218.327 - Sustainability and Construction Innovation Assessment One – Research Report 1. Summary Provide a summary of your work, including objectives, key findings, and the report's key conclusions (250-word limit, 10 marks). Hint: write this at the end, when the rest of the report is complete. 2. Introduction Provide an introduction to your report. In the first part of your introduction, explain sustainability principles in building design and construction. Provide background information on how innovation could support sustainable design and construction. In the second part of your introduction, summarise building and environmental legislation and industry initiatives relevant to the New Zealand construction industry (500-word limit, 20 marks). 3. Case studies (part 1) Discuss at least 2 case studies of how innovations have been applied to improve building design and construction sustainability in New Zealand (750-word limit, 30 marks). 4. Case studies (part 2) Discuss at least 2 case studies of how building and environmental legislation and industry initiatives have been applied to improve building design and construction sustainability in New Zealand (750-word limit, 30 marks). 5. Conclusion Discuss the key findings of your report (250-word limit, 10 marks). 6. References Use APA referencing style. to list all the cited sources here.
PR03 Summary: The purpose of this project is to exercise some of the core concepts learned in web development. Students will have 3 options to choose from for this last assignment. They can choose to either (1) build a game (2) build an infographic (3) build a full-stack application. It’s recommended to pick the last option, the full-stack application, because students will learn more about the interactions that occur between the frontend and backend of web development. OPTION I - GAME Requirements: Students can choose to build any game they want to code. Examples can include tic tac toe, connect 4, simon game, tetris, battleship…etc. The game must meet the basic use cases of the game selected. Preview: The game does not have to follow any particular visual style. but here are some examples: OPTION II - INFOGRAPHIC Requirements: Students can also choose to build any infographic they want to code. Examples can include a chart to show the annual GDP, or number of people in space, or number of spaceX flights. The infographic must use a get api (such as $.getJSON() or axios.get()) to collect data from a free data resource such as the link below, and display it on a chart. The chart can either be built using vanilla JavaScript. or a popular infographic library like Chart.js or D3.js. • https://project-awesome.org/jdorfman/awesome-json-datasets#climate Preview: The infographic does not have to follow any particular visual style. but here are some examples: OPTION III – FULL-STACK Requirements: Students can also choose to build a full-stack application. The application could either be a utility similar to what is shown on the links below or any app like a game but must CRUD a database i.e. create, read, update, and delete data. It will have a frontend, backend, and database and hosted on the internet. The app can be completed by following the links below one line at a time, but students must change the styles of the frontend to make it look different. • https://www.youtube.com/watch?v=j55fHUJqtyw&t=66s&ab_channel=TraversyMedia • https://www.youtube.com/watch?v=X-JZ-QPApUs&ab_channel=TraversyMedia • https://www.youtube.com/watch?v=W-b9KGwVECs&t=619s&ab_channel=TraversyMedia Preview: Screenshot of the tutorial from the links above: SUBMISSIONS: Grading: The grading will be loosely ended, but will focus on how well the use cases are met, whether the app is bug-free, and the overall quality of the project compared to other students. It’s important to test your app thoroughly. The application will be tested on chrome only and no other browsers. Deadline: The deadline is found under the ‘end’ attribute displayed on the header of the submission slab for ‘pr03’. The project can be built using any fiddle or hosting service but the app must be successfully deployed on the internet if a fiddle is not used. Example hosting sites include: • heroku • render • github pages • netlify • vercel • firebase • aws • azure • stackblitz • codepen • codesandbox When the app is complete, paste the link on the submission slab of Apollo and hit submit.
ME5311 PROJECT Instructions Each student should use the dataset provided for the project, and conduct a thorough analysis of the dataset choosing some of the tools that you learned during the course. Report You are required to compile a brief report in the template provided in Overleaf without changing the font style and size, and the margins of the document. The report should be • maximum 6-page long (excluding references); • containing a maximum of 2 figures; • containing a maximum of 20 references (note, references are not counted for the page limit). The report is due by 21st April at 23:59. The Overleaf template can be found here: https://www.overleaf.com/read/mxyqfhkdtbhr We ask you to copy the project, and start drafting your own project. For those who have no experience with Latex, the only files you need to modify are: ME5311-template.tex (for the report), and ME5311-references.bib (for the bibliography). Grading We will be ultimately grading all your projects, based on the report; however, we ask you to grade your own project, and submit your grading as part of your assignment. Dataset (~ 2 × 1 GB): Spatio-temporal data Description The Earth’s climate, widely known as a multi-scale, high dimensional, nonlinear and chaotic system, significantly influences ecosystems, societies, and economies globally. By combining historical observations and numerical model outputs, researchers are now able to provide highly detailed understanding of past weather and climate using reanalysis datasets. This dataset, with a spatial resolution of 0.5。× 0.5。and daily temporal resolution, spans from 1979-12-31 to 2022-12-31 and covers a portion of the Indo-Pacific region (70。E-150。E, 10。S-40。N). It includes two key atmospheric variables: sea level pressure and two-meter temperature. The dataset comprises 16,071 daily snapshots, each containing 16,261 (161 × 101) grid points. One visualization example of time snapshot (2022- 12-31) is provided in Fig. 1. Sea Level Pressure and Two-meter Temperature are stored in“slp.nc”and“t2m.nc”, respectively. If your laptop lacks sufficient memory during the project, please refer to the attached code for instructions on how to downsample the data further. Figure 1: Daily mean sea level pressure and two-meter temperature in 2022-12-31. (The unit of T2m is converted from Kelvin to degree Celsius by minusing 273.15) How to load the data An example of how you can load the data in Python is reported below (file is in the same folder as the dataset): 1 import os 2 import xarray as xr 3 4 # dimensions of data 5 n_samples = 16071 6 n_ latitudes = 101 7 n_ longitudes = 161 8 shape = ( n_samples , n_ latitudes , n_ longitudes ) 9 10 # load data 11 ds = xr . open_ data set ( ’ slp . nc ’ ) # change to ’ t2m . nc ’ for temperature data 12 13 # visualize dataset content 14 print ( ds ) 15 16 # get ’ slp ’/ ’ t2m ’ values 17 # ’msl ’ is the variable name for slp data , change to ’ t2m ’ for temperature data 18 da = ds [ ’msl ’] 19 x = da . values 20 print ( x ) 21 print ( x . shape ) 22 23 # get time snapshots 24 da = ds [ ’ time ’] 25 t = da . values 26 print ( t ) 27 28 # get longitude values 29 da = ds [ ’ longitude ’] 30 lon = da . values 31 print ( lon ) 32 33 # get latitude values 34 da = ds [ ’ latitude ’] 35 lat = da . values 36 print ( lat ) 37 38 # # ONLY if not enough memory 39 # low_res_ ds = ds [{ ’ longitude ’: slice ( None , None , 2) , ’ latitude ’: slice ( None , None , 2) }] 40 # low_res_ ds . to_net cdf ( path = ’ s lp _ low_res . nc ’) # change to ’ t2m_ low_res . nc ’ for temperature data Listing 1: Loading the dataset in Python. See file load_data.py Similarly, you can load the data in Matlab as follow (file is in the same folder as the dataset): 1 clc ; clear ; close all 2 3 % dimensions of data 4 n_samples = 16071; 5 n_ latitudes = 101; 6 n_ longitudes = 161; 7 8 % load data 9 ncfile = ’ slp . nc ’ ; % change to ’ t2m ’ for temperature data 10 11 % visualize dataset content 12 nc info ( ncfile ) 13 ncdisp ( ncfile ) 14 15 % get ’ slp ’/ ’ t2m ’ values 16 % ’msl ’ is the variable name for slp data , change to ’ t2m ’ for temperature data 17 x = ncread ( ncfile , ’msl ’ ) ; 18 19 % get time snapshots 20 t = ncread ( ncfile , ’ time ’ ) ; 21 22 % get longitude values 23 lon = ncread ( ncfile , ’ longitude ’ ) ; 24 25 % get latitude values 26 lat = ncread ( ncfile , ’ latitude ’ ) ; Listing 2: Loading the dataset in Matlab. See file load_data.m Modeling suggestions Although the provided dataset is related to climate, no background in climate science is required for its analysis. • What kind of information can you retrieve about this type of data? • For example, can we model it via a reduced order model? • Is the system predictable? • How can you characterize this data from a dynamical systems point of view? • Some methods introduced in the lectures seem only applicable to low dimensional systems. Is it possible to apply them to high dimensional system? The above are just some suggestions. Pick one or more topics from the course, to make a compelling analysis of the data!
