Details of the assessment brief are on the following pages. We will go through all of this in more detail in the taught sessions, so please don’t be concerned if there are elements and terminology you are unfamiliar with. INTRODUCTION: “There is only one thing in the world worse than being talked about, and that’s not being talked about.” Oscar Wilde Fashion doesn’t just mean clothes. With an emphasis on the skincare and beauty sectors and with an initial focus on the SHESEIDO GROUP of brands, however you can look at other similar brands too, if you prefer. This assessment brief concentrates on building brand equity and establishing positive consumer relationships through narrative and story building. This module will task you with creating an inventive and appropriate PR campaign for your chosen brand. Link to the SHISHEIDO GROUP SITE – use this collection as a starting point. After detailed research into your chosen brand and its current situation you will need to conceive and plan a relevant and appropriate PR campaign as a response to a critical and current fashion, lifestyle, social or environmental issue that communicates your brand’s stance on this chosen topic. This campaign is not about products, promotions, sales or profits at all, and is much more focussed on telling a relevant and appropriate ‘story’ that your chosen brand seeks to tell, with the aim being to communicate an emotive and engaging message to a perceived audience and, through this process, hopefully raising awareness of the brand and its values. Your PR campaign will be all about making a statement or taking a stance on something important and relevant. What this is, its rationale, and what it conveys is totally up to you. The module builds upon your creative skills and knowledge that you began to explore in Level 4 and will enable you to develop a greater understanding of the fusion of strategy and creativity within the fashion/lifestyle. industries. In summary: with an emphasis on building brand equity, (we will explore what this actually means in class!) and establishing positive consumer relationships through narrative and story building, you will be tasked with creating a creative, inventive and appropriate PR campaign – make sure you focus on narrative building NOT sales! MODULE OVERVIEW: “Advertising is saying you’re good. PR is getting someone else to say you’re good.” Jean-Louis Gassée, Business Executive, Apple You will need to thoroughly research and investigate your chosen brand to gain a better insight into their company strategy, product range and consumer profile, which will then allow you to get into a strong position to start considering the promotional, PR and communication strategies that you will need to develop to be successful in this module. You will need to consider your chosen brand’s message and its audience, plus any other impacting issues- all of which we will examine in the taught sessions. Do note that the focus of this module is much more about creativity, narrative, and storytelling rather than purely academic writing and research. There are four main areas you will be able to express your ideas in this manner: 1) Innovation and inventiveness demonstrated through your PR campaign concepts and ideation 2) Creative writing through press releases and editorials 3) Engaging and compelling photography and styling demonstrated by your four final chosen campaign images 4) Imaginative and emotive storytelling demonstrated through your 30 second brand film YOUR CREATIVE DESIGN PROJECT- THE DETAILS: Situation Analysis: You will need to research and investigate your chosen brand in order to gain a better insight into its company strategy, product range and its consumer profile. All this will help inform. the rationale behind your PR campaign. PR Campaign: Use the knowledge gained from your situational analysis of current issues to carefully devise a suitable PR campaign appropriate to your chosen brand. Find a rationale as to why you (your brand) needs a PR campaign at this time- what is its purpose? Your campaign must feature a strong narrative-driven focus and make an emotional connection with the target audience. You will need to consider your message, your perceived audience, and other impacting issues such as the changing retail landscape, political, social and environmental issues as well as social behaviour, AI and engagement. We will explore these aspects in more detail within the taught sessions- so don’t worry too much about how you might achieve this at this stage. Overview of your Intentions: Your Creative Design Project/Portfolio should include highly detailed creative concepts and visualizations, as well as plenty of supporting storyboards and mood boards and other relevant creative outcomes as appropriate. The 1000-word written part of the assessment is essentially the rationale and justification of your campaign. Your investigation into your chosen brand and the PR message will be examined here too. Treat this part of the project as an overview of your intentions: what are the aims of your campaign, what is the best way to ensure those aims are met and how will you measure the success of your campaign? Essential elements to include in your submission: Your rationale for your PR campaign, supporting press releases, a media list, pre-launch, launch and post-launch campaign timelines, examples of editorial writing, a supporting film and four self-styled and photographed images to be used as you think appropriate. Mockups and visualisations of your concepts and some indication of how you might measure the campaign success would be invaluable too. You might, depending on your campaign focus, also consider including: Evidence of potential gamification concepts, AI visualisations, social media activities, events, pop-up stores, the appointment of a brand ambassadors, celebrity endorsements, guerilla marketing and so on– it’s up to you, but your campaign must engage your audience fully, be memorable, highly creative and strategically well planned and appropriate to the brand. MORE INFORMATION ON YOUR SUBMISSION REQUIREMENTS: Your Submission Appendices: The word count for this module is quite low, only 1000 words for a 30-credit module. Therefore, you will need to make use of your appendices to expand upon your work and campaign rationales. So, all other written elements, for example the written promotional parts of your campaign such as press releases and editorials, should be placed within your appendices to avoid being included in the word count. These appendices should also include theoretical frameworks and other models that support your creative strategy. Effective use of these appendices will play a critical role in your response to the challenges of this brief. 4x Original self-styled images: Additionally, you will need to include four original and self-styled photographs that are to be used as part of your communication strategy- these images should be brand, campaign, and issue relevant. They will be used across multiple channels and platforms but, they also need to be of the highest quality possible and have been refined and retouched in post-production (e.g. Photoshop or similar). Part of your task within your Creative Design Project is to demonstrate how these four images will be used in context of your PR campaign concept through mockups and visualisations. You must also include you chosen brand’s logo and any other content such as hashtags and taglines as part of your mock-ups too. Brand film HD quality/H264 MP4 format: Finally, Your PR campaign strategy must also include a 30-second, brand-film that reinforces your brand and PR campaign narrative. Do be aware however that you are not advertising or selling products but rather something more evocative and emotionally engaging to your audience- something that reinforces your brand message through storytelling. You will need to storyboard your film concepts, consider the role of art direction, narrative, an appropriate soundtrack, styling and locations as well as actually produce the film. Your film must include at least 50% of your own original footage – the rest may feature found footage or brand/product elements where creating it yourself is unworkable, but you will need to indicate your sources for this footage within your accompanying reference list.
