Undergraduate degree or Masters




НазваниеUndergraduate degree or Masters
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Course Title:

Academic Writing

Course Code:

AW

Course Status:

Generic

Recommended Prior Study:

Undergraduate degree or Masters

Learning Outcomes:

After completing the module the student should be able to:

  1. Communicate findings, in both written and oral form, in a professional manner

  2. Assess previous research reports/research papers completed in an area

  3. Critically appraise research data and assimilate, integrate and discuss in a logical way

  4. Produce an appropriate project description and specification

  5. Present and defend their findings clearly

Aims & Objectives:

To improve technical communication skills.

To develop research and technical communication skills and awareness of the legal and ethical framework surrounding the activities of a professional engineer, including: personnel, health, safety, and risk (including environmental risk) issues.

To enable students to demonstrate theoretical and practical research skills.

To develop in students the ability to specify and design a major research project.

To provide students with the opportunity to conduct and defend orally an independent research project.

Syllabus Contents (Main topics):

Introduction “Why do research”.

On-line literature search methods.

Interpreting your observations.

Presenting your findings.

Speaking and writing for the technical professions.

Analysing observations and choosing appropriate means of presenting research findings.

Introduction to search methods, technical writing and speaking.

Assessment Procedure:

Coursework: 40% Literature search & Research critique

Coursework: 20% Presentation of proposed project.

Coursework: 40% Detailed Doctoral Project proposal.

Indicative Sources:

  1. Alison, B. (1997) 'The Students Guide to Writing Dissertations and Theses' Kogan Page

  2. Booth, V. (1993) 'Communicating in science: writing a scientific paper and speaking at scientific meetings' Cambridge University Press

  3. Galliers, R. (1994) 'Information Systems Research: Issues, Methods and Practical Guidelines' McGraw-Hill Education - Europe 187247439X

  4. Martin, M.W and Schinzinger, R (1997) 'Ethics in Engineering' 3rd McGraw-Hill 0-07-114195-2

  5. Sharp, J.A. and Howard, K (1996) 'The management of a student research project' 2nd Gower

  6. Swetnam D (2000) 'Writing Your Dissertation: The Best Selling Guide to Planning, Preparing and Presenting First Class Work' How to Books

  7. Turk, C and Kirkman, J (1995) 'Effective writing' 2nd E & FN

  8. SponVan Wegenen, K.R. (1991) 'Writing a Thesis :Substance and Style' Prentice-Hall 0139710868




Course Title:

Methodology of the Scientific Research

Course Code:

MSR

Course Status:

Generic

Recommended Prior Study:

Undergraduate degree or Masters

Learning Outcomes:

After completing the module the student should be able to:

  1. Demonstrate and develop fundamental research skills such as literature search, hypothesis/question formation, presentation of findings, and critical assessment of conclusions and implications

  2. To provide a theoretical background for conducting postgraduate work

  3. To provide a programme of training in the research process

Aims & Objectives:

To enable students to demonstrate theoretical and practical research skills.

To develop in students the ability to specify and design a major research project.

To develop skills in planning, interpretation, analysis and data processing.

Syllabus Contents (Main topics):

Introduction to literature search methods including on-line methods.

Interpreting and analysing your observations.

Analysing observations and choosing appropriate means of presenting research findings.

Science and scientific methodology: Epistemology, classification of research: theory development and testing; the deductive-inductive research process; and the role of independent and dependent variables.

Data collection techniques: Observational Techniques; Survey Techniques; Experimental Techniques.

Qualitative and quantitative data collection and analysis.

Project planning, Time management and Gantt charts.

Critical evaluation of published work

Introduction to data analysis software (e.g. SPSS)

Assessment Procedure:

Continuous assessment:

25% Description of literature search rationale

25% Critical review of literature

25% Analysis and reflection on illustrative results

25% Suggested time management plan

Indicative Sources:

  1. Galliers, R. (1994) 'Information Systems Research :Issues, Methods and Practical Guidelines' McGraw-Hill Education - Europe 187247439X

  2. Gash, S. 2000. Effective literature searching for students. Gower. ISBN 0566081253

  3. Sharp, J. A. And Howard, K. 1996. The management of a student research project (2nd edition). Gower. ISBN 056607706x

  4. Williamson, K. (2002) 'Research Methods for Students, Academics and Professionals :Information Management and Systems' 2nd Centre for Information Studies, Charles Sturt University, NSW 1876938420




Course Title:

Legal Grounds and Structure of Doctoral Thesis

Course Code:

LGSDT

Course Status:

Generic

Recommended Prior Study:

Undergraduate degree or Masters

Learning Outcomes:

After completing the module the student should be able to:

  1. Formulate research proposals, and plan and conduct the five stages of empirical investigation: design, sampling, data collection, data processing, and reporting

  2. Demonstrate and develop fundamental research skills such as literature search, hypothesis/question formation, presentation of findings, and critical assessment of conclusions and implications

  3. produce an appropriate project description and specification

  4. Undertake a major research project and demonstrate competence in its execution

Aims & Objectives:

To provide a theoretical background for conducting postgraduate work

Formulate a research question of interest; apply relevant methods of investigation; and analyze, interpret and critically assess the findings.