SG2047 VISUALIZING SOCIETY TASK 2 - DESIGN A DATA GRAPHIC COURSEWORK 2024|25 Overview Your task is to use visualization software to design effective graphical depictions of a multivariate data set that captures variation in aspects of society across a designated region of London. This will require you to use interactive graphical techniques to explore the data set and knowledge of visualization to design effective static graphics that communicate your findings. You must use and cite established knowledge about visualization design to inform and justify your graphics – including the series of Data Visualization Design Tests or HeurVIStics and other principles, guidelines and examples that we have been considering in the module. Your designs will be submitted as a Dashboard (PNG) – a single static image in which a series of graphics are structured and annotated to deliver a narrative about society told through the data. You must also provide a structured Commentary (Online Text) in which you explain what is revealed about society through your visualization, describe and justify design decisions, and reflect upon the design process and your learning. You must also submit a complete and suitably formatted list of all the References (PDF) used to inform. the work. All three components must be submitted using the Moodle submission areas by Weds 23rd April. See the Task 2 Submission Area for the exact deadline. Submit well in advance of this. Late work will not be marked – a mark of zero will be returned if work is not submitted on time. This individual piece of assessed coursework will account for 70% of your module mark. The Brief You have been given a rich data set containing information about various aspects of society in London, recorded at high spatial resolution in the 2021 UK Census of population. You must use your skills in, and knowledge of, visualization to … 1. explore the data set – finding interesting features of society that are captured by the data in the parts of London on which you have been asked to focus; 2. communicate your findings – through excellent data graphics that use visualization to show these features effectively and an associated commentary that supplements the visuals; 3. explain your process – by documenting design decisions and your learning in light of the theory, principles and guidelines that you have studied for informing visualization design; You should be looking to find differences, detect trends and compare places in the part of London that is your focus, in ways that characterise a range of aspects of society. You will then need to design revealing graphics that communicate these findings effectively, describe and explain them and to reflect on the process. This must be achieved through your use of the software we have been working with during the module – the graphics must be created in and exported from Tableau Desktop – and some structured documentation. You will be creating a dashboard in Tableau and should use your growing knowledge of graphical design and the nature of society in London to inform the work. The Data The data set consists of more than 70 variables recorded in the 2021 UK Census of Population. While collected at household level, the data have been aggregated to Lower Super Output Areas (LSOA) for this analysis and visualization exercise. London has just under 5,000 LSOAs, but you have been allocated an individual focus – a personal Geographic Subset of these based on a small number of adjacent boroughs. You must focus your work solely on the LSOAs contained in your unique Geographic Subset – those in the boroughs you have been allocated. Please focus on the variation across and within the area at LSOA level – by designing effective data dense graphics that show local detail and nuance rather than high-level borough-based comparisons. Ignore the boroughs other than as a means of identifying your Geographic Subset of LSOAs. The data are available as a Tableau Packaged Workbook (TWBX) on Moodle. You will need to download the workbook, filter it to show the LSOAs in the boroughs that are in your Geographic Subset and use this as the basis of your visualization in Tableau. Remember that your exploration and your graphics must only involve and show LSOAs that are in your Geographic Subset - the region that you have been allocated. Focus on the detail, the LSOAs, not the boroughs. The Items You will need to submit three items as described below and in the formats specified : 1. DASHBOARD – a Single Static Image of a Dashboard created in Tableau ( PNG) This must contain your annotated graphics in a single Tableau dashboard – these are your Designs for Visualizing Society in London. This series of annotated static graphics must present information established through your visual exploration in ways that show complexity with clarity. The dashboard must be of landscape orientation and sized at exactly - 1600*900 pixels. Create a PNG of your dashboard with _Dashboard / Export Image … / Portable Network Graphics (*.png)_ Remember that this is a static image – so it cannot rely upon any interaction or dynamic features such as tooltips, filtering, mouseover, highlighting, etc. Imagine that you will be printing it out on paper for use as a poster and design your dashboard with this constraint in mind. 2. COMMENTARY – Description, Encodings, Decisions & Reflection (Online Text) A short script, to be read when viewing the Tableau dashboard. The markers will read this as they view the dashboard. The script. must consist of four sections, each of no more than 250 words : i. your description – in which you explain what you have discovered about society in London. It should make direct reference to the graphics and any labels and annotations that you have added to help with your visual explanation. It should comment on the important features in the graphics that support these findings. Remember that you have been asked to find differences, detect trends and compare places. Your description should address these characteristics directly – so here is where you point them out. Imagine you are reading this commentary out to the markers as they look through the dashboard – this is your chance to describe what you have found, the narrative that you add to the graphics; ii. your encodings – in which you describe the encodings and explain how they are effective. You must explicitly select one of the graphics in your dashboard and draw on the guidance given by authors such as Roth (see the Variation test) and Munzner (remember her rankings?) in your explanations. The graphic you select must be data dense and relational – showing information for all LSOAs and more than one variable while also representing more than one aspect of society. So – choose, design and explain carefully! iii. your decisions – in which you identify three of the Design Tests for Data Visualization – the HeurVIStics - and explain whether they have been achieved in your graphics. You must explain how if the tests are passed, and why not if they are failed. Select one or two of your graphics as examples to show that the tests can be usefully passed to help visualize society, but also that there are circumstances when effective design involves failing them, for good reason. Your considered selections of the tests and the graphics will be key to doing well here. This is a great place to show your knowledge of the complexity of design and that you are aware of this and can still make informed and effective design decisions. iv. your reflection – in which you explain how you have visualized society in London. It should outline your approach to visualization and discuss the most important principles, decisions and challenges involved in the exploration and design and how these have shaped your work and your knowledge: What was straightforward? What was challenging? What have you learned? Where did the theory help? Where was the theory difficult to apply? Here is where you show your knowledge of visualization for exploration & communication. You may decide to focus on specific graphics in the dashboard and must comment on any difficulties, solutions and learning achieved. This is the place to show how your knowledge informed, and was informed by, your experience. Be sure to relate the theory that you have learned to your practical experience of visualizing society in light of your understanding of the data as it developed; Create the text for your commentary in a word processor or text editor. Complete a thorough spelling and grammar check, then copy and paste the text into the ‘online text’ box in the Moodle submission area. Be sure to add spaces after all full stops. Use blank lines to separate paragraphs, with two blank lines separating each of the four sections. Do not use any other formatting such as tables, indentation, bullets, emboldened text or italics – this will not be captured. Markers will use a screen-reader to automatically read the script aloud as they consider the dashboard. The dashboard (that we see) and the commentary (that we hear) should match up, with the commentary provided in the online text referring to annotated graphics and specific features in the dashboard. When writing the text, imagine that you are describing the dashboard to the marker in a presentation “the label on the left shows … ”, “the cluster by the river suggests … ” . 3. PDF – References ( PDF) A one-page document that contains full references to any work cited in the submission. This document must be in PDF format, with a minimum font size of 10pt and must only contain references – no additional text. Anything other than references will be ignored. Please provide full references to all cited sources using Harvard, APA or an appropriate established alternative. The Submission All items must be submitted via Moodle before the deadline specified in the submission area. Check the time and date on Moodle – this is definitive! Late submissions will not be marked. A mark of zero will be returned in such cases other than where the University’s procedures for reporting extenuating circumstances have been followed and the Board of Assessment has accepted any such circumstances. You are strongly advised to check the submission deadline on Moodle immediately and to submit your work well before it. You may submit work well in advance of the deadline and update this subsequently with revised submissions as you improve upon your work through reflection and redesign before the deadline. This is an effective way to develop your submission and is often regarded as good practice. We will only see and mark the final submission. So, submit a ‘banker’ early on, then build on this. Work is only considered ‘submitted’ if a readable digital copy has been completely uploaded through Moodle before the submission area closes, using the appropriate assignment mechanism. Neither paper submissions nor files sent by e-mail are accepted. All submitted work will be analysed using the Turnitin plagiarism detection service. Where academic misconduct is deemed to have occurred a mark of zero will be returned. Where poor academic conduct is deemed to have occurred marks will be reduced accordingly. Submissions will not be marked if they are late or in a format other than that stated here. Individual Work This is an individual piece of work and you are each working on different regions of London as listed in the Geographic Subset on Moodle in the Task 2 assessment area. You are welcome, and even encouraged, to support each other with general help in thinking about graphics, data, the reading that you complete to inform your approach and the Design Tests for Data Visualization. However, you must not share your solutions with other students. So please discuss concepts, ideas and graphics in broad terms rather than in relation to the specific solutions that you are developing for your coursework. You each have separate data sets with separate patterns, and we expect a variety of very different solutions to be submitted. Accusations of academic misconduct (collusion) may arise if individual solutions or submitted work are discussed or shared. Marking The exercise is intended to allow you to show that you have achieved the intended module learning outcomes as described in the Module Overview on the module homepage. You should check these carefully and regularly when planning and working on this exercise. Marks will be awarded according to the rubric provided on Moodle – look for this icon. Be sure to check the criteria and levels of achievement expected for the different grades. This should inform you in developing your solutions and planning your work.