Bayesian Statistics assessment (2024-2025) Instructions • All the instructions should be followed and all questions answered. Please answer as concisely as you can, and do not include anything beyond what is needed to answer the questions. • The submitted material must include - A report of the analysis (in any document format, such as PDF or Word), which includes answers to the specific questions asked. There is no prescribed minimum or maximum length, however the length of the questions will be such that they can be answered in a report of not more than 1500 words. - R and/or JAGS code, in a plain text format, commented where necessary, that runs without error and reproduces all results required to answer the questions. The code may be mixed with the answers, e.g. using a report-generating format such as R Markdown. If using this kind of format, both source and compiled versions should be submitted. A fully-answered question will demonstrate that students can do all of the following: • develop a Bayesian statistical model to answer a scientific question • implement and fit the model using software, including checks of convergence for MCMC algorithms • summarise appropriate outputs from the fitted model • check model fit, criticise and compare alternative assumptions • clearly explain the scientific findings from the analysis. Background A set of people are examined, once every month, for levels of an antibody which gives immunity to an infection. We want to estimate from these data how immunity evolves in the time period following vaccination. The full dataset is given in the file antibody_data.csv, and the variables are: • y: antibody titre level (in log units/ml) • year: years after vaccination • indiv: individual identifier The antibody is measured with error. We are unsure how the level will change over time, except that we assume that between 1 and 13 months after vaccination, the true antibody level is a linear function of time. We want to describe this change with a linear regression. Given our experience with studying similar situations, we would be surprised if the true level exceeded log(20) ≈ 3.0 log units/ml, or was less than log(2) ≈ 0.7 log units/ml, within a rough order of magnitude, at any time. Questions (a) Obtain prior distributions for the intercept and slope parameters of the linear regression model, which reflect these judgements. (There is no unique correct answer, but any reasoning used to obtain the distributions should be clearly explained.) (b) Develop a linear regression in JAGS that can be used to answer the question, and fit it to the subset of the data restricted to the period from 1 month to 13 months (inclusive) after vaccination. Present diagnostics to justify that the sample you produce can be treated as a sample from the posterior distribution, and that it is sufficiently large to give parameter estimates to an appropriate level of precision. (c) Given the results of the model, describe, in precise words, how the antibody level changes over time, including posterior summary statistics for an appropriate quantity or quanti-ties. (d) Plot a suitable summary of the posterior predictive distribution corresponding to each data point, alongside the data, in a way that ensures the points for each individual can easily be compared with each other. Interpret the result and explain how the conclusion drawn in (c) might be affected. (e) Extend the linear model in (b) to include random effects that represent variations be- tween people in the average antibody level, as follows: (i) Write down equations representing the extended model and prior distributions. (The same priors as in (a,b) may be used where appropriate, and vague priors, or reasonable substantive priors, may be chosen for any additional parameters needed.) (ii) Implement it in JAGS and describe how the the average antibody level varies be- tween people. (iii) Using the same technique you used in part (d), show that it fits the data better than the simple linear regression.
