Syllabus MTech CompEngg Syllabus Mumbai University

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AC- 30/07/2017
Item No. – 4.10



UNIVERSITY OF MUMBAI



Proposal for Starting a New P rogram

School of Engineering Science

at
University of Mumbai, Kalyan Sub -
Center
From
Academic Year 2017 -18

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AC- 30/07/2017
Item No. – 4.10
Proposal for starting School of Engineering Science at University of
Mumbai, Kalan Sub center .

Table of Content

Sr. No. Topic Page No.
I. Proposal Summary 2
II. Background 2
III. Need for a Focused and Dedicated Program 3
IV. Objectives of the New Program 3
V. Curriculum Design and Teaching
Methodology 4
VI. Resources Need for program 5
VII. Budget 6
VIII. Structure Course Curriculum 7

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AC- 30/07/2017
Item No. – 4.10
I. Proposal Summary

1. Proposed by: Faculty of Technology, University of Mumbai.
2. Program : School of Engineering Science
3. Course Name: M. Tech.(Computer Engineering)
4. Course Level/Duration : Post Graduate – Two years
5. Course Name: M. Tech. (Computer Engineering)
6. Proposed Start Date: Academic Year 2016 -17 - August: 2016 .
7. Proposed Strength: 30 students
8. No. of Batches: One
9. Eligibility for admission:
i. Candidate should have passed B. E./B. Tech. Degree in
branch of Computer Engineering , Information
Technology, Electronics Engineering , Electronics and
Telecommunication Engineering , Electrical
Engineering, Instrumentation Engineering .
ii. Valid Gate score
10. Structure Course Curriculum: Separately attached. (Annexure
A)

II. Background

University of Mumbai carved out in 156 years of its functioning
attests to its manifold achievements as the intellectual and moral
powerhouse of the society. The University has always given its
best to the country in general and to the city of Mumbai in
particular by enthusia stically shouldering an ever -growing load of
social values and opportunities.
Initially, the University concentrated its efforts on controlling
teaching at the undergraduate level and in conducting
examinations. Later on it took up research and the task o f imparting

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AC- 30/07/2017
Item No. – 4.10
instructions at the Post -Graduate level. This resulted in the
establishment of the University Departments beginning with the
School of Sociology and Civics & Politics. The independence of
the country led to the re -organization of the functions and powers
of the University with the passing of the Bombay University Act of
1953.
It has two campuses of areas 243 acres and 14 acres at Vidyanagari
and Fort respectively; sub -campuses/centers at Ratnagiri 20 acres,
Thane 6.50 acres and Kalyan 6.26 acre s with 60 University
Departments & Institutes and 749 affiliated colleges. It has
established its name in industrial & International collaborations and
runs various professional courses.
At national level, it has excelled in sports, cultural and out -reach
activities. In the last five years it has seen 104% increase in under -
graduate students, 112% increase in post -graduate students and
147% increase in distance - education students. There is 156%
increase in the number of research papers published in
Inter national journals. Twelve Department/sections are recognized
under various national programmes, such as
SAP/CAS/DRS/DSA/COSIST/FIST. More than eighty teachers are
on various professional bodies. Eighteen National/International
awards are won by teachers in the last five years. Every year about
20 teachers visit abroad for academic activities. Recently more than
ten self -supporting courses have been started by the University .

Kalan - Dombvali Municipal Corporation is sponsored the proposal
for starting Scho ol of Engineering Science at University of
Mumbai, Kalan Sub center.

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AC- 30/07/2017
Item No. – 4.10
III. Need for a Focused and Dedicated Program

 Efficient and resource –optimal computing is extremely important
in today’s world. There is increased need for advancement in
computer archite cture and integration of computer hardware,
software, algorithms and data management techniques. The
advanced knowledge of these aspects enhances career prospects in
computing. M Tech in Computer Engineering is intended to train
the students in advanced ar eas in the core courses and specialized
areas in Computer Engineering.
 The objective of this program is industry -relevant curriculum and
train the manpower required to meet the industry needs. The
curriculum is aimed at giving strong theoretical foundation and
hands -on exposure in Advanced Operating Systems, Embedded
System Design, Cloud Computing, Big Data, Distributed
Computing and Image Processing.
 The mandatory project work empowers the students to gain in -
depth knowledge.

