A Data Programming Project Now that you have had a chance to explore some techniques and tools in Python, it is time to start working on your own exploratory data analysis project. This is a chance for you to explore a research area of your choosing. You will identify a clear agenda for research and explore this topic at a high level. Expectations: - Identify your own research area and questions, including importing knowledge from external sources. - Acquiring a dataset that is fit for purpose. - Exploring the dataset through different lenses, identifying key features and potential flaws in the data. - Produce a systematic, rigorous and well-reasoned report on how you work through the dataset. - Describe at both a technical and analytical level, how and why you are approaching the problem space in a particular way. - Identify gaps in your approach, the dataset and any techniques, tools, libraries or data structures that you choose to utilise. - Consider the ownership (provenance) of data through a data processing pipeline and how this might manifest. - Consider how data can be prepared, refined and explored for further analysis e.g. for a final year project. - Critically analyse, evaluate and summarise findings from a mini-research project. - Reflect on both processes and outcomes of your project, including any missing steps or stages. - Give a valuable account as to how your analysis provides useful and interesting insights around some dataset. You should present your work in a single Jupyter Notebook (.ipynb file) as part of a larger (ZIP) archive of files. Any data that you use should also be included and readily accessible for checking – included in the ZIP archive. Your ZIP archive should not exceed 30MB in total, including your ipynb file and any data that you choose to utilise. The dataset should not be more than 10MB in total size. The marking rubric includes a description of expectations and deliverables, where sections a-j are each worth a total of 5 marks.
INFOSYS 110 Digital Systems (Exam) 2021 MOJO Coffee: Excellent coffee is never a rational thing; it's a drink imbued with inspiration, freedom , celebration, history, dreams . It's about experience as much as refreshment. It's about personal space, about the pursuit of perfection, about the meeting of minds , about escape and reward. That's the Mojo and it's to treasure. Founded as a boutique roastery café in Wellington by Steve and Julie Gianoutsos in 2003, Mojo Coffee is now one of New Zealand’s most experienced independent coffee roasters and café operators . Starting from humble beginnings on Wakefield Street, Mojo has grown like a family, working with passionate individuals along the way. Mojo Coffee now has 35 locations across Auckland and Wellington. When Covid-19 struck in 2020 Mojo Coffee decided to make their locations cash free. This meant that they no longer accepted cash for payments and customers pay by card or via the Mojo App. Existing Mojo App Functionality: The Mojo App is available on both Android and iOS. All registered users can get 10% off all hot drinks and freshly roasted coffee beans for home, every visit. All that is required is to scan the app at the till. Other handy functions on the app include printing or emailing GST receipts (this is very useful for customers who are claiming their coffees as business expenses), loading credit using your credit card and tracking your transaction history. This case is adapted from information found on https://mojo.coffee/ but is fictitious . 1 Using the information from the exam case, suggest a. One output item mentioned that has been historically non-digital, but has now become “digital-first” . Briefly explain your answer. [2] b. One example of a TPS and one example of a DSS that Mojo could utilise in the process of generating such useful information. [2] c . Two examples of data collected by your TPS and two examples of information generated by your DSS. [4] Construct your answer using the following template. Copy and Paste it into the answer area and fill in your answers accordingly: a. The "Digital-First" item: Explanation: b. One example of TPS: One example of DSS: c. Data example 1: Data example 2: Information example 1: Information example 2: 2 Mojo spreads across 35 locations . Mojo has the option of either having a single information system running with a centralised database or, allowing each store to run and maintain its own information system , each with its own database. Based on what you have learnt from INFOSYS110, which option makes more sense for Mojo? Explain your recommendation. [3] Suggest two advantages and two disadvantages associated with your recommendation [4]. Construct your answer using the following template. Copy and Paste it into the answer area and fill in your answers accordingly: Your recommendation: Explanation for your recommendation: Advantage 1: Advantage 2: Disadvantage 1: Disadvantage 2: Fill in your answer here 3 When a customer enters the store and scans the app, the counter staff get shown: 1. what drink the customer normally orders and; 2. a prompt to suggest an accompanying snack that the customer is likely to enjoy based on their, and other customer’s , past choices . a. What type of analytics is being utilised in 1? Justify your answer. [2] b. What type of analytics is being utilised in 2? Justify your answer? [2] c . What type of unsupervised data mining technique might be used for 2? Justify your answer. [2] Construct your answer using the following template. Copy and Paste it into the answer area and fill in your answers accordingly: a. Type of analytics utilised in 1: Justification: b. Type of analytics utilised in 2: Justification: c. Type of unsupervised data mining technique: Justification: 4 Mojo are given the following visualisations: Visualisation 1: Visualisation 2: a. Identify two insights that Mojo can derive from visualisation 1 and how they might apply them in their business . [4] b. Identify two insights that Mojo can derive from visualisation 2 and how they might apply them in their business . [4] c . Identify two reasons why it might be risky for Mojo to rely on these visualisations when making business decisions . [4] d. Identify an example of the use of pre-attentive processing in visualisation. [2] Construct your answer using the following template. Copy and Paste it into the answer area and fill in your answers accordingly: a. Visualisation 1 Insight 1: Application: Insight 2: Application: b. Visualisation 2 Insight 1: Application: Insight 2: Application: c. Reason 1: Reason 2: d. Example: 5 The Mojo Team is looking to enhance the functionality of their app and have kicked off a project to enable customers to pre-order their coffees on the app. The idea is that customers place their orders on the app and then, when they reach the store, they scan in, and the in-store staff start making their coffees . It is anticipated that reduced wait times will allow for increased customer satisfaction and also for more orders to be processed during busy times . The project manager estimates that this project will take about 3 months to implement and cost Mojo about $50 000 in one off costs , and about $5 000 per annum in ongoing maintenance costs . Mojo is estimating a 10% increase in profit per annum , because of this initiative. a. What makes this a project? State three characteristics about this work that qualifies it as a project rather than BAU (Business as usual). Briefly explain how each of the characteristics apply. [3] b. What is the time constraint in this project? Be specific as definitions will get no marks . [1] c . What is the cost constraint? Be specific as definitions will get no marks . [1] 2 months into the project Julie Gianoutsos points out that if the Mojo app could utilise the GPS functionality of modern phones to detect when the customers are on the way to the store. She suggests modifying the app so that the barista gets a notification to start making the coffee when a customer is within 200 metres of the store. d. If this was to be actioned, then what would be the likely impact on the project in terms of the project management triangle? Justify your answer. [2] e. Explain how this added functionality could benefit Mojo. [2] f. Explain how this added functionality could hurt Mojo. [2] Construct your answer using the following template. Copy and Paste it into the answer area and fill in your answers accordingly: a. Characteristic 1: Explanation: Characteristic 2: Explanation: Characteristic 3: Explanation: b. Time constraint: c. Cost constraint: d. Impact: Justification: e. Explanation (benefit Mojo): f. Explanation (hurt Mojo): 6 Mojo has decided to store all the ordering, payment and customer data utilised by the app on the Amazon Cloud rather than storing them on their own computers . a. Why would they choose to do that? [1] Mojo realise that if they have access to their customers ’ GPS data, they could send alerts with incentives for customers to pop in to their stores whenever a customer was within 100 metres of the store. b. They are wondering if this is ethical. If they used the “ rights approach” ethical framework then how would you advise them? Justify your answer. [2] One of the baristas accessed the database to look up a customer's phone number to ask them out on a date. c . Which information security principle is this violating? Justify your answer. [2] d. Which of the four risk management responses is the most appropriate one to use to resolve this risk? In justifying your answer outline how your response could be actioned.[2] Construct your answer using the following template. Copy and Paste it into the answer area and fill in your answers accordingly: a. Why? b. Advice: Justification: c. Information security principle: Justification: d. Appropriate risk management response: Justification: 7 A part-time staff at Mojo is currently an INFOSYS110 student with a passion in computer programming. During quiet times at work , he contemplates about the code required for Mojo’s digital loyalty programme, where patrons get a free coffee after nine drinks are purchased at Mojo. Being a beginner in coding, he came up with a basic idea where the app may ask a customer the following question: “ How many drink(s ) have you purchased?” Upon answering this question by inputting a numerical value, the app will process this data and inform the customer about whether they are eligible for a free coffee, or how many more drink(s ) they have to purchase before they get a free one. Responses from the app may therefore be one of the two options below: “You are eligible for a free coffee!” Or “You will have to purchase X more drink(s ) to get your free coffee!” (where X is the number of additional drink(s ) required). To facilitate this , the following JavaScript code is proposed (with blanks A to E): var cupsPurchased = (A) ("How many drink(s ) have you purchased?"); (B) (cupsPurchased
Teaching and Learning Mathematics (EDUC22001) Assessment 2 There are two assessed pieces of work for this course. The first is a 2000 word Portfolio, most or all of which can also help you prepare for the final Teaching and Learning Assignment. This should be handed in via Blackboard/Turnitin (Deadline: 7th November, 2024, 2pm). [50%] This is the guide for the second Teaching and Learning mathematics Assessment, the essay (Deadline: 8th January, 2025, 2pm) [50%]. 2) Final Essay The second assignment for this course is a 2000 word essay which critically reflects on your reading of the relevant literature, and connects it to your experience of learning or teaching mathematics. The assignment should attempt to relate to some of the themes and ideas we have discussed on the course, as well as the wider mathematics education literature (Deadline: 8th January 2025, 2pm). Possible experiences to base the assignment on: You could base your assignment on a particular focal experience of learning (e.g. problem solving) or of assisting learning, on this course, or as a tutor, or on a course placement either in or out of school. Examples of such experiences have previously included: experience of trying to learn some new mathematics; tutoring someone within your family or friends who is attempting to learn mathematics that you could offer to help; and teaching assistance in a school. You could pair up with someone else in the class and one could reflect on the teaching experience and one (in a separate assignment!) on the learning experience. You could also teach yourself something, either through extending one of the investigations from the class (or from elsewhere), or by choosing any mathematical topic that you don’t already know well. Possible topics to choose from (or come up with your own): • Mathematics emotions (e.g. anxiety) • Applying maths in the ‘real’ world (e.g. breathing statistics, vaccines, etc. ) • Using games in mathematics (e.g. countdown) • Mathematics in the media (e.g. film) • Instrumental and relational understanding (e.g. teaching and learning fractions) • Freudenthal and mathematics ‘models’ (e.g. the empty number line, or Cuisinere rods, or the array model) • Problem solving in mathematics classroom • Mathematics and Gender (or ethnicity, class, …) • Mathematics pedagogy and social justice • Decolonising the mathematics curriculum (a certain topic like symmetry, Pascal’s triangle, etc. OR a wider critical debate on decolonising mathematics early years and primary curriculum) What should be included in the assignment? Identifying the relevant literature and your review of it (which you might have written about in assignment 1) A brief description of the activity and people involved; A description of the experience of teaching or learning e.g. any planning, what happened, but also, how it related to the themes of the course; Critical reflection on the process. This could include: Why you did what you did, how you felt it went, reflecting on the themes of the course in relation to what you did, what you could have done differently and any other reflections on the experience. Key criterion: Relating any of the above to the themes of the course AND to the mathematics education literature. All arguments have to be substantiated with evidence. Min. 10 references.
