Read Credit-Based B.A.(Hons) in Computing text version

The Hong Kong Polytechnic University

Department of Computing

Definitive Programme Document / Programme Booklet for Bachelor of Science (Honours) Scheme in

Computing

Programme Code: 61031

September 2006

Table of Contents Part 1: 1.1 General Information Introduction

1.1.1 Scheme Title............................................................................ 1.1.2 Scheme Code............................................................................... 1.1.3 Programme Titles........................................................................ 1.1.4 Programme Codes..................................................................... 1.1.5 Host Department....................................................................... 1.1.6 Mode of Attendance & Duration...................................................... 1.1.7 Programme Structure...................................................................... 1.1.8 Final Awards............................................................................. 1.1.9 Double Degree Awards............................................................... 1.1.10 Implementation Date under CBS...................................................

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1 1 1 1 1 1 1 1 1 1 2 3 3 4 4 4

1.2 1.3

Entrance Requirements.......................................................... Aims, Objectives and Outcomes of the Programmes........................

1.3.1 BSc (Hons) in Computing Programme............................................. 1.3.2 BSc (Hons) in Information Technology Programme.................................. 1.3.3 BSc (Hons) in Enterprise Information Systems........................................ 1.3.4 Outcomes....................................................................................

Part 2: 2.1 2.2

Programme Structure and Curriculum Design Programme Structure................................................................... Normal Pattern of Study.........................................................

2.2.1 Sample Study Pattern for BSc in Computing...................................... 2.2.2 Sample Study Pattern for BSc in Information Technology...................... 2.2.3 Sample Study Pattern for BSc in Enterprise Information Systems.............. 6 7 11 12 13 14 14

2.3 2.4 2.5

Work Integrated Education (WIE).............................................. Additional Subjects............................................................... Programme Award

2.5.1 Minimum and Maximum Credits for the Programme Award...................... 2.5.2 Normal and Maximum Periods Allowed............................................. 2.5.3 Minimum and Maximum Credits Per Semester.................................... 2.5.4 Credit Transfer........................................................................... 2.5.5 Language Requirements.............................................................. 2.5.6 General Education Requirements................................................... 2.5.7 Co-curricular Activity Requirements................................................ 2.5.8 Eligibility for Award.................................................................. 2.5.9 Award Classification..................................................................

15 16 16 16 16 17 17 17 17 18 18 18 18

2.6

Major / Minor / Double Degree and Transfer.................................

2.6.1 Major and Minor....................................................................... 2.6.2 Double Degree......................................................................... 2.6.3 Transfer between Programmes......................................................

2.7

General Assessment Regulations (GAR)......................................

2.7.1 Assessment of a subject............................................................... 2.7.2 Retaking of Subjects.................................................................. 2.7.3 GPA Calculations..................................................................... 2.7.4 Progression/ Academic Probation/ Deregistration................................ 2.7.5 Classification of Awards.............................................................. 2.7.6 Exceptional Circumstances........................................................... 2.7.7 Plagiarism..............................................................................

20 20 21 22 23 23 24 25 26 26 26 26

2.8

Work Integrated Education (WIE) Administration...........................

2.8.1 Intended Learning Outcomes of the WIE Component........................... 2.8.2 Structure of the WIE Component................................................... 2.8.3 Assessment of the WIE Component................................................

Part 3: 3.1

Programme Management, Resource and Support Programme Operation and Management......................................

3.1.1 Departmental Learning and Teaching Committee................................. 3.1.2 Subject Assessment Review Panel (SARP)......................................... 3.1.3 Board of Examiners (BoE)........................................................... 28 28 29 29 30 30 30 31 31 33

3.2

Facility and Support..............................................................

3.2.1 Computing Facilities.................................................................... 3.2.2 Computing Hardware...................................................................... 3.2.3 Computing Software.................................................................. 3.2.4 Computing Laboratories.............................................................. 3.2.5 WebCT Teaching and Learning Support...........................................

Part 4: 4.1

Subject Syllabi Detailed Subject Description Forms........................................ ........

Level 1 Subjects AMA103 AMA105 AP101 APSS184 COMP100 COMP102 COMP111 ELC1004 ELC1005 Foundation Mathematics I for Science and Engineering------------Logic: Qualitative and Quantitative-----------------------------------College Physics I---------------------------------------------------------Understanding the Hong Kong Community--------------------------Introduction to Information Technology------------------------------Enterprise Information Technology-----------------------------------Information Technology Systems--------------------------------------English for University Studies I----------------------------------------English for University Studies II----------------------------------------

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35 37 39 41 44 46 48 50 52

Level 2 Subjects AF2104 Business Accounting----------------------------------------------------AF2108 Financial Accounting----------------------------------------------------AMA211 Introduction to Calculus and Linear Algebra-------------------------COMP201 Principles of Programming---------------------------------------------COMP210 Discrete Structures-------------------------------------------------------COMP211 Data and System Modeling---------------------------------------------COMP212 Computer Organization and Systems----------------------------------EIE217 Digital System Design---------------------------------------------------EIE218 Analog and Digital Communications----------------------------------EIE239 Communication Fundamentals-----------------------------------------MM2021 Organization and Management-----------------------------------------MM2711 Introduction to Marketing------------------------------------------------

54 56 58 60 62 64 66 68 71 74 77 79

Level 3 Subjects COMP302 Foundations of Software Engineering----------------------------------COMP303 Human Factors & User Interfaces--------------------------------------COMP304 Operating Systems--------------------------------------------------------COMP305 Data Structures & Algorithms-------------------------------------------COMP309 System Programming-----------------------------------------------------COMP311 Foundations of Database Systems--------------------------------------COMP312 Computer Communications Networks--------------------------------COMP316 Object Oriented Methods for Information Systems Development-COMP318 Systems Simulation-------------------------------------------------------COMP319 Introduction to Multimedia Computing--------------------------------COMP320 Introduction to Internet Computing------------------------------------COMP321 Introduction to E-business-----------------------------------------------COMP322 Enterprise Information Systems Project Implementation------------COMP323 Foundations of Chinese Computing------------------------------------COMP324 Project Methodology and Implementation ---------------------------------COMP325 Information Systems Management-------------------------------------COMP326 Business Strategies and Enterprise Re-engineering------------------EIE339 Digital Transmission and Switching Systems-------------------------ELC3501 English for Engineering Students---------------------------------------Level 4 (SAND) Subjects COMP4000 Industrial Placement----------------------------------------------------Level 4 (FT) / (SAND) Subjects COMP406 Artificial Intelligence-----------------------------------------------------COMP407 Computer Graphics-------------------------------------------------------COMP408 Parallel & Distributed Computing--------------------------------------COMP416 Internetworking Protocols and Software-------------------------------COMP417 Data Warehousing & Data Mining Techniques in Business and Commerce---------------------------------------------------------------COMP418 Electronic Commerce-----------------------------------------------------COMP422 Multimedia Systems and Applications---------------------------------COMP431 Business Process and Workflow Management------------------------COMP432 Logistics Management---------------------------------------------------COMP433 Information Retrieval-----------------------------------------------------COMP434 Computational Models---------------------------------------------------COMP435 Biometrics and Security--------------------------------------------------COMP436 Middleware and Distributed Objects-----------------------------------COMP437 Mobile Computing--------------------------------------------------------COMP439 Game Programming------------------------------------------------------COMP440 Customer Relationship Management-----------------------------------COMP441 Software Testing and Quality Assurance------------------------------COMP442 Decision Support Systems-----------------------------------------------COMP443 Knowledge and Information Management----------------------------COMP444 Internet Infrastructure Security------------------------------------------COMP445 Software Process and Project Management---------------------------COMP446 Computational Finance---------------------------------------------------COMP447 Scientific Computing-----------------------------------------------------COMP448 Virtual Reality and Applications----------------------------------------COMP451 Final Year Project---------------------------------------------------------COMP452 Computing Professionals in Society------------------------------------EIE406 Advanced Internet Technologies and Applications-------------------EIE424 Distributed Systems and Network Programming---------------------EIE429 Corporate Networking----------------------------------------------------EIE445 Cellular Communication Systems---------------------------------------

81 83 85 87 89 92 95 97 100 102 104 107 110 113 116 119 121 123 126

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130 133 135 138 141 144 146 149 151 153 155 157 159 161 164 167 169 171 174 177 180 183 185 188 191 195 198 201 204 206

Part 1: General Information

1.1 Introduction 1.1.1 1.1.2 1.1.3 Scheme Title Scheme Code Programmes Titles : Undergraduate Scheme in Computing : 61031 : Bachelor of Science (Honors) in Computing Bachelor of Science (Honors) in Information Technology Bachelor of Science (Honors) in Enterprise Information Systems : 61031-FCS / 61031-SCS 61031-FIT / 61031-SIT 61031-FIS / 61031-SIS 61031-DMM / 61031-SMM 61031-DLS / 61031-SLS 61031-ECS / 61031-EIT / 61031-EIS : Department of Computing : Full-time - 3 years normal and 6 years maximum Sandwich - 4 years normal and 7 years maximum One more year for foundation year admittees : Credit-based : BSc (Honors) Degree in Computing BSc (Honors) Degree in Information Technology BSc (Honors) Degree in Enterprise Information Systems BSc (Honors) Degree in Computing / BBA (Honors) Degree in Management BSc (Honors) Degree in Computing / BSc (Honors) Degree in Geomatics (Geo-IT) : September 2005

1.1.4

Programme Codes

1.1.5 1.1.6

Host Department Mode of Attendance & Duration

1.1.7 1.1.8

Programme Structure Final Awards

1.1.9

Double Degree Awards

1.1.10

Implementation Date under CBS

This Definitive Programme Document is subject to review and changes which the Programme Host Faculty/Department/School can decide to make from time to time. Students will be informed of the changes as and when appropriate.

BSc (Hons) Scheme in Computing (FT/SAND) ­ Definitive Programme Document / Programme Booklet 2006/07

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1.2

Entrance Requirements Applicants must have the minimum of: EITHER (a) either Grade E in two AL subjects (other than those specified below) or and (b) (c) Grade E in AS Use of English; and Grade E in AS Chinese Language & Culture or Grade E in AL Chinese Language & Literature or Grade D in a Language other than Chinese and English at HKCEE; and (d) Grade E in five subjects at HKCEE including grade C or above in Mathematics or Additional Mathematics (or a pass in AL/ASL Mathematics). OR (e) Higher Diploma or Associate Degree in Computing Studies or an equivalent discipline. OR (f) Diploma with Credit in Computing Studies or an equivalent discipline. Grade E in one AL subject (other than those specified below), and two AS subjects (other than those specified below);

Applicants who have completed a course of study deemed equivalent to Year 1 of the programme may be considered for direct entry to Year 2 with an Advanced Standing Status. Applicants may be required to meet additional criteria due to the evolution of the programme. Applicants to foundation year (stage 0) are evaluated based on a 6-year high school and 4-year university curriculum structure. For instance, applicants from China are evaluated based on JEE. Currently, the university is admitting some non-local students to the foundation year.

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1.3

Aims, Objectives and Outcomes of the Programmes According to Wikipedia, an encyclopedia written through cooperative efforts of many contributors over the web, Information Technology (IT), also known as Information and Communications Technology (ICT), is concerned with the use of technology in managing and processing information, especially in large organizations. In particular, IT deals with the use of computers and computer software to convert, store, protect, process, transmit, and retrieve information. Furthermore, the public (reflected by the writers of Wikipedia) takes the view point that computer professionals are often called IT specialists / consultants or Business Process Consultants. In other words, the business flavour should be an integral element and our programmes have maintained this in our curriculum. The main aims and objectives of the Undergraduate Scheme in Computing are to provide Professional IT education at the degree level to students so that they can readily apply their skills in their IT jobs upon graduation and be all-rounded students. The scheme also lays the foundation for students should they elect to pursue future study, in both MSc or MPhil degrees. We aim at providing the necessary articulation for our students to the different MSc awards offered under our Postgraduate Scheme in Computing, whenever possible. Under the broad definition of IT, we distil the important elements comprising and supporting IT and structure them into three different programmes under the Undergraduate Scheme in Computing, with a difference in emphasis, under the common theme of Computing. The BSc (Hons) in Computing programme is the core Computing programme, with a balanced curriculum relevant to the traditional Computer Science (CS) programmes, and augmentation with practical elements and application natures in line with the mission of the University. The programme has a rather strong software flavour on systems development. The BSc (Hons) in Information Technology programme has a strong orientation towards hardware and networking aspects, to make it a balanced programme based on the three important pillars, namely software, hardware and networking (following the narrow definition of IT). It is a hybrid form of traditional Computer Engineering (CE) programme and Computer Science (CS) programme. On the other hand, the BSc (Hons) in Enterprise Information Systems programme steers away from hardware and possesses a much stronger flavour in information systems and their management aspects. Unlike traditional Management Information Systems (MIS) programmes, the EIS programme is designed to be a technical IS programme that trains graduates capable of developing systems, as well as to mange them effectively in businesses as well as enterprises.

1.3.1

BSc (Hons) in Computing Programme:

This programme is aimed at producing graduates with good fundamental computing concepts, sound intellectual and practical skills, and ability to creatively apply computing and related technologies to different information processing areas such as business, industry and public sectors. The programme is based upon computer science, with a strong application element being emphasized. This programme is continuously kept up to date with state-of-the art technology and the transfer of knowledge through support of strong applied research (research underpinning teaching). Graduates are trained to be responsive to technical and human aspects of computing. They are prepared with the ability to continue personal development and progress with the evolution in the computing discipline. Particularly, they are equipped with essential system development

BSc (Hons) Scheme in Computing (FT/SAND) ­ Definitive Programme Document / Programme Booklet 2006/07

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and system integration knowledge that can contribute to the development of Hong Kong and China in the new century.

1.3.2

BSc (Hons) in Information Technology Programme:

This programme is designed to train and equip students to become competent and effective IT professionals. They will learn core knowledge from the three pillars in IT, namely software, hardware, and networking, with additional techniques in problem solving, system integration, user interface design, and IT professionalism. This programme is continuously kept up to date with state-of-the art technology and the transfer of knowledge through support of strong applied research (research underpinning teaching). With support from Electronic and Information Engineering Department expertise on the hardware aspects, students are exposed to the frontier applied technologies. Graduates will have a good foundation in the three core technologies, with which they can solve real-world problems in a disciplined and integrated manner, and capable of performing complex system integration that involves varieties of hardware and firmware. They are expected to contribute to the development of Hong Kong and China in the new century.

1.3.3

BSc (Hons) in Enterprise Information Systems Programme:

This programme is aimed at producing graduates who can manage business projects in the commercial sector, with strong hands-on skills and thorough understanding of the state-of-the-art technologies and their applicability in solving real commercial problems for enterprises. Graduates are trained to be strong in project management, planning and the logistics of human resource deployment, from a management perspective, besides the essential technical skill they need in realizing those projects. They are expected to be able to take up real-life business projects readily, and be able to take a leading role in the information system management and development process. They are also trained with a more global outlook towards IT strategies for an enterprise, including international ones, so that they will be able to contribute to the development of Hong Kong and China in the new century.

1.3.4

Outcomes:

The Undergraduate Scheme in Computing is an outcome-oriented programme. In line with the Strategic Objective 1.1 of the Hong Kong Polytechnic University, students should be nurtured to become all-round upon graduation. The outcome-oriented programme is designed to be geared towards the objective. Learning outcomes are associated with the programme as a whole, as well as with each individual subject. There are two specific categories of learning outcomes, namely Category A and Category B. Category A outcomes are tied to the development of professional and academic knowledge and skills and Category B outcomes are relevant to the attributes of all-roundness. Upon finishing the constituent programmes, students graduating from the scheme would be achieving the programme learning outcomes. Double degree graduates are expected to fulfil the corresponding single degree programme outcomes.

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The Outcomes of the Undergraduate Scheme in Computing are listed below, in which each programme has a more specialized outcome relevant to its focus of study. In particular, students graduating with a degree from the scheme should be able to: 1. communicate effectively in Chinese and English verbally at a level sufficient for general project and system presentation, as well as general conversation (B); 2. communicate in writing with technical documents comprehensible to peers, users and managers (B); 3. demonstrate a global outlook in factors that can affect the way computing systems are developed and used (B); 4. understand and value ethical issues in design and development of computing systems, in safeguarding information therein and in developing dependable systems as computing professionals and engineers (A/B); 5. think and reason in a creative manner, especially in applying computing and related technologies to different information processing areas, such as business, industry and public sector (A/B); 6. think and reason critically on different alternatives in problem solving and application development, and be able to design and evaluate for the proper solution (A/B); 7. possess technical knowledge in solving computing problems and to realize solutions in programming and associated technology (A); 8. be responsive to and follow closely the advancement in information technologies, staying tuned to the impact and application of state-of-the-art technologies, with an attitude of continuous and lifelong learning (A/B); 9. understand and keep an open eye on the industry advancement and its influence on the need of information technology (A/B); 10. work together as a team in project design and development, while exhibiting leadership in a group or team whenever designated or necessary (B); 11. achieve specialized outcomes with respect to constituent programmes (A): a. BSc (Hons) in Computing: solve problems and develop generic and/or specialized solutions with computing and information technologies in different application areas. b. BSc (Hons) in Information Technology: possess a vision for and an ability to integrating large interconnected systems with hardware, software and networking. c. BSc (Hons) in Enterprise Information Systems: understand the commercial needs from both computing and management perspectives and be able to develop information systems that are readily useful to businesses and enterprises.

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Part 2: Programme Structure and Curriculum Design

2.1 Programme Structure Excluding sandwich year, normal students in the Undergraduate Scheme in Computing will complete any one of the three programmes in three years. Students admitted into foundation year (stage 0), following a four-year university curriculum will need one more year. The first year (stage 1) is the basic or fundamental year for Computing discipline, in which students will learn the fundamental knowledge in the area of computing, as well as in the relevant supporting disciplines, such as mathematics, management and English. The fundamental knowledge is essential for students to build up their problem solving skills. The second year (stage 2) is the broadening year, in which students will accumulate more knowledge in computing, at an intermediate level. The subjects lay the necessary breadth for them to select subjects or streams according to their interest in their final year. The final year (stage 3) is the specialization year, in which students will choose a number of subjects that he/she likes most that will give him/her more in-depth knowledge in the selected computing discipline. An important feature of BSc Scheme in Computing is that there is a good variety of elective subjects for which students can build for their interests. Students in the BSc in Computing programme can elect to proceed towards the double degree. What they need to do is to select the minor option, with a minor in Management or a minor in Geomatics (Geo-IT). They can then receive a major/minor degree in Computing after completing stage 3 and with a top-up year taking subjects in the minor discipline, the double degree. The diagram below illustrates the basic progression pattern. The dotted rectangle in the middle defines the progression pattern for the three programmes (single degree) and the complete picture indicates the progression pattern for double degree students. Admission into the foundation year of study is normally conducted via AECO. The foundation year study is focused in the general discipline. Subjects include generic science and engineering subjects, language subjects and cultural subjects, to prepare them for university life. This is indicated on the left in the diagram.

Stage 0 Stage 1

Physics, Maths Information Tech English, HK Community

Foundation year

Fundamental year

Programming Operating system Data structure

minor option (only for BScC)

Summer employment

Networking Database Software Engineering

Broadening year

Stage 2

Broadening year with minor subject

Management Geomatics (Geo-IT)

Stage 2

Industrial placement

Specialization year

E-commerce Mobile computing Biometrics Data mining

Industrial placement Stage 3 Stage 3

Specialization year with minor subject Management Geomatics (Geo-IT)

Double degree in BBA Management BSc Geomatics(Geo-IT)

Top-up year in minor

Stage 4

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2.2

Normal Pattern of Study The Bachelor of Science Scheme in Computing curriculum is summarized below. Normally, the subjects should be completed in three years (full-time) or four years (sandwich), unless a student has applied for self-paced study. Students admitted to foundation year will require one more year in stage 0.

Award BScIT

Foundation year study 100 Introduction to Information Technology AMA 103 Foundation Mathematics I for Science and Engineering AP 101 College Physics I ELC 1004 English for University Studies I Level 1 Elective 1 111 Information Technology Systems AMA 105 Logic: Qualitative and Quantitative APSS 184 Understanding the Hong Kong Community ELC 1005 English for University Studies II Level 1 Elective 2 201 Principles of Programming 210 Discrete Structures 212 Computer Organization and Systems AMA 211 Introduction to Calculus and Linear Algebra ELC 3501 English for Engineering Students (1 credit per semester) General Education 1 (2 credits) 211 Data and System Modeling 304 Operating Systems 305 Data Structures and Algorithms ELC 3501 English for Engineering Students (1 credit per semester) MM 2021 Management and Organization

BScC Stage 0 Sem 1

100 Introduction to Information Technology AMA 103 Foundation Mathematics I for Science and Engineering AP 101 College Physics I ELC 1004 English for University Studies I Level 1 Elective 1 111 Information Technology Systems AMA 105 Logic: Qualitative and Quantitative APSS 184 Understanding the Hong Kong Community ELC 1005 English for University Studies II Level 1 Elective 2 201 Principles of Programming 210 Discrete Structures 212 Computer Organization and Systems AMA 211 Introduction to Calculus and Linear Algebra ELC 3501 English for Engineering Students (1 credit per semester) General Education 1 (2 credits) 211 Data and System Modeling 304 Operating Systems 305 Data Structures and Algorithms ELC 3501 English for Engineering Students (1 credit per semester) MM 2021 Management and Organization AF 2104 Business Accounting or AF 2108 Financial Accounting

BScEIS

100 Introduction to Information Technology AMA 103 Foundation Mathematics I for Science and Engineering AP 101 College Physics I ELC 1004 English for University Studies I Level 1 Elective 1 111 Information Technology Systems AMA 105 Logic: Qualitative and Quantitative APSS 184 Understanding the Hong Kong Community ELC 1005 English for University Studies II Level 1 Elective 2 201 Principles of Programming 210 Discrete Structures 212 Computer Organization and Systems AMA 211 Introduction to Calculus and Linear Algebra ELC 3501 English for Engineering Students (1 credit per semester) General Education 1 (2 credits) 211 Data and System Modeling 304 Operating Systems 305 Data Structures and Algorithms ELC 3501 English for Engineering Students (1 credit per semester) MM 2021 Management and Organization AF 2104 Business Accounting or AF 2108 Financial Accounting

Sem 2

Stage 1 Sem 1

Sem 2

Sem 1/2

IC training (optional) 31 credits

EIE 239 Communication Fundamentals IC training (optional) 31 credits

IC training (optional) 31 credits

BSc (Hons) Scheme in Computing (FT/SAND) ­ Definitive Programme Document / Programme Booklet 2006/07

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Stage 2 Sem 1

302 Foundations of Software Engineering 311 Foundations of Database Systems 312 Computer Communications Networks 303 Human Factors and User Interfaces 309 System Programming

302 Foundations of Software Engineering 311 Foundations of Database Systems 312 Computer Communications Networks

302 Foundations of Software Engineering 311 Foundations of Database Systems 312 Computer Communications Networks 303 Human Factors and User Interfaces 321 Introduction to E-business

EIE 217 Digital Systems Design EIE 218 Analog & Digital Communications Sem 2 320 Introduction to Internet Computing 324 Project Methodology and Implementation

324 Project Methodology and Implementation 322 Enterprise Information Systems Project Implementation EIE 339 Digital Transmission & Switching Systems 3-Elective 1 3-Elective 2 3-Elective 3

3-Elective 1 3-Elective 2 3-Elective 3 MM 2711 Introduction to Marketing 30 credits 30 credits 30 credits COMP 4000 Industrial Placement (0 credit, 24 training credits, optional) Stage 3 Sem 1 451 Final Year Project (4 credits) 452 Computing Professionals in Society 4-Elective 4 4-Elective 5 General Education 2 (2 credits) 451 Final Year Project (5 credits) 4-Elective 6 4-Elective 7 Elective 8 29 credits 90 credits · · 451 Final Year Project (4 credits) 452 Computing Professionals in Society 4-Elective 4 4-Elective 5 General Education 2 (2 credits) 451 Final Year Project (5 credits) 4-Elective 6 4-Elective 7 Elective 8 29 credits 90 credits 29 credits 90 credits 451 Final Year Project (4 credits) 452 Computing Professionals in Society 4-Elective 4 4-Elective 5 General Education 2 (2 credits) 451 Final Year Project (5 credits) 4-Elective 6 4-Elective 7 Elective 8

3-Elective 1 3-Elective 2 3-Elective 3

Sem 2

Total

3-Elective and 4-Elective means level 3 and level 4 electives respectively. Students need to take at least 5 core elective subjects for their award.

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The list of electives is as below (note that the electives are subject to change, and may not be offered every year). Some electives like COMP 320 are compulsory in some award.

Level 1 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 3 4 4 4 4 Subject 102 Enterprise Information Technology 316 Object Oriented Methods for Information Systems Development 318 Systems Simulation 319 Introduction to Multimedia Computing 320 Introduction to Internet Computing 321 Introduction to E-business 323 Foundations of Chinese Computing 325 Information System Management 326 Business Strategies and Enterprise Re-engineering 406 Artificial Intelligence 407 Computer Graphics 408 Parallel and Distributed Computing 416 Internetworking Protocols and Software 417 Data Warehousing and Data Mining Techniques in Business and Commerce 418 Electronic Commerce 422 Multimedia Systems and Applications 431 Business Process and Workflow Management 432 Logistics Management 433 Information Retrieval 434 Computational Models 435 Biometrics and Security 436 Middleware and Distributed Objects 437 Mobile Computing 439 Game Programming 440 Customer Relationship Management 441 Software Testing and Quality Assurance 442 Decision Support Systems 443 Knowledge and Information Management 444 Internet Infrastructure Security 445 Software Process and Project Management 446 Computational Finance 447 Scientific Computing 448 Virtual Reality and Applications EIE 319 System Engineering and Analysis EIE 406 Advanced Internet Technologies and Applications EIE 424 Distributed Systems and Network Programming EIE 429 Corporate Networking EIE 445 Cellular Communication Systems BScC Foundation year elective Core Core Compulsory Exclusion Exclusion Exclusion Core Core Core Core Core Core Core Core Core Core Core Core Core Core Exclusion Exclusion Exclusion Core Exclusion Core Core Core Core Core Core Core Core Compulsory Core Core Award BScIT Foundation year elective BScEIS Foundation year elective Exclusion Core

Exclusion Core Core Core Core Core Core

Exclusion Exclusion Exclusion Exclusion Exclusion

Core

Core

Exclusion Exclusion Exclusion Exclusion Exclusion

BSc (Hons) Scheme in Computing (FT/SAND) ­ Definitive Programme Document / Programme Booklet 2006/07

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Subject pre-requisites, weighting and other information are listed:

Year 1 1 1 1 1 1 1 2 2 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 Dept COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP COMP Subject 100 Introduction to Information Technology 102 Enterprise Information Technology 111 Information Technology Systems 201 Principles of Programming 210 Discrete Structures 211 Data and System Modeling 212 Computer Organization and Systems 302 Foundations of Software Engineering 303 Human Factors and User Interfaces 304 Operating Systems 305 Data Structures and Algorithms 309 System Programming 311 Foundations of Database Systems 312 Computer Communications Networks 316 Object Oriented Methods for Information Systems Development 318 Systems Simulation 319 Introduction to Multimedia Computing 320 Introduction to Internet Computing 321 Introduction to E-business 322 Enterprise Information Systems Project Implementation 323 Foundations of Chinese Computing 324 Project Methodology and Implementation 325 Information System Management 326 Business Strategies and Enterprise Reengineering 406 Artificial Intelligence 407 Computer Graphics 408 Parallel and Distributed Computing 416 Internetworking Protocols and Software 417 Data Warehousing and Data Mining Techniques in Business and Commerce 418 Electronic Commerce 422 Multimedia Systems and Applications 431 Business Process and Workflow Management 432 Logistics Management 433 Information Retrieval 434 Computational Models 435 Biometrics and Security 436 Middleware and Distributed Objects 437 Mobile Computing 439 Game Programming 440 Customer Relationship Management 441 Software Testing and Quality Assurance 442 Decision Support Systems 443 Knowledge and Information Management 444 Internet Infrastructure Security 445 Software Process and Project Management 446 Computational Finance 447 Scientific Computing 448 Virtual Reality and Applications 451 Final Year Project 452 Computing Professionals in Society Credit 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 9 3 Weight 1 1 1 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 Prerequisite 201, 210 201 201 201 304 201, 210 or 305 201, 302 201, 211 305, 311 201 201 311, 312, 321 201 302 302 305 305 304, 312 312 311 311, 320 319, 407 302 305, 311 210, 305, 309 211, 319 201 304, 311, 312 321 302 312 302 211, 417 211, 305 407 Contact Hours Lect T/L/S 14 42 28 14 14 42 14 42 28 14 28 14 28 14 28 14 28 20 28 14 28 21 28 14 28 14 28 28 28 28 28 28 28 28 28 21 28 28 28 28 30 35 28 28 28 28 28 28 28 30 28 28 24 28 28 28 28 28 24 28 28 28 14 14 14 14 14 14 14 14 14 21 14 14 14 14 12 7 14 14 14 14 14 14 14 12 14 14 18 14 14 14 14 14 18 14 14 240 14 Assessment CA Exam 100 0 60 40 60 40 60 40 60 40 55 45 55 45 60 40 65 35 55 45 60 40 55 45 55 45 55 60 55 55 55 60 70 55 70 55 60 55 60 55 55 55 55 55 55 60 55 55 55 55 55 55 60 55 55 55 60 55 60 55 60 100 100

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45 40 45 45 45 40 30 45 30 45 40 45 40 45 45 45 45 45 45 40 45 45 45 45 45 45 40 45 45 45 40 45 40 45 40 0 0

BSc (Hons) Scheme in Computing (FT/SAND) ­ Definitive Programme Document / Programme Booklet 2006/07

Besides subjects relevant to Computing, students are also required to take subjects related to language and general education. In particular, students are required to take an English language subject, ELC 3501, a common subject for Faculty of Engineering, with 2 credits. They are also required to take at least one 2-credit general education subject from the China Studies category and one 2-credit general education subject from the Broadening category during their 3 or 4 years of studies, with a minimum of 4 credits. General Education subjects may be offered by other universities (e.g. Chinese University of Hong Kong). The study patterns for double degree students are rather complicated. There are three options to a double degree: double major, full degree plus a major, and two full degrees (double degree). Before a student completes the top-up self-financed year of study for a double degree, a student upon completion of 90 credits can opt to graduate with a major/minor option, i.e. major in Computing / minor in Management and major in Computing / minor in Geomatics (Geo-IT). Please refer to the booklets Double Degree for Computing Students: BSc in Computing and BBA in Management, and Double Degree for Computing Students: BSc in Computing and BSc in Geomatics (Geo-IT) for specific details. 2.2.1 Sample Study Patterns for BSc in Computing Students in BSc in Computing enjoy a large pool of elective subjects. By orienting their elective subjects towards specific themes, they could become specialized in certain stream of Computing study. We give three examples in this section, with the core subjects highlighted.

Stream Year 1 Sem 1 Internet and E-commerce Foundation 201 Principles of Programming 210 Discrete Structures 212 Computer Organization and Systems AMA 211 Introduction to Calculus and Linear Algebra ELC 3501 English for Engineering Students General Education 1 211 Data and System Modeling 304 Operating Systems 305 Data Structures and Algorithms ELC 3501 English for Engineering Students MM 2021 Management and Organization AF 2104 Business Accounting Broadening 302 Foundations of Software Engineering 311 Foundations of Database Systems 312 Computer Communications Networks 303 Human Factors and User Interfaces 309 System Programming 320 Introduction to Internet Computing Digital Entertainment 201 Principles of Programming 210 Discrete Structures 212 Computer Organization and Systems AMA 211 Introduction to Calculus and Linear Algebra ELC 3501 English for Engineering Students General Education 1 211 Data and System Modeling 304 Operating Systems 305 Data Structures and Algorithms ELC 3501 English for Engineering Students MM 2021 Management and Organization AF 2104 Business Accounting 302 Foundations of Software Engineering 311 Foundations of Database Systems 312 Computer Communications Networks 303 Human Factors and User Interfaces 309 System Programming 320 Introduction to Internet Computing High Performance Systems 201 Principles of Programming 210 Discrete Structures 212 Computer Organization and Systems AMA 211 Introduction to Calculus and Linear Algebra ELC 3501 English for Engineering Students General Education 1 211 Data and System Modeling 304 Operating Systems 305 Data Structures and Algorithms ELC 3501 English for Engineering Students MM 2021 Management and Organization AF 2104 Business Accounting 302 Foundations of Software Engineering 311 Foundations of Database Systems 312 Computer Communications Networks 303 Human Factors and User Interfaces 309 System Programming 320 Introduction to Internet Computing

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Sem 2

Year 2 Sem 1

Sem 2

BSc (Hons) Scheme in Computing (FT/SAND) ­ Definitive Programme Document / Programme Booklet 2006/07

Year 3 Sem 1

324 Project Methodology and Implementation 316 Object Oriented Methods for Information Systems Development 321 Introduction to E-business 325 Information System Management Specialization 451 Final Year Project 452 Computing Professionals in Society 417 Data Warehousing and Data Mining Techniques in Business and Commerce 432 Logistics Management

324 Project Methodology and Implementation 316 Object Oriented Methods for Information Systems Development 318 Systems Simulation 319 Introduction to Multimedia Computing 451 Final Year Project 452 Computing Professionals in Society 406 Artificial Intelligence

324 Project Methodology and Implementation 316 Object Oriented Methods for Information Systems Development 318 Systems Simulation 323 Foundations of Chinese Computing 451 Final Year Project 452 Computing Professionals in Society 408 Parallel and Distributed Computing 417 Data Warehousing and Data Mining Techniques in Business and Commerce General Education 2 451 Final Year Project 433 Information Retrieval 434 Computational Models 447 Scientific Computing

407 Computer Graphics

Sem 2

General Education 2 451 Final Year Project 416 Internetworking Protocols and Software 418 Electronic Commerce 433 Information Retrieval

General Education 2 451 Final Year Project 435 Biometrics and Security 439 Game Programming 448 Virtual Reality and Applications

2.2.2

Sample Study Patterns for BSc in Information Technology Students in BSc in Information Technology enjoy a large pool of elective subjects, inclusive of EIE subjects. By orienting their elective subjects towards specific themes, they could become specialized in certain stream of Information Technology study. We give three examples in this section, with the core subjects highlighted.

Stream Year 1 Sem 1

Sem 2

Year 2 Sem 1

Internet Communications Systems Foundation 201 Principles of Programming 210 Discrete Structures 212 Computer Organization and Systems AMA 211 Introduction to Calculus and Linear Algebra ELC 3501 English for Engineering Students General Education 1 211 Data and System Modeling 304 Operating Systems 305 Data Structures and Algorithms ELC 3501 English for Engineering Students MM 2021 Management and Organization EIE 239 Communication Fundamentals Broadening 302 Foundations of Software Engineering 311 Foundations of Database Systems 312 Computer Communications Networks EIE 218 Analog & Digital Communications EIE 217 Digital Systems Design

Multimedia Systems

Integration Technology

201 Principles of Programming 210 Discrete Structures 212 Computer Organization and Systems AMA 211 Introduction to Calculus and Linear Algebra ELC 3501 English for Engineering Students General Education 1 211 Data and System Modeling 304 Operating Systems 305 Data Structures and Algorithms ELC 3501 English for Engineering Students MM 2021 Management and Organization EIE 239 Communication Fundamentals 302 Foundations of Software Engineering 311 Foundations of Database Systems 312 Computer Communications Networks EIE 218 Analog & Digital Communications EIE 217 Digital Systems Design

201 Principles of Programming 210 Discrete Structures 212 Computer Organization and Systems AMA 211 Introduction to Calculus and Linear Algebra ELC 3501 English for Engineering Students General Education 1 211 Data and System Modeling 304 Operating Systems 305 Data Structures and Algorithms ELC 3501 English for Engineering Students MM 2021 Management and Organization EIE 239 Communication Fundamentals 302 Foundations of Software Engineering 311 Foundations of Database Systems 312 Computer Communications Networks EIE 218 Analog & Digital Communications EIE 217 Digital Systems Design

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Sem 2

EIE 339 Digital Transmission & Switching Systems 324 Project Methodology and Implementation 318 Systems Simulation 319 Introduction to Multimedia Computing 320 Introduction to Internet Computing Specialization 451 Final Year Project 452 Computing Professionals in Society 408 Parallel and Distributed Computing EIE 445 Cellular Communication Systems General Education 2 451 Final Year Project 444 Internet Infrastructure Security EIE 439 Corporate Communication Networks 416 Internetworking Protocols and Software

EIE 339 Digital Transmission & Switching Systems 324 Project Methodology and Implementation 316 Object Oriented Methods for Information Systems Development 319 Introduction to Multimedia Computing EIE 319 System Engineering and Analysis 451 Final Year Project 452 Computing Professionals in Society 407 Computer Graphics 408 Parallel and Distributed Computing General Education 2 451 Final Year Project 422 Multimedia Systems and Applications 433 Information Retrieval 448 Virtual Reality and Applications

EIE 339 Digital Transmission & Switching Systems 324 Project Methodology and Implementation 316 Object Oriented Methods for Information Systems Development 320 Introduction to Internet Computing EIE 319 System Engineering and Analysis 451 Final Year Project 452 Computing Professionals in Society 437 Mobile Computing EIE 406 Advanced Internet Technologies and Applications General Education 2 451 Final Year Project 416 Internetworking Protocols and Software 436 Middleware and Distributed Objects 444 Internet Infrastructure Security

Year 3 Sem 1

Sem 2

2.2.3

Sample Study Patterns for BSc in Enterprise Information Systems Students in BSc in Enterprise Information Systems enjoy a large pool of elective subjects. By orienting their elective subjects towards specific themes, they could become specialized in certain stream of Enterprise Information Systems study. We give three examples in this section, with the core subjects highlighted.

