EECS 678 – Fall 2019 1 Chapter 6 1. What is a critical section? What are the three conditions to be ensured by any solution to the critical section problem? 2. The following code only ensures two of the three conditions for solving the critical section problem. What condition does it not support? Modify the code to provide support for all three conditions to address the critical section problem. int mutex = 0; do { while(TestAndSet(&mutex)); // Critical section mutex = 0; // Remainder section }while (TRUE); 3. Provide the pseudo code definitions of the following hardware atomic instructions: (a) TestAndSet and (b) Swap. 4. A general synchronization solution using locks looks as follows: int mutex; init_lock(&mutex); do { lock(&mutex); // critical section unlock(&mutex); // remainder section }while(TRUE); Provide the definitions of init lock, lock, and unlock when using (a) TestAndSet, (b) Swap and (c) Semaphores. 5. Define semaphores (simple semaphores and semaphores with no busy waiting). 6. What is priority inversion? How does the priority inheritance protocol address this issue? 7. Explain why spinlocks are not appropriate for uniprocessor systems, yet may be suitable for multiprocessor systems. 8. Show that if the wait and signal semaphore operations are not executed atomically, then mutual exclusion may be violated. 9. List the drawbacks of Semaphores. How can Monitors overcome the drawbacks? 10. How do monitors ensure mutual exclusion? 11. The code on Slide 53 shows a solution to the bounded bufer problem using monitors and condition variables. Using illustrative figures (as demonstrated in class) show how the fol- lowing sequence of process events will be handled with (a) Hoare and (b) Mesa condition variable semantics. Events: C1 P1 C2 Here, Pn indicates ‘producer’ and Cn indicates a ‘consumer’ process. 12. How do the semantics of the wait() and signal operations difer in semaphores and monitors? 2 Chapter 5 1. (a) is the amount of time to execute a particular process (submission time to completion time). (b) is the amount of time a process is waiting in the ready queue. (c) modeling uses a pre-determined workload and defines the performance of each algo- rithm for that workload. 2. Describe the diference between preemptive and non-preemptive scheduling. State why strict non-preemptive scheduling is unlikely to be used on machines supporting programs that provide interactive user services. 3. The processes listed below( P1, P2, P3, P4, and P5) are assume to all arrive at time 0. Perform. the following analysis addressing how diferent scheduling algorithms would execute these processes, and how each would perform. as measured by diferent metrics. • (a) Draw 4 Gantt charts illustrating the execution of these processes using FCFS, SJF, non-preemptive priority (a smaller priority number implies a higher priority), and RR (quantum=1) scheduling P2P3 P53724112243NameBurstTimePriorityP1 P3 P5155119828517SegmentBaseLength01234219230090132719526001410058096PagePageFrame0123456789-2 A 0
MATH 2568 PROBLEM SET 3 Due February 2, 2025 Problem 1 (Complete the proof of Theorem 3 in the notes). Let A be an m × n matrix, C and D be n × p matrices, and ~v and w~ be n-vectors. As indicated in the notes, (a) Use the identity (r+s)A = rA+sA for any scalars r and s to show that A(+) = A+A (b) Use (a) to show that A(C + D) = AC + AD. Problem 2. Express the vector in the 2-dimensional plane R2 as the sum of a vector which lies on the line y = 3x and a vector on the line y = x/2. Problem 3. Let A be an n ⇥ n matrix and ~v be the n-vector Suppose there exists a constant k such that the sum of the entries of any given column of A is k. Show that AT = k. Problem 4. We’ve seen that matrix multiplication does not generally commute. However, it can happen that AB = BA for particular matrices A and B. Find all matrices that commute with the matrix Problem 5. (a) Find all 3 ⇥ 3 matrices A such that (b) Find all vectors ~v such that
CSCI 4041 Algorithms and Data Structures - Spring 2025 Homework 2 - Correctness and Sorting Due Date: Friday, February 21, 2025 by 11:59pm. Instructions: This is an individual homework assignment. You may work together to discuss con- cepts, but the solutions must be your own work. Submit your answers on Canvas, which is linked to Gradescope (be sure to correctly map the page for each problem). We will not grade *Practice Problems*, however, you are responsible for knowing how to solve them in order to prepare for quizzes and exams. This homework is divided into two parts. Part A focuses on written problems involving correctness. Part B involves programming solutions to real world sorting problems. Part A - Correctness (Written Problems) Problem H2.1: Proving Correctness Consider the MERGE( . . .) function in Section 2.3, p. 31 of the textbook, which takes two sorted arrays and merges them into one sorted array. The python function below, merge3(A,B,C), takes three sorted arrays, A,B, and C , and merges the values from each into a single sorted array, D. Let n = ∣A∣ + ∣B∣ + ∣C∣ . merge3(A, B, C): D = [] ... ... return D Answer the following questions: (a) Write the algorithm for merge3(A,B,C). You may write the algorithm using python, pseu- docode, or another language. Regardless of which of these you use, you may assume there is an append function to add an element to the end of D. (b) Analyze the runtime for your algorithm. (c) Describe a loop invariant or loop invariants that will help you prove correctness of merge3(A,B,C). (d) Prove that your algorithm is correct by showing that your loop invariant(s) remains true during initialization, maintenance, and termination. (e) Create a merge sort3( . . .) algorithm that uses merge3(A,B,C) to recursively sort the solu- tions of three sub problems. (*Practice Problem*) (f) Use the Master Theorem to analyze the runtime of merge sort3( . . .). (*Practice Problem*) (g) Which algorithm has a slower growing asymptotic runtime, MERGE-SORT( . . .) in Section 2.3, p. 34 of the textbook or merge sort3( . . .)? (*Practice Problem*) Problem H2.2: Loop Invariants Describe specific loop invariant(s) for proving correctness for each of the following algorithms. You do not have to prove that the algorithms are correct. Remember if there are multiple loops, you need an separate invariant for each loop: (a) (*Practice Problem*) find_min(A) min = A[1] for i = 1 to A . length if min > A[i] min = A[i] return min (b) (*Practice Problem*) all_less_than_test_value(A, testVal) allLess = True for j = 1 to A . length if A[j] >= testVal allLess = False return allLess (c) divisible_by(A, k) D = [] for i = 1 to A .length if A[i] % k == 0 D.append(A[i]) return D (d) scaled_sum(A) sum = 0 for i = 1 to A .length sum = sum + A[i]*i return sum (e) euclidean_norm(Matrix, n) sum = 0 for i = 1 to n for j = 1 to n sum = sum + Matrix[i, j]*Matrix[i, j] return sqrt(sum) Problem H2.3: Recursion Invariants For each algorithm below and recursion invariant, use induction to prove the invariant is true for the algorithm (initialization, maintenance, termination). (a) Recursion Invariant: power(a,n) calculates an−1 for any a ∈ R and for all n ∈ Z, n ≥ 1: power(a, n) if (n == 1): return 1 if (n % 2) == 0 // n is even x = power(a, n / 2) return a * x * x else // n is odd x = power(a, (n + 1) / 2) return x * x (b) (*Practice Problem*) textbfRecursion Invariant: deep sum(A) sums all the numbers in an array, including num- bers that are recursively stored in sublists. For example, deep sum([[1,2],3,[4,5,[6]]]) = 1 + 2 + 3 + 4 + 5 + 6. deep_sum(A) if A is Number return A if A . length == 0 return 0 return deep _sum(A[1]) + deep _sum(A[2:A . length]) (c) (*Practice Problem*) Recursion Invariant: reverse(A) reverses the elements in array A. def reverse(A): n = len(A) if n
Assignment Remit Programme Title BSc Accounting and Finance Module Title Financial Reporting Module Code 07 33175 Assignment Title Individual report Level LI Weighting 50% Hand Out Date 20/01/2025 Due Date & Time 27/02/2025 Before 12pm (12-noon) Feedback Post Date 16th working day after the deadline date Assignment Format Report Assignment Length 1,500 words Submission Format Online Individual Module Learning Outcomes: This assignment is designed to assess the following module learning outcomes. Your submission will be marked using the Grading Criteria given in the section below. LO 1. Explain and critically evaluate accounting for tangible and intangible assets, inventories, tax, provisions, or the reporting of financial performance. LO 2. Explain the information in published financial reports. Assignment: Prepare a report discussing the non-current assets of a FTSE250 company which: • discusses the requirements of applicable non-current asset International Financial Reporting Standards (IFRS) and explains how the accounting standards have been applied by the company (with reference to both the requirements of IFRS and the accounting policies of the company), and • analyses the non-current assets of the business, including (but not limited to) a discussion of the changes to non-current assets when compared to the prior year’s results. Notes on the task: • You have been allocated a company for this assignment. You can find your allocated company on Canvas. • Even though several students will be allocated to the same company this is not a group assignment. Your submission should be your own individual work. • Discussing the assignment with peers constitutes collusion, a form of academic misconduct, as the ideas generated are not solely your own but derived from group input, even if you write the work independently afterward. The University defines collusion as "collaborating with other students on work that is presented as your own individual work. This can include working together on essays." More information can be found at this link. You should not discuss your work for this assignment with anyone else. • You will find the company Annual Report on the investor relations section of the company website or by searching the company register on the Companies House website which can be found at this link. To find your company on the Companies House website, please enter your company name in the search box and select the ‘Filing History’ tab to view and download the Annual Report. • Please use the latest full year annual report. You can ignore the half year (or interim) report. • Your report should focus on the consolidated group financial statements. • Your report should only discuss the non-current assets and accounting standards covered within this module that apply to your company (i.e., Goodwill from IFRS 3 Business Combinations, IAS 16 Property Plant and Equipment, IAS 40 Investment Properties, IAS 38 Intangible Assets, IAS 23 Borrowing Costs, IAS 36 Impairment, and IAS 20 Government Grants – capital grants only). Please ignore any other non- current assets held by a company that have not been covered on this module. • You should use data from all relevant areas of the Annual Report, which may include the accounting policies, statement of profit or loss, statement of financial position, statement of cash flows and the notes to the financial statements. • Please include relevant extracts from your company’s financial statements in the appendix. • You should include all workings for your analysis in an appendix. • Please ensure that the structure follows that of a report format with clear headings. Remember reports are formal documents which can include headings, sub-headings, numbered sections, and graphics such as tables, flowcharts, diagrams, or graphs (where appropriate). All these devices help the reader navigate the report and understand its content. However, please ensure that any tables, financial statement extracts and/or graphics are referred to in the main body of the report. • The word limit is a maximum of 1,500 words. Reports that exceed this will be penalised with the following grade point deductions: o Up to 10% over: no penalty o 11% to 20% over: 5% penalty o 21% to 30% over: 10% penalty o More than 30% over: 15% penalty Tables, figures,the reference list, and the appendix do not count towards the word count. • The use of external sources must be appropriately cited and referenced. You are required to use the Harvard referencing style. • If you have any questions related to the assignment, please use the discussion forum on Canvas or speak to the module leader in class. • The deadline for assignment queries is 12-noon on Monday 24th February. The team will not be responding to any queries received after this date. This ensures compliance with the university guidelines, which allow up to two working days to respond to queries before the marking deadline, providing adequate time for thorough responses. • We recommend that you read the discussion forum prior to submitting your work to ensure you have read all the relevant information relating to this assignment. Grading Criteria: Your submission will be graded according to the following criteria: Item Criteria Weighting 1 Discussion of the application of all relevant accounting standards and the company's accounting policies. 30 2 Analysis of non-current assets: choice of analysis methods 30 3 Analysis of non-current assets: calculations 15 4 Analysis of non-current assets: discussion 10 5 Use of relevant information from the Annual Report 5 6 Creativity and communication style 10 Total 100% See the marking rubric at the end of the remit for more information on how your work will be marked and graded.
