Instructions This assignment will test your knowledge and skills in writing an application software for a given problem, understanding its business rules, and coding a suitable solution using Python. As such, the assignment requires you to integrate and synthesise what you have learnt so far in this unit (content from week 1 to week 9), in order to design and create a proper working solution. Background: This programming assignment involves an escalation of the landing gear sensors problem discussed during the lectures and in your first assessment (also repeated here for your reference). You need to use your proposed solutions and calculations from Assignment 1, but this time you need to wrap everything up in a graphical user interface (GUI). This Assignment has two parts: · Part 1: Use your proposed solution to the airplane challenge and replace the shell- based menu by a suitable GUI. · Part 2: The “black box” (that is, the dictionary) you implemented in Assignment 1 and in Part 1 above, needs now to be developed via an external text file. Submission · This is a SOLO ASSIGNMENT. · Allocated marks are shown at the end of each item. · This assignment requires you to complete Python code written in .py modules, in addition to supporting files. · Create a folder called “uxxxxx Assignment2” and drop all your files in there. Python modules are compulsory. No modules, no marks. · Compress (zip) ALL your files and folders created above in one single file called uxxxxx_Assignment2.zip. Upload this file on Canvas by the due date using the drop box provided in the corresponding assignment. · There are 60 marks in total for this assignment. Assessment 2: Python application programming: GUI. Recap from Assignment 1 In Assignment 1, you briefly explained the problem to be solved, including inputs and outputs, and handwritten calculations. You developed the logic for the Boolean circuit and calculated the lift. All the previous steps were used to create a shell-based menu in Python. The following information/problem on the aircraft functional monitoring system is for revisiting the challenge from Assignment 1 as a reference only. You DO NOT need to redo this part!!! Your Challenge (Adapted from Floyd, Th. Digital Fundamentals, Pearson, 2015) As part of an aircraft's functional monitoring system, a logic circuit is needed to display the status of the landing gears before landing. The system should illuminate a green LED if all three landing gears are fully extended when the 'gear down' switch is activated in preparation for landing (the pilots need an extra visual signal lasting 10 seconds as a warning about the activation of the switch). Conversely, a red LED should light up if any of the landing gears fail to extend properly (see Figure 1). Figure 1: Airplane’s Landing Gear Sensors. In addition, a rotational sensor located in the directional gear below the cockpit, informs the pilots if the gear is not aligned with the aircraft’s fuselage (set up as 0 degrees when properly aligned). If this is the case, the red led described above should also be activated (see Figure 2). The circuit relies on sensors: a HIGH voltage indicates that a landing gear is extended, while a LOW voltage indicates it is retracted. All sensors are digital transducers. However, the directional sensor is an analogue transducer, that is, the signal it portrays happens to be continuous. Aiming to preserve the integrity of the fuselage if the landing approach fails due to a gear system’s malfunction, airplane’s lift needs to be calculated and presented to the pilots in the cabin. Figure 2: Airplane’s Directional Gear in Wrong Position. Credits: SamChui.com. “Batik Airbus A320 Lands with NLG Rotated 90 Degrees” The following information/problem on the aircraft functional monitoring system is for Assignment 2. You need to complete the following tasks in Part 1 and 2. Part 1: In your Assignment 1, the user input and output were not very satisfactory from the human computer interaction and usability point of view. Hence, your task in this assignment is to design and implement a Graphical User interface (GUI) using buttons and labels that provides an easy to use interface. Use the same code for the calculations from your Assignment 1. Reusing code is an important part of software development. You have a great degree of freedom in what GUI elements you choose and how you would like to design the layout of your GUI. What matters is the functionality of the design, and that the user can input the required data in a sensible fashion. However, some elements are compulsory, as we need to assess your understanding of performing a suitable GUI. Part 1 Marks allocation: [Total Marks: 45] Your GUI application must allow a user to input various data element, your GUI must: · Use the Grid element. [3 marks] · Add Label elements throughout your GUI. [3 marks] · Use the Background Colour property. [3 marks] · Allow a user to select choices from an either list box, drop-down menu, or scroll-down menu element. [5 marks] · Allow a user to input the data using an entry widget. [3 marks] · Output data using an entry widget. [3 marks] · Allow a user to click on a Calculate button that triggers any calculation. [3 marks] · Allow a user to press an Exit or Quit button to properly close the program. [3 marks] Marks are also allocated as follows: · GUI Design. Is it simple to use and easy to understand? [3 marks] Assessment 2: Python application programming: GUI. · Program is written using well-defined functions including a main() function to direct the program. [3 marks] · Program code layout. Separate blocks of code by a blank line. [3 marks] · Separate GUI functionality from calculations. You should use a separate method for the calculations. It is good practice and follows good programming style to separate GUI code from other code. [3 marks] · Use comments. [3 marks] · The program must have an introduction. [2 marks] · Business rules are met. That is, your code solves the problem you are proposing (or at least contributes to its solution). [2 marks] Part 2: The second part of this assignment is to add to your code and GUI an external .txt file that can be read (in the example case study from Assignment 1, the astronaut tool weight data), and put these into an appropriate storage in memory (it is suggested that you use either a nested list or a dictionary) and display the details to the user when requested. Please note that the text file needs to be written by yourself according to your proposed solution. You can use any text editor such as Notepad (do not use Word) . Part 2 Marks Allocation: [Total Marks: 15] · The text file is properly written according to the problem proposed [5 marks] · The text file should only be read once. You probably want to do that at the start of the program. Consider how you would do that. [5 marks] · Correct display of data based on the details in the text file. [5 marks]
ECE MATLAB 4 Assignment In this assignment, we will examine the design of digital IIR filters via the bilinear trans-form. and impulse invariance techniques. Suppose we wish to design a digital filter with the following specifications: passband from 0 to 0.4π, stopband from 0.5π to π. The passband ripple should not exceed 3 dB, and the stopband attenuation should always be at least 30 dB. Assume a sampling rate of 16 kHz (i.e., T = 1/16000) for this assignment. For the analog filters, please use the plotting range 0 : π/20 : π/T. For the digital filters, please use the plotting range 0 : π/200 : π. 1. To start with, we’ll need an analog filter. Determine the specifications on the analog filter that correspond to the digital specifications given above. Use the function ellip to design the filter. You can use ellipord to determine the correct order and cut-off frequency to give to ellip. Plot the frequency response using freqs, and confirm that it meets the specifications you worked out. Plot the polezero diagram for the filter. Since this is an analog filter, don’t use zplane. Instead, use roots to find the poles and zeros and plot them using plot. 2. Use the bilinear function to transform. your analog filter to a digital IIR filter. For this part, do not use any frequency pre-warping. Plot the frequency response and polezero diagram of the filter. Also, zoom in on the passband and stopband and determine if they meet the spec. If not, explain why. We know that the bilinear transform. should map any roots of the analog filter in the left-half s-plane into the interior of the unit circle in the z-plane. Did this occur? 3. Repeat part 2), but this time use frequency pre-warping to ensure perfect accuracy at the passband edge frequency. How does the frequency response differ from the previous case? Does this filter meet the spec? How do the locations of the poles and zeros compare to part 2)? 4. Use the impinvar function to design a digital IIR filter from the analog filter designed in part 1) via the impulse invariance method. Show the frequency response and pole-zero diagram. Explain the differences inpassband and stopband ripple as compared to the bilinear transform. cases. How do the locations of the poles and zeros compare to the bilinear transform. cases? Were zeros on the imaginary axis in the splane mapped to the unit circle in the z-plane? 5. Repeat steps 1) and 3) using a Butterworth and Chebyshev type 1 filter. You can use the functions buttord, cheb1ord and butter,cheby1 to design the analog filter. Do the resulting filters meet the spec?Also, compare the order of the filters you get to the order of the one in part 1).
