Module Details Module Details

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CMPSMB17 - Information Systems Issues

Module Code:
CMPSMB17
Department:
CMP
Academic Year:
2015 - 16
Credit Value:
20
Levels:
Level M
Module Organiser:
Dr. Dan Smith

Overview

This module explores basic information systems development and considers the stages and tools used in the traditional lifecycle approach. Although the main focus will be on describing the various methods used in contemporary development, time will also be spent looking at wider topics vital to the successful completion and implementation of information systems, such as stakeholder participation, prototyping and evaluation. The lecture course will be complemented by an individual project to explore an aspect of information systems development.


Module Objectives

Module specific:

  • To introduce students to the concept of the systems development lifecycle and its many activities.
  • To introduce and compare the traditional structured and object oriented approaches to information systems development.
  • To gain understanding of and experience with various structured and OO analysis and design techniques and tools.
  • A good understanding of selected aspects of information systems development.

Transferable skills:

  • Basic experience of the decompositional analysis approach to complex problem solving.
  • Experience with various structured and OO analysis and design techniques.
  • Knowledge of the critical factors in information systems development.
  • Additional experience of understanding, analysing and summarising a body of new material.

A basic understanding of the concept of information systems development and the importance of undertaking the early activities such as feasibility, fact finding and analysis before moving to design.

 


Learning Outcomes

On completion of this module, students should be able to:

  • Describe the ways in which organisations use information and what sources may be used and how the quality of that information may be assessed,
  • Understand the activities of the systems development lifecycle, structured and OO approaches to systems development at a general level,
  • Evaluate the feasibility of proposed systems,
  • Analyse the data flows and processes of an existing information system and use this knowledge to describe and document the results of this analysis.


Teaching and Assessment

Teaching Approach

This module is delivered as a programme of lectures, supported by workshops and laboratory classes. Reading, workshop preparation and laboratory preparation time is required in addition to formal contact hours.

Total hours: 22

Lectures: 11; Hours: 11, Indicicative content (with provisional weekly schedule)

  1. Introduction, information, systems and information systems.
  2. The early stages of the systems development life cycle. Feasibility
  3. Investigation and Requirements Elicitation, Stakeholder Participation.
  4. The SDLC; introduction to top-down decomposition. Rich Pictures
  5. Data flow modelling
  6. Process specifications, UML, use cases
  7. Reading week
  8. Entity Relationship diagrams
  9. Class diagrams.  Structure charts.
  10. Human computer interaction.
  11. The latter stages of the systems development lifecycle. Alternative approaches.
  12. Evaluation.  Maintenance.

Workshops: 12; Hours: 12, Indicative content (with provisional weekly schedule)

  1. Introduction
  2. Feasibility studies
  3. Investigations
  4. Rich Pictures
  5. Data Flow Modelling
  6. UML
  7. Reading week
  8. ERD modelling
  9. Class Diagrams
  10. HCI
  11. Implementation
  12. Evaluation

Laboratory Work: 0 hours

 

Methods of Assessment

Coursework and Project


Resources

Teaching Resources:

Lecture notes and other resources for the module will be available on Blackboard.

Library Resources:

The main library catalogue currently lists over 600 items on Information Systems,  Analysis and Design and Database systems by various authors.

Required text:

Satzinger J. W. (2008) Systems Analysis in a Changing World, ISBN 0324593775(This text is excellent for a slightly more in-depth look at the 'harder' end of systems analysis and design,  i.e. it is excellent for a comparison of the structured and OO approaches, with numerous examples of each.)


Conventions and Standards

Submission:

Written coursework should be submitted by following the standard CMP practice. Students are advised to refer to the Guidelines and Hints on Written Work in CMP.

Deadlines:

If coursework is handed in after the deadline day or an agreed extension:

 

Work submitted Marks deducted
After 15:00 on the due date and before 15:00 on the day following the due date 10 marks
After 15:00 on the second day after the due date and before 15:00 on the third day after the due date 20 marks
After 15:00 on the third day after the due date and before 15:00 on the 20th day after the due date.  All the marks the work merits if submitted on time (ie no marks awarded) 
After 20 working days Work will not be marked and a mark of zero will be entered


Saturdays and Sundays will NOT be taken into account for the purposes of calculation of marks deducted.

All extension requests will be managed through the LTS Hub. A request for an extension to a deadline for the submission of work for assessment should be submitted by the student to the appropriate Learning and Teaching Service Hub, prior to the deadline, on a University Extension Request Form accompanied by appropriate evidence. Extension requests will be considered by the appropriate Learning and Teaching Service Manager in those instances where (a) acceptable extenuating circumstances exist and (b) the request is submitted before the deadline. All other cases will be considered by a Coursework Coordinator in CMP.

For more details, including how to apply for an extension due to extenuating circumstances download Submission for Work Assessment (PDF, 39KB)
 

Plagiarism:

Plagiarism is the copying or close paraphrasing of published or unpublished work, including the work of another student; without due acknowledgement. Plagiarism is regarded a serious offence by the University, and all cases will be reported to the Plagiarism Officer. Details from UEA's Policy on Plagiarism and Collusion.

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CMPSMA2Y - Directed Study

Module Code:
CMPSMA2Y
Department:
CMP
Academic Year:
2015 - 16
Credit Value:
20
Levels:
Level M
Module Organiser:
Dr. Beatriz De La Iglesia

Overview

The objective of this module is to give students an opportunity to study an area of computing science, that they would not otherwise be able to study, through a programme of individual study and directed reading. STUDENTS CANNOT REGISTER FOR THIS MODULE UNTIL THEY HAVE AGREED A TOPIC AND SUPERVISOR WITH THE MODULE ORGANISER.


Module Objectives

  • To gain a critical understanding of the state of the art and current research issues in a research field in computing
  • To collate and present research level material in a coherent manner

Transferable skills:

  • Collating advanced technical material
  • Presentation of advanced material
  • Ability to understand research level material
  • Technical writing and referencing
  • Improved skills in reading, assimilating and summarising computing research and survey papers and other literature
  • Additional experience of writing survey reports that adhere to the conventions for good technical writing in English

 


Learning Outcomes

Subject specific:

State-of-the-art knowledge of a specialised topic or emerging area of computing science.


Teaching and Assessment

Teaching Approach

Total hours: usually 10 group supervisions of one hour each plus about 5 hours of seminars and lectures, as appropriate.

Tutorial meetings with your supervisor are arranged at mutually convenient times.

You are expected to attend and participate in relevant research group and School seminars which are advertised from time to time.


 

Methods of Assessment

Setting of coursework:

The assessment details will be agreed by week 2 of the semester and all coursework assessment will be due in week 12.


Resources

Teaching Resources:

Tutorials

Library Resources:

Course texts:

Supplied by your individual or group supervisor.


Conventions and Standards

Submission:

Written coursework should be submitted by following the standard CMP practice. Students are advised to refer to the Guidelines and Hints on Written Work in CMP.

Deadlines:

If coursework is handed in after the deadline day or an agreed extension:

 

Work submitted Marks deducted
After 15:00 on the due date and before 15:00 on the day following the due date 10 marks
After 15:00 on the second day after the due date and before 15:00 on the third day after the due date 20 marks
After 15:00 on the third day after the due date and before 15:00 on the 20th day after the due date.  All the marks the work merits if submitted on time (ie no marks awarded) 
After 20 working days Work will not be marked and a mark of zero will be entered


Saturdays and Sundays will NOT be taken into account for the purposes of calculation of marks deducted.

All extension requests will be managed through the LTS Hub. A request for an extension to a deadline for the submission of work for assessment should be submitted by the student to the appropriate Learning and Teaching Service Hub, prior to the deadline, on a University Extension Request Form accompanied by appropriate evidence. Extension requests will be considered by the appropriate Learning and Teaching Service Manager in those instances where (a) acceptable extenuating circumstances exist and (b) the request is submitted before the deadline. All other cases will be considered by a Coursework Coordinator in CMP.

For more details, including how to apply for an extension due to extenuating circumstances download Submission for Work Assessment (PDF, 39KB)
 

Plagiarism:

Plagiarism is the copying or close paraphrasing of published or unpublished work, including the work of another student; without due acknowledgement. Plagiarism is regarded a serious offence by the University, and all cases will be reported to the Plagiarism Officer. Details from UEA's Policy on Plagiarism and Collusion.

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CMPS3P6Y - Statistics Project

Module Code:
CMPS3P6Y
Department:
CMP
Academic Year:
2014 - 15
Credit Value:
20
Levels:
Level 3
Module Organiser:
Dr. Pierre Chardaire

Overview

Major objectives of this module are to enable students to gain experience of independent project work from a technical and an organisational standpoint, to help students develop oral and written communication skills, to familiarise students with research resources and practices common in statistics, and to introduce students to activities that are similar to those that they are likely to encounter in their careers. Each student will be allocated to a supervisor who will offer technical guidance and will advise on presentation of the assessed work.


Conventions and Standards

Submission:

Written coursework should be submitted by following the standard CMP practice. Students are advised to refer to the Guidelines and Hints on Written Work in CMP.

Deadlines:

If coursework is handed in after the deadline day or an agreed extension:

 

Work submitted Marks deducted
After 15:00 on the due date and before 15:00 on the day following the due date 10 marks
After 15:00 on the second day after the due date and before 15:00 on the third day after the due date 20 marks
After 15:00 on the third day after the due date and before 15:00 on the 20th day after the due date.  All the marks the work merits if submitted on time (ie no marks awarded) 
After 20 working days Work will not be marked and a mark of zero will be entered


Saturdays and Sundays will NOT be taken into account for the purposes of calculation of marks deducted.

All extension requests will be managed through the LTS Hub. A request for an extension to a deadline for the submission of work for assessment should be submitted by the student to the appropriate Learning and Teaching Service Hub, prior to the deadline, on a University Extension Request Form accompanied by appropriate evidence. Extension requests will be considered by the appropriate Learning and Teaching Service Manager in those instances where (a) acceptable extenuating circumstances exist and (b) the request is submitted before the deadline. All other cases will be considered by a Coursework Coordinator in CMP.

For more details, including how to apply for an extension due to extenuating circumstances download Submission for Work Assessment (PDF, 39KB)
 

Plagiarism:

Plagiarism is the copying or close paraphrasing of published or unpublished work, including the work of another student; without due acknowledgement. Plagiarism is regarded a serious offence by the University, and all cases will be reported to the Plagiarism Officer. Details from UEA's Policy on Plagiarism and Collusion.

