[pdf-embedder url="https://assignmentchef.com/wp-content/uploads/2025/01/EEE8087_Time-Slicing_Notes.pdf"] EEE8087 Real Time Embedded Systems Worksheet 4. The Time-Slicing Structure This week we startwork on the central components of an elementary real-time operating system (RTOS) that divides the processor's time between separate user tasks. These tasks will need to communicate with the system, and will request its services by means of a 'software interrupt'. Implementation of Software Interrupts A software interrupt is known as a 'trap'. It causes the processor to respond in a very similar way as it does to a hardware interrupt, and so allows system calls from the user program and interrupts from hardware devices to enter the operating system in a consistent way. There are 16 trap instructions available, numbered 0 to 15, and written trap #0 ... trap #15 Each of the 16 trap instructions may have its own interrupt service routine (ISR). After pushing the PC and SR, the processor then accesses a table in low memory, at address 80H. As for the hardware interrupts, the table contains a 4-byte value corresponding to the address of the ISR for each software interrupt. Vectors for the two types of interrupt will normally be combined into a single block of code. ;interrupt vectors org $64 ;origin 64H hvec1 dc.l hisr1 ;address of hardware ISR 1 hvec2 dc.l hisr2 ; ... etc org $80 ;origin 80H svec0 dc.l sisr0 ;address of software ISR 0 svec1 dc.l sisr1 ; ... etc Controlling Interrupts There is, however, an important difference between hardware and software interrupts. Hardware interrupts are in order of priority, with 7 being the highest priority and 1 the lowest. If two hardware interrupts occur at the sametime, then the one at the higher priority will be accepted and the other one will be kept waiting until the first ISR has completed. If a hardware interrupt occurs shortly after another one, but while the ISR for the first interrupt is still in execution, then the processor will again compare the priorities of the two interrupts. If the new interrupt is of a higher priority, then it will interrupt the lower priority ISR. If the new interrupt is at a lower priority than the currently executing ISR, it will be kept waiting until that ISR completes. Software interrupts do not behave in an analogous way. Since the processor can only execute one instruction at a time, it would be impossible for two software interrupts to occur at the sametime, and unless a programmer includes atrap instruction within an ISR, there will also be no occasions on which a trap takes place during the processing of another trap. There is therefore no point in prioritising the software interrupts, and all 16 are at the same priority. There is, however, the question of the relative priority of the hardware and software interrupts. What if a hardware interrupt is raised at the sametime as the processor is executing a software interrupt instruction? This is handled by assigning all the software interrupts to priority level 0. Processing of a software interrupt is therefore interruptible by a hardware interrupt at any of the priority levels 1 to 7. Within your system, however, regardless of the type of interrupt being processed, you will want to prevent the acceptance of any other interrupt. Your system will therefore be completely uninterruptible. Once entered, it will always run to completion and then return to the user task that was running when the interrupt was raised. You will therefore need to disable interrupt acceptance, the procedure for which is explained now. Using the simulator, examine the 16-bit status register. Bits 8, 9 and 10 (labelled 'INT') hold a 3-bit value that represents the interrupt priority mask. When an interrupt is accepted, the mask is set to the priority level of that interrupt. A hardware interrupt will only be accepted if its priority is greater than the current setting in the mask. Normally, the mask is set to 000 (decimal 0) thereby allowing the acceptance of any hardware interrupt. However, it will remain at zero during its response to a software interrupt, since that is the priority of these interrupts, and will thereby allow the hardware to interrupt the software ISR. If you wish to prevent this, then the following instruction, placed at the very start of a software ISR, sets the mask to binary 111 (decimal 7). Any hardware interrupts will now be disabled, and held pending until the mask is returned to zero. or #$0700,sr ;disable hardware interrupts The status register will have been automatically saved on the stack at the start of the interrupt servicing. On execution of the 'return from exception' instruction (RTE), it will be restored, and the mask reset to the zero value that it held previously, thereby allowing the acceptance of any hardware interrupt that might have been raised in the meantime and is currently pending. If you want to enable hardware interrupts at any other time, the following instruction will set the mask to zero. and #$f8ff,sr ;enable hardware interrupts* Practical Work Assessment question Work in groups of three on this question. Your submission should include the following. Your software, including the RTOS and the test programmes you used to demonstrate it. Submit the source code, not the assembler output listing. Documentation: a .PDF file is preferable, otherwise .DOC. The names and student numbers of all three group members should be shown on the software heading and on the frontpage of the documentation. There are therefore two items to be submitted: a single software file, and the documentation. These items should be placed into a single zipped file, and uploaded to a Canvas submission point to be advised. The submission deadline is 2pm on Friday 17th January, 2025. Each item will now be described in detail. The RTOS The work consists of writing a basic time-slicing system, along the lines of the one discussed in the lecture. It should allow the execution of several concurrent user tasks, with support for task scheduling and inter-task communication. An outline programme is provided on Canvas, but you will write the service routines (including reset), the scheduler, and the user tasks for each application. The user tasks are located in memory, above the system itself. Each task has its own area of memory, with the programme code at the lowest address, data above it, and top-of-stack at the next address above this task's memory area. For example, the following task occupies memory between 2000H and 2FFFH. It has its code at 2000H, data at 2C00H, and stack at the top of the data area. Address 2000H Programme code 2C00H Data 3000H Top-of-stack The system runs in the foreground, and is entered following either a timer interrupt, a software interrupt from one of the tasks requesting service, or another hardware interrupt. The following system calls should be supported by means of software interrupts. They can either each be allocated to a separate trap number, or (as in the demonstration system) they can all be called on the same trap, with one of the registers used to hold a value identifying the requested function. Some of the calls also require additional parameters in other registers. 1. Create task Function: A currently unused TCB is marked as in use and set up for a new task. It is placed on the ready list. The requesting task remains on the ready list. Two parameters indicate the start and end of the memory area occupied by the new task and its data. Parameters: The start address of the new task, The address of its top-of-stack. 2. Delete task Function: The requesting task is terminated, its TCB is removed from the list and marked as unused. Any memory allocated to it is returned to the system. Parameters: None. 3. Wait mutex Function: If the mutex variable is one, it is set to zero and the requesting task is placed back onto the ready list. If the mutex is zero, the task is placed onto the wait list, and subsequently transferred back to the ready list when another task executes a signal mutex. Parameters: None. 4. Signal mutex Function: If the mutex variable is zero, and a task is waiting on the mutex, then that task is transferred to the ready list and the mutex remains at zero. If the mutex is zero and notask is waiting, the mutex is set to one. In either case, the requesting task remains on the ready list. Parameters: None. 5. Initialise mutex Function: The mutex is set to the value 0 or 1, as specified in the parameter. Parameters: 0 or 1. 6. Wait time Function: The requesting task is placed onto the wait list until the passage of the number of timer interrupts specified in the parameter, when it is transferred back to the ready list. Parameters: Number of timer intervals to wait. An additional function is executed automatically at start-up, or if the user presses the reset button. System reset Function: The system is initialised: all internal variables are reset, and each TCB is marked as unused. A TCB for task T0 is then created, and T0 becomes the running task. A practical RTOS would also include the following functions. These are not required in your submissions, but they are mentioned here for completeness of these notes. 7. Wait I/O: Function: The requesting task is placed onto the wait list, until an interrupt signifies completion of an I/O operation, when the task is transferred back to the ready list. Parameters: None. 8. Allocate memory Function: For tasks that require a large amount of memory, it is more efficient to allocate it as required when the task runs. A large area of memory is therefore kept free within the system, and a block from it, of say 16 kbytes, is returned to the requesting task. If the request is satisfied, the requesting task remains on the ready list. If there is insufficient free memory available, then the requesting task is put on the wait list until memory is returned when another task terminates. Parameters: On return, the start address of the allocated memory is held in the parameter register. The system assumes that a default user task, T0, is present. The system runs this task immediately after a reset. It will need to be located at a predetermined address, which will be coded into the reset function. Your system should be robust, and deal with errors in an intelligent way. For example, what if the user tries to create more tasks than there are available TCBs? Test programmes Test your system using the following programmes. You will recognise these as modified versions of the questions in last week's worksheet, this time running under your RTOS. 1. Testing create task and wait time functions. A stopwatch counts in seconds. It starts when button 0 is pressed and stops when the button is pressed again. The display shows two digits, and should be neatly formatted with unused digits blanked. It is programmed as follows. Timer interrupts are set to 100ms. Task 0 starts task 1, and both tasks run concurrently. A shared variable running is held in a memory location, and is set by T1 and read by T0. T0 displays a 2- digit value on the 7-segment display, initialised to zero. If running is set, T0 increments the display, then waits for 10 time intervals, and then repeats. If running is not set, T0 does nothing. T1 tests pushbutton 0. Each time the button is pressed, running changes state. 2. Testing initialise mutex, wait mutex, and signal mutex functions. A radiation monitor contains two devices that each generate a pulse each time a particle of ionising radiation is detected. The system alternately samples each detector for 100 ms, and records the count, a and b, from each device. It also keeps a running total of the two counts, c = a + b. The system measures the time since it started, and after 8 seconds displays the average count per second between the two detectors, that is, (2c / 2) / 8, or c / 8. (Because it monitors each detector for only half the time, there is an implicit assumption that the total for that detector is twice its actual count.) If at anytime during the 8-second measurement interval the total count c exceeds a certain critical value, the system immediately displays a danger warning by lighting the RH LED, and then continues running for the remainder of the 8 seconds. The LH LED is used to indicate an internal error, as will be explained later. It would be convenient to indicate a detection by pressing a button, but since we need to test this system in real-time, and it is not possible to press the buttons hundreds of times per second, we will simulate a fast arrival rate of detection pulses simply by programming the system to increment the two counters continuously. The programming is as follows. Timer interrupts are set to 100ms. Three tasks run concurrently. After performing any initialisation, tasks 0 and 1 update the counters, either a and c, or b and c, using the following instruction sequence which is repeated continuously. move.l a,d0 add.l #1,d0 move.l d0,a move.l c,d0 add.l #1,d0 move.l d0,c At the end of this sequence, variable c is tested to determine whether it has exceeded the critical value, and if so, the RH LED is lit to indicate a danger condition. You will note that variable c is updated by both tasks, which are liable to interfere with each other. A mutex operation is therefore used to enforce exclusion and prevent simultaneous updates. A call to mutex wait should be placed before the three instructions that increment this variable, and a signal call at their end. Task 2 waits for 8 seconds, then displays the result c / 8 on the 7-segment display. (The division can be done by shifting; see the notes for week 1.) The result may be shown in hexadecimal, which avoids doing a conversion to decimals. This task also checks that the mutex functions have worked: if the final value of a + b - c > 1, then there has been an error and this is indicated by lighting the LH LED. Submitting the test programmes. Your test programmes should be included at the end of your RTOS code. Place both programmes together, calling them prog1 and prog2. At the start of the user code, put the following branch instructions. org usrcode bra prog1 ; bra prog2 By commenting out one of these instructions, as has been done for prog2 above, it is easy to select the other for running. This is a much better arrangement than keeping two versions of the RTOS, with a different test programme in each, or pasting each test programme into the RTOS whenever it is required. However, since both programmes will be assembled together, you will have to ensure that you use different identifier names within the two programmes. You could, for example, start all labels and variable names within prog1 with 'p1' and those in prog2 with 'p2'. Documentation This consists of a user manual. It will explain your system to a user, and will therefore focus on what it does and how to use it. It will include a brief overview of how the system works internally, but only to an extent that is required for the programmer to use the system correctly. It should be structured as follows. 1. A general description, including, for example: explanation of the principles of multitasking and time-slicing, and how they are implemented; description of the memory layout of the user tasks as shown above; explanation of the startup behaviour: a default task runs, which may then start other tasks. 2. An itemised description of each of the user functions and their parameters. Explain all aspects of the behaviour of each function that are of interest to the user. For example, when a new task is created, does it run immediately, or is it put at the end of the ready queue? What if two tasks are waiting for the sametime, and so become ready together? Your descriptions should also state how long each function takes to execute. This time should be quoted in terms of instructions, and may be within a specified range, e.g., a particular function might execute in 30 - 50 instructions. 3. A short note about your two test programmes. How do they demonstrate that the system is working? Were there any unresolved problems with them? With normal typeface and spacing (such as used here) it would be reasonable to expect a length of no more than five or six pages. Submission in .PDF format is preferred, but .DOC(X) is also acceptable.