ECE3700J Introduction to Computer Organization Lab 6 – Cache Memory Purpose Cache memory is the top level of the memory hierarchy that interacts with the CPU directly. Communications between CPU and the rest of the memory hierarchy are typically through cache. Simplified interfaces between the CPU and cache and between cache and the main memory are shown in the following structural diagram. This lab is intended to help you better understand the organization of memory hierarchy and the relationship between different levels of memory. Tasks Assume the following properties of the memory: - Byte addressable - Size of the main memory: 1024 bytes - Size of the cache: 64 bytes - Size of a block: 4 words - Cache associativity: Direct mapped - Write technique: write back - Cache replacement policy: Least Recently Used (LRU) When CPU needs to access a data/instruction in the memory, it sends a 10-bit address to the cache. If there is a hit in cache, CPU then reads or writes the cache memory according to the read/write signal. If there is a cache miss, cache should request the missing block from the main memory by sending the same 10-bit address to the main memory. You may assume the main memory always has hit, and add reasonable latency to the main memory access. Once main memory operation is finished according to its read/write signal, output signal Done should be asserted. Then CPU should resend the same address to try to request the data again. Model the cache memory and main memory in Verilog HDL. Write a testbench to act like a CPU to provide a sequence of addresses for reading or writing. Pre-load the main memory with randomly generated data by your team. Simulate the functions of the memory hierarchy with a Verilog simulator of your choice. Notes about the design: 1. Clock signal is not needed. 2. You do not need to implement an FSM. 3. Synthesis and RTL schematics are not required. 4. You are free to add some new features, say, using a write buffer, or adding a new signal, if you think it is necessary. 5. For output of main memory, only showing the part whose value has been changed during the simulation process is enough. 6. You are free to create your own design, but it should be reasonable, and you need to give a clear explanation to us during demonstration. 7. FPGA hardware implementation is not required. Team Organization This lab is a team effort. Each team should consist of 3 students, randomly grouped. The work should be appropriately divided and distributed among all team members. Students are not allowed to switch teams without permission of the instructor. Deliverables • Demonstration – Every team should demonstrate to the teaching group the following before your lab session ends: 1) Simulation results of the top-module of your design showing significant signals and changes of your memory 2) Each team member should be prepared for an oral exam on this lab during the demonstration. • Peer Evaluation – Each team member is required to provide a peer evaluation for the team effort in this lab. The marks of the peer evaluation should be integers ranging between 0 to 10, inclusively, with 10 indicating the biggest contribution. A mark should be given to each team member including yourself according the team member’s contribution based on your observation. A brief description of contribution of each team member should also be provided, as shown in the following table. • Source Files – All your Verilog source files and any other supporting files. This is a 2-week lab. The full score for this lab is 300 points. All required documents should be submitted on Canvas before 22:00pm, July 27, 2024. Grading • Demonstration: 80% - Working Verilog model (simulation): 50% - Individual oral exam: 30% • Source files and peer evaluation: 20%
INFOSYS 110 Digital Systems (Exam) 2021 i Exam Case - Fetu'u - A digital platform to get into an IT career. Fetu'u is a digital platform designed to make it easier for people to get into a career in IT. It provides upskilling, allows people to identify career pathways , and connects mentors to students based on their common interests and career objectives . The platform has been in development for a couple of years and is being readied for release later in 2021. One of its founders , Saia Mataele, says his first focus is to target Maori and Pasifika, because of their historically low participation rates in IT. He wants to increase diversity in the technology sector and believes his platform. will be able to help make that happen. How it works Students need to create an online profile and answer several questions about themselves and their goals . These might include what they studied at university, any extracurricular activities they do, what type of skills and jobs they are interested in, and any companies they want to find out more about. Members can edit their online profile at any time, but the real magic happens behind the scenes , where the developers have created systems that can provide tailored content for each individual. These analytics allow Fetu’u’s digital platform to have four main features: 1. Learn Fetu’u will recommend further learning opportunities based on the student’s current experience and future goals . These might include studying at registered academic institutions , as well as nano-degrees and relevant podcasts . 2. Showcase Saia Mataele knows that a huge part of making IT attractive for Maori and Pasifika students is to show them people who have achieved success in the industry and are of Maori and Pasifika heritage. This platform. will allow members to hear directly from these people and learn about their journey and what they’ve done in the industry. 3. Mentoring The advanced business analytics will allow Fetu’u to automatically match members with relevant mentors based on their profile data. 4. Pathways It’s hoped that the analytics embedded in the platform. will allow recruiters to quickly and easily find future talent. Future options - not everyone has access to the internet, so they plan to go even wider. One option is a licensing model for school programs where their teachers can get information and resources to help educate students as schools don’t currently teach the skills that this industry requires . 1 In order to justify the continued funding and utilisation of Fetu’u instead of any other substitute platforms for the same purpose, Fetu’u must be capable of generating useful information for both the organisation and the students . This can be considered as the competitive advantage of the platform . Using the information from the exam case, suggest: a. one item mentioned that has been historically non-digital, but has now become “digital-first” . Briefly explain your answer. (4 marks) b. one example of a TPS and one example of a DSS that Fetu’u utilises in the process of generating such useful information. (4 marks) c . two examples of data collected by your TPS and two examples of information generated by your DSS. (4 marks) d. using your examples above, how Garbage In, Garbage Out (GIGO) may happen at Fetu’u, what the likely outcome will be, and how such problem may be avoided. (4 marks) Construct your answer using the following template. Copy and Paste it into the answer area and fill in your answers accordingly: a. The "Digital-First" item: Explanation: b. One example of TPS: One example of DSS: c. Data example 1: Data example 2: Information example 1: Information example 2: d. How GIGO may happen: Likely outcome: How it may be avoided: 2 The organisational structure of Fetu’u consists of several departments , including Systems Development, Student Liaison, Data Analysis , Accounting & Finance, and Sponsor Liaison. Fetu’u has the option of (a) having a cross-organisation information system running with a centralised database, or (b) to let each department run and maintain its own information system . Based on what you have learnt from INFOSYS110, which option will you recommend to Fetu’u? Explain your recommendation. Suggest two advantages and two disadvantages associated with your recommendation. Construct your answer using the following template. Copy and Paste it into the answer area and fill in your answers accordingly: Your recommendation: Explanation for your recommendation: Advantage 1: Advantage 2: Disadvantage 1: Disadvantage 2: 3 Saia knows that he will need to use business analytics to make sense of the data but is unsure of which techniques are available to him . Explain how the two data mining techniques we have studied in class can help Saia to: (a) reduce the need to spend time focusing on each individual member (5 marks), and (b) help to identify which learning content might be relevant to each member. (5 marks) Keep your answer to each part under 100 words . In your answer, include your choice of technique for each purpose, a brief description of the technique, and a short explanation about why this technique is suitable. Construct your answer using the following template. Copy and Paste it into the answer area and fill in your answers accordingly: a. Suitable technique: Brief description: Explanation: b. Suitable technique: Brief description: Explanation: 4 Saia has , by using Data Analytics techniques , successfully categorised the Year 1 and Year 2 students into three categories , based on the levels of help that they are likely to require. In the report for the management team at Fetu’u, Saia intends to use the following visualisation to illustrate the differences in the distribution of students for Years 1 & 2. Category 1 being students who are keen, and are in need of intensive support. Category 2 consists of students who are managing well, while Category 3 is for students who are doubtful about a career in IT. Identify three aspects about this visualisation that needs to be addressed and improved. For each aspect, explain why it is a problem , and suggest how it may be addressed and improved. Construct your answer using the following template. Copy and Paste it into the answer area and fill in your answers accordingly: Aspect 1: Explanation: How to improve: Aspect 2: Explanation: How to improve: Aspect 3: Explanation: How to improve: 5 Before Saia and his team of three staff can release Fetu’u’s digital platform , some final work is required. If they are going to achieve their goal of a July 2021 release, the following things will need to be done: · Record and edit videos of successful Maori & Pacifica members of the IT industry for the “showcase” section of the platform , · Collate and embed learning opportunities relevant to the Supply Chain Management pathway, . Finalise agreements with recruitments companies so that they can place their logos on the platform . a. Getting the Fetu’u platform ready for release is a project. State four characteristics about this job that qualifies it as a project. Briefly explain how each of the characteristics apply. (8 marks) b. What is the time constraint? (3 marks) c . What is the cost constraint? (3 marks) d. It soon becomes clear that the team of 4 will not be able to complete all of the above activities before July 2021. Suggest one way that Saia can proceed and suggest the likely impact on the "quality ” of the project. (8 marks) Construct your answer using the following template. Copy and Paste it into the answer area and fill in your answers accordingly: a. Characteristic 1: Explanation: Characteristic 2: Explanation: Characteristic 3: Explanation: Characteristic 4: Explanation: b. Time constraint: c. Cost constraint: d. Your suggestion: The likely impact on quality: 6 Although Fetu’u will provide a positive impact for both its members and the industry as a whole, Saia knows he needs to find a way to fund the platform financially. The data warehouse will store a vast amount of member data which might be useful for employers , universities , and even Government institutions . A large online recruitment firm has approached Fetu’u and offered to fund the data storage costs if they (and all their employees) are allowed full access to all student data. Provide one security and two ethical considerations Saia should consider in storing and selling access to the data to this online recruitment firm . For each consideration, recommend one way that the risk can be mitigated or minimised. Explain and justify your recommendations . Construct your answer using the following template. Copy and Paste it into the answer area and fill in your answers accordingly: Security Consideration: Recommendation for risk management: Explanation and Justification: Ethical Consideration 1: Recommendation for risk management: Explanation and Justification: Ethical Consideration 2: Recommendation for risk management: Explanation and Justification:
ECE5550: Applied Kalman Filtering NONLINEAR KALMAN FILTERS 6.1: Extended Kalman filters ■ We return to the basic problem of estimating the present hidden state (vector) value of a dynamic system, using noisy measurements that are somehow related to that state (vector). ■ We now examine the nonlinear case, with system dynamics xk = fk−1(xk−1, uk−1,wk−1) z k = hk (xk, uk,vk ), where uk is a known (deterministic/measured) input signal,wk is a process-noise random input, and vk is a sensor-noise random input. ■ There are three basic nonlinear generalizations to KF • Extended Kalman filter (EKF): Analytic linearization of the model at each point in time. Problematic, but still popular. • Sigma-point (Unscented) Kalman filter (SPKF/UKF): Statistical/ empirical linearization of the model at each point in time. Much better than EKF, at same computational complexity. • Particle filters : The most precise, but often thousands of times more computations required than either EKF/SPKF. Directly approximates the integrals required to compute f (xk | Zk ) using Monte-Carlo integration techniques. ■ In this chapter, we present the EKF and SPKF. The Extended Kalman Filter (EKF) ■ The EKF makes two simplifying assumptions when adapting the general sequential inference equations to a nonlinear system: • In computing state estimates, EKF assumes E[fn(x)] ≈ fn(E[x]); • In computing covariance estimates, EKF uses Taylor series to linearize the system equations around the present operating point. ■ Here, we will show how to apply these approximations and assumptions to derive the EKF equations from the general six steps. EKF step 1a: State estimate time update. ■ The state prediction step is approximated as ˆ(x) = E[fk−1(xk−1 , uk−1,wk−1) | Zk−1] ≈ fk−1(ˆ(x)1 , uk−1 , ¯(w)k−1), where ¯(w)k−1 = E[wk−1]. (Often,¯(w)k−1 = 0.) ■ That is, we approximate the expected value of the state by assuming it is reasonable to propagateˆ(x)1 and¯(w)k−1 through the state eqn. EKF step 1b: Error covariance time update. ■ The covariance prediction step is accomplished by first making an approximation for˜(x) . x˜k − = xk − ˆxk − = fk−1(xk−1, uk−1, wk−1) − fk−1(xˆk + −1, uk−1, w¯ k−1). ■ The first term is expanded as a Taylor series around the prior operating “point” which is the set of values {ˆ(x)1 , uk−1 , ¯(w)k−1} Defined as k — 1 Defined as k — 1 ■ k— ≈ ( k—1k( )—1 ). ■ Substituting this to find the predicted covariance: ≈ k—1Σ,k — 1 k(T)— 1 k—1k(T)— 1 . ■ Note, by the chain rule of total differentials, 0 0 ■ Similarly, ■ The distinction between the total differential and the partial differential is not critical at this point, but will be when we look at parameter estimation using extended Kalman filters. EKF step 1c: Output estimate (where k = E[vk ]). ■ The system output is estimated to be k = E[hk (xk, uk,vk ) | Zk — 1] ≈ hk (^(x)k— , uk, v-k ). ■ That is, it is assumed that propagating xˆk − and the mean sensor noise is the best approximation to estimating the output. EKF step 2a: Estimator gain matrix. ■ The output prediction error may then be approximated using again a Taylor-series expansion on the first term. z k ≈ hk (^(x)k— , uk, v-k ) ■ Note, much like we saw in Step 1b, ■ From this, we can compute such necessary quantities as z˜,k ≈ˆCk − ˜x,kˆCk T +ˆDk v˜ˆDk T , − ˜x˜z,k ≈ E[(x˜k −(ˆCk x˜k −ˆDkv˜k) T ] = x − ˜,kˆCk T . ■ These terms may be combined to get the Kalman gain Lk = − ˜ x, kCk T Cˆk x − ˜,kCˆTk+ Dˆk v˜ DˆTk−1. EKF step 2b: State estimate measurement update. ■ The fifth step is to compute the a posteriori state estimate by updating the a priori estimate ^(x)k( ) = ^(x)k— Lk (z k — k ). EKF step 2c: Error covariance measurement update. ■ Finally, the updated covariance is computed as + ˜ x, k = − ˜ x, k − Lk z˜ , kLk T = (I − Lk ˆ Ck)x − ˜ , k.
BUSINESS 115 SEMESTER TWO, 2024 Q1 [10 MARKS] Economics is best defined as the study of a. How people make choices under conditions of scarcity and the results of their choices. b. Prices and quantities. c. Wages and incomes. d. Graph drawing. e. Inflation and interest rates. Q2 [10 MARKS] Joe wants to start his own business. The business he wants to start requires that he purchase a factory that costs $400,000. Joe currently has $500,000 in the bank earning 3% interest per year. He chooses to use $200,000 of his own money and $200,000 borrowed from a bank to purchase the factory. The interest payment on the bank loan is 6% per year. 1. Joe’s annual implicit cost of purchasing the factory is . a. $6,000 b. $400,000 c. $12,000 d. $18,000 e. $200,000 2. Joe’s annual opportunity cost of purchasing the factory is . a. $12,000 b. $18,000 c. $200,000 d. $400,000 e. $6,000 Q3[10 MARKS] When a production possibilities frontier shifts outward, it is demonstrating the concept of a. Trade-offs. b. Economic growth. c. Efficiency. d. Opportunity cost e. Increasing input prices. Q4 [10 MARKS] Consumption of some goods generates benefit for the consumer, as shown by the demand curve in the diagram below, and external benefits for the rest of society. An example is education. 1. What is the equilibrium price in this market?a. Between, but not including, $8 and $10 b. $10 c. Greater than $10 d. There are two equilibria in this market, one with a price of $8 and one with a price of $10 e. $8 2. What is the socially-optimal quantity of the good consumed in this market?a. Greater than 10 units b. Between, but not including, 8 and 10 units c. There are two socially optimal quantities in this market, 8 units and 10 units d. 8 units e. 10 units 3. If the government wanted to subsidize this market to achieve the socially-optimal quantity of the good consumed, how large would the subsidy need to be?a. Greater than $4 per unit b. More than $2 but less than $4 per unit c. $4 per unit d. $2 per unite. Less than $2 per unit Q5 [10 MARKS] 1. The equilibrium market price and quantity traded are, respectively a. $4; 3 units traded. b. $6; 5 units traded. c. $0; 5 units traded. d. $10; 0 units traded. e. $1; 0 units traded. 2. If a $6 tax per unit were imposed by the government, what price would buyers pay for the good (per unit) in equilibrium?a. $4 b. $2 c. $6 d. $10 e. $8 3. How much revenue would be raised by a $6 tax (per unit) for the government?a. $120 b. $60 c. $6 d. $800 e. $10 4. Using the demand curve provided, what is the price elasticity of demand for a price increase from $2 to $6?a. 1 b. 4 c. 1/2 d. 1/4 e. 2 Q6 [10 MARKS] In a closed economy, national saving is a. Usually greater than investment. b. Sometimes greater and sometimes less than investment, depending on the GDP. c. Always less than investment. d. Equal to investment. e. Usually less than investment because of the leakage of taxes Q7 [10 MARKS] The misperceptions theory of the short-run aggregate supply curve says that, if the price level increases more than people expect, firms believe that the relative price of what they produce has: a. Decreased, so they increase production. b. Decreased, so they stop production. c. Increased, so they increase production. d. Increased, so they stop production. e. Increased, so they decrease production. Q8 [10 MARKS] Welfare payments are often indexed for inflation using the CPI. Some people claim that welfare recipients are harmed by years of low inflation because they do not receive as large an increase in their payments as they do in years of high inflation. Which of the following statements is correct? a. Such claims are correct if the prices of the goods consumed by welfare recipients increase faster than the prices of the goods in the basket used to compute the CPI. b. Such claims are correct under all circumstances. c. Such claims are correct if the basket of goods consumed by welfare recipients is the same as the basket used to compute the CPI. d. Such claims are correct if the prices of the goods consumed by welfare recipients increase more slowly than the prices of the goods in the basket used to compute the CPI. e. Such claims are incorrect under all circumstances. Q9 [10 MARKS] If the RBNZ wanted to increase the money supply, it could make a. Open market purchases and lower the official cash rate. b. Open market purchases and raise the official cash rate. c. Open market sales and lower the official cash rate. d. Open market sales and raise the official cash rate. e. None of the above
CSE 101 Midterm 1 Review Problems 1. Using only the List ADT operations defined in the project description for pa1, write a client function with the heading bool isPalindrome(List L) Your function will return true if the integer sequence represented by L isa palindrome (i.e. is identical to its own reversal), and will return false ifL is not a palindrome. 2. Using only the List ADT operations defined in the project description for pa1, write a client function with the heading void Replace(List L, int x, int y) Your function will replace all occurrences of x in L with y. If x is not in L, your function will make no changes to the integer sequence in L. 3. Run the BFS algorithm on the digraph pictured below, with vertex 4 as the source. Fill in the table giving the adjacency list representation, colors, distances from the source, and parents in the BFS tree. List the discovered vertices in the order that they enter the queue. Draw the resulting BFS tree. 4. Given a connected (undirected) graph G , the diameter of G is the maximum possible distance between any two vertices x andyin G , i.e. diameter(G) = max{ δ(x, y) | x, y ∈ V(G) } Using only the Graph ADT functions defined in the project description for pa2, write a client function with the heading int diameter(Graph G) Your function will compute and return the diameter of its input graph G. 5. Run the DFS algorithm on the digraph pictured below. Process vertices in the main loop of DFS() by increasing vertex label. Process vertices in the for loop of Visit() by increasing vertex label. As vertices finish, push them onto a stack. Fill in the table below giving the adjacency list representation, discover times, finish times and parents in the DFS forest. Draw the resulting DFS forest, and show the state of the stack when DFS is complete. Classify all edges as of type tree, back forward or cross. Determine whether the graph is acyclic. If it is acyclic, determine a topological sort of the vertices, and determine the number of distinct topological sorts. If it is not acyclic, list all directed cycles.