Algorithms and Data Structures I Project 5: The Stock Market Background The stock market allows investors to buy shares of publicly-traded companies. Investors can make a profit by selling shares they own for a higher price than what they paid. Profit is calculated as: profit = (price_sold - price_bought) * num_shares For example, if I buy 2 shares of company A for $5 each, and then a week later sell them for $8 each, I have made $6 in profit: $8 - $5 = $3 and $3 * 2 shares = $6. Unfortunately, stock prices don’t just go up. Sometimes a stock will be bought and then sold at a lower price for a loss. For example, I can buy 3 shares of company X at $10 each, and then sell all three shares later on for $4 each. This would net me ($4 - $10) * 3 = - $18. In this project, share transactions, or Trades, hold the following information: - TradeType: whether the investor bought or sold shares - Lot: a group of shares Each Lot contains the following information: - Ticker: which company the shares are for - quantity: how many shares are in the lot - pricePerShare: the price for each share in the Lot Lots of shares (that’s Lots with a capital L) must be sold in the order they were bought, also known as first in first out (FIFO). This means we should use a Queue to represent a history of Trades. For example, take this history of Trades: When selling shares in Trade 3, the first 20 of the 30 sold shares must come from Trade 1. This means that the shares from Trade 1 are sold at a profit of $2 per share or $40 total. Trade 3 still has 10 shares left to sell. These 10 must now come from the Lot in Trade 2. They are sold at a profit of $6 per share, or $60 total. The total profit from selling 30 shares in Trade 3 is $40 from Trade 1 + $60 from Trade 2 = $100 total profit for Ticker AAA. Exercise Your job is to complete the implementation of the Portfolio class, which extends the PortfolioInterface. The Portfolio class starts with two private fields (you can add more if you’d like): - Hash Map positions - Maps Tickers to a Queue of Lots that were purchased by the Portfolio. Because the Lots are stored in a Queue, the first Lots removed from the Queue are the first that must be sold. - Note: Java’s Queue is an abstract class. You can use the java .util .ArrayDeque when adding new Queues to the positions HashMap. - Hash Map profits - Maps Tickers to their total amount of profit (or loss) so far. Every time a Lot is sold, the profits map should be updated to reflect change in profits or losses from that Lot’s Ticker. The PortfolioInterface lists a few methods that you are responsible for implementing: - void handleTrade(Trade trade) - Process a single Trade. If it is a BUY, then shares are added to the portfolio. If it is a SELL, then shares must be removed from the portfolio in the order they were received and the profits must be calculated and updated. - Note: You can safely assume that calls to handleTrade() that SELL shares will only ever happen when the Portfolio has enough shares of that Ticker to sell. The shares might be split across multiple Lots, but there will always be enough to sell. - void handleTrades(List trades) - Processes a list of Trades from the beginning of the list to the end. Trades in this list might sell shares that were bought in Trades located earlier in the list. - double getProfit(Ticker ticker) - Returns the net profit for all sales involving shares from Ticker - double getTotal Profit() - Returns the net profit for the entire Portfolio, that is, the sum of profits for every Ticker. - int getSharesHeld(Ticker ticker) - Returns the number of shares that the portfolio holds for Ticker. Ex: if a Portfolio sells all of its shares for a given Ticker, calling getSharesHeld afterwards must return 0. Starter Code The Starter Code for Project 5 is located here. Here is a rundown of each starter file: - Ticker.java - Represents a hashable Ticker for a company (ex: Apple’s stock ticker is “AAPL”, Google’s is “GOOG”) - Lot.java - Represents a group (or “ Lot”) of shares. Includes the Ticker of the company, the quantity of shares in the Lot, and the price per share. - Note: There is a setQuantity() method in the event that a Lot has to be split up during a partial sale (see example with company AAA above) - Trade.java - Represents a trade of one Lot of shares. Has a TradeType (either BUY or SELL) and a Lot. - PortfolioInterface.java - The Interface that the Portfolio class must implement. Each method in this file has a descriptive comment explaining what the method should do. - Portfolio.java - An implementation of the PortfolioInterface that you will complete for this project. - Project5.java - A driver program that creates a Portfolio and buys and sells some Lots of shares. - You can either run Project.java directly (java Project5) or with a filename argument (java Project5 trades .csv) and it will bulk-handle a CSV file of Trades - trades.csv - A comma-separated-values (CSV) file containing 200 fictional Trades. You can test your work by running java Project5 trades .csv. Sample Output Running java Project5 should yield: I own 10 shares of AAA Profits : 150 .0 I own 0 shares of BBB Total Profits : 125 .0 Profit to-date : 12466 .91 Company BBB : Shares still holding : 175 Profit to-date : 15712 .980000000003 Company DDD : Shares Company Profit to-date : 17877 .830000000005 Company Profit to-date : -639 .2 Company Profit Shares still holding : 209 Deliverables You are responsible for submitting only Portfolio.java. All other files must remain unchanged.
MECH9325 Fundamentals of Acoustics and Noise Assignment – Acoustic performance of a coating with inclusions Part 2 due Monday 21 April 5pm (Moodle online submission) Aim In the first part of this assignment, you numerically modelled a multilayered homogeneous material comprising multiple layers of the same PDMS material. The aim of this second part is to numerically model voids and/or hard scatterers embedded in the PDMS. Background Inclusions embedded within a soft material such as PDMS result in wave scattering at frequencies around the resonance frequency of the inclusions. Wave scattering facilitates the conversion of sound waves into shear waves which are effectively damped due to high shear damping of the soft material. Inclusions are typically voids or hard scatterers which have their own resonance characteristics. Voids exhibit monopole resonance associated with pulsating motion, while hard scatterers undergo translational motion at dipole resonance. At frequencies around the resonance frequency of the inclusions, the coating acts as an efficient sound absorber. Theoretically, effective medium approximation theory can used to model the inclusions as homogenised layers with effective material and geometric properties. The PDMS material with inclusions then becomes a multilayered design composed of alternating layers of the homogeneous material (PDMS) and the homogenised layer of inclusions (characterised in terms of an effective length, an effective density, and an effective longitudinal modulus). From the effective properties, all the terms for the transfer matrix can be calculated. The sound transmission is then obtained using the transfer matrix method. However, this is beyond the scope of this assignment! For your interest, you can see the inclusions modelled as a homogenised layer and the use of the transfer matrix method in terms of the effective properties in the following references. https://doi.org/10.1016/j.ijmecsci.2024.109587 see Figure 1 and Eq. (6) https://doi.org/10.1016/j.wavemoti.2016.10.006see Figure 2 and Eq. (21) https://doi.org/10.1016/j.apacoust.2020.107501 see Figure 2 and Eqs. (13)-(15) Models Use the single layer model from Part 1 as a base. Increase the cross-section dimension to 0.1m. Use the following material properties for PDMS and steel for the hard scatterer. Material PDMS Steel Density (kg/m3) 1000 7890 Longitudinal modulus (GPa) 2.26(1+0.02i) 283 Shear modulus (GPa) 0.006(1+0.3i) 80.77 Model 1 Model a spherical void of radius 0.015m in the centre of the PDMS slab, with water on the incidence and transmission sides of the PDMS. Obtain the absolute value for the reflection and transmission coefficients, and present your results as 2D plots as a function of frequency. You could compare your results with Figure 2 (left column) in https://doi.org/10.1121/10.0026357. Also obtain the displacement surface plot of the PDMS at the monopole resonance frequency (frequency of minimum transmission coefficient). Model 2 Extend the PDMS slab to model two spherical voids with the centres separated by 0.1m. Obtain the absolute value for the reflection and transmission coefficients, and present your results as 2D plots as a function of frequency. You could compare your results with Figure 3 (left column) in Model a hard steel sphere of radius 0.03m in the centre of the PDMS slab. Obtain the absolute value for the reflection and transmission coefficients, and present your results as 2D plots as a function of frequency. You could compare your results with Figure 2 (right column) in https://doi.org/10.1121/10.0026357. Also obtain the displacement surface plot of the PDMS at the dipole resonance frequency (frequency ofminimum transmission coefficient). Model 4 Extend the PDMS slab to model two hard steel spheres with the centres separated by 0.1m. Obtain the absolute value for the reflection and transmission coefficients, and present your results as 2D plots as a function of frequency. You could compare your results with Figure 3 (right column) in https://doi.org/10.1121/10.0026357 Poster Provide your results in a one-page poster. Your poster should include an introduction, description of the numerical model, results and discussion. The poster should not be too detailed or busy. For example, the lecture slides for this course are visually much easier to read than the lecture notes. The presentation of a poster should aim to be similar to the lecture slides by using large font size, bullet points where possible, no large chunks of text and large clear figures with easy to read axis labels. Your poster can also include references in smaller font size.
