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[SOLVED] Homework Assignment 3 E- ModelingSQL

Homework Assignment 3: E-R Modeling Details This homework assignment evaluates your skills in designing database schemas and drawing ER diagrams. Click on the link below to download the template file that you will use for this assignment. Notice that for this assignment, you will submit two files: your modified sql file plus one diagrams in PDF format. APAN5310_HW3_UNI.sql (https://courseworks2.columbia.edu/courses/228578/files/24691700?wrap=1)(https://courseworks2.columbia.edu/courses/228578/files/24691700/download?download_frd=1) Instructions The attached document is a .sql file. Each question has a corresponding area noted by START and END tags where you will type in your answer. You may use any text editor to type your answers but we recommend that you work within pgAdmin. When done, save the .sql file and rename it as per the instructions below. You must submit your work before the posted deadline. Type your SQL statements between the START and END tags for each question. Do not alter this template .sql file in any other way other than adding your answers. Do not delete the START/END tags. The .sql file you submit will be validated before grading and will not be graded if it fails validation due to any alteration of the commented sections. Our course is using PostgreSQL. We grade your assignments in PostgreSQL. You risk losing points if you prepare your SQL queries for a different database system (MySQL, MS SQL Server, Oracle, etc). It is highly recommended that you insert additional, appropriate data to test the results of your queries. You do not need to include your sample data in your answers. Make sure you test each one of your answers in pgAdmin. If a query returns an error it will earn no points. Important You may only use and submit the .sql or .txt file that is provided for you in this assignment. No other means of submission will be accepted. Failure to submit the provided .sql or .txt file or properly naming it will automatically result to a zero (0) grade for this assignment. Submit your .sql or .txt file as the main submission. Only ONE submission attempt is allowed. Then, add your TWO PDF files as separate comments to your submission. Do not attach .sql or .txt files as comments. Date and time of comment submission must also be before the deadline or they will be counted as late (and only two total comments for PDF files are allowed). Submission To complete your submission, 1. Click the blue Submit Assignment button at the top of this page. 2. Click the Choose File button, and locate your submission. Make sure you have properly named your sql or txt file so that it matches the format "APAN5310_HW3_UNI.sql" (i.e. for UNI: ab3245 it would be APAN5310_HW3_ab3245.sql). Name your diagram PDF files accordingly and upload those as well. 3. Feel free to include a comment with your submission. 4. Finally, click the blue Submit Assignment button. Grading Rubric All SQL queries are evaluated based on the following criteria: 1. Query logic (i.e. use of correct clauses): 30% 2. SQL syntax (i.e. use of correct attributes and predicates): 20% 3. Expected output (i.e. correct and error-free query execution): 50%

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[SOLVED] Assignment 2 Deep Learning for Patient Outcome Prediction

Machine Learning Applications for Health Assignment 2: Deep Learning for Patient Outcome Prediction [Update as of September 22]: Please note that length of stay (LoS) is typically recorded after the patient is discharged. For in-hospital mortality, LoS will not be used as a feature and therefore will not be included in the feature analysis for step 1 either. Introduction Profound hypotension is a life-threatening condition in critically ill patients. For clinicians on the front lines, the ability to accurately and rapidly identify which of these patients face the greatest risk of in-hospital mortality is paramount. This assignment focuses on the application of deep learning for clinical prediction. You will work with a pre-identified cohort of patients with profound hypotension to develop a model that predicts a critical outcome: in-hospital mortality. The Task Your primary objective is to construct, train, and evaluate a Multi-Layer Perceptron (MLP) to classify patients based on their in-hospital mortality risk (a classification task). You will navigate the entire machine learning workflow, from exploratory data analysis and feature preprocessing to hyperparameter tuning and model interpretation. The deadline for this assignment is Wednesday, October 8th, at 11:59 PM. Dataset You are provided with the dataset hypotension patients.csv. The key features for your model will include demographics, a co-morbidity score, and a severity of illness score. The target outcome, in hospital mortality, is derived from the dod (Date of Death) column. The provided cohort has the following columns: "ID": Patient de-identified number; "anchor_age": Age of the patient (years); "gender": F for female and M for male; "dod": Date of Death (if empty means survived - patient outcome variable); "apsiii”: Severity of illness score; "LoS": Length of stay in ICU (days - patient outcome variable); "charlson_comorbidity_index”: Comrbidity index. Assignment Steps Step 1: Describe the main properties of the patient cohort via summary statistics Begin by performing an exploratory data analysis to understand the fundamental characteristics of the patient cohort. Calculate and present summary statistics (i.e., mean and standard deviation) for all numerical features. Visualize the distributions of all the relevant features using appropriate plots of histograms. Write a brief summary interpreting these findings, describing the overall patient population. (Up to 200 words) Step 2: Linear MLP Development and Hyperparameter Tuning Develop a linear Multi-Layer Perceptron. A linear MLP is a neural network that does not use nonlinear activation functions in its hidden layers, effectively acting as a linear classifier. Your task is to determine the optimal architecture for this model. Systematically tune the model key hyperparameters: the number of hidden layers (1,2,3), the number of neurons per layer (16,32,64), and the learning rate (1e2, 1e-3, 1e-4). Justify your final hyperparameter choices using a clear validation-based approach (e.g., a grid search). Provide plots that visualize the tuning process and support your selection of the best-performing model configuration. Summarize your methodology, the chosen parameters, and the reasoning behind your choices. (Up to 300 words) Step 3: Evaluating the Impact of Non-Linearity Investigate the benefit of introducing nonlinearity into your model. Using the best architecture (layers and neurons) found in Step 2, create a nonlinear MLP by adding a non-linear activation function (e.g., ReLU or other activation functions) between the hidden layers. Train this non-linear model and evaluate its performance on the test set. Directly compare the performance metrics (i.e., accuracy, precision, recall, F1-score and confusion matrix) of the linear model against the non-linear model. Write a justification for your choice of activation function and discuss what the performance comparison reveals about the complexity of the patterns in the data. (Up to 300 words) Your code should be written in Python. You can use any publicly available libraries of your choice. Submission Requirements Your submission should consist of three files: 1. A README file that states your name, the assignment, a description of the problem being addressed by the code, and instructions on how to create the environment to run your submission. 2. Afile that completely specifies the code environment you used (that is, the dependencies and version numbers for all the software you used in your solution. This could be either a requirements.txt (vanilla Python) or environment.yaml (for Anaconda). 3. A single Jupyter notebook with all the code, output, and explanatory text included.

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[SOLVED] FIN 5320 Group Project

FIN 5320 Group Project Instructions This group assignment is due no later than Friday 10/17 at 11:59pm CST. You can do the assignment either in Microso! Excel (recommended) or Python. If you do your assignment in Excel, please submit your spreadsheet showing your work and a pdf document with your report. I expect your spreadsheet and report to be formatted professionally. If you do your assignment in Python, please convert your Jupyter notebook to HTML and submit the HTML file. Please submit the resulting HTML file and a pdf document with your report. Using ChatGPT to get the Python code to run is okay, but copy-and-pasting full paragraphs in your report is not. Your grade on this assignment depends exclusively on what you write in your report, and how you format the document. Your report must use titles, proper capitalization, paragraphs explaining your work, properly formatted tables and figures, equations if necessary, and full sentences. Your report should read and look like a professional report generated by a large investment bank for an important client. I will check all assignments for plagiarism using Turnitin. Objective As a group of portfolio managers at an asset management firm, you have been tasked with implementing a Treynor-Black style. model to construct a portfolio designed to outperform. the market. You know that you could use the formulas derived by Treynor and Black (1973) in their original paper, but you would like to add portfolio weights constraints, and also try with other alternatives, so you decide to modify their approach. Security Selection Begin by selecting six stocks that you believe are either underpriced or overpriced. For each stock, provide a justification for your selection, such as financial ratios suggesting mispricing, recent news events, a broker’s recommendation, or other relevant factors. For each selected security, perform. a standard OLS regression as follows:           (1) where  represents the monthly excess returns for security over the risk-free rate, and  represents the monthly excess returns of the market. Use the 13-week Treasury Bill CBOE Index (^IRX) as a proxy for the risk-free rate, and be sure to convert its annualized rate into a monthly rate compounded monthly for your calculations. For the market proxy, use the SPDR S&P 500 ETF Trust (SPY), and ensure that you use Adjusted Prices to account for dividends when computing returns. Run the regressions using five years of historical data. I do not need to see the output of each regression. Instead, generate one single table that displays the relevant information for all securities at once: Alpha (per year) Beta R-square Volatility of returns (per year) Firm-specific volatility (per year) To compute the firm-specific volatility, you can use Therefore, you will also need to compute the volatility of excess market returns. For each security, generate a scatter plot that includes the regression line. Display all your plots tightly in a three-row two-column configuration. Maximizing the Sharpe Ratio of Individual Stocks In this part of the analysis, I want you to maximize the Sharpe ratio of a portfolio consisting only of the six stocks you selected in the previous part. You will constraint the weights to be positive, and no weight can be larger than 40% of the portfolio. Your estimation problem is then given by In this particular case we have stocks. You can compute the portfolio risk-premium as where  You can use the αi and βi estimated in (1), and assume a market risk-premium of  per year. To compute , first compute for each month t = 1, . . .  ,T the return of the portfolio as and then compute an annualized sample standard deviation as where  Note that this is how the Excel function =stdev.s() computes the standard deviation. Your Sharpe ratio is now a function of the portfolio weights that can be maximized using Excel or Python by imposing the appropriate constraints. Report the composition, expected return, standard deviation, Sharpe ratio, alpha and information ratio of your portfolio. Comment on the strengths and weaknesses of using only six stocks to form. your optimal portfolio. Adding the Market The idea of Treynor and Black (1973) was to add the market to the previous optimization problem. That way you have an active portfolio composed of six stocks and a passive portfolio which is the market portfolio. You can use the SPY to proxy for the market which is now your seventh stock. Treynor, Jack L., and Fischer Black. 1973. “How to Use Security Analysis to Improve Portfolio Selection.” Journal of Business 46 (1): 66–86. Report the composition, expected return, standard deviation, Sharpe ratio, alpha and information ratio of your new portfolio. Comment on the strengths and weaknesses of adding the market in addition to your original six stocks to form. your optimal portfolio. Assess the proportion of the portfolio that stays passive vs. active, and whether the weights of the active portfolio make sense. Conclusion Based on your previous results, write a convincing paragraph with a recommendation as to what is the best approach to form. your portfolio. Contrasts the benefits vs. costs of adding the market in your portfolio allocation.

