COMM 2850/STS 2851: Communication, Environment, Science, and Health Homework #1 Assignment (Summer 2025) [50 pts total] Due Wednesday, July 9 @ 9:00 PM EST Details: You will write a 2-3 page report that responds to a particular prompt. Your report should have an introduction, conclusion, references page, and respond to the prompt in the body of the report. You will be graded on how well you have engaged with the course material and the strength of your discussion. All assignments need to be typed, double-spaced, using normal type-fonts (Times New Roman, 12 point is a good choice), 1-inch margins, and need to be submitted in either a .docx or .pdf file format. I prefer APA 7 publication and citation style, but you may use any style. guide as long as you are consistent within your assignments. You may go beyond the 3 page limit if you need. If you choose to use generative AI tools (ChatGPT, CoPilot, Claude, etc.) on the assignments, please include a brief disclaimer at the end of your assignment explaining: · How you used it (e.g. What exact prompts did you ask it?) · How it contributed to your work (e.g. Did your paraphrase what the tool gave you? Did it help you think through complex topics? Did it write an outline?) · How you validated the information provided from the AI tool Prompt: In April 2025, several Cornell graduate students founded the McClintock Letters Initiative, which encourages scientists nationwide to write opinion pieces for their hometown newspapers. To date, the initiative has had over 100 op-eds published across 35 states. The initiative has also been covered by major outlets such as The New York Times, Science, NBC News, and more. The initiative is named after Barbara McClintock, the first American women to win an unshared Nobel Prize in the sciences, who was outspoken about being a woman in the sciences. The initiative aimed to publish all letters on McClintock’s birthday, which was June 16th. Drawing on Weeks 1 and 2 of content and the materials linked above, please address the following points in your 2-3 page response: 1. Campaign Analysis: Analyze the campaign by addressing: a. What are its goals and intended outcomes? b. What assumptions might the project make about its audiences/scientists? c. What might you do differently to help improve its impact? 2. Social Science Research Methods Describe at least one social science research method (survey, experiment, observation, interviews, content analysis) that you could use to evaluate a key aspect of the initiative (e.g. effectiveness of messaging, seeing how scientists’ perceptions change after writing, etc). Be as detailed as possible in describing: a. Your research question b. What method/why this method is most appropriate for your question. Please include who/what you might be sampling. c. Any limitations or challenges with this method.
Global Business School for Health Assessment brief (Business Project Group Report 70%) 2024-25 Module code and name GBSH0008 Business Project Title of Assessment Business Project Group Report What learning outcomes will be assessed Subject-Specific Knowledge: - Demonstrate knowledge across the subject area - Be able to use different aspects of business and management for evaluating an idea and putting forward a business case Intellectual, Academic and Research Skills: - The importance of planning and preparation required to develop a business case for an idea - Learn how companies and financial institutions evaluate business cases - Finance in terms of business planning – estimating costs and benefits, calculating return on investment, and managing risks Practical and Transferable Skills: - Project management skills - Marketing research - The comprehension and use of relevant communication for application for team-based work and management - Business innovation, creativity and entrepreneurial behavior. - The importance of stakeholder engagement - Business case design and presentation Keywords Strategy, Project Management, Business Case, Budget Forecasts Description of the assessment The Business Case Project module is a vital part of the GBSH master’s level degree experience, carrying 30 credits for the entire project module. This module provides significant experience in business case development, enabling you to apply and refine the skills and knowledge gained throughout your programme. You will work as a group to identify a commercial/service/process opportunity in a product, process, service or company (“a health innovation or business idea”), outline an implementation model for this idea; and then appraise and present your findings in the context of opportunities for impact, business viability and market-based drivers. In this context, opportunities for impact refer to improvements in health outcomes, healthcare provision, efficiency (including financial and resource optimisation), or increased access. Business Project Group Report You and your group colleagues will generate a health innovation or business idea to investigate in the Business Case Project. You will work as a team to demonstrate your ability to develop a business proposal for your idea and pitch it in a persuasive manner. You will outline the business case for the development of this health innovation or business idea. The idea can stem from any part of the health ecosystem, such as hospitals, health systems, healthcare services, science, pharma, technology, data analytics, or related processes and methodologies. Then, you and your group will appraise and present your findings in the context of potential opportunities, commercial and financial viability, and market-based drivers. This can be in any area of health that you and your team might be interested in. Project proposals have the capacity to encompass a wide range of translational applications, and the project work encourages you to investigate your own enterprise capacity independently and may in some cases identify projects which have immediate developmental potential. Teams need to frame. their idea, ideally as a question and/or problem, that limits the scope to something you can meaningfully investigate in the time available. A topic that starts as a broad research investigation should rapidly be narrowed down to a suitable framing. Different topics may require unique tools, frameworks, and scenarios. The chosen area should enable meaningful analysis of the relevant health innovation or business idea. Concluding that an opportunity is not feasible is an acceptable outcome and the entire journey should be recorded as part of the project. Students should speak with their supervisors and mentors after having conducted an initial investigation into whether the data, information, and customer base are sufficiently accessible to build a Business Case around. Length: 8,000 words (exc. Executive Summary and references). Structure: The format of your submission will depend on your writing style. and how you’d like to develop the analysis of the business it is expected that most submissions cover the following/similar subheadings. Sections from the Business Model Canvas (BMC) by Alexander Osterwalder have also been highlighted below, where relevant for a section, to support you align you ideation process of your health innovation and business idea and analytical writing of your business case. 1. Executive summary (250 words - not counted) A concise summary of the business idea, including its purpose, target audience, and expected impact. This section should frame. the context/problem of focus and provide a snapshot of the key aspects of the health innovation or business idea and its business model. Questions to consider when drafting this section include: What is the health innovation or business idea? What problem does it solve, and why is it important? Who are the target stakeholders (e.g., patients, healthcare providers, regulators)? What are the key conclusions from the report? 2. Introduction and Background (1,000 words) Summary of overall project mission. This section should cover the background to the technology, health innovation, change, and marketinformation needed to understand the rest ofthe business case. Provides context for the health innovation or business idea, outlining the problem being addressed, its significance, and the broader healthcare ecosystem. This section presents material about your background knowledge needed to develop the health innovation or business idea(s). This section should also describe the students' rationale for selecting this idea. In the chosen area of interest, an investigation of an independent project emerging from a current market opportunity directly within an enterprise context should be conducted. Atthe end ofthis section, make sure that you critically evaluate the existing research, evidence base and currentthinking, which informs a particular innovative idea and opportunitiesfor entrepreneurial development. Questions to consider when drafting this section include: In your selected health area, what is the health ecosystem-level problem and why is it significant? Who are the stakeholders and what do they need? What are the specific benefits, what stakeholder problem could be solved by this idea, and what are the major barriers? Why is the problem not resolved yet? Why is a health innovation or business idea needed to be developed? BMC: Value proposition, Customer segments. 3. Technical feasibility and industry considerations (2,000 words) 3.1. Technical feasibility (from a technology, scientific or change management perspective) An early-stage idea may originate from a piece of research, a new application for an existing innovation or product, a problem in healthcare delivery, or a market opportunity that requires researching possible solutions. The potential processes, platforms and methodologies required for the development and deployment of the health innovation or business idea should be considered. Page 4 of 12 At the end of this section, make sure that you demonstrate the technological/scientific or operational (e.g. change management) soundness of the health and business idea. This should be presented as the Technical Feasibility. For change management, this could be presented as the feasibility of adoption of a health innovation or solution in healthcare contexts. In this section you should also consider, if the idea is able to be implemented and if it requires different practices in healthcare, new packaging or new delivery systems. Questions to consider when drafting this section include: What are the technological, scientific or change management foundations of the solution and are there existing studies that validate your concept? What resources and activities are critical for the development of the health innovation or business idea? What are the stages for the development of this health innovation or business idea (e.g. piloting, evaluation, clinical trials, etc.)? Are there any operational challenges that exits for implementing or scaling this idea? BMC: Key resources, Key activities, Key partners. 3.2. Market analysis and competitiveness A market can be internal or external. Internal markets refer to innovations and change that impact employees. External markets comprise a set of actual or potential customers/patients of a product, process or service. At the end of this section, make sure that you evaluate whether the idea represents a market or organisational improvement opportunity, what drives current behaviour, how this idea fit with the needs of end-user needs or organisations and their strategic fit, and any important perceptions that exist around the idea. This section should also cover the existing competitor or substitute landscape including the identification of who/what these are, and how their presence constitutes a threat for your health innovation or business idea (or an opportunity, e.g. partnering). You may want to use Michael Porter’s five force model to complete this section. Existing data, such as Market Reports (available from UCL Library) or information available online (e.g., academic journals or UCL and the British Library) may be drawn upon. Questions to consider when drafting this section include: How big or important is the market/benefit/utility of the innovation? Is this market attractive? What is the size of the market? What is the need? How many potential users? What needs exist in a community or gap in existing product/care pathways? What are the market trends, who are the competitors? Did you analyse stakeholders? Is there a market for this product or service? What are the options for entering this market, who are the competitors and substitutes, and what are the opportunities for partnering in the innovation process? What is this innovation's benefit to customers and end users, and does the cost-benefit estimate make this viable? BMC: Customer segments, Channels, Customer relationships, Value propositions, Key partners 4. Business viability (2,500 words) 4.1. Regulatory considerations, Legislation, IP Implementation of an idea may require regulatory approval and, in many cases, intellectual property protection. You should clearly identify the relevant regulatory, legal, IP and ethical frameworks relevant for your health innovation or business idea. Depending on your idea, you may want to employ a PESTEL analysis for this section. All these factors will ultimately impact the implementation of the idea, time to market and route to market. These should also be relevant to the market you have chosen. For instance, for regulations, this would mean considering FDA in the US, EMA in Europe, MHRA in the UK. At the end of this section make sure that you evaluate what the regulatory, legal, ethical and IP landscape is around the proposed idea, and the impact of these on the development and deployment of your health innovation or business idea in the chose health area. Questions to consider when drafting this section include: Are there similar innovations in the regulatory pipeline that inform. your pathway to market? What are the regulatory, legal, ethical and IP considerations for your innovation, and how will you address them? 4.2. Financial Model This section should clearly outline the financial viability of your innovation. It provides a detailed breakdown of costs, revenue streams, and financial risks, demonstrating whether the business model is sustainable and scalable. Identify the cost of risk and cost of investment as part of your decision-making process. Identify all costs associated with delivering the value propositions including development of the idea (e.g. prototyping, R&D, piloting), operations (e.g. manufacturing, distribution, customer support) and talent acquisition/organizational growth. Consider the time and costs associated with regulatory, legal or ethical approvals. Clearly articulate how you will generate revenue. Highlight factors enabling or hindering financial success. Tables or graphs and financial rations can be used to present projects, cash flows, etc. Questions to consider when drafting this section include: What are the main costs incurred in delivering the value proposition, and how are they categorized (fixed vs. variable)? How do you plan to price your innovation, and what is your pricing justification? What are your revenue projections, and how do they align with market size and customer segments? What are the key financial risks, and how will you mitigate them? BMC: Cost structure, Revenue streams, Channels. 5. Strategy to market/implementation (2,000 words) This section synthesizes insights from earlier sections to craft a cohesive plan for entering and positioning in the market. It evaluates the feasibility of implementation and identifies steps to achieve commercial success The overall feasibility analysis combines insights from previous sections, including, technical feasibility, market desirability and the business viability to develop a strategy. Considering using frameoworks like SWOT analysis, Blue Ocean Strategy or Strategy road mapping to inform. this section. At the end of this section, make sure you develop scenarios, next steps, investment needs, and timelines are some of the considerations. You and your group members should use this section to discuss additional information that would be needed, and what point in the development of the idea, to make decisions on whether to enter the market or not. This should take into account all the sections above. For instance, you should test your assumptions on whether you have a full understanding of the customer needs, the characteristics of the market and competitors, and business and financial viability. If not, then you should critically evaluate what data is needed, how you will gather it and by when, in order to make an informed analysis on whether you’ll be able to enter the market or not. Questions to consider when drafting this section include: What is the unique mission and market positioning of your idea and how does it align to the customer/stakeholder needs and market dynamics? How do you want to position your idea in the market or within an organisation? What are the short-term and long-term objectives and milestones in your implementation roadmap and how will you measure success (KPIs)? What are the tactics or change processes you want to use? Are there any partnerships or collaborations that you need to build in order to achieve your milestones? Based on this, what is the expected return and benefit realisation over the coming three years? Consider financial and non-financial benefits (e.g. improved patient outcomes, market share). You can use tables and graphs, Gantt charts, etc. BMC: All sections 6. Future work (500 words) This section explores future opportunities for growth, improvement, or iteration of the innovation. It demonstrates forward-thinking and adaptability. Briefly suggest ideas for future development of the work and/or future applications. For example, the second wave of the innovation implementation or the future expansion in your portfolio, as well are research and data needs and risk mitigation for future strategies. Questions to consider when drafting this section include: How can the solution evolve to meet future customer needs? What opportunities exist for scaling the solution to new markets or demographics? What additional research, pilots, or partnerships are needed for future development? What are the potential risks in future stages, and how will you address them?