ELEC7310, MODULE I: POWER SYSTEM STABILITY AND DYNAMICS (SECURITY) Assignment # 3: Small Signal Stability Submission Date: April 11, 2025 Use any analytical software tools (PSAT, PSS/E, DSA Tool, or PST are preferred) to study the small signal stability of the following test system. Fig. 1. A single-line diagram of two-area test system. The Fig.1 shows a single-line diagram of two-area power system, typically used for power system low frequency (small signal stability) oscillation studies. The system consists of eleven nodes, including four generators with step-up transformers and two loads, and thirteen branches. The basic data of the test system for both static and dynamic analysis can be obtained from the example 12.6 of reference [1]. In PSAT the two-area test system can be obtained by modifying the “d_kundur1” Simulink file given in “tests” folder. The required modifications include removing the ZIP loads and the fault. Carry out Eigen value analysis and comment on the system stability status for the steps (a) to (g). Identify different modes of oscillations and justify your answers by considering frequency of oscillations and participation factors. (a) Model all the generators as classical models to study the small signal performance of the system and report on the obtained results. (b) Model all the generators in detail; all the generators have identical parameters, calculate the eigenvalues of the system at the base case and 20% increased loading level. (c) Introduce different exciters in each of those generators and repeat the eigenvalue calculation. (d) Introduce governor models and repeat the calculation again. (e) Using the participation factor analysis, find out what are the state variables dominant in the critical mode and the corresponding machine (problematic one). (f) Introduce a Power System Stabilizer (PSS) in the problematic machine and calculate the eigenvalues again. (g) Repeat the calculation with PSS in all four machines of the system. (h) Draw the time-domain responses of generator rotor angles and tie-line power flow to justify your obtained results in (f) and (g). Students are requested to present all the relevant results in tables and/or graphs. It is also expected from the students to make appropriate comments on each step of this analysis. Total mark: 8 [1] P. Kundur, Power System Stability and Control: McGraw-Hill, 1994.
CS 330, Spring 2025, Homework 6 Due: March 26th 2025, at 11:59 pm on Gradescope Collaboration policy Collaboration on homework problems is permitted, you are allowed to discuss each problem with at most 3 other students currently enrolled in the class. Before working with others on a problem, you should think about it yourself for at least 45 minutes. Finding answers to problems on the Web or from other outside sources (these include anyone not enrolled in the class) is strictly forbidden. You must write up each problem solution by yourself without assistance, even if you collaborate with others to solve the problem. You must also identify your collaborators. If you did not work with anyone, you should write “Collaborators: none.” It is a violation of this policy to submit a problem solution that you cannot orally explain to an instructor or TA. Typesetting Solutions should be typed and submitted as a PDF file on Gradescope. Solution guidelines For problems that require you to provide an algorithm, you must provide: 1. pseudocode and, if helpful, a precise description of the algorithm in English. As always, pseudocode should include • A clear description of the inputs and outputs • Any assumptions you are making about the input (format, for example) • Instructions that are clear enough that a classmate who hasn’t thought about the prob- lem yet would understand how to turn them into working code. Inputs and outputs of any subroutines should be clear, data structures should be explained, etc. If the algorithm is not clear enough for graders to understand easily, it may not be graded. 2. a proof of correctness, 3. an analysis of running time and space. You may use algorithms from class as subroutines. You may also use facts that we proved in class. You should be as clear and concise as possible in your write-up of solutions. A simple, direct analysis is worth more points than a convoluted one, both because it is simpler and less prone to error and because it is easier to read and understand. Problem 1. Transporting an Oversized Painting A famous art museum, the Isabella Stewart Gardner Museum, in Boston is undergoing ren- ovations, and you have been tasked with safely moving various enormous and delicate paintings from between the galleries. The museum has n rooms connected by corridors, each corridor e ∈ E having a maximum width ce (think of it as the narrowest point in that corridor). The corridors are undirected (they are hallways after all!), and all widths ce are distinct. If you plan a route through several corridors, the clearance of that route is the minimum corridor width along the chosen path (the painting can be no taller or wider than that bottleneck corridor). A maximum-clearance route between two rooms i and j is a route that maximizes this minimum corridor width among all paths from i to j. Intuitively, it tells you how large an artwork can be transported from i to j without getting stuck in a too-narrow corridor. You want an algorithm that computes, for a given starting room s, a spanning tree of corridors that ensures maximum-clearance routes from s to all other rooms. You suspect this task is closely related to constructing a maximum spanning tree (MaxST) with corridor widths as edge weights. Recall: a maximum spanning tree of a graph G is a subset of edges forming a tree (i.e., no cycles) that touches all vertices (spanning) while maximizing the sum of its edge weights, in contrast to a minimum spanning tree that would minimize it. (a) You will start by stating the cut and cycle property for maximum spanning trees (MaxST). (a.1) Recall the cut property of a Minimum Spanning Tree (MinST) states that for any cut of the graph G the minimum weight edge in that cut must be in any possible MinST. Now state the MaxST property. (a.2) Recall the cycle property of a MinST states that for all cycles in the graph G, the maximum weight edge in that cycle can not be in the MST. Now state the MaxST property. (b) Show that in any graph G with unique corridor widths ce, the path given by using edges from the maximum spanning tree of G (with respect to ce) yields the maximum-clearance route between any two rooms. [Hint: Try a proof by contradiction: if there were a strictly better route, combining it with the MaxST edges would form a cycle that contradicts the cycle property from part (a).] (c) Give a polynomial-time algorithm that takes a graph G with distinct corridor widths and outputs the maximum spanning tree. [Hint: You may modify a standard minimum-spanning-tree algorithm from class.] (d) State and justify your algorithm's running time. (e) Prove that your algorithm is correct. [Hint: If your algorithm indeed returns the MaxST, part (b) applies directly. So your proof can be an argument you return the MaxST and a reference to your proof of (b).]