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CMPE3I07 - Sound and Image 2

Module Code:
CMPE3I07
Department:
CMP
Academic Year:
2014 - 15
Credit Value:
20
Levels:
Level 3
Module Organiser:
Dr. Ben Milner

Overview

This module continues the exploration of computer processing of sound and image signals begun in Sound and Image I. In the sound component, we focus on speech processing, a technology that has already had a huge impact and holds great promise for the future. We cover: 1) speech-coding, which enables us to understand how one of the most significant technologies of recent times (the mobile telephone) is able to transmit speech at a low data-rate; 2) speech recognition, which is now becoming commonplace in interactive voice systems; and 3) speech synthesis. In the "image" component, we focus on the analysis of image signals and learn how to apply advanced filtering and enhancement techniques to images to restore them, and the basics of computer vision systems. These concepts are re-enforced with practical coursework, which gives students hands-on experience of processing audio and video signals.


Module Objectives

Module specific:

  • Understanding of the effects of a sampled representation of a continuous signal
  • Knowledge of the processes involved in speech production and the fundamentals of articulatory and acoustic phonetics
  • Understanding and analysis of the source-filter model of speech production and how it is applied in speech coding
  • An overview of the processes involved in speech recognition, appreciation of the problems that underlie each and an appreciation of how stochastic modelling can be used
  • Appreciation of the different approaches to speech synthesis and the advantages and disadvantages of each
  • Understanding of signal representation in the frequency domain
  • Understanding of frequency domain analysis for multi-dimensional signal
  • Understanding of image filtering techniques
  • Understanding of the differences between enhancement methods and restoration methods
  • Understanding of frequency domain techniques for image restoration
 

Transferable skills:

  • Enhanced MATLAB programming skills
  • Skills in the manipulation of sound and image files
  • Enhanced problem-solving skills
  • Increased knowledge and appreciation of speech and language


Learning Outcomes

Subject specific:

  • In-depth understanding of DSP and its application
  • Ability to design discrete-time filters and process signals with them
  • Ability to use DSP techniques to process audio and video signals for use in audio and video coding and recognition systems
  • Understanding of the important areas in image and speech technology and of the research issues in them


Teaching and Assessment

Teaching Approach

Total hours: 49

Lectures:  22, hours: 1, Content (with provisional weekly schedule)

  1. Introduction to module; Introduction to the speech signal
  2. Source/filter model of speech production I 
  3. Source/filter model of speech production II 
  4. Speech recognition: the front end 
  5. Speech recognition: stochastic methods and search methods 
  6. Speech recognition; acoustic and language modelling 
  7. Speech synthesis I 
  8. Speech synthesis II 
  9. Speech dialogue systems 
  10. Speech Coding
  11. Vectors and Review of Complex Numbers
  12. Complex Exponential Representation of Signals
  13. Complex Fourier Series
  14. Introduction to the DFT
  15. Frequency Domain Filtering
  16. Frequency Domain Filter Design
  17. Image Restoration
  18. Wiener Filtering
  19. Audiovisual Speech
  20. Audiovisual Speech Synthesis
  21. Revision I
  22. Revision II


Workshops: 10, hours: 15, Content (with provisional weekly schedule)

  1. Assignment I briefing 
  2. Speech coding 
  3. Speech recognition I 
  4. Speech recognition II
  5. Speech synthesis
  6. Complex Exponentials
  7. Discrete Fourier Transforms 
  8. Assignment II Briefing 
  9. Frequency Domain Filtering
  10. Filter Design

Laboratory Work: 12, hours: 12, Content (with provisional weekly schedule)

  1. Front-end speech processing 
  2. Speech Coding 
  3. Vowel recognition
  4. Image processing 1 
  5. Introduction to the DFT
  6. Image Restoration

Methods of Assessment

Coursework


Resources

In lectures, handouts will be distributed for material that is difficult or lengthy to copy from the board e.g. derivations of formulae. These handouts will be available on Blackboard. However, the handouts are not comprehensive, and students are expected to make their own notes from lecturers' notes on the board. In workshops, students will be expected to tackle problems individually but with help available from the seminar leader and one other teacher. For some workshops, the class will read sections of a textbook beforehand and then analyse the material in the workshop. Laboratory work (MATLAB programming) will take place during time-tabled laboratory periods using networked personal computers. CMP teaching laboratories running MATLAB are available to CMP students during term time outside time-tabled teaching hours.

Library Resources

Required purchases

  • W. and J. Holmes, Speech Synthesis and Recognition,CRC
  • R. Gonzalez, and R. Woods, Digital Image Processing Prentice Hall

Possible alternative purchases:

Gonzalez, R. and Woods,R., Digital Image Processing Prentice Hall,


Conventions and Standards

Submission:

Written coursework should be submitted by following the standard CMP practice. Students are advised to refer to the Guidelines and Hints on Written Work in CMP.

Deadlines:

If coursework is handed in after the deadline day or an agreed extension:

 

Work submitted Marks deducted
After 15:00 on the due date and before 15:00 on the day following the due date 10 marks
After 15:00 on the second day after the due date and before 15:00 on the third day after the due date 20 marks
After 15:00 on the third day after the due date and before 15:00 on the 20th day after the due date.  All the marks the work merits if submitted on time (ie no marks awarded) 
After 20 working days Work will not be marked and a mark of zero will be entered


Saturdays and Sundays will NOT be taken into account for the purposes of calculation of marks deducted.

All extension requests will be managed through the LTS Hub. A request for an extension to a deadline for the submission of work for assessment should be submitted by the student to the appropriate Learning and Teaching Service Hub, prior to the deadline, on a University Extension Request Form accompanied by appropriate evidence. Extension requests will be considered by the appropriate Learning and Teaching Service Manager in those instances where (a) acceptable extenuating circumstances exist and (b) the request is submitted before the deadline. All other cases will be considered by a Coursework Coordinator in CMP.

For more details, including how to apply for an extension due to extenuating circumstances download Submission for Work Assessment (PDF, 39KB)
 

Plagiarism:

Plagiarism is the copying or close paraphrasing of published or unpublished work, including the work of another student; without due acknowledgement. Plagiarism is regarded a serious offence by the University, and all cases will be reported to the Plagiarism Officer. Details from UEA's Policy on Plagiarism and Collusion.

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CMPE3D01 - Embedded Systems

Module Code:
CMPE3D01
Department:
CMP
Academic Year:
2014 - 15
Credit Value:
20
Levels:
Level 3
Module Organiser:
Dr. Mark Fisher

Overview

Embedded processors are at the core of a huge range of products e.g. mobile telephones, cameras, passenger cars, washing machines, DVD players, medical equipment, etc. The embedded market is currently estimated to be worth around 100x the 'desktop' market and is projected to grow exponentially over the next decade. This module builds on the material delivered in CMPC2M09 to consider the design and development of real-time embedded system applications for commercial off the shelf (COTS) processors running real-time operating systems (RTOS) such as eLinux.


Module Objectives

Module specific:

  • To review of data-path and instruction-set architecture of modern RISC processors.
  • To describe in detail the MIPS and ARM processor architecture.
  • To investigate programming techniques for embedded systems.
  • Design, construct and analyse a small, concurrent, reactive real-time embedded system
  • Critically evaluate the requirements for embedded RTOS.
  • Review the structure of a RTOS and examine a number of industry standard systems
  • Investigate the role of open source embedded solutions (e.g. eLinux)
  • Introduce techniques for hardware interface and network services                                             

Transferable skills:

  • Ability to manage detail and think logically.


Learning Outcomes

Subject specific:

  • Knowledge of the architecture and performance of RISC processors.
  • Knowledge of instruction formats and representations for the ARM processor.
  • Write assembly language programs for the ARM processor
  • Be competent in basic use of C for programming embedded systems.
  • Understand the role of development platforms and cross compilers in the development chain.
  • Design and implement a small concurrent real-time embedded system (e.g. Washing Machine controller)
  • Describe requirements for RTOS in Embedded applications
  • Understand structure of Embedded RTOS
  • Describe methods for process synchronisation and communication.
  • Appreciate issues of real-time scheduling.
  • Install and configure an eLinux kernel


Teaching and Assessment

Teaching Approach

Concepts will be introduced during lectures but the majority of learning outcomes will be addressed through practical laboratories using the ARM 7 SDK and RealView Development Suite (or an equivalent SDK/IDE).

Download weekly lectures, seminars, laboratory work, assignments, etc.

Total hours: 20 

Lectures: 10, hours: 2, Content (with provisional weekly schedule)

  1. Week 1 Introduction to Embeded Systems 
  2. Week 2 A short course on C: Part 1 
  3. Week 3 A short course on C: Part 2 
  4. Week 4 Assembly Language Programming 
  5. Week 5 General Purpose Input/Output 
  6. Week 6 USART
  7. Week 8 Real Time Systems 1 
  8. Week 9 Real Time Systems 2 
  9. Week 10 Scheduling Theory 
  10. Week 11 Interrupts 

Laboratory: 5, hours: 2, Content (with provisional weekly schedule)

  1. Getting Started with ARM 7 SDK and RealView Development Environment 
  2. Assembly language programming  
  3. Interfacing with peripherals: handling interrupts and exception 
  4. Downloading and installing a Linux kernel  
  5. Building a root file system for a target board  
  6. Design project

Methods of Assessment

This module is assessed by examination (60%) and coursework (40%). The coursework takes the form of a mini project: Mini Project: E.g. Design and implementation of washing machine controller: 80% weighting

Setting of coursework:

Coursework will be posted on Blackboard  in week 2 and week 4. Blackboard managed tests go live immediately after the lecture and remain available for one week only. Questions must be answered within 1 hour - only one attempt is permitted.


Resources

Teaching Resources

The library catalogue currently lists 43 records on Embedded Systems. A wide range of resources are also available via ARMs University Program website: http://www.arm.com/community/university 

Course texts:

Required Purchases

  1. Furber,S., (2000) ARM System-on-Chip Architecture, Pearson Education Ltd. . ISBN-13: 978-0-201-67519-1 
  2. Yaghmour,K. (2003) Building Embedded Linux Systems, O'Reilly

Possible Alternative Purchases 

  1. Catsoulis,J.(2003) Designing Embedded Hardware, O'Reilly, , ISBN 0-596-00362-5.  
  2. Heath,S., (2003) Embedded Systems Design, Newnes, . ISBN 0 7605 5546 1.  
  3. Rusling,D., The Linux Kernel, available at: http://www.linuxhq.com/guides/TLK/tlk.html (last accessed: 19.11.09)  
  4. Corbet,J., (2005) Alessandro Rubini and Greg Kroah-Hartman, Linux Device Drivers, O'Reilly


Conventions and Standards

Submission:

Written coursework should be submitted by following the standard CMP practice. Students are advised to refer to the Guidelines and Hints on Written Work in CMP.