Assignment 1 Translation Project on a Technical Documentation and Translation Commentary BACHELOR DEGREE – Semester 1, AY24/25 TRI305 Translation Workshop I SUBMISSION DEADLINE: Friday 25 October 2024, by 5.00 pm. 1. General Information • This assignment is designed to assess all of the learning outcomes of the module as specified in the module handbook. • You will conduct a translation project on a given English technical documentation (pages 5-13) into Chinese or your mother tongue and write a translation commentary on this project. You are requested to translate and adapt the FDA regulatory medicine package insert with NMPA regulatory one or your motherland authorised one. The NMPA-authorised form. with specifications has been enclosed in this paper (pages 14-19), and attached as an independent editable file as well. • Base on this project, you are required to write a reflective translation commentary to review your translation and adaptation progress. Your translation commentary should meet a minimum word count of 200. • Two NMPA-authorised medicine package inserts has been given as the examples for your reference. Notice that some sections of the provided form might be remained empty for the lack of information from source text. • This assignment will require you to demonstrate your proficiency in applying theoretical concepts and practical skills learned throughout the module. You will conduct comprehensive analysis of the translation project with translation techniques. Additionally, you will critically assess the machine translation quality or the effectiveness of the prompts when you used generative AI or your translation strategies used to conduct computer-aided translation tool. - Bibliography (optional): If applicable, include a comprehensive list of references used in your analysis, ensuring consistent adherence to a specific citation style. throughout the coursework. 2. Submission • The filename of the soft copy should adhere to the following format: Full Name [ID Number] For example, Xiaojun Zhang [12345678]. First name + Surname, first name shall be your registered name on LMO. • You will submit your translation and your translation commentary in a single document in either MS Word or PDF format on the module page on LMO. • Submissions without following exactly the instructions given herein may not reach the instructor, and marks will bededucted. • For late submission, penalties will be given in accordance with the University Policy. Please refer to the rules as detailed in the University’s “Code of Practice for Assessment” . • For mitigating circumstances, students who believe that their performance on the assessed coursework may have been impaired by illness or other exceptional circumstances should follow the procedures set out in the University’s “Mitigating Circumstances Policy” . Such students are also advised to contact their Development Advisor for further guidance and support. • The final submission deadline for this assignment is Friday 25 October 2024. 3. Evaluation Criteria • Your coursework will be evaluated based on two sets of markin descriptors: • Marking Descriptors for Technical Translation of Department of Literary and Translation Studies • Marking Descriptors for Critical Analysis of Department of Literary and Translation Studies Package leaflet: Information for the user Package leaflet: Information for the user Ibuprofen 200 mg Film-coated tablets Ibuprofen 400 mg Film-coated tablets Ibuprofen (as lysine) Read all of this leaflet carefully before you start taking this medicine because it contains important information for you. Always take this medicine exactly as described in this leaflet or as your doctor or pharmacist has told you. - Keep this leaflet. You may need to read it again. - Ask your pharmacist if you need more information or advice. - If you get any side effects, talk to your doctor or pharmacist. This includes any possible side effects not listed in this leaflet. See section 4. - You must talk to a doctor if you do not feel better or if you feel worse after 3 days in case of migraine or fever, or after 4 days for the treatment of pain. What is in this leaflet: 1. What Ibuprofen is and what it is used for 2. What you need to know before you take Ibuprofen 3. How to take Ibuprofen 4. Possible side effects. 5. How to store Ibuprofen 6. Contents of the pack and other information. 1. What Ibuprofen is and what it is used for Ibuprofen contains the active substance ibuprofen. It belongs to a group of medicines known as non-steroidal anti-inflammatory drugs (NSAIDs). NSAIDs provide relief by changing the body’s response to pain and high temperature. [200mg only] Ibuprofen tablets are used for the symptomatic treatment of mild to moderate pain, such as headache, dental pain, period pain and fever and pain as the result of a cold. [400 mg only] Ibuprofen tablets are used for the symptomatic treatment of mild to moderate pain, such as headache, acute migraine headache with or without aura, dental pain, period pain and fever and pain as the result of a cold. 2. What do you need to know before you take Ibuprofen Do not take Ibuprofen: ● if you are allergic to ibuprofen or any other ingredients of this medicine (listed in section 6) ● if you have had an allergic reaction such as asthma, difficulty in breathing, swelling of the face, tongue or throat nettle rash, itchy runny nose to acetylsalicylic acid (ASA) or other NSAIDs ● if you have (or have had two or more episodes of) a stomach ulcer or bleeding ● if you have had gastrointestinal perforation or bleeding when taking NSAIDs ● if you are suffering from cerebrovascular or other active bleeding ● if you are suffering from unclarified blood-formation disturbances ● if you have severe dehydration (caused by vomiting, diarrhoea or insufficient fluid intake) ● if you have severe liver, kidney or heart failure ● if you are in the last 3 months of pregnancy. [200 mg only] Ibuprofen contraindicated in children under 6 years (less than 20 kg body weight). [400 mg only] Ibuprofen is contraindicated in adolescents under 40 kg body weight or children under 12 years. Warnings and precautions: Talk to your doctor or pharmacist before taking Ibuprofen: ● if you have recently had major surgery ● if you have or have had asthma or allergic disease as shortness of breath may occur ● if you suffer from hayfever, nasal polyps or chronic obstructive respiratory disorders as an increased risk of allergic reactions exists. The allergic reactions may present as asthma attacks (so-called analgesic asthma), Quincke’s oedema or urticaria ● if you have heart problems ● if you have a history of gastrointestinal disease (such as ulcerative colitis, Crohn’s disease) ● if you have systemic lupus erythematosus or mixed connective tissue disease (a disease affecting the skin, joints and kidneys) ● if you have certain hereditary blood formation disorders (e.g. acute intermittent porphyria) ● if you have a blood clotting disorder ● if you are taking other NSAIDs. The use with concomitant NSAIDs, including cyclo-oxygenase-2 specific inhibitors, increases the risk of adverse reactions (see section “Other medicines and Ibuprofen” below) and should be avoided ● if you have chickenpox (varicella) it is advisable to avoid use of Ibuprofen ● if you are elderly. Patients with kidney or liver problems should first consult a doctor before taking ibuprofen tablets. Anti-inflammatory/pain-killer medicines like ibuprofen maybe associated with a small increased risk of heart attack (“myocardial infarction”) or stroke, particularly when used at high doses. Do not exceed the recommended dose or duration of treatment (see section 3). You should discuss your treatment with your doctor or pharmacist before taking ibuprofen if you: ● have heart problems including heart failure, angina (chest pain), or if you have had a heart attack, bypass surgery, peripheral artery disease (poor circulation in the legs or feet due to narrow or blocked arteries), or any kind of stroke (including ‘mini-stroke’ or transient ischaemic attack, ‘TIA’) ● have high blood pressure, diabetes, high cholesterol, have a family history of heart disease or stroke, or if you are a smoker. Very rare reports of potentially life-threatening skin rashes (Stevens-Johnson syndrome, toxic epidermal necrolysis) have been reported with the use of ibuprofen. Patients are at higher risk of such reactions during the first month of therapy. Stop taking Ibuprofen and talk to your doctor or pharmacist if you notice a skin rash, mucosal lesions, or any other signs of allergic reactions (see section 4). Undesirable effects maybe minimised by using the minimum effective dose for the shortest period of time. The elderly are at increased risk of side effects. In general the habitual use of (several sorts of) analgesics can lead to lasting severe kidney problems. This risk maybe increased under physical strain associated with loss of salt and dehydration. Therefore it should be avoided. There is a risk of renal impairment in dehydrated children and adolescents. Prolonged use of any type of painkiller for headaches can make them worse. If this situation is experienced or suspected, medical advice should be obtained and treatment should be discontinued. The diagnosis of medication overuse headache (MOH) should be suspected inpatients who have frequent or daily headaches despite (or because of) the regular use of headache medications. NSAIDs may mask symptoms of infection and fever. In prolonged administration of Ibuprofen regular checking of your liver values, the kidney function, as well as the blood count, is required. Your doctor may ask you to have blood tests during treatment. Other medicines and Ibuprofen What should you avoid when you are taking this medicine? Ibuprofen may affect or be affected by some other medicines. For example: ● medicines that are anti-coagulants (i.e. thin blood/prevent clotting e.g. aspirin/acetylsalicylic acid, warfarin, ticlopidine) ● medicines that reduce high blood pressure (ACE-inhibitors such as captopril, beta-blockers such as atenolol, angiotensin-II receptor antagonists such as losartan) Some other medicines may also affect or be affected by treatment with ibuprofen. You should therefore always seek the advice of your doctor or pharmacist before you use ibuprofen with other medicines. Tell your doctor or pharmacist if you are taking, have recently taken or might take any other medicines. In particular, tell them if you are taking: ● Acetylsalicylic acid, or other NSAIDs - Since this may increase the risk of gastrointestinal ulcers or (anti-inflammatories and analgesics) bleeding ● Digoxin (for heart insufficiency) - Since the effect of digoxin maybe enhanced ● Glucocorticoids - Since this may increase the risk of gastrointestinal ulcers or (medicinal products containing bleeding cortisone or cortisone-like substances) ● Anti-platelet agents - Since this may increase the risk of bleeding ● Acetylsalicylic acid (low dose) - Since the blood-thinning effect maybe impaired ● Medicines for thinning the blood - Since ibuprofen may enhance the effects of these medicines (such as warfarin) ● Phenytoin (for epilepsy) - Since the effect of phenytoin maybe enhanced ● Selective serotonin reuptake inhibitors - As these may increase the risk of gastrointestinal bleeding (medicines used for depression) ● Lithium - Since the effect of lithium maybe enhanced (a medicine for manic depressive illness and depression) ● Probenecid and Sulfinpyrazones - Since the excretion of ibuprofen maybe delayed (medicines for treating gout) ● Medicines for high blood pressure and - Since ibuprofen may diminish the effects of these water tablets medicines and there could be a possible increased risk for the kidney ● Potassium sparing diuretics - Since this may lead to hyperkalaemia (high potassium levels in the blood) ● Methotrexate - Since the effect of methotrexate maybe enhanced (a medicine for cancer or rheumatism) ● Tacrolimus and cyclosporin - Since kidney damage may occur (immunosuppressive medicines) ● Zidovudine - Since the use of ibuprofen may result in an increased risk of (a medicine for treating HIV/AIDS) bleeding into a joint or a bleed that leads to swelling in HIV (+) haemophiliacs ● Sulfonylureas (antidiabetic medicines) - Interactions maybe possible ● Quinolone antibiotics - Since the risk for convulsions maybe increased ● Mifepristone - Since ibuprofen may reduce the effect of this medicine (medicine prescribed for pregnancy termination) ● Bisphosphonates (medicines prescribed - Since these may increase the risk of gastrointestinal ulcers to treat osteoporosis) or bleeding ● Oxpentifylline (pentoxyfilline) - Since this may increase the risk of gastrointestinal bleeding (medicine prescribed to increase the blood flow to arms and legs) ● Baclofen,a muscle relaxant - Since the toxicity of baclofen maybe enhanced Low dose ASA Do not take this medicine if you are taking ASA at doses of above 75 mg daily. If you are on low-dose ASA (up to 75 mg daily) speak to your doctor or pharmacist before you take Ibuprofen. Ibuprofen with alcohol Consumption of alcohol should be avoided while taking Ibuprofen as it may intensify possible side effects. Pregnancy, breast-feeding and fertility Do not take Ibuprofen in the last 3 months of pregnancy. If you are in the first 6 months of pregnancy, breast-feeding, think you maybe pregnant or are planning to have a baby, ask your doctor or pharmacist for advice before taking this medicine. Ibuprofen tablets belong to a group of medicines which may impair fertility in woman. This effect is reversible on stopping the medicine. It is unlikely that Ibuprofen, used occasionally, will affect your chances of becoming pregnant, however tell your doctor before taking this medicine if you have problems becoming pregnant. Driving and using machines For short-term use and at normal dosage this medicine has no or negligible influence on the ability to drive and use machines. If side-effects such as tiredness, dizziness, drowsiness and visual disturbances occur, do not drive or operate machines. Alcohol consumption increases the risk of these side effects. 3. How to take Ibuprofen Always take this medicine exactly as described in this leaflet or as your doctor or pharmacist has told you. Check with your doctor or pharmacist if you are not sure. The product is intended for short term use only. You should take the lowest effective dose for the shortest time necessary to relieve your symptoms. You should not take Ibuprofen for longer than 3 days in the case of migraine or fever, or 4 days for the treatment of pain unless your doctor tells you to. If symptoms persist or worsen consult your doctor. [200 mg only] Adults and adolescents over 40 kg body weight(12 years of age and above): The recommended dose is 200 mg to 400 mg (1 or 2 tablets), up to three times a day as required. Leave at least four hours between 200 mg (1 tablet) doses and at least six hours between 400 mg (2 tablets) doses. Do not take more than 1200 mg (6 tablets) in 24 hours. For treatment of migraine headache the recommended dose is 2 tablets of 200 mg as a single dose. If necessary, take 400 mg (2 tablets) dose with intervals of 4 to 6 hours. Do not take more than 1200 mg (6 tablets) in any 24 hours. Use in children over 6 years (20 kg - 40 kg body weight): The recommended daily dose is 20 mg to 30 mg of ibuprofen per kg body weight divided into three or four separate doses as shown in the table below. Leave at least six to eight hours between doses. Body weight Single dose Maximum daily dose 20 kg - 29 kg one 200 mg tablet (equals 200 mg ibuprofen) three 200 mg tablets (equals 600 mg ibuprofen) 30 kg - 39 kg one 200 mg tablet (equals 200 mg ibuprofen) four 200 mg tablets (equals 800 mg ibuprofen) If in children aged from 6 years and in adolescents this medicinal product is required for more than 3 days, or if symptoms worsen a doctor should be consulted. Use in children under 6 years (less than 20 kg body weight): Ibuprofen is contraindicated for use in children under 6 years (less than 20 kg body weight). [400 mg only] Adults and adolescents from 40 kg body weight (12 years of age and above) The recommended dose is 400 mg (1 tablet), up to three times a day as required. Leave at least six hours between 400 mg (1 tablet) doses. Do not take more than 1200 mg (3 tablets) in 24 hours. If in children aged from 12 years and in adolescents this medicinal product is required for more than 3 days, or if symptoms worsen a doctor should be consulted. For treatment of migraine headache the recommended dose is 1 tablet of 400 mg as a single dose. If necessary, take 400 mg (1 tablet) dose with intervals of 4 to 6 hours. Do not take more than 1200 mg (3 tablets) in any 24 hours. Use in adolescents under 40 kg body weight or in children under 12 years of age: Ibuprofen is contraindicated for use in adolescents under 40 kg body weight or in children under 12 years. Method of administration Ibuprofen tablets are swallowed whole with plenty of water. Do not chew the tablets. Patients with a sensitive stomach should take the tablets during a meal. Taking the tablets after a meal may delay the onset of pain or fever relief. Do not exceed the recommended dose or take more frequently than recommended. If you take more Ibuprofen than you should You may experience nausea, stomach ache, headache, vomiting, diarrhoea, ringing in the ears, vomiting blood and blood in stools. More serious poisoning can lead to dizziness, drowsiness, excitation, disorientation, low blood pressure, reduced breathing (respiratory depression), blue discolouring of the skin and mucosa (cyanosis), loss of consciousness, convulsions and coma. You should seek immediate medical advice in the event of an overdose, even if you feel well. If you forget to take Ibuprofen Simply refer to the directions above on how to take the medicine and do not take more than is advised. Do not take a double dose to makeup for a forgotten dose. If you have any further questions on the use of this medicine, ask your doctor or pharmacist. 4. Possible side effects Like all medicines, this medicine can cause side effects, although not everybody gets them. Side effects maybe minimised by taking the lowest dose for the shortest time necessary to relieve the symptoms. Elderly people using this product are at increased risk of developing problems associated with side effects. Medicines such as Ibuprofen maybe associated with a small increased risk of heart attack (“myocardial infarction”) or stroke. Some of the undermentioned undesirable effects are less frequent when the maximum daily dose is 1200 mg compared to high-dose therapy in rheumatism patients. If you think you have any of the following side effects or symptoms, stop taking this medicine and seek immediate help: ● stomach and intestinal ulcers, sometimes with bleeding and perforation, vomiting blood or have black tar-like stools (common: may affect up to 1 in 10 people) ● kidney disease with blood in the urine which can be associated with renal failure (uncommon: may affect up to 1 in 100 people) ● severe allergic reactions (very rare: may affect up to 1 in 10,000 people) such as: - difficulties in breathing or unexplained wheezing - dizziness or faster heartbeat - drop in blood pressure leading to shock - swelling of your face, tongue or throat ● potentially life-threatening skin rashes with severe blisters and bleeding in the lips, eyes, mouth, nose and genitals (Steven-Johnson syndrome) or serious skin reactions which starts with painful red areas, then large blisters and ends with peeling of layers of skin. This is accompanied by fever and chills, aching muscles and generally feeling unwell (toxic epidermal necrolysis) (very rare: may affect up to 1 in 10,000 people) ● severe condition of the skin that may affect the mouth and other parts of the body with symptoms including: red, often itchy spots, similar to the rash of measles, which starts on the limbs and sometimes on the face and the rest of the body. The spots may blister or may progress to form. raised, red, pale-centred marks. Those affected may have fever, sore throat, headache and/or diarrhoea (very rare: may affect up to 1 in 10,000 people) ● severe flaking or peeling of the skin (very rare: may affect up to 1 in 10,000 people) ● inflammation of the pancreas with severe upper stomach pain, often with nausea and vomiting (very rare: may affect up to 1 in 10,000 people) ● nausea, vomiting, loss of appetite, feeling generally unwell, fever, itching, yellowing of the skin and eyes, light coloured bowel motions, dark coloured urine which maybe signs of hepatitis or liver failure (very rare: may affect up to 1 in 10,000 people) ● disease of the heart with shortness of breath and swelling of the feet or legs due to fluid build-up (heart failure) (very rare: may affect up to 1 in 10,000 people) ● aseptic meningitis (infection around the brain or spinal cord with symptoms including fever, nausea, vomiting, headache, stiff neck and extreme sensitivity to bright light and clouding of the mental state and thus not being fully in contact with the environment) (very rare: may affect up to 1 in 10,000 people) ● heart attack (“myocardial infarction”, very rare: may affect up to 1 in 10,000 people) or stroke (not known: frequency cannot be estimated from the available data) ● severe kidney damage (papillary necrosis), particularly in long term use (rare: may affect up to 1 in 1,000 people) ● worsening of infection-related inflammations (e.g. development of flesh eating bacteria syndrom) particulalry if using other NSAIDs (very rare: may affect up to 1 in 10,000 people) Stop taking the medicine and tell your doctor if you experience: Very common (may affect more than 1 in 10 people) ● indigestion or heartburn ● abdominal pain (pains in your stomach) or other abnormal stomach Uncommon (may affect up to 1 in 100 people): ● Visual disturbances Tell your doctor if you experience any of the below side effects: Very common (may affect more than 1 in 10 people) ● nausea,wind, diarrhoea, constipation, vomiting Common (may affect up to 1 in 10 people): ● headache, sleepiness, dizziness, spinning sensation tiredness, agitation, inability to sleep, irritability ● stomach and intestinal ulcers, sometimes with bleeding and perforation; hidden blood loss which may lead to a condition in which there is a decreased number of red blood cells (symptoms include tiredness, headaches, being short of breath when exercising, dizziness and looking pale), black tar-like stools, vomiting blood, mouth ulcers and cold sores, inflammation of the colon (symptoms include diarrhoea, usually with blood and mucus, stomach pain, fever), worsening of inflammatory bowel disease, inflammation of bowel wall Uncommon (may affect up to 1 in 100 people): ● hives, itching, unusual bleeding or bruising under the skin, skin rash, asthma attacks (sometimes with hypotension) ● runny or blocked nose, sneezing, facial pressure or pain, difficulty in breathing ● inflammation of the stomach (symptoms include pain, nausea, vomiting, vomiting blood, blood in the bowel motions) ● increased sensitivity of the skin to sun ● swelling of the face, lips, mouth, tongue or throat which may cause difficulty in swallowing or breathing, sometime with high blood pressure ● fluid build-up in the body's tissues especially inpatients with high blood pressure or kidney problems Rare (may affect up to 1 in 1,000 people) ● a disease affecting the skin, joints and kidneys (lupus erythematosus syndrome) ● depression, confusion, hallucinations, mental illness with strange or disturbing thoughts or moods ● buzzing, hissing, whistling, ringing or other persistent noise in the ears ● increase of blood urea nitrogen, serum transaminases and alkaline phosphatase, decrease in haemoglobin and haematocrit values, inhibition of platelet aggregation, prolonged bleeding time, decrease of serum calcium, increase in serum uric acid, all seen on a blood test ● loss of vision Very rare (may affect up to 1 in 10,000 people): ● fast or irregular heartbeats (palpitations) ● fluid build-up in the body's tissues ● high blood pressure ● inflammation of the food pipe, narrowing of intestines ● liver disease, liver damage (especially in long-term use), liver failure, yellowing of the skin and/or eyes, also called jaundice ● unusual hair loss or thinning ● severe skin infections with soft tissue complications may occur if you have chickenpox ● menstrual period disorders ● build-up of fluid in the lungs, symptoms include breathlessness, which maybe very severe and usually worsens on lying down. Not known (frequency cannot be estimated from availble data) ● worsening of an inflammatory disease that can affect any part of the gastrointestinal tract (symptoms include pain, fever, diarrhoea and loss of weight), worsening of inflammation of the colon ( symptoms diarrhoea, usually with blood and mucus, stomach pain, fever)
midterm_IADS2024 - Jupyter Notebook IADS midterm Please ensure all code is executed and the corresponding outputs are included. Write the code directly in this notebook rather than creating a new one. Part 1: Multiple choice and theoretic questions Please write your answer after each question Question 1. What would the p-value of 0.04 mean for t-test comparing two samples of observations (select all that applies): A) sample averages are at least 4% different B) the samples follow the underlying distributions with the same mean C) the samples follow the underlying distributions with the different mean D) one can reject the null hypothesis that the samples follow the underlying distributions with the same mean at 5% significance level (or with 95% confidence) since p-values is below 0.05 E) one can't reject the null hypothesis that the samples follow the underlying distributions with the same mean at 5% significance level (or 95% confidence) singe p-value does not reach 0.05 F) one can reject the null hypothesis that the samples follows the underlying distributions with the different means at 5% significance level (or 95% confidence) G) probability that two samples have the same means is 4% Question 2. What is true regarding normal and log-normal distributions: A) Quantities following log-normal distributions have higher probabilities for outliers compared to normal distributions B) Outliers significantly different from the mean are more common for the normally distributed variables compared to log normally distributed variables C) Logarithm of the normally distributed quantity follow a log-normal distribution D) Logarithm of the log-normally distributed quantity follows a normal distribution E) Probability density function of the log-normally distributed variable equals to the logarithm of the probability density function of the normally distributed variable Question 3. Imagine training a model which considers multiple sattelite images of urban traffic and tries to find groups of typical (repeated with minor deviations) scenarios. How would you classify this problem from Machine Learning perspective? A) Supervised leanring; B) Unsupervised learning; C) Semi-supervised learning; D) Reinforcement learning. Question 4. Please explain why would you need separate training, validation and test samples to learn the model. In which cases you may need all three, including a validation sample? Part 2: NYPD data analysis In this part, you need to download New York Police Department (NYPD) complaints data for 2019 and write code for three following sections (each having own sub-sections): Data cleaning, Exploratory analysis and Hypothesis testing download NYPD complaints data: two options: 1. download with curl or urllib methods 2. download with API
Complex Systems comp90072 – The Art of Scientific Computing 1 Introduction 1 Introduction One might ‘intuitively’ argue that in general, catastrophic events have equally catastrophic causes; or more formally, large perturbations to the state of a system must have proportionally large causes. For example, a planet orbiting its star will deviate from its orbit in proportion to the size of the object that hits it such that a small meteorite crashing into the Earth has a negligible effect whilst having a black hole fly through the Solar System might result in the Earth being flung out into interstellar space. Although there are countless examples in physics were the cause and effect are proportional, this is not always the case as we will investigate in this lab. Although the scenario of planet orbiting a star is quite easy to describe, not all systems are quite so simple. Many systems (and often the more interesting ones) in fact contain an extremely large number of interconnected components giving rise to an enormous number of degrees of freedom. Naïvely, one might assume that if we can describe how each component behaves with its immediate neighbours, we might be able to draw conclusions as to the behaviour of the system as a whole; but this is in general not possible save for the very simplest of microscopic interactions. Even if we are able to write down the Lagrangian of the system, solving the equations of motion will be intractable. In this lab, we will be investigating an (initially simplistic) example of a sand pile on a lattice. The general idea is that we will be adding grains of sand onto a lattice and we will have to ‘topple’ points of the lattice according to a set of rules. Despite the rules being extremely simple to begin with, we will see that the complex behaviours arise. 1.1 Self-organized Criticality and Scale Invariance In 1987, Bak, Tang and Wiesenfeld introduced the concept of self-organized criticality (soc) [1,2]. It is a property of certain systems (typically slowly driven complex systems) whereby it will evolve towards a particular configuration without the need to finely tune parameters of the system. This particular configuration the system is evolving towards is called the attractor as it ‘attracts’ the system to it. In addition to having an attractor, systems exhibiting socgenerally exhibit some sort of scale invariance. As the name suggests, scale invariance is the property whereby a system looks the same over a broad range of scales. Most likely you have seen this property in mathematics in fractals whereby the pattern repeats itself as you zoom in as seen in figs. 1 and 2. Scale invariance can also arise in real physical systems and manifests itself by forming some sort of power-law for the frequency of an event compared to its size. Examples of phenomena which exhibit power-law behaviour include: • earthquakes (which are described by the Gutenberg–Richter Law); • solar flares; Figure 1: Mandelbrot set which exhibits scale invariance as certain patterns repeat at different scales (above pictures showing different ’zoom’ into the Mandelbrot set). • forest fires; • epidemics; and, • fluctuations in financial markets. Note that all of the systems above are slowly driven. That is, they are only ever affected by small localized effects and thus are never greatly perturbed. Question 1: Why is it that a system exhibiting scale invariance will have phenom- ena which are described by a power law? Self-organizing criticality as a framework has been used to study an extraordinarily diverse range of systems. It has been used to characterise, analyze and predict earthquakes, financial markets, evolution and extinction events, pulsar glitches, neuronal behaviour and much more. Figure 2: The btw sand pile exhibiting scale-invariant patterns. In this sand pile, the sand was dropped continuously onto the centre. 1.2 Non-equilibrium Statistics As discussed above, the systems we will be investigating have an enormous number of degrees of freedom making it difficult to work with analytically and impossible to solve the exact dynamics of the system. In order to still get an insight on the system, we must rely on statistical tools and in particular, tools which work with non-equilibrium systems. Non-equilibrium statistics underlies how we think about systems that display self-organizing criticality and does so in a holistically. When a system is critical, microscopic phenomena (such as a local increases in stress) are not responsible for the macroscopic observables of the system (such as an earthquake’s size, duration, area etc). In particular, the proportions of large and small events do not depend on the exact microscopic details of what is happen- ing. Consequently, one cannot analyze the building blocks of a system in order to explain the large scale phenomena. In other words, a detailed understanding of the microscopic interactions of the system do not translate into system-level understanding. 1.3 Aim The primary aim of this lab will be to build a basic sand pile model and study socwithin this system and the associated non-Gaussian statistics. The basic model can subsequently be extended in any of a number of ways to replicate more physically accurate systems or investigate how the system behaves under different conditions. 2 Bak–Tang–Wiesenfeld Model 2 Bak–Tang–Wiesenfeld Model When modelling a complex system, it is often difficult (or impossible) to create mathematical formalism that is both sufficiently realistic and computationally/theoretically tractable. As a result, researchers will consider a simplified model that captures the important elements of the physical system in question. The btwmodel is an excellent example of a simplified model which exhibits soc. The btwmodel describes a (somewhat abstract) sand pile. The grains of sand are located on an 푁 × 푀 lattice such that 푝 t(푖, 푗) is the number of grains located on site (푖, 푗) at time 푡, where 푖 ∈ [1, . . . , 푁], 푗 ∈ [1, . . . , 푀] and 푡 ∈ N0. At each time step 푡, a new grain of sand is added to a random site in the lattice causing the sand piles at each site to grow. If an individual pile of sand reaches a height of 4 or more, then the pile topples and distributes four grains of sand to its four immediate neighbours (we are not considering diagonal neighbours): 푝 t(푖, 푗) = 푝 t(푖, 푗) - 4, 푝 t(푖 ± 1, 푗) = 푝 t(푖 ± 1, 푗) + 1, 푝 t(푖, 푗 ± 1) = 푝 t(푖, 푗 ± 1) + 1. Note that this process is instantaneous and does not increment 푡 . Furthermore, if the toppling happens on the edge of the lattice (i.e. 푖 ∈ {1, 푁 } and/or 푗 ∈ {1, 푀 }),the grains that would topple to a site off the table are deleted from the system. Question 2: In what ways does the btwmodel satisfy the properties required for a system to exhibit soc? Question 3: Why is it important for the table to have finite boundaries? What if we had an infinite lattice, but dropped the sand on only a (finite) subset of the lattice? If the lattice begins with no sand at all, we might expect the sand to just accumulate to begin with as very few grains of sand will topple off the edge. Eventually though, the slow addition of sand should balance out with those grains of sand toppling off the edge of the grid. Figure 3: An example of a simple avalanche taking place on a 3 × 3 grid. Question 5: Explain the difference between: a steady state, a statistically station- ary state, and an equilibrium state. Do you expect the btw model reach an equilibrium state or statistically stationary state? In terms of system observables, how might we characterize this state? The addition of a grain of sand to the lattice has a chance of creating an unstable site which topples; but the toppling in turn can create further unstable sites which will subsequently topple. As a result, the addition of a single grain of sand can create a chain of toppling which we call an avalanche as depicted in fig. 3. It will be these avalanches that we will be most interested in. In particular, we will consider the following properties: Topples The number of topples required to take the grid from its initial unstable config- uration to a stable one; Area The number of unique sites which have been toppled; Loss The number of grains of sand which are toppled off the lattice; and, Length A ‘length’ which characterizes the avalanche. Note that we are purposefully leaving the length definition quite vague. You’ll have to decide where from and to this length is defined, and which metric to use (such as the 퐿1- norm or 퐿2-norm, a.k.a. Manhattan distance and Euclidean distance respectively). Don’t forget to justify your choice. Question 6: Is there a difference between sampling a system over time and sampling an ensemble of systems? If so, under what circumstances? Hint: Lookup the property of ergodicity and argue whether or not you believe the btw model is ergodic. Question 7: Record the frequency with which avalanches have a specific number of topples, area, loss and length. What kind of distribution do you get for each? If possible, can you find a fit for the distribution? (E.g. for a Gaussian, find the mean and width of the distribution; for a power law, find the exponent.) Question 8: Do you expect any correlation between the four properties we are recording for the avalanche? Justify why/why not, then verify this with your simulation. 