Supply Chain Management (BMGT3006S) PART 1: INTRODUCTION This Study Guide is designed to provide you with details of this module; the learning outcomes; plus, delivery and assessment arrangements. The Study Guide consists of 6 parts. Part 1 gives background details to the subject area are provided and the broad aims of the module are set out. Part 2 consists of the module outline. In this part the (a) module learning outcomes, (b) the themes and topics to be explored are explained along with the (c) learning supports to be used. Part 3 gives details of the module delivery arrangements. It sets out the session arrangements and the expectations in relation to your prior preparation and student engagement. Part 4 provides details of the assessment techniques used in this module explaining the assessment components, their rationale. Part 5 explains the UCD grading policy and grade descriptors drawing on the university document are given for each assessment component (i) Assignment 1, (ii) Assignment 2 and (iii) Examination. Part 6 presents the concluding comments. Accessing Brightspace Live Zoom Classes This module will be wholly delivered via UCD’s integrated Zoom classroom. Kindly logging into Brightspace, go to “BMGT3006S-Supply Chain Management-2024/25 Autumn”, click “My Class”, “Zoom”. Please always login using your UCD email address and your name. Your name should be visible to the lecturer and other students to facilitate collaboration. Please join your online session no later than five minutes before the advised time of your session. Engagement tools on Collaborate Throughout the online sessions for this module, you will be frequently asked to engage with both your lecturer, and with your fellow students. The lecturer may send you into breakout groups and you discuss some class content in smaller groups before your findings are discussed with the whole class. You may use the “Share Screen” function (if enabled) to show some summary points of the breakout group discussions. If you select “Chat,” a chat window will open and you can communicate with the whole class or with your lecturer. If you would like to send a private message to your lecturer, please select your lecturer’s name instead of everyone. By clicking on “Reactions”, another menu will open. This menu allows you to raise your hand if you have a question or would like to comment. If you see a hand icon in the left upper corner of your screen, your hand is currently raised. You can lower your hand by clicking on this icon a second time. The lecturer can also lower your hand. When you join a Zoom session, you will be muted, and your camera is turned off. But for better engagement in the class, it is advised to keep your camera turned on. Please only unmute yourself if you would like to speak to avoid background noises. You can change your audio and video setting by clicking the small arrow beside the “Unmute” or “Start Video” icon. Background Details The Supply Chain Management Course is one of the the modules under the Logistics Pathway. This module focuses on the study of business relationships between a company, its suppliers and its customers. Students develop in-depth knowledge of the entire flow of the end-to-end supply chain, from raw materials to finished products. A special emphasis is placed in information and supply flow through the value chain and the management of relationships. The module can also serve as an introduction to other Logistics Pathway subjects such as Operation Management, Global Logistics and Supply Chain Planning and Control where specific in-depth supply chain processes and mathematical models will be discussed. Module Aims The aim of this module is to provide students with an overview of the theory and practice of Supply Chain Management. It takes a process approach in that it provides a guiding framework in helping to understand the decisions involved in designing a supply chain strategy. This module focuses on the theoretical and practical aspects of SCM, and its role in enhancing customer fulfilment. It discusses the critical issues involved in supply chain design, and examines bridges to supply chain integration and collaboration. The module draws on student prior learning or work experience and combines insights from strategy, international trade and investment theory, human resource management and other areas. The assessment tasks for this module have been designed with this in mind as detailed later in the study guide. Programme Goals Programme Code: BBS36 (Sg) Programme Title: Bachelor of Business Studies Pathway: Logistics and Supply Chain Management Programme Goals Programme Learning Outcomes Programme Learning Outcome Assessed 1) Programme Goal 1: Informed Thinkers: Our graduates will be knowledgeable on management theory and will be able to apply this theory to business problems (Knowledge). Programme Learning Outcome 1a: Explain current theoretical underpinnings of business, the management of organisations and supply chains. Exam – Essay Question Programme Learning Outcome 1b: Apply appropriate methods, tools and techniques for identifying, analysing and resolving business problems within functional and across functional business areas of the supply chain. Exam – Essay Question 2) Programme Goal 2: Communication, Analytical and Critical Thinking Skills: Our graduates will have well developed skills of communication, analysis and critical thinking (Skills and Competencies). Programme Learning Outcome 2a Prepare a short business presentation (written and/or oral) on a current business issue. Continuous Assessment Programme Learning Outcome 2b: Analyse specific business case studies or problems and formulate a report detailing the issues and recommended actions. Continuous Assessment Programme Learning Outcome 2c: Conduct secondary research on logistics-related issues and report on the findings and draw appropriate conclusions. Continuous Assessment 3) Programme Goal 3: Personal and Professional Development: Our graduates will demonstrate a commitment to personal and professional excellence and development (Skills, Competencies and Attitudes). Programme Learning Outcome 3a: Develop collaborative learning and team-work skills by engaging in module-related team activities. Continuous Assessment Programme Learning Outcome 3b: Demonstrate capacity for problem solving collaboratively and individually. Continuous Assessment 4) Programme Goal 3: Ethical Awareness: Our graduates will demonstrate an awareness of ethical issues in business and their impact on society (Attitudes). Programme Learning Outcome 3a: Demonstrate an awareness of ethical values and business issues concerning the advancement of the broader societal ‘good’. Exam and Continuous Assessment Programme Learning Outcome 3b: Illustrate an understanding of how business decisions might influence society and the wider community at large. Exam and Continuous Assessment PART 2: MODULE OUTLINE Module Title: Supply Chain Management Module Code: BMGT3006S No. of ECTS: 10 Module Learning Outcomes · Critically appraise and evaluate any supply chain; · Demonstrate strategically and critically on the role of supply chains; · Describe and discuss how supply chain management supports the development and execution of a company’s winning competitive strategy; On completing this module, students will be expected to be able to: · Build a Strategic Framework to Analyse Supply Chains. · Design the Supply Chain Network. · Plan and Coordinate Demand and Supply in a Supply Chain. · Manage Cross-Functional Drivers in a Supply Chain. · Understand the Use of Informational Technology in a Supply Chain. Module Text: Wisner, J.D. (2023) Principles of Supply Chain Management: A Balanced Approach, 6th edition, Cengage. ISBN 9780357715604 Themes and Topics 1. Supply Chain Management and Competitive Strategy a. The Objective of a Supply Chain b. Achieving Strategic Fit c. Drivers of Supply Chain Performance 2. Designing the Supply Chain a. Factors Influencing Network Design Decisions b. Framework for Network Design Decisions c. Risk Management in Supply Chains 3. Planning and Coordinating Demand and Supply in a Supply Chain a. Demand Forecasting in a Supply Chain b. Aggregate Planning in a Supply Chain c. Coordinating in a Supply Chain 4. Managing Cross-Functional Drivers in a Supply Chain a. Sourcing Decisions in a Supply Chain b. Pricing and Revenue Management in a Supply Chain c. Sustainability in the Supply Chain 5. Information Technology in the Supply Chain a. The Role of IT in a Supply Chain b. The Supply Chain IT Framework c. The Future of IT in the Supply Chain Learning Materials For this module, please read the assigned chapters in the prescribed text and the additional readings assigned (see list below). 1. Ohmae, K. (1989). Managing in a borderless world. Harvard Business Review, 3(4), 60-64. 2. Drucker, P.F. (1994). The theory of the business. Harvard Business Review, 72(5), 95-104. 3. Prahalad, C.K., & Hamel, G. (1990). The core competence of the corporation. Harvard Business Review, 68(3), 79-91. 4. Fisher, M.J. Hammond, W. Obermeyer, and A. Raman. ‘Making Supply Meet Demand in an Uncertain World.’ Harvard Business Review (May – June 1994): 83-93 5. Quayle, M. ‘Purchasing and Supply Chain Management’. Information Management, 19, no.1/2 (2006): 1-3 6. Mejza, M.C. and J.D. Wisner. ’The Scope and Span of Supply Chain Management.’ International Journal of Logistics Management, 12, no.2 (2001): 37:55 7. Ohmae, K. ‘The Global Logic of Strategic Alliances.’ Harvard Business Review (March – April 1989): 143 – 52 8. Han, B., S.K. Chen, and M. Ebrahimpour. ‘The Impact of ISO 9000 on TQM and Business Performance.’ The Journal of Business and Economic Studies, 13, no. 2 (fall 2007): (1:25 pages) 9. Giunipero, L. and D. Percy, ‘World Class Purchasing Skills: An Empirical Investigation.’ Journal of Supply Chain Management, 36, no. 4 (2000): 4-13. Students completing this module are expected to participate in session discussions and learning activities and be familiar with recent developments in the business world. To facilitate this, the following source material is useful · The Economist · The Wall Street Journal · Fortune · Business Week · The Financial Times
Assignment – Spatial Data and Asset / Facilities Management Submission Date: see Moodle, note pre-submission topic declaration Submission Method (links to all forms on Moodle): o Pre-Submission – Declare your topic title, description and the names, geometry types and dimensions of your three location-based, nested, assets – to avoid risks of plagiarism your topic area should come from the existing list. Online form, first come first served o Submission A PDF of your pyramid, uploaded via Moodle / Turnitin Completing an online form. with information about the decisions you are making Five separate SQL scripts via an online form A PDF of your map uploaded via Moodle/Turnitin A PDF of your 3D visualisation uploaded via Moodle/Turnitin This assignment is worth 70% of the marks for the module. - An assignment is an independent piece of work: o Your work should not be identical to, or similar to, that of any other student or the work we do in class. Please make sure you follow all UCL procedures for academic integrity. o Discussing your assignment work or sharing your work with other students or having very similar answers is collusion. - If you have questions about this assignment, please post them on Moodle - That way everyone is given the same information - That way I remember what I’ve said to you and don’t mark you down for doing something that I wasn’t expecting - Any questions should be generic – as this is an assessment which will gauge how much you’ve learned during the module I won’t be able to solve very specific assignment-related problems for you. - Do not post any part of your assignment answer on Moodle - We reserve the right to block the Moodle forum if too many questions are asked multiple times and/or if questions are asked where the answer is in the assignment text. This would mean that none of your fellow students will be able to ask questions so be very careful! - The deadline for posting questions is 5 days before the assignment deadline - This is a digital submission – it is up to you to ensure that the files you upload to Turnitin or the online submission process are not corrupt in any way (in Turnitin you might be able to do this by downloading the uploaded files to check them, for the online submissions you will receive an e-mail which you should keep as evidence of successful submission) NB: You are limited to a maximum of 10 e-mails per day to avoid overloading the testing system Database Design and Build (70%) Overview The assignment involves the selection of a location-based asset management topic of your choice for which you will create a hierarchical pyramid to show how the features (assets) and decisions based on information about those features nest upwards. The pyramid should have 3 levels of spatial nesting You will then make a list of 7 decisions. Two of the decisions MUST use data output from lower level decisions (i.e. bottom-> middle and middle -> top). All decisions should relate to ONE level of the pyramid (up to you which level for the other decisions). You will then create the physical database for your topic, insert some data and demonstrate using queries how this data can be used as evidence for the decisions. Step 1 - Topic Pre-Selection/Declaration (online form, link on Moodle) See Moodle for details of where the topic list has been sourced from. You MUST check the topic description before you select a topic, and make sure you understand the topic. If the remainder of your assignment does not match the topic you will not pass. Select a topic and provide a topic title and list your three spatial asset tablenames and geometry types and dimensions. These must be nested (i.e. the top level contains the middle level and the middle level contains the bottom level): • The top level should be a 3D volume • The middle level should be a 3D volume or a 2D area (provided it nests inside the top level using st_contains) • The bottom level can be a 2D or 3D point or a 2D or 3D line or a 2D or area or a 3D volume (provided it nests inside the middle level using st_contains) Not nesting the assets correctly will result in marks being lost for decisions as well There is no specific deadline for this task but you should make sure you lock in your topic BEFORE doing any other work on the assignment! You should not use a university or school example as this would be too similar to the example we covered in class and would be plagiarism. Your decisions should also not be similar to those used in the class or lab examples – i.e. do not adapt existing text and SQL – make sure you start completely from scratch. Step 2 - Decisions (online form, link from Moodle) List the Decisions (link to online form. will be given in Moodle) 1. Write a description of the 7 decisions that your database will support • The decisions need context and should include some information as to what information is needed but also WHY the information is needed, how it will be used by the decision maker - In other words, you need to be clear on what the information will actually be used for - what is being decided. • All decisions should be based on a numeric value • Decisions should also include a realistic threshold value in the text See Appendix and Step 4 for further information. 