Course Code & Description: UMND2393 Legal, Ethical and Professional Issues Coursework Value: 30% (Assignment 1) Intake: October 2023 Trimester: February 2025 A. Learning Outcomes On completion of this course assignment, the student will be able to: 1. Analyse relevant ethical principles involved when resolving ethical dilemma. (Analysis) 2. Discuss the interventions in ethical decision-making process. (Application) 3. Discuss the systematic approach to decision-making in resolving this ethical dilemma. (Application) B. Assignment Question This is an individual assignment. In this assignment, you are required to explore the given hypothetical ethical dilemma in nursing and answer the questions that follow. Assignment: Ethical Dilemma in Nursing Practice - Scenario-Based Assignment Scenario: You are a registered nurse working in a busy hospital ward. One of your patients, Mr. John Smith, a 72-year-old man with a history of chronic heart disease, is admitted after suffering a myocardial infarction (heart attack). His prognosis is poor, and he is in critical condition. His family has been informed about his condition and the possible need for surgery. However, Mr. Smith has refused the surgery, citing his desire not to undergo any more invasive procedures after a previous surgery a few years ago, which led to complications. His wife, Mrs. Smith, is very insistent that he should undergo surgery, believing it will save his life. She argues that his refusal is based on fear and emotional distress rather than rational thought. The medical team has discussed Mr. Smith's refusal and the implications of his decision. The doctor and the nurses are caught in a dilemma: should they respect Mr. Smith's autonomy and refusal of treatment, or should they consider the intervention as a life-saving option in the best interest of the patient, given his critical state? Questions: 1. Analyze the ethical principles involved in the scenario. 2. Discuss potential interventions that you, as nurse involved, will take to resolve this dilemma. 3. Discuss the systematic ethical decision-making approach that will be taken to resolve this dilemma in nursing practice. C. Assessment Criteria 1. Word count: 1800-2200 2. Format: • Cover page: Follow the standard format • Table of contents: list the topics with the page numbers • Use Times New Roman font size 12 • Single double spacing between sentences. Two double spacing between paragraphs • Pagination - middle bottom page as plain number • Margins: - Top: 2.0 cm - Bottom: 2.0 cm - Right: 2.0 cm - Left: 4.0 cm • Attach the marking scheme as the last page. 3. Harvard Referencing: • In-text referencing correctly cited • Reference list prepared in accordance with guideline • Recent 5 years, quality sources used • At least five scholarly references should be used to support your analysis. 4. Penalty for late submission: • Per day penalty: 5% • Maximum penalty: 20%
MARK2052 MARKET Research: Project Description and details To be emailed to your tutor along with the final data file based on any changes you make by Week 10 (Friday 11:59pm). There is no Moodle link for this. Women buy cars too!! And our client believes that the purchase behaviour of this segment is becoming more important by the day and hence want to study it. The problem is most car dealerships and the accompanying service centres know little to nothing about this segment. So, what factors should they focus upon? A car dealership had a small focus group with 30 women of different ages and based on that arrived at a survey that was administered to just female respondents. Note that you don’t have data from the focus group, but only from the resulting survey. They have hired you as a MR consultancy to understand what women want from a car dealership (and probably also the car – to use the right incentives to sell your product)! One of your main aims should be to understand the deficiencies of the current survey and argue about the pros and cons of the current survey. Towards this, make notes when you are analysing the data. What else could you have asked that would have provided the client with more insights – Something that they could use to make that extra sale! The project will investigate the motivations of Female consumers towards car dealerships and what they are looking for in those dealerships. Thankfully, the client has asked the respondents about that the customers look for in a car. You will need to design your analyses to be able to a) ASK THE RIGHT QUESTIONS – i.e., a question that the manager can use to make an extra dollar (Every aim should be translated into an aim that helps in making this extra dollar) and b) answer these questions. All the answers from an aim that you craft should be able to help you tell the manager which ‘P’ (in the 4Ps) to change. If you can’t suggest changing a ‘P’ based on the aim that you posit, please revisit your aim! If you think that you have an important question that you have raised in part a) and cannot answer it with the data that you have, it will be an important question that you might want to include in the deficiencies section. The class will introduce you to the tools available, but it is your responsibility as a group to run as many tests as possible to answer these questions to the maximum extent possible. Please note that the emphasis in the project is primarily on your learning of a range of analysis techniques/ 1) Pointing out and arguing about the merits and demerits of the survey 2) The logic of all the tests that you run to address the aims (each of which should translate to managerial usefulness). Please state the tests run even if you do not find significance in your results. 3) The lack of significant results IS NOT A NEGATIVE. The focus is on your analysis rather than your results, and of course what you can tell the manger. Please keep a record of each meeting your group has as details need to be included in an appendix of the Final reports (refer to format of each of these reports for more information). Data Description After you are provided the data, the next step of any analysis is to gain a solid understanding of the data - who is in the sample and what patterns are in the data? This means you will need to carry out statistical tests that allow you to find out among other things, the composition of your sample, how the sample as a whole answered each question, whether all members in the sample answered the same way. For this last point you will need to choose a range of sub-groups (e.g., age, status, etc.) and explore whether members of these subgroups differ in how they answered all the questions (e.g., do they differ in their views towards comfort). Exploring the general pattern of responses, and any differences between various subgroups, allows you to know how to handle the data for the next stage of the analysis, e.g., if young and old have a very different pattern of response across a range of questions then it may be beneficial to split the data set for the second stage of analysis. Therefore, your priority is to “get to know the data”, NOT to answer specific research objectives. It is highly recommended that your group generates some aims (for a good aim, see what has been discussed in bold previously) for this part of the analysis - that is, write down 4-6 aims you want answered from your descriptive analyses. (Aims may be in the form. of questions if you wish.) One question that often arises is if the aims should be broad or narrow! This will depend on you. Forming broad has an advantage in the fact that they force you to run multiple tests and one of the results might be managerially actionable. Forming narrow ones brings down the number of tests, but you run the probability of not being able to formulate managerially relevant results. These 4-6 aims are fairly broad-based – they are NOT just related to one or two questions in the questionnaire. They help you to understand the patterns within respondents’ responses. For example, in general, what is a woman’s attitude towards protagonists …; do old and young females differ in …... and these need to help the managers in changing one of their 4 Ps These questions (aims) then guide what you do and how you write up the interim report (for yourself and not to be submitted). Please note, that in gaining this initial understanding of the data you will need to look at every part of the questionnaire. [NOTE: From this description you may end up gaining insight into some of your research objectives, however you do not fully address these objectives at this stage.] Feel free to schedule a meeting with your LIC (not the tutor) at any point if you need feedback. To achieve this description of the data you should make use of the techniques that will be covered in lectures and tutorials. Once you have performed a range of analyses, you will need to write a detailed overview of what you found. This does NOT mean you provide a report consisting of copious tables with accompanying explanations. It means that you will need to think about the key interesting things you have found from your analyses, then write a coherent and flowing report so that the reader learns about the data. This implies that your report WILL contain different information than another groups' report because there are always many different ways to go about exploring the data (and your aims will be different to the other group’s!). Your written description of the data will be supported by key summary tables. To use an analogy – you only show the 'tip of the iceberg'. NOTE: Summary tables are required – NOT dumped SPSS output tables. This is done since a key element of any report is clarity of communication – not just in the written overview, but also in any supporting material. Therefore, a summary table contains the key pieces of information from the SPSS output that you use in interpreting and making sense of the results. Format of report Please do not start writing the formal report before week 7 of the semester, or before you have conducted all possible data descriptions. THIS DOES NOT IMPLY THAT YOU DO NOT START ANALYZING YOUR DATA. We will talk in detail about the project report in week 6 and the break-up of the marking criteria. An overall sense of the criteria are however provided below. Marking criteria: · Presentation of the report overall · Clarity, internal referencing (e.g. from summary findings to detail in appendix) and flow of report · Appropriateness of techniques used · How well the “story” is told – its depth and added value (e.g. the usefulness of your information – does it help the reader to understand the data, how well it is communicated.) · Comprehensiveness and clarity of communication of supporting material (in particular, the summary tables) · Satisfactory collection and entry of questionnaires from all members · Cohesion of the group (shared effort), based on the report and the peer feedback · Late projects Submissions for Final Report that are handed in after the due time will be subject to an immediate penalty of 10% (of the course) per day. Computer problems, work commitments, car breakdowns etc will NOT be accepted as excuses for lateness. You do not need to bind any written documents so long as they are held together securely. · Group Feedback Each member of the group is expected to contribute equally to the completion of each stage of the project. All students are expected to fill out an evaluation sheet for all their group-members and this feedback WILL BE GRADED. If discrepancies in members’ contribution arise in this feedback, the lecturer will discuss this with the appropriate students. Based on the feedback and these discussions, the lecturer reserves the right to adjust individual group member’s marks.
Data Mining: Projects List February 19th, 2025 1 Problem 1: Comparison of different positional encoding mecha- nisms for Vision Transformers (ViTs) Compare absolute positional encoding (APE) with various Relative Positional Encoding (RPE) meth- ods on regular classification tasks with Vision Transformers (ViTs). The family of RPE methods you test should include in particular: (1) regular additive RPE discussed in the class with 2L − 1 learnable parameters (where L stands for the sequence length), (2) a variant where the (i,j)-entry of the RPE matrix is given as a polynomial of the L1-distance between corresponding patches in the patch-grid and with learnable coefficients, (3) two RoPE variants (of your choice) taken from [Heo et al., 2024]. The comparison should be conducted on the MNIST and CIFAR datasets and should focus on the accuracy of different models on the evaluation set. It is fine to use a fraction of the CIFAR dataset for training different models, in the presence of limited computational resources. 2 Problem 2: Performer model for the custom attention kernel Consider a customized attention matrix A ∈ RL×L (where L stands for sequence length), given as: Ai,j = (qi(T)kj)4 (1) Design a Performer model providing unbiased estimation of the above attention matrix and more computationally efficient that the regular Transformer applying that kernel. Consider two cases: (1) dQK(4) ≪ L and (2) dQK ≪ L, but dQK(4) ≫ L. In the latter setting, quantify the accuracy of your approximation (coming from the Performer model), by computing the empirical mean squared error of the attention matrix estimation as a function of the number of random projections that you use. 3 Problem 3: Linearization of the feedforward layers in NNs Consider a feedforward layer of the following form, where W ∈ Rd×d , x, y ∈ Rd: y = f(Wx). (2) Assume that f is a GELU function. Propose an algorithm to approximate it via the following ”linearized variant”, where Φ : Rd×d → Rd×m , Ψ : Rd → Rm are some functions (to be constructed by you): y′ = Φ(W)Ψ(x). (3) The approximation does not need to be unbiased. Can you propose the unbiased variant ? 4 Problem 4: Smoothened version of the local attention matrix In this problem, we do not make a distinction between query and key vectors, i.e. we assume that qi = ki for i = 1,..., L, where L stands for sequence length. Assume that query/key vectors for the attention mechanism are taken from R3 . Assume furthermore that the attention matrix used to model that data explicitly zeroes out interactions between tokens that are too far from each other: for some hyperparameter δ > 0. Can you design an unbiased approximation of A of the form. A = Q′ (K′)T , (5) where Q′ , K′ ∈ RL×m and m is another hyperparameter (in particular we might have: m ≪ L) ? References [Heo et al., 2024] Heo, B., Park, S., Han, D., and Yun, S. (2024). Rotary position embedding for vision transformer. In Leonardis, A., Ricci, E., Roth, S., Russakovsky, O., Sattler, T., and Varol, G., editors, Computer Vision - ECCV 2024 - 18th European Conference, Milan, Italy, September 29-October 4, 2024, Proceedings, Part X, volume 15068 of Lecture Notes in Computer Science, pages 289–305. Springer.