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[SOLVED] ESS321H1 F Mineralogy Fall 2025 Syllabus

ESS321H1 F Mineralogy Fall 2025 Syllabus Course Overview Systematic mineralogy (including identification, classification, and description); physical and chemical properties of minerals; crystallography and crystal systems (symmetry, crystal structure, crystal systems); optical techniques in mineral identification. Systematic mineralogy (including identification, classification, and description); physical and chemical properties of minerals; crystallography and crystal systems (symmetry, crystal structure, crystal systems); optical techniques in mineral identification. Course Learning Outcomes By the end of this course, you will be able to identify common rock-forming minerals using physical properties and optical techniques. You will be able to describe the chemical, structural and physical basis for mineral properties. You will understand how these minerals relate to geological processes and how they are significant to daily life.  However, my learning goals for you are only half the picture. In the first few classes we will talk about what you want to get out of this course, and I will do my best to work in those topics.   Prerequisites: ESS224H1, ESS234H1 Corequisites: None Exclusions: None Recommended Preparation: None Credit Value: 0.5 Course Materials These textbooks are suggested reading. If you don't understand something from class, please consult them. They're available at the Earth Sciences Library.  Klein, C., & Dutrow, B. (2007). Manual of mineral science (23rd ed.). John Wiley & Sons, Inc.   Deer, W., Howie, R., and Zussman, J. (1992). An introduction to the Rock-Forming Minerals (2nd ed.). Pearson.  Nesse, W. (2013). An Introduction to Optical Mineralogy (4th ed.) Oxford University Press. Marking Scheme Assessment Percent Details Due Date Lab Reports & 1 Quiz 35% The first lab submission is a short quiz on mineral ID. All other lab submissions are a lab report format. They will be due by 9AM on the date of the next lab session. 20250915, 20250922, 20250929, 20251006, 20251020, 20251110, 20251117, 20251124 Mid Term 15% During class time 20251016 Lab Tests 25% During Lab time. Each test will cover one half of the lab material. 20251103, 20251201 In-Person Final Exam 25%   Final Exam Period David Summer will be handling most of the marking for the lab reports and I thank him in advance for his hard work. Mid terms, tests and exams will be marked by the instructor. Late Assessment Submissions Policy A penalty of 10% of the total mark for lab assignments will apply per 24 hour period. This includes weekends and holidays.

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[SOLVED] ITEC 2620 Introduction to Data Structures

Homework Handout ITEC 2620  Introduction to Data Structures Fall Semester, 2025 This document outlines the class homework policy which includes acceptable formats, submitting and collecting homeworks, and remarking requests. Please read this document carefully and make sure you adhere to all rules to receive full credit. 1    Homework Format All homeworks must be a single PDF file.  They can be either handwritten and scanned (or photographed) or typeset in LATEX, but the end result in all cases has to be a single  readable PDF file submitted via eCLass.  If handwritten,  do not use red/pink/orange colours that do not scan well and make sure the handwriting is legible.  If typeset in LATEX, make sure to use formatting tools such as headings, paragraphs, equations, tables, boldface, etc to make your solutions easy to understand (and not just a wall of text). In all cases, everything must be easily readable. The first page of all homeworks must be a standalone cover page containing the following: •  The full names (as they appear in eClass) and student numbers of all group members •  The course code (ITEC2620) •  The assignment number •  The date of submission •  The total number of pages included in the homework submission To receive full credit, make sure you adhere to the following rules: • Every answer you provide must be numbered clearly and correspond to the problem and sub- problem you are answering. • Every page should be numbered. • Final answers must be clearly identified (put it in a box or underlined). • You may use any algorithm, or esult from the textbook on homework questions, but you must cite the textbook such that a TA can reasonably find what you are referencing, i. e., (chapter 9.2, page 302, paragraph 2). • When asked to write pseudo code,  do  not write source code.  Use your judgement as to how much detail to include. Refer to the textbook and lecture notes for the type of pseudocode we expect. • Always justify your answer. You must show us the thinking process that led to the answer. 2    Submitting and Collecting Homeworks are to be completed by groups of 2-3 students.   All homeworks will be collected at the  deadline  indicated  by  each  homework.   No  homeworks  will  be  collected  late.    Strict adherence to deadlines is expected. All times posted in eClass are Toronto local times. A few minutes past the deadline the submission process at eClass will close for the assignment, and solutions will be posted. As such absolutely no late homework will be collected. •  Please submit assignments in the respective homework section on eClass. •  Submissions will be closed immediately after the mentioned deadline.  We suggest students to submit assignments  at least  an hour before  the  deadline.   This  is  to  avoid  any  disruptions  you might  have  with  internet  connection  and/or  overloaded  servers  during  the  last  minutes  of  a submission. • eClass allows for unlimited re-submissions before the deadline. In case of any updates to your submission please use the submit button to upload the latest revision. The older versions will be over-written. •  Make sure to check that the document you are uploading is the solution file.  The  name of the file should be of the following format: ITEC2620HW   (ID of the homework)   (StudentIDs).pdf Ex: ITEC2620HW   1 219102323-218113985-220226062.pdf • A student can be part of only one group. Each group should upload only one submission.  Your submission will be disqualified and you will not be marked if we receive multiple submissions on your student ID. 3    Homework Formatting and Submission Checklist Please consult the following steps when submitting a homework assignment to ensure it is submitted correctly and you receive full credit for your submission. 1.  The document is a single PDF file whose name is formatted according to Section 2 “Submitting and Collecting”. 2.  The  first  page  of the  document  is  a  standalone  cover  page  containing  the  full  names  and student numbers of all group members, the course code, the assignment number, the date of submission, and the total number of pages in the document. 3.  The rest of the document contains your group’s solutions to the homework questions.  These solution should be clear, concise, easily readable, and follow all the general homework rules outlined in Section 1  “Homework Format”. 4.  The document is submitted by one  (and only one) of the group members via eClass to the correct homework section before the homework deadline.  

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[SOLVED] ITEC 2620 Introduction to Data Structures Fall Semester 2025 Homework 1

Homework 1 ITEC 2620 Introduction to Data Structures Fall Semester, 2025 Due: October 8, 2025, 11:59pm ET 1. [Short Answers, 30] For all questions below justify your answer. (a)  Order the following four functions from asymptotically smallest to asymptotically largest, indicating ties if there are any: lg(n!);    2lg 4n ;    lg n;    (n/70)!;    3n;    n3  - n (b)  What is the worst case time complexity for binary search on a BST with n elements and why? Does this complexity change if you know that the BST is approximately balanced? Explain your reasoning. (c)  An algorithm triples its execution time every time the input size increases by one. What is the time complexity of this algorithm? Explain your reasoning. (d)  Discuss why performing binary search on a sorted linked list is generally less efficient than linear search. What factors contribute to this inefficiency? (e)  Insertion sort is generally considered “efficient” when the array is nearly sorted.  Explain why. (f)  You are given the in-order and post-order traversals of a binary tree: In-order traversal:  [4, 2, 5, 1, 3, 6] Pre-order traversal:  [1, 2, 4, 5, 3, 6] Construct and draw the binary tree from these traversals and briefly explain your ap- proach. 2. [Complexity Analysis, 20 points] What is the time complexity of the following algorithm as a function of the problem size n? Show your reasoning. void runTasks ( int [ ]   arr )   { int n  =  arr . length ; int i   =  n ; boolean marker  = false ; while ( i   >  0)   { for ( int j  =  0 ;   j  < n ; j++) { process ( arr [ j ] ) ;   //  O( 1 ) } i f ( ! marker  &&  i  ==  n   /   3)   { for ( int k  =  0 ;   k  < n ; k++) { process ( arr [ k ] ) ;   //  O( 1 ) } marker  = true ; } i   /=   3 ; } } 3. [Recursion, 30 points] Write a recursive function to calculate the height of a binary tree.  The height of a binary tree is the number of edges on the longest path from the root to a leaf node.  For an empty tree (null root), the height is defined as -1. You are given the following tree node structure: class TreeNode   { int val ; TreeNode   l e ft ; TreeNode   right ; TreeNode ( int val )   { this . val  =  val ; this . l e ft   = null ; this . right  = null ; } } Write a function: public int find Height ( TreeNode   root )   { //   Your   imp lem entation   h ere } The function should calculate the height of the binary tree rooted at root.  You can provide code or pseudocode, but your answer should be accompanied by an explanation of what you did and why. Use recursion to solve the problem. Non-recursive solutions will not receive any marks.  Clearly handle the base case for an empty tree.

