UNIVERSITY OF DAR ES SALAAM

COLLEGE OF INFORMATION AND COMMUNICATION TECHNOLOGIES

DEPARTMENT OF COMPUTER SCIENCE AND ENGINEERING

Curriculum for MSc in Computer and IT Systems Engineering

Degree Programme

June 2016

i 

EXECUTIVE SUMMARY

ES1: The drive to make Tanzania a middle income country clearly depends on having reliable, efficient and affordable electrical power supply for industries, services and households. The College observed that there are a number of challenges in realizing a reliable power source due to management, monitoring and controlling challenges because the power system network is very extensive extending to rural areas where accessibility may be a problem. To that effect the College has developed a taught MSc in Computer and IT Systems Engineering degree programme to build capacity in Smart Grid for electric power system, noting that the smart grid area needs wide-ranging competences.

ES2: The College of ICT received funding for five years effective 2015 from Sida to facilitate

preparation of the curriculum and to sponsor eight (8) MSc. students to the project. ES3: The main objective of the MSc in Computer and IT Systems Engineering programme is

to provide graduates with a comprehensive coverage of the skills required by an engineer working in instrumentation, electronic systems, and hardware and software aspects of computer engineering. The programme provides an excellent basis for engineers wishing to update their knowledge as well as for students who wish to go on to do research.

ES4: The programme is designed to integrate research, innovation and education by

incorporating the project-based-learning approach in its programme to enhance integration of the University with industry and society in order to enhance technology and knowledge transfer.

ES5: The programme is considered as an implementation of the Tanzania Development Vision

2025, which advocates having a well-educated and learning society in order to meet the challenges of development. Computer and IT Systems Engineering is one of the sectors which play a very vital role in the economy of a country. The programme will therefore contribute towards the country’s economy by increasing the number and quality of computer and IT systems managers in organizations.

ES6: The new programme also responds to the UDSM vision 2061 and mission.

ES7: The programme is a twenty four months (24) if taken in evening mode and eighteen months (18) if taken in regular mode, leading to the award of MSc in Computer and IT Systems Engineering. For Regular mode, the courses have been arranged to cover the first year, and the first six months of the second year are devoted to a dissertation project. For evening mode, the courses have been arranged to cover the first year, and the second year is devoted to a dissertation project.

ES8: The programme is organized around a number of core and elective courses in Computer Science, Computer Engineering, Electronics Engineering and mathematics with the aim

ii 

of preparing students to pursue careers in academia, research or highly technical entrepreneurial innovation.

ES9: Upon completion of the programme, graduates will be able to innovate, develop, direct, coordinate and technically manage projects, through integration of computer science, computer engineering and electronics engineering broader knowledge in multidisciplinary contexts.

ES10: To be eligible for admission into this programme, the student should satisfy the general University minimum requirements with the following additional requirements:

a) Direct Entry Qualification

UQF level 8 with background in ICT related undergraduate programmes or Electrical Engineering related Programmes which includes ICT courses with at least a second class degree with minimum GPA of 2.7 out of 5 from institutions recognized by TCU.

Candidates with pass degrees may also be considered for admission if: i. Their undergraduate performance in the subject of study was a B grade or

higher; ii. They have satisfied UDSM regarding their academic potential through

subsequent research experience and/or additional training.

b) Equivalent Entry Qualification

A Postgraduate Diploma in ICT related programmes or Electrical Engineering related Programmes which includes ICT courses from a respected institution recognized by TCU or equivalent with at least an upper second class B+ award with minimum GPA of 3.5 out of 5. Candidates with equivalent qualifications must also possess at least advanced secondary school certificates with principal passes in both Physics and Mathematics.

ES11: Assessment of the courses shall follow the UDSM and CoICT examination regulations as approved by Senate. UDSM regulations governing the award of postgraduate degree in the CoICT shall also apply.

ES12: Course codes in the programme will be using two letters followed by three digits according to the University coding format. The first digit denotes level of degree award (here referred to MSc), the middle digit denotes major specialization and the last digit denotes serial course number. New courses will use "CS"- Computer Science code, while adopted courses will use existing codes. If new courses are from different departments, then the codes for that department will be used (such as TE, ES, etc).

ES13: The MSc in Computer and IT Systems Engineering degree programme will require a student to complete a minimum of 180 credits, 156 of which are core courses, which include 60 credits for dissertation. The student will be required to take a minimum of 24 credits from the list of elective courses.

iii 

ES14: The department has adequate number of academic staff who are currently teaching computer science and engineering courses.

ES15: The College of Information and Communication Technologies has five computer laboratories shared by all Colleges’ departments. Of these, four computer laboratories have a capacity of 30 students each, while one laboratory has a capacity of up to 50 students.

ES16: From the rehabilitation of Kijitonyama campus, a lecture room with a seating capacity of more than 1,200 has been realized. This space is adequate to accommodate all CoICT programmes’ lectures and also for the planned enrolment expansion.

ES17: Most of the required laboratory equipment has been purchased under the World Bank (WB) project. Costs for additional facilities and consumables will be covered from the warrant of funds.

ES18: The curriculum has indicated a number of recommended textbooks needed for each course which will have to be purchased and put in the College library. The curriculum has also indicated a number of software packages required for teaching of courses, some of which will have to be purchased.

iv 

Table of Contents

EXECUTIVE SUMMARY ........................................................................................................ i Table of Contents ...................................................................................................................... iv LIST OF TABLES .................................................................................................................... vi LIST OF ABBREVIATIONS AND ACRONYMS ............................................................... viii 1.  INSTITUTIONAL PROFILE............................................................................................. 1 

1.1  Name of Institution...................................................................................................... 1 1.2  Cluster of Institution.................................................................................................... 1 1.3  Nature of the Provider ................................................................................................. 1 1.4  Programme Host Department ...................................................................................... 1 1.5  Head of Department and His/Her Address .................................................................. 1 1.6  List of Programmes That Are Currently Offered ........................................................ 1 

2.  PROGRAMME DETAILS ................................................................................................. 2 2.1  Programme Title .......................................................................................................... 2 2.2  Programme Cluster ...................................................................................................... 2 2.3  Programme Sub-Fields ................................................................................................ 2 2.4  UQF Level ................................................................................................................... 2 2.5  Duration ....................................................................................................................... 2 2.6  Minimum Credit for Graduation and Notional Hours of Learning ............................. 2 2.7  Programme Expected Learning Outcomes .................................................................. 2 2.8  Programme Status (Full Time/Part Time) ................................................................... 3 2.9  Mode of Delivery ........................................................................................................ 3 2.10  Location of Delivery ................................................................................................... 3 2.11  Intake Numbers for Each Year in the Next Four Years .............................................. 3 2.12  Entry Requirements ..................................................................................................... 3 2.13 Nature of Practical Training ....................................................................................... 4 

3.  RATIONALE FOR ESTABLISHMENT OF THE PROGRAMME ................................. 4 3.1  Justification for the Programme .................................................................................. 4 3.2  Consultation Process ................................................................................................... 5 3.3  Programme Objectives and Philosophy ...................................................................... 7 

3.3.1  Main Objective ..................................................................................................... 7 3.3.2  Specific Objectives .............................................................................................. 7 3.3.3  Programme Philosophy ........................................................................................ 7 

3.4  Programme Exit Level................................................................................................. 7 3.5  Exit Level Outcomes and Associated Assessment Criteria ......................................... 7 

4.  PROGRAMME MANAGEMENT ..................................................................................... 9 4.1  Entry Arrangement ...................................................................................................... 9 4.2  Transfer and Progression ............................................................................................. 9 4.3  Arrangement for Recognition of Prior Learning ......................................................... 9 4.4  Learning Assumed to be in Place (Pre- Requisite-Formal Learning) ......................... 9 4.5  Details of Learning Support Available ........................................................................ 9 4.6  Transfer Arrangement ............................................................................................... 10 4.7  Benchmarking and International Comparability ....................................................... 10 

v 

4.8  Normal Learning Matrix Indicating Course Credit Hours ........................................ 10 5.  ASSESSMENT DETAILS ............................................................................................... 11 6.  FACILITIES AND SERVICES ....................................................................................... 11 

6.1  Facilities .................................................................................................................... 11 6.2  Library ....................................................................................................................... 12 6.3  Equipment ................................................................................................................. 12 6.4  Information and Communication Technology .......................................................... 13 6.5  Learner Support Services .......................................................................................... 14 6.6  Financial Implications and Funding Mechanism ...................................................... 14 

7.  MODULE DESCRIPTION .............................................................................................. 14 7.1  Programme Description ............................................................................................. 14 7.2  Course Coding ........................................................................................................... 15 7.3  Core Courses ............................................................................................................. 15 7.4  Elective Courses ........................................................................................................ 17 7.5  Indicative Timing of Courses .................................................................................... 18 7.6  Already Approved Courses ....................................................................................... 21 7.7  New Courses to be approved ..................................................................................... 21 7.8  Dissertation ................................................................................................................ 22 7.9  Course Contents ........................................................................................................ 22 

8. LIST OF ACADEMIC STAFF AVAILABLE TO RUN THE PROGRAM ..................... 67 9. CURRICULUM VITAE FOR ACADEMIC STAFF ....................................................... 72 APPENDICES ....................................................................................................................... 104 

Appendix A: List of Books to be Purchased ...................................................................... 104 Appendix B: List of Software to be Purchased .................................................................. 111 Appendix C: Attendance List for Internal Stakeholders’ Workshop Participants ............. 113 Appendix D: External Stakeholders’ Workshop Participants ............................................ 114 

D.1: Invited Stakeholders as per Organizations ............................................................. 114 D.2: Attendance List for Stakeholders Participants........................................................ 119 

vi 

LIST OF TABLES

Table 1.1: List of Currently Offered Programmes ..................................................................... 1 Table 2.1: Projected Students Admission .................................................................................. 3 Table 3.1: Exit Levels Outcomes and Assessment Criteria for MSc in CITSE ........................ 8 Table 4.1: Normal Learning Matrix Course Credit Hours per Semester (Core & Elective) ... 10 Table 6.1: Available Facilities ................................................................................................. 11 Table 6.2: Library Staff Qualifications .................................................................................... 12 Table 6.3: Available Equipment .............................................................................................. 12 Table 6.4: Equipment for Information and Communication Technology ............................... 13 Table 7.1: Code Number for Specialization ............................................................................ 15 Table 7.2: Core Courses ........................................................................................................... 15 Table 7.3: Core Courses offered in MSc programmes at CoICT ............................................ 16 Table 7.4: Elective Courses ..................................................................................................... 17 Table 7.5: Regular Mode Indicative Timings of Courses ........................................................ 18 Table 7.6: Evening Mode Indicative Timings of Courses ....................................................... 19 Table 7.7: Summary of Required Minimum Number of Credits – MSc. in CITSE ................ 21 Table 7.8: List of Courses which need Senate Approval ......................................................... 21 Table 7.9: CS 601 Systems Engineering.................................................................................. 22 Table 7.10: CS 602 Microprocessors and Embedded Systems................................................ 24 Table 7.11: CS 603 Power System Operation and Control ..................................................... 26 Table 7.12: CS 604 Power System Modelling ......................................................................... 27 Table 7.13: CS 605 Smart Grid................................................................................................ 29 Table 7.14: CS 606 Research Methods in Science and Engineering ....................................... 31 Table 7.15: CS 607 Hardware Description Language ............................................................. 34 Table 7.16: CS 608 Optimization and Operations Research ................................................... 36 Table 7.17: CS 609 Adaptive Control...................................................................................... 38 Table 7:18: CS 610 Problem Driven Group Project ................................................................ 39 Table 7.19: CS 621 Distributed Algorithms ............................................................................ 41 Table 7.20: CS 622 Cyber Security for Smart Grid ................................................................. 42 Table 7.21: CS 623 Secure Software Design and Programming ............................................. 44 Table 7.22: CS 624 New Developments in Smart Grid ........................................................... 45 Table 7.23: CS 631 Mathematical Modeling and Methods ..................................................... 47 Table 7.24: CS 699 Dissertation .............................................................................................. 48 Table 7.25: ES 630 Power Electronics .................................................................................... 49 Table 7.26: IS 607 Artificial Intelligence ................................................................................ 50 Table 7.27: IS 611 Advanced Object Oriented Programming ................................................. 52 Table 7.28: IS 614 Multimedia Communication and Systems ............................................... 53 Table 7.29: IS 631 Advanced Data Warehousing and Data Mining ........................................ 55 Table 7.30: IS 654 Cloud Computing ...................................................................................... 57 Table 7:31: TE 627 Ad-hoc and Sensor Networks .................................................................. 59 Table 7.32: TE 631 Advanced Signal Processing ................................................................... 60 Table 7.33: TE 633 Wireless Communication ........................................................................ 62 Table 7.34: TE 648 Powerline Communications ..................................................................... 64 

vii 

Table 8.1: List of academic staff with their qualifications ...................................................... 67 Table A.1: List of Books Needed for the MSc in CITSE ..................................................... 104 Table B.1: List of Software Packages to be Purchased ......................................................... 111 Table D.2: List of invitees who attended the External Stakeholders Meeting ....................... 117 

viii 

LIST OF ABBREVIATIONS AND ACRONYMS

CITSE : Computer and IT Systems Engineering CoICT : College of Information and Communication Technologies CS : Computer Science CSE : Computer Science and Engineering

ICT : Information and Communication Technologies IT : Information Technology KTH : KTH Royal Institute of Technology, Sweden MSc : Masters of Science Sida : Swedish International Development Cooperation Agency TCU : Tanzania Commission for Universities UDSM : University of Dar es Salaam UQF : University Qualifications Framework

1 

1. INSTITUTIONAL PROFILE 1.1 Name of Institution

College of Information and Communication Technologies (CoICT), University of Dar as Salaam (UDSM)

1.2 Cluster of Institution

College of Information and Communication Technologies 1.3 Nature of the Provider

Public, Government Owned

1.4 Programme Host Department Computer Science and Engineering (CSE)

1.5 Head of Department and His/Her Address 

Dr. Honest Kimaro, The Head of Department, Computer Science and Engineering, College of Information and Communication Technologies (CoICT), UDSM, Kijitonyama Campus, Bagamoyo Road, P.O. Box 33335, Dar es Salaam, Tanzania. Email: cse@udsm.ac.tz Phone No. +255-(0)22-2700225

1.6 List of Programmes That Are Currently Offered

Table 1.1 shows the list of currently offered programmes.

Table 1.1: List of Currently Offered Programmes Programme Name Programme

level Intake

capacity When started

Date of next

review

a) Certificate in Computer Science

Certificate (UQF 6)

100 2002 2020

b) Diploma in Computer Science Diploma (UQF 6)

100 2002 2020

c) BSc. In Computer Engineering and Information Technology

Undergraduate (UQF 8)

70 2000 2020

d) BSc. In Computer Science Undergraduate (UQF 8)

150 1997 2020

2 

Programme Name Programme level

Intake capacity

When started

Date of next

review

e) BSc. With Computer Science Undergraduate (UQF 8)

80 1991 2020

f) MSc. In Computer Science Postgraduate (UQF 9)

30 1977 2020

g) MSc. In Health Informatics Postgraduate (UQF 9)

30 2007 2020

h) PhD by Thesis Doctorate (UQF 10)

10 1999 -

2. PROGRAMME DETAILS

2.1 Programme Title

MSc in Computer and IT Systems Engineering (MSc in CITSE)

2.2 Programme Cluster

Engineering

2.3 Programme Sub-Fields

Computer System Engineering, IT systems Eng, computer Science, Information Systems, networking, IT security.

2.4 UQF Level

Level 9.

2.5 Duration

18 months for full time (regular) and 24 months for evening mode.

2.6 Minimum Credit for Graduation and Notional Hours of Learning

Students will be required to complete a minimum of 180 credits (1800 notional hours), 156 of which are core (including 60 credits for dissertation) and 24 credits are from the list of elective courses and/or some core courses from within CoICT or outside CoICT but within UDSM. Electives outside CoICT to be approved by CSE department.

2.7 Programme Expected Learning Outcomes

The programme is intended to prepare graduates, upon completion, to be able to:

a) Use acquired knowledge to investigate new and emerging technologies, tools and applications in computer and information technology fields

b) Use concepts from a range of areas including technical and management skills and apply them effectively in engineering projects

3 

c) Develop and apply mathematical and computer-based models and other engineering techniques for solving problems in computer and information technology taking into account a range of commercial and industrial constraints

d) Generate innovative designs for products, systems, components and processes to fulfil new and emerging needs in the field of computer engineering and information technology

e) Make audio/visual/written presentations to convey a body of technical information in a co-ordinated and comprehensive manner and

f) Demonstrate qualities of a professional team member specifically in the areas of interpersonal skills, scheduling, working within deadlines and budget restrictions.

2.8 Programme Status (Full Time/Part Time)

Full Time (Regular Mode) and Part Time (Evening Mode)

2.9 Mode of Delivery

Face-to-face. The courses will be delivered as a combination of lectures and tutorials and for some courses they will include laboratory work.

2.10 Location of Delivery

College of Information and Communication Technologies (CoICT) located at Kijitonyama campus and Mwalimu Nyerere campus.

2.11 Intake Numbers for Each Year in the Next Four Years

Table 2.1 shows the projected admission for the next four years.

Table 2.1: Projected Students Admission

Programme Projected Admission

2016/2017 2017/2018 2018/2019 2019/2020

MSc in CITSE 10 15 20 25

2.12 Entry Requirements

a) Direct Entry Qualification

UQF level 8 with background in ICT related undergraduate programmes or Electrical Engineering related Programmes which includes ICT courses with at least a second class degree with minimum GPA of 2.7 out of 5 from institutions recognized by TCU.

Candidates with pass degrees may also be considered for admission if: i. Their undergraduate performance in the subject of study was a B grade or

higher; ii. They have satisfied UDSM regarding their academic potential through

subsequent research experience and/or additional training.

b) Equivalent Entry Qualification

A Postgraduate Diploma in ICT related programmes or Electrical Engineering related

4 

Programmes which includes ICT courses from a respected institution recognized by TCU or equivalent with at least an upper second class B+ award with minimum GPA of 3.5 out of 5. Candidates with equivalent qualifications must also possess at least advanced secondary school certificates with principal passes in both Physics and Mathematics.

2.13 Nature of Practical Training

Not applicable to this programme

3. RATIONALE FOR ESTABLISHMENT OF THE PROGRAMME

3.1 Justification for the Programme

Tanzania has seen exclusive national development plans namely MKUKUTA, vision 2025, and the 2010 five year development plan aimed at improving the economy, living standards and livelihood of Tanzanians. Another initiative is the Big Results Now project aimed at accelerating achievement of middle income status by 2025 and transition out of aid dependency by identifying and resolving constraints to results delivery in the Government’s priority areas that include energy. Other applicable policies include the national energy policy and the electricity act.

The drive to make Tanzania a middle income country clearly depends on having reliable, efficient and affordable electrical power supply for industries, services and households. This fact was acknowledged by Tanzania’s Growth and Poverty Reduction Strategy, MKUKUTA, setting it to be one of the preconditions for economic growth and social welfare.

Access to electricity will improve education and health services in the rural areas, provide conducive environment for small and medium scale industries and businesses to thrive, encourage expansion of services to underserved areas and communities and encourage value addition activities for agricultural products hence reducing migration to cities and towns in search for better life.

The government resolved to provide extensive access to electricity to both rural and urban communities from either national power grid or from isolated power sources from fossil fuel and renewable energy.