IV. Important objectives of the new program –

1. Graduate of Program will have successful technical and
professional career.
2. Graduate will be competent in technical skills to cater the needs
of the local industry, academic institutes, R& D institutions,
administration, entrepreneurship, leadership for the overall up
liftment of society.
3. Graduate of Program will be able to analyze real life problems,
design computing systems appropriate to its solutions that are
technically sound, economically feasible and socially
acceptable .

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AC- 30/07/2017
Item No. – 4.10
4. Graduate will exhibit professionalism, ethical attitude,
communication skills, team work in their profession and adapt
to current trends by engaging in lifelong learning .

V. Curriculum Design and Teaching Methodology
1. Course curriculum for the new program should been designed
as per choice based credit system.
2. Course curriculum for the new program has been designed to
meet the course objectives. The quality standard of the
curriculum is slightly higher than the other M. Tech. programs
keeping in mind the high standards demanded by the global
companies and hence provides higher career placement
potential.
3. The subjects chosen are based on its’ requirements in industry
rather than crowding the curriculum with too many specialized
subjects.
4. Syllabus content has been decided duly considering its utility
value for indu stry/business application .
5. The emphasis is on the quality of the syllabus content and not
on exhaustive coverage of the topic.
6. Teaching methods for the program will be combination of
conceptual lectures, case study analysis and Practical or hands
on projec ts. On campus training followed by on the industry
internship are intended to augment the application capability of
the students.
7. Curriculum includes training in relevant areas of information
technology, Research work and communication/Presentation
Skills.
8. The quality of examinations would match with University
standards and prescribes a higher minimum score for pass; to
call for more directed efforts on the part of the students.

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AC- 30/07/2017
Item No. – 4.10
VI. Resource need for new M.Tech Program
1. Faculty / Staff Resources:

M.Tech . in Computer Engineering is has organized itself in to a
full fledge program with a Director (Coordinator) and dedicated
two of faculty members as well as qualified professionals on
visiting basis from the Industry.
Sr.
No Post Qualification Number
of po st
1 Director
(Professor) PhD in Computer Engineering having
min. 13 yrs. Experience. 1
2 Associate
Prof. PhD in Computer Engineering having
min. 10 yrs. Experience. 1
3 Asst.
Professor MTech/ ME in Computer Engineering
having 5 yrs. Experience. 1
4 Clerk Any Graduate 1

2. Laboratory:
 For M.Tech . in Computer Engineering one Laboratory
having 3 0 computers with latest configuration is required.
 Laboratory should connect in LAN as well as min.10 Mbps
internet connection.
 One printer and one scanner.

3. Classroom & tutorial room
 One class room of 60 sqm.
 One office of 60 sqm.
 One Director/ Coordinator of 20 sqm
 Faculty room of 20 sqm

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AC- 30/07/2017
Item No. – 4.10
VII. Budget :
1. Revenue :
First Year M. Tech Tuition Fee Rs. 61000/ - per student
Intake : 30
Total Reven ue for First year M Tech.: Rs 1 8,30000 /-
2. Expenditure
Sr.
No. Item Quantity Cost per
Item (Rs) Total Cost
(Rs)
1
COMPUTERS
---------------------------
(Intel P -Iv, 2.8 Dual Core
Cpu 2180@ 2.8 Ghz
,M/B Intel G31gl ,Ddr2
Ram 4 Gb,Software(02
Ss & 01 App)
------------------------
a. 30 For Lab,
b. 02 for office
c. 02 for Faculty
d. 01 for Director
35
30000
1050000
2 COMPUTER TABLE 35 3000 105000
3 PRINTER 02 7000 14000
4 SCANNER 01 5000 5000
5 UPS 01 10000 10000
6 INTERNET (10 MBPS) 1:1 15000 15000
7 LAN CONNECTION -- 10000 10000
8 FULL TIME
DIRECTOR/
COORDINATOR 1 Rs 1.40
Lakh per
month 1680000
9 VISITING FACULTY 75 credit Rs.1000
per hr 75000
10 CLERK 1 Rs 15000 180000
Total Cost 31,44000 /-

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AC- 30/07/2017
Item No. – 4.10
VIII. Structure Course Curriculum:
Program Structure for M. Tech. (Computer Engineering) at
University Campus
Semester -I