STATS 763 - 2020 - Final assessment Due by 4 July 2020 at 12:59 PM Question 1. [15 marks total] All cases of non-pregnancy-related listeriosis (a contaminated food-borne disease) occurring in Germany in 2012-2013 were identified. Controls were randomly sampled throughout the country using stratified sampling by age group. Basic information about the sample and population is given in the table below: We are interested in the effect of consuming cold sausage on listeriosis occur-rence. The data are described as follows: The first few records in the data are as follows: > lis %>% head # A tibble: 6 x 6 Listeriosis ‘Age group‘ ‘Education level‘ Sex Residence ‘Cold sausage‘ 1 0 66-75 years Medium Female Town 0 2 0 mod summary(mod) Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -2.68228 0.61584 -4.355 1.4e-05 *** ResidenceTown 0.47075 0.50280 0.936 0.349264 ResidenceCity 0.33780 0.53923 0.626 0.531105 ‘Age group‘66-75 years 0.14661 0.35010 0.419 0.675433 ‘Age group‘>75 years -0.27777 0.38667 -0.718 0.472621 ‘Cold sausage‘ 1.88051 0.66232 2.839 0.004571 ** ‘Education level‘Medium -0.90318 0.35747 -2.527 0.011602 * ‘Education level‘High -1.50549 0.42215 -3.566 0.000371 *** SexFemale 0.06277 0.23756 0.264 0.791629 ResidenceTown:‘Cold sausage‘ -1.29123 0.69861 -1.848 0.064722 . ResidenceCity:‘Cold sausage‘ -0.12498 0.71799 -0.174 0.861827 ‘Age group‘66-75 years:‘Cold sausage‘ -0.83537 0.55918 -1.494 0.135369 ‘Age group‘>75 years:‘Cold sausage‘ -0.41770 0.58412 -0.715 0.474645 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 (Dispersion parameter for quasibinomial family taken to be 1.038695) Null deviance: 702.15 on 1853 degrees of freedom Residual deviance: 663.69 on 1841 degrees of freedom AIC: NA Number of Fisher Scoring iterations: 6 a) [2 marks] Explain briefly why it is necessary to include the Age group in this model to correctly estimate the effect of eating cold sausage on non-pregnancy-related (NPR) listeriosis. b) [2 marks] Explain briefly why the coefficient estimates for cold sausage above are ap-proximately those of log-relative risks. c) [3 marks] What is the estimated relative risk of NPR listeriosis from eating vs not eating cold sausage amongst Village residents older than 75 years? d) [3 marks] Is there any combination of factor levels for which the estimated relative risk of NPR listeriosis from eating vs not eating cold sausage is smaller than 1? If so, describe any such combination. e) [2 marks] Consider the log-odds ratio of NPR listeriosis amongst Village residents younger than 66 years. What would its standard error be under a binomial regression model with logit link? f) [3 marks] An alternative way to analyse these data is design-weighted estimation, using for instance the svyglm function from the survey package. What weights would you use on each observation to estimate similar relative risks as above? Question 2. [15 marks total] In economics and sociology there are competing theories to explain the higher in-come of people with university degrees. Here are three examples: • The Human Capital theory says that university education improves both specific knowledge about certain topics and some general reasoning and com-munication skills, so that people who gain university degrees become more valuable employees than they would otherwise have been. Some degrees are more valuable than others because you learn more employment-relevant skills doing them. • The Signalling theory says that university education is difficult, and gaining a university degree shows employers that you are more able than other poten-tial employees, even though the education you receive is not valuable to the employer. Some degrees are more valuable than others because they are more difficult and so people who get those degrees have higher average ability. • The Social Stratification theory says that university education functions to show that you come from a relatively affluent or otherwise high-status family, and so you are not the sort of person that the employer likes to discriminate against. Some degrees are more valuable than others because they discrimi-nate more effectively against low-status people. Here is a causal directed graph for relationships between these variables, where the lack of an arrow indicates you may assume there is no effect. a) [6 marks] For each of the three theories, remove as few edges as possible from the graph to give the graph if that theory were the only explanation operating. (you may either draw the graphs or list the edges to be removed) b) [3 marks] Under the Signalling hypothesis, what are the confounding paths from degree to income? c) Suppose that ability was measured on a random sample of people by testing at high school, and status by an interview of individuals and families i [2 marks] If (unrealistically) the measurements were perfectly accurate, give a model that would estimate the (total) effect of learning on income ii [2 marks] Which theory or theories would be supported by a large value of this effect? iii [2 marks] If, instead, the measurements were made with substantial error or un-certainty, what would be the impact on the effect estimate? Question 3. [20 marks total] A company is marketing an expensive new drug to lower cholesterol. In order to justify the price, they want to find a subset of potential users where the effect of the drug is particularly large. They have data on 3,500 people who took the drug in a randomised trial, with two cholesterol measurements before the start of treatment and six measurements after the start of treatment, all at three-month intervals (Yi1...Yi8), with Di = 6/1 (Yi3 + Yi4 + Yi5 + Yi6 + Yi7 + Yi8) − 2/1 (Yi1 + Yi2), the average change, being the preferred summary of the effect. They also have 10,000 binary predictor variables G1, . . . , G10000, with each one measuring whether the person has (1) or does not have (0) a particular genetic variant. Scientists expect that most of the genetic variants will have no effect on cholesterol, but that some will have quite large effects on cholesterol regardless of whether the person is taking the drug (they affect both the pre-treatment and on-treatment values) and others will have quite large effects on the reduction in cholesterol due to taking the drug (they affect only the on-treatment values). a) i [4 marks] What is one technique covered in the course that would be appropriate for finding a model to predict D from the Gs? ii [4 marks] In this context, what are the the advantages and disadvantages of cross-validation in estimating prediction error compared to a training set/validation set split of the data? b) Data is also available on the proportion Xit of their prescribed pills that person i took in the time period leading up to measurement Yit (for t > 2). The researchers are willing to assume that the genetic variables do not affect the proportion of pills that someone takes. i [4 marks] If you simply regress the observations (Yit) t>2 on Xit using lm(), what parts of the output will be correct and what parts will be misleading? ii [4 marks] What is one technique for getting valid inference about the association between X and Y ? iii [4 marks] The researchers are interested in how much the relationship between X and Y varies from person to person. How could you estimate this?
RLG313: Love, Sex, Family Winter 2025 Course Description: This course will explore the multiple and shifting intersections between religion,on the one hand,and love, sex,and family,on the other.We will pay close attention to the way religions construct,control,and shape these social formations in the Americas from the nineteenth through to the twenty-first centuries.We will use case studies to inform our analysis(e.g.,the Moral Majority and the overturning of Roe v.Wade;Mormon polygamy;sex workers in Mennonite country;and Pope Francis'declaration of human-animal kinship as "selfish").We will also attend to the long reach of traditional notions of love,sex,and family and their "translation"into secularized forms(e.g.,media,entertainment,popular culture)for contemporary life.By analyzing a variety of different romantic and kinship arrangements,this course will help make clear the contingency,constructedness,and historical development of these notions,however natural or inevitable they may seem. Learning Outcomes: In this course, you will.. · understand the religious roots of modern formations of gender,sexuality,and kinship,focusing on religions in the Americas/Turtle Island(e.g.,Judaism,Christianity,lslam,Indigenous traditions,and New Religious Movements) · think critically about how these religious roots and their modern formations are used,perpetuated, and transformed in different legal,cultural,political,relational,and ethical contexts · critically analyze and creatively apply the course concepts through close reading,careful research,inquisitive writing,and thoughtful in-class discussions Class Structure and Expectations: This course will be offered in-person at the University of Toronto St.George campus during the Winter semester on Thursdays from 3-5pm in Sidney Smith (SS),room 1083.We will start class at 3:10pm.Each two-hour session will be run as a lecture with opportunities for discussion,small group activities, and individual work throughout.Careful and critical reading of the assigned materials before class is essential. You will not be able to complete the weekly assignments or participate in discussions without a good understanding of the required readings.Students are expected to come to class prepared,which means: bringing the assigned readings with you to class;doing the assigned readings before class;raising questions,responding to peers,and/or providing one's own understandings,responses,or critiques of the readings during our in class discussions.Understandably,you may not be able to closely read all of the assigned materials for a given week but please try to at least be familiar with them and return to them as needed.All course materials are available on Quercus or directly through the U ofT Library Catalogue website.Let me know if you have any issues accessing the materials listed in the weekly schedule(on Quercus). Evaluation: Assignment Portion of Grade Due Date Participation 10% Ongoing Reflections 1-Family Types &Terms(10%) 2-Readings(15%) 25% Monday January 27@11:59pm Monday March 24@11:59pm Family Tree 25% Monday February 24@11:59pm Final Essay or Take-Home Exam 40% Monday April 14@12noon O commit to your choice by April 9@12noon(email Prof. Pasqua &TAs) O exam goes live on Friday April 11 @12nooon Assignment Descriptions: Note:Further instructions and/or rubrics maybe added to each assignmentpage on Quercus.Check Qvercus for updates as due dates approach Participation Students are encouraged to attend class regularly and to be active members of the classroom dynamic. This means being present,actively listening,aswell as asking questions,and/or respondingto prompts raised by the instructor and your peers when appropriate.Participation may take the form of in-class discussions,group work,and writing activities,all of which will be based on the assigned readings and lecture materials.I understand that our class time is limited and it will not always be possible for all voices to be heard,so there will be an additional opportunity to share your thoughts with your classmates on a discussion board that will be open for 48 hours after class.I will post questions that can betaken up and/or students can raise their own questions,comments,and reflections that emerge from the week's materials. Reflections 1-Family Types &Terms This reflection(350-500 words)asks students to briefly describe three different types of families (e.g., intergenerational,nuclear,the Addams Family)or to define three family related terms(e.g.,marriage, divorce,mother,sister).Please make these as different as you can manage and write one paragraph per family type/term.These families might be real or fictional,from any time period,families you personally know (including your own),or families that you've encountered in books or films.The terms can reflect your own experiences,propose alternative/creative/fantastical definitions,or respond critically to the biases, power dynamics,and/or social constructions of more traditional terms.No citations or bibliography are required. 2-Readings This reflection(500-750 words)asks students to choose a set of readings and the primary materials (text,image,video,etc.)discu ssed in one week of the course and write a critical response to the themes,questions,and points of discussion that come out of these texts.The goal is to critically engage the ideas and offer your own perspectives rather than summarizing the readings.References are not included in the word count. In both cases,these are not formal essays:rather they are intended to help hone your ability to think critically and in a focused way. Family Tree Create a family tree. You can draw or use photos, stock images,illustrations,maps,collaging,and/or digital visualization tools,such as Canva,etc.to do so.The goal is to visually explore the people you are connected to and how you relate to them.This can be biological and/or chosen family,or any other form. of kinship relation you can think of(e.g.,pets,food,work,natural environments).Feel free to be creative and use as much or as lile information as you feel comfortable with.Anonymizing or using pseudonyms to protect this data is welcome and encouraged. Then,write a positionality paper (700-1000 words)on what you learned about yourself and these relations.What kinds of family structures are you or they a part of?How does/doesn't religion factor into these family stories and relationships?Use at least one of the course readings to support your discussion. Some research may be required (e.g.,interviewing family members,the history of a nation,religious,or ethnic group).You might also find it useful to build on the ideas explored in the first reflection paper in this essay. Final Essay or Take-Home Exam The last assignment is your choice of a final essay(1800-2300 words)or a take-home exam(1800-2300 words). Students will commit to either writing an essay or the take-home exam by an email sent to the instructor(and cc'ing both TAs)by April 9 at noon. Those writing a final paper are free to choose the topic of the final essay,as long as it fits into the general themes of the class.They must include a bibliography with at least four sources,including two from our class.Take-home exams will be based directly on class readings and discussions and do not require additional research. Students will have 72 hours to complete the take-home exam.