Stream Year 1 Sem 1

Sem 2

Year 2 Sem 1

E-business Foundation 201 Principles of Programming 210 Discrete Structures 212 Computer Organization and Systems AMA 211 Introduction to Calculus and Linear Algebra ELC 3501 English for Engineering Students General Education 1 211 Data and System Modeling 304 Operating Systems 305 Data Structures and Algorithms ELC 3501 English for Engineering Students MM 2021 Management and Organization AF 2104 Business Accounting Broadening 302 Foundations of Software Engineering 311 Foundations of Database Systems 312 Computer Communications Networks 303 Human Factors and User Interfaces 321 Introduction to E-business

Software Engineering 201 Principles of Programming 210 Discrete Structures 212 Computer Organization and Systems AMA 211 Introduction to Calculus and Linear Algebra ELC 3501 English for Engineering Students General Education 1 211 Data and System Modeling 304 Operating Systems 305 Data Structures and Algorithms ELC 3501 English for Engineering Students MM 2021 Management and Organization AF 2104 Business Accounting 302 Foundations of Software Engineering 311 Foundations of Database Systems 312 Computer Communications Networks 303 Human Factors and User Interfaces 321 Introduction to E-business

Intelligent Business Systems 201 Principles of Programming 210 Discrete Structures 212 Computer Organization and Systems AMA 211 Introduction to Calculus and Linear Algebra ELC 3501 English for Engineering Students General Education 1 211 Data and System Modeling 304 Operating Systems 305 Data Structures and Algorithms ELC 3501 English for Engineering Students MM 2021 Management and Organization AF 2104 Business Accounting 302 Foundations of Software Engineering 311 Foundations of Database Systems 312 Computer Communications Networks 303 Human Factors and User Interfaces 321 Introduction to E-business

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Sem 2

Year 3 Sem 1

MM 2711 Introduction to Marketing 322 Enterprise Information Systems Project Implementation 320 Introduction to Internet Computing 325 Information System Management 326 Business Strategies and Enterprise Re-engineering Specialization 451 Final Year Project 452 Computing Professionals in Society 431 Business Process and Workflow Management 432 Logistics Management

MM 2711 Introduction to Marketing 322 Enterprise Information Systems Project Implementation 316 Object Oriented Methods for Information Systems Development 323 Foundations of Chinese Computing 325 Information System Management 451 Final Year Project 452 Computing Professionals in Society 431 Business Process and Workflow Management 441 Software Testing and Quality Assurance General Education 2 451 Final Year Project 436 Middleware and Distributed Objects 443 Knowledge and Information Management 445 Software Process and Project Management

MM 2711 Introduction to Marketing 322 Enterprise Information Systems Project Implementation 316 Object Oriented Methods for Information Systems Development 319 Introduction to Multimedia Computing 325 Information System Management 451 Final Year Project 452 Computing Professionals in Society 406 Artificial Intelligence 417 Data Warehousing and Data Mining Techniques in Business and Commerce General Education 2 451 Final Year Project 442 Decision Support Systems 443 Knowledge and Information Management 446 Computational Finance

Sem 2

General Education 2 451 Final Year Project 418 Electronic Commerce 440 Customer Relationship Management 442 Decision Support Systems

2.3

Work Integrated Education (WIE) The Hong Kong Polytechnic University is promoting Work Integrated Education (WIE) as one of the important mechanism to improve the all-roundedness of students. Department of Computing is in strong advocate and support of this. Students in the Undergraduate Scheme in Computing must accumulate at least 4 WIE credits before they can graduate. Double degree students only need to satisfy the WIE requirement of either degree. Major/minor students must satisfy the WIE requirement of their major, i.e. 4 credits. The one year placement will amount to 24 credits. The administration of WIE is elaborated in Section 7.

2.4

Additional Subjects Starting from 2002/03, students can take additional subjects, which are for personal interest only and will not be counted towards the award. The credits will be used for calculating the cumulative GPA but not the weighted GPA, which is for award classification purposes. Students can take a maximum of three additional subjects (9 credits), which can be selected from within or outside the BAC curriculum. No additional fees will be charged for flat-fee paying students, but students in the credit-fee paying scheme need to pay. No retake is necessary for any failed additional subjects, and for further information of these subjects, please refer to the subject registration facilities on the web.

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2.5

Programme Award 2.5.1 Minimum and Maximum Credits for the Programme Award

BScC students are required to complete a minimum of 90 credits as follows: (i) Compulsory subjects COMP 201, 210, 211, 212, 302, 303, 304, 305, 309, 311, 312, 320, 324, 451, 452 AMA 211, AF 2104/2108, MM 2021 8 elective subjects Mandatory language subjects: ELC 3501 2 General Education subjects 60 credits

(ii) (iii) (iv)

24 credits 2 credits 4 credits

BScIT students are required to complete a minimum of 90 credits as follows: (i) Compulsory subjects 60 credits COMP 201, 210, 211, 212, 302, 304, 305, 311, 312, 324, 451, 452 EIE 217, EIE 218, EIE 239, EIE 339, AMA 211, MM 2021 8 elective subjects Mandatory language subjects: ELC 3501 2 General Education subjects 24 credits 2 credits 4 credits

(ii) (iii) (iv)

BScEIS students are required to complete a minimum of 90 credits as follows: (i) Compulsory subjects COMP 201, 210, 211, 212, 302, 303, 304, 305, 311, 312, 321, 322, 451, 452 AMA 211, AF 2104/2108, MM 2021, MM 2711 8 elective subjects Mandatory language subjects: ELC 3501 2 General Education subjects 60 credits

(ii) (iii) (iv)

24 credits 2 credits 4 credits

--------------------------------------------------------Optional (i) 1 Computer Training Subject (2 modules) (The students can choose this training at will) 2 training credits

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Students admitted into foundation year of a 4-year curriculum need to complete a minimum of 120 credits, with 30 additional credits in stage 0 as follows: (i) Compulsory subjects COMP 100, COMP 111 AMA 103, AMA 105, AP 101, APSS 184 2 elective subjects Mandatory language subjects: ELC 1004, ELC 1005 Normal and Maximum Periods Allowed 18 credits

(ii) (iii)

6 credits 6 credits

2.5.2

The normal and maximum periods for completion of the awards (not counting the foundation year, if any) are 6 and 12 semesters respectively for the full-time mode, or 8 and 14 semesters respectively for the sandwich mode. For double degree students, the normal and maximum periods are 8 and 16 semesters respectively for the full-time mode, or 10 and 16 semesters respectively for the sandwich mode. Students choosing the sandwich mode undertake the industrial placement for 48 weeks only after successfully completing not less than 27 credits from Level 2, and 30 credits from Level 3 or 4. 2.5.3 Minimum and Maximum Credits Per Semester

The minimum and maximum number of credits per semester is 12 and 21 respectively. Students will not be allowed to take zero subjects in any semester unless they have obtained prior approval from the department; otherwise they will be classified as having unofficially withdrawn from their study. Any semester in which the students are allowed to take zero subjects will nevertheless be counted towards the maximum period of registration. (Academic Regulations and Procedures for Credit-based Programmes Section 24.2-3 of Chapter A3). 2.5.4 Credit Transfer

Students may apply for credit transfer at initial enrolment, re-enrolment or during add/drop period at the beginning of the semester. For procedural detail, please refer to the Student Handbook or consult the Programme Leader / Department's General Office. Credit transfer with grade is applicable normally only to subjects offered within the University. 2.5.5 Language Requirements

Students must pass ELC 3501 and the exit tests for English and Mandarin. (2 credits) 2.5.6 General Education Requirements

Students must pass two subjects: one broadening and one China Studies. (4 credits)

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2.5.7

Co-curricular Activity Requirements

Students are required to participate in at least one non-credit bearing co-curricular activity in order to satisfy the overall requirement of general education before graduation. Students will be considered as having fulfilled the requirement of cocurricular activities if they have participated in any one of the activities below. Students' participation in such activities will be recorded in the Co-curricular Achievement Transcript (CAT) administered by SAO. The co-curricular activities aim at rendering additional values, and helping students to broaden their horizons and inspiring them to actualize all-round development outside the classroom. Co-curricular activities include Complementary Studies Programme, Leadership and Competence for Success Programme, Physical Education Programmes, Personal Development Programmes, hall education programmes, pre-placement training / career training organized by SAO, seminars and lunch talks by prominent speakers, study tour or exchange activity offered / organized by the Faculty / the Department / supporting units, cultural appreciation programme, and any other activities in a variety of forms that the Department considers essential as part of the overall requirement of general education. Note that summer attachments, internships, mentorship programmes, community service and Work-Integrated Education form part of the formal programme curricular and will not be counted as co-curricular activities. 2.5.8 Eligibility for Award

A student would be eligible for award if he satisfies all the conditions listed below: (i) Accumulation of the requisite number of credits for the particular award, as defined in the definitive programme document, (ii) Satisfying all the 'compulsory' and 'elective' requirements as defined in the definitive programme document, and (iii) Having a Grade Point Average (GPA) of 2.0 or above at the end of the programme. 2.5.9 Award Classification

The weighted GPA (WGPA) is used to determine award classification. The weights for subjects in Level 1, Level 2, Level 3 and Level 4 are 0.1, 0.2, 0.3, and 0.4 respectively. The same weight is applied for all subjects in the same level.

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2.6

Major / Minor / Double Degree and Transfer 2.6.1 Major and Minor

The BSc Scheme in Computing is composed of three awards: BSc in Computing, BSc in Information Technology, BSc in Enterprise Information Systems. Both BSc in Information Technology and BSc in Enterprise Information Systems are full degrees. BSc in Computing can be a full degree, with curriculum depicted in Section 4. In addition, it provides the flexibility of a major / minor option. A student can graduate with a major / minor option with a major in BSc in Computing and a minor in any discipline offering a minor. A major in BSc in Computing needs to complete at least 54 credits in COMP subjects (including the compulsory subjects), plus AMA 211, MM 2021, AF 2104 or 2108, ELC 3501 and GE requirements. A minor normally requires the completion of at least 18 credits. There could be additional specific requirement for individual minors. Students are suggested to refer to the minor offering department for details. There are two special types of major / minor pairs: minor in Management and minor in Geomatics (Geo-IT). Both are the three-year exit version for the two double degrees. Student studying double degrees can opt to graduate after 3 years with the major / minor degree, if so desired, as long as they satisfy the major and minor requirements, complete 90 credits and GE, language, WIE and pass the language exit tests. A student opting for the major / minor option should complete a form AS-113 and submit to the department before the deadline. 2.6.2 Double Degree

There are three options to a double degree: double major, full degree and a major, and two full degrees. There are different credit requirements to each of these three options, as listed below. Option Degree BBA in Management BSc in Geometics (GeoIT) Double major 126 120 Full degree and major 132 129 Double degree 144 137

A student opting for the double degree should complete a form AS-113 and submit to the department before the deadline. Students pursuing double degree in BSc in Geometics (Geo-IT) are encouraged to apply early so as to catch the registration of LSGI subjects in semester 2. 2.6.3 Transfer between Programmes

There is a common first semester to the three awards, and a common first year between BSc in Computing and BSc in Enterprise Information Systems. The curriculum is designed for flexible transfer between the programmes. A student who wishes to transfer between programme should do that within the first year by completing the programme transfer form under Department of Computing.

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Transfer processed after 31 March will not be reflected within university time-table scheduling process and may risk the conflict in time-table for compulsory subjects in the coming year. Transfer may also be applied within the foundation year of study. Students beyond first year or those admitted with Advanced Standing status are normally not allowed to transfer.

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2.7

General Assessment Regulations (GAR) Academic regulations for assessment, progression, de-registration, re-assessment, subject retake, grading, award classification, subject registration, study deferment, subject exemption, and credit transfer, etc. are published in the University's document: Academic Regulations and Procedures for Credit-based Programmes. For BSc Scheme in Computing, the following additions shall apply: (a) To pass a subject a student must achieve the minimum passing grades in both coursework and examination designated by the teaching department. For some departments, it is considered a pass only when D grades or above are obtained for both the examination and the coursework components. For Department of Computing, there is a cap on the grade of D+ if a student fails one of the components. Only re-assessment of one subject is allowed per semester.

(b)

The following useful information (6.1 to 6.7) is extracted from the two documents: Academic Regulations and Procedures for Credit-based Programmes and the Student Handbook for your reference. 2.7.1 Assessment of a Subject

Students' performance in a subject shall be assessed by coursework and/or examinations and/or continuous assessment as depicted in individual subject syllabus. Coursework may include tests, assignments, projects, laboratory work, field exercises, presentations and other forms of classroom participation. The contribution made by each student in coursework involving a group effort shall be determined and assessed separately. Assessment grades shall be awarded on a criterion-referenced basis. At the beginning of each semester, the subject teacher will inform students of the details of the methods of assessments to be used within the assessment framework. Criteria would be given for each subject with respect to the expectation. Performance in the Coursework and/or Final Examination components will be assessed, according to the weighting factor of both components in a certain subject. For subjects offered by Department of Computing, a student does not need to pass both components in order to pass a subject. However, if a student fails in one component, he/she is deemed to be at best marginal. In other words, the maximum overall grade of the subject can only be D+. For subjects offered by other departments, the passing criteria may vary according to the syllabus. The grade conversion of assessment result is as specified in the General Assessment Regulations, according to the following table: Subject grade A+ Excellent A The student's work is excellent. It exceeds the subject learning outcomes in nearly all regards.

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Short description

Elaboration on subject grading description The student's work is outstanding. It exceeds the subject learning outcomes in all regards.

BSc (Hons) Scheme in Computing (FT/SAND) ­ Definitive Programme Document / Programme Booklet 2006/07

Subject grade B+

Short description

Elaboration on subject grading description The student's work is very good. It exceeds the subject learning outcomes in the majority of regards.

Good B The student's work is good. It exceeds the subject learning outcomes in some regards. The student's work is wholly satisfactory. It fully meets all the subject learning outcomes. Satisfactory C The student's work is satisfactory. It largely meets all the subject learning outcomes. The student's work is barely adequate. It fails marginally to meet all the subject learning outcomes. Marginal D The student's work is weak. It fails to meet the subject learning outcomes in some regards. Failure The student's work is inadequate. It fails to meet most of the subject learning outcomes.

C+

D+

F

The overall grade for a subject is obtained by combining the results for the Coursework and Final Examination, where applicable, using the weightings as specified in each subject syllabus. Numerical grade is defined for each letter grade for the computation of the GPA. Grade A+ A B+ B C+ C D+ D F Grade Point 4.5 4 3.5 3 2.5 2 1.5 1 0

All assessment grades must be endorsed by the respective Subject Assessment Review Panels. 2.7.2 Retaking of Subjects

Normally, students may retake only those subjects for which they have failed, i.e. obtained an F grade. Students are not allowed to retake subjects for which they have passed with grade C or above. Retaking of a subject which has been passed at grade D or D+ will require the approval of the Department. The number of retakes of a failed subject is not restricted. Only the grade obtained in the final attempt of retaking will be

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included in the calculation of the Grade Point Average (GPA). (The grades obtained in previous attempts will only be reflected in transcript of studies.) Note that this GPA calculation for retaking applies to the retake of the same subject only. In cases where a student takes another subject to replace a failed subject, the fail grade will be retained and taken into account in the calculation of the GPA, despite the passing of another subject. 2.7.3 GPA Calculations

The maximum GPA and weighted GPA is 4.0. Each subject level has a specific WEIGHTING FACTOR used in the calculation of the weighted GRADE POINT AVERAGE (GPA). The weighting factors for subjects in Level 1, Level 2, Level 3, and Level 4 are: 0.1, 0.2, 0.3 and 0.4 respectively, inclusive of subjects at foundation year. At the end of each semester, a student's performance will be defined in terms of the Grade Point Average (GPA) as follows: Subject Grade Point x Subject Credit Value n GPA = ------------------------------------------------------------------------- Subject Credit Value n where n = number of all subjects taken by the student including failed subjects. Exempted, ungraded or incomplete subjects, and subjects for which credit transfer has been approved without a grade assigned to it, will be excluded from the GPA calculation. In addition, subjects for which a student has been allowed to withdraw from (i.e. those with the grade code "W") will be excluded. A subject which has been given an "S" grade code (i.e. absent from examination), will be included in the GPA calculation and will be counted as "zero" grade point. The GPA is therefore the unweighted cumulative average, calculated for all subjects, including failed subjects, taken by a student from the start of the programme to a particular reference point in time. GPA is an indicator of overall performance. At the end of the final year, a student's overall performance or weighted GPA is calculated for award classifications as follows: Subject Grade Point x Subject Credit Value x Wi n Weighted GPA = ------------------------------------------------------------------------- Subject Credit Value x Wi n where Wi is the weight assigned to the subject level. Any subjects passed after the graduation requirement has been met or subjects taken on top of the prescribed credit requirements for award shall not be taken into account in the grade point calculation for award classification. However, if a student passes more elective subjects (or optional subjects) than the requirement for graduation in or before the semester within which he becomes eligible for award, the elective subjects (or optional subjects) with higher contribution (with the exception of the additional subjects taken out of interest and not for satisfying the award requirements) shall be

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counted in the grade point calculation for award classification (i.e. the passed subjects with lower contribution will be excluded from the grade point calculation for award classification), irrespective of when the excessive elective subjects (or optional subjects) are enrolled. 2.7.4 Progression/Academic Probation/Deregistration

The Board of Examiners shall, at the end of each semester, determine whether each student is (a) (b) (c) eligible for progression towards an award; or eligible for an award; or required to be deregistered from the programme.

When a student has a Grade Point Average (GPA) lower than 2.0, he will be put on academic probation in the following semester. Once when a student is able to pull his GPA up to 2.0 or above at the end of the probation semester, the status of "academic probation" will be lifted. The status of "academic probation" will be reflected in the examination result notification but not in transcript of studies. A student will have `progressing' status unless he falls within the following categories, either of which may be regarded as grounds for deregistration from the programme: (i) the student has exceeded the maximum period of registration for that programme as specified in the definitive programme document; or the student's GPA is lower than 2.0 for two consecutive semesters and his Semester GPA in the second semester is also lower than 2.0; or the student's GPA is lower than 2.0 for three consecutive semesters.

(ii)

(iii)

Notwithstanding Sections (ii) and (iii) above, a student may be deregistered from the programme enrolled before the time specified in Sections (ii) or (iii) above if his academic performance is poor to the extent that the Board of Examiners deems that his chance of attaining a GPA of 2.0 at the end of the programme is slim or impossible. 2.7.5 Classification of Awards

The following are guidelines for Boards of Examiners' reference in determining award classifications: Honours 1st Guidelines The student's performance/attainment is outstanding, and identifies him as exceptionally able in the field covered by the programme in question. The student has reached a standard of performance/ attainment which is more than satisfactory but less than outstanding.

2:i

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2:ii

3rd

The student has reached a standard of performance/ attainment judged to be satisfactory, and clearly higher than the `essential minimum' required for graduation. The student has attained the `essential minimum' required for graduation at a standard ranging from just adequate to just satisfactory.

A Pass-without-Honours degree award will be recommended only under exceptional circumstances, when the student has demonstrated a level of final attainment which is below the `essential minimum' required for graduation with Honours from the programme in question, but when he has nonetheless covered the prescribed work of the programme in an adequate fashion, while failing to show sufficient evidence of the intellectual calibre expected of Honours degree graduates. For example, if a student has a Grade Point Average (GPA) of 2.0 or more, but his Weighted GPA is less than 2.0, he may be considered for a Pass-without-Honours classification. There is no automatic link between the weighted GPA and the award classification; for instance, a weighted GPA of 3.7 does not automatically mean graduation with First Class Honours because award classification is a decision by the Board of Examiners. 2.7.6 Exceptional Circumstances

Absence from an assessment component If a student is unable to complete all the assessment components of a subject due to illness or other circumstances beyond his/her control, and considered by the Subject Assessment Review Panel as legitimate, the Panel will determine whether the student will have to complete the assessment and, if so, by what means. This assessment shall take place before the commencement of the following academic year (except that for Summer Term, which may take place within 3 weeks from the finalisation of Summer Term results). Aegrotat award If a student is unable to complete the requirements of the programme in question for the award due to very serious illness, or other very special circumstances which are beyond his/her control, and considered by the Board of Examiners as legitimate, the Faculty/School Board will determine whether the student will be granted an aegrotat award. Aegrotat award will be granted under very exceptional circumstances. A student who has been offered an aegrotat award shall have the right to opt either to accept such an award, or request to be assessed on another occasion to be stipulated by the Board of Examiners; the student's exercise of this option shall be irrevocable. The acceptance of an aegrotat award by a student shall disqualify him/her from any subsequent assessment for the same award. An aegrotat award shall normally not be classified, and the award parchment shall not state that it is an aegrotat award. However, the Board of Examiners may determine whether the award should be classified provided that they have adequate information on the students' academic performance. Other particular circumstances

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A student's particular circumstances may influence the procedures for assessment but not the standard of performance expected in assessment. 2.7.7 Plagiarism

Plagiarism is a very serious matter. All students should read the session on "Plagiarism and Bibliographic Referencing" which is provided in the Student Handbook. Students should also refer to the following departmental policy on plagiarism: First offence: zero marks on the plagiarised assignment/ continuous assessment for both the copycat and the one who offers to be copied and deduct additional marks that carries the same weight as the assessed component. For example, if a student is caught plagiarising on written assignment which contribute to 20% of the total grade, both the copycat and the one who offers to be copied will receive zero marks for 40% (i.e. 20% X 2) of the grade. For serious first offence, teaching staff can follow the penalty for serious or repeated offence. For serious or repeated offence: submit the case to the Student Discipline Committee and the final decision will be made by the Committee.

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2.8

Work Integrated Education (WIE) Administration Department will help to secure one year placement positions and with the help of SAO, maintain list of summer placement. The WIE supervisor of a student will be in charge of monitoring the progress of the student, who must actively report his/her progress and consult with industrial supervisor to align his/her work with the agreed upon learning outcomes (as stipulated in section 7.1 and 7.2) . WIE supervisor will provide advice and guidelines, and can interact with industrial supervisor to ensure that learning outcomes can be attained. 2.8.1 Intended Learning Outcomes of the WIE Component

After satisfying WIE requirement, a student should be able to know better how the industry works and be offered a chance to apply his/her technical skills in solving real problems. In general, student should improve on problem solving skills and critical thinking, in acquiring better global outlook in industrial standard and practices. More importantly, team spirit, communication and interpersonal skills will be developed. Depending on the actual placement job, the exact learning outcomes may vary and is to be set by student and endorsed by an academic staff serving as a WIE supervisor at the beginning of the WIE undertaking. 2.8.2 Structure of the WIE Component

There are two modes of WIE: one year industrial placement and summer placement. One year industrial placement consists of a working period of 48 weeks (roughly 11 months) in a company. The student will be placed to a company, through the department placement procedure normally taking place in semester 2 of year 2. A placement student receives salary and works under the supervision of industrial supervisor. This is considered as a formal subject COMP 4000 and will be assessed by the WIE supervisor. Occasional visits by WIE supervisor and submission of final report enables assessment to be done. A successfully completed industrial placement would normally be awarded 24 WIE credits, which belong to co-curricular credits. Summer placement or placement in other appropriate period requires students to look for jobs themselves. Department and SAO would help to provide job information. Student must inform department in advance to set up the learning outcome as well as the placement period, with respect to the particular case. Inappropriate training will be rejected and will not count towards WIE. For every two weeks of placement (during summer or term-break), one WIE (co-curricular) credit will be awarded. For certain cases, part-time employment may be acceptable, subject to prior approval by the department. In that case, one WIE credit corresponds to 78 hours of approved work. Assessment will be made at agreed upon checkpoints by the WIE supervisor, who can be an academic staff or his/her designate. A final report with assessment is needed for the passing grade and granting of WIE credits. A student can take summer or term-break placement in any year and must accumulate at least 4 WIE credits before he/she can graduate. Double degree students need only to satisfy the WIE requirement of either degree. 2.8.3 Assessment of the WIE Component

WIE is assessed continually. Each WIE registration must be accompanied with an agreement between the student, the placement company supervisor (called industrial

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supervisor), and the WIE supervisor from the department. The learning outcomes should be specified in an agreement form, which upon endorsement by the department, will be used as an evaluation yardstick against the student during the placement. Occasional visits by the WIE supervisor to the company or visit by students to WIE supervisor enable monitoring of student progress and alignment to learning outcome. Students must submit a written report detailing his/her achievement during the placement period, with a reflection on the learning outcomes attained. A passing grade is awarded only when the learning outcomes are basically met. Each placement interval, in case of multiple summer placements are pursued, must be accompanied by the same set of procedure. WIE training credits will not be counted towards the Grade Point Average (GPA) nor the Weighted GPA (WGPA).

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Part 3: Programme Management, Resource and Support

3.1 Programme Operation and Management The Undergraduate Scheme in Computing is managed by the Departmental Undergraduate Programme Committee stipulated by guidelines set by the University. This committee will be responsible for the academic standards, content, delivery and assessment of all undergraduate programmes within its purview. Specifically, the Departmental Undergraduate Programme Committee will comprise: · Head of Department; · Departmental Learning and Teaching Committee Chair; · Programme leader of each undergraduate programme; · representatives of subject lecturers from each programme; · representatives from co-hosting department for each double-degree programme; · student representatives from each programme. A small Programme Execution Group will manage the day-to-day operation of each constituent programme under the Undergraduate Scheme in Computing. The group will operate in an informal manner, being organized by the Award Coordinator/Programme Leader with approval from Head of Department. The Programme Execution Groups for the programmes report to the Departmental Undergraduate Programme Committee. The programme gets feedback from students through the Student/Staff Consultative Group, which is a window for students to contribute to better the programme. Two student representatives from each year are included from each award to participate in the student/staff consultative group. The group consists of the Head of Department, Award Coordinator, subject lecturers and student representatives. It will meet approximately twice a year for constructive discussion of the award and the scheme and of possible improvements, in a less formal context than the Scheme Committee. This group is comprised of: Programme Leader Programme Tutor Subject Leaders Student representatives (2 to 3 from each year). The programme tutor meets and helps students regularly. If it is necessary, he/she shall resolve student problems together with the Programme Leader and the Programme Committee. Other committees relevant to the management of the scheme include: 3.1.1 Departmental Learning and Teaching Committee

The Departmental Learning and Teaching Committee (DLTC) will be overseeing the operation and administration of all the awards hosted by the Department of Computing. It is formed under the regulations of the department and the university. Its main duties are: · To promote quality learning and teaching in the department, particularly at the classroom level, and at the teacher-student interface. · To keep under review the quality of learning and teaching in the department. · To develop strategies and guidelines relating to the enhancement of learning and teaching quality in the department. · To evaluate and prioritize proposals from departmental staff on learning and teaching development projects - for funding by the DLTC and other relevant

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·

agencies. To monitor progress of learning and teaching development projects carried out in the department. Subject Assessment Review Panel (SARP)

3.1.2

The examination and assessment arrangement conforms to the Academic Regulations & Procedures for Credit-based Programmes. The Department's Subject Assessment Review Panel (SARP) monitors the academic standard and quality of subjects and has complete discretion in ratifying subject grades to ensure consistency. It is also responsible for deciding upon the granting of re-assessment to students and the form of such re-assessment. The composition and terms of reference of the SARP are stipulated in the Academic Regulations and Procedures for Credit-based Programmes. 3.1.3 Board of Examiners (BOE)

A Board of Examiners (BoE) of the Scheme will meet at the end of each semester after the grades are endorsed by the SARP to consider students' classifications of award and to deal with problematic cases. The composition and terms of reference of the BoE are also stipulated in the Academic Regulations and Procedures for Credit-based Programmes. The BoE will consider and make decisions concerning the progression, academic probation, deregistration cases of students. In addition, it will decide on the eligibility for awards and award classification for graduating students.

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3.2

Facility and Support 3.2.1 Computing Facilities The Department attaches importance to the practical work of students. Academic programmes and research activities are well supported with a wide range of computing facilities available through the departmental Computing Laboratories (located at 6/F of PQ Wing and 4/F of QT Wing) and the University's Information Technology Services Office (ITS) via the departmental Local Area Network (LAN). The departmental LAN consists mainly of 100 Mbps UTP Ethernet segments interconnected together using the state-of-art gigabit network switches provided and maintained by the University. This departmental LAN is also connected to The Hong Kong Polytechnic University campus Gigabit Network and then to the Internet. The Internet connection is used heavily for web access, electronic mail, internet news, remote logins, file transfers, and other forms of interaction with the world-wide computing community. A wide variety of computing hardware and software is available to support both the undergraduate and postgraduate teaching. Most of the facilities are located in the laboratories mentioned in section 9.4. 3.2.2 Computing Hardware · · · · · · · · · · · · · · · · · · · · 4-CPUs Sun Fire 4800 Server 2-CPUs Sun Fire V880 Server 2-CPUs Sun Fire E280R Servers 10-CPUs Sun Ultra Enterprise 4000 Server 4-CPUs Sun Ultra Enterprise 3000 Server 2-CPUs Sun Ultra Enterprise 2 servers HP Blade BL20p G2 servers HP Proliant DL 380 G3 servers HP Proliant 7000 Xeon P3/500 PC servers Cisco Dial-in Modem servers Castelle FAXpress server Pentinum-3 and -4 PCs Sun Blade 150 workstations Sun UltraSPARC 5 workstations Sun UltraSPARC 30 workstations HP LaserJet Printers HP Colour Laser Printers HP Colour Scanners Epson Color Inkjet printers Orinoco Wireless Access points

3.2.3

Computing Software

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· · · · ·

· ·

· · · ·

· ·

Data mining and warehousing tool - Clementine Data Mining Database management system - Oracle - Microsoft SQL Server Project management software - Microsoft Project Distributed computing software - MPI - Visibroker Graphics tools - Virtool - Adobe PhotoShop - Microsoft Visio 2000 Office software - Microsoft Office XP/2000 Operation system software - MS Win XP/2000/98 - Novell Netware - RedHat Linux Programming language - Java - Microsoft Visual Studio.Net Simulation packages - CSIM - ALPHA-Sim Software Engineering packages - Rational Rose Statistical and Mathematical analysis tools - Matlab - SAS - SPSS Web Publishing - Macromedia Dreamweaver - Microsoft FrontPage Web Server software - Apache/Tomcat

3.2.4

Computing Laboratories

Project laboratory - located on 6/F of PQ Wing - dedicated to the final year Undergraduate students, who carry out their final year project implementations - equipped with Wireless Access point for notebook PC connection to departmental LAN - supported by 4 sets of Sun UltraSPARC 5 workstations, 36 sets of Pentium-4 PCs, a HP Color scanner and a high speed HP Laser printer Student laboratory

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- located both on 6/F of PQ Wing and 4/F of QT Wing - provide a general computing environment for student's work - equipped with Wireless Access point for user's notebook PC connection to departmental LAN - supported by a total of 15 sets of Pentium-4 PCs, 1 sets of Sun UltraSPARC 5 workstations, 1 set of HP Color Scanner, 1 set of Epson Color Inkjet printer and 5 sets of high speed HP Laser printer PC laboratory (4 rooms) - located on 6/F of PQ Wing and 4/F of QT Wing - provides the facilities for basic and advanced programming on the Window environment for all students in the department - serves as an instruction laboratory with overhead LCD projectors during some class hours - supported by a total of 135 sets of Pentium-4 PCs PC/Unix laboratory - located on 6/F of PQ Wing - provides a mix of Window and Unix computing environment - serves as an instruction laboratory with overhead LCD projectors during some class hours - supported by a total of 19 sets of Sun Blade 150 / UltraSPARC 5 workstations and 28 sets of Pentinum-4 PCs Linux laboratory - located on 4/F of QT Wing - provides a mix of the prevailing Linux and Window computing environment for all students in the department - serves as an instruction laboratory with overhead LCD projectors during some class hours - supported by a total of 40 sets of Pentium-4 PCs

Research laboratories A number of special laboratories including: · Internet and Mobile Computing Laboratory · Software Development and Management Laboratory · The Chinese Computing Laboratory · The Biometrics Laboratory · Game Laboratory have been created for research development and teaching support.

3.2.5 WebCT Teaching and Learning Support

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To enhance interactive learning and facilitate communications, the proposed programme will be supported by the WebCT system. WebCT is a web-based teaching and online content management system which does not require teachers to do computer programming. All the essential functions for interactive teaching/learning through Internet are built-in as standard features. These include: 1. Online Bulletin Board (newsgroup) 2. Online Chat Room (similar to ICQ) 3. Online Whiteboard (for drawing pictures jointly through Internet) 4. Web Page Creation (no programming required, just do typing, import or cut and paste) 5. Interactive Quiz (no programming required) 6. Internal Mail 7. Class Calendar 8. Internal Content Search 9. Password Authentication 10. Student database for class management and performance tracking Furthermore multimedia components such as digital video, digital sound, computer graphics and animations can be imported into WebCT for creating web-based lessons. Please browse http://webct.polyu.edu.hk for details.

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Part 4: Subject Syllabi

4.1 Detailed Subject Description Forms The detailed Subject Description Forms are presented in the following section. General Education subject syllabi are not included.

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SUBJECT DESCRIPTION FORM

Subject Title: Foundation Mathematics I for Science Number of Credits: 3

Subject Code: AMA 103 28 hours 14 hours

Hours Assigned: Lecture Tutorial/Student Presentation

Pre-requisite: Nil

Objectives: The lectures aim to provide the students with an integrated knowledge required for the understanding and application of mathematical concepts and techniques. To develop students' ability for logical thinking and effective communication, tutorial and presentation sessions will be held.

Student Learning Outcomes: This is a subject to provide students with a solid foundation in Differential and Integral Calculus. It is essential for all undergraduate students of Engineering or Science. The emphasis will be on application of mathematical methods to solving basic engineering science problems. Upon satisfactory completion of the subject, students are expected to be able to: (i) understand the concept of functions and inverse functions; (ii) use mathematical induction in various contexts; (iii) understand the algebra and geometry of complex numbers and apply complex numbers to solve science and engineering problems; (iv) apply mathematical reasoning to analyse essential features of different mathematical problems such as differentiation and integration; (v) apply appropriate mathematical techniques to model and solve problems in science and engineering; (vi) extend their knowledge of mathematical techniques and adapt known solutions in different situations; (vii) undertake continuous learning.

Syllabus: Basic concepts Mathematical induction; Functions and inverse functions; Elementary functions, trigonometric functions; Complex numbers; De Moivre's Theorem; Roots of a complex number. Differential Calculus: Limits and continuity; Derivatives; Techniques of differentiation; Mean value Theorem; Higher derivatives; Maxima and minima; Curve sketching. Integral Calculus:

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Definite and indefinite integrals; Fundamental Theorem of Calculus; Techniques of integration; Taylor's Theorem; Applications in geometry, physics and engineering.

Method of Assessment: Continuous Assessment Examination 40% 60%

To ensure that students learn and reflect continuously, Continuous Assessment is an important element and students are required to obtain Grade D or above in both the Continuous Assessment and the Examination components. The continuous assessment comprises of assignments, in-class quizzes and tests. The assignments are used to assist the students to reflect and review on their progress. The end-of-semester examination is used to assess the knowledge acquired by the students and their ability to apply and extend such knowledge.

Reference Books: 1. D. Varberg, E.J. Purcell Calculus & S.E. Rigdon 8th edition 2. Dept. of Applied Math Foundation Mathematics 2004 3. F.R. Giordano, Calculus for Engineers and Scientists M.D. Weir & R.L. Finney Prentice Hall 2000 HK PolyU Addison-Wesley 1988

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SUBJECT DESCRIPTION FORM

Subject Title: Logic: Qualitative and Quantitative Subject Code: AMA 105 Number of Credits: 3 Hours Assigned: Lecture 28 hours Tutorial/Lab 14 hours

Pre-requisite:

Nil

Objectives: This subject aims to develop students' ability in logical and analytical thinking through the qualitative and quantitative aspects of logic. Introduction to the key concepts and relationships of formal logic will be done primarily through lectures. Examples and case studies will be presented in small group tutorials. Finally, self-study will be encouraged through student accessible computer-based exercises. Assessment will be in the form of both in-class mid-term tests as well as group projects associated with tutorials. The first part will emphasize qualitative logic and will be taught by the General Education Centre. The second part will emphasize quantitative logic. Some topics from discrete mathematics will be presented as illustrations of the general theory. This part will be taught by the Department of Applied Mathematics.

Student Learning Outcomes: On completion of this subject, students are expected to be able to demonstrate some ability with respect to the following skills: (i) demonstrate basic logical reasoning (ii) see the relationship between formal logic and natural language (iii) apply logical reasoning in both everyday and academic situations (iv) recognize and refute common logical fallacies (v) appreciate the axiomatic approach in mathematics (vi) understand why proofs of mathematical statements work (vii) apply logical reasoning in problem solving.

Syllabus: Qualitative Logic: Introduction_What is Logic? Logic Puzzles. Some Basic Concepts and Logical Relations. Propositional Logic. Syllogistic Logic. Inductive Reasoning. Some Common Informal Fallacies. Quantitative Logic: Sets and propositions; Permutations and combinations; Relations and Functions; Graphs and Trees; Natural Numbers.

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Method of Assessment: Continuous Assessment Examination 40% 60%

To ensure that students learn and reflect continuously, Continuous Assessment is an important element and students are required to obtain Grade D or above in both the Continuous Assessment and the Examination components. The continuous assessment comprises of assignments, in-class quizzes and tests. The assignments are used to assist the students to reflect and review on their progress. The end-of-semester examination is used to assess the knowledge acquired by the students and their ability to apply and extend such knowledge.