Course Code Course Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Theory TW/
Pract Total
MTech -CEC101 Core Course -1 4 - 4 -- 4
MTech -CEC102 Core Course -2 4 - 4 -- 4
MTech -CEC103 Core Course -3 4 - 4 -- 4
MTech -CEDEC -
I Department Elective Course -I 4 - 4 - 4
MTech -CEIEC -I Institute Elective Course -I 4 -- 4 -- 4
MTech -CEL101 Laboratory -I -- 2 - 1 1
MTech -CEL102 Laboratory -II - 2 - 1 1
Total 20 04 20 02 22
Semester -II
Course Code Course Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Theory TW/ Pract Total
MTech -CEC201 Core Course -4 4 - 4 -- 4
MTech -CEC202 Core Course -5 4 - 4 -- 4
MTech -CEC203 Core Course -6 4 - 4 -- 4
MTech CEDEC -II Department Elective Course -II 4 - 4 - 4
MTech -CEIEC -II Institute Elective Course -II 4 -- 4 -- 4
MTech -CEL201 Laboratory -III -- 2 - 1 1
MTech -CEL202 Laboratory -IV - 2 - 1 1
Total 20 04 20 02 22

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AC- 30/07/2017
Item No. – 4.10
# Departmental Elective Course (DEC) Every student is required to take one department
Elective course for semester -I and semester -II and different sets of courses will run in the both
the semesters. Students can take those courses in the list of department Electives, which are
closely allied to the ir disciplines.
# Institute Elective Course (IEC): Every student is required to take one Institute Elective
course for semester -I and semester -II which are not closely allied to their disciplines and
different sets of courses will run in the both the seme sters.
Semester -III
Course Code Course Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Theory Pract
/Pract Total
MTech -CE301 Special topic seminar -- 06 -- 3 3
MTech -CE302 Dissertation -I -- 24 -- 12 12
Total -- 30 -- 15 15

Semester -IV
Course Code Course Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Theory Pract Total
MTech -CE401 Dissertation -II -- 30 -- 15 15
Total -- 30 -- 15 15

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AC- 30/07/2017
Item No. – 4.10

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AC- 30/07/2017
Item No. – 4.10



UNIVERSITY OF MUMBAI



School of Engineering Science, Kalyan Sub -Center
Rules and Regulations
for
M. Tech . (Computer Engineering)

Course Introduced from A. Y. 2017 -18 onwards

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AC- 30/07/2017
Item No. – 4.10


Preamble
M. Tech . in Computer Engineering programme is offered to students
who are interested in advanced learning and research in any area of
Computer Science and Engineering. Applicants to this programme are
expected to have a background in Computer Science and Engineering
or Information Technology.
The objective of the programme is to enable the learner to apply
his/her enhanced skill and knowledge at the top research laboratories
and companies in the country and even abroad.
The programme is a 72 -credit degree programme, which is usually
spread ov er 4 semesters for a full -time student. About two -thirds of the
credits involve coursework, and the remaining consists of project
work. The emphasis is on conducting original research and writing a
thesis individually. The programme is flexible enough to a llow a
student to specialize in any topic of interest by taking elective
(optional) courses and working on a research project in that area.
University of Mumbai feels that it is desirable to provide specialized
M. Tech. programme in Computer Engineering to address the needs
of the industry, which today requires more specialized resource in
each field.
School of Engineering Science, University of Mumbai, Kalan Sub
center has taken a lead in incorporating philosophy of Choice Based
Education in th e process of curriculum development.

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AC- 30/07/2017
Item No. – 4.10
1. Introduction

University of Mumbai carved out in 156 years of its functioning attests
to its manifold achievements as the intellectual and moral powerhouse
of the society. The University has always given its best to the country
in general and to the city of Mumbai in particular by enthusia stically
shouldering an ever -growing load of social values and opportunities.
Initially, the University concentrated its efforts on controlling teaching
at the undergraduate level and in conducting examinations. Later on it
took up research and the task o f imparting instructions at the Post -
Graduate level. This resulted in the establishment of the University
Departments beginning with the School of Sociology and Civics &
Politics. The independence of the country led to the re -organization of
the functions and powers of the University with the passing of the
Bombay University Act of 1953.
It has two campuses of areas 243 acres and 14 acres at Vidyanagari
and Fort respectively; sub -campuses/centers at Ratnagiri 20 acres,
Thane 6.50 acres and Kalyan 6.26 acre s with 60 University
Departments & Institutes and 749 affiliated colleges. It has established
its name in industrial & International collaborations and runs various
professional courses.
At national level, it has excelled in sports, cultural and out -reach
activities. In the last five years it has seen 104% increase in under -
graduate students, 112% increase in post -graduate students and 147%
increase in distance - education students. There is 156% increase in the
number of research papers published in Inter national journals. Twelve
Department/sections are recognized under various national
programmes, such as SAP/CAS/DRS/DSA/COSIST/FIST. More than
eighty teachers are on various professional bodies. Eighteen
National/International awards are won by teachers in the last five
years. Every year about 20 teachers visit abroad for academic
activities. Recently more than ten self -supporting courses have been
started by the University .

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AC- 30/07/2017
Item No. – 4.10
Kalan - Dombvali Municipal Corporation is sponsored the proposal for
starting Scho ol of Engineering Science at University of Mumbai,
Kalan Sub center.

2. Admission Process
School of Engineering Science , University of Mumbai, has been
offering post-graduate programs leading to Master’s degree in
Techno logy (M.Tech.) since 2017 -18.
Admissions to this program are based on primarily on the valid
GATE (Graduate Aptitu de Test Examination) score as per the
norms set by the DTE .

M. Tech. eligibility criteria

Candidates seeking admission t o Maharashtra M.Tech. programme
will have to fulfill the eligibility criteria set by Directorate of Technical
Education (DTE), Maharashtra, to be considered for admission. The
important eligibility criteria for admission are given below:
 The candidate need s be an Indian National.
 Hold a Bachelor’s degree in the relevant field of
Engineering/Technology from an All India Council for
Technical Education or Central or State Government approved
institution or its equivalent with minimum 50% marks (45% in
case of candidates belonging to backward class categories and
persons with disability and belonging to the State of
Maharashtra).
 Passed Bachelor Degree in the relevant field of Engineering
and Technology as per the DTE eligibility criteria for
admission to the P ost Graduate course the candidate is seeking
admission to.
 Must have obtained a positive (non -zero) score in GATE.

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AC- 30/07/2017
Item No. – 4.10
3. Intake
The intake for the M. Tech. (Computer Engineering) program is 30 and
reservation as per norms DTE and State of Maharashtra.
4. Fees:

5. Attendances
 Attendance in classes for all the subjects is compulsory and should
be 100%.
 Relaxation of maximum 25% in attendance is permissible to the
students on account of medical problems or any genuine reason.
 Student not having 75% attendance in any course/ practical will not
be allowed to appear in the end -term examination of that respective
course/ practical and given XX grade. He/she has to reregister for
all such courses .

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering)





UNIVERSITY OF MUMBAI



Syllabus for M. Tech . (Computer Engineering)
School of Engineering Science, Kalan Sub -Center
(As per Choice Based Credit and Grading System)
from
Academic Year 2017 -18

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering)
From Co -ordinator’s Desk:

To meet the challenge of ensuring excellence in engineering education, the issue of quality
needs to be addressed, debated and taken forward in a systematic manner. Accreditation is the
principal means of quality assurance in higher education. The major emphasis of accreditation
process is to measure the outcomes of the program that is being accredited. In line with this
Faculty of Technology of University of Mumbai has taken a lead in incorporating philosophy of
outcome based education in the process of curriculum development.
Faculty of Technology, University of Mumbai, in one of its meeting unanimously resolved that,
each Board of Studies shall prepare some Program Educational Objectives (PEO‟s) and give
freedom to affiliated Institutes to add few (PEO‟s) and course objectives an d course outcomes
to be clearly defined for each course, so that all faculty members in affiliated institutes
understand the depth and approach of course to be taught, which will enhance learner‟s learning
process. It was also resolved that, maximum senior faculty from colleges and experts from
industry to be involved while revising the curriculum. I am happy to state that, each Board of
studies has adhered to the resolutions passed by Faculty of Technology, and developed
curriculum accordingly. In addition to outcome based education, Choice Based Credit and
Grading System is also introduced to ensure quality of engineering education.
Choice Based Credit and Grading System enables a much -required shift in focus from teacher -
centric to learner -centric educati on since the workload estimated is based on the investment of
time in learning not in teaching. It also focuses on continuous evaluation which will enhance
the quality of education. University of Mumbai has taken a lead in implementing the system
through i ts affiliated Institutes Faculty of Technology has devised a transparent credit
assignment policy adopted ten points scale to grade learner‟s performance. Choice Based Credit
and Grading System were implemented for First Year Master of Engineering from the academic
year 2016 -2017. Subsequently this system will be carried forward for Second Year Master of
Engineering in the academic year 2017 -2018.