CMPUT 474 Winter 2025 The Nature of Computation Overview This course will investigate the fundamental nature of computation, addressing the basic questions of what is (and is not) computable, what can (and cannot) be computed efficiently, and what consequences follow from certain machine and programming language restrictions. After an introduction to the foundations of computing and its relation to mathematics, the course will investigate finite state automata, regular languages, stack-augmented automata, context free languages, Turing machines, computability, recursive functions, the limits of mathematical reasoning, computational complexity, the classes P, NP and PSPACE, NP-completeness, and the complexity hierarchy. Objectives To understand and appreciate the fundamental nature of computation and the limits of mathematical reasoning. Pre-requisites CMPUT 204 or 275, one of CMPUT 229, EE 380 or ECE 212 and one of MATH 225, 227 or 228, or consent of the instructor. Course Topics The fundamentals of computation and mathematical reasoning, computability, complexity, restricted models of computation. Course Work and Evaluation Four assignments Midterm exam (covers first half of the course) Final exam (covers second half of the course) Course Work Weight Assignment 1 10% Assignment 2 10% Midterm exam 30% Assignment 3 10% Assignment 4 10% Final exam 30% Course Materials Textbook: Introduction to the Theory of Computation, 3rd Edition, by Michael Sipser Book website
Individual Assignment Weightage: 80%, 100 marks Introduction to Computer Science - Part 1 (50 marks) Construct a solution algorithm for the following problems. Your solution should contain: A defining problem A pseudo code algorithm A desk check of the algorithm u Three testcases for each question. Two valid and one error test case Question 1 The Express Delivery Service provides the fastest doorstep collection and delivery within 2-hour in Singapore. The delivery charge is calculated based on the zonal classification in Singapore and there are two main types of zones, one is Central Business District (CBD) with the postal codes starting with 01 to 08, 17 to 19, 22 and 23 and other one is NON-CBD for all other areas other than CBD. The postal code in Singapore contains exactly 6 numeric digits. Below mapping table is used to calculate the delivery charge, Category Delivery Charge Weight Within CBD $15.00 Up to 5kg CBD to NON-CBD / NON-CBD to CBD $20.00 Up to 5kg Outside CBD $25.00 Up to 5kg Design an algorithm that will prompt for and receive the postal code for both pickup and delivery location and calculate the delivery charge and print it. The program will then prompt for “Do you want to calculate for another delivery (Yes/No)?” and is to repeat the processing until “No” is entered. Question 2 An Individual income taxis calculated based on the total taxable income of an individual in a year. The tax rate is defined based on the taxable income table shown below. Taxable Income ($) Rate (%) On the first 20,000 0 On the next 20,000 2.0 On the next 30,000 3.5 On the next 40,000 7.0 Above 110,000 11.5 For example, if John’s taxable income is $65,000 in 2021, his income tax would be $1275 based on the below calculation, John’s Income Tax for 2021 = (20000 x 0%) + (20000 x 2%) + (25000 x 3.5%) = 0 + 400 + 875 = $1275 Taxpayer’s details are maintained in a file that contains National Identity ID, Full Name and Taxable income for the year 2021. Design an algorithm that will read the taxpayer’s details and calculate the income tax for each taxpayer in the file and print the full name and income tax. Question 3 In an organisation, Employee’s bonus is computed based on the company performance and employee performance. Bonus multiplier for employee’s performance rating is defined in the table below. Employee’s Performance Rating Description Bonus Multiplier 1 Require Improvement 0.8 2 Achieved 1 3 Exceed 1.5 4 Exceptional 2 Bonus multiplier for company performance is defined in the table below, Company Performance Bonus Multiplier 105% 1.5 Employee’s bonus is computed using the formula below, Employee’s Bonus = Employee’s Salary X Bonus Multiplier for Employee’s Performance X Bonus Multiplier for Company Performance Employees’ performance details are maintained in a file that contains employee ID, employee name, employee salary, and employee performance rating (1, 2, 3 or 4). Design an algorithm that will prompt for and receive the company performance in percentage and compute the bonus for each employee in the file and print the employee ID, employee name and bonus. Introduction to Computer Science - Part 2 (50 marks) Implement the three questions algorithm in Part 1 into Java programming. Your code should contain appropriate validations and must focus on code optimisation. You need to submit: Three Java code For each question explain (100-150 words) how the logic works. Three sample output screenshots o Two normal and one error testcases
ESE 572: Analog Integrated Circuits Homework 2: Due on 10/09 Be sure to show all your work to receive partial credit. 1. (2 pts) Design a common-source amplifier with active load using the 0.18-μm CMOS device parameters and assuming a supply voltage of 1.8 V. The amplifier should have a power consumption of 1 mW, and again of at least 5 V/V. Ensure all transistors have Veff = 250 mV and L = 0.25 μm. 2. (2 pts) Consider the common-source amplifier shown below. The transistors are sized and (W/L)1 = 6 μm/0.3 μm and (W/L)2 = 4 μm/0.3 μm. Transistor Q1 is biased so that Veff = 200 mV. Using the 0.18-μm CMOS device parameters and assuming a supply voltage of 1.8 V, estimate: a. the power consumption of the amplifier b. the small-signal output resistance of the amplifier c. the small-signal gain of the amplifier 3. (2 pts) The amplifier below is to be designed using devices from the 0.18-μm CMOS process. The amplifier must drive a 3 kΩ load resistor connected between Vout and ground (load resistor not shown below). Ibias = 0.2 mA and all transistors are sized identically with agate length L = 0.25 μm. Choose the gate width, W, to provide a small signal gain of at least 0.8 V/V. You may assume that the body of transistor Q1 is tied to its source so that there is no body effect. 4. (2 pts) Assume that the common-gate amplifier below has a bias current of 0.1 mA and that all transistors have aW/L of 10 μm/0.18 μm. Find the small-signal gain and input resistance of the amplifier. Use the device parameters for the 0.18-μm CMOS process. 5. (12 pts) Assuming all MOSFETS are in saturation, calculate the small signal voltage gain of each circuit below (λ≠0, γ = 0). 6. (3 pts) A NMOS cascode amplifier with active load is shown below. It is realized using 0.35 μm CMOS devices. VDD = 3.3V, Ibias = 100 μA, (W/L)1,2,5,6 = 10 μm/0.5μm and (W/L)3,4,7,8 = 10 μm/0.5μm a. What is the small signal gain and output resistance? b. What is the total power consumption of the circuit? c. Estimate the range of output voltages over which all transistors remain in saturation. 7. (2 pts) Modify the design in problem 6 to double the small signal voltage gain without changing the power consumption or available output voltage swing. 8. (4 pts) The differential gain circuit below is perfectly symmetric. Assume all transistors are kept in saturation and that γ = 0. a. Draw the equivalent half-circuit. b. Derive an expression for the circuit’s small-signal differential gain in terms of the transistor small-signal parameters: gm, ro, etc. c. Derive an expression for the circuit’s small-signal output resistance in terms of the transistor small-signal parameters. d. Find the common mode gain and CMRR of the circuit in terms of the transistor small signal parameters if the current source Ibias has an output resistance of RSS. 9. (1 pt) The first step in designing any analog system is to characterize the devices offered in the fabrication technology. You will be using a 45 nm CMOS process. As a first step, simulate the following graphs for MOSFET transistors in Cadence. ID vs. VDS for 0
CMPUT 331, Winter 2025, Assignment 1 Before beginning work on this assignment, carefully read the Assignment Submission Specifications posted on Canvas. Introduction The Caesar Cipher does not offer much security as the number of keys is small enough to allow a brute-force approach to cryptanalysis. However, with some modifications, it can be greatly improved. In this assignment, you will modify the Caesar Cipher implemented by the textbook (“caesarCipher.py”) to improve its encryption strength. You will produce five files for this assignment: • a1p1.py, a1p2.py, a1p3.py: python solutions to problems 1, 2, and 3 respectively • a1.txt: written responses to problem 4 • a README file (README.txt or README.pdf) Submit your files in a zip file named 331-as-1.zip. Problem 1 (2 Marks) For this problem, modify the provided skeleton file, “a1p1.py”. You may use the provided “caesarCipher.py” file as reference to implement three functions named “get map”, “encrypt”, and “decrypt”. The function “get map” takes one argument: • letters: a string of letters such as “AaBbCcDd...”, where each letter corresponds to its shift amount 0, 1, 2, 3, 4, 5, ..., 51 The “get map” function plays a crucial role in establishing the connections between letters and their respective shift amounts. It should return two dictionaries: the first mapping each letter to its corresponding shift, and the second allowing the reverse mapping of shifts to their respective letters. These dictionaries are essential references for the other functions, for example, enabling efficient querying of shift amounts based on the given letter. While the default argument value is “AaBbCcDd...”, your implementation should seamlessly accommodate others, such as “ZzYyXxWw...”. These variations will be tested during the assignment evaluation. Example output of “get map”: char_to_index = {‘A’: 0, ‘B’: 1, ‘C’: 2, ...} index_to_char = {0: ‘A’, 1: ‘B’, 2: ‘C’, ...} The “encrypt” and “decrypt” functions take two arguments: • message: plaintext string to encrypt • key: one of the 52 uppercase/lowercase letters corresponding to the shift amounts, for instance, A = 0, a = 1, B = 2, b = 3, C = 4, c = 5... etc. The “encrypt” function should return the message string such that each letter has been caesar-shifted by the key amount. Non-letters characters (such as spaces or punctuation) are to be appended to the resulting string unmodified. The “decrypt” function should reverse the shift performed by encrypt and return the original plaintext. The following demonstrates invocation sequences that should run without error and produce identical output: python3 -i a1p1.py >>> test(); encrypt("AaBbCcDd...", "x") ‘xYyZzAaB...’ >>> test(); decrypt("xYyZzAaB...", "x") ‘AaBbCcDd...’ >>> test(); encrypt("Welcome to 2025 Winter CMPUT 331!", "x") ‘tCJAMKC RM 2025 tGLRCP zjmrq 331!’ >>> test(); decrypt("tCJAMKC RM 2025 tGLRCP zjmrq 331!", "x") ‘Welcome to 2025 Winter CMPUT 331!’ >>> test(); encrypt("This is Problem 1 of Assignment 1.", "y") ‘rGHR HR nQNAKDL 1 NE yRRHFMLDMS 1.’ >>> test(); decrypt("rGHR HR nQNAKDL 1 NE yRRHFMLDMS 1.", "y") ‘This is Problem 1 of Assignment 1.’ Problem 2 (2 Marks) One weakness of the Caesar Cipher comes from the fact that every letter is enciphered the same way. If the first letter of the message is shifted forward by three positions, every letter is shifted forward by three positions. Let’s start by fixing this flaw. Make a copy of your “a1p1.py” code named “a1p2.py” and modify it such that: 1. The first letter of the message is shifted according to the chosen key, exactly as before (i.e. for encryption a key of “b” shifts the first letter up by 3). 2. All remaining letters are shifted using the previous letter of the message (plaintext) as a key. If the previous character is punctuation, use the letter before it. python3 -i a1p2.py >>> test(); encrypt("AaBbCcDd...", "y") ‘yabcdefg...’ >>> test(); decrypt("yabcdefg...", "y") ‘AaBbCcDd...’ >>> test(); encrypt("Welcome to 2025 Winter CMPUT 331!", "y") ‘uaQORBR YI 2025 keWHYW tOBJN 331!’ >>> test(); decrypt("uaQORBR YI 2025 keWHYW tOBJN 331!", "y") ‘Welcome to 2025 Winter CMPUT 331!’ >>> test(); encrypt("This is Problem 2 of Assignment 1.", "x") ‘qaQB BB hgGQNQR 2 BU fsLBPUARSH 1.’ >>> test(); decrypt("qaQB BB hgGQNQR 2 BU fsLBPUARSH 1.", "x") ‘This is Problem 2 of Assignment 1.’ Problem 3 (2 Marks): Now make another copy of your “a1p1.py” code and name it “a1p3.py” (Note: copy a1p1.py and not a1p2.py). Modify your encrypt and decrypt functions so that the key is a string instead of a single letter. We will call this string the keyword. Modify your code so that it enciphers a message as follows: 1. If the keyword is n characters long, then the 1st, 2nd, 3rd..., and nth letters of the message are enciphered using the 1st, 2nd, 3rd..., and nth letters of keyword respectively. You may assume that the keyword only contains upper and lowercase letters. If the message is shorter than the keyword then the extra characters in the keyword are to be ignored. 2. The rest of the string is enciphered using the above method except as if the (n+1)th character is the beginning of the string. Note that non-letter characters (such as spaces, punctuation, and numbers) will not be encrypted. When encountering these characters, the encryption process will simply skip them and resume with the next letter. Here is an example: encrypt("Welcome to 2025 Winter CMPUT 331!", "XxYyZz") It should work as follows: XxYyZzX xY yZzXxY yZzXx Welcome to 2025 Winter CMPUT 331! TCjBnMb Rm 2025 uhNqCp aLoRq 331! In this example, the letters above the plaintext represent the key used to encrypt the plaintext into the ciphertext. Spaces indicate that no key is applied. Specifically, “X” is the key used to encrypt the first letter “W”. Numbers, such as “2025”, and punctuation marks, such as “!”, are not encrypted, so no key is applied to them. python3 -i a1p3.py >>> test(); encrypt("AaBbCcDd...", "XxYyZz") ‘XYZABCAB...’ >>> test(); decrypt("XYZABCAB...", "XxYyZz") ‘AaBbCcDd...’ >>> test(); encrypt("Welcome to 2025 Winter CMPUT 331!", "XxYyZz") ‘TCjBnMb Rm 2025 uhNqCp aLoRq 331!’ >>> test(); decrypt("TCjBnMb Rm 2025 uhNqCp aLoRq 331!", "XxYyZz") ’Welcome to 2025 Winter CMPUT 331!’ >>> test(); encrypt("This is Problem 3 of Assignment 1.", "ZYXzyx") ‘SffS HQ OplBKCl 3 mc zRQhekMDLs 1.’ >>> test(); decrypt("SffS HQ OplBKCl 3 mc zRQhekMDLs 1.", "ZYXzyx") ‘This is Problem 3 of Assignment 1.’ Problem 4 (4 Marks) For this problem, consider the encryption strength of the original caesar cipher and each of your modified ciphers. Some of the ciphers, multiple valid keys that result in plaintext being enciphered in the same way. Please record your answers in the provided file “a1.txt” for the following questions. 4a: How many distinct keys, keys which each produce different ciphertexts for the same message, do each of the four ciphers have? 4b: Is the problem 2 cipher stronger than the original caesar cipher? 4c: Will encrypting the space help address the weaknesses of the Caesar cipher? Note: Please strictly follow the template provided in a1.txt. Any change in the template might result in a potential mark deduction.
CHEN 4010 - Exam 2 Nov 6, 2024 Time: 60 minutes Total Points: 100 State your assumptions and demonstrate your reasoning and analysis clearly. No points will be given for just writing down the result. 1. Use the method ofFrobenius to find the solution of the following equation: (35 points) 2. Consider a pipe through which a fluid is flowing carrying a solute A. The solute balance for species A is given as: where v0 is the constant, uniform. (plug) fluid velocity profile, DA is solute diffusivity in the fluid, and CA is the solute molar composition. There is radial diffusion but no axial diffusion of A. The solute flux at the fluid-wall interface is given as: where KOLis the overall transport coefficient. The inlet solute composition is C0 at the axial position z=0. Show that the average composition CA obeys the analytical solution at position z=L: where Bi = K0LR/DA and the eigenvalues are obtained from λnJ1 (λn ) = BiJ0 (λn ) (30 points) 3. Consider is an electric wire of circular cross section with radius R and electrical conductivity ke, ohm-1 cm-1. Through this wire there is an electric current with current density I amp/cm2. The transmission of an electric current is an irreversible process, and some electrical energy is converted into heat (thermal energy). The rate of heat production per unit volume is given by the expression The quantity Se is the heat source resulting from electrical dissipation. We assume here that the temperature rise in the wire is not so large that the temperature dependence of either the thermal or electrical conductivity need be considered. The surface of the wire is maintained at temperature T0. Please determine (i) the radial temperature distribution within the wire, (ii) maximum temperature rise, and (iii) heat outflow at the surface. (35 points)
FINS5510 Personal Financial Planning Overview Financial Plan Date* Assignment Due Date 1pm Friday Week 4 (31 Jan 2025) Release of Results 5pm Friday Week 7 (14 Feb 2025) *All times are based on Sydney time The purpose of this assignment is to help you to develop a detailed financial plan that will act as a financial roadmap for the rest of your life. Each section of your financial plan provides you with the opportunity to reflect deeply on the theory covered in the course and to make practical, specific and detailed application of that theory to your expected future life stages. You should work on your financial plan gradually during the term as you cover each Unit. You should use the Microsoft Word template provided and submit the final document in PDF format. There is no word limit for this assignment but most submissions are between 3,000 and 9,000 words. This is an individual assignment. Copying the work of another student, basing your financial plan on another student’s work, asking anyone else to write your financial plan, obtaining assistance from an Artificial Intelligence computer program, providing a copy of your financial plan to another student or posting your financial plan on a website is academic misconduct and will result in a fail grade being awarded for this course. Weight The Financial Plan assignment is worth 50% of your assessment for this course. Backup your work You should be writing your financial plan assignment gradually over the term after you have completed each Unit. You also need to plan for a situation in which the file may become corrupted or your device is damaged. Please create regular copies of your work and place them into a ‘Backups’ folder. Make sure this folder is synchronisedonto a USB key or a cloud-based storage solution such as OneDrive or Dropbox (or an equivalent service in China for students who cannot access these services). Note that UNSW provides you with a free Onedrive account. Loss of data or a damaged device does not constitute grounds for Special Consideration. Note that if you have saved your file in your UNSW Onedrive account, you should be able to restore a backup from your file history. Here is a linkon how to do this. If you lose your file and are unable to restore from a backup, a standard late penalty of 5 marks (out of 100) per day will apply. Technical problems with your file or device does not represent grounds for a Special Consideration extension. Late Penalties Late submission will incura penalty of 5% per day or part thereof (including weekends) from the due date and time. An assessment will not be accepted after 5 days (120 hours) of the original deadline unless special consideration has been approved. An assignment is considered late if the requested format, such as hard copy or electronic copy, has not been submitted on time or where the ‘wrong’ assignment has been submitted. The late penalty applies to your score for the financial plan (not the maximum possible score). For example, if your raw score is 70/100 and the plan is submitted 2 days late, a 10 mark penalty will apply and so your score would be reduced to 60/100. Note that there is a small ‘grace period’ of a few minutes after the submission time to allow for slow internet connections or slow website performance. No penalty will apply if the submission is within this ‘grace period’ . Please do not email me asking if your submission falls within this grace period. Since you are supposed to be working on this assignment gradually each week as the course progresses, the maximum period of special consideration that will be granted for this assessment (for any reason) is 7 days from the original due date. Also, the maximum extension that will be granted for Equitable Learning Plans will also by 7 days from the original due date. Any