Reference Books: 1. Gensler, Harry. 2. Fisher, Alec 3. Copi, I.M., Cohen C. 4. Johnson, D.L. 5. Hurley, Patrick J. 6. Guttenplan, Samuel 7. Salmon, W.C. 8. Hodges, Wilfred 9. Liu, C.L. 10.Cupillari A. Introduction to Logic Critical Thinking Introduction to Logic, 10th edition Elements of Logic via Numbers and Sets A Concise Introduction to Logic The Languages of Logic: An introduction to formal logic Logic, 3rd edition Logic Elements of Discrete Mathematics The nuts and bolts of proofs Routledge, New York 2002 OUP, Cambridge 2001 Macmillan, New York 1998 Springer 1998 Wadsworth Publishing Co. Belmont, 1988 Basil Blackwell, Oxford 1986 Prentice-Hall, Englewood Cliffs 1984 Harmondsworth 1977 McGraw Hill, 1985 Academic Press 2001

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SUBJECT DESCRIPTION FORM

Subject Title: College Physics I Number of Credits: 3 experiments

Subject Code: AP 101 Hours Assigned: Classroom teaching and Laboratory Lecture 28 hours Tutorial 6 hours Laboratory 8 hours Multimedia Teaching/Learning and other Virtual Laboratory12hours Self-study 60 hours

activities

Pre-requisite: Nil

Co-requisite : Nil

Exclusion: Nil

Objectives: This is the first bridging course in physics of the Foundation Programme for students admitted from mainland. It provides a broad foundation in mechanics and thermal physics, preparing students to study science, engineering, or related programmes. Student Learning Outcomes: On successful completion of this subject, students are expected to be able to: 1. solve simple problems in mechanics using vector method; 2. solve problems on rotation of rigid body about fixed axis; 3. define simple harmonic motion and solve simple problems; 4. apply Archimedes' principle to solve problems in hydrodynamics; 5. apply Bernoulli's equation to simple problems in fluid flow; 6. explain ideal gas laws in terms of kinetic theory; 7. apply the first law of thermodynamics to simple processes; and 8. solve simple problems related to the Carnot cycle; Teaching and Learning Approach: Lectures are given to deliver the subject outline and key physics concepts to the students. The students will also get the guidance on further reading. Tutorials are provided to help the students gain analytical abilities through problem-solving strategy and also help them strengthen the concepts taught. Laboratories are designed to help the students gain hands-on experience in the operation of equipment and apply their knowledge in the experiments.

Syllabus: 1. Preparation in mathematics Review of algebra, geometry and trigonometry; Function and graph; Derivative;

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Integration; Vectors and coordinate system. 2. Mechanics Measurement of space, time and mass; Kinematics; Dynamics and Newton's laws; Force and motion; Impulse and momentum; Work and energy; Conservation of energy; Gravitation field and gravitation acceleration; Systems of particles; Collisions; Rigid body; Rotation; Angular momentum; Oscillations and simple harmonic motion; Pendulum; Statics and elasticity; Hydrostatics and Archimedes' principle; Bernoulli's equation. 3. Thermal physics Conduction, convection and radiation; Black body radiation and energy quantization; Ideal gas and kinetic theory; Work, heat and internal energy; First law of thermodynamics; Entropy and the second law of thermodynamics; Carnot cycle; Heat engine and refrigerators.

Method of Assessment: Continuous Assessment Examination

60% 40%

To pass the subject, students must obtain grade D or above in the examination.

Essential Reading and CD-ROM 1. Giancoli. (2000). Physics for Scientists and Engineers. 3rd edition. Prentice Hall. 2. (2000). Physics CAI in CD-ROM. USTC. 3. (2000). Computer Simulation System for College Physics Experiment. Version 2.0 for Windows. USTC. Reference List 1. Halliday, Resnick and Walker. (2005). Fundamentals of Physics. 7th edition. Wiley. 2. Young and Freedman. (2004). University Physics. 11th edition. Pearson. 3. Knight. (2004). Physics for Scientists and Engineers with Modern Physics. Pearson. 4. Giambattista, Richardson and Richardson. (2007). College Physics. 2nd edition. MaGraw-Hill. 5. Jewett and Serway, Serway's. (2006). Principles of Physics. 4th edition. Thomson.

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SUBJECT DESCRIPTION FORM

Subject Title: Understanding the Hong Kong Community 184 Number of Credits: 3

Subject Code:

APSS

Hours Assigned: Lecture Tutorial/Lab

28 hours 14 hours

Pre-requisite:

Nil

Objectives: The subject aims to provide the students with an integrated knowledge required for the understanding and application of sociological concepts to understand the social and cultural development of Hong Kong.

Student Learning Outcomes: On successful completion of this subject, students are expected to be able to: 1. 2. 3. 4. 5. describe the historical development of the pre-1841 Hong Kong; understand the social life of the pre-1841 Hong Kong; depict the historical trajectory of the colonial Hong Kong; analyze the social, cultural and political aspect of the colonial Hong Kong; understand the social life of the post-1997 Hong Kong.

Teaching And Learning Approach: Apart from the lectures, students would participate in outings by which they are introduced to, on the one hand, the historic sites that could exhibit the traditional social lives of Hong Kong people, and on the other the modern landscapes of Hong Kong. In addition, students are arranged to participate in community service projects to reinforce their hands-on understanding in the community. Students are required to attend seven tutorials and present their views on various aspects of the traditional and modern social lives in Hong Kong. Students are encouraged to focus on the cultural and social aspects of Hong Kong society. Medium of Instruction: English Medium of Assessment: English

Syllabus: Students are required to attend seven tutorials and present their views on various aspects of the traditional and modern social lives in Hong Kong. They are encouraged to focus on the cultural and social aspects of Hong Kong society.

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1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17.

Pre-1841 Hong Kong: Wall Communities and the Form of Living Visit: Markets at Yuen Long, Fanling and Sheung Shui Domestic Villages and the Survival Strategies Visit: Tai O- a fishing Village Visit: Tai O- a fishing Village 1841: The Coming of the Colonial Hong Kong Visit: Central and Sheung Wan The Chinese Communities Visit: Wan Chai Post-1950's Hong Kong: the Minimally Integrated Social and Political System Visit: Hong Kong Museum of History The Development and the Future of Social Service in Hong Kong Hands-on Participation in Community Service Project Modern City Life of Hong Kong: Shopping Malls Residence Patterns of Hong Kong People: Public Housing and Home Ownership Landscape of Hong Kong: Disney World, Tourism and Economic Development Hong Kong's Tomorrow

Method of Assessment: Continuous Assessment 100% - mid-term paper on fieldtrips reflection - end-of term paper on social life of HK - participation (seminars/fieldtrips/service) - group presentation on service reflection

(20%) (35%) (15%) (30%)

Reference Books: Main textbooks and reference books Cody, Jeffrey W. and James R. Richardson (1997) "Urbanizing Forest and Village Trees in Hong Kong's Shatin Valley, 1976-1997", Traditional Dwellings and Settlements Review 9: 21-33. Ku, Agnes (1999) Narratives, politics, and the public sphere: struggles over political reform in the final transitional years in Hong Kong (1992-1994), Aldershot, Brookfield USA, Ashgate, Chapter 2, pp. 18-48 Leung, Benjamin K.P., 1996. University Press. Perspectives on Hong Kong Society, Hong Kong: Oxford

Lau, S.K., et al., various years. Indicators of Social Development: Hong Kong. Hong Kong: Hong Kong Chinese University Press. Leung, Benjamin K.P., 1990. Social Issues in Hong Kong. Hong Kong: Oxford University Press. Various Years, The Other Hong Kong Report, Hong Kong: Hong Kong Chinese University Press.

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20011841-1945, , 2000 , , (1997) "I.": 17-46. (2001) : 23-30. (2002) : . : . 2003 : , , 2002: , ,

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SUBJECT DESCRIPTION FORM

Subject Title: Introduction to Information Technology Number of Credits: 3

Subject Code: COMP 100 14 hours 42 hours

Hours Assigned: Lecture Laboratory

Pre-requisite: Nil

Co-requisite: Nil

Exclusion: Nil

Objectives: This subject provides students with the basic concepts of information technology and computing, as well as knowledge and practice on deploying and controlling common information technology applications. This subject is suitable for all students as a first subject in information technology, whether they intend to continue to study information technology or not. Students who intend to study information technology-related programmes are strongly recommended to take both COMP100 and COMP111. Student Learning Outcomes: On successful completion of this subject, students are expected to be able to: 1. understand how a computer works; 2. understand the potentials of information technologies in business and industry; 3. use popular operating systems to carry out sequence of tasks; 4. appreciate the power of programmed computer operation; 5. understand the current trends in the development of popular information technologies such as the Internet and related tools; 6. appreciate IT-related intellectual property issues and their protection. Teaching and Learning Approach: The course material will be delivered as a combination of mass lectures and small group supervised laboratory sessions. Students will get familiarized with common operating systems and environment, internet and multimedia tools. They will also attempt simple script, shell programs etc and appreciate exercising automatic control over the computer and applications.

Syllabus: 1. Introduction to Computer Systems Major components of computer systems: central processing units, storage devices and media, inputs / outputs; working principle of computers; contemporary types of CPU, memory, input / output devices currently in use. 2. System Software Functions and operations of system software; basic features and commands of MS Windows and Unix / Linux; script language and task control. 3. Communication, Multimedia and the Internet

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Communication and networking; Internet resources and tools; multimedia information creation and application. 4. IT Applications Introduce typical applications of information technologies such as office automation, knowledge management, education, entertainment, digital edutainment, manufacturing, geo-informatics, bio-informatics, etc. 5. Inside IT Applications Role of programming in IT applications, e.g. shell programs, macros in Excel, robotic control, concept of algorithm and programming, debugging. 6. IT Intellectual Property Security, privacy and ethics with software; copyright and patent law; trade secrets and registered design.

Method of Assessment: Continuous Assessment 100%

Reference Books: 1. Shelly, G.B., Cashman, T.J. and Vermaat, M. (2005). Discovering Computers 2005. Thomson Course Technology. 2. Toliver, P., Johnson, Y. and Wise, S. (2002). The Select Series: Microsoft Office XP. Volume 1. Prentice-Hall. 3. Long, L.E. and Long, N. (2005). Computers. 12th Edition. Prentice-Hall.

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SUBJECT DESCRIPTION FORM

Subject Title: Enterprise Information Technology Subject Code: COMP 102 Number of Credits: 3 Hours Assigned: Lecture Laboratory 28 hours 14 hours

Pre-requisite: Nil

Co-requisite: Nil

Exclusion: Nil

Objectives: This subject provides students with the concept of information systems and their role in today's enterprises. This subject can be taken with or without having taken COMP100 as a prerequisite. It is suitable for all students. Student Learning Outcomes: On successful completion of this subject, students are expected to be able to: 1. understand the use of information systems at various organizational levels; 2. understand the basic principles of the modelling, storage, retrieval and management of information in an enterprise; 3. appreciate the use of strategic information systems for competitive advantages; and understand ethical and social implications of information systems 4. understand ethical and social implications of information systems. Teaching and Learning Approach Lectures for delivery of conceptual knowledge and analytical techniques in case studies. Tutorials/Laboratories for discussion of real business cases and hands-on experience of tools and databases.

Syllabus: 1. Basic principles of databases Data, information and knowledge; modelling and storage of information in databases; querying and retrieval of data; transaction processing. 2. More advanced manipulation and management of information The principles and applications of data warehousing, data mining, and knowledge management in an enterprise. 3. Decision Support for Business Intelligence Decision and executive support systems; business intelligence technologies such as expert systems, genetic algorithms for organizational modelling, neural networks and fuzzy logic for business applications; hands-on experience in using tools such as SPSS, data mining tool, neural network engine.

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4. Electronic Commerce/Business Business use of the Internet, world wide web, intranets and extranets; electronic banking; cyber trading and investing; marketing on the internet; smart card trends, development methods and tools; security and cryptography. 5. Networked Enterprise Managing cooperative work environments; workflow and business process engineering; groupware and platforms for collaborative work, e.g. Novell. 6. Knowledge Management Concepts Corporate memory, intellectual capital, personal knowledge management, knowledge transfer, business intelligence.

Method of Assessment: Continuous Assessment Examination

60% 40%

Reference Books: 1. O'Brien, James. (2007). Introduction to Information Systems: Essential for the Business Enterprise. 13th Edition. McGraw-Hill. 2. Laudon, K.C.., et.al. (2006). Management Information Systems: Managing the Digital Firm. 9th edition. Prentice Hall. 3. O'Brien, James. (2006). Management Information Systems: Managing Information Technology in the Business Enterprise. 7th Edition. McGraw-Hill. 4. Linthicum, David S. (2000). Enterprise Application Integration. Addison-Wesley. 5. Silberschatz, A., Korth, H.F. and Sudarshan, S., Database System Concepts, Fifth Edition, McGraw-Hill. 6. Shelly, Cashman, and Serwatka. (2004). Business Data Communications: Introductory Concepts and Techniques. 4th Edition. Course Technology/Thomson Learning.

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SUBJECT DESCRIPTION FORM

Subject Title: Information Technology Systems Number of Credits: 3

Subject Code: COMP 111 Hours Assigned: Lecture Laboratory 28 hours 28 hours

Pre-requisite: Nil

Co-requisite: Nil

Exclusion: Nil

Objectives: This subject provides the students with the foundations of information systems, and basic methods of problem-solving with computer-based tools. It can be taken with or without having taken COMP100. Students who intend to study information technology-related programmes are strongly recommended to take both COMP100 and COMP111. Student Learning Outcomes: On successful completion of this subject, students are expected to be able to: 1. understand underlying principles of computer organization; 2. solve simple problems with computer-based tolls involving programming, algorithms and other technologies; and 3. be able to control and be aware of the opportunities and limitations provided by readymade tools and software. Teaching and Learning Approach: Lectures for delivery of conceptual knowledge and problem solving techniques. Tutorials/Laboratory for discussions, hands-on programming and implementation of solutions.

Syllabus: 1. Fundamental Concepts Computer logic and organization, binary number representation and manipulation, modern computer architectures and trends, computer cluster, supercomputer, the computational grid. 2. System Software Operating system concepts, basic software development methods and tools, programming language, compiler, project management (Unix make file), debugger. 3. Basic Programming Basic C programming, simple data types, expression, control structure, structured data types, I/O, files. 4. Basic Algorithm and Problem Solving Problem solving procedure and tool, flowchart, pseudo-code, simple algorithms like linear search and bubble sort, implication on program execution time.

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5. Data Communication, the Internet, and the World Wide Web Networking concepts; TCP/IP and Novell; features of Internet and Internet address, mobile computing. 6. Problem Solving with Computer-based Tools Integration of different computer-based technologies such as system software, application software, databases, networking, and mobile technologies to solve real-world problems. software.

Method of Assessment: Continuous Assessment Examination

60% 40%

Reference Books: 1. 2. 3. 4. 5. Paul K. Andersen. (2003). Just Enough UNIX. McGraw-Hill. H. M. Deital and P.J. Deital. (2005). C How to Program. 5th edition. Prentice-Hall. Marty Poniatowski. (2002). UNIX User's Handbook. 2/E. Prentice Hall PTR. John McMullen. (1999). UNIX User's Interactive Workbook. Prentice Hall PTR. Robert Cowart and Brian Knittel. (2003). Using Microsoft Windows XP Professional. Special Edition. Que.

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SUBJECT DESCRIPTION FORM

Subject Title: English for University Studies I Number of Credits: 3

Subject Code: ELC 1004 Hours Assigned: Seminar 42 hours

Pre-requisite:

Nil

Objectives: This course aims to help students study effectively in an English-medium learning environment and to enhance their proficiency in English. The course is designed to enable students to use English effectively in the academic contexts they will encounter in their studies. The main emphasis is on improving students' confidence and competence in grammar, vocabulary and pronunciation in these contexts. The study method is primarily seminar-based. Seminar activities will include discussions, role-plays and individual and group activities. Use will be made of information technology where appropriate. Learning and teaching materials developed by the English Language Centre will be used throughout this course. Teachers will recommend additional reference materials as required. Student Learning Outcomes: At the end of the course, the students are expected to be able to use the language and study skills needed to:

· deliver effective oral presentations · summarise and paraphrase materials from written and spoken sources · plan, write and revise expository academic essays

Syllabus: This syllabus is indicative. The balance of the components, and the weighting accorded to each, will be based on the specific needs of the students. 1. Spoken communication Developing and practising the research and specific oral skills required to prepare and deliver oral presentations; developing awareness of interpersonal communication strategies in different social contexts. 2. Written communication Analysing and practising functions common in academic writing; understanding common patterns of organisation in academic writing; taking notes from written and spoken sources; introducing paraphrasing, summarising and referencing skills; improving coherence and cohesion in writing; introducing appropriate tone and style in academic writing; developing revision and proofreading skills. 3. Reading and listening Understanding the content and structure of information delivered both orally and in print form; reading and listening for different purposes.

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4. Language development Developing relevant grammar, vocabulary and pronunciation skills.

Method of Assessment: Continuous Assessment

100%

Reference books: Boyle, J. & Boyle, L. (1998). Common Spoken English Errors in Hong Kong. Hong Kong: Longman. Brannan, B. (2003). A writer's workshop: crafting paragraphs, building essays. Boston, Mass.: McGraw-Hill. Collins COBUILD English dictionary for advanced learners. (2001). Glasgow: Collins. Eastwood, J. (1999). Oxford practice grammar. Oxford: Oxford University Press. Hancock, M. (2003). English pronunciation in use. Cambridge: Cambridge University Press. Jay, A. and Jay, R. (2000). Effective presentation. London: Prentice Hall. Jordan, R. (1999). Academic writing course. Harlow: Longman. McCarthy, M. and O'Dell, F. (2001). English vocabulary in use: upper-intermediate. Cambridge: Cambridge University Press. Oshima, A. and Hogue, A. (1991). Writing academic English. New York: Longman. Redman, S. (2003). English vocabulary in use: pre-intermediate and intermediate. Cambridge: Cambridge University Press.

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SUBJECT DESCRIPTION FORM

Subject Title: English for University Studies II Number of Credits: 3

Subject Code: ELC 1005 Hours Assigned: Seminar 42 hours

Pre-requisite: English for University Studies I

Objectives: This course aims to further develop those English language skills required of students to communicate effectively in academic contexts. The course is designed to enhance the written and spoken communication skills that students will need to function effectively in their university studies. These skills will also be beneficial to their future employment in any organisation where internal and/or external oral communication is conducted in English. The study method is primarily seminar-based. Seminar activities will include discussions, role-plays and individual and group activities. Use will be made of information technology where appropriate. Learning and teaching materials developed by the English Language Centre will be used throughout this course. Teachers will recommend additional reference materials as required.

Student Learning Outcomes: At the end of the course, students are expected to be able to use the language and study skills needed to: participate effectively in formal and informal discussions refer to sources in academic essays plan, write and revise argumentative essays

Syllabus: This syllabus is indicative. The balance of the components, and the weighting accorded to each, will be based on the specific needs of the students. 1. Spoken communication Enhancing and practising the specific oral and aural skills required to participate effectively in formal interactions involving such activities as seminar discussions and debates, as well as in a variety of informal contexts. 2. Written communication Describing and interpreting data; understanding common organisational patterns of academic essays; enhancing referencing skills; improving coherence and cohesion in writing; reinforcing revision and proofreading skills; achieving appropriate tone and style in academic writing. 3. Reading and listening Understanding the content and structure of information delivered both orally and in print

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form; reading and listening for different purposes. 4. Language development Developing relevant grammar, vocabulary and pronunciation skills.

Method of Assessment: Continuous Assessment

100%

Reference books: Carter, R., Hughes, R. and McCarthy, M. (2000). Exploring grammar in context: upperintermediate and advanced. Cambridge: Cambridge University Press. Collins COBUILD English dictionary for advanced learners. (2001). Glasgow: Collins. Madden, C. G. and Rohlck, T. N. (1997). Discussion and interaction in the academic community. Ann Arbor, MI: University of Michigan Press. McCarthy, M. and O'Dell, F. (2001). English vocabulary in use: upper-intermediate. Cambridge: Cambridge University Press. McCarthy, M. and O'Dell, F. (2002). English vocabulary in use: advanced. Cambridge: Cambridge University Press. Oshima, A. and Hogue, A. (1991). Writing academic English. New York: Longman. Oshima, A. & Hogue, A. (1997). Introduction to academic writing. New York: Longman.

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SUBJECT DESCRIPTION FORM

Subject Title: Business Accounting Number of Credits: 3

Subject Code: AF2104 Hours Assigned: Lecture Tutorial 28 hours 14 hours

Pre-requisite: Nil

Objectives: · · To provide students with an understanding how accounting information are formulated and to apply it in a business context. To develop students' knowledge and appreciation of the accounting information required for different types of decision making.

Student Learning Outcomes: On successful completion of this subject, students will be able to: · · · · · Have an understanding of financial accounting concepts and the way the concepts are applied in the preparation of financial statements. Be able to prepare and interpret a basic set of financial statements. Enable students to identify the uses and limitations of accounting information in decisionmaking Equip students with basic cost concepts and techniques for decision-making, planning and control Be able to identify and evaluate the information for capital investment decision-making.

Teaching/Learning Approach: Lectures which emphasize the concepts and the key issues and tutorials that provide a forum for discussing applications of the concepts and the key issues.

Syllabus: Overview of Financial Statements and Reporting Process Accounting as an information system, users of accounting information. Forms of business organizations. Overview of business activities. Accounting guidelines. The accounting profession in Hong Kong. Principal financial statements. Other items in published annual reports. Preparation of the Basic Financial Statements An overview of the balance sheet and its underlying concepts. The accounting process.

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Income statement measurement and its principles. An overview of statement of cash flow. Preparation of final accounts for limited companies. Accounting for Inventory and Fixed Assets Choice of different valuation bases and their implications on financial statement reporting. Introduction to Financial Statement Analysis Objectives of financial statement analysis. Use of ratio analysis. Usefulness of ratios. Analysis of profitability. Liquidity and risk. Capital structure. Interpretation of the analysis. Limitations of financial statement analysis. Introduction to Management Accounting Introduction and relationship of management accounting with financial accounting. Cost accounting. Planning and control: budgeting. Short Term Decision Making Basic cost concept and cost behavior and the application of cost-volume-profit analysis. Capital Investment Appraisal Concept of present value. Investment appraisal methods: payback, accounting rate of return, net present value and internal rate of return.

Method of Assessment: Continuous Assessment Examination 40% 60%

To pass the subject, students must obtain grade D or above in both Continuous Assessment and examination.

Reference Books: Marshall, D.H., at el, Accounting What the Numbers Mean, 7th Edition, McGraw-Hill. Staff Responsible Musetta So

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SUBJECT DESCRIPTION FORM

Subject Title: Financial Accounting Number of Credits: 3

Subject Code: AF2108 Hours Assigned: Lecture Tutorial 28 hours 14 hours

Pre-requisite: Nil

Objectives: This subject introduces the discipline of financial accounting. It enables students to apply basic financial theories, analyze financial reports and understand the operation of financial markets. It also contributes to the development of their IT skills and ethical understanding. Student Learning Outcomes: On successfully completing this subject, students will be able to: · · · · · Appreciate the role and importance of accounting information in assisting decision-making in a business context. Undertake the work involved in the recording, processing, summarizing and reporting phases of the accounting cycle. Understand the assumptions, principles and conventions underlying financial accounting processes. Understand the basic concept of ethics in a business context and how to analyze and solve accounting related ethical dilemma using a simple framework. Apply basic analytical tools for the interpretation of financial statements.

Teaching/Learning Approach: A two hour mass lecture will be conducted each week to initiate students into the ideas, concepts and techniques of the topics in the syllabus, which is then reinforced by a one hour tutorial designed to consolidate and develop students' knowledge through discussion and practical problem solving. A case study requiring the application of computer software to handle financial data will be assigned and assessed. Syllabus: The Business and Accounting Environment Different types of businesses, their common objectives and basic features. The environmental variables that affect the recording and reporting of financial information. The need for accounting as a basis for decision making. Ethical considerations in financial reporting. The Financial Accounting Framework Accounting equation and double entry bookkeeping system. Differences between cash and accrual bases of accounting. Preparation of journals, ledger accounts, trial balance and basic financial statements. Prepayments and accruals. Valuation of debtors, stock and fixed assets.

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Quality of earnings and earnings management. Control of cash through bank reconciliation statement. Accounting Principles and Concepts Fundamental accounting concepts and other accounting principles that underlie the preparation of financial statements. Company Accounting

Features of the corporate form of business ownership. Rights and obligations of interested parties. Issues relating to company accounts. Preparation of financial statements of a company. Corporate governance issues in financial reporting.

Analysis and Interpretation of Financial Statement Need for analysis and interpretation of financial statements. Interpretation techniques including ratio analysis and cash flow statement. Calculation and interpretation of basic financial ratios. Limitations of ratio analysis.

Method of Assessment: Continuous Assessment Examination

50% 50%

To pass the subject, students must obtain grade D or above in both Continuous Assessment and examination.

Reference Books Weygandt, J.J., D.E. Kieso and P.D. Kimmel, Financial Accounting, 5th Edition, Wiley, 2005. Horngren C.T., W.T Harrison and L.S. Bamber, Accounting, 6th Edition, Prentice Hall, 2005. Warren C.S., J.M. Reeve and P.E. Fess, Financial Accounting, 9th Edition, South-Western, 2005. Libby, R., P. Libby and D.G. Short, Financial Accounting, 4th Edition, McGraw-Hill, 2004. Williams, J.R., S.F. Haka, M.S. Bettner and R.F. Meigs, Financial Accounting, 11th Edition, McGraw-Hill, 2003. Wild, J.J., Financial Accounting, 2nd Edition, McGraw-Hill, 2003. The Statements of Standard Accounting Practice, Hong Kong Institute of Certified Public Accountants. Staff Responsible Gerald Chau

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SUBJECT DESCRIPTION FORM

Subject Title: Introduction to Calculus and Linear Algebra Subject Code: AMA211 Number of Credits: 3 Hours Assigned: Lecture Tutorial 28 hours 14 hours

Pre-requisite: Nil

Objectives: The lectures aim to provide the students with an integrated knowledge required for the understanding and application of mathematical concepts and techniques. To develop students' ability for logical thinking and effective communication, tutorial and presentation sessions will be held.

Student Learning Outcomes: The subject aims to introduce students to some fundamental knowledge of calculus and linear algebra. The emphasis will be on application of mathematical methods to solving practical problems. Upon satisfactory completion of the subject, students are expected to be able to: (i) apply mathematical reasoning to analyse essential features of different mathematical problems; (ii) extend their knowledge of mathematical techniques and adapt known solutions to different situations; (iii) develop and extrapolate mathematical concepts in synthesizing and solving new problem; (iv) search for useful information in solving problems; (v) undertake continuous learning.

Syllabus: Calculus: Continuous functions; Derivatives and slopes; Rules of differentiation; Implicit differentiation; Applications of differentiation including curve sketching; Optimization and approximation; Definite and indefinite integrals; Techniquess of integration, Double integrals. Linear Algebra: Systems of linear equations; Matrices and vectors; Vector space and subspace; Linear dependence and basis; Dimension and rank; Linear operations and functionals; Dual space; Determinants; Eigenvalue problems; Applications.

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Method of Assessment: Continuous Assessment Examination 40% 60%

To ensure that students learn and reflect continuously, Continuous Assessment is an important element and students are required to obtain Grade D or above in both the Continuous Assessment and the Examination components. The continuous assessment comprises of assignments, in-class quizzes and tests. The assignments are used to assist the students to reflect and review on their progress. The end-of-semester examination is used to assess the knowledge acquired by the students and their ability to apply and extend such knowledge.

Textbooks and Reference Books: Department of Applied Mathematics H. Anton G.B. Thomas, R.L. Finney, J.R. Hass & F.R.Giordano Foundation Mathematics 2nd edition Elementary Linear Algebra 8th edition Thomas' Calculus 11th edition The Hong Kong Polytechnic University 2003 John Wiley & Sons 2000 Addison Wesley 2004

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SUBJECT DESCRIPTION FORM

Subject Title: Principles of Programming Number of Credits: 3

Subject Code:

COMP 201 14 hours 42 hours

Hours Assigned: Lecture Tutorial/Lab Co-requisite: Nil Exclusion: Nil

Pre-requisite: Nil

Objectives: · · To provide students knowledge on the fundamental elements in computer programming. To introduce advanced computer programming techniques necessary for developing more sophisticated computer application programs.

Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) understand the programming elements for solving computing related problems; (2) possess the ability to design and develop efficient computer programs for solving problems; (3) develop a computer program in a stepwise manner; (4) use various software tools for developing computer programs; (5) possess the ability to learn independently advanced programming techniques; (6) possess the ability to learn independently other high level programming languages; Attributes for all-roundedness (1) solve problems using systematic approaches; (2) identify and develop problem solutions in a logical manner; (3) learn independently any new technology.

Syllabus: Topic 1. Introduction Basic concepts of computers. 2. Fundamentals of computer programming Compilation, testing and debugging; elementary programming concepts. 3. Flow controls Selection constructs, repetition constructs, methods (functions). 4. Object-based programming Classes and instances, constructors and finalizers, static methods, static variables and others.

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Duration Lecture 1 Lab/Tut -

1

2

3

12

2

8

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5. Strings Character strings, string methods. 6. Arrays List of items, ordered and indexed lists. 7. Event-driven programming and GUI Events, listeners, graphical user interface. 8. Exception handling Exceptions and errors, handlers. 9. Advanced object-oriented programming techniques Polymorphism, abstract classes, interfaces. 10. Miscellaneous advanced topics Topics such as Java packages and beans, etc. Total Laboratory Experiment:

1

3

1 1

3 3

1

3

2

6

1

2

14

42

This subject emphasizes both on the conceptual elements in computer programming and practical experiences. Students are required to attend a number of laboratory sessions. During the labs, students acquire practical experience by working on some programming exercises under the guidance by the instructors. The labs allow the students to consolidate their concepts learnt in the lectures. Other practical work helps to reinforce the programming skills learned for applications. Case Study: Nil

Method of Assessment: Continuous Assessment 60% Assignments, quizzes and tests, marked exercises completed during lab sessions Examination 40%

Textbooks: 1. C. Thomas Wu, An Introduction to Object-Oriented Programming with Java, McGraw-Hill, 3rd Edition Update, 2004. Reference Books: 1. Deitel & Deitel, Java: How to Program, Prentice-Hall, 6th Edition, 2005. 2. Various materials on the web, especially http://java.sun.com

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SUBJECT DESCRIPTION FORM

Subject Title: Discrete Structures Number of Credits: 3

Subject Code: COMP 210 Hours Assigned: Lecture Tutorial

28 hours 14 hours

Pre-requisite: Nil

Co-requisite: Nil

Exclusion: COMP 207

Objectives: · · To introduce students to the concepts and applications of discrete mathematical structures. To help students attain the fundamental mathematical knowledge and reasoning skills they need to be successful in upper-level computing subjects.

Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) apply discrete structures knowledge and skills to solve real world problems using computers; (2) understand the major mathematical knowledge in computer systems; (3) apply the computer programming techniques to solve practical engineering problems; Attributes for all-roundedness (1) acquire mathematical knowledge and skills required to further study other more advanced computing-related subjects; (2) relate learned mathematical knowledge to other computing subjects.

Syllabus: Topic 1. Set, relations and functions Sets, relations and functions, equivalence, cardinality, order relations. 2. Propositional and predicate logic Logical expressions; truth tables; Karnaugh maps; tautologies; formal reasoning; predicates; quantifiers; proof system; soundness and completeness. 3. Mathematical skills Mathematical induction; counting techniques; inclusion-exclusion principle; pigeonhole principle. 4. Graphs and trees Graph, digraph, isomorphism; connectivity; Euler and Hamilton path; shortest path problems; planar graphs; graph coloring; trees and tree traversal; spanning trees and minimum spanning trees; decision tree and isomorphism of tree.

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Duration of Lectures 4

6

4

6

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5. Basic network problems Network flows; maximal-flow minimum-cut problem; minimal-cost flow problem; applications, e.g., network design, transportation problem. 6. Boolean algebras and combinatorial circuits Combinatorial circuits and its properties, Boolean algebras, Boolean functions and synthesis of circuits. 7. Analysis of the complexity of algorithms Algorithms, rate of growth of functions, Complexity of Algorithms, Big O notation and representation. Total Laboratory Experiment: Nil Case Study: Nil

4

2

2

28

Method of Assessment: Continuous Assessment Four graded assignments and two quizzes Examination 60% 40%

Textbooks: 1. Johnsonbaugh, R., Discrete Mathematics, Fifth Edition, Prentice Hall, 2001. 2. Rosen, K. H. Discrete Mathematics And Its Applications, Fifth Edition, McGraw Hill, 2003. Reference Books: 1. Dossey, J.A., Discrete Mathematics, Fourth Edition, Addison Wesley, 2002. 2. Kolman, B., Busby, R.C. and Ross, S.C., Discrete Mathematical Structures, Fourth Edition, Prentice Hall, 2000. 3. Truss, J.K., Discrete Mathematics for Computer Scientists, Second Edition, AddisonWelsey, 1999. 4. Hein, J.L., Discrete Structures, Logic and Computability, Second Edition, Jones & Bartlett Publishers, 2002.

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SUBJECT DESCRIPTION FORM

Subject Title: Data and System Modeling Number of Credits: 3

Subject Code:

COMP 211 28 hours 14 hours

Hours Assigned: Lecture Tutorial

Pre-requisite: Nil

Co-requisite: Nil

Exclusion: COMP 207, AMA 217

Objectives: · · To introduce students to the concepts and applications of probability and statistics. To help students attain techniques for modeling and analyzing data and systems that are important for success in upper-level computing subjects.

Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) understand the association of probability and statistics with system phenomena; (2) apply different distributions to the process of system design and analysis; (3) possess the capability to read research papers in which concepts are expressed formally in terms of probability and statistics; (4) acquire skills to formulate hypotheses and decide when to accept/reject them; Attributes for all-roundedness (1) solve problems in a systematic manner; (2) visualize and classify system behavior analytically.

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Syllabus: Topic 1. Probability Conditional probability; Bayes's rules; random variables; expectation; Stochastic process; Poisson and exponential distributions. 2. Statistics Sampling; sample mean and variance; normal, -squared, t- and Fdistributions; statistical inference and estimation methods; hypothesis testing. 3. Data and system modeling techniques Problem formulation; data modeling and system modeling; deterministic and random processes; sampling, estimation and inductive inference; memoryless distributions. 4. Queueing models Different Markov models (M/M/1, M/M/n, M/G/1) with limited and unlimited capabilities. Total Laboratory Experiment: Nil Case Study: Nil Duration of Lectures 7

7

6

8

28

Method of Assessment: Continuous Assessment Examination

55% 45%

Reference Books: 1. Ross, S.M., Introduction to Probability Models, 8th Edition, Academic Press, 2003. 2. Ross, S.M., A First Course in Probability, Sixth Edition, Prentice Hall, 2002. 3. Walpoleand, R.E. and Myers, R.H., Probability and Statistics for Engineers and Scientists, Seventh Edition, Prentice Hall, 2002. 4. Mitrani, I., Probablistic Modelling, Cambride University Press, 1998. 5. Jain, R., The Art of Computer Systems Performance Analysis, Techniques for Experimental Design, Measurement, Simulation, and Modeling, Wiley, 1991. 6. Shearer, J.L., Kulakowski, B.T. and Gardner, J.F., Dynamic Modeling and Control of Engineering Systems, Prentice Hall, 1997.

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SUBJECT DESCRIPTION FORM

Subject Title: Computer Organization and Systems Number of Credits: 3

Subject Code: COMP 212 28 hours 14 hours

Hours Assigned: Lecture Laboratory

Pre-requisite: Nil

Co-requisite: Nil

Exclusion: COMP 208

Objectives: This subject is designed to provide students with an introductory but comprehensive knowledge on computer systems, computer organization, computer system architecture and assembly language programming. Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) understand the organization of a modern computer system and be able to relate them to real examples implemented in commercially successful products; (2) understand the internal organization of a computer system through practicing with an assembly language; (3) apply concepts and skills to solve real life problems using a low level programming language. Attributes for all-roundedness (1) provide framework for thinking about computer organization; (2) continue the lifetime learning necessary for staying at the forefront of computing systems development.

Syllabus: Topic 1. Overview of computer systems Introduction to Information Technology; concepts of a digital system; overview of computer system structures; computer evolution and performance; different types of computer systems. 2. Memory, I/O and storage devices Input and output devices; interconnecting system components; interfacing; buses; interrupts in I/O systems; standard bus interfaces; main memory; RAM; ROM; secondary storage; cache memory; virtual memory and operating systems support. 3. Computer arithmetic

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Duration of Lectures 4

6

4

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Number systems; decimal system; binary system and arithmetic; octal and hexadecimal systems; BCD representation; conversion between representations; floating point representations. 4. Boolean Algebra and logic networks Boolean algebra and networks; basic logical operations; derivation of logical expressions; logic gates; flip-flops; counters; half and full adders. 5. CPU and assembly language Instruction sets, characteristics and functions; CPU structure and functions; reduced instruction set computers; assembler commands; program instructions; assembler and execution of programs; assembly language programming. Total Laboratory Experiment: Nil Case Study: Nil 5

9

28

Method of Assessment: Continuous Assessment Examination

55% 45%

Textbooks: 1. Stallings, W., Computer Organization and Architecture: Designing for Performance, Sixth Edition, Prentice Hall, 2003. Reference Books: 1. Mano, M.M. and Kime, C.R., Logic and Computer Design Fundamentals, Second Edition, Prentice Hall, 2000. 2. Hamacher, C., Vranesic, Z. and Zaky, S., Computer Organization, Fifth Edition, McGrawHill, 2002. 3. David A. Patterson and John L. Hennessy, Computer Organization and Design: The Hardware/Software Interface, Third Edition, Morgan Kaufmann, 2005. 4. Barry B. Brey, The Intel Microprocessors: 8086/8088, 80186/80188, 80286, 80386, 80486, Pentium, Pentium Pro, and Pentium II Processors: Architecture, Programming, and Interfacing, Sixth Edition, Prentice Hall, 2003. 5. Antonakos, J.L., The 68000 Microprocessor, Fourth Edition, Prentice Hall, 1999.

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SUBJECT DESCRIPTION FORM

Subject Title: Digital System Design Number of Credits: 3

Subject Code:

EIE217 (for 61031)

Hours Assigned: Lecture/Tutorial 33 hours Laboratory 9 hours (Equivalent to 27 laboratory hours)

Pre-requisite: nil

Co-requisite: nil

Exclusion: nil

Objectives: To provide first year students with the foundation of the hardware aspects of computer engineering, and enable them to gain understanding and skills that will be used in later computer related courses. Student Learning Outcomes: On successful completion of this subject, the students will be able to: Category A: Professional/academic knowledge and skills 1. Understand the enabling technologies for digital systems. 2. Understand the different components for building digital systems. 3. Design and analysis of basic digital systems and their applications. Category B: Attributes for all-roundedness 4. Think critically. 5. Learn independently. 6. Work in a team and collaborate effectively with others. 7. Present ideas and findings effectively.

Syllabus: 1. 2. 3. 4. 5. 6. 7. 8. 9. Number Systems, Operations, and Codes. Logic Gates and PLD. Boolean Algebra and Logic Simplification Combinational Logic. Functions of Combinational Logic and Programming. Flip-Flops, Registers, and Counters. Sequential Logic Programming Logic Circuit Design with PLDs. Practical Examples of Digital System Design.

Laboratory Experiment: Practical Works 1. Logic Trainer.

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2. 3. 4. 5. 6. 7.

Basic Logic Gates and Their Applications. Familiarization of Combinational MSI. Flip-Flops. Counters. Design of Synchronous Digital Sequential Circuits. Programmable Logic Device.

Method of Assessment: Coursework: 40%

Examination: 60%

Textbook: 1. T.L. Floyd, Digital Fundamentals, 8th ed., Upper Saddle River, NJ: Prentice-Hall, 2003.

Reference Books: 1. 2. 3. 4. Capilano Computing Systems, LogicWorks 5: Interactive Circuit Design Software, Addison-Welsey, 2003. R. E. Haskell, Introduction to Computer Engineering, Prentice-Hall International Edition, 1993. J. F. Wakerly, Digital Design: Principles and Practices, 3rd ed., Upper Saddle River, NJ: Prentice-Hall, 2001. M. M. Mano, Digital Design, 3rd ed., Upper Saddle River, NJ: Prentice-Hall, 2002.

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Alignment of Teaching and Learning (T&L) Methods with Learning Outcomes: T&L Method Lectures Quiz Outcome numbers 1,2 1,2 Remarks Fundamental principles and key concepts of the subject are delivered to students. Students' knowledge on/understanding of certain topics can be easily estimated, and the corresponding teaching time will be adjusted accordingly. Supplementary to lectures and are conducted with smaller class size; Students will be able to clarify concepts and to have a deeper understanding of the lecture material; Problems and application examples are given and discussed. Students will go through a number of development and design exercise of various digital systems and their components.

Tutorials

1,2,3

Laboratory sessions

3,4,5,6,7

Alignment of Assessment and Learning Outcomes: Assessment Method Assignments, tests and examination Learning Outcome 1,2,3 Remarks End-of chapter type problems used to evaluate students' ability in applying concepts and skills learnt in the classroom. Students need to think critically and creatively in order to come with an alternate solution for an existing problem. Each group of students is required to produce written reports. For some of the practical works, students are required to make demonstration to illustrate their understanding of the related technical knowledge and skills.

Laboratory sessions

3,4,5,6,7

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SUBJECT DESCRIPTION FORM

Subject Title: Analog and Digital Communications SubjectCode: Number of Credits: 3

EIE218 (for 61031)

Hours Assigned: Lecture/Tutorial 33 hours Laboratory 6 hours (Equivalent to 18 laboratory hours)

Pre-requisite: Communications Fundamentals (EIE239) Co-requisite:

nil

Exclusion: nil

Objectives: This subject provides an in-depth treatment on the conversion of analogue signal to digital signal, the use of digital signal in communication systems. It aims to equip students with sufficient knowledge to analyze communication systems. Upon completion, students would be able to: 1. understand the limitation and practical constraints in A/D and D/A conversions, 2. understand the use of different line codes and their applications, 3. understand and analyse the performance of practical digital communication systems in the presence of noise and transmission errors, 4. understand the performance of different channel coding techniques, 5. construct, test and debug a simple hardware circuit, 6. use of hardware construction tools, power supplies, signal generators, oscilloscopes, multimeters. Student Learning Outcomes: On successful completion of this subject, the students will be able to: Category A: Professional/academic knowledge and skills 1. Understand the problem, impairments and limitations in A/D, D/A conversions. 2. Understand the effect of quantization noise on the performance of the system. 3. Appreciate the use of non-uniform quantization and Delta Modulation on the signal quantities. 4. Understand and analyze the use of various line codes for different systems. 5. Understand the use of PCM and TDM. 6. Understand the capacities of different error correction coding. 7. Practice the hardware skill in the construction, test, verification a project. Category B: Attributes for all-roundedness 8. Present a topic clearly. 9. Think critically. 10. Learn independently. 11. Work individually and in a team and collaborate effectively with others.

Syllabus:

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1. Analog Pulse Modulation 1.1 Pulse amplitude modulation, pulse width modulation, pulse position modulation, time division multiplexing. 2. Digital Transmission of Analog Signal 2.1 Sampling theorem and aliasing, ideal sampling and re-construction, natural sampling, flat-top sampling. 2.2 Quantization of signals, uniform quantization, non-uniform quantization, differential quantization, delta modulation. 2.3 Coded transmission of analog signals. 2.4 Line codes and spectra. 2.5 Multiplexing PCM signals. 3. Error Control Coding 3.1 Error detection codes, error correction codes. 3.2 Linear block codes, binary cyclic codes, convolutional codes. Laboratory Experiment: Practical Works: A hardware mini-project (A to D) might be used in place of the experiments. The students are ideally work in pares. The total time allocated for the project is 18 hours. The work involves the construction an A/D converter with LED displays. This is mainly an hardware project that attempts to integrate the concepts and theory learnt in the lectures to a real, practical object. It is divided into three stages so that the student can proceed at his pace according to his ability. Check points are set at various stages so that the student knows how well he has progressed. It requires the 1. studying the specifications of various electronic components, 2. hardware construction, 3. use of hardware construction tools, 4. use of power supplies, signal generators, test and monitoring instruments, 5. verification of the concepts to the experimental results, 6. team work.

Method of Assessment: Coursework: 40%

Examination: 60%

Textbook: 1. S. Haykin, Communication Systems, 4th ed., Wisely, 2001.

References: 1. 2. 3. A.B. Carlson, P.B. Crilly and J.C. Rutledge, Communication Systems, 4th ed., McGrawHill, 2002. B.P. Lathi, Modern Digital and Analog Communication Systems, 3rd ed., Oxford University Press, 1998. McGraw-Hill, F.G. Stremler, Introduction to Communication Systems, 3rd ed., AddisonWesley, 1990.

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Alignment of Teaching and Learning (T&L) Methods with Learning Outcomes: T&L Method Lectures Tests Outcome numbers 1,2,3,4,5,6 Remarks

Tutorials

Laboratory sessions

Fundamental principles and key concepts of the subject are delivered to students. 1,2,3,4,5,6 Students knowledge on/understanding of certain topics can be easily estimated, and the corresponding teaching time will be adjusted accordingly. 1, 2,3,4,5,6 Supplementary to lectures and are conducted with smaller class size; Students will be able to clarify concepts and to have a deeper understanding of the lecture material; Problems and application examples are given and discussed. 1,7 Students will go through the process of implementation a hardware design, verify its correction operation. They would have learnt how to interpret and extract information from specifications, use of tools and instruments, team work.

Alignment of Assessment and Learning Outcomes: Assessment Method Assignments, tests and examination Learning Remarks Outcome 1,2,3,4,5,6 End-of chapter type problems used to evaluate students ability in applying concepts and skills learnt in the classroom. Students need to think critically and creatively in order to come with an alternate solution for an existing problem. 1,7 Students are monitored at various stages to make sure that they have achieved certain required skill in the completion of the different parts of the project. Each group of students is required to produce written reports. Students are required to demonstrate team work. The have to understand the use of various tool and instrument for the construction of the project. It needs technical knowledge and skills.

Laboratory sessions, miniproject

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SUBJECT DESCRIPTION FORM

Subject Title: Communication Fundamentals Number of Credits: 3

Subject Code: EIE239 (for 61031) Hours Assigned: Lecture/tutorial 33 hours Laboratory 9 hours (Equivalent to 18 laboratory hours)

Pre-requisite: nil

Co-requisite: nil

Exclusion: nil

Objectives: This subject will provide students with the basic elements and fundamental concepts of electronic communications. It enables students to master the essential skills for learning and understanding of practical electronic communication systems. Through a series of lab exercises, students will have the chance of enhancing their understanding of the fundamental concepts. Student Learning Outcomes: On successful completion of this subject, the students will be able to: Category A: Professional/academic knowledge and skills 1. Understand the basic elements in a communication system. 2. Understand the spectral properties of signals. 3. Understand the operation of AM and FM modulation techniques and their areas of application. 4. Understand the logic concepts and applications of information theory. Category B: Attributes for all-roundedness 5. Think critically. 6. Learn independently. 7. Present ideas and findings effectively.

Syllabus: 1. Model of a Communication System 1.1 Information source, encoder, decoder, communication channel, modulator, demodulator. 2. System and Signal Analysis 2.1 Systems and signals. 2.2 Fourier series, Fourier transform, power spectral density. 2.3 Linear modulation system. 3. Analog Signal Transmission 3.1 Amplitude modulation, frequency modulation. 3.2 Frequency division multiplexing. 3.3 Commercial broadcasting. 4. Information and Channel Capacity 4.1 Measure of information, source encoding, discrete and continuous communication channels.

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Laboratory Experiment: Practical Works 1. Fourier analysis 2. Sampling of signals 3. Huffman coding

Method of Assessment: Coursework: 40% Examination: 60%

Textbooks: 1. 2. J. Proakis, Communication System Engineering, 2nd ed., Prentice-Hall, 2002. F.G. Stremler, Introduction to Communication Systems, 3rd ed., Addison-Wesley, 1990

Reference Books: 1. 2. 3. 4. K.S. Shanmugam, Digital & Analog Communication Systems, John Wiley & Sons, 1985. H. Taub and D.L. Schilling, Principles of Communication Systems, 2nd ed., McGraw-Hill, 1986. W. Schweber, Electronic Communication Systems, Prentice-Hall, 1991. Simon Haykin, Communication Systems, John Wiley & Sons, 3rd ed., 1994

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Alignment of Teaching and Learning (T&L) Methods with Learning Outcomes: T&L Method Lectures PISER Outcome numbers 1, 2,3,4 1, 2,3,4 Remarks Fundamental principles and key concepts of the subject are delivered to students. Students' knowledge on/understanding of certain topics can be easily estimated, and the corresponding teaching time will be adjusted accordingly. Supplementary to lectures and are conducted in special sessions; Students will be able to clarify concepts and to have a deeper understanding of the lecture material; Problems and application examples are given and discussed. Students will go through all the important steps in lossless compression using Huffman Coding and system simulation using Matlab.

Tutorials

1, 2,3,4,5

Laboratory sessions

1,2,4,6,7

Alignment of Assessment and Learning Outcomes: Assessment Method Assignments, tests and examination Learning Outcome 1,2,3,4,5 Remarks End-of chapter type problems used to evaluate students' ability in applying concepts and skills learnt in the classroom. Students need to think critically and creatively in order to come with an alternate solution for an existing problem. Each student is required to produce written reports. For some of the practical works, students are required to make demonstration to illustrate their understanding of the related technical knowledge and skills.

Laboratory sessions

1,2,4,6,7

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SUBJECT DESCRIPTION FORM

Subject Title: Management & Organisation Number of Credits: 3

Subject Code: MM2021 Hours Assigned: Lecture Seminar

28 hours 14 hours

Pre-requisite: Nil Exclusion: Introduction to Management (MGT201/MM201) Organisational Behaviour (MGT202/MM211) Organisation & Management (MGT203/MGT389/MM202/MM302) People and Management (MM2191)

Objectives: This subject introduces the basic theories and concepts concerning firstly, the functions of managing a business, secondly, the study of human behaviour and its implications for the management of organisations, and thirdly, the importance of social responsibility and ethics in managing organisations. The subject will also develop students' critical thinking and communication skills, both oral and written. Student Learning Outcomes On completion of this subject, students will: · Be able to identify the nature of managerial work in a variety of forms of organisation, and assess the impact of the external environment on managers' jobs. · Be able to explain and analyse the functions of management ­ planning, organising, leading, and controlling. · Understand the essence of human behaviour and be able to assess the implications for the management of organisations and businesses. · Be able to evaluate the arguments surrounding social responsibility and ethical behaviour in organisations and businesses, and in so doing have an enhanced awareness of the importance of such issues. · Have further developed their critical thinking, and oral and written communication skills. Teaching/Learning Approach: In the lectures the general principles of the syllabus topic will be presented and developed. In the seminars, students will develop and apply the general principles of the topic in studentcentred activities.

Syllabus: Managers and Management Define the nature of managerial work taking into account the impacts of the external environment in modern society. Provide an overview of the evolution of management thoughts.

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Management Functions The major elements of the management functions: planning, organising, leading, and controlling, and their importance for the effective management of business organisations. Planning Foundations of planning. Decision making and problem solving. Strategic management. Organising an Enterprise Review of a variety of organisational structures and the identification of the conditions under which they are appropriate. Managerial communication and information technology. Staffing and human resource management. Leading The manager's role as a leader. Foundations of human behaviour. Leading and motivating employees ­ individuals and groups. Controlling Foundations of control. Operations and quality management. Controlling for organisational performance. Social Responsibility and Managerial Ethics Arguments for and against social responsibility as a business objective. Factors affecting managerial ethics. Approaches to improving ethical behaviour.

Method of Assessment: Continuous Assessment Examination

50% 50%

To pass the subject, students must obtain grade D or above in both Continuous Assessment and examination. Reference Books: *Individual subject lecturer may prescribe different textbooks for the course. Recommended Textbook Robbins, S.P. and Coulter, M., Management, 8th ed., Prentice-Hall, 2005. Recommended References Certo, Modern Management, 10th ed., Prentice-Hall, 2006. Jones, Contemporary Management, 4th ed., McGraw-Hill, 2006. Kinicki & Williams, Management : A Practical Introduction, 2nd ed., McGraw Hill, 2006. McShane, Organizational Behavior, 3rd ed., McGraw-Hill, 2005. Robbins, Essentials of Organizational Behavior, 8th ed., Prentice-Hall, 2005. Schermerhorn, J.R. Management, 8th ed., John Wiley & Sons, 2005. Sieren, Boos and Boos, China Management Handbook, MacMillan, 2002. Current journal articles, periodicals & newspapers will also be assigned for study.

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SUBJECT DESCRIPTION FORM

Subject Title: Introduction to Marketing Number of Credits: 3

Subject Code:

MM2711 28 hours 14 hours

Hours Assigned: Lecture Seminar

Pre-requisite: Nil

Exclusion:

Marketing and the Consumer (M2791)

Objectives: This core subject introduces the basic principles and concepts of Marketing. It provides an analytical foundation for further study of Marketing and also contributes to the Learning Outcomes for all students in two ways. First, the content directly addresses the creation of value, ethics, cultural diversity and globalization. Second, the classroom activities and assessments develop students' teamwork, ability to communicate in English, creative thinking and learning to learn. Student Learning Outcomes: On successfully completing this subject, students will be able to: · · · · · · Understand the role and value of marketing in today's increasingly competitive, dynamic and turbulent environment. Analyse market situations in different cultural / global environments, identifying marketing opportunities and threats; and understand organisations' response process to these environments. Synthesise the process of marketing planning and the process of corporate planning. Formulate marketing mix strategies and programmes and implement them. Apply marketing theories, models, and information technology to practical marketing situations. Establish the relationship between marketing & society in the context of social responsibility and marketing ethics.

Teaching/Learning Approach Keynote lectures, requiring the active engagement of students, will provide them with the conceptual frameworks required for the analysis of Marketing issues. Classroom work will involve teams of students working together to prepare and give presentations, and to critique the work presented by others. Emphasis is placed throughout on the application of theory to the solution of practical and realistic marketing problems in the local and the global setting

Syllabus: Fundamentals of Modern Marketing Marketing in the modern organization, types of marketing, overview of the marketing process, strategic marketing planning, introduction to the marketing mix, developing competitive

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advantages. Analysing Marketing Structure and Behaviour Global and competitive marketing environment, consumer and organization markets and their buying behaviour. Researching and Planning of Marketing Activities Marketing research and audit, marketing information system, marketing planning and forecasting. Selecting Market Opportunities Market segmentation, market targeting, product positioning, pricing, promotion and placing. Introduction to the Marketing Mix Product, Pricing, Promotion and Placing Marketing and society Social and Marketing ethics: marketing impacts on individual consumers, society and other businesses.

Method of Assessment: Continuous Assessment Examination 50% 50%

To pass the subject, students must obtain grade D or above in both Continuous Assessment and examination.

Reference Books: Recommended Textbook Kotler, P. and Armstrong, G., Principles of Marketing, New Jersey, Prentice Hall, 2004. References Boone, E.L. and Kurtz, L.D., Contemporary Marketing, Thomson, South-Western, 2004. Etzel M.J., Walker B.J. and Stanton W.J., Marketing, McGraw Hill /Irwin, 2004. Lamb Hair McDaniel, Marketing. Thomson, South-Western, 2004.

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SUBJECT DESCRIPTION FORM

Subject Title: Foundations of Software Engineering Subject Code: COMP 302 Number of Credits: 3 Hours Assigned: Lecture 28 hours Tutorial 14 hours

Pre-requisite: COMP 201, COMP 210

Co-requisite: Nil

Exclusion: Nil

Objectives: This subject provides students with: · a general knowledge of the application of software engineering techniques in different stages and aspects of software development; · practice in applying the theories, concepts and techniques acquired during lectures through the actual accomplishment of a guided case study project. Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) apply software engineering techniques in the systems specifications and design stages of software projects; (2) apply software engineering techniques to real-life case study projects; (3) acquire concepts in software quality assurance standards and be able to develop skills and practices in quality software development; Attributes for all-roundedness (1) solve complex problems in groups and be able to communicate effectively through project presentations; (2) communicate in writing with technical documentation throughout the various stages of project development.

Syllabus: Topic 1. Software process Software process and process models; software reuse. 2. Specification and requirement analysis Event-based specification; model-based specification; requirements analysis; prototyping. 3. Software analysis and design System analysis and models; overview of software design process and strategies; function-oriented design; objected-oriented design.

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Duration of Lectures 2

4

10

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4. Programming techniques and tools Programming style; fault avoidance and tolerance; exception handling; defensive programming; computer-aided software engineering; software development environment; features of programming languages. 5. Software verification and validation Testing techniques and tools; static analysis; formal proof; design and code reviews, inspection, walkthrough; software reliability; software safety. 6. Software metrics Complexity metrics; use of metrics for software monitoring and control; software quality assurance. Total Laboratory Experiment: Nil

2

6

4

28

Case Study: Students will practice their skills in developing a group project representing a real-life application.

Method of Assessment: Continuous Assessment Case Study Other Course Work Examination 60% 30% 30% 40%

Textbooks: 1. Pressman, R., Software Engineering: A Practitioner's Approach, 6th Edition, McGraw-Hill, 2005. Reference books: 1. Sommerville, I., Software Engineering, 7th Edition, Addison-Wesley, 2004. 2. Booch, G., Object Oriented Analysis & Design with Applications, Second Edition, Addison-Wesley, 1994. 3. Jacobson, I., Booch, G. and Rumbaugh, J., The Unified Software Development Process, Addison-Wesley, 1999. 4. Pierre Bourque and Robert Dupuis, Guide to the Software Engineering Body of Knowledge, IEEE Computer Society, 2004. 5. Kathy Schwalbe, Information Technology Project Management, Third Edition, Course Technology (Thomson Learning), 2003.

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SUBJECT DESCRIPTION FORM

Subject Title: Human Factors and User Interfaces Number of Credits: 3

Subject Code: COMP 303 28 hours 14 hours

Hours Assigned: Lecture Laboratory

Pre-requisite: COMP 201

Co-requisite: Nil

Exclusion: Nil

Objectives: · · · To provide students with a broad view of both theoretical and practical issues in human factors for design of human-computer interfaces. To equip students with knowledge and understanding of the nature of human computer interactions, human characteristics, computer system and interface architecture. To equip students with sound skills in design, development and evaluation of user interfaces.

Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) gain a deep understanding of the human factor, the most important foundation of user interface and interaction design; (2) grasp the theoretical issues in user interface and interaction design, e.g., Fitts' Law, OAI model etc. as well as their applications in the design of various systems; (3) evaluate a human computer interface design; (4) familiarize to the requirements of different application platforms; Attributes for all-roundedness (1) solve problems by using systematic approaches; (2) learn team working skills; (3) write technical reports and present the findings. Syllabus: Topic 1. Nature of Human Computer Interaction (HCI) Definitions and importance of HCI; history and intellectual roots of HCI; roles various disciplines play within HCI. 2. Evaluation Role of evaluation; evaluation techniques; experiments and benchmarking. 3. Human Characteristics Perception and representation; models and limits of human memory; mental models; use of metaphors; support user aspects of language, social and organizational aspects; input and output devices: performance characteristics (human and system); speech input and output.

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Duration of Lectures 2

4 6

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4. Dialogue interactions and formal models Task analysis and predictive modeling; dialogue interaction: types and techniques; multimedia and non-graphical dialogues; response time; statistical models for describing interaction processes. 5. Awareness and CSCW CSCW, awareness and situated awareness, groupware; awareness and design issues; awareness in MMORPGs; interaction patterns; design rationale for CSCW-oriented applications. 6. Design guidelines and metrics User-centered design and task analysis; software engineering design models; structural HCI design and envisioning design; standards and metrics; guidelines to support design; standards and metrics; documentation and online information. 7. Development and applications Design rationale; participatory design and prototyping; user interface management systems; WWW applications designs; groupware; collaborative work and virtual environments. Total Laboratory Experiment and other Practical Work: Topic 1. 2. 3. 4. Familiarization of HCI tools. Understanding of human factors. Design of a human computer interface. Evaluation strategies.

6

6

3

1

28

Duration of Laboratory 2 4 6 2 Total 14

Case Study: Nil

Method of Assessment: Continuous Assessment Examination

65% 35%

Textbook: 1. A. Dix, J. Finlay, G. Abowd, and R. Beale, Human-Computer Interaction, 3rd Edition, Prentice Hall, 2004. Reference Books: 1. B. Shneiderman, Designing the User Interface: Strategies for Effective Human-Computer Interaction, 3rd Edition, Addison Wesley, 1998. 2. W.J. Smith, ISO and ANSI Ergonomic Standards for Computer Products. A Guide to Implementation and Compliance. Prentice Hall, 1996. 3. P.K. Andleigh and K. Thakrar, Multimedia Systems Design, Prentice Hall, 1996. 4. M.E.S. Morris and R.J. Hinrichs, Web Page Design: A Different Multimedia, Prentice Hall, 1996. 5. K. Mullet and D. Sano, Designing Visual Interfaces. Prentice Hall, 1995.

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SUBJECT DESCRIPTION FORM

Subject Title: Operating Systems Number of Credits: 3

Subject Code:

COMP 304 28 hours 14 hours

Hours Assigned: Lecture Tutorial/Lab

Pre-requisite: COMP 201

Co-requisite: Nil

Exclusion: Nil

Objectives: This subject provides students knowledge on: · resource management provided by operating systems; · concepts and theories of operating systems; · implementation issues of operating systems. Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) identify the services provided by operating systems; (2) understand the internal structure of an operating system and be able to write programs using system calls; (3) understand and solve problems involving process control, mutual exclusion, deadlock and synchronization. Attributes for all-roundedness (1) develop skills in problem solving using systematic approaches; (2) solve complex problems in groups and develop group work.

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Syllabus: Topic 1. Introduction to operating systems Types and functionalities of operating systems; system components and services; resource management. 2. Process management Process concepts; process manipulation; asynchronous concurrent processes; mutual exclusion; synchronization; deadlock; scheduling algorithms. 3. Memory and secondary storage management Virtual memory; paging and segmentation system; secondary storage allocation; directory and file system structure. 4. Protection and security Protection and access control; capabilities; security and cryptography. 5. Case studies on operating systems Structure of Unix, Windows NT, etc. Total Laboratory Experiment: Unix environment, shell scripts, system calls. Case Study: Contemporary OS like Unix, Windows. Duration of Lectures 4

8

8

4

4

28

Method of Assessment: Continuous Assessment Examination 55% 45%

Textbooks: 1. Silberschatz, A. and Galvin, P., Operating System Concepts, 6/E, John Wiley and Sons, 2005. Reference Books: 1. Stallings, W., Operating Systems: Internals and Design Principles, 4/E, Prentice Hall, 2001. 2. Keith Haviland, Dina gray, Ben Salama, Unix System Programming : A Programmer's Guide to Software Development, Second Edition, Addison Wesley, 1999. 3. Gary Nutt, Operating Systems: A Modern Perspective, 3/E, Addison Wesley, 2004.

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SUBJECT DESCRIPTION FORM

Subject Title: Data Structures and Algorithms Subject Code: Number of Credits: 3

COMP 305 28 hours 21 hours

Hours Assigned: Lecture Tutorial/Lab

Pre-requisite: COMP 201

Co-requisite: Nil

Exclusion: Nil

Objectives: · · To provide knowledge in various data structures and algorithms. To introduce techniques for analyzing the efficiency of computer algorithms.

Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) understand the properties of various data structures; (2) identify the strengths and weaknesses of different data structures; (3) design and employ appropriate data structures for solving computing problems; (4) possess the knowledge of various existing algorithms; (5) analyze and compare the efficiency of algorithms; (6) possess the ability to design efficient algorithms for solving computing problems; Attributes for all-roundedness (1) solve problems independently; (2) think critically for improvement in solutions.

Syllabus: Topic 1. Introduction Types of algorithms; analysis of algorithms; data structures; abstract data types. 2. Analysis of algorithms Mathematical techniques; classification of algorithms and their efficiencies; average-case and worst-case analysis. 3. Data structures: representation and algorithms Linear structures: linked-lists, stacks, queues; tree structures: binary trees, balanced trees, m-way trees, tree traversals; other common data structures: priority queues, heaps. 4. Sorting and searching algorithms Quadratic-time algorithms: bubble sort, insertion sort, selection sort; optimaltime algorithms: quick sort, merge sort, heap sort; searching algorithms:

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Duration of Lectures 2

2

8

8

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sequential search, binary search, tree search, dictionary and hashing. 5. Graph algorithms Depth-first and breadth-first search; test for acyclicity; topological sorting. 6. Text processing and data compression Prefix and suffix; dictionary; run-length encoding; Huffman coding. 7. Selected advanced topics Advanced topics such as AVL trees, divide-and-conquer. Total Laboratory Experiment: Use of different data structures Case Study: Nil 2

4

2

28

Method of Assessment: Continuous Assessment Examination 60% 40%

Textbooks: 1. Mark Allen Weiss, Data Structures and Algorithm Analysis in C, Second Edition, Addison Wesley, 1997. 2. Goodrich, M.T. and Tamassia, R., Data Structures and Algorithms in Java", Second Edition, John Wiley, 2001.

Reference Books: 1. Adam Drozdek, Data Structures and Algorithms in Java, Broooks/Cole, 2001. 2. Cormen, Leiserson and Rivest, Introduction to Algorithms, MIT Press, 1990.

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SUBJECT DESCRIPTION FORM

Subject Title: System Programming Number of Credits: 3

Subject Code:

COMP 309 28 hours 14 hours

Hours Assigned: Lecture Tutorial/Lab

Pre-requisite: COMP 304

Co-requisite: Nil

Exclusion: Nil

Objectives: · · · To introduce students the concepts and principles of system programming and to enable them to understand the duties and scope of a system programmer. To provide students the knowledge about both theoretical and practical aspects of system programming, teaching them the methods and techniques for designing and implementing system-level programs. To train students in developing skills for writing system software with the aid of sophisticated OS services, programming languages and utility tools.

Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) organize the functionalities and components of a computer system into different layers, and have a good understanding of the role of system programming and the scope of duties and tasks of a system programmer; (2) grasp the concepts and principles, and be familiar with the approaches and methods of developing system-level software (e.g., compiler, and networking software); (3) apply the knowledge and techniques learnt to develop solutions to real-world problems; (4) select and make use of the OS kernel functions and their APIs, standard programming languages, and utility tools; (5) organize and manage software built for deployment and demonstration; Attributes for all-roundedness (1) analyze requirements and solve problems using systematic planning and development approaches; (2) write technical project reports in well-organized and logical manner; (3) work in teams and collaborate with classmates.

Syllabus: Topic 1. Introduction to system programming Layered structure of a computer system; system software and application software; scope and tasks of system programming. 2. Overview of compiler construction Syntax and semantics of programming languages; language translation

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Duration of Lectures 1

2

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3.

4.

5.

6.

7.

8.

9.

approaches; tasks of a compiler; the compiler process. Lexical analysis Tasks of lexical analysis; specifying tokens by regular grammars and regular expressions; recognizing tokens by Finite Automata (FA); construction of FA from regular expressions; converting NFA to DFA; simulating DFA. Syntax analysis Tasks of syntax analysis; specifying language constructs by context-free grammars; BNF; derivation; parse and syntax trees; recognizing language constructs by Pushdown Automata; top-down and bottom-up parsing methods. Code generation Intermediate compilation phases; symbol table; intermediate code generation; code optimization; code generation. Introduction to UNIX programming Evolution of UNIX; features of UNIX; UNIX standards; good style of UNIX programming. UNIX file systems Files; types of UNIX files; UNIX file system; structure and representation of files in UNIX file system; directories; accessing files in UNIX; I/O redirection; devices and device drivers; UNIX file interface (APIs). UNIX processes UNIX shell; UNIX process creations and execution; process management; parent and child processes; UNIX process interfaces (APIs). UNIX inter-process communications Concurrency and communications; local and remote process communications; UNIX signals and interface; pipes; UNIX sockets and interface; RPC. Total

4

5

2

2

4

4

4

28

Tutorials: 8 hours Laboratory Experiment: Topic 1. UNIX system and C programming. 2. LEX and YACC. 3. UNIX programming (processes and files). Duration of Laboratory 2 2 2 Total 6

Case Study: Nil

Method of Assessment: Continuous Assessment Examination 55% 45%

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Textbook: 1. A.V. Aho, R. Sethi and J.D. Ullman, "Compilers: Principles, Techniques, and Tools". Addison-Wesley, 1986. 2. B. Molay, "Understanding Unix/Linux Programming". Pearson Education, 2003. Reference Books: 1. A.W. Appel, "Modern Compiler Implementation in Java", Cambridge University Press, 1998. 2. K.C. Louden, "Compiler Construction: Principles and Practice", PWS Publishing Company, 1977. 3. C.N. Fischer and R.J. LeBlanc, Jr, "Crafting a Compiler with C", The Benjamin/Cummings Publishing Company, 1991. 4. L.L. Beck, "System Software: an Introduction to System programming", Addison Wesley, 1990. 5. W.R. Stevens, "UNIX Network Programming", Vols. 1&2, Prentice Hall, 1998/1999. 6. J.S. Gray, "Interprocess Communications in UNIX", 2nd edition, Prentice Hall, 1998. 7. U. Vahalia, "UNIX Internals: The New Frontiers", Prentice-Hall, 1996.

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SUBJECT DESCRIPTION FORM

Subject Title: Foundations of Database Systems Subject Code: Number of Credits: 3 Hours Assigned: Lecture Tutorial/Lab

COMP 311 28 hours 14 hours

Pre-requisite: COMP 201 and (COMP 305 or COMP 210) Co-requisite: Nil Exclusion: Nil

Objectives: This subject provides students knowledge on: · design, develop, implement, and administrate a database system of considerable complexity; · possess enough background to evaluate various DBMSs of different data models and make the appropriate selection for an organization. Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) acquire a good understanding of the architecture and functioning of database management systems, as well as to be able to use the associated tools and techniques; (2) understand and apply the principles and practices of good database design and analysis; (3) recognize the direction of database technology and their implication so as to manage and plan database system developments. Attributes for all-roundedness (1) appreciate development of database technologies for lifelong learning, e.g., web databases; (2) build up on team spirit, presentation and technical writing skills.

Syllabus: Topic 1. Basic concepts of database system Database and its applications; DBMS design objectives and its components; ANSI/SPARC three-level system architecture; data independence. 2. Database design Entity-relationship model; functional dependencies; normalization. 3. Relational data model Relational structure; relational languages: relational algebra, relational calculus, SQL; relational constraints: entity constraints, referential integrity constraints and foreign keys.

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Duration of Lectures 2

6

6

Page 92

4. File structures and physical database design File organization; indexing and hashing. 5. Application designs and query processing Relational view definition and management; equivalence of expressions, estimation of query-processing cost, join strategies; database and the World Wide Web; embedded SQL and ODBC. 6. Implementation issues Buffer management; transaction processing; concurrency control; crash and recovery; security and integrity. Total Laboratory Experiment:

4 6

4

28

There are two types of laboratory/tutorial sessions: · Practice of technical skills such as database CASE tools, SQL and application programming. · Reinforce design and analysis skills through group interactions, presentations and prototype demonstrations. Case Study: Real-life/industrial database application development examples will be discussed in classes and/or tutorials when appropriate.

Method of Assessment: Continuous Assessment 55% Individual assignments, short quizzes and term project Assignments are for students to practice their technical skills Quizzes are to encourage students to have a consistence study pace The term project includes database design and analysis as well as verbal and written Presentations Examination 45%

Textbooks: 1. Michael Manning. Database Design, Application Development, & Administration, 2nd edition, McGraw-Hill, 2004. Reference Books: 1. David Kroenke. Database Processing: Fundamentals, Design and Implementation, 8th edition, Prentice Hall, 2002.

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2. A Silberschatz, H.F. Korth, S. Sudarshan. Database System Concepts 4th Edition. McGraw Hill, 2002. 3. Hector Garcia-Molina, Jeffrey D. Ullman & Jennifer Widom. Database System Implementation, Prentice Hall, 2000. 4. C. J. Date. An Introduction to Database Systems, Addison-Wesley Longman, 1999.

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SUBJECT DESCRIPTION FORM

Subject Title: Computer Communications Networks Number of Credits: 3

Subject Code:

COMP 312 28 hours 14 hours

Hours Assigned: Lecture Tutorial/Lab

Pre-requisite: Nil

Co-requisite: Nil

Exclusion: Nil

Objectives: The key objective is to acquire a foundational understanding of computer communications technologies. Emphasis will be on the link layer and above. Networking concepts will be illustrated using the TCP/IP and ATM networks. Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) acquire a good knowledge of the computer network, its architecture and operation; (2) understand and apply the principles and practices of computer networks; (3) realize network communication skills through programming. Attributes for all-roundedness (1) follow future trends of computer networks, e.g., recent optical networks, ATM, 3G; (2) build up on team work, presentation and technical writing skills.

Syllabus: Topic 1. Fundamentals Protocol layering concept; service primitives and protocols; data encapsulation. OSI reference model; and TCP/IP reference model; physical characteristics of transmission medium: data rate, bandwidth and channel capacity. 2. Data link and MAC sublayer Data link layer basics: framing, error detection, automatic repeat request protocols; common existing protocols: ATM, CSMA, IEEE 802.11. 3. Network layer Connection-oriented and connectionless networks; distance vector and link state routing algorithms; case study of IP: IP addressing and subnets, Address Resolution protocols, routing mechanisms. 4. Transport layer User Datagram Protocol (UDP); Transmission Control Protocol (TCP).

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Duration of Lectures 4

6

8

6

Page 95

5. Application layer Various types of networking applications. Total Laboratory Experiment: Laboratory exercises on networking such as socket programming. Case Study: Case studies on latest computer networking technologies.

4

28

Method of Assessment: Continuous Assessment Examination 55% 45%

Textbooks: 1. L. Peterson and B. Davie, Computer Networks: A Systems Approach, Third Edition, Morgan Kaufmann, 2003. Reference Books: 1. W. R. Stevens, TCP/IP Illustrated Volume I, The Protocols, Addison Wesley, 1994. 2. A S. Tanenbaum, Computer Networks, Third Edition, Prentice-Hall, 1996. 3. D. E. Comer, Internetworking with TCP/IP: Volume I--Principles, Protocols, and Architecture, Third Edition, Prentice-Hall, 1995. 4. S. Keshav, An Engineering Approach to Computer Networking, Addison Wesley Longman, 1997. 5. W. Stallings, High-Speed Networks: TCP/IP and ATM Design Principles, Prentice-Hall, 1998. 6. W. Stallings, Network and Internetwork Security: Principles and Practice, IEEE Press, 1995 7. W. R. Stevens, UNIX Network Programming Volume 1 ­ Networking APIs: Sockets and XTI, Second Edition, Prentice-Hall, 1998.

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SUBJECT DESCRIPTION FORM

Subject Title: Object-oriented Methods for Information Systems Development Subject Code: COMP 316 Number of Credits: 3 Hours Assigned: Lecture 28 hours Tutorial/Lab/Sem 14 hours

Pre-requisite: COMP 201, COMP 302

Co-requisite: Nil Exclusion: COMP 314, COMP 414

Objectives: · · · To introduce students to the concepts and practices of the object-oriented approach to software development. To familiarize students with the tools and languages for object-oriented analysis, design and implementation. To expose students to the applications of object-oriented technologies.

Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) analyze a problem using an object-oriented approach; (2) design an object-oriented model for a problem, and implement the design using appropriate object-oriented tools and techniques; (3) document the analysis and design of an information system using UML; (4) determine the degree to which a technology conforms to the object-oriented paradigm; Attributes for all-roundedness (1) analyze and solve information system problems in a systematic manner; (2) cooperate with team members in problem solving; (3) report and present the solution to an information system problem clearly.

Syllabus: Topic 1. Information system analysis and design System Development Life Cycle: requirement definition and specification; analysis and design; implementation; testing. 2. Object-oriented paradigm Rationale for the OO approach; OO software development life cycle; objects and classes; abstraction, aggregation, messages, services, encapsulation, association, generalization, inheritance hierarchy, polymorphism, metaclass.

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Duration of Lectures 4

4

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3. Object-oriented analysis and design Object behaviour analysis; identification of classes and objects in a problem domain; object relationships; identification of structures, attributes instance connection, services and message connections; design issues in problem domain: data management, task management and human interface components, mapping an OO data model into a relational model; reuse, patterns, and frameworks; Unified Modeling Language (UML). 4. Object-oriented languages and systems Characteristics of object-oriented tools such as C++, Java, Smalltalk. 5. Object-oriented Project Management Applications in information system analysis, design and software engineering; user interfaces, system conversion, user training, user guide and operations manual, system development planning and scheduling, software cost estimation. Total Tutorials/Laboratories/Project presentations and seminars: Topic 1. OO/UML development tools such as Rational Rose. 2. Class exercises on OO analysis and design problems. 3. Presentations and demonstrations of projects. Total Case Study: Nil

12

4

4

28

Duration of Laboratory 14

14

Method of Assessment: Continuous Assessment 60% Individual exercises, tests, group project involving implementation, demonstration and presentation Examination 40%

Reference Books: 1. Timothy C. Lethbridge and Robert Laganiere. Object-Oriented Software Engineering ­ Practical software development using UML and Java, McGraw-Hill, 2nd Edition, 2005. 2. Simon Bennett, Steve McRobb and Ray Farmer. Object-Oriented System Analysis and Design Using UML, 2nd Edition, McGraw-Hill, 2002. 3. Wolfgang Emmerich. Engineering Distributed Objects, John Wiley & Sons, 2000. 4. Grady Booch, James Rumbaugh and Ivar Jacobson. The Unified Modeling Language User Guide, Addison Wesley, 1999. 5. Grady Booch. Object-Oriented Analysis and Design with Applications, 3rd Edition, Benjamin/Cummings, 2005. 6. B. Meyer. Object-Oriented Software Construction, 2nd Edition, Prentice Hall, 2002.

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7. M. Fowler and K. Scott. UML Distilled: A Brief Guide to the Standard Object Modeling Language, 3rd Edition, Addison Wesley, 2003. 8. B. Hughes and M. Cotterell. Software Project Management, 3rd Edition, McGraw-Hill, 2002. 9. Deitel & Deitel. Java: How to Program, 6th Ed., Prentice Hall, 2004. 10. Deitel & Deitel. C++: How to Program, 5th Ed., Prentice Hall, 2005.

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SUBJECT DESCRIPTION FORM

Subject Title: Systems Simulation Number of Credits: 3

Subject Code: Hours Assigned: Lecture Tutorial/Lab

COMP 318 28 hours 14 hours

Pre-requisite: COMP 201, COMP 211

Co-requisite: Nil

Exclusion: COMP 308

Objectives: · · To provide students with basic knowledge of modern computer simulation methods and languages. To enable students to apply computer simulation techniques to simulate the operations of various kinds of real-world facilities or processes.

Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) acquire the ability to think and reason in a creative and critical manner when applying IT technology to different information processing areas, such as business, industry and public sectors; (2) acquire the skills that include analytic modelling and simulation so that appropriate solution alternatives in problem solving and application development can be soundly determined by a process of guided evaluation; (3) know how to use simulation packages and tools that are immediately applicable in business and industry; Attributes for all-roundedness (1) solve problem with an analytic and critical view; (2) learn to collect performance data independently and analyze them empirically so that the dynamics of the target system can be deciphered.

Syllabus: Topic 1. Computer simulation Applications of computer simulation; continuous model, model, and combined model. 2. Modeling and analysis techniques for simulation Models versus simulation models; replication; autocorrelation; regenerative methods. discrete Duration of Lectures 3

6 sequential batching;

3. Simulation of deterministic and random processes Random number generator; generation of random variates for various

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distributions, e.g. exponential, triangular, Zipfian, Gaussian; inverse transform method; acceptance-rejection method; discrete event simulation concepts; event scheduling; list processing and time advance algorithms; trace-driven simulation; verification and validation. 4. Computer simulation languages and software Entity-oriented language, e.g. GPSS; process-oriented/event-oriented language, e.g. Simscript; embedded language, e.g. CSIM; simulation software, e.g. Petri-net. 5. Problem solving and case studies Simulation experiments; problem solving in realistic applications; case studies, e.g. system performance simulation, network simulator, and flight simulator. Total Laboratory Experiments and other Practical Work: Topic (vary year after year) 1. 2. 3. 4. Set up the link to a time-Petri-net packet. Draw Petri-nets for different systems for logical analysis. Program the firing sequence for system constraints analysis. Evaluate Petri-nets that model real-life systems (e.g. a TCP channel). Total Case Study: Nil Duration of Laboratory 1 1 1 2 5 8

4

28

Method of Assessment: Continuous Assessment Examination 55% 45%

Reference Books: 1. Banks, J., Carson, J., Nelson, B. and Nicol, D., Discrete-Event System Simulation, Third Edition, Prentice-Hall, 2001. 2. Jain, R., The Art of Computer Systems Performance Analysis, Techniques for Experimental Design, Measurement, Simulation, and Modeling, Wiley, 1991. 3. Banks, J., Carson, J. and Sy, J., Getting Started With GPSS/H, Second Edition, Wolverine Software Corporation, 1995. 4. Gould, H. and Tobochnik, J., An Introduction to Computer Simulation Methods: Applications to Physical System, Benjamin Cummings, 1996. 5. Law, A.L. and Kelton, D.W., Simulation Modeling and Analysis, Third Edition, McGrawHill, 2000. SUBJECT DESCRIPTION FORM

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Subject Title: Introduction to Multimedia Computing Number of Credits: 3

Subject Code: COMP 319 28 hours 14 hours

Hours Assigned: Lecture Tutorial/Lab

Pre-requisite: COMP 305, COMP 311

Co-requisite: Nil

Exclusion: COMP 419

Objectives: · · To provide the foundation knowledge of multimedia computing, e.g. compression standards, data formats, media characteristics, storage and transmission requirements, that are essential to multimedia system design. To provide programming training in multimedia systems and multimedia Web designs.

Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) understand the characteristics of different media and be able to take into considerations of different requirements in multimedia system designs; (2) create multimedia contents, including speech and audio, image and graphics, and animation and video; (3) analyze different multimedia data, e.g. image and speech, for some systems; (4) understand different compression principles and techniques and be able to use them in different multimedia system designs; (5) understand different multimedia compression standards, e.g. JPEG, MPEG, ASF, and be able to design and develop multimedia systems according to the standards; (6) program multimedia data and be able to develop Web media applications; Attributes for all-roundedness (1) solve problems using systematic approaches; (2) learn independently and search for the information required in solving problems.

Syllabus: Topic 1. Overview of multimedia computing Definitions, terms, terminologies, characteristics and requirements of different media; components of multimedia systems; multimedia industry. 2. Multimedia I/O and devices High performance I/O; multimedia I/O; RAID technology; multimedia storage; network components and standards. 3. Multimedia data representation and analysis Representation of sound/audio, image and graphics, video and animation;

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Duration of Lectures 2

2

8

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speech generation, analysis and software; image synthesis and analysis; animation concepts; language and display. 4. Multimedia coding and compression Coding requirements; compression principles; entropy and hybrid coding; compression standards: JPEG, MPEG, DVI, ASF, etc. 5. Multimedia systems supports Operating system requirements for multimedia data, including data storage, multitasking, data sharing, congestion control, admission control, traffic policing, traffic analysis and prediction, buffer management, and scheduling. Total Laboratory Experiments and other Practical Work: Topic 1. Building user interface using Flash. 2. Animation using Flash. 3. Media content integration for web-site construction. 4. Text and masking in Flash. 5. Programming in Flash using ActionScript. 6. Building simple applications with Flash. 7. Revision exercises for lecture topics. Duration of Laboratory 1 1 1 1 2 2 6 Total 14 10

6

28

Case Study: Nil

Method of Assessment: Continuous Assessment Examination 55% 45%

Reference Books: 1. Z.N. Li and M.S. Drew, Fundamentals of Multimedia. Prentice Hall, 2003. 2. K. Jeffay and H. Zhang, Readings in Multimedia Computing and Networking. Morgan Kaufmann, 2002. 3. S.V. Raghavan and S.K. Tripathi, Networked Multimedia Systems: Concepts, Architecture, and Design. Prentice Hall, 1998. 4. G. Lu, Communication and Computing for Distributed Multimedia Systems. Artech House, 1996. 5. B. Furht and M. Milenkovic, A Guided Tour of Multimedia Systems and Applications. IEEE Computer Society Press, 1995.

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SUBJECT DESCRIPTION FORM

Subject Title: Introduction to Internet Computing Number of Credits: 3

Subject Code:

COMP 320 28 hours 14 hours

Hours Assigned: Lecture Laboratory

Pre-requisite: COMP 201

Co-requisite: Nil

Exclusion: COMP 420

Objectives: · · · Highlight the impact of Internet in facilitating a truly distributed, wide area and highly accessible computing environment. Examine the analysis, design and implementation techniques required to develop the network, enterprise and Internet based information systems. Review state-of-the-art technologies such as distributed client/server computing paradigm, middleware concepts and architecture, web-based client/server computing technologies, XML, wireless and intelligent Internet computing.

Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) identify different components of distributed client/server on Internet computing; (2) understand the basic concepts of Internet services and related technologies; (3) be proficient in using Java Servlets and related Web development tools; (4) design, develop and implement interactive Web applications; (5) identify different components of XML and its related standards and technologies; (6) understand latest and future Web technology, including wireless and intelligent Internet computing. Attributes for all-roundedness (1) communicate effectively in project / system presentation and technical documents / reports; (2) learn independently for problem solving and solution seeking; (3) collaborate with other team members for project design and development, while exhibiting leadership in a project team whenever designated or necessary; (4) think and reason in a critical and creative mind, especially in applying different computing technologies to interactive Web applications.

Syllabus: Topic 1. Introduction to distributed client/server Internet computing Client/server evolution and its relation to Internet computing Internet vs Intranet computing; overview of Internet services including file servers, database servers, transaction servers, web servers; concepts of two-tier versus

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Duration of Lectures 6

Page 104

three-tier architectures; network infrastructure and support for internet computing; building blocks of network infrastructure including bridges, routers and gateways. 2. Web-based client/server computing Revolution of Web as the intergalactic client/server Internet computing platform; web model. Web protocols and hypertext technology; HTTP data representation and response; interactive Web-based client/server; Web programming with Servlets; Servlet JDBC; Servlet Session Tracking technology. 3. Extensible Markup Language (XML) XML introduction: XML Schema, DTD concepts, design and modelling; XML conjunction standards: DOM and SAX, XLink and XPointer, XSL and XSLT; XML data management: Querying XML data, XML data storage, XML relational mapping; related applications using XML technology. 4. Latest and future Internet computing Introduction to wireless Internet; wireless Internet applications; intelligent Internet computing using agent technology. Total Laboratory Experiment: Topic 1. 2. 3. 4. Javascripts workshop. Java Servlet workshop. XML and WAP workshop. Internet Computing (IC) project workshop.

14

4

4

28

Duration of Laboratory 2 6 4 2 Total 14

Case Study: Nil

Method of Assessment: Continuous Assessment 55% Lab Assignments, Quiz, Term Paper, Group Project Examination 45%

Reference Books: 1. Orfali, R., Harkey, D. and Edwards. J., The Essential Client/Server Survival Guide, Third Edition, Wiley, 1999. 2. Chan, H.C.B., Lee, R.S.T., Dillon, T.S. and Chang, E., E-Commerce: Fundamentals and Applications, John Wiley and Sons, 2001. 3. Bradley, N., The XML Companion, Third Edition, Addison-Wesley, 2002. 4. Hall, M. and Cornell, G., Core Web Programming, Prentice Hall, 1998. 5. Deitel, H.M. and Deitel, P.J., XML: How to Program, Prentice Hall, 2000.

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6. Moss, K., Java Servlets, McGraw Hill, 1999. 7. Mann, S., Programming Applications with the Wireless Application Protocol: The Complete Developer's Guide, Wiley, 2000. 8. Lee, Raymond S. T., Fuzzy-Neuro Approach to Agent Applications (From the AI Perspective to Modern Ontology), Springer-Verlag, Heidelberg.

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SUBJECT DESCRIPTION FORM

Subject Title: Introduction to E-Business Number of Credits: 3

Subject Code:

COMP 321 28 hours 8 hours 6 hours

Hours Assigned: Lecture Laboratory Tutorial

Pre-requisite: COMP 201

Co-requisite: COMP 311, COMP 312 Exclusion: Nil

Objectives: · · · To introduce the fundamental concepts of the use and application of telecommunications, systems and technology in the e-business environment. To introduce the changes in organisational opportunities and expectations created through the use of e-Business processes enabled by integrating information systems, telecommunications and internet-based technologies. To provide training on developing the e-business applications and web sites using the market software packages, web authoring and development tools.

Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) understand what an e-Business system is, what the components are, and how e-Business systems interact with and support all aspects of organisational activities; (2) apply the functions of the various types of hardware, software, telecommunications, security and their uses to enable and support integrated, e-Business processes in any organisation; (3) understand the strategies and approaches for the e-business processes engineering; (4) understand the basic methods and procedures involved in planning and controlling the development and modification of an e-Business system in an organisation; (5) implement the e-business applications. Attributes for all-roundedness (1) improve their critical thinking skills and analytical skills in terms of how information systems interface with the organisation, how an organisation can gain a sustainable competitive advantage through the applications of e-Business systems, and the challenges and barriers of e-business application development through case studies and group discussion; (2) enhance their problem solving skill, team working skills, technical report writing and presentation skill through e-business application development group project.

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Syllabus: Topic 1. Overview of e-business E-commerce vs e-business; internet, intranet and extranet; e-business models; the core business area in organizations; foundation of information systems in business; the intranetworked and internetworked E-business enterprise; industrial applications of e-business system. 2. Software solution for e-business Languages for the web; searching mechanisms; software agents; multimedia and webcasting on the web; decision making; packaged solutions for ebusiness; data integration with XML. 3. The social infrastructure for e-business E-business planning; e-business strategy; e-business management; e-business development; e-business evaluation. 4. The technical infrastructure for e-business Access devices and channels; electronic delivery of goods and services; the web; front-end and backend computing infrastructure; communication protocols; network and data security; authentication; encryption; digital payments, and digital money. 5. E-business system design and development E-business system design; web pages design; web database design; client-side and server-side programming; systems integration. 6. E-business environments The economic environment; the social environment; the political environment; the ethical environment for e-business. Total Laboratory Experiment: Topic 1. Overview of market e-business software packages. 2. E-business systems programming. 3. Data integration programming. Duration of Laboratory 2 3 3 Total 8 Duration of Lectures 4

4

4

4

10

2

28

Case Study: Duration of Tutorial 1. Case study of e-business processing engineering. 2 2. Case study of e-business application development. 2 3. Case study of global e-business and total integrated e-business solution. 2 Total 6 Topic

Method of Assessment: Continuous Assessment Examination 60% 40%

Page 108

BSc (Hons) Scheme in Computing (FT/SAND) ­ Definitive Programme Document / Programme Booklet 2006/07

Textbook: 1. James A., O'Brien, "Introduction to Information Systems: Essentials for the Internetworked E-Business Enterprise", 11st Ed., McGraw-Hill, 2002. Reference Books: 1. Paul Beynon-Davies, "e-Business", 1st Ed., Palgrave Macmillan, 2004. 2. Abhijit Chaudhury, Jean-Pierre Kuilboer, "E-business and e-commerce infrastructure: technologies supporting the e-business initiative", 1st Ed., McGraw-Hill, 2002. 3. O'Brien, James A, "Management Information Systems: Managing Information Technology in the E-Business Enterprise", 6th Ed., McGraw-Hill, 2003. 4. Ravi Kalakota, Ravi Kalakota, Marcia Robinson, Don Tapscott, "E-Business 2.0: Roadmap for Success", 2 nd Ed., Addison-Wesley, 2001. 5. Jorge Gasós, Klaus-Dieter Thoben, "E-business applications: technologies for tomorrow's solutions", 1st Ed., Springer, 2003. 6. William J. Buffam, "E-Business and IS Solutions: An Architectural Approach to Business Problems and Opportunities", 1st Ed., Addison-Wesley, 2000.

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SUBJECT DESCRIPTION FORM

Subject Title: Enterprise Information Systems Project Implementation Subject Code: COMP 322 Number of Credits: 3 Hours Assigned: Lecture Laboratory Tutorial 28 hours 4 hours 10 hours

Pre-requisite: COMP 311, COMP 312, COMP 321 Co-requisite: Nil

Exclusion: COMP 324

Objectives: · · · · To provide orientation and understanding of the information systems requirements and opportunities for the enterprise. To provide the information picture both strategically and operationally to evaluate and procure enterprise information systems. To teach the methodologies of analyzing enterprise business, workflow, information architecture and information systems. To teach the techniques and approaches of enterprise information system planning, design, implementation and management.

Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) possess an overview picture of enterprise information system environment; (2) make clear connection and alignment in the Enterprise Information System requirements and implementation to the enterprise mission, vision, values, strategies and initiatives; (3) design, organize and conduct a business and functional requirement analysis for the enterprise information systems; (4) implement the project plan and structure it that accommodates and facilitates change management best practices and organization transformation; (5) prepare, analyze and evaluate system requirement and specification, request for proposal, vendor selection, software packages selection, and implementation processes of enterprise information systems; (6) understand the management issues in enterprise information systems development. Attributes for all-roundedness (1) improve their critical thinking skills and analytical skills through case studies and group discussion of enterprise information systems development; (2) enhance their problem solving skill, team working skills, technical report writing and presentation skill through enterprise information system implementation project.

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Syllabus: Topic 1. Overview of Enterprise Information System environment Introduction to enterprise information systems and information portal; the function of a chief information officer; common enterprise resource planning modules; systems architecture of enterprise information systems; enterprise information systems integration; enterprise strategy. 2. Enterprise Information System analysis Needs analysis; value system and value chain modeling; business process modeling and mapping; task level modeling; information architecture; current enterprise information system analysis; transition strategies. 3. Enterprise Information System planning Project planning; information system architecture and implementation planning; change management and transformation planning; outsourcing. 4. Enterprise Information System design and implementation System requirement and specification; vendor selection; approaches of software package selection; request for proposal; making choices and selections; negotiating agreements; justification and evaluation; enterprise information system implementation processes. 5. Enterprise Information System project management Project monitoring and control; system testing; enterprise system risks and controls; people and technology management; success and failure factors. Total Laboratory Experiment: Topic 1. Demonstration of Enterprise Information Systems. Duration of Laboratory 4 Total 4 Duration of Lectures 6

10

3

6

3

28

Case Study: Duration of Tutorial Case study of enterprise engineering. 2 Case study of enterprise information system design and implementation. 2 Case study of integrated enterprise information systems. 2 Case study of outsourcing enterprise information system. 2 Case study of enterprise information software failure. 2 Total 10 Topic

1. 2. 3. 4. 5.

Method of Assessment: Continuous Assessment Examination 70% 30%

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Textbook: 1. Dunn, Cheryl L., "Enterprise information systems: a pattern-based approach", 3rd Ed., McGraw-Hill, 2005. Reference Books: 1. "Enterprise information systems", Kluwer Academic, 2000 ­ 2005. 2. Kerzner, Harold, "Project management: a systems approach to planning, scheduling, and controlling", 8th Ed., Wiley, 2003. 3. Meredith, Jack R., "Project management: a managerial approach", John Wiley, 2003. 4. Shields, Murrell G., "E-business and ERP: rapid implementation and project planning", John Wiley & Sons, 2001. 5. Buffam, William J., "E-business and IS solutions: an architectural approach to business problems and opportunities, Addison-Wesley, 2000. 6. Chaffey, Dave, "E-business and e-commerce management: strategy, implementation, and practice", 2nd Ed., Prentice Hall, 2004.

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SUBJECT DESCRIPTION FORM

Subject Title: Foundations of Chinese Computing Number of Credits: 3

Subject Code:

COMP 323 28 hours 14 hours

Hours Assigned: Lecture Laboratory

Pre-requisite: COMP 201

Co-requisite: Nil

Exclusion: COMP 423

Objectives: · · To provide the students with a basic understanding of the foundation in system coding and design for text processing with a specific emphasis on the Chinese language and its coprocessing with other languages such as English. To provide training in software design methodology for the recognition of human/machine interface.

Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) understand the technical difficulties in representing and processing text written or encoded in Chinese; (2) understand the (operating) system support for displaying and entering Chinese in computers; (3) understand some Chinese information processing applications (e.g. Chinese information retrieval, Chinese abstraction and Machine Translation) that demonstrates the integrated use of various techniques; (4) handle Chinese text data encoded in various standards or format (e.g. GB and Big5); (5) handle the software development of Chinese enabled software applications in the context of developing internationalized software and in adhering to international software development practices; (6) handle some basic algorithmic problems and some basic computational Chinese linguistic techniques to enable efficient and intelligent Chinese enabled software applications. Attributes for all-roundedness (1) solve problems using systematic approaches; (2) learn independently and be able to search for the information required in solving problems.

Syllabus: Topic 1. Characteristics of Chinese language Historical development; geographical variations (dialects); linguistic descriptions (character, morph, word, phrase and sentence) and quantitative analysis (Zip Law, coverage curve). 2. Representation of Chinese character sets

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Duration of Lectures 3

6

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3.

4.

5.

6.

Mathematical description of representation; character set organization (e.g., GB and Big5); encoding schemes (ISO2022 and UTF); discussion of (de facto) standard character sets (for PC, workstation and network); character decoding techniques and character conversion problems; unbounded alphabet representation and processing. Output processing of Chinese Font technology; typesetting terminology and text rendering process; bitmap fonts (representation, compression and scaling problems); vector / outline fonts (Limn algorithm); X-Windows fonts (BDF and Postscript) and font related operations (installation, specification, extraction and user-defined glyph addition); automatic glyph construction. Input processing of Chinese Introduction to Chinese input processing by pen, image, speech and keystrokes; design and evaluation issues for different keystroke input methods: shape-based (e.g. Q9), phonetic-based and shape-phonetic based input methods; input method architecture (e.g. for Microsoft Windows and XWindows). Software development for Chinese computing Open systems, internationalization, localization, ANSI-C model, Windows programming for Chinese computing (Microsoft- and X-Windows). Selected topics in Chinese computing Character set selection (NP-complete); hashing functions for Chinese character sets; string searching (KMP, BM and Quick); dictionary lookup; string-set searching; word segmentation; Chinese information retrieval; abstraction or machine translation. Total

4

4

6

5

28

Laboratory Experiment: Topic 1. 2. 3. 4. 5. 6. Locale Setting for operating systems and Locale detection checking of character encoding using binary reading tool Foundations of Multilingual Website design and web page language setting Installation of Input Method Engine (IME) to operating system System font set detection Character string data handling and processing in programming environment, codeset announcement and conversion 7. Programming using Internationalization methodology Total Duration of Laboratory 14

14

Case Study: Nil

Method of Assessment: Continuous Assessment Examination 55% 45%

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Textbook: 1. Lunde, K., Chinese, Japanese, Korean and Vietnamese Computing, O'Reilly & Associates, 1999. Reference Books: 1. Hopcroft, J.E. and Ullman, J.D., Introduction to Automata, Theory and Languages, Addison-Wesley, 1979. 2. McGilton, H. and Campione, M., Postscript by Example, Addison-Wesley, 1993. 3. Jain, K.A., Fundamentals of Digital Image Processing, PHI, 1989. 4. Berry, K. and Hargraves, K.A., GNU Font utilities (Limn algorithm), 5. Kano, N. Developing International Software, Microsoft Press, 1995. 6. Nutt, G.J., Open Systems, Prentice Hall, 1992. 7. Huang, J.K.T. and Huang, T.D., An Introduction to Chinese, Japanese and Korean Computing, Singapore: World Scientific, 1989. 8. ,,,, 1993. 9. The Unicode Consortium, The Unicode Standard, Version 2.0, Addison-Wesley Developer Press, 1991-96. 10. 1992. 11. ACM Transactions on Asian Language Information Processing. 12. Journal and Conference Proceedings of Computer Processing of Oriental Languages. 13. Communications of COLIPS. 14. Journal of Chinese Information Processing.

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SUBJECT DESCRIPTION FORM

Subject Title: Project Methodology and Implementation Number of Credits: 3

Subject Code: COMP 324 28 hours 6 hours 8 hours

Hours Assigned: Lecture Laboratory Tutorial

Pre-requisite: COMP 302

Co-requisite: Nil

Exclusion: COMP 322

Objectives: · · · To deliver project management theory, principle and stages. To deliver the methods, procedures, and systems for defining, planning, scheduling, controlling, and organizing project activities. To deliver the organizational, managerial, and human behavioral issues relevant to project management.

Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) understand the concepts and techniques of project planning, scheduling, monitoring, and controlling and time/cost analysis; (2) use the project management tools to plan, schedule and monitor the project; (3) write a requirement analysis report, feasibility study report and project proposal report; testing report and documentation; (4) understand the process management and people management issues of project management; (5) gain knowledge and some practical experience in planning, organizing, and managing project; (6) apply the project management knowledge to industrial project. Attributes for all-roundedness (1) improve critical thinking skills and analytical skills through case studies and group discussion of project management; (2) enhance the problem solving skill, team working skills, technical report writing and presentation skill through project implementation project.

Syllabus: Topic 1. Introduction to project management Principle of project management; project management phrases; project management process; project methodologies; role of project manager and project team; impact of limited resources.

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2. Organizing a project Project planning; human resource planning; project scheduling and monitoring; project cost reporting; feasibility studies; negotiations and contracts; measurement of project management performance; project quality. 3. Project implementation Requirement-specification; data modeling; process modeling; network modeling; system analysis and design; system implementation and testing; documentation. 4. Successful factors of project management Project planning, control and monitoring; change management; people management; risk management; risk and contingency plan; risk mitigation strategies; leadership and managerial Skills. Total Laboratory Experiment:

14

6

4

28

Duration of Laboratory 1. Critical path Method; Program Evaluation and Review Technique; Gantt 3 chart. 3 2. Demonstration of project management tools (MS Office Project). Topic Total Case Study: Topic 1. 2. 3. 4. Case study of management an industrial project. Case study of handling changes and risk in a project. Case study of leadership skill in project management. Case study of project management and implementation failure. Total Duration of Tutorial 2 2 2 2 8 6

Method of Assessment: Continuous Assessment Examination 70% 30%

Textbook: 1. Jack R. Meredith and Samuel J. Mantel, "Project Management: A Managerial Approach", 5th Ed., Wiley, 2003. Reference Books: 1. Milton Rosenau, Jr., "Successful Project Management - A Step by Step Approach with

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Practical Examples", 3rd Ed., John Wiley & Sons, 1998. 2. Kerzner, Harold, "Project management: a systems approach to planning, scheduling, and controlling", 8th Ed., Wiley, 2003. 3. Clifford F Gray and Eric W Larson, "Project Management: The Managerial Process", 2nd Ed., McGraw-Hill, 2003. 4. Earl Hall & Juliane Johnson, "Integrated Project Management", Prentice-Hall, 2003.

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SUBJECT DESCRIPTION FORM

Subject Title: Information Systems Management Number of Credits: 3

Subject Code: COMP 325 21 hours 21 hours

Hours Assigned: Lecture Seminar

Pre-requisite: COMP 302

Co-requisite: Nil

Exclusion: COMP 405

Objectives: · · To present an integrated view of the planning, management, and control of information systems in the organization. To allow students the opportunity to develop critical evaluation in the selection and appraisal of relevant approaches, methods and techniques in solving real-life business problems related to the use of information systems.

Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (3) understand the strategic role played by the information systems department in modern enterprises; (4) understand the various activities related to the management of information systems; (5) appreciate and evaluate existing and emergent information technologies on their applicability to modern enterprises; (6) integrate the technical computer-related knowledge learned in other subjects, and to apply the knowledge to solve real-life business problems; Attributes for all-roundedness (1) improve presentation and communication skills (through case study presentations); (2) develop the ability to learn independently and to find/integrate information from different sources required in solving real-life problems.

Syllabus: Topic 1. Information systems management's leadership role Escalating benefits of using IT; changing roles of the information systems department and staff. 2. Information systems planning Strategic impact of IT; competitive forces model; value chain analysis. 3. Benefits and costs of information systems Resource allocation; client-server computing; agents. 4. Organizations and information systems

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Duration of Lectures 2

3

2 3

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Two-way relationship between organization and IS; technical and behavioral definitions of organization; how organization affects IS; organizational resistance to change caused by IS; how IS affects organization. 5. Managing information systems implementation Concept of implementation; importance of relationship between IS staff and users; causes of implementation success and failure: user involvement, management support, level of risk, quality of management; project management techniques; overcoming user resistance. 6. Managing operations Outsourcing; pros and cons of outsourcing. 7. Redesigning the organization with information systems Linking business plan to IS plan; types of organizational change: automation, rationalization of procedures, business re-engineering, paradigm shift; steps in business process redesign. 8. Information systems control Aims of IS control; control architecture (e.g. cost center approach, profit center approach); control process; IT auditing. Total Laboratory Experiment: Nil Case Study: Presentations will be held during the seminars, where the students will form groups to read and present real-life cases related to the subject's topics. 3

2

3

3

21

Method of Assessment: Continuous Assessment Case Study Project Examination 55% 35% 20% 45%

Reference Books: 1. L.M. Applegate, F.W. McFarlan and J.L. McKenney, Corporate Information Systems Management: Text and Cases, 5th Edition, McGraw Hill, 1997. 2. K.C. Laudon and J.P. Laudon, Management Information Systems - Organisation and Technology in the Networked Enterprise, 6th Edition, Prentice Hall, 2000. 3. B.C. McNurlin and R.H. Sprague, JR., Information Systems Management in Practice, 6th ed., Prentice Hall, 2004. 4. M. Porter, Competitive Advantage: Creating and Sustaining Superior Performance, Free Press, 1998.

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SUBJECT DESCRIPTION FORM

Subject Title: Business Strategies and Enterprise Re-engineering Subject Code: COMP 326 Number of Credits: 3 Hours Assigned: Lecture Tutorial/Lab 28 hours 14 hours

Pre-requisite: Nil

Co-requisite: Nil

Exclusion: Nil

Objectives: · To understand basic concepts and theories of business strategies. · To understand the necessary infrastructure and functional components for Enterprise Business Re-engineering (BPR). · To understand the strategy formulation for Enterprise BPR. · To understand the design and development of Enterprise BPR. Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) identify the basic business information strategy; (2) devise strategies for business process re-engineering; (3) align business strategies with IT strategies; (4) identify state-of-art enterprise re-engineering models; (5) relate and align business strategies for enterprise re-engineering; (6) understand the latest and future development of business information strategy and enterprise re-engineering including data mining, data warehousing, intelligent multi-agentbased EC systems. Attributes for all-roundedness (1) communicate effectively (both in Chinese and English) verbally at a level sufficient for project and system presentation, as well as general conversation; (2) communicate effectively in writing with technical documents and reports; (3) learn independently for problem solving and solution seeking; (4) collaborate with other team members for project design and development, while exhibiting leadership in a project team whenever designated or necessary; (5) think and reason in a critical and creative mind, especially in applying different computing technologies to business process re-engineering.

Syllabus: Topic 1. Introduction to enterprise business strategy The essentials of business strategy; strategy initiation; new EC business strategy; strategy formulation; case studies. 2. Business Process Re-engineering (BPR)

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10

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Introduction to BPR; BPR models; process decomposition; phased approach to BPR; process selection and scoping; design and implementation of BPR; measurement and validation; case studies. 3. Alignment of IT and e-commerce for Enterprise BPR Business-oriented e-commerce; enterprise EC; strategic alliance; BPR outsourcing; case studies in enterprise BPR in e-commerce. 4. Enterprise BPR system development tools CASE tools: SAP AG, workflow analyzer, process charter, crossflow; comparison of enterprise BPR development tools; case studies. 5. Latest and future development of Enterprise BPR Data warehousing; web mining for knowledge management; workflow systems; intelligent multi-agent technology; intelligent multi-agent-based systems for Enterprise BPR. Total Laboratory Experiment: Nil Case Study: Case studies on enterprise business strategies, BPR, enterprise BPR, development tools etc. 8

6

8

42

Method of Assessment: Continuous Assessment Case Studies Quiz Written Assignment Examination Reference Books: 1. Jeo, P., Essence of Business Process Re-Engineering, Prentice Hall, 1995. 2. East, Stuart, System Integration: A Management Guide for Manufacturing Engineers, McGraw-Hill, 1994. 3. Lozinsky, Enterprise-wide Software Solutions: Integration Strategies and Practices, Addison Wesley, 1998. 4. Harrison, J and John, C. H., Foundations in Strategic Management, South-Western College, 1998. 5. Hill, C. W. L. and Jones, G. R., Strategic Management: An Integrated Approach, Houghton & Mifflin, 1998. 6. King, D., Lee, J., Warkentin, M., Chung, H.M., Electronic Commerce: A Managerial Perspective, Prentice Hall, 2002. 7. Chan, H. C. B., Lee, R. S. T., Dillion, T. S. and Chang, E., E-Commerce: Fundamentals and Applications, John Wiley and Sons Ltd, 2001. 8. Lee, R. S. T., Fuzzy-Neuro Approach to Agent Applications (From the AI Perspective to Modern Ontology), Springer-Verlag, Heidelberg, 2005. SUBJECT DESCRIPTION FORM

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60% 24% 18% 18% 40%

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Subject Title: Digital Transmission and Switching Subject Code: Systems Number of Credits: 3

EIE339 (for 61031)

Hours Assigned: Lecture/Tutorial 33 hours Laboratory 18 hours

Pre-requisite: Analog and Digital Communications (EIE218) Co-requisite: nil Exclusion: nil

Objectives: To provide students with a wide-spread understanding of current digital transmission and switching technologies and enable them to design and manage modern telecommunication systems. Student Learning Outcomes: On successful completion of this subject, the students will be able to: Category A: Professional/academic knowledge and skills 1. Understand the basic principles for designing digital communication systems. 2. Understand the different multiplexing schemes. 3. Understand the basic principles for designing a simple switching system. Category B: Attributes for all-roundedness 4. Think critically. 5. Learn independently. 6. Present ideas and findings effectively.

Syllabus: 1. Transmission Media 2. Baseband Data Transmission 2.1 Analysis of distortion mechanisms and eye diagram, inter-symbol interference (ISI) and pulse shaping. 2.2 Baseband binary PAM system, M-ary signaling schemes, equalization. 3. Digital Carrier Modulation System 3.1 ASK, FSK, PSK and QAM modulation. 3.2 Error probability performance for various digital modulation schemes. 4. Digital Multiplexing 4.1 Frequency-division multiplexing (FDM) and time-division multiplexing (TDM). 4.2 Asynchronous digital multiplexing hierarchy. 4.3 Synchronous digital multiplexing, SDH and SONET. 5. Switching Principles and Systems 5.1 Traffic engineering. 5.2 Circuit switching, packet switching.

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Laboratory Experiment: Practical Works 1. Simulation of a baseband PAM binary data transmission system. 2. Equalizer design in a baseband PAM binary transmission system. 3. Frequency Shift Keying (FSK). 4. Differential Phase Shift Keying (DPSK). 5. Differential Quadrature Phase Shift Keying (DQPSK). 6. Phase Shift Keying (PSK) & Quadrature Phase Shift Keying (QPSK).

Method of Assessment: Coursework: 40% Examination: 60%

Textbooks: 1. S.S. Haykin, Communication Systems, Wiley, 2001. 2. W. Stallings, Data and Computer Communications, 6th ed., Prentice-Hall, 2000. Reference Books: 1. J.G. Proakis and M. Salehi, Communication Systems Engineering, 2nd ed., Prentice-Hall, 2002. 2. J.E. Flood, Telecommunications Switching, Traffic and Networks, Prentice-Hall, 1994. 3. E.B. Carne, Telecommunications Primers: Data Voice and Video Communications, 2nd ed., Prentice-Hall, 1999. Alignment of Teaching and Learning (T&L) Methods with Learning Outcomes: T&L Method Lectures Tutorials Outcome numbers 1, 2, 3 1, 2, 3 Remarks Fundamental principles and key concepts of the subject are delivered to students. Supplementary to lectures and are conducted with smaller class size; Students will be able to clarify concepts and to have a deeper understanding of the lecture material; Problems and application examples are given and discussed. Students will go through the components of digital communication systems and evaluate their performance.

Laboratory sessions

4,5,6

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Alignment of Assessment and Learning Outcomes: Assessment Method Assignments, tests and examination Learning Outcome 1,2,3 Remarks End-of chapter type problems used to evaluate students' ability in applying concepts and skills learnt in the classroom. Students need to think critically and creatively in order to come with an alternate solution for an existing problem. Each group of students is required to produce written reports. For some of the practical works, students are required to make demonstration to illustrate their understanding of the related technical knowledge and skills.