Computer Aided Engineering (MEC524) Assignment: 3D Modelling & Downstream Applications You are required to model an assembly using Solid Edge software. The suitability of the assembly selected must be ratified by the tutor before you commence modelling. You should aim to demonstrate good modelling practice as you utilise a range of modelling techniques. In addition, you should make evident the value of 3D CAD modelling by using a broad range of the functionality of the Solid Edge software, including downstream applications of the model as identified below. Please note that model complxity has little to no bearing on marks if you are not confident with CAD/CAE consider choosing a simple product to model. 1 Modelling & Downstream Applications 70 A Part Modelling 5 B Designing in the Assembly Context 10 C Assembly Modelling 10 D Animation of Assemblies 10 E Drafting 10 F Rendering 10 G Rapid Prototyping 10 H Product Data Exchange, Standard Parts & Collaboration 5 Optional Components *Choose One* 20 X Sheet Metal Environment 20 Y Surface Modelling 20 Z Finite Element Analysis 20 2 Report 50 [A – Z] Concise, suitably illustrated discussion of your part modelling approach and each downstream application. For each downstream application the value of the approach should be shown and suitably illustrated with properly referenced examples from the technical press. All discussion/screenshots/images/videos should be clearly cross-referenced to the relevant files in your archive. See detailed guidance for each section below, marking scheme is available on MEC502 BlackBoard Learn. 40 Structure, Conciseness, Clarity, Readability, Presentation 10 Total 140 Submission Your report should be submitted asan A4 document (11 pt. using an appropriate Serif font (e.g., Times New Roman), 20 pages not inlcuding title/contents/references) to the Turnitin submission point on Blackboard. It should be properly structured with a title page, contents page, introduction and pages numbered and sections A - Z clearly identified as outlined above. Please include high quality images throughout and make the report engaging. An archive (.zip) containing a copy of relevant files should be uploaded to BlackBoard Learn as per supplied instructions. The archive, at root level, should contain one folder with the name B00123456, where B00123456 represents YOUR student ID. Within this main folder you should use an appropriate folder structure so that all files are in a logical place and easily navigable for review by the tutor. Clear referencing must be provided within the report to files, their location, how they should be opened and used. It is imperative that you make sure that assembly files etc. open correctly with all necessary part files available in the correct folders in your file structure. Section Breakdown The following details the specific tools you may wish to demonstrate and discuss the use of on a per-section basis. This list is by no means exhaustive and as such you may wish to include any additional details you deem relevant. A Part Modelling Demonstrate the use of modelling techniques, don’t explain how the tool works, explain why you used these tools for the part you modelled, 2 examples are appropriate. Challenging approaches preferred, using advanced tools such as Sweep, Loft, Helix, Web, Vent, etc. B Designing in the Assembly Context Explore and discuss the use of tools to design with respect to the assembly context, show how certain features are linked and explain why it is appropriate to link these features with respect to design for manufacture. Variable Tables, Project to Sketch, Inter-part Copies, Creating Parts In-Place, Assembly Sketches, Assembly Features, Assembly-Driven Part Features C Assembly Modelling Create fully defined assemblies, make use of advanced tools within assembly environment to assist in design process. Relationships, Bill of Materials, Sections, Exploded Views, Physical Properties, Interference Checking, Analysing Motion, Detecting Collisions D Animation of Assemblies Create unique and interesting animations to demonstrate modelled prodcut or assembly of product, utilise the various tools available to make created videos high quality. Camera Paths, Motors, Explosions E Drafting Create high quality and informative engineering drawings of assembly model and key parts. Discuss the implementation of advanced engineering drawing tools and commands. Dimensions, Tolerances, Section Views, Detail Views, Parts List, Hole Table, Bend Table, Title Block F Rendering Create a variety of high quality photorealisitic renders of product and assemblies. Demonstrate use of various rendering features in the creation of high quality images and videos. Materials, Cameras, Scenes, Custom Backgrounds, Animation G Rapid Prototyping Choose at least one part to modify/improve, discuss exporting of file for printing software and how tooptimise file for printing. Include details of selected protoptying technique, including software and settings used. H Product Data Exchange, Standard Parts & Collaboration Explore and discuss the use of standardised part files from reputible sources (i.e. purchase of bolts and screws from website inlcuding download and use of percise part files). Export part(s) in compatible file formats (STEP/IGES) and import externally sourced part for use in assembly. Demonstrate sensible naming conventions, file organisation and file exports. Optional Components *Choose One* X Sheet Metal Environment Explore the creation of apart file created in the sheet metal environment, discuss the benefits of creating part files this way and why you used certain commands to create the file. Tab, Flange, Dimple, Corner, Break, Hole for producing brackets, enclosures, etc. Y Surface Modelling Explore and implement core surface modelling tools and techniques to create part file with unqiue surfacing shape. Including generation of a split surface and modelling of two parts of a mould tool. Project, BlueSurf, Bounded, Sweep, Extrude, Trim, Stitch, Split, Keypoint. Z Finite Element Analysis Explore and dicuss the creation of a simple Finite Element Analysis study, calculate appropriate force to apply, apply appropriate boundary conditions and analyse results. Including boundary conditions, material/structural modification, and analysis of results. Guidance The following guidelines are offered to help you with your assignment. 1. The report should NOT be written in the first person (“I” should not appear). For example, you should not say, “I created the feature by using the Extrude command.” It should be written in the passive; e.g. “The Loft function enables the user to …” . 2. The key to writing a concise and clear report is to use plenty of carefully selected illustrations of sketches, intermediate stages, etc. Illustrate your description throughout with appropriate screenshots and keep your descriptions brief. When describing your modelling approach, bullet points are particularly appropriate. Screenshots can be captured easily using the Snipping Tool. 3. In Sections A – Z,a description of how you have achieved the result is NOT required. However, you should concisely explain what you have done and most importantly show the value of these downstream applications, as well as how they would be used in an industrial product design environment. Examples from the technical press, properly referenced, should be included. You should demonstrate a thoughtful, critical evaluation of the downstream applications. A non- exhaustive list of the sort of things you should include can be found in the Section Breakdown. 4. The file structure in your ZIP file should correspond to the sections in Part 1 Modelling and Downstream Applications and conform to the arrangement shown below, using the folder names specified. Please ensure Design Manager is used to move/rename files and folders to avoid breaking associative links. If you feel you need to place some files differently, you must be very careful to clearly state where they are. The B00123456 folder (where B00123456 represents YOUR student number) should be the top-level folder in the ZIP file.
Biological Psychology l Definition: ¡ Study of the biological basis of behavior. and cognition, also known as behavioral neuroscience, biopsychology, or psychobiology. ¡ Integrates principles of biology to understand physiological, genetic, and developmental mechanisms of behavior. and cognition in humans and animals. l Behavior: Observable actions performed by humans or animals. l Cognition: Mental processes, including thought, memory, perception, and decision-making. l Key Insights: ¡ Brain Plasticity: The brain’s ability to change structurally and functionally to adapt to new experiences or recover from damage. ¡ Evolutionary Perspective: Expansion of the prefrontal cortex (PFC) in humans enhanced intellectual abilities and distinguishes humans from other species. ¡ Neuroscience and Mental Health: n Mental disorders and neurological diseases are profoundly impactful. n Neuroscience provides a better understanding of these conditions, potentially reducing stigma. The Scientific Method in Biological Psychology 1. Observation: Identify phenomena based on empirical evidence. 2. Hypothesis Formation: a. Use inductive reasoning to propose testable explanations. b. Example: Behavioral changes might correlate with neural activity. 3. Experimentation: a. Design experiments to evaluate hypotheses systematically. b. Use control groups to isolate variables and test effects reliably. 4. Interpretation: a. Deductive reasoning to analyze results. b. Apply skepticism to ensure conclusions are robust and unbiased. 5. Falsifiability: a. Introduced by Karl Popper (1934). b. A hypothesis must be testable and disprovable to be considered scientific. c. Non-falsifiable claims (e.g., phrenology) are not scientific. Experimental Approaches in Neuroscience l Main Question: How does the brain produce behavior. and cognition? l Methodology: ¡ Measure biological processes (e.g., neuron activity) and behavioral responses simultaneously. ¡ Use advanced tools (e.g., Neuropixels probes) to observe single-neuron activity during cognitive tasks. ¡ Example Studies: n Speech processing in the superior temporal gyrus (auditory cortex). n Word planning in the prefrontal cortex during speech tasks. l Control Groups: ¡ Essential for determining the effects of interventions. ¡ Help compare experimental conditions against baseline. l Validity: ¡ Control Validity: Ensures reliability under controlled conditions. ¡ Ecological Validity: Reflects the natural, real-world context of behaviors. Analysis of Experimental Data l Statistical Testing: ¡ Classic null-hypothesis significance testing assesses whether observed differences are due to chance. ¡ Bayes Factor: Provides a likelihood estimate comparing two competing hypotheses. l Importance of Robust Analysis: ¡ Reduces errors. ¡ Enhances reproducibility of findings. Neuroscience Applications l Technological Advances: ¡ Tools like Neuropixels enhance understanding of neural activity in specific brain regions. l Social-Reward Learning in Mice: ¡ Study: Mice given psychedelic drugs exhibited increased preference for ‘social’ environments, demonstrating enhanced social-reward learning. l Potential Benefits: ¡ Novel methods may help treat mental and neurological disorders. ¡ Brain interventions could improve overall human cognition and behavior. Open Science and Modern Research l Open Science Movement: ¡ Aims to make scientific research transparent, reproducible, and accessible. ¡ Encourages sharing raw data, methodologies, and analyses. l Human Factors in Science: ¡ Although the scientific method is robust, human errors or biases can affect outcomes. ¡ Emphasizing open science minimizes these risks and fosters collaboration. Detailed Exam Notes: Lecture 2 - Basic Ideas in Modern Neuroscience Main Assumption of Neuroscience l Thebrainproduces all mental phenomena and behavior. This foundational idea drives the field of neuroscience and stems from centuries of scientific discoveries. Historical Development of Neuroscience 1. Ancient Beliefs: a. Early civilizations (e.g., Egyptians, Greeks) believed theheartwas the source of intellect and mental life. 2. Galen’s Contribution: a. Romans thought the soul resided in the chest because the voice originates there. b. Galen demonstrated that cutting the laryngeal nerve silences animals, proving that intellect and control originate in thebrain, where the nerve is connected. 3. René Descartes (Reflex Concept): a. Proposed thatreflexesexplain some behaviors as physical phenomena, laying the groundwork for understanding involuntary actions. 4. Luigi Galvani: a. Discoveredanimal electricity, showing that electrical signals could make frog muscles twitch, linking electricity to nervous system function. 5. Santiago Ramón y Cajal: a. With the advent of microscopy, Cajal showed that thenervous systemis made up of discrete cells (neurons), refuting earlier beliefs in a continuous network. 6. Sir Charles Scott Sherrington: a. Expanded the reflex concept to explain that even complex movements can arise from interconnected reflex circuits. 