2. You should have two decisions that build on information provided by a lower level query (i.e. three decisions in total) . You should make use of VIEWS to achieve this. • Create a view for the decision corresponding to the bottom level of the pyramid, and for the decision query select from this view • Create a view for the decision corresponding to the middle level of the pyramid that includes data from the view from the bottom level of the pyramid, and for the decision query select from this view • Create a view for the decision corresponding to the top level of the pyramid, that includes data from the middle level view, and for the decision query select from this view Step 3 - Pyramid (turnitin upload) 1. Create a THREE LEVEL pyramid for this organisation - similar to the example from the Centennial case study. This should include the names of the spatial asset/features that are at the bottom, middle and top levels of your pyramid a. These names must be IDENTICAL to the name of the table that stores data for this feature. b. All table names should be lower case c. All three tables (assets) must match the tables you declared in the pre- submission stage d. All three features must be spatial - i.e. mappable (they can be 2D or 3D depending on how they were originally declared) e. The features must nest - i.e. features at the lowest level must be contained inside features at the middle level, and features at the middle level contained inside features at the upper level. Include a cover sheet in this PDF as Moodle requires a minimum of 35 words for plagiarism checks. Step 4 - Database creation (5 script. files, online form) For this part of the assignment: 1. Script. creation as follows: a. Create an SQL script that contains the SQL used to create the tables in your database system. Call this script. createtable_ucxxxxx.txt (where ucxxxxx is your UCL login). All table names should be lowercase, use _ to separate out any words (not spaces or -) • Make sure you use addGeometryColumn to add location columns – the SQL testing scripts will not work if this is not present • Make sure you use the parameters approach following the in-class example. b. Create a separate SQL script for all the constraints. Call this script. createconstraints_ucxxxxx.txt c. Create a separate SQL script. to populate each table with data - call this script. insertdata_ucxxxxx.txt: • A minimum of 2 rows of data for the top level of the pyramid • A minimum of 3 rows of data for the middle level (nested within the top level data) • A minimum of 9 rows of data for the bottom level (nested within the 3 rows of the middle level) • A minimum of THREE rows of data for all other tables. The data should be sufficient to allow you to test out the SQL for your listed decisions. So that we can test your work independently, your SQL must create ALL the data required from scratch – don’t use any data that has been imported via QGIS / sourced from third parties. The spatial data you create does not need to be very sophisticated in terms of geometry complexity. All data should use a projected coordinate system (i.e. not lat/lng – if you don’t know the projected coordinate system for your location use British National Grid) d. Upload a script that creates a series of views that will help to simplify your queries – minimally, you should have 3 views, one for each level of the pyramid that aggregates from the lower levels. You should also have a latest_parameters view. Your file should only contain views – do not include the select statements to test the views. Call this createviews_ucxxxxx.txt e. Create a script. file with the 7 SQL queries that provide data used to support the decisions you listed in the first part of the assignment. Call this decisions_ucxxxxx.txt • The result of each decision query should appear as a three-column table, with ONLY ONE ROW as follows.: • The decision text is hard coded in your SQL, the threshold value is hard coded in the SQL, the result is a number calculated from the inserted data. As a very simple example of hard coding in SQL (note the single straight quotes) select ′This is a decision ′, ′22.3′, > from ucfscde.buildings; • To meet the Step 2 (2) criteria, three of the seven statements should be just select * from ucxxxxx.view_name 2. Use the provided test system (link on Moodle) to upload and test your scripts. You will receive an e-mail report each time you run the test. Keep this as evidence that you have submitted your scripts. Some CHECKS • The SQL scripts should be manually created – i.e. typed by you • You must use the provided PostGIS database • The first line of the createtable script should drop cascade the ucxxxxx schema (if it exists) and create it again • All the SQL should work in your schema – e.g. your create table scripts should be similar to: create table ucxxxxx.buildings (……), your insert scripts insert into ucxxxxx.buildings and queries select from ucxxxxx.buildings • Do not include views in the decision queries – use a separate views file • Include comments in your scripts to make them easy to read – use -- to mark the comments o Any comments should be prefixed by -- (not /* */) • Each element (create table, constraint, row insert, decision query etc) in the script should be separated by a ; • Make sure that the filenames are correct. • Any decision that requires the use of number values as part of the calculation - distances, minimum or maximum sensor values, cost for painting, available budget and similar should use parameters. Step 5 - Map and 3D visualisation (one PDF via Turnitin) Upload a PDF to Moodle containing a QGIS screenshot showing the spatial data you create and a 3D screenshot created in FME. The screenshots should include the entire QGIS/FME windows (including menus and layer list) so that it clearly shows that the data is spatial and the map has been created from data in the database.
COM60704/ COM62004 MEDIA WRITING MEDIA WRITING - ASSIGNMENT BRIEF Assessment 1: Individual Assignment - Feature Package (30%) Writing a feature article for publication requires so much more than simply putting pen on paper (or fingers on keyboard). From the developing of the slant of your article to the selection of sources to interview and quote to the final writing and editing, much thought needs to go into the entire process. In this assignment, it is necessary for you to draw upon the learning outcomes of your module topics so far, including that of interviewing, reporting, audience, and readership, writing and editing techniques as well as feature writing. You are required to: 1. Propose 2. Research 3. Interview (at least three human sources, including the profile subject), 4. Write, and 5. Edit/Proofread To ultimately produce a FEATURE WRITING of 1,000 to 1,200 words (1-to-2-page spread) that is suitable as COVER STORY for a print publication (i.e.: newspaper or magazine). Please note: the story angle must be pitched to and approved by the lecturer beforehand. Refer to the Module Assignment Brief for further details. Questions you need to ask before beginning this assignment: • What is your motivation to write about this issue? What is your agenda (purpose) and opinion on the issue? • Where and how will you source for materials/information that you need to build your story? Having your own opinions on the subject matter is a start, but all opinions need to be supported with evidence and facts. • To whom are you writing for? Do you think they will want to read your piece of work? • Which medium or platform do you intend to publish your story in? Newspaper? Magazine? Online? The medium will dictate how extensive/in-depth your opinion piece will be. • What kind of impact or effect do you want to leave on your readers? How do you want them to feel/react after reading your piece? INSTRUCTIONS • Firstly, pick an issue close to your heart that you want to write about and make sure you have a strong, evidence-based opinion on the issue. Outline the main points you want to make. (e.g. you want to write about climate change issues, and you believe the fight will be spearheaded by young people. You can write about how you and other young people are doing your part to act on climate change, drawing from various news articles and personal experiences. You can interview one or two other young people to comment on your story as well) • You need to do adequate research to plan and build on your story to ensure that whatever views and opinions you want to promote and share, they are credible. As such, leverage on issues that is currently trending which you are passionate or care about. • Before writing the story, like any journalist or columnist in the newsroom, you will need to pitch this story idea first to the editor (which is your module coordinator). This will take place in Week 3. Your story pitch will need to satisfactorily address the five questions that was outlined above. • You will need to quote from a minimum of two people/sources to lend credibility to your story. If you are quoting a person, ensure he/she has considerably expertise or experience to comment on the issue. If it is from a previously published source, ensure it is fact-checked, accurate and credible SUBMISSION FORMAT • Submission of this assignment will be made through myTIMeS in PDF format only. Your submission needs to include following: 1. Assignment coversheet (first page) 2. Your feature article (1,000 -1,200 words, 1.5 paragraph spacing, Times New Roman font 12) a. Article’s headline and your byline + student ID + Publication name (where do you envision this story being published?) b. You may include any accompanying images with photo captions and source. 3. List of references used 4. Appendix: Basic details of your sources, and Interview Q&A 5. Please include Turnitin Report in the submission. The plagiarism percentage cannot be more than 10% 6. Feedback form. (last page) MARKING RUBRICS Gather, generate, and communicate messages by combining, synthesizing, or reapplying new and existing information through various media platforms. Criteria Deliver content with consideration of audience, purpose, and context surrounding the task, both orally and in written form as well as any other appropriate forms Weightage 30% Outstanding (22-30) Deliver compelling content which demonstrates a thorough understanding of appropriate context, audience, and purpose, in oral, written and any other appropriate forms Mastering (15-21) Deliver a central content which demonstrates a thorough understanding of appropriate context, audience, and purpose, in oral, written and any other appropriate forms Developing (8-14) Deliver basic content which demonstrates a basic understanding of appropriate context, audience, and purpose, in oral, written and any other appropriate forms Beginning (0-7) Deliver superficial content which demonstrates a lack of understanding of appropriate context, audience, and purpose, in oral, written and any other appropriate forms Assessment 2: Group Assignment - Developing an Online Media Website (40%) Writing for media encompasses many different forms of written works and styles. In this module, you have learned a range of writing – from factual news and human-interest stories to promotional writing. In this major group assignment, it is necessary for you to draw upon the various learning outcomes from the entire module including that of news writing, feature writing, promotional writing, broadcast writing as well as editing techniques. You are required to: 1. Form. into groups of 6 - 8 (maximum 8) 2. Research 3. Interview 4. Write 5. Video shoot 6. Edit 7. Design To ultimately produce a complete WEBSITE FOR A SPECIFIC THEME Points to note: • Every piece of writing that makes up the website content needs to be ORIGINAL and non-plagiarised from any existing resource. • The design and layout of the website is up to you, and it need not be overly complex. ASSESSMENT • Gather, generate, and communicate messages by combining, synthesizing, or reapplying new and existing information through various media platforms. • Demonstrate suitable media writing and editing styles for print, broadcast and online media platforms. • Develop, interpret, and express ideas through written and verbal communication. • Working collaboratively in a team. THEMES Some possible examples include current issues, music, performing arts, fine arts, spoken words, film, animation, literature, photography, video games, visual arts and design etc. GROUP WORK • Each member of the group to produce minimum of 2 write-up. Include proper headline and byline. • Flexibility and divergent thinking • Demonstrate disciplinary convention and display organisation • Build positive relationships, establish, and maintain cooperative relationships and actively participate within a group (Measuring: Relationship Management and Active Participation) SUBMISSION FORMAT • Submission of this assignment will be made through myTIMeS in PDF format only. Your submission needs to include following: 1. Assignment coversheet (first page) – List down all the group members’ name and to include website title and URL link. 2. List of references used 3. Group leader to fill in the Google form. uploaded on myTIMeS with details of the website.