Gain knowledge and experience of the skills entailed in conducting research, including those concerned with literature searches, research design, fieldwork, statistical analysis, and report-writing.

To develop in students the ability to specify and design a major research project.

To provide students with the opportunity to conduct and defend orally an independent research project.

Syllabus Contents (Main topics):

Introduction “Why do research”

Interpreting your observations.

Project analysis and design

Ethics in engineering, computing and technology

Project planning

Time management and use of Gantt charts

Data collection techniques: Observational Techniques; Survey Techniques; Experimental Techniques.

Structured presentation of research material

Processes and procedures for dissertation submission and defense

Assessment Procedure:

Coursework: 40% Outline of thesis structure and content

Coursework: 20% Presentation of proposed project

Coursework: 40% Detailed Doctoral Project proposal

Indicative Sources:

  1. Alison, B. (1997) 'The Students Guide to Writing Dissertations and Theses' Kogan Page

  2. Galliers, R. (1994) 'Information Systems Research :Issues, Methods and Practical Guidelines' McGraw-Hill Education - Europe 187247439X

  3. Martin, M.W and Schinzinger, R (1997) 'Ethics in Engineering' 3rd McGraw-Hill 0-07-114195-2

  4. Sharp, J.A. and Howard, K (1996) 'The management of a student research project' 2nd Gower

  5. Swetnam D (2000) 'Writing Your Dissertation: The Best Selling Guide to Planning, Preparing and Presenting First Class Work' How to Books

  6. Turk, C and Kirkman, J (1995) 'Effective writing' 2nd E & FN Spon

  7. Williamson, K. (2002) 'Research Methods for Students, Academics and Professionals :Information Management and Systems' 2nd Centre for Information Studies, Charles Sturt University, NSW 1876938420

  8. Van Wegenen, K.R. (1991) 'Writing a Thesis :Substance and Style' Prentice-Hall 0139710868




Course Title:

Intellectual Property Protection

Course Code:

IPP

Course Status:

Generic

Recommended Prior Study:

Undergraduate degree or Masters

Learning Outcomes:

After completing the module the student should be able to:

  1. Assess the essential contemporary legal, moral and ethical issues relating to intellectual property, as they concern the use of, and exploitation of, technology in the work environment.

  2. Examine the potential conflicts between EU IP rights, EU competition law, and National IP rights.

  3. Scrutinise the European Patents Convention and the workings of the European Patents Office.

  4. Evaluate the implications of Electronic Data Interchange and Cross-Border Data Flows in the EU.

Aims & Objectives:

Consideration and examination of intellectual property rights as they impinge on the exploitation of technology; rights, duties and responsibilities of inventors; licensees; employers and employees.

Syllabus Contents (Main topics):

Introduction and rational of Intellectual Property Rights

Nature of Intellectual Property

Law of Patent

Industrial Designs

Trade Marks and Trade Names

Law of Confidential Information

Copyright and Design Copyright

Proposed EC Trade Mark

European Patents Convention

European Patents Office

EDI and Cross Border Data Flows

Assessment Procedure:

100% coursework: A number of reports on ‘Case study’ examples

Indicative Sources:

  1. Phillips and Firth 'Introduction to Intellectual Property'

  2. Bainbridge, D. (2002) 'Intellectual Property' 5th Longman

  3. Dworki & Taylor (1988) 'Copyright, Design and Patents act' Blackstones Statutes

  4. Cornish, W. & Llewelyn, D. (2003) 'Intellectual Property :Patents, Copyright, Trade Marks and Allied Rights' 5th Thomson 0-421-78120-3

  5. Holyoak, J and Torremans, P (2001) '''Intellectual Property Law''' 3rd Butterworths

  6. Bentley L. and Sherman B. (2004) 'Intellectual Property Law' 2nd OUP




Course Title:

Post Doctoral Seminar

Course Code:

PDS

Course Status:

Generic

Recommended Prior Study:

Undergraduate degree or Masters

Learning Outcomes:

After completing the module the student should be able to:

  1. Demonstrate and develop fundamental research skills such as literature search, hypothesis/question formation, presentation of findings, and critical assessment of conclusions and implications

  2. Present a seminar paper and respond appropriately to comments received

Aims & Objectives:

Practice the skills involved in seminar presentation, including those required in effective summarizing of ideas and information, and oral communication.

To develop research and technical communication skills and awareness of the legal and ethical framework surrounding the activities of a professional engineer, including: personnel, health, safety, and risk (including environmental risk) issues.

To enable students to demonstrate theoretical and practical research skills.

To develop in students the ability to specify and design a major research project.

Syllabus Contents (Main topics):

Introduction to search methods, technical writing and speaking

On-line literature search methods.

Interpreting your observations.

Presenting your findings.

Speaking and writing for the technical professions.

Analysing observations and choosing appropriate means of presenting research findings.

Science and scientific methodology: Epistemology, classification of research: theory development and testing; the deductive-inductive research process; and the role of independent and dependent variables.

Data collection techniques: Observational Techniques; Survey Techniques; Experimental Techniques

Assessment Procedure:

Presentation of a research seminar paper:

25% for the aural presentation

25% for the presentation (visual style and impact)

25% for the presentation (technical content)

25% for responses to questions

Indicative Sources:

  1. Booth, V. (1993) 'Communicating in science: writing a scientific paper and speaking at scientific meetings' Cambridge University Press

  2. Galliers, R. (1994) 'Information Systems Research :Issues, Methods and Practical Guidelines' McGraw-Hill Education - Europe 187247439X

  3. Turk, C and Kirkman, J (1995) 'Effective writing' 2nd E & FN Spon

  4. Williamson, K. (2002) 'Research Methods for Students, Academics and Professionals :Information Management and Systems' 2nd Centre for Information Studies, Charles Sturt University, NSW 1876938420

Course Title:

Advanced Algorithms

Course Code:

AA

Course Status:

Main

Recommended prior study:

Introduction to algorithms

Linear algebra

Learning outcomes:

This course introduces advanced algorithmic paradigms and applications. After completing the course, the student should know the main principles of design and analysis of algorithms. The student should know how to:

  1. Design and implement algorithms in the real world;

  2. Map problems to algorithmic problems;

  3. Understand the general notion of complexity classes, P and NP, completeness and hardness, and the relationships between classes by reduction.

Aims & Objectives:

The course covers a range of advanced algorithms in areas such as graph algorithms, string matching and network flows, the notion of complexity classes for algorithmic tasks, completeness and hardness. The main objective of this course is studying techniques for developing fast algorithms, particularly for optimization problems. For these problems there are typically a finite number of candidate solutions and the goal is to find an optimal solution (with min cost or max gain). To verify whether a candidate solution is optimal often requires non-trivial work. The other emphasis is on the correctness proofs.

Syllabus Contents (Main topics):

Graph Algorithms

Backtracking

Divide and Conquer

Network Flows

Dynamic Programming

Greedy Algorithms

String Matching Algorithms

Linear Programming. Duality

LP Relaxation

NP-completeness

Approximation Algorithms

Branch and Bounds Methodology

Assessment Procedure:

20% of the final mark is from homework exercises, 20% from the project, and 60% from the final exam.

Indicative Sources:

Literature is not mandatory, but the main issues of this course can be found from selected chapters of these


Books:

  1. Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest and Clifford Stein, Introduction to Algorithms, 2001

  2. Jon Kleinberg and Eva Tardos, Algorithm Design, 2005

  3. Dan Gusfield. Algorithms on Strings, Trees, and Sequences. Computer Science and Computational Biology, Cambridge University Press, 1997




Course Title:

Advanced Computer Architectures

Course Code:

ACA

Course Status:

Main

Recommended prior study:

Computer science fundamentals

Computer structure and organization

Computer architecture

Learning outcomes:

Students will understand the fundamental concepts and designs of advanced computer architectures including advanced instruction level parallelism, thread-level parallelism, and application specific processors. Students learn and develop their skills from simulator design and quantitative analysis of experimental results.

Aims & Objectives:

Students get acquainted with the architectural concepts of contemporary advanced computer systems. The course covers the advanced concepts of microprocessor architecture and microarchitecture, exploiting instruction-level and thread-level parallelism, multiple-issue processors. Parallel computer architectures are treated in the aspects of the abstract and physical machine models. The structure and organization of system area networks are studied. The spectrum of parallel architectures is studied including vector processors, symmetric shared-memory architectures, distributed shared-memory architectures, and multicomputers (massively parallel processors and clusters of workstations). Methods and approaches for performance estimation are presented for both uniprocessor and multiprocessor systems.

Syllabus Contents (Main topics):

Pipelined and superpipelined Processors

Superscalar Processor Design

ILP Exploitation

Advanced Speculation Techniques

Thread-Level Parallelism

Multicore processors

Data flow architectures

Advanced parallel computer architectures

Abstract and physical machine models

Parallel vector processors

Symmetric shared-memory architectures

UMA & NUMA cache coherent multiprocessor architecture

Massively parallel processors

Computer clusters architectural styles

Distributed shared memory architectures

GRID architectures

Assessment Procedure:

60% Exam, 40% Assignments

Indicative Sources:

Books:

  1. John Hennesy, David Patterson, Computer Architecture, A Quantitative Approach, Morgan Kaufmann Publishers, 2003.

  2. Theo Ungerer, Parallelrechner und parallele Programmierung, Spektrum Akademischer, Verlag Heidelberg Berlin, 1997.

  3. Brinkschulte Ungerer, Mikrocontroller und Mikroprozessoren, Springer, 2002.

  4. Kai Hwang, Zhiwei Xu, Scalable Parallel Computing, McGraw-Hill, 1998.

  5. Michael Flynn, Computer Architecture (Pipelined and Parallel Processor Design), Jones and Bartlett Publishers, 1995.

  6. Harry Jordan, Gita Alaghband, Fundamentals of Parallel Processing, Prentice Hall, 2003.
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