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[SOLVED] COSC2123/3119 Algorithms and Analysis

Algorithms and Analysis COSC2123/3119 The Maze of Many: An Exploration of Graph Traversal and Planning Problems Assessment Type Individual assignment. Submit online via GitHub. Due Date Week 11, Friday October 10, 19:59 (before 8pm). A late penalty will apply to assessments submitted after 7:59 pm. Marks 30 1    Learning Outcomes This assessment relates to four learning outcomes of the course which are: •  CLO 1: Compare, contrast, and apply the key algorithmic design paradigms: brute force, divide and conquer, decrease and conquer, transform and conquer, greedy, dynamic pro- gramming and iterative improvement; •  CLO 2:  Compare, contrast, and apply key data structures:  trees, lists,  stacks, queues, hash tables and graph representations; •  CLO 3: Define, compare, analyse, and solve general algorithmic problem types: sorting, searching, graphs and geometric; •  CLO 4: Theoretically compare and analyse the time complexities of algorithms and data structures; and •  CLO 5:  Implement, empirically compare, and apply fundamental algorithms and data structures to real-world problems. 2    Overview Across multiple tasks in this assignment, you will design and implement data structures that represent mazes as graphs and algorithms to explore these mazes. You will address both fully connected, non-cyclical mazes and mazes with cycles.  Some of the components ask you to critically assess your solutions through both theoretical analysis and controlled empirical ex- periments to encourage reflection on the relationship between algorithm design and real-world performance. The assignment emphasizes on strategic thinking and the ability to communicate solutions clearly and effectively.

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[SOLVED] ECON 503 FALL 2022 SAMPLE MIDTERM EXAM

ECON 503, FALL 2022 SAMPLE MIDTERM EXAM Problem 1 (Parts a. and b. are past midterm questions. I have deliberately left the comments on the common mistakes as I thought you might find them useful) a. Show that for two events A and C the following holds: if A C (A is a subset of C), then P(A) ≤ P(C). (8 points) b. Use the result from part a. and Bayes’ rule to show that if P(A)  >  0 then P[(A ∩ B)  l A] ≥ P[(A ∩ B)  l (A U B)]. (12 points) In order to get full points you need to provide a formal proof supporting your answers. c. You are going to play two games of chess with an opponent whom you have never played against. Your opponent is equally likely to be a beginner, an intermediate, or a master; depending on this your chances of winning an individual game are 0. 9, 0. 5 or 0. 3, respectively. c1. What is the probability to win the first game? (5 points) c2. Congratulations: you won the first game! Given this, what is the probability that you will win the second game? Assume that conditional on the skill level of your opponent the outcomes of each game are independent. (15 points) Problem 2 (This is a past midterm exam question. The hint was provided.)           (15 points in total) Suppose there are two urns containing balls; call these urns A and B. The balls in urn A are labelled with either the number 1 or the the number 2, with an equal share of each type. The balls in urn B are labelled with either the number 2, or 3, or 4, or 5, with an equal share of each type of balls. Consider a random variable X obtained by the the following experiement. Flip a coin. If the coin comes up Heads, then draw a ball from urn A and define X as the number on that ball. If If the coin comes up Tails, then draw a ball from urn B and let X be the number on  that ball. a. Find the PWF ofX.        (10 points) Hint: Since the balls numbered 1 and 2 in urn A are of equal share each, then they are equally likely; similarly, for balls numbered 2, or 3, or 4, or 5 in urn B. b. Find the CDF ofX, FX(x) and draw its graph. (5 points) Problem 3 (20 points in total) A continuous random variable X has a PDF given by:   a. Show that c = 2/3 makes fX(x) a valid PDF, and impose this value in all subsequent parts of the question. (3 points) b. Find the CDF of X, FX(x). (5 points) c. Find P(1 ≤x ≤2). (3 points) d. Find P(x < 2/1  lx 

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[SOLVED] ME 2356-Mechanics of Materials

Department of Mechanical and Industrial Engineering ME 2356-Mechanics of Materials Lab 1 Instructions I. GOALS The primary goals of this experiment are: 1. To determine the relationship between tensile normal stress and normal strain for various materials 2. To learn techniques for tensile testing on electromechanical testers 3. To analyze stress-strain data to determine mechanical properties including Young’s modulus, yield strength, ultimate tensile strength, and fracture strength 4. To learn about the photoelasticity and stress concentration II. OVERVIEW OF EXPERIMENT There are three experiments in this lab. • The first part includes tension tests of a material on the large Instron mechanical testing machine. • In the second part you will perform. a manual tensile test to study unloading and reloading of the sample. • In the third part, you will perform. a photoelasticity test to look at stress concentration on different samples. III. RELEVANT THEORY Testing in tension is one of the most common mechanical testing methods, since one test can be used to determine several important mechanical properties. In a tension test, tensile forces are applied to a specimen, and the resulting changes in the specimen’s length are recorded. Standard specimens are of a ‘dogbone’ shape, as shown in Figure 1, with a reduced cross-section in the middle of the sample. This reduced cross-section contains the ‘gauge length’; we will determine strain by measuring the length of this part of the specimen and tracking how it changes during loading. The gauge length is important, as it is necessary to determine the strain from the displacement data. Figure 1: Typical tensile specimen The testing machine itself typically measuresload and displacement. However, in order to be able to design with materials, we generally want stress and strain. Stress is given by: where σ is the normal engineering stress, F is the load, and A0 is the original cross-sectional area of the gauge length. Engineering strain is given by: where ε is normal engineering strain, li is the instantaneous length and l0 is the initial gauge length. Strain is unitless, whereas stress is given in MPa. Remember, the machine will provide force data – you will need to convert this to stress during your analysis. Also remember that the machine itself will provide displacement data, and you will need to convert this to strain during your analysis. The strain data provided by a tensile test machine are often considered to be unreliable. That is because the displacement that the machine reads out reflects the stretching of the sample plus the stretching of the machine’s components. To achieve more reliable data, engineers typically use another means of measuring strain, the extensometer. The extensometer clips onto the sample, extends with the sample (ideally requiring no force for its extension) and reports its elongation. Extensometers typically report their results directly in terms of strain, calculated as described above. However, it is still important to have the raw displacement measurement because the extensometer must be removed well before the test is finished. If the extensometer is still attached when the specimen breaks, it will break, too. Stress strain curves provide information about a number of properties, as shown in Figure 2. The initial linear portion of the curve is the elastic region. The slope of the curve in this region provides the Young’s modulus, which is a key indicator of the stiffness of a material. The proportional limit is at the of the linear region, where the fitted line to this region deviates from the curve. The elastic region ends at the yield point, which is identified as follows. Draw a line that is parallel to the elastic region but is offset to the right of it by a strain of 0.002. Where this line crosses the stress-strain curve is defined as the yield point. For this reason, it is also referred to as the 0.2% offset yield strength. The maximum stress found during the tensile test is designated the ultimate tensile strength. After this point is exceeded, the gauge section becomes narrower – this is referred to as necking. After necking begins, the sample tends to rapidly progress to failure. The stress at the point of failure is the fracture strength. During the lab you will be using your data to determine these materials properties. Figure 2: Typical properties determined from a stress strain curve. All of the values discussed so far have been determined from a plot of engineering stress and strain. However, engineering stress does not consider the changing cross-sectional area of the specimen. True stress does take this into account, and is determined by: where σT is the true stress and Ai is the instantaneous cross-sectional area. You will be measuring the cross-sectional area of the sample after failure, when the cross section has become thinner due to necking. This will allow you to determine true stress at failure in the necking region. Another material property that can be determined from tensile testing is the ductility, which can be expressed as a reduction in area: where A0 is the initial cross-sectional area of the sample and Af is the final cross-sectional area of the sample. The reduction in area is measured at the point of fracture. Finally, the resilience of a material, as measured by the modulus of resilience, can be determined from stress-strain data. Resilience is a measure of the ability of a material to absorb and recover energy in the elastic region. It can be determined by finding the area under the engineering stress-strain curve up to the point of yielding or: where Ur is the modulus of resilience and εy is the strain at yielding. Assuming the elastic region is linear, this becomes: where σy is the yield strength. 1. INSTRON – EXPERIMENT 1 There are two distinct methods to measure mechanical properties of a sample rod under tension: (i) Force-controlled or Fixed-load (F = constant) configuration. This is the simple test you performed in high school to measure spring constant (k) of a rubber band. A rubber band is hung on fixed wall at top. Small weights (F) are added to a pan hanged on the lower end, while the incremental extension (d) is measured using a ruler. A set of data d(F) is plotted to yield a slope of (dF/dd) which is the spring constant. The pseudo elastic modulus is given by where k = (E A / L) is the spring constant expressed in terms of the elastic modulus, cross-sectional area and original length. This method allows measurement only up to the ultimate strength at A (shown on the graph below) before failure such as necking and fracture occurs. No data can be obtained for necking along curve section AB. (ii) Displacement-controlled or Fixed-grips (d = constant) configuration. Measurement is performed by universal testing machines (UTM) such as Instron or MTS. Sample rod is firmly held by a lower grip that is stationary and an upper grip that moves at a slow speed. As the sample extends, the associated force is measured by a load cell. The software generates data set of F(d) and the slope of (dF/dd) is the spring constant. This method allows full measurement of curve OAB from initial loading to final failure, including the intermediate necking AB. Figure 3. Stress-strain curve showing necking region. We will be using an Instron 5582 testing frame. (shown in Figure 4) for this experiment. This machine has a 100 kN maximum load and can measure in both tension and compression. For small amounts of strain, such as in the elastic region of a tensile stress-strain curve, an additional tool called an extensometer (also described above) is used to provide a more accurate measure of strain. The extensometer is clipped onto the sample to measure these initial strains. The extensometer needs to be removed after the material reaches the yield point, but before the sample breaks. Failure to do this will damage the extensometer. The data is recorded using the Instron Bluehill software. Figure 4. Instron 5582 Electromechanical Testing Machine. 1.1 INSTRON: PROCEDURE 1. Mount the sample in the Instron machine: a) Install the specimen into the “jaws” of the Instron machine. Make sure it is lined up with the grooves in the jaws. Hand-tighten the upper jaw first by turning the crank. Slowly move the upper jaw down using the scroll wheel on the key panel and when the sample is all the way down in the lower jaw, hand-tighten the jaw. By placing the sample in the upper jaw first and then the lower jaw, we make sure to minimize sample deformation. b) Measure the initial length Lo and initial diameter Do of the specimen. (use the distance between the grips as the initial length, Fig 5. right) Figure 5. Instron components and sample. c) Connect the extensometer directly to the sample. Hold down the black push button (this aligns a push pin to set the initial length of the extensometer) and slide the clips on to the sample. Ensure that the extensometer is located in the middle of the sample length. Release the push button to retract the alignment pin. Figure 6. The extensometer. 2. Set up a tensile test in BlueHill software: a) In the ‘Method’, choose ‘Tension Method’. b) Set units to ‘SI’. c) In the ‘Measurements’ tab: Double click on ‘Strain’. This will add ‘Strain 1’ to the list on the right side. This is the strain value from the extensometer. d) In the ‘Test control’ tab: i. Under ‘Test’: enter the displacement rate as 10 mm/min. ii. Under ‘Strain’, make sure that ‘Strain 1’ is chosen as the ‘Primary source’. Select the option to ‘remove extensometer during test’. For measurement choose ‘Strain1’ . Set the value to 2% and for ‘Action during removal’ choose ‘Pause test and continue data capture’. e) In the ‘Workspace’ tab, under ‘Raw Data’, double click on ‘Strain 1’ to add it to the list on the right. f) In the ‘Export’ tab: to export the Raw data, under ‘Export 1’, check the ‘Raw Data’ for the ‘Content’ and uncheck the rest. g) Save and name your method by clicking on ‘Save method’ on the top right (save on Desktop). 3. To run the test. Click on home and then ‘Test’. Choose the method you just created, then click ‘OK’. 4. Open ‘System Details’ (can be found on Fig. 7) to add ‘Strain 1’ to the display. 5. To ensure the load cell is balanced and the elongation and strain are zeroed, for each one, click on the ‘Digits’ on the top and click ‘Balance’ or ‘Zero’ (digits shown on Fig 7). 6. Start the test by clicking the ‘Start’ button in the bottom right. The test will pause automatically at 2% strain (when the curve plateaus). Once it pauses, open the Instron door and carefully remove the extensometer. Then continue running the test until the specimen breaks. 7. Before removing the sample’s broken sections from the Instron, close the gap between the broken sections (by manually moving the upper jaw down using the scroll wheel on the key panel) and measure the final length Lf and the final diameter df. 8. To export the data, click on Export (Fig. 7) and choose your sample. Chose “Export to ExportFile1.csv”. Then click “Desktop”. Type your name for the file name and click “Save”. 9. Send the file to you and your groupmates through Canvas Inbox. Figure 7. Bluehill, Test tab. 1.2 INSTRON: RESULTS, ANALYSIS, AND REPORTING This section is worth 46 points out of 100. All the calculations and analyses must be performed in MATLAB. Resources to help you get back up to speed on MATLAB are available on Canvas. The university also has a MATLAB TA who holds office hours to help Northeastern students with MATLAB questions. 1. Write a brief introduction to the lab report (see template) (5 points) 2. Write a brief explanation of the Intron experiment in the Methods section of the template. (5 points) Include: a. What instruments were used. b. What sample was tested. c. What was measured. d. How the measurements were taken. e. Show all equations used in your analysis of the data. 3. Report the values of L0, Lf, Do, Df, A0, and Af in a carefully labeled table. (2 points) 4. In Matlab plot the raw force and displacement data for the sample. You should be plotting displacement on the x-axis and force on the y-axis. Label your axes and include the units. (3 points) 5. Convert your experimental data to engineering stress and strain. In Matlab, plot curves for both engineering stress vs. strain and stress vs. extensometer strain on the same graph, labeling each curve. label the axes and include the units. Watch out for units! Check the units in your raw data. Extensometer might be in % strain. (5 pts, including the MATLAB code) 6. Mark the major points and regions on the stress-strain graph. You can use Microsoft Word or Power Point to label the points and regions on your graphs (7 points, 1 point each). This includes: a. Elastic region. b. Plastic region. c. Necking region. d. Proportional limit. e. Yield strength. f. Ultimate strength. g. 0.2% offset line. 7. Calculate the following mechanical properties, report them in a clearly labeled table: (12 points, 2 points each) a. Young’s modulus (using extensometer data) by fitting a line to the linear part of the graph. b. Proportional limit (using crosshead data) c. Yield strength (0.2% offset) d. Ultimate tensile strength e. True stress in the necked region just prior to failure f. % Reduction in Area (%RA) at failure 8. Discussion: Calculate the elastic energy density of the specimen up to the yield point. Discuss how this quantity is related to the Modulus of Resilience. (3 points) 9. Discussion: Compare the calculated values with reference values from the internet. Name the sources of error and limitations. Discuss reproducibility (if someone else repeated the same experiment, would they get the same results as you? Why or why not?). (4 points) 2 MANUAL TESTER - EXPERIMENT 2 This experiment is to investigate the unloading and reloading behavior. of a material. In this experiment, you will load a sample until plastically deformed, unload it, and then reload it until failure. This will produce a graph similar to the graph in figure 8 (depending on the material used). Figure 8. Stress-strain curve with unloading and reloading. 2.1 MANUAL TESTER: PROCEDURE All specimens have a nominal diameter of 3.33 mm and a nominal working length of 3.2 cm. 1. Mount a sample in the Materials Testing Machine: a. Place the sample (short threaded side down) through the top hole and screw it into the bottom hole. Screw in the sample until the top edge of the last thread is flush with the top of the load cell (Fig 9. Red arrows). The longer threaded section of the sample should go up through the hole in the center of the load bar. Turn the crank counter-clockwise to flush the surfaces shown by blue arrows in Fig 9. b. Check that the height of the load bar is correct; the bottom edge of the longerthreaded section should be flush with the bottom of the load bar. c. While holding the sample so that it does not turn, screw the sample nut onto the longer threaded section on the top until the sample is held “almost tightly”. Do not overtighten. d. Attach the safety shields. Figure 9. Mounted sample. 2. The PASCO Capstone software has been prepared for you. 3. Set a Pre-Load a. Click Record to begin collecting data and rotate the crank clockwise until the force is up to 50-100 N. b. Click Stop and DO NOT change the crank position. Since the Materials Testing Machine is set to automatically zero itself the next time you start recording data, this puts a pre- load of 50 N to 100 N on the sample, which results in better data. 4. Initial load cycle (you will pass the yield point) : a. Click Record to begin collecting your real data. b. Slowly rotate the crank clockwise to load the specimen in tension. Watch the software’s real-time graph of force and position. Continue increasing the load until afterthe specimen has completely passed the yield point (i.e. until the force-position curve has completely flattened out). c. Once you’re convincingly past the yield point, stop turning the crank. Do NOT stop the data recording. d. Unload cycle: Slowly rotate the crank counterclockwise to remove the load from the specimen. Watch the force-position graph as you unload the specimen. Continue unloading until the force returns to about 100N. Do NOT stop the data recording. 5. Second load cycle (load to failure): a. Slowly rotate the crank clockwise to load the specimen in tension. Continue loading until the specimen breaks. b. Click Stop to end the data recording. c. Export the force and position data of only the last run on the computer desktop as a .csv file with a name that identifies who you are and what type of material was tested. 6. Export the data: a. Click on “file” then click “Export Data”. b. Click “Deselect all” and then in the lefthand menu select “Position” Run #2 and “Force” Run #2 c. Click export to file and save the data as a .csv file with your name and the material type (steel, brass, Al, etc.) d. Go to Chrome, send the file to you and your teammate through Canvas. 7. Remove the specimen and put it into the recycling basket before you leave. 2.1 MANUAL TESTER: RESULTS, ANALYSIS, AND REPORTING This section is worth 32 points out of 100. All the calculations and analyses must be performed in MATLAB. 1. Write a brief explanation of the manual tester experiment in the Methods section of the template. (5 points) Include: a. What instruments were used. b. What sample was tested. c. What was measured. d. How the measurements were taken, etc. e. Show all equations used in your analysis of the data. 2. In Matlab plot the raw force (load) and displacement data for the sample. You should be plotting displacement on the x-axis and force on the y-axis. Label your axes and include units. (5 points) 3. Convert your experimental data to engineering stress and strain. In Matlab, plot curves for stress vs. strain. label the axes and include the units. (5 pts, including the MATLAB code) a. Note that: All specimens have a nominal diameter of 3.33 mm and a nominal working length of 3.2 cm. 4. Label the following on your stress-strain plot. You can use word or Power Point to Label (4 points): a. Initial loading Young’s modulus by fitting a line to the linear part of the graph. b. Reloading Young’s modulus. c. Yield strength (0.2% offset) d. Ultimate tensile strength. 5. Calculate the following mechanical properties and report them in a clearly labeled table (8 points): e. Initial loading Young’s modulus by fitting a line to the linear part of the graph. f. Reloading Young’s modulus. g. Yield strength (0.2% offset) h. Ultimate tensile strength. 6. Discussion: Compare the calculated values with reference values from the internet. Name the sources of error and limitations. Discuss reproducibility (if someone else repeated the same experiment, would they get the same results as you? Why or why not?). (5 points) 3 POLARISCOPE – EXPERIMENT 3 When you performed the mechanical tests above, you used specimens that had a uniform. cross-section along the entire length being measured. The cross-section of the specimens increased gradually from the area being studied to the larger area that was held in the grips. These constant cross-sections and gradual changes in area are important because they prevent stress concentrations from forming. You may have already discussed stress concentrations in class, and you may discuss them more in the future. Whether you have or not, this portion of the lab will give you the opportunity to learn about how they work firsthand and to see how practicing engineers can evaluate them experimentally. Stress concentration occurs at a point in a specimen where the loading cross-section changes suddenly. The change in the cross-section could be a sudden change in the width of the cross-section, a hole punched out of the middle of the specimen, etc. Whenever there is a stress concentration, the stress is locally higher than the average value on the cross-section. Photoelasticity describes changes in the optical properties of a material under mechanical deformation. It is often used to experimentally determine the stress distribution in a material, where it gives a picture of stress distributions around discontinuities in materials (i.e. at stress concentrations). Photoelastic experiments (also informally referred to as photoelasticity) are an important tool for determining critical stress points in a material (i.e., the points that experience the highest stress) and are used for determining stress concentration in irregular geometries. A polariscope is used to visualize stress distributions via photoelasticity. The polariscope consists of two linear polarizers and a light source. First the light is passed through the first polarizer which converts the light into plane polarized light. The apparatus is set up in such a way that this plane polarized light then passes through the stressed specimen. This light then follows, at each point of the specimen, the direction of principal stress at that point. The light is then made to pass through the analyzer, and we finally get the fringe pattern. Finite element analysis can also be used to represent the stress distribution in a sample as a color distribution. Figure 10 below shows a comparison of photoelasticity vs. finite element analysis. Figure 10. Photoelasticity vs. Finite Element Analysis 3.1 POLARISCOPE: PROCEDURE In this part, two samples will be used: a sample with a hole and a dogbone. The procedure is the same for both samples. 1. Lower the loading screw until it barely touches the sample. Do not load the sample just yet. 2. Take a picture of the unloaded sample through the polarizer. 3. Load the sample until you see a slight change in the color over the sample. Take another picture in this state (low compression). 4. Turn the crank for another half-round and take a picture (high compression). Figure 11. Polariscope setup 3.2 POLARISCOPE: RESULTS, ANALYSIS, AND REPORTING This section is worth 22 points out of 100 For sample 1 and sample 2: (6 photos in total, 3 photos for each sample) 1. Photos of the unloaded samples (2 photos, 4 points) 2. Photos of the samples under load when the slight change in color appears. Mark the region where high stress starts to appear. You can use Word to mark the area where stress starts to appear. (4 points) 3. Photos of the high compression (after you turned the crank another half round). Mark the regions of high stress in the photo. Can you word to mark this. (4 points) 4. Discussion: Compare the result (i.e. the location where the highest stresses are observed) with the stress concentrations that you expect under each loading condition. (5 pts) 5. Discussion: Discuss possible applications of this method in industry. (5 pts) REPORTING Use the “report template” posted on the web page to prepare your report. All graphs should have clearly labeled axes including appropriate units, and captions that indicate the equipment the data was gathered on and the sample name. It is required that you use Matlab for all data figures and analysis (when specified). Copy your code in the appendix.