Pre-Master’s Program Quantitative Skills for Postgraduate Studies Individual Research Project, Total Marks: 50 marks Instructions: ÿ Students are to complete the report to the best of their ability. (Help is always available from your teacher.) ÿ Students who fail to submit the report will be awarded 0%. ÿ Any requests for extensions must be made in writing at least 48 hours before the submission deadline. ÿ Do not re-produce the question. ÿ You should model your report on solutions to problems given in class. ÿ Use the ‘Project Report Requirements’ and ‘Submission Requirements’, on Page 2, to ensure that your project report meets the requirements. Note that there are marks allocated for these requirements. ÿ The question for this assessment is on Pages 3 – 4 of this document. ÿ Use the ‘Assessment Rubric’ on Pages 6 – 11 to guide your responses. Project report requirements: ÿ Typed using a word processor such as Windows Word ÿ The University of Adelaide College Assignment cover sheet – Completed, signed and scanned into the word document ÿ Cover Page ÿ Content Page ÿ Relevant paragraph heading format ÿ 1.5 line spacing ÿ Arial or Times New Roman font – size 12 ÿ Header and Footer o Header – Name and student number o Footer – Assignment name and Page number ÿ In-text reference using Harvard Referencing ÿ End of text reference list using Harvard Referencing Note: > Tables, charts, diagrams and other images from external sources must be referenced. > Ensure that you have referenced all content from other sources. Submission requirements: 1. Name your word / pdf file with the format “First name_Last name_Student number_QSPS_IRP” e.g. “John_Smith_a1234567_QSPS_IRP”. 2. Submit your word / pdf document online (in MyUni) through the submission link ‘IRP’. 3. Name your Excel file with the format “First name_Last name_Student number_QSPS_IRP_Ex” e.g. “John_Smith_a1234567_QSPS_IRP_Ex”. 4. Submit your Excel document online (in MyUni) through the submission link ‘IRP_Excel’. 5. Submit your assignment by 2359hrs Friday, 6 January 2025. 6. Unapproved late submissions will have marks deducted. Report Question: The “World Tea Organization (WTeaO.org) is a world-wide platform. that unites and serves world tea associations, experts, producers, merchandisers & tea lovers, and promotes the Tea Science, Tea Health, Tea Art, Tea Business and Tea Culture of “Healthy, Harmony, Pure, Nature” all over the world.” . Having heard of the success of the Mombasa/Nairobi Tea Auctions in Kenya, the World Tea Organization is interested to know more about the auctions. As a specialist in the area of Quantitative Skills, the World Tea Organization has requested that you produce a report. Using the Excel document, ‘Tea Prices Working Document_Your name’ and the information that you have prepared for the ‘End of Topic Tasks’ from Week 7 to Week 12, prepare a report that includes the following: ÿ A description of the data and its source. ÿ A description of the sampling method used to draw any random samples and reasoning as to why this method was used. ÿ A visual representation of any random sample and the population data. o Include a description of the visual representation for both the population data and random sample. o Include a comparison of the visual representation of the population data and random sample. ÿ A comparison of the key measures of central tendency and dispersion of both the population data and random sample. o Include key summary outputs / tables. o Include diagrams where appropriate. ÿ The probability that the tea prices at the auctions will increase based on previous months’ prices. o Include any calculations, data or diagrams that are relevant. ÿ The proportion of months where the price of tea at the auctions is lower than $3.80 but above $2.00, expressing this as a percentage. o Include an explanation as to what this implies for the price of tea at the auctions in future months. ÿ A confidence interval of your choice* for the population mean tea prices. o Include a description of the reason for your choice*. o Include an explanation of the purpose of the confidence interval. ÿ Information on whether there is evidence at a 5% significance level that the tea prices of the random sample is different from the population mean. o Include your definitions for the null hypothesis and alternative hypothesis, and your reasons for their definition. o Include information on the test statistics used. o Include a description of the critical values and the rules for rejection. o Include a conclusion of the test and explain your conclusion. ÿ The influence of the demand for tea on the tea prices at the auctions. o Include relevant diagrams describing the relationship and a description of the diagram. o Include trend(s) identified (if any) of the population data, using appropriate techniques (Least-squares regression or moving averages), and provide reasons for the choice of technique included. o Include a mathematical model (and a brief explanation of the model) showing the relationship between the demand for tea and the tea prices at the auctions. o Include a clear discussion on the values of the correlation coefficient and coefficient of determination.
MTH020 INTRODUCTORY MATHEMATICAL MODELLING 2024-25 1st SEMESTER FINAL PROJECT BACHELOR DEGREE - YEAR 1 REQUIREMENT OF FINAL PROJECT The students work in teams on certain practical problems with knowledge mainly from one of the following or related areas for mathematical modelling, then present their outcomes in final reports and posters. (a). Data visualisation, data fitting, and linear regression. (b). Time series analysis, in particular, autoregressive integrated moving average (ARIMA) models. (c). Graph theory, in particular, shortest path and minimum spanning tree. (d). Linear programming, in particular, simplex method. DESCRIPTION OF FINAL PROJECT (1). The duration from the release date to the due date is 6 weeks, for example, 18 November - 30 December 2024, or any other equivalent period. (2). Students are free to find classmates to form. teams, each typically consisting of 3 to 6 members. (3). Every student team designates a team leader, responsible for the duties of communication, submission, etc. (4). Every team find one or several related practical problems worthy of study and of appropriate level regarding the academic background of the team members. (5). The practical problems could be adapted from reliable resources, such as problems from previous mathematical contests in modelling, e.g., MCM/ICM, CUMCM, from textbooks or reference books, or could be designed by the team members themselves out of consideration of the real world around them. (6). The practical problems should be solved mainly with the theories and techniques in the aforementioned areas for mathematical modelling. (7). The relevant computation could be fulfilled with any computer programming language or software / application / program in which they are skilled, not limited to Matlab or Python. (8). The team members are suggested to take different roles for different tasks such as modelling, programming, and writing, and meanwhile cooperate closely with each other. (9). The outcomes ought to be demonstrated in a final report and a poster, both written in English. (10). The final reports and posters be marked according to criteria in modelling, results, and writing, respectively. (11). The contribution of each team member be reviewed and graded by every other member in the team. We call the results peer marks. (12). For each student, this Final Project contributes 65% to the overall mark of the module MTH020. The final report contributes 50% to the mark of the Final Project, the poster 30%, and the average peer mark 20%. Support files ought to be submitted at the sametime, although carrying no marks. More details are in the Marking Scheme below. (13). The final report and poster could be produced with software / application / program such as Microsoft Office Word, PowerPoint, a LaTeX typesetting system, or the like. There are LaTeX distributions MiKTeX under Windows, MacTeX under macOS, TeX Live under Unix / Linux, and CTeX for Chinese language, etc., all with full compilation system and compatible editors. But, the website https://www.overleaf.com/seems particularly easy to use for beginners. (14). The format of the final report ought to be a PDF document of A4 paper size, portrait orientation, suitable font, font size, margins, line and paragraph spacing, etc. There is no limit of number of pages. (15). The format of the poster ought to be a PDF document of 80cm*140cm paper size, portrait orientation, suitable font, font size, margins, line and paragraph spacing, etc., on a single page. (16). The final report could include a title page with the title, list of team members, summary, and key words, properly structured sections and subsections such as statement of problems, assumptions, models, calculated / computed results with analysis, conclusions and discussions, references, appendix of programming code, etc. (17). The poster could include the title, list of team members, abstract, problem, assumptions, models, results, conclusions, and references. (18). Whenever necessary, definitions, propositions, remarks, and equations should be numbered consistently and cross referenced properly, as well as proper citation of the references in the context. (19). Existent templates from various resources may be used for your final report and poster, and award-winning papers of prestigious mathematical contests in modelling could betaken as exemplars. (20). Generative artificial intelligence (AI) tools, such as ChatGPT, Microsoft Copilot, are allowed to use in knowledge learning, reference searching, resource locating, content polishing, programming code generating, and so forth. But, (i) explicit declaration should be made in any part done aided with AI, (ii) websites and names of AI tools should be clearly included in the references part, and (iii) the entire record for the sessions of dialogues with the AI tools should be completely appended to the final report, after the appendix of programming code. (21). At different stages of the Final Project, the module examiner will send out announcements via email from the Learning Mall Core. More instructions will be provided for technical steps such as grouping students into teams, collection of peer marks, submission of final reports and posters, etc. (22). Outstanding posters maybe printed out for public display to a broader audience. (23). Any violation of academic integrity will result in penalties and demerit points. For detailed information please refer to the University’s ‘Academic Integrity Policy’ and the ‘Student Discipline Point System’ appended to the ‘Regulations for Conduct of Examinations’ .
ECON33001 MACROECONOMICS OF DEVELOPMENT Semester One, 2024 1. Consider the following production function for human capital h(Sj, Qj ) = Qj exp (μjS j ) where Sj is the years of schooling in country j, Qj is quality of schooling in country j. To carry out development accounting we need an estimate of human capital. We have sample of migrants from a number of countries working in the US. We also have sample of workers for the same countries working in their home country. The samples of workers working in the US and working at home consist of different workers. The information about each worker in the samples include wages, years of schooling and a set of wage relevant characteristics. However, we do not observe school quality in country j, Qj. (a) [12 MARKS] To construct human capital we need to estimate the returns to years schooling, μj. Explain why it is crucial for estimating the returns to schooling to assume that different types of human capital are perfect substitutes in the production function. (b) [12 MARKS] How do we estimate on the data the returns to years of schooling? (c) [12 MARKS] Suppose we want estimate the return to years of schooling on all of our samples. How μj can be linked to the above production function for human capital? (d) [14 MARKS] What can be learn from (c) about the estimation of Qj? Is there an issue with estimation of Qj? 2. Consider a two–sector version of the growth model with agricultural and manufactured goods. Time is discrete and runs forever and there is a continuum of measure one of identical households. The utility function is given by where the consumption aggregator is and µ and C¯ are positive constants. The production functions for agricultural and manufac- tured goods take the form. where T = 1 island, Lat + Lmt = 1 is total labor, and At is total factor productivity. At grows at a constant factor γ > 1. (a) [12 MARKS] Argue that A0 >C¯ is a necessary condition for an interior equilibrium, thus, an equilibrium with positive employment in both sectors. (b) [12 MARKS] Derive the equilibrium conditions, and show that along the equilibrium path, laboris reallocated from agriculture to manufacturing (“structural transforma-tion”). Provide intuition for why structural transformation takes place in this econ- omy. (c) [12 MARKS] Show that the growth rate of real GDP, Yt = Pt Cat + Cmt , is increasing over time. Provide the intuition for why that is the case. (d) [14 MARKS] Land owners are often opposed to structural transformation. Suggest how to modify this model so that it can be used to provide an explanation for their opposition.
DEN401/DENM004 Computational Engineering Assessment 2022/2023 Question 1 A chimney is designed to vent gases over the top of an industrial building. For the design purposes chimney can be considered as a uniform hollow circular tube with a mean diameter D, a wall thickness t and the height H. The design requirements are that the chimney must not fail under the wind loads, and that the amount of material it is made of is the lowest possible. For the design purposes the chimney can be considered as a cantilever beam that is subjected to a uniform. lateral wind load q (N/mm), as shown in Figure 1. The following requirements are to be satisfied: 1. the chimney must not fail in either bending or shear, 2. the deflection at the top should not exceed 127 mm. 3. the ratio of the mean diameter to the wall thickness must not exceed 60. All relevant information and equations are given in the Table of figure 2. According to the design requirements the ranges of values are D and t are: 150 ≤ D ≤ 650 mm and 2 ≤ t ≤ 15 mm. Figure 1: Chimney showing loading and dimensions a) Formulate the optimum design problem. [25 marks] b) Solve the optimization problem using the graphical method using only the following 11 values of the mean diameter: (150, 200, 250, 300, 350, 400, 450, 500, 550, 600, 650) [25 marks] Figure 2: Material properties and relevant equations for the problem shown in Figure 1 Question 2 In the design of a structural component the criteria F1 and F2 are to be minimised; where F1 describes the maximum stress in MPa and F2 describes the cost of the component in pounds £ . These criteria depend on one design variable x in the following way: F1 (x) = 200(x2 - 4x + 5) F2 (x) = 25(48 - 9x) The design variable x can take any values in the range between 0 and 4. a) Plot the Pareto optimum set by identifying several points in the space of the two criteria F1 and F2 . [10 marks] b) Assuming that the desirable value of the criterion F1 is 250 MPa and that of the criterion F2 is £500, formulate and solve the corresponding minmax problem. Identify the obtained design as a point of the Pareto optimum set. [8 marks] c) Describe briefly how this minmax problem can be re-formulated using the bounded objective function formulation. State (i) the benefits and (ii) any setbacks this formulation brings as compared to the original formulation of the multiobjective problem. [8 marks] Consider the two-beam problem shown in Figure 3. The beams are of length L = 1m and L = 0.25m, have moment of inertia I=2 × 10-4 m4 and modulus of elasticity E=200 GPa. Some force is applied to the left side of the beam causing a vertical displacement of 0.001 m. Figure 3: Beam bending problem domain. d) Using two elements to resolve the two-beam sections, solve the displacement problem and find the rotations and displacements at the three points of the two beams. You may use any node and element numbering as you wish. [17 marks] e) What force was used to cause the displacement on the left side? [8 marks] Question 3 The plane stress structure, of thickness t = 0.01 m, shown in Figure 4 is represented by a single triangular element. The node numbers of the elements are shown in red, their positions are stated in metres. Figure 4: Diagram of 2D Plane Stress Structure a) Using the interpolating properties of the FEM basis functions, write an expression for the 3 linear basis functions at the nodes of the element. [12 marks] b) Form. the force vector of the element’s stifness equations for the surface pressure applied to the bottom edge. Do this by evaluating the integral along element’s surface using an appropriate numerical integration rule. [18 marks] c) Use your solution to part b) to solve for the displacements using the following global matrix system. If you have not answered b), use the vector provided in equation 2. The force vector - ONLY TO BE USED IF YOU HAVE NO ANSWER FOR PART b). Note this has no relation to the answers to part b). [10 marks] d) An additional body force of B kN/m3 in the y direction is placed evenly across the element. Determine the maximum value of B such that the displacement does not exceed 0.0001m in the negative y direction. [10 marks]
1. The USDA has tasked you with evaluating changes in the price of cereals and bakery products sold at retail (in the grocery store). (a) [10 pts] Collect the Consumer Price Index from the Bureau of Labor Statistics (CUUR0000SAF111). Your download should include every month between 1990 and August 2024. (b) [10 pts] What type of index is used to develop this series? (c) [10 pts] Where might you find alternative series? (d) [10 pts] Plot the data and describe. Are there any periods where the series changed in an obvious way? Which historical events might these changes align with? (e) [10 pts] Estimate the percent price change between January 2020 and January 2024. How does this compare to the percent price change between January 2016 and January 2020? 2. You have been asked to evaluate how corn markets and production changed following the implemen- tation of the renewable fuel standard (RFS). You will have to develop a theoretical model(s), locate data, and analyze that data. (a) [10 pts] Citing at least one peer-reviewed source, briefly describe RFS effect on U.S. corn markets. (b) [10 pts] Develop a theoretical model of how you expect the change described in part (a) to influence economic decisions. (c) [10 pts] Identify, extract, and assess at least one data source describing changes in a relevant output market(s). Cite your source(s). (d) [10 pts] Identify, extract, and assess at least one data source describing changes in a relevant input market(s). Cite your source(s). Statistics or econometrics can be helpful but are not required. (e) Describe how your data support or contradict the theoretical model described in part (b).
Assignment 2 Specification (Version 2) Machine/Deep Learning and Natural Language Processing Document Analysis (COMP4650 /COMP6490), 2024 Semester 2 Tasks This assignment consists of 5 tasks related to classifying job descriptions. Task 1: Analyse the Document Collection (max 5 marks, indicative) Familiarise yourself with the following job postings dataset available at https://www.kaggle.com/datasets/shivamb/real-or-fake-fake-jobposting-prediction/data. The set contains around 18K job postings, out of which about 800 are fake. Analyse the set; in this linguistic analysis, you may wish to report on not only linguistic characteristics of postings but also describe their structure by comparing and contrasting text under some key posting fields and/or within different categories considered in text classification tasks below. Report in your PDF file your analysis methods and results (max 360–440 words), supported by possible Tables and Figures plus the list of references. Submit your code as part of your ZIP file. Task 2: Text Classification with Logistic Regression (max 5+ 5 = 10 marks, indicative) In Task 2, you will use the dataset from Task 1 to perform. text classification. Recall from the lectures that a text classifier predicts a label for a piece of input text, and such a text classifier can be trained from examples that have the ground truth labels. In Task 2, you will build logistic regression classifiers to label the job descriptions in the dataset. Task 2 will consider the following two text classification problems: 1. Given a job description (found in the “description” column of the dataset file), predict the required education level of the job (found in the “required_education” column). a. There are 13 different educational levels found in the “required_education” column of the dataset. To simplify this first classification problem, you can consider only those job postings where the “required_education” column has one of the following three values: “Master’s Degree”, “Bachelor’s Degree”, “High School or equivalent”. You can filter out the other job postings where the required educational level is not one of the above for this first classification problem. b. You should use only those non-fraudulent job postings (indicated by the “fraudulent” column) to train, validate and test your first classifier. 2. Given a job description, predict whether it is a fraudulent job posing (found in the “fraudulent” column, where 0 indicates a real job posting and 1 indicates a fake job posting). Imagine a job seeker who has access to many job postings that do not state the required educational level, and some of these job postings may be fake. Hypothetically, the job seeker can apply the second classifier as described above that you will build to detect and filter out the fake job postings, and then apply the first classifier that you will build to identify those job postings that the job seeker is qualified for. For this assignment, however, you will independently train and test the two classifiers. Part A (max 5 out of the max 10 Task 2 marks, indicative) A simple approach to building a logistic regression model for text classification is to use Term Frequency x Inverse Document Frequency (TF-IDF) features. This approach is relatively straightforward to implement and can be very hard to beat in practice. We will provide you with some starting code for the first classification problem, i.e., prediction of the educational level based on a job description. It should be straightforward to adopt the code for the second classification problem once you have completed the code for the first. Specifically, to build a logistic regression classifier using TF-IDF features, you should first implement the get_features_tfidf function (in features.py) that takes a set of training job descriptions as input and calculates the TF-IDF (sparse) document vectors. You may want to use the TfidfVectorizer in the scikit-learn package. You should use it after reading the documentation. For text preprocessing, you could set the analyzer argument of TfidfVectorizer to the tokenise_text function provided in features.py. Alternatively, you may set appropriate values to the arguments of TfidfVectorizer or write your own text preprocessing code. Next, implement the search_C function (in classifier.py) to try several values for the regularisation parameter C and select the best based on the accuracy on the validation data. The train_model and eval_model functions provided in the same Python file might be useful for this task. To try regularisation parameters, you should use an automatic hyper-parameter search method presented in the lectures. You should then run job_classification.py which first reads in the dataset and splits it into training, validation and test sets; it then trains a logistic regression text classifier and evaluate its performance on the test set. Make sure you first uncomment the line with the analyse_classification_tfidf function (which uses your get_features_tfidf function to generate TF-IDF features, and your search_C function to find the best value of C) in the top-level code block of job_classification.py (i.e., the block after the line “if name == ’ main ’:”) and then run job_classification.py. For training and testing this first classifier, remember to filter out fraudulent job postings and job postings whose required educational level is not among these three values: “Master’s Degree”, “Bachelor’s Degree”, “High School or equivalent”. Next, modify your code to train and test a second classifier for fraudulent job posting detection, i.e., a binary classification problem where the class labels are found in the “fraudulent” column of the dataset. Because this classifier is independent of the first classifier, here you should use job postings of all educational levels. Answer the following questions in your answers PDF for each of the two classification problems (max 360–440 words, supported by possible Tables and Figures plus the list of references): 1. What range of values for C did you try? Explain, why this range is reasonable. Also explain what search technique you used and why it is appropriate here. 2. What was the best performing C value? 3. What was your accuracy on the test set? Also make sure you submit your code as part of your ZIP file. Part B (max 5 out of the max 10 Task 2 marks, indicative) Another simple approach to building a text classifier is to train a logistic regression model that uses aggregated pre-trained word embeddings. While this approach, with simple aggregation, normally works best with short sequences, you will try it out on the job descriptions. Your task is to use Word2Vec in the gensim package to learn embeddings of words and predict the qualifications required of job descriptions using a logistic regression classifier with the aggregated word embedding features. You should use it after reading the documentation. First implement the train_w2v function (in word2vec.py) using Word2Vec from the gensim package, then implement the search_hyperparamsfunction (in word2vec.py) to tune at least two of the many hyper-parameters of Word2Vec (e.g. vector_size, window, negative, alpha, epochs, etc.) as well as the regularisation parameter C for your logistic regression classifier. You should use an automatic hyper- parameter search method presented in the lectures. (Hint: The search_C function in classifier.py and the get_features_w2v in features.py might be useful.) Next implement the document_to_vector function in features.py. This function should convert a tokenised document (which is a list of tokenised sentences) into a vector by aggregating the embeddings of the words/tokens in the document using trained Word2Vec word vectors. Last, you should uncomment the line with the analyse_classification_w2v function (and comment out the line with analyse_classification_tfidf) in the top-level code block of job_classification.py, and then run job_classification.py to train a logistic regression text classifier with the word vectors from your Word2Vec model, and evaluate the classification performance on the test set. Similar to Part A, train and test two classifiers for the two classification tasks: prediction of the required educational level, and identification of fraudulent job postings. Answer the following questions in your answers PDF for each of the two classification problems (max 360–440 words, supported by possible Tables and Figures plus the list of references): 1. What hyper-parameters of Word2Vec did you tune? What ranges of values for the hyper parameters did you try? Explain, why the ranges are reasonable. Also explain what search technique you used and why it is appropriate here. 2. What were the best performing values of the hyper-parameters you tuned? 3. What was your accuracy on the test set? Compare it with the accuracy you got in Part A of this question and discuss why one is more accurate than the other. Also make sure you submit your code as part of your ZIP file. Task 3: Text Classification with a Transformer Encoder (max 5 marks, indicative) In this task, you will apply a transformer-based classifier to perform. the same text classification tasks as in Task 2 and compare the classification performance with the results you have got for Task 2. Specifically, you will train a transformer encoder using PyTorch. An input sequence is first tokenised and a special [CLS] token prepended to the list of tokens. Similar to BERT, the final hidden state (from the transformer encoder) corresponding to the [CLS] token is used as a representation of the input sequence in this text classification task. First, implement the get_positional_encoding function in job_classifier.py. This function computes the following positional encoding: t ∈ {0, … , T − 1} Next, complete the __init__ method of class JobClassifier by creating a TransformerEncoder consisting of a few (determined by parameter num_tfm_layer) TransformerEncoderLayer with the specified input dimension (emb_size), number of heads (num_head), hidden dimension of the feedforward sub-network (ffn_size) and dropout probability (p_dropout). Then implement the forward method of class JobClassifier. You should implement the following steps sequentially in the function: (a) add the positional encoding to the embeddings of the input sequence; (b) apply dropout (i.e. call the dropout layer of JobClassifier); (c) call the transformer encoder you created in the __init__ method; (Hint: make sure you set the parameter src_key_padding_mask to an appropriate value.) (d) extract the final hidden state of the [CLS] token from the transformer encoder for each sequence in the input (mini-batch); (e) use the linear layer to compute the logits (i.e., unnormalised probabilities) for binary classification and return the logits. You should read the documentation before implementing these methods. Last, complete the train_model function to learn the classifier using the training dataset. You should optimise the model parameters through mini-batch stochastic gradient descent with the Adam optimiser. Make sure you evaluate the model on the validation set after each epoch of training and save the parameters of the model that achieves the best accuracy on the validation set. You are now able to run job_classifier.py which prepares the training, validation and test datasets, trains a classifier and evaluates its accuracy on the test set. Note that this approach does not directly use the combined training and validation datasets to re-train the model, and we adopt it here for simplicity. Tuning hyper-parameters systematically is not required (but encouraged if you have access to sufficient computational resources) for this question, and setting the hyper-parameters to some reasonable values (from your experience) is acceptable. In your answers PDF, you should record the values of hyper-parameters used in your text classifier. Similar to Task 2, train and test two classifiers for the two classification tasks: prediction of the required educational level, and identification of fraudulent job postings. Answer the following questions in your answers PDF for each of the two classification problems (max 360–440 words, supported by possible Tables and Figures plus the list of references): 1. What is the architecture of your classifier? (Hint: you may print your classifier in Python and record the output in your answers PDF.) 2. What was your accuracy on the test set? 3. Compare your classification performance with those you got for Task 2 (Part A and Part B). Discuss the advantages and limitations of the three approaches to job description classification. Also make sure you submit your code as part of your ZIP file. Task 4: Text Classification with a Pre-trained Language Model (max 1 + 1.5 = 2.5 marks, indicative) Pre-trained language models such as BERT and ChatGPT have been widely used for many NLP problems. As you have learned in the lectures, these pre-trained language models have strong capabilities to handle a wide range of tasks with little or no further training. In Task 4, you will use pre-trained language models to perform. the same text classification problem as in Task 2 and Task 3. Part A (max 1 out of the max 2.5 Task 4 marks, indicative) In Lab 6, you will see how to fine-tune a smaller version of BERT. Adopt the strategy of fine-tuning DistilBERT as you will learn in Lab 6 on the job posting dataset. Compare the text classification performance of using the original DistilBERT and your fine-tuned DistilBERT on the two classification tasks. Note that you will still use the [CLS] token produced by the model to perform. classification. Analyse and discuss the results you observe in your answers PDF in free-form. text (max 90–110 words, supported by possible Tables and Figures plus the list of references). Also make sure you submit your code as part of your ZIP file. Part B (max 1.5 out of the max 2.5 Task 4 marks, indicative) Prompt-based zero-shot text classification using a pre-trained language model such as ChatGPT has emerged as a new way of classifying text without any training involved. See, for example, the following Hugging Face page that explains how it works: https://huggingface.co/tasks/zero-shot-classification In this part of Task 4, use a Large Language Model (LLM) of your choice (e.g., ChatGPT, Gemini, or Llama) to predict the required educational level of a sample of job postings in the dataset and observe the performance of the LLM on the task. Report your findings in your answers PDF in free-form. text (max 180-220 words, supported by possible Tables and Figures plus the list of references). Things you can consider trying include, but are not limited to, the following (you are not required to do all of them): • Compare different LLMs on the job posting classification task, using the same subset of data you have sampled. • Compare the performance of the prompt-based zero-shot method with the previous methods you have tried in Task 2 and Task 3. • Use the LLM’s API to batch process a large sample of the data for prompt-based zero-shot classification, if you have access to the API. (This requires additional work of understanding the LLM’s API, which is not covered in this course.) • Discuss the pros and cons of a training-based method you have explored in the earlier parts of the assignment and of this prompt-based zero-shot method. Note: You do not need to use an LLM to predict whether a job posting is fraudulent in Part B of Task 4. You should submit your code, prompts, or other supporting information as part of your ZIP file. Task 5: Reflect on Your Learning and Academic Integrity (max 2.5 marks, indicative) Add a short written, free-form. text answer (max 180-220 words) to reflect on your learning and academic Integrity considerations relevant to your Assignment 2 work in your PDF file. In particular, explain where, how, and why you used Generative AI tools in coding and/or academic writing. Demonstrate your critical thinking skills in analysing and assessing the advantages and disadvantages of this tooling to your learning. If you chose not to use Generative AI tools, reflect on the advantages and disadvantages of this choice to your learning.
ECE3700J Introduction to Computer Organization Lab 5 – Resolving Hazards Purpose This lab is intended to take care of data hazards and control hazards that may arise in pipelined processors by adding forwarding mechanism, hazard detection components, and signals for stalls in hardware. Tasks This lab is based on the pipelined processor lab. You will add the necessary forwarding paths, hazard detection components, and stall mechanisms to the pipelined processor designed in previous lab to avoid stalls in software program. For data hazard, consider the cases that have been discussed in the lectures only. For control hazard, assume branch is always not taken. The entire design should be modeled in Verilog HDL. The design must be simulated with a Verilog simulator of your choice and synthesized by using Xilinx synthesis tool, meeting the following requirements: • Simulation results must be error-free • An RTL schematic must be produced from the synthesis tool FPGA hardware implementation is NOT required for this lab. A simple RISC-V assembly testing program with data and control hazards will be provided for you to verify that your processor can execute those instructions continuously and correctly. Team Organization This lab is a team effort. Each team should consist of 3 students, randomly grouped. The work should be appropriately divided and distributed among all team members. Students are not allowed to switch teams without permission of the instructor. Deliverables • Demonstration – Every team should demonstrate to the teaching group the following before your lab session ends: 1) Simulation results of your design by executing the given RISC-V assembly program; 2) RTL schematic generated by the synthesis tool. Each team member should be prepared for an oral exam on this lab during the demonstration. • Lab report – The lab report should be a written report including: 1) Brief description of all aspects of the modeling and implementation of the processor; 2) Screen shots and brief explanations of simulation results for all potential cases of data hazard and control hazard. 3) RTL schematic of your Verilog model generated with Xilinx Vivado software; • Peer Evaluation – Each team member is required to provide a peer evaluation for the team effort in this lab. The marks of the peer evaluation should be integers ranging between 0 to 10, inclusively, with 10 indicating the biggest contribution. A mark should be given to each team member including yourself according the team member’s contribution based on your observation. A brief description of contribution of each team member should also be provided, as shown in the following table. • Source Files – All your Verilog source files and any other supporting files should be submitted as appendix to the lab report. This is a 1-week lab. The full score for this lab is 500 points. All required documents should be submitted on Canvas before 22:00pm, July 13, 2024. Grading • Lab report: 40% • Demonstration: 40% - Working Verilog model (simulation): 30% - Individual oral exam: 10% • Source files and peer evaluation: 20%
FBE 506 Quantitative Methods in Finance Assignment #6 1. The production technology of a manufacturer is estimated to be Q = 150N - .025N2, where Q is output and N is labor input. The manufacturer has no constraint in hiring labor. a. What will be the optimum N and Q under the given assumption. The tight job market and the skill requirement of the industry that the manufacturer is operating has limited the hiring of the labor to no more than 250. b. Formulate the optimizing problem of the manufacturer under the new job market condition. c. Find the optimum N and Q under new condition. d. What does Lagrangian multiplier imply in this problem? 2. Find the critical points of Y = X3 -11X2 + 14X + 80. Test for the second-order condition to find which point is maximum, minimum, or inflection point. 3. The variance/covariance matrix of two assets A and B are given as: .075 .018 .052 The average annual returns to two assets are A and B are .13 and .21, respectively. The return to risk-free asset is 0.03. a. Construct the portfolio possibilities curve (efficient frontier) by assuming no short sales and by minimizing the risk of the portfolio (GMV). Graph the efficient frontier and find the risk and return of the portfolio. b. Construct the portfolio possibilities curve assuming that short sale is allowed. c. Graph the two curves together distinguishing them with different colors. d. Construct a portfolio that the investor tries to minimize the risk of the portfolio subject to portfolio return of the be higher than return to risk-free asset. e. Graph the efficient frontier, CAL, and find the tangency point. f. What will be the expected return to portfolio if the investor is willing to take 25% risk?
ASSESSMENT TASK INFORMATION: EUB405 Assessment 1 - Critique This document provides you with information about the requirements for your assessment. Detailed instructions and resources are included for completing the task. The Criterion Reference Assessment (CRA) Rubric that markers use to grade the assessment task is included. Task overview Assessment name Critique (written) Task description This task involves the critique of teaching material used in a learning area and suggestions for scaffolding to reflect the needs of EAL/D learners. Commonly used teaching resources are designed for learners who are proficient in Standard Australian English (SAE). Through identifying language demands and cultural assumptions and representations, you will evaluate a multimodal resource typically used in Queensland schools for its efficacy for use with a group of EAL/D learners at Bandscale Level 5. This group is broad and varied and includes migrant students who are literate in their L1, refugee-background learners who may have had interrupted schooling and who have limited literacy in their L1; Indigenous learners who may speak Aboriginal English or a creole, etc. Learners in each of these groups may speak several languages but are still learning SAE. This is an authentic assessment because it provides you with real world experience in identifying opportunities to teach language alongside content, and in differentiating teaching materials for learners who are developing proficiency in SAE. Task snapshot Length 1500 words +/-10% (word length includes in-text referencing and excludes your reference list and appendices) Weighting 40 % Individual or Group Pair Formative or Summative The final product is summative; however, feedback on your assignment has a formative dimension, as it is designed to ‘feed forward’ to assist with your ability to teach language alongside content. How will I be assessed Rubric (HD – LF) Learning outcomes measured 1. Demonstrating professional knowledge of the needs of EAL/D learners, including an awareness of recent developments in the learning areas of second language acquisition, learning and teaching (CLO1). 2. Reflecting critically on the ways in which educational theories of curriculum, teaching, and learning shape and inform. pedagogical, planning and assessment practices in relation to EAL/D learners (CLO2). 3. Demonstrating the skills required to synthesise complex ideas about second language acquisition and learning to create inclusive and positive learning environments in discipline areas (CLO3). 4. Communicating effectively and professionally communicating in all modes of scholarly and professional engagement to support EAL/D learners in discipline areas (CLO8). The assessment related directly to APSTs 1.2, 1.3, 1.4, 2.4 (please see https://www.aitsl.edu.au/teach/standards for further information on these standards). Submission information What you need to do 1. In pairs, you will critique a multimodal text for use by EAL/D learners at Bandscale Level 5. Select a typical multimodal classroom text from a chosen area of the curriculum. This can be from Prep to Year 6 (e.g., Year 3 Science, Year 5 Maths, Year 6 English). The text must be multimodal (contain written text and audio or visuals). A maximum of two indicative pages from the text will be selected for the critique. If you use a video, include two relevant screen shots and a transcript. of the selected excerpt from the video. The multimodal text could be: a section from a school textbook; a short story; a picture book; a section of a novel or film; an educational video; classroom handouts; other commercially produced resources. Worksheets/task-sheets alone will not be a suitable resource: you need enough text to analyse - at least 200 words. When choosing the text, make sure it is TYPICALLY USED, not specially written so that it is easy for EAL/D learners or has no cultural bias. These are not typical, although some more recently produced teaching materials do make an effort. 2. Annotate and critique the text, identifying the language demands and the cultural dimensions (cultural representations, cultural bias, knowledge) that are assumed and valued in the resource, including a clear Indigenous perspective. It is essential that you not only identify language demands and cultural dimensions that may be challenging, but also use relevant EAL/D literature to explain why these features may be challenging to EAL/D learners. For the purpose of this assignment we will assume that your EAL/D learners are around Band 5 for all language skills in the State Schools Queensland Bandscales. https://education.qld.gov.au/student/Documents/intro-guide-bandscales-state-schools-qld.pdf. Scaffolding to enable you to do this is embedded in the workshop activities throughout the unit. 3. Offer specific suggestions on how you would scaffold the text so that it is more accessible/appropriate for EAL/D learners. Base your decisions on current, reputable and relevant readings from the unit and further reading and support your ideas with reference to this literature. 4. In writing up the report, you will present it in two parts. You can set it out as a report with sub-headings. 5. Part 1 – Identifying language demands and cultural assumptions and representations. Begin this section with your annotated resource, followed by your written explanation of which features you have identified and why these features may prove challenging for your EAL/D learners at Band 5. Critique each resource in turn: a. Brief summary of where the resource is from and where it is used in the subject area/phase of learning. (50 words) b. Comment on the language demands of the resource and why these features may prove challenging for your EAL/D learners at Band 5 by drawing on relevant EAL/D literature. Look for: complexity of the language used e.g., vocab and associated concepts, sentence types, grammar structures used (use the additional sheet called ‘Finding the language help’ on Canvas and lecture/tutorial input and readings). c. Comment on the cultural information that is assumed and valued in the resources and why these features may prove challenging for your EAL/D learners at Band 5 by drawing on relevant EAL/D literature. Use the 7 Forms of Cultural Bias checklist we will use in class. Explain the evidence in the resource. How might this bias be problematic? Consider Indigenous learners and draw on what you have learned in the Indigenous unit. Parts 1b. and 1c. will take up approx. 550 words of prose (not including the selected text or annotations). 6. Part 2 - Offer specific suggestions for how you would scaffold the text, so it is more accessible and appropriate for EAL/D learners at Band 5. Ensure that in your response to Part 2 you address the key language demands and cultural assumptions you identified in Part 1. Base your pedagogical decisions on current, reputable literature. Avoid general suggestions, such as ‘show a picture’. Suggest specific scaffolding strategies and materials to help EAL/D learners to access and engage with the content of the text and to make it more culturally inclusive (900 words). 7. The analysis and suggested scaffolding should draw upon a total of at least eight relevant EAL/D readings from the unit and your own readings. Resources available to complete task · QUT cite|write – APA guide · How to submit an assignment with Turnitin What you need to submit One Adobe PDF document or Microsoft Word document that contains the following items: 1. Assignment Cover Sheet – must include: · unit code, unit name, semester and year, assignment title, student name, student number, word count · the following statement of authorship: In submitting this work, I declare that, unless otherwise acknowledged, this work is wholly my own. I understand that my work may be submitted to Turnitin and consent to this taking place. Submission requirements This assessment task must: 1. use QUT APA referencing for citing academic literature 2. be submitted in electronic format as an Adobe PDF document or Microsoft Word document via Turnitin by following these steps: a. Access the Turnitin Submission link >>View/Complete b. Click on the Submit button c. Give the submission a title, select the correct file and click Upload d. Click Confirm e. Click Return to Assignment list f. To check successful submission, you will receive a text match %, and you are able to resubmit, view or download your paper g. ALWAYS check your student email for the submission receipt Moderation All staff who are assessing your work meet to discuss and compare their judgements before marks or grades are finalised.
BISM7216 Business Process Improvement – Tutorial 2 (2024) Starter question: Explain the role of the main BPM stakeholders. Question 1: Consider the phases of the BPM lifecycle. Which of these phases is/are not included in a business process re-engineering project? Question 2: What are the benefits and shortcomings of BPM vs BPR? Question 3: Think back to our discussion of Taylorism in the lecture. What do you think are the negative consequences for the worker? What about for the organization? Question 4: What are the three main process traditions that underpin BPM as we know it today? Explain the core focus of each tradition. Question 5: What are the benefits of using a BPM Maturity Model? Question 6: What are the 6 success factors underlying the BPM Maturity Model?
ECE5550: Applied Kalman Filtering KALMAN FILTER GENERALIZATIONS 5.1: Maintaining symmetry of covariance matrices ■ The Kalman filter as described so far is theoretically correct, but has known vulnerabilities and limitations in practical implementations. ■ In this unit of notes, we consider the following issues: 1. Improving numeric robustness; 2. Sequential measurement processing and square-root filtering; 3. Dealing with auto- and cross-correlated sensor or process noise; 4. Extending the filter to prediction and smoothing; 5. Reduced-order filtering; 6. Using residue analysis to detect sensor faults. Improving numeric robustness ■ Within the filter, the covariance matrices and must remain 1. Symmetric, and 2. Positive definite (all eigenvalues strictly positive). ■ It is possible for both conditions to be violated due to round-off errors in a computer implementation. ■ We wish to find ways to limit or eliminate these problems. Dealing with loss of symmetry ■ The cause of covariance matrices becoming asymmetric or non-positive definite must be due to either the time-update or measurement-update equations of the filter. ■ Consider first the time-update equation: • Because we are adding two positive-definite quantities together, the result must be positive definite. • A “suitable implementation” of the products of the matrices will avoid loss of symmetry in the final result. ■ Consider next the measurement-update equation: ■ Theoretically, the result is positive definite, but due to the subtraction operation it is possible for round-off errors in an implementation to result in a non-positive-definite solution. ■ The problem may be mitigated in part by computing instead • This may be proven correct via ■ With a “suitable implementation” of the products in the term, symmetry can be guaranteed. However, the subtraction may still give a non-positive definite result if there is round-off error. ■ A better solution is the Joseph form covariance update. • This may be proven correct via ■ Because the subtraction occurs in the “squared” term, this form “guarantees” a positive definite result. ■ If we end up with a negative definite matrix (numerics), we can replace it by the nearest symmetric positive semidefinite matrix. ■ Omitting the details, the procedure is: • Calculate singular-value decomposition: Σ = USVT . • Compute H = VSVT . • Replace Σ with (Σ + Σ T + H + HT )/4. 5.2: Sequential processing of measurements ■ There are still improvements that may be made. We can: • Reduce the computational requirements of the Joseph form, • Increase the precision of the numeric accuracy. ■ One of the computationally intensive operations in the Kalman filter is the matrix inverse operation in ■ Using matrix inversion via Gaussian elimination (the most straightforward approach), is an O(m3) operation, where m is the dimension of the measurement vector. ■ If there is a single sensor, this matrix inverse becomes a scalar division, which is an O(1) operation. ■ Therefore, if we can break them measurements intom single-sensor measurements and update the Kalman filter that way, there is opportunity for significant computational savings. Sequentially processing independent measurements ■ We start by assuming that the sensor measurements are independent. That is, that ■ We will use colon “:” notation to refer to the measurement number. For example, z k :1 is the measurement from sensor 1 at time k. ■ Then, the measurement is where Ck(T):1 is the first row of Ck (for example), and vk :1 is the sensor noise of the first sensor at time k, for example. ■ We will consider this a sequence of scalar measurements z k :1 ... z k:m , and update the state estimate and covariance estimates in m steps. ■ We initialize the measurement update process with and ■ Consider the measurement update for the ith measurement, z k:i = E[xk | Zk — 1 , z k :1 ... z k:i — 1] Lk:i (z k:i — E[z k | Zk — 1 , z k :1 ... z k:i — 1]) ■ Generalizing from before ■ Next, we recognize that the variance of the innovation corresponding to measurement z k:i is ■ The corresponding gain is and the updated state is with covariance ■ The covariance update can be implemented as ■ An alternative update is the Joseph form, ■ The final measurement update gives and Sequentially processing correlated measurements ■ The above process must be modified to accommodate the situation where sensor noise is correlated among the measurements. ■ Assume that we can factor the matrix Σ = SvS , where Sv is a lower-triangular matrix (for symmetric positive-definite Σv, we can) . • The factor Sv is a kind of a matrix square root, and will be important in a number of places in this course. • It is known as the “Cholesky” factor of the original matrix. • In MATLAB, Sv = chol(SigmaV,'lower'); • Be careful: MATLAB’s default answer (without specifying “lower”) is an upper-triangular matrix, which is not what we’re after. ■ The Cholesky factor has strictly positive elements on its diagonal (positive eigenvalues), so is guaranteed to be invertible. ■ Consider a modification to the output equation of a system having correlated measurements • Note that we will use the “bar” decoration (-) frequently in this chapter of notes. • It rarely (if ever) indicates the mean of that quantity. • Rather, it refers to a definition having similar meaning to the original symbol. • For example, z-k is a (computed) output value, similar in interpretation to the measured output value zk. ■ Consider now the covariance of the modified noise input ■ Therefore, we have identified a transformation that de-correlates (and normalizes) measurement noise. ■ Using this revised output equation, we use the prior method. ■ We start the measurement update process with and ■ The Kalman gain is and the updated state is with covariance (which may also be computed with a Joseph form update, for example). ■ The final measurement update gives and LDL updates for correlated measurements ■ An alternative to the Cholesky decomposition for factoring the covariance matrix is the LDL decomposition where Lv is lower-triangular and Dv is diagonal (with positive entries). ■ In MATLAB, [L,D] = ldl(SigmaV); ■ The Cholesky decomposition is related to the LDL decomposition via ■ Both texts show how to use the LDL decomposition to perform a sequential measurement update. ■ A computational advantage of LDL over Cholesky is that no square-root operations need betaken. (We can avoid finding Dv(1)/2.) ■ A pedagogical advantage of introducing the Colesky decomposition is that we use it later on.
CAVA 1001 & CAVA1003 Visual Art Foundation 1 Digital Print-media Digital Collage Workshop Grace Wood, Lay Down, 2019, digital collage on fabric The invention of the computer and software products such as Adobe Photoshop saw a radical new development in artistic production. It brought with it completely new ways of creating images. Digital collage was one of the new methods made available to artists who could now work completely within a digital space. Contemporary artists such as Lucas Blalock, Jodie Whalen, Rachel De Joode, Marian Tubbs, and Daniel Gordon, among many others are today utilising digital software along with various digital printing methods to create collage-based artworks that either end up as prints and videos, or part of larger installations. In week 5 & week 6, we will be talking about some of the contemporary artists making digital collages today, and the various printing methods they use to create their artworks. You will also learn how to make your own digital collage using Adobe Photoshop. Artists: Lucas Blalock http://www.rodolphejanssen.com/artist/lucas-blalock/ Jodie Whalen https://www.jodiewhalen.com/ Rachel De Joode https://racheldejoode.com/work/soft-in-the-centre Marian Tubbs http://www.mariantubbs.com/photo Daniel Gordon http://www.danielgordonstudio.com/ Samuel Hodge https://samuelhodge.com/ Asger Carlsen http://www.asgercarlsen.com/ Keiichi Tanaami https://keiichitanaami.com/index.html Extra Technical Tutorial: Making a basic digital collage with Photoshop https://www.youtube.com/watch?v=nBGluN5W5I4 More detailed tutorial: https://www.youtube.com/watch?v=GxPB2R9qhPI&list=PLuDNcF6cwbUIMHpd%20%204u1fERu9rGVBoas6K&index=3 Materials you will need to complete this workshop: -Adobe Photoshop (CS6 or later) -Maximum of 5 digital photos or digital images of any kind. These can be photos you have taken (preferred) on your phone/camera or can be sourced online and uploaded onto your computer desktop. Outcome: You will make one or two digital collages using Adobe Photoshop. As this workshop is for Print-media, remember to think about what materials you would choose to print your final works onto. (paper-what size and stock?) (Perspex or Glass?) (Aluminium or canvas?) (silk or timber?) Your final work is created with the potential to be printed on A4 or larger and or on any material you like.
EEEET2424/2427- COMPUTER AND NETWORK SECURITY MINI PROJECT Aim The project is designed for you to explore one particular sub-area in computer and network security. This light research flavoured project provides you an opportunity in conducting literature review, problem identification and technical report writing. Project Group Size This is an individual project. ProjectSelection You need to pick one of the two topics listed at the end of this document. Project Assessment Maximum marks: 100 Weight in the course: 20% Length: 5~20 pages Final report: [
Assignment 4: Assessing Maintainability Overview The goal of this assignment is to review two different implementations of Kalah Links to an external site., following the code review process as discussed in class. You must submit your comments on GitHub, and complete a Canvas quiz. Resources The two implementations are in this file: . Unzip the file before you start the following actions. The archive file contains two implementations: Design Blue and Design Green (hereafter referred to as "Blue" and "Green"). For each design, there is: src — contains the Java source code for the implementation, organised the same as for the other assignments. Note that information identifying the developer of the implementation has been replaced by something like "?????????". That is the only change from the original submission. METADATA — provides measurements and results of other analysis for the implementation. This information may be useful. However, there is no need to use it, and be aware that there may be the occasional accuracy problem. Note that the files with the suffix .tsv are formatted tab-separated. Deliverables You are to review two Java implementations of Kalah, and comment on aspects of maintainability of each implementation. Your reviews are to be provided by Github Pull Request comments (see below) and reports for each implementation by providing answers to the Canvas quiz. Submission You submit by completing the quiz and ensuring your GitHub Classroom repository is up to-date. We will download your repository for marking on the due date. You provide your report by answering the questions in the Canvas ungraded surveys for the implementations. Late submissions are not permitted. Actions Note that these instructions use different design IDs than what you will be using for the assignment. Substitute the design IDs for what you have been given (design1000 for Blue and design1038 for Green) in what is below. 1. Accept the GitHub classroom Invite (above) for Assignment 4. 2. On GitHub, using the Add file drop-down, click upload files. 3. Drag and drop the design####-blue folder directly to upload to your repository. 4. After you have dragged and dropped the design####-blue folder, you should see something similar to the following on screen: 5. Under Commit changes, do the following: a. Enter a meaningful message as the commit message. A meaningful message could be "Commit Kalah design ####". b. Choose create a new branch for your commit and then create a pull request. Name the new branch "-design####-blue" (replace with your UPI/username and #### with the given design ID). c. Click Propose changes. 6. GitHub will direct you to Open a pull request. On this page, rename the pull request to "-design####-blue" (replace with your UPI/username and #### with the given design ID) and click Create pull request. 7. You should see something similar to the following in your pull request. 8. Repeat Step 2 ~ 6 for design####-green. You should upload the code on a new branch "upi-design####-green" and create a new pull request with the name "UPI-design####-green". 9. You should have 2 new branches, excluding the main branch, and 2 pull requests for this assignment. Making Comments in a Pull Request 1. Under your repository, click Pull requests. Then, select the pull request you would like to review. 2. On the pull request, click Files changed. 3. You can start adding comments on a single line of code or on multiple lines. 4. Click Start a review to add comments. You can Add review comment if you have already started the review. Any comments you made in the review will be pending until you Submit review. To submit your review, go to Finish your review on the top right hand corner. 5. Alternatively, you can Add a single comment. The comment will be posted immediately. 6. Make sure you do not have any pending comments before the due date. 7. Make sure you have answered all the questions on Canvas and made comments in the pull request for the explanation. To find the link for each comment, go to Conversation in the pull request. On the top right hand corner of each comment, choose Copy link. Similarly, you can find the link for each comment under Files changed. For more information on how to comment in a pull request on GitHub, see Starting a review. IMPORTANT NEVER commit any implementations of Kalah to the main branch. DO NOT merge your pull requests to the base branch, i.e. the main branch for this assignment. You do not need to close the pull requests. Assessment This assignment covers many of the aspects of Maintainability discussed in the course. Your answers will be assessed according to the level of understanding of these aspects they show. Report The report that you should complete is available here. Note: In these questions "type" refers to any class, interface, or enum. In evaluating the maintainability of the implementations, you may want to consider the following Change Cases (but you are of course allowed to consider other change cases you think of). You do not need to answer any questions about these change cases, but they may help guide your review of the implementations. PNM Player name. Change the names of the players: from "Player 1" to "First Player", "player 1" to "first player", "Player 2" to "Second Player", and "player 2" to "second player". CNM Choose (Player) Name. Allow the players to choose their names. The names are displayed on the left immediately above the board for Player 2, and on the right immediately below the board. NHS Number houses. At the beginning of the game, the players can choose how many houses there are. CID Command ID. Change quit command something else (e.g. "Q") PLB Player Label. Change it to something else, such as "PL1" and "PL2". NSD Number of Seeds. Allow the players to specify the initial number of seeds in the houses, up to 99. DIR Direction of sowing. Change the direction that seeds are sown from anti-clockwise to clockwise. Question 1 Evaluate implementa!on Blue's representa!on of the context schema concept of player. That is, how well does the implementa!on provide the behaviour of player as described in the requirements. Provide the link to the GitHub Pull Request comment that discusses how well this concept are represented in the implementa!on. You should only make 1 (ONE) comment and it should be a"ached to the most useful point in the code to support your answer. Question 2 Evaluate implementation Green's representa!on of the context schema concept of player. That is, how well does the implementa!on provide the behaviour of player as described in the requirements. Provide the link to the GitHub Pull Request comment that discusses how well this concept are represented in the implementa!on. You should only make 1 (ONE) comment and it should be a"ached to the most useful point in the code to support your answer. Question 3 There is at least one concept from the context schema that is missing from implementa!on Blue, that is, there is no explicit representation of that concept in the implementa!on. Provide the link to the GitHub Pull Request comment that identifies and describes one such missing concept (1 sentence should be sufficient). You should only make 1 (ONE) comment and it should be a"ached to the location where the relevant information is provided (if there is more than one such location just pick one of them). Question 4 There is at least one concept from the context schema that is missing from implementa!on Green, that is, there is no explicit representation of that concept in the implementa!on. Provide the link to the GitHub Pull Request comment that iden!fies and describes one such missing concept (1 sentence should be sufficient). You should only make 1 (ONE) comment and it should be a"ached to the loca!on where the relevant information is provided (if there is more than one such location just pick one of them). Question 5 We know we should use meaningful names, but we also know it can be difficult to find exactly the right name. Consequently there will almost always be a poor name. Provide a link to a GitHub Pull Request comment that identifies 1 (ONE) name in implementation Blue that was not the best choice and explains what the problem is with that name. The name can be for anything, including methods, fields, and variables. You should a"ach the comment to the declaration of the name. Question 6 We know we should use meaningful names, but we also know it can be difficult to find exactly the right name. Consequently there will almost always be a poor name. Provide a link to a GitHub Pull Request comment that identifies 1 (ONE) name in implementation Green that was not the best choice and explains what the problem is with that name. The name can be for anything, including methods, fields, and variables. You should comment on the declaration of the name. Question 7 Provide a link to a GitHub Pull Request comment that proposes and justifies a be"er name than the poor one you have identified in the previous question for implementation Blue You should add a new Pull Request comment to the same location as you made the comment for the previous question (that is, there should be two separate Pull Request comments for that declaration). Question 8 Provide a link to a GitHub Pull Request comment that proposes and justifies a be"er name than the poor one you have identified in the previous ques!on for implementation Green You should add a new Pull Request comment to the same location as you made the comment for the previous ques!on (that is, there should be two separate Pull Request comments for that declaration). Question 9 For implementa!on Blue, iden!fy all the places where an inheritance relationship is created, that is, where one class (or interface) extends another class (or interface) or implements an interface. You should make a GitHub Pull Request comment for each inheritance relationship a"ached to the relevant keyword (extends or implements). The comment should indicate what the parent type is and what the child type is. Provide the link to each such comment (i.e. one link per inheritance rela!onship). Question 10 For implementation Green, identify all the places where an inheritance rela!onship is created, that is, where one class (or interface) extends another class (or interface) or implements an interface. You should make a GitHub Pull Request comment for each inheritance relationship a"ached to the relevant keyword (extends or implements). The comment should indicate what the parent type is and what the child type is. Provide the link to each such comment (i.e. one link per inheritance rela!onship). Question 11 For each inheritance relationship in implementation Blue listed in the previous question for this implementation, identify all the places where the child type is used unchanged where the parent type is expected, that is, a substitution takes place. Provide a GitHub Pull Request comment at the point where the use takes place. Provide a link to each such comment (i.e. one link per inheritance use). If no substitution takes place, the comment should read "NONE". Question 12 For each inheritance rela!onship in implementa!on Green listed in the previous question for this implementa!on, identify all the places where the child type is used unchanged where the parent type is expected, that is, a substitution takes place. Provide a GitHub Pull Request comment at the point where the use takes place. Provide a link to each such comment (i.e. one link per inheritance use). If no subs!tu!on takes place, the comment should read "NONE". Question 13 Provide a link to a GitHub Pull Request comment that identifies one type where implementation Blue does not follow SRP. Your comment should explain why SRP is not followed. If there is more than one type just pick one. Question 14 Provide a link to a GitHub Pull Request comment that identifies one type where implementation Green does not follow SRP. Your comment should explain why SRP is not followed. If there is more than one type just pick one. Question 15 Provide a link to a GitHub Pull Request comment that iden!fies one location where implementation Blue does not follow LSP. Your comment should explain why LSP is not followed. If there is more than one location just pick one. Question 16 Provide a link to a GitHub Pull Request comment that iden!fies one location where implementation Green does not follow LSP. Your comment should explain why LSP is not followed. If there is more than one location just pick one. Question 17 Briefly discuss what is required to implement the DIR (change direction of sowing, see list at end of assignment description) change case for the Blue implementation. You must give examples from the implementation to justify your answer. Question 18 Indicate how confident you are in your answer for what is required to implement the DIR change case for Blue. You have high confidence if you think that you have found all the places that will need to change and you do not expect any problems making the changes you have identified. Low (do not think have found everything) Medium (think found everything but not sure stated changes will work) High (found everything and think stated changes will work) Question 19 Briefly discuss what is required to implement the DIR (change direction of sowing, see list at end of assignment description) change case for the Green implementation. You must give examples from the implementation to justify your answer. Question 20 Indicate how confident you are in your answer for what is required to implement the DIR change case for Green. You have high confidence if you think that you have found all the places that will need to change and you do not expect any problems making the changes you have identified. Low (do not think have found everything) Medium (think found everything but not sure stated changes will work) High (found everything and think stated changes will work) Question 21 Decide which of the two implementa!ons is the more maintainable, that is, of the implementa!ons Blue and Green which would you think would require the least effort on which to perform. maintenance tasks? Blue Green Question 22 Give the best single reason why you made the decision you made in the previous ques!on. You may refer to other answers you have given, but you must be as brief as possible in your answer. Your answer will be assessed on the level of understanding shown of the course material and on its brevity. Answers longer than 100 words should not be needed.