2.1 Abelian Property Although the btwmodel is a model of‘sand piles’, it is extremely unrealistic—after all,sand piles aren’t formed on a lattice and even if they were, a site wouldn’t go from four grains of sand to none from toppling on its neighbours. Nevertheless, it exhibits an extremely useful mathematical property when it comes to analysing its behaviour: the topplings are Abelian. In other words, it doesn’t matter in which order we execute each toppling, the end result is the same. To give a concrete example, consider the following start to an avalanche: There are now two unstable sites, (1, 2) and (3, 2). If the model were not Abelian, we would need to keep track of the order in which sites are toppled and make sure that we topple the correct next unstable site; however as the btwsand pile model is Abelian, we can do this in whatever order we wish and arrive at the same result thereby greatly simplifying the computational complexity of avalanches. You might take it for granted that the btwmodel is Abelian, but this can be fairly easily shown rigorously. To begin with, we can consider the lattice of sand piles to be 퐿 which is a finite subset of Z푑 where 푑 is the dimensionality of the lattice. For any site 풙 ∈ 퐿, the number of grains of at each point of the lattice is given by the function 푝 : 퐿 → N0 . (3) Astable configuration corresponds to the scenario where 푝(풙 ) < 푘 for all 풙 ∈ 퐿 while an unstable one has at least one site 풙 ∈ 퐿 where 푝(풙 ) ≥ 푘 where 푘 defines is the stability threshold. From an unstable configuration 푝, we must introduce a way to describe the toppling; for this, we introduce the toppling matrix Δ (풙 , 풚). This stabilizes an unstable site 풙 in the configuration 푝 by redistributing the sand to site 풚 . The toppling matrix must satisfy the following conditions: ∀풙 , 풚 ∈ 퐿 where 풙 ≠ 풚 , Δ (풙 , 풚) = Δ (풚, 풙 ) ≥ 0, (4a) ∀푥 ∈ 퐿, Δ (풙 , 풙 ) :0 Otherwise Question 10: Explain and justify the definition of the toppling matrix in the btwmodel and verify that it satisfies all the conditions set out in eq. (4). What is the stability threshold 푘 ? Given the definition of the toppling matrix, it is now possible to define the toppling operator 푇풙 which maps a configuration 푝 to a new configuration 푝 /: Question 11: Show that 푇풙 and 푇풙/ commute for unstable configurations. In general, multiple topplings are required in order to stabilize a configuration 푝 and we can introduce a stabilization operator which maps an unstable configuration to a stable configuration T : 푈L → 푆 L (7) where 푈L is the space of all possible height configurations and 푆 L C 푈L is the subset of stable height configurations. To give a concrete example, the stabilization operator for fig. 3 consists of four topplings: 푝 / = T푝 = 푇(2,3)푇(1,3)푇(1,2)푇(2,2)푝 . (8) 3 Extending the btw Model Thus we see that a stabilization operator can be represented as 푁 where 푁 is the number of instabilities through an avalanche. Question 12: Show that Tis well defined. In other words, show that given some unstable configuration 푝, 푝/ = T푝 is unique (you can’tend with two different stable configurations). This is equivalent to the sequence of 푇풙 푖 required is unique up to re-ordering. Hint: Read the original papers for hints as to how this can be done. 3 Extending the btwModel The btwmodel is clearly unrealistic; however, you have just seen that it still exhibits very interesting statistics. You can now extend this model in any of a number of ways. Irrespective of which extension(s) you choose, remember to make predictions as to what you expect and then test these predictions with your simulation. You should also compare your extension to the baseline btwmodel: in what ways is it similar and in what ways does it differ? A few extensions you may consider (and combine or extend as your please): 1. Change the toppling so that it depends on the gradient: if a site has 푘 more grains of sand than its neighbour it is unstable and it drops 1 grain of sand onto this neighbour and repeat until it is stabilized. 2. Change the toppling to be random: instead of redistributing the four grains of sand to all four neighbours, it selects one of the four neighbours at random for each grain of sand. What about adjusting the probability to drop to a neighbour based on the height difference? 3. Change the boundary conditions: a) Make the toppling ‘wraparound’ in 푥 (like a cylinder) so that grains of sand can only drop off the top or bottom of the grid. b) What happens if grains of sand can’t topple off the edge, but instead there is a hole in the centre of the grid (imagine a kind of hourglass). 4. Change how fast grains of sands are added to the grid. Instead of adding 1 grain of sand at a time, add 2, or 3, or 푛 . Do you add each of these grains to different sites or the same? 5. Change how you are adding grains of sand. Instead of being uniformly random on the grid, what if grains of sand were only dropped on a small subset of the grid, or followed a different distribution (such as a Gaussian centred on the middle of the grid). 6. Make the avalanche happen really slowly so that the toppling rule, eq. (1), becomes: p 푡+1(i, j) = p 푡 (i, j) - 4, p 푡+1(i ± 1, j) = p 푡 (i ± 1, j) + 1, (10) p 푡+1(i, j ± 1) = p 푡 (i, j ± 1) + 1. Perhaps you don’t want to increase the timestep every topple, but every nth topple. 7. Instead of a rectangular lattice, change it to a hexagonal lattice (have a look at hexagonal coordinatesystems). 8. Change the toppling rule so that instead of dropping to the 4 directly adjacent sites, it drops to the 8 surrounding sites. Or maybe change it so that it drops to all sites with a radius of 2 of the initial site. 9. Add a force that will push grains of sand in a particular direction (such as wind, or if the grid was sloped). References References [1] P. Bak, C. Tang and K. Wiesenfeld, ‘Self-organized criticality: an explanation of the 1,푓 noise’, Phys. Rev. Lett. 59, 381–384 (1987)1 0 . 1 1 0 3 / P h y s R e v L e t t . 5 9 . 3 8 1 . [2] P. Bak, C. Tang and K. Wiesenfeld, ‘Self-organized criticality’, Phys. Rev. A 38, 364– 374 (1988)1 0 . 1 1 0 3 / P h y s R e v A . 3 8 . 3 6 4 .
ACTU PS5821 Actuarial Methods - Autumn 2024 Assignment - 4 Assigned 9/27/24, Due 10/5/24 Problem 1. A population consists of 30% smokers with µx = 0.2 and 70% non-smokers with µx = 0.1. Calculate the 75th percentile of a randomly selected individual’s future timelife random variable. Problem 2. Calculate the complete expectation of life at age 40 if you are given the following. 40p0 = 0.6, E(T0 ) = 62 and E[min(T0 , t)] = t − 0.005t2 , 0 < t 0 where where S = 1 if (x) smokes and S = 0 otherwise. Also, 10p[3(n)0(o)n]smoker = 0.96 (a) Find the value of β (b) Calculate the probability that a life randomly drawn from a population of lives selected at age 30 of which 40% are smokers, will survive at least 10 years. Problem 5. T20 follows a uniform distribution with a limiting age of 120. Find n such that˚(e)20: ni = 48
MAT E 640 Advanced Thermodynamics in Materials Department of Chemical and Materials Engineering Final Exam December 19, 2011 180 minutes Answer all questions. State any assumptions you make and explain your answers. The total number of marks is 70. 1. Choose true or false to the following statements. (14 marks) T F Based on a statistical approach to entropy, the equilibrium state represents the most probable distribution for that system. T F The entropy for all real materials goes to zero as the temperature approaches absolute zero. T F Increasing under-cooling can always promote the nucleation rate, but suppress the growth rate. T F The Gibbs free energy change associated with the mixing of different ideal gases at constant temperature is only due to a change in the configurational entropy of the gases. T F For the van der Waals equation of state, the constant b is a correction factor for the finite volume of the particles in a real gas, while the constant a is a correction factor for temperature. T F The process of liquid-liquid phase separation always occurs by nucleation and growth. T F The critical nuclei size for homogeneous nucleation is larger than that for heterogeneous nucleation at the same temperature and pressure. 2. A binary solution has activity coefficients, γ1 and γ1, given by where x1 and x2 are the mole fractions, where Tm is the melting point and β = 4 ln5 . (Note, this is not a regular solution since α is not a constant) a) What is the free energy of mixing, ΔGM, upon forming the binary solution (in terms of R, T, α, and x1)? (4 Marks) b) Find the change in partial molar enthalpy of component 1 upon mixing of this binary solution (in terms of R, α, β, Tm, and x1), H1 − H10 . Is this quantity positive or negative? What does this tell you about the interaction between components 1 and 2? (6 Marks) c) What are the two spinodal compositions for this solution at T = 0.8Tm ? (4 Marks) 3. For a subregular solution, solution model is given by: a) Determine ΔGM(X)S (3 Marks) b) Determine ΔHM(X)S and ΔSM(X)S (4 Marks) c) Find ΔG 1(X)S and ΔG 2(X)S (4 Marks) d) Determine activities a1 and a2 . (4 Marks) 4. A pressure-volume isotherm is shown below for the CO2 van der Waals gas. a) What is the approximate value of the equilibrium vapor pressure? How do you determine this value? [3 marks] b) What is the pressure of the system when the molar volume for the liquid is 0.125L? [2 marks] c) What are the molar volumes of the liquid and vapor when the two phases are in equilibrium? [3 marks] 5. For the Au-Sn phase diagram given below draw schematics of plausible molar free energy curves showing the common tangent construction as a function of composition, x Sn, at T1=350 。C (30 at.%< x Sn
Comparison of Linear and Quadratic Regression Models The following data presents the growth in worldwide Internet usage from 1995 through 2011: Year: 1995 1996 1997 1998 1999 2000 2001 No. of users (in millions): 16 36 70 147 248 361 533 Year: 2002 2003 2004 2005 2006 2007 2008 No. of users (in millions): 597 719 817 1018 1093 1319 1574 Year: 2009 2010 2011 No. of users (in millions): 1802 2013 2267 1. Enter the data into L1 and L2 and create a linear model for the data: a. What is your linear model?___________________________ b. What is the slope? _____ c. Interpret the slope within the context of the problem. d. What is the r-value? _______ What does this tell you about the linear relationship between x and y? e. What is the r2 value? What does this tell you about the relationship between x and y? f. Do a scatterplot of Y1 and the data. What does that tell you about the linear model? g. Store the predictions in L3 and the Residuals in L4. h. Do a scatterplot of X-values vs Residuals. When doing this plot, first Deselect Y1. Sketch the plot here. What does this tell you about the linear model? i. Create a quadratic model:___________________________ j. What is the R2 value? What does this tell you about the relationship between x and y? k. Do a scatterplot of Y1 and the data. What does that tell you about the quadratic model? l. Store the predictions in L3 and the Residuals in L4. m. Do a scatterplot of X-values vs Residuals. When doing this plot, first Deselect Y1. Sketch the plot here. What does this tell you about the quadratic model? n. Look at the Residual plot and use the Trace Key to find the ‘largest’ residual (it could be positive or negative.) Go back to your Stat Editor and find the corresponding x-value, y-value and predicted y-value. o. Use your model stored in Y1 to estimate the number of internet users for 2012.