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[SOLVED] Homework Assignment 4 Intermediate and Advanced

Homework Assignment 4: Intermediate and Advanced SQL Details This homework assignment evaluates your skills in performing intermediate and advanced database operations with SQL. Click on the link below to download the template file that you will use for this assignment, and the initial ERD. APAN5310_HW4_ERD.pdf (https://courseworks2.columbia.edu/courses/228578/files/24691901?wrap=1) APAN5310_HW4_UNI.sql (https://courseworks2.columbia.edu/courses/228578/files/24691848?wrap=1) (https://courseworks2.columbia.edu/courses/228578/files/24691848/download?download_frd=1) Instructions The attached document is a .sql file. Each question has a corresponding area noted by START and END tags where you will type in your answer. You may use any text editor to type your answers but we recommend that you work within pgAdmin. When done, save the .sql file and rename it as per the instructions below. You must submit your work before the posted deadline. Type your SQL statements between the START and END tags for each question. Do not alter this template .sql file in any other way other than adding your answers. Do not delete the START/END tags. The .sql file you submit will be validated before grading and will not be graded if it fails validation due to any alteration of the commented sections. Our course is using PostgreSQL. We grade your assignments in PostgreSQL. You risk losing points if you prepare your SQL queries for a different database system (MySQL, MS SQL Server, Oracle, etc). It is highly recommended that you insert additional, appropriate data to test the results of your queries. You do not need to include your sample data in your answers. Make sure you test each one of your answers in pgAdmin. If a query returns an error it will earn no points. Important You may only use and submit the .sql or .txt file that is provided for you in this assignment. No other means of submission will be accepted. Failure to submit the provided .sql or .txt file or properly naming it will automatically result to a zero (0) grade for this assignment. Submit your .sql or .txt file as the main submission. Only ONE submission attempt is allowed. Then, add your TWO PDF files as separate comments to your submission. Do not attach .sql or .txt files as comments. Date and time of comment submission must also be before the deadline or they will be counted as late (and only two total comments for PDF files are allowed). Submission To complete your submission, 1. Click the blue Submit Assignment button at the top of this page. 2. Click the Choose File button, and locate your submission. Make sure you have properly named your sql file so that it matches the format "APAN5310_HW4_UNI.sql" (i.e. for UNI: ab3245 it would be APAN5310_HW4_ab3245.sql). Name your diagram PDF files accordingly and upload those as well. 3. Feel free to include a comment with your submission. 4. Finally, click the blue Submit Assignment button. Grading Rubric All SQL queries are evaluated based on the following criteria: 1. Query logic (i.e. use of correct clauses): 30% 2. SQL syntax (i.e. use of correct attributes and predicates): 20% 3. Expected output (i.e. correct and error-free query execution): 50%

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[SOLVED] MARK3082 Strategic Marketing Term 3 2025

MARK3082 Strategic Marketing Term 3, 2025 Assessment 1: Class contribution All week(s) 14% In tutorials and lectures Description of assessment task MARK3082 is a highly hands-on course, grounded in a strong theoretical foundation. We will reinforce theory through discussions that build on course readings and pre-work. Starting in Week 2, you are expected to come to lectures and tutorials prepared to discuss and/or apply specific theories or concepts from the assigned readings and Moodle pre-work. Each week, your lecturer and tutor will record your contributions. The maximum credit you can earn for discussions is 14%. Contribution formula: Up to 16 points for case study discussions in tutorials ( up to 4 points per case study) Up to 3 points for simulation outcomes Up to 3 points for lecture discussions Maximum: 14 points In Week 5, you will receive individual feedback from your tutor on your current points for case study discussions. Assessment 2: Quizzes Week 4 (during lecture) Week 10 (during lecture) 16% (8% + 8%) Quiz 60 minutes Via Moodle course site Description of assessment task You will have two quizzes, one in Week 4 and one in Week 10, each consisting of 10 multiple-choice questions. All questions will relate to mini-case studies. Your goal is to apply the knowledge you have acquired in the weekly lectures, tutorials, and readings to these mini-case studies. Format Quizzes will be accessible via Moodle. Each quiz will be available for one hour at the beginning of the lecture. After the quiz, we will have the regular lecture for that week’s topic. Assessment 3: Reflections Week 5 Week 10 40% (20% + 20%) Written response Reflection A:1500, Reflection B: 1500 words (+/- 10%) Via Moodle course site Description of assessment task During tutorials, you will work in a pre-defined group on a strategic marketing simulation. Your group will represent the executive branch of a company and will aim to make decisions that will maximise your company’s performance. The simulation consists of 8 rounds. For each round, you will be provided with new information, which you will use to inform. marketing budgetary decisions. At the end of every round, your decisions’ impact on your company’s performance will be evaluated and you will receive new information for the following round. In the reflection pieces, you will be asked to reflect on a) the simulation decisions made until that point, and b) the teamwork related to the management of the company. There will be two reflection parts: Reflection A and B. Specific questions for both reflections will be available on Moodle at least one week prior to the assessment deadline. Although the simulation is a group activity, the reflection is an individual assessment – you will have to answer the reflection questions and submit your answers individually. Format 1500 words (+/-10%), must be 1.5 line spaced, 2.5 cm margins, 12 pt font, Times New Roman or Arial, first page must have your name, zID, and page numbers. References will not be counted in the word limit. Only one group member needs to submit the report for Reflection A. For Reflection B, only one group member needs to submit the report for the first two questions, and every student needs to submit the report for the third question. Assessment 4: Personal branding Report: Week 11 30% Written response: 4 parts (Job advertisement, CV, Cover letter, and Branding strategy) Job advertisement: no predefined length, CV: 2-3 pages, Cover letter: up to 2 pages, Branding strategy: 1 page Report: via Moodle course site Description of assessment task As you approach the completion of your studies, developing a clear and compelling personal brand is essential for successfully transitioning into the workforce. This assessment is designed to give you hands-on experience in crafting the core materials employers review during hiring, so you can enter the job market with confidence and professionalism. For this assessment, you will undertake a mock job application to demonstrate your personal brand in action. Select one real job advertisement and prepare: Ø A tailored résumé (CV) highlighting your key skills and experiences; Ø A bespoke cover letter that communicates your fit and unique value proposition; Ø A concise personal-branding strategy (500 words max +/-10%) outlining how you will position yourself to stand out to employers. Your submission should showcase not only professionalism in formatting and language but also strategic alignment between your credentials and the employer’s needs. This exercise will help you refine your personal-brand narrative and practical application for the job market. Format Document details: CV: Highlight your key achievements (2–3 pages). Cover letter: Explain the fit between you, the position, and the company (1–2 pages). Branding strategy: Detail for tutors and LIC why you chose this specific job ad and outline your personal-branding approach (up to 1-2 pages). Job advertisement: Include the original job ad (no length limit). While submitting the report, please merge all four files and submit them as one document. Please use 1.5 line spaced, 2.5 cm margins, 12 pt font Times New Roman or Arial. Marking Rubrics Assessment 3: Reflections Criteria % Developing (P-C) Exemplary (D-HD) Identifies relevant course topics/skills to integrate with practical experience 30% Course topics or skills are not clearly identified. Limited or no justification of points that lacks connection to course content. Limited or no explanation of link to practical simulation experience. Describes course topics/skills that are mostly relevant to the reflection question. Attempts to justify points using terms, concepts or ideas raised in the course. Provides some explanation of link(s) to practical simulation experience with limited depth. Accurately describes course topics/skills that are relevant to the reflection question. Justifies points using appropriately referenced terms, concepts and ideas raised in the course. Provides insightful explanation of link(s) to practical simulation experience. Applies appropriate frameworks, tools and standards to justify decisions 30% Applies inappropriate frameworks, tools or standards, if at all. Does not adequately consider strengths, limitations or impacts. Does not adequately consider industry standards. Applies frameworks, tools or standards with some contextual links. Outlines some strengths, limitations and impacts. Includes some consideration of industry standards. Applies frameworks, tools or standards that are appropriate to the context. Provides a clear explanation of strengths, limitations and potential impacts. Makes clear links to accepted industry standards. Demonstrates reflective practice in evaluation of own and others’ contributions (applicable only for the Reflection B) 30% Demonstrates minimal self-reflection, with little consideration of personal growth, learning and impact. Provides limited or non-constructive assessment of the group. Shows limited consideration of feedback and self-evaluation. Demonstrates a satisfactory level of self-reflection, acknowledging some areas of personal growth, learning and impact. Provides a fair assessment of the group. Shows some willingness to adapt and adjust approach based on feedback and self-evaluation. Demonstrates a comprehensive and insightful evaluation of personal growth, learning, and impact. Provides a thoughtful, balanced and constructive assessment of the group. Shows an openness and willingness to adapt and adjust approach based on feedback and self-evaluation. Communicates effectively and appropriately 10% Ideas lack logical coherence and/or are difficult to follow. Expresses ideas in a convoluted or over-simplified, making it difficult for the reader to grasp the meaning. Displays limited adherence to academic writing standards, with noticeable deviations or inconsistencies from style. guide. Ideas are generally easy to follow, but with some logical gaps. Expresses ideas and information using mostly clear language. Mostly adheres to academic writing standards (i.e., correct referencing, within word count, etc). Ideas are developed logically and insightfully in a well sequenced, easy to follow format. Expresses complex ideas and information in accessible language. Adheres to academic writing standards (i.e., correct referencing, within word count, etc). Assessment 4: Personal branding Presentation Criteria % Developing (P-C) Exemplary (D-HD) Clarity of communication and visual appeal 30% The materials lack a clear structure and contain multiple errors that hinder understanding. Visual design is inconsistent or distracting. The content is generally understandable but shows occasional lapses in organization or grammar. Visual layout is serviceable but could improve. The materials are exceptionally well‐structured, error‐free, and immediately engaging. Design elements enhance comprehension and professionalism. Fit between the position and applicant characteristics 30% There is little to no alignment between the applicant’s experience and the job requirements. Key skills and accomplishments are missing or irrelevant. The application shows some awareness of the role’s requirements but omits important details or overemphasizes less relevant strengths. The applicant clearly targets the role, highlighting precise experiences and skills that map directly to the job description and company needs. Strength of the personal branding 30% Branding is generic or nonexistent, offering no clear value proposition. The documents read as interchangeable with any other candidate. A basic personal brand is emerging but lacks differentiation or a compelling narrative. Some unique attributes are mentioned. Personal branding is vivid and memorable, presenting a strong, unique value proposition that clearly distinguishes the candidate. Connection between the documents 10% The CV, cover letter, and strategy feel disjointed, with conflicting messages or repeated information. There is no clear narrative thread. Documents reference each other in places but transitions are awkward and cohesion is partial. Some themes recur without full integration. All materials form. a seamless, cohesive narrative, reinforcing key themes and ensuring each document builds logically on the others.