Deadlines:

If coursework is handed in after the deadline day or an agreed extension:

 

Work submitted Marks deducted
After 15:00 on the due date and before 15:00 on the day following the due date 10 marks
After 15:00 on the second day after the due date and before 15:00 on the third day after the due date 20 marks
After 15:00 on the third day after the due date and before 15:00 on the 20th day after the due date.  All the marks the work merits if submitted on time (ie no marks awarded) 
After 20 working days Work will not be marked and a mark of zero will be entered


Saturdays and Sundays will NOT be taken into account for the purposes of calculation of marks deducted.

All extension requests will be managed through the LTS Hub. A request for an extension to a deadline for the submission of work for assessment should be submitted by the student to the appropriate Learning and Teaching Service Hub, prior to the deadline, on a University Extension Request Form accompanied by appropriate evidence. Extension requests will be considered by the appropriate Learning and Teaching Service Manager in those instances where (a) acceptable extenuating circumstances exist and (b) the request is submitted before the deadline. All other cases will be considered by a Coursework Coordinator in CMP.

For more details, including how to apply for an extension due to extenuating circumstances download Submission for Work Assessment (PDF, 39KB)
 

Plagiarism:

Plagiarism is the copying or close paraphrasing of published or unpublished work, including the work of another student; without due acknowledgement. Plagiarism is regarded a serious offence by the University, and all cases will be reported to the Plagiarism Officer. Details from UEA's Policy on Plagiarism and Collusion.

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CMPC3Z12 - Directed Study 2

Module Code:
CMPC3Z12
Department:
CMP
Academic Year:
2014 - 15
Credit Value:
10
Levels:
Level 3
Module Organiser:
Dr. Rudy Lapeer

Overview

This Spring Semester directed studies module offers 10 credits as part of the coursework of any 20 credit Spring Semester CMP module available in Options A and B range of the third year of the Computing Science, Imaging and Multimedia course. CMPC3Z12 is a 'proxy' module to allow students to 'even up' credits when taking a 30 credit FTM module.


Conventions and Standards

Submission:

Written coursework should be submitted by following the standard CMP practice. Students are advised to refer to the Guidelines and Hints on Written Work in CMP.

Deadlines:

If coursework is handed in after the deadline day or an agreed extension:

 

Work submitted Marks deducted
After 15:00 on the due date and before 15:00 on the day following the due date 10 marks
After 15:00 on the second day after the due date and before 15:00 on the third day after the due date 20 marks
After 15:00 on the third day after the due date and before 15:00 on the 20th day after the due date.  All the marks the work merits if submitted on time (ie no marks awarded) 
After 20 working days Work will not be marked and a mark of zero will be entered


Saturdays and Sundays will NOT be taken into account for the purposes of calculation of marks deducted.

All extension requests will be managed through the LTS Hub. A request for an extension to a deadline for the submission of work for assessment should be submitted by the student to the appropriate Learning and Teaching Service Hub, prior to the deadline, on a University Extension Request Form accompanied by appropriate evidence. Extension requests will be considered by the appropriate Learning and Teaching Service Manager in those instances where (a) acceptable extenuating circumstances exist and (b) the request is submitted before the deadline. All other cases will be considered by a Coursework Coordinator in CMP.

For more details, including how to apply for an extension due to extenuating circumstances download Submission for Work Assessment (PDF, 39KB)
 

Plagiarism:

Plagiarism is the copying or close paraphrasing of published or unpublished work, including the work of another student; without due acknowledgement. Plagiarism is regarded a serious offence by the University, and all cases will be reported to the Plagiarism Officer. Details from UEA's Policy on Plagiarism and Collusion.

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CMPC3Z11 - Directed Study 1

Module Code:
CMPC3Z11
Department:
CMP
Academic Year:
2014 - 15
Credit Value:
10
Levels:
Level 3
Module Organiser:
Dr. Rudy Lapeer

Overview

This Autumn Semester directed studies module offers 10 credits as part of the coursework of any 20 credit Autumn Semester CMP module available in Options A and B range of the third year of the Computing Science, Imaging and Multimedia course. CMPC3Z11 is a 'proxy' module to allow students to 'even up' credits when taking a 30 credit FTM module.


Conventions and Standards

Submission:

Written coursework should be submitted by following the standard CMP practice. Students are advised to refer to the Guidelines and Hints on Written Work in CMP.

Deadlines:

If coursework is handed in after the deadline day or an agreed extension:

 

Work submitted Marks deducted
After 15:00 on the due date and before 15:00 on the day following the due date 10 marks
After 15:00 on the second day after the due date and before 15:00 on the third day after the due date 20 marks
After 15:00 on the third day after the due date and before 15:00 on the 20th day after the due date.  All the marks the work merits if submitted on time (ie no marks awarded) 
After 20 working days Work will not be marked and a mark of zero will be entered


Saturdays and Sundays will NOT be taken into account for the purposes of calculation of marks deducted.

All extension requests will be managed through the LTS Hub. A request for an extension to a deadline for the submission of work for assessment should be submitted by the student to the appropriate Learning and Teaching Service Hub, prior to the deadline, on a University Extension Request Form accompanied by appropriate evidence. Extension requests will be considered by the appropriate Learning and Teaching Service Manager in those instances where (a) acceptable extenuating circumstances exist and (b) the request is submitted before the deadline. All other cases will be considered by a Coursework Coordinator in CMP.

For more details, including how to apply for an extension due to extenuating circumstances download Submission for Work Assessment (PDF, 39KB)
 

Plagiarism:

Plagiarism is the copying or close paraphrasing of published or unpublished work, including the work of another student; without due acknowledgement. Plagiarism is regarded a serious offence by the University, and all cases will be reported to the Plagiarism Officer. Details from UEA's Policy on Plagiarism and Collusion.

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CMPC3P5Y - Industrial Project Report

Module Code:
CMPC3P5Y
Department:
CMP
Academic Year:
2014 - 15
Credit Value:
40
Levels:
Level 3
Module Organiser:
Dr. Mark Fisher

Overview

This module provides an opportunity for students to undertake individual project work during their industrial training placement.


Module Objectives

Module Specific:

  • Gain experience in the undertaking a piece of independent work within the context of an industrial placement.
  • Describe the work and present results to managers and colleagues in both in oral and written form.

Transferable skills:

  • Technical writing: students must prepare a substantial, properly structured technical report.
  • Oral presentation: students present their work.
  • Use IT and library resources to gather specific information needed for the project; collate and present this appropriately.


Learning Outcomes

On completion of this module students should be able to:

Subject specific:

  • Plan, manage and complete a substantial task independently (this work may be undertaken as part of a larger body of work completed as a team member)
  • Develop an understanding of how the project relates to other activities within the company and the need for effective communication to manage and coordinate activities.


Teaching and Assessment

Teaching Approach

Shortly after the first visit by the industrial placement coordinator the student and the industrial supervisor will agree on a task which will form the focus of the industrial project. The student will prepare a brief summary of the work and this will be emailed to the industrial training coordinator for approval. The work is then undertaken by the student during some of the remaining time (minimum 4 weeks). 

Total time: 4 weeks (minimum).

Methods of Assessment

The module is assessed by:

  1. The student makes an oral presentation to the industrial supervisor and industrial training coordinator (to coincide with the second industrial training visit). This counts 20% towards the final module mark.
  2. The student must submit a technical report (maximum 6000 words) before the end of the placement period, detailing the work undertaken. The report may be designated company confidential and as such it will be returned to the industrial supervisor following assessment. This counts 80% towards the module mark.

Setting of coursework:

Coursework will be posted on Blackboard in week 2 and week 4. Blackboard managed tests go live immediately after the lecture and remain available for one week only. Questions must be answered within 1 hour - only one attempt is permitted.


Resources

Teaching Resources

The module is managed using Blackboard. The student, industrial supervisor and industrial training coordinator manage and coordinate project work and assessments by email.

Library Resources

Students are registered with the university in their placement year and have access to library and IT resources.


Conventions and Standards

Submission:

Written coursework should be submitted by following the standard CMP practice. Students are advised to refer to the Guidelines and Hints on Written Work in CMP.

Deadlines:

If coursework is handed in after the deadline day or an agreed extension:

 

Work submitted Marks deducted
After 15:00 on the due date and before 15:00 on the day following the due date 10 marks
After 15:00 on the second day after the due date and before 15:00 on the third day after the due date 20 marks
After 15:00 on the third day after the due date and before 15:00 on the 20th day after the due date.  All the marks the work merits if submitted on time (ie no marks awarded) 
After 20 working days Work will not be marked and a mark of zero will be entered


Saturdays and Sundays will NOT be taken into account for the purposes of calculation of marks deducted.

All extension requests will be managed through the LTS Hub. A request for an extension to a deadline for the submission of work for assessment should be submitted by the student to the appropriate Learning and Teaching Service Hub, prior to the deadline, on a University Extension Request Form accompanied by appropriate evidence. Extension requests will be considered by the appropriate Learning and Teaching Service Manager in those instances where (a) acceptable extenuating circumstances exist and (b) the request is submitted before the deadline. All other cases will be considered by a Coursework Coordinator in CMP.

For more details, including how to apply for an extension due to extenuating circumstances download Submission for Work Assessment (PDF, 39KB)
 

Plagiarism:

Plagiarism is the copying or close paraphrasing of published or unpublished work, including the work of another student; without due acknowledgement. Plagiarism is regarded a serious offence by the University, and all cases will be reported to the Plagiarism Officer. Details from UEA's Policy on Plagiarism and Collusion.

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CMPC3P2Y - Computing Project

Module Code:
CMPC3P2Y
Department:
CMP
Academic Year:
2014 - 15
Credit Value:
40
Levels:
Level 3
Module Organiser:
Dr. Pierre Chardaire

Overview

This module will give you experience of independent project work and, via the lecture programme, will provide a primer on the law, ethical and professional behaviour, project management, reporting and other aspects of being a computer scientist. You will be allocated a supervisor and will be expected to work closely with him or her on a mutually agreed project. The project choice will normally take place in the summer preceding the module and will be based around a list of approved projects provided by members of Faculty and, occasionally, external customers. If you want to work on your own project then this may be possible but you should discuss this with the module organiser at an early stage.


Module Objectives

Module specific:

  • Gain experience in practical problem solving
  • Gain experience of undertaking and completing a large piece of independent work.
  • Learn to apply techniques previously learnt in the course to the solution of problems.
  • Gain experience in planning, design and implementation, testing and analysis.

Transferable skills:

  • Gain experience of applying research methodologies to practical applications
  • Gain experience of one-to-one working with a supervisor
  • Develop the discipline of accurate documentation
  • Gain experience of the preparation of a substantial, properly structured report
  • Experience of oral presentation of work in front of an audience and at the bench


Learning Outcomes

On completion of this module students should achieve the following:

  • The ability to identify the key issues in a project and undertake research to understand previous relevant work
  • A clear understanding of the organisational problems associated with a project
  • Improved practical problem solving skills
  • The ability to form a productive working relationship with a supervisor
  • Skills to plan, design and analyse a realistic project
  • The ability to write a substantial, properly structured report


Teaching and Assessment

Teaching Approach

There is no set syllabus. Students either choose a project from a published list or propose a project of their own. In the former case the student is then allocated to the supervisor who had put that project on the list. The supervisor provides support and guidance. In the case of 'own-projects', this must be first discussed with the Project Coordinator who will determine whether it is viable and of sufficient substance. If he is satisfied, he will then direct the student to appropriate members of staff who might be able to supervise. If the student identifies a suitable supervisor, then the project is approved. The allocation of projects is completed by the end of the second year.

The Coordinator provides a briefing session at the start of the project and before the deadlines for the summative assessments. The project runs continuously through both teaching terms of the third year with students responsible for organising themselves and their work, with advice from their supervisor, whom they are expected to see on a mutually agreed regular basis.

Methods of Assessment

Project


Resources

Teaching Resources:

Briefing notes and other materials will be made available via Blackboard.

Recommended reading:

  • Zobel, J. Writing for Computer Science, Springer


Conventions and Standards

Submission:

Written coursework should be submitted by following the standard CMP practice. Students are advised to refer to the Guidelines and Hints on Written Work in CMP.

Deadlines:

If coursework is handed in after the deadline day or an agreed extension:

 

Work submitted Marks deducted
After 15:00 on the due date and before 15:00 on the day following the due date 10 marks
After 15:00 on the second day after the due date and before 15:00 on the third day after the due date 20 marks
After 15:00 on the third day after the due date and before 15:00 on the 20th day after the due date.  All the marks the work merits if submitted on time (ie no marks awarded) 
After 20 working days Work will not be marked and a mark of zero will be entered


Saturdays and Sundays will NOT be taken into account for the purposes of calculation of marks deducted.

All extension requests will be managed through the LTS Hub. A request for an extension to a deadline for the submission of work for assessment should be submitted by the student to the appropriate Learning and Teaching Service Hub, prior to the deadline, on a University Extension Request Form accompanied by appropriate evidence. Extension requests will be considered by the appropriate Learning and Teaching Service Manager in those instances where (a) acceptable extenuating circumstances exist and (b) the request is submitted before the deadline. All other cases will be considered by a Coursework Coordinator in CMP.

For more details, including how to apply for an extension due to extenuating circumstances download Submission for Work Assessment (PDF, 39KB)
 

Plagiarism:

Plagiarism is the copying or close paraphrasing of published or unpublished work, including the work of another student; without due acknowledgement. Plagiarism is regarded a serious offence by the University, and all cases will be reported to the Plagiarism Officer. Details from UEA's Policy on Plagiarism and Collusion.

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CMPC3P1Y - Business Information Systems Project

Module Code:
CMPC3P1Y
Department:
CMP
Academic Year:
2014 - 15
Credit Value:
40
Levels:
Level 3
Module Organiser:
Dr. Pierre Chardaire

Overview

This module is the project for Business Information Systems students and is reserved exclusively for those students. It will give you experience of independent project work and, via the lecture programme, will provide a primer on the law, ethical and professional behaviour, project management, reporting and other aspects of being a business information systems professional. You will be allocated a supervisor and will be expected to work closely with him or her on a mutually agreed project. The project choice will normally take place in the summer preceding the module and will be based around a list of approved projects provided by members of Faculty and, occasionally, external customers. If you want to work on your own project then this may be possible but you should discuss this with the module organiser at an early stage.


Module Objectives

Module specific:

  • Gain experience in practical problem solving
  • Gain experience of undertaking and completing a large piece of independent work.
  • Learn to apply techniques previously learnt in the course to the solution of problems.
  • Gain experience in planning, design and implementation, testing and analysis.

Transferable skills:

  • Gain experience of applying research methodologies to practical applications
  • Gain experience of one-to-one working with a supervisor
  • Develop the discipline of accurate documentation
  • Gain experience of the preparation of a substantial, properly structured report
  • Experience of oral presentation of work in front of an audience and at the bench


Learning Outcomes

On completion of this module students should achieve the following:

  • The ability to identify the key issues in a project and undertake research to understand previous relevant work
  • A clear understanding of the organisational problems associated with a project
  • Gain experience of applying research and investigative methodologies to practical applications
  • The ability to form a productive working relationship with a supervisor
  • Skills to plan, design and analyse a realistic project
  • The ability to write a substantial, properly structured report


Teaching and Assessment

Teaching Approach

There is no set syllabus. Students either choose a project from a published list or propose a project of their own. In the former case the student is then allocated to the supervisor who had put that project on the list. The supervisor provides support and guidance. In the case of 'own-projects', this must be first discussed with the Project Coordinator who will determine whether it is viable and of sufficient substance. If he is satisfied, he will then direct the student to appropriate members of staff who might be able to supervise. If the student identifies a suitable supervisor, then the project is approved. The allocation of projects is completed by the end of the second year.

The Coordinator provides a briefing session at the start of the project and before the deadlines for the summative assessments. The project runs continuously through both teaching terms of the third year with students responsible for organising themselves and their work, with advice from their supervisor, whom they are expected to see on a mutually agreed regular basis.

Methods of Assessment

Project


Resources


Conventions and Standards

Submission:

Written coursework should be submitted by following the standard CMP practice. Students are advised to refer to the Guidelines and Hints on Written Work in CMP.

Deadlines:

If coursework is handed in after the deadline day or an agreed extension:

 

Work submitted Marks deducted
After 15:00 on the due date and before 15:00 on the day following the due date 10 marks
After 15:00 on the second day after the due date and before 15:00 on the third day after the due date 20 marks
After 15:00 on the third day after the due date and before 15:00 on the 20th day after the due date.  All the marks the work merits if submitted on time (ie no marks awarded) 
After 20 working days Work will not be marked and a mark of zero will be entered


Saturdays and Sundays will NOT be taken into account for the purposes of calculation of marks deducted.

All extension requests will be managed through the LTS Hub. A request for an extension to a deadline for the submission of work for assessment should be submitted by the student to the appropriate Learning and Teaching Service Hub, prior to the deadline, on a University Extension Request Form accompanied by appropriate evidence. Extension requests will be considered by the appropriate Learning and Teaching Service Manager in those instances where (a) acceptable extenuating circumstances exist and (b) the request is submitted before the deadline. All other cases will be considered by a Coursework Coordinator in CMP.

For more details, including how to apply for an extension due to extenuating circumstances download Submission for Work Assessment (PDF, 39KB)
 

Plagiarism:

Plagiarism is the copying or close paraphrasing of published or unpublished work, including the work of another student; without due acknowledgement. Plagiarism is regarded a serious offence by the University, and all cases will be reported to the Plagiarism Officer. Details from UEA's Policy on Plagiarism and Collusion.

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CMPC3M08 - Software Engineering 2

Module Code:
CMPC3M08
Department:
CMP
Academic Year:
2014 - 15
Credit Value:
20
Levels:
Level 3
Module Organiser:
Dr. Joost Noppen

Overview

Industrial software development is seldom started from scratch, companies generally have large systems of legacy software that need to be maintained, improved and extended. This module focuses on advanced software engineering topics, such as reverse engineering to understand legacy software, refactoring and design patterns to improve the design of software systems and developing new software products using third-party software components. Assessment will be done by a group project which consists of a design and analysis task, and the group implementation task of a software project. Confidence in Java programming language skills as well as software engineering practice (phased development with agile methods, Unified Modeling Language, test-driven development) are pre-requisites. Software Engineering I (2M02) is required for this module.


Module Objectives

Module Objectives

  1. To introduce the theory and processes for understanding and refactoring legacy software systems.
  2. To introduce students to the Object-Oriented Development techniques of application frameworks and design patterns to maximise extensibility and reuse of software systems.
  3. To give students foundational skills and experience of developing a mobile application framework for the Android platform and the creating applications based on this framework.


Learning Outcomes

Learning Outcomes

Module Specific
On completion of this module, students will be able to:

  • Analyse, understand and document a legacy software system using a reverse engineering approach.
  • Identify areas and aspects of legacy systems that need to be redesigned in the light of a set of requirements
  • Create a systematic set of classes and relations, i.e. an application framework combined with design patterns, that can be used as a foundation for the creation of a range of applications
  • Undertake an extensive project that comprises stages of business logic analysis, design and prototype implementation based on legacy software and an application framework
  • Competence and understanding in the use and creation of the Android mobile application environment

Transferable skills

  • Experience of software development processes based on legacy software code bases
  • Understanding of designing software for longevity, reusability and extensibility using industry standard concepts of application frameworks and design patterns
  • Knowledge of contemporary tools and approaches for understanding and documenting existing software systems
  • Understanding of mobile application development for industry standard platforms
  • Improved modelling, communication and presentation skills with respect to software development
  • Improved analysis and problem-solving skills


Teaching and Assessment

Teaching Approach

Teaching Approach

Contact time: 22 hours lectures, 4 hours seminar, 32 hours supervised lab sessions

Lectures (indicative content)

  1. Module Introduction and Android Basics
  2. Reverse Engineering, Reuse and Application Frameworks
  3. Design Patterns Part 1
  4. Design Patterns Part 2
  5. Android Application Development Topics
  6. Change management and software evolution
  7. Reading Week
  8. Software cost estimations & quality management
  9. Security of Mobile Applications
  10. Guest Lecture
  11. Now and the future of software engineering
  12. Revision

Seminar (Indicative content)
Seminar sessions will be scheduled to support topics covered. Topics will include:

  • Test-driven development
  • Group based software development
  • Documenting the development of a software system

Lab classes (indicative content)
Lab classes will be scheduled to for students to perform a simplified software engineering life cycle for the development of an application framework and mobile application based on a legacy software system. The emphasis will be analysing and refactoring existing software to suit a range of applications using advanced object-oriented development techniques. The labs are divided in the design creation of an application framework phase and a complex mobile application development phase. The development phases will have a deadline at which a design document is to be provided with all the information on the development that has been done up to that point as well as the software that has been created.

  1. Introduction to the Work Environment (ADT)
  2. Analysis and Rev Engineering of Case Study Source Code
  3. Refactoring of the architecture of the case study
  4. Introducing design patterns into the case study
  5. Introducing design patterns into the case study
  6. Finalising refactoring and case study documentation
  7. Seminar/Lab: Define assignment on top of the UEA Open Day Concept
  8. Prototype Implementation Iteration 1
  9. Prototype Implementation Iteration 1
  10. Prototype Implementation Iteration 2
  11. Prototype Implementation Iteration 2
  12. Prototype Implementation Demonstration

Methods of Assessment

Method of Assessment:

Assessment is by project that consists of two stages. Stage 1 consists of the reverse engineering, refactoring and documenting a legacy application framework to support the creation of Android applications in an easy to use manner. Stage 2 consists of the creation of a complex Android application using the application framework created in stage 1. For this part of the project a full documentation, source code and demonstration is expected.


Resources

Teaching Resources

Copies of the lecture notes will be made available on the day before the lecture at the latest via the Blackboard system. Materials for seminars and labs will be posted on Blackboard. Instructions for using specialised software (Android Developer Tools, ArgoUML) will be published on Blackboard. Changes in these instructions may become necessary, students therefore are advised to check these regularly. Laboratory sessions take place during a timetabled weekly laboratory period. CMP teaching laboratories are also available to CMP students during term time outside timetabled teaching hours. General computing resources are located elsewhere on campus (e.g. the library).

Library Resources

Additional reading and electronic resources:

Notice that versions stated above may differ from those used in the module. Please refer to the notes provided in the module as these take precedence over the list above.


Conventions and Standards

Submission:

Written coursework should be submitted by following the standard CMP practice. Students are advised to refer to the Guidelines and Hints on Written Work in CMP.

Deadlines:

If coursework is handed in after the deadline day or an agreed extension:

 

Work submitted Marks deducted
After 15:00 on the due date and before 15:00 on the day following the due date 10 marks
After 15:00 on the second day after the due date and before 15:00 on the third day after the due date 20 marks
After 15:00 on the third day after the due date and before 15:00 on the 20th day after the due date.  All the marks the work merits if submitted on time (ie no marks awarded) 
After 20 working days Work will not be marked and a mark of zero will be entered


Saturdays and Sundays will NOT be taken into account for the purposes of calculation of marks deducted.

All extension requests will be managed through the LTS Hub. A request for an extension to a deadline for the submission of work for assessment should be submitted by the student to the appropriate Learning and Teaching Service Hub, prior to the deadline, on a University Extension Request Form accompanied by appropriate evidence. Extension requests will be considered by the appropriate Learning and Teaching Service Manager in those instances where (a) acceptable extenuating circumstances exist and (b) the request is submitted before the deadline. All other cases will be considered by a Coursework Coordinator in CMP.

For more details, including how to apply for an extension due to extenuating circumstances download Submission for Work Assessment (PDF, 39KB)
 

Plagiarism:

Plagiarism is the copying or close paraphrasing of published or unpublished work, including the work of another student; without due acknowledgement. Plagiarism is regarded a serious offence by the University, and all cases will be reported to the Plagiarism Officer. Details from UEA's Policy on Plagiarism and Collusion.

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CMPC3I18 - Computer Vision

Module Code:
CMPC3I18
Department:
CMP
Academic Year:
2014 - 15
Credit Value:
20
Levels:
Level 3
Module Organiser:
Dr. Michal Mackiewicz

Overview

Computer Vision is about "teaching machines how to see". It includes methods for acquiring, analysing and understanding images. The unit comprises lectures and laboratories. Practical exercises and projects, undertaken in the laboratory support the underpinning theory and enable students to implement contemporary computer vision algorithms.


Module Objectives

Module specific:

  • To understand the fundamental differences between human and machine vision.
  • To gain knowledge of the processing steps involved in the camera processing pipeline.
  • To appreciate the different approaches to shape representation and image segmentation.
  • To gain an understanding of vision as the source of 3-D information.
  • To gain an understanding of vision as the source of semantic information.
  • To be familiar with the modern applications of vision.
  • To understand the importance of evaluation in computer vision.
  • To be able to critically compare vision algorithms.

Transferable skills:

  • Oral Communication: The students will receive formative feedback during laboratory classes.
  • Written Communication: Coursework are assessed by technical reports; this develops skills in information gathering and presentation.
  • Research Skills: Coursework completion requires certain amount of careful reading and following literature references.
  • Problem Solving: Programming is an intellectual activity which develops a step-wise approach to problem solving.


Learning Outcomes

On completion of the module students should be able to:

  • Be able to describe a restricted range of vision algorithms.
  • Be able to compare specified algorithms from the point of view of their complexity, robustness and modularity.
  • Understand the role of colour, shape and segmentation.
  • Understand the role of statistical methods in computer vision.
  • Write simple Matlab programs to manipulate images.

Transferable skills:

Enhanced Matlab programming and program design


Teaching and Assessment

Teaching Approach

Concepts will be introduced during lectures and students consolidate their understanding by undertaking laboratory work.

Total hours: 50

Lectures: 20; Hours 20; Content (per lecture):

  1. Introduction to CV; Image formation; Human and machine vision.
  2. Low-level vision; camera processing pipeline.
  3. Image segmentation.
  4. Shape representation and description.
  5. Image Indexing and matching
  6. Object recognition: detection, categorisation
  7. Statistical pattern recognition; learning and optimisation.
  8. 3D computer vision, geometry and radiometry. Shape from X.
  9. Image Fusion
  10. CV Applications.

Note: The order and emphasis may change depending on assignment topics.

Laboratory Work: 10, hours: 30, Content (with provisional weekly schedule):

  1. Image formation.
  2. Edge detection and segmentation.
  3. Image indexing and matching.
  4. Coursework 1
  5. Coursework 1 cont.
  6. Statistical pattern recognition.
  7. 3-D computer vision.
  8. Multi-sensor image fusion.
  9. Coursework 2
  10. Coursework 2 cont.

Note: Coursework activities will depend on the project chosen and may vary from year to year. Coursework 1 will be set at week 3, submission week 6. Coursework 2 will be set at week 8, submission week 12.

Methods of Assessment

Students receive formative feedback during laboratory classes.

The module is assessed by a combination of coursework and a formal course test. The course test is of 1 hour duration and accounts for 20% of the marks.

The coursework is divided into two separate pieces:

  1. Coursework 1 – 40% - low-level vision
  2. Coursework 2 – 40% - high-level vision


Resources

The module is managed using ‘Blackboard’. Copies of lecture slides will be made available on the day of the lecture at the latest. Tutorial sheets will be distributed prior to laboratory classes. Student numbers will be limited to 20 at laboratories, supported by the subject lecturer and a teaching assistant (postgraduate student).

Course texts:

Image Processing, Analysis and Machine Vision, V.Hlavac, M. Sonka, R.Boyle, 4th ed., 2014

Computer Vision: A Modern Approach by D. A. Forsyth and Jean Ponce, 2012


Conventions and Standards

Submission:

Written coursework should be submitted by following the standard CMP practice. Students are advised to refer to the Guidelines and Hints on Written Work in CMP.

Deadlines:

If coursework is handed in after the deadline day or an agreed extension:

 

Work submitted Marks deducted
After 15:00 on the due date and before 15:00 on the day following the due date 10 marks
After 15:00 on the second day after the due date and before 15:00 on the third day after the due date 20 marks
After 15:00 on the third day after the due date and before 15:00 on the 20th day after the due date.  All the marks the work merits if submitted on time (ie no marks awarded) 
After 20 working days Work will not be marked and a mark of zero will be entered


Saturdays and Sundays will NOT be taken into account for the purposes of calculation of marks deducted.

All extension requests will be managed through the LTS Hub. A request for an extension to a deadline for the submission of work for assessment should be submitted by the student to the appropriate Learning and Teaching Service Hub, prior to the deadline, on a University Extension Request Form accompanied by appropriate evidence. Extension requests will be considered by the appropriate Learning and Teaching Service Manager in those instances where (a) acceptable extenuating circumstances exist and (b) the request is submitted before the deadline. All other cases will be considered by a Coursework Coordinator in CMP.

For more details, including how to apply for an extension due to extenuating circumstances download Submission for Work Assessment (PDF, 39KB)
 

Plagiarism:

Plagiarism is the copying or close paraphrasing of published or unpublished work, including the work of another student; without due acknowledgement. Plagiarism is regarded a serious offence by the University, and all cases will be reported to the Plagiarism Officer. Details from UEA's Policy on Plagiarism and Collusion.

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CMPC3G91 - Graphics 2

Module Code:
CMPC3G91
Department:
CMP
Academic Year:
2014 - 15
Credit Value:
20
Levels:
Level 3
Module Organiser:
Prof. Andy Day

Overview

This module introduces the fundamentals of 3D geometric transformations and viewing using OpenGL. It teaches the theory and implementation of fundamental visibility determination algorithms and techniques for lighting, shading and anti-aliasing. Issues involved with modern high performance graphics processor are also considered. It also studies 3D curves and fundamental geometric data structures.


Module Objectives

Module specific:

  • To understand 3D geometric transformations
  • To implement viewing transformations using OpenGL
  • To explore and understand algorithms for 3D visibility computation
  • To understand a variety of methods for anti-aliasing.
  • To introduce some of the fundamentals of graphics hardware
  • To introduce methods for lighting and shading
  • To understand 2D convex hull algorithms

Transferable skills:

  • Algorithm design and implementation.
  • Report writing
  • Research techniques


Learning Outcomes

On completion of this module students should be able to:

  • Implement 3D viewing and hidden surface removal using OpenGL
  • Write a 3D graphics program using OpenGL with C++
  • Understand and implement algorithms for visibility testing.
  • Understand various anti-aliasing techniques.
  • Understand the fundamentals of lighting, shading, textures and graphics hardware.


Teaching and Assessment

Teaching Approach

This module is delivered as a programme of lectures, supported by laboratory classes.

Total Hours: 50

Lectures: 20; Hours 20; Content

  1. Geometry of 3D geometric transforms
  2. Useful 3D geometry
  3. Viewing and other fundamental 3D operations in OpenGL
  4. Introduction to hidden surface removal
  5. Hidden surface removal algorithms
  6. Hidden surface removal algorithms
  7. Binary Space partition algorithms
  8. Binary space partition algorithms
  9. 2D convex hulls
  10. 2D convex hulls
  11. Introduction to curves in 2D
  12. Further curves
  13. Introduction to lighting
  14. Further lighting
  15. Introduction to shading
  16. Textures
  17. Anti-aliasing
  18. Anti-aliasing
  19. Graphics hardware
  20. Graphics hardware.

Laboratory Work: 30; Hours: 30; Content

  1. Demonstration of simple 3D graphics programs using OpenGL
  2. Implementation of basic 3D graphics programs
  3. 3 - 11 Implementation of coursework - graphics program.

Workshops: 0 hours

Methods of Assessment

This module is assessed by coursework that is demonstrated to a member of the teaching staff. The program listing and report must also be submitted to the unit organiser for assessment. Deadlines are set to ensure that each programming task is completed.

Setting of coursework

Laboratory assignments are set at the beginning of each week. Assignment sheets can be downloaded from Blackboard and printed; a number of networked printers are available for CMP students.


Resources

Where necessary, lectures will be given using a data projector to allow example programs to be demonstrated. Example programs and course notes are distributed via the portal; accessible to all students registered for the module.

Laboratory work will take place during time-tabled laboratory periods. CMP teaching laboratories are available to CMP students during term time outside time-tabled teaching hours. General computing resources are located elsewhere on campus (e.g. the library).

 

Required reading:

  • Foley,J. D., van Dam,A., Feiner, S. K.  and Hughes,J. F.  Computer Graphics: Principles and Practice,Addison-Wesley, ISBN 0-201-12110-7
  • Rogers,D. F., Procedural Elements for Computer Graphics,McGraw-Hill, 1985 ISBN 0-07-053534-5
  • Angel,E. Interactive Computer Graphics second edition, Addison-Wesley, OpenGl programmers manual


Conventions and Standards

Submission:

Written coursework should be submitted by following the standard CMP practice. Students are advised to refer to the Guidelines and Hints on Written Work in CMP.

Deadlines:

If coursework is handed in after the deadline day or an agreed extension:

 

Work submitted Marks deducted
After 15:00 on the due date and before 15:00 on the day following the due date 10 marks
After 15:00 on the second day after the due date and before 15:00 on the third day after the due date 20 marks
After 15:00 on the third day after the due date and before 15:00 on the 20th day after the due date.  All the marks the work merits if submitted on time (ie no marks awarded) 
After 20 working days Work will not be marked and a mark of zero will be entered


Saturdays and Sundays will NOT be taken into account for the purposes of calculation of marks deducted.

All extension requests will be managed through the LTS Hub. A request for an extension to a deadline for the submission of work for assessment should be submitted by the student to the appropriate Learning and Teaching Service Hub, prior to the deadline, on a University Extension Request Form accompanied by appropriate evidence. Extension requests will be considered by the appropriate Learning and Teaching Service Manager in those instances where (a) acceptable extenuating circumstances exist and (b) the request is submitted before the deadline. All other cases will be considered by a Coursework Coordinator in CMP.

For more details, including how to apply for an extension due to extenuating circumstances download Submission for Work Assessment (PDF, 39KB)
 

Plagiarism:

Plagiarism is the copying or close paraphrasing of published or unpublished work, including the work of another student; without due acknowledgement. Plagiarism is regarded a serious offence by the University, and all cases will be reported to the Plagiarism Officer. Details from UEA's Policy on Plagiarism and Collusion.

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CMPC3C11 - Advanced Statistics

Module Code:
CMPC3C11
Department:
CMP
Academic Year:
2014 - 15
Credit Value:
20
Levels:
Level 3
Module Organiser:
Prof Elena Kulinskaya

Overview

This module covers two topics in statistical theory: Linear and Generalised Linear models and also includes Stochastic processes. The first two topics consider both the theory and practice of statistical model fitting and students will be expected to analyse real data. Stochastic processes include the random walk, Markov chains, Poisson processes, and birth and death processes.


Module Objectives

Module specific

  • To appreciate the ideas which underlie a range of statistical methods.
  • To apply these methods
  • To critically evaluate results
  • To be able to explain the results to non-specialist

Transferable skills

  • Written communication.
  • Oral communication
  • Model critique
  • Statistical thinking


Learning Outcomes

Subject specific

Ability to model stochastic data


Teaching and Assessment

Teaching Approach

Total hours: 36

Lectures: 33 hours: 33, Content: (with provisional weekly schedule)

  • Linear  models
  • Properties, Gauss-Markov theorem, inference
  • Regression diagnostics
  • Generalised Linear models (GLMs)
  • Logistic and Poisson regression
  • Binomial and Poisson models
  • Random walk
  • Markov chains
  • Poisson processes
  • Birth and death processes

Workshops: 0 hours

Laboratory Work: Fortnightly; 6 hours

Methods of Assessment

This module is assessed by a combination of coursework and an end of unit examination. The examination accounts for 60% of the unit's marks. It is scheduled during the summer exam period and lasts 3 hrs.

The coursework is divided into four components each of which is designed to enable a student to use the techniques covered in the lectures on real data.

Setting of coursework:

Coursework will be handed out in the lectures.


Resources

Teaching Resources

  • Access to R is provided, as are tutorial sessions on R
  • Lecture notes are available on Blackboard.
  • Case studies are discussed

Library Resources

Course Texts

  • Dobson, Annette J. and Barnett, Adrian, An Introduction to Generalized Linear Models, Chapman and Hall/Crc Texts in Statistical Science Series (Paperback Jul 2008)
  • Jones, P.W. and Smith, P. (2001) Stochastic Processes: An introduction. Arnold, London.


Conventions and Standards

Submission:

Written coursework should be submitted by following the standard CMP practice. Students are advised to refer to the Guidelines and Hints on Written Work in CMP.

Deadlines:

If coursework is handed in after the deadline day or an agreed extension:

 

Work submitted Marks deducted
After 15:00 on the due date and before 15:00 on the day following the due date 10 marks
After 15:00 on the second day after the due date and before 15:00 on the third day after the due date 20 marks
After 15:00 on the third day after the due date and before 15:00 on the 20th day after the due date.  All the marks the work merits if submitted on time (ie no marks awarded) 
After 20 working days Work will not be marked and a mark of zero will be entered


Saturdays and Sundays will NOT be taken into account for the purposes of calculation of marks deducted.

All extension requests will be managed through the LTS Hub. A request for an extension to a deadline for the submission of work for assessment should be submitted by the student to the appropriate Learning and Teaching Service Hub, prior to the deadline, on a University Extension Request Form accompanied by appropriate evidence. Extension requests will be considered by the appropriate Learning and Teaching Service Manager in those instances where (a) acceptable extenuating circumstances exist and (b) the request is submitted before the deadline. All other cases will be considered by a Coursework Coordinator in CMP.

For more details, including how to apply for an extension due to extenuating circumstances download Submission for Work Assessment (PDF, 39KB)
 

Plagiarism:

Plagiarism is the copying or close paraphrasing of published or unpublished work, including the work of another student; without due acknowledgement. Plagiarism is regarded a serious offence by the University, and all cases will be reported to the Plagiarism Officer. Details from UEA's Policy on Plagiarism and Collusion.

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CMPC3B10- Systems Engineering

Module Code:
CMPC3B10
Department:
CMP
Academic Year:
2014 - 15
Credit Value:
20
Levels:
Level 3
Module Organiser:
Dr. Pam Mayhew

Overview

This module draws together a wide range of material and considers it in the context of developing modern large-scale computer systems. Topics such as Outsourcing, Process Improvement, System Failure, Project Management, Configuration Management, Maintainability, Legacy Systems and Re-engineering, Acceptance and Performance Testing, Metrics and Human Factors are covered in this module. The module is supported by a series of industrial case studies and includes speakers from industry.


Module Objectives

Module specific :

  • To introduce the concept of systems and to consider the domain of computer-based systems engineering (CBSE)
  • To investigate the nature of both systems and computer-based systems failure and how the systems approach may be used to better understand such failures
  • To introduce students to the various aspects of quality which have to be taken into consideration in CBSE
  • To investigate the levels of risk inherent in the domain of CBSE projects
  • To examine the use of product and process metrics in CBSE
  • To examine testing strategies in CBSE
  • To investigate the principles of managing large scale CBSE projects
  • To explore the concept of software process improvement as a means of effecting continual improvement to the CBSE process
  • To assess the importance of adopting a configuration management approach to CBSE projects
  • To investigate the concept of software maintenance
  • To explore the concept of peopleware
  • Learn to use case studies to reflect on a range of industrial examples

Transferable skills:

  • Written Communication: Students have to write a paper for inclusion in the unit's mock conference
  • Oral Communication: Students are encouraged to participate in workshop discussions, and have to present their coursework paper at the module's mock conference
  • Gain experience of identifying and interpreting factors which affect the industrial environment and thereby be a more immediately useful employee, even from first employment.


Learning Outcomes

On completion of the module students should be able to:

  1. Describe the importance of examining systems from a holistic viewpoint rather than concentrating purely on the software component.
  2. Describe, with the use of examples, some of the common failures associated with computer-based systems.
  3. Describe the role of project management and risk management in the system development process.
  4. Explain the relationship between metrics, quality, and reliability, and whole life cycle testing.
  5. Explain the importance of, and issues surrounding, testing, configuration management, and maintenance.
  6. Explain the meaning and relevance of software process maturity models.
  7. Explain the importance of peopleware considerations to successful systems development.
  8. Have a clear understanding of the factors which affect an industrial environment
  9. Have acquired skills to help with the identification and interpreting of factors which affect the development, manufacture, distribution, marketing and sales of products


Teaching and Assessment

Teaching Approach

Total hours: 48

Lectures: 36 hours (with provisional weekly schedule)

  1. Systems Engineering: Investigating systems engineering as a discipline. The systems approach. Computer-based systems engineering (CBSE). The CBSE functions: process, quality, and project. Systems Failure: the nature of systems failure; the use of the systems approach to understand systems failure
  2. Outsourcing
  3. Project Management
  4. Quality: Quality control; Quality assurance; Total quality management; Quality documents; Audits; Validation and verification; software quality characteristics
  5. Risk Assessment: what is risk: systems engineering risks; the 5 fundamental risk factors in CBSE; risk management
  6. Metrification: the need for measurement in software and systems engineering; measuring the unmeasurable; GQM framework; classification of software measures; components of software measures; scope of software metrics; cost and effort estimation; metrification models; data collection; the human issues with metrification
  7. Spare / Reading Time
  8. Process Improvement: the software process; a 'defined' process; immature and mature organisations; the capability maturity model; ISO9000 series of standards; Bootstrap; SPICE;
  9. Configuration Management: the nature of systems changes; what is configuration management; configuration control; configuration audits and reviews. Maintenance: motivations for maintenance; types of maintenance activity; reducing the maintenance problem; image of maintenance; organising maintenance activities
  10. Testing: Testers, verification, validation, organising for testing
  11. Peopleware: The project manager's point of view, "quality is the key", improving productivity, making work fun!
  12. Coursework presentations
  13. Coursework presentations
 

Seminars:  12 hours (with provisional weekly schedule)    

  1. Understanding the inherent nature of software, and themes from Brooks' No silver bullet paper.
  2. Globally Distributed Software Development
  3. Examining a systems failure
  4. Risk - investigating the London Ambulance Systems debacle
  5. Metrification exercises
  6. Spare / Reading Week
  7. Software Product Line
  8. Looking at departmentalisation in software maintenance
  9. Comparison of traditional engineering and systems engineering
  10. People Issues
  11. Coursework presentations
  12. Coursework presentations

Laboratory work: 0 hours

Methods of Assessment


Setting of Coursework:

Coursework will be set in week 3. A copy of the coursework will be handed to students during the week 3 lecture but will also be made available on Blackboard for students to download and print. The written report should be posted in the appropriate coursework boxes in CMP during week 11 The presentations will take place in week 12.


Resources

The majority of the lectures in this course can be given through use of a standard overhead projector. No other special teaching resources are envisaged.

Library Resources

Module Text

There is no specific text to purchase for this module as the literature will be made available when you need it.

Suggested Background Reading

  • DeMarco and Lister, Waltzing with Bears: Managing Risks on Software Projects, Dorset House Publishing, 2003.
  • DeMarco and Lister, Peopleware: Productive Projects and Teams, Dorset House Publishing, 1999.
  • Galin, Software Quality Assurance: From theory to implementation, Pearson/Addison Wesley, 2004.
  • Hall and Fernandez-Ramil, Managing the Software Enterprise, Thomson, 2007.
  • Pressman, Software Engineering: A Practitioner's Approach, (6th Ed), McGraw Hill 2004.
  • Somerville, Software Engineering, (8th Ed.), Addison Wesley, 2006.
  • Stevens, Brook, Jackson, Arnold, Systems Engineering: Coping with Complexity, Prentice Hall, 1998.

Web-based material:

There is a wealth of comprehensive material on the web, including:


Conventions and Standards

Submission:

Written coursework should be submitted by following the standard CMP practice. Students are advised to refer to the Guidelines and Hints on Written Work in CMP.

Deadlines:

If coursework is handed in after the deadline day or an agreed extension:

 

Work submitted Marks deducted
After 15:00 on the due date and before 15:00 on the day following the due date 10 marks
After 15:00 on the second day after the due date and before 15:00 on the third day after the due date 20 marks
After 15:00 on the third day after the due date and before 15:00 on the 20th day after the due date.  All the marks the work merits if submitted on time (ie no marks awarded) 
After 20 working days Work will not be marked and a mark of zero will be entered


Saturdays and Sundays will NOT be taken into account for the purposes of calculation of marks deducted.

All extension requests will be managed through the LTS Hub. A request for an extension to a deadline for the submission of work for assessment should be submitted by the student to the appropriate Learning and Teaching Service Hub, prior to the deadline, on a University Extension Request Form accompanied by appropriate evidence. Extension requests will be considered by the appropriate Learning and Teaching Service Manager in those instances where (a) acceptable extenuating circumstances exist and (b) the request is submitted before the deadline. All other cases will be considered by a Coursework Coordinator in CMP.

For more details, including how to apply for an extension due to extenuating circumstances download Submission for Work Assessment (PDF, 39KB)
 

Plagiarism:

Plagiarism is the copying or close paraphrasing of published or unpublished work, including the work of another student; without due acknowledgement. Plagiarism is regarded a serious offence by the University, and all cases will be reported to the Plagiarism Officer. Details from UEA's Policy on Plagiarism and Collusion.

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CMPC3B06 - Introduction to Computational Biology

Module Code:
CMPC3B06
Department:
CMP
Academic Year:
2014 - 15
Credit Value:
20
Levels:
Level 3
Module Organiser:
Dr. Taoyang Wu

Overview

Computational biology is one of the great growth areas of both computing sciences and biology due to the development of robotic systems that are able churn out vast amounts of biological data. The challenge computational biologists' face involves turning this data into understanding. This data is often in the form of DNA, RNA or protein sequence. Although an introduction to the basics of molecular biology will be given, the module will mainly focus on the computational methods used in computational biology and bioinformatics. Topics will include sequence analysis, structural genomics and protein modelling, genome assembly and phylogenetics. Lecturers will highlight the relevance of the material to cutting-edge research.


Module Objectives

Module specific

  • To introduce the basics of molecular biology
  • To develop an understanding of the fundamental methods of computational biology
  • To introduce the dynamic programming algorithm
  • To give an overview of the new emerging areas of research in computational biology

Transferable Skills

  • Algorithmic thinking
  • Systematic approach to the solution of complex problems


Learning Outcomes

On completion of this module students should:

  • Have an understanding of the basic concepts of genetics and molecular biology
  • Have an understanding of the dynamic programming algorithm for sequence alignment
  • Understand methods for multiple sequence alignment
  • Understand techniques used in the prediction of RNA structure
  • Understand the basic concepts and algorithms of phylogenetics
  • Grasp the basic concepts used to characterise, compare and model protein structures


Teaching and Assessment

Teaching Approach

Lectures 33 hours + labs

  1. Introduction to the basics concepts of molecular biology and genetics.
  2. The basic algorithms of biological sequence alignment including dynamic programming and heuristic methods.
  3. Introduction to protein structure and computational methods used to compare and characterise protein structures.
  4. Protein simulation techniques.
  5. RNA methods: Introduction to RNA structure,  RNA secondary structure prediction and methods for RNA secondary structure comparison.
  6. Introduction to phylogenetic trees: algorithms for the construction and analysis of trees and networks that describe the evolution of species, populations and individuals.
  7. Latest topics in genomics: genome sequencing, the human genome, genome applications in health including ethical concerns, sequence assembly, the shortest superstring problem, and graph theoretical approaches to sequence assembly

Methods of Assessment

Examination and Course test


Resources

There is no single text but sections of the following books may be helpful:

  • Alberts, B., Johnson, A., Walter,P.,Lewis,J., Raff, M., Roberts, K., Molecular Biology of the Cell, Garland Publishing Inc, US
  • D.Mount, Bioinformatics, Cold Spring Harbor Laboratory Press
  • J.Setubal, J.Meidanis, Introduction to computational molecular biology,  PWS Publishing Company
  • R.Durbin, S.Eddy, A.Krogh, G.Mitchison,  Biological sequence analysis, Cambridge University Press
  • C. Branden, J. Tooze, Introduction to Protein Structure, Garland


Conventions and Standards

Submission:

Written coursework should be submitted by following the standard CMP practice. Students are advised to refer to the Guidelines and Hints on Written Work in CMP.

Deadlines:

If coursework is handed in after the deadline day or an agreed extension:

 

Work submitted Marks deducted
After 15:00 on the due date and before 15:00 on the day following the due date 10 marks
After 15:00 on the second day after the due date and before 15:00 on the third day after the due date 20 marks
After 15:00 on the third day after the due date and before 15:00 on the 20th day after the due date.  All the marks the work merits if submitted on time (ie no marks awarded) 
After 20 working days Work will not be marked and a mark of zero will be entered


Saturdays and Sundays will NOT be taken into account for the purposes of calculation of marks deducted.

All extension requests will be managed through the LTS Hub. A request for an extension to a deadline for the submission of work for assessment should be submitted by the student to the appropriate Learning and Teaching Service Hub, prior to the deadline, on a University Extension Request Form accompanied by appropriate evidence. Extension requests will be considered by the appropriate Learning and Teaching Service Manager in those instances where (a) acceptable extenuating circumstances exist and (b) the request is submitted before the deadline. All other cases will be considered by a Coursework Coordinator in CMP.

For more details, including how to apply for an extension due to extenuating circumstances download Submission for Work Assessment (PDF, 39KB)
 

Plagiarism:

Plagiarism is the copying or close paraphrasing of published or unpublished work, including the work of another student; without due acknowledgement. Plagiarism is regarded a serious offence by the University, and all cases will be reported to the Plagiarism Officer. Details from UEA's Policy on Plagiarism and Collusion.

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CMP3A01 - Machine Learning

Module Code:
CMP3A01
Department:
CMP
Academic Year:
2014 - 15
Credit Value:
20
Levels:
Level 3
Module Organiser:
Dr. Tony Bagnall

Overview

This module covers the core topics that dominate machine learning research: classification, clustering and reinforcement learning. We describe a variety of classification algorithms (e.g. Neural Networks, Decision Trees and Learning Classifier Systems) and clustering algorithms (e.g. k-NN and PAM) and discuss the practical implications of their application to real world problems. We then introduce reinforcement learning and the Q-learning problem and describe its application to control problems such as maze solving.


Module Objectives

Module specific:

  • To understand the nature of classification, clustering and reinforcement learning problems and to have an overview of the areas of business and science in which they may occur.
  • To comprehend the workings of the classification, clustering and reinforcement algorithms covered in the course and the motivation for why the work in the way they do
  • To be able to execute by hand simple versions of these algorithms on toy problems
  • To be able to implement basic versions of these algorithms that can be applied to real world problems
  • To be able to use a variety of tools with fully implementations of these algorithms
  • To be able to usefully compare the performance of these algorithms and to grasp which algorithms work best for which type of problem
  • To be able to present these results in a logical, scientific way to the owner of the problem.

Transferable skills:

  • To gain further experience in understanding algorithms
  • To improve programming skills
  • To learn how to understand and utilize complex existing code.
  • To understand how to logically structure a report describing a scientific approach to problem solving


Learning Outcomes

On completion of this module students should be able to:

Formulate problems as classification or clustering problems and apply a wide range of algorithms to the task


Teaching and Assessment

Teaching Approach

Total hours: 45 (approx.)

