Faculty of Technology – Course work Specification 2015/16 Module name: Applied Computational Intelligence Module code: IMAT5234 Title of the Assignment: IMAT5234 assessment specifications This coursework item is: (delete as appropriate) Summative This summative coursework will be marked anonymously No The learning outcomes that are assessed by this coursework are: 1. Understanding of the process of modelling for practical problems 2. Understanding of CI techniques in an application area by developing a novel solution for a given topic or student’s own proposed application 3. Practice research skills, in terms of developing appropriate methods, evaluation and experimental design 4. Practice academic writing by writing an article on own proposed application with possibility of submission to a conference This coursework is: (delete as appropriate) Individual This coursework constitutes 80% to the overall module mark. Date Set: Jan 30 2016 Date & Time Due: Part 2: Report – Sunday 21st May, 23:59 Presentations – 4th and 11th May. Refer to remainder of document for more details. Your marked coursework and feedback will be available to you on: If for any reason this is not forthcoming by the due date your module leader will let you know why and when it can be expected. The Head of Studies ([email protected] ) should be informed of any issues relating to the return of marked coursework and feedback. Note that you should normally receive feedback on your coursework by no later than four working weeks after the formal hand-in date, provided that you met the submission deadline. Report: Friday 16th June When completed you are required to submit your coursework to: 1. Blackboard Late submission of coursework policy: Late submissions will be processed in accordance with current University regulations which state: “the time period during which a student may submit a piece of work late without authorisation and have the work capped at 40% [50% at PG level] if passed is 14 calendar days. Work submitted unauthorised more than 14 calendar days after the original submission date will receive a mark of 0%. These regulations apply to a student’s first attempt at coursework. Work submitted late without authorisation which constitutes reassessment of a previously failed piece of coursework will always receive a mark of 0%.” Academic Offences and Bad Academic Practices: These include plagiarism, cheating, collusion, copying work and reuse of your own work, poor referencing or the passing off of somebody else's ideas as your own. If you are in any doubt about what constitutes an academic offence or bad academic practice you must check with your tutor. Further information and details of how DSU can support you, if needed, is available at: http://www.dmu.ac.uk/dmu-students/the-student-gateway/academic-support-office/academic-offences.aspx and http://www.dmu.ac.uk/dmu-students/the-student-gateway/academic-support-office/bad-academic-practice.aspx Tasks to be undertaken: • Report for a mini-project on applications of CI: this mini project aims to take you through steps of modelling of an application and implementation of CI algorithms to solve it. Some students use this mini project for a proof of concept for their final MSc project but several problems and topics will also be provided for those one of you who may not have thought of a topic yet. Ideally the solution developed within this project will have a new contribution and could be published as a conference paper (ideal but not compulsory). The final report will form 60% of the total mark of the module. Your own ideas for this project should be checked before you begin your work on this assignment. Please send an email with a paragraph for each idea describing your proposed assignment work to [email protected]. You can also discuss your ideas with me by email, in the lab, by Skype (my skype username is: samadahmadi) or group discussions pages on blackboard. You will carry out investigative work into the chosen area, this should include the following activities: o A critical review of associated literature to be included in your report. o Either a practical implementation to illustrate some feature of an application area or appropriate experimental work to support an investigation on existing data/research. This could take the form of either:  practical work (if for example you base your study in the area of Robotics or Expert Systems etc.) OR  it may be more experimental: trying a new application area with existing CI algorithms; 1. Presentation: This is a 20 minutes presentation (including 5 minutes for questions and 5 minutes of demo, if relevant) to your tutor and other students in the classroom face-to-face or on Skype (For distance students who cannot present their work within the normal hours of the lecture/lab sessions on skype, an alternative time that fits with their work schedules will be arranged. Presentations use powerpoint or pdf or other formats and will form 20% of your total mark. Presentations should clearly introduce: the presenter and the topic of research, problem definition, summary of existing literature and tools, proposed solution, methodology, experimental design, data collection, experimental results, conclusions and future work and references. This could be slightly different for different topics. Deliverables to be submitted for assessment: 1. Prepare a presentation (worth 20% of overall mark) 2. Write a report (worth 60% of overall mark) that includes: o A critical review of the associated literature o A description of the planned research, methodology and evaluation methods o A description of the activities undertaken (e.g. any implementation &/or design of experiments) o The findings of the work o Conclusions and further work The report and all the code and data must be submitted electronically using the link on Blackboard and the report also submitted using Turnitin. The length of the report should be not less than 14 pages in IEEE conferences template format including references (please do not submit until your report is within this range and in the correct format). We require you to use a standard template for your report and have selected that of the IEEE conferences. The templates are in MS word or Latex and