7. Wilder Penfield: a. Stimulated the brains of conscious epilepsy patients during surgery and elicited specificconscious experiences, proving certain brain regions correspond to distinct mental phenomena. Behavioral Neuroscience l Definition: The study of the biological basis of behavior. l Importance: ¡ Relevance: n Brain dysfunction (e.g., mental disorders, neurological diseases) is a major problem for humanity. n Understanding the brain can improve treatment and outcomes. ¡ Mystery: n The human brain is the most complex system known to exist, and we are far from fully understanding its mechanisms. Current Directions and Innovations in Neuroscience 1. Focused Ultrasound Stimulation: a. Emerging non-invasive technology for influencing brain function, with potential applications in therapy and neuroscience research. 2. Psychedelic Research: a. Renewed interest in using mind-altering substances (e.g., psilocybin, LSD) to treat conditions such as depression, PTSD, and anxiety. 3. Neuromarketing: a. The application of neuroscience to marketing strategies, such as understanding consumer preferences. b. Targeted Dream Incubation: A cutting-edge technique designed to introduce advertisements into people's dreams. 4. Brain-Machine Interfaces (BMI): a. Innovations like Elon Musk's Neuralink aim to create devices capable of direct communication with the brain, potentially revolutionizing how humans interact with technology. Key Figures and Discoveries Scientist Contribution Galen Brain as the source of mental phenomena; disproved the heart as the control center. Descartes Proposed reflexes as physical explanations for some behaviors. Galvani Discovered the role of electricity in nerve and muscle function. Cajal Demonstrated that the nervous system is composed of individual cells (neurons). Sherrington Showed that even complex behaviors arise from reflexive processes. Penfield Elicited conscious experiences through direct brain stimulation. Key Takeaways 1. Central Question: a. How does the brain produce mental phenomena and behavior? 2. Relevance: a. Neuroscience addresses critical human issues, including mental health, neurological diseases, and brain dysfunction. 3. Future Directions: a. Advancements in technology and methods (e.g., BMIs, psychedelics) are paving the way for transformative discoveries. 4. Challenges: a. The complexity of the brain makes it one of the greatest scientific challenges. Detailed Exam Notes: Lecture 3 - Macroscopic and Microscopic Neuroanatomy Planes in Anatomy l Planesdivide the body to describe directions, useful in anatomical terminology: ¡ Superior/Inferior: Above/Below. ¡ Anterior/Posterior: Front/Back. ¡ Medial/Lateral: Close to/Far from the midline. l Rostro-Caudal Axis: ¡ Equivalent to the cranio-caudal axis in most vertebrates. ¡ In humans, this axis curves due to upright posture. Overview of the Nervous System 1. Central Nervous System (CNS): a. Comprises thebrainandspinal cord. b. Protected by: i. Bones(skull and vertebrae). ii. Meninges: 1. Layers: Dura mater, Arachnoid mater, Pia mater. 2. Reinforcement structures:Falx cerebri(between hemispheres) andTentorium cerebelli(between cerebrum and cerebellum). 2. Peripheral Nervous System (PNS): a. Includescranial nervesandspinal nerves. Gray and White Matter l Gray Matter: ¡ Darker regions due to high density of neuronal cell bodies. ¡ Forms: n Nucleiin the CNS. n Gangliain the PNS. l White Matter: ¡ Lighter regions due to myelinated axons. ¡ Forms: n Tractsin the CNS. n Nervesin the PNS. ¡ Function: Connects regions of gray matter. Functional Divisions of the Nervous System 1. Somatic Nervous System: a. Connects to muscles and sensory receptors. b. Controls voluntary movements and processes sensory input. 2. Autonomic Nervous System (ANS): a. Regulates involuntary processes. b. Subdivisions: i. Sympathetic(thoracolumbar): Fight-or-flight. ii. Parasympathetic(craniosacral): Rest-and-digest. iii. Enteric: Controls gastrointestinal functions. Anatomy of the Brain 1. Key Components: a. Cerebrum: i. Largest part of the brain, divided into two hemispheres. ii. Cortex: Surface layer with gyri (ridges) and sulci (grooves), increasing surface area. b. Cerebellum: i. Coordinates movement and balance. c. Brainstem: i. Includes medulla oblongata, pons, and midbrain. d. Pituitary Gland (Hypophysis): i. Visible at the brain’s base, controls hormonal functions. e. Diencephalon: i. Includes the thalamus and hypothalamus. f. Midline Structures: i. Visible in sagittal brain cuts, e.g., corpus callosum, ventricles. 2. Gray Matter Structures: a. Basal Ganglia: i. Dorsal Striatum: Caudate nucleus, Lentiform. nucleus (Putamen + Globus pallidus). ii. Ventral Striatum: Nucleus accumbens, Olfactory tubercle. iii. Subthalamic nucleus(diencephalon). iv. Substantia nigraandventral tegmental area(midbrain). b. Limbic System: i. Emotional and memory functions. ii. Includes the hippocampus, amygdala, cingulate gyrus, fornix, and stria terminalis. 3. White Matter Tracts: a. Intra-hemispheric: Within one hemisphere. b. Inter-hemispheric: Between hemispheres (e.g., corpus callosum). c. Projection Tracts: Link cortex to lower CNS areas. Brain Imaging Techniques 1. Computerized Tomography (CT): a. Uses X-rays to measure tissue density. b. Generates detailed images by combining slices. 2. Magnetic Resonance Imaging (MRI): a. Uses strong magnetic fields to align and excite atomic nuclei, producing high-resolution images. 3. Diffusion Tensor Imaging (DTI): a. Maps white matter tracts by tracking water diffusion along axons. Cellular Organization of the Nervous System 1. Neurons: a. Specialized for signal transmission. b. Components: i. Dendrites: Receive input. ii. Axons: Transmit output. iii. Synapses: Connection points between neurons. c. Morphology indicates direction of information flow. d. Approximately86 billion neuronsin the human brain with10^15 synapses. 2. Glial Cells: a. Support neurons and participate in neural signaling. b. Types: i. Astrocytes: Connect neurons to blood capillaries. ii. Microglia: Clean up cellular debris. iii. Oligodendrocytes(CNS) andSchwann Cells(PNS): Form. myelin sheaths to insulate axons. Brodmann Areas l Korbinian Brodmann: ¡ Created a map of the cerebral cortex based on microstructural differences. ¡ Brodmann areas are widely used to reference specific brain regions. Neurodegenerative Diseases 1. Alzheimer’s Disease (AD): a. Most common neurodegenerative disease and cause of dementia. b. Characterized by: i. Neurofibrillary tangles. ii. Amyloid plaques. 2. Parkinson’s Disease (PD): a. Second most common neurodegenerative disorder. b. Defined by: i. Lewy bodies, particularly in the substantia nigra. c. Symptoms: i. Bradykinesia (slowness). ii. Rigidity. iii. Tremor. iv. Postural instability. 3. Multiple Sclerosis (MS): a. Ademyelinating diseasewhere myelin loss disrupts neural signal transmission. b. Causes: i. Oligodendrocyte dysfunction. ii. Microglial activity. Comprehensive Exam Notes: Lecture 4 - The Physiology of the Brain Core Functions of the Brain 1. Electrical Signals: a. Brain functions are primarily based on neurons generating and transmitting electrical signals. 2. Metabolism: a. The brain relies on a high level of metabolic activity. b. Requires glucose and oxygen, supplied by the circulatory system and regulated by cerebrospinal fluid (CSF). Circulatory System of the Brain 1. Blood Supply: a. Suppliesoxygenandglucosefor cellular energy production. b. Arteriesdeliver oxygen-rich blood;veinsreturn oxygen-depleted blood. 2. Key Arteries: a. Vertebral arteriesandinternal carotid arteries: i. Converge at theCircle of Willis, a protective loop ensuring continuous blood supply. ii. Branch into: 1. Anterior, middle, and posterior cerebral arteries(forebrain supply). 2. Basilar arterybranches (brainstem supply). 3. Blood-Brain Barrier (BBB): a. Composed of specialized capillaries surrounded byastrocytesandpericytes. b. Regulates the passage of substances, protecting the brain from harmful agents. Ventricular System and Cerebrospinal Fluid (CSF) 1. Structure: a. Lateral ventricles(in all brain lobes),third ventricle, andfourth ventricle. b. Connected by thecerebral aqueductand pathways to thesubarachnoid space. 2. CSF Production and Dynamics: a. Produced by thechoroid plexusesin the ventricles (~500 mL daily). b. Total volume: ~140 mL, refreshed 3-4 times a day. 3. Functions of CSF: a. Cushions the brain, removes waste, and maintains homeostasis. b. Glymphatic System: Clears brain debris (e.g., proteins, toxins) via CSF flow. i. Efficiency depends onarterial pulsation, highest duringdeep sleep. ii. Declines with aging, contributing to neurodegenerative disease risk. 4. Aging Effects: a. Reduced deep sleep and arterial stiffness decrease glymphatic efficiency. Strokes and Brain Circulation Disorders 1. Definition: a. A stroke occurs when blood supply to a brain region is insufficient. 2. Types: a. Ischemic (blocked blood flow). b. Hemorrhagic (ruptured blood vessels). 3. Symptoms: a. Depend on the affected brain region (e.g., motor deficits, speech difficulties). Functional Imaging of the Brain 1. Positron Emission Tomography (PET): a. Uses radioactive tracers to measure blood flow and metabolic activity. b. Provides regional activity mapping. 2. Functional MRI (fMRI): a. Tracks blood oxygenation differences (oxygenated vs. deoxygenated hemoglobin). b. Reflects changes in neural activity over time. Electrical Activity in the Brain 1. Overview: a. Neural activity is based on ion movement across membranes, generating electrical signals. b. Early research using squid neurons revealed the molecular basis of these signals. 2. Membrane Potential: a. Resting potential (~ -70mV) is set by: i. Potassium channels. ii. Sodium-Potassium pumps. iii. Negatively charged intracellular proteins. b. Hyperpolarization: Increased potential difference (more negative inside). c. Depolarization: Decreased potential difference (less negative inside). 3. Action Potential: a. Triggered when a threshold potential is reached. b. Propagated along neurons, enabling signal transmission. c. Key mechanism for communication in the nervous system. 4. Electroencephalography (EEG): a. Detects summated brain electrical activity via scalp electrodes. b. Applications: i. Sleep studies: Analyze sleep patterns. ii. Event-Related Potentials (ERPs): Study cognitive responses to stimuli. The Glymphatic System 1. Discovery: a. Functions like the lymphatic system but is unique to the brain. b. Glial cells facilitate CSF flow through brain tissue. 2. Role in Neurodegeneration: a. Inefficient glymphatic clearance is linked to: i. Alzheimer's disease (accumulation of amyloid-beta). ii. Other neurodegenerative diseases. 3. Sleep Dependency: a. Glymphatic flow peaks duringdeep sleep. b. Aging disrupts deep sleep, reducing glymphatic efficiency. Summary of Key Concepts l Metabolic and electrical processesare central to brain function. l Thecirculatory systemandCSF dynamicsmaintain brain homeostasis and waste clearance. l Functional imaging and EEG provide insights into brain activity. l Understanding the glymphatic system highlights the link between sleep, aging, and neurodegeneration. Comprehensive Exam Notes: Lecture 5 - The Cellular Physiology of the Neuron Overview of the Nervous System l Thenervous systemrelies onneuronsto generate, conduct, and transmit electrical signals, which result in behavioral and cognitive phenomena. l Neuronsare the fundamental units responsible for the brain's communication, whileglial cellsprovide support, nourishment, and protection to neurons. Cell Structure and Function 1. Basic Components of a Cell: a. Cell Membrane: i. Separates the intracellular environment from the external environment. ii. Vital for maintaining homeostasis by regulating what enters and exits the cell. iii. Controls ion concentrations and pH within the cell, ensuring optimal conditions for protein function. b. Cytoplasm: i. The liquid inside the cell that contains the organelles and proteins essential for cell life. ii. Organelles: 1. Endoplasmic Reticulum (ER): Synthesizes proteins and lipids, critical for cellular function and structure. 2. Mitochondria: The powerhouse of the cell. ProducesATP(energy) viacellular respiration(glycolysis, citric acid cycle, and oxidative phosphorylation), requiringoxygenandglucose, producingcarbon dioxideandwateras byproducts. c. Nucleus: i. Contains theDNA, which holds the genetic instructions for protein synthesis. ii. The DNA is transcribed intomRNA, which is translated into proteins that perform. various cellular functions. Electrical Properties of Neurons 1. Resting Membrane Potential: a. The electrical potential difference across the neuronal membrane at rest (~ -70mV). b. This potential is primarily determined by thesodium-potassium pump(Na+/K+ ATPase), which actively transportsNa+ions out of the cell andK+ions into the cell. c. The differential distribution of ions across the membrane creates a negative charge inside the cell relative to the outside. d. The cell membrane is selectively permeable to certain ions, especiallyK+(which leaks out of the cell), contributing to the resting potential. 2. Changes in Membrane Potential: a. Hyperpolarization: Occurs when the inside of the cell becomes more negative than the resting potential (more negative than ~-70mV). This is usually caused by the influx ofCl⁻ions or efflux ofK⁺ions. b. Depolarization: Occurs when the membrane potential becomes less negative or more positive (approaching 0 mV). This is due to the influx ofNa⁺ions. Action Potential 1. Generation of Action Potential: a. If the depolarization reaches a threshold (around -55mV), anaction potentialis initiated. The action potential is a rapid, all-or-nothing electrical event that propagates along the axon. b. Voltage-Gated Ion Channels: i. Sodium Channels: Open in response to depolarization, allowingNa⁺to rush into the cell, further depolarizing the membrane. ii. Potassium Channels: Open later to allowK⁺to leave the cell, repolarizing the membrane. c. Phases of Action Potential: i. Resting State: All ion channels are closed. ii. Depolarization: Sodium channels open, andNa⁺rushes in. iii. Repolarization: Potassium channels open, andK⁺flows out. iv. Hyperpolarization: Potassium channels remain open briefly, causing the inside of the cell to become more negative than the resting potential. v. Refractory Period: After an action potential, the neuron briefly cannot fire another action potential (absolute refractory period), followed by a relative refractory period. 