The government started implementing the programme to increase sharply the electrical generation capacity using natural gas, coal, geo-thermal, water, heavy and jet fuel, solar and wind energy. Hence, the number of power sources will keep growing in different parts of the country with different capacities and types. As a conclusion more fine grained and distributed integrated solutions are needed where electricity consumers can act also as electricity suppliers especially in remote community levels.

The electrical power demand and power system has hence grown extensively and is bound to increase further at the same rate or higher in terms of sources, transmission and distribution, loads, and controls following the government’s drive to provide the majority of its citizens with access to electricity and economical activities growth. However, the utility company still uses traditional power system management methods which are inefficient causing frequent power disruptions, long maintenance response period, costly

5 

and time consuming fault localization, etc. Therefore, the cost of electricity is high, which makes the cost of production processes and of products uncompetitive to imported products thereby killing local business (SMEs) growth. The cost is also high because of high technical and non-technical losses.

There is need to use smart grid to introduce intelligence in the grid to improve efficiency in monitoring, control and management of the electrical power system.

The University of Dar Es Salaam (UDSM) together with KTH – Royal Institute of Technology, Sweden in recognition of the need to introduce intelligence in the entire electrical power system network (smart grid) joint developed a research training project called iGRID intended to improve reliability of services offered by the utility company. One of the project objectives is to develop capacity through M.Sc. and PhD training in smart grid monitoring, management and control for the national and isolated grids and their integration for efficient and flexible energy supply system.

The implementation and operation of smart grid requires wide-ranging competences and skills which the programme intend to develop. They include communications and networks to enable the smart grid, computer systems and information security, control of the entire electrical power system network, data management which includes big data, automation in monitoring which includes automatic meter reading/smart meters, GIS mapping of sources, transmission and distribution networks and consumers and micro-grids and local power generation. There is no programme in place to provide these competences.

There is no single postgraduate programme whose design aims to integrate research, training and innovation while facilitating group work in multidisciplinary environment with training to embed students in a society in seeking challenges to be addressed through research to foster innovation and entrepreneurship.

3.2 Consultation Process

The curriculum development followed the processes stated and the results from these processes have been incorporated in this document. This includes the prescribed courses, the delivery methods, admission requirements and types of graduates output. They were also used to refine the programme learning objectives.

i. The process started after The University of Dar es Salaam (UDSM) together with KTH – Royal Institute of Technology, Sweden, in recognition of the need to introduce intelligence in the entire electrical power system network (smart grid), jointly developed a research training project named iGRID, which intends to improve reliability of services offered by the utility company.

ii. In January 2016, a group of six (6) academic staff members developed a draft curriculum.

iii. On 23rd March, 2016, a seminar was conducted involving all academic staff from the CSE Department and the inputs received were used to improve the drafted curriculum.

iv. On 11th April, 2016, an internal stakeholders’ workshop involving all academic and technical staff at CoICT was held to review the developed curriculum prior

6 

to submission to the external stakeholders’ workshop. The internal stakeholders’ attendance sheet is attached in appendix C. A number of inputs were obtained and used to improve the MSc and PhD curriculum documents.

v. From 11th April, 2016 to 17th April, 2016, the tracer study was done to gather stakeholders’ views that would both inform the establishment of postgraduate programmes in Computer and IT Systems Engineering and shaping the structure and contents of the programme that reflect the technological and market needs of various players in the industry. Sampling of regions/cities to visit was done purposely focusing on those with large concentration of organizations with departments whose core business functions are related to ICT, telecommunication, electronics, and electrical engineering. These areas included: Tanga, Mwanza, Arusha, Mbeya, and Dar es Salaam. Study participants associated 135 various organizations which were categorized into central/local governments (9%), parastatals (12%), private companies (53%), government agencies (5%), professional institutions (1%), regulatory bodies (2%), Non-governmental organizations (1%), and academic or training institutions (17%). It is significant to note that most of the respondents are prospective applicants for the programme which reflects genuine feelings about the programme. Detailed information regarding the needs analysis has been attached as a separate document. The gathered inputs from tracer study have been incorporated in the curriculum documents. The study clearly indicated the support for the MSc and both PhD and MSc. The project based approach was strongly supported and the delivery modes of regular and evening mode. The majority preferred the evening mode so that they can work and study.

vi. External stakeholders’ workshop was held on the 19th April, 2016. All key stakeholders were invited from within the University and from outside the University. Those from outside the University included different players in the Electrical Utility Company (TANESCO), Regulatory Authorities, Mobile operators, Broadcasters, Government Ministries and Departments, Government Agencies, Public Institutions, Academic Institution, power generation companies, and industrialists. The list of invited external stakeholders and the external stakeholders’ attendance sheet is attached in appendix D. Their contribution and information provided during the workshop was commendable and have been incorporated in the curriculum document.

vii. The developed curricula will be presented to the College Board for consideration for approval and submission to higher University organs in time to be set after incorporating inputs from the external stakeholders’ workshop.

viii. Inputs from our collaborating partner institution KTH, Sweden, were also received and incorporated in this curriculum document.

ix. Benchmarking with other Universities was done through relative Internet search. 

7 

3.3 Programme Objectives and Philosophy

3.3.1 Main Objective

The course aims to provide graduates with a comprehensive coverage of the skills required by an engineer working in instrumentation, electronic systems, and hardware and software aspects of computer engineering.

The programme provides an excellent basis for engineers wishing to update their knowledge as well as for students who wish to go on to do research.

3.3.2 Specific Objectives

The program has been developed to fulfil the following specific objectives:

a) To provide students with enhanced theoretical background and applied knowledge that they need to practice as Computer and IT Systems engineers who can lead in research and development.

b) To enable students acquire the ability to innovate, develop, direct, coordinate and technically manage projects in the fields of information technology and computer system engineering

c) To equip students with skills to be able to start their own businesses through incubation process

d) To provide a gateway to doctoral studies in Computer and IT system engineering

3.3.3 Programme Philosophy

The programme strives to achieve its objectives in all aspects, including students’ selection, improved curriculum and graduate outcomes. The faculty and students engage in teaching and learning, community outreach and advocacy with the focus on improving the use of ICT in energy sector.

3.4 Programme Exit Level

UQF level 9 – MSc in Computer and IT Systems Engineering after full completion and passing of all specified courses and dissertation with a total minimum of 180 credits including dissertation work.

3.5 Exit Level Outcomes and Associated Assessment Criteria

Table 3.1 shows exit levels outcomes and assessment criteria.

8 

Table 3.1: Exit Levels Outcomes and Assessment Criteria for MSc in CITSE Description Exit levels outcomes Assessment criteria

Knowledge Graduate of MSc in Computer and IT Systems Engineering will have acquired: a) Comprehensive understanding of the

scientific principles and awareness of the most recent technologies, tools and applications in Computer and Information Technology Systems fields

b) Comprehensive knowledge and understanding of mathematical and computer models in Computer and Information Technology Systems disciplines and an appreciation of their limitations

c) Comprehensive understanding of the concepts from a range of areas including technical and management skills and ability to apply them effectively in engineering projects

Coursework, assignments, final exams and dissertation

Skills Graduate of MSc in Computer and IT Systems Engineering will have developed skills in:

a) Developing and using mathematical and computer-based models for solving problems in Computer and Information Technology Systems

b) Demonstrate skills in audio/visual/written presentation to convey a body of technical information in a coordinated and comprehensive manner

c) Integrating Computer and Information Technology Systems engineering using their generalist and broader knowledge in multidisciplinary contexts

d) Coordinating and technically managing projects in the fields of Computers and Information Technology

Coursework, assignments, final exams and dissertation

Competence Graduates of the MSc in Computer and IT Systems Engineering will demonstrate ability to: a) Use fundamental knowledge to investigate

new and emerging technologies b) Apply mathematical and computer-based

models for solving problems in computer

Coursework, assignments, final exams and dissertation

9 

Description Exit levels outcomes Assessment criteria

and information technology and ability to assess the limitations of particular cases

c) Generate an innovative design for products, systems, components or processes to fulfil new needs

d) Apply engineering techniques taking into account range of commercial and industrial constraints

4. PROGRAMME MANAGEMENT

4.1 Entry Arrangement

Requirement for successful participation in this programme, assessment for entry eligibility into the programme, further selection arrangement, policies and procedures with regard to allocation of places and appeals procedures to follow UDSM’s postgraduate policies and regulations.

4.2 Transfer and Progression

To follow UDSM’s postgraduate transfer and progression regulations.

4.3 Arrangement for Recognition of Prior Learning

Arrangements for recognition of prior learning (formal and informal learning) will follow UDSM’s regulations.

4.4 Learning Assumed to be in Place (Pre- Requisite-Formal Learning)

Refer to Entry Requirements Section 2.12.

4.5 Details of Learning Support Available

 Following are learning support available: a) General and dedicated library services to postgraduate students; b) Internet connectivity wired and wireless; c) Equipped computer laboratories; d) Registered (paid for) electronic resources including various journals accessible on

campus; e) Supervision and academic /career advisory services; f) Open source based learning management systems managed by the Centre for Virtual

Learning (CVL) in CoICT providing improvement in teaching and learning environment for staff and students through online teaching and learning support services;

g) An ICT incubator under the University of Dar es Salaam ICT Incubator (UDICTI) to promote innovation, entrepreneurship and businesses creation based on research activities during and/or after graduation;

10 

h) Stationery service within the campus; and i) Link to research groups in the host department.

4.6 Transfer Arrangement

To follow UDSM’s Postgraduate regulations.

4.7 Benchmarking and International Comparability

This programme is comparable to similar programmes offered in other universities worldwide and has been benchmarked with programmes offered by University of Nottingham (UK), Brunel University London (UK), University of Birmingham (UK), University College Dublin (UCD) Ireland, College of Engineering at Tennessee State University (USA), The Nelson Mandela African Institution of Science and Technology (NM-AIST), just to mention few.

4.8 Normal Learning Matrix Indicating Course Credit Hours

Table 4.1 shows the normal learning matrix indication course credit hours per semester for the MSc. In CITSE.

Table 4.1: Normal Learning Matrix Course Credit Hours per Semester (Core & Elective)

Course Code

Core/ Elective

Lecture Hrs

Tutorial Hrs

Assignment Hrs

Independent Hrs

PracticalHrs

TotalTotalHrs

Credits

CS 602 Core  45 15 15 30 15 120 12 CS 605 Core 45 15 15 30 15 120 12 CS 606 Core 45 15 15 30 15 120 12 CS 608 Core 45 15 15 30 15 120 12 CS 621 Core 45 15 15 30 15 120 12

CS 631 Core 45 - 15 30 30 120 12 CS 698 Core - 10 - 80 30 120 12 CS 699 Core - - - - - 600 60IS 607 Core 45 15 15 30 15 120 12 CS 601 Elective 45 15 15 30 15 120 12 CS 603 Elective 45 15 15 30 15 120 12 CS 604 Elective 45 15 15 30 15 120 12 CS 607 Elective 45 15 15 30 15 120 12 CS 609 Elective 45 15 15 30 15 120 12 CS 622 Elective 45 15 15 30 15 120 12 CS 623 Elective 45 15 15 30 15 120 12 CS 624 Elective 45 15 15 30 15 120 12 ES 630 Elective 45 15 15 30 15 120 12 IS 611 Elective 45 15 15 30 15 120 12 IS 614 Elective 45 15 15 30 15 120 12 IS 631 Elective 30 6 6 8 30 80 8 IS 654 Elective 45 15 15 30 15 120 12 TE 627 Elective 45 15 15 30 15 120 12 TE 631 Elective 45 15 15 30 15 120 12

11 

Course Code

Core/ Elective

Lecture Hrs

Tutorial Hrs

Assignment Hrs

Independent Hrs

PracticalHrs

TotalTotalHrs

Credits

TE 633 Elective 45 15 15 30 15 120 12 TE 648 Elective 45 15 15 30 15 120 12

5. ASSESSMENT DETAILS

Programme assessment shall follow the UDSM and CoICT examination regulations as approved by Senate. UDSM regulations governing the award of degrees in the College of Information and Communication Technologies shall apply.

6. FACILITIES AND SERVICES

6.1 Facilities

Facilities shown in Table 6.1 are available at CoICT Kijitonyama Campus to be used for Postgraduate studies.

Table 6.1: Available Facilities S/N Space type Quantity Capacity

for each 1. Lecture room 4 50 2. Lecture room 3 150 3. Lecture room 4 180 4. Lecture Theater 1 300 5. Computer Laboratory 4 30 6. Computer Laboratory (Mwalimu Julius

Nyerere Mlimani campus) 1 80

7. Internet cafe 1 30 8. Measurements and control Laboratory 1 30 9. Telecommunication Engineering

Laboratory 1 30

10. Microcontroller Laboratory 1 30 11. Electronics Laboratory 1 30 12. Workshop General 1 30 13. Studio (Multimedia) lab 1 30 14. Research Room (Postgraduate) 1 30 15. Special room (Postgraduate) 2 30 16. Research laboratory (Postgraduate) 1 30 17. Video conferencing system 1 Can link 2

sites

12 

6.2 Library

a) Access to the library facilities Students will have access to the UDSM main library (Wilbert Chagula Library). In addition, learners will also have access to online resources such as Optical Society of America (OSA) and IEEE Electronic Library (IEL) through UDSM library. IEL provides an online access to more than 2 million full-text documents in electrical engineering and computer science, and OSA provides access to conference papers and over 35 journals titles in photonics, applied optics, display technology, light wave technology, communications and networking, optical networking and others. Also the UDSM main library has a special reserve where all theses and research materials produced by researchers at UDSM are kept and accessible to students.

b) Location and staff qualifications of the library staff Learners will use the Wilbert Chagula Library at Mwalimu Julius Nyerere Mlimani Campus, University of Dar es Salaam, which has qualified Librarians. Qualifications of the library staff is as shown in Table 6.2.

Table 6.2: Library Staff Qualifications

S/N Qualifications Total 1. Professors 1 2. Associate Professors 4 3. Senior Librarians 3 4. Librarians 5 5. Assistant Librarians 6 6. Assistant Librarian trainees 3 7. Senior Library Officers 6 8. Library Officers 12 9. Library Assistants 29

c) Materials Detailed list of all relevant readings are as shown in Appendix A. The curriculum has also indicated a number of software required in the teaching of the courses as shown in Appendix B.

6.3 Equipment

Available equipment are as shown in Table 6.3.

Table 6.3: Available Equipment

No. Equipment/Description Qty No. Equipment/Description Qty 1. Spectrum Analyzer 1 21. Function Generator 6 2. Handheld Spectrum

Analyzer 1 22. Sweep Generator 4

3. EMC Spectrum Analyzer 1 23. Bench Dual Display Count 20

13 

multi-meter 4. Dual Trace Oscilloscope 4 24. Phase meter 2 5. 4-input channel Oscilloscope 4 25. Microwave Generator 2 6. Programmable Waveform

Generator 2 26. Multimedia Projectors 10

7. Logic checker 2 27. Digital Trainer Board 10 8. Microwave Multi-meter 1 28. Telecommunication Trainer

Board 5

9. Data Pattern Generator 2 29. Microwave training system 2 10. PC Based Logic Analyzer 2 30. Digital Microwave Radio

Tes t Kit 2

11. SWR/Power Meter 4 31. PCB drilling machine set 2

12. LCR Meter 4 32. Wire wrapping tool 2 13. Electronic Component

Tester 4 33. Professional Prototyping Board 4

14. Linear Master IC Tester 4 34. 8-bit Microprocessor trainer kit 20 15. Digital IC Tester 4 35. Electronic soldering station 4 16. Servers 5 36. Chungpa Microprocessor Training

Kit with AT89C51,PIC6F874, ATMEGA8535 uControllers boards

29

17. UPS for PCs 50 37. Spartan3 Development Kit 10 18. UPS for Servers 2 38. Microprocessor Kit 8085 with

Power Supply 18

19. Electronics De-soldering station

7 39. Deluxe EPROM Eraser 2

20. PC Universal Programmer 2 40. Digilent XILINX Spartan-3E Microprocessor Board

7

21. Universal Counter 2 41. DC power supply 8 22. Digital Multi-meters 2 42. Variac (Auto Transformer) 5 23. AC Milli-voltmeter 2 43. 6 1/2 Digits Multimeter 10 24. Digital Storage Oscilloscope 5 44. Video Conferencing system 1

6.4 Information and Communication Technology

Table 6.4 shows the equipment for Information and Communication technology

Table 6.4: Equipment for Information and Communication Technology

S/N Equipment type Quantity 1. Desktop Computers 2502. Software Sufficient3. Whiteboards 254. Projectors 155. Smart boards 5

14 

6.5 Learner Support Services

Apart from the services mentioned under sub-section 4.5, the CoICT and UDSM at large has the following a) Students’ advisory services where by Dar es Salaam University Students

Organization (DARUSO) was established to make students discuss their issues. b) Sports and game facilities whereby playgrounds for Football, Netball, Basketball,

Volleyball, swimming poor etc are available, some at CoICT and many at Mwalimu Julius Nyerere Mlimani Campus (UDSM main campus).

c) Well equipped Health Centre to serve staff and all students.

6.6 Financial Implications and Funding Mechanism

Under the WB project, more classrooms and laboratory spaces have been created from the rehabilitation of Kijitonyama Campus. A good number of laboratory equipment, including: computers, servers, Networking, Telecommunications and Electronics equipment has also been procured. The department has adequate number of staff to teach all the courses without the need for part time lecturers. The curriculum has indicated a number of textbooks and software needed for the programme. Software are being shared among different postgraduate programmes in the department and in the college. The financial implications cater for all the books to be purchased for MSc in CITSE, amounting to US$ 27,318 (US$ Twenty Seven Thousand, Three hundred and eighteen only) as shown in appendix A and also commercial softwares to be purchased amounting to US$ 9,165 (US$ Nine Thousand, One hundred and sixty five only). At the commencement of this MSc programme, it is expected to have a moderate enrolment and, hence, the list of the books and software can be purchased in phases. As much as possible, the department is planning to make good use of available Free and Open Source Software (FOSS) and e-books. However, some of the books and software will have to be purchased. The expected sources of funds to procure the books and the software is from warrant of funds and internally generated funds from the college.

7. MODULE DESCRIPTION

7.1 Programme Description

The programme is a twenty four months (24) if taken in evening mode and eighteen months (18) if taken in regular mode, leading to the award of MSc in Computer and IT Systems Engineering. For Regular mode, the courses have been arranged to cover the initial one year, and the first six months of the second year are devoted to a dissertation project. For evening mode, the courses have been arranged to cover the initial one year, and the second year is devoted to a dissertation project.

15 

The programme provides advanced knowledge and skills in all aspects of computer hardware, software and their integration. The programme is intended to train students in Computer and IT Systems Engineering and equip them with the necessary knowledge and skills to design, implement, manage and maintain information technology and communications systems.

The programme further provides advanced knowledge and research experiences in the following concentration areas:

a) Computer Communication and Networks b) Network Security c) Controls Systems and Signal Processing d) Information Management and Analytics e) Systems Optimization f) Electronics and Information Technology

7.2 Course Coding

Course codes in the programme will be using two letters "CS"/"IS"/"TE"/"ES" followed by three digits according to the University coding format. The first digit denotes level of degree award (here referred to MSc), the middle digit denotes major specialization and the last digit denotes serial number. New courses will use CS code while adopted courses will use existing codes. If new courses are from different departments, then the codes for that department will be used (such as TE, ES, etc).