School of Mechanical and Manufacturing Engineering MECH9325 Fundamentals of Acoustics and Noise Assignment – Acoustic performance of a multilayered coating Due date: Monday 31 March 5pm (Moodle online submission) Aim The aim of this assignment is to theoretically and numerically investigate the acoustic performance of multilayered coating. Background A silicone material called polydimethylsiloxane (PDMS) is often used as a noise control material in underwater applications due to its acoustic impedance being relatively close to that of water, thus allowing sound waves to transition into the material with minimal reflection. In this assignment, both the transfer matrix method and the finite element method will be used the characterise the acoustic performance of a multilayered coating using PDMS as the host material. Part 1 of this assignment will consider a multilayered homogeneous material comprising multiple layers of the same PDMS material. Transfer Matrix Method The transfer matrix method is a common method to model acoustic elements. Consider an acoustic element of length L. An incident harmonic plane wave propagating in the x-direction impinges on the left hand side of the element. An expression for the harmonic plane wave of unity amplitude is given by pinc = ei(wt-kx) where w is the angular frequency, k is the longitudinal wavenumber (also known as the acoustic wavenumber), t is the time variable, x is the spatial variable, and i = √ 1. The acoustic pressure and particle velocity on the incidence side of the element are denoted by pinc and uinc . Similarly, the acoustic pressure and particle velocity on the transmission side of the element are denoted by ptr and utr. Using the transfer matrix method, the acoustic pressure and particle velocity on the transmission side can be found in terms of the acoustic pressure and particle velocity on the incidence side as follows (1) where M is the transfer matrix given by (2) In Eq. (2), z = Pc is the characteristic impedance of the material where P is the density of the material and c is the speed of sound in the material, and k = w/c is the acoustic wavenumber. For multiple acoustic elements, the transfer matrix of the total design is obtained by multiplying together the transfer matrix of each element in sequential order of the elements as follows M = M1 . M2 … Mn (3) Consider the homogeneous material of length L divided in N identical layers each of length Ln, that is, Ln = L/N. The transfer matrix method of each layer becomes (4) The total transfer matrix is obtained by multiplying together the transfer matrix of each layer in sequential order of the layers, which yields (5) Using the elements of the transfer matrix, the transmission and reflection coefficients are obtained as follows (6) (7) where zinc and ztr are the characteristic impedances ofthe fluid on incidence and transmission sides of the material. In this case, zinc = ztr = Pwcw where Pw , cw are the density and speed of sound in water. From the transmission coefficient, the transmission loss (in dB) is obtained as TL = -10log10 |T| (8) Single layer and Multilayered Designs In Part 1 you are required to model a single layer PDMS material and a multilayered PDMS material as shown in Figs. 1(a) and 1(b), with water on the incidence and transmission sides of the material. Consider an incident harmonic plane wave. Obtain the reflection coefficient, transmission coefficient and transmission loss of the single and multilayered homogeneous materials theoretically (using the transfer matrix method programmed in Matlab) and numerically (using COMSOL). A Matlab script. is appended to this document. (a) (b) Figure 1 (a) Homogeneous material and (b) multilayered homogeneous material with water on the incidence and transmission sides. Numerical Model Using the finite element software COMSOL, develop a 3D numerical model to calculate the reflection and transmission coefficients, and the transmission loss. You can model either a square duct or a circular duct (dimensions are given below for a square duct). Use the following parameters. Dimensions of the square duct cross-section: 0.05m by 0.05m Length of single layer PDMS material: 0.2m Length of duct before/after material: 0.5m Length of Perfectly Matched Layer before/after duct: 0.4m Maximum number of layers: 10 Density of water: 1000 kg/m3 Speed of sound in water: 1500 m/s Density of PDMS: 1000 kg/m3 Speed of sound in PDMS: 1000 m/s Frequency range: 1 Hz up to 5000 Hz in steps of 25 Hz COMSOL Installation Download and install the COMSOL software. To do this, the first step is to register for a COMSOL Access Account at www.comsol.com/access/ Once you have registered, you can then download COMSOL 6.3 from the following link www.comsol.com/product-download/ Use the ISO for offline installation (down the bottom of the product download page). If you attempt to download via the online installer, you may run into connectivity issues. In the final step, use the following passcode 17211400000004001-PAUS-250706-5083305-70EA692E560A You will also be able to access a wide range of helpful and innovative resources. Useful Resources Please use the following resources useful to generate your numerical models: 1. Geometry tutorial:https://www.youtube.com/watch?v=I6te1NFnS44 2. Meshing tutorial:https://www.youtube.com/watch?v=UK8O-LV1uoU 3. Frequency analysis: Tutorial Models for Various Analyses of a Bracket Download bracket_basic.mph and models.sme.bracket_frequency.pdf, following the instructions in the PDF to build the full model. The final model is also provided on this webpage as bracket_frequency.mph. Results Theoretically and numerically calculate the absolute value for the reflection and transmission coefficients, and the transmission loss, for the single layer PDMS and the multilayered PDMS. Present your results as 2D plots as a function of frequency. You can superimpose your results for the single and multiple layers, as well as superimpose your results obtained theoretically and numerically. Discuss the values of the coefficients. Poster Provide your results in a poster. A couple of poster templates have been provided. You can also design your own poster layout. Your poster should include an introduction, description of the numerical model, results and discussion. A poster should not be too detailed or busy. For example, the lecture slides for this course are visually much easier to read than the lecture notes. The presentation of a poster should aim to be similar to the lecture slides by using large font size, bullet points where possible, no large chunks of text and large clear figures with easy to read axis labels. Your poster can also include references in smaller font size. Matlab Script Matlab script. of a single layer clc clear close all %% Material properties rho_water = 1000; %density of water rho_PDMS = 1000; %density of PDMS c_water = 1500; %speed of sound in water c_PDMS = 1000; %speed of sound in PDMS z_water = rho_water*c_water; %characteristic impedance of water z_PDMS = rho_PDMS*c_PDMS; %characteristic impedance of PDMS L = 0.2; %total thickness of PDMS block j=1; for f=10:10:5000 %frequency sweep k = 2*pi*f/c_PDMS; %acoustic wavenumber of PDMS %Transfer matrix M = [cos(k*L), 1i.*z_PDMS.*sin(k*L); 1i.*sin(k*L)./z_PDMS, cos(k*L)]; %1i is the imaginary unit %Elements of the transfer matrix M11 = M(1,1); M12 = M(1,2); M21 = M(2,1); M22 = M(2,2); %Transmission coefficient T(1,j) = 2./(M11 + M12/z_water + z_water*M21 + M22); T(1,j) = sqrt(real(T(1,j)).^2 + imag(T(1,j)).^2); %Reflection coefficient R(1,j) = (M11 + M12/z_water - z_water*M21 - M22)/(M11 + M12/z_water + z_water*M21 + M22); R(1,j) = sqrt(real(R(1,j)).^2 + imag(R(1,j)).^2); %Transmission loss TL(1,j)= -10*log10(T(1,j)); freq(1,j)=f; j=j+1; end % Figures figure(1) plot(freq,TL,'k-') xlabel('Frequency (Hz)') ylabel('Transmission loss (dB)') figure(2) plot(freq,T,'k-') xlabel('Frequency (Hz)') ylabel('Transmission coefficient') figure(3) plot(freq,R,'k-') xlabel('Frequency (Hz)') ylabel('Reflection coefficient') Modification to Matlab script. for multiple layers L = 0.2; %total thickness of PDMS block N=4; %number of layers Ln = L/N; %thickness of each layer %Transfer matrix of one layer Mn = [cos(k*Ln), 1i.*z_PDMS.*sin(k*Ln); 1i.*sin(k*Ln)./z_PDMS, cos(k*Ln)]; %Total transfer matrix for N number of layers M=Mn*Mn*Mn*Mn;
CPT206 Computer Programming for Financial Mathematics: Coursework 1 Task Specification This is the specification task sheet for the Coursework 1 assessment component of your CPT206 module. The task covers all Learning Outcomes, and has a weighting of 15% towards the final grade for this module. For this assessment, you will solve one practice exercise of your choice each week in Weeks 3, 6, 9, and 12, and report on your solution. Your task is described precisely in Section 1. Detailed submission instructions are provided in Section 2. 1 Task description In Weeks 3, 6, 9, and 12, a small number of practice exercises will be uploaded to the Learning Mall (section “CW1 materials”, Quiz “Week X exercises”). In each of these weeks, you should select one of these exercises to solve (four exercises in total), and write a report on your solution (four reports in total). The solution should be submitted to the Learning Mall Quiz, with the code and accompanying report submitted to the dedicated Learning Mall assignment page (see Section 2 for details). The report should consist of the following three sections. 1. Code explanation (15 marks). In this section you should provide a brief explanation of the different parts of your code, and detail how they meet the requirements as laid out in the exercise specification on Learning Mall. 2. Code development and testing (40 marks) . There are no limitations on tools used to help you develop the code solution. In particular, the use of generative AI is permitted for code development. In this section of the report, you should explain how you solved the coding exercise, including any use of generative AI tools or others (for example, by including screenshots of your conversation with XipuAI). You must however ensure that you have a full understanding of your code solution, so as to be able to explain it satisfactorily in Section 2 above. In this section, you should also detail the testing you performed on your code. This should include some test cases not provided in the Learning Mall exercise. Any debugging that was needed to fix your code should also be included in this section. For example, if your code initially failed to pass some of the hidden tests on Learning Mall, explain here how you solved the issue(s). 