CS 210: Data Management for Data Science Homework 2: SQL, Data Collection, and Data Storage 1 Theory Questions (20 points) 1. Describe the purpose of the following SQL commands, and write down the syntax for each command: SELECT, INSERT, UPDATE, DELETE, JOIN. 2. Describe the differences between CSV and JSON data formats. When might you choose one format over the other? 2 Experiment (30 points) 2.1 SQL Queries 2.1.1 Database Setup • Create a relational database using MySQL or PostgreSQL. Name it company db. • Create the following tables: – employees (id, first name, last name, department, salary) – departments (id, department name) • Create and insert some data by yourself. 2.1.2 Basic SQL Queries 1. Write a SQL query to retrieve all employees from the employees table. 2. Write a SQL query to insert a new employee into the employees table. 3. Write a SQL query to update the salary of an employee with a specific id. 4. Write a SQL query to delete an employee with a specific id. 2.1.3 Advanced SQL Queries 1. Write a SQL query to find the highest salary in each department. 2. Write a SQL query to list employees along with their department names using a JOIN statement. Please write down the SQL query code of each task and include all screenshots of your experiments in your submitted PDF document. 3 Submission Requirements 1. Submission Format: All files should be submitted via Canvas. Submit the report in PDF format, and attach source code files mentioned in the tasks. 2. Note: Make sure to test all your scripts thoroughly before submission.
Module Code: ITS66704 (April 2025) Module Name: Advanced Programming Bachelor of Computer Science (Hons) Bachelor of Software Engineering (Hons) LEARNING OUTCOME By the end of this assignment, students will be able to: • Apply problem solving skills to evaluate and solve specific problems in advanced object-oriented programming (MLO2). OBJECTIVES Develop a customer service desktop application using JavaFX as the frontend interface and Langchain4j for AI-powered conversational support. You can define the target customer relevant to your application, e.g. a student service system, technical support system, airline ticketing service system etc. The system should also provide real-time chat assistance with a focus on customer queries, product information, and issue resolution. For students opting for bonus credit, implement advanced RAG techniques including query transformation, multi-source retrieval, and re-ranking of results. Your lecturer will show you example implementation of RAG using Java in class. You can read more about Langchain4j here. REQUIREMENTS You are to design and develop a JavaFX-based Customer Service Desktop Application. The application can model any customer service context (e.g., technical support ticketing system, product returns, hotel reservation services, etc.). The number of modules covered will be up to your group to decide. A typical customer service application includes components that help manage customer interactions, support requests, issue tracking, and service delivery. Below is a list of common components grouped by functionality. Ideally each student should own and develop one module from the list below. Core Components Component Description User Management Allows registration, login, and role-based access (e.g., admin, customer, agent). Ticketing System Let customers submit support tickets; includes ticket creation, tracking, and status updates. Knowledge Base / FAQ Provides self-service resources for common issues or questions. Live Chat / Chatbot* Enables real-time interaction with agents or automated chatbot assistance. Bonus marks will be given for good implementation. Email Integration Allows communication through automated/manual email replies. CRM Integration Links with customer relationship management to retrieve customer history and profile. Due to time constraints, the other operational features (e.g., dashboard, search and filter tools, SLA management, escalation rules, assignment and routing), monitoring and reporting (e.g., analytics and reports, customer feedback tools, audit trail/logs) and support and security (role-based access control, data encryption and privacy, backup and recovery) are optional and need not be implemented. The project is split into two key deliverables: • Part 1 - Analysis and Design (100%) • Part 2 - Development and Implementation (100%) Part 1 - Analysis and Design (100%) Objective: You are required to analyze the application’s requirements for the proposed customer service application module, define its scope, and present a complete design document with interface mockups and architecture overview. Deliverables: • Requirement specifications • Use case diagrams and descriptions • UI wireframes or sketches • Class diagrams and object-oriented design overview • Description of event handling and data flow The marking scheme for Part 1 is as follows: Criteria Marks Assessment Details 1. Problem Definition & Objectives 10 Clear explanation of the purpose, target users, and customer service scope. 2. Requirements Specification 10 Functional and non-functional requirements well identified and categorized. 3. Use Case Diagram & Description 10 Proper UML use case diagram with at least 3–4 valid use cases and descriptions. 4. UI Wireframes/Sketches 10 Meaningful wireframes for all main screens, labelled and logically laid out. 5. Class Diagram & OOP Design 10 Class diagram with relevant entities, attributes, relationships, and methods. 6. Event Handling Plan 10 Explanation of expected events and handlers in key UI components. 7. Data Storage 10 Strategy for storing, retrieving, and validating data (e.g., use of lists, file I/O). 8. Architecture Overview 10 Clear explanation of MVC or any architectural pattern applied. 9. Tool Usage & Planning 10 Tools selected (JavaFX, Scene Builder, IDEs) and project timeline draft. 10. Documentation Quality 10 Neat, organized, and complete submission with proper headings and consistency. Deliverables A well-structured and properly formatted academic document that contains the detailed specifications for the proposed system, associated solution high-level design diagrams, and interface prototype diagrams. Ensure that your submission includes a cover page (page 1 of this document) which shows your group member names and student IDs. All submissions should be in pdf format (GroupNo_ProjectPartA.pdf). Part 1 Due Date: 22/06/2025 11:59pm submit via mytimes.taylors.edu.my submission link. Part 2 - Development and Implementation (100%) Objective: Based on your analysis, implement the full application using JavaFX, applying OOP principles, proper GUI design, and event handling mechanisms. Deliverables: • Complete source code (organized by packages) • JavaFX GUI application (must be runnable) • Test cases or user testing evidence (screenshots, logs) • Final user guide or README • Video demo (optional but recommended) The marking scheme for Part 2 is as follows: Criteria Marks Assessment Details 1. Functional Implementation 10 Key features described in Part 1 are implemented and working correctly. 2. GUI Design & Layout 10 Clean, user-friendly layout using JavaFX components and proper scene switching. 3. Event Handling 10 Buttons, inputs, and other UI elements respond correctly using JavaFX event handling. 4. Code Organization & OOP 10 Code modularity, use of classes, inheritance, and interface where applicable. 5. Data Handling 10 Proper handling of customer data (e.g., validation, storage, reading from file). 6. Input Validation & Error Handling 10 Input fields are validated, and exceptions are managed gracefully. 7. MVC or Architecture Use 10 Evidence of clear separation of concerns in the implementation. 8. Readability & Comments 10 Code is readable, uses naming conventions, and contains helpful comments. 9. Testing & Debugging 10 Test cases shown or described with evidence of debugging effort. 10. Completeness & Bonus Features 10 The app is fully functional with extra features (e.g., comprehensive chatbot, search, export, reports).
MIET1068 - Mechanical Design 2 Revision of Solid Mechanics through Worked Examples 3D Stress, Equivalent Stress and more... About This resource serves as a refresher for key concepts in the mechanics of solids, essential for successfully completing this course. It is strongly recom-mended that you have a solid understanding of these concepts, typically gained through completing prerequisite courses (Mechanics of Solids 3 and Mechanical Design 1 ). If you have not successfully completed these prerequisites, please consider dropping this course and fulfilling the requirements first, or consult with the teaching staff for guidance. For those who have met the prerequisites, this document offers a concise review, complementing the revision videos available on Canvas. It provides additional information and practical applications of concepts through simple analysis problems. The problems are organised by topic and progressively increase in complexity. Instructions To make the most of this resource, follow these steps: 1. Attempt: Solve each problem independently, without consulting the solutions. 2. Identify Gaps: Determine which concepts you struggle with or need to review. 3. Relearn: Revisit these concepts using relevant literature and attempt the problems again. 4. Check Solutions (Only after steps 1-3): Compare your solutions to the provided ones. 5. Further Revision: Note areas where your understanding can be im-proved. 6. Revise Again: Focus your studies on these areas to solidify your knowledge. 7. Optional Challenge (Advanced): Create and solve variations of the problems you found most challenging. Questions Please attempt them first without consulting the solutions. 1. A pressure vessel is designed to operate at a maximum design stress of 180 MPa. The vessel is made of a material with a yield strength of 240 MPa. Determine the factor of safety against yielding. 2. A cylindrical pressure vessel has an internal diameter of 0.5 m and a wall thickness of 10 mm. If the internal pressure is 2 MPa, determine the hoop stress and longitudinal stress in the vessel. 3. A cylindrical pressure vessel made of steel (yield strength Sy = 250 MPa) has an internal diameter of 0.8 m and a wall thickness of 15 mm. Determine the maximum allowable internal pressure using the Tresca yield criterion. 4. Repeat Question 3 using the von Mises yield criterion. 5. The state of stress at a point in a cylindrical pressure vessel is given by: σl = 10 MPa, σθ = 20 MPa, τrθ = 5 MPa. Determine the principal stresses and their orientations. 6. A thin-walled cylindrical pressure vessel has a radius of 0.2 m and a wall thickness of 5 mm. It is subjected to an internal pressure of 3 MPa and a torque of 10 kNm. Determine the principal stresses and the maximum shear stress in the vessel. 7. A cylindrical pressure vessel is subjected to combined loading: internal pressure of 4 MPa, axial load of 200 kN, and torque of 50 kNm. The vessel has a mean radius of 0.3 m and a wall thickness of 10 mm. Determine the equivalent stress using the von Mises and Tresca criteria. 8. A thick-walled cylindrical pressure vessel has an inner radius of 0.1 m and an outer radius of 0.15 m. The internal pressure is 5 MPa. Determine the radial and hoop stresses at the inner and outer surfaces of the vessel. 9. A cylindrical pressure vessel has an internal diameter of 1 m and a wall thickness of 20 mm. The internal pressure fluctuates between 2 MPa and 6 MPa. Determine the mean stress and stress amplitude. 10. A cylindrical pressure vessel made of a material with a fatigue strength of 200 MPa is subjected to fluctuating stresses as described in Question 9. Determine the fatigue life of the vessel using the Soderberg criterion. (Assume Sy = 350 MPa)
COMP6771 General Directed Weighted Graph 2 The Task In this assignment, you will write a generic directed weighted graph (GDWG) with value-semantics in C++. Both the data stored at a node and the weight stored at an edge will be parameterised types. The types may be different. For example, here is a graph with nodes storing std::string and edges weighted by int : using graph = gdwg::graph; Formally, this directed weighted graph G = (N, E) will consist of a set of nodes N and a set of unweighted/weighted edges E. Explicit assumption for N and E: copyable, comparable (i.e. you can do ==, < etc.), streamable (i.e. you can use operator graph&; 7. Effects: All existing nodes and edges are either move-assigned to, or are destroyed. 8. Postconditions: *this is equal to the value other had before this operatorʼs invocation. other.empty() is true . All iterators pointing to elements owned by *this prior to this operatorʼs invocation are invalidated. All iterators pointing to elements owned by other prior to this operatorʼs invocation remain valid, but now point to the elements owned by *this . 9. Returns: *this . graph(graph const& other); 10. Postconditions: *this == other is true . auto perator=(graph const& other) -> graph&; 11. Postconditions: *this == other is true . All iterators pointing to elements owned by *this prior to this operatorʼs invocation are invalidated. Returns: *this . 2.3 Edge Class Hierachy The edge class is an abstract BASE class that declares PURE virtual functions which must be implemented by its derived classes. You will note that ONLY the member functions listed below can be specified as public , you are free to create other private virtual functions to help with the implementation of the derived classes and the features required for gdwg::graph . NOTE: We didn't specify the keywords for functions such as const , virtual , override , or noexcept , this is intentional. You should use them where appropriate. auto print_edge() -> std::string; 1. Effects: Returns a string representation of the edge. 2. Returns: A string representation of the edge. 3. Remarks: The format of the string representation is src -> dst | W | weight if the edge is weighted, and src -> dst | U if the edge is unweighted. Note: print_edge will be used in the operator bool; 4. Effects: identify whether the edge is weighted. 5. Returns: true if the edge is weighted, and false otherwise. auto get_weight() -> std::optional; 7. Effects: Returns the weight of the edge, std::nullopt if the edge is unweighted. 8. Returns: The weight of the edge. auto get_nodes() -> std::pair; 9. Effects: Returns the source and destination nodes of the edge. 10. Returns: A pair of the source and destination nodes of the edge. As a polymorphic base class, edge should also have a public virtual destructor. 2.3.2 weighted_edge The weighted_edge class inherits from edge and represents a weighted edge in the graph. It MUST implement the edge classʼs pure virtual functions to provide appropriate funtionality for weighted edges. Additionally, the weighted_edge class should have a constructor that takes the src , dst node, and weight as parameters and initialises the corresponding private member variables. 2.3.3 unweighted_edge The unweighted_edge class inherits from edge and represents an unweighted edge in the graph. It MUST implement the edge classʼs pure virtual functions to provide appropriate functionality for unweighted edges. Similar to the weighted_edge class, the unweighted_edge class should have a constructor that takes the src node and dst node as parameters and initialises the corresponding private member variables.
CSCI336 – Interactive Computer Graphics SIM Session 3 2022 Assignment 1 Task 1 Write an OpenGL program to create a simple 2D scene with an animated Ferris wheel. The image in Figure 1 shows an example of the scene (a working program will be shown in one of the lectures). Figure 1: Ferris wheel. Ferris wheel o Construct a 2D scene like the one shown in Figure 1 (does not have to be identical). The scene should consist of the following objects: A line for the ground A triangle for the base supporting the Ferris wheel A triangle fan for the Ferris wheel spokes Several carriages (Note that your program should only contain the vertex specification of a single carriage, you can reuse this with different transformations) Note: the rendering order affects the final image. The “Painter’s Algorithm” – things drawn later will overwrite the previous content. (4 marks) o Implement basic animation using transformations. Make the Ferris wheel rotate. The carriages should rotate along with the wheel spokes. (4 marks) Allow the user to toggle animation by pressing “p” on the keyboard, and to change the direction of rotation by pressing “d”. (2 marks) As the Ferris wheel rotates, make the carriages sway (rotate a little clockwise, then counter-clockwise). Each carriage should have a different sway angle. (2 marks) Task 2 Write an OpenGL program to create a simple 3D scene of a planetary system using colour cubes to represent the “planets”. The image in Figure 2 shows an example of the scene (a working program will be shown in one of the lectures). Figure 2: Planetary system. Construct the 3D scene using perspective projection. o The scene should consist of a large “sun” in the centre and two other “planets” that orbit the sun. Note that your program should contain the vertex specification of a single colour cube. The sun and the planets are to use the same vertex specification, i.e. use transformations to alter the position, size and rotation. (2 marks) o Implement basic animation. The sun and the planets rotate about their respective centres. Each planet also orbits the sun. Each planet’s rotation and orbit angle should be different. The planetary orbits and rotation only need to be in the horizontal plane, i.e. rotation about the y-axis. (2 marks) o Display the orbit paths, i.e. the red circles in Figure 2. You only need the vertex specification of a single line loop. Use transformations to display the orbit path at different positions and sizes. (2 marks) o Implement two “moons” that rotate about their own centres and orbits the outer planet. Each moon’s rotation and orbit angle should be different. (2 marks) Screenshots In your submission, include screenshots demonstrating your working programs (for both tasks 1 and 2) and the features that were implemented. Save the screenshots using one of the common image formats, i.e. bmp/jpg/png. Instructions and Assessment Follow the instructions from your tutor. The assignment must be your own work. If asked, you must be able to explain what you did and how you did it. Marks will be deducted if you cannot correctly explain your code. The mark allocations shown above are merely a guide. Marks will be awarded based on the overall quality of your work. Marks may be deducted for other reasons, e.g., if your code is too messy or inefficient, if you cannot correctly explain your code, etc. For code that does not compile, does not work or for programs that crash, the most you can get is half the marks (i.e. 10 marks or less). It is better to comment out sections of your code that do not work and include a note for the marker.
CS 323: Numerical Analysis and Computing (Fall 2022) Problem Set 3 Deadline: Thu, Oct. 20, at 23:59 pm Please submit your solutions in a single file (e.g., pdf) to Gradescope before the deadline. After the deadline, we will subtract 15% for each day that is delayed further. You have 3 late days in total for all homework submissions. Please notify the TAs before the deadline if you plan to use the late days. You are encouraged to collaborate on homework problems in a team of size at most 3. However, You must submit homework solutions individually and clearly state your collaborators. Feel free to use calculators for calculating numbers like π 2 ,(10!), e0.1 , unless you are asked to use some particular formulas to approximate these numbers. For written problems, please explain your steps to get the answers. For all programming problems, please turn in your code along with your solutions. Problem 0. Please write down your name and Rutgers netID. Problem 1. ([S] Exercise 8.1) Suppose it takes processor time t to evaluate f(x) or f' (x) given x ∈ R. So, computing the pair (f(x), f' (x)) takes time 2t. For this problem, assume that individual arithmetic operations take negligible amounts of processor time compared to t. 1. Approximately how much time does it take to carry out n iterations of Newton’s method on f(x)? Approximately how much time does it take to carry out n iterations of the secant method on f(x)? 2. Why might the secant method be preferable in this case? Problem 2. ([S] Exercise 8.10) Suppose we have a polynomial p(x) = akx k + · · · + a1x + a0. You can assume ak ≠ 0 and k ≥ 1. 1. Suppose the derivative p'(x) has no roots in (a, b). How many roots can p(x) have in this interval? 2. (Optional, extra points) Using the result of Problem 2.1, propose a recursive algorithm for estimating all the real roots of p(x). Assume we know that the roots of p(x) are at least apart and that they are contained with an interval [a, b]. Problem 3. ([AH] Chapter 3.3 Problem 3) On most computers, the computation of √a is based on Newton’s method for finding a root of f(x) = x 2 − a. 1. Show that the iteration formula of Newton’s method is 2. Derive the error and relative error formulas: where RE stands for relative error. (Hint: use the error formula of Newton’s method for finding a root α of function f: , where cn is a number between α and xn.) 3. For x0 near √a, the last formula becomes Assume RE(x0) = 0.1, use this formula to estimate the relative error in x1, x2, x3. Problem 4. ([A]) Suppose we use the secant method to find a root α of f(x). Show that at any iteration, if xn = α, then we must have xn+1 = α. References [S] Numerical Algorithms, by Solomon [AH] Elementary Numerical Analysis, by Atkinson and Han [A] Lecture notes by Aanjaneya
Module Code: MN7029SR Module Title: Financial Decision Making Assessment Title: Assessment 2: Individual Work Assessment due date: 12 November 2024 MN7029SR Financial Decision Making Academic Year 2024/25 Assessment 2 Individual Assignment Ppt slides: 20 to 25 First Marker: Second Marker: Title of presentation: Assessment criteria Level of achievement Marks to be awarded First Marker Second Marker Calculation and explanation of WACC for the company 15 m A projected cash flow for the project 15 m Calculation of NPV and Payback Period using the WACC you have calculated 15 m Calculation of NPV and Payback Period using a 20% cost of capital 15 m A decision as to whether the project should go ahead and your justification for this decision 5 m An explanation of the benefits and limitations of the 4 main investment appraisal techniques 10 m An explanation of the different types of funding available to a company (Long term, short term, equity and debt and others), the advantages and disadvantages of each and a detailed explanation of what a bank might look at in deciding whether to make a loan to a company and the steps they might take for extra protection on the loan repayment. 15 m Your report and presentation: executive summary, professionalism, summary recording, logical flow and conclusion (structure & format and intext & references) 10 m Total 100 m Areas for Improvements From First Marker Knowledge and understanding Analysis and evaluation From Second Marker Knowledge and understanding Analysis and evaluation Agreed Marks First Marker’s marks /date Second Marker’s marks/date
COURSE DESCRIPTION This course explores the world of entrepreneurship from new ventures as engines of innovation to the choices and challenges of becoming a founder. The course will integrate practical examples and class speakers into consideration of the many decisions around starting a new venture; building product and growing operations, acquiring customers, and financing the startups’ expansion. Course Themes Entrepreneurship and Innovation as a career choice Current Best Practices in Entrepreneurship The Business Model Canvas The Value Proposition Canvas The Lean Startup Method Customer Discovery Sizing the Market Building Product and Product Market Fit (MVP’s, prototypes and the new tools of startups) Growth and Marketing Storytelling Venture Finance (Options and Standards) Exits and Outcomes Course Methods The course centers around using a personal example to explore the questions around startups and becoming a founder, through the completion of exercises – using standard tools and outputs. We’ll develop a Business Model Canvas, a Pitch Deck, a simple financial model, as well as do some research and analysis around the topics. Cases and examples will be the subject of discussions throughout. Required Materials Coursebook 24-3 Individual Readings assigned online Video: Udacity Course “How to Build a Startup” Optional but useful Books: the Lean Startup – Eric Reis ISBN: 0307887898 Talking to Humans: Success starts with understanding your customers – Giff Constable, Frank Rimalovski Testing with Humans: How to use experiments to drive faster, more informed decision making – Giff Constable, Frank Rimalovski GRADING PLAN The course grade will be based on the following components: · Class Participation (discussions and Q&A): 25% (Participations and Pitches) · Exercises (Business Model Canvas, Product Exercise, Marketing Exercise, Financial Exercise, Pitch Deck): 10% each/50% Total · Final Presentation: 25% TURNING IN CLASSWORK If not otherwise specified, all deliverables should be submitted to Brightspace with a backup of email to each of the following two addresses: [email protected] and [email protected]. You should use a return receipt (notification) flag option from your email system to allay fears of late delivery. This feature is available from the email system at home.nyu.edu. ABOUT THE PROFESSOR Jeremy Kagan is a growth and innovation consultant, and advisor to corporations, startups and digital media companies. He is the former Managing Director of the Eugene Lang Center for Entrepreneurship at Columbia Business School, where he oversaw the entrepreneurial curriculum, student programs, the Lang venture capital fund, and the Columbia Startup Lab. He co-taught the Lean Launchpad class, an intensive one-week boot camp with Steve Blank. He is also a Professor of Digital Marketing, and Faculty Director of the Digital Marketing Strategy executive education program, and teaches both graduate and executive education classes. His book “Digital Marketing: Strategy and Tactics”, the first textbook for digital marketing, was published in 2018 by the Wessex Press, and is now in its second edition, with international editions now available as well. His new book “Designing the Successful Corporate Accelerator” will be released from Wiley in 2021. Kagan previously was the founder and CEO of Pricing Engine, a digital marketing platform. that enabled small businesses to benchmark, optimize and expand their search and social advertising campaigns. He was part of the Entrepreneur’s Roundtable Accelerator’s first cohort in New York City, and remains an active alumni mentor with both the regular and global programs. Kagan is also an award-winning mentor at other accelerators around the city, and is an Entrepreneur in Residence for the Founder Institute. CLASS STANDARDS AND POLICIES VIRTUAL CLASS POLICY The guideline for the class is to have video on, microphones muted, but the expectation is that students will be actively participating in the class, both answering questions and participating in class discussions about startup related topics. Maintaining visual focus and participating in discussion is both vital to the success of the virtual format, and a sign of respect and courtesy to your fellow classmates, the professor, and guest speakers. DIVERSITY & INCLUSION This course strives to support and cultivate diversity of thought, perspectives, and experiences. The intent is to present materials and activities that will challenge your current perspectives with a goal of understanding how others might see situations differently. By participating in this course, there is the expectation that everyone commits to contributing to an inclusive learning environment for all. If you feel that an aspect of this class is not inclusive, please let me know and we can examine the situation together.
Title: Business management and volunteering through the lens of power and human agency Introduction In this article, We delve into the nuanced dynamics of power within the realms of business management and volunteer work. I scrutinize seminal texts and theories from sociology and organizational behavior. to assess how power is both asserted and contested within organizations. My analysis draws on Steven Lukes's influential "Power: A Radical Perspective," complemented by Stewart Clegg's 2012 critique regarding the omission of human agency in conventional frameworks. Moreover, I incorporate insights from the Hawthorne studies and Charlie Chaplin's 1936 film "Modern Times," enriching my understanding of interpersonal relations and technological impacts in the workplace. By situating these discussions within a theoretical group project and a volunteer initiative, 1 illustrate practical applications of these concepts. Group Assignment: Eco Tech Innovation Project Our group project involved the fictional company EcoTech, which specializes in green technologies. We were tasked with creating a project management strategy that harnesses the varied perspectives of the team to successfully introduce new products. This setup provides a fertile ground for analyzing the power dynamics outlined by Steven Lukes, as well as assessing the impact of human agency and technological integration in organizational contexts. Detailed Analysis of Power Dynamics EcoTech's innovative projects are an excellent setting for demonstrating the three-dimensional theory of power proposed by Steven Lukes in Power: A Radical Perspective. Firstly, overt power is primarily exercised by senior management, who wield authority over major project decisions, directly influencing both strategic direction and resource allocation. Secondly, hidden power is evident as senior management manipulates the flow of information and resources by setting the project agenda deciding which issues are prioritized and which are overlooked. Thirdly, latent power is manifest in the way senior management shapes the expectations and desires of team members through the promotion of company culture and values, such as innovation and sustainable development, thus subtly influencing employees' behaviors and objectives. As Foucault (1977) articulated in "The Birth of the Prison", power is not solely exerted through commands but also permeates every level of the organization, enacted through routine monitoring and regulation, a dynamic clearly observable at EcoTech. A Case Study of Human Agency In this discussion, we delve into a compelling scenario at EcoTech, where Alex, a senior project engineer, embodies the concept of human agency. Confronted with the corporate mandate for swift project development to meet aggressive market demands, Alex advocates for a methodological pivot towards sustainability and innovation. His proposal, although initially slower, is designed to yield significant long-term benefits, illustrating the strategic foresight lacking in the company's current approach. This case exemplifies how individuals can employ their specialized knowledge and persuasive abilities to challenge and potentially transform. entrenched power dynamics within corporate structures. The theoretical backing for our analysis is drawn from Anthony Giddens's concept in "The Constitution of Socigy: An Outline of the Theory of Structuration' (1984), which posits that routine activities can exert a profound influence on the redistribution of resources and the modification of organizational norms. Alex's proactive stance at EcoTech vividly demonstrates how strategic actions can instigate change, even within rigid power structures, serving as a practical application of Giddens's theory. Furthermore, Alex's initiative highlights the role of individual agency in fostering innovation and driving sustainable practices in the face of traditional, profit-driven business models. His efforts to reshape EcoTech's project development processes emphasize the potential for professional expertise and ethical conviction to align corporate objectives with broader environmental and social goals. This aligns with contemporary discussions in organizational behavior. that advocate for a balance between rapid development and sustainable outcomes. Alex's case at EcoTech not only serves as an exemplar of theoretical principles in action but also encourages a reevaluation of how businesses can integrate ethical considerations into their operational strategies. The Role of Technology In the EcoTech project, technology plays a pivotal dual role: it serves as an essential tool for achieving environmental goals while also transforming power dynamics within the organization. Implementing sophisticated project management software enhances data transparency, which empowers team members by strengthening their involvement in decision-making processes. This empowerment may lead to a more balanced distribution of power, potentially smoothing out imbalances between overt and covert power exertions within the company. Furthermore, the integration of this technology reshapes various work and communication practices, subtly influencing team member behaviors and shaping their expectations. The nuanced analysis of the EcoTech project underscores the intricate interplay of power dynamics, human agency, and technology within the organizational setting. This scenario demonstrates how these elements converge to create a complex, interactive system that impacts innovation and operational efficiency. Lukes' theoretical framework provides a solid foundation for examining these interactions, emphasizing the multidimensional aspects of power within organizational structures. Meanwhile, Clegg's critique reinforces the need to consider the unpredictability and diverse nature of individual behaviors, which are essential for driving innovation and effectuating change in contemporary work environments. By leveraging these theoretical insights, EcoTech can navigate the challenges and opportunities presented by technological integration, ensuring that power dynamics do not hinder but rather enhance the collaborative and innovative potential of its team. This approach not only aligns with modern management strategies but also sets a precedent for other organizations aiming to harmonize technology with human-centric leadership and decision-making processes. Volunteer Activities: Community Greening Project The volunteer project I'm involved with focuses on a city greening initiative, orchestrated by local volunteers and supported by various businesses. This environment offers a valuable opportunity to explore power dynamics outside traditional corporate frameworks, particularly examining how human agency manifests in volunteer-driven activities. Analysis of Power Dynamics in Community Greening Programs In community greening projects, Steven Lukes' three-dimensional power theory unveils complex, multi-level interactions and conflicts. Local governments prominently exercise overt power, granting necessary permits and funding which are essential for the projects' initiation and sustainability. Corporations wield covert power by providing sponsorships and resources, subtly steering projects to align with their own sustainability goals, thus integrating corporate social responsibility into their brand strategy. This use of corporate power also extends to latent dimensions, as companies enhance their market position by shaping public perceptions of their commitment to sustainable practices. Such actions are often designed to influence community sentiment and consumer behavior. favorably, aligning public goodwill with the company's brand image. On the grassroots level, volunteers and community organizations play a crucial role. Their direct participation, fueled by local knowledge, allows them to tailor projects to better suit specific community needs. For example, they might choose plant species that are indigenous to the local ecology or design green spaces that cater more effectively to the community's daily activities. This form. of participation not only challenges the traditional top-down power structure but also significantly influences the project's ultimate design and impact. Robert Putnam in Bowling Alone: The Collapse and Renewal of American Community' (2000), highlights the broader societal benefits of such volunteer activities. He argues that community greening projects do more than just beautify the environment; they enhance social bonds, fostering a sense of trust and mutual aid among community members which, in turn, strengthens the societal structure as a whole. By examining these dynamics through Lukes' framework, we can see how power in community greening projects operates on various levels, from the overt legal and financial interventions by local governments to the more subtle influences of corporate sponsorship and the grassroots empowerment of community volunteers. Each layer of interaction contributes to a dynamic field of power relations where different stakeholders pursue both shared and divergent goals, reshaping the landscape of community development. Critique: Human Agency in Voluntary Settings In Stewart Clegg's "Power and Organizations" (2006), the analysis of human agency in volunteer-driven initiatives provides profound insights, particularly in the context of community greening projects. Clegg illustrates how community leaders leverage their agency to strategically shift resource distribution or challenge detrimental policies from corporate or governmental bodies, which could otherwise undermine long-term communal interests. Furthermore, the engagement and input from volunteers are shown to refine project goals, shifting the focus from symbolic gestures, like token tree planting, to more substantial efforts that increase actual green spaces. Amartya Sen's "Development as Freedom" (1999) reinforces this perspective by positing that development should expand individuals freedoms and enable them to realize their aspirations. In the realm of community greening, this theoretical framework manifests through volunteers exerting their agency in project planning and execution. Their participation not only enhances personal and communal agency but also aligns with Sen's broader definition of development, emphasizing empowerment and substantive improvement over superficial achievements. These insights underscore the critical role of human agency in shaping development projects in ways that are both meaningful and directly responsive to the needs of the community. By integrating the conceptual frameworks of Clegg and Sen, it becomes evident that empowering volunteers in decision-making processes not only enriches their own sense of agency but also contributes significantly to sustainable community development. This approach fosters a more engaged community, where development is not just imposed but collaboratively envisioned and implemented. Integration of Hawthorne Studies and Modern Times The Hawthorne studies underscored the significant role of recognition and involvement in boosting productivity, a principle that is equally vital in nonprofit volunteer initiatives. Specifically, in community greening projects, recognizing each volunteer's contributions can greatly enhance participation and the overall success of the project. Moreover, the film "Modern Times" critiques the alienation that can arise from unchecked technological advancement and industrialization, paralleling concerns that modern gardening technology, while efficient, should not alienate or displace volunteers. Jane Jacobs' "The Death and Life of Great American Cities' advocates for the integral role of community residents in urban planning, a concept that aligns with the ethos behind community greening projects. These initiatives not only beautify and improve urban environments but also bolster residents' sense of ownership and belonging to their neighborhoods. This analysis highlights the interaction between power dynamics, human agency, and both technical and psychological factors in community greening efforts, illustrating a complex yet effective framework for such initiatives. Community volunteerism serves not only as an environmental improvement endeavor but also as a platform. to explore and understand the nuances of social power dynamics. This examination helps shed light on the deep-seated social and psychological forces at play in community activities, emphasizing the need for a balanced and thoughtful approach to the integration of human factors and technology in organizational practices. Conclusion Through Lukes framework of power, enriched by Clegg's critique on human agency, this article examines the intricate dynamics within a hypothetical business situation and a volunteer activity I participated in. By integrating insights from the historical Hawthorne studies and the 1936 film "Modern Times," we deepen our understanding of the interplay between power and human agency in shaping both organizational and volunteer settings. This approach not only augments our theoretical grasp but also offers actionable insights for navigating power dynamics across various organizational landscapes. Reference list Clegg, S.R. (2006). Power and Organizations. [online] SAGE Publications Ltd. Available at: https://uk.sagepub.com/en-gb/eur/power-and-organizations/book225763. Foucault, M, (1991). Discipline and punish: the Birth of the prison. S.L.: Penguin Books. Giddens, A. (1984). The constitution of society outline of the Theory of Structuration; Cambridge Malden, Ma Polity Press. Jacobs, J. (1961). The Death and Life of Great American Cities. New York: Vintage Books; Lukes, S. (2005). Power: a radical view. Basingstole: Palgrave; Putnam, R.D. (2000). Bowling alone: the Collapse and Revival of American Community. New York: Simon & Schuster. Rocthlisberger, F. and Dickson, W.J. (1939). APA PsycNer. online) psycnet apa.org. Available at: https://psycnet.apa.org/record/1940-00509-000; Sen, A. (1999). Development as Freedom. Oxford: Oxford University Press, Wikipedia Contributors (2019). Modern Times (film). [online] Wikipedia. Available at: https://en.wikipedia.org/wiki/Modern_Times_(film).
Assessment Task 1 – SAS Predictive Business Analytics DATA EXPLORATION 1. Business Problem With the increasing popularity of passive income strategies implemented to assist with long term secured savings, many banks have opportunities to launch direct marketing campaigns targeted at potential clientele, who prefer regularity in their returns, due to fixed interest rates. Generally the target customer for these campaigns is someone planning for long term returns, instead of short-term cash flow injection, as specified within a standard fixed term deposit. Unique records within the ‘BANK_DIRECT_MARKETING’ dataset explicitly documents real-world examples of these direct marketing campaigns, and is a subset of a larger dataset extracted from a Portuguese bank, over a time period of two years, from May 2008 to November 2010 (Moro et al., 2011). The total number of unique records amounts to 10,578 entries [VERIFY]. During this time, the bank documented data relating to 17 marketing campaigns, targeted at convincing potential customers to enter a term deposit contract, via in-house telemarketing (Moro et al., 2011). Using this dataset, our goal is to provide meaningful insights based on 18 input attributes such as job type, education, and marital status, mentioned in section 3.1 – data dictionary. Ultimately, upon completion of initial data exploration of attribute data, we aim to highlight key insights or trends within the data, and describe every attribute in respect to their distribution within the dataset. These steps will create the basis for further modelling and prediction steps within the data mining process; to eventually predict which customers would be more likely to agree to a term deposit, and help streamline future marketing campaigns. 2. Report Structure This report aims to present key insights and observations derived from a comprehensive examination of the selected ‘BANK_DIRECT_MARKETING’ data set (UCI Machine Learning Repository, 2012), which will be documented below. The report is segregated into three major sections: data exploration, comparative analysis, and data pre-processing. Within the data exploration section, attributes will be individually categorised, highlighting their distribution, along with key metrics. Building upon this, comparative analysis will delve deeper into the data by providing bivariate and multivariate relationship insights for certain attributes. These comparisons will provide a basis for any required pre- processing that will occur in the following section. Lastly, a summary of findings will be collated to document useful trends identified in the first three sections of the report; as well as future objectives and challenges faced during exploratory data analysis. All observations catalogued below were obtained with the use of the SAS Viya for Learners cloud platform.
1. Assignment 1（7.14） Since ethics is a study of human interactions, it's important to know that your peers have different strengths and weaknesses depending on their brain type. Understanding the basics of the 16 brain types and knowing your own personality-traits can give you insight into how others think and act (including yourself). With this understanding, you can work to better understand your classmates's dynamics along with your own strengths and weaknesses. This assignment has three parts: Read the following articles to become familiar with the 16 Myers-Briggs types and theory:16 Myers-Briggs types @ The Myers & Briggs Foundation Are Introverts or Extroverts More Productive? @ LifeHack Determine your MBTI preferences by completing an informal Myers-Briggs Type Indicator (MTBI) test. The full version of the test is typically administered by a trained professional. However, there are numerous informal versions of the test online for free. Here are two of them:Personality Typology Test from Humanetrics.com Type Explorer Test from 16Personalities.com Write a short paper (about 400 words) that discusses your brain type results. Your paper should include:One paragraph that includes where you took the test, what you thought of the test and your four-letter personality type. One paragraph that includes your personality-type strengths and how you see that applying to you. One paragraph that includes some of your personality-type weaknesses and how you see that applying to you as well as how you can work to minimize those weaknesses. http://www.myersbriggs.org/my-mbti-personality-type/mbti-basics/the-16-mbti-types.htm http://www.lifehack.org/articles/productivity/are-introverts-extroverts-more-productive.html http://www.humanmetrics.com/cgi-win/jtypes2.asp https://www.16personalities.com/free-personality-test 2. Discussion: Privacy(7.17) Analyzing the Privacy Implications of Amazon's Ring Changes in Law Enforcement Collaboration Read the article linked above, about Amazon’s Ring decision to discontinue the "Request for Assistance" feature in its Neighbors app. This case relates to the Privacy chapters in the textbook "Gift of Fire". The article provides a comprehensive view of the situation, including restrictions for many airlines. Discuss the ethics of this situation (you may refer to updated articles on this issue). How does Ring's decision balance individual privacy with the needs of public safety? Is this a step in the right direction for protecting user privacy, or does it hinder law enforcement efforts? Do you believe that such technologies contribute to a surveillance society, and if so, how should this be managed? Do you agree with Ring's decision to remove the "Request for Assistance" feature? Why or why not? Word limit: 300 words or more. Remember to cite your sources. For full points, be sure to reply to at least 2 other posts with comments of 150 words. Limit quoting from the other posts you are commenting on - use your own words. https://www.cnbc.com/2024/01/24/amazons-ring-will-stop-letting-police-request-doorbell-video-footage.html?utm_campaign=mb&utm_medium=newsletter&utm_source=morning_brew 3. Assignment 2(7.20) The right to free speech is not a carte blanche right to say anything and everything on social media without some kind of ramifications, even when protected under the first amendment. Sometimes there are ethical, civil, political or legal implications. While speaking what you believe to be your "truth" is certainly a worthy ideal in theory, is there evidence to back up the statements? What about the case of misinformation, which is rampant on social media, and has wide influence? Read the following article: https://www.cnn.com/2024/03/17/politics/supreme-court-social-media-disinformation-first-amendment-covid-election-2024/index.html about concerns related to misinformation on social media, from everything related to COVID-19, to the 2024 elections. Write a short paper (>= 500 words) where you reflect on the issues raised here: misinformation, the obligation of many platforms to flag or remove these, and finally whether such could be considered as interfering with the Freedom of Speech. As always, at least 90% of the word requirement should be met without quoting other sources. You may reference other articles or sources on the Internet as long as you properly cite them. Upload your document in Word or PDF format. 4. Assignment 3: Intellectual Property(7.24) Copyright is among the most complex categories of law in the United States. Copyright laws and standards can differ dramatically between different mediums. Music is often considered to have one of the most stringent standards for determining a copyright violation, with it being common to rule on copyright violations based on perceived similarities in relatively short melodies. In 2020, a pair of musicians and programmers, as a form. of protest, attempted to neutralize this form. of musical copyright by generating and submitting to the public domain every possible short melody. Read the following article on their efforts. Write a short paper (> 400 words) where you briefly summarize the article's main points. In addition, you should discuss the ethics and copyright considerations of procedurally generated artistic content. Consider whether such content can or should be elligible for copyright protections and whether efforts like this could prevent future artists from claiming copyright violations, legitimate or otherwise. Also consider the possibility and efficacy of similar initiatives in other mediums like visual art or literature. As always, at least 90% of the word requirement should be met without quoting other sources. Upload your document in Word or PDF format. 5. Dicussion: computer crime and security (7.27) Meta. Abandons Hacking Victims, Draining Law Enforcement Resources, Officials Say https://www.wired.com/story/meta-hacked-users-draining-resources/ 41 US state attorney generals urge Meta. to take charge to protect users from hackers and scammers. In 2023, the number of hacking incidents on social media has drastically increased, and users feel that their social media platforms, such as Facebook and Instagram, are not doing enough to protect them. What can we, as individual users, do to reduce hacking risks? Should Meta. be ethically responsible for protecting its users from hackers and phishing attacks? Who should be ethically responsible for security? Additionally, consider how law enforcement could intervene in this situation. Should the government be able to override Meta’s decision and help protect users and their privacy? Consider these questions as you provide your perspective on the article. Write a response of at least 300 words addressing these questions. Respond to at least 2 peers (min. 150 words) for full points; check the grading rubric for details. 6. Assignment #4 - Computer Crime(7.28) https://www.csis.org/programs/strategic-technologies-program/significant-cyber-incidents This site (link also provided above) lists cybercrimes that have happened in the recent weeks. Pick any one from this list, and do a deep dive: explain what the cybercrime was about, the perpetrators, whether it was a crime/hactivism/cyber warfare, the motivation behind this, the vulnerabilities this crime exposed or created, and the net cost (if known) behind this crime. You may need to refer to other websites, and please cite sources that you use. As always, at least 90% of this assignment (>= 500 words) need to be based on your own words. Submit your document as a word or pdf file. 7. Discussion: Workplace(7.30) Read the following article: https://economictimes.indiatimes.com/news/company/corporate-trends/the-new-ai-disruption-tool-devine-or-devil-for-software-engineers/articleshow/108654112.cms?from=mdr The recent unveiling of Devin, an AI tool claiming to be the world's first fully autonomous software engineer, has sparked significant debate within the tech community. While supporters welcome its potential to revolutionize software development and streamline tasks for engineers, others express concerns about its impact on traditional tech jobs. In light of Devin's reported effectiveness and capabilities, how do you envision its introduction influencing the future of software engineering? What ethical considerations should be taken into account regarding the deployment of AI tools like Devin in the workplace? How can tech companies balance innovation and efficiency with the responsibility to protect and support their workforce in the face of automation and AI-driven disruption? Post your thoughts in 300 words or more. For full points, be sure to reply to at least 2 other posts with comments of 150 words. 8. Discussion: Evaluating and controlling technology (8.2) In Chapter 7 of A Gift of Fire, the focus is on evaluating and controlling technology. In light of the chapter's content, read the article below and consider its arguments. Article: https://www.washingtonpost.com/opinions/2023/04/14/tiktok-teens-mental-health-regulation/ Craft a well-reasoned response that addresses the balance between regulation and personal responsibility while incorporating ideas about technology evaluation and control discussed in the chapter. Consider the following: Where should the line be drawn between regulation and individual choice? Are corporations sufficiently motivated to self-regulate? What practical steps can individuals take to manage their responsible use of technology? Write at least a 300-word response addressing these questions. Respond to at least 2 peers (min. 150 words) for full points; check the grading rubric for details. 9. Assignment 5 (8.4) Read the following article about leaks from the Pentagon that happened a year ago. Write a short paper (>= 500 words) that summarizes the events, and the involvement of the social media platform. Discord. Whose error caused this leak? Could it have been prevented? What have been the outcomes so far? As always, at least 90% of the word requirement should be met without quoting other sources. If you research other articles or opinions, be sure to properly cite your other Internet sources. Upload your document in Word or PDF format. · Quiz 1 (on Ch. 1 - Unwrapping the gift - due by 7/15/24) · Quiz #2 (on Ch. 2 - Privacy - due by 7/18/24) · Quiz #3 (on Ch.3 - Freedom of Speech - due by 7/22/24) · Quiz #4 (on Ch.4 - Intellectual Property - due by 7/25/24) · Quiz #5 (on Ch. 5 & 6 - Crime and Security and Work - due by 7/31/24) · Quiz #6 (on Ch. 7 & 8 - Eval. & Ctrl Tech and Errors/Risks/Failures - due by 8/6/24) · FINAL EXAM: Aug. 09, 2024 (online)