Table 7.1 shows the knowledge areas/specializations and corresponding middle digits.

Table 7.1: Code Number for Specialization S/N Major Specializations Middle

Digit 1. Engineering/Computer Engineering 0/1 2. Computer Science 2 3. Other 3 4. Dissertation 9

 

7.3 Core Courses

At the end of the programme each student is required to complete 156 credits of core courses including 60 credits for dissertation. Table 7.2 summarises the core courses.

Table 7.2: Core Courses

S/N Code No. Course Name Credits1. CS 602 Microprocessors and Embedded Systems 12 2. CS 605 Smart Grid 12 3. CS 606 Research Methods in Science and Engineering 124. CS 608 Optimization and Operations Research 12

16 

5. CS 610 Problem Driven Group Project 12 6. CS 621 Distributed Algorithms 127. CS 631 Mathematical Modeling and Methods 12 8. CS 699 Dissertation 60 9. IS 607 Artificial Intelligence 12

Total 156  

Table 7.3 show all core courses offered in MSc programmes at CoICT and in which programme each course is offered.

Table 7.3: Core Courses offered in MSc programmes at CoICT

S/N

Cou

rse

Cod

e

MS

c. in

Com

pute

r an

d IT

Sys

tem

s E

ngin

eeri

ng

MS

c. in

Com

pute

r S

cien

ce

MS

c. in

Hea

lth

Info

rmat

ics

MS

c. in

Inf

orm

atio

n S

yste

ms

MS

c. in

C

omm

unic

atio

ns a

nd

Net

wor

k E

ngin

eeri

ng

MS

c. in

Ele

ctro

nics

E

ngin

eeri

ng a

nd

Info

rmat

ion

Tec

hnol

ogy

1. CS 602 X 2. CS 605 X 3. CS 606 X 4. CS 608 X 5. CS 610 X 6. CS 621 X 7. CS 631 X 8. CS 699 X 9. ES 613 X 10. ES 619 X 11. ES 621 X 12. ES 699 X 13. IS 605  X X X X X 14. IS 607 X X 15. IS 611 X 16. IS 613 X 17. IS 614 X 18. IS 615  X 19. IS 616  X 20. IS 618  X 21. IS 620 X X 22. IS 621 X 23. IS 622 X X 24. IS 623 X X X 25. IS 624  X 26. IS 625 X X X

17 

S/N

Cou

rse

Cod

e

MS

c. in

Com

pute

r an

d IT

Sys

tem

s E

ngin

eeri

ng

MS

c. in

Com

pute

r S

cien

ce

MS

c. in

Hea

lth

Info

rmat

ics

MS

c. in

Inf

orm

atio

n S

yste

ms

MS

c. in

C

omm

unic

atio

ns a

nd

Net

wor

k E

ngin

eeri

ng

MS

c. in

Ele

ctro

nics

E

ngin

eeri

ng a

nd

Info

rmat

ion

Tec

hnol

ogy

27. IS 626  X 28. IS 628 X 29. IS 631 X 30. IS 660 X 31. IS 661 X 32. IS 662 X 33. IS 663 X 34. IS 666 X 35. IS 668 X 36. IS 669 X 37. IS 699  X X X 38. TE 621 X 39. TE 623 X 40. TE 625 X 41. TE 629 X 42. TE 633 X 43. TE 636 X 44. TE 637 X 45. TE 647 X 46. TE 699 X

7.4 Elective Courses

In order to complete 180 credits, each student will be required to take elective courses. The minimum number of credits from elective courses is 24 credits. Table 7.4 summarises the elective courses.

Table 7.4: Elective Courses

S/N Code No. Course Credits 1. CS 601 Systems Engineering 12 2. CS 603 Power Systems Operation and Control 12 3. CS 604 Power Systems Modelling 12 4. CS 607 Hardware Description Language 12 5. CS 609 Adaptive Control 12 6. CS 622 Cyber Security for Smart Grid 12 7. CS 623 Secure Software Design and Programming 12 8. CS 624 New Developments in Smart Grid 12 9. ES 630 Power Electronics 12

18 

10. IS 611 Advanced Object Oriented Programming 12 11. IS 614 Multimedia Communication and Systems 1212. IS 631 Advanced Data Warehousing & Data Mining 8 13. IS 654 Cloud Computing 12 14. TE 627 Ad-hoc and Sensor Networks 12 15. TE 631 Advanced Signal Processing 12 16. TE 633 Wireless Communication 12 17. TE 648 Powerline Communications 12

Minimum required credits 24  

7.5 Indicative Timing of Courses

Regular Mode Table 7.5 shows a list of courses for MSc in Computer and IT Systems Engineering for the regular mode of delivery. The courses have been arranged to cover two semesters in the first year of study. The dissertation is carried out during the first six months of the second year of study.

Table 7.5: Regular Mode Indicative Timings of Courses

S/N Course Code

Course Title

Credits

Year 1 Year 2

Sem1 Sem2 1st six month

Core courses 1. CS 602 Microprocessors and Embedded

Systems 12

2. CS 605 Smart Grid 12 3. CS 608 Optimization and Operations

Research 12

4. CS 610 Problem Driven Group Project 6 6 5. CS 631 Mathematical Modelling and

Methods 12

6. CS 621 Distributed algorithms 12 7. CS 606 Research Methods in Science and

Engineering   12

8. IS 607 Artificial intelligence 12 9. CS 699 Dissertation   60

Total Core 54 42 60 Elective minimum 24 credits 12 12 Sub-Total 66 54 60 Total 180

Elective Courses 10. CS 601 Systems Engineering 12 11. CS 623 Secure Software Design and 12

19 

S/N Course Code

Course Title

Credits

Year 1 Year 2

Sem1 Sem2 1st six month

Programming12. IS 611 Advanced Object Oriented

Programming 12

13. IS 654 Cloud Computing 12 14. TE 627 Ad-hoc and Sensor Networks 12 15. TE 633 Wireless Communication 12 16. TE 648 Powerline Communications 12 17. CS 603 Power Systems Operation and control   12 18. CS 604 Power Systems Modelling 12 19. CS 607 Hardware Description Language 12 20. CS 609 Adaptive Control 12 21. CS 622 Cyber Security for Smart Grid 12 22. CS 624 New Developments in Smart Grid 12 23. ES 630 Power Electronics 12 24. IS 614 Multimedia Communication and

Systems 12

25. IS 631 Advanced Data Warehousing & Data Mining

8

26. TE 631 Advanced Signal Processing 12

Evening Mode

Table 7.6 shows a list of courses for MSc in Computer and IT Systems Engineering arranged in evening mode of delivery. The courses have been arranged to cover two semesters in the first year. Dissertation will be in the second year.

Table 7.6: Evening Mode Indicative Timings of Courses

S/N Course Code

Course Title

Credits

Year 1 Year 2

Sem1 Sem2

Core courses 1. CS 602 Microprocessors and Embedded

Systems 12

2. CS 605 Smart Grid 12 3. CS 608 Optimization and Operations

Research 12

4. CS 610 Problem Driven Group Project 6 6 5. CS 631 Mathematical Modelling and

Methods 12

20 

S/N Course Code

Course Title

Credits

Year 1 Year 2

Sem1 Sem2

6. CS 621 Distributed algorithms 12 7. CS 606 Research Methods in Science and

Engineering   12

8. IS 607 Artificial intelligence 12 9. CS 699 Dissertation   60

Total Core 54 42 60 Elective minimum 24 credits 12 12 Sub-Total 66 54 60 Total

Elective Courses 10. CS 601 Systems Engineering 12 11. CS 603 Power Systems Operation and

control   12

12. CS 607 Hardware Description Language 12 13. CS 609 Adaptive Control 12 14. CS 622 Cyber Security for Smart Grid 12 15. CS 623 Secure Software Design and

Programming 12

16. CS 624 New Developments in Smart Grid 12 17. ES 630 Power Electronics 12 18. IS 614 Multimedia Communication and

Systems 12

19. IS 631 Advanced Data Warehousing & Data Mining

8

20. TE 631 Advanced Signal Processing 12 21. CS 604 Power Systems Modelling 12 22. IS 611 Advanced Object Oriented

Programming12

23. IS 654 Cloud Computing 12 24. TE 627 Ad-hoc and Sensor Networks 12 25. TE 633 Wireless Communication 12 26. TE 648 Powerline Communications 12

The structure of the MSc. in CITSE degree Regular Mode and Evening Mode programme is summarized in Table 7.7.

21 

Table 7.7: Summary of Required Minimum Number of Credits – MSc. in CITSE S/N Description Credits

1. Total Units for core courses 96 2. Minimum Total Units for elective courses 24 3. Total Units for dissertation 60

Minimum Total Units for the Programme 180

7.6 Already Approved Courses

None.

7.7 New Courses to be approved

Table 7.8 shows the list of courses which need to be approved by Senate.

Table 7.8: List of Courses which need Senate Approval

S/N Code No.

Course Name Credits Remark

1. CS 601 Systems Engineering 12 New 2. CS 602 Microprocessors and Embedded Systems 12 New 3. CS 603 Power Systems Operation and Control 12 New 4. CS 604 Power Systems Modelling 12 New 5. CS 605 Smart Grid 12 New 6. CS 606 Research Methods in Science and

Engineering 12 New

7. CS 607 Hardware Description Language 12 New 8. CS 608 Optimization and operations Research 12 New 9. CS 609 Adaptive Control 12 New 10. CS 610 Problem Driven Group Project 12 New 11. CS 621 Distributed algorithms 12 New 12. CS 622 Cyber Security for Smart Grid 12 New 13. CS 623 Secure Software Design and Programming 12 New 14. CS 624 New Developments in Smart Grid 12 New 15. CS 631 Mathematical Modeling and Methods 12 New 16. CS 699 Dissertation 60 New 17. ES 630 Power Electronics 12 New 18. IS 607 Artificial Intelligence 12 Adopted 19. IS 611 Advanced Object Oriented Programming 12 Adopted 20. IS 614 Multimedia Communication and Systems 12 Adopted 21. IS 631 Advanced Data Warehousing & Data Mining 8 Adopted 22. IS 654 Cloud Computing 12 Adopted 23. TE 627 Ad-hoc and Sensor Networks 12 Adopted 24. TE 631 Advanced Signal Processing 12 Adopted 25. TE 633 Wireless Communication 12 Adopted

22 

S/N Code No.

Course Name Credits Remark

26. TE 648 Powerline Communications 12 New  

7.8 Dissertation

For maximum effectiveness, students’ dissertation will be graded and will contribute to the final GPA. The weight is in proportion to its total number of contact hours, as any other core course. In the regular mode the final assessment of the dissertation will be done at the end of the first semester of the second year, and in the evening mode the final assessment of the dissertation will be done at the end of second year. Dissertation process will be guided by the University's general regulations and guidelines for postgraduate programmes approved by the Senate.

7.9 Course Contents

Tables 7.9 through 7.34 show contents of all courses (Core and elective) offered in this programme.

Table 7.9: CS 601 Systems EngineeringCourse Code CS 601 Total Credits: 12 Course Name Systems Engineering

Delivery Mode:

Lecture Hrs/Sem

TutorialHrs/Sem

PracticalHrs/Sem

AssignmentsHrs/Sem

Independent Studies Hrs/Sem

Total Hrs/Sem

45 15 15 15 30 120 Assessment Mode:

Coursework (50%) + University Examination (50%).

Prerequisites: None Objective: To introduce systems engineering principles and develop a “systems”

perspective of and approach to solving complex problems

Learning Outcomes:

Upon completion of the course the student should:

i. Have the basic principles of systems engineering (SE) ii. Have well-based knowledge and familiarity of key SE practices and

processes iii. Understand the roles of the systems engineer within an organization iv. Appreciate the need and role of systems engineering and the systems

engineer in addressing complex problems and developing engineering solutions

v. Understand interactions with others like managers, specialists and sponsors

vi. Apply systems engineering practices to practical problems vii. Demonstrate familiarity with basic systems engineering processes

through limited “hands on” practice during assignments, team projects and class interactions

23 

Course Contents: Unit I: Systems Theories Systems thinking. Wymorian theory of systems engineering. Wiener’s cybernetic

principles. Bertalanffy’s general systems theory. Checkland’s soft systems methodology

Unit II: Product & System Life Cycles Waterfall vs. Vee vs. Spiral models. System life cycles. Systems engineering

standards Unit III: Requirements Engineering Stakeholder salience. Characteristics of good requirements. Requirements derivation

and decomposition. System specification. Functional analysis Unit IV: Concept development Pugh method. Trade space exploration. Unit V: Detailed design Systems engineering modeling. Artifacts. Design reviews Unit VI: Test and evaluation Use cases. Test strategies. Test planning & execution Unit VII: Decision making Multi-attribute utility theory. Risk and uncertainty Unit IX: System attributes & human factors Reliability & Maintainability. Human systems integration Unit X: Life-cycle costing Design to cost. Activity-based costing. Parametric cost estimation Unit XI: Reusability and COTS Reuse principles. Reuse framework. Commercial off-the-shelf evaluation Unit XII: Systems architecting The architecting paradigm. Heuristics as tools. Limitations of heuristics Unit XIII: Planning & organization Systems engineering management plan. Statement of work Unit XIV: Program management The iron triangle. Earned value. PERT carts. Leading indicators for systems

engineering Unit XV: Model-based systems engineering & risk analysis Object oriented design. DODAF. Dependency structure matrix. Risk

assessment/quantification/mitigation Reading List:

1. Alexander, I. F., Stevens, R., Alex, I., & Young, R. R. (2002). Writing better requirements. Boston: Addison-Wesley Educational Publishers. ISBN: 0321131630)

2. Faulconbridge, R. I. (2014). Systems engineering practice. Australia: Argos Press Pty. ISBN: 1921138076

3. Kossiakoff, A. , Sweet, W.N., Seymour, S. & Biemer, S.M. (2011). Systems engineering principles and practice (2nd ed.). Wiley-Interscience, ISBN-13: 978-0470405482

4. Meadows, D. H. (2008). Thinking in systems: A primer. United States: Chelsea Green Publishing Co. ISBN: 1603580557

5. Wasson, C. S. (2015). System engineering analysis, design, and development:

24 

Concepts, principles, and practices. United States: John Wiley & Sons. ISBN: 1118442261

6. Relevant Journals and Conference Papers

Table 7.10: CS 602 Microprocessors and Embedded Systems Course Code

CS 602 Total Credits 12

Course Name

Microprocessors and Embedded Systems

Delivery Mode:

Lectures Hrs/Sem

Tutorials Hrs/Sem

Practical Hrs/Sem

Assignment Hrs/Sem

Independent Study Hrs/Sem

Total Hrs/Sem

45 15 15 15 30 120 Assessment Mode

Coursework (50%), Final Examination (50%)

Prerequisites:

None

Objective: The objectives of this course are to: i. Provide students with a sound understanding of the structure and operation

of embedded systems ii. Equip students with the knowledge and skills to develop embedded systems

for solving problems that occur in the industry and society Learning Outcome:

After this course, students are expected to be able to: i. Describe the components of embedded systems

ii. Define and execute architectural trade-offs, hardware-software interaction, and interfacing with sensors and actuators.

iii. Solve embedded systems problems through integration of hardware and software

iv. Design, develop, test, configure and maintain embedded systems v. Program embedded systems in both assembly and a high-order language. A

good working knowledge of the c programming language is suggested. Course Contents: Unit I: Microprocessors, micro-controllers and embedded systems Mini computers, microprocessors, micro controllers and digital signal processors

Differences between microprocessors and microcontrollers Applications of microprocessors and microcontrollers Overview of the architecture and different types of microcontrollers Software development for microprocessors and microcontrollers

Unit II: Introduction to Hardware Design

Practical electronic circuit design, prototyping and testing, amplification, voltage regulation, clock generation, sensor and signal conditioning circuits, and power supply design. The design and modelling of digital hardware systems using a hardware description language. Digital circuit design, logic synthesis and verification, the electronic properties of logic gates, electrical interfacing between logic families, asynchronous to synchronous interfacing, clock distribution and timing.

Unit IIII: Interfacing devices to embedded systems Interfacing external hardware to embedded systems, software control of hardware.

25 

Bus structures, parallel and serial interfacing, GPS and other embedded communications technologies. The design and implementation of microcontroller-based embedded target systems; circuit design, fabrication, assembly and testing of multi-layer printed wiring board assembly for a specified embedded control and communication application. The application of programmable logic devices, the design and implementation of adaptive computing systems

Unit IV: Low-level software development The design, programming and testing of software for embedded systems.

The implementation of software for low-level device interfacing and real-time control in microcontroller environments. Fundamentals of software engineering, system requirements, effective methods of design, coding, and testing, team software development, verification and validation, software quality, and the application of engineering tools

Unit V: High level software development The organization of operating systems for various computer platforms, process

scheduling, process synchronization, multi-process computation, deadlock avoidance, and file system organization and integrity. Software design and implementation using the C language. Algorithm design, modular code design, programming style, functions, arrays, pointers, strings, data structures, and input/output Software design and implementation using efficient and effective data organization. Analysis and implementation of essential data structures in the context of embedded software development and algorithms. Efficiency and cost evaluation of selected algorithms.

Reading List: 1. Barr, M., & Massa, A. (2006). Programming Embedded Systems: With C and

GNU Development Tools (2nd ed.). O'Reilly Media. ISBN-13: 978-0596009830 2. Berger, A. S. (2001). Embedded Systems Design: An Introduction to Processes,

Tools and Techniques. CMP Books, ISBN-13: 978-1578200733 3. Catsoulis, J. (2005). Designing Embedded Hardware (2nd ed.). O'Reilly Media,

ISBN-13: 978-0596007553 4. Godse A. P., & Godse, D. A. (2008). Microprocessors and Microcontrollers.

Technical Publications Pune, ISBN-13: 978-8184312973 5. Kant K. (2014). Microprocessors and Microcontrollers: Architecture,

Programming and System Design 8085, 8086, 8051, 8096. Prentice-Hall of India Pvt. Ltd. ISBN-13: 978-8120348530.

Required Laboratory Equipment:1. Computer Lab with installed development software for microcontrollers 2. Microcontroller development kits

26 

Table 7.11: CS 603 Power System Operation and Control Course Code CS 603 Total Credits: 12 Course Name Power System Operation and Control

Delivery Mode:

Lecture Hrs/Sem

Tutorial Hrs/Se

Practical Hrs/Sem

Assignment Hrs/Sem

Independent Studies Hrs/Sem

Total Hrs/Sem

45 15 15 15 30 120

Assessment Mode:

Continuous Assessment (50%) + University Examination (50%)

Prerequisites: None Objective: i. To provide an overview of power system operation and control

ii. To provide knowledge to model power-frequency dynamics and to design power-frequency controller

iii. To provide knowledge to model reactive power-voltage interaction and the control actions to be implemented for maintaining the voltage profile against varying system load

iv. To study the economic operation of power system v. To learn about SCADA and its application for real time operation and

control of power systems. Learning Outcomes:

i. To make students express Economic operation of power system and importance of LFC control

ii. To improve student’s ability in solving problems (numerical problems at present) by posing different problem models related to Economic Load Dispatch, Load Frequency Control and reactive power control

iii. Ability to model and design turbine and Automatic controller. iv. Ability to express variation of frequency in the power system with

varying load Course Contents:

Unit I: Introduction

System load – variation - load characteristics - load curves and load-duration curve (daily,weekly and annual) - load factor - diversity factor. Importance of load forecasting and simpletechniques of forecasting. An overview of power system operation and control and the role of computers in the implementation. (Qualitative treatment with block diagram)

Unit II: Real Power - Frequency Control

Basics of speed governing mechanism and modeling - speed-load characteristics – load sharingbetween two synchronous machines in parallel. Control area concept LFC control of a single-area system. Static and dynamic analysis of uncontrolled and controlled cases. Integration ofeconomic dispatch control with LFC. Two-area system – modeling - static analysis of uncontrolledcase - tie line with frequency bias control of two-area system - state variable model

27 

Unit III: Reactive Power–Voltage Control

Basics of reactive power control. Excitation systems – modeling. Static and dynamic analysis - stability compensation - generation and absorption of reactive power. Relation between voltage, reactive power at a node - method of voltage control - tap-changing transformer. System level control using generator voltage magnitude setting, tap setting of OLTC transformer and MVAR injection of switched capacitors to maintain acceptable voltage profile and to minimize power and transmission loss 

Unit IV: Unit Commitment and Economic Dispatch

Statement of economic dispatch problem – cost of generation – incremental cost curve co-ordination equations without loss and with loss, solution by direct method and λ-iteration method. (No derivation of loss coefficients). Statement of Unit Commitment problem – constraints; spinning reserve, thermal unit constraints, hydro constraints, fuel constraints and other constraints. Solution methods - Priority-list methods - forward dynamic programming approach. Numerical problems only in priority-list method using full-load average production cost.

Unit V: Computer Control of Power Systems

Need of computer control of power systems. Concept of energy control centre (or) load dispatch centre and the functions - system monitoring - data acquisition and control. System hardware configuration – SCADA and EMS functions. Network topology - state estimation - security analysis and control. Various operating states (Normal, alert, emergency, in-extremis and restorative). State transition diagram showing various state transitions and control strategies.

Reading List: 1. Elgerd, O.I. (2003). Electric Energy Systems theory An introduction (2nd ed.). Tata

McGraw Hill Publishing Company Ltd. New Delhi, ISBN: 13: 9780070992863

2. Halder, S, & Chakrabarti, A. (2010). Power System Analysis: Operation and Control, PHI Learning , ISBN-13: 978-8120340152

3. Halder, S, & Chakrabarti, A. (2010). Power System Analysis: Operation and Control. PHI Learning , ISBN-13: 978-8120340152

4. Kundur P. (2010). Power System Stability and Control, Tata McGraw Hill Education Pvt. Ltd., New Delhi, ISBN: 13: 9780070359581

5. Ramana, N.V. (2011). Power System Operation and Control. Pearson, ASIN: B00BIZS35A

6. Wood, A. J., Wollenberg, B.F. & Sheble, G.B. (2013). Power Generation, Operation, and Control (3rd ed.). Wiley-Interscience, ISBN-13: 978-0471790556

Table 7.12: CS 604 Power System Modelling Course Code CS604 Total Credits: 12 Course Name Power System Modelling

Delivery Mode:

Lecture Hrs/Sem

Tutorial Hrs/Sem

Practical Hrs/Sem

Assignment Hrs/Sem

Independent Studies Hrs/Sem

Total Hrs/Sem

45 15 15 15 30 120

28 

Assessment Mode:

Continuous Assessment (50%) + University Examination (50%)

Prerequisites: Control Engineering Fundamentals Objective: The objective of this course is to provide the attendees with comprehensive

knowledge on power system modelling. This would include modelling of power networks, generating units and loads, the fundamental concept of power system stability and methods of analysis. Knowledge on advanced methods based on FACTS would also be discussed. It also aims to equip the attendees with an awareness of the advanced modeling, and analysis techniques applicable to power systems.

Learning Outcomes:

Upon successful completion of this course, the student will be able to i. Sound understanding of the characteristics and modelling process of

synchronous machines ii. Sound understanding of the system loads in power system stability

studies, their uses in the design of controllers and development of techniques for assessment and improvement of system performance under steady state, dynamic and transient conditions.

iii. Sound understanding of the concepts of operation, modelling of power electronics-based FACTS devices

iv. An understanding of how FACTS devices enhance power network performance.

v. An insight into the actual application of modelling in solving practical issues in power systems through case studies.

vi. An excellent starting place for graduate students interested in carrying out research in related fields.

Course Contents: Unit I: Introduction

Components of power system. The need for modeling of power system, different areas of power system analysis.

Unit II: Modeling of Synchronous Machine Synchronous Machine, Park’s Transformation, Per Unit Quantities, Equivalent

Circuits of synchronous Machine, Determination of parameters of equivalent circuits, Analysis of Steady State Performance, Transient Analysis of synchronous machine.

Unit III: Modeling of non-electrical Components Simplified models of non-electrical components like boiler, steam & hydro-turbine &

governor system. Unit IV: Modeling of Transmission Line and Transformer Modeling of Transmission line, Transformation to D-Q components, steady state

equations, D-Q transformation using α – β variables. Transformer modeling such as tap-changing & phase-shifting transformer.

Unit V: Modeling of excitation system

29 

Types of excitation systems, Modeling of excitation system components, Models of standard excitation systems.

Unit VI: Modeling of AC Loads Type of Loads, Basic load modeling concepts, modeling of general AC loads,

modeling of induction machines, modeling of synchronous machines. Unit VII Modeling of FACTS controllers Modeling of phase control based SVCs, Modeling of SVCs, Modeling Classical

(phase control based) HVDC systems, Modeling of HVDC Light® Systems, Modeling of controls for Distributed Generation systems, Concepts of deregulation

Reading List: 1. Anderson, P.M. & Fouad, A.A. (2002). Power system Control and Stability (2nd ed.)

Wiley-IEEE Press, ISBN-13: 978-0471238621. 2. Journal articles and conference articles on FACTS Controllers. This is somehow

current technology and therefore most of readings can be obtained from Journal/Conference articles and industry brochures.

3. Journal articles, conference articles and industry (ABB, GE, etc) brochures on HVDC Lihgt. This is somehow current technology and therefore most of readings can be obtained from Journal/Conference articles and industry brochures.

4. Kundur, P. (2008). Power system Dynamics Stability and Control. Tata McGraw Hill, ISBN: 13, 9780470725580

5. Mathur, R.M, & Varma, R. K (2002). Thyristor-Based FACTS Controllers for Electrical Transmission Systems. IEEE Press, Wiley-InterScience, ISBN-13: 978-0471206439

6. Padiyar, K.R. (2004). Power system Dynamics: Stability and Control. Anshan, ISBN-13: 978-1904798019

7. Sauer, P.W, & Pai, M.A. (2007). Power system Dynamics Stability. Stipes Publishing Co, ISBN-13: 978-1588746733.

8. Tleis, N. (2007). Power Systems Modelling and Fault Analysis: Theory and Practice. Newnes, ISBN-13: 978-0080974453

Table 7.13: CS 605 Smart Grid Course Code CS 605 Total Credits: 12 Course Name Smart Grid Subject Status Elective

Delivery Mode:

Lecture Hrs/ Sem

Tutorial/ Hrs/ Sem

Practical Hrs/ Sem

Assignment Hrs/ Sem

independent studies Hrs/ Sem

Total Hrs/Sem

45 15 15 15 30 120 Assessment Mode:

Course Work: 50 Final Exam: 50

30 

Prerequisites: None Objective: i. Learn about the new intelligent energy grid

ii. Review the communication technology for distribution automation of AC energy and then advance into technology trade-off considerations.

iii. Gain a solid technical foundation for understanding smart meters and home power networking.

iv. Introduce smart grid technologies, their applications and control issues covering Smart Generation (Renewable and Microgrid), Smart Transmission (Integration of Renewable Energy Sources, Wide Area Measurements) and Smart Distribution (Demand Response Management and Power Quality Management).

v. Provide a platform to explore the challenges and opportunities of smart grid for power system researchers and engineers.

Learning Outcomes:

i. Understand the grid architectures, evaluate the feasible in given context and implement the most suitable one

ii. Justify the need of technological change to smart grid and its deployment iii. Examine the impact of policies and market framework for smart grid iv. Recognise the need for smart grid and to know the attributes of the smart

grid. v. Apply device level information and communication technologies in power

system. vi. Discuss various Dynamic Energy Systems Concepts. vii. Define and explain the concept of Microgrid.

Course Contents:

Unit I: Introduction

Introduction to smart grid, electricity network, local energy networks, electric transportation, low carbon central generation, attributes of the smart grid, alternate views of a smart grid.

Unit II: Smart Grid to Evolve a Perfect Power System Introduction, overview of the perfect power system configurations, device level power

system, building integrated power systems, distributed power systems, fully integrated power system, nodes of innovation.

Unit III: Smart Grids: Command and Control, Metering and Home Area Networks Reviews communication technology necessary to control the network from the

generation site to the end appliance in a residential home. Introduce smart grid business model that uses consumer portals, automatic sensors, home networking and advanced metering infrastructure. Concept of energy -port, generic features of the energy port. Polices and programs in action; multinational, national, state, city and corporate levels. Framework, factors influencing customer acceptance and response. Data centers and information technology loads, future neighborhood.

Unit IV: Intelligrid Architecture for the Smart Grid Introduction, launching intelligrid, intelligrid today, smart grid vision based on the

intelligrid architecture, barriers and enabling technologies. Unit V: Dynamic Energy Systems Concept smart energy efficient end use devices, smart distributed energy resources, advanced

whole building control systems, integrated communications architecture, energy

31 

management, role of technology in demand response, current limitations to dynamic energy management, distributed energy resources, overview of a dynamic energy management, key characteristics of smart devices, key characteristics of advanced whole building control systems, key characteristics of dynamic energy management system.

Unit VI: Internet of Things and Energy Port as Part of the Smart Grid Translates linking and sharing of data to linking and sharing for smart objects.

Concept of energy-port, generic features of the energy port Unit VII: Microgrid Definitions, Advantages of Microgrid, Architecture and design of a Microgrid, and

Barriers in Microgrid. SCADA systems, securing smart grids, matching community needs, smart meters and devices in the context of establishing microgrids. Definitions, Advantages of Microgrid, Architecture and design of a Microgrid.

Reading List: 1. Blume, S.W. (2007). Electric Power System Basics for the Nonelectrical

Professional. Wiley-Interscience, ISBN-13: 978-0470129876 2. Bush, S.F. (2014). Smart Grid: Communication-Enabled Intelligence for the Electric

Power Grid. Wiley-IEEE Press, ISBN: 978-1-119-97580-9 3. Gellings, C.W. (2009). The Smart Grid: Enabling Energy Efficiency and Demand Side

Response. CRC Press, ISBN-13: 978-1439815748 4. Iniewski, K. (2012). Smart Grid Infrastructure & networking. McGraw-Hill

Education, ISBN-13: 978-0071787741. 5. Jenkins, N., Liyanage, K, Wu, J., & Yokoyama, A. (2012). Smart Grid:Technology

and Applications. Wiley, ISBN-13: 978-0470974094 6. Momoh, J. (2012). Smart Grid: Fundamentals of Design and Analysis. Wiley, IEEE

Press. ISBN-13: 978-0470889398 7. Stephens, J.C. , Wilson, E.J. & Peterson,T.R. (2015). Smart Grid (R)Evolution:

Electric Power Struggles. Cambridge University Press, ISBN-13: 978-1107047280. 8. Vyas, B., & Paliwal, N. (2015). Smart Grid Technology. Ashirwad Publications,

ISBN: 9789383266449 9. Wood, A. J., Wollenberg, B.F., & Sheble, G.B. (2013). Power Generation,

Operation, and Control (3rd ed.). Wiley-Interscience, ISBN-13: 978-0471790556 Required Laboratory Equipment: N/A

Table 7.14: CS 606 Research Methods in Science and Engineering Course Code CS 606 Total Credits: 12 Course Title Research Methods in Science and Engineering

Delivery Mode:

Lecture Hrs/Sem

Tutorial Hrs/Sem

Practical Hrs/Sem

AssignmentHrs/Sem

Independent Studies Hrs/Sem

Total Hrs/Sem

45 15 15 15 30 120

Assessment Mode:

Continuous Assessment (50%) + University Examination (50%) (Shall include developing a research proposal as part of the coursework assessment)

Prerequisites: None

32 

Objective: To provide students with the broad spectrum of knowledge on developing scientific thinking in addressing scientific problem, knowledge gap in the field of specialization and solving real life problems through acceptable research methods and procedures. Intends to enable students to initiate, implement and write up research, whether it is for a research project, a dissertation or thesis, a paper, a journal article or for competitive intelligence purposes.

Learning Outcomes:

By the end of the course the student should acquire the following skills and knowledge to: i. Explain the meaning of the terms “research”, “research

methodology”, and “research methods” and distinguish between modes 1, 2 and 3 types of research.

ii. Explain how scientific knowledge differs from non-scientific forms of knowledge.

iii. Explain the gap between research and practice/policy in the economic and management sciences.

iv. Identify the key elements of a scientific mindset v. Explain the five key dimensions of research, i.e. the epistemological,

methodological, sociological, ontological, and teleological dimensions.

vi. Describe various steps in the research process, including specification of problem statement, research question, hypotheses generation, choice of methods, and writing of the research report.

vii. Distinguish between quantitative and qualitative research including simulation, design, analytical and experimental methods.

viii. Access support material for researchers on the internet. ix. Make an informed choice from the large number of alternative

methods and experimental designs available. x. Explain how scientific and engineering research study results can be

interpreted, evaluated, and applied across many professions xi. Develop a research proposal and write research report (dissertation)

Course Contents: Unit I: Understanding the Philosophy of Research

The concept of academic research, nature of academic research (philosophy), Types of Research (Descriptive Vs Analytical, applied Vs fundamental, Quantitative Vs Qualitative). Research approaches – quantitative and qualitative approaches. Research Process.

Unit II: Formulating a Research problem

The research problem, sources of research problem, considerations in selecting a research problem, steps in formulating a research problem and objectives, the study population, identifying variables, constructing research questions and hypotheses and how they are differently applied.

Unit III: Conceptualizing a research design

Features of a good design. Concepts relating to research design. Selecting a study design, quantitative and qualitative study designs. Generation/formulation and of scientific original ideas and concepts.

Unit IV: Literature Review

The place of the literature review in research, how to review the literature, writing literature review, how to do citation from different sources, different referencing styles, problem in citing and referencing, copying and plagiarism. Extension of

33 

scientific research work from previous research work. Identifying research gap as potential for further research.

Unit V: Research Methodological concepts and approaches

Conceptual Framework, the role of theories in methodology, Sampling techniques, Criteria of selecting a sampling procedure. Different types of sample designs. Scientific research approaches including analytical, design, modeling, simulation and experimental.

Unit VI: Formulation and Selection of research instruments, equipment, tools and materials.

Selection of research equipment, tools and materials: determining specifications of equipment, tools and materials, determining critical requirements for experimental research set-up, determining requirements for modeling and simulation set-up, determining for real-time simulation set-up, mapping of real-time simulation to real-world situation.

Unit VII: Establishing the validity and reliability of a research instrument

Types of validity in quantitative research, validity and reliability in qualitative research.

Unit VIII: Design, Simulation and Data Analysis Tools

Using application software both for qualitative and quantitative data analysis like Excel, SPSS, Stata and Nnvivo. Should include engineering/computer science based software: Matlab/Simulink (contains even statistical analysis), Maple (for symbolic computation - Matlab can also do symbolic computation), PSCAD, IDE for Digital Systems (Xilinx, Altera Software), etc. the candidates should only be introduced with the tools. Candidates should be able to go into details of specific tools themselves while they doing research.

Unit IX: Writing a research proposal

How to write a research proposal, the research proposal in quantitative and qualitative research, contents of a research proposal.

Unit X: Writing a research report

Steps in writing report. Layout of the research report (Preliminary pages, Main text, End matter), writing variables, referencing, Research methodology and practice evaluation. Types of reports.

Unit XI: Dissemination of Research Findings/Results

How to write research and academic publication, Assessing and analyzing Literature review, structuring paragraphs, tenses in research and academic writing; linking ideas and arguments, connectives, how to use research and academic writing supporting tools like EndNote, Mendeley Desktop. Presentations of research findings in conferences and to the public, organization and effective preparation of research findings, preparation of presentation slides, colouring of slides, effective colour contrast for texts, diagrams and figures, clarity readability of diagrams and figures, readable text size and colour, etc.

Reading List: 1. Barrow, M. M. (2013). Statistics for Economics, Accounting and Business Studies

(6th ed.). Pearson Education Limited, ISBN: 978-0273764335. 2. Bryman, A. (2012). Social Research Methods (4th ed.). Oxford University Press,

ISBN: 978-0199588053. 3. Creswell, J. W. (2013). Research Design: Qualitative, Quantitative, and Mixed

Methods Approaches (4th ed.). SAGE Publications Inc , ISBN-13: 978-1452226101.

4. Kothari, C. R. (2013). Research Methodology, Methods and Techniques (3rd ed.).

34 

New Age International Pvt Ltd Publishers, ISBN-13: 978-8122436235 5. Krishnan, N. (2013). Engineering Research Methodology A Computer Science and

Engineering and Information and Communication Technologies Perspectiv (1st ed.) accessible online https://www.researchgate.net/publication/259183120_Engineering_Research_Methodology_A_Computer_Science_and_Engineering_and_Information_and_Communication_Technologies_Perspective

6. Kumar, R. (2014). Research Methodology: A Step-by-Step Guide for Beginners (4th ed.). SAGE Publications Ltd, ISBN-13: 978-1446269978.

7. Patton, M. Q. (2014). Qualitative Research & Evaluation Methods: Integrating Theory and Practice (4th ed.). SAGE Publications, Inc, ISBN: 978-1412972123

8. Thiel, D.V. (2014). Research Methods for Engineers (1st ed.). Cambridge University Press,ISBN-13: 978-1107610194

9. Yin, R.K. (2013). Case Study Research: Design and Methods (5th ed.). SAGE Publications, Inc, ISBN: 978-1452242569

Required Laboratory Equipment: Computers with installed referencing and data analysis packages (Excel, Stata,

SPSS, Nnvivo, Mendeley, EndNote), Matlab/Simulink, Xilinx, Altera, FPGA development Kits, Realtime simulation kits.

Table 7.15: CS 607 Hardware Description Language Course Code CS 607 Total Credits: 12 Course Name Hardware Description Language

Delivery Mode:

Lecture Hrs/Sem

Tutorial Hrs/Sem

Practical Hrs/Sem

Assignments Hrs/Sem

Indep. Studies

Total Hrs/Se

45 15 15 15 30 120 Assessment Mode:

Continuous Assessment (50%) + University Examination (50%)

Prerequisites: Programming experience in high-level programming language such as

C, C++, Java, etc.

Basic knowledge on digital logic fundamentals. Objective: The objective of the course is to introduce to students methodologies and

computer-aided design (CAD) tools for the design of complex electronic systems. Emphasis is on high-level description languages and their use for specifying, designing, simulating and synthesizing digital circuits into FPGA (Field Programmable Gate Array) devices. Students will learn coding for synthesis, good digital design practices, and writing test benches for exercising the designs. Special attention will be devoted to VHDL.

Learning Outcomes:

Upon completion, students should be able to: Course learning Goals:

i. Describe the behavior and performance of designs targeting FPGAs ii. Translate a functional system description into appropriate digital

blocks coded in VHDL

35 

iii. Perform synthesis, place-and-route and map a digital design onto a target FPGA

iv. Simulate the behavior of VHDL designs using testbenches written in VHDL and simulated using appropriate simulator (such as Xilinx ISIM or ModelSim)

v. Convert between different VHDL data types using arithmetic libraries

Course Contents: Unit I: Introduction Why HDL, brief history of HDL, Procedural programming languages versus Hardware

description languages Unit II: Code structure, data types, Operators and Attributes Fundamental VHDL units, LIBRARY Declarations, Entity, Architecture; standard data

types, user-defined data types, subtypes, arrays, port array, Records, data conversion; Operators (logical, relational, shift, adding, multiplying), attributes, user-defined attributes, operator Overloading, Generic

Unit III: Behavioral Modeling Entity declaration, architecture body, Statements: process, variable assignment, signal

assignment, Wait, If, Case, Null, Loop, Exit, Next, Report; Unit IV: Signals and Variables CONSTANT, SIGNAL, VARIABLE, SIGNAL versus VARIABLE, Number of

Registers, Using signals in a process Unit V: State Machines Combinational and sequential components, Output and Next State Functions Unit VI: Subprograms, Packages, and Libraries FUNCTION, PROCEDURE, ASSERT; PACKAGE, COMPONENT, PORT MAP,

GENERIC MAP Unit VII: Model Simulation Simulation, Writing a Test Bench (waveform generation and monitoring behaviour,

Overloaded Read and Write procedures), Validation, File Objects (text and Binary Files), dumping results into a text file.

Reading List: 1. Botros, N.M. (2005). HDL Programming Fundamentals: VHDL and Verilog (1st ed.).

Charles River Media, ISBN-13: 978-1584508557 2. Chu, P.P. (2008). FPGA Prototyping by VHDL Examples: Xilinx Spartan-3 Version

(1st ed.). Wiley-Interscience, ISBN-13: 978-0470185315 3. Kloos, C.D. (2013). Hardware Description Languages and Their Applications:

Specification, Modelling, Verification and Synthesis of Microelectronic Systems.Springer-Verlag New York Inc., ASIN: B010B9GQIY

4. Lin. M. (2008). Digital System Designs and Practices: Using Verilog HDL and FPGAs (1st ed.). Wiley, ISBN-13: 978-0470823231

36 

5. Navabi , Z. (2010). Digital System Test and Testable Design: Using HDL Models and Architectures 2011th Edition. Springer, ISBN-13: 978-1441975478

6. Pedroni, V. A. (2010). Circuit Design and Simulation with VHDL (2nd. ed.). The MIT Press, ISBN-13: 978-0262014335

7. Readler, B. (2011).Verilog by Example: A Concise Introduction for FPGA Design.Full Arc Press,ISBN-13: 978-0983497301

8. Readler, B. (2014). Vhdl By Example. Full Arc Press, ISBN-13: 978-0983497356 Required Laboratory Equipment:

Xilinx Foundation ISE or Modelsim, FPGA based development boards (e.g. Xilinix Training kits)

Table 7.16: CS 608 Optimization and Operations Research Course Code CS 608 Total Credits: 12 Course Name Optimization and Operations Research Delivery Mode:

Lecture

Hrs/Sem

Tutorial

Hrs/Sem

Assignment

Hrs/Sem

Independent

Studies Hrs/Sem

Practical

Hrs/Sem

Total

Hrs/Semester

45 15 15 15 30 120 Assessment Mode:

Continuous Assessment (50%) + University Examination (50%)

Prerequisites: Optimization methods Objective: The objectives of the course are to:

i. Introduce students to use quantitative methods and techniques for effective decisions–making.

ii. Enable students understand the interfacing of human decision-makers, computer science, and information systems.

iii. Enable students model formulations and applications used in solving decision problems as applies to operation research

Learning Outcome:

Upon successful completion of this course, the student will be able to: i. Describe Optimization and Operations Research concepts and their

relationships; ii. Articulate mathematical theory of optimization models and algorithm;

iii. Describe operations research decision analysis and methodologies iv. Analyze and evaluate the complexity, efficiency and sensitivity of

optimization models solve problems of using the tools of operations research and information systems

v. Solve problems of using the tools of operations research and information systems

Course Contents: Unit I:Introduction

37 

  Optimization and Operations research definitions, roots and origins, organizations and impact; Appearance and Recognition of Operations Research; Operations Research Decision analysis; The methodology of operations research.

Unit II: Optimization: the mathematical theory of models and algorithms   Linear optimization: Geometry of linear optimization; The simplex method; Duality

theory; Sensitivity analysis; Network flows; Computational complexity of linear optimization; interior-point methods for linear optimization Unconstrained Optimization: Basics of uncontained optimization; methods of unconstrained optimization; Low-storage methods for unconstrained problems

Nonlinear Optimization: Optimality conditions for constrained problems; Feasible-Point methods; Penalty and barrier methods; Applications of nonlinear optimization

Deterministic Optimization: Generic optimization problems; linear programming; graph and network programming; combinational optimization and integer programming; multi-objective optimization

Stochastic Operations Research: Stochastic programming; Stochastic decision Processes; Game Theory

Unit III: Optimizations and computers: complexity and efficiency   The Algorithmic (IN-) Tractability of models ; Illustrative examples, Linear

Programming (LP), Minimization and Maximization problems, Linear Programming – Simplex Method for Maximizing; Simplex maximizing example for similar limitations, Mixed limitations; Mixed constraints and Minimization examples; Sensitivity Analysis: Changes in Objective Function, Changes in RHS. Feasible Solutions and Optimal Solutions. The Assignment Model: the Different Combinations Method and the Short-Cut Method.

Unit IV: Operations research and information systems: the implementation issues   Tradition OR/MS based decision systems; Interactive optimization; Decision support

systems: system architecture, levels of technology, development methodology Reading List:

1. Derigs, U. (2007). Optimization and Operations Research -Vol.1. United Kingdom: EOLSS Publishers Co Ltd, ISBN: 9781905839483.

2. Griva, I., Nash, S.G & Sofer, A. (2009). Linear and Nonlinear Optimization (2nd ed.). Philadelphia, Society for Industrial and Applied Mathematics, ISBN-13: 978-0898716610.

3. Hillier, F.S. & Lieberman, G.J. (2001). Introduction to Operational Research. McGraw Hill (7th ed.). ISBN-13: 978-0072321692

4. Puterman, M.L. (2005). Markov Decision Processes: Discrete Stochastic Dynamic Programming. Wiley, ISBN: 978-0471727828.

5. Winston, W.L. (2003). Operations Research: Applications and Algorithms (4th ed.). Duxbury Press, , ISBN-13: 978-0534380588.

38 

Table 7.17: CS 609 Adaptive Control

Course Code CS 609 Total Credits: 12 Course Name Adaptive Control

Delivery Mode:

Lecture Hrs/Sem

Tutorial Hrs/Sem

Practical Hrs/Sem

Assignments Hrs/Sem

Indep. Studies Hrs/Sem

Total Hrs/Sem

45 15 15 15 30 120 Assessment Mode:

Coursework (50%) + University Examination (50%).

Prerequisites: Control Systems Engineering Objective: The objective of this course is to provide knowledge of existing algorithms

for adaptive control, with a basic understanding of how to implement them. The subject of adaptive control provides a rigorous approach to design and analyze systems that incorporate feedback, learning, and adaptation using control theoretic tools. In this course the concepts of system identification and behaviour analysis using adaptive control schemes such as model reference adaptive control and self-tuning regulators will be taught. The issues of convergence, stability, and robustness will also be addressed. Various analytical methods in adaptive control will be discussed. Methods from averaging theory and singular perturbation will be developed. In addition, the course will provide the theoretical foundations of the field and introduce the student to research in adaptive control.

Learning Outcomes:

Upon completion, students should be able to: i. Demonstrate knowledge of the principal structures used for adaptive

control systems ii. Derive and analyze the properties of selected direct and indirect

adaptive control algorithms. iii. Estimate parameters of unknown dynamical systems iv. Design indirect self-tuning regulators (ISTR) via minimum degree pole

placement (MDPP) v. Design direct self-tuning regulators (DSTR) via minimum degree pole

placement (MDPP) vi. Design Model Reference Adaptive Controllers (MRAC) via the MIT

Rule vii. Design Model Reference Adaptive Controllers (MRAC) via

Lyapunov’s stability theory viii. Design adaptive controllers using input-output (I/O) stability theory

Course Contents: Unit I: Introduction Performance objectives and design constraints, Adaption concepts, Direct and

indirect adaptive control. The principle of certainty-equivalence Unit II: Recursive Parameter Estimation Recursive methods: Least square method, Extended least square, Instrumental

variable, maximum likelihood. Stochastic approximation Unit III: Model Reference Adaptive Control Parameterization of the certainty-equivalence controller. MRAC schemes for linear

systems with relative degree one and two. Lyapunov stability theory. Uniform global asymptotic stability of MRACs: uniform persistency of excitation condition

39 

Unit IV: Adaptive Pole Placement Control Simple APPC schemes, PPC for known plant parameters, Indirect APPC schemes,

Hybrid schemes, Stability issues with APPC Unit V: Robust Adaptive Control Schemes Robustness of adaptive systems. Unstructured and structured uncertainties,

Instability in adaptive systems, Robust adaptive laws, Dead-zone and projection-based technique

Unit VI: Averaging-based Analysis Averaging, Singular perturbation theory Unit VII: Adaptive Control of Nonlinear Systems Adaptive back-stepping. Design with over-parameterization. Tuning functions

method. Output-feedback design. Unit VIII: Gain Scheduling Linearization of nonlinear actuators, Gain scheduling methods, Time scaling,

Nonlinear Transformation Unit IX: Disturbance Rejection Adaptive regulation, internal model principle, Observers for disturbance, Phase-

locked loop structure Unit X: Self Tuning Regulators Design methods -Minimum variance, Linear quadratic (LQ), Pole placement,

Model following. Control methods - Pole placement control, Minimum variance control, Multistage predictive control

Reading list: 1. Astrom, K., & Wittenmark, B. (2008). Adaptive Control (2nd ed.). Dover

Publications, Mineola, NY, USA: ISBN-13: 978-020155 8661 2. Ioanno, P. & Fidan, B. (2006). Adaptive Control Tutorial. SIAM, Philadelpia, PA:

ISBN-10: 0-89871-615-2 3. Ioannou, P.A. & Sun, J. (2012). Robust Adaptive Control. Dover Publication,

ISBN-13: 978-0486498171 4. Kristic,M., Kanellakopoulos, I., & Kokotovic, P.V. (1995). Nonlinear and

Adaptive Control Design. Wiley, ISBN: 978-0-471-12732-1 5. Ljung, L. (1999). System Identification: Theory for the User (2nd Ed.). Prentice

Hall, ISBN-13: 978-0136566953 6. Tao, G. (2003). Adaptive Control Design and Analysis. John Wiley & Sons, Inc.

ISBN0471-27452-6 Required Laboratory Equipment:

1.

Computers with installed numerical computing and data visualization package - MATLAB, LabVIEW

2. Testing and Measuring Instruments – Digital Oscilloscope, Function/Pulse Generator

Table 7:18: CS 610 Problem Driven Group Project

Course Code CS 610 Total Credits: 12 Course Name Problem Driven Group Project

Delivery Mode:

Lecture Hrs/Sem

TutorialHrs/Sem

PracticalHrs/Sem

AssignmentsHrs/Wk

Independent Studies Hrs/Sem

Total Hrs/Sem

10 30 80 120 Assessment Progress Reports and Presentations (40%)

40 

Mode: Final Report, Presentation and Project Result Demonstration (60%) Prerequisites: None Objective: The objectives of the course are:

i. To develop the capacity to work in multidisciplinary settings to solve real life problems.

ii. To develop and enhance academia and industrial linkages. iii. To foster innovation and create business opportunities from

academic activities iv. Motivate learning in the students. v. Develop critical reasoning abilities in the students.

vi. Enable the students adopt critical thinking and structure knowledge in the context of problems in their field of study.

vii. Develop self-learning skills in the students. viii. To enhance entrepreneurship skills.

Learning Outcomes:

Upon completion, students should be able to: i. Take responsibility, or ownership, for their learning,

ii. Adopt better work habits and attitudes toward learning iii. Develop more independence in solving problems iv. Study questions and combine them using critical thinking skills to

come up with answers. v. Employ effective self-directed and self-motivated learning skills and

proactive thinking vi. Find and use appropriate resources for problem solving

vii. Utilize collaborative and team-work skills in problem solving Course Contents: The course instructor and learners shall work with industry and the society to identify

challenges in work places, service provision and industries and agree on how to approach and address the challenge. The challenges must be from societal and industrial challenges that aim at among other factors to improve productivity and/or comfort, efficiency, developing new ways/approached/products that are directly applicable and useful or affecting how people do things. The identified challenges shall be assigned to a group of students from three to a maximum of five for each challenge where each student shall be assigned specific task to address in the challenge such that they jointly through individual tasks shall address the challenge. All members of the group shall support team members to ensure success of their assignment without jeopardizing the responsibility of each of the team members academic role. Each shall be assessed the role as a team player and also own contribution through accomplishment of a given task within the challenge. The members shall be encouraged to work as a team while also knowing on their own task. They shall also be required to work closely with the community where the challenge was identified and interest to have it addressed indicated by them. The students will be allocated into groups with own role in the group and the instructor will guide the students in their project work. The students will be required to make a presentation of their work and their project result, as well as write a report. The assessment will be obtained from the process of solving the challenge, presentations, and report. Minimum requirement shall be providing working solution for the challenge. Hence, individual student contributions and understanding will be assessed as well

41 

as group solution. Therefore, the final marks are not uniformly distributed to each group members.

Reading List: 1. Knowlton, D. S. & Sharp, D. C. (2003). Problem-Based Learning in the

Information Age. Jossey-Bass, ISBN-978-0787971724. 2. Savin-Baden, M. (2000). Problem-Based Learning in Higher Education: Untold

Stories. Open University Press, ISBN- 978-0335203376. 3. Savin-Baden, M. (2008). A Practical Guide to Problem-based Learning Online.

Routlege, ISBN-0415437873. 4. Torp, L. & Sage, S. R. (2002). Problems as Possibilities: Problem-Based Learning

for K-16 Education (2nd ed.). Association for Supervision and Curriculum Development, ISBN- 978-0871205742

5. Uden, L.,& Beaumont, C. (2005). Technology and Problem-Based Learning. Information Science Publishing, ISBN-1591407443.

Table 7.19: CS 621 Distributed AlgorithmsCourse Code CS 621 Total Credits: 12 Course Name Distributed Algorithms

Delivery Mode:

Lecture Hrs/Sem

TutorialHrs/Sem

PracticalHrs/Sem

AssignmentsHrs/Wk

Independent Studies Hrs/Sem

Total Hrs/Sem

45 15 15 15 30 120 Assessment Mode:

Coursework (50%) + University Examination (50%).

Prerequisites: General knowledge about some distributed systems. Experience with sequential algorithms and their analysis.

Objective: i. Provide an introduction to the most important basic results in the area of distributed algorithms

ii. Learn distributed algorithms development techniques for shared memory and message passing models

iii. Study the main classes of parallel algorithms iv. Study the complexity and correctness models for distributed

algorithms v. Learn the conceptual models for the specification and verification of

distributed algorithms vi. Understand the complexity models of distributed algorithms

vii. Prepare interested students to begin independent research or take a more advanced course in distributed algorithms.

Learning Outcomes:

Upon completion of the course the student should be able to: i. Understand and account for models, limitations, and fundamental

concepts in the area of message passing and shared memory concurrency, and apply this understanding to example systems and algorithms.

ii. Adapt and design algorithms for execution in parallel and distributed environments.

iii. Analyze the algorithms for correctness, reliability, security and performance.

42 

Course Contents: Unit I: Properties of distributed algorithms Time and message complexity. Safety and liveness properties. Time in an

asynchronous system. Total correctness, invariants, fairness. Unit II: Basic algorithms Broadcast and convergecast algorithms. Spanning trees of various kinds. Breadth-

first search. Shortest paths. Unit III: Leader election Leader election in rings. Asynchronous leader election with identities. Synchronous

leader election by abusing the synchronous model. Unit IV: Fault tolerance Fault-tolerant consensus. Link failures: the two generals’ problem. Process failures

(stopping, Byzantine). Algorithms for agreement with stopping and Byzantine failures. Time bounds for consensus problems. Number-of-processor bounds for Byzantine agreement. Weak Byzantine agreement.

Unit V: Shared Memory Mutual exclusion: tournament algorithm, bakery algorithm. Complexity measures for

shared-memory algorithms Unit VI: Atomicity Atomic objects. Atomic snapshot algorithms. Atomic read/write register algorithms Reading List:

1. Attiya, H., & Welch, J. L. (2004). Distributed computing: Fundamentals, simulations, and advanced topics, (2nd ed.). United States: John Wiley & Sons. ISBN: 0471453242

2. Cachin, C., Guerraoui, R., & Rodrigues, L. (2011). Introduction to reliable and secure distributed programming. Germany: Springer-Verlag Berlin and Heidelberg GmbH & Co. K. ISBN: 3642152597

3. Fokkink, W. (2014). Distributed algorithms: An intuitive approach. Cambridge: The MIT Press. ISBN: 0262026775

4. Herlihy, M., &Shavit, N. (2008). The art of multiprocessor programming. Amsterdam: Morgan Kaufmann Publishers In. ISBN: 0123705916

5. Varela, C. A. (2013). Programming distributed computing systems: A Foundational approach. United States: MIT Press. ISBN: 0262018985

Table 7.20: CS 622 Cyber Security for Smart Grid Course Code CS 622 Total Credits: 12 Course Name Cyber Security for Smart Grid

Delivery Mode:

Lecture Hrs/Sem

Tutorial Hrs/Sem

Practical Hrs/Sem

Assignment Hrs/Sem

Independent studies Hrs/Sem

Total Hrs/Sem

45 15 15 15 30 120 Assessment Mode:

Coursework (50%) + University Examination (50%).

Prerequisites: Computer Security and Network Fundamentals Objective: The Course will provide students with the necessary elements of computer

security related to smart power grid. Students will gain a comprehensive

43 

knowledge on the potential threats, vulnerabilities, and risks of smart grid; and recent research advances and industrial practices on smart grid cybersecurity.

Learning Outcomes:

At the end of the course, students should be able to: i. Secure both clean and corrupted systems, protecting personal data,

securing simple computer networks, and safe Internet usage applicable in smart grid.

ii. Understand distributed computation in the grid with privacy and confidentiality guarantees applicable in smart grid.

iii. Incorporate approaches to secure networks, firewalls, intrusion detection systems, and intrusion prevention systems in protecting smart grid infrastructures

iv. Examine secure software construction practices including Security plans and standards.

v. Understand cybersecurity and privacy challenges in cyber-physical systems typical in smart grid.

Course Contents: Unit I: Smart grid and risk management Traditional power grid, smart grid architecture, smart grid security threats and

reported vulnerabilities Unit II: Common security tools Firewalls, access control list (ACL), virtual private network (VPN), intrusion

detection system (IDS), security information and event management, and anti-virus.

Unit III: Fundamentals of applied cryptography Symmetric and asymmetric crypto, one-way functions, common applications

and implementations Unit IV: Smart grid cybersecurity Advanced metering infrastructure (AMI) security; demand response security

issues in smart grid; home area network, gateway and neighborhood area network security; supervisory control and data acquisition (SCADA) system security

Unit V: Security and Privacy Cyber Security Challenges in Smart Grid, Load Altering Attacks, False Data

Injection Attacks, Defense Mechanisms, Privacy Challenges. Sensor Networks, Phasor Measurement Units, Communications Infrastructure, Fault Detection and Self-Healing Systems, Applications and Challenges

Reading List: 1. Anderson, R. J. (2008). Security engineering: A guide to building dependable

distributed systems (2nd ed.). Indianapolis, IN: Wiley Technology Pub, ISBN-13: 978-0470068526

2. Betz, D.J, & Stevens, T. (2011). Cyberspace and the State: Toward a Strategy for Cyber-Power. The International Institute for Strategic Studies, ASIN: B006JE3440

44 

3. Knapp, E. D., & Samani, R. (2013). Applied Cyber security and the smart grid: Implementing security controls into the modern power infrastructure. United States: Syngress Media,U.S., ISBN-13: 978-1597499989

4. Kramer, F. (2009). Cyberpower and National Security. Potomac Books, ISBN-13: 978-1597974233.

5. Sorebo, G. N., & Echols, M. C. (2011). Smart grid security: An end-to-end view of security in the new electrical grid. United States: CRC Press, ISBN-13: 978-1439855874

6. Stallings,W. (2016). Cryptography and Network Security: Principles and Practices (7th ed.). Pearson, ISBN-13: 978-0134444284

Table 7.21: CS 623 Secure Software Design and Programming Course Code CS 623 Total Credits: 12.0 Course Name  Secure Software Design and Programming

Delivery Mode:

Lecture Hrs/sem.

Tutorial/self-reading Hrs/Sem.

Practical Hrs/Sem.

Total Hrs/Semester

45 60 15 120 Assessment Mode:

Coursework: 50%, Final Exam: 50%.

Prerequisites: Programming Objective: The course provide theory and practice of software security, focusing on

common software security risks, including buffer overflows, race conditions and random number generation, and on the identification of potential threats and vulnerabilities early in the design cycle. It emphasises on methodologies and tools for identifying and eliminating security vulnerabilities, techniques to prove the absence of vulnerabilities, and ways to avoid security holes in new software and on essential guidelines for building secure software: how to design software with security in mind from the ground up and to integrate analysis and risk management throughout the software life cycle.

Learning Outcomes:

After completion of this course the students will have understanding on concepts of software security and ability to develop software with far fewer security vulnerabilities

Course Contents: Unit I : Overview

Attacker overview

Secure/Insecure Software

Software Security Problem Unit II : Error Checking and Handling

Input Validation

Buffer Overflows

45 

Errors /exceptions handling Unit III: Cryptography, Access control and Internet Vulnerabilities

Privacy, Secrets, and Cryptography

Implementing Authentication and Access Control

Web Application Vulnerabilities Unit IV: Secure Programming, Code analysis, and Virtualization

Secure Programming Best Practices

Static Code Analysis and Runtime Analysis

Virtualization : Securing Virtual Machines Unit V: Network Security

Usability [phishing]

Privilege Separation

Java Security

Network Security & Worms Unit VI: Security Testing and Risk Management

Security Testing

Risk management as part of entire system life cycle Recommended Readings: 1. Chess, B. and West, J. ((2007), Secure Programming with Static Analysis. Addison-

Wesley Professional, ISBN-13: 978-0321424778 2. Garfinkel,S, Spafford, G. Schwartz, A. (2003), Practical UNIX and Internet Security,

3rd Edition. O'Reilly Media, ISBN-13: 978-0596003234 3. Richardson, T. and Thies, C.N., (2012), Secure Software Design, Jones & Bartlett

Learning, ISBN-13: 978-1449626327 4. Wheeler, D.A. (2004),Secure Programming for Linux and Unix HOWTO. Available

at: http://www.dwheeler.com/secure-class/Secure-Programs-HOWTO.pdf

Required Laboratory Equipment: Linux Operating System

Table 7.22: CS 624 New Developments in Smart Grid Course Code CS 624 Total Credits: 12 Course Name New Developments in Smart Grid

Delivery Mode:

Lecture Hrs/Sem

Tutorial Hrs/Sem

Practical Hrs/Sem

Assignments Hrs/Sem

Indep. Studies Hrs/Sem

Total Hrs/Sem

45 15 15 15 30 120 Assessment Mode:

Continuous Assessment (50%) + University Examination (50%)

Prerequisites: None

46 

Objective: The objective of the course is to equip learners the learners with new developments in Smart Grid field.

Learning Outcomes:

Upon completion, students should be able to: i. Apply emerging applications in smart grid fields. ii. Describe new developments in smart grid technologies iii. Identify appropriate modelling, simulation, and evaluation schemes

and how to apply them effectively iv. Describe the role of the human in the emerging smart grid

technologies. v. Understand new researches in smart grid field

Course Contents: Unit I: Emerging trends in Smart Grid Technologies Emerging trends in different aspects of smart grid technologies, the technologies and its

projected impact Unit II: New Applications in Smart Grid Technologies New developments in control strategies, emerging security issues and its management

schemes, New monitoring and instrumentation techniques, energy storage techniques, emerging researches

Unit III: Emerging Modelling and Simulation Schemes / Tools Modelling and simulation strategies for addressing emerging challenges different smart

grid aspects Unit IV: Developments in Data Analytics Challenges New big data analytics and data mining challenges in smart grid environment research

and developments in big analytics and data mining, emerging security concerns in big data analytics

Reading List: 1. Berger, L. T., & Iniewski K. (2012). Smart Grid Applications, Communications,

and Security (1st ed.). Wiley, ISBN-13: 978-1118004395 2. IEEE Transactions on Smart Grid, most recent five years publications, Publisher;

IEEE 3. Iniewski, K. (2012). Smart Grid Infrastructure & Networking (1st ed.). McGraw-

Hill Education, ISBN-13: 978-0071787741 4. International Journal of Smart Grid and Green Communications, Publisher;

Inderscience Publishers, most recent five years publications 5. International Journal on Smart Grid and Renewable Energy, ISSN Online: 2151-

4844, Website: http://www.SciRP.org/journal/sgre, most recent five years publications

6. International Journal, Technology and Economics of Smart Grids and Sustainable Energy, ISSN: 2199-4706, most recent five years publications

7. Journal and Conference Papers, http://ses.jrc.ec.europa.eu/journal-and-conference-papers, publisher; EU Commission Institute for Energy and Transport (IET)

47 

8. Sato T., Kammen D. M., Duan B., Macuha M., Zhou Z., Wu J., Tariq M. , & Asfaw, S. A. (2015). Smart Grid Standards: Specifications, Requirements, and Technologies (1st ed.). Wiley, ISBN-13: 978-1118653692

Required Laboratory Equipment: Computers with installed numerical computing and data visualization packages -

MATLAB, LabVIEW

Table 7.23: CS 631 Mathematical Modeling and Methods Course Code CS 631 Total Credits: 12 Course Name Mathematical Modeling and Methods

Delivery Mode:

Lecture Hrs/Sem

TutorialHrs/Sem

Practical Hrs/Se

Assignments Hrs/Wk

Independent Studies Hrs/Sem

Total Hrs/Sem

45 30 15 30 120 Assessment Mode:

Coursework (50%) + University Examination (50%).

Prerequisites: None

Description:

This course introduces mathematical modeling using graphical, numerical, symbolic, and verbal techniques to describe and explore real-world data and phenomena. Emphasis is on the use of elementary functions to investigate and analyze applied problems and questions, supported by the use of appropriate technology, and on effective communication of quantitative concepts and results.

Objective: The objectives of this course are to: i. Provide the basic tools in formulating a mathematical model of a

physical system, analysing the mathematical model, interpreting the results, and predicting the behaviour of the original physical system

ii. Provide basic tools in solving the real world problems through mathematical modeling and approach

iii. Provide knowledge on the use of mathematics to help make sense of the real world: identify variables, formulate a model describing the relationship between the variables, interpret results, and validate and report the reasoning for real world problem solutions.

Learning Outcomes:

Upon successful completion of this course, the student will be able to i. Model situations from a variety of settings in mathematical forms by

extracting quantitative data from a given situation, translating the data into information in various modes, evaluating the information, extracting essential information, making logical deductions, and arriving at reasonable conclusions.

ii. Manipulate mathematical information, concepts and thoughts in verbal, numeric, graphical and symbolic forms while solving a variety of problems.

iii. Solve multiple-step problems through different (inductive, deductive, and symbolic) modes of reasoning.

48 

iv. Express mathematical information, concepts, and thoughts in verbal, numeric, graphical and symbolic forms while solving a variety of problems.

v. Shift among the verbal, numeric, graphical, and symbolic models of considering relationships.

vi. Use appropriate technology in the evaluation, analysis, and synthesis of information in problem solving situations.

Course Contents: Unit I: Mathematical Models Concepts Classification of problems; Types of models - deterministic models and models based

on empirical observations, Probabilistic and statistical models; Scientific models -physical models, conceptual models, and mathematical models; The modeling process; Formulation of linear programming (LP) models - graphical solutions, simplex method, duality theory and applications

Unit II: Computational and Mathematical Models Common problems in goodness-of-fit measures; Numerical measures of goodness-of-

fit and badness-of-fit inferential tests; and Uncertainty and randomness in models Unit III: Classic and Effective Models Equations governing the models; Results derived from the models; Improving model

solutions; Limitations of successful models; Specific models - dimensional analysis, sensitivity analysis, and optimization models

Unit IV: Solar Energy Fundamentals and Modeling Techniques Solar radiation deterministic models; Linear solar energy models; Non-linear solar

energy models; and Spatial solar energy models Unit V: Forecasting Models Mathematical models of power-line noise; Markov and nonparametric regression

models; and Computational modeling with optimal control Reading List:

1. Maki D. P. & Thompson M. (2005). Mathematical Modeling and Computer Simulation (1st ed.). Cengage Learning, ISBN-13: 978-0534384784

2. Tung, K. K. (2007). Topics in Mathematical Modeling. Princeton University Press. ISBN-13: 978-0691116426

3. Sen, Z. (2008). Solar Energy Fundamentals and Modeling Techniques: Atmosphere, Environment, Climate Change and Renewable Energy. Springer-Verlag London Limited. ISBN-13: 9781848001336

4. Meerschaert, M. M. (2013). Mathematical Modeling (4th ed.). Academic Press, ISBN-13: 978-0123869128

5. Bender, E. A. (2000). An Introduction to Mathematical Modeling. Dover Publications, ISBN-13: 978-0486411804

6. Banerjee, S. (2014). Mathematical Modeling: Models, Analysis and Applications (1st ed.). Chapman and Hall/CRC, ISBN-13: 978-1439854518

Table 7.24: CS 699 Dissertation Course Code CS 699 Total Credits: 60 Course Name Dissertation Prerequisites: Completed coursework

49 

Objective: The dissertation is aimed at providing training to students on how toapply the knowledge that they acquire in the programme towards solving practical real life problems. It tests a student's ability to integrate the knowledge acquired in the difference courses taught in the programme towards attaining the understanding of the course as a discipline that hasan array of tools that can be employed to aid problem solving in real life.

 

Table 7.25: ES 630 Power Electronics Course Code ES 630 Total

Credits 12

Course Name Power Electronics Delivery Mode

Lectures Hrs/Sem

Tutorials Hrs/Sem

PracticalHrs/Sem

Assignment Hrs/Sem

Independent Study Hrs/Sem

Total Hrs/Sem

45 15 15 15 30 120 Assessment Mode:

Coursework (50%) + University Examination (50%)

Prerequisites: None Objective: The main objective of this course is to enable students:

i. To understand and acquire knowledge about various power semiconductor devices.

ii. To prepare the students to analyze and design different power converter circuits.

Learning Outcome:

After this course, students are expected to be able to: i. Apply modelling, analysis, and control techniques to power

conversion processes and systems ii. Design power electronic circuits including inverters, rectifiers and

DC-DC converters iii. Analyze and design magnetic components, filters, power supplies,

and radio-frequency power amplifiers Course Contents: Unit I: Introduction Switching in power electronics, Rectification of AC, BJTs and

MOSFETs,Half and Full wave rectification, Filtering and rectification, Load Regulation; Power factor, Harmonic Distortion, Power factor compensation

Unit II: Rectifiers Phase controlled rectifiers; Silicon controlled rectifiers, Thyristors, Diacs Unit III: DC/DC Converters The Buck converter, The Boost converter, Buck-Boost converters, Direct

and Indirect converters, Ripples and Filters, Continuous and Discontinuous Conduction Modes.

Unit IV: Magnetics Ampere's and Faraday's Laws, Magnetization, Modelling Transformers,

Modelling Inductors, The Skin Effect and Losses, Hysteresis Eddy Currents

50 

Unit V: Isolated DC/DC Converters Flyback converter, Single-ended Forward Converter, Two-switch Single-

ended Forward Converter, Leakage Inductances,Double-ended Forward Converter Modelling and Control, Averaging, Circuit Simulation, Ripple Instability

Unit VI: DC/AC Inverters Fourier Series Analysis, Inverter Structures,PWM Control, Harmonic

Cancellation, Multilevel Converters, Sine-Triangle PWM, Inverter Control Techniques, Power factor Correction Rectifiers

Unit VII: Switching and Thermal Losses and Interference Switching Losses and Snubbers, Semiconductor Losses, Zero Voltage and

Zero Current Switching, Thermal Modelling and Heat sinking, Convection, Radiation, Conduction, Thermal Capacitance and Impedance Power MOSFET, Electromagnetic Interference, EMI Filtering Filter design for EMI control

Unit VIII: Three Phase Systems Delta and Y networks, Constant power sources, 3 phase rectification, Half

and Full wave rectification, Higher order rectifiers Unit IX: Resonant Power Conversion Resonant Circuits, Class D Convertors, Class E Convertors, Resonant

Gate Drives, Power Transfer and Matching Techniques Recommended Textbooks:

1. Erickson R. W. & Maksimovic D. (2001). Fundamentals of Power Electronics (2nd ed.). Springer, ISBN-13: 978-0792372707

2. Erickson R. W. (2013). Fundamentals of Power Electronics. Springer, ISBN-13: 978-1461576488

3. Hart, D. (2010). Power Electronics (1st ed.). New Jersey, NJ: McGraw-Hill Education, ISBN:978-0073380674.

4. Mohan N., Undeland T. M. & Robbins W. P. (2002). Power Electronics: Converters, Applications, and Design (3rd ed.). Wiley, ISBN-13: 978-0471226932.

5. Muhammad R. H. (2006). SPICE for Power Electronics and Electric Power (2nd ed.). Boca Raton, FL: CRC Press, ISBN: 9780849334184.

6. Shaffer R., (2006). Fundamentals of Power Electronics With Matlab (1st ed.). Charles River Media, ISBN-13: 978-1584508526

Required Laboratory Equipment: Analogue electronics experiment sets (DC Power source, AC power

source, oscilloscope, Digital Multimeter), power meters., LCR meters.

Table 7.26: IS 607 Artificial IntelligenceCourse Code IS 607 Total Credits: 12 Course Name Artificial Intelligence

Delivery Mode:

Lecture Hrs/Sem

TutorialHrs/Sem

PracticalHrs/Sem

AssignmentsHrs/Sem

Independent Study Hrs/Sem

Total Hrs/Sem

45 15 15 15 30 120 Assessment Coursework (50%) + University Examination (50%).

51 

Mode:

Prerequisites: Basics knowledge in Probability, Programming, Discrete Math/Mathematical Logic

Objective: The objective of this course is to give students an understanding of Artificial Intelligence methodologies, techniques, tools and results. The course will provide a strong foundation of fundamental concepts in Artificial Intelligence, basic exposition to the goals and methods of Artificial Intelligence and enable the student to apply these techniques in applications which involve perception, reasoning and learning. Students will learn the theoretical and conceptual components of this discipline and firm up their understanding by using AI and Expert System tools in assigned projects.

Learning Outcomes:

Upon completion, students should be able to: i. Identify problems that suggest themselves to AI solutions. ii. Articulate the strengths and limitations of various AI techniques iii. Apply AI techniques including, search, knowledge representation and

reasoning in problem solving. iv. Carry out a design in the framework of AI. v. Implement appropriate AI solutions for real world problems. vi. Use software tools in the implementation and analysis of intelligent

systems Course Contents: Unit I: Search Concept of search and the representation of spaces for search. Classes of search and

popular search algorithms. Unit II: Knowledge representation Goal behind knowledge representation and representation techniques. Semantics,

propositional logic and first-order logic in knowledge representation. Unit III: Machine learning Machine learning algorithms. Supervised and unsupervised learning, Unit IV: Neural Networks Supervised and unsupervised neural network learning rules. Feedforward and back

propagation algorithm. Associative neural networks. Unit V: Fuzzy logic Fuzzy sets theory and application. Fuzzy rules, fuzzification, defuzzification and

inference systems, Mamdani and Takagi-Sugeno fuzzy controllers. Unit VI: Evolutionary computing Natural evolution process and Genetic algorithms. Reading List:

1. Charles, D. (2007). Biologically Inspired Artificial Intelligence for Computer Games. IGI Global. ISBN-13: 978-1591406464

2. Engelbretch, A.P. (2007). Computational Intelligence: An Introduction (2nd ed.). Wiley, ISBN: 978-0470035610.

3. Jones, M.T. (2008). Artificial Intelligence: A Systems Approach. Laxmi Publications, ISBN: 978-8131804049.

4. Russel, S. & Norvig, P. (2009). Artificial Intelligence: A Modern Approach (3rd ed.). Pearson India, ISBN: 978-9332518698.

5. Shi, Z. (2011). Advanced Artificial Intelligence. World Scientific, ISBN: 978-9814291347.

6. Vlahavas, L. & Vrakas, D. (2008). Artificial Intelligence for Advanced Problem

52 

Solving Techniques. Information Science Reference, ISBN-13: 978-1599047058.

Table 7.27: IS 611 Advanced Object Oriented Programming Course Code IS 611 Total Credits: 12 Course Name Advanced Object Oriented Programming

Delivery Mode:

Lecture Hrs/Sem

TutorialHrs/Sem

PracticalHrs/Sem

AssignmentsHrs/Sem

Independent Studies Hrs/Sem

Total Hrs/Sem

45 15 15 15 30 120 Assessment Mode:

Coursework (50%) + University Examination (50%).

Prerequisites: Any Structured programming knowledge Objective: To equip students with knowledge on object-oriented programming

principles and techniques. To understand the differences between structured and object oriented programming. The course demonstrate ways in which object-oriented programming, in this case Java, facilitates code reusability in developing large and complex software.

Learning Outcomes:

Upon completion, students should be able to: i. Demonstrate an understanding of the underlying principles and concepts

of Object-Oriented Programming ii. Apply the concepts of data encapsulation, inheritance, and

polymorphism to large-scale software iii. Design and develop object-oriented computer programs iv. Design and develop programs with Graphical User Interfaces

capabilities v. Integrate robustness, reusability, and portability into large-scale

software development vi. Use an object-oriented language to develop rather complex programs

with team-work in mind Course Contents: Unit I: Basic concept of Object Oriented Programming (OOP) Evolution of OOPL, Comparison with Structured Programming, Features of Object

Oriented Programming, Classes and Objects, methods, constructors, overloaded methods and constructors, Access Control, Nested and Inner Classes, Exceptional Handling, Multithreading.

Unit II: Overview of Variables and Control Structures Primitives variables & reference variables, Java’s selection statements, iteration and

jump statements. Unit III: Java library (API) and user defined packages Exploring basic packages (lang, util), creating and using user defined packages. Unit IV: Inheritance and Polymorphism Inheritance tree, abstract classes and abstract methods, interfaces, methods

overloading and overriding. Unit V: Graphical User Interface (GUI) Development and Java Applets

53 

Introduction to GUI, layout managers and components, Event Handling and developing applets.

Unit VI: Data Capture, Storage and Retrieval Interactivity (application receive user inputs), I/O basics, Byte Streams and Character

Streams, Predefined Streams, reading and writing console input/output, reading and writing files

Unit VII: Connectivity Database Connection (JDBC, Hibernate), Socket Programming. Unit VIII: Distributed Computing and Web based java application Remote Method Invocation (RMI), Web services in Java, Servlets/Struts, JSPs,

EJBs/Springs. Unit IX: Java Application Packaging and Deployments Local, Semi-local and Remote deployments. Reading list:

1. Arnold, K., Gosling J., & Holmes, D. (2005). The Java Programming Language (4th ed.). Prentice Hall, ISBN: 978-0321349804.

2. Bishop, J. (2001). Java Gently: Programming Principles Explained (3rd ed.). Addison-Wesley, ISBN: 9780201751574.

3. Deitel, H.M. & Deitel, P. J. (2007). Java How to Program illustrated (9th ed.). Prentice Hall, ISBN: 978-0132575669.

4. Horstmann C. S. & Cornell G. (2012). Core Java 2 (Volume I-Fundamentals) (9th ed.). Prentice Hall, ISBN: 978-0137081899.

5. Kak, A. (2003). Programming with Objects: A Comparative Presentation of Object Oriented Programming with C++ and Java. Wiley-IEEE Press, ISBN: 978-0471268529.

6. Sierra, K. & Bates, B. (2007). Head First Java (2nd ed.). O´Reilly, ISBN: 978-0596009205.

Required Laboratory Equipment: Java Development Kit (JDK), Integrated Development Environment (IDE) such

as eclipse or NetBeans

Table 7.28: IS 614 Multimedia Communication and Systems Course Code IS 614 Total Credits: 12 Course Name Multimedia Communication and Systems

Delivery Mode:

Lecture Hrs/Sem

TutorialHrs/Sem

PracticalHrs/Sem

AssignmentsHrs/Sem

Independent Study Hrs/Sem

Total Hrs/Sem

45 15 15 15 30 120 Assessment Mode:

Coursework (50%) + University Examination (50%).

Prerequisites: Any programming language. Knowledge in Computer Network and Operating System.

54 

Objective: Students will be introduced to principles and current technologies of multimedia systems. Issues in effectively representing, processing, and retrieving multimedia data such as sound and music, graphics, image and video will be addressed. The students will gain hands-on experience in those areas by implementing some components of a multimedia streaming system as their term project. Latest Web technologies and some advanced topics in current multimedia research will also be discussed.

Learning Outcomes:

Upon completion, students should be able to: i. Describe different multimedia tools and how they are being used ii. Analyze the structure of the tools in the light of low-level constraints

imposed by the adoption of various QoS schemes (ie bottom up approach)

iii. Analyze the effects of scale and use on both presentation and lower level requirements (ie top down approach)

iv. Plan experiments to test user perception of multimedia tools • state the properties of different media streams; compare and contrast different multicast protocols

v. Describe mechanisms for providing QoS guarantees in the network and propose experiments to analyze their performance.

Course Contents: Unit I: Overview of Multimedia Processing & Coding Overview of Multimedia Services and Applications, Video coding fundamentals,

Lossless Compression & Lossy Compression Transform Coding, Motion Compensated Predictive Coding.

Unit II: Multimedia Coding Standards Audio (Pulse Code Modulation – PCM, GSM, MP3), GIF, JPEG/JPEG-2000,

H.26x, MPEG-1/4/7, AVC and Scalable Video Coding Unit III: Multimedia Networking End-to-End QoS for Video Delivery, Wireless Video , Error Control in Video

Streaming and Cross-Layer Video Adaptation Reading List:

1. Mihaela, S. & Philip, C. (2007). Multimedia over IP and Wireless Networks: Compression, networking, and Systems. Academic Press, ISBN: 978-0124156982.

2. Mitra, S. & Bhatnagar, G. (2001). Introduction to Multimedia Systems (Communications, Networking and Multimedia) (1st ed.). Academic Press, ISBN-13: 978-0125004527.

3. Rao, K. R. , Bojkovic, Z.S., & Milovanovic, D.A. (2002). Multimedia Communication Systems: Techniques, Standards, and Networks (1st ed.). Prentice Hall, ISBN-13: 978-0130313980.

4. Steinmetz, R. and Nahrstedt, K. (2004). Multimedia Systems. X.media.publishing, ISBN-13: 978-3540408673

5. Sun, M. (2000). Compressed Video over Networks. CRC Press, ISBN: 978-0824794231.

55 

6. Yao, W., Joern, O., & Ya-Qin, Z. (2001). Video Processing and Communications. Prentice Hall, 978-0130175472.

Table 7.29: IS 631 Advanced Data Warehousing and Data Mining Course Code IS 631 Total Credits: 8

Course Title Advanced Data Warehousing and Data Mining

Delivery Mode:

Lecture Hrs/Sem

Tutorial Hrs/Sem

Practical Hrs/Sem

Assignment Hrs/Sem

Independent Study Hrs/Sem

Total Hrs/Sem

30 6 6 8 30 80 Assessment Mode:

Coursework (50%) + University Examination (50%).

Prerequisites: Database management Systems, Programming Basics, SQL skills

Objective: To provide students with in-depth knowledge, skills and understanding in the areas of Data Warehousing and Data Mining. This includes their role, utilization and benefits for organisations, as well as architectures and underlying technologies relevant for their development.

Learning Outcomes:

Upon completion, students should be able to:

i. Gather requirements for data warehousing ii. Represent a data set in a form that will be useful for data mining iii. Design, develop and maintain data warehouse iv. Evaluate different models used for OLAP and data pre-processing; v. Formulate a data mining problem vi. Evaluate the performance of different machine learning algorithms vii. Critically select appropriate tools, representations and algorithms for a

given data mining scenario Course Contents:

Unit I: Introduction to data warehouse Data Warehouse Definitions, Value of Datawarehouse, Reasons for building Data

warehouse, Reasons for NOT building. Datewarehousing: Properties, Datawarehousing: Applications, Multidimensional Model/ Data Modelling in DW, Hierarchy of Data, Operations in Multidimensional Model, Multidimensional Schema , Star Schema, Snowflake Schema, Fact Constellation, and other topics.

Unit II: Data Warehouse modeling and Architecture Datawarehousing Architecture Views (From different perspectives: IT Infrastructure,

Data Flow Business Usage and BI Application Development). Data Warehouse Project Planning, Extraction, Translation and Loading (ETL), Transform and Loading techniques. Source, Processing and Target Stages. ELTOracle Warehouse Builder

56 

exercise. Discussion of at least two major Datawarehousing Architectures and compare the two and strategy for choosing the best Architecture

Unit III: Data warehousing Systems and Components Source systems, Data Acquisition, Data Processing system, Data Loading system,

Datawarehousing Management components (scheduler, Backup & Recovery, Monitoring)

Unit IV: Data warehousing Design and Development Types of development models, Development Stages, Designing Datawarehousing

Systems Unit V: Online Analytical Processing Difference between a Database, Datawarehouse, On-line Transaction Processing

(OLTP) and OLAP. OLAP Operations, OLAP Data Structures / Construction, Business Analytics mapping

Unit VI: Data Warehouse Administration and Security Overview of Data Warehouse Security, Using Roles and Privileges for Data

Warehouse Security, Using Virtual Private Database in Data Warehouses, Overview of

Oracle Label Security, Overview of Fine-Grained Auditing in Data Warehouses,

Overview of Transparent Data Encryption in Data Warehouses

Unit VII: Introduction to Data mining Overview, Motivation(for Data Mining),Data Mining-Definition & Functionalities,

Data Processing, Form of Data Preprocessing, Data Cleaning: Missing Values, Noisy

Data,(Binning, Clustering, Regression, Computer and Human inspection),Inconsistent

Data, Data Integration and Transformation. Data Reduction:-Data Cube Aggregation, Dimensionality reduction, Data Compression, Numerosity Reduction, Clustering,

Discretization and Concept hierarchy generation

Unit VIII: Concept Description Definition, Data Generalization, Analytical Characterization, Analysis of attribute

relevance, Mining Class comparisons, Statistical measures in large Databases.

Measuring Central Tendency, Measuring Dispersion of Data, Graph Displays of Basic

Statistical class Description, Mining Association Rules in Large Databases, Association rule mining, mining Single-Dimensional Boolean Association rules from

Transactional Databases– AprioriAlgorithm, Mining Multilevel Association rules from

Transaction Databases and Mining Multi-Dimensional Association rules from Relational Databases

Unit IX: Classification and Predictions What is Classification & Prediction, Issues regarding Classification and prediction,

Decision tree, Bayesian Classification, Classification by Back propagation, Multilayer

57 

feed-forward Neural Network, Back propagation Algorithm, Classification methods K-

nearest neighbor classifiers, Genetic Algorithm.

Unit X: Cluster Analysis Data types in cluster analysis, Categories of clustering methods, Partitioning methods.

Hierarchical Clustering- CURE and Chameleon, Density Based Methods-DBSCAN,

OPTICS, Grid Based Methods- STING, CLIQUE, Model Based Method –Statistical

Approach, Neural Network approach, Outlier Analysis

Reading List: 1. Aggarwal, C.C. (2015). Data Mining: The Textbook. Springer, ISBN-13: 978-

3319141411 2. Jensen, C.S., Pedersen, T.B., Thomsen, C., & Ozsu, M.T. (2010). Multidimensional

databases and data warehousing. Morgan and Claypool Publishers , ISBN-13: 978-1608455379

3. Kamber, M. & Pei, J. (2011). Data Mining: Concepts and Techniques (3rd ed.). Morgan Kaufmann, ISBN-13: 978-0123814791

4. Malinowski, E. & Zimányi, E. (2011). Advanced Data Warehouse Design: From Conventional to Spatial and Temporal Applications (2nd ed.). Springer, ISBN-13: 978-

3540744047 5. Matteo G., & Rizzi S. (2009). Data warehouse design : modern principles and

methodologies. McGraw Hill, ISBN:978-0-07-161039-1 6. Radulovich, D. (2014). Data Mining A Crash Course for Scientists and

Engineers. CreateSpace Independent Publishing Platform, ISBN-13: 978-1500884994 7. Witten, I.H & Frank, E. (2011). Data Mining: Practical Machine Learning Tools and

Techniques (3rd ed.). Morgan Kaufmann, ISBN-13: 978-0123748560 Required Laboratory Equipment: Computers with installed open source database management systems like

XAMP/WAMP and data mining software such as SPSS, SAS, Angoss Software.  

Table 7.30: IS 654 Cloud Computing Course Code IS 654 Total Credits: 12 Course Name Cloud Computing

Delivery Mode:

Lecture Hrs/Sem

Tutorial Hrs/Sem

Practical Hrs/Sem

Assignment Hrs/Sem

Independent Hrs/Sem

Total Hrs/Sem

45 15 15 15 30 120 Assessment Mode:

Coursework (50%) + University Examination (50%).

Prerequisites: Computer architecture, operating systems, networking, and databases Objective: This course provides a hands-on comprehensive study of Cloud concepts and

capabilities across the various Cloud service models including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Software as a Service (SaaS), and Business Process as a Service (BPaaS). It introduces the basics of the

58 

emerging cloud computing paradigm, learn how this paradigm came about, understand its enabling technologies, and understand the computer systems constraints, tradeoffs and techniques in setting up and using the cloud.

Learning Outcomes:

Upon completion, students should be able to: i. Describe the concept of Cloud as PaaS, IaaS ii. Work in cloud environment iii. Build their own cloud iv. Demonstrate the role of Cloud Consultant v. Visualize, HA, DR planning

Course Contents: Unit I: Classical Data Centre (CDC) foot prints & Concepts Key elements of a CDC (compute, storage, and network), Common storage

networking technologies in a CDC. Unit II: Introduction to cloud Virtualization concepts: Types of Virtualization & its benefits, Introduction to

Various Virtualization OS (e.g.Vmware, KVM etc.), HA/DR using, Virtualization, Moving VMs , SAN backend concepts, Cloud Fundamentals: Cloud Building Blocks, Understanding Public & Private cloud environments.

Unit III: Cloud as IaaS Private Cloud Environment: Basics of Private cloud infrastructure, QRM cloud demo,

Public Cloud Environment: Understanding & exploring Amazon Web services, Managing and Creating Amazon EC2 instances, Managing and Creating Amazon EBS volumes, Tata Cloud details & demo, Managing Hybrid Cloud environment.

Unit IV: Cloud Security Cloud Security Mechanisms Used to Counter Threats and Attacks, Single Sign-On

for Cloud-Based Services, Cloud-Based Security Groups and Hardened Virtual Server Images, Virtualization Attacks and Overlapping Trust Boundaries

Unit V: Setting up the Cloud How to build private cloud using open source tools, Understanding various cloud

plugins, Setting up the cloud environment: Autoprovisioning, Custom images, integrating tools like Nagios, Integration of Public and Private cloud.

Unit VI: Future Directions Cloud Domain and scope of work, Cloud as PaaS, SaaS, Cloud Computing

Programming Introduction, Trends and market of cloud Reading List:

1. Antonopoulos, N. & Gillan, L. (2010). Cloud Computing principles, system and applications. Springer, ISBN: 978-1849962407.

2. Buyya, R., Broberg, J. & Goscinski, A.M. (2011). Cloud Computing principles and paradigms. Wiley, ISBN: 978-0470887998.

3. Hwang, K., Dongarra, J. & Fox, G. (2011). Distributed and Cloud Computing: From Parallel processing to the Internet of Things. Elsevier/Morgan Kaufmann, ISBN: 978-0123858801.

59 

4. Schulz, G. (2011). Cloud and Virtual Data Storage Networking. Auerbach Publications, ISBN: 978-1439851739.

5. Smoot, S.R. & Tan, N.K. (2012). Private Cloud Computing: Consolidation, Virtualization, and Service-Oriented Infrastructure. Morgan Kaufmann, ISBN: 978-0123849199.

 

Table 7:31: TE 627 Ad-hoc and Sensor Networks Course Code TE 627 Total Credits: 12 Course Name Sensor Networks

Delivery Mode:

Lecture Hrs/Sem

Tutorial Hrs/Sem

Practical Hrs/Sem

Assignments Hrs/Sem

Indep. Studies

Total Hrs/Sem

45 15 15 15 30 120 Assessment Mode:

Coursework (50%), Final Examination (50%).

Prerequisites: None Objective: The objective of this course is to provide the basic principles behind a

Wireless Sensor Network. Wireless sensor networks provide the basis for new computing paradigms that challenge many of the classical approaches to developing distributed and networking systems Wireless sensor networks provide the basis for new computing paradigms that challenge many of the classical approaches to developing distributed and networking systems. Following the ISO Open Systems Interconnection (OSI) model, challenges of designing network protocols, services and applications for WSNs composed of large numbers of constrained devices are discussed. This course also provides an introduction to widely adopted network simulator, focusing in particular on the simulation of wireless networks.

Learning Outcomes:

Upon completion, students should be able to: i. Architect sensor networks for various application setups. ii. Explore the design space and conduct trade-off analysis between

performance and resources. iii. Assess coverage and conduct node deployment planning. iv. Devise appropriate data dissemination protocols and model links cost. v. Determine suitable medium access protocols and radio hardware. vi. Prototype sensor networks using commercial components. vii. Provision quality of service, fault-tolerance, security and other

dependability requirements while coping with resource constraints. viii. Evaluate the performance of sensor networks and identify bottlenecks.

Course Contents: Unit I: Introduction to Sensor Network Course Information, Introduction to Wireless Sensor Networks: Motivations,

Applications, Performance metrics, History and Design factors Unit II: Network Architecture Traditional layered stack, Cross-layer designs, Sensor Network Architecture Unit III: Hardware Platforms Motes, Hardware parameters., Network simulators Unit IV: Medium Access Control Protocol Design

60 

Fixed Access, Random Access, WSN protocols: synchronized, duty-cycled and wakeup concepts

Unit V: Introduction to Markov Chain Discrete time Markov Chain definition, properties, classification

and analysis Unit VI: MAC Protocol Analysis Asynchronous duty-cycled. X-MAC Analysis (Markov Chain) Unit VII: Routing Protocols Introduction, MANET protocols Unit VIII: Routing Protocols for WSN Resource-aware routing, Data-centric, Geographic Routing, Broadcast, Multicast Unit IX: Opportunistic Routing Analysis Analysis of opportunistic routing (Markov Chain) Unit X: Clustering Clustering goals, types, high-level overview, clustering in WSNs Unit XI: QoS Management Basic functions, centralized solution, Topology control, Sensor

mode selection Unit XII: Localization and Time Synchronization Overview of different localization and synchronization techniques Unit XIII: Programming in WSN Introduction to TinyOS, Interfaces, Modules, Configuration, Programming in

TinyOS. Challenges and limitations of programming WSNs. Reading list:

1. Karl, H. & Willig, A. (2007). Protocols and Architectures for Wireless Sensor Networks. Wiley Publishers. ISBN-13: 978-0470519233

2. Raghavendra, C.S., Sivalingam, K, & Znati, T.M. (2005). Wireless Sensor Networks. Springer.ISBN:1-4020-7883-8

3. Sohraby, K, Minoli, D. & Znati, T. (2007). Wireless Sensor Networks Technology, Protocols, and Applications. John Wiley & Sons.ISBN-13: 978-0471743002

4. Obaidat, M.S. & Misra, S. (2015).Principles of Wireless Sensor Networks (1st ed.). Cambridge University Press, ISBN-13: 978-0521192477

5. Bell, C. (2013). Beginning Sensor Networks with Arduino and Raspberry Pi 2013th Edition. Apress, ISBN-13: 978-1430258247

Required Laboratory Equipment: Computers with installed numerical computing and data visualization packages -

MATLAB, LabVIEW  

Table 7.32: TE 631 Advanced Signal Processing Course Code TE 631 Total Credits: 12

Course Name Advanced Signal Processing

Delivery Mode:

Lecture

Hrs/Sem Tutorial

Hrs/Sem Practical

Hrs/Sem Assignment Hrs/Sem

Independent Hrs/Sem

Total Hrs/Semester

45 15 15 15 30 120

Assessment Mode:

University Examination 50%, Continuous Assessment 50%

61 

Prerequisites: Signal and System, DSP

Objective: To provide a broad treatment of the fundamentals of speech, image, audio and video processing

Learning

Outcome:

On successful completion of this subject, the students will be able

to:

i. Understand the fundamentals of speech, image, audio and video signal processing and associated techniques.

ii. Solve practical problems with some basic speech, image, audio and video signal processing techniques.

iii. Design simple systems for realizing some multimedia applications with some basic speech, image, audio and video signal processing techniques.