Laboratory sessions

4,5,6

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SUBJECT DESCRIPTION FORM

Subject Title: English for Engineering Students Number of Credits: 2

Subject Code:

ELC3501

Hours Assigned: Seminar 2 hours/ bi-weekly for 14 sessions 28 hours

Pre-requisite: nil

Co-requisite: nil

Exclusion: nil

Objectives: To develop those English language skills required of engineering students to communicate effectively in their future professional careers. Attention will be given to helping students develop the core competences identified by the University as vital to the development of effective life-long learning strategies and skills. Student Learning Outcomes: By the end of the subject, students should be able to use appropriate language and text structure to: Category A: Professional/academic knowledge and skills 1.Write reports related to technical studies. 2.Write workplace correspondence related to engineering professions. 3.Present information and ideas professionally. Category B: Attributes for all-roundedness 4.Communicate effectively in speech and in writing. 5.Work individually on their own initiative, and as team members. 6.Engage in lifelong learning for career development and personal growth. Syllabus: 1. Written Communication Identifying and writing functions common in technical subject discourse; understanding and applying principles of technical text structure; developing paraphrasing, summarising and referencing skills; improving editing and proofreading skills; achieving appropriate tone and style in technical and report writing; selecting and using relevant content, appropriate style, acceptable format, structure and layout in letters, memoranda and reports. 2. Spoken Communication Recognising the purposes of and differences between spoken and written communication in English in professional contexts; identifying and practising interactional and linguistic skills for oral presentations; preparing and delivering presentations. 3. Language Appropriacy

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Introducing notions of context-sensitive language use in both spoken and written English. 4. Language Development Improving and extending relevant features of students' grammar, vocabulary and pronunciation. Teaching and Learning Approach and Teaching Schedule: The subject is designed to introduce students to the communication skills, both oral and written, that they may be expected to need to function effectively in their future professions. These skills will be necessary for successful employment in any organisation where internal and/or external communication is conducted in English. The study method is primarily based on seminars which will include discussions, roleplay, individual and group activities. In addition to learningmaterials specially prepared by English Language Centre staff, use will be made of information technology and the ELC's Centre for Independent Language Learning.Teachers will also recommend additional reference materials as required.A considerable amount of individual self-access learning is expected of students. Method of Assessment: Continuous Assessment: 100% Reference Books: Written Communication 1. Bilbow, G.T, Business Writing for Hong Kong, Hong Kong: Longman, 2000. 2. Guffey, M.E., Essentials of Business Communication, 6th ed., Ohio:SouthWesternCollege Pub, 2004. 3. Houp, K.W. (et al.), Reporting Technical Information, New York: OxfordUniversity Press, 2002. 4. White, F.D., Communicating Technology: Dynamic Processes and Models for Writers, New York: HarperCollinsCollege Publishers, 1996. Spoken Communication 1. Conradi, M. and Hall, R., That Presentation Sensation, London: Pearson Education Ltd, 2001. 2. Sampson, E., Creative Business Presentation: Inventive Ideas for Making an Instant Impact, London: Kogan Page, 2003. 3. Walther, G. R., Power Talking Skills: How to Say What You Mean and Get What you Want, A video seminar. Newcastle, WA: Speaking From Experience, Inc, 1996. 4. Longman Dictionary of Contemporary English, Harlow: Longman, 2003. 5. © The English Language Centre 2000 2006

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SUBJECT DESCRIPTION FORM

Subject Title: Industrial Placement Number of Credits: 24 Training Credits

Subject Code:

COMP 4000

Hours Assigned: 48 weeks industrial training

Pre-requisite: Nil

Co-requisite: Nil

Exclusion: Nil

Objectives: · · · To provide the opportunity for students, companies and the University to interact; this interaction brings about a unique learning environment not available on campus. To let students gain experience by practicing techniques acquired in the classroom, such as system analysis, design, implementation, testing and/or maintenance. To let students learn how to interact effectively, efficiently and professionally with others.

Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) relate academic principles to social and technical environments; (2) gain knowledge, confidence, and maturity, which help complete the final year more successfully; (3) gain better understanding of computing practices so that better choices of electives and final year projects can be decided; Attributes for all-roundedness (1) build up a good degree of understanding of business practice which is usually not available in the campus; (2) apply those principles learnt in the classroom to real-life problems; (3) improve interpersonal and communication skills.

Placement Procedure: The detailed placement procedures are contained in a separate document prepared by the Department, and its essence includes: (1) (2) (3) solicitation of suitable placement places by the Department; helping students to arrange job interviews; helping students to confirm placement offers with contracts.

Prior to the industrial placement students are counselled, and a set of relevant documents on placement procedures will be provided. Normally, students should complete certain requirements on the skill sets (please refer to the Definitive Programme Document) before they can opt for placement. During placement the Department assigns an academic staff as the WIE (Work-Integrated

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Education) supervisor for each student. The WIE supervisor is encouraged to visit the students within the first two months of the placement period. The purpose is to help the placed student whenever possible, and to liaise with the company to settle with any early problem detected. The learning outcomes by the student should be specified in an agreement form, which upon endorsement by the Department, will be used as an evaluation yardstick against the student during the placement. Students must submit a written report detailing his/her achievement during the placement period, with a reflection on the learning outcomes attained.

Method of Assessment: Assessment of student placements are based on the following: (1) continuous assessment by the tutor through site visits, and by the company; (2) final placement report submitted by the student when placement has ended. The final assessment of a placement report is either pass or fail, with respect to the two items above. It carries 24 training credits, and the credits do not count towards the academic credits for graduation, nor do they contribute to the GPA calculation. Under normal situations, a failing grade may be awarded when the student does not complete the required placement duration, or performs poorly during placement, in not achieving the agreed learning outcomes.

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SUBJECT DESCRIPTION FORM

Subject Title: Artificial Intelligence Number of Credits: 3

Subject Code:

COMP 406 28 hours 14 hours

Hours Assigned: Lecture Tutorial/lab

Pre-requisite: COMP 305

Co-requisite: Nil

Exclusion: Nil

Objectives: · · · · · To introduce the fundamental concepts of artificial intelligence; To equip students with the knowledge and skills in logic programming using Prolog; To explore the different paradigms in knowledge representation and reasoning; To understand the contemporary techniques in machine learning; To evaluate the effectiveness of hybridization of different artificial intelligence techniques.

Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) understand the history, development and various applications of artificial intelligence; (2) familiarize with propositional and predicate logic and their roles in logic programming; (3) understand the programming language Prolog and write programs in declarative programming style; (4) learn the knowledge representation and reasoning techniques in rule-based systems, casebased systems, and model-based systems; (5) appreciate how uncertainty is being tackled in the knowledge representation and reasoning process, in particular, techniques based on probability theory and possibility theory (fuzzy logic); (6) master the skills and techniques in machine learning, such as decision tree induction, artificial neural networks, and genetic algorithm; (7) apply and integrate various artificial intelligence techniques in intelligent system development; (8) understand the importance of maintaining intelligent systems. Attributes for all-roundedness (1) explore the nature of human intelligence and its role in problem solving; (2) deepen thoughts and understanding of human abilities such as learning, reasoning and planning; (3) appreciate the rooted philosophical arguments in logic and its impact on human thoughts.

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Syllabus: Topic 1. Artificial Intelligence (AI): its roots and scope Early history and applications; the development of formal logic; the Turing test; overview of AI application areas: game playing, automated theorem proving, expert systems, natural language understanding and semantics, planning and robotics, and machine learning. 2. Artificial intelligence as representation and search The Propositional Calculus and Predicate Calculus; using inference rules to produce predicate calculus expressions; strategies and structures for state space search; heuristic search; recursion-based search; admissibility, monotonicity and informedness of search algorithms. 3. Knowledge representation and reasoning Rule-based production systems; case-based reasoning systems and model based reasoning systems; reasoning under uncertain situations: stochastic methods, fuzzy logic and fuzzy set theory; fuzzy expert systems. 4. Machine learning Decision tree induction algorithms; artificial neural networks; genetic algorithms. 5. Hybrid intelligent techniques and maintenance of intelligent systems Hybridization of neural networks, fuzzy logic, genetic algorithms and other intelligent techniques for problem solving; maintenance of the completeness, correctness and consistency of intelligent systems. Total Laboratory Experiment: Topic 1. 2. 3. 4. Prolog programming language exercises and practices. Artificial neural network exercises using Matlab or other similar software. Building a decision tree induction program. Developing a program to run the genetic algorithm. Total Case Study: Nil 14 Duration of Laboratory Duration of Lectures 3

9

6

6

4

28

Method of Assessment: Continuous Assessment Examination 55% 45%

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Textbooks: 1. George F. Luger, Artificial Intelligence: Structures and Strategies for Complex Problem Solving, 5th Edition, Addison Wesley, 2005.

Reference Books: 1. Sankar K. Pal and Simon C. K. Shiu, Foundations of Soft Case-Based Reasoning, John Wiley, 2004. 2. Michael Negnevitsky, Artificial Intelligence: A Guide to Intelligent Systems. 2nd edition, Addison Wesley, 2005.

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SUBJECT DESCRIPTION FORM

Subject Title: Computer Graphics Number of Credits: 3

Subject Code:

COMP 407 28 hours 14 hours

Hours Assigned: Lecture Laboratory

Pre-requisite: COMP 305

Co-requisite: Nil

Exclusion: Nil

Objectives: This subject allows students to: · learn basic and fundamental computer graphics techniques; · learn image synthesis techniques; · examine applications of modelling, design and visualization. Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) gain proficiency in 3D computer graphics API programming; (2) understand the interactive computer graphics architecture; (3) possess in-depth knowledge of display systems, image synthesis, shape modeling, and interactive control of 3D computer graphics applications; (4) enhance their perspective of modern computer system with modeling, analysis and interpretation of 2D and 3D visual information. Attributes for all-roundedness (1) understand, appreciate and follow the development and advancement of computer graphics technologies, including advanced technologies for 3D modelling, high performance rendering.

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Syllabus: Topic 1. Basic computer graphics hardware/software interfaces Graphical input/output devices; 2D primitive drawing; rasterization; 2D transformation; 3D transformation and projection; synthetic camera and viewing volume; clipping; object modeling and hierarchical structures. 2. Image synthesis and generation techniques Some of the important image generation techniques including hardware-based rendering, scan-conversion, local illumination models, reflections and shading; related issues such as anti-aliasing and texture mapping. 3. Applications of computer graphics Introduction to OpenGL and device independent Application Programming Interfaces (API); virtual reality; hardware supported 3D modeling and rendering. Total Laboratory Experiment: Laboratory exercises will normally be conducted using the currently available computer graphics API such as OpenGL. The students will be exposed to basic frame-buffer control, pixel processes, rasterization, 2D drawings, 3D transformations, projections, scene hierarchy, modeling objects, color and interactive animation. Case Study: If applicable, case studies may be conducted on modeling and design systems that are used in commercial applications. Total Duration 16

12

14

42

Method of Assessment: Continuous Assessment Examination 60% 40%

Textbooks: 1. Hill, F.S. Jr., Computer Graphics Using Open GL, Second Edition, Prentice Hall, 2001. Reference Books: 1. Angel, E.S., Interactive Computer Graphics, A top-down approach with OpenGL, Second Edition, Addison-Wesley, 2000. 2. Angel, E.S., OpenGL: A Primer, Addison-Wesley, 2000. 3. Watt, A., 3D Computer Graphics, Third Edition, Addison-Wesley, 2000. 4. Hearn, D. and Baker, M., Computer Graphics, Second Edition, Prentice-Hall, 1994.

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SUBJECT DESCRIPTION FORM

Subject Title: Parallel and Distributed Computing Number of Credits: 3

Subject Code: COMP 408 28 hours 14 hours

Hours Assigned: Lecture Tutorial/lab

Pre-requisite: COMP 304, COMP 312

Co-requisite: Nil

Exclusion: Nil

Objectives: · · To provide students with contemporary knowledge in parallel and distributed computing; To equip students with skills to design and analyze parallel and distributed applications.

Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) understand the evolution of high performance computing (HPC) with respect to laws and the contemporary notion that involves mobility for data, hardware devices and software agents; (2) understand, appreciate and apply parallel and distributed algorithms in problem solving; (3) evaluate the impact of network topology on parallel/distributed algorithm formulations and traffic their performance; (4) gain hand-on experience with the agent-based and Internet-based parallel and distributed programming techniques; (5) master skills to measure the performance of parallel and distributed programs; (6) learn advanced techniques such as Internet caching and its application in practical systems; Attributes for all-roundedness (1) evaluate whether a parallel and distributed application is efficient or not by using the right tools, especially those time-critical ones; (2) apply the different techniques, including internet-based ones, efficaciously in e-business perspectives.

Syllabus: Topic 1. Overview High performance computing (HPC) paradigms evolution with respect to different laws and learning curves; importance of Moore's Law; supercomputing and the grid; network of workstations; applications of parallel and distributed computing. 2. Parallel computing Different HPC system architectures and models: tightly coupled versus loosely coupled architectures, SIMD versus MIMD architectures; shared

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Duration of Lectures 4

8

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memory MIMD; message passing; problem decomposition parallelization; synchronization techniques; parallel languages.

and

3. Distributed computing Fundamental issues and problem types; naming facility; Lamport's logical clock; message passing primitives; remote procedure call; synchronization mechanisms; resource allocation; client-server computing; agents. 4. Selected topics In-depth studies on EITHER parallel computing OR distributed computing. Parallel computing topics may include design of parallel algorithms, common parallel operators and reduction, one-to-all versus all-to-all operators, grid computing, performance monitoring. Distributed computing topics may include load balancing, distributed deadlock, fault-tolerance, dependability of distributed systems, use of caching to reduce response time, Internet-based distributed computing, Internet congestion control, Internet end-to-end performance measurement. Total Laboratory Experiment:

8

8

28

Duration of Laboratory 1. Installing mobile agent or relevant platform. 1 2. Learning the programming language for the platform. 2 3. Application of the programming language to solve problems, e.g., Internet 2 congestion control, distributed resource management. Total 14 Topic Case Study: Nil

Method of Assessment: Continuous Assessment Examination

55% 45%

Textbooks: 1. G. Coulouris, J. Dollimore and T. Kindberg, Distributed Systems: Concepts and Design, Third Edition, Addison Wesley, 2001. 2. B. Wilkinson and M. Allen, Parallel Programming ­ Techniques and Applications Using Networked Workstations and Parallel Computers, Prentice Hall, 1999. Reference Books: 1. C. Leopold, Parallel and Distributed Computing ­ A Survey of Models, Paradigms, and Approaches, John Wiley & Sons, Inc. 2001. 2. A. Zomaya, Parallel and Distributed Computing Handbook, McGraw Hill, 1996.

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3. K. Blazewics, et al., Handbook on Parallel and Distributed Processing, Springer-Verlag, 2000. 4. A.S. Tanenbaum, Distributed Operating Systems, Prentice Hal, 1995. 5. V. Kumar, A. Grama, A. Gupta and G. Karypis, Introduction to Parallel Computing, Benjamin Cummings, 1994. 6. Selected current articles from ACM and IEEE journals and conference proceedings.

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SUBJECT DESCRIPTION FORM

Subject Title: Internetworking Protocols and Software Number of Credits: 3

Subject Code:

COMP 416 30 hours 12 hours

Hours Assigned: Lecture Laboratory

Pre-requisite: COMP 312

Co-requisite: Nil

Exclusion: Nil

Objectives: · · · Acquire foundational understanding on the concept of Internetworking in terms of the technologies and techniques that drive Internet; Deepen understanding of advanced concepts of TCP/IP protocol suite and its architecture; Earn practical exposure of TCP/IP operations in the form of realistic and practical experiments.

Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) identify and explain the essential components that drive internetworking (students would be equipped with the knowledge to explain the relationships between the components and how they affect one another); (2) understand the important issues encompassing internetworking and how these issues affect the evolution of Internet and its applications; (3) understand the complete architecture of Internetworking and the operations of underlying protocols and software; (4) rapidly learn new techniques and to align new technologies to existing Internetworking infrastructure; (5) equipped with practical knowledge on configuring and monitoring network operations using Internet tools and software. (6) develop networking software that demonstrates their understanding of the concepts taught in the class. Attributes for all-roundedness (1) understand and solve internetworking problems in a systematic and principled approach; (2) develop practical software and present results in the form of technical report; (3) learn to work effectively as a team member.

Syllabus: Topic 1. TCP/IP protocol suite Hierarchical address routing; connecting LAN and WAN technologies; IP classful addressing: IP classes, special IP addresses, subnet addressing, multihome addresses; address resolution protocol and RARP.

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Duration of Lectures 3

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2. Advanced addressing and IP Supernetting; assigning address blocks; classless addressing; slash notation; IP packet format; ICMP error reporting. 3. Transport protocol Transport services and protocols; protocol mechanisms including error, flow and congestion control; transport addressing; connection control; connection termination; credit-based flow control; silly window syndrome: Nagle's algorithm; TCP timers: setting timeouts; TCP congestion control: slow-start, multiplicative decrease and additive increase; TCP packet format; TCP state transitions; User Datagram Protocol. 4. Internet routing Direct versus indirect internet routing; routing methods; routing decisions; interior gateway routing versus exterior gateway routing; routing protocols: RIP versus OSPF, BGP, autonomous systems; OSPF routing mechanisms: area border routers, Dijkstra's algorithm; link state routing. 5. SNMP Simple Network Management Protocol: Management Information Base (MIB); Structure of Management Information (SMI); SNMP protocol; setting traps. 6. Internet multicast N-to-N unicast; proxy and Internet multicast; hardware multicast; Internet Group Management Protocol (IGMP); Distance Vector Multicast Protocol (DVMP); Core Base Tree (CBT) multicast; MOSPF; Protocol Independent Multicast (PIM); reliable multicast. 7. Internet services BOOTP versus DHCP; Domain Name Services (DNS); Inverse Domain Mapping; SMTP; POP3; IMAP4; private networks and security: Virtual Private Networks (VPN); intranet versus extranet; private network addressing; IP Security (IPSec); Authentication Header mode versus Encapsulating Security Payload (ESP); Network Address Translation (NAT). 8. Mobile Internet Mobile IP; home agent; foreign agent; agent discovery protocol; triangle routing; mobile transport protocol: TCP over wireless, Indirect TCP (I-TCP), Snoop TCP; Realtime Transport Protocol (RTP). Total Laboratory Experiment: Topic 1. 2. 3. 4. Using Internet tools Ethereal for packet capturing and analysis Simple Mail Transfer Protocol (SMTP) Network management Total Case Study: Nil

3

4

4

3

4

6

3

30

Duration of Laboratory 3 3 3 3 12

Method of Assessment: Continuous Assessment 55%

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BSc (Hons) Scheme in Computing (FT/SAND) ­ Definitive Programme Document / Programme Booklet 2006/07

Examination

45%

Textbooks: 1. Behrouz A. Forouzan, "TCP/IP Protocol Suite", 2nd Edition, McGraw Hill. Reference Books: 1. Douglas Comer, "Internetworking with TCP/IP: Principles. Protocols, and Architectures", 4th edition, Prentice Hall. 2. W. Richard Stevens, "TCP/IP Illustrated, Vol 1", Addison Wesley. 3. Andrew Tanenbaum, "Computer Networks", Prentice Hall. 4. Articles from IEEE/ACM Transactions on Networking, IEEE Internet Computing, The Internet Protocol Journal, ACM Communications Magazine.

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SUBJECT DESCRIPTION FORM

Subject Title: Data Warehousing and Data Mining Techniques in Business and Commerce Subject Code: COMP 417 Number of Credits: 3 Hours Assigned: Lecture/Tutorial 35 hours Laboratory 7 hours

Pre-requisite: COMP 311

Co-requisite: Nil

Exclusion: Nil

Objectives: This subject is aimed at teaching students to: · make effective use of data stored in databases; · create a clean, consistent repository of data within a data warehouse; · utilize various levels and types of data summarization to support management decision making; · discover patterns and knowledge that is embedded in the data using several different techniques, such as neural nets, decision trees and statistical techniques. Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) understand why there is a need for data warehouse in addition to traditional operational database systems; (2) identify components in typical data warehouse architectures; (3) design a data warehouse and understand the process required to construct one; (4) understand why there is a need for data mining and in what ways it is different from traditional statistical techniques; (5) understand the details of different algorithms made available by popular commercial data mining software; (6) solve real data mining problems by using the right tools to find interesting patterns; (7) understand a typical knowledge discovery process such as CRISP-DM; (8) obtain hands-on experience with some popular data mining software. Attributes for all-roundedness (1) solve real-world problems in business and commerce using data mining and data warehousing tools; (2) learn independently and search for relevant information to write reports to recommend appropriate data warehousing and data mining tools.

Syllabus: Topic 1. Introduction to data warehousing and data mining

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Duration of Lectures / Tutorials 3

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Introduction to data warehousing and data mining; possible application areas in business and finance; definitions and terminologies; types of data mining problems. 2. Data warehousing Data warehouse and data warehousing; data warehouse and the industry; definitions; operational databases vs. data warehouses. 3. Data warehouse architecture and design Data warehouse architecture and design; two-tier and three-tier architecture; star schema and snowflake schema; data characteristics; static and dynamic data; meta-data; data marts. 4. Data processing Data replication, data capturing and indexing, data transformation and cleansing; replicated data and derived data; Online Analytical Processing (OLAP); multidimensional databases; data cube. 5. Data mining and knowledge discovery Data mining and knowledge discovery, the data mining lifecycle; preprocessing; data transformation; types of problems and applications. 6. Association rules Mining of association rules; the Apriori algorithm; binary, quantitative and generalized association rules; interestingness measures. 7. Classification Classification; decision tree based algorithms; Bayesian approach; statistical approaches, nearest neighbor approach; neural network based approach; genetic algorithms based technique; evaluation of classification model. 8. Clustering Clustering; k-means algorithm; hierarchical algorithm; Condorset; neural network and genetic algorithms based approach; evaluation of effectiveness. 9. Sequential data mining Sequential data mining; time dependent data and temporal data; time series analysis; sub-sequence matching; classification and clustering of temporal data; prediction. 10. Other techniques Computation intelligence techniques; fuzzy logic, genetic algorithms and neural networks for data mining. Total Laboratory Experiment: Topic 1. 2. 3. 4. Knowledge discovery lifecycle using CRISP-DM Discover Association rules and sequential patterns using Clementine Discover Classification rules using Clementine Discover Clusters using Clementine

3

6

3

2

3

6

4

2

3

35

Duration of Laboratory 2 2 2 1 Total 7

Case Study: · · Application of data mining techniques to solve real business problems. Attributes leading to success and failure of data warehousing projects tutorials when appropriate.

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BSc (Hons) Scheme in Computing (FT/SAND) ­ Definitive Programme Document / Programme Booklet 2006/07

Method of Assessment: Continuous Assessment Examination 55% 45%

Reference Books: 1. Inmon, W.H., Building the Data Warehouse, Second Edition, John Wiley & Sons, 1996. 2. Mattison, R., Data Warehousing and Data Mining for Telecommunications, Artech House, Boston, 1997. 3. Wtehorn, M., Business Intelligence: the IBM Solution: Datawarehousing and OLAP, Springer, London, 1999. 4. Han, J. and Kamber, M., Data Mining: Concepts and Techniques, Morgan Kaufmann, 2001. 5. Rud, O.P., Data Mining Cookbook: Modeling Data for Marketing, Risk, and Customer Relationship Management, John Wiley, 2001. 6. Groth, R., Data Mining: Building Competitive Advantage, Prentice Hall, 1998. 7. Berry, M.J.A., Mastering Data Mining: the Art and Science of Customer Relationship Management, Wiley, 2000. 8. Kovalerchuk, B., Data Mining in Finance: Advances in Relational and Hybrid Methods, Kluwer Academic, Boston, 2000. 9. Berry, M.J.A., Data Mining Techniques for Marketing, Sales and Customer Support, Wiley, 1997.

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SUBJECT DESCRIPTION FORM

Subject Title: E-Commerce Number of Credits: 3

Subject Code:

COMP 418 28 hours 14 hours

Hours Assigned: Lecture Laboratory

Pre-requisite: COMP 311, COMP 320

Co-requisite: Nil

Exclusion: Nil

Objectives: To thoroughly understand the information technology for supporting E-commerce; specifically, the students should · understand applied cryptographic technology and Web security protocols; · understand the necessary infrastructure and functional components to develop E-commerce systems; · understand the design and application of E-commerce systems. Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) identify different components of e-commerce and related systems; (2) identify different components of Web security and cryptographic technology; (3) identify different kinds of Internet payment systems; (4) design, develop and implement typical e-commerce and wireless e-commerce systems by using Java Servlets, J2ME and related technologies; (5) understand the latest and future development of e-commerce, including virtual marketplace and e-commerce agents. Attributes for all-roundedness (1) communicate effectively in project / system presentation and technical documents / reports; (2) learn independently for problem solving and solution seeking; (3) collaborate with other team members for project design and development, while exhibiting leadership in a project team whenever designated or necessary; (4) think and reason in a critical and creative mind, especially in applying different computing technologies to e-commerce applications.

Syllabus: Topic 1. Introduction to E-commerce Systems E-commerce fundamentals; major components of E-commerce, consumeroriented E-commerce, business-oriented E-commerce; E-servicing; Eadvertising. 2. World-wide-web

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Duration of Lectures 7

3

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Web model; web system; hypertext transfer protocol (HTTP); web publishing; web programming with Servlets. 3. Applied cryptography and web security Cryptology: Cryptography vs. Steganography; general principles of applied cryptography on E-commerce; public key and private key encryption; message authentication and hash functions; key management; key agreement; authentication protocols; digital signatures; digital certificates; Java cryptography. 4. Internet payment systems Digital cash; electronic checks; secure electronic transaction (SET); SET vs. SSL; Internet payment systems; smart card system. 5. Wireless E-commerce and future development of E-Commerce Introduction to wireless E-commerce; wreless Internet using J2ME; MIDlet programming; future of wireless Internet; intelligent agents; intelligent Ecommerce systems; virtual marketplace. Total Laboratory Experiment: Topic 1. 2. 3. 4. Basic/advance Java Servlet workshop J2ME programming workshop Java Cryptography workshop E-Commerce project workshop (building virtual book store VBS)

6

6

6

28

Duration of Laboratory 4 4 3 3 Total 14

Case Study: Nil

Method of Assessment: Continuous Assessment 55% Lab Assignments, Quiz, Term Paper, Group Project Examination 45% Textbook: 1. Chan, H.C.B., Lee, R.S.T., Dillon, T.S. and Chang, E., E-Commerce: Fundamentals and Applications, John Wiley and Sons, 2001. Reference Books: 1. King, D., Lee, J., Warkentin, M., Chung, H.M., Electronic Commerce: A Managerial Perspective, Prentice Hall, 2002. 2. Stallings, W., Cryptography and Network Security: Principles and Practice, Prentice Hall, 1999. 3 Furche, A. and Wrightson, G., Computer Money: A Systematic Overview of Electronic Payment Systems, Morgan Kaufmann Publishers, Inc., 1996. 4. Moss, K., Java Servlets, Mc-GrawHill, 1999. 5. Ortiz, C.E. and Giguere, E., Mobile Information Device Profile for Java 2 Micro Edition, Wiley, 2001. 6. Muchow, J.W., Core J2ME: Technology and MIDP, Prentice Hall, 2002. 7. Lee, Raymond S. T., Fuzzy-Neuro Approach to Agent Applications (From the AI Perspective to Modern Ontology), Springer-Verlag, Heidelberg.

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SUBJECT DESCRIPTION FORM

Subject Title: Multimedia Systems and Applications Number of Credits: 3

Subject Code: COMP 422 28 hours 14 hours

Hours Assigned: Lecture Tutorial/Lab

Pre-requisite: COMP 319 or COMP 407

Co-requisite: Nil

Exclusion: Nil

Objectives: · · To provide knowledge of a wide spectrum of multimedia system technologies that are essential to modern web-based and non-web-based information system design. To equip students with skills in multimedia programming and system development.

Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) understand the characteristics of different media and develop search engines for multimedia data; (2) understand the requirements of processing video data and develop video processing systems; (3) generalize the knowledge and skills learnt from (1) & (2) to handle other media types, e.g. speech and sensor data; (4) understand different multidimensional indexing techniques and use them in multimedia databases; (5) understand different web-based graphics techniques and apply them to e-commerce applications; (6) understand the principles, techniques and tools in computer game and digital movies development; Attributes for all-roundedness (1) solve problems using systematic approaches; (2) learn independently and search for the information required in solving problems; (3) conduct case study and present findings professionally.

Syllabus: Topic 1. Multimedia information retrieval Characteristics of multimedia data; potential applications of multimedia information retrieval systems; concept of content-based image retrieval/search; image content analysis: color analysis, shape analysis, spatial analysis, etc.; retrieval techniques: color histogram, shape histogram, etc.; performance measurement and web-based implementation.

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Duration of Lectures 6

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2. Video information processing Video processing requirements; granularity of video data; video segmentation or scene change detection; video indexing and key frame selection; applications of video information processing systems: TV news archival, TV commercial removal, etc. 3. Multimedia indexing and database management Multidimensional indexing: k-d trees, R-trees, etc.; multimedia databases; spatial databases; query languages for multimedia data objects; spatialtemporal properties of multimedia data. 4. Web-based virtual reality, 3-D modeling and applications Virtual reality techniques; web animation; 3-D model construction; VRML; X3D/Web3D; E-commerce applications; introduction to game development: game development cycle, tools and techniques; principles and tools in digital movies development. 5. Selected topics in multimedia systems and applications Different new topics will be selected for study, e.g. multimedia security, MMS, new MPEG standards, distributed virtual reality, mobile games, and the like. Total Laboratory Experiments and other Practical Work: Topic (vary year after year) 1. 2. 3. 4. Use of spatial database, e.g. Oracle Spatial Database. Use of game development tools, e.g. Virtools and 3D Studio Max. Development of an image search engine. Case study of emerging multimedia system technologies Total Case Study: Nil

4

6

6

6

28

Duration of Laboratory 4 4 4 2 14

Method of Assessment: Continuous Assessment Examination

55% 45%

Reference Books: 1. Borko Furht Ed., Handbook of Multimedia Computing. CRC Press, 1999. 2. Alberto Del Bimbo, Visual Information Retrieval. Morgan Kaufmann, 1999. 3. Yihong Gong, Intelligent Image Databases: Towards Advanced Image Retrieval. Kluwer, 1998. 4. V.S. Subrahmanian, Principles of Multimedia Database Systems. Morgan Kaufmann, 1998. 5. T. Akenine-Moller and E. Haines, Real-Time Rendering, 2nd Edition, A.K. Peters, 2002.

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6. 7. 8. 9.

Oracle Spatial Database Manuals, Oracle Corporation, 2004 Z.N. Li and M.S. Drew, Fundamentals of Multimedia. Prentice Hall, 2003. X3D, VRML language specification documentations. Web3D Consortium, 2005. K. Jeffay and H. Zhang, Readings in Multimedia Computing and Networking. Morgan Kaufmann, 2002.

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SUBJECT DESCRIPTION FORM

Subject Title: Business Process and Workflow Management Number of Credits: 3

Subject Code: COMP 431 28 hours 14 hours

Hours Assigned: Lecture Seminar

Pre-requisite: Nil

Co-requisite: Nil

Exclusion: Nil

Objectives: · To present a process-oriented view to business modeling and the application of workflow technologies to business process engineering. · To equip students with the fundamental knowledge of workflow management systems. Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) understand the role of business processes in modern enterprises; (2) understand the basic steps in business process engineering/re-engineering; (3) understand the application of workflow technologies to process modeling and implementation; (4) understand the building blocks of a workflow management system; (5) understand the existing industrial workflow standards; (6) apply workflow technologies to solve business problems; Attributes for all-roundedness (1) improve presentation and communication skills (through case study presentations); (2) learn independently and to find/integrate information from different sources required in solving real-life problems.

Syllabus: Topic 1. Introduction to business process Modern business environment; process-oriented view to organizations; examples of business processes. 2. Business process engineering Process analysis; process re-engineering; business engineering and workflow. 3. Fundamental concepts of workflow Major components of a workflow management system; Buildtime metamodel: process data, activities, control flow, data flow; Runtime system structure; workflows and objects.

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Duration of Lectures 2

4

6

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4. Advanced functions of workflow Events; dynamic modification of workflows; advanced join conditions; container materialization; context management; performance spheres; compile spheres; transactions. 5. Workflow systems architecture Application structure; middleware; Internet and mobile workflow; emergent technologies. 6. Workflow standards OMG's Workflow Management Facility; Workflow Management Coalition standards. Total Laboratory Experiment: Nil

8

4

4

28

Case Study: Presentations will be held during the seminars, where the students will form groups to read and present real-life cases related to the subject's topics.

Method of Assessment: Continuous Assessment Examination

55% 45%

Reference Books: 1. L. Ficher (ed.), Workflow Handbook 2004, Future Strategies Inc., 2004. 2. F. Leymann, D. Roller, Production Workflow: Concepts and Techniques, Prentice-Hall, 2000. 3. T. Schael, T. Schal, T. and T.W. Schaller, Workflow Management Systems for Process Organisations, Springer, 1998. 4. Articles from journals, magazines, and conference proceedings, including ACM TOCS, ACM TODS, IEEE TKDE, IEEE TSE, IEEE TOC, CACM, IEEE Computer, ICDE, CIKM.

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SUBJECT DESCRIPTION FORM

Subject Title: Logistics Management Number of Credits: 3

Subject Code:

COMP 432

Hours Assigned: Lecture 28 hours Tutorial/Lab/Sem 14 hours

Pre-requisite: COMP 302

Co-requisite: Nil

Exclusion: Nil

Objectives: · To provide the knowledge in logistics operations, system evaluation and strategic management. · To demonstrate the techniques for logistics simulation and evaluation. Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) understand the importance of logistics and its role in competitive strategy; (2) be aware of the value of information on decision making and logistics system performance; (3) recognize production systems and how such systems improve the operation management; (4) possess knowledge in system analysis, operation evaluation and performance monitoring of logistics operations; (5) perform case modelling, simulation and concepts; Attributes for all-roundedness (1) improve presentation and communication skills (through case study presentations); (2) learn independently and to find/integrate information from different sources required in solving real-life problems; (3) build up on team spirit, presentation and technical writing skills.

Syllabus: Topic 1. Principles of logistics management Development of logistics; economic significance of logistics; importance of logistics management in transportation and distribution systems. 2. Multi-modal transport operations Multi-modal transport concept; business practices; rules and responsibilities; liability and legal issues. 3. Supply chain Customer service dimensions; supply chain management concepts and applications; strategic alliance; supply chain integration.

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Duration of Lectures 4

4

4

Page 151

4. Global logistics Elements and management of global logistics; transportation options and strategies. 5. Inventory Inventory costs, control and management; capacity planning; warehousing. 6. Logistics management Logistics performance measurement; management tools and methods in assessing logistics operations; databases and data exchange standards and technologies; e-logistics. Total Laboratory Experiment: Nil Case Study: Seminars are held for students to discuss real-life cases related to the subject's topics.

4

4

8

28

Method of Assessment: Continuous Assessment Case studies, tutorial exercises, project Examination 60%

40%

Reference Books: 1. Coyle, John Joseph, The Management of Business Logistics: A Supply Chain Perspective, 7th Edition, Thomson Learning, 2003. 2. Handfield R. and Nichols E Jr, Introduction to Supply Chain Management, Prentice Hall, 1999. 3. Harrison, Alan, Logistics Management and Strategy, Harlow, England: Financial Times/Prentice Hall, 2002. 4. Deborah L. Bayles, E-Commerce Logistics and Fulfillment: Delivering the Goods, Prentice Hall, 2002. 5. Carlos F. Daganzo, Logistics Systems Analysis, Springer, 1996. 6. Stock, James R., Strategic Logistics Management, 4th Edition, McGraw-Hill, 2001. 7. Vogt J. J., Business logistics management : theory and practice, Oxford University Press, 2002. 8. Articles from magazines, and journal references, including Harvard Business Review, Journal of Business Logistics, Journal of Information Technology, Logistics Information Management.

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SUBJECT DESCRIPTION FORM

Subject Title: Information Retrieval Number of Credits: 3

Subject Code:

COMP 433 28 hours 14 hours

Hours Assigned: Lecture Tutorial/Lab

Pre-requisite: COMP 305, COMP 311

Co-requisite: Nil

Exclusion: Nil

Objectives: · · · · · To provide the foundation knowledge in information retrieval. To equip students with sound skills to solve computational search problems. To appreciate how to evaluate search engines. To appreciate the different applications of information retrieval techniques in the Internet or Web environment. To provide hands-on experience in building search engines and/or hands-on experience in evaluating search engines.

Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) understand the basic concepts of information retrieval; (2) apply information retrieval techniques in solving computational search problems; (3) better utilize search engines for solving problems; (4) appreciate the limitations of different information retrieval techniques; (5) write programs to implement search engines; (6) evaluate search engines; Attributes for all-roundedness (1) solve problems using systematic approaches; (2) learn independently and be able to search for the information required in solving problems; (3) write technical reports and present the findings; (4) learn team working skills.

Syllabus: Topic 1. Fundamentals of information retrieval System architecture; limitations of information retrieval systems; evaluation methodology; performance measures; benchmarking. 2. Models of information retrieval Boolean retrieval models; fuzzy Boolean retrieval models; vector space models; inner product similarities; cosine similarities; term weighting schemes. 3. Query processing

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Duration of Lectures 2

4

4

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4.

5.

6.

7.

8.

Query languages; basic query processing for Boolean retrieval models; query processing for vector space models; query expansion; relevance feedback. Indexing strategies Inverted file construction; efficient dictionary management; indexing to support phrasal search and proximity. Text properties and information extraction Zipf law; Heap's law; HTML markup; XML markup; Document Object Models; (DOM); string searching; filler pattern matching. Text clustering Hierarchical clustering algorithms; adaptive clustering algorithms; k-means clustering algorithms. Web retrieval Characteristics of the web; spidering; weighting schemes for web documents; web link analysis. Text categorization Rocchio classifier; k-NN classifier; naïve Bayesian classifier and evaluation methodology. Total

4

4

4

4

2

28

Laboratory Experiment and Tutorial: Topic 1. 2. 3. 4. Evaluation techniques. Ranking techniques. Text processing techniques. Web processing techniques. Duration of Laboratory 2 4 4 4 Total 14

Case Study: Nil

Method of Assessment: Continuous Assessment Mini-project, report and presentation Classwork and exercises Examination 55% 30% 25% 45%

Reference Books: 1. G.G. Chowdhury. An Introduction to Modern Information Retrieval, London, Facet, 2004. 2. R.A. Baeza-Yates, B. Riberio-Neto. Modern Information Retrieval, ACM Press, 1999. 3. D.A. Grossman and O. Freider. Information Retrieval: Algorithms and Heuristics, Kluwer Academic Publishers, 1998. 4. G. Grefenstette (ed.) Cross-language Information Retrieval, Dorhrecht, The Netherlands: Kluwer Academic Publishers, 1998. 5. I.H. Witten, A. Moffat and T.C. Bell. Managing Gigabytes: Compressing and Indexing Documents and Images, New York: Van Nostrand Reinhold, 1994.