2. Propagation of Action Potential: a. Action potentials propagate down theaxonwithout decrement, allowing the signal to travel long distances. b. Inmyelinated axons, action potentials jump from one node of Ranvier to the next (saltatory conduction), which significantly increases conduction speed. c. Unmyelinated axonsconduct signals more slowly as the action potential must propagate continuously along the axon. Neural Transmission 1. Excitatory and Inhibitory Signals: a. Excitatory Transmission: i. Increases the likelihood that the postsynaptic neuron will reach the threshold for firing an action potential. ii. Typically mediated byglutamate(the major excitatory neurotransmitter). iii. Depolarizes the postsynaptic cell by allowingNa+influx. b. Inhibitory Transmission: i. Reduces the likelihood of an action potential firing by hyperpolarizing the postsynaptic cell. ii. Typically mediated byGABA(the major inhibitory neurotransmitter). iii. Increases the influx ofCl⁻or efflux ofK⁺, making the inside of the cell more negative. 2. Summation of Signals: a. Spatial Summation: Multiple signals arriving at different locations on the neuron are summed together. b. Temporal Summation: Multiple signals arriving at the same location in rapid succession are summed together. Synaptic Transmission 1. Steps in Synaptic Transmission: a. Action potentialreaches thepresynaptic terminal. b. This triggers the opening ofvoltage-gated calcium channels, allowingCa²⁺to enter the presynaptic neuron. c. The influx ofCa²⁺triggers the release of neurotransmitters from synaptic vesicles into the synaptic cleft byexocytosis. d. Neurotransmitters then bind to receptors on thepostsynaptic membrane. 2. Neurotransmitter Receptors: a. Ionotropic Receptors: These receptors areion channelsthemselves. When bound by neurotransmitters, they open and allow ions to flow into or out of the cell, causing rapid changes in membrane potential. b. Metabotropic Receptors: These receptors activateG-proteinsthat indirectly influence ion channels via second messenger systems (e.g., cAMP), leading to slower but prolonged effects. Cellular Protein Functions and Synthesis 1. Proteins in the Neuron: a. Proteins are essential for nearly every function within the cell, including enzyme activity, signal transduction, structural support, and neurotransmitter synthesis. 2. Protein Synthesis: a. DNAcontains the instructions for making proteins. b. mRNAis transcribed from DNA and exported from the nucleus. c. Ribosomesin the cytoplasm translate the mRNA into proteins by reading thecodonsand adding the correspondingamino acids. d. tRNAmolecules bring amino acids to the ribosome, where they are added to the growing protein chain. 3. Axonal Transport: a. Axonal transportmoves proteins and other materials from thecell bodyto theaxon terminals. b. Microtubulesandmotor proteins(kinesin and dynein) facilitate the movement of materials along the axon. Gene Expression 1. Central Dogma of Molecular Biology: a. DNA→mRNA→Protein. b. The sequence of nucleotide bases in theDNAdictates the amino acid sequence of proteins. 2. Gene Regulation: a. Different cells express different proteins based ongene expression, which is tightly regulated. b. Gene expression can be assessed by measuring the presence ofmRNAor the proteins themselves. Neuroplasticity and Synaptic Changes 1. Dendritic Arborization: a. Neurons can change their structure by growing new dendritic branches (arborization) or retracting old ones. This is a key component ofneuroplasticity, which allows for learning and memory formation. 2. Axonal Growth: a. Axonal growth and guidance are influenced bychemoattractants(which attract axons) andchemorepellents(which repel axons).
DIGT 1001 Digital Storytelling Curriculum Design Document Course Description Digital Storytelling is a course that provides students with the opportunity to learn about the techniques and methods involved in creating stories for the digital age. This form. of storytelling is an incredible tool for both personal expression and professional communication. Students are introduced to the different components involved in creating a digital story, with an emphasis on narrative development through multimedia. By the end of the course, students will create their own digital stories that allow for creative exploration and the use of technical skills. Learning Outcomes 1. Analyze the essential elements of effective storytelling, including structure, audience engagement, and tone. 2. Use digital tools proficiently (e.g., video editing software, audio mixers, and graphic design apps) to create multimedia stories. 3. Integrate diverse media formats (text, images, audio, video) into cohesive and impactful narratives. 4. Critically evaluate digital stories for their technical, aesthetic, and emotional effectiveness. 5. Create and present a polished, original digital story that communicates a personal or social message. 6. Critically reflect on individual performances, identify potential improvements and possible insufficiency. Graded Course Components Assessment Due Date Percent of Grade Weekly Discussion Posts Fridays at 5 PM ET 30% Digital Story Draft & Peer Review Week 6 25% Final Digital Story Submission Week 10 35% Reflection Essay Week 11 10% Participation in Workshops Ongoing Optional/Bonus Course Flow Students are expected to engage with weekly resources, including readings, videos, and examples of digital storytelling. Weekly discussions will focus on analyzing storytelling techniques and providing peer feedback. Assignments will build toward the final project, with iterative drafting and refining. Optional live workshops will offer hands-on training in digital tools and storytelling strategies. Example schedule: ● Mondays: Engage with readings and tutorials. ● Wednesdays: Contribute to discussion posts. ● Fridays: Submit assignments or peer reviews. Alignment Matrix Module/Week Topic(s) Outcome(s) Assessment(s) Week 1 - 2 Introduction to Digital Storytelling Outcome 1 Discussion Post Week 3 - 4 Storyboarding & Scripting Outcomes 1, 3 Discussion Post Draft of Storyboard Week 5 - 7 Multimedia Integration Outcomes 2, 3 Discussion Post Multimedia Mockup Week 8 - 9 Editing & Refinement Outcomes 2, 4 Discussion Post Peer Review of Draft Week 10 Final Digital Story Outcomes 3, 5 Final Project Submission Week 11 Reflection Essay Outcome 6 Reflection Essay Submission
TTTK2323 Mobile Programming Course Project: Group Assignment Project Overview: For this group project, your task is to develop a mobile application using Android Studio with Kotlin that incorporates industry-standard technologies. The app should be a solution to a real-world problem and demonstrate the following key features: 1. Data Handling: The app must integrate data 2. User Interface: The app should feature an intuitive and user-friendly interface that follows modern design principles, ensuring a good user experience (UX). 3. Real-World Problem Solving: Choose a real-world problem from the list below or propose your own relevant issue: o Environmental pollution o Lack of community support systems o Local tourism promotion o Support for small farmers to sell their produce o Promoting sustainability practices o Increasing accessibility for people with disabilities o Reducing food waste o Helping local artisans market their products o Improving public transportation access o Enhancing local disaster preparedness o Encouraging healthy living in urban areas o Addressing mental health awareness 4. Core Features: The app must include at least six main features that directly contribute to solving the chosen problem. Each team member is required to develop at least two functions as part of the overall app functionality. Features Related to Lecture Material: • Basic UI • User Interaction • Material Design • App Architecture • Navigation • Responsive UI • Data from the Internet • Data Storage I • Data Storage II • Additional and Advanced Features Project Requirements: • Individual Responsibilities: Each group member must develop two functions within the app. During the evaluation, each member will be asked to explain and demonstrate the part they developed. Be prepared to discuss the technical aspects, code structure, and functionality of your contributions. • Complexity: The project will be graded based on the complexity of the following elements: o Navigation: Implement smooth and intuitive navigation across multiple screens. o Data Storage: Use persistent data storage methods (e.g., SQLite, Room Database, Firebase). o User Interaction: Include dynamic user interaction such as forms, buttons, and gesture controls. o Innovative Features: It is strongly encouraged to incorporate at least one advanced technology to increase data complexity. Examples include: Using device sensors (e.g., GPS,accelerometer) Camera integration (e.g., for scanning QR codes) Machine learning components (e.g., for image recognition) AR (Augmented Reality) or VR features Cloud-based solutions (e.g., Firebase, AWS) Originality: Your project must be original. Plagiarism of code from any source will result in an automatic zero for the project. You may refer to examples and pre-existing code but must write the functionality yourself. Project Milestones: • Progress Evaluation 1 (5%): Initial idea and basic app structure. 1. 3-Minute Demo Video: Record and submit a 3-minute video demonstrating an interview to identify the app's requirements. 2. Layout Sketch: Provide a sketch of the app’slayout. 3. Partial Layout Development (20%): Develop part of the layout based on knowledge from Lecture 1 to Lecture 3. • Progress Evaluation 2 (5%): Functional prototype with core features. • Final Presentation (20%): A complete and polished app, with a demonstration of all features and a clear explanation of the technology used. Innovation and Impact: Your app should show an element of innovation and be useful to society. Think creatively and aim to build an app that makes a difference in solving the problem you've chosen.
FIN6102 Spreadsheet and VBA Modelling in Finance Homework 1 Suppose that you are an investment manager with a bank, and you’represented with the following investment opportunities of loans. You are evaluating the loans on 31 Dec, 2024. All payments are in arrears (meaning payment at end of each period). Loan 1 Loan 2 Loan 3 Loan 4 Drawdowns $14 million on Dec 31, 2024 $22 million on 31 Dec, 2024 $16 million on 31 Dec 2024, and $4 million on 30 Jun 2026. $20 million on Dec 31, 2027 Term (years from first Drawdown to maturity) 7 yrs 9 yrs 6 yrs 5 yrs Repayment Schedule Loan is paid back in equal installments, meaning that the total payment (principal + interest) for each period is the same. Payment is made semi-annually Interest is paid semi-annually for the first 5 years, then the loan is then paid back in equal installments. Interest is paid semi-annually. The principal is paid back at maturity. Interest is capitalized semi- annually for the first 2 years and is paid semi-annually thereafter. Then the loan (with the capitalized interest) will be paid back with equal principal payments semi-annually. Interest Rate 6.50% 8% for the interest only periods, 8.5% during the remaining periods. 7.00% 9.5% for the first two years, 10.5% for the remainder of the years. 1. List out the cash flow and outstanding amount for each loan for every year with semi-annual frequency. See template provided in the Excel workbook. Note that you only need to fill the years for each loan as they last. 2. Assume a discount rate of 5%, calculate the net present value of each loan as of Dec 31, 2024. 3. Suppose that you have only 40 million dollars budget, so you can’t take all the loans. Assuming you can either choose one investment or leave it (i.e., you cannot choose to invest in a fraction of the investment). Your target is to maximize the future value of your portfolio at the end of year 2033, which loans will you choose? 4. If you can invest at any fraction of the loan (but not more than 100%), how should you construct your portfolio? Assume that no interest will be earned for cash at hand. Describe the process of solving the problem. (Hint: use Solver) 5. What if you can earn an interest of 5% for your remaining cash at hand (use semi-annual compounding), will that change your answer for question 3 and 4? What is the final value of your portfolio at the end of 2033? 6. If each loan has an independent probability of default of 1% on the date of Dec 31, 2028 (the last day of 4 years). There is no probability of default at any other time. If they default, you will lose all the outstanding principal in the loan. For the portfolio that you constructed in 4: a. What is your 4-year 99% Value at Risk (in million dollars)? b. What is your 4-year 99% Expected Shortfall (in million dollars)? Hint: at end of Dec 31, 2028, your portfolio value = cash at hand + principal that has not defaulted. Calculate the probability of each portfolio value and its P&L. Then use it for VaR/ES calculation.
Intermediate Econometrics - 5QQMN938 Assessment 1– Individual Coursework (40% of total module grade) The Task Project Brief The global economy has recently experienced a period of inflationary pressure characterised by a complex set of political and socio-economic events. The Covid-19 pandemic’s lockdowns resulted in forth-and-back switch from goods to services as economies reopened. These swift changes put pressure on the supply chains and occurred during unprecedented fiscal and monetary stimulus. The Ukrainian-Russo conflict since 2022 has only exacerbated the pressure. By mid-2022, global inflation had tripled relative to its pre- pandemic level. Policymakers around the world have responded, resulting in a global tightening cycle, or “Great Tightening”. The International Monetary Fund (IMF) recently wrote: “As global disinflation continues, services price inflation remains elevated in many regions, pointing to the importance of understanding sectoral dynamics and of calibrating monetary policy accordingly.” Source: IMF World Economic Outlook October 2024 In this project you will become an inflation forecaster for a country in a selection of global economies (see “Country Allocation” below). Your analysis will be to analyse the total inflation rate as well ascore inflation. You will provide some background and context to recent and historical trends in inflation, select between econometric forecasting models and make forecasts of total and core inflation in 2025Q1. The dataset “MajorCountries.xlsx” contains data on the total and core consumer price index (CPI) for 08 selected countries. Each series is taken from the national source and was downloaded from the aggregator Macrobond. The data are quarterly, and the dataset contains all available observations until the present. Your task is to produce an A4 poster which can be used as your economy’s “Quarterly Inflation Update” and presented at an economic forum on inflation. The poster should be visually appealing and convey all of the information in a concise way. The design and layout of the poster is up to you (short text, graphics, tables, equations, infographics etc. are all allowed). The poster should have the following basic structure: Data Analysis: Provide background and context to total and core CPI inflation in your country (using the quarter-on-quarter inflation rate), identify any notable historic movements and analyse the series’ recent time series behaviour. Further concise and relevant discussions are encouraged. Econometric Modelling: Select and report appropriate forecasting models for the two CPI inflation rates, using primarily the BIC to select between all AR(p) models with lags of p from one to four. Discuss and critically evaluate the models and the limitations of the modelling approach. Forecasting: Produce and graphically display the forecasts for the two inflation rates for the period 2025Q1. Evaluate the forecasts and their uncertainty and make a conclusion in the context of the global economic situation. Appendix: Provide all Stata codes used in the analysis. These can be placed on a separate page after the A4 poster. The provision of Stata codes which replicate all of the results in the project is a minimum requirement. Students who wish to explore using different coding languages can do so, but it will not attract any additional grades. Examples The format and design of the poster is up to you. However, you may take inspiration from posters you find online. For example, the STEM for Britain poster competition. This gives examples of similar research posters. It is up to you to judge whether they look good or bad! Pay particular attention to their use of headings, colour, sparing use of text, graphics and infographics, presentation of graphs, tables and equations. Refer to Keats’s marking criteria for more. Submission The final submission should only include the cover sheet, the A4 poster (one page) and an appendix with Stata codes (fit to one page, you can use two columns if necessary). The total submission should therefore not exceed two sides of A4 after the cover sheet. There is no specific word limit for the poster as this will include visual elements, but you are strongly recommended not to exceed 300 words of text (this does not apply to the Stata appendix of cover sheet). Bear in mind that part of the marks for the project is awarded for presentation (see “Marking” below) where very concise discussion and summary is preferred. Before submitting a poster, which looks like an essay, check the marking criteria (posted on Keats) for the project. The use of an A4 poster must be strictly followed. You must submit a pdf of the document to Turnitin. If you use Microsoft Word, you should export this to pdf first using File->Export. For Equations or Mathematical Notations, you can use Insert/Equations for professional formatting.
Using multiple absorbers In the vibration absorber short lab you have looked at the effect of adding a tuned mass damper (TMD) to the structure to reduce the amplitude of vibration at resonance. While this was accomplished, the TMD also introduced two additional resonant peaks, at frequencies each side of the original peak. In an earthquake, excitation of the structure occurs over a range of frequencies, and these two peaks (even though lower) may still produce unacceptably large vibration. Additionally, in a real structure, it may be more practical to have multiple small absorbers, rather than a few large ones. In this experiment, you are to investigate the use of multiple absorbers, tuned such that they spread the peaks and reduce vibration over a range of frequencies. Using an Octave/Matlab model of the structure, carry out a similar analysis to that done in the vibration absorber short lab, but using multiple absorbers. Here are a few suggested questions to investigate: Compare, for example, the effects of using 1, 10, 100 and 1000 absorbers tuned to slightly different frequencies (with the same total mass in each case). Which gives the widest spread? What is the minimum total mass of absorbers required to reduce the maximum (harmonic) response of the structure to, say, 10% of its value with no absorbers? How does this change if you analyse the impulse response? Is there are trade-off between the optimum tuning to deal with harmonic and impulse responses? Can you think of a way to test these predictions on the structure?
Math 2568 Midterm Spring 2025 1. (20 points) Consider the vectors: (a) Determine whether or not the set of vectors {⃗v1, ⃗v2, ⃗v3} is linearly dependent or linearly inde pendent. (b) Determine whether or not the set of vectors { ⃗w1, ⃗w2, ⃗w3, ⃗w4} is linearly dependent or linearly independent. (Hint: No row reduction is necessary to answer this.) 2. (20 points) Consider the linear system of equations A⃗x = ⃗b with augmented matrix In (a)–(c), a matrix in echelon form. which is row equivalent to the augmented matrix is given. In each case, determine whether the original system: (i) is inconsistent (ii) has a unique solution (iii) has infinitely many solutions; in this case, find the general solution. 3. (20 points) Find a number b so that the matrix is singular. 4. (20 points) Let be an m × n matrix, be an n × p matrix, be an p × q matrix, be an n-vector, and be a p-vector. (a) Express B ⃗w as a linear combination of the n-vectors B⃗ 1, . . . , B⃗ p. (b) Suppose m, n, p, and q are all different integers. Determine which of the following products are defined and find their dimensions: (i) B⊤C (ii) A⃗v (iii) B⊤A (iv) C ⊤C (v) BB⊤ 5. (20 points) (a) Let ⃗v and ⃗w be solutions to the homogeneous linear system A⃗x = ⃗0. Show that c⃗v + d ⃗w is also a solution to this system. (b) Let A and B be two n × n matrices. Show that if B is singular, then AB must be singular. (Hint: Consider the homogeneous system definition of singularity.)
MIE 1622H: Assignment 1 – Mean-Variance Portfolio Selection Strategies January 27, 2025 Due: Saturday, February 15, 2025, not later than 11:59p.m. Use Python for all MIE1622H assignments. You should hand in: • Your report (pdf file and docx file). Maximum page limit is 4 pages. • Compress all of your Python code (i.e., ipynb notebook with plots and necessary outputs intact) into a zip file and submit it via Quercus portal no later than 11:59p.m. on February 15. Where to hand in: Online via Quercus portal, both your code and report. Introduction The purpose of this assignment is to compare computational investment strategies based on mini- mizing portfolio variance, maximizing expected return and maximizing Sharpe ratio. You will need to take into account the effect of trading costs. We start with the classical Markowitz model of portfolio optimization. We are trading only stocks S1,..., Sn, and the total number of stocks isn = 30. At holding period t the expected (daily) return of stock i is µi(t), the standard deviation of the return is σi(t) . The correlation between the returns of stocks i ≠ j is ρij(t) . To abbreviate notation we introduce the return vector µt = (µ1(t) , . . . ,µn(t))T and the covariance matrix Qt = [ρij(t)σi(t)σj(t)]i,j=1,...,n. At time period t we estimate µt and Qt from the period t — 1 time series. There are 12 holding periods and each holding period lasts 2 months (2 years in total). As a result, you can re-balance your portfolio at most 12 times. Each transaction has a cost composed of a variable portion only. The variable fee is due to the difference between the selling and bidding price of a stock, and is 0.5% of the traded volume. This means that if a stock is quoted at 30 dollars and the investor buys 10 shares, then they are going to pay 0.005·30 · 10 = 1.50 dollars on top of the 300 dollars the 10 shares would cost otherwise. If they sell 20 shares at the same 30 dollar price then they get 600 dollars, minus the 0 .005 · 600 = 3 dollar transaction cost. Your may not need to account for transaction fees in your optimization, but you need to take them into account when computing portfolio value. The goal of your optimization effort is to create a tool that allows the user to make regular decisions about re-balancing their portfolio and compare different investment strategies. The user wants to consider the total return, the risk and Sharpe ratio. They may want to minimize/maximize any of these components, while limiting one or more of the other components. The basic building block is a decision made at the first trading day of each 2-month holding period: given a current portfolio, the market prices on that day, and the estimates of the mean and covariance of the daily returns, make a decision about what to buy and sell according to a strategy. You are proposed to test five strategies: 1. “Buy and hold” strategy; 2. “Equally weighted” (also known as “1/n”) portfolio strategy; 3. “Minimum Variance” portfolio strategy; 4. “Maximum Expected Return” portfolio strategy; 5. “Maximum Sharpe ratio” portfolio strategy. To test your bi-monthly decisions, you are given adjusted closing prices of 30 stocks over a two-year period. Obviously, you cannot use the actual future prices when making a decision, only the price at that day, the expected return and covariance estimates. These estimates were derived from the actual data and are quite accurate. Once you are done with trades for a current holding period, you should move on to the next period, use new prices (and new estimates), and make another decision. You also need to track the value of your portfolio on each day, so that you have it handy at the first trading day of a new period. You re-balance your portfolio on the first trading day of each 2-month holding period (up to 12 re-balances during 2 years). The 30 stocks for this assignment are from U.S. stock market, priced in U.S. dollars. Their quotes are given on trading days as adjusted closing prices. The data set is from January 2020 to Decem- ber 2021. The list of assets and their sectors is: 1. Technology: AAPL, MSFT, NVDA, IBM, AMD, CSCO, HPQ, SONY 2. Financial Services: JPM, BAC, MS 3. Healthcare: JNJ, UNH, PFE 4. Consumer Cyclical: AMZN, F, HOG 5. Consumer Defensive: KO, PG 6. Energy: XOM, CVX 7. Real Estate: AMT, PLD 8. Communication Services: GOOG, T, VZ 9. Industrials: HON, CAT 10. Utilities: NEE, DUK The initial portfolio is as follows:“HOG” = 3447 shares, “VZ” = 19385 shares. The value of the initial portfolio is about one million dollars. The initial cash account is zero USD. The cash account must be nonnegative at all times. Your optimization algorithm may suggest buying or selling a non-integer number of shares, which is not allowed. You need to round the number of shares bought or sold to integer values and subtract transaction fees. If the value of your portfolio after re-balancing plus the transaction fees are smaller than the portfolio value before re-balancing, the remaining funds are accumulated in the cash account. Cash account does not pay any interest, but cash funds should be used toward stock purchases when portfolio is re-balanced next time. An estimate of the daily returns of the stocks (for trading days) and the covariances of the returns are computed for you. These estimates are based on the previous two-month data and are updated every second month. You can only use the current estimate for the calculations and are not allowed to change or update the estimates in any way. Note that for buying and selling asset shares, you need to optimize over asset weights. Current weight of asset i in a portfolio is wi = V/vi·xi , where V is the current portfolio value, vi is current price of asset i and xi is the number of units (shares) of asset i in your portfolio. As the initial portfolio value for the 2020-2021 period is $1,000,016.96 USD, the price of the HOG stock on the first trading day of holding period 1 is 34.08 USD, and we hold 3447 shares, then w12 1 = V1/v1 12·x1 12 = 1000016.96/34.08·3447 = 0.1175. Questions 1. (50%) Implement investment strategies in Python: You need to test five portfolio re-balancing strategies: 1. “Buy and hold” strategy: it is the simplest strategy where you hold initial portfolio for the entire investment horizon of 2 years. The strategy is already implemented in the function strat_buy_and_hold. 2. “Equally weighted” (also known as “1/n”) portfolio strategy: asset weights are se-lected as wi(t) = 1/n, where n is the number of assets. You may need to re-balance your portfolio in each period as the number of shares i(t) changes even when wi(t) = 1/n stays the same in each period. The strategy should be implemented in the function strat_equally_weighted. 3. “Minimum Variance” portfolio strategy: compute minimum variance portfolio for each period and re-balance accordingly. The strategy should be implemented in the function strat_min_variance. 4. “Maximum Expected Return” portfolio strategy: build a portfolio that maximizes ex- pected return for each period and re-balance accordingly. The strategy should be im- plemented in the function strat_max_return. 5. “Maximum Sharpe ratio” portfolio strategy: compute a portfolio that maximizes Sharpe ratio for each period and re-balance accordingly. The strategy should be implemented in the function strat_max_Sharpe. Design and implement a rounding procedure, so that you always trade (buy or sell) an integer number of shares. Design and implement a validation procedure in your code to test that each of your strategies is feasible (you have enough budget tore-balance portfolio, you correctly compute transaction costs, funds in your cash account are non-negative). There is a file portf optim.ipynb on the course web-page. You are required to complete the code in the file. Make sure to restart the notebook and re-run all cells on Google Colab before submitting, and have all outputs and plots intact when saving the notebook. Your Python code should use only CPLEX optimization solver without CVXPY module. You are required to briefly comment on your code to explain important logic and implementation details. Some marks may be deducted for lack of explanation or poorly commented code. You are required to provide a mathematical formulation to the optimization problem you solve in strategy 3, 4, and 5 and explain relevant information (variables, constraints, objec- tive function, data parameters, etc). This should be done in the report and can refer to comments/code from the ipynb file. For this assignment you need to use Google Colab and install the trial version of CPLEX (available on Colab) as sizes of the optimization problems are small. To install CPLEX on Google Colab just run !pip install cplex. 2. (25 %) Analyze your results: • Produce the following output for the 12 periods (two years): Period 1: start date 01/02/2020, end date 02/28/2020 Strategy "Buy and Hold", value begin = $ 1000016 .96, value end = $ 887595 .87, cash account = $0 .00 Strategy "Equally Weighted Portfolio", value begin = . . . , value end = . . . , cash account = . . . ... Period 12: start date 11/1/2021, end date 12/31/2021 Strategy "Buy and Hold", value begin = $ 964589 .81, value end = $ 942602 .39, cash account = $0 .00 Strategy "Equally Weighted Portfolio", value begin = . . . , value end = . . . , cash account = . . . • Plot one chart in Python that illustrates the daily value of your portfolio (for each trading strategy) over the two years using daily adjusted closing prices provided. Include the chart in your report. • Plot three charts in Python for strategy 3, 4, and 5 to show dynamic changes in portfolio allocations. In each chart, x-axis represents the rolling up time horizon, y-axis denotes portfolio weights between 0 and 1, and distinct lines display the position of selected assets over time periods. You may use these figures to support your analysis or discussion. • Compare your trading strategies and discuss their performance relative to each other. Which strategy would you select for managing your own portfolio and why? • Compute the risk measures (variance, maximum drawdown, and Sharpe ratio) for the “Maximum Expected Return” portfolio strategy over the 2020-2021 time period and compare those to measures for other strategies. 3. (25 %) Discuss possible improvements to your trading strategies: • Test your Python program for different variations of your strategies, e.g., select “1/n” portfolio at the beginning of period 1 and hold it till the end of period 12 (as if the re- balancing strategy required large transaction costs). Discuss if you are able to achieve better results. • Can you suggest any improvements of the trading strategies that you have implemented? • To potentially reduce risk measures for the “Maximum Expected Return” portfolio strat- egy, apply sector diversification constraints by ensuring that the total weight of stocks in each sector is between 0% and 25%. Then, compare your results with those in the previous section. • Re-test all of your strategies for the 2023-2024 time period and plot the daily value of your portfolio over these two years using the daily adjusted closing prices provided in the new dataset (adjclose_2023_2024.csv file). Use the new initial portfolio consisting of “HOG” = 10,904 shares and “CVX” = 3,542 shares,whose total value is again about one million dollars, and apply the updated risk-free rate of 4.5% (instead of 1.5% for 2020- 2021). Then, considering the economic contexts of these two distinct two-year periods, compare the performance of all strategies and clearly discuss how market conditions may have influenced performances, rewards and risks of your portfolios during 2020–2021 versus 2023–2024 time periods. • (Optional Question) Using a generative AI tool (e.g., ChatGPT), produce a one-page, executive-style summary of your portfolio modeling results and analyses. Include this AI-generated summary in your report and briefly discuss its clarity, accuracy, and any important points it may have missed relative to your own written conclusions. You can get additional 5% for answering this optional question, but your maximal mark for the assignment cannot exceed 16 points. Python Code to be Completed (available on Quercus) # Import libraries import pandas as pd import numpy as np import math """# Strategies For strategies 3,4 and 5 include mathematical formulation of optimization problem in report and/or in notebook """ def strat_buy_and_hold(x_init, cash_init, mu, Q, cur_prices): x_optimal = x_init cash_optimal = cash_init return x_optimal, cash_optimal def strat_equally_weighted(x_init, cash_init, mu, Q, cur_prices): return x_optimal, cash_optimal def strat_max_return(x_init, cash_init, mu, Q, cur_prices): return x_optimal, cash_optimal def strat_min_variance(x_init, cash_init, mu, Q, cur_prices): return x_optimal, cash_optimal def strat_max_Sharpe(x_init, cash_init, mu, Q, cur_prices): return x_optimal, cash_optimal """# Data loading and initialization of portfolios""" # Input file input_file_prices=’adjclose_2020_2021 .csv’ # path to close_2020_2021 file # Read data into a dataframe. df = pd.read_csv(input_file_prices) # Convert dates into array [year month day] def convert_date_to_array(datestr): temp = [int(x) for x in datestr.split(’/’)] return [temp[-1], temp[0], temp[1]] dates_array = np.array(list(df[’Date’] .apply(convert_date_to_array))) data_prices = df.iloc[:, 1:] .to_numpy() dates = np.array(df[’Date’]) # Find the number of trading days in Nov-Dec 2019 and # compute expected return and covariance matrix for period 1 day_ind_start0 = 0 if ’2021’ in input_file_prices: day_ind_end0 = len(np.where(dates_array[:,0]==2019)[0]) elif ’2022’ in input_file_prices: day_ind_end0 = len(np.where(dates_array[:,0]==2020)[0]) cur_returns0 = data_prices[day_ind_start0+1:day_ind_end0,:] / data_prices[day_ind_start0:day_ind_end0-1,:] - 1 mu = np.mean(cur_returns0, axis = 0) Q = np.cov(cur_returns0.T) # Remove datapoints for year 2019 data_prices = data_prices[day_ind_end0:,:] dates_array = dates_array[day_ind_end0:,:] dates = dates[day_ind_end0:] # Initial positions in the portfolio init_positions = np .array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3447, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 19385, 0]) # Initial value of the portfolio init_value = np.dot(data_prices[0,:], init_positions) print(’ Initial portfolio value = $ {} ’ .format(round(init_value, 2))) # Initial portfolio weights w_init = (data_prices[0,:] * init_positions) / init_value # Number of periods, assets, trading days N_periods = 6*len(np .unique(dates_array[:,0])) # 6 periods per year N = len(df.columns)-1 N_days = len(dates) # Annual risk-free rate for years 2020-2021 is 1.5% r_rf = 0 .015 # Number of strategies strategy_functions = [’strat_buy_and_hold’, ’strat_equally_weighted’, ’strat_min_variance’, ’strat_max_return’, ’strat_max_Sharpe’] strategy_names = [’Buy and Hold’, ’Equally Weighted Portfolio’, ’Minimum Variance Portfolio’, ’Maximum Expected Return Portfolio’, ’Maximum Sharpe Ratio Portfolio’] N_strat = 1 # comment this in your code #N_strat = len(strategy_functions) # uncomment this in your code fh_array = [strat_buy_and_hold, strat_equally_weighted, strat_min_variance, strat_max_return, strat_max_Sharpe] """# Running computations and printing results""" portf_value = [0] * N_strat x = np.zeros((N_strat, N_periods), dtype=np.ndarray) cash = np.zeros((N_strat, N_periods), dtype=np.ndarray) for period in range(1, N_periods+1): # Compute current year and month, first and last day of the period if ’2020’ in input_file_prices: if dates_array[0, 0] == 20: cur_year = 20 + math.floor(period/7) else: cur_year = 2020 + math.floor(period/7) elif ’2021’ in input_file_prices: if dates_array[0, 0] == 21: cur_year = 21 + math.floor(period/7) else: cur_year = 2021 + math.floor(period/7) cur_month = 2*((period-1)%6) + 1 day_ind_start = min([i for i, val in enumerate((dates_array[:,0] == cur_year) & (dates_array[:,1] == cur_month)) if val]) day_ind_end = max([i for i, val in enumerate((dates_array[:,0] == cur_year) & (dates_array[:,1] == cur_month+1)) if val]) print(’ Period {0}: start date {1}, end date {2}’ .format(period, dates[day_ind_start], dates[day_ind_end])) # Prices for the current day cur_prices = data_prices[day_ind_start,:] # Execute portfolio selection strategies for strategy in range(N_strat): # Get current portfolio positions if period == 1: curr_positions = init_positions curr_cash = 0 portf_value[strategy] = np.zeros((N_days, 1)) else: curr_positions = x[strategy, period-2] curr_cash = cash[strategy, period-2] # Compute strategy x[strategy, period-1], cash[strategy, period-1] = fh_array[strategy](curr_positions, curr_cash, mu, Q, cur_prices) # Verify that strategy is feasible (you have enough budget to re-balance portfolio) # Check that cash account is >= 0 # Check that we can buy new portfolio subject to transaction costs ###################### Insert your code here ############################ # Compute portfolio value p_values = np.dot(data_prices[day_ind_start:day_ind_end+1,:], x[strategy, period-1]) + cash[strategy, period-1] portf_value[strategy][day_ind_start:day_ind_end+1] = np.reshape(p_values, (p_values.size,1)) print(’ Strategy "{0}", value begin = $ {1: .2f}, value end = $ {2: .2f}, cash account = ${3: .2f}’ .format( strategy_names[strategy], portf_value[strategy][day_ind_start][0], portf_value[strategy][day_ind_end][0], cash[strategy, period-1])) # Compute expected returns and covariances for the next period cur_returns = data_prices[day_ind_start+1:day_ind_end+1,:] / data_prices[day_ind_start:day_ind_end,:] - 1 mu = np.mean(cur_returns, axis = 0) Q = np.cov(cur_returns.T) """# Plot results""" # Plot results ###################### Insert your code here ############################ """# Repeat for years 2023-2024""" # Input file input_file_prices_new=’adjclose_2023_2024 .csv’ # path to close_2023_2024 file # Read data into a dataframe. df_new = pd.read_csv(input_file_prices_new) # Initial positions in the portfolio init_positions_new = np .array([0, 0, 0, 0, 0, 0, 0, 3542, 0, 0, 0, 10904, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]) # Annual risk-free rate for years 2023-2024 is 4.5% r_rf2023_2024 = 0 .045 # Repeate the previous calculation for the time period 2023-2024 ###################### Insert your code here ############################ """# Plot the results for years 2023-2024""" # Plot results for 2023-2024 ###################### Insert your code here ############################ Sample Python Function for Trading Strategy def strat_buy_and_hold(x_init, cash_init, mu, Q, cur_prices): x_optimal = x_init cash_optimal = cash_init return x_optimal, cash_optimal
Assessment (non-exam) Brief Module code/name MSIN0047 Entrepreneurial Finance Academic year 2024/25 Term 2 Assessment title Financial Model Spreadsheet and Financial Pitch Deck (Level 7) Individual/group assessment Individual Submission deadlines: Students should submit all work by the published deadline date and time. Students experiencing sudden or unexpected events beyond your control which impact your ability to complete assessed work by the set deadlines may request mitigation via the extenuating circumstances procedure . Students with disabilities or ongoing, long-term conditions should explore a Summary of Reasonable Adjustments. Students may use the delayed assessment scheme for pre-determined mitigation on a limited number of assessments in a year. Check the Delayed Assessment Scheme area on Portico to see if this assessment is eligible. Return and status of marked assessments: Students should expect to receive feedback within 20 working days of the submission deadline, as per UCL guidelines. The module team will update you if there are delays through unforeseen circumstances (e.g. ill health). All results when first published are provisional until confirmed by the Examination Board. Copyright Note to students: Copyright of this assessment brief is with UCL and the module leader(s) named above. If this brief draws upon work by third parties (e.g. Case Study publishers) such third parties also hold copyright. It must not be copied, reproduced, transferred, distributed, leased, licensed or shared with any other individual(s) and/or organisations, including web-based organisations, without permission of the copyright holder(s) at any point in time. Academic Misconduct: Academic Misconduct is defined as any action or attempted action that may result in a student obtaining an unfair academic advantage. Academic misconduct includes plagiarism, self-plagiarism, obtaining help from/sharing work with others be they individuals and/or organisations or any other form of cheating that may result in a student obtaining an unfair academic advantage. Refer to Academic Manual Chapter 6, Section 9: Student Academic Misconduct Procedure - 9.2 Definitions. Referencing: You must reference and provide full citation for ALL sources used, including AI sources, articles, text books, lecture slides and module materials. This includes any direct quotes and paraphrased text. If in doubt, reference it. If you need further guidance on referencing please see UCL’s referencing tutorial for students. Failure to cite references correctly may result in your work being referred to the Academic Misconduct Panel. Use of Artificial Intelligence (AI) Tools in your Assessment: Your module leader will explain to you if and how AI tools can be used to support your assessment. In some assessments, the use of generative AI is not permitted at all. In others, AI may be used in an assistive role which means students are permitted to use AI tools to support the development of specific skills required for the assessment as specified by the module leader. In others, the use of AI tools may be an integral component of the assessment; in these cases the assessment will provide an opportunity to demonstrate effective and responsible use of AI. See page 3 of this brief to check which category use of AI falls into for this assessment. Students should refer to the UCL guidance on acknowledging use of AI and referencing AI . Failure to correctly reference use of AI in assessments may result in students being reported via the Academic Misconduct procedure. Refer to the section of the UCL Assessment success guide on Engaging with AI in your education and assessment. Content of this assessment brief Section Content A Core information B Coursework brief and requirements C Module learning outcomes covered in this assessment D Groupwork instructions (if applicable) E How your work is assessed F Additional information
CHEMICAL ENGINEERING CENG0005 – Physical Chemistry – CW 2025 Real gas reaction mixture a) A batch reactor of constant volume of 500 cm3 at 573 K is filled with 1.5 mol of a gaseous component, Dimer (D), with a critical temperature of 560 K and critical pressure 27 bar. Assuming real gas behaviour according to van der Waals (vdW) equation of state (EoS), calculate the pressure in the reactor. [10] b) The dimer component undergoes an elementary decomposition reaction to a gaseous monomer component (M) according to the reaction: D → 2 M. The critical temperature of component M is 420 K, and its critical pressure is 42 bar. Calculate the reactor pressure as function of the conversion of D using vdW-EoS for mixtures. Use the following mixing rules for the two van der Waals constants: i) Describe your calculation method and present any equations/formulae used. [30] ii) Tabulate and plot your results. For your calculations, table, and plot, use a conversion increment of 0.05 (5 %). [30] c) Perform. the same calculations, tabulating and plotting your results, assuming that the reaction mixture of D and M behaves like an ideal gas. [10] d) Compare and comment on the results between b and c above (real/vdW pressure vs ideal gas pressure), discussing in particular the dominant intermolecular forces. [6] e) Calculate the compressibility factor at all conversion values as in b-ii and plot them, i.e. plot the compressibility factor against conversion. Describe your calculation method presenting any equations/formulae used. Comment on all features of the plot, discussing in particular the dominant intermolecular forces. [14]
BACKGROUND:You’ve been hired by the IPLRA (International Programming Language Review Association) to conduct a security audit for their newly released API. They are excited to finally release an API to the community for developers across the world to leverage. In fact, they see this API as a way to increase their amount of reviews by 800%. The only thing standing in their way is a final audit and approval, by you. Unfortunately, after only 5 minutes of looking at the API, you’ve found issues and need to report them. Your goal is to bring visibility to these vulnerabilities in their API by finding the flags for each scenario. Good luck on your flag hunt and we hope you enjoy learning all about modern web APIs.Note: The IPLRA is not real and we made it up.SETUP:To get set up for the flags, carefully follow the steps below.You will need switch users. Log into the VM with the following user.The username, password and VM location are located on Canvas.Run this at the terminal to start the API$ ./StartContainer.shproject_apisecurity.json is available in the /home/apisec/Desktop folder. Put all flags in this file and submit it as your final deliverable.To access the Web API open Chrome in the VM and navigate to this URL. This is the Swagger documentation page that describes the API and allows for testing: http://localhost:8080/swagger/index.html_*Note: You can also click the “Swagger UI” bookmark in _Chrome******GATECH_ID IS A REQUIRED HEADER******NOTE: This is not the Georgia Tech Username, it is the GTID that you can find usng the steps on the Required ReadingBe very careful! When you copy and paste be sure to strip off all leading spaces or special characters.Submission Details:File submission instructions:This project needs to be submitted via gradescope. Navigate to the course in Canvas, click ‘Gradescope’, click ‘Project API Security’ and submit there.The contents of the submission file should be the following. There is a project_apisecurity.json file in your vm with a template set up, or you can copy-paste this to your newly created project_apisecurity.json file elsewhere and replace the placeholders with the flags you retrieve from each relevant task.Note: You can use TextEdit or Vim to create and edit this file. Do not use LibreOffice or any Word Document editor. It must be in proper JSON format with no special characters in order to pass the autograder and these Word Document editors are likely to introduce special characters.If you can’t find the file in the VM just copy this format below:{“flag1”: “”,“flag2”: “”,“flag3”: “”,“flag4”: “”,“flag5”: “”,“flag6”: “”,“flag7”: “”, “flag8”: “”}An example of what the submitted file content should look like:{“flag1”: “4ec60c3e084d8387f0f33916e9b08b99d5264a486c29130dd4a5a530b958c5c0f1faeaca2ce30b478281ec546a4729f“flag2”: “f496d9514c01e8019cd2bc21edfeb8e33f4a29af14a8bf92f7b3c14b5e06c5c0f1faeaca2ce30b478281ec546a4729f“flag3”: “b621bba0bb535f2f7a222bd32994d3875bcfcad651160c543de0a01dbe2e0c5c0f1faeaca2ce30b478281ec546a4729“flag4”: “f38e2cafb43ab4a0a647a8b08fc97bca25aa7cfb517029d5dd02faf49bff5c5c0f1faeaca2ce30b478281ec546a4729“flag5”: “1711ee5eb85b9020d1f4193ee6d884abd12a2eadc4890d28c490ae0c36446c5c0f1faeaca2ce30b478281ec546a4729“flag6”: “1711ee5eb85b9020d1f4193ee6d884abd12a2eadc4890d28c490ae0c36446c5c0f1faeaca2ce30b478281ec546a4729“flag7”: “1711ee5eb85b9020d1f4193ee6d884abd12a2eadc4890d28c490ae0c36446c5c0f1faeaca2ce30b478281ec546a4729 “flag8”: “f38e2cafb43ab4a0a647a8b08fc97bca25aa7cfb517029d5dd02faf49bff5c5c0f1faeaca2ce30b478281ec546a4729}TABLE OF CONTENTSThis flag will introduce you to basic API functionality using a documentation and test harness tool called Swagger. Swagger is a very popular tool used to develop and test web APIs and has plugins/modules in most programming languages. You can learn more about Swagger here: https://swagger.io/You’ll need to leverage Swagger (or any other http tool you desire such as curl or Postman) to determine how the API is configured and what endpoints to invoke to earn this flag.Warning: The site doesn’t use file storage or a database, all data is stored in memory. If you crash the web API or restart the VM, any data you have created/modified will have been lost and you’ll need to begin at step 1.To earn your flag you must perform the following actions by making API calls.Hints:In order to get this flag you need to create a new reviewer in the system. Unfortunately, the developers locked down this functionality some time ago so you’ll need an auth token in order to perform it. You read in the newspaper last week that Programming Reviews LLC had a big data breach so there is a good chance you can come across some credentials.To earn your flag you must perform the following actions.Hints:https://learning.postman.com/docs/getting-started/introduction/Include your flag2 into the json file and now onto Flag 3! Now that you’ve used an Auth token we’re going to dig a bit deeper into JWT (JSON Web Tokens). This flag is simple and designed only to get you acquainted with how JWTs are constructed. There are numerous resources to help you work with JWTs, one we recommend is https://jwt.io/ but you are not required to use this site for the project. Choose any library, tool or site you wish to inspect and construct JWT tokens.To earn your flag you must perform the following actions.Hints:The next few flags will require some trial and error and a bit of research on your part to succeed. Your task is to craft JWT tokens such that you can use the token to successfully authenticate and earn your flag.You are a PHP ninja! You can’t get enough of this language. When you learned that others hate it and gave it bad reviews you felt the need to “correct the situation”. You’ve learned of an API that allows you to delete reviews. Muhahahah! The problem is that only the site moderator can do this and you don’t have his credentials. This has not stopped you in the past.To earn your flag you must perform the following actions.Hints:You’ve learned about a new experimental programming language that is TOP SECRET! This language only requires 1 single keyword to find a polynomial time algorithm to solve any NP-hard problem! You want the 1 million dollar reward for solving this problem and thus need access to this programming language. Find the language.To earn your flag you must perform the following actions.Hints:
Distance VectorTable of Contents PROJECT GOAL………………………………………………………………………………………………………………… 2 Part 0: Getting Started………………………………………………………………………………………………….. 2 Part 1: Files Layout……………………………………………………………………………………………………….. 2 Part 2: TODOs………………………………………………………………………………………………………………. 3 Part 3: Testing and Debugging……………………………………………………………………………………….. 4 Part 4: Assumptions and Clarifications……………………………………………………………………………. 4 Part 5: Correct Logs for Provided Topologies……………………………………………………………………. 6 Part 6: Spirit of the Project……………………………………………………………………………………………. 7 Part 7: FAQs…………………………………………………………………………………………………………………. 8 What to Turn In………………………………………………………………………………………………………………. 9 What you can and cannot share………………………………………………………………………………………… 9 Rubric…………………………………………………………………………………………………………………………… 10 In the lectures, you learned about Distance Vector (DV) routing protocols, one of the two classes of routing protocols. DV protocols, such as RIP, use a fully distributed algorithm to find shortest paths by solving the Bellman-Ford equation at each node. In this project, you will develop a distributed Bellman-Ford algorithm and use it to calculate routing paths in a network. This project is similar to the Spanning Tree project, except that we are solving a routing problem, not a switching problem.In “pure” distance vector routing protocols, the hop count (the number of links to be traversed) determines the distance between nodes. Some distance vector routing protocols, that operate at higher levels (like BGP), must make routing decisions based on business valuations. These protocols are sometimes referred to as Path Vector protocols. We will explore this by using weighted links (including negatively weighted links) in our network topologies.We can think of Nodes in this simulation as individual Autonomous Systems (ASes), and the weights on the links as a reflection of the business relationships between ASes. Links are directed, originating at one Node, and terminating at another.You should review some materials on Bellman-Ford. Some resources include:Download and unzip the Project Files for Distance Vector from Canvas in the Assignments section. This project can be completed in the class VM or on your local machine using Python3.10.x. You must be sure that your submission runs properly in Gradescope.The DistanceVector directory contains the following files:There are a few TODOs in DistanceVector.py:To run your algorithm on a specific topology, execute the run.sh bash script:./run.sh *TopoSubstitute the correct, desired filename for *Topo. Don’t use the .txt suffix on the command line. This will execute your implementation of the algorithm in DistanceVector.py on the topology defined in *Topo.txt and log the results (per your logging function) to *Topo.log .NOTE: You should not include the full filename of the topology when executing the run.sh script. For example, to run the algorithm on topo1.txt you should only specify topo1 as the argument to run.sh.For this project, you may create as many topologies as you wish and share them on Ed Discussion. We encourage sharing new topologies with log outputs. Topologies with format errors will get an error back when you try to run them.We’ve included four good topologies for you to use in testing and one bad topology to demonstrate invalid topology. The provided topologies do not cover all the edge cases; your code will be graded against more complex topologies.“advertise” other nodes it can reach (Nodes C and D). (partitioned networks) o topologies that do not require intermediate steps (such as a topology with a single node)Below are the correct final logs for the provided topologies. We are providing them to help you identify correct behavior with respect to negative cycles and the assumptions in the instructions. We are only providing the final round; each topology should produce at least 2 rounds of output. SimpleTopo:A:(A,0) (B,1) (C,3) (D,3) B:(B,0) (A,1) (C,2) (D,2) C:(C,0) (B,2) (A,3) (D,0) D:(D,0) (C,0) (B,2) (A,3) E:(E,0) (D,-1) (C,-1) (B,1) (A,2) SingleLoopTopo:A:(A,0) (D,5) (E,6) (B,6) (C,16) B:(B,0) (A,2) (D,7) (C,10) (E,0) C:(C,0) D:(D,0) (E,1) (B,1) (A,3) (C,11) E:(E,0) (B,0) (A,2) (D,7) (C,10) SimpleNegativeCycle: ComplexTopo:ATT:(ATT,0) (CMCT,-99) (TWC,-99) (GSAT,-8) (UGA,-99) (VONA,-11) (VZ,-3) CMCT:(CMCT,0) (TWC,-99) (ATT,1) (VONA,-10) (GSAT,-7) (UGA,-99) (VZ,-2) DRPA:(DRPA,0) (EGLN,1) (GT,-1) (UC,-1) (CMCT,-99) (TWC,-99) (ATT,13) (OSU,-1) (VONA,2) (GSAT,5) (UGA,-99) (PTGN,1) (VZ,10) EGLN:(EGLN,0) (GT,-2) (UC,-2) (DRPA,1) (CMCT,-99) (OSU,-2) (TWC,-99) (ATT,13) (PTGN,0) (VONA,3) (GSAT,5) (UGA,-99) (VZ,11) GSAT:(GSAT,0) (VONA,-3) (VZ,5) (UGA,-99) (ATT,7) (CMCT,-99) (TWC,-99) GT:(GT,0) (UC,0) (EGLN,2) (OSU,0) (DRPA,3) (PTGN,2) (CMCT,-99) (VONA,5) (TWC,-99) (ATT,15) (VZ,13) (GSAT,7) (UGA,-99) OSU:(OSU,0) (UC,0) (GT,0) (EGLN,2) (PTGN,2) (VONA,5) (DRPA,3) (VZ,13) (GSAT,7) (CMCT,-99) (ATT,15) (UGA,-99) (TWC,-99) PTGN:(PTGN,0) (OSU,-1) (UC,-1) (GT,-1) (EGLN,1) (VONA,3) (VZ,11) (GSAT,5) (DRPA,2) (ATT,13) (UGA,-99) (CMCT,-99) (TWC,-99) TWC:(TWC,0) (CMCT,-99) (ATT,1) (VONA,-10) (VZ,-2) (GSAT,-7) (UGA,-99) UC:(UC,0) (GT,0) (EGLN,2) (OSU,0) (PTGN,2) (DRPA,3) (VONA,5) (CMCT,-99) (VZ,13) (GSAT,7) (TWC,-99) (ATT,15) (UGA,-99) UGA:(UGA,0) (ATT,50) (CMCT,-99) (TWC,-99) (GSAT,42) (VONA,39) (VZ,47) VONA:(VONA,0) (VZ,8) (GSAT,2) (ATT,10) (UGA,-99) (CMCT,-99) (TWC,-99) VZ:(VZ,0) (ATT,2) (CMCT,-99) (TWC,-99) (GSAT,-6) (UGA,-99) (VONA,-9) The goal of this project is to implement a simplified version of a network protocol using a distributed algorithm. This means that your algorithm should be implemented at the network node level. Each network node only knows its internal state, and the information passed to it by its direct neighbors. Declaring global variables will be a violation of the spirit of the project.The skeleton code we provide you runs a simulation of the larger network topology. For simplicity, the Node class defines a link to the overall topology. This means it is possible using the provided code for one Node to access another Node’s internal state. This goes against the spirit of the project and is not permitted. If you have questions about whether your code is accessing data it should not, please ask on Ed Discussion or during office hours!You should not use any global variables for managing any data relating to the Nodes. However, you may use a global variable as a setting. I.E.: NEGATIVE_INFINITY = -99Q: May I import a python module into DistanceVector.py? For example, may I use import collections, typing, etc. A: Your solution should not require any outside Python modules. Please do not import any other modules.Q: What is the best way to format and process node messages? A: There is no right or wrong way to format messages. For best results keep things simple.Q: Is it required that the distance vectors displayed in my log files be alphabetized? A: Look at the finish_round function in Toology.py. Note how the DVs are alphabetized each round, and this is reflected in the provided correct output logs. The nodes within individual vectors are not required to be sorted.Q: Should my solution include an implementation of split horizon? A: That is not a requirement for this project.Q: What if there really is a valid path between two indirectly linked nodes with no cycle and the total cost is -99 or less? To complete this project, submit ONLY your DistanceVector.py file to Gradescope as a single file. Do not modify the name of DistanceVector. You can make an unlimited number of submissions to Gradescope. Your last submission will be your grade unless you activate a different submission. There are some very important guidelines for this file you must follow:Do not share the content of your DistanceVector.py file with your fellow students, on Ed Discussion, or elsewhere publicly. You may share any log files for any topology, and you may also share new topologies. Additionally, code that you write that is not required for turn-in, like testing suites may be shared. It may be a good idea to share a “correct” log for a particular topology, if you have one, when you share the code for that topology.When sharing log files, leave alphabetization on so that your classmates can use the diff tool to see if you are getting the same log outputs as they are.All work must be your own, and consulting Distance Vector Routing solutions, even in another programming language or just for reference, are considered violations of the honor code. Do not reference solutions on Github! Do not use IDE extensions (like Github Copilot) that write or recommend blocks of code to you (autocomplete for function names is fine). For more information see the Syllabus Definition of Plagiarism. We have worked hard to provide you with all the material you need to complete this project without help from Google/Stack Overflow (Searching basic Python syntax is fine). Don’t risk an honor code violation for the project. GRADING NOTE: There is no partial credit for individual topologies; each topology is either “passed” or “failed”.As with previous projects in this course, due to the size of the class, we will not accept resubmissions, modifications to old submissions past the deadline, etc.
BACKGROUND:You’ve been hired by the IPLRA (International Programming Language Review Association) to conduct a security audit for their newly released API. They are excited to finally release an API to the community for developers across the world to leverage. In fact, they see this API as a way to increase their amount of reviews by 800%. The only thing standing in their way is a final audit and approval, by you. Unfortunately, after only 5 minutes of looking at the API, you’ve found issues and need to report them. Your goal is to bring visibility to these vulnerabilities in their API by finding the flags for each scenario. Good luck on your flag hunt and we hope you enjoy learning all about modern web APIs.Note: The IPLRA is not real and we made it up.SETUP:To get set up for the flags, carefully follow the steps below.You will need switch users. Log into the VM with the following user.The username, password and VM location are located on Canvas.Run this at the terminal to start the API$ ./StartContainer.shproject_apisecurity.json is available in the /home/apisec/Desktop folder. Put all flags in this file and submit it as your final deliverable.To access the Web API open Chrome in the VM and navigate to this URL. This is the Swagger documentation page that describes the API and allows for testing: http://localhost:8080/swagger/index.html_*Note: You can also click the “Swagger UI” bookmark in _Chrome******GATECH_ID IS A REQUIRED HEADER******NOTE: This is not the Georgia Tech Username, it is the GTID that you can find usng the steps on the Required ReadingBe very careful! When you copy and paste be sure to strip off all leading spaces or special characters.Submission Details:File submission instructions:This project needs to be submitted via gradescope. Navigate to the course in Canvas, click ‘Gradescope’, click ‘Project API Security’ and submit there.The contents of the submission file should be the following. There is a project_apisecurity.json file in your vm with a template set up, or you can copy-paste this to your newly created project_apisecurity.json file elsewhere and replace the placeholders with the flags you retrieve from each relevant task.Note: You can use TextEdit or Vim to create and edit this file. Do not use LibreOffice or any Word Document editor. It must be in proper JSON format with no special characters in order to pass the autograder and these Word Document editors are likely to introduce special characters.If you can’t find the file in the VM just copy this format below:{“flag1”: “”,“flag2”: “”,“flag3”: “”,“flag4”: “”,“flag5”: “”,“flag6”: “”,“flag7”: “”, “flag8”: “”}An example of what the submitted file content should look like:{“flag1”: “4ec60c3e084d8387f0f33916e9b08b99d5264a486c29130dd4a5a530b958c5c0f1faeaca2ce30b478281ec546a4729f“flag2”: “f496d9514c01e8019cd2bc21edfeb8e33f4a29af14a8bf92f7b3c14b5e06c5c0f1faeaca2ce30b478281ec546a4729f“flag3”: “b621bba0bb535f2f7a222bd32994d3875bcfcad651160c543de0a01dbe2e0c5c0f1faeaca2ce30b478281ec546a4729“flag4”: “f38e2cafb43ab4a0a647a8b08fc97bca25aa7cfb517029d5dd02faf49bff5c5c0f1faeaca2ce30b478281ec546a4729“flag5”: “1711ee5eb85b9020d1f4193ee6d884abd12a2eadc4890d28c490ae0c36446c5c0f1faeaca2ce30b478281ec546a4729“flag6”: “1711ee5eb85b9020d1f4193ee6d884abd12a2eadc4890d28c490ae0c36446c5c0f1faeaca2ce30b478281ec546a4729“flag7”: “1711ee5eb85b9020d1f4193ee6d884abd12a2eadc4890d28c490ae0c36446c5c0f1faeaca2ce30b478281ec546a4729 “flag8”: “f38e2cafb43ab4a0a647a8b08fc97bca25aa7cfb517029d5dd02faf49bff5c5c0f1faeaca2ce30b478281ec546a4729}TABLE OF CONTENTSThis flag will introduce you to basic API functionality using a documentation and test harness tool called Swagger. Swagger is a very popular tool used to develop and test web APIs and has plugins/modules in most programming languages. You can learn more about Swagger here: https://swagger.io/You’ll need to leverage Swagger (or any other http tool you desire such as curl or Postman) to determine how the API is configured and what endpoints to invoke to earn this flag.Warning: The site doesn’t use file storage or a database, all data is stored in memory. If you crash the web API or restart the VM, any data you have created/modified will have been lost and you’ll need to begin at step 1.To earn your flag you must perform the following actions by making API calls.Hints:In order to get this flag you need to create a new reviewer in the system. Unfortunately, the developers locked down this functionality some time ago so you’ll need an auth token in order to perform it. You read in the newspaper last week that Programming Reviews LLC had a big data breach so there is a good chance you can come across some credentials.To earn your flag you must perform the following actions.Hints:https://learning.postman.com/docs/getting-started/introduction/Include your flag2 into the json file and now onto Flag 3! Now that you’ve used an Auth token we’re going to dig a bit deeper into JWT (JSON Web Tokens). This flag is simple and designed only to get you acquainted with how JWTs are constructed. There are numerous resources to help you work with JWTs, one we recommend is https://jwt.io/ but you are not required to use this site for the project. Choose any library, tool or site you wish to inspect and construct JWT tokens.To earn your flag you must perform the following actions.Hints:The next few flags will require some trial and error and a bit of research on your part to succeed. Your task is to craft JWT tokens such that you can use the token to successfully authenticate and earn your flag.You are a PHP ninja! You can’t get enough of this language. When you learned that others hate it and gave it bad reviews you felt the need to “correct the situation”. You’ve learned of an API that allows you to delete reviews. Muhahahah! The problem is that only the site moderator can do this and you don’t have his credentials. This has not stopped you in the past.To earn your flag you must perform the following actions.Hints:You’ve learned about a new experimental programming language that is TOP SECRET! This language only requires 1 single keyword to find a polynomial time algorithm to solve any NP-hard problem! You want the 1 million dollar reward for solving this problem and thus need access to this programming language. Find the language.To earn your flag you must perform the following actions.Hints:
