Scenario # 1 Honesty Your team works for a small company, SmallCorp Consultants. The company's only contract at present is a $6M year-long project for Bluestone Mining to write a software system to analyse geological data. Your team discovered a way of designing the system that means that the project can be completed in 2 months, rather than 1 year, and at a cost of only $1M. Your boss tells your team to keep quiet and ignore the "better solution" as they want to keep the team working on the project as long as possible, and Bluestone has already indicated that they are happy to pay the $6M as they believe the project is worth that much. What are the actions that your team will take? · Report this situation to the higher management authorities of the company. Do not directly tell the client company for the interest of our employer. ● Also record and document that we have reported this finding to the management team, to prevent us being held accountable of ethical misconducts if anything happens in the future. · Document down and justify the possibility of designing the system in 2 months, and cost of only $1M. Who should be responsible? · If we report this finding, then we should not be liable for this situation. The management team of SmallCorp Consultants should be responsible. Share with the class the ethical conducts that are considered? · IEEE Principle 2 – CLIENT AND EMPLOYER Software engineers shall act in a manner that is in the best interests of their client and employer, consistent with the public interest. In particular, software engineers shall, as appropriate: · ACM Code of Ethics and Professional Conduct 1.3 Be honest and trustworthy. Honesty is an essential component of trustworthiness. A computing professional should be transparent and provide full disclosure of all pertinent system capabilities, limitations, and potential problems to the appropriate parties. Making deliberately false or misleading claims, fabricating or falsifying data, offering or accepting bribes, and other dishonest conduct are violations of the Code. Scenario # 2 ICT Privacy · ACS Code of Professional Conduct 1.2.3. Honesty not knowingly mislead a client or potential client as to the suitability of a product or service; You have a part-time job working for the University's ICT unit. You have been assigned to work in a team that tests on the development changes made to the Sydney Student portal. As part of this job, your team has access to a copy of all course and student data. Your team is able to see the students' results. Some of the students are known to your team while others are not. What are the actions that your team will take? · Report this situation to our manager. · Stop this job for now to prevent further breach of student privacy. · Use testing data (anonymized) instead of real data. Are there any privacy issues being bridged? · Yes, results of students should be confidential and only accessed by themselves and the university. Only the students themselves can give permission to who is allowed to see. · Unless the students give permission for the university to use their results for ICT changes, then no one should be able to see their results and names. Share with the class the ethical conducts that are considered? · ACM Code of Ethics and Professional Conduct 1.6 Respect privacy · ACS Code of Professional Conduct 1.2.1. The Primacy of the Public Interest Scenario # 3 Liability Your team has written a simple game app. It includes a simple function called left-pad which pads out a string. The entire code source has been made open source. Someone uses your team's left-pad function in their string manipulation code. Someone uses the string manipulation library in their data logging toolkit. Someone uses the logging toolkit in a traffic control system. Your team's code has a bug. It crashed the traffic control system and 3 people were killed in ensuing car accidents. Is your team liable for the deaths? · According to most open-source licenses, the developer is not liable for problems caused by their software. · When software is a service, developers are generally not liable. · So, we can say our team is not liable for the deaths. Who should be responsible? · The people who use the logging toolkit and develop a traffic control system. · They are the direct developers who did not test the code of their product properly. What are the actions that your team will take? · We believe we are not held responsible for the accidents. · We will assist the process of bug fixing. Share with the class the ethical conducts that are considered? · ACM Code of Ethics: 2.2 Acquire and maintain professional competence. 2.1 Strive to achieve high quality in both the processes and products of professional work. · IEEE Principle 5 – MANAGEMENT 5.01 Ensure good management for any project on which they work, including effective procedures for promotion of quality and reduction of risk. · IEEE - Product Software engineers shall ensure that their products and related modifications meet the highest professional standards possible.
002499 ACCOUNTING INFORMATION SYSTEMS ECOMMRCE 1000 LECTURER: INDRIT TROSHANI Official Reading Time: 10 mins Writing Time: 180 mins Total Duration 190 mins Instructions to Candidate: 1. Answer ALL SIX (6) questions. 2. This is a Closed Book examination. You should answer all questions in the answer book and should begin each answer on a new page in the answer book. 3. The marks shown add up to 100. This examination constitutes 70% of the total assessment. Please allocate your time according to the marks shown. 5. Please allocate your time according to the percentage contribution of the questions. 6. Examination materials must NOT be removed from the examination room. Materials: • 1 Blue answer book • No materials allowed QUESTION 1 (1) Give three examples each of the advantages and the disadvantages of an ERP system with a centralized database. How you can increase the chance of a successful ERP implementation? [8 marks] (2) Another question worth 2 marks goes here. [2 marks] (4) What is information integrity? Illustrate your answer using examples from the above tables. [3 marks] (5) Explain four advantages of using relational databases. Illustrate with examples. [4 marks] [Total mark – Question 1 = 17 marks] QUESTION 2 (1) Another question worth 6 marks goes here. [6 marks] (2) Another question worth 3 marks goes here. [3 marks] (3) Another question worth 2 marks goes here. [2 marks] (4) Ajax Manufacturing installed a new barcode based inventory tracking system in its warehouse. To close the books each month on a timely basis, the six people who work in the warehouse must scan each item in a 36-hour period while still performing their normal duties. During certain months, when inventory expands to meet seasonal demands, the scan takes as many as 30 hours to complete. In addition, the scanners do not accurately record some inventory items that require low operating temperatures. A recent audit brought to management’s attention that the inventory records are not always accurate. Which aspect(s) of feasibility did Ajax fail to consider prior to installing the inventory tracking system. [4 marks] [Total mark – Question 2 = 15 marks] QUESTION 3 (1) Distinguish between document flowcharts, system flowcharts, data flow diagrams, and program flow charts. How are they similar? How are they different? [4 marks] (2) Describe four control procedures that organisations should have in place to ensure that only authorised users access the system and that user access is limited according to their responsibilities. [4 marks] (3) What are some of the consequences to a company that makes a poor decision in selecting a new AIS? [2 marks] (4) Another question worth 8 marks goes here. [8 marks] [Total mark – Question 3 = 18 marks] QUESTION 4 Businesses often modify or replace their financial information system to keep pace with their growth and take advantage of improved IT. This requires a substantial time and resource commitment. When an organisation changes its AIS, a systems analysis takes place. (1) Explain the purpose and reasons for surveying an organisation’s existing system. [6 marks] (2) Explain the activities commonly performed during systems analysis. [6 marks] (3) Systems analysis is often performed by a project team composed of a systems analyst, a management accountant, and other knowledgeable and helpful people. What is the accountant’s role in systems analysis? [6 marks] [Total mark – Question 4 = 18 marks] QUESTION 5 Question 5 goes here [Total mark – Question 5 = 17 marks] QUESTION 6 (1) Sara Jones owns a rapidly growing retail store that faces stiff competition due to poor customer service, late and error-prone billing, and inefficient inventory control. To continue its growth, its AIS must be upgraded but Sara is not sure what it wants the AIS to accomplish. Sara has heard about prototyping, but does not know what it is or whether it would help. How would you explain prototyping to Sara? Include an explanation of its advantages and disadvantages as well as when its use is appropriate. What is the difference between authentication and authorisation? [7 marks] (2) Clint Grace has been business over 30 years and has definite ideas about how his ten retail stores should be run. He is financially conservative and is reluctant to make expenditures that do not have a clear financial payoff. Store profitability has declined sharply and customer dissatisfaction is high. Store managers never know how much inventory is on hand and when purchases are needed until a shelf is empty. Clint asks you to determine why profitability has declined and to recommend a solution. You determine that the current AIS is inefficient and unreliable and that company processes and procedures are out of date. You believe the solution is to redesign the systems and business processes using BPM. What are some challenges you might face in redesigning the system? How will you present your recommendations to Clint? What are the limitations, if any, of relying on the results of penetration tests to assess the overall level of security? [8 marks] [Total mark – Question 6 = 15 marks]