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SUBJECT DESCRIPTION FORM

Subject Title: Computational Models Number of Credits: 3

Subject Code: Hours Assigned: Lecture Tutorial

COMP 434 28 hours 14 hours

Pre-requisite: COMP 210, COMP 305, COMP 309 Co-requisite: Nil

Exclusion: Nil

Objectives: This subject provides students knowledge on: · computational models and theoretical computer science; · fundamental concepts behind computing and problem solving. Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) acquire fundamental knowledge and concepts in computational models and theoretical computer science; (2) understand the limitation of computers and algorithms in problem solving, in the presence of unsolvable and intractable problems; (3) appreciate existence and development of smart algorithms that solve problems effectively; (4) evaluate the effectiveness of computer algorithms employed in different applications; (5) apply the knowledge in specific applications such as algorithm design, compiler construction. Attributes for all-roundedness (1) develop critical thinking on evaluating solution models and approaches; (2) describe, express and solve problems through formalism and precise formulation.

Syllabus: Topic 1. Formal languages and automata Strings and languages; grammars; regular languages; context-free languages; context-sensitive languages; recursively enumerable languages; final automata; pushdown automata; deterministic and non-deterministic automata; pumping lemma for regular and context-free languages; Turing machines. 2. Unsolvable problems Technique of diagonalization; undecidable or unsolvable problems, e.g., halting problem, Post's correspondence problem. 3. Computational complexity Complexity of algorithms; algorithm analysis techniques; complexity classes.

BSc (Hons) Scheme in Computing (FT/SAND) ­ Definitive Programme Document / Programme Booklet 2006/07

Duration of Lectures 10

2

4

Page 155

4. NP-hard and NP-complete problems Intractable problems; definition of the class NP; problem reduction; wellknown NP-complete problems, e.g., 3SAT, bin packing, office hours scheduling, travelling salesperson problem. 5. Dynamic programming and approximation Principle of dynamic programming; branch-and-bound; approximated solutions; simulated annealing. 6. Applications Complexity implication; lexical analyzer (lex); parser (yacc); real-life NPcomplete applications, e.g., TSP variant, scheduling. Total Laboratory Experiment: Nil Case Study: Existence of real-life NP-hard problems and their approximated solutions.

4

4

4

28

Method of Assessment: Continuous Assessment Examination 55% 45%

Reference Books: 1. J.E. Hopcroft, R. Motwani, and J.D. Ullman. Introduction to Automata Theory, Languages, and Computation. Second Edition, Addison-Wesley, 2001. 2. D.C. Kozen. Automata and Computability. Springer, 1997. 3. D. Kelley. Automata and Formal Languages: An Introduction. Prentice Hall, 1995. 4. S.Y. Yan. An Introduction to Formal Languages and Machine Computation. World Scientific, 1998. 5. R. Sedgewick and P. Flajolet. An Introduction to the Analysis of Algorithms. AddisonWesley, 1996. 6. M.R. Garey and D. Johnson. Computers and Intractability: A Guide to the Theory of NPcompleteness. W.H. Freeman, 1979. 7. A.V. Aho, J.E. Hopcroft, and J. Ullman. Data Structures and Algorithms. Addison-Wesley, 1983.

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SUBJECT DESCRIPTION FORM

Subject Title: Biometrics and Security Number of Credits: 3

Subject Code: Hours Assigned: Lecture Tutorial

COMP 435 28 hours 14 hours

Pre-requisite: COMP 211, COMP 319

Co-requisite: Nil

Exclusion: Nil

Objectives: · · · To understand the problems with current security systems. To introduce biometric computing knowledge and methods. To learn some basic biometrics systems based on the learned techniques.

Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) understand fundamental problems with current biometric systems; (2) recognize physical and behavial biometric characteristics; (3) apply biometric technology into two applications: security and diagnosis; (4) learn some useful biometric techniques to solve the current problems; Attributes for all-roundedness (1) communicate effectively with project presentation and technical reports; (2) learn independently for problem solving and solution seeking for biometrics applications.

Syllabus: Topic 1. Introduction to biometrics and authentication Why biometrics? What about biometrics? How to design biometric systems? Biometrics definitions and notations; biometric applications; information security; security technologies and systems; authentication. 2. Fundamental techniques Biometrics data acquisition and biometrics database; the related image processing and pattern recognition technologies, including digital image and signal representation, pattern extraction and classification; basic PCA/LDA approaches of automated biometrics identification and verification. 3. Typical physical biometrics Basic physical characteristics of biometrics; some basic introduction of physical biometrics systems (such as fingerprint, palm-print, finger, hand, face, iris, and face, as well as tongue, etc.). Duration of Lectures 4

6

8

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4. Typical behavial biometrics Basic behavioral characteristics of biometrics; some basic introduction of behavioral biometrics systems (such as voice, signature, and gesture recognition, as well as pulse, etc.). 5. Multi-biometrics and applications Security application: Internet/Intranet; e-commerce; banking services; immigration and naturalization service; computer systems; physical access; telephone systems; time, attendance and monitoring. Diagnosis application: tongue diagnosis and pulse diagnosis. Total Case Study: Security and diagnosis applications using biometrics authentication technologies.

6

4

28

Method of Assessment: Continuous Assessment Examination 60% 40%

Reference Books: 1. Zhang, D., Automated Biometrics: Technologies & Systems, Kluwer Publisher, 2000. 2. Zhang, D., (Ed.), Biometric Solutions for Authentication in an e-World, Kluwer Publisher, 2002. 3. Stallings, W. Cryptography and Network Security: Principles and Practice, Third Edition, Prentice Hall, 2003. 4. Jain, et al. (Eds.), Biometrics: Personal Identification in Networked Society, Kluwer Publisher, 1999. 5. Sid-Ahmed, M.A., Image Processing, Theory, Algorithms, & Architectures, McGraw-Hill, 1995. 6. Awcock. G.W., et al., Applied Image Processing, McGraw-Hill, 1996. 7. Abrams, M.D., Jajodia, S., and Podell, H.J., Information Security: An Integrated Collection of Essays, IEEE Computer Society Press, 1994. 8. Derek Atkins, et al., Internet Security Professional Reference, Second Edition. New Riders Publishing, 1997. 9. Russell, D., Computer Security Basics, O'Reilly & Associates, 1991. 10. Zhang, D., Palmprint Authentication, Kluwer Academic Publishers, USA, 2004. 11. Zhang, D. and Jain, A.K. (Eds.), Proc. First International Conference on Biometric Authentication (ICBA), 800pp, Springer Verlag, LNCS 3072, 2004 12. Zhang, D., Jing, X. and Yang, Y., Biometric Images Discrimination (BID) Technologies, IRM Press, USA, 2005. 13. Zhang, D. and Jain, A.K. (Eds.), Advances in Biometrics, International Conference ICB2006, Springer Verlag, LNCS 3832, 2006. 14. IEEE Transaction on Pattern Analysis and Machine Intelligence. 15. IEEE Transaction on Image Processing.

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SUBJECT DESCRIPTION FORM

Subject Title: Middleware and Distributed Objects Number of Credits: 3

Subject Code:

COMP 436 30 hours 12 hours

Hours Assigned: Lecture Seminar/Lab

Pre-requisite: COMP 201

Co-requisite: Nil

Exclusion: COMP 403

Objectives: · To present an integrated view of the basic building blocks of a distributed system and how middleware can help developers to more easily satisfy the requirements of building distributed systems. · To provide the foundation knowledge of middleware, particularly object-oriented middleware. · To provide training in using CORBA as middleware to build practical distributed systems. Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) understand the basic structure of distributed systems; (2) understand the motivation of using middleware; (3) understand the basic theories underlying the design of middleware; (4) learn to make judgment in choosing a suitable middleware for application problems; (5) understand the basic concepts of CORBA; (6) develop distributed object-based systems using CORBA. Attributes for all-roundedness (1) apply the technical knowledge learned to solve real-life practical problems; (2) appreciate and evaluate existing and new technologies.

Syllabus: Topic 1. Principles of object-oriented middleware Role of middleware in distributed systems; types of middleware; objectoriented middleware; local versus distributed objects; developing systems with object-oriented middleware. 2. Fundamentals of CORBA Architecture; Interface definition language (IDL); system development using CORBA. 3. Communication paradigms of CORBA Synchronous requests; oneway requests; deferred synchronous requests;

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asynchronous requests; dynamic invocation; CORBA event service; pros and cons of different communication paradigms of CORBA. 4. Portable Object Adaptor (POA) Objects vs. servants; lifecycle of objects; request invocation via POA; servant activator and servant locator. 5. Case study 1: load balancing Using POA to implement various load balancing solutions for distributed systems. 6. Case study 2: resource management Using CORBA to implement facilities for resource management in distributed systems, e.g. resource lookup, resource acquisition; CORBA naming service. Total Laboratory Experiment: In the laboratory session, students will learn how to develop distributed systems using an implementation of CORBA, called VisiBroker (or the Borland Enterprise Server ­ VisiBroker Edition), using Java as the programming language. Case Study: Case studies on load balancing and resource management with CORBA. 8

5

5

30

Method of Assessment: Continuous Assessment Examination 55% 45%

Textbooks: 1. W. Emmerich, Engineering Distributed Objects, Wiley, 2000. Reference Books: 1. 2. 3. 4. F. Bolton, Pure CORBA, Sams, 2002. R. Orfali, D. Harkey and J. Edwards, Client/Server Survival Guide, 3rd ed., Wiley, 1999. IEEE Distributed Systems Online,. Articles from journals, magazines, and conference proceedings, including ACM TOCS, IEEE TPDS, IEEE TSE, IEEE TOC, CACM, IEEE Computer, ICDE, DOA.

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SUBJECT DESCRIPTION FORM

Subject Title: Mobile Computing Number of Credits: 3

Subject Code:

COMP 437 28 hours 14 hours

Hours Assigned: Lecture Tutorial/Lab

Pre-requisite: COMP 304, COMP 311

Co-requisite: Nil

Exclusion: Nil

Objectives: · · · To introduce students the basic concepts and principles of mobile computing; To provide students the knowledge about theoretical and practical aspects of mobile computing; To train students in developing skills for developing solutions and building software for mobile computing applications using standard languages and tools.

Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) grasp the concepts and features of mobile computing technologies and applications; (2) have a good understanding of how the underlying wireless and mobile communication networks work, their technical features, and what kinds of applications they can support; (3) identify the important issues and the principles of developing mobile computing systems and applications; (4) organize the functionalities and components of mobile computing systems into different layers and learn various related techniques for realizing the functionalities; (5) develop solutions for mobile computing applications by analyzing their characteristics and requirements, selecting the appropriate computing models and software architectures, and applying standard programming languages and tools; (6) organize and manage software built for deployment and demonstration. Attributes for all-roundedness (1) analyze requirements and solve problems using systematic planning and development approaches; (2) search for and read critically the information required in solving problems; (3) write and present technical survey papers in well-organized and logical manner; (4) work in teams and collaborate with classmates.

Syllabus: Topic 1. Introduction to mobile computing Motivations, concepts, challenges, and examples of mobile computing; relationship with distributed computing, Internet computing, ubiquitous computing, and pervasive computing.

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2. Introduction to wireless communication and networks Wireless communication concepts; modulation and multiplexing techniques (spread spectrum, multi-access methods); medium access control; classification of wireless networks: WPAN, WLAN, WMAN, WWAN; evolution of cellar communication systems (1G, 2G, 3G, etc). 3. Mobility management Handoff and location management concepts; mobility management in PLMN; mobility management in mobile Internet; mobility management in mobile agent systems; adaptive location management methods. 4. Mobility computing models and application architectures Extended client-server model; peer-to-peer model; mobile agent model; wireless Internet; smart client; messaging; mobile data management; mobile OS; WAP, WML, J2ME. 5. Location-based services Concepts and applications; mobile positioning techniques; GIS; LBS architecture and protocols. 6. Mobile computing middleware Functionalities of mobile computing middleware; reflective middleware; tuple space middleware; context-aware middleware; publication/subscription and other middleware solutions. 7. Ad hoc networks and applications Concepts and applications; routing in mobile ad hoc networks; sensor networks. Total Tutorials: 8 hours Laboratory Experiment: Topic 1. WAP programming. 2. J2ME programming.

6

4

6

4

2

4

28

Duration of Laboratory 2 4 Total 6

Case Study: Nil

Method of Assessment: Continuous Assessment Examination 55% 45%

Textbooks: 1. Martyn Mallick, Mobile and Wireless Design Essentials, Wiley Publishing, 2003. Reference Books: 1. H.M. Deitel, P.J. Deitel, T.R. Nieto, and K. Steinbuhler, Wireless Internet & Mobile Business ­ How to Program, Prentice Hall, 2002.

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2. J. Schiller, Mobile Communications, 2nd edition, Pearson Education, 2003. 3. D.P. Agrawal and Q.-A. Zeng, Introduction to Wireless and Mobile Systems, Brooks/Cole, Thomson Learning, 2003. 4. J. Burkhardt, H. Henn, S. Hepper, K. Rindtorff and T. Schaeck, Pervasive Computing: Technology and Architecture of Mobile Internet Applications, Addison-Wesley, 2002. 5. Evaggelia Pitoura and George Samaras, Data Management for Mobile Computing, Kluwer Academic Publishers, 1998.

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SUBJECT DESCRIPTION FORM

Subject Title: Game Programming Number of Credits: 3

Subject Code: Hours Assigned: Lecture Tutorial/Lab

COMP 439 28 hours 14 hours

Pre-requisite: COMP 305

Co-requisite: Nil

Exclusion: Nil

Objectives: · · · · · To let students understand the nature of computer games and digital entertainment; To equip students with the knowledge and skills in programming interactive games and virtual reality simulations; To allow students to explore the different techniques and tools in rendering and animation in 3D computer games; To ensure students understanding game AI, multi-user games and networking To guide students to study and evaluate the social impact of computer game.

Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) understand the history, evolution and recent development in computer games; (2) understand the overall hardware and software architecture of a typical 3D computer game; (3) familiarize with the different practical implementation techniques that apply to the development of computer games across different platforms; (4) learn game design, testing, and playability principles; (5) learn the computing game programming aspects, such as event loops, execution threads, rendering, animation, terrain and background representation, polygonal models, texturing, collision detection and physically-based modeling, game AI, and multi-user games and networking; (6) understand the social impact of computer games; Attributes for all-roundedness (1) work in a team to build a 3D computer game; (2) communicate effectively and present, both in terms of an oral presentation and a written report, the result of developing a 3D computer game; (3) appreciate the broader perspectives of digital entertainment, and social impact of computer games.

Syllabus: Topic 1. Introduction and game history Early origins of video games and computer game programming; arcade games; some popular home game systems; game design methodology and

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2.

3.

4.

5.

6.

principles; current development in computer game industry. Game software, hardware and platforms Different game platforms: Web-based, console-based (e.g., play station, Xbox, game cube), pc-based, handheld games, mobile and wireless game platforms. Programming techniques in computer games 3D models, geometry, rotation, and quaternion interpolation; camera control, texturing, terrain, lighting, level of details (LOD), collision detection; shading, non-photorealistic rendering, image-based rendering. Game behavior and game AI Algorithms in game animations: acceleration, motion analysis, game physics, collision detection, and the like; game AI, such as path finding, chasing and evading, pattern movement, flocking, obstacle avoidance, swarming, learning the opponent behaviors; search and heuristics in games, finite state machines, decision trees. Languages and tools in game programming Java 3D, Maya, 3D studio max, VRML, X3D, Virtools, and other authoring tools for various components in the game, such as graphics, audios, sound digitizer, and the like. Social impacts of computer games Gender, race, social and cultural characteristics in computer games; youth violence and digital entertainment software rating; future of computer games. Total

3

6

6

6

4

28

Laboratory Experiment / Tutorial: Topic 1. A team project of building a 3D computer game. 2. Programming exercises in various aspects of game algorithms and game AI techniques. Total Case Study: Nil Duration of Laboratory 14

14

Method of Assessment: Continuous Assessment Examination

55% 45%

Textbook: 1. Tomas Akenine-Moller and Eric Haines, Real-Time Rendering, 2nd Edition, A K Peters Ltd, 2002. Reference Books: 1. Mark DeLoura (Editor), Game Programming Gems, Charles River Media, 2000. 2. Mark DeLoura (Editor), Game Programming Gems 2, Charles River Media, 2001. 3. Mark DeLoura (Editor), Game Programming Gems 3, Charles River Media, 2002.

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4. Eric Lengyel, Mathematics for 3D Game Programming & Computer Graphics, Charles River Media, 2001.

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SUBJECT DESCRIPTION FORM

Subject Title: Customer Relationship Management Number of Credits: 3

Subject Code:

COMP 440

Hours Assigned: Lecture 24 hours Tutorial/Lab/Sem 18 hours

Pre-requisite: COMP 321

Co-requisite: Nil

Exclusion: Nil

Objectives: · To provide the knowledge in CRM / eCRM, people management, process management, customer behaviour and analysis, which are essential for business operations. · To introduce CRM measurement and tools in the market. Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) understand the concepts of CRM / eCRM in eCommerce environments; (2) build the knowledge infostructure to support decision making and marketing; (3) apply the latest development in Internet marketing / CRM tools; (4) develop skills and CRM-based business strategies; Attributes for all-roundedness (1) improve presentation and communication skills (through case study presentations); (2) learn independently and to find/integrate information from different sources required in solving real-life problems; (3) build up on team spirit, presentation and technical writing skills.

Syllabus: Topic 1. Introduction to CRM CRM process; management issues and measurement; customer values; CRM initiatives and economic impact. 2. CRM strategies planning Customer strategy; brand strategy; channel strategy. 3. Customer behavior and analysis Customer profitability; customer buying values analysis; customer profiling. 4. Knowledge-enabled CRM and Technology Knowledge management; data warehouse; data mining techniques and analysis; eCRM application development; CRM software packages; integrated CRM solutions.

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Duration of Lectures 4

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6

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5. Marketing strategies Mobilizing operations; personalization; customization; loyalty programs. Total Laboratory Experiment: Nil

4

24

Case Study: Seminars are held for students to discuss in-depth real-life cases related to the subject's topics, to give presentations and write reports.

Method of Assessment: Continuous Assessment Case studies, tutorial exercises, project Examination 60% 40%

Reference Books: 1. Swift, Ronald S., Accelerating customer relationships: Using CRM and relationship technologies, Prentice Hall, 2001. 2. Amrit Tiwana, The Essential Guide to Knowledge Management: eBusiness and CRM Applications, Prentice Hall, 2001. 3. Laura Brown, John Gravely, Special Edition Using Microsoft CRM, Prentice Hall, 2004. 4. Francoise Tourniaire, Just Enough CRM, Prentice Hall, 2003. 5. Richard J. Roger and Michael W. Geatz, Data Mining: A tutorial-based Primer, Addison Wesley, 2003. 6. Articles from magazines, and journal references, including ComputerWorld, Harvard Business Review, IT Solution Journal.

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SUBJECT DESCRIPTION FORM

Subject Title: Software Testing and Quality Assurance Number of Credits: 3

Subject Code:

COMP 441 28 hours 14 hours

Hours Assigned: Lecture Tutorial/Sem

Pre-requisite: COMP 302

Co-requisite: Nil

Exclusion: Nil

Objectives: · To present the concepts, techniques and metrics for quality assurance in software development. · To develop a good understanding of issues, techniques and tools for software testing. · To enable students to gain a working knowledge of techniques for management of testing projects. Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) appreciate the importance of software quality assurance; (2) apply software testing techniques for information systems development; (3) know the inputs and deliverables of the testing process; Attributes for all-roundedness (1) work together as a team in preparing a report; (2) communicate in writing a technical document; (3) communicate effectively in English for general project presentation.

Syllabus: Topic 1. Software quality assurance Quality factors; cost of quality. 2. Testing fundamentals Understanding defects; testing concepts; levels of testing; test process 3. Code-based techniques Control flow and data flow testing; mutation testing; domain testing; errororiented testing. 4. Specification-based techniques Equivalence partitioning; boundary value testing; state machine testing; program verification. Duration of Lectures 4

4

4

4

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5. Inspection technique Team and roles; process. 6. Test tools Test generation; code coverage tool; defect tracking. 7. Measuring software quality Product metrics; process metrics; GQM; testing maturity model. Total Laboratory Experiment: Nil Case Study:

4

4

4

28

Case studies and projects are adopted for students to discuss and study the software quality assurance and testing process. Report writing and presentation is needed.

Method of Assessment: Continuous Assessment Examination 55% 45%

Textbooks: 1. Kaner, C., Falk, J., Nguyen, H.Q., Testing Computer Software, John Wiley, 1999. Reference Books: 1. Nguyen, H.Q., Testing Applications on the Web, John Wiley, 2001. 2. Paulish, D.J. and Moller, K.H., Software Metrics: A Practitioner's Guide to Improved Product Development, IEEE, 1992. 3. Tamres, L., Introducing Software Testing, Addison Wesley, 2002. 4. Wallmuller, E., Software Quality Assurance: A Practical Approach, Prentice Hall, 1994. 5. IEEE Standard 829, 1008, 1012, 1059, 1028, 1044.

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SUBJECT DESCRIPTION FORM

Subject Title: Decision Support Systems Number of Credits: 3

Subject Code:

COMP 442 28 hours 14 hours

Hours Assigned: Lecture Tutorial/Lab

Pre-requisite: Nil

Co-requisite: Nil

Exclusion: Nil

Objectives: · · · · · To understand the nature of decision marking and the role of computerized support. To equip students with the knowledge and skills in building decision support systems. To explore the different paradigms in decision models and analysis. To understand the contemporary techniques for business intelligence. To learn and evaluate the effectiveness of enterprise decision support systems and knowledge management.

Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) understand the history, development and various applications of decision support systems; (2) familiarize with the different phases in human decision marking; (3) understand the overall hardware and software architecture of a typical decision support system; (4) learn the different models in decision analysis, such as mathematical programming optimization, decision trees, problem-solving search methods, heuristic programming, simulation, and the like; (5) appreciate how uncertainty is being tackled in the decision support systems, in particular, techniques based on probability theory and possibility theory (fuzzy logic) will be discussed; (6) master the skills and techniques for business intelligence, such as data warehousing, data mining, business analytics, and visualization; (7) develop a simple decision support system; (8) learn the collaboration and communication issues in enterprise decision support systems; (9) understand the importance of maintaining decision support systems; Attributes for all-roundedness (1) work in a team to build an enterprise oriented decision support system; (2) communicate effectively and present, both in terms of an oral presentation and a written report, the result of an enterprise oriented decision support system; (3) appreciate the broader perspectives of human decision marking and the co-operative issues in organizational decision making.

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Syllabus: Topic 1. Decision Support Systems (DSS): An Overview Managers and decision marking; computer support for decision marking; the concept of a DSS: a knowledge management system and an intelligent system; hybrid support systems and group decision support systems. 2. Decision marking models, analysis and DSS development Phases in human decision marking process; characteristics and capabilities of DSS; components of DSS; hardware/software and other requirements of building a DSS; DSS models: mathematical programming optimization, decision trees, problem-solving search methods, heuristic programming, simulation, and the like; uncertainty representation in DSS: probability theory and possibility theory (fuzzy logic). 3. Business intelligence and knowledge management Data warehousing; data mining; business analytics and visualization; organizational learning and transformation; knowledge management approaches; information technology and knowledge management. 4. Group DSS and enterprise decision supports Group decision making; communications and collaborations; group support systems and enterprise information systems; executive support systems: MRP, ERP/ERM, SCM, CRM, BPM, BAM, and the like. 5. DSS for e-business and maintenance of DSS/group DSS Decision supports in e-business; DSS models and technologies to support ebusiness; maintenance of DSS/group DSS: update of knowledge, models, data and interfaces; issues of correctness, completeness and consistency in DSS. Total Laboratory Experiment and Tutorial: A team project of building a decision support system chosen from a set of DSS models and analysis techniques, such as mathematical programming, simulation, knowledge-based systems, data mining, fuzzy logic and the like. Case Study: Exercises and case studies of group decision support systems, cooperative enterprise DSS and knowledge management. Duration of Lectures 3

9

6

6

4

28

Method of Assessment: Continuous Assessment Examination 55% 45%

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BSc (Hons) Scheme in Computing (FT/SAND) ­ Definitive Programme Document / Programme Booklet 2006/07

Textbook: 1. Efraim Turban, Jay E. Aronson and Ting-Peng Liang, Decision Support Systems and Intelligent Systems, 7th Edition, Prentice Hall, 2005. Reference Books: 1. Michael Negnevitsky, Artificial Intelligence: A Guide to Intelligent Systems. 2nd Edition, Addison Wesley, 2005.

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SUBJECT DESCRIPTION FORM

Subject Title: Knowledge and Information Management Number of Credits: 3

Subject Code:

COMP 443 28 hours 14 hours

Hours Assigned: Lecture Tutorial/Lab

Pre-requisite: Nil

Co-requisite: Nil

Exclusion: Nil

Objectives: This subject provides students knowledge on: · acquisition, representation and processing of knowledge and information; · concepts and applications of knowledge and information management. Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) learn fundamental knowledge and concepts in the acquisition and representation of knowledge and information; (2) appreciate the need of effective knowledge and information management in the knowledge society; (3) develop the ability to manage knowledge and information effectively; (4) evaluate the effectiveness of different knowledge and information approaches; (5) apply the skills learned in real-life applications and information systems; Attributes for all-roundedness (1) develop critical thinking on evaluating solution models and approaches; (2) learn independently for problem solving and solution seeking; (3) acquire and practice effective communication and presentation skills; (4) work together as a team to solve problems.

Syllabus: Topic 1. Introduction to knowledge and information management Data, information and knowledge; information processing; information and knowledge society; knowledge as enterprise asset; knowledge network; difference between information and knowledge management; knowledge life cycle; knowledge acquisition, representation, storage and retrieval, transfer, application and management. 2. Knowledge and information management approaches Schools of knowledge management: economic school, organizational school, strategic school; barrier to knowledge management; impact of culture and technology.

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Duration of Lectures 4

4

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3. Knowledge and information acquisition Information and knowledge acquisition techniques, e.g. interview, observation, questionnaires, concept sorting, protocol-analysis; learning process; knowledge discovery; knowledge claim formulation, validation and evaluation; data mining. 4. Knowledge and information representation Representation of information; representation of knowledge: rules, frames, semantic networks, Bayesian networks, first order, modal and temporal logics, ontology. 5. Knowledge and information processing Information storage, retrieval and use; knowledge storage, retrieval and use, e.g. production systems, expert systems, inference engines; knowledge transfer and exchange. 6. Knowledge management and applications Knowledge management techniques; strategies for knowledge management; chief knowledge officer and chief information officer; enterprise information portal framework and application; content management; collaborative portal; e-business. Total Laboratory Experiment and Case Study:

6

4

4

6

28

Acquisition, representation, and processing of knowledge and information in case studies of real-life systems; use of tools such as Clementine.

Method of Assessment: Continuous Assessment Examination 55% 45%

Reference Books: 1. J.M. Firestone. Enterprise Information Portals and Knowledge Management. Butterworth Heinemann, 2003. 2. P. Gottschalk. Strategic Knowledge Management Technology. Idea Group Publishing, 2005. 3. E.M. Awad and H. Ghaziri. Knowledge Management, Prentice Hall, 2004. 4. T.H. Davenport and L. Prusak. Working Knowledge: How Organizations Manage What They Know. Boston: Harvard Business School Press, 1998. 5. R. Brachman and H. Levesque. Knowledge Representation and Reasoning. Morgan Kaufmann, 2004. 6. J. Davies, D. Fensel, F. van Harmelen. Towards the Semantic Web: Ontology-Driven

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Knowledge Management. John Wiley & Sons, 2003. 7. E. Waltz. Knowledge Management in the Intelligence Enterprise. Artech House, 2003. 8. Articles from IEEE Transactions on Knowledge and Data Engineering, Knowledge and Information Systems: An International Journal, Proceedings of International Conference on Information and Knowledge Management and others.

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SUBJECT DESCRIPTION FORM

Subject Title: Internet Infrastructure Security Number of Credits: 3

Subject Code:

COMP 444

Hours Assigned: Lecture/Tut/Lab 42 hours

Pre-requisite: COMP 312

Co-requisite: Nil

Exclusion: Nil

Objectives: To equip students with a foundational understanding of the threats to the Internet infrastructure security and the countermeasures. Students will be equipped to · understand and evaluate the current Internet infrastructure from the network security point of view; · acquire practical experience in implementing, setting up, and testing network security measures. Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) acquire a foundational understanding of the three cryptographic primitives: secret-key encryption, public-key encryption, and one-way hash functions; (2) understand the major security issues in implementing the four major security functions: secrecy, identity authentication, message authentication, and nonrepudiation; (3) understand the major security issues and problems in the TCP/IP protocol suite and the lower layers, and the countermeasures to mitigate the corresponding attacks; (4) acquire practical skills, such as setting up a secure private network using firewalls, secure tunnels, and end-to-end secure applications, implementing and/or integrating security functions, and assessment of system security; (5) understand the major threats to the Internet-wide security today, such as denial-of-service attacks and Internet worms. Attributes for all-roundedness (1) acquire critical and independent analytical skills in the process of analyzing the security problems in the Internet; (2) acquire the skill of synthesizing various security problems into a small set of fundamental security issues and solutions.

Syllabus: Topic 1. Preliminaries Types of attacks; threat model; the role of cryptography in network security. 2. Cryptographic functions and services Block cipher; block cipher modes; hash functions; message authentication

BSc (Hons) Scheme in Computing (FT/SAND) ­ Definitive Programme Document / Programme Booklet 2006/07

Duration of Class 3

6

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codes; a secure channel and the implementation issues. 3. Key negotiation and management Diffie-Hellman algorithm; RSA algorithm; key negotiation protocols; key management issues; Public Key Infrastructure. 4. IP and lower-layer security IP security and Internet key exchange protocols; routing security; wireless network security; quantum cryptography. 5. End-to-end security TCP security; Secure Socket Layer; examples of secure application protocols; e.g., Secure Shell, Kerberos, and Pretty Good Privacy. 6. Advanced topics Internet worms; denial-of-service; DDOS. Total Laboratory Experiment: Laboratory exercises for project. Case Study: Nil 12

6

6

9

42

Method of Assessment: Continuous Assessment Examination

60% 40%

Textbooks: 1. N. Ferguson and B. Schneier, Practical Cryptography, Wiley, 2003. Reference Books: 1. C. Adams and S. Lloyd, Understanding Public-Key Infrastructure, New Riders, 1999. 2. M. Bishop, Introduction to Computer Security, Addison Wesley, 2005. 3. S. Brands, Rethinking Public Key Infrastructures and Digital Certificates, The MIT Press, 2001. 4. J. Buchmann, Introduction to Cryptography, Springer, 2000. 5. D. B. Chapman and E. D. Zwicky, Building Internet Firewalls. Second Edition, O'Reilly & Associates, 2000. 6. W. Cheswick and S. Bellovin, Firewalls and Internet Security, Second Edition, Addison Wesley, 2003. 7. N. Doraswamy and D. Harkins, IPSec, Prentice Hall, 1999. 8. S. Flannery, In Code: A Mathematical Journey, Workman Publishing, 2000. 9. O. Goldreich, Foundations of Cryptography: Basic Tools, Cambridge University Press, 2001. 10. C. Kaufman, R. Perlman and M. Speciner, Network Security: Private Communication in a Public World, Second Edition, Prentice Hall PTR, 2002.

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11. S. Mann and E. Mitchell, Linux System Security, Prentice Hall PTR, 2000. 12. B. Schneier, Applied Cryptography, Second Edition, Wiley, 1996. 13. B. Schneier, Secrets and Lies, Wiley, 2000. 14. Journal articles and conference proceedings.

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SUBJECT DESCRIPTION FORM

Subject Title: Software Process and Project Management Subject Code: Number of Credits: 3 Hours Assigned: Lecture Tutorial/Sem

COMP 445 28 hours 14 hours

Pre-requisite: COMP 302

Co-requisite: Nil

Exclusion: Nil

Objectives: · To provide students a systematic approach to initiate, plan, execute, control and close a software project. · To develop a good understanding of the nine project management areas, and the role of a typical PM. · To equip students with understanding of the best practices, and techniques used in project management processes. · To enable students to gain a working knowledge of ISO 9000 and CMMI, and process improvement techniques. Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) appreciate the importance of software process and management; (2) apply project management techniques for information systems development; (3) Apply the management skills to monitor and control a software project; Attributes for all-roundedness (1) work together as a team in preparing a report; (2) communicate in writing a technical document; (3) communicate effectively in English for general project presentation.

Syllabus: Topic 1. Project management fundamentals Attributes of project; project life cycle; project management processes; successful project manager; general management skills. 2. Project integration management Project plan; change control; configuration management; corrective and preventive action; stakeholder analysis. 3. Project scope management Project charter; net present value; cost/benefit analysis; scope planning, definition, verification and change control. 4. Project time management Project size and metrics; identifying activities; WBS; PBS; CPA; scheduling;

BSc (Hons) Scheme in Computing (FT/SAND) ­ Definitive Programme Document / Programme Booklet 2006/07

Duration of Lectures 4

2

2

2

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critical chain. 5. Project cost management Estimation techniques; earned value analysis; COCOMO; resource planning; value analysis; cost management plan, budgeting and control. 6. Project quality management Quality model; quality definition; ISO 9001; CMMI; improvement cycle; trend analysis. 7. Human resource management Organization structure; team building; conflict; effective team; team meeting; reward and recognition systems. 8. Communication management Communication means; communication techniques for teams of different sizes; barriers to communication; building effective team communication; reviews; performance reporting. 9. Risk management Different types of risk; risk response planning; risk analysis; risk monitoring and control. 10. Procurement management Procurement planning; solicitation planning; solicitation; source selection; contract administration; contract closeout; negotiation. 11. Process improvement models Software process improvement tools and techniques. Total Laboratory Experiment: Nil Case Study: Case studies and projects are adopted for students to discuss and study the software process and management. Report writing and presentation is needed. 2

2

2

2

2

2

6 28

Method of Assessment: Continuous Assessment Examination 55% 45%

Textbooks: 1. Cadle, J., Yeates, D., Project Management for Information Systems, Prentice Hall, 2004. Reference Books: 1. A Guide to the Project Management Body of Knowledge, PMBOK Guide 2000 Edition, Project Management Institute, 2000. 2. Hughes, B., Cotterell, M., Software Project Management, McGraw-Hill, 1999. 3. Kerzner, H., Project Management, A systems approach to Planning, Scheduling, and Controlling, John Wiley &Sons, 2001.

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4. ISO standard. http://www.iso.ch 5. SEI. CMMI Tutorial, www.sei.cmu.edu/cmmi/publications/stc.presentations/tutorial.html

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SUBJECT DESCRIPTION FORM

Subject Title: Computational Finance Number of Credits: 3

Subject Code:

COMP 446

Hours Assigned: Lecture 24 hours Tutorial/Lab/Sem 18 hours

Pre-requisite: COMP 211, COMP 417

Co-requisite: Nil

Exclusion: Nil

Objectives: · To introduce the knowledge of financial models, quantitative methods and computational analysis techniques. · To demonstrate the methodologies for financial simulation and evaluation. Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) understand the fundamental concepts of financial engineering; (2) be aware of the computational tools for finance; (3) make reasonable judgment in choosing suitable computation model to solve problems in finance; (4) perform financial simulation and analysis; Attributes for all-roundedness (1) improve presentation and communication skills (through case study presentations); (2) learn independently and to find/integrate information from different sources required in solving real-life problems; (3) build up on team spirit, presentation and technical writing skills.

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Syllabus: Topic 1. Introduction to financial options Derivative; foreign exchange; random walks and Markov processes; Ito's lemma; Black-Sholes equations; hedging. 2. Computational tools for finance Numerical methods for PDEs; finite difference methods; Monte Carlo simulation; modeling tools for financial options. 3. Computational intelligence techniques for financial problems Prediction; forecasting; classification; technical analysis; artificial intelligence techniques; financial data mining and information retrieval. 4. Case studies Customer credit risk analysis; foreign exchange forecast, etc. Total Laboratory Experiment: Nil Case Study: Seminars are held for students to discuss in-depth real-life cases related to the subject's topics, to give presentations and write reports. Duration of Lectures 8

4

8

4

24

Method of Assessment: Continuous Assessment Case studies, tutorial exercises, project Examination 60%

40%

Reference Books: 1. Neftci, Salih, N., Principles of Financial Engineering, Academic Press, 2003. 2. Levy, G., Computational Finance: Numerical Methods for Pricing Financial Instruments, Elsevier, 2003. 3. Los, C.A., Computational Finance: A Scientific Perspective, World Science Publishing, 2001. 4. Rudiger Seydel, Tools for Computational Finance, Springer-Verlag, 2002. 5. Lavy, H., Levy, M. and Solomon, S., Microscopic Simulation of Financial Markets, Academic Press, 2003. 6. Articles from magazines, and journal references, including Asian Journal of Business and Information Systems, Journal of Computational Intelligence in Finance, Journal of Computational Finance.