submissions received after this will automatically be awarded a score of zero. Special Consideration Special consideration will only be granted in exceptional cases. You are responsible for developing your financial plan gradually as you work through each Unit of the course materials. You should work on your financial plan as you cover each Unit and avoid leaving it until last minute. You are responsible for completing your financial plan well before the due date/time to allow for unexpected circumstances or illness. Being ill during the last week before the date of submission will not normally constitute grounds for special consideration. Loss of data or a damaged device does not constitute grounds for Special Consideration. You are responsible to regularly backup your work and synchronise it onto a cloud-based storage solution (such as OneDrive or Dropbox). If special consideration is granted, the maximum extension that will be granted is 7 days from the original due date. Any financial plans received more than 7 days from the original due date will automatically be awarded a score of zero. An application for Special Consideration together with supporting documentation must be submitted online within 3 working days of the due date. The process for applying for special consideration is here:https://student.unsw.edu.au/special-consideration No Short Extensions The university has recently introduced the option for students to apply for a short extension without providing documentation (such as a medical certificate). This assessment task is not eligible for a short extension without documentation. Individual Assessment This is an individual assessment. You are permitted to discuss the contents of this assessment with your family, a spouse or partner. However, all written work, research and supporting calculations must be your own work. Seeking assistance with your written work or financial modelling constitutes academic misconduct. Seeking assistance from Artificial Intelligence computer programs also constitutes academic misconduct. Providing assistance to any other students also constitutes academic misconduct. Copying or paraphrasing the work of any other student (from current or previous terms) constitutes academic misconduct. Copying the work of another student and then changing the details to reflect your situation and strategies constitutes academic misconduct. Using another student’s financial plan as a ‘reference’ for you while you complete your own financial plan is also academic misconduct. Posting a copy of your assignment on a website is academic misconduct (except for submitting your assignment on the course website under the appropriate submission link). If another student approaches you for assistance, please note the time, date and details of the incident and email the details to meat [email protected]. UNSW has no tolerance for students who are dishonest or seek to obtain an unfair advantage over other students. Academic misconduct is a serious offence. It can result in zero being awarded for this assessment, a failure grade for the course and/or removal from the University. No Artificial Intelligence Using Artificial Intelligence programs or services is not permitted in this assessment. There are two exceptions to the above ‘no use of Artificial Intelligence’ rule. Students for whom English is their second language are allowed to use Artificial Intelligence programs (such as Google Translate) to translate from their native language into English or to translate from English to their native language. Students with writing difficulties are allowed to use Artificial Intelligence programs (such as Grammarly) to help correct their spelling and grammar. Template You should use the Microsoft Word template document provided under the ‘Financial Plan’ section of the course website. Do not use another student’s financial plan as your template. Note that as a student at UNSW, you have access to the full suite of Microsoft Office 365 applications. More information about accessing this software is provided below. Software Your Learning Community Report should be submitted as a Microsoft Word document. All students at UNSW have access to the full suite of Microsoft Office 365 products for free (on both Windows and Mac). This includes downloadable versions of the entire Microsoft Office suite to 15 devices (5 desktops, 5 tablets and 5 mobiles). The steps for downloading the latest version of MS Office are as follows: 1. Go to https://login.microsoftonline.com 2. Login with the same zPass that you use for Moodle using the ‘[email protected]’ version of your UNSW student email. For example: [email protected] 3. Click the ‘Install apps’ button 4. Choose ‘Office 365 apps’ . For students who use the Linux operating system, you should use a word processor that accepts the Microsoft Word document format (for the template) and export to PDF format. Exporting to PDF You are required to submit your assignment using the Microsoft Word template provided in PDF format. Using Microsoft Word, you can export to PDF format using the following process: 1. Select the ‘ File’ menu at the top left of the screen. 2. Select ‘ Export’ from the left panel. 3. Select ‘Create PDF/XPS Document’ 4. Press the ‘Create PDF/XPS’ button. 5. Check the file name and location is correct. 6. Press ‘ Publish’ button. Formatting For headings and body text, please use the styles in the Microsoft Word template provided. Fonts: Please only use either Arial (PC) or Helvetica (Mac) fonts. Students with dyslexia who find these fonts difficult to read may use Times New Roman. Font sizes: Please use font size 11 pt for your body text. Line spacing: Use the default in the Microsoft Word Template provided (1.08 lines). Styles: Use the styles provided in the Microsoft Word Template provided. File format: You should submit your file in PDF format. Filename: Please use the filename following the format ‘zID Plan’ . If your zID is z999999, you should name your document ‘z999999 Plan’ . For tables, diagrams, captions, footnotes and other minor formatting elements, you can choose your own formatting and styles. Please make sure they are easy to read. Table of Contents You should update the page numbers in the table of contents before submitting the final version of your financial plan. This can be done as follows: 1. User your mouse to select the table of contents on page 1 2. Go to the ‘References’ tab on the command bar at the top of Microsoft Word 3. Select ‘Update Table’ under the ‘Table of Contents’ group on the Ribbon. 4. Select ‘Update Page Numbers Only’ to only update the page numbers or select ‘Update Entire Table’ to also update your Headings.
CSE 101 Introduction to Data Structures and Algorithms Programming Assignment 8 In this project you will re-create the Dictionary ADT from pa7, but now based on a Red-Black Tree. Red black trees are covered in Chapter 13 of the text, and will be discussed at length in lecture. All relevant algorithms for RBTs (and BSTs) are posted on the webpage under Examples/Pseudo-code. Aside from having a RBT as its underlying data structure, your Dictionary ADT will have only slight changes to its interface. The recommended approach for this project is to just copy Dictionary.cpp from pa7 and make the necessary changes, but you can start from scratch if you feel it is necessary. The header file Dictionary.h is posted in Examples/pa8. It's most significant difference from the header file for pa7 is a new field in the Node class of type int called color. Other than that, the only difference is a new section for RBT helper functions. Although these functions are listed as optional, and you may make changes as you like, you should consider them as absolutely necessary for this project. Feel free to add other helper functions if you find it useful. You will create two top-level clients in this assignment. The first will be called Order.c, with the same specifications as in pa7. No changes should be necessary from that project. Again, several pairs of input- output files are given in Example/pa8, along with a random input file generator. Note that the input files are identical to those of pa7, but the paired outputs are different. In particular, the output file sections giving all keys in a pre-order traversal are different, since the trees are now balanced by the RBT algorithms. The output is also different in that function preOrderString() indicates which keys are stored in red Nodes. The second top-level client will be called WordFrequency.cpp. It will read in each line of a file, parse the individual words on each line, convert each word to all lower case characters, then place it (as key) in a Dictionary. Individual words in the input file maybe repeated however. The number of times a given word is encountered (its frequency) will also be stored (as value) in the Dictionary. Thus, as your program is reading in words, it should first check to see if the word (key) is already present, using contains(). If it is a new word, add it using setValue(). If it already exists, increment the corresponding value by calling getValue(). Recall that the getValue() function returns a reference to a value, which can then be used to alter that value. Use the example FileIO.cpp posted in /Examples/C++/FileIO as the starting point for WordFrequency.cpp, since much of what you need is already there. The program FileIO.cpp contains a string variable called delim, which is initialized to be a single space. string delim = " "; This is the delimiter used by the string functions find_first_of() and find_first_not_of() to determine which characters belong to tokens, and which do not. Thus FileIO.cpp tokenizes the file around spaces. Your program WordFrequency.cpp will instead tokenize around a larger set of characters. The words in our file will be substrings that contain only alphabetic characters. To accomplish this, you can reset delim as follows. string delim = " t\" ',/?;:[{]} |`~!@#$%^&*()-_=+0123456789"; So, to parse the input file, remove all whitespace, punctuation and special characters. What's left are the words to be placed in the Dictionary, along with their frequencies. Once all the words from an input file are placed in the Dictionary, along with their frequences, your program WordFrequency.cpp will print the Dictionary to the output file. You will find two very large text files here called Shakespeare.txt (containing the complete works of William Shakespeare) and Gutenberg.txt (containing several English language texts provided by Project Gutenberg). You will also find the corresponding output files called Shakespeare-out.txt and Gutenberg-out.txt. Test WordFrequency.cpp on these files. Also, as before, a test client called DictionaryClient.cpp is posted in Examples/pa8. This program is similar to the pa7 version, but it has different output, which you can find in DictionaryClient-out. You should still consider it a weak test of the Dictionary ADT, and as always, design your own tests. Altogether this should be a straightforward assignment, especially if pa7 went well for you. Submit the following 7 files in the usual manner before the end of the grace period. README.md Written by you, a catalog of submitted files and any notes to the grader Makefile Provided, alter as you see fit Dictionary.h Provided, you may alter the "helper functions" sections, but nothing else Dictionary.cpp Written by you, the majority of work for this project DictionaryTest.cpp Written by you, your test client of the Dictionary ADT Order.cpp Written by you, a client for this project, unchanged from pa7 WordFrequency.cpp Written by you, a client for this project