Dr. Suresh K. Ukarande
Co-ordinator,
Faculty of Technology,
Member - Academic Council
University of Mumbai, Mumbai

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering)
Preamble:
The M. Tech . in Com puter Engineering programme is offered to students who are interested in
advanced learning and research in any area of Computer Science and Engineering. Applicants to
this programme are expected to have a background in Computer Science and Engineering or
Information Technology.
The o bjective of the p rogram me is to enable the l earner to apply his/her enhanced skill and
knowledge at the top research laboratories and companies in the country and even a broad.
The programme is a 74 -credit degree programme, which is usually spread over 4 semesters for a
full-time student. About two -thirds of the credits involve coursework, and the r emaining consists
of project work. The emphasis is on conducting original research and writing a thesis
individ ually. The programme is flexible enough to allow a student to specialize in any topic of
interest by taking elective (optional) courses and working on a research project in that area.
University of Mumbai feels that it is desirable to provide specialized M. Tech. programme in
Computer Engineering to address the needs of the industry, which today req uires more
specialized resource in each field.
Faculty of Technology, University of Mumbai has taken a lead in incorporating philosophy of
Choice Based E ducation in the process of curriculum development.

Dr. Subhash K. Shinde
Chairperson,
Adhoc Board of Studies in Computer Engineering,
University of Mumbai, Mumbai .

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) Program Structure for M. Tech . in Computer Engineering,
University of Mumbai )
Semester –I

Course Code
Course Name Teaching
Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSC101 Algorithm & Complexity 04 --- --- 04 --- --- 04
CSC102 Advance Computer Network and
Design 04 --- --- 04 --- --- 04
CSC 103 Advanced Operating Systems 04 --- --- 04 --- --- 04
CSEL -I Elective -I 04 --- --- 04 --- --- 04
CSEL -II Elective -II 04 --- --- 04 --- --- 04
CSL101 Lab-I: Computational Laboratory on
Core Courses -- 02 -- 01 --- -- 01
CSL102 Lab-II :Laboratory on Elective
Courses -- 02 -- 01 --- -- 01
Total 20 04 -- 22 -- -- 22

Course
Code Course
Name Examination Scheme
Theory
TW Oral/
Pract Total Internal
Assessment End
Sem.
Exam Exam
Duration
( in Hrs) Test 1 Test 2 Avg.
CSC10 1 Algorithm & Complexity 20 20 20 80 3 -- --- 100
CSC102 Advance Computer Network
and Design 20 20 20 80 3 -- --- 100
CSC103 Advanced Operating Systems 20 20 20 80 3 -- --- 100
CSEL -I Elective -I 20 20 20 80 3 -- --- 100
CSEL -II Elective -II 20 20 20 80 3 -- --- 100
CSL101 Lab-I: Computational Laboratory
on Core Courses --- --- --- ---- ---- 25 25 50
CSL102 Lab-II :Laboratory on Elective
Courses --- --- --- ---- ---- 25 25 50
Total 100 100 100 400 ---- 50 50 600

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering)
Program Structure for M. Tech . in Computer Engineering,
University of Mumbai
Semester –II

Course
Code
Course Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CS201 High performance Computing 04 --- --- 04 --- --- 04
CS202 Data Science 04 --- --- 04 --- --- 04
CS203 Ethical Hacking and Digital Forensics 04 --- --- 04 --- --- 04
CSEL -III Elective -III 04 --- --- 04 --- --- 04
CSEL -IV Elective -IV 04 --- --- 04 --- --- 03
CSL201 Lab-III: Computational Laboratory on
Core Courses -- 02 -- 01 --- -- 01
CSL202 Lab-IV: Laboratory on Elective Courses
-- 02 -- 01 --- -- 01
Total 20 04 --- 22 -- -- 22

Course
Code Course
Name Examination Scheme
Theory
TW Oral/
Pract Total Internal
Assessment End
Sem.
Exam Exam
Duration
( in Hrs) Test 1 Test 2 Avg.
CSC201 High performance Computing 20 20 20 80 3 -- --- 100
CSC202 Data Science 20 20 20 80 3 -- --- 100
CSC203 Ethical Hacking and Digital
Forensics 20 20 20 80 3 -- --- 100
CSEL -III Elective -III 20 20 20 80 3 -- --- 100
CSEL -IV Elective -IV 20 20 20 80 3 -- --- 100
CSL201 Lab-III: Computational
Laboratory on Core Courses --- --- --- ---
- ---- 25 25 50
CSL202 Lab-IV :Laboratory on Elective
Courses --- --- --- ---
- ---- 25 25 50
100 100 100 400 ---- 50 50 600

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering)
Program Structure for M. Tech . in Computer Engineering,
University of Mumbai
Semester –I
Course Code Elective - I Course
Code Elective -II
CSE1011 Logic & Automated Reasoning CSE1021 User Experience Design
CSE1012 Image Analysis & Interpretation CSE1022 Mobile & Adaptive System
CSE1013 Natural Language Processing CSE1023 Advanced Network
Programming
CSE1014 Computational Intelligence CSE1024 Operations Research




Semester –II
Course Code Elective -III Course
Code Elective -IV
CSE2031 Data Storage & Retrieval CSE2041 ICT for Social cause
CSE2032 Internet of Things CSE2042 Internet Routing Design
CSE2033 Advance Soft Computing CSE2043 Grid and Cloud Computing
CSE2034 Semantic Web & Social
Network Analysis CSE2044 Project Management

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering)


Program Structure for M. Tech . in Computer Engineering,
(With Effect from 2016 -2017)
University of Mumbai
Semester –III

Course
Code
Course Name Teaching Scheme (Contact
Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CS301 Special Topic Seminar ---- 06 -- --- 03 -- 03
CS302 Dissertation -I --- 24 -- --- 12 -- 12
Total
---- 30 -- --- 15 -- 15
Course
Code Course
Name Examination Scheme
Theory
TW Oral/
Pract Total Internal Assessment End
Sem.
Exam Exam
Duration
( in Hrs) Test 1 Test 2 Avg.
CS301 Special Topic Seminar --- --- --- --- --- 50 50 100
CS302 Dissertation -I --- --- --- --- --- 100 --- 100
Total --- --- --- ---- --- 150 50 200

Semester –IV


Course Code
Course Name Teaching Scheme (Contact
Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CS401 Dissertation -II -- 30 -- --- 15 -- 15
Total -- 30 -- --- 15 -- 15
Course
Code Course
Name Examination Scheme
Theory
TW Oral/
Pract Total Internal Assessment End
Sem.
Exam Exam
Duratio
n ( in
Hrs) Test 1 Test 2 Avg.
CS401 Dissertation -II -- --- --- --- --- 100 100 200

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) Total -- --- --- --- --- 100 100 200

Course Objectives:
1. To analyze the algorithms using space and time complexity.
2. To teach problem formulation and problem solving skills .
3. To acquire knowledge of various applied algorithms.
4. To understand selected topics in algorithms that have found applications in areas
such as geometric modelling, graphics, robotics, vision, computer animation, etc.

Course Outcomes: At the end of the course student should be
 Able to prove the correctness and analyze the running time of the basic algorithms
for those classic problems in various domains
 Able to apply the algorithms and design techniques to solve prob lems.

Prerequisite: Data structure, Analysis of Algorithms, Set Theory
Sr.
No. Module Detailed Content Hours
1 Foundations  Algorithms, Analysing algorithms, Growth of
Functions -Asymptotic notation, Mathematical
Background for algorithm analysis
 Recurrences, The substitution method, The
recursion -tree method, The master method,
Randomized algorithms 4
2 Advanced
Design and
Analysis
Techniques  Dynamic Programming -Elements of dynamic
programming, Matrix -chain multiplication
 Greedy Algorithms -Elements of the greedy strategy,
Huffman codes
 Amortized Analysis -Aggregate analysis, The
accounting method, The potential method, Dynamic
tables 6 Subject
Code Subject Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSC101 Algorithm and
Complexity 04 -- -- 04 -- -- 04
Examination Scheme
Theory Examination
Term
Work Pract Oral Internal Assessment End
Sem
Exam Test 1 Test 2 Avg
20 20 20 80 -- -- --