COMP9313 2021T3 Project 3 (20 marks) Set Similarity Join Using Spark on Google Dataproc Problem Definition: Given two collections of records R and S, a similarity function sim(., .), and a threshold τ, the set similarity join between R and S, is to find all record pairs r (from R) and s (from S), such that sim(r, s) >= τ. In this project, you are required to use the Jaccard similarity function to compute sim(r, s). Given the following example, and set τ=0.5, the result pairs are (r1, s1) (similarity 0.75), (r2, s2) (similarity 0.5), (r3, s1) (similarity 0.5), (r3, s2) (similarity 0.5). Input files: You are required to do the “self-join”, that is, a single input file is given, in which each line is in format of: “RecordId list”, and this file serves as both R and S. An example input file is as below (integers are separated by space): 0 1 4 5 6 1 2 3 6 2 4 5 6 3 1 4 6 4 2 5 6 5 3 5 This sample file “tiny-data.txt” can be downloaded at: https://webcms3.cse.unsw.edu.au/COMP9313/21T3/resources/69118 Another sample input file “flickr_small.txt” can be downloaded at: https://webcms3.cse.unsw.edu.au/COMP9313/21T3/resources/69119 Output: The output file contains the similar pairs together with their similarities. Each line is in format of “(RecordId1,RecordId2)tSimilarity” (RecordId1
Semester One Final Examinations, 2021 STAT1201 Analysis of Scientific Data Exam information Course code and title STAT1201 Analysis of Scientific Data Semester Semester 1, 2021 Exam type Online, non-invigilated, final examination Exam technology Exam accessed through the Exam Tool in Blackboard Exam date and time Your examination will begin at the time specified in your personal examination timetable. If you commence your examination after this time, the end for your examination does NOT change. The total time for your examination from the scheduled starting time will be: 2 hours 10 minutes (including 10 minutes reading time during which you should read the exam paper and plan your responses to the questions). A 15-minute submission period is available for submitting your examination after the allowed time shown above. If your examination is submitted after this period, late penalties will be applied unless you can demonstrate that there were problems with the system and/or process that were beyond your control. Exam window You must commence your exam at the time listed in your personalised timetable. You have from the start date/time to the end date/time listed in which you must complete your exam. Permitted materials During the exam you may access your own notes and any of the material on the STAT1201 Blackboard and Edge sites. A Casio fx-82 series or UQ approved calculator may be used. You may not make use of any other material. This includes web sites,books, or other software Required materials Ensure the following materials are available during the exam: You will need access to RStudio to complete the exam. Instructions The exam involves a total of 50 multiple-choice questions split into four scenarios. You may attempt the scenarios and questions in any order and return to make changes if needed. The Exam is accessed through the STAT1201 Blackboard page under Examinations. Answers are automatically recorded so there is no submission process at the end of the exam. Who to contact If you have any concerns or queries about a particular question, or need to make any assumptions to answer the question, state these using the ‘Assumptions’ link at the bottom of the exam. If you experience any technical difficulties during the exam, join Zoom 835 0875 5861 (via app or by dialling +61 2 8015 2088), or email [email protected] with details of the issue. submissions Answers are automatically recorded so there is no submission process at the end of the exam. Important exam condition information Academic integrity is a core value of the UQ community and as such the highest standards of academic integrity apply to all examinations, whether undertaken in- person or online. This means: • You are permitted to refer to the allowed resources for this exam, but you cannot cut-and-paste material other than your own work as answers. • You are not permitted to consult any other person – whether directly, online, or through any other means – about any aspect of this examination during the period that it is available. • If it is found that you have given or sought outside assistance with this examination, then that will be deemed to be cheating. Undertaking this online exam deems your commitment to UQ’s academic integrity pledge as summarised in the following declaration: “I certify that I have completed this examination in an honest, fair and trustworthy manner, that my submitted answers are entirely my own work, and that I have neither given nor received any unauthorised assistance on this examination”. MDMA and post-traumatic stress disorder A study investigated if psychotherapy combined with limited administration of 3,4 Methylenedioxymethamphetamine (MDMA) can reduce symptoms of post-traumatic stress disorder. Severity of symptoms was measured via the CAPS-IV score with higher scores indicating more severe symptoms. Subjects recruited to the study were randomly allocated to one of the three dosage levels (Low – 40 mg, Medium – 100 mg, High – 125 mg). The primary outcome was the reduction in CAPS-IV score one month after the end of treatment. A secondary outcome was whether the subject experience a drop of 20% or more in CAPS-IV score. Download the csv file using the link below and read it into RStudio: MDMA.csv The data contains the following variables: • Before - CAPS-IV scores before treatment. • After - CAPS-IV scores at the one month after the second treatment session. • Change - Reduction in CAPS-IV scores (Before – After). • Drop20 - Was a 20% reduction in CAPS-IV score achieved (TRUE or FALSE). • Dose – Dosage level of MDMA given (Low – 40 mg, Medium – 100 mg, High – 125 mg). Question 1 Based on the information above, which of the following best describes the study? Answer: Randomised comparative experiment Distractors: ❑ Observational study ❑ Randomised complete block design ❑ Randomised comparative double-blind experiment. Question 2 Mean CAPS-IV score before treatment in low dose group Answer: 78.5 Distractors: ❑ 78 ❑ 77.75926 ❑ 62.2963 Question 3 Researchers conduct a one-way ANOVA to determine if there is a difference in the mean reduction in CAPS-IV for the three dosage levels of MDMA. Which of the following describes the null hypothesis that is test in a one-way ANOVA? Answer: The mean change in CAPS-IV score is the same for all dosage levels. Distractors: ❑ The mean change in CAPS-IV score is zero for all dosage levels. ❑ The mean change in CAPS-IV score is different for all dosage levels. ❑ The mean change in CAPS-IV score is different for at least one dosage level. Question 4 What is the residual degrees of freedom in the one-way ANOVA to compare dosage level? Answer: 51 Distractors: ❑ 2 ❑ 52 ❑ 53 Question 5 What is the Total Sum of Squares for the one-way ANOVA to compare dosage levels? Answer: 297.43 Distractors: ❑ 56.26 ❑ 241.17 ❑ 303.04 Question 6 Based on the F-test for the one-way ANOVA to compare the dosage levels, you can conclude there is Answer: strong evidence to suggest that there is an effect of MDMA dosage level on the mean change in patient’s CAPIS-IV score (p < 0.01) Distractors: ❑ no evidence to suggest that there is an effect of MDMA dosage level on the mean change in patient’s CAPIS-IV score (p >0.1) ❑ weak evidence to suggest that there is an effect of MDMA dosage level on the mean change in patient’s CAPIS-IV score (p < 0.1) ❑ moderate evidence to suggest that there is an effect of MDMA dosage level on the mean change in patient’s CAPIS-IV score (p < 0.05) Question 7 What is the R2 value for this one-way ANOVA? Answer: 0.1892 Distractors: ❑ 0.1574 ❑ 0.8108 ❑ 0.4349 Question 8 Which of the following is NOT an assumption of the one-way ANOVA Answer: Linear relationship between mean change in CAPS-IV score and dosage level. Distractors: ❑ The subjects recruited to the study are independent. ❑ The variability of the change in CAPS-IV scores does not depend on the dosage level. ❑ The change in CAPS-IV score has a normal distribution. Question 9 Which of the following plots would be useful in assessing model assumptions? Answer: Normal probability plot of the residuals from the one-way ANOVA Distractors: ❑ Normal probability plot of the changes in CAPS-IV score ❑ Scatterplot of the fitted values from the one-way ANOVA against dosage level. ❑ Scatterplot of Before against After CAPS-IV scores. Question 10 The researchers would like to understand which (if any) dosage levels of MDMA result in different mean changes in CAPS-IV score. Using Tukey’s Honestly Significant Difference, the researchers are able to conclude that the mean change in CAPS-IV score are different at the 5% (familywise) significance level for the following dosage levels: Answer: Low – Medium, and Low – High Distractors: ❑ Only Low – High ❑ Low – High, and Medium – High ❑ Low – Medium, Low – High, and Medium – High Question 11 A secondary outcome for the experiment was whether subjects experienced a 20% drop in CAPS-IV scores at one month after the second treatment session. How many subjects in the study experienced a 20% drop in their CAPS-IV score? Answer: 26 Distractors: ❑ 18 ❑ 22 ❑ 29 Question 12 What proportion of participants received a low dose of MDMA and experienced a 20% drop in their CAPS-IV score? Answer: 0.074 Distractor: ❑ 0.154 ❑ 0.222 ❑ 0.160 Question 