Institution Enhancing Privacy Protection in AI Systems, Such as Federated Learning and Differential Privacy Techniques ABSTRACT As AI systems deal with increasingly sensitive data, the question of their privacy arises. In this chapter, the study is going to discuss two effective models of privacy: Federated Learning and Differential Privacy. FL is the training of models across sources of decentralized data without collecting the data whereby the privacy of individual data is protected. DP guarantees that an AI model output does not expose sensitive information about any individual data point. All these models are trained on the MNIST data set. This data set contains 60,000 samples for training and 10,000 samples for testing with each being a 28×28 grayscale image. This means that in this study, FL had a quite low training loss of 0.3189 and high accuracy of 90.74%, while its validation loss and accuracy were 0.1274 and 96.70%, respectively. In contrast, the DP had relatively large training loss of 1.4815 and an accuracy of 52.07% with validation metrics of 0.8784 as the loss and 72.83% the accuracy. From the models, FL was strong with high accuracy and low loss compared with a privacy-preserving mechanism DP.In this respect, the authors suggest that although FL provides strong accuracy and data privacy, the latter can be enhanced using DP, at the expense of some degree of performance metrics. A modulated hybrid of FL and DP is, hence, capable in real-world applications of striking a balance between privacy and model performance. Optimal balancing in this respect, in view of different degrees of privacy and frequency of clients' participation, will be explored in future research for purposes of strengthening AI models' degree of effectiveness and privacy protection. Chapter One: Introduction 1.0 Introduction In recent years, AI technologies have become transformative across many sectors, offering capabilities that almost a decade ago would have seemed somewhat science-fiction-like. This is largely because AI systems leverage vast volumes of sensitive data, from health records to financial transactions. However, their relevance and scale in several domains make them prime targets for malicious actors and subjects of scrutiny within the wider regulatory landscape[7]. Securing data privacy within AI systems is central to appropriately fostering user trust and ensuring conformance with privacy regulations, such as the General Data Protection Regulation in Europe and the California Consumer Privacy Act in the United States. Traditional approaches to ensuring privacy of data, such as through encryption or access controls, appear lackluster in the face of the large influx of data within the AI systems. The conventional approaches are often found lacking in mitigating the risks that arise through data breaches and unauthorized access since the models are often trained on a large, centralized dataset. A general problem with centralized training of such models is the high risk of acute data breaches that sensitive information is exposed to[13]. These concerns represent the necessity of the development of privacy-enhancing techniques at a more advanced level, at the same time ensuring the integrity of the AI-driven system. In consequence, emerging and successful techniques, such as federated learning and differential privacy, are promising techniques to guarantee user privacy and security within AI applications. Among the most promising solutions to preserve privacy in AI systems is federated learning. Unlike centralized techniques, federated learning enables model training on mobile devices and edge servers without requiring raw data to be transferred to a central server, hence protecting individual data sources. This approach toward distributed learning is that it maximizes privacy by avoiding moving data considered sensitive to other locations. It also allows AI model training on siloed or regulated data, which may not be accomplished due to concerns about privacy [5]. This makes federated learning particularly useful in situations where data can't be centralized because it is regulated or logistically challenging, especially in sectors like healthcare or finance. Another dominant privacy-preserving technique in AI work is differential privacy. It provides robust protection against disclosure of sensitive details about any particular data point in computational results, even when auxiliary information is known. It works by adding carefully calibrated noise to the data or to the process of computation, such that it is difficult to infer anything about the data of any individual from the results. This thereby keeps the output statistically reliable while providing protection for individual data points. Differential privacy particularizes in guarding statistical queries such that if a query includes any particular individual's data, differential privacy makes responses such that nothing could be inferred differently if that particular individual's data were removed or not included in the query[16]. This statistical deniability is important in the guarantee of privacy in AI applications, whereby it prevents the big threat of membership inference attacks, in which an attacker tries to understand whether a particular individual's data is part of the dataset, and reconstruction attacks, in which an attacker attempts to recover the original data from the outputs. Together, federated learning and differential privacy represent powerful tools for enhancing privacy in AI systems. Federated learning works regarding the challenge posed by data centralization through decentralized model training, while differential privacy ensures that each data point remains private upon analysis and computation. Used collectively or independently, these are very important in constructing safe and trusted AI systems, following strict privacy regulations and protecting user data against malicious actors[22]. Despite the potential of federated learning and differential privacy, several practical issues still need to be figured out while integrating and deploying them. One of the main challenges related to federate learning is the construction of robust communication protocols and efficient aggregation mechanisms. As federated learning envisions several devices locally training models and sending updates to a central server, highly reliable and secure communication channels are imperatively necessary. Differential privacy also raises significant challenges, mainly concerning computational overhead, but it involves trade-offs between privacy and utility. Differential privacy algorithms add noise to data or computations, which can reduce the accuracy of results. Thus, there is a need to set the correct balance between these two metrics. If the noise is too high, the utility of the data diminishes; if it is too low, privacy may be compromised. This makes this tradeoff particularly challenging in the mandates of high-data-fidelity scenarios such as medical diagnostics or financial modeling[14]. Moreover, the computational overhead associated with differential privacy can potentially be substantial, since generating and applying the noise typically requires additional processing, rendering differential privacy less feasible in resource-constrained environments. To tackle these challenges, several prospective solutions are still under research. In the case of federated learning, ongoing work on secure multi-party computation, homomorphic encryption, and communication-efficient protocols aims to improve the security and decrease the pressure on communication resources. In the case of differential privacy, adaptive privacy budgeting and developing hybrid models that combine differential privacy with other means of privacy preservation are used to strike a better balance between privacy and utility.while federated learning and differential privacy hold immense promise for the augmentation of privacy in AI systems, their deployment in practice is associated with serious technical issues; solutions to these are key to unlocking the promise of fully privacy-preserving AI technologies. This research identifies the underlying principles, advantages and disadvantages, and applications of the federated learning model. Federated learning enables decentralized model training, where data remains on local devices, thus safeguarding individual privacy and avoiding raw data transfers to a central server. This approach is most beneficial in industries like healthcare and finance, where sensitivity of data and other regulatory requirements are top priorities.to federated learning, this paper will cover differential privacy, a mechanism introduced by adding controlled noise to data or computations in order to prevent the identification of individuals within a dataset. Differential privacy guarantees that nondisclosure or disclosure of whether a single data point is in the dataset should not make a significant difference, hence preserving user privacy even if some auxiliary information exists to potential attackers. Figure 1: privacy preserving network The relative comparison illustrated in the paper will contrast the strengths and weaknesses of the two methods mentioned. While federated learning does well in an environment with decentralized data, varying privacy requirements, and faces challenges from the communication overhead and data heterogeneity, differential privacy with strict mathematical privacy guarantees poses the need for the preprocessing of data, which usually requires delicate tuning to balance the privacy and utility of the data and at the cost of more computational need.this research is the first to operationalize the practical utility of federated learning and differential privacy in a fully implemented Python code base, bringing them to realistic settings. The implementation illustrates how such techniques can be leveraged for developing privacy-preserving AI systems, hence setting a practical groundwork for both developers and researchers alike. By showing the efficiency and the challenges related to the use of such privacy-enhancing techniques, it will be highly responsible for the dissemination and widespread adoption of privacy-preserving AI technologies[27]. This comprehensive study will serve again to clear the air on practical considerations and potential regarding federated learning and differential privacy, thus enabling more trust in AI systems and responsible use in sensitive applications. The insights gained from this research will be invaluable for developing AI systems that prioritize respect of user privacy while maintaining high utility and performance. 1.1 Background The growing deployment of AI applications across society has increased the attention on privacy issues. Often, AI systems require massive amounts of data to be effective. Henceforth, misuse of personal data through advanced AI algorithms can enable unauthorized access and exploitation of sensitive information. Sensitization around privacy in AI systems has spurred the development of concomitant new approaches by researchers and practitioners for handling this.One of the key privacy challenges in AI systems is the centralization of sensitive data for training models[31]. To this point, in traditional machine learning models, data from different sources are pooled in and used to train models at a centralized location. Centralization of data creates risks for both security and privacy. Firstly it acts as a honey pot for hackers, making it more data-breached and at more significant risks. When data is pooled into a single repository, it creates a target that is incredibly profitable to hackers, significantly raising the risk of breaches and unauthorized access. New privacy-preserving measures try to address these issues. Some prominent ones include federated learning and differential privacy. While federated learning decentralizes the model training process, with data residing locally on devices and only model updates shared with a central server, which doesn't risk data breaches as the raw data never leaves its original device, differential privacy only ensures that the participation of a single datum will not significantly influence the gain or loss of a decision about any individual. It does this by introducing just the right amount of noise into the data or computation. Such techniques hold much promise, but there are practical challenges in their implementation: great communication protocols and efficient aggregation mechanisms are required[22]. Differential privacy brings in some trade-offs between privacy and data utility through its parameter optimization. It is paramount for these challenges to be addressed for the full-fledged adoption and effectiveness of widespread privacy-preserving AI technologies. Aggregate data privacy is championed with decentralized model training, hence making federated learning effective. Federated learning differs from traditional centralized methods in that model training occurs on edge devices or user devices without sending raw data to the central server. Instead, it includes sharing model updates such as gradients or weights between devices and with the central server[19]. This makes sure sensitive data is kept local, considerably lowering risks of data breach or any unauthorized access. Dealing with sensitive medical data can be successfully managed by federated learning, since the data never leaves the patient's device, hence maintaining privacy and satisfying all regulations that prohibit data sharing and data transfer. In federated learning, different data sources can be incorporated, thus making models more robust and general without compromising privacy. It is in scenarios of sensitive data, where data cannot be moved because of privacy regulations.Differential privacy can give strong mathematical assurance that privacy will not be breached by an AI system. It guarantees that the output of a differentially private computation does not meaningfully change whether any individual data point is included in the input. The noise is added in a way that leakage from the computations prevents adversaries from being able to make any private inferences about any specific data point. The noise addition ensures that the privacy of individuals is protected, as the presence or absence of any single data point does not significantly alter the results. Differential privacy is particularly beneficial when means, variances, or any other forms of descriptions of the aggregated data results are shared or published because, even in the presence of auxiliary information, sensitive information remains unattainable. By doing this incorporation of differential privacy, the AI systems can get strong privacy guarantees and, at the same time, can maintain the utility of data. Together, federated learning and differential privacy thus provide powerful solutions to enhance privacy[21]. While federated learning takes care of the problem of data centralization by enabling decentralized model training, differential privacy caters to the protection of individual data points by robust mathematical guarantees. These techniques are essential for building secure, trustworthy AI systems in compliance with privacy regulations and protecting user data from malicious actors. However, both federated learning and differential privacy—the most promising avenues for enhancing AI privacy—have their own major directions of improvement to jointly solve formidable challenges in implementation and adoption. The key tools that make up federated learning include secure communication protocols, effective mechanisms of aggregation, and the ability to deal with heterogeneity of data emanating from different sources. For differential privacy, the major challenge is to optimize privacy parameters so that the trade-off between privacy and utility is minimized, with usually large computational costs. Federated learning involves robust communication protocols that guarantee secure transmission of the model updates between the devices and the central server. This entails protection against possible attacks that may intercept or tamper with the data in transit[14]. There is need for effective aggregation mechanisms able to combine model updates from different devices in a way that preserves the integrity and accuracy of the global model. The heterogeneity of data is a critical issue, given that data from different sources may largely differ in terms of features, quantity, and quality. In that regard, it is crucial to ensure that federated learning systems can handle such diversity to be broadly applicable.Differential privacy adds noise to the data or computations to protect individual data points. Such a process calls for delicate recomposing of privacy parameters to ensure noise addition is enough, yet it is sufficient to offer the necessary protection without rendering data valueless. This trade-off between privacy and utility, in general, is associated with a huge computational overhead because addition of noise and the subsequent analysis of data are resource-intensive activities. Researchers still need to discover effective algorithms and techniques that successfully strike this trade-off with an improved computational profile with little impact on the assurance of privacy and data utility The rise in importance for privacy in AI systems therefore calls for a complete understanding of how federated learning and differential privacy can be successfully implemented and optimized. The present study, therefore, estreats to cover this gap by examining the principles, advantages, limitations, and applications of federated learning and differential privacy[11]. The study will, through this examination of these techniques, emphasize their importance in the development of AI systems offering a more considerable level of privacy to the users.More than providing only a theoretical framework explanation of the privacy enhancement techniques in AI, the research will be providing practical insights through Python implementation. providing an insight into how these methods can be implemented in realistic settings, the study will push the field a step closer to the adoption and development of privacy-preserving AI technologies. The results will be of great value for researchers, developers, and practitioners seeking to implement effective privacy in AI systems while at the same time protecting user data and preserving the utility and performance of AI models. 1.2 Motivation The present research is thus motivated by the pressing need to address issues of AI privacy that are increasingly gaining prominence in our lives. With the increasing relevance of AI technologies in sectors like healthcare, finance and transportation, ensuring data security has become even more imperative. Privacy breaches not only compromise sensitive information from individuals but also erode public confidence and cause significant legal and regulatory challenges for organizations. In particular, the GDPR applies to Europe, and the CCPA applies to firms that collect personal data within the United States, establishing stringent procedures for maintaining privacy. Failure to comply and meet these strict standards has resulted in drastic penalties levied against noncomplying organizations. Organizations that fail to reach this level of privacy are subject to high penalties and may face potential damage to brand reputation when legal ramifications and fines are passed. Naturally, as the field of AI continues to become firmly established and shape several aspects that contribute to value in society—ranging from healthcare delivery to financial decision-making and even transportation systems—robust privacy measures become of utmost priority. It is for this reason that people prefer to use AI programs, where their sensitive data is stored on the condition that it will not be accessed nonsensitively or misused[26]. Thus, there must be a strong requirement for ensuring that AI systems preserve privacy and security in order to maintain public trust and confidence in technology. With all these challenges and complexities of AI privacy, in this research, we will provide insights towards the development of effective privacy-preserving techniques that will guarantee regulatory compliance with individuals' privacy rights. Therefore, we will want to propose a deep understanding of federated learning and differential privacy, substantiated with practical implementations, to propose useful insights for organizations and policymakers working to negotiate the dynamic landscape of regulation and enforcement in the area of AI privacy. Federated learning and differential privacy are some of the most promising ways to ensure effective privacy in AI systems, with a decentralized approach to model training that provides robust mathematical guarantees against sensitive data distributions' exploitation. In this respect, particular interest in these techniques is driven by the potential of changing the way AI and ML systems handle sensitive information, thus ensuring user privacy.The proposed research shall evaluate these two strategies thoroughly, respecting their importance in empowering companies and practitioners in the complex data privacy landscape[17]. More specifically, understanding the principles and practical applications of federated learning and differential privacy will allow an organization to develop and support trust and enhanced compliance in a data-driven society.In federated learning, model training is performed by decentralized devices, such as mobile phones or edge servers, without requiring the raw data to be transmitted to a central server. This will not just keep individual data sources private, but also make it possible to develop and train AI models based on siloed or regulated data that reside across them, in full compliance with regulations such as GDPR and CCPA. On the other hand, differential privacy gives strong mathematical guarantees that the output of computations remains unchanged, regardless of whether specific individual data points are included. By adding carefully calibrated noise to data or computations, differential privacy ensures that sensitive information cannot be revealed from a computation, thereby safeguarding user privacy even in the presence of auxiliary information. The work shall evaluate the techniques of federated learning and differential privacy to provide leading companies and practitioners with the tools and knowledge necessary for enhanced privacy protection in AI systems. Through the adoption of these state-of-the-art approaches, an organization can bolster trust among users and stakeholders as proof of its firm commitment to sound data-handling practices and seamless regulatory compliance. 1.3 Objectives The main objective of this research is to explore and assess the effectiveness of federated learning and differential privacy techniques in improving privacy protection in AI systems. Specifically, the research will seek to apply: 1. A critical and deep review of federated learning and differential Privacy is presented in this paper, focusing on their principles, advantages, limitations, application domains, and areas applied to solving real-world problems 2. Compare federated learning with differential Privacy from both sides based on their strengths and weaknesses to reveal the essentials of Privacy. 3. Explore the realistic applications of federated learning and differential privacy methods implemented in Python code that need to be set in context with its application to a simulation.
MODULE TITLE: Financial Analysis Management & Enterprise – FAME Assignment 1 PROGRAMME: MBA – Full Time MODULE PERIOD: JUNE – JULY 2024 ASSESSMENT TYPE: 2000 Words Assignment Report 1. Your question is in 3 parts, as follows: Choose a listed company on the London Stock Exchange (LSE) in any of the following sectors: Retailers, Food & Beverages, Health Care, Oil & Gas, Pharmaceuticals & Biotech, Telecommunications and Utilities. Obtain the annual reports of the company and one of its main competitors for the latest three years from its website or other sources. a) Using financial ratios, ccritically compare and analyse their financial performance over the last three years. b) If you were going to buy one of these companies’ shares, which one would you choose? Explain your reasons. 2. Presentation · Your reports and briefing paper should be clearly and logically structured in whatever format appears to be the most suitable for supporting the analysis, arguments, conclusions and recommendations. Locate the ratio calculations in an appendix and only present the actual ratios in the body of the report. · Key points of the comparative analysis may be summarised as a bulleted list to optimise the use of your words. · Tables, graphs and charts are a convenient way of organising your findings and presenting data. They also make it easier for the end user of your report (and the marker) to understand your findings and so you are recommended to use visual aids where appropriate. 3. Assessment Requirements: · The submission of your work assessment should be organised and clearly structured. · Maximum word length allowed is 2000 words, excluding words in Charts & Tables and in the Appendixes section of your report. · Student is required to submit a type-written document in Microsoft Word format with Times New Roman font type, size 12 and line spacing 1.5. · This assignment is worth 100% of the final assessment of the module. · Indicate any sources of information and literature review by including all the necessary citations and references adopting the Harvard Referencing System. · Students who have been found to have committed acts of Plagiarism are automatically considered to have failed the entire module. If found to have breached the regulation for the second time, you will be asked to leave the course. · Plagiarism involves taking someone else’s words, thoughts, ideas or essays from online essay banks and trying to pass them off as your own. It is a form. of cheating which is taken very seriously. 4. Marking Scheme: Word Limit Marks (%) Background on company and competitor 200 15 Use of financial ratios, to evaluate the financial performance and financial position of selected company and competitor 1600 60 Recommendation on shares to buy 200 15 Presentation, use of tables, referencing and detailed financial ratio workings in appendix 10 Total 2000 100% 5. Learning Outcomes tested in this assignment Upon successful completion of this module the student will be able to: 1. Demonstrate a critical awareness, comprehension and synthesis of a business and its future prospects. 2. Identify, organise, analyse and critically evaluate financial information, articulate conclusions and form. recommendations, based on a disciplined, thoughtful and well-structured appraisal of the evidence and founded on clear theoretical underpinnings. 3. Structure and communicate ideas based on an understanding and appreciation of the practical application of key issues and theories in corporate financial management. 4. Display an ability to evaluate complex business issues, synthesise concepts and to formulate and propose advice based on informed judgement. 5. Articulate conclusions and make recommendations, in an independent manner, which are based on informed analysis and critical appraisal. 6. Notes on Plagiarism Plagiarism is passing off the work of others as your own. This constitutes academic theft and is a serious matter that is penalized in assignment marking. Plagiarism is the submission of an item of assessment containing elements of work produced by another person(s) in such a way that it could be assumed to be the student’s own work. Examples of plagiarism are: · The verbatim copying of another person’s work without acknowledgement · The close paraphrasing of another person’s work by simply changing a few words or altering the order of presentation without acknowledgement · The unacknowledged quotation of phrases from another person’s work and/or the presentation of another person’s idea(s) as one’s own. · It also includes self-plagiarism' (which occurs where, for example, you submit work that you have presented for assessment on a previous occasion). And the submission of material from 'essay banks' (even if the authors of such material appear to be giving you permission to use it in this way) Copying or close paraphrasing with occasional acknowledgement of the source may also be deemed to be plagiarism is the absence of quotation marks implies that the phraseology is the student’s own. Plagiarised work may belong to another student or be from a published source such as a book, report, journal or material available on the internet. 7. Harvard Referencing The structure of a citation under the Harvard referencing system is the author’s surname, year of publication, and page number or range, in parentheses, as follows: · The page number or page range is omitted if the entire work is cited. The author’s surname is omitted if it appears in the text. Thus we may say: “Jones (2001) revolutionized the field of trauma surgery.” · Two or three authors are cited using “and” or “&”: (Deane, Smith, and Jones, 1991) or (Deane, Smith & Jones, 1991). More than three authors are cited using et al. (Deane et al. 1992). · An unknown date is cited as no date (Deane n.d.). A reference to a reprint is cited with the original publication date in square brackets (Marx [1867] 1967, p. 90). · If an author published two books in 2005, the year of the first (in the alphabetic order of the references) is cited and referenced as 2005a, the second as 2005b. · A citation is placed wherever appropriate in or after the sentence. If it is at the end of a sentence, it is placed before the period, but a citation for an entire block quote immediately follows the period at the end of the block since the citation is not an actual part of the quotation itself. · Complete citations are provided in alphabetical order in a section following the text, usually designated as “Works cited” or “References”. The difference between a “works cited” or “references” list and a bibliography is that a bibliography may include works not directly cited in the text. · All citations are in the same font as the main text. Examples of book references are: · Smith, J. (2005a). Dutch Citing Practices. The Hague: Holland Research Foundation. · Smith, J. (2005b). Harvard Referencing. London: Jolly Good Publishing. In giving the city of publication, an internationally well-known city (such as London, The Hague, or New York) is referenced as the city alone. If the city is not internationally well known, the country (or state and country if in the U.S.) are given. Examples of journal references are: · Smith, John Maynard. “The origin of altruism,” Nature 393, 1998, pp. 639-40. · Bowcott, Owen. “Street Protest”, The Guardian, October 18, 2005, accessed February 7, 2006.
MAST30012 Discrete Mathematics Semester 2, 2022 Assignment 3 Due 11:59pm Monday October 17 Q1: (8 marks) (a) Using only formal power series manipulations (e.g. addition, multiplication, differentiation) of the geometric series find expressions for i. A(x), the generating function for the sequence an = n3 - n for n ≥ 0, and ii. B(x), the generating function for the sequence for n ≥ 0. (b) Find an explicit expression for bn (i.e. a polynomial in n). Q2: (11 marks) Let T be the set of lattice paths which • take steps from the step set {(1, 2), (1, -1)}, and • start at the origin (0, 0), remain on or above the line y = 0, and end on the line y = 0. Let Tn be those paths in T with n steps, and let tn = |Tn|. The path with no steps is a valid path, so t0 = 1. (a) Explain why tn = 0 if n is not a multiple of 3. (b) Draw the paths in T3 and T6. (c) If T(x) is the generating function for the sequence tn, find a functional equation satisfied by T(x), and explain what each term in the functional equation means. (Hint: this equation should be cubic in T(x).) Do not try to solve the equation! (d) Remember that Dyck paths and binary trees are both counted by the Catalan numbers. The paths in Tn are also in bijection with a certain set of trees. Explain what this set of trees is. The n in Tn refers to the number of steps in a path – what is the corresponding meaning of n for the set of trees? (e) If the step set {(1, 2), (1, -1)} is replaced with {(1, k), (1, -1)} for an integer k ≥ 1, what happens to the functional equation you found in (c)? Q3: (11 marks) Starting from the word ‘keyboard’, rearrange the letters to get ‘drakeboy ’. (a) Let the permutation τ correspond to the arrangement (so the letter in position i moves to position τi). Write τ as a two-line array. (b) Let the permutation σ correspond to the map (so the letter in position i becomes the letter in position σi). Write σ as a two-line array. (c) What is the relationship between τ and σ? (d) Write τ in standard cycle format. (e) What is the parity of τ? (f) What is the smallest value of n such that τn = id (the identity permutation)? (g) Write τ as a product of transpositions. (h) Represent σ as a bipartite graph (please don’t make it too small!) (i) How is the number of inversions in σ related to the bipartite graph? How many inversions does σ have? (j) Write down the set of inversions Iσ of σ.
Experimental physics The refractive index of water Introduction In this investigation, you will be observing the apparent positions coins underwater in order to measure the refractive index of water. After this, you will be observing the refraction of light in water. The investigation is designed to give you an understanding of: Snell's law Ray tracing to explain observations Theory The following information may be useful. Figure 1 - Ray angles at a refraction boundary are measured with respect to a 'normal'. What you will need Assemble this equipment before you start the exercise: A tall transparent container (20 cm or higher). Note: a square or rectangular container such as the one shown on the right works better for part 2. A ruler A long, straight object that can withstand getting wet, such as a pen, a skewer or a straw. Two identical coils (for example, two 10c coins). Not necessary, but may be helpful: Sticky tape (to stick on the side to mark different heights) A jug (to pour the water) A permanent marker (to mark heights on the sticky tape) Part 1-Measuring nwater Procedure 1. Choose five (5) evenly spaced heights on your container (do not start at zero). You may want to mark these heights on the side of the container. If you stick sticky tape on the side of the container first, then it will not be permanently marked. 2. Fill the container to the lowest of these heights and record this in the results table. 3. Place one coin on the bottom of the container (it is underwater). Look at the container from above and move the other coin beside the container (it is in air) until the two coins looks like they are at the same height (note: they will not be at the same height, but they will look like they are, because they will appear to be the same size to you). Figure 2 - Comparing the apparent positions of two coins, one submerged underwater. 4. Record the height of the coin in air relative to the surface of the water (labelled heoin in figure). Try to estimate the uncertainty in this height by working out the range of heights over which they look like they are at the same height. As this is a matter of judgement, you may have relatively large uncertainties, and this is okay. You may be able to reduce these uncertainties by taking a photo and working out when the two coins are the same size. Include a discussion of how you calculated these uncertainties in your report. 5. Now add water to the container until the water level is at the next height. Repeat steps 3 and 4, obtaining the distance between the outside coin and the water surface when the coins look like they are at the same height. Record your measurements in the results table. 6. Repeat these steps for the three remaining heights. Results Record your results in a table like this one. Estimate the uncertainty in hwater from how precisely you think you have measured the height of the water in the container. Analysis Plot a graph with hwater on the Y-axis and hcoin on the X-axis. The gradient of the graph should be the refractive index of water. You may wish to use the Excel template Linear plot with uncertainties.xis to plot this graph (it is available onll the Moodle page), and note the equations of the line of best fit, and the two lines of worst fit. Record your value for nwater with an uncertainty. Include a discussion of how the uncertainties were calculated. Include a screenshot of this graph in your report. Part 2-Observing refraction Procedure 1. Place your straight object (the pen/skewer/straw, etc) so that is it half submerged under the water. 2. Gradually change the angle that the straight object makes with the surface of the water as shown in the diagram. 3. Photograph your object as it makes different angles with the water (say, three photos). Include a label in the frame. of each of your photographs that contains your name, zlD and the date. 4. Describe how your observations change as the angle changes. Figure 3-This diagram shows how the straight object actually is, but you will observe where it appears to be. Figure 4-This photo shows a good angle to take your photographs. The long straight object has been omitted. Questions 1. Explain, using equations and diagrams, why the gradient of the graph you plotted in part 1 is equal to the refractive index of water, nwater. For this equation, do the derivation algebraically; do not refer to the value that you have measured. 2. Compare the value that you have measured for nwater to the accepted value of nwater = 1.33. Discuss any discrepancies; make sure that you refer to the size of your uncertainty in your answer. 3. Suggest a better technique to measure nwater. This technique does not have to be limited by the equipment you have at home -you may propose any equipment that you think is necessary. 4. Use ray tracing to clearly explain why the straight object looks the way it appears to you in the water. This answer requires diagrams and words (and possibly equations). Marks will be awarded for clarity. Hint: Consider light reflected of the far, submerged end of the straight object. How does it get to your eye?
Module Information Title of module: Personal and Professional Development Module code: ULMS864 Credit value: 15 Semester in which the module is taught: Semester 1 Module Aims and Learning Outcomes This module aims to develop students’ self-awareness in relation to their values, behaviours, motivations, and development of their skills in leadership and management. It enables reflection on current and future skill and knowledge needs, and supports personal and career development planning. The module aims to develop students as reflective management practitioners within their own context. Specific skills development activities are supported through an action learning that encourages students to examine real management problems or issues using their own experiences and case study material. The module focuses on the skills and knowledge required by effective leaders and managers in contemporary organisations. Over the course of the module: -Students will learn about the work undertaken by managers in the context of a range of organisational settings; -The nature of the management role will be problematized through a series of cases and scenarios that will encourage learners to explore the nature of professionalism and ethics in management; -The module also aims to develop students as managers who engage in scholarly, reflective practice both during their time on the programme and in their future careers. Learning Outcomes 1. Students will be able to recognise and reflect upon their own values, perspectives, motivations and behaviours and those of others in a global context, and the impact these can have within groups and organisations. 2. Students will be able to explain how values and ethics impact on professional practice. 3. Students will be able to explain and interpret the types of professional and ethical dilemmas managers may encounter and have to deal with. 4. Students will be able to use and apply theory appropriately to explain the nature of these situations and why they occur and propose how managers’ workplace behaviour may be consciously adapted to recognise and resolve them. 5. Students will be able to identify their own needs for development of the management and leadership skills both relevant to the students' own context and to the wider field of management in a globalised world. 6. Students will be able to demonstrate a high level of self-awareness by generating, analysing and reflecting on feedback from a range of sources in relation to personal/interpersonal/leadership and management skills 7. Students will be able to recognise the need for managers' continuous learning and development, and to acquire skills and techniques to improve practice. How will this module develop my ULMS Graduate skills? This module helps students to develop the skills set out in the module specification. Details of how the stated skills will be tested are shown in the module specification. In addition, the Management School has identified a set of key skills which it expects its students to develop throughout their studies. These are skills actively sought by employers and which together form. the “ULMS Graduate” (see appendix A at the end of this module guide). Teaching and Learning Strategies This module includes live lectures (10 hours). You will find these activities scheduled on your timetable as ‘ON CAMPUS LECTURES’ . The lecture introduces you to the week’s topic, including academic and practitioner discussions around the issue. In addition, we will have seminar groups (10 hours). You will find these activities scheduled on your timetable as ‘ON CAMPUS SEMINARS’ . You will be given tasks/activities each week, so you must come to seminars prepared to discuss your ideas and review those of others. Students are expected to participate actively in sessions. Both lectures and seminars are held in person, please refer to your timetable for details. Many of the learning materials will be posted on CANVAS each week, and the seminar, in small groups, will provide an opportunity to apply your learning and develop techniques that will help you in your assessment. New materials and discussion questions might be posted on CANVAS, according to current affairs and issues during the module. Students will be expected to undertake background and follow-up reading and to access materials via the web and CANVAS. Your non-contact study hours should total around 120 hours for this module. Most communication and support for learning will be posted on CANVAS. You should, therefore, access CANVAS regularly. The university supports your learning via the Study Skills web page. Your Student Handbook (and Study Skills Booklet) also provides advice on the skills required for your assessments (e.g., ULMS Academic Masterclasses and/or KnowHow sessions). Assessment Strategy - How will this module be assessed? Summary Assessment 1: Reflective learning log, 1500 words (30%) Submission deadlines and date of return of work to students: December 9th, 12pm (midday). Assessment 2: Individual essay, 2000 words (70%) Submission deadlines and date of return of work to students: January 10th, 12pm (midday). How to submit your work: Online submission only. See detailed instructions below. By submitting your work, you are acknowledging that you understand theUniversity’s Academic Integrity Policy, that you have not plagiarised, colluded, or bought your work, and that you have not copied work extensively from previous assessments you have submitted. Weighting of the assessment components: Assessment 1: Reflective learning log = 30% Assessment 2: Individual essay = 70%