Final assessment MCS 300 Debates in Global Media Essay (2000-2500 words, Individual) To be submitted by 1pm Monday, Week 12, January 20nd, 2025 Term 1, 2024-2025 Brief In your presentation assignment, you practiced how to construct and frame. a case study, and you were asked to experiment with changing your angle and framing. Building on this exercise, the final essay asks you to conduct a comparative analysis whereby you compare two cases. In week 2, we discussed the advantages of comparative research such as de-westernizing media studies and developing theory. We also discussed some difficulties around finding terminology and avoiding essentialisms. Keeping these important reminders in mind, choose two phenomena that you can construct as somehow equivalent and hence comparable cases, whereby you comment on similarities and differences alike. You are encouraged to get out of your cultural comfort zone (even if choosing a Chinese-US comparison would seem the most obvious) and engage with different regions but also remain mindful of the internal differences within those regions themselves in terms of ethnicity, class, gender, and urban/rural divides, et cetera. The two cases need to allow you to discuss at least three concepts from our module readings (key and/or recommended). Your research can be based on any method for data collection that you find appropriate but also the use of secondary literature (existing studies) is allowed (with proper referencing). Doing original research requires an Ethics Form. if human subjects are involved (i.e., interview, focus group, social media posts by users who do not have the expectation of public scrutiny). As this is only a short essay, you need to consider what would be the proper size of the study you conduct. In other words, you are not expected to undertake a huge amount of empirical research but to frame. your case in a pragmatic and doable way. Consultation The lecture in week 10 will review comparative methods and other research skills. Seminars in week 9 and 10 are reserved for sharing and consultations about your final essay. Please get signed up with your tutor to share your ideas and ask questions. If you desire further personal consultation, please be reminded that the tutors Charlotte Curle and Emily Hoyle are only available until December 13 and Rolien is available until December 15. Learning Outcomes The assessment is designed to develop your academic skills as you move on to prepare your dissertation in Lent term. These skills include: a) How to select a case study that can illustrate and speak to the relevant themes/theories b) How to gauge the appropriate focus of the case study in relation to the scale of the essay c) How to develop research questions in relation to the case study and theory d) Critical analysis of case study through application of theory Think of this essay as an encouraging environment to practice research design on a small scale and to hone those skills before taking them to the larger dissertation project. Checklist · Have you formulated a research question(s) that is analytical and not just descriptive? · Have you explained the rationale for your project: why is it interesting and important? · Have you reflected on the comparison that you make and avoided unnuanced essentialisms? · Have you critically discussed your case study in relation to AT LEAST 3 theories / concepts learnt on the module? · Is the scope of your argument reasonable and proportionate to the evidence that you can provide? · Does your essay have a focus and a coherent argument that answers the research question(s)? · Have you taken the time to contextualize the phenomena you discuss so that a reader who is unfamiliar with the context can understand your work? Rubric Outstanding- Very Good Key characteristics Good-Satisfactory Key characteristics Passible Key characteristics Research question Introduces a research question that is analytical in nature; that is highly relevant to the module; and that addresses an original comparison. Introduces a research question that is somewhat analytical in nature but could be improved; that is relevant to the module; that addresses a more familiar and less nuanced comparison yet still covers new aspects. Introduces a research question that is not well articulated yet; that is somewhat relevant to the module; that addresses a less nuanced comparison while covering few new aspects. Content Knowledge and Conceptual Clarity Demonstrates exemplary knowledge of the content and concepts; demonstrates the ability to apply concepts in an original way; Reflects meaningfully on the comparison. Demonstrates good knowledge of the content and concepts; demonstrates the ability to apply concepts in a meaningful way with original elements; Reflects on the comparison. Demonstrates some knowledge of the content and concepts; the application of concepts is nascent but remains underdeveloped; Does not specify the comparison. Argumentation and Communication Clearly and convincingly communicates answer to the research question; Essay is organized in an optimal way; Referencing is carefully executed; The author’s “voice” comes through and guides the reader. Consistently communicates answer to the research question; Essay demonstrates logical organization and is readable; Referencing is carefully executed; The author’s “voice” is emerging. Communicates a basic answer to the research question; Disorganized approach to the question; some obstacles to the reader's comprehension; Referencing is lacking proper care; The author’s “voice” is barely detectable. Framing and soundness of claims Cases are framed in a way that enables sound argumentation and rich evidence. Cases are framed in a way that enables overall logical argumentation and evidence, with some slippages. Cases are not framed in a way that enables overall sound enough argumentation, while there is some evidence.
Homework 1 GSND 5345Q, Fundamentals of Data Science Due Friday, January 17th, 2025 Please answer the following questions and put your answers in a Word Document or PDF. You will be able to submit your document under the Assignments tab on Canvas. Homework Questions, Part 1: Ethical Considerations (50 points) Instructions: For each of the following questions, provide a thoughtful (but brief) response that demonstrates your understanding of ethical considerations in data science. Your answers should reference relevant principles, frameworks, or real-world examples where applicable. Aim for clarity, directness, and critical thinking. For the examples provided with each question, discuss how they relate to the broader ethical challenges posed by the topic. Be sure to support your arguments with evidence or reasoning, and consider multiple perspectives where appropriate. 1. How do we address bias in data science models? Example: What steps can be taken to mitigate biases in healthcare AI? 2. What are the limits of informed consent in big data applications? Example: How do we ensure consent is meaningful in large-scale social media data use? 3. How can transparency and interpretability be balanced with complexity? Example: Should there be mandatory explainability for AI systems impacting financial decisions? 4. How should organizations disclose the use of AI tools like ChatGPT? Homework Questions, Part 2: Ethics Case Studies (50 points) Instructions: For each case study below, research the scenario described and summarize: 1. The ethical issues involved — Identify and explain the key ethical dilemmas or problems in each case. 2. The lessons learned — Discuss the takeaways or improvements that could be made to prevent similar issues in the future. Your answers should be detailed and include references to relevant ethical principles, real-world consequences, and potential solutions. Where applicable, consider how laws, policies, or best practices could address the issues. The comments below provide partial answers; use them as guidance but provide expanded detail in your own words. Case Study 1: Biased Algorithms Description: Amazon’s AI hiring tool showed bias against female candidates. • Ethical Issues: Algorithm trained on historical data reflecting gender bias. • Lessons Learned: Importance of diverse and unbiased training datasets. Case Study 2: Data Privacy Breach Description: Cambridge Analytica’s misuse of Facebook data. • Ethical Issues: Unauthorized use of personal data for political campaigns. • Lessons Learned: Strengthening data consent mechanisms and user awareness. Case Study 3: Facial Recognition Technology Description: Use of facial recognition by law enforcement. • Ethical Issues: Privacy invasion and racial bias in accuracy. • Lessons Learned: Need for strict regulations and ethical guidelines. Case Study 4: Redlining Description: Historically, mortgage lenders once widely redlined core urban neighborhoods and Black-populated neighborhoods in particular. • Ethical Issues: Discrimination and perpetuation of economic inequalities through biased practices. • Lessons Learned: Need for equitable lending practices and proactive measures to address systemic bias.
ECE 785 Capstone in Cyber-Security or Artificial Intelligence Catalog Description Comprehensive M.S. capstone project in Cyber-Security or Artificial Intelligence. Course Information This course is designed as the capstone project course for M.S.E.C.E students who are completing the Cybersecurity or Artificial Intelligence track. Students are expected to propose a project they are interested in working on or seek out projects related to Cybersecurity or Artificial Intelligence from faculty. Course Outline 1. Identify a project and a project supervisor a. You can propose your project idea OR b. You can seek out a project from a faculty member c. You project supervisor will b the faculty you are working with on your projector the course instructor if you did not find another faculty supervisor 2. Write up a Project Proposal 3. Meet with your project supervisor regularly during the semester 4. Submit bi-weekly progress reports a. These can be meeting notes for the bi-weekly meetings 5. Submit your project as a posted or demo for Computing Day (late April) 6. At the end of the semester, you will need to: a. Present your project b. Submit a final report or paper on your project c. Have your project supervisor send a final grade to the course instructor Deliverables 1. Project Proposal 2. Project Status Reports (bi-weekly) 3. Computing Day Poster 4. Project Presentation 5. Project Final Report/Paper
TU2983: Advanced Databases Individual Assignment 3 Transaction Form. and Software Installer IMPORTANT NOTE: This assignment continues from the work you have done in “Individual Assignment 1 & 2”. You are required to re-use same Visual Basic Project that you created for “Individual Assignment 1 & 2”, or use an improved version of the same Visual Basic Project for “Individual Assignment 1 & 2”: 1. You will use the same topic that was previously assigned to you in “Individual Assignment 1”. 2. All windows forms that you previously created for “Individual Assignment 1 & 2” must be used, or be improved. 3. The database file that you previously created for “Individual Assignment 1 & 2” must be used, or be improved. 4. The pictures that you have previously collected for “Individual Assignment 1 & 2” must be used. 5. You will add new windows forms required for this assignment to your previous Visual Basic Project. 6. Evaluation of “Individual Assignment 3” will only be made on the following Tasks: ASSIGNMENT 3 will be evaluated using your final program that is installed using your SETUP.EXE installer only, and no longer through Visual Studio. TASK 1: Build a form. for the user to MAKE ORDERS for multiple products. 1. The ORDER for multiple products must be made in a single form, using a single ORDER ID. 2. The MAKE ORDER form. must show/display calculated values such as SUB-TOTALS and TOTALS. However, these calculated values do not need to be stored in the database. 3. The ORDER for products must be processed as a TRANSACTION. 4. When entering data into the MAKE ORDER form, all items in the order must be successfully COMMITed into the database, or ROLLED-BACK completely if there is an error. IMPORTANT: Your evaluator will test ACID compliance of your ORDER TRANSACTION by deliberately causing an error when entering data for the order. FIGURE 1: Approximate appearance of your MAKE ORDER and VIEW ORDER form. TASK 2: Build a form. that the user can use to VIEW existing ORDERS. 1. This VIEW ORDER form. is only used to look at existing ORDERS already in the database, and to look at the list of products ordered in each ORDER. 2. Both your MAKE ORDER form. and VIEW ORDER form. should look something like FIGURE 1 (it does not need to be identical). → TASK 3: Create an INSTALLER for your program and a Splash Screen (i.e. main product title screen) 1. Use a “Setup and Deployment” project in Visual Studio to create the installer. IMPORTANT: “Express” versions of Visual Studio do not have the “Setup and Deployment” project option. 2. Make sure there is a Desktop shortcut for executing your installed program. 3. Design your Splash Screen appropriately to suit your individual topic. You will also be evaluated based on the aesthetics and appearance of your Splash Screen. 4. Make sure your FULL NAME, MATRIC NUMBER and SHOP/PROJECT NAME are labeled on the Splash Screen. TASK 4: Create a *.ZIP/*.RAR containing your project’s contents, and upload it to UKMfolio (*see NOTE below). 1. Compress the following folders in a single *.ZIP/*.RAR file: a. One folder labelled as _SOURCECODE, that contains you entire VB project source code, database, and pictures. b. One folder labelled as _INSTALLER, that contains your program’s SETUP.EXE file and installer (*.msi) files (i.e. everything in the ‘Debug’ directory of your “Setup and Deployment”). 5. *** IMPORTANT ***: Your *.ZIP/*.RAR must not exceed 125mb (Megabytes). If it does exceed 125mb, you need to reduce the resolution of all your pictures, in order to reduce their file size. 6. Upload your *.ZIP/*.RAR file to UKMfolio, at the Lab Assignment 3 Submission Link.
F24 ECE 551 HW04, Due 11PM Thu. Oct. 03 Pr. 1. (a) Prove the vec trick , i.e., for A ∈ F P ×M, X ∈ FM×N , B ∈ F N×Q. : vec(AXB) = (B⊤ ⊗ A)vec(X), (1) where vec(.) is the operator that stacks the columns of the input matrix into a vector, and ⊗ denotes the Kronecker product. Here we really mean transpose B⊤ even if B is complex valued! (b) Suppose A, X, and B are all N × N dense matrices. Determine how many scalar-scalar multiplications are needed for the LHS vec(AXB) and compare to the number for the RHS (B⊤ ⊗ A)vec(X). Which version uses fewer? One use of (1) is analyzing the 2D discrete Fourier transform. (DFT), which may be explored in later HW. Pr. 2. (Projection onto orthogonal complement of a 1D subspace) (a) Determine an orthonormal basis for the orthogonal complement of the span of the vector (b) Determine an orthonormal basis for the orthogonal complement of the span of the vector (c) Determine (by hand, no Julia) the projection of the vector onto the orthogonal complement of span({z}) without using the orthonormal basis you found in the previous part. Hint. You may want to derive the general mathematical expression needed in the next part first, and then use that expression to solve this problem by hand. (d) Write a function called orthcomp1 that projects an input vector y onto the orthogonal complement of span({x}) for an (nonzero) input vector x of the same length as y. For full credit, your final version of the code must be computationally efficient, and it should be able to handle input vectors of length 10 million without running out of memory. Your code must not call svd or eig or I and the like. This problem can be solved in one line with elementary vector operations. In Julia, your file should be named orthcomp1.jl and should contain the following function: """ z = orthcomp1(y, x) Project `y` onto the orthogonal complement of `Span({x})` # In: * `y` vector * `x` nonzero vector of same length, both possibly very long # Out: * `z` vector of same length For full credit, your solution should be computationally efficient. """ function orthcomp1(y, x) Email your solution as an attachment to [email protected]. Test your code yourself using the example above (and others) before submitting to the autograder. Be sure to test it for very long input vectors. (e) Submit your code (a screen capture is fine) to gradescope so that the grader can verify that your code is computa-tionally efficient. (The autograder checks only correctness, not efficiency.) Pr. 3. Let A be a diagonal matrix with real entries that are distinct and nonzero. Let x be a vector with all nonzero entries. (a) Determine how the eigenvalues of the rank-1 update B = A + xx′ are related to the eigenvalues of A and the vector x. Your final expression must not have any matrices in it. Hint. They will be implicitly related (not in a closed form. expression) as the solution of an equation involving the eigenvalues of A and the elements of x. Hint: G + H = G(I + G−1H) if G is invertible, and see HW1. (b) Use your solution to the previous part to determine the eigenvalues of B when Hint: Julia’s Polynomials.jl package can be useful here. Pr. 4. (a) Show that f(x) = ∥Ax − b∥2 is a convex function on R N when matrix A has N columns. Hint. Use the triangle inequality: ∥x + y∥2 ≤ ∥x∥2 + ∥y∥2 and the equality 1 = α + (1 − α). (b) Show that the largest singular value of a matrix, i.e., the function σ1(X) : FM×N 7→ R, is a convex function of the elements of the M × N matrix X. Hint. Use the fact that σ1(X) = max∥u∥2=1 ∥Xu∥2. Also use these two basic properties of maxima / suprema: f(t) ≤ g(t) ⇒ maxt f(t) ≤ maxt g(t) and maxt (f(t) + g(t)) ≤ (maxt f(t)) + (maxt g(t)). (c) (Optional.) Prove or disprove that the second singular value of a matrix, i.e., the function σ2(X) : FM×N 7→ R, is a convex function of the elements of the M × N matrix X when min(M, N) ≥ 2. Pr. 5. For A ∈ FM×N , b ∈ FM and x ∈ F N , show that (I − A+A)x and A+b are orthogonal vectors. Hint. Use a compact SVD. Non-graded problem(s) below (Solutions will be provided for self check; do not submit to gradescope.) Pr. 6. Spherical manifold optimization problems (a) Suppose A ∈ FM×N has rank 0 < r ≤ min(M, N) and SVD (1) xopt = arg max∥x∥2=1 ∥Ax∥2 = ? (2) yopt = arg max∥y∥2=1 ∥A′y∥2 = ? (3) When are xopt and yopt unique (to within a sign ambiguity)? (4) Do answers change if you replace A with −A in the optimization problems? Explain why or why not. (5) What constraints could you add to above manifold optimization problem (with the same objective function) so you get ur and vr? (b) Suppose A ∈ F N×N is Hermitian, and has eigendecomposition with descending eigenvalue ordering λ1 ≥ . . . ≥ λN ∈ R. Define: xopt = arg max∥x∥2=1 x ′Ax. (1) Prove that xopt = zv1 where |z| = 1. (2) What is x ′ optAxopt? (3) When is xopt unique (aside from the sign ambiguity)? (c) Same A as in previous part. For some 1 < K ≤ r, define: (1) Prove that xopt = zvK where |z| = 1, via an equivalent formulation involving projections. (2) What is x ′ optAxopt? (3) When is xopt unique (aside from the sign ambiguity)? Pr. 7. Suppose A ∈ FM×N with M ≥ N has full column rank, i.e., rank(A) = N. Show, using an SVD of A, that A+ = (A′A) −1A′ . When A is known to be full column rank, one could use this direct formula to compute the pseudoinverse instead of employing an SVD. Pr. 8. Consider the following set of three measurements (xi , yi): (1, 2), (2, 1), (3, 3). (a) Find the line of the form. y = αx + β that best fits (in the 2-norm sense) this data. (b) Find the line of the form. x = γy + δ that best fits (in the 2-norm sense) this data. Hint. Re-use your answer from part (a).
Simulation of Engineering Systems 3 Assignment: Position Control System for a Robotic Arm Part 1: Modelling, Simulation & Validation Aim Part 1 of this Simulation of Engineering Systems 3 Assignment involves the modelling, simulation and validation of a Position Control System for a Robotic Arm. This part of the assignment involves developing a mathematical model of the dynamics of a simple robotic arm and its position control system. This model will be implemented in Matlab code and as a Simulink block diagram. The responses from the Simulink block diagram will be used to analyse and validate the Matlab model and its associated simulation. This document provides background information about this system, followed by the problem specification for the mathematical model of the system and its simulation. Also, the Assignment Specifications are provided as a step by step guide for this part of the assignment. Introduction Robotic Arms or Manipulators are used extensively in a number of industries e.g. manufacturing, testing, maintenance, exploration. These robot arms are electro-mechanical systems that replicate the articulated motion of human arms. In certain cases this technology is used in prosthesis development for limb replacement. This assignment involves the development of a simulation of a position control system for a robotic arm as outlined in this document. Background The development of robotic arms started in the manufacturing industries where the repetitive processes involved in production of goods (e.g. cars) required increased precision and articulation. Unfortunately these increases could not be achieved through human workers and programmable robot arms or manipulators were created (see Figure 1). Figure 1: Industrial Robot Manipulator The type of arm shown in Figure 1 replicates the anatomy of human arms with increased power provided by the actuation systems that drive each joint. Other types of robot manipulator have been refined from these industrial manipulators in order to serve other industries and performance needs. One such application of this technology has been in the development of articulated prostheses for limb replacement. In particular they have been used to develop actuated prosthetic arms as shown in Figure 2. This application is the focus of this assignment. Figure 2: Prosthetic Arm The motion of this 2 link arm is predominantly through the actuated elbow joint. This is usually driven by a d.c. motor controlled to give the correct position for the hand. The hand provides fine, dexterous motions for performing tasks, which is not considered in this assignment. The motion of the elbow is outlined in Figure 3 below. Figure 3: Prosthetic Arm Elbow Motion Schematic Diagram The actuator (i.e. motor) is connected to the upper arm. For most of the assignment the upper arm is assumed to remain stationary at a specified angle. The actuator rotates the forearm by means of a set of gears. This controlled rotating motion described in Figure 3 is the focus of this assignment as outlined in the Problem Specification below. Problem Specification The motion of the arm is regulated by an automatic control system that determines the necessary rotational deflection of the forearm. In order to achieve this, the arm must be equipped with the necessary systems to ensure its automatic movement within it operating environment. The general principle of automated actuator systems is to feed information from joint rotation sensors to the arm’s control system. In this study we will consider the development of a simulation that represents the Elbow Control System only. This system changes the voltage applied to the elbow actuator to produce the required rotational motion and thus change the deflection angle of the forearm. For most of the assignment the Upper Arm is kept at a constant angle of deflection θU (set at a value of 3。initially). The geometry of this rotational motion is shown in Figure 4. Figure 4: Geometry of rotating motion The elbow control system produces the required actuator rotation to move the forearm to a reference angle. It achieves this by comparing the actuator deflection angle, θM (radians), with the reference angle, θFref (radians). This provides indirect control of the Forearm’s deflection angle, θF (radians). A diagram of the total system is shown in Figure 5. From Figure 5 it can be seen that the Elbow Control System uses the error difference between the reference deflection angle and the actuator’s deflection angle. In this case the value for θFref (the reference angle) is taken to be 55° . The reference deflection passes through the Reference Amp which is represented by a simple gain KR. Also, the motor deflection is measured by the Actuator Sensor, which is represented by a simple gainKS. Figure 5: Elbow Control System The control system itself is a proportional controller of the following form. VE = Gc Δθ (1) Here Gc of the controller and Δθis a function related to the difference between the reference angle and the actuator deflection angle. The resulting commanded voltage VE (volts) then passes through the Gear Compensator,which is simply again, KG. The compensated voltage, VA (volts), is used to control the elbow actuator to drive the gears and thus indirectly generate an appropriate forearm deflection (θF). It achieves this by means of a proportional gain GC and an integral term with gain KI (this is assumed to be zero in the initial stages of the assignment). These gains determine the performance of the control system. This is an overview of the entire system. A key part of the overall Elbow Control System is the arm and its interaction with the actuator and gears. In Figure 5 this part of the system is regarded as the conversion process between the actuator voltage, VA, and the forearm deflection, θF. This process is more involved than this simplified system diagram would lead you to believe. The actuator voltage is used to drive the actuator i.e. a d.c. motor) to deflection θM (radians) by means of its generated torque TM (Nm). The drive shaft of the actuator is connected to Gear 1 (radius r1 meters), which acts as a load on the motor. As Gear 1 rotates it transfers torque TF (Nm) to Gear 2 (radius r2 meters), which in turn rotates the forearm to the desired deflection angle. The gear ratio GR is calculated in the following manner: This ratio can be used to calculate the torque relationship between the gears i.e. TF = GR × TM = GR × KFθG1 (3) Here θG1 is the angular deflection of Gear 1 (radians) and KF is a torque gain. A detailed description of this system and how it interacts with the robot arm can be seen in Figure 6. Figure 6: Actuator, Gears and Arm As mentioned previously, the actuator in this case is a d.c. motor and its electro-mechanics can be represented by the following relationships: Here i is the motor current (A), Δ①is the difference in speed between the motor and Gear 1 (rad/s),JM is the moment of inertia for the motor armature (kgm2), L isthe inductance (H),R is the resistance (Ω), BS is the damping coefficient, KT is the torque constant and KE is the back emf constant. Treating the first gear as a load on the motor’s shaft allows its own dynamics to be defined. This can be represented by the following equation. Here θG1 is the deflection of the gear (radians) and JG1 is the moment of inertia for the gear (kgm2). Since the second gear is attached to the forearm they both have the same dynamics (i.e. θF = θG2). The transfer of torque from Gear 1 to Gear 2 provides the following dynamic relationship for the forearm i.e. Here JF is the total moment inertia of the forearm and hand (kgm2), BSF is the viscous damping coefficient for the forearm, mF the masses of the forearm and hand (kg), lF is of the length of the forearm (m) and g is the acceleration due to gravity (m/s2). These equations represent the dynamics of the prosthetic robot arm and its related systems. Assignment The combination of all these elements produces a mathematical model for the Elbow Control System for the Robot Arm. Using this description as a basis, follow the steps outlined below to complete the first part of your assignment for this course: Mathematical Modelling & Continuous Time Simulation 1. Use the description given above to derive the state space model for the Robot Arm System. 2. Use this model and the parameter values given in the Appendix A to produce an equation or script. based simulation of the Robot Arm System in Matlab. 3. Employ a suitable initial conditions and numerical integration solver with a suitable step-size in the simulation of your system. Justify your choice of the initial conditions, solver and step- size. Do not use the in-built Matlab integration functions. 4. Analyse the dynamic response of the system. Do you think this a good design for the Elbow Control System? Explain your answer. Block Diagram & Validation 5. Using basic, commonly used blocks in Simulink, construct a block diagram simulation of the Robot Arm System. 6. Use the responses from this block diagram simulation to validate your Matlab model from steps (1) & (2) and simulation responses from step (3).
115020 Accounting Fundamentals Assessment 4:Written Assignment Due Date: Week 13 Weighting: 40%(comprised of 2 sections:Part 1(10%)+Part 2 (30%)) Length: 800 words (Part 2 only) Task Description: Obtain a copy of the two most recent Annual Reports of EITHER The Warehouse Group OR Hallenstein Glasson Holdings Limited.Complete a financial statement analysis for your chosen company and prepare an analysis based on the questions below. (Alternatively,your teacher may provide you any two public listed companies'Annual Reports in PDF format,downloadable from Stream). The Warehouse Group Limited WHS-NZX,New Zealand's Exchange Hallenstein Glasson Holdings Limited HLG-NZX,New Zealand's Exchange Part 1(10%Weighting) For your chosen company,calculate the following ratios for the 2 most recent years,following these steps: 1.List relevant data as a balance sheet,separating current and non-current assets and liabilities. 2.Show your ratios in a table with the formula used for calculations (NOTE:For some companies,it may not be possible to complete all of these calculations,but a minimum of 5 ratios from the following list should be provided) The possible ratios to be calculated are: Liquidity Ratios: Current ratio Quick ratio Profitability Ratios: Gross profit margin Net profit margin Return on assets Return on ordinary shareholders'equity Solvency Ratio: Debt to equity Part 2(30%weighting) Use the above ratios to carry out a ratio analysis of the company in the following areas and make a recommendation of whether the company would be a good investment based on your analysis.This part of the assessment should be written in the form of an 800 word report consisting of the following sections (NOTE:Depending on the ratios which were calculated in Part 1,your report may have fewer sections than this): □ Introduction □ Liquidity Analysis Profitability Analysis □ Long-term solvency Analysis □ Final Recommendations-This should be a summary of your comments on the above analyses and a recommendation of whether to invest in this company or not. Learning Outcomes for this Task: LO4 Perform. analytical evaluations using data such as basic financial statement analysis,break-even analyses,future value of money, investment evaluations,and payback periods. Formatting: All assignments should be word processed,have a title and page numbers. Font size should be 12,with 1.5 line spacing.Write your name,student number,and teacher's name clearly on each page.Your submission must be in .doc format (i.e.not a PDF). Draft: You must submit a draft prior to submitting the final version for assessment at a time specified by your teacher(s). You will be expected to take any feedback of your draft into account and put these suggestions into action on your final submission. Assessment Criteria: To see the details of the assessment criteria,please see end of this document Academic Misconduct: Any form. of academic misconduct is taken very seriously. Work found to be plagiarised,ghost-written,collaborated on will be penalised.Depending on the severity of the misconduct,a mark of zero may be given for the assessment.Please see your teacher for guidance on avoiding academic misconduct. Submission: Both the draft and the final writing is to be submitted via your class Stream page via Turnitin.If you are unsure of how to do this,please ask to your teacher(s)before the due date. Marks will be awarded for submissions that are made on time.You will not receive these marks if your assessment is submitted late. Special Consideration: lf you are unwell or there is another compelling or compassionate reason that affects your assessment or your ability to submit it on time,you may apply for special consideration.