13 If there was no association between experiencing a 20% drop in CAPS-IV score and dosage level, what is the expected count for subjects in the low dose group experiencing a 20% drop in CAPS-IV score? Answer: 8.667 Distractors: ❑ 8.308 ❑ 12 ❑ 9 Question 14 What is the value of the 2 statistic used to test for an association between experiencing a 20% drop in CAPS-IV score and dosage level? Answer: 9.049 Distractors: ❑ 4.352 ❑ 5.217 ❑ 7.273 Question 15 What is the degrees of freedom for the 2 test in Question 12? Answer: 2 Distractors: ❑ 3 ❑ 5 ❑ 6 Question 16 Based on this analysis, you can conclude that there is Answer: moderate evidence to suggest that there is an association between dosage level and experiencing a 20% drop in CAPS-IV score (p = 0.0108) Distractors: ❑ no evidence to suggest that there is an association between dosage level and experiencing a 20% drop in CAPS-IV score (p = 0.1135) ❑ weak evidence to suggest that there is an association between dosage level and experiencing a 20% drop in CAPS-IV score (p = 0.0736) ❑ moderate evidence to suggest that there is an association between dosage level and experiencing a 20% drop in CAPS-IV score (p = 0.0263) Age estimation from blood cells DNA methylation is a known biomaker for age and has been applied in forensic investigations. The aim is to construct a model which accurately predicts a person’s age from DNA methylation data obtained from blood samples. The blood samples were taken from people aged between 1 year and 90 years old. The percentage of DNA methylation was measured for two genes ELOVL2 and PDE4C. Download the csv file using the link below and read it into RStudio: DNA.csv The data contains the following variables: • Age - Chronological age (years) • Gender – (Female/Male) • ELOVL2 - % of DNA methylation at ELOVL2 • PDE4C - % of DNA methylation at PDE4C Question 1 What is the interquartile range of the ELOVL2 variable? Answer: 42.69 Distractors: ❑ 46.00 ❑ 29.55 ❑ 37.69 Question 2 Based on a box plot of ELOVL2, how would you describe the shape of its distribution? Answer: Approximately symmetric Distractors: ❑ Symmetric with outliers ❑ Skewed to the right ❑ Skewed to the left Question 3 Which of the following best describes the relationship between Age and ELOVL2? Answer: A strong positive linear relationship (r = 0.96) Distractors: ❑ A positive non-linear relationship ❑ A strong negative linear relationship (r = -0.96) ❑ A weak positive linear relationship (r=0.32) Question 4 What is the slope of the least-squares line for the relationship between Age and ELOVL2? Answer: 0.7571 Distractors: ❑ 2.2376 ❑ 0.8117 ❑ 0.8731 Question 5 What is the margin of error in a 95% confidence interval for the slope of the relationship between Age and ELOVL2? Answer: 0.0547 Distractors: ❑ 0.0536 ❑ 0.1124 ❑ 0.0273 Question 6 Based on the linear model, what is the estimated Age of a person whose blood sample has 60% DNA methylation at ELOVL2? Answer: 47.662 Distractors: ❑ 50.121 ❑ 45.948 ❑ 63.236 Question 7 Can we improve the model of Age by including the percentage of DNA methylation at both ELOVL2 and PDE4C? We can address this question using a multiple regression model of Age where the explanatory variables are ELOVL2 and PDE4C. Assuming there is no interaction term, the PDE4C coefficient in the multiple regression model is Answer: 0.2446 Distractors: ❑ 0.5261 ❑ 0.1112 ❑ 0.7683 Question 8 What is the line sum of squares (or explained sum of squares) for the multiple regression model in question 7? Answer: 19101 Distractors: ❑ 18989 ❑ 20450 ❑ 17365 Question 9 Based on the normal probability plot of residuals for the multiple regression model fitted in Question 7 we can conclude: Answer: The distribution of the residuals appears roughly normal. Distractors: ❑ The distribution of the residuals is skewed to the right. ❑ The distribution of the residuals is skewed to the left. ❑ The residuals have a non-constant variance. Question 10 Which of the following plots could not be used to detect a violation of the linearity assumption for the multiple regression model: Answer: Normal probability plot of residuals Distractors: ❑ Scatter plot of residuals against fitted values ❑ Scatter plot of residuals against values of ELOVL2 ❑ Scatter plot of residuals against values of PDE4C Question 11 Assume that the model assumptions are satisfied. Based on the multiple regression model, you can conclude that there is Answer: moderate evidence to suggest an association between Age and percentage of DNA methylation at PDE4C, after taking into percentage of DNA methylation at ELOVL2 (p 0.1). ❑ weak evidence to suggest an association between Age and percentage of DNA methylation at PDE4C, after taking into percentage of DNA methylation at ELOVL2 (p < 0.1). ❑ strong evidence to suggest an association between Age and percentage of DNA methylation at PDE4C, after taking into percentage of DNA methylation at ELOVL2 (p < 0.01). Question 12 Based on the multiple regression model, what is the residual for the person Aged 51 years whose blood sample has 71.63% DNA methylation at ELOVL2 and 62.06% DNA methylation at PDE4C? Answer: -3.49 Distractors: ❑ -5.46 ❑ 3.49 ❑ -2.76 Question 13 Based on the multiple regression model, construct a 95% prediction interval for the age of a person whose blood sample has 40% DNA methylation at ELOVL2 and 50% DNA methylation at PDE4C. The upper limit for this prediction interval is Answer: 44.87 (years) Distractors: ❑ 24.93 (years) ❑ 48.16 (years) ❑ 43.27 (years) Question 14 Overall, the multiple regression model suggests that old age is associated with Answer: a high percentage of DNA methylation at both ELOVL2 and PDE4C. Distractors: ❑ a high percentage of DNA methylation at ELOVL2 and low percentage of DNA methylation at PDE4C. ❑ a low percentage of DNA methylation at ELOVL2 and high percentage of DNA methylation at PDE4C. ❑ a low percentage of DNA methylation at both ELOVL2 and PDE4C. Obstructive sleep apnea A study was conducted to determine if there is a difference in the efficacy of two treatments of obstructive sleep apnea (OSA). Thirty patients (20 male, 10 female) were recruited to the study with fifteen patients being randomly allocated each of the mandibular advancement splint (MAS) treatment group and tongue stabilizing device (TSD) treatment group. The efficacy of the treatments were compared in terms of the reduction in the apnea-hypopnea index (AHI). The thirty patients at the commencement of the study had an average AHI of 28.32 with a sample standard deviation of 16.94. After two months the AHI of each patient was again measured. The MAS treatment group experienced an average reduction in AHI of 11.28 with a sample standard deviation of 9.23. The TSD treatment group experienced an average reduction in AHI of 13.45 with a sample standard deviation of 10.66. Question 1 The standard error for the sample mean AHI of patients at commencement is Answer: 3.0928 Distractors: ❑ 3.1457 ❑ 5.1705 ❑ 0.5646 Question 2 The margin of error for a 95% confidence interval of the population mean AHI of patients at commencement is Answer: 6.3255 Distractor: ❑ 6.3163 ❑ 5.2493 ❑ 5.2550 Question 3 Let M be the population mean decrease in AHI for the MAS treatment and let T be the population mean decrease in AHI for the TSD treatment. The researchers would like to test Answer: H0: M = T versus H1: M ≠ T Distractors: ❑ H0: M = T versus H1: M < T ❑ H0: M = T versus H1: M > T ❑ H0: M = 0 versus H1: M > 0 Question 4 The standard error for the difference in the sample means for the two treatment groups is Answer: 3.6408 Distractors: ❑ 1.1515 ❑ 1.3260 ❑ 7.1360 Question 5 The t statistic used to test the hypotheses in Question 2 is Answer: -0.5960 Distractors: ❑ -1.8844 ❑ -2.1239 ❑ -0.9447 Question 6 To do a test by hand, we can use the minimum degrees of freedom from the two samples. Here the degrees of freedom to be used is Answer: 14 Distractors: ❑ 29 ❑ 15 ❑ 16 Question 7 Based on the test, using your degrees of freedom from Question 6, you can conclude that there is Answer: no evidence to suggest the mean decrease in AHI is different between the two treatments (p = 0.56). Distractors: ❑ no evidence to suggest the mean decrease in AHI is different between the two treatments (p = 0.28). ❑ weak evidence to suggest the mean decrease in AHI is different between the two treatments (p = 0.08). ❑ moderate evidence to suggest the mean decrease in AHI is different between the two treatments (p = 0.02). Question 8 Assuming the data was available, which of the following tests would provide an alternative nonparametric test to test the hypotheses of Question 3? Answer: Rank Sum test Distractors: ❑ Sign test ❑ Signed rank test ❑ Chi-squared test Question 9 A secondary measure (“response to treatment”) was defined as resolution of all symptoms or an improvement in symptoms and ≥ 50% reduction in AHI. In the MAS group 10 patients experienced a “response to treatment”. The standard error for the proportion of patients in the MAS group that experience a “response to treatment” is Answer: 0.1217 Distractors: ❑ 0.0574 ❑ 0.0905 ❑ 0.2381 Question 10 The margin of error for constructing a 95% confidence interval by hand for the population proportion of patients that would experience a “response to treatment” with the MAS is Answer: 0.2385 Distractors: ❑ 0.2831 ❑ 0.5164 ❑ 0.2610 Question 11 In addition to the 10 patients in the MAS group who experienced a “response to treatment”, 7 patients in the TSD group also experienced a “response to treatment”. The standard error for the difference in the proportion of patients experiencing a “response to treatment” between the two groups is Answer: 0.1772 Distractors: ❑ 0.0539 ❑ 0.1232 ❑ 0.3655 Question 12 The researchers would like to test if there is a difference in the population proportion of patients that experience a “response to treatment” between the two treatment