Main Examination Period 2019 BUSM096 Business Relationships and Networks Question 1 How can the concept of ‘derived demand’ and Pfeffer and Salancik’s Resource- Dependence Theory be linked? Use your argument to show why end consumers are relevant for companies working in business-to-business exchanges. [50 marks] Question 2 What causes the ‘dark side of business relationships’, and how are these causes different from those of the ‘bright side of business relationships’? Use the concept of value to illustrate your argument. [50 marks] Question 3 “The concept of ‘networking capabilities’ is mainly about managing in existing business relationships.” Critique this statement by analysing different networking capabilities, both with reference to dyadic business relationships and business networks. [50 marks] Question 4 “It is important, and inevitable, for everyone in a company to share the same network picture.” Critique this statement, and link your argument to the concept of ‘network insight’. [50 marks]
CSE 101 Midterm 2 Review Problems 1. Rank the following functions from lowest to highest asymptotic growth rate. 1) 2n 2) n ln(n) 3) n 4) 2ln(n) 5) ln(ln(n)) 6) n √n 7) n2 8) ln(n2) 9) √n Write your answer as a permutation of the set {1, 2, 3, 4, 5, 6, 7, 8, 9}, giving the corresponding line numbers of the above functions in the required order (left to right, slowest growing function to fastest growing function.) No justifications are required. 2. Consider the List ADT from pa5 but without the cleanup()function. Write a C++ client function with heading void RemoveDuplicates(List& L) that does the same thing as cleanup(), except that it does not matter where the cursor ends up. In other words, the call RemoveDuplicates(L) will alter List L so that it contains only the first occurrence of each of its data items. To do this, you may use all ADT operations in List.h except cleanup(). 3. Let T be a Binary Search Tree containing the keys {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13}. Suppose that a pre-order tree walk prints the keys in order: 2, 1, 12, 10, 8, 7, 5, 4, 3, 6, 9, 11, 13, and that a post-order tree walk prints the keys in order: 1, 3, 4, 6, 5, 7, 9, 8, 11, 10, 13, 12, 2. Determine the structure of T. (Note: only one of the two tree walks is really necessary since each of them uniquely determines the structure of T.) Present your solution either by drawing a picture of the tree, or by constructing a table giving the parent of each Node. 4. Use the TreeInsert() algorithm to insert the following keys: 6, 2, 1, 4, 10, 8, 7, 9, 12, 11, 14, 13, 15 (in order) into an initially empty BST. a. Draw the resulting BST b. Use the Delete() algorithm to delete the following keys: 8, 6, 13, 14 (in order) from the BST you drew in part (a), then draw the resulting tree. 5. Suppose we alter the List ADT from pa5 by doing typedef char ListElement; at the beginning of List.h, making it a list of char instead of int. Assume a List L consists entirely of parenthesis characters '(' and ')'. The List L is called a Well Formed Formula (WFF) iff all parentheses can be matched in pairs (open and close). For instance "(()(()))" and "()()(())" are WFFs, while "(()()" and "(()))" are not. The empty List is considered to be a WFF. Write a client function with heading bool isWFF(List L) that returns true or false, according to whether L is or is not a WFF. (Hint: search for adjacent matching pairs and delete them. If L becomes empty, then return true.)
Probability Examples I. Blood types: All human blood can be “ABO-typed” as one of O, A, B, or AB, but the distribution of the types varies a bit among groups of people. Here is the distribution of blood types for a randomly chosen person in the U.S. Blood Type O A B AB U.S. probability 0.45 0.40 0.11 0.04 Consider a married couple. 1. What is the probability that the wife has type A blood and the husband type B blood? p(A) ·p(B)=0.4x0.1=0.04 The probability is 0.04. 2. What is the probability that one of the couple has type A blood and the other has type B blood? 0.4x0.11+0.11x0.4=0.088 The probability is 0.088 3. What is the probability that a wife and husband share the same blood type? p(OO)+p(AA)+p(BB)+p(AB AB)=(0.45)(0.45)+(0.4)(0.4)+(0.11)(0.11)+(0.04)(0.04) =0.3762 II: Heart Disease is one of the leading causes of death in the U.S – approximately 25% of deaths in the U.S. can be attributed to Heart Disease. Medical researchers have determined that there are several risk factors, including High Blood Pressure, high cholesterol and diabetes. Approximately 49% of the population has at least one of these risk factors. ( Note: some individuals with these risk factors never do have a heart attack and some individuals who die of heart disease have no risk factors.). Information collected from the Center for Disease Control tells us the following: P(dying Heart Disease) = P(H) = 0.25 P(having at least one risk factor for Heart Disease) = P(R)= 0.49 P(having at least one risk factor and dying of Heart disease) = P( H and R) = 0.16 (Use a Venn Diagram to model this data.) (a.) What is the probability that an individual randomly selected from the population will NOT die of heart disease? p(H)=0.25 p(H’)=1-0.25=0.75 (b.) What is the probability that an individual will die of heart disease and he/she has no risk factors? p(H and not R)=0.25-0.16=0.09 (c.) What is the probability that an individual will die of Heart disease, given that the individual has at least one risk factor? p(not H and R)=0.49-0.16=0.33 (d.) What is the probability that an individual had at least one risk factor, given that the individual died of Heart Disease? p(R/H)=016/0.25=0.64=64% III. Testing for HIV: Enzyme immunoassay (EIA) tests are used to screen blood specimens for the presence of antibodies to HIV, the virus that causes AIDS. Antibodies indicate the presence of the virus. The test is quite accurate but not always correct. Here are approximate probabilities of positive and negative EIA outcomes when the blood tested does and does not actually contain antibodies to HIV: Test Result: + - Antibodies Present 0.9985 0.0015 Antibodies absent 0.0060 0.9940 Suppose that 1% of a large population carries antibodies to HIV in their blood. (a.) Draw a tree diagram for selecting person from the population and testing his or her blood. (b.) What is the probability that the EIA test is positive for a randomly chosen person from this population? P(T)=(0.9985×0.01)+(0.0060×0.99)=0.015925=1.59% (c.) What is the probability that a person has the antibody, given that the EIA test is positive? p(A/T)0.0985x0.01/0.015925=0.6268 Note: This illustrates a fact that is important when considering proposals for widespread testing for HIV, illegal drugs, or agents of biological warfare: if the condition being tested is uncommon in the population, many positives will be false positives.
School of Computing and Engineering ASSIGNMENT SPECIFICATION Module Details Module Code CHI2400 Module Title Information Architecture Course Title/s BSc (Hons) Computing MComp Computing BSc (Hons) Applied Computing (Top-up) BA (Hons) Computing in Business BSc (Hons) Information Technology BSc (Hons) Information Technology (Top-up) Assignment 1 1. Assignment Aims This assignment is made up of two separate tasks. Your first task is focussed on client-side issues the second task is focussed on server-side issues. Both tasks relate to the design of information seeking environments for students. 2. Learning Outcomes: • Critically review the ways information can be structured to support information seeking • Critically review concepts related to information seeking behaviour (ISB) and apply this understanding to the evaluation of existing search tools used in academic research, e-commerce and social media • Construct controlled vocabularies and ontologies to label digital content for later retrieval 3. Assessment Brief Task One (60%) You are tasked with designing a UI for an academic search tool that helps researchers and students find academic papers, books, and journals. The system will have features such as advanced search, filters, results display, and the ability to save and cite papers. Your goal is to implement UI patterns that simplify these interactions. What you should submit A report documenting user requirements and a clear specification for the design of a user interface. Your report should be organised under the following headings: 1. Requirements Analysis (10 marks) In this section, you should identify 8 Use Cases related to academic searching. Your Use Cases may include some of the following: Filter results (by date, relevance, citation count, etc.), view detailed information about a paper, save papers for later reference, export citations in different formats, view citation counts and impact and so on. For two of the Use Cases, you should provide a short scenario analysis – this does not need to be more than 100 words long. 2. User Flow (10 marks) In this section, you should present a basic flow for a typical user’s journey. Ideally, the journey you describe will be based on one of your own search journeys. Key steps in the journey might include the following pages: Landing Page: Search bar and basic search options, Search Results Page: A list of academic papers with filters and sorting options, Paper Details Page: Details about the selected paper (authors, abstract, citation formats), Save and Citation Options: Ability to save papers and export citations. 3. UI Patterns to Support User Flow (24 marks) In this section, you should identify and document some UI patterns supporting your proposed User Flow. Try to present two patterns for each phase in the flow. We have been discussing a four-phase model so I am expecting to see 8 user interface patterns in total. For each pattern, you should provide: a name, a short description, an indication of when this pattern could support the search process, a description of how the pattern might be implemented with screenshots showing how it can be applied (these may be taken from an existing application or be a mockup to help the reader understand what the implemented pattern might look like) and a discussion of how the pattern might help a student based on your own search experience. Here is an example of a pattern documented in this way: Pattern: Search_Filters Description As the name suggests, filters can be used to look for specific results, they reduce the amount of literature retrieved to specific literature that exactly matches the type of filter used. When Search filters are useful during all search stages and could be used during pre-search, exploratory search, or focused search activities. How Search filters can be provided in the form. of a check-box such as the ones used by Google Scholar and depicted in figure 1. Alternatively IEEE Xplore (see figure 2) provides filter as hyperlinks. Figure 1: Search filters. Figure 2: Filters in IEEE Xplore. Discussion Filters are easy to use, and I use them all the time to look for literature that is maximum 8 to 10 years old. So, the date filter is very important to me. The degree of relevance to the research topic is not always accurate. For example, applying author filter on results might lead to retrieving literature written by that author but on a different topic. 4. Wireframes (16 marks) Sketch or create low-fidelity wireframes for four pages. Each page should be associated with a different phase in our four-phase search model. So there should be a wireframe. for a page supporting Getting Started, one for Exploratory Search and so on. Task Two (40%) Create a simple ontology. In this task you will make use of Protégé to develop a simple ontology for a domain of your own choosing. Your ontology should contain no fewer than 20 classes. In developing the ontology you should go through the following steps: Step 1. Identify the domain and scope of the ontology (about 150 words). Step 2. Define the classes and the class hierarchy (approximately 20 classes). Step 3. Define the object properties of classes – the relationships between classes (at least 6 object properties). Step 4. Define the data properties of the classes (at least 6 data properties). Step 5. Create instances (at least 12 instances). Step 6. Check the ontology with a series of suitable queries (at least 10 queries). 4. Marking Scheme Task One (60%) The number of marks awarded for each section of your report is provided in the specification above. Task Two (40%) Steps 1 to 5 will be awarded 6% each, with the remaining 10% awarded for Step 6, as follows: - Step 1: 3% for the domain and 3% for the scope of the ontology - Step 2: 1% for every 3 classes (18 classes at minimum) - Step 3: 1% for each object property (6 object properties at minimum) - Step 4: 1% for each data property (6 data properties at minimum) - Step 5: 0.5% for every instance (12 instances at minimum) - Step 6: 1% for each query (10 queries at minimum)