3. Personal reflection (20 marks). Finally, your report should include a personal reflection on your learning experience through completing the coding exercise. Questions that you may wish to consider could include, but are certainly not limited to, the following. What knowledge did you gain? How did solving the exercise improve your programming skills? If desirable, you may refer to specific objectives of that week’s lecture or the wider aims and learning outcomes of the course itself. Your report should be typed into e.g. a Word document, using single line spacing and a size 12pt font. If including small pieces of code to demonstrate specific aspects , you may wish to distinguish these from your report writing by using a Monospaced font such as Courrier or similar. The total length of the report should not exceed two pages. 2 Submission instructions In the dedicated “Coursework 1 submission” Assignment activity on the Learning Mall in Weeks 3, 6, 9, and 12, you should submit the following two files: • Your report, converted to a PDF file, named as “CPT206 CW1 Week{X} {StudentID}”. • The source code of your solution, in a “.java” file (or “.py” for Week 12). Keep the same file name as you used when developing the solution. The formatting and contents of your code should be identiical to the final version submitted to the Learning Mall. Marks will be awarded not just for correctness of the code, but also for code quality (25 marks in total for code). You will also submit the actual code solution to the Learning Mall weekly practice exercise Quiz. For each week, the submission deadline is Sunday, at 23:59 (China-time), of that week of teaching. So for example, for the Week 3 report, the deadline is Sunday, 9 April, at 23:59 (China-time). No late submissions will be accepted. While the use of various tools, including generative AI, is permitted in the development of the code solution, the report must be individual work. Plagiarism (e.g. copying materials from other sources without proper acknowledgement) is a serious academic offence. Plagiarism and collusion will not be tolerated and will be dealt with in accordance with the University Code of Practice on Academic Integrity. Submitting work created by others, whether paid for or not, is a serious offence, and will be prosecuted vigorously. The use of generative AI for content generation is not permitted in the report, other than the code solution presented in Section 1. Such a use would be considered in breach of the University Code of Practice on Academic Integrity, and dealt with accordingly.
LICA351: Contemporary Hong Kong Cinema Essay Questions Essay due on or before 12.00pm, Monday 28 April 2025. All essays must be 2700-3300 words. Please note the importance of presentation: grammar, spelling, legibility, the need for proper referencing and a bibliography. You will be penalised for carelessness or ineptitude on any of these fronts. Answer one of the following questions: 1. What is the legacy of the Shaw Brothers wuxia tradition on contemporary Hong Kong cinema? 2. David Bordwell suggests that Hong Kong action films foreground “expressive amplification” and “gestural clarity.” At the level of visual style, how have Hong Kong filmmakers approached the challenge of creating vivid and kinetic scenes of spectacle? Consider in relation to two or three films. 3. What are the major stylistic methods favoured by Hong Kong directors in constructing scenes of physical action? Contrast any appropriate Hong Kong films except Police Story and A Better Tomorrow. 4. Examine how any two of the following features operate in two films screened on the module: i) sentimentality; ii) episodic plotting; iii) the ‘scavenger aesthetic’; iv) tonal ruptures; v) Cantopop scoring; vi) character change. 5. Mount a defence of either (i) a culturalist, or (ii) a poetics approach to Hong Kong cinema, exemplifying your argument through close reference to one or two films. 6. “Faced with the date of June 30 1997…what power could a Hong Konger desire more than to control time itself?” (Joelle Collier). Discuss the significance of this theme to one or two of the following films: i) Happy Together; ii) A Better Tomorrow; iii) Rouge; iv) All About Ah Long; v) Police Story; vi) Made in Hong Kong. 7. How has the aesthetic, ideological, and political nature of Hong Kong cinema been affected by any two of the following historical events: i) the 1984 Joint Declaration; ii) the 1997 handover; iii) the Tiananmen Square massacre? 8. Chris Berry suggests that Happy Together “may be homophobic” (p.194). What leads Berry to propose this, and what might be problematic about his argument? Is Happy Together a homophobic film? 9. The films of Fruit Chan are mostly considered “independent” films. Taking any two or three films by this director, discuss the degree to which the label “independent” can be applied to them. 10. How have Hong Kong’s phallocentric film genres negotiated the role of female characters? Examine through two or three films. 11. In what ways has Hong Kong cinema been affected by any two of the following: i) the SARS virus; ii) piracy; iii) the China co-production system; iv) competition from rival cinemas; v) the Asian financial crisis? 12. How have the institutions, economics, and aesthetics of Hong Kong cinema changed since the mid-1980s, and how have these changes affected the nature of the films that are made in Hong Kong? 13. Discuss the ways that any one of the following filmmakers has helped sustain and promote Hong Kong cinema within and beyond the region: i) Wong Kar-wai; ii) Johnnie To; iii) Jackie Chan; iv) John Woo; v) Fruit Chan; vi) Stephen Chow; vii) Ann Hui. In what ways does this filmmaker deepen and promote the “brand” of Hong Kong cinema? 14. Examine the extent to which EITHER Infernal Affairs OR Shaolin Soccer OR Wu Xia negotiates a balance between transnational innovation and local tradition. 15. A Simple Life has been construed as an instance of “authentic Hong Kong-flavoured cinema…in an era when Hong Kong-mainland joint production seems to have become increasingly prevalent” (Han Li). To what extent is Hong Kong “localism” evident in present-day Hong Kong cinema, and how far does A Simple Life embody Hong Kong’s local traditions?
SUMMER TERM 2024 DEPARTMENTALLY MANAGED REMOTE ONLINE EXAMINATION ECON0006: INTRODUCTION TO MATHEMATICS FOR ECONOMICS Assessment Component: 80% Remote Online Controlled Condition Examination Time Allowance: You have 2 hours to complete this examination, plus an additional collation time of 20 minutes and an Upload Window of 20 minutes. The additional collation time has been provided to cover any additional tasks that may be required when collating documents for upload, and the Upload Window is for uploading and correcting any minor mistakes. The additional collation time and Upload Window time allowance should not be used for additional writing time. If you have been granted SoRA extra time and/or rest breaks, your individual examination duration and additional collation time will be extended pro-rata and you will also have the 20- minute Upload Window added to your individual duration. If you miss the submission deadline during the 40-minute Late Submission Period and do not receive approved mitigation for the circumstances relating to your late submission, a Late Submission Penalty will be applied by the Module Administrator. At the end of the Late Submission Period, you will not be able to submit your work via Moodle and you will not be permitted to submit work via email or any other channel. All work must be submitted anonymously in a single PDF file. Do not write your name and student number in either the file or the file name. The file name must be in the following format: Module Code-%Exam i.e. ECON0006-80%Exam. Page Limit: 24 pages. Academic Misconduct: By submitting this assessment, you are confirming that you have not violated UCL’s Assessment Regulations relating to Academic Misconduct contained in Section 9 of Chapter 6 of the Academic Manual. Number of Questions Answered Policy: In cases where a student answers more questions than requested by the examination rubric, the policy of the Economics Department is that the student’s first set of answers up to the required number will be the ones that count (not the best answers). All remaining answers will be ignored. QUESTIONS Answer ALL FIVE questions from Part A and TWO questions from Part B. Questions in Part A carry 10 per cent of the total mark each and questions in Part B carry 25 per cent of the total mark each. PART A 1. Find the values ofa for which the matrix is not invertible. For all other values ofa find an expression for the inverse. 2. Find the range of values ofk for which the quadratic forms are positive definite. 3. Suppose Z = y3 exy. Use the small increments formula to find, in terms of e, an approximation to the change in z when x changes from 1 to 1 + Δx andy changes from 1 to 1 + Δy, where Δx and Δy are small. Now suppose you are additionally given x = 2t, y = t 2 + t. Use the chain rule to find, in terms of e, dZ/dt when t = 1. 4. Find the x andy coordinates of the critical points of the function f (x, y) = 3x2 − y3 +12xy − 36y and classify each critical point as a local maximum, local minimum, saddle point or none of these. 5. Find the general solution of the difference equation 3y t+1 + 2y t = 3. What happens to the general solution as t → ∞? Find also the solution which satisfies y = 1 when t = 0 and sketch its graph. PART B 6. Find the determinant of the matrix Solve the equation system x + 2y + λz = 0 2x + 3y — 2z = λ λx + y + z = 3 for all values of λ . 7. (a) Suppose the production function in an economy takes the form. F(K, L) = KαLβ (α, β > 0) where K andL denote capital and labour respectively. Find a condition in terms of α and β for the production function to exhibit decreasing returns to scale. Show that if this production function exhibits decreasing returns to scale, then it also exhibits diminishing returns to each input. State, with reasons, whether the converse is true. (b) Suppose F(K,L) is a general production function satisfying F(0,0) = 0 . Show that if F(K,L) is concave then it cannot display increasing returns to scale. (c) Now suppose the production function in an economy takes the form. Q = H(K, L)ert where Q, K, L and t denote aggregate output, capital, labour and time respectively. Suppose further that r is a positive constant, H(K, L) is homogeneous of degree s where s is a positive constant and K and L have the same constant proportionate rate of growth m. Find the rate of growth of output. 8. Consider the production function where Q, K and L denote output, capital and labour respectively and where a and b are positive constants. Sketch the isoquant diagram. Suppose that the prices of capital and labour are r and w respectively. Find the cost function. Find also the elasticity of substitution.