Lectures:  20-30 hours

  1. Introduction: Basic Principles (simple univariate classifiers) Naive Bayes
  2. Nearest Neighbour Classifiers
  3. Decision Trees
  4. Linear Classifiers
  5. Artificial Neural Networks
  6. Support Vector Machines, Performance Evaluation
  7. Bayesian Networks
  8. Unsupervised learning 1:Hierarchical and partitional clustering
  9. Unsupervised learning 2: reinforcement learning
  10. Learning Classifier Systems for supervised and unsupervised learning

Exercise classes: 10 hours

Laboratory work: 5-10 hours

Methods of Assessment

Examination with Coursework or Project


Resources

Teaching Resources

Lectures will be given using a combination of data monitor and overhead projection. Lecture notes, exercise sheets and other relevant material will be available via Blackboard.

Library Resources

Module texts ( and further reading)

Mitchell,T.,  Machine Learning, Mcgraw-Hill International edition


Conventions and Standards

Submission:

Written coursework should be submitted by following the standard CMP practice. Students are advised to refer to the Guidelines and Hints on Written Work in CMP.

Deadlines:

If coursework is handed in after the deadline day or an agreed extension:

 

Work submitted Marks deducted
After 15:00 on the due date and before 15:00 on the day following the due date 10 marks
After 15:00 on the second day after the due date and before 15:00 on the third day after the due date 20 marks
After 15:00 on the third day after the due date and before 15:00 on the 20th day after the due date.  All the marks the work merits if submitted on time (ie no marks awarded) 
After 20 working days Work will not be marked and a mark of zero will be entered


Saturdays and Sundays will NOT be taken into account for the purposes of calculation of marks deducted.

All extension requests will be managed through the LTS Hub. A request for an extension to a deadline for the submission of work for assessment should be submitted by the student to the appropriate Learning and Teaching Service Hub, prior to the deadline, on a University Extension Request Form accompanied by appropriate evidence. Extension requests will be considered by the appropriate Learning and Teaching Service Manager in those instances where (a) acceptable extenuating circumstances exist and (b) the request is submitted before the deadline. All other cases will be considered by a Coursework Coordinator in CMP.

For more details, including how to apply for an extension due to extenuating circumstances download Submission for Work Assessment (PDF, 39KB)
 

Plagiarism:

Plagiarism is the copying or close paraphrasing of published or unpublished work, including the work of another student; without due acknowledgement. Plagiarism is regarded a serious offence by the University, and all cases will be reported to the Plagiarism Officer. Details from UEA's Policy on Plagiarism and Collusion.

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CMP-7030Y - Research Techniques

Module Code:
CMP-7030Y
Department:
CMP
Academic Year:
Credit Value:
20
Levels:
Level M
Module Organiser:
Dr. Wenjia Wang

Overview

This module aims to prepare postgraduate students with necessary intellectual and practical skills for successfully carrying out research work for their MSc Dissertation in Computing Sciences and Computational Biology. Specifically, it teaches research methodologies, techniques and tools used in computing sciences, and more importantly, provides systematic trainings to enhance students' transferable skills and their understanding in ethics, social and legal issues involved in computing professions.


Module Objectives

Module specific:

The objectives of this module are to teach students with a range of research methods, techniques, and tools (see the topics of the lectures below) and to prepare them with necessary practical skills for proposing and doing their dissertation project in Computing Sciences in a methodical manner.

Transferable Skills:

  • To improve technical writing and literature review skills
  • To enhance critical thinking and reasoning skills under uncertainties
  • To improve ability for quantitative analysis and critical evaluation
  • To improve oral presentation skills. 
  • To learn time management, project design and planning skills.
  • To produce quick-learning and adaptable graduates.  


Learning Outcomes

On completion of this module students should have achieved the following:

  • Knowledge and understanding of the main approaches to research in computing science,
  • The ability to use computing-specific information resources effectively,

Transferable skills:

On completion of this module students should be able to:

  • Use the Internet and Library effectively to locate technical information and literature,
  • Write reports that adhere to the conventions for good technical writing in English,
  • Enhance oral communication and presentation skills
  • Improve critical thinking and reasoning skills
  • Understand and apply simple project management techniques to their own work,
  • Understand and apply statistical hypothesis techniques applied to computing problems,
  • Assess the appropriateness of different evaluation strategies used in computing research.
  • Understand computing ethics and professionalism.   


Teaching and Assessment

Teaching Approach

Total hours: 40

Lectures: 22 hours   (with provisional weekly schedule)

  1. Introductions to research in the School of Computing Sciences
  2. Improving academic writing techniques
  3. Tools for technical writing
  4. Literature review skills
  5. Visualisation methods
  6. Data analysis methods and tools, and critical evaluation
  7. Critical thinking and reasoning under uncertainties
  8. Research project design and planning
  9. MSc dissertation project proposal
  10. Computing ethics, social and legal issues, and professionalism

Workshops: 6 hours

Laboratory work:  12 hours

Methods of Assessment

Coursework


Resources

Lecture notes and other material will be made available on the Blackboard.

Recommended reading:

  • Zobel, J. (2006) Writing for Computer Science, Springer,

  • Robson, C.(2002) Real World Research, Blackwell

Additional reading lists will be issued before sessions as necessary.


Conventions and Standards

Submission:

Written coursework should be submitted by following the standard CMP practice. Students are advised to refer to the Guidelines and Hints on Written Work in CMP.

Deadlines:

If coursework is handed in after the deadline day or an agreed extension:

 

Work submitted Marks deducted
After 15:00 on the due date and before 15:00 on the day following the due date 10 marks
After 15:00 on the second day after the due date and before 15:00 on the third day after the due date 20 marks
After 15:00 on the third day after the due date and before 15:00 on the 20th day after the due date.  All the marks the work merits if submitted on time (ie no marks awarded) 
After 20 working days Work will not be marked and a mark of zero will be entered


Saturdays and Sundays will NOT be taken into account for the purposes of calculation of marks deducted.

All extension requests will be managed through the LTS Hub. A request for an extension to a deadline for the submission of work for assessment should be submitted by the student to the appropriate Learning and Teaching Service Hub, prior to the deadline, on a University Extension Request Form accompanied by appropriate evidence. Extension requests will be considered by the appropriate Learning and Teaching Service Manager in those instances where (a) acceptable extenuating circumstances exist and (b) the request is submitted before the deadline. All other cases will be considered by a Coursework Coordinator in CMP.

For more details, including how to apply for an extension due to extenuating circumstances download Submission for Work Assessment (PDF, 39KB)
 

Plagiarism:

Plagiarism is the copying or close paraphrasing of published or unpublished work, including the work of another student; without due acknowledgement. Plagiarism is regarded a serious offence by the University, and all cases will be reported to the Plagiarism Officer. Details from UEA's Policy on Plagiarism and Collusion.

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CMP-7028A - Artificial Intelligence

Module Code:
CMP-7028A
Department:
CMP
Academic Year:
Credit Value:
20
Levels:
Level M
Module Organiser:
Dr. Pierre Chardaire

Overview

This module introduces the students to core techniques in Artificial Intelligence an some topics in algorithmics. Topics covered include First-Order logic and resolution proofs, introduction to Prolog programming, state space representation and search algorithms, knowledge representation, and expert systems, Bayesian and neural networks.


Module Objectives

On completion of the module, students should be able to:

  • Solve simple propositional and predicate logic problems
  • Understand the need for search and be able to explain simple search techniques
  • Understand how AI techniques are used in game playing
  • Write programs in prolog
  • Manipulate probabilities and analyse Bayesian networks
  • Describe a variety of machine learning techniques and assess their applicability for a given scenario
  • Understand the principles and use of both expert system and case based reasoning


Learning Outcomes

On completion of this unit students should have achieved:

  • Competence in logical problem solving skills
  • Understanding of declarative programming
  • Improved ability to develop mathematical models


Teaching and Assessment

Teaching Approach

Total hours: 36

Lectures: 22 hours (with provisional weekly schedule)

  1. Propositional logic , predicate logic
  2. Resolution theorem proving
  3. Logic programming: Prolog
  4. Prolog techniques
  5. State based search method 
  6. Advanced state based search methods
  7. Problem reduction based search methods
  8. Knowledge representation 
  9. Introduction to machine learning techniques
  10. Artificial neural networks, Bayesian networks 
  11. Expert systems and Case based reasoning

Laboratory work: 14 hours

Topics:

  1. Introduction to prolog (4 weeks)
  2. Neural networks and bayesian networks (3 weeks)

 

Methods of Assessment

Prolog programming exercise (set in week 5, due week 10, returned assessment week 1), makes up 40% of the marks for the module. A three hour exam makes up the remaining 60% of the marks for the module.


Resources

Teaching Resources:

SWI - Prolog on laboratory machines

Library Resources:

Recommended reading:

  • Luger,G.F. (2005) Artificial Intelligence: Structures and Strategies for Complex Problem Solving, fifth edition, Addison-Wesley
  • Russell,S., Norwig, P.(2003) Artificial Intelligence: a modern approach, (2e) Prentice Hall
  • Dean,T., Allen, J. and Aloimonos, Y.(1996) Artificial Intelligence: Theory and Practice, Addison-Wesley
  • Bratko, I. (2001). Prolog: programming for artificial intelligence. Pearson education.


Conventions and Standards

Submission:

Written coursework should be submitted by following the standard CMP practice. Students are advised to refer to the Guidelines and Hints on Written Work in CMP.

Deadlines:

If coursework is handed in after the deadline day or an agreed extension:

 

Work submitted Marks deducted
After 15:00 on the due date and before 15:00 on the day following the due date 10 marks
After 15:00 on the second day after the due date and before 15:00 on the third day after the due date 20 marks
After 15:00 on the third day after the due date and before 15:00 on the 20th day after the due date.  All the marks the work merits if submitted on time (ie no marks awarded) 
After 20 working days Work will not be marked and a mark of zero will be entered


Saturdays and Sundays will NOT be taken into account for the purposes of calculation of marks deducted.

All extension requests will be managed through the LTS Hub. A request for an extension to a deadline for the submission of work for assessment should be submitted by the student to the appropriate Learning and Teaching Service Hub, prior to the deadline, on a University Extension Request Form accompanied by appropriate evidence. Extension requests will be considered by the appropriate Learning and Teaching Service Manager in those instances where (a) acceptable extenuating circumstances exist and (b) the request is submitted before the deadline. All other cases will be considered by a Coursework Coordinator in CMP.

For more details, including how to apply for an extension due to extenuating circumstances download Submission for Work Assessment (PDF, 39KB)
 

Plagiarism:

Plagiarism is the copying or close paraphrasing of published or unpublished work, including the work of another student; without due acknowledgement. Plagiarism is regarded a serious offence by the University, and all cases will be reported to the Plagiarism Officer. Details from UEA's Policy on Plagiarism and Collusion.

Click the button to print the current page.