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[SOLVED] CORPFIN 7033 Quantitative Methods Semester 2 2025

Quantitative Methods (M) & (UAC) Semester 2, 2025 Major Project Project Instructions ●   The project is separated into 3 interrelated tasks. All 3 tasks are due at the same time and should be prepared as a single report. The final report due date is Friday the 31st of October at 5pm Adelaide time (GMT  +09:30). Please submit your reports online via MyUni by uploading a single file in Microsoft Word format (either .doc or .docx) through the Assignments tab and associated link. If your assignment is late, please email it to George personally ([email protected]) – Do not submit via MyUni if your assignment is late. ●   Tasks 1, 2 and 3 most closely relate to Topics 2, 8 and 9 as detailed in the course outline. ●   This is a group project. You are only permitted to complete it in groups of 2 or 3 students. Individual submissions, and those from groups larger than 3, are not permitted. Importantly, make sure that you self-allocate into a numbered group on MyUni (you will be shown how to do this during classes in Week 9). When submitting your report, only 1 student from each group should upload the report to MyUni, under your unique group, with the names and student IDs ofall group members included on the front page. ●   The project comprises  15% of your final Quantitative Methods (M) grade. The Grading Rubric is also available on MyUni, giving additional detail on the assessment breakdown. ●   Your final report will be processed through Turnitin  (including Turnitin’s AI writing indicator) as a check for plagiarism so please ensure that you only present your own work. In addition, your final report needs to meet all of the following criteria: Font:                            Times New Roman Font size:                     12 point Page margins:              2.54cm all around (Normal) Page Limit:                   10 pages only (A4, single sided). The page limit should not be exceeded for any reason (i.e., not for appendices, raw data, STATA coding) Appropriate font, font size, page margins, and page limit are all graded against ‘Report Structure and Written Presentation Quality’ (10%). ●   Further Advice: In total, your title, table of contents, and a short introduction should take 1 page (max). Ensure your report is free from spelling and grammatical errors. Ensure your report is clear and well-structured. Ensure your report is written in context and answers questions in context. Make sure it is clear which model is your “Headline Regression Model” (Final answer) Junction is a small town with two suburbs. The data file “Major Project — Data Set” contains data on 535 houses sold in Junction between 2020 and 2025. This data includes the price at which the house was sold, which of two agents sold the house (all houses are sold through an agent by law), the year in which the house was sold as well as data on various characteristics of each house sold (age, size, number of stories etc.). These characteristics serve as possible explanatory variables of sale price. Data definitions follow: OBS =   observation AGE =   age of house in years SHOPS =    1 if house is close to a shopping precinct, 0 otherwise CRIME =   crime rate of the suburb within which the house is located TOWN =   distance in kilometres to the town centre STORIES =   number of dwelling stories OCEAN =   1 if house has an ocean view, 0 otherwise POOL =   1 if house has a pool, 0 otherwise PRICE =   price at which the house was sold (in dollars) AGENT =   selling agent — “W&M” (0) or “A&B” (1) SIZE =   size of the house in square metres SUBURB =   Mayfair (0) or Claygate (1) TENNIS =    1 if house has a tennis court, 0 otherwise SOLD =   year of last sale (2020 to 2025) Your tasks Task 1 - 20% of project grade (recommended length: 2 pages) You are required to provide a comprehensive summary of the data set contained in the “Major Project — Data Set” file. How you choose to do this is entirely at your discretion. However, it is recommended that you consider using both summary statistic and graphical methods while also noting any peculiarities within the data set. Task 2 (including Headline Regression Model) - 50% of project grade (recommended length: 4 pages) You have been hired by Jenny, the wealthy owner of a house on Elm Street in Junction (not included in the data set) to predict the price at which her house will sell. Her house has two stories, is in Claygate, is 164 square metres large, is not near a shopping precinct and is 10 km from the town centre. She estimates that the house is about 11 years old and in a low crime area according to her experiences. Jenny inherited the house from her uncle and is therefore unsure when it was last sold. Some other features of the property can be seen below: You are expected to build a regression model of house prices. In doing so, make sure that you use an appropriate number of predictors to develop your estimates. Once you have constructed an appropriate model, use it to obtain and provide for Jenny’s house: 1.         A point prediction of the sales price which it can be expected to fetch 2.         A 95% interval prediction for this sale price 3.         An estimate of the marginal effect of house size on this sale price 4.        Financial advice on whether Jenny should use “W&M” or “A&B” to sell her house. “W&M” charges a commission of 2.8% whereas “A&B” charges a commission of 3.5% of the final sale price. Jenny, who claims to have some knowledge of regression analysis, has stressed that she thinks you should use a regression model with an R2  of at least 88%. Note: Task 1 directed you to take note of any peculiarities in the data set. There are other additional errors in the data set that you may not have picked up on in Task 1. These will only become clear to you once you start working on Task 2. Several problems can result if you fail to handle these issues correctly, so be mindful to address them, both in your regression application as well as your final report. If resolving any of the errors in the dataset requires you to make assumptions, make sure to clearly state your reasoning and approach in your report. Task 3 - 20% of project grade (recommended length: 3 pages) Please provide a reflective discussion on how you executed Task 2 of the project above. Specifically, consider the following: 1.         Verify that your regression model  does not suffer from any misspecification errors and provide the relevant regression diagnostics which support your findings. 2.        If you found that your model is in fact partially misspecified in part (1) of Task 3 above, explain what you did to ensure that the misspecification only has a minimal impact on your results in Task 2 above. That is, explain how you corrected any misspecifications that occurred during your modelling. 3.        Were there any other oddities in the data set or your model? Explain. 4.        Is there anything else worth mentioning which is relevant to your work or to your results for Jenny?