BUSN9165 - Big Data Analytics and Visualisation Individual project instruction 1. Assessment structure The individual project accounts for 80% of the module grade. Please choose one data set in the list below for your project. The length of the report should be of 3000 words, excluding references. All the relevant literature and resources for your project should be properly cited in the Harvard referencing style (you will find this website helpful). For your convenience, a template is provided here. Previous exemplars are available here. Marks allocated to criteria: Criteria 20% 1. Introduction to data and research question (~1000 words) Please introduce the data set used and its background. The relevant literature (e.g., academic journal articles and textbooks) should be surveyed and properly cited with Harvard referencing style. More importantly, please identify a problem to be addressed with this data set (i.e., the research question). Please note that the problem should be specific (i.e., relevant in the application domain and linked to the variables available from the data set). 15% 2. Data processing and exploration (~500 words) Please explain: Which variables are available from the data set? Which variables have been selected for the analysis and why? Any data transformations have been done and why? 25% 3. Data visualisation and interpretation (~800 words) Please provide at least three data visualisations as descriptive analytical results (e.g., properties of the variables selected) and advanced analytical results (e.g., relationships between the variables selected, machine learning results). Please follow best practices taught in the module regarding data visualization. Importantly, please interpret the results and findings with details. Note that the data visualisations should be nontrivial representations of information, yet easy to interpret. 20% 4. Data insights and conclusions (~700 words) Please provide the insights drawn from the analytics and summarise the findings. In particular, is the problem (i.e., research question) identified at the beginning addressed by the analytics? How? 20% 5. Writing, styling and references The clarity, logic and presentation of the report, including spelling, grammar and punctuation. The general styling and references should be clear and consistent. 2. Recommended data sets NOTICE: Before starting the individual project, you will need to confirm your choice of data set with this link on Moodle . The link will be available from Wednesday, February 19th 2025, 12:00 pm. Any submissions without data choice confirmation will have the marks reduced accordingly. While the use of generative AI technologies such as ChatGPT could be helpful for learning Python programming, it is important to note that employing it to produce any portion of a written report is strictly prohibited. Please find a list of recommended data sets below, which can be downloaded from https://amazon-reviews-2023.github.io/ or directly loaded to Colab from Hugging Face. All of them have significant textual content (i.e., Amazon reviews). Therefore, text analytics tools should be employed. Please note that each dataset includes reviews (ratings, text, helpfulness votes) as well as product metadata (descriptions, category information, price, brand, and image features), which are linked by product parent_asin number. • All_Beauty • Amazon_Fashion • Appliances • Arts_Crafts_and_Sewing • Automotive • Baby_Products • Beauty_and_Personal_Care • Books • CDs_and_Vinyl • Cell_Phones_and_Accessories • Clothing_Shoes_and_Jewelry • Digital_Music • Electronics • Gift_Cards • Grocery_and_Gourmet_Food • Handmade_Products • Health_and_Household • Health_and_Personal_Care • Home_and_Kitchen • Industrial_and_Scientific • Kindle_Store • Movies_and_TV • Musical_Instruments • Office_Products • Patio_Lawn_and_Garden • Pet_Supplies • Software • Sports_and_Outdoors • Tools_and_Home_Improvement • Toys_and_Games • Video_Games • Others (please email to confirm)
PHYS10362 — 2nd Assignment: Z0 boson March 2025 The Z0 boson is an elementary particle that mediates the weak nuclear interaction. It is studied at particle physics facilities such as Fermilab and CERN where beams of particles collide and their products are analysed. In this assignment, you are tasked with deducing the mass and lifetime of the Z0 boson by studying data from electron-positron collisions resulting in electron-positron products i.e. e-e+ → Z0 → e-e+ events. If possible, you should also compute the uncertainty of these values. Your work should produce some graphics to support your analysis. Theory The Feynman diagram for the process we are interested in is shown below in figure 1. Figure 1: Lowest order Feynman diagram depicting a Z0 boson resonance in e-e+ annihilation. The boson then decays to e+ e- . Time increases on the horizontal axis, anti-fermion lines point backwards. When beams of electrons and positrons collide head-on, the rate, R, at which e-e+ pairs are produced through this interaction is given by: R = σ · L (1) where L is the instantaneous luminosity and is determined by the properties of the beam and im- portantly for this assignment, σ is the cross-section of the interaction and has dimensions of area. Typically σ is expressed in units of a barn(b) where 1b = 10-28 m2 (100 fm2 ). The underlying physics of the interaction is encoded in the cross-section e.g. its magnitude depends on the coupling strength of the weak interaction and the mass and lifetime of the Z0 boson. The likelihood that the Z0 boson produces a given final state is proportional to a quantity called the partial width. For instance the partial width for Z0 → e-e+ , which we will denote by Γee, is 83.91 MeV. Whilst the partial width for Z0 decaying into hadrons is 1744 MeV; a reflection of the fact that a Z0 → hadrons event is significantly more likely than a Z0 → e-e+ event. The cross-section for e-e+ → Z0 → e-e+ is given by (2) where σ is in natural units of GeV-2 . In natural units ℏ = c = 1. Here the mass of the Z0 boson is mZ and its width is ΓZ which is related to the lifetime of the Z0 boson, τZ by: (3) and in natural units ΓZ has units of energy. E is the centre-of-mass energy of the colliding beams. Project description An experiment has taken place to determine the mass and width of the Z0 boson by measuring the cross-section at different centre-of-mass energies. Two detectors were used intermittently over different energy ranges. The data can be found in z boson data 1 .csv and z boson data 2 .csv. Unfortunately, there were some faults that led to invalid data points which you must filter out. You are tasked with obtaining mZ and ΓZ from this data by fitting to equation 2. Do not attempt to turn this into a linear problem and do not try and fit the parameters independently. This will significantly over-complicate the problem and will almost certainly return the wrong result. Previous studies suggest that mZ ~ 90 GeV/c2 and ΓZ ~ 3 GeV. To convert equation 2 from natural units, you should use (4) where mb are mili-barns. Your program should: • Read in, validate and combine both data files. • Perform a minimised χ2 fit by simultaneously varying mZ and ΓZ . • Calculate both mZ and ΓZ to four significant figures in GeV/c2 and GeV respectively. • Calculate the reduced χ2 to 3 decimal places. • Calculate τZ to 3 significant figures in seconds. • Produce a useful plot of your result. • Ideally, you should also find the uncertainties on mZ , ΓZ and τZ to the appropriate precision. With regards to style, in addition to what was asked for in the previous assignment, we expect your code to: • Have a useful file check that halts the code neatly if there is an issue. • Read in data using inbuilt functions; do not ask the user to input the file names. • Use inbuilt functions to perform the minimisation. • Be versatile and applicable to data with similar validation issues. • To make any plots by attaching axes attributes to figure objects. • Save any plots as a .png file. • Achieve a linter score of at least 9.80/10.00 (maximum penalty of 10 marks: a score of 8.33/10.00 corresponds to a deduction of 1.57 marks and -2.40/10.00 corresponds to a deduction of 10.00 marks). Additional marks are available for extra features. You do not need to include them all to get full marks for this aspect. Can you display extra information in these plots? Can you format these plots nicely? Can it be applied to systems with different decay products? Could it be applied to different files with different validation issues? Can you make the initial guess on mZ and ΓZ general? Could it work without knowing the initial value for Γee? An inbuilt function is anything that comes with the Spyder release (5.4.3) on the university PCs e.g. numpy. You can use any packages that come with Spyder but do NOT use ones that you have installed separately on your laptop. The pylint score we will use is that obtained on the university PCs i.e. pylint version 2.16.2 with Spyder 5.4.3 and Python 3.11.7. You should check your linter score on the university PCs and that your code runs there without any issues before submitting it. More detail on how the mark is split can be found in the illustrative rubric on BlackBoard.