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) 3 Graph
Algorithms  Single -Source Shortest Paths -The Bellman -Ford
algorithm, Dijkstra‟s algorithm, Difference
constraints and shortest paths
 All-Pairs Shortest Paths -The Floyd -Warshall
algorithm
 Maximum Flow -Flow networks, The Ford -Fulkerson
method, Maximum bipartite matching 8
4 Computational
Geometry  Line-segment properties, Determining whether any
pair of segments intersects,
 Finding the convex hull, Finding the closest pair of
points 8
5 NPC and
Approximation
Algorithms  NP-Completeness: NP -completeness and
reducibility, NP -completeness proofs, NP -complete
problems,
 Approximation algorithms: The vertex -cover
problem, The traveling -salesman problem, The set -
covering problem, The subset -sum problem 10
6 Applied
Algorithms  Number -Theoretic : Number Theoretic notion,
Greatest common divisor, The Chinese remainder
theorem, RSA
 String M atching Algorithms :The Rabin -Karp
algorithm, The Knuth -Morris -Pratt algorithm,
Longest common subsequence
 Parallel Algorithm: Mesh Algorithm and its
applications
 Probabilistic Algorithm: Game Theoretic
Techniques
 Randomized Algorithms: Monte Corlo and Las
Vegas algorithms 12

Text Books:
1. Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein, “Introduction
to Algorithms”, PHI, India Second Edition
2. Horowitz, Sahani and Rajsekaran, Fundamentals of Computer Algorithms”, Galgotia
3. Rajeev Motwani, PrabhakarRaghavan, “ Randomized Algorithm”, Cambridge University
Press
Reference Books:
1. Aho, Hopcroft, Ullman: The Design and analysis of algorithms”, Pearson Education
2. Vijay V. Vajirani, “Approximation Algorithms”,Springer.

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) 3. S. K. Basu, “Design Me thods and Analysis of Algorithm”, PHI
4. SanjoyDasgupta, Christos Papadimitriou, UmeshVazirani, “Algorithms”, Tata McGraw -
Hill Edition

Internal Assessment: Assessment consists of two tests out of which; one should be compulsory
class test (on minimum 02 Mo dules) and the other is either a class test or assignment on live
problems or course project .

Theory Examination:
1. Question paper will comprise of total s ix question
2. All q uestion carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3
then part (b) will be from any module other than module 3)
4. Only Four question need to be solved.

In question paper weightage of each module will be proportional to number of
respective lecture hours as mention in the syllabus.

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) Subject
Code Subject Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSC102 Advanced Computer
Networking and
Design 04 -- -- 04 -- -- 04
Examination Scheme
Theory Examination
Term
Work Pract Oral Internal Assessment End
Sem
Exam Test 1 Test 2 Avg
20 20 20 80 -- -- --

Course Objectives:
1. To study the problem of congestion control and service integration in TCP/IP networks
focusing on protocol design, implementation and performance issues.
2. To understand the principles of network design and enable students to setup, configure and
interconnect an IP network.
3. To debate the current trends and leading research in the computer networking area.

Course Outcomes: Learner will abl e to
 Understand the theoretical issues in protocol design and apply it to Quality of service in
networks .
 Understand issues in the design of network processors and apply them to design network
systems
 Simulate working of wired and wireless networks to understand networking concepts .
 Develop solutions by applying knowledge of mathematics, probability, and statistics to
network design problems .
 Understand the basics of software defined networking and explore research problems in that
area.
Sr.
No. Module Detailed content Hours
1 Internetworking Congestion control and Resource allocation : Issues of
Resource Allocation, Queuing Disciplines: FIFO, Fair
Queuing, TCP Congestion Control: Additive
Increase/Multiplicative Decrease, Slow Start, Fast
Retransmit and Fast Recovery.
Congestion -Avoidance Mechanisms : DECbit, Random
Early Detection (RE D), So urce-Based Congestion
Avoidance, Quality of Ser vice: Application Requirements,
Integrated Services (RSVP), Differentiated Services (EF,
AF). 10

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) 2 Routing: IPv4 Routing Principles, Routing Information Protocol
(RIP), IGR P and EIGRP, OSPF for IPv4 and IPv6, Border
Gateway Protocol (BGP), EIGRP, High Availability
Routing . 08
3 IPv6 IPv4 deficiencies, patching work