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[SOLVED] CIVE 462 DESIGN OF STEEL STRUCTURES PRACTICE QUESTIONS 1 Prolog

Department of Civil Engineering CIVE 462 DESIGN OF STEEL STRUCTURES 2025 PRACTICE QUESTIONS 1 1. Details of a single-storey steel industrial building located in Dorval QC are provided in Figure 1. Based on previous construction experience in the area, the following information has been specified by the senior design engineer and the architects: Grade 350w wsections, Grade 300W angle sections and base plate material, ASTM A500 Grade C HSS members, 25 MPa concrete strength, roofing and ceiling materials are elastic in nature, roof contains 1.52 mm thick 38 mm deep steel roof deck, 12.7 mm thick fibre board over the entire deck area, 100 mm of rigid foam insulation, 4 ply asphalt roofing with gravel, standard ductwork, the self-weight of the joists has been estimated at O.15 kPa and the selfweight of the beams at 0.20 kPa. A 1.0 kPa occupancy load is to be considered for the roof. Joists at columns, and those immediately adjacent to columns, will have bottom chord extensions. a) Determine the overall uniform. gravity loads on the roof. b) Design an appropriate square HSS interior column based on gravity loads (nealect connection eccentricities). Column selection tables may be used for an initial member choice; full design calculations must then be camed out. Once you have designed this column, change the grade to 350W hot-rolled and determine the capacity of an HSS which has the same outer dimensions but is one thickness size less. c) Design a typical interior Gerber beam and link beam. Use beam selection tables. For the cantilever length, use a distance of 12% of the span between columns. Ignore deflection for this example. Figure 1

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[SOLVED] CIVE 462 Design of Steel Structures

Course Outline CIVE 462 Course Title:                         Design of Steel Structures Credits:                                 3 Contact Hours:                     (3-3-3) Course Prerequisite(s):        CIVE 318 Course Corequisite(s):         N/A Course Description:              Design of structural steel  members: plate girders, members under combined  loadings, eccentrically  loaded  connections,  composite  floor  systems.  Design  of  single-storey concentrically  braced  frame.  buildings  subjected  to  gravity, wind  and seismic  loading. Introduction to design software. Canadian Engineering Accreditation Board (CEAB) Curriculum Content CEAB curriculum category content Number of AU's Description Math 0 Mathematics include appropriate elements of linear algebra, differential and integral calculus, differential equations, probability, statistics, numerical analysis, and discrete mathematics.   Natural science   0 Natural science includes elements of physics and chemistry, as well as life sciences and earth sciences.  The subjects are intended to impart an understanding of natural phenomena and relationships through the use of analytical and/or experimental techniques.   Complementary studies     0 Complementary studies include the following areas of study to complement the technical content of the curriculum: engineering economics and project management; the impact of technology  on  society;  subject   matter  that  deals  with  the  arts,   humanities  and  social sciences;    management;     oral    and     written    communications;     health    and     safety; professionalism, ethics, equity and  law; and sustainable development and environmental stewardship.     Engineering science     29 Engineering science involves the application of mathematics and natural science to practical problems. They  may  involve  the  development  of  mathematical  or  numerical  techniques, modeling, simulation, and experimental procedures. Such subjects include, among others, applied aspects of strength of materials, fluid mechanics, thermodynamics, electrical and electronic circuits, soil mechanics, automatic control, aerodynamics, transport phenomena, elements of materials science, geoscience, computer science, and environmental science.     Engineering design     29 Engineering  design  integrates  mathematics,  natural  sciences,  engineering  sciences,  and complementary  studies  in  order  to  develop  elements,  systems,  and  processes  to  meet specific needs.  It  is a creative,  iterative, and open-ended  process, subject to constraints which may be governed by standards or legislation to varying degrees depending upon the discipline. These constraints  may also  relate to  economic,  health, safety,  environmental, societal or other interdisciplinary factors. Accreditation units (AU's) are defined on an hourly basis for an activity which is granted academic credit and for which the associated number of hours corresponds to the actual contact time: one hour of lecture (corresponding to 50 minutes of activity) = 1 AU; one hour of laboratory or scheduled tutorial = 0.5 AU. Classes of other than the nominal 50-minute duration are treated proportionally. In assessing the time assigned to determine the AU's of various components of the curriculum, the actual instruction time exclusive of final examinations is used. Graduate Attributes This course contributes to the acquisition of graduate attributes as follows: Graduate attribute KB PA IN DE ET IT CS PR IE EE EP LL Level descriptor   A   D D               I = Introduced;        D = Developed;       A = Applied KB - Knowledge Base for Engineering: Demonstrated competence in university level mathematics, natural sciences, engineering fundamentals, and specialized engineering knowledge appropriate to the program. PA - Problem Analysis: An ability to use appropriate knowledge and skills to identify, formulate, analyze, and solve complex engineering problems in order to reach substantiated conclusions. IN - Investigation: An ability to conduct investigations of complex problems by methods that include appropriate experiments, analysis and interpretation of data, and synthesis of information in order to reach valid conclusions. DE - Design: An ability to design solutions for complex, open-ended engineering problems and to design systems, components or processes that meet specified needs with appropriate attention to health and safety risks, applicable standards, economic, environmental, cultural and societal considerations. ET - Use of Engineering Tools: An ability to create, select, adapt, and extend appropriate techniques, resources, and modern engineering tools to a range of engineering activities, from simple to complex, with an understanding of the associated limitations. IT - Individual and Team Work: An ability to work effectively as a member and leader in teams, preferably in a multi-disciplinary setting. CS - Communication Skills: An ability to communicate complex engineering concepts within the profession and with society at large. Such   abilities include reading, writing, speaking and listening, and the ability to comprehend and write effective reports and design documentation, and to give and effectively respond to clear instructions. PR - Professionalism: An understanding of the roles and responsibilities of the professional engineer in society, especially the primary role of protection of the public and the public interest. IE - Impact of Engineering on Society and the Environment: An ability to analyse social and environmental aspects of engineering activities. Such abilities include an understanding of the interactions that engineering has with the economic, social, health, safety, legal, and cultural aspects of society; the uncertainties in the prediction of such interactions; and the concepts of sustainable design and development and environmental stewardship. EE - Ethics and Equity: An ability to apply professional ethics, accountability, and equity. EP - Economics and Project Management: An ability to appropriately incorporate economics and business practices including project, risk and change management into the practice of engineering, and to understand their limitations. LL - Life-Long Learning: An ability to identify and to address their own educational needs in a changing world, sufficiently to maintain their competence and contribute to the advancement of knowledge.  

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[SOLVED] ECON 221 - Statistical Methods I Problem Set 1

Department of Economics ECON 221 - Statistical Methods I Problem Set # 1 Instructions: •  Please, write your answers in a separate file (i.e. Word), save it as a PDF document and name it with your last name and your student ID number linked by an underscore (i.e. Yourname 12345678.pdf). •  Answer all questions.  Clearly indicate which question each answer belongs to. • Include only the relevant parts of the R output, summarize the results in a separate table, if needed. • You need to upload on Moodle 2 files: 1.  The PDF file described above with your answers and relevant R output. 2.  Your R code file, with comments, named the same way as the PDF file, with an extension *.R (i.e. Yourname 12345678.R). Your R code must NOT include your answers. I. Problems - Use R for your computations. You have to show your work.  No credit without an explanation (20 marks each). 1.  Consider the Wages data set posted on Moodle:  (2 marks each) (a)  Are there any missing values in any of the variables in the data set? (b)  If there are, how would you remove them? (c)  Create  a new variable,  WAGE,  which is the exponential of LNWAGE.   Is this new variable categorical or numerical?  Qualitative or quantitative?  Nominal, ordinal, interval or ratio? (d)  Create a histogram for that variable by choosing the appropriate number of bins. (e)  Compute the mean and median for the wage variable. Which is higher? (f)  Compute the skewness of the WAGE variable.  Is it skewed, left or right, why? (g)  Compute the 5-number summary for that variable and produce a boxplot.  Interpret the numbers. (h)  Compute the range, IQR, min, max, population and sample variance and standard deviation for the WAGE variable. (i)  Are there diferences between population and sample measures for variances and standard devia- tions? Why? (j)  Compute and interpret the maximum value of the z-score for the WAGE variable. 2.  Construct a new character variable, JOB, which contains  “PROF” if PROF=1,  “CLER” if CLER=1, etc.  (5 marks each) (a)  Is this  new variable  categorical or  numerical?   Qualitative or  quantitative?   Nominal,  ordinal, interval or ratio? (b)  Create appropriate table(s) and chart(s) for the JOB variable (frequency distribution, pie chart, Pareto chart, barplot). (c)  Convert the JOB variable into a factor variable and present the mean WAGE, AGE, EX for each group. (d)  Briefly interpret your findings in part (c) in terms of how wages (WAGE), age (AGE) and expe- rience (EX) vary across job categories (JOB). 3.  Now consider the relationships between variables (5 marks each): (a)  Provide a scatter plot between WAGE on the vertical axis and AGE on the horizontal.  Label the  axes  and provide  a title  for the plot.   Provide  intuition  about the observed  nature of the relationship. (b)  Compute and interpret the covariance and correlation coefficient for WAGE and AGE. (c)  Redo (a) and (b) with the education variable (ED) and experience variable (EX), instead of AGE. (d)  Compute, present and interpret the entire correlation matrix between WAGE, AGE, ED, EX, FE and UNION. 4.  Now consider relationships between different groups (5 marks each): (a)  Generate 2 new variables, WAGE F and WAGE M for females and males, respectively, depending on the variable FE (FE=1 for WAGE F). Compute the mean and median for those 2 variables. Which one is higher across the 2 groups? What does the comparison of mean and median tell us about the symmetry or skewness of the wage distributions? (b)  Repeat (a) with the non-white (NONWH) and union (UNION) variables instead of FE variable. (c)  Present a table ranking from highest to lowest the mean wage for the different job categories. Does the order make sense? (d)  Briefly summarize your results in parts (a)-(c), highlighting the factors that contribute to wage differences and the direction of their effects. 5.  Now consider some probabilities (4 marks each): (a)  Calculate the probability that a person taken at random is a member of a union (i.e.  UNION=1). (b)  Calculate the probability that a person taken at random is a married female (i.e.  MARR=1 and FE=1). (c)  Calculate the probability that a person makes less than $9 an hour given they are female. (d)  Present a contingency table between job category (JOB) and union membership (UNION). (e)  Continue  with  part  (d)  and  calculate  the  respective  joint,  marginal,  and  conditional  proba- bilities  for  all  categories.   (i.e.    P(UNION),  P(JOB),  P(JOB&UNION),  P(JOBjUNION),  and P(UNIONjJOB)). APPENDIX - Data Set Variables Description 1. ED - years of education. 2. SOUTH - 1 if person resides in the South. 3. NONWH - 0 if person is Caucasian. 4. HISP - 1 if person is Hispanic. 5. FE - 1 if person is female. 6. MARR - 1 if person is married and spouse is present in the same household. 7. MARRFE - 1 if the person is a married female. 8. EX - years of experience on labour market. 9. EXSQ - years of experience on labour market squared. 10. UNION - 1 if union member. 11. LNWAGE - natural logarithm of hourly wage (in USD). 12. AGE - age in years. 13. MANUF - 1 if person works in manufacturing sector. 14. CONSTR - 1 if person works in construction sector. 15. MANAG - 1 if person works in management or administration. 16. SALES - 1 if person works in sales sector. 17. CLER - 1 if person is an o ce worker. 18. SERV - 1 if person works in services sector. 19. PROF - 1 if person is a professional or technical worker.

