This final project has the purpose of assessing all learning outcomes in the unit. The learning outcomes are as follows:
1. Explain and apply the process of computational scientific model building, verification and interpretation;
2. Analyse the differences between core classes of modelling approaches (Numerical versus Analytical; Linear versus Non-linear; Continuous versus Discrete; Deterministic versus Stochastic);
3. Evaluate the implications of choosing different modelling approaches;
4. Rationalise the role of simulation and data visualisation in science;
5. Apply all of the above to solving idealisations of real-world problems across various scientific disciplines. Assignment Project Exam Help
What to submit
Follow these procedures to submit this assignment
The assignment must be submitted online via Moodle, and should follow the following procedure:
• All your scripts and reports MUST contain your name and student ID.
– You are free to program the assignment in either MATLAB or Python.
– Your submitted archive must extract to a directory named as your student ID. – This directory should contain all elements of the submission including
∗ The report (in PDF format)
∗ The source code for the model and analysis, appropriately documented with comments.
∗ The video of your presentation in MP4 format ∗ The slides used for your presentation in PDF format
• Submit your zipped file electronically via Moodle.
Task description
To demonstrate all learning outcomes, you will develop an extension of a model discussed in the classroom. An extension addresses the same problem, but adds or relaxes specific assumptions about the model. For example, taking a deterministic model and introducing assumptions to do a stochastic analysis, or providing stochastic analysis for a simulation.
• Gillespie
• Markov chains
• Montecarlo simulation
• Heuristics
• Game theory
Your extension should address two different modelling questions, and use the algorithms, techniques and visualisations discussed in the clasroom to answer those questions. Assignment Project Exam Help
Submission structure
Report structure
Fill the following table.
Base model One sentence description of the base model
Extension assumptions One paragraph description on how assumptions are modified and the nature of the extension
Techniques showcased Technique 1. Technique 2.
Modelling question 1 Questions being addressed.
Modelling question 2
Important: This table should be briefly discussed and signed by your demonstrator on week 11 and week 12, during the lab session – not via email or forum post, please plan accordingly.
Section 2: Introduction
• Learning outcomes 1, 5. 10% of project final mark
• Identify the problem you want to solve and its motivation, describe what the extension will be and identify questions your model will answer. In other words, this section takes the information in the specification table and develops it providing more detail and a motivation of your questions, and how your techniques are appropriate.
• Write clearly. Your mark is based on what we can understand so spend time crafting the text.
Section 3: Model description
• Learning outcomes 1, 2, 5. 35% of project final mark
• Be clear and help the reader as much as you can.
Section 4: ResultsAssignment Project Exam Help
• Learning outcomes 2, 3, 4, 5. 35% of project final mark
• Be clear and help the reader as much as you can.
Section 5: List of algorithms and concepts
• Learning outcomes 2, 5. 5% of project final mark
• List of algorithms and concepts used in the unit that play a role in your model and interpretation.
Video presentation
You should submit a presentation where you discuss your extended model. The presentation should be no longer that 10 minutes, and use slides to enhance the description of the model and the explanation of your results. It is suggested the presentation keep a similar structure to that of the report. The presentation is worth 15% of project final mark.
A simple procedure to record the presentation using zoom can be found here: https://www.youtube.
com/watch?v=P6cTbnUPwfY
Source code
All code should be submitted and appropriately commented. It will be checked for correctness and be part of the marking in the model section (if the code is used to produce results, or in the results section if the code is used to analyze results). Clarity is in your best interest.
You can use any of the standard libraries we used in the class as long as you can explain what the library is doing.
Feedback opportunities
• Workshop 1 of week 9 will discuss the project task and provide examples. There will be no pre-workshop video, use the time to start thinking about what you want to do.
• Week 10’s applied: You are welcome to have a very brief discussion of topic with lab demonstrator – they can provide simple advise con how to fine tune your question or idea.
• Week 11’s applied: Present a draft of the specification table to your demonstrator and explain what you expect in terms of results.
• Week 12’s applied: Discuss your progress with your demonstrator.