218.327 - Sustainability and Construction Innovation Assessment Two – Research Report 1. Summary Provide a summary of your report, including aims, key findings, and the study's key conclusions (250-word limit, 5 marks). Hint: write this at the end, when the rest of the report is complete. 2. Introduction Provide an introduction to your report. In your introduction, provide background information on the Mason Brothers building in Wynyard Quarter. Summarise the innovative sustainable features included in the Mason Brothers building. Explain how those features help achieve sustainability principles in building design and construction (300-word limit, 10 marks). 3. The United Nation’s Sustainable Development Goals (SDGs) Discuss any relationship between the sustainable features included in Mason Brothers building and the United Nations' SDGs (300-word limit, 10 marks). 4. Analysis of Passive Design Features Analyse four passive design features embedded in Mason Brothers building. Compare and contrast those four passive design features against the passive design features embedded in the University of Auckland's upcoming new Recreational and Wellness Centre building regarding their operating principles and environmental impact. Provide supplementary images and references to literature (1000-word limit, 40 marks). 4.1 Passive Building Design Feature One 4.2 Passive Building Design Feature Two 4.3 Passive Building Design Feature Three 4.4 Passive Building Design Feature Four 5. LEED Rating System Discuss how the University of Auckland's upcoming new Recreational and Wellness Centre would meet the following goals of the LEED rating system. I. Reduce contribution to global climate change (250-word limit, 5 marks). II. Enhance individual human health (250-word limit, 5 marks). III. Protect and restore water resources (250-word limit, 5 marks). IV. Protect and enhance biodiversity and ecosystem services (250-word limit, 5 marks). V. Promote sustainable and regenerative material cycles (250-word limit, 5 marks). VI. Enhance community quality of life (250-word limit, 5 marks). 5.1 LEED Goal One: Reduce Contribution to Global Climate Change 250-word limit (5 marks) 5.2 LEED Goal Two: Enhance Individual Human Health 250-word limit (5 marks) 5.3 LEED Goal Three: Protect and Restore Water Resources 250-word limit (5 marks) 5.4 LEED Goal Four: Protect and Enhance Biodiversity and Ecosystem Services 250-word limit (5 marks) 5.5 LEED Goal Five: Promote Sustainable & Regenerative Material Cycles 250-word limit (5 marks) 5.6 LEED Goal Six: Enhance Community Quality of Life 250-word limit (5 marks) 6. Conclusion Write a conclusion to the report indicating the key findings of your study (250-word limit, 5 marks).
ISE 537 Spring 2025, GPP Final Project Due Friday, May 9, 2025 by 11:59 pm. Please select one of the three topics listed below for your final project. The final project should be completed individually. A guideline on the minimum components is listed under each topic. General instruction is provided at the end and it applies to all topics. Please submit your final report before the deadline and late submission is not allowed. 1. Dynamic Trading Strategy Design • The auxiliary materials Lecture Notes 6-9 and Jupyter Notebooks (“Lecture 7-8 Regres- sion for Pair Trading.ipynb” are related to this project. • Design an improved version of the pairs trading strategy (introduced in class) by includ- ing more stocks in your strategy. • You can consider using the top 100 stocks (https://companiesmarketcap.com/) and their daily close price during the period of 2024 - 2025 [Note: you may not have access to all the stocks from Yahoo Finance during this period; please explain how you handle this issue]. • Explain whether dimension reduction techniques are needed. • Explain how you measure the performance. • Please show both the in-sample and out-of-sample performance. • Show evidence that the strategy you develop is profitable. 2. Price Prediction: Comparison between ARIMA Model and LSTM • The auxiliary materials Lecture Notes 10-12 and 16-17 and Jupyter Notebooks (“Lec 10-11 Time Series,” “Lec 12 Time Series.ipynb,” “Lecture 16 Deep Learning.ipynb,” and “Lecture 17 Stock Price Prediction using LSTM.ipynb”) are related to this project. • Choose two stocks as you wish for the prediction. Do predictions separately for each stock. • Pick a period (explain why) and use daily close price from Yahoo Finance for the pre- diction. • Show evidence of convergence for the LSTM model and explain how you pick the lags for the ARIMA model. • Compare the out-of-sample performance between ARIMA Model and LSTM. (Remember to do this in a rolling fashion!) • Explain the pros and cons of both methods. Any difference between the performances of the two stocks you pick? 3. Reinforcement Learning for Optimal Execution • The auxiliary materials Lecture Notes 13, 20-23 and the Jupyter Notebook “Lecture22- Reinforcement Learning for Optimal Execution.ipynb” are related to this project. • Train the Q-learning algorithm with the simulation environment provided in the Jupyter Notebook (“Lecture 22: Reinforcement Learning for Optimal Execution”) on BrightSpace. • Show evidence of convergence. • Use Sharpe Ratio as the criterion and compare the performance of Q-learning to the following two strategies: (a) executing with a constant trading speed, (b) executing everything at time 0. • Design a new simulation environment and repeat the above procedures. Explain your results. General Instruction for Final Projects: • We would like you to on the one hand, approach the problem from a practical perspective, and on the other hand, have a systematic methodology. You are encouraged to go beyond the requirements mentioned and use the quantitative techniques you have to solve the problems. • The final report is expected to contain the following components: — Introduction to the dataset you use, the data format and the steps you perform for data pre-processing. — Brief introduction to the models you use in the project. — Detailed discussion for the model evaluation: proper choice of evaluation criterion (or loss function), out-of-sample test, comparison to benchmark models. — Detailed explanation on how model parameters are selected. — Detailed explanation of your results. — Discussion on financial interpretation or economic insights of your model. — A conclusion paragraph to summarize the methodology and your results. — *Optional* If you explore some other related aspects for the project of your choice, extra credits (up to 20 points to the final grade) will be granted based on the quality of the additional materials. If you decide to do some extra work, please clearly indicate what is additional in your report. • Do not include your codes in the report (nor attach them at the end). Codes should be submitted via a separate submission channel on Brightspace. • Page limit: minimum of 3 pages and maximum of 10 pages. • You can use the Python codes on Brightspace or any open-sourced codes you find online. Please acknowledge the source in your report if you use open-sourced codes.
2024-25 Semester 2 - Coursework 1 Undergraduate – Year 2 MFE108TC - Introduction to Mechatronics Submission Deadline: 24:00 18 May 2025 (Sunday Week 13) on LMO Part A Questions (70 Marks) QUESTIONS 1 (25 MARKS) Figure 1 Schematic of the electrical-magnetic coil layout. A core with three legs is shown in Figure 1. Its depth is 8 cm, and there are 400-turn coil on the center leg. The core is composed of a steel having the magnetization curve shown in Figure 2. Answer the following questions: (a) What current is required to produce a flux density of 0.5T in the central leg of the core? （ 4 marks） (b) What current is required to produce a flux density of 1 T in the central leg of the core? Is it twice the current in part (a)? （5 marks） (c) What are the reluctances of the central and right legs of the core under the conditions in part (a) （8 marks） (d) What are the reluctances of the central and right legs of the core under the conditions in part (b) （8 marks） Figure 2 Magnetization intensity vs Flux density for the selected core. QUESTION 2 (25 MARKS) Figure 3 Circuit diagram for question 3. A linear machine shown in Figure 3 has a magnetic flux density of 1.5 T directed into the page, a resistance of 0.5 Ω , a bar length l=1.5m, and a battery voltage of 200 V. (a) Find the initial force on the bar at starting? What is the initial current flow? (4 marks) (b) Find the no-load steady-state speed of the bar? （5 marks） (c) If the bar is loaded with force of 50 N opposite to the direction of motion, what is the new steady state speed?（8 marks） (d) What is the efficiency of the machine under these circumstances? (8 marks) QUESTION 4 (20 MARKS) A 460V, 60Hz, 25-hp, four-pole, Y-connected wound-rotor induction motor has the following impedances in ohms per phase referred to the stator circuit: R1 = 0.641 Ω , R2 = 0.332 Ω , X1 = 1. 106 Ω; X2 = 0.464 Ω , XM = 26.3 Ω Figure 4 Induction motor diagram for Question 4. Obtain results for the following questions. For each question, detailed solution procedure is required with all the necessary equations and calculations. (a) At what speed and slip does this occur? (5 marks) (b) What is the maximum (pullout) torque of this motor? (5 marks) (c) What is the starting torque of this motor? (5 marks) (d) Calculate the rated current (full load current)? (5 marks) Part B PLC Demonstration (30 Marks) PART B (30 MARKS) According to the Lab Manual, students are required to use PLC-based programming to design control logic for the system as shown below. Figure 5. Electromagnetic-relay based control system for Y-Delta starter. Now, design a PLC-based control system that can achieve the same functionality as the above control system. Detailed requirements are: 1. Sketch the PLC-based Electrical Control Circuit Schematic Diagram (10 Marks) : In your sketch, indicate different parts of the circuit, e.g. where is the power circuit and where is the control circuit (and where is this control circuit drawing power from?) as well as your additional design. 2. Give a table detailing I/O allocation for the PLC (10 Marks). 3. Draw flowcharts and explain the PLC logic control process (10 Marks). Submission Deadline: 24:00 18 May 2025 (Sunday Week 13) on LMO