Course Contents:

Unit I: Image Processing

Frequency Domain Image Filtering and Enhancement: 2-D signals and systems, 2D symmetry and periodicity,2D DFT, symmetry and other properties, 2-D FIR filters, frequency response, circular symmetry, Visual Perception and Color Spaces , Physiological characteristics of the eye and image formation, Humancolor vision

Spatial Domain Image Enhancement and Filtering & Restoration: Image decimation and interpolation, multi-resolution pyramids, Image sampling, patio- temporal (M-D) sampling theory, Edge detection, Image enhancement, Noise filtering, Image restoration: Image degradation model, Inverse Filtering, Wiener filtering

Fundamentals of image Compression Entropy coding: Lossless image compression, JPEG image compression, JPEG-2000, image compression, Multi- resolution and Wavelet Transform

Unit II: Video Processing

Video sampling, flicker, spatial frequency response, Motion modeling and estimation, Optical flow modeling and estimation, Block matching, feature matching, Parametric motion estimation, Video filtering , Deinterlacing, Denoising)

Video Compression & Broadcasting Standards: MC-DCT video compression: MPEG-1, MPEG-2 video compression,H.263/MPEG-4 video compression: Compression efficiency, MPEG-4 AVC/H.264 video compression, Scalable video coding (SVC), Error resilient compression, Video over IP

Color models: CIE, RGB, CMYK, HSI, HSV, L*a*b*

Unit III: Speech Processing

62 

Production and Acoustic Phonetics: The process of speech production, Acoustic theory of speech production, Digital models of speech signals of speech signal, Articulator phonetics, Acoustic Phonetics, Co- articulation, Prosody

Speech Analysis, Synthesis and Coding: Time and frequency domain analysis of speech, Linear predictive coding, (LPC) analysis, Cepstral analysis, Speech parameter (pitch) estimation, Principles of speech synthesis, Articulatory synthesis, Formant synthesis and LPC synthesis, Quantization, Speech redundancies, Time domain waveform coding, Linear predictive coding, Linear delta modulation, Adaptive delta modulation, Adaptive differential pulse code modulation, Filter bank analysis, Phase vocoders and Channel vocoders

Speech Enhancement, Speech Recognition: Nature of interfering sounds, speech enhancement techniques, spectral subtraction and filtering, harmonic filtering, Spectral subtraction, Adaptive noise cancellation, Baye’s rule, Segmental feature extraction, MFCC, DTW, HMM approaches for speech recognition

Unit IV: Lab experiments

Lab experiments on: Audio compression; Speech signal analysis; Psychoacoustic behavior; Motion estimation and its application in video coding; Image processing techniques; Image compression

Reading List: 1. Bovik, A. (2005). Handbook of Image and Video Processing (2nd ed.). Academic

Press. ISBN-13: 978-0121197926

2. Gonzalez, R.C. & Woods, R.E. (2007). Digital Image Processing (3rd ed.). Pearson, Addison-Wesley, ISBN-13: 978-0131687288

3. Woods, J.W. (2011). Multidimensional Signal, Image and Video Processing andCoding (2nd ed.). Academic Press, ISBN 0-12-088516-6

4. Wang, Y., Ostermann, J. & Zhang, Y.Q. (2002). Video Processing and Communications, Prentice Hall, ISBN-13: 978-0817634384

5. Gold, B., Morgan, N. & Ellis, D. (2011). Speech and Audio Signal Processing:Processing and Perception of Speech and Music (2nd ed.). Wiley-Interscience, ISBN-13: 978-0470195369

 

Table 7.33: TE 633 Wireless Communication Course Code TE 633 Total Credits: 12 Course Name Wireless Communication

Delivery Mode:

Lecture

Hrs/Sem

Tutorial

Hrs/Sem

Practical

Hrs/Sem

Assignment Hrs/Sem

Independent Hrs/Sem

Total Hrs/Semester

45 15 15 15 30 120Assessment

Mode:

Continuous Assessment (50%) + University Examination (50%)

Prerequisites: Introduction to Mobile communications (BSc) Objective: To provide students with an understanding of the fundamental principles

63 

of current and future mobile communications systems and technologies. Learning

Outcome:

Upon completion of this course, students should be able to:

i. Understand the wireless channel and principles of radio systems ii. Understand the techniques behind current technologies

(e.g.MIMO) iii. Model and analyse such a system

Course Contents: Unit I: Capacity of Wireless Channels AWGN channel capacity, LTI Gaussian channels, Capacity of fading

channels, Unit II: Spread Spectrum and Multi-carrier Transmission Multi-carrier transmission techniques, Multi-carrier modulation and OFDM, Spread

spectrum (FHSS, DSSS, CDMA principles, spreading, dispreading, scrambling,multiuser detection, etc)

Unit III: Smart Antennas Spatial Multiplexing; Channel modeling and propagation (fading and

diversity, multi- dimensional propagation, MIMO channel modeling and propagation, analytical MIMO channel representations, physical MIMO channel models); MIMO Capacity and Multiplexing Architectures; Space-Time Coding (with perfect, partial or without transmit channel knowledge), Frequency Selective MIMO (MIMO-OFDM) MIMO Receivers: Diversity-Multiplexing trade-off; Multi-User Communications: Multi-User MIMO: (channel capacity, diversity and scheduling, precoding) Multi-Cell MIMO (channel capacity, resource allocation, coordination and cooperation, coordinated scheduling, beamforming and power control)MIMO Application (in current/future systems e.g. LTE-A, etc)

Unit IV: Project Write a review of / Simulate / Summarise a paper, book or standard

(e.g.simulation of a simplified MIMO based system such as LTE-A) Unit V: Special topics / Future Advances in the field Reading List:

1. Molisch, A.F. (2011). Wireless Communications (2nd ed.). Wiley, ASIN: B006E6SBE6

2. Clerckx, B. & Oestges, C. (2013). MIMO Wireless Networks: Channels, Techniques and Standards for Multi-Antenna, Multi-User and Multi-Cell Systems (2nd ed.). Academic Press (Elsevier), Oxford, UK: ASIN: B00BJH2XPS

3. Goldsmith, A. (2005). Wireless Communications. Cambridge Univ. Press, ISBN-13: 978-0521837163

4. Stuber, G. (2012). Principles of Mobile Communications (3rd ed.). Springer, ISBN-13: 978-1461403630

5. Tse, D. & Viswanath, P. (2005). Fundamentals of Wireless Communication. Cambridge University Press, ISBN-13: 978-0521845274

Required Laboratory Equipment: MATLAB software

 

64 

Table 7.34: TE 648 Powerline Communications Course Code TE 648 Total Credits: 12 Course Name Powerline Communications

Delivery Mode:

Lecture Hrs/Sem

Tutorial Hrs/Sem

Practical Hrs/Sem

Assignments Hrs/Sem

Indep. Studies

Total Hrs/Sem

45 15 15 15 30 120 Assessment Mode:

Continuous Assessment (50%) + University Examination (50%)

Prerequisites: Communication Theory, channel modelling, modulation and coding, multiple access standards, knowledge of networking

Objective: i. To investigate the issues pertaining to communication over existing power line infrastructure for the purposes of control, in-home communications, and broadband access communications.

ii. To study the applications that powerline communication enables, including but not limited to AMR, SMART GRID, SCADA, and various green energy applications.

iii. To examine the existing PLC standards in light of their purposes and the challenges they face.

iv. To analyse various approaches for efficiency and suitability for the environment.

v. To gain experience about emerging technologies referred as powerline communication (PLC), PLC application, standards, transmission principles, channel and noise characteristics, main PHY and MAC algorithms.

vi. To provides the knowledge and the tools to allow an informed use of the technology as well as to allow the design and development of PLC based solutions

Learning Outcomes:

Upon completion, students should be able to: i. Gain knowledge on the issues pertaining to communication over existing

power line infrastructure for the purposes of control in home communications and broadband access communications

ii. Knowledge of PLC applications, standards, challenges and solutions for reliable communications over powerline.

iii. Knowledge about main differences with respect to wireless communications systems

Course Contents: Unit I: Overview of PLC History and evolution of Power Line Communication (PLC) technology

PLC applications. Unit II: Power line Channel Characterization and Modelling Channel Characterization: channel response, noise, Interference. Channel modelling:

top-down approach and statistical modelling. Principles of transmission line theory (TLT).

65 

Channel modelling: bottom-up approach using TLT. Background and impulsive noise models. Multiple input multiple output (MIMO) PLC.

Unit III: Physical layer techniques used in PLC Single carrier modulation, filter bank modulation, ultra-wide band modulation.

Media access control for PLC. Resource allocation algorithms. Relaying and cooperative schemes in the context of PLC.

Unit IV: Realization of PLC Access Systems Architecture of the PLC Systems, Modulation Techniques for PLC Systems, Error

Handling, PLC Services, PLC MAC Layer 125: Structure of the MAC Layer, Multiple Access Scheme, Resource-sharing Strategies, Traffic Control Performance Evaluation of Reservation MAC Protocols: Reservation MAC Protocols for PLC, Modelling PLC MAC Layer, Investigation of Signalling MAC Protocols, Error Handling in Reservation MAC Protocols, Protocol Comparison

Unit V: Power Supply Networks forPower Line Communication Narrowband & Broadband PLC, Structure of PLC access network, PLC network

elements, Connection to core network, Structure of campus communication network and performance issues. Architecture of Smart grid technology.

Unit VI: PLC Network Characteristics Network Topology, Features of PLC Transmission Channel, Electromagnetic

Compatibility of PLC Systems, Disturbance Characterization

Unit VI: PLC for Smart Grid Communications Two-way Digital Communications Paradigm

o Network Architectures o IP-based Systems o Advanced Metering Infrastructure

Unit VII:PLC standards and protocols: An overview of the main standards for both NB-PLC and broad-band BB-PLC such as

IEEE P1901, IEEE P1901.2, ITU G.hn, ITU G.hnem, PRIME, G3 and their intended use in different application scenarios.

Unit VIII: Power line carrier Interface equipment Principle, purpose, types of coupling, Interface equipment and communication

standards. Power line modems and networks, Digital PLCC, broadband over powerline, Applications

Unit IX:PLC Applications Introduce different applications of PLC Reading List: 1. Anatory, J. and Theethayi, N. (2010). Broadband Power Line Communications Systems:

Theory and Applications. WIT Press,, ISBN 9781845644178 2. Best Readings in Power Line Communications, IEEE Communications Society, online:

http://www.comsoc.org/best-readings/powerline-communications 3. Ferreira, H.C., Lampe, L., Newbury, J., & Swart, T.G. (2013). Power Line

Communications: Theory and Applications for Narrowband and Broadband Communications Over Power Lines. Wiley, ISBN: 9780470740309

4. Held, G. (2006). Understanding Broadband over Power Line. CRC Press, ISBN: 9780849398469

66 

5. Lampe, L., Tonello, A.M. & Swart, T.G. (2016). Power Line Communications: Principles, Standards and Applications from Multimedia to Smart Grid (2nd ed.). Wiley,ASIN: B01EYG5A14.

Required Laboratory Equipment: Computers installed with simulation environment – MATLAB

67 

8. LIST OF ACADEMIC STAFF AVAILABLE TO RUN THE PROGRAM

The department of CSE in collaboration with department of ETE has a good number of academic staff members who are currently teaching Computer Engineering, Electronics Communication Science and Telecommunication Engineering courses. Each academic member of staff is allowed to teach a maximum of three courses per semester. The three courses can either be from undergraduate, postgraduate or both programs.

Table 8.1: List of academic staff with their qualifications

S/N Course(s) codes

Name Qualification Status Date of Birth Nationality

1) CS 606,CS 604, CS 609,CS 698,

Prof. N.H. Mvungi PhD. (Leeds), MSc. (Eng.) (Salford), BSc. (Eng.) (Dar), R. Eng. (T), AMSTS

Full Time 1.3.1953 Tanzanian

2) CS 608,CS 606, CS 698

Dr. G.R. Koda BSc., MSc. (Comp.Sc.) (Dar), MSc. (Inf. Sys. Sc.) (Carleton), PhD. (Dar)

Full Time 18.5.1948 Tanzanian

3) CS 602,CS 623, IS 631

Dr. B.B.R. Bagile BSc. (Eng.) (Dar), MSc (Bradford, UK), PhD. (Southampton, UK)

Full Time 5.4.1958

Tanzanian

4) CS 623,IS 611, IS 614

Dr. Mercy Mbise B.Eng, (Hons) (Essex), PhD. (Essex) Full Time 6.6.1974 Tanzanian

5) CS 608,CS 698 Dr. H.C. Kimaro BSc. (Comp.Sc.) (Dar), MSc. (Delft), PhD. (Oslo)

Full Time 29.11.1971 Tanzanian

6) CS 602,CS 603, CS 621,IS 611, CS 698

Dr. G. N. Justo BSc. (with Comp.Sc.) (Dar), MSc. (Maths) (Zimbabwe) PhD. (London)

Full Time 25.7.1971

Tanzanian

68 

S/N Course(s) codes

Name Qualification Status Date of Birth Nationality

7) CS 623,CS 698, CS 606,CS 707

Dr. E.A. Kalinga PhD – UDSM (2011), MSc. in EIT – UDSM (2000), Bachelor in EE – Mysore University India (1989)

Full Time 30.7.1962

Tanzanian

8) CS 622 Dr. K. Kapis M.Eng.Sc. (Curtin) MSc. (Eng.) (Odessa), PhD. (OUT)

Full Time 12.6.1959 Tanzanian

9) CS 621,CS 623, IS 631

Dr. J. Lungo BSc. (Comp.Sc.) (Dar), MSc. (Inf. Sys. Sc.) (Oslo), PhD. (Oslo)

Full Time 17.11.1974 Tanzanian

10) CS 602,CS 603, IS 611

Dr. F. Simba BSc. (ESC.) (Dar), MSc. (Dar), PhD. (Dar) Full Time 18.2.1975 Tanzanian

11) CS 601,CS 602, CS 606,CS 604, CS 609,CS 607

Dr. N. Y. Hamisi B.Eng. (Mysore - India), MSc. (Dar), PhD (Dar)

Full Time 5.1.1961 Tanzanian

12) CS 621 Dr. M. Meghji BSc.(Dar), MSc. (Victoria University), PhD (Edith Cowan University)

Full Time 24.9.1973 Tanzanian

13) CS 621,IS 614, IS 654,CS 698, CS 606

Dr. J. Mtebe BSc. (Comp. Sc.) (Dar), MSc. e-learning (USQ-Australia), PhD (Tampere)

Full Time 23.3.1976 Tanzanian

14) TE 631, TE 627 Prof. M.L.Luhanga

BSc. (Dar.), MEng. (Cal Poly), PGCE (Leeds), M.Phil., Ph.D. (Columbia)

Full Time 10.1.1949 Tanzanian

15) TE 633 Prof H.R. Mgombelo

BSc. (Dar.), MSc. (Eng.) (Leningrad, USSR), Ph.D. (Bradford, U. K.)

Full Time

11.1.1949 Tanzanian

16) ES 630 TE 633,CS 604,

Prof. H.N.Kundaeli

BSc. (Dar), Dip., MSc. (Electronics) (Eindhoven), PhD. (Dar)

Full Time

25.11.1953

Tanzanian

69 

S/N Course(s) codes

Name Qualification Status Date of Birth Nationality

CS 698 17) ES 630,TE 627,

CS 631

Dr. M.M. Kissaka BSc. (Dar), PhD. (Manchester, UK) Full Time 25.12.1959 Tanzanian

18) ES 630 Dr. A.J. Mwambela

BSc. (Dar), MSc.(Durham), Ph.D. (Dar) Full Time 25.02.1963 Tanzanian

19) TE 631,CS 698, IS 607,CS 631

Dr. O.F. Hamad BE., ME. (BIT), PhD (CNU, Korea) Full Time 21.3.1971 Tanzanian

20) ES 630,TE 627 Dr. L.V. Massawe BSc. (Dar), MSc. (Ryukyu, JP), Ph.D. (CUT, SA) Full Time 22.11.1977 Tanzanian

21) ES 630,CS 631 Dr. C. John BSc. (Dar), MSc. (Oita, JP), PhD. (Essex, UK) Full Time 31.7.1975 Tanzanian

22) TE 648,TE 631 Dr. H.U. Iddi H.U. Iddi, BSc., MSc(Dar), PhD. (UTM, MY) Full Time 4.11.1973 Tanzanian

23) TE 631, TE 633

Dr. K.S. Ibwe B.Sc. (Dar), MSc. (Chalmers), PhD (Dar) Full Time 17.05.1980 Tanzanian

24) TE 631,TE 627, IS 607

Dr. B. Maiseli B.Sc. (ES), MSc. (Dar), PhD (China) Full Time 04.11.1980 Tanzanian

25) TE 648,ES 630, CS 604,CS 631

Dr. S. Naiman BSc., MSc. (Dar), Ph.D (Dar) Full Time 28.6.1974 Tanzanian

26) CS 631, CS 624 Prof. H. C. Hannu Tenhunen

MSc. in Electrical Engineering (Helsink), Ph.D. in Electrical Engineering (Cornell University)

Visiting Staff

Swedish

27) CS 631, CS 624 Prof. Bjorn Pehrson

BSc., MSc. and PhD Visiting Staff

Swedish

70 

S/N Course(s) codes

Name Qualification Status Date of Birth Nationality

28) CS 608, CS 602, CS 607, CS 609, TE 631

Prof. Imed Ben Dhaou

MSc in Electrical Engineering (Tampere) 1997, Ph.D, (Stockholm) 2002

Visiting Staff

1972 Tunisian

29) CS 631, CS 604, CS 621, IS 654

Dr. Simon Taylor PhD Visiting Staff

British

30) CS 603, CS 604, CS 610

Dr. Mighanda J. Manyahi

B.Sc. (Dar.), M.Sc. (Strathclyde), Ph.D. (Uppsala)

Full Time 13.4.1961 Tanzanian

31) CS 610 Prof Dominic J. Chambega

M.Sc. (Moscow, USSR), Ph.D. (Strathclyde, U. K.)

Full Time 13.8.1949 Tanzanian

32) CS 624, ES 630 Prof. Bakari M. M. Mwinyiwiwa

B.Sc. (Dar), M.Eng. (McGill Montreal, Canada), Ph.D. (McGill Montreal, Canada)

Full Time 22.5.1960 Tanzanian

33) CS 604, CS 624 Dr. Alexander Kyaruzi

B.Sc. (Dar), M.Sc. (George Washington, USA), D. Eng. (George Washington, USA)

Full Time 19.7.1954 Tanzanian

34) CS 603, CS 604 Dr. Beda J. Kundy

B.Sc. (Dar), M.Sc. (Strathclyde), Ph.D. (Stellenbosch, SA)

Full Time 18.8.1954 Tanzanian

35) CS 604, CS 610, ES 630

Dr. Nelson Lujara

B.Sc. (Dar), M. Eng. (McGill, Canada), D.Eng. (Rand Afrikaans, SA)

Full Time 19.11.1958 Tanzanian

36) Cs 604, Cs 624 Dr. Santos L. Kihwele

B.Sc. (Dar) M.Sc. (Dar/KTH, TZ/Sweden), Ph.D. (Yonsei, Seoul Korea)

Full Time 6.6.1976 Tanzanian

71 

S/N Course(s) codes

Name Qualification Status Date of Birth Nationality

37) CS 603, CS 604 Dr. Jackson J. Justo

B.Sc. (Dar), Ph.D. (Dongguk, Seoul Korea) Full Time 25.06.1979 Tanzanian