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[SOLVED] ESS103H1F Geology in Public Issues Fall 2025

ESS103H1 F Geology in Public Issues Fall 2025 Syllabus Course Overview Geologic hazards: earthquakes, volcanoes, landslides, tsunamis. The distribution and politics of natural resources, including petroleum and ore deposits. Nuclear power and nuclear waste disposal. Global change: the geologic record of hot and cold climates, and how the earth survives. ESS103H1 is primarily intended as a science Distribution Requirement course for Humanities and Social Science. Course Learning Outcomes By the end of this course students will be able to: -make better informed decisions about environmental issues in the news -understand various geologic energy resources and their advantages and disadvantages -improve their science literacy and communication skills -create a scientific Story Map to communicate scientific research

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[SOLVED] FEMST 20 Introduction to Gender and Power Fall Quarter 2025

FEMST 20: Introduction to Gender and Power Fall Quarter 2025 Course Description: This course introduces students to the foundational concepts in the field of Feminist Studies. Throughout this course students will not only engage with key texts but learn about the context and history of feminism, the framework used by theorists and activists alike, and the structural networks which make up gendered, racial, sexed, and classed hierarchies. This course asks students to engage with their own experiences of gender and power and to think critically of feminist methods for knowing and being. Learning Objectives: · Students will define and analyze structural inequities through an introduction to threshold concepts in Feminist studies throughout all readings for the course. These include: social construction of gender; privilege and oppression; intersectionality; queer theory, transgender studies and feminist praxis. · Students will identify similarities and differences in marginalized people’s lives and explain how various social factors (gender, race, ethnicity, class, age, nationality, sexuality, religion, body size, and disability) shape individual identity, experience, social position, and power relations. · Students will be asked to evaluate how feminist research and theory questions “objectivity” and “normativity” throughout discussions. · Students will practice applying a feminist lens to connect personal, political, and social concepts in weekly reflections. · Students will design a creative project that analyzes a feminist/queer/transgender organization, NGO, social policy agency or artists’ collective in order to apply feminist philosophy, theory, oraxis and history toward understanding pressing social problems of our times. Students will analyze the problem that the organization is attempting to tackle, how are they approaching questions of empowerment, agency, ending isolation, building power by analyzing their organizational website, social media, annual reports, YouTube videos etc. (Detailed prompt will be provided by the 6th week of the quarter Required Texts: · Launius, Christie and Holly Hassel. Threshold Concepts in Women’s and Gender Studies, 2nd Edition. New York: Routledge, 2018. Green Cover (~$40, new) Note: You may use the e-textbook or paperback version; the book can also be rented on Amazon · Bushra Rehman. Roses in the Mouth of a Lion · Additional assigned readings are posted on this course’s CANVAS page. Grading Autobiographical Reflection 5X4=20 Lecture Section: 15 points Book Review = 25 points Final Project 40points Grade Breakdown Letter Percentage A 100%-93% A- 92.99%-90% B+ 89.99%-87% B 86.99%-83% B- 82.99%-80% C+ 79.99%-77% C 76.99%-73% C- 72.99%-70% D+ 69.99%-67% D 66.99%-60% F 59.99%-0% Assignments Weekly Reading · Each week you will be required to read 3-4 texts which work together to provide an overview of the weekly topic. Please come to class having read most of the weekly readings. I expect that on Tuesdays you would have covered 50% of the readings assigned for the week, and by Thursdays the rest 50%. My lectures will cover the first 50% on Tuesdays (usually the first 2 readings), and the rest on Thursdays. During your discussion sections your TA will help you with the readings for the entire week. Each TA will administer various brief exercises during the lecture section to ensure you are engaging with the materials. This will constitute brief reflections on the readings, or discussions or zine making (see description in the next item). Lecture Section: 15 points Your TA’s will administer various modalities to understand (1) your understanding of and engagement with the assigned readings, and (2) start making connections between these materials and the world. Your TA will provide details in their TA sections. Autobiographical Reflection Writing Exercises (20 points) · Four Autobiographical free writing exercises. Students will be required to write experiences from their own lives which connect to the readings during specific weeks. You will be alerted on the Tuesday of the week if you are expected to write a reflection related to any of the readings for that week. All reflections will be due within a week of the reading. Thus, much like a pop up quiz, the reflection writing exercise will pop up and you will have one week to submit the writings. You will submit these on CANVAS (starting from second or third week of the quarter). I will provide feedback by middle of the following week. (5X4=20). Book Review (25 points) We are reading a witty coming of age memoir by Bushra Rehman. You are expected to produce a 2-page review of the novel. You are expected to describe the plot, analyze the representation of LGBTQ characters. We will discuss this more by end of October. Book Review is due by midnight Sunday, November 16th. Final Project (40 points) A report on an organization (NGO, local collective, cultural or arts organizations) 4pages The organization needs to address issues related to Lesbian, Gay, Bisexual, Transgender and Queer politics, and communities. This project is due on December 09 via CANVAS. Course Policies: This course will be held synchronously online till October 05th. We will be meeting during scheduled lecture hours online, as well in-person for the discussion sections. There is a weekly schedule but no scheduled office hour for the first week. Please make sure to give me and your TA team a full 48hrs to respond. Please be sure to include your name and proper language when emailing. It is not appropriate for your email to read like a text. A proper email should have a greeting, your question or concern, information with which to identify you, and a closing. Finally, we will not respond to emails that are answerable by consulting your syllabus or the CANVAS page. Otherwise, your teaching team is happy to clarify any questions or discuss any material with you. I am happy to read drafts of your book review and final projects. Questions about all assignments will be entertained toward the end of class periods, or during office hours. REMEMBER: when you email me or your TA, please ensure to Cc each of us. This way we can respond to your queries as a team. CANVAS: All course materials, lectures, assignments, instructions, and resources will be available on the class website. It is crucial that you familiarize yourself with our class page and look there for anything you might need for the course first. Mutual Respect: Some of the topics and themes in this course might be challenging and as such I expect that we all maintain a virtual space of respect. We are all coming from different experiences and I expect everyone to be able to participate openly without judgement. There are no stupid questions. However, there is inappropriate language. This will not be accepted and includes, slurs, hate speech, and/or problematic (racist, sexist, homo/transphobic, ableist, ect.) posts. Those who violate this policy will be given a warning email by me, if it continues, they will be dropped from the course. Additionally remember, the online medium can be difficult to ascertain tone and emphasis. Be generous and clear when engaging with classmates. Grades: You can expect to receive grades within a week of the assignment due date for the Reflection Exercises. If you would like to discuss a grade you must wait 48 hours before contacting myself and/or your TA about your grade. This is a 48hrs cool off period to ensure we maintain our environment of mutual respect. Your TA’s take great care in grading and are happy to talk to you about your work as long as you respect their labor and efforts. We do not do any grade bumping in this class and will not respond to emails which request bumping grades up. If you would like to discuss your grade it is imperative that you contact your TA prior to the last week of class. Late Assignments: It is important that you try to keep up with all course work. If you need an extension, you must contact your TA at least 24 hours prior to the due date. Unless emergent, extensions will not be granted day of. Please contact your TA ASAP if something comes up.

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[SOLVED] ESS103 Rough Draft Autumn 2025

ESS103 Rough Draft Autumn 2025 ESS103 Term Assignment Part II. This assignment handout includes the two topic choices that you may choose from. Due Oct 5 th, 2025. This assignment is intended to increase your skills in scientific literacy, the ability to use evidence and data in order to evaluate scientific information. Your job is to take a complicated topic and make it both simple and interesting for your audience. Consider your audience as your peers, these are all non-science students. This is an individual assignment, not group work. To accomplish this task you will demonstrate skills in choosing/paraphrasing/citing peer reviewed scientific journal articles to properly research one of the assigned topic choices and create a visually appealing and informative Story Map. This Story Map will include the revised rough draft as well as your revised individual maps in addition to images, videos, and potentially even audio clips and your map tutorials (if relevant) if you like as you tell your story in an interesting and impactful way. Please keep in mind as you are writing the difference between synthesis and summary. A summary is an objective, short written presentation in your own words of ideas, facts, events, in a SINGLE PIECE OF TEXT. A synthesis is a “combination” of SEVERAL TEXTS into a single one, which aims to create an understanding or original perspective of the information in those texts. Your goal is a synthesis, so you should not be using fact after fact from one paper all in a row - which would be a summary. The rough draft should contain all of the text that you intend to include in your final story, and be written in paragraph format - report style. (no thesis required). You will have the opportunity to make improvements to the text that you will include in the Story Map based on TA feedback at the rough draft stage, but you should treat the rough draft as a full, text based report - not an annotated bibliography or collection of research bullet points. The top skills that you will be assessed upon include: choosing and using peer reviewed journal article sources, citing properly both in-text and in the end references in the APA 7th Edition format, and your inclusion of geoscientific content - properly paraphrased - from those scientific sources. You will prove that you have indeed used peer reviewed journal sources using Ulrichs Web screenshots. Please see this sample marking rubric, as it is very similar to yours, Fig 1. Fig 1. Find the original marking rubric on Quercus, it is very similar to this one. Although this one reads "autumn and ESS205" it is very similar to yours for this autumn ESS103 course.

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