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SUBJECT DESCRIPTION FORM

Subject Title: Scientific Computing Number of Credits: 3

Subject Code:

COMP 447 28 hours 14 hours

Hours Assigned: Lecture Tutorial/Lab

Pre-requisite: COMP 211, COMP 305 Nil

Co-requisite: Nil

Exclusion:

Objectives: · · · To provide an introductory survey of fundamental concepts in scientific computing. To demonstrate how scientific computing solves scientific and engineering problems. To equip students with sound skills in solving problems in scientific computing using a scientific computing programming language (e.g. MATLAB) or a professional technical programming language (e.g. C++).

Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) Understand the basic concepts of scientific computing; (2) apply scientific computing techniques in solving scientific and engineering problems; (3) appreciate the limitations of different scientific computing techniques; (4) write programs to implement scientific computing techniques; (5) Familiarize with a programming environment that supports scientific computing; (6) Be proficient in using the programming constructs for scientific computing; Attributes for all-roundedness (1) solve problems using systematic approaches; (2) learn independently and search for the information required in solving problems; (3) write technical reports and present the findings; (4) learn team working skills.

Syllabus: Topic 1. Scientific computing fundamentals Scientific computing overview; mathematical modeling; well-posed problems; approximations in scientific computing; error bounds; stability issues; computer arithmetic; time-space complexity. 2. Scientific computing software Mathematical software libraries; scientific computing environments. 3. Numerical linear algebra

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Duration of Lectures 4

2

4

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Solving linear equations; norms and condition numbers; orthogonal methods to solve linear least squares; eigenvalues and singular values; pseudoinverses. 4. Nonlinear systems Nonlinear equations in one dimension; systems of nonlinear equations. 5. Optimization One-dimensional optimization; multidimensional unconstrained optimization; nonlinear least squares; constrained optimization. 6. Integration and differential equations Finite difference approximations, automatic differentiation; initial value problems for ordinary differential equations; boundary value problems for ordinary equations; finite numerical quadratures; double and multiple integrals. 7. Partial differentiation Time-dependent problems; time-independent problems; direct methods for sparse linear systems; iterative methods. Total Laboratory Experiment: Duration of Laboratory 1. Programming for scientific computing (e.g. vector computation, matrix 4 computation, etc.). 2. Solving scientific problems using scientific computing techniques. 5 3. Solving engineering problems using scientific computing techniques. 5 Topic Total Case Study: Nil 14 4

6

4

4

28

Method of Assessment: Continuous Assessment - Assignment/Project - Classwork/Exercise - Laboratory work Examination 55% 25% 20% 10% 45%

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Reference Books: 1. M.T. Health, Scientific Computing: An Introductory Survey, 2nd ed., McGraw-Hill, 2002. 2. A. Quateroni and F. Saleri, Scientific Computing with MATLAB (Text in Computational Science and Engineering 2), Springer-Verlag, 2003. 3. J.S. Liu, Monte Carlo Strategies in Scientific Computing, Springer, 2002. 4. B. Lucqion and O. Pironneau, Introduction to Scientific Computing, John Wiley & Sons, 1998. 5. G.H. Golub and J.M. Ortega, Scientific Computing and Differential Equations: An Introduction to Numerical Methods, Academic Press, 1992.

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SUBJECT DESCRIPTION FORM

Subject Title: Virtual Reality and Applications Subject Code: COMP 448 Number of Credits: 3 Hours Assigned: Lecture Laboratory 28 hours 14 hours

Pre-requisite: COMP 407 438

Co-requisite: Nil

Exclusion: COMP 421, COMP

Objectives: This subject will provide students with: skills for generating 3D VR worlds; animation techniques; visualization and rendering techniques; virtual and augmented reality interfaces and devices; the principles of development for large VR worlds; dynamics and persistence for VR environments;. evolution and scalability of VR; virtual reality applications: 3D games, movies and special effects, GIS, aerospace, medicine, science and engineering applications Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) solve problems in 3D modeling for VR worlds; (2) understand illumination and light transport techniques for VR rendering; (3) understand the major problems in time and space sampling of 3D graphics; (4) implement a scalable rendering system; (5) understand the characteristics of visualizing physical and non-physical data; (6) develop and maintenance of large VR environments; (7) understand Augmented Reality and its applications. Attributes for all-roundedness (1) gain a new perspective on virtual reality, augmented reality and physically-based simulations as well as information visualization; (2) design and develop high quality visual applications that are required in all aspects of digital communication, representation and dissemination of data for scientific, engineering, medical and financial analysis; VR models, development, scalability, interaction and social impact.

Syllabus: Topic Duration of Lectures

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1. High performance computer graphics hardware support Computer graphics pipeline; image buffers; geometrical data streams; color management; programmable GPU; texture memory; display systems; image resolution; interactive control and event management. 2. Object space and image space sampling Device independent image representation; sampling; filtering; anti-aliasing techniques; object space discretization; surface sampling criteria; point-based representations; view mapping and projections; multi-phase object-space and image-space rendering. 3. Shape modeling and representation Point-based object representation; polygonal mesh representations; boundary surface representations and volumetric object and space partitioning; implicit and parametric shape representations; piece-wise continuous curves and surface patches; basis functions; subdivision schemes and scalability. 4. Physical light and color Achromatic light and intensity; illumination and dynamic range; physical light spectrum; colorimetry; color spaces and gamut mapping; color perception; advanced color models for VR rendering. 5. Scalable shape modeling and representation Large data representation and scientific visualization; structural information; multidimensional projections; representation of time and space; virtual reality with applications in science and engineering; medical diagnosis; geographic information systems; data flows and relational diagrams. Total Laboratory Experiment:

4

8

8

4

4

28

Laboratory exercises will normally be based on exercises and demonstration of the commonly available computer graphics API such as OpenGL. The students will be exposed to examples of shape modeling, rendering, animation and data visualization. Case Study: If applicable, case studies may be conducted on modeling and design systems that are used in commercial applications.

Method of Assessment: Continuous Assessment Examination 60% 40%

Suggested Reference Books: 1. S. Diehl, Distributed Virtual Worlds: Foundations and Implementation Techniques Using VRML, Java, and CROBA, Springer-Verlag, 2001. 2. Alan Watt and Fabio Policarpo, 3D Games - Real-time Rendering and Software Technology, Addison Wesley, vol. 1 and 2, 2001.

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3. Halimahtun M. Khalid (Editor), Virtual Reality: Select Issues & Applications (Hardcover), Asean Academic Pr Ltd (December 2000), ISBN: 1901919277 4. Alan Watt and Mark Watt, Advanced Animation and Rendering Techniques, Theory and Practice, Addison-Wesley, 1992. 5. Hill, F.S. Jr., Computer Graphics Using Open GL, Second Edition, Prentice Hall, 2001. 6. Watt, A., 3D Computer Graphics, Third Edition, Addison-Wesley, 2000. 7. Watt, A. and Policarpo, F. The Computer Image, Addison-Wesley, 1998. 8. John Vince, Essential Virtual Reality fast: How to Understand the Techniques and Potential of Virtual Reality, Springer-Verlag, 1998, ISBN: 1852330120 9. Michael Mortenson, Mathematics for Computer Graphics Applications: An Introduction to the Mathematics and Geometry of CAD/CAM, Geometric Modeling, Scientific Visualization, and Other CG Applications, Industrial Press, 1999. 10. Singhal, Sandeep and Zyda, Michael, Networked Virtual Environments - Design and Implementation, ACM Press Books, SIGGRAPH Series, 23 July 1999, ISBN: 0-20132557-8, 315 pages. 11. Michael Zyda and Jerry Sheehan (editors), Modeling and Simulation: Linking Entertainment & Defense, National Academy Press, September 1997, ISBN: 0-309-058422, 181 pages.

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SUBJECT DESCRIPTION FORM

Subject Title: Final Year Project Number of Credits: 9 hours

Subject Code: COMP 451 Hours Assigned: Staff Contact Self Work 40 hours 200

Pre-requisite: Nil

Co-requisite: Nil

Exclusion: COMP 401

Objectives: The final year project represents the most important ingredient in the undergraduate study, to provide a student the opportunities to apply knowledge acquired in the undergraduate study. It aims at developing and measuring the capabilities of a student in analyzing and solving complex and possibly real-case problems. Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) conduct literature survey to locate for materials and sources relevant to the selected problem area; (2) understand the materials obtained and connect the materials with the problem to be solved; (3) define and specify the problem precisely; (4) assimilate and apply the knowledge learnt in generating good solutions to the problem; (5) think critically the formulation of alternative models and solutions to the problem, in the analysis of approaches to the solution and their implementation; (6) evaluate the final outcome in an objective manner; Attributes for all-roundedness (1) develop critical thinking in general problem solving; (2) improve presentation and communicate skills via oral presentation; (3) enhance technical report writing skills with proper organization of materials; (4) develop the ability to learn independently and to find/integrate information from different sources required in solving real-life problems; (5) manage the project efficiently and effectively through the assistance and supervision of the supervisor.

Project Management: The calendar duration of the project spreads over the final year of the curriculum and extends normally from September to April. The total man-effort required is approximately 40 hours of staff contact and 200 hours of laboratory work and independent study for a normal student, which includes the total time spent on literature search, background reading, fact finding, project development, and report writing. The actual amount of time spent may vary for individuals. Projects are normally sponsored by academic staff of the department or in

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conjunction with external organizations or other departments in the university. However, a student may propose a topic which forms an extension of his/her work during industrial placement, or an area of his/her own research interest contingent upon the condition that he/she could find an interested academic staff to supervise the project. A typical research process to the final year project is as shown:

Projects should be problem-oriented and there is no restriction to the nature of the problem except that it should be relevant to the computing discipline and there must be a computing element in the project. The project could be practical, academic or a hybrid in which the student is encouraged but not constrained to have some original contributions. The student has to submit a proposal, a mid-term checkpoint progress report and a final report throughout the academic year for the final year project. The proposal must be approved by the supervisor before the student can proceed to the final year project. A rejected proposal must be rewritten and resubmitted. An oral presentation and demonstration is essential at the end of the project. If deemed appropriate, mid-term presentation may be held. At or before the beginning of the academic year, each student will be assigned a supervisor who is in charge of the entire project. The assignment of supervisor normally follows a set of prescribed procedures, announced a few months before the academic year. The supervisor is responsible for assessing the student based on the set of abilities, as laid down in the "objectives" and "learning outcome" sections above, that the student demonstrated. The deliverables required from a student are: an Initial Proposal, a Mid-term Checkpoint Progress Report, and a Final Report. The deadlines for these are normally week 4, week 14 and week 28 of year 4 respectively. At the end of year 4, there will be an oral presentation and demonstration which will normally be conducted during week 29 to 31. There is no limitation as the content of these deliverables except that the initial proposal should include the original problem definition while the final report should include the initial proposal. The check point progress report should be limited to two pages and signed by the supervisor if he/she approves and agrees with the content of the progress report. Late submission of these reports is construed as a lack of self discipline and good project management skill on the part of the student who should be penalized accordingly unless the student could give a reasonable justification such as on the ground of valid medical reasons.

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Method of Assessment: Continuous Assessment Supervisor Co-examiner

100% 75% 25%

There will be an oral presentation of the projects. The presentation lasts for 30 minutes, including demonstration and question/answer session. The supervisor and co-examiner will score according to the following indicative criteria and weightings. However, the project evaluation will be based on a holistic approach. For instance, an eventually good project with poor self-discipline and lack of consistent progress will not be awarded the grade A. Supervisor 15% 40% 10% 10% Co-examiner 5% 10% 10% 0%

Problem Identification (literature search) Problem Solving (critical thinking) Communication and Presentation (Demonstration and Reports) Project Management and Self-Discipline

The major criteria are standardized for ease of management and fairness to all. However, the supervisor and co-examiner could refine a certain criterion in terms of detailed breakdown. Because of the different degrees of involvement, the co-examiner will be responsible for 25% of the marks based on the first three criteria only while the supervisor will contribute to 75% of the marks in terms of all four. Technically, the supervisor would liaise with the co-examiner on the expected results of the project and should provide an independent assessment of the project based on the criteria of their concern. In principle, they should arrive at an agreed overall final grade if no major discrepancies arise. In addition, internal moderators will be appointed to moderate the projects. This often takes the form of a judging (and arbitration) panel to consider all projects with high and low grades for fairness and quality assurance for their final grades, and to recommend best FYP award candidates. The panel also helps to resolve any disagreement between supervisor and co-examiner. Some other projects may also be moderated so as to even out any undue differences.

Reference Books: 1. Burns, R.B. Introduction to Research Methods, Third Edition, Longman, 1997. 2. Kumar, R. Research Methodology: A Step-by-step Guide for Beginners, Longman, 1996. 3. Mauch, J.E., Park, N. Guide to the Successful Thesis and Dissertation: A Handbook for Students and Faculty, Fifth Edition, Marcel Dekker, 2003. 4. Rudestam, K.E., Newton, R.R. Surviving Your Dissertation: A Comprehensive Guide to Content and Process, Second Edition, Sage Publications, 2001. 5. Roberts, C.M. The Dissertation Journey: A Practical and Comprehensive Guide to Planning, Writing, and Defending Your Dissertation, Corwin Press, 2004. 6. Garson, G.D. Guide to Writing Empirical Papers, Theses and Dissertations, Marcel Dekker, 2002. 7. Oshima, A. Writing Academic English, Third Edition, Addison-Wesley Longman, 1999. 8. APA. Publication Manual of The American Psychological Association, Fifth Edition, American Psychological Association, 2001. 9. Szuchman, L.T. Writing with Style: APA Style Made Easy, Brooks/Cole, 1999. 10. Statistics, simulation, programming, and relevant books. 11. ACM and IEEE magazines, Transactions and Journals.

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12. Other International Journals. 13. Relevant conference proceedings and magazines (including ACM and IEEE conferences). 14. Technical reports from universities and major companies.

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SUBJECT DESCRIPTION FORM

Subject Title: Computing Professionals in Society Number of Credits: 3

Subject Code: COMP 452

Hours Assigned: Lecture 28 hours Tutorial/Seminar 14 hours

Pre-requisite: Nil 427

Co-requisite: Nil

Exclusion: COMP 402,

Objectives: The general objective is to understand the social responsibilities of the computing professionals, because they hold a very powerful position in society. To be addressed in particular are professionalism and computer ethics. This means (i) identifying correctly the potential for an ethical problem in a particular context, the moral rules that might be compromised, and the cause of these issues; (ii) being aware of the responsibilities with respect to ethical issues in human activities affected by computers; (iii) deciding on courses of action and recommend changes to prevent recurrence of those events; and (iv) communicating well-informed opinions based on fact in a well-reasoned professionally competent way. There is another objective which is to develop students' ability to analyze the fact and to communicate well in writing and orally because only well-informed opinions based on fact and presented in a well-reasoned professionally competent way are acceptable. This makes the writing intensive side of this course, which emphasizes clear written expression. The third objective is to participating in class discussion as well as taking quizzes and completing a number of written assignments, since opinions can be changed, and improved, through thoughtful discussion so that students are expected to come to class well-prepared. Student Learning Outcomes: After taking this subject, the students should be able to: Professional/academic knowledge and skills (1) be aware of the ethical issues surrounding computers; (2) heighten their sensitivity to ethical issues in the use of computers and in the practice of the computer profession, so that they are more likely to see issues and respond appropriately; (3) apply the conceptual tools provided in the course to develop analytical skills for determining what to do in ethical decision making or what the likely impacts the computer will have in this or that context; and (4) work alone or in groups to arrive at ethical decisions. Attributes for all-roundedness (1) communicate effectively (both in Chinese and English) verbally at a level sufficient for project and system presentation, as well as general conversation; (2) communicate effectively in writing with technical documents and reports; (3) learn independently for problem solving and solution seeking; (4) collaborate with other team members for project design and development, while exhibiting leadership in a project team whenever designated or necessary;

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(5) think and reason in a critically, especially on different issues related to computing professional in the society. Syllabus: Topics 1. Overview 2. Why computer ethics? Policy issues Social context Moral and legal considerations Is computer ethics unique? 3. What is Computer ethics? Traditional/philosophical ethics Computer ethics 4. Critical thinking and ethical arguments 5. Professionalism Characteristics of a profession The system of professions Is computing a profession? Professional ethics Code of ethics and professional conduct 6. Ethical and social analysis Elements of analysis Skills of analysis 7. Accountability and responsibility Accountability Responsibility Buying/selling software Other issues 8. Ownership Rights Legal protection Philosophical basis Consequentialist argument 9. Privacy Personal privacy Computer and privacy Privacy legislation 10. Intellectual property Software as intellectual property Property rights Intellectual property protection Copyright 11. Social issues Digital divide Employment and work Quality of Work-life

Lecture 2 hrs

Tut/Sem 1 hrs

4 hrs

2 hrs

2 hrs 2 hrs

1 hrs 1 hrs

6 hrs

3 hrs

2 hrs

1 hrs

2 hrs

1 hrs

2 hrs

1 hrs

2 hrs

1 hrs

4 hrs

2 hrs

Total 28 hrs Laboratory Experiment: Nil Guest Speakers:

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14 hrs

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Guest speakers are invited to discuss and share with students the state-of-the-art developments and opinions in the topics.

Method of Assessment: The course will be conducted both as a seminar and a lecture. Students are expected to read and understand the ideas in the reading, explain the ideas, analyze issues and see them from diverse perspectives, and formulate and critique arguments. Therefore, students are required to demonstrate this in class discussion and in written assignments. Quizzes will be given that aim at determining the student's grasp of the materials learned. Continuous Assessment Class participation Quizzes Scenarios analysis and response Project 100% 10% 50% 20% 20%

Main Text: 1. Johnson, D.G., Computer Ethics (3rd edition),Prentice Hall, 2001 Reference books: 2. Quinn, M.J., Ethics for the Information Age, Addison Wesley, 2005 3. Tavani, H.T., Ethics and Technology, John Wiley &Sons, 2004 4. Kallman, E.A. & Grillo, J.P., Ethical Decision Making and Information Technology, McGraw-Hill, 1993 5. Bynum, T.W. & Rogerson, S., Computer Ethics and Professional Responsibility, Blackwell Publishing, 2004 Supplementary Reading: 6. Spinells, R.S. & Tavani, H.T., Readings in CyberEthics, Jones & Bartlett Publishers, 2004 7. Journal papers and press reports of current interest will be assigned as required and available

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SUBJECT DESCRIPTION FORM

Subject Title: Advanced Internet Technologies and Applications Subject Code: EIE406 (for42077, 61020 and 61031) Number of Credits: 3 Hours Assigned: Lecture/Tutorial 36 hours Laboratory 6 hours (Equivalent to 18 laboratory hours)

Pre-requisite: For 42077 Co-requisite: nil Exclusion: Computer Networking and Internet Technologies (EIE323) For 61024 and 61031 nil

nil

Objectives: Based on the already acquired basic knowledge about the Internet, this subject introduces to the students the principles, protocols and performance evaluation techniques of various advanced Internet technologies such as next generation Internet, multimedia protocols, Quality of Service and mobile IP. Student Learning Outcomes: On successful completion of this subject, the students will be able to: Category A: Professional/academic knowledge and skills 1. Understand the current state-of-the-art developments in Internet technologies and applications. 2. Understand the development of next generation Internet. 3. Appreciate the principles used in designing Internet protocols, and so understand why standard protocols are designed the way that they are. 4. Be able to solve problems and design simple Internet applications. Category B: Attributes for all-roundedness 5. Think critically. 6. Learn independently. 7. Work in a team and collaborate effectively with others. 8. Present ideas and findings effectively.

Syllabus: 1. IP Routing and Label Switching IP addresses and subnet masks; Distance-vector and Link-State routing; Routing Information Protocol (RIP) and Open Shortest Path First (OSPF) protocol; Classless Interdomain Routing (CIDR); Source Routing; Label Switching; IP Switching, IP forwarding: longest-prefix match.

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2. IP version 6 Addressing; IPv6 Datagram; Comparison of IPv4 and IPv6; Extension Headers; ICMP, TCP/UDP; IPv6 Routing. 3. TCP Performance and Congestion Control TCP performance modeling; Congestion control: slow start, congestion avoidance, fast retransmit and fast recovery. 4. Multimedia Protocols IP Multicasting; Internet Group Management Protocol (IGMP); Real Time Protocol (RTP) and RealTime Control Protocol (RTCP); Resource Reservation Protocol (RSVP). 5. Quality of Services in IP networks Integrated and differentiated services. Protocols for QoS support. Multi-protocol label switching (MPLS). 6. Mobile IP Mobile IP architecture and services; Agent Discovery; Router Discovery Protocol; Agent Advertisement; Registration; Security; Foreign Agents and Home Agents; Broadcasting and Multicasting. 7. Selected Topics in Internet Applications Voice-over-IP (VoIP): Business model, architecture, standards. Multimedia Streaming: Streaming protocols, RTSP. Laboratory Experiment/Mini-Project: 1. 2. 3. 4. 5. 6. Study of TCP congestion control Study of multimedia traffic on the Internet Multimedia streaming Quality of service on the Internet Performance evaluation of a multimedia communication system Voice over IP

Method of Assessment: Coursework: 40% Examination: 60%

Reference Books: 1. J.F. Kurose and K.W. Ross, Computer Networking: A Top Down Approach Featuring the Internet, Addison Wesley, 3rd ed., 2005. 2. U. Black, Advanced Internet Technologies, Prentice-Hall, 1999. 3. S.A. Thomas, IPng and the TCP/IP Protocols: Implementing the Next Generation Internet, Wiley Computer Publishing, John Wiley & Sons, Inc, 1996. 4. D.E. Comer, Computer Networks and Internets, Prentice-Hall international Inc., 3rd ed., 2001.

Alignment of Teaching and Learning (T&L) Methods with Learning Outcomes: T&L Method Outcome Remarks

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Lectures Tutorials

numbers 1,2,3,4 1,2,3,4,5

Laboratory sessions

4,5,6,7,8

Fundamental principles and key concepts of the subject are delivered to students. Supplementary to lectures and are conducted with smaller class size; Students will be able to clarify concepts and to have a deeper understanding of the lecture material; Problems and application examples are given and discussed. Students will have practical work on various Internet technologies and applications.

Alignment of Assessment and Learning Outcomes: Assessment Method Assignments, tests and examination Learning Outcome 1,2,3,4 Remarks End-of chapter type problems used to evaluate students' ability in applying concepts and skills learnt in the classroom. Students need to think critically and creatively in order to come with an alternate solution for an existing problem. Each group of students is required to produce written reports. For some of the practical works, students are required to make demonstration to illustrate their understanding of the related technical knowledge and skills.

Laboratory sessions, mini-project

4,5,6,7,8

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SUBJECT DESCRIPTION FORM

Subject Title: Distributed Systems and Network Programming

Subject Code: EIE424 (for 42070, 42077, 42078, 61024, 61031 and 05005) Hours Assigned: Lecture/Tutorial 36 hours Laboratory 6 hours (Equivalent to 18 laboratory hours)

Number of Credits: 3

Pre-requisite: For 42070 Co-requisite: nil Object Oriented Design and Programming (EIE320) For 42077 Principles of Programming (COMP201) or Object Oriented Design and Programming (EIE320) For 61024 and 61031 Principles of Programming (COMP201)

Exclusion: nil

Objectives: This subject will provide students with the principles and practical programming skills of developing distributed systems. It enables students to master the development skill for providing distributed services on the Web. Through a series of lab exercises, students will have the chance of developing interoperable and distributed Web applications. Student Learning Outcomes: On successful completion of this subject, the students will be able to: Category A: Professional/academic knowledge and skills 1. Understand the enabling technologies for building distributed systems. 2. Understand the different components for developing Web Services. 3. Set up and configure a standard Web Service system and develop simple Web Service applications. Category B: Attributes for all-roundedness 4. Think critically. 5. Learn independently. 6. Work in a team and collaborate effectively with others. 7. Present ideas and findings effectively.

Syllabus: 1. Introduction to Distributed Systems 1.1 Characteristics. Design goals. Architecture examples. 2. Enabling Tools and Techniques for Building Distributed Systems 2.1 Networked Computing TCP/IP protocol suite. Socket programming. 2.2 Component-based Software Development

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Component models. JavaBeans; CORBA; Remote Method Invocation (RMI); OM/DCOM; Enterprise JavaBeans (EJB). 2.3 Extensible Markup Language (XML) XML Markup; parser; CDATA sections; XML namespaces. Document Type Definition (DTD); well-formed XML documents; document type declaration; element of type declarations; attribute declarations. 3. Distributed Services on the Web: Web Services 3.1 Introduction to Web Services. 3.2 Simple Object Access Protocol (SOAP): SOAP specification; message processing; use of namespaces. 3.3 Web Services Description Language (WSDL): Role of WSDL in Web services, WSDL documents, remote web-services invocation using WSDL. 3.4 Universal Description, Discovery and Integration (UDDI): role of UDDI in Web services; UDDI registries; discovery technologies. Laboratory Experiment: Practical Works 1. Remote Method Invocation (RMI) 2. Extensible Markup Language (XML) 3. XML-RPC 4. SOAP 5. WSDL 6. UDDI

Method of Assessment: Coursework: 40% Examination: 60%

The continuous assessment consists of assignments, laboratory reports and tests.

Textbooks: 1. 2. M.L. Liu, Distributed Computing: Principles and Applications, Addison-Wesley, 2003. C. Ethans, Web Services Essential, O. Reilly, 2002.

Reference Books: 1. 2. 3. 4. R. Nagappan, Developing Java Web services : Architecting and Developing Secure Web services using Java, Wiley Pub., 2003. U. Wahli, G.G. Ochoa, S.Cocasse, and M.Muetschard, Websphere Version 5.1 Application Developer 5.1.1 Web Services Handbook, IBM, 2nd ed., 2004. P. Pacheco, Parallel Programming with MPI, Morgan Kaufmann, 1998. S. Graham, etal, Building Web Services with Java, Sams, 2nd ed., 2004.

Alignment of Teaching and Learning (T&L) Methods with Learning Outcomes: T&L Method Outcome numbers Remarks

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Lectures PISER

1, 2 1, 2

Tutorials

1, 2

Laboratory sessions

3,4,5,6

Fundamental principles and key concepts of the subject are delivered to students. Students' knowledge on/understanding of certain topics can be easily estimated, and the corresponding teaching time will be adjusted accordingly. Supplementary to lectures and are conducted with smaller class size; Students will be able to clarify concepts and to have a deeper understanding of the lecture material; Problems and application examples are given and discussed. Students will go through the development process of various distributed systems and evaluate their performance.

Alignment of Assessment and Learning Outcomes: Assessment Method Assignments, tests and examination Learning Outcome 1,2,3 Remarks End-of chapter type problems used to evaluate students' ability in applying concepts and skills learnt in the classroom. Students need to think critically and creatively in order to come with an alternate solution for an existing problem. Each group of students is required to produce written reports. For some of the practical works, students are required to make demonstration to illustrate their understanding of the related technical knowledge and skills.

Laboratory sessions, mini-project

3,4,5,6

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SUBJECT DESCRIPTION FORM

Subject Title: Corporate Networking Number of Credits: 3

Subject Code: EIE429 (for 42077) Hours Assigned: Lecture/tutorial 39 hours Laboratory 3 hours (Equivalent to 9 laboratory hours)

Pre-requisite: nil Co-requisite: nil Exclusion: Corporate Communication Networks (EIE439)

Objectives: Telecommunication and computer networking technologies have been advancing rapidly in recent years. New technologies have been developed, and new economic orders have been built. Against this background, this subject is designed to: 1. Give a practical treatment on the design, implementation and management of multinational corporate networks. 2. Introduce the variety of facilities, technologies and communication systems to meet future needs of network services. 3. Discuss in details network planning, management, marketing, performance and security issues. 4. Evaluate critically the performance of existing and emerging global communication networking technologies and their impact on enterprise and world economy. Student Learning Outcomes: On successful completion of this subject, the students will be able to: Category A: Professional/academic knowledge and skills 1. Describe the operational, marketing, functional attributes of different components of enterprise networks [1,2] 2. Evaluate critically the design, implementation, and performance of enterprise networks with regard to different criteria [1,3,4] 3. Design enterprise networking solutions by taking into account various constraints and requirements [1,2,3] Category B: Attributes for all-roundedness 4. Develop a global outlook by recognizing the effect of advancement in communication technologies on business opportunity and world economic, social and cultural development [4] 5. Think and evaluate critically [3,4] 6. Take up new technology for life-long learning [2,4] 7. Present ideas and findings effectively [3] 8. Work in a team, and collaborate effectively with other members [4]

Syllabus: 1. Communication Networks and their Features

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Global networks, enterprise networks, private networks, network topology and optimization, network evolution strategy. 2. Protocols and Technologies WAN protocols, Virtual Local Area Network, IP Switching and MPLS, Metro Ethernet WAN, Voice over IP, Softswitch. 3. Network Security Cryptography, firewall, IP Security, Virtual Private Network (VPN). 4. Traffic Theory and Marketing Teletraffic theory, tariff and cost analysis, deregulations. Laboratory Experiments: 1. Voice over IP experiment and softswitch. 2. Virtual Private Network and IP Security. 3. LAN switching management.

Method of Assessment: Continuous Assessment: 50%

Examination: 50%

Textbook: 1. V. Theoharakis, Enterprise Networking: Multilayer Switching and Applications, Idea Group Pub., 2002. Reference Books: 1. Housel, Thomas J., Global Telecommunications Revolution: The Business Perspective, McGraw-Hill/Irwin, 2001. 2. R.R. Panko, Corporate Computer and Network Security, Prentice-Hall, 2004. 3. D. Cameron, Global Network Security: Threats and Countermeasures, Computer Technology Research Corp., 2000. 4. Handbook of Telecommunications Economics, Amsterdam; Boston, Mass. : Elsevier, 2002. 5. M. Mueller, Telecom Policy and Digital Convergence, City University of Hong Kong Press, 1997. 6. Global Networks, Linked Cities, Routledge, 2002. 7. Jean-Jacques, Competition in Telecommunications, MIT Press, 2000. 8. D. Minoli, Enterprise Networking: Fractional T1 to SONET, Frame Relay to BISDN, Artech House, 1993.

Alignment of Teaching and Learning (T&L) Methods with Learning Outcomes: T&L Method Lectures, supplemented with interactive questions and answers, and short quizzes Outcome numbers 1,2 Remarks In lectures, students are introduced to the knowledge of the subject, comprehension is strengthened with interactive Q&A and short quizzes. They will be able to explain and generalize complex structure of knowledge (e.g. relationship between different players in the telecommunication market) In tutorials, students apply what they have learnt in analyzing the cases and solving the problems given

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Tutorials where case studies are conducted,

3,5,6

BSc (Hons) Scheme in Computing (FT/SAND) ­ Definitive Programme Document / Programme Booklet 2006/07

and problems are given to students for them to solve

Three laboratory exercises, where students will perform hands-on tasks in different topics. After the laboratory, they will have to write a report to reflect on what they have learnt and the experience and knowledge they have derived. Assignment and Homework, solving endof-chapter problems

4-8

by the tutor. They will analyze the given information, compare and contrast different scenarios (e.g. the pros and cons of using different networking technologies in different situations) and propose solutions or alternatives. Students perform hands-on tasks in laboratory to either strengthen what they have learnt or explore new frontiers. They will be able to synthesize a structure of knowledge by designing and planning the tasks, and relate the observation to theories and principles. They will also evaluate outcomes of the tasks they perform and interpret the data they gather (e.g. the security features afforded by VPN routers, and their pros and cons).

1-6

Through working assignment and homework, and end-of-chapter problems in text books, students will develop a firm understanding and comprehension of the knowledge taught. They will analyze given information and apply knowledge in solving problem. For some design type of questions (e.g. designing an Intranet for a company), they will have to synthesize solutions by evaluating different alternatives.

Alignment of Assessment Strategies with Learning Outcomes: Assessment Methods Assignment/Homework/ Case study reports Learning Outcome 1-6 Remark Assignment/Homework and case study reports are given to students to assess their competence level of knowledge and comprehension, ability to analyze given information, ability to apply knowledge and skills in new situation, ability to synthesize structure, and ability to evaluate given data to make judgment. The criteria (i.e. what to be demonstrated) and level (i.e. the extent) of achievement will be graded according to six levels: (A+ and A), Good (B+ and B), Satisfactory (C+ and C), Marginal (D) and Failure (F). These will be made known to the students before an assignment/homework is given. Feedback about their performance will be given promptly to students to help them improvement their learning. Students will be required to perform three laboratory works and write three laboratory reports. The emphasis is on assessing their ability to apply, synthesize and evaluate. Expectation and grading criteria will be given as in the case of assignment/homework.

Laboratory works and reports

4,5,6

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Mid-semester test

1-6

End-of-semester test and Examination

1-6

There will be a mid-semester test to evaluate students' achievement of all the learning outcomes and give feedback to them for prompt improvement. Expectation and grading criteria will be given as in the case of assignment/homework. There will be an end-of-semester test and examination to assess students' achievement of all the learning outcomes. These are mainly summative in nature. Expectation and grading criteria will be given as in the case of assignment/homework.

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SUBJECT DESCRIPTION FORM

Subject Title: Cellular Communication Systems Number of Credits: 3

Subject Code: EIE445 (for 42077, 61024 and 61031) Hours Assigned: Lecture/Tutorial 36 hours Laboratory 12 hours

Pre-requisite: For 42077 Co-requisite: nil Telecommunication Technologies (EIE325) For 61024 and 61031 Analogue and Digital Communications (EIE218) Exclusion: Mobile Communications (EIE447)

Objectives: This subject aims at introducing to the students the knowledge about digital cellular communication systems and wireless communication networks. It is primarily focused on the applications, but to understand these properties requires a look at the underlying of wireless technologies. Student Learning Outcomes: On successful completion of this subject, the students will be able to: Category A: Professional/academic knowledge and skills 1. Describe the multiple access methods, FDMA, TDMA and CDMA. 2. Understand the basic principles of different cellular systems and the spectrum efficiency considerations. 3. Understand the enabling technologies for wireless networks including IEEE802.11a and IEEE 802.11b standards. 4. Understand the wireless systems and standards of Global System for Mobile (GSM) and Code Division Multiple Access (IS-95). Category B: Attributes for all-roundedness 5. Think critically. 6. Learn independently. 7. Work in a team and collaborate effectively with others. 8. Assimilate new technological and development in related fields.

Syllabus: 1. Overview of Multiple Access Techniques 1.1 Introduction to multiple access. 1.2 Frequency division multiple access (FDMA). 1.3 Time division multiple access (TDMA). 1.4 Code division multiple access (CDMA).

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1.5 Cellular system design and spectrum efficiency 1.6 Packet radio, ALOHA, slotted-ALOHA, CDPD, PRMA. 2. Wireless Networking 2.1 Introduction to wireless networks. 2.2 Merging wireless networks and public switched telephone network (PSTN). 2.3 Traffic routing in wireless networks. 2.4 Wireless data services, signaling system No. 7(SS7). 2.5 Protocols for network access. 2.6 IEEE 802.11 standard 3. Global System for Mobile Communications (GSM) 3.1 GSM system architecture. 3.2 Linear predictive coder, GSM codec. 3.3 Burst, interleaving and channel coding, ciphering, GMSK modulation. 3.4 Network management, radio resource management. 3.5 Mobility and security management, network operations. 4. Code Division Multiple Access(CDMA) Cellular Standard (IS-95) 4.1 Walsh functions, direct sequence spreading, long code generation. 4.2 Access channel, reverse channel, forward channel. 4.3 Power control, near-far effect, interference in the reverse link and forward link, pseudonoise code sequences. 4.4 Optimum receiver, rake receiver, interference canceller. 4.5 Capacity of CDMA cellular system. Laboratory Experiment: Practical Works 1. Quadrature Phase Shift Keying (QPSK). 2. Noise in Digital Communication Systems. 3. Simulation of GMSK transmitter. 4. Simulate reverse channel Interference in a one cell reuse CDMA System.

Method of Assessment: Coursework: 40% Examination: 60%

Textbooks: 1. 2. V.K. Garg, IS-95 CDMA and CDMA2000, Prentice-Hall, 2000. V.K. Garg and J. Wilkes, Principles and Applications of GSM, Prentice-Hall, 2000

Reference Books: 1. 2. 3. 4. 5. 6. V.K. Garg and J. Wilkes, Wireless and Personal Communications Systems, Prentice-Hall, 1996. R. Prasad, CDMA for Wireless Personal Communications, Artech House, 1996. S. Redl, M. Weber, and M. Oliphant, An Introduction to GSM, Artech House, 1995. D.J. Goodman, Wireless Personal Communications Systems, Addison-Wesley, 1997. T.S. Rappaport, Wireless Communications: Principles and Practice, Prentice-Hall, Inc., 1996. J.A. Viterbi, CDMA: Principles of Spread Spectrum Communication, Addison-Wesley, 1995.

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Alignment of Teaching and Learning (T&L) Methods with Learning Outcomes: T&L Method Lectures PISER Outcome numbers 1, 2 1, 2 Remarks Fundamental principles and key concepts of the subject are delivered to students. Students' knowledge on/understanding of certain topics can be easily estimated, and the corresponding teaching time will be adjusted accordingly. Supplementary to lectures and are conducted with smaller class size; Students will be able to clarify concepts and to have a deeper understanding of the lecture materials; Problems and application examples are given and discussed. Students will go through the development process of various mobile communication systems and evaluate their performance.

Tutorials

1, 2

Laboratory sessions

3,4,5,6

Alignment of Assessment and Learning Outcomes: Assessment Method Assignments, tests and examination Learning Outcome 1,2,3 Remarks End-of chapter type problems used to evaluate students' ability in applying concepts and skills learnt in the classroom. Students need to think critically and creatively in order to come with an alternate solution for an existing problem. Each group of students is required to produce written reports. For some of the practical works, students are required to make demonstration to illustrate their understanding of the related technical knowledge and skills.

Laboratory sessions, mini-project

3,4,5,6

BSc (Hons) Scheme in Computing (FT/SAND) ­ Definitive Programme Document / Programme Booklet 2006/07

Page 210

Information

Credit-Based B.A.(Hons) in Computing

214 pages

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