can be acquired from: http://www.ieee.org/web/publications/pubservices/confpub/AuthorTools/conferenceTemplates.html o This will also make the transition from your report to a possible conference paper easier (in case of enough contributions to knowledge). o The report forms 60% of your overall grade for this module. How the work will be marked: All assignments will be marked by the module leader and a percentage of failed and highest marks will be moderated. Module leader/tutor name: Samad Ahmadi Contact details: [email protected] Appendix 1 – below are some ideas and examples from previous years for your final report. You are not restricted to choosing from these topics and if you have an idea of your own that is usually preferable. Examples from previous years: • Mathematical modelling of problems from work or our daily lives: o Optimisation of a Stagger Chart for Aviation Fleet Planning • Applications of CI in image recognition o Adaptive Differential Evolution Applied to Point Matching 2D GIS Data o Fast Handwritten Digit Recognition with Multilayer Ensemble Extreme Learning Machine • Data mining and text mining: o Semantic Analysis for Document Similarity and Search Queries • Applications of AI in video games o Learning from User Experience in Games o Reactive control of Ms. Pac Man using information retrieval based on genetic programming o A GCSE maths tutoring game using neural networks o Training a Multi Layer Perceptron with Expert Data and Game State Representation using Convolutional Neural Networks • Applications of games technologies such as KINECT e.g. in assisted living, computer • vision • Search algorithms in optimization problems • Clustering algorithms • The Loebner Prize - http://www.loebner.net/Prizef/loebner-prize.html • Practical applications of AI algorithms for data mining: examples in credit agencies, • Security: e.g. Intrusion detection using CI algorithms and data mining • Philosophy of AI – e.g. consciousness, ethics etc. • Applications of AI in finance or business – Refer to the Artificial Intelligence Handbook • AI and music (or AI and the arts) • Applications in bio-informatics – e.g. Protein Folding, • Security/Military applications Name.................................................... Marking Scheme for Student Seminars – worth 20% of overall mark (Marks in red italics are for those who started the course before Sept 2010) 0 – 44% (0-34%) Fail 45-49% (35-40%) Marginal Fail 50-54% (40-49%) Pass 55-59% (50-59%) Pass 60-69% (same) Merit >70% (same) Distinction Structure. Evidence of preparation: quality of supporting materials (e.g. slides/ handouts) Poorly structured. Little or no evidence of preparation. Poor delivery & poor or no supporting materials. Weak structure. Only limited evidence of any preparation. Satisfactory approach to structure and some evidence of appropriate preparation. Well structured and prepared, but with some limitations. Very well structured and prepared. Some minor limitations. Highly professional approach. Excellent supporting materials. Very minor or no limitations Content Little or no real content. Very poor standard. Some relevant information provided but generally weak in terms of content. Satisfactory level of content but lacking in depth. A good attempt to research the area and evidence of a fair understandi ng of the associated issues. Some limitations. Very good content. Very well researched and evidence of good understanding . Some minor limitations. Evidence of thorough research into subject area. Expressed in a way that show a sound understanding of the area and associated issues. Very minor or no limitations. Handling of questions Unable to answer questions appropriately. Some attempt to answer questions but answers generally unsatisfactory. Satisfactory attempt to answer questions. Fair attempt at handling questions and any associated discussion. Questions generally handled very well and very good ability to discuss the area. Excellent answers provided to all or almost all questions. Able to discuss area with authority. Marking scheme for essay/report – worth 60% of overall mark (Marks in red italics are for those who started the course before Sept 2010) 0 – 44% (0-34%) Fail 45-49% (35-40%) Marginal Fail 50-54% (40-49%) Pass 55-59% (50-59%) Pass 60-69% (same) Merit >70% (same) Distinction Coverage of area, including background, planning, literature review. Not acceptable Some attempt to cover the area but with serious limitations. Brief with significant limitations. Good coverage, but with some notable limitations. Very good coverage of area and associated issues with good review of literature. Excellent coverage, showing a sound understanding of topic. Excellent critical review of literature. Ready for publication Practical (e.g. implementation or experimental work) Very little of value Weak, with substantial limitations. Some effort evident. Satisfactory amount of work. Significant limitations in design & documentation. Good work, with some limitations. Very good work, very good documentation and design. Only minor limitations Challenging work, well documented, well designed, enough contribution for conference publication Conclusions, recommendations, critical evaluation, new ideas, etc. Missing or poor or not meaningful A minimal attempt with serious limitations. Not acceptable. Satisfactory but with significant limitations. Good, but with some notable limitations. Lacks depth. Very good, comprehensive, with good ideas. Excellent, follows logically from body of report and contains excellent and original ideas. Structure and presentation. References, bibliography. No clear structure, and presentation very weak. Poor or no bibliography, reference list, citations in report. Weak structure poor presentation. Poor bibliography, reference list, citations in report. Satisfactory approach to structure and presentation. List of references present but with significant limitations. Well structured and presentation good. Most references in correct format from both web and traditional sources. Very well structured but not in full conference template, still some grammatical and spelling problems Presented in the relevant conference template, appropriate lenths of sections with main stress on contribution sections