groups. Carrying out this test by hand, you can conclude there is Answer: no evidence to suggest a difference in the population proportion of patients that experience a “response to treatment” (p > 0.1) Distractors: ❑ weak evidence to suggest a difference in the population proportion of patients that experience a “response to treatment” (p < 0.1) ❑ moderate evidence to suggest a difference in the population proportion of patients that experience a “response to treatment” (p < 0.05) ❑ strong evidence to suggest a difference in the population proportion of patients that experience a “response to treatment” (p < 0.01) Parasites The fish Rutilus rutilus is one of the hosts of the parasitic worm Ligula intestinalis. The distribution of the number (X) of Ligula intestinalis worms infecting a randomly selected host from the Rutilus rutilus population is as follows: x 0 1 2 3 P(X = x) 0.21 0.45 0.23 0.11 Question 1 The expected number of Ligula intestinalis in a fish from the Rutilus rutilus population is Answer: 1.24 Distractors: ❑ 0.79 ❑ 1 ❑ 2.24 Question 2 The standard deviation of Ligula intestinalis in a fish from the Rutilus rutilus population is Answer: 0.9069 Distractors: ❑ 0.8224 ❑ 1.3281 ❑ 0.5238 Question 3 We are often interested in prevalence of parasitic infection, that is the probability a randomly selected individual from the host species has at least one parasite. Based on the above probabilities, what is the prevalence of Ligula intestinalis in the Rutilus rutilus population? Answer: 0.79 Distractors: ❑ 0.21 ❑ 0.89 ❑ 0.45 Question 4 Ligula intestinalis can sometimes be difficult to identify in hosts. Suppose we correctly identify an infected host as having one or more parasite only 80% of the time. What is the probability that a randomly selected fish from the Rutilus rutilus population is identified as being infected by Ligula intestinalis? Answer: 0.632 Distractors: ❑ 0.36 ❑ 0.712 ❑ 0.11 Question 5 A randomly selected fish from the Rutilus rutilus population is inspected and no Ligula intestinalis parasites are identified. What is the probability that this fish has no Ligula intestinalis parasites? Answer: 0.5706 Distractors: ❑ 0.368 ❑ 0.158 ❑ 0.834 Question 6 A sample of 10 fish from the Rutilus rutilus population is taken. The distribution of the number of fish infected with Ligula intestinalis in the sample is Answer: Binomial(10, 0.79) Distractors: ❑ Binomial(10, 0.8) ❑ Normal(0.79, 0.13) ❑ Normal(7.9, 1.3) Question 7 The probability that six or fewer fish are infected with Ligula intestinalis in the sample from Question 4 is Answer: 0.1391 Distractors: ❑ 0.0993 ❑ 0.6177 ❑ 0.2508 Question 8 A sample of 100 fish from the Rutilus rutilus population is taken. The distribution of the number of infected hosts is approximately Answer: Normal(79, 4.1) Distractors: ❑ Normal(0.79, 0.041) ❑ Normal(79, 8.89) ❑ Binomial(79,0.79)
School of Mathematics and Statistics Solutions to Extreme Value Theory Sample Quiz Week 13 STAT5611: Statistical Methodology Semester 2, 2021 Lecturers: Neville Weber and Michael Stewart Please write out your responses, scan and upload before 2pm. You do not need to derive again results stated and/or derived in lectures or tutorials, just refer to them as needed. 1. The Kumaraswamy distribution with parameters c > 0 and d > 0 has CDF F (x; c, d) = 0 for x ≤ 0 1− (1− xc)d for 0 < x < 1 1 for x ≥ 1. (1) For the rest of this question, we assume c > 0 and d > 0 are fixed, and therefore just write F (·). (a) Derive the high quantile or upper- 1n quantile function U(n) = F −1 (1− 1n). Solution: Write Un = U(n), set F (Un) = 1− 1n and solve for Un: F (Un) = 1− (1− U cn)d = 1− 1 n (1− U cn)d = 1 n 1− U cn = 1 n1/d = n−1/d U cn = 1− n−1/d U(n) = Un = ( 1− n−1/d )1/c (b) Show that U(·) is regularly varying at infinity and find its exponent. Solution: Fix x > 0. Then U(tx) U(t) = ( 1− (xt)−1/d)1/c( 1− t−1/d)1/c → 1 as t→∞ since both numerator and denominator tend to 1. Therefore U(·) is slowly varying at infinity, i.e. regularly varying at infinity with exponent 0. (c) Show that U(·) is of extended regular variation at infinity, find its exponent and an appro- priate scaling function. Solution: Fix x > 0. Then since (1 + x)1/c = 1 + (x/c) + o(x) as x→ 0, as n→∞, U(n) = ( 1− n−1/d )1/c = 1− (n−1/d/c) + o ( n−1/d ) Therefore, for fixed x > 0, U(nx) = 1− [(nx)−1/d]/c+ o ( n−1/d ) and so U(nx)− U(n) = −[(nx)−1/d]/c+ (n−1/d/c) + o ( n−1/d ) = −n −1/d c [ x−1/d − 1 + o(1) ] as t→∞. Therefore, with scaling function a(n) = n−1/d/(cd), U(nx)− U(n) a(n) → −d ( x−1/d − 1 ) = Hγ(x) , with γ = −1/d, therefore U(·) is of extended variation at infinity with exponent −1/d. (d) Suppose X1, . . . , Xn are iid with common CDF F (·) as at (1) above, and write Mn = maxi=1,...,nXi. Find constants an > 0, bn so that Mn − bn an converges in distribution, and derive the limiting CDF. Solution: If we take bn = U(n) and an = a(n) (the scaling function in the previous part), we know we will get the GEVD(γ) as the limiting distribution, for γ = −1/d, but this may be laborious to derive properly. Alternatively, we can look at the form. of 1−F (·) and based on that propose a simpler normalisation. For example, we may take bn ≡ 1 and an = n−1/d. Then we get P { Mn − bn an ≤ x } = P {Mn ≤ bn + anx} = P { Mn ≤ 1 + n−1/dx } . Note next that 1− F ( 1 + n−1/dx ) = 0 for x ≥ 0[1− (1 + n−1/dx)c]d for x < 0. For x < 0, ( 1 + n−1/dx )c = 1 + cn−1/dx+ o ( n−1/d ) , so n [ 1− F ( 1 + n−1/dx )] = n [ −cn−1/dx ]d = [−cx]d Therefore, by Proposition 1.3, P ( Mn ≤ 1 + n−1/dx ) → { e−[−cx] d for x < 0 1 for x ≥ 0 which is a scaled version of a reversed Weibull(d) distribution (which is then also a linear transformation of GEVD(−1/d)). 2. The (unit scale) Rayleigh distribution has CDF F (x) = { 0 for x < 0 1− e−x2/2 for x ≥ 0. (2) (a) Determine, for each u > 0 and each x > 0, the excess CDF Fu(x) = P (u < X ≤ u+ x) P (X > u) . Solution: Fu(x) = F (u+ x)− F (u) 1− F (u) = 1− e−(x+u)2/2 − [ 1− e−u2/2 ] e−u2/2 = 1− e−ux−x2/2 2 (b) Find a measurable function a(·) such that for each x > 0 lim u→∞ 1− Fu(a(u)x) = 1−G(x) for a CDF G(.) satisfying G(0) = 0. Derive the form. of this CDF G(·). Solution: 1− Fu(a(u)x) = e−u[a(u)x]−[a(u)x]2/2 Taking a(u) = 1/u, we get 1− Fu(x/u) = e−x−(x/u)2/2 As u → ∞, this tends to e−x. This is 1 − G(x), for G(·) the unit-mean exponential distri- bution. Also, note that the function a(u) = u is monotone and thus measurable. (c) Is F (·) in the domain of attraction of a (generalised) extreme value distribution? If so, which one? Solution: The CDF G(·) from the previous part is also the generalised Pareto distribution with shape γ = 0. Thus by the Proposition in lecture 8, F (·) ∈ DOA of GEVD(0), i.e. the Gumbel distribution. (d) Suppose now that X1, . . . , Xn are iid with common CDF F (·) as at (2) above, and write Mn = maxi=1,...,nXi. Deduce sequences an > 0, bn so that Mn − bn an converges in distribution, and derive the resultant limiting distribution. Solution: We may take u = un = U(n) = F −1 (1− 1n), so that (as seen in the previous part, for x > 0) 1− Fu(x/u) = 1− F (un + x/un) 1− F (un) = n [1− F (un + x/un)]→ e −x and indeed this also holds for x ≤ 0 too. Thus by Proposition 1.3, taking an = bn = un, we get for any real x, P { Mn − bn an ≤ x } = P {Mn ≤ bn + x/an} = P {Mn ≤ un + x/un} → e−e−x . It remains to determine un. But note that 1 n = e−u 2 n/2 − log n = −u2n/2 un = √ 2 log n . 3. The log-logistic distribution with unit scale parameter and shape parameter c > 0 has CDF F (x; c) = xc 1 + xc . (3) For the rest of this question, we assume c > 0 is fixed and just write F (·). (a) Show that 1− F (·) is regularly varying at infinity and determine its exponent. Solution: 1− F (x) = 1 1 + xc = 1 xc(1 + x−c) = x−c ( 1 + x−c )−1 ∼ x−c as x→∞. Thus, for fixed x > 0, 1− F (tx) 1− F (t) ∼ (tx)−c t−c = x−c . So 1− F (·) is regularly varying at infinity with exponent −c. 3 (b) Suppose X1, . . . , Xn are iid with common CDF F (·) given at (3) above. Deduce sequences an > 0, bn such that Mn − bn an converges in distribution, and determine the limiting CDF. Solution: From the previous part, if un = F −1 (1− 1n), then as n→∞, un →∞ and so for x > 0, 1− F (unx) 1− F (un) = n [1− F (unx)]→ x −c . For x ≤ 0, 1− F (unx) = 1 n [1− F (unx)] = n→∞ as n→∞. In other words, for all real x, n [1− F (unx)]→ G¯(x) = { +∞ for x ≤ 0 x−c for x > 0. Therefore, taking bn ≡ 0 and an = un, by Proposition 1.3, P { Mn − bn an ≤ x } = P {Mn/un ≤ x} = P {Mn ≤ unx} → { 0 for x ≤ 0, e−(x −c) for x > 0. It remains to determine un: 1− F (un) = 1 n = 1 1 + ucn 1 + ucn = n ucn = n− 1 un = (n− 1)1/c . Note also that we may replace this any sequence un such that 1− F (un) ∼ n−1, e.g. un = n1/c, and get the same limiting distribution. Other normalisations are possible (although all will give some scaled and/or shifted version of this same limiting Fre´chet distribution). (c) Show that F (·) is in the Hall-Welsh class, that is find constants γ > 0, β > 0, C > 0 and D such that, as x→∞, 1− F (x) = Cx−1/γ {1 +Dx−β + o (x−β)} . Solution: As shown above in (a), as x→∞, 1− F (x) = x−c (1 + x−c)−1 = x−c {1− x−c + o (x−c)} So F (·) is in the Hall-Welsh class, with • γ = 1/c; • β = c; • C = 1; • D = −1. (d) Suppose X(1) ≤ . . . ≤ X(n) are the order statistics of X1, . . . , Xn and denote Hill’s estimator of γ based on X(n−r), X(n−r+1), . . . , X(n) (for integer 1 ≤ r ≤ n) by γˆr = 1 r r∑ i=1 [ logX(n−i+1) − logX(n−r) ] . 4 Deduce a sequence r = r(n) so that the resultant γˆr has the smallest possible asymptotic mean-squared error. Solution: We can use the formula from question 4 in the Week 12 Tutorial: r = [ (1 + βγ)2 2D2 (βγ) 3 ]1/(2βγ+1) (Cn) 2βγ/(2βγ+1) . Note that in this case, βγ = C = D2 = 1 so this simplifies considerably: r = ( 4 2 )1/3 n2/3 = (√ 2n )2/3 . 5
MTH2010-MTH2015 - Multivariable Calculus - S2 2021 Started on Saturday, 23 October 2021, 9:07 PM State Finished Completed on Saturday, 23 October 2021, 9:08 PM Time taken 1 min 41 secs Grade 0.00 out of 60.00 (0%) Print friendly format Information Information PLEASE READ ALL INSTRUCTIONS CAREFULLY. There are 60 marks available and the exam is worth 60% of your final unit mark. For each problem, you will be required to select a response from a drop-down menu, to select responses from various options, or to input a number into a box. Numerical answers are integers, possibly with a negative sign in front, unless otherwise specified. Please enter as "5" or "-5" as required. You are permitted and encouraged to use pen or pencil and blank sheets of paper for your working out. Symmetry of second derivatives. If has continuous second partial derivatives, then Second derivatives test. At a critical point of where , let . If and , then has a local minimum; if and , then has a local maximum; and if , then has a saddle point. Lagrange multipliers. To maximise/minimise subject to the constraint , solve Polar coordinates. Cartesian and polar coordinates are related by Line integrals of functions. For a parametrisation for of a curve in and a function , Line integrals of vector fields. For a parametrisation for of a curve in and a vector field , f(x,y) = . f∂ 2 ∂x∂y f∂ 2 ∂y∂x f(x,y) ∇f = 0 D= −f xx f yy f 2 xy D> 0 > 0f xx f D> 0 < 0f xx f D< 0 f f(x) g(x) = 0 ∇f(x) = λ∇g(x). x= rcosθ and y= rsinθ. r(t) = (x(t),y(t)) a≤ t≤ b C R 2 f(x,y) f(x,y)ds= f(x(t),y(t)) dt.∫ C ∫ b a (t + (tx ′ ) 2 y ′ ) 2 − −−−−−−−−−− √ r(t) = (x(t),y(t)) a≤ t≤ b C R 2 F(x,y) d ( )d∫ ∫ b ′ Question 1 Not answered Marked out of 2.00 Question 2 Not answered Marked out of 2.00 Fundamental theorem for line integrals. For a parametrisation for of a curve and a function , Surface integrals of functions. For a parametrisation for of a surface in and a function , Surface integrals of vector fields. For a parametrisation for of a surface in and a vector field , Green's theorem. For a region in the plane and functions and , Stokes' theorem. For a surface in space and a vector field , Divergence theorem. For a solid region in space and a vector field , F ⋅ dr= F ⋅ (t)dt.∫ C ∫ a r ′ r(t) = (x(t),y(t)) a≤ t≤ b C f ∇f ⋅ dr= f(r(b))− f(r(a)).∫ C r(u,v) = (x(u,v),y(u,v),z(u,v)) (u,v) ∈D S R 3 f(x,y,z) f(x,y,z)dS = f(x(u,v),y(u,v),z(u,v)) | × |dA.∬ S ∬ D r u r v r(u,v) = (x(u,v),y(u,v),z(u,v)) (u,v) ∈D S R 3 F(x,y,z) F(x,y,z) ⋅ dS= F(x(u,v),y(u,v),z(u,v)) ⋅ ( × )dA.∬ S ∬ D r u r v D P(x,y) Q(x,y) ( − )dA= P dx+Qdy.∬ D ∂Q ∂x ∂P ∂y ∫ ∂D S F(x,y,z) curl F ⋅ dS= F ⋅ dr.∬ S ∫ ∂S E F(x,y,z) div FdV = F ⋅ dS. ∭ E ∬ ∂E Consider the following two lines in : and (a) The two lines intersect at ( , , ). (b) If is the angle between these two lines, then . You may enter your answer as a decimal. R 3 {(t,1+2t,2−2t)} {(1+4s,3− s,s)}. θ cosθ= Consider the vector function given by and let be the corresponding space curve. r :R→R 3 r(t) = (2 + t,t+1, −2),t 2 t 2 C Question 3 Not answered Marked out of 3.00 (a) The plane given by intersects at the points (1, 0, -1) and ( , , ). (b) At the point (3, 2, -1), the vector ( , 1 , ) is tangent to C. 2x+ y−3z= 5 C Match the following functions with their contour maps below. Contour map A Contour map B Contour map C xy+ +1y 2 8 −8x 3 y 3 +xyx 2 y 2 x− y + +2x 2 y 2 cosx+siny + sin x 2 y 2 pContour map D Contour map E Contour map F Question 4 Not answered Marked out of 4.00 Question 5 Not answered Marked out of 4.00 (a) Consider the limit . Which one of the following statements is correct? The limit does not exist. The limit is infinite. The limit exists and is equal to . The limit exists and is equal to . None of the previous statements is correct. (b) Consider the limit . Suppose that you want to test the limit along all lines passing through . Which one of the following statements is correct? One obtains the same limit along all lines, so the limit must exist. One obtains the same limit along all lines, but the limit might not exist. One obtains two different limits along two different lines, so the limit does not exist. One obtains two different limits along two different lines, but the limit might still exist. None of the previous statements is correct. (c) Consider the function defined by y for and . Which one of the following statements is correct? The function is continuous at all points. The function is continuous at all points except for . The function is continuous at all points except for those of the form. for . The function is continuous at all points except for those of the form. for . The function is never continuous, because it is not well-defined. None of the previous statements is correct. (d) Consider the function n . Which one of the following statements is correct? The function is differentiable at (0,0). The function is not differentiable at (0,0), because the partial derivative with respect to x does not exist. The function is not differentiable at (0,0), because the partial derivative with respect to y does not exist. The function is not differentiable, because the partial derivatives are not defined for some points near (0,0). The function is not differentiable, because the partial derivatives are not continuous near (0,0). None of the previous statements is correct. lim (x,y)→(1,0) 2xy +x 2 y 2 0 1 lim (x,y)→(0,0) x+ y 2 + yx 2 (0,0) f(x,y) = −x 4 y 4 +x 2 y 2 (x,y) ≠ (0,0) f(0,0) = 1 2 (0,0) (x,x) x ∈R (x,x) x ∈R ∖ {1,−1} f(x,y) = |x| ⋅ y 1/3 Consider the function given by f : →RR 2 Question 6 Not answered Marked out of 4.00
EEET2387 Switched Mode Power Supplies Final Individual Assignment [200 marks available] The following is allowed: to aid your work. spreadsheets and Wolfram Alpha to aid you with numerical calculations and approxima- • You are allowed to use any calculator. The following is NOT allowed: the solutions to the problems contained within this assignment. • You are not allowed to pay or get another person to prepare your assignment. • You are not allowed to copy other people’s work. A breach of any of the above may result in disciplinary action in accordance with the University Please refer to RMIT’s Academic integrity webpage for further information. information. Use the QR-code to submit your Assessment Declaration. from a minimum voltage of 7.2 V to a maximum voltage of 13.2 V . A control circuit adjusts 36 Ω. The converter operates with a switching frequency (fs) of 71.460 kHz. Assume that Vd Co Rload Vo+ id Io vsw+ - vD- S vL - Figure 1: Buck-boost converter. is no more than 35% of the average inductor current (IL) for all operating conditions. (∆vo) is no more than 1.5% of the average output voltage (Vo) for all operating con- (c) [10]Calculate the maximum inductor current (IL,max). Consider all operating conditions. tance (Co) calculated in question 1(b). (Vo) is 9 V , the load resistor (Rload) is 36 Ω, and the filter inductance (L) is as (Cd) is large, and the output capacitance (Co) is as calculated in question 1(b). Plot two switching periods. Clearly indicate the numerical values for the switching period the numerical values for the maximum inductor current (IL,max), minimum inductor Total Marks for Question 1= 40 marks The nominal output voltage (Vo) is 48V . The nominal output load (Rload) is 82Ω. The of primary winding (N1) is 340. The input capacitor (Cd) is 100µF and the output ca- magnetising inductance Lm) and that losses are negligible. Co Rload Vo - im isw + Lmv1 - D Cd (a) [8]Specify the number of turns of the transformer secondary winding (N2) that achieves cycle (D) is 0.5. Assume that the converter operates in continuous conduction mode (b) [10]Calculate the transformer magnetising inductance (Lm) that achieves boundary con- (Rload) and duty cycle (D) of 0.5. converter operates with 40% of the nominal output load (Rload). input voltage (Vd), nominal output voltage (Vo), and 85% of the nominal output load Total Marks for Question 2= 40 marks the following specifications: Minimum AC Input Voltage 127 Vrms AC Maximum Output Power Rating 48 W Converter Efficiency 85% The transformer for this converter is to be designed using a TDK PC47EE50-Z transformer of the linked datasheet. elled copper wire. The boundary between DCM and CCM for the converter is required transformer is to be less than 0.2 T. the inductor current is triangular. (c) [2]Calculate the equivalent output load resistance for the converter operating conditions. (e) [12]If the transformer air gap is given as `air = 0.456 × 10−3 m, calculate the number inductance of 1.5 mH. [HINT: calculate the total reluctance to determine Np]. flux around the air gap. If you had to take this fringing into account for the calculations we ignore fringing in question 3(e)? (h) [5]Calculate the number of parallel conductors required to keep the average current previously calculated in question 3(a). 4. A Texas Instruments UC2842 PWM controller chip [2] is to be used to indirectly control current-mode control of the auxiliary output. The flyback converter has a switching fre- of the controller is shown in Figure 3. Refer to the UC2842 datasheet available via the Vin 85− 265 Vrms AC ∆Vout 100 mV Vp−p ripple Vaux 12 V DC Table 2: System Parameters. UCx843 Reference VREF Good Internal UVLO S PWM R 1 V E/A GROUND VFB ISENSE Comparator OUTPUT PWRGND2R UC1842, UC2842, UC3842, UC1843, UC2843, UC3843 www.ti.com SLUS223F –APRIL 1997–REVISED APRIL 2020 UC2845 UC3845 8 Detailed Description The UCx84x series of control integrated circuits provide the features necessary to implement AC-DC or DC-to- circuitry includes undervoltage lockout (UVLO) and current limiting. Internally implemented circuits include a ensure latched operation, a pulse-width modulation (PWM) comparator that also provides current-limit control, N-channel MOSFETs, is low when it is in the off-state. range, and maximum duty-cycle. Typical UVLO thresholds of 16 V (ON) and 10 V (OFF) on the UCx842 and for the UCx843 and UCx845 devices are 8.4 V (ON) and 7.6 V (OFF), making them ideal for use with regulated approaching 100%. The UCx844 and UCx845 obtain a duty-cycle range of 0% to 50% by the addition of an The UC184x-series devices are characterized for operation from –55°C to 125°C. UC284x-series devices are 70°C. Figure 11. UCx842 and UCx843 Block Diagram, No Toggle gram [2]. in this controller that enables current-mode control, and provide a brief description of (b) Show with a circuit how this controller would be integrated into a flyback converter should include fully labelled circuit sketches or schematics that include the following i. [7]The oscillator circuit with appropriate standard resistor and capacitor values to is less than 7% of the switching period. amplifier feedback elements. No compensation elements are required. to 3 mA during start-up of the chip’s VCC supply at maximum AC input voltage circuit should be designed so that VCC reaches the typical UVLO turn-on threshold be considered as 19 V.] tion with spike suppression. Assume that the peak primary current is 1.3 A. switching device for the power supply. Design the gate drive interface between the 0.5% of the switching frequency when the MOSFET is switched with a ±10 V pulse gate drive circuit interface. [HINT: Use the minimum threshold voltage.] 5. The 12 V main output of a 48 W (rated output) flyback converter is regulated by an iso- to deliver 12 V at 0.15 A. The general form. of this TL431 feedback circuit is shown in Fig- regulator chip [2]. Refer to the UC2842 datasheet available via the provided hyperlink for Section of the UC2842 datasheet. mentally, and the transfer function parameters are listed in Table 3. Lm = 1.5 mH Ns Dmax = 0.45 Rcs = 0.75 Ω ILED = 5 mA fs = 95.280 kHz Table 3: System Parameters. Point (d) R27R24C33 CTR R19 R23 Point (c) Figure 4: Type 2 Compensator using (a) [2]Using the converter parameters provided, calculate the equivalent load resistance Rload. AvRcs converter power stage and provide the open loop transfer function in standard form. (c) [2]Determine a suitable crossover frequency for the converter. Assume that the secondary (d) [4]Determine the open-loop plant gain of the converter power stage |G(ωc)| at the selected AvRcs (e) [14]Select suitable frequencies for the TL431 regulator pole and zero, and accordingly in Figure 4, given that the required mid-band gain is 8.772. sator Bode magnitude and phase characteristic on semi-log graph paper (available Python or Wolfram Alpha. References datasheet, April 2011. [Online] Available: https://www.jp.tdk.com/tefe02/e141.pdf 1997 [Revised April 2020]. [Online] Available: https://www.ti.com/lit/gpn/uc3844 able: https://www.vishay.com/docs/91104/91104.pdf
An Online Payment Service Project Description RU Pizzeria sells pizzas. Your team will develop a software for the Pizzeria to manage the orders. Your team must use JavaFX to develop the GUIs for taking the orders, placing the orders, and cancelling an order. Currently, the Pizzeria offers 3 flavors of pizzas, Deluxe, Hawaiian and Pepperoni, with store customized toppings. However, the Pizzeria allows the customers to customize the toppings as well. The store staff will be the one using the software to take the orders from the customers. Each order is uniquely identified by the customer’s 10-digit telephone number. For simplicity, the system will not keep track of the dates of the orders. The store manager has given you the list of requirements as follows. (1) The Pizzeria offers 3 different sizes of pizzas, small, medium, or large, for each flavor. Deluxe pizza includes 5 toppings, the price for a small size is $12.99. Hawaiian pizza includes 2 toppings, the price for a small size is $10.99. Pepperoni pizza includes 1 topping, the price for a small size is $8.99. Add $2.00 for each size increase Add $1.49 for each additional topping, up to 7 toppings maximum. Pizza prices do not decrease if the number of toppings dropped below the number of store customized toppings. (2) The system shall allow the store staff to choose the pizza flavors with different sizes. (3) Upon the selection of the pizza flavor, the system shall display the image of the selected pizza, the list of store customized toppings, a list of available toppings for customization, and a list of sizes to choose from. (4) The store staff shall be able to customize the selected pizza by adding or removing the toppings and the system shall display the running subtotal with 2 decimal places. (5) The system shall allow the store staff to add multiple pizzas to the same order and remove selected pizzas from the order. (6) The store staff shall be able to check the detail of the current order before placing the order. These shall include the list of pizzas with the selected toppings, subtotal for each pizza, total amount of the pizzas in the order, sales tax amount and the order total, which is the total amount plus sales tax. The tax rate is 6.625%. (7) The system shall be able to keep track of all the store orders, allow the store staff to browse the store orders and cancel an order. These shall include displaying all the store orders by the customers’ phone numbers, the order total for each order with 2 decimal places, and the list of pizzas in each order. (8) The system shall be able to export the store orders and save them in a text file, which includes a list of store orders. Each store order shall include the customer’s phone number, the list of pizzas with selected toppings and the order total Project Requirements 1. This is a group assignment. You must work with your designated partner in order to get the credit for this project. 2. You MUST follow the software development ground rules, or you will lose points for not having a good programming style. 3. All methods should not exceed 40 lines, or -2 points for each violation, maximum 5 points off. 4. Each Java class must go in a separate file. -2 points if you put more than one Java class into a file. 5. Your software must provide 4 GUIs listed below, -5 points for each GUI missing. The user can navigate between the GUIs to add/remove pizzas to/from an order, review/place the order, check all orders, and cancel an order. Main Menu, which shall include the options of ordering different flavors of pizzas, checking the current order, and managing the store orders placed by the user. Pizza customization, which displays the image of the chosen pizza flavor, sizes to choose from, a list of preset toppings, a list of additional toppings, the running total of the pizza while the user is customizing the toppings. You MUST use this GUI for all pizza flavors. If you create a GUI for each pizza flavor, you will lose 10 points. Current order, which displays the phone number, the list of pizzas with selected toppings, subtotal, sales tax, and order total. All dollar amounts must be displayed with 2 decimal places. The user can review the order, remove the selected pizza, and place the order. Store orders, which displays all the orders placed so far. The GUI shall list the detail of each order and display the total amount of each order, with 2 decimal places. The user can select an order and cancel the order. The GUI shall display the remaining orders after the cancellation. The user can also export the store orders to a text file, which shall include the details of every order, consistent with the details displayed on the GUI.
TextFilter In this project, you will implement a Transmission Control Protocol (TCP) client and server that does a three-way handshake, a well-known protocol sequence used in communication networks. This project has three parts: ● The client will be reused for part B and C. 3. Event-driven server. In this part, you should implement a single-threaded but concurrent server using event-driven techniques. In this project, you will learn and implement synchronous (3a, 3b) and asynchronous (3c) communication between the server and clients. Please make good use of TA hours, Open Office Hours, and Recitations. Please be aware that the example code provided for each part of this project only provides examples of certain features, and is NOT a starter template for each part of the project. Features demonstrated by the example code can be seen below Based on our past experience, asynchronous communication can be unintuitive and students need to have a different mindset to organize communication logic. This will be the main focus of the second recitation. Before asking the question, please search in Piazza to see if there are any similar questions asked before. If it is about a bug you are facing, it is likely that it is discussed in the Common Mistakes document. ● GitHub URL: ● Description of Question: ● Expected Behavior.: ● Observed Behavior.: Project 3a: The Client and Single-threaded Server You will implement a three-way handshake communication using TCP as follows: ● Step 2: The server receives and prints the “HELLO X” message from the client, and sends “HELLO Y” to the client, where Y is X+1. o If Y = X+1, the client sends “HELLO Z” to the server, where Z=Y+1, and closes the connection. ● Step 4: If the server receives the “HELLO Z” message from the client, and prints the message to screen. In addition, if Z != Y+1, prints an “ERROR”. The server then closes the connection. For printing to screen (stdout), make sure that you do “fflush(stdout)” right after you do the print. Compilation: You should use the gcc command to compile tcpclient.c (gcc –o tcpclient tcpclient.c ) and tcpserver.c (gcc –o tcpserver tcpserver.c). Please always make sure that all compile warnings are fixed, as the autograder might fail to compile otherwise. Generally, the server and a client in your implementation should work on any two hosts in the network. You can use the loopback address 127.0.0.1 as the default IP address for the server and all clients.
Rutgers ECE 434 LINUX OS Processes and Inter Process Communication Question 1 (100 marks total) You are in charge of managing bookings for car ferries. There are m car ferries that are numbered from 0 to m 1, in order of their departure time. For simplicity, no two ferries depart at the same time, and so the numbering is unique. For j in the range 0 to m 1, the jth ferry to depart is fj whole meters in length. The length of each ferry is non-negative (i.e. it is greater than or equal to zero). There are n different cars, c0, c1; : : : cn 1, where n > 0. Each car has a length (in whole meters), as well as a ferry that they have booked a ticket for. The length of each car must be greater than zero, and the number of the ferry that they are booked for must be greater than or equal to 0 and less than m 1 (i.e. no cars can be booked for the last ferry to depart, ferry number m 1). The cars are ordered in non-decreasing order of the ferry that each car has a ticket for. That is, for any i from 0 to n 2, the number of the ferry that ci has a ticket booked for is less than or equal to the number of the ferry that car ci+1 has a ticket booked for. Each of the first m 1 car ferries may have zero or more car bookings (and the last car ferry can have no car bookings). In fact, it is possible for one or more of the ferries to be over-booked. A ferry is over-booked if the sum of the lengths of the cars which are booked for the ferry exceeds the length of the ferry. Your job, as the manager of the ferry bookings, is to review the bookings and determine a ferry allocation for each car, where each car is either able to be allocated to: (i) the ferry that they have a ticket for (their chosen ferry) (ii) the first ferry that departs after the ferry that they have a ticket for (i.e. if a car has a ticket booked for ferry j, then they can be allocated to the next ferry, ferry j + 1.) (iii) no ferry at all { i.e. they can have their ticket canceled. Such an allocation of cars to ferries is valid if and only if: There is exactly one allocation for each car, and each car is either allocated to (i) the ferry that they have a ticket for, or (ii) the first ferry that departs after the ferry that they have a ticket booked for, or (iii) for no ferry at all. The sum of the lengths of the cars allocated to each ferry does not exceed (i.e. is less than or equal to) the length of the ferry. Note that even though the last ferry cannot have any bookings made for it, cars can still be allocated to it, i.e. a car with a booking for ferry m 2 may be able to be allocated to ferry m 1. Each car has as a cost associated with being rescheduled to the next ferry, and a cost associated with having their ferry ticket canceled. The rescheduling cost, as well as the cancellation cost must be greater than zero, and the cancellation cost must be greater than the cost of being rescheduled to the next ferry. The cost of an allocation for a car is either: (i) equal to 0, if the car is allocated to the ferry that they have a booking for; or (ii) the rescheduling cost for that car, if the car is rescheduled to the next ferry; or (iii) the cancellation cost for that car, if the car is not allocated to a ferry at all. Your job is to find a valid allocation of cars to ferries, that minimizes the total allocation cost, i.e. the sum of the allocation cost for each car.
Project 4: Journal Question 1 The table below shows the counts of reach by age group and gender for a particular facebook page. (a) State the Null and alternative hypothesis of the test that needs to be conducted. (b) State which test statistic should be used for the test and provide its equation. (c) Describe the randomisation process to obtain the distribution of the test statistic. (d) Given the following randomisation distribution and sample test statistic value of 3.1, what is the conclusion of the test? Question 2 Tweets have started to appear from unknown sources, using an alien language. The three most recent tweets are: • do da da da do • di di di do do • da da da da da da (a) Should we perform. stop word removal and/or stemming on these three tweets? (b) Construct the document term frequency matrix. (c) Construct the cosine similarity score of each document to the query “da di” by using term frequencies. (d) Which tweet is more similar to the query? Justify your answer. Question 3 The following graph shows the relationships between a set of YouTube clips. Using this graph: (a) Construct the adjacency matrix. (b) Compute the graph diameter. (c) Calculate the betweenness centrality for each vertex. (d) Which vertex is most central according to the betweenness centrality? (e) Find the density of the graph.
Cloud Computing and Big Data Homework Assignment 2 Course Overview STAT380 is a 3-credit undergraduate course. This is a case study-based course in the use of computing and statistical reasoning to answer data-intensive questions. This course addresses the fact that real data are often messy by taking a holistic view of statistical analysis to answer questions of interest. Various case studies will lead students from the computationally intensive process of obtaining and cleaning data, through exploratory techniques, and finally to rudimentary inferential statistics. This process will exploit students exposure to introductory statistics as well as the R programming language, hence the required prerequisites, yet novel computing and analytical techniques will also be introduced throughout the course. For the collection of data,students will learn scripting and database querying skills; for their exploration, they will employ R capabilities for graphical and summary statistics; and for their analysis, they will build upon the basic concepts obtained in their introductory statistics course. The varied case studies will elucidate additional statistical topics such as identifying sources of bias and searching for highdimensional outliers. Course Goals At the end of this course, successful students will be able to… Collect and tidy complex data from varied sources such as logs, email messages, and relational databases Perform. visualization and exploratory data analysis using the R programming language Employ statistical learning to understand relationships in data, including both supervised and unsupervised learning approaches. Assess model validation and prediction through simulation and cross-validation. Prerequisite Skills STAT 200 and STAT184 Textbook Required: An Introduction to Statistical Learning (https://link-springer- com.ezaccess.libraries.psu.edu/book/10.1007%2F978-1-4614-7138-7) by Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani (2017). Available for free through the Penn State Libraries E-Book program at no cost to students. Student can use the Library Resources link at the left hand side course navigation to access the book. Recommended Reading: Modern Data Science with R (https://catalog.libraries.psu.edu/catalog/31178880) by B. Baumer, D. Kaplan and N. Horton (2017). Available online for free. A data.table and dplyr tour. Free through https://atrebas.github.io/post/2019-03-03- datatable-dplyr/#data.table-and-dplyr (https://atrebas.github.io/post/2019-03-03-datatable-dplyr/#data.table-and-dplyr) Course Material All course material and assignments will be made available via Canvas. Students are responsible to visit the Canvas course site regularly and keep track of announcements/emails. Lectures: The lectures will not be recorded. Students are required to attend lectures. Assignments: Weekly/bi-weekly assignments will be administered as Kaggle competitions. A project workflow template will be shared which you will be expected to follow for all assignments. Code submissions will be via Canvas and usually will be due by 2359 (ET) on Sundays. Assignment due dates are set to Sundays, to allow maximum time for students to work on them. Note that the deadline on the Kaggle website is usually incorrect, so please ignore it. Students should not wait till the last moment to start working on their assignments as support will be extremely limited during the weekends. NO LATE homework will be accepted! Kaggle: All assignments and projects in this class will be set up as Kaggle competitions. You will be required to create an account at Kaggle.com. You are encouraged to use your Penn State email address to sign up. R/RStudio: We will use R/RStudio extensively in this class. All class assignments will require you to use R for statistical analysis. To be successful in this class it is recommended that students have access to a computer with R/RStudio installed locally. Alternatively, students can use RStudio Server hosted by Penn State’s Teaching and Learning with Technology (TLT), however support for this is highly limited and therefore inadvisable. To access TLT’s RStudio Server from off campus locations you will be required to login through VPN (you will find more information on downloading and installing VPN at https://psu.pb.unizin.org/researchresourceshandbook/chapter/vpn/ (https://psu.pb.unizin.org/researchresourceshandbook/chapter/vpn/) ). Extra Credit: There are no make-up assignments and no extra credit opportunities. Communication Kaggle: We will be using Kaggle for class related questions and discussions once the competitions start. This will enable everyone to benefit from each others questions and also help each other. Content related questions can be posted to the entire class. I encourage you to ask questions if you are struggling to understand a concept, and to answer your classmates’ questions when you can. We will monitor the discussion boards at least once per day. Do Not use Kaggle for issues related to your grade or other private matters; please use Canvas INBOX (on the left class navigation banner) option for those questions or comments. Email: For any questions, comments or inquiries of personal nature (i.e. anything not related to class material), please use the CANVAS INBOX option (on the left class navigation banner). If you have your CANVAS email forwarded to a personal account, please DO NOT reply to me using your personal email accounts as these will not automatically come through CANVAS. I will check my CANVAS email regularly throughout the workweek (Monday-Friday), and possibly on weekends as I get the chance. I will try my best to get back to you within 24 hours, if I do not feel free to ping the message. Please keep in mind that questions asked less than 24 hours before the deadline may go unanswered and it is your responsibility to turn in the assignments on time.
Software Engineering 265 Assignment3 You are working for a company called ArcadeRetro which recreates popular arcade games for modern audiences. The company is currently developing a game called Demolition Man. In the game, the player must guide Bomb Guy around the map, destroying walls to reach the goal whilst avoiding enemies. Working on your assignment Gameplay Map The map designates where Bomb Guy and enemies are allowed to move. Laid out as a grid, enemies can move along rows and columns where there is no wall. Maps are 13 rows tall, and 15 columns wide, with a 64 pixel offset between the top of the screen and the start of the first row. Each grid space is 32×32 pixels. Map layouts are stored in text files, and the name of the map file can be found in config.json under the “path” attribute. Sample Map and config.json files can be found under resources on Ed. Map files store the maps as multidimensional character arrays, where each character represents what is in that cell. Note that a map is valid if it has a bounding border, a starting location for Bomb Guy, and a Goal Tile (all maps used for marking will be valid, but you should write your own tests for invalid maps and handle them as you see fit). There is no minimum requirement for the number of enemies, or the layout of the remainder of the map. Note that if another character is represented in the Map file (for example, ‘P’ to represent the starting location for Bomb Guy), the tile should be empty.
Web Server Workload Characterization Assignment 3 and 4, COMPSCI 315 Due: Refer to the deadline on Canvas; Submission via Canvas 1 Introduction >Internet traffic measurement involves collecting network data that can be analyzed for several purposes such as traffic modeling, designing better network protocols, and traffic management. The growth in popularity of Web in the 1990s resulted in researchers trying to characterize Web traffic. These research works have utilized Web server logs to understand the workload characteristics of Web servers. The results of the research has led to improving performance of Web applications, designing better caching and load balancing techniques, and providing better user experience to clients, among other things [1, 3–5]. 2 Web Server Access Logs In this assignment, you will analyze one of two university Web server access logs [2]: 1. A campus-wide Web server at the University of Saskatchewan (UofS_access_log). 2. A department-level Web server at the University of Calgary (UofC_access_log). The server access log contains information about all requests made to the server and the corresponding server responses. The server log is in the fixed text-based Common Log Format and has the following syntax: hostname - - [dd/mm/yyyy:hh:mm:ss time_zone] object response_code transfer_size The hostname is the resolved name or IP address of the client making a request for an object stored on the Web server. The following fields (- -) are usually empty, but may contain user-identifier information such as username. The next field indicates the day and time the request was made along with the time zone. The URL requested is noted in the object field. The response_code field indicates the HTTP response code returned by the server. The transfer_size field records the bytes transferred by the server. For example, the following is a line from the UofS_access_log: imhotep.usask.ca - - [15/Sep/1995:16:02:09 -0600] "GET /changes.html HTTP/1.0" 200 1254 This line represents a request made by host imhotep.usask.ca on September 15, 1995 at 4:02:09 p.m. The time zone is central time (GMT-0600). The host requested the HTML file called changes.html using HTTP version 1.0. This request was successfully completed by the server as shown by the status code 200. The server transferred 1254 bytes to the host imhotep.usask.ca. Note the following about the datasets: • UofS_access_log: This trace contains seven month’s worth of all HTTP requests to the university Web server. The logs fully preserve the originating host and HTTP request. A local client is one containing usask.ca in the hostname or an IP address with 128.233.X.X. All others are considered remote clients. Timestamps have 1 second resolution. • UofC_access_log: This trace contains approximately one year’s worth of all HTTP requests to the University of Calgary’s Department of Computer Science Web server. The hosts making requests to the server have had their addresses removed to preserve privacy. Hosts are identified as either local or remote where local is a host from the University of Calgary, and remote is a host from outside of the University of Calgary domain. Paths have been removed. Files were numbered from 1 for the first file encountered in the trace. Files retain the original file extension, so that the type of file can be determined. Paths of the filenames have been removed. Modified filenames consist of two parts: num.type, where num is a unique integer identifier, and type is the extension of the requested file. Timestamps have 1 second resolution. 3 Web Server Workload Analysis Choose one dataset you like and answer all questions: 1. Based on your learning of Internet measurements in this course answer the following questions: (a) What measurement mechanism was used for the collection of the Web server logs? Active, Passive, or both. (b) What type of network were the measurements taken from? Edge network, core network, or both. (c) What type of analysis techniques did you apply on the dataset to get the answers? Online, offline, or both. (d) Is analyzing server logs the only way to characterize the workload of a Web server? Why? 2. How many requests are made per day on average? 3. How many bytes were transferred during the entire log duration expressed in Megabytes (MB)? 4. What is the average number of bytes transferred per day expressed in MB per day? 5. Produce a breakdown of the server response codes expressed in percentage of the total number of requests. Group the status code as follows: Successful, Not Modified, Found, Unsuccessful. A successful response (status code: 200) means that the server received a request for a valid object (for which the client has the necessary access privilege), the object was found, and returned successfully to the client. A not modified response (status code: 304) means that the client already has a copy of the requested object in its cache, wants to verify if the object is up-to-date, and the client is informed that the object has not been modified at the server. A found response (status code: 302) results when the requested object is known to be stored in a different location than the URL requested by the client. The server responds with the new URL in this situation. A unsuccessful response (status code: 4XX and 5XX) happens when the requested object does not exist on the server, the client did not have access permission, or there was a server-side error. 6. How many requests are made by local clients and remote clients, respectively? Report your answer as a percentage of total requests. 7. How many bytes are transferred by local clients and remote clients, respectively? Report your answer as a percentage of total bytes transferred. 8. Produce a breakdown of requests by file type category. The file categories are as follows: Video, Sound, Dynamic, Formatted, HTML, Images, Others. Report your answer as a percentage of total requests. The file categories by file extensions are described in Table 1. 9. Using Table 1, produce a breakdown of bytes transferred by each file category. Report your answer as a percentage of total bytes transferred. 10. Using Table 1, calculate the average transfer sizes (in bytes) of each file category. Table 1: File categories Category File extension HTML html, htm, shtml, map Images gif, jpeg, jpg, xbm, bmp, rgb, xpm Sound au, snd, wav, mid, midi, lha, aif, aiff Video mov, movie, avi, qt, mpeg, mpg Formatted ps, eps, doc, dvi, txt Dynamic cgi, pl, cgi-bin Others Everything else 11. Identify all unique object requests in the log and sort them based on frequency. Next, identify all the objects that were requested only once in the log. What percentage of unique objects are accessed only once in the log? What percentage of bytes are accessed only once in the log? 12. Produce a Cumulative Distribution Function (CDF) plot of the transfer sizes of all distinct objects. The x-axis should be in log-10 scale. 13. Produce at least one plot to show the percentage of total requests per hour of the day, the percentage of total requests per day of the week, or percentage of total requests per month of the year. 14. Produce a CDF plot of the inter-reference times of objects that are requested more than once. The x-axis should be in log-10 scale. For questions 6 onwards, your analysis should be based on successful requests only. Report your results to 2 decimal places. Some requests in the log may be malformed. It is safe to ignore these requests in your analysis. Please check that these requests account for a negligible fraction of the total requests. Briefly comment on your results (Explain the results and discuss their implications). 4 Submission Complete the attached file with your answers. Convert this file to PDF format. Rename it to your username.pdf. Submit the file to Canvas. Submit answers to questions 1-7 as part of Assignment 3. Submit answers to questions 8-14 as part of Assignment 4. A code template will be provided at a later date. For added challenge, you are encouraged to write the parser and analysis scripts from scratch using a programming language of your choice. You are free to use online resources (e.g., online code, tools) as long as you provide appropriate attribution. You do not need to submit the code. You should keep the code, in case we wish to see it. You are encouraged to discuss the assignment with each other, however, the code and the produced results must be done individually. Questions regarding this assignment and code template should be directed to the course tutors. 5 Grading Scheme Each question is worth 10 points. Assignment 3 is worth 70 points. Assignment 4 is worth 70 points. For each question, you will receive full points for the correct answer. You will receive 50% points for an answer, which is close to the correct answer. You will receive zero points for an answer that is far off from the correct answer. Each answer should have a brief explanation to receive full marks. References [1] Martin Arlitt and Tai Jin, A Workload Characterization Study of the 1998 World Cup Web Site, IEEE Network 14 (2000), no. 3. [2] Martin Arlitt and Carey Williamson, Internet Web Servers: Workload Characterization and Performance Implications, IEEE/ACM Trans. Netw. 5 (1997), no. 5, 631–645. [3] Leeann Bent, Michael Rabinovich, Geoffrey M. Voelker, and Zhen Xiao, Characterization of a Large Web Site Population with Implications for Content Delivery, WWW 9 (2006), no. 4. [4] Venkata Padmanabhan and Lili Qiu, The Content and Access Dynamics of a Busy Web Site: Findings and Implications, Proc. ACM SIGCOMM, 2000. [5] Weisong Shi, Y Wright, Eli Collins, and Vijay Karamcheti, Workload Characterization of a Personalized Web Site and its Implications for Dynamic Content Caching, Proc. WCW, 2002.
PhD Course C Sharp Requirement Whether you develop programs for enterprise solutions, high performance computing, digital signal processing, games or mobile applications you are likely to develop them in either Java or C# in the future – in fact you are likely to develop programs in both languages as a Gartner Group survey shows that 30% of enterprise applications will have code in both languages. In this course you need to do the following exercises. 1. Follow the instructions on Visual Studio 2013 Express Editions: Creating a Console Application with Visual C# Express 2. Follow the instructions on Visual Studio 2013 Express Editions: Creating a Windows Application with Visual C# Express 3. Try out the Visual C# Samples
COMP1001 More Text Processing Requirement This question prints the leaves of a symmetric tree. A user will be prompted for a symbol and a positive position for the tip of the leaves. Starting from the tip, the tree will fan out on both sides symmetrically until left side of the leaves reaches the left edge, assuming that the right edge has no limit. For example, 1 Please enter a symbol: * 2 Please enter a positive position 3 of the symbol on the first line: 10 4 * 5 *** 6 ***** 7 ******* 8 ********* 9 *********** 10 ************* 11 *************** 12 ***************** 13 *******************
CS3530 Rat In A Maze Problem Requirement In this problem you will solve the “Rat in a maze problem”, using Stacks and Queues (Lectures 12-14). The main points we shall be covering are: 1. Using Stacks and Queues in an application 2. Re-enforcement of the usage and advantages of makefiles / make utility in UNIX/Linux 3. Use of abstract data types in C++, and separate compilation 4. Use of header files and libraries for Stacks and Queues
CS140 Matrix-Vector Multiplication Requirement This assignment is to write a parallel program to multiply a matrix by a vector, and to use this routine in an implementation of the power method to find the absolute value of the largest eigenvalue of the matrix. You will write separate functions to generate the matrix and to perform. the power method, and you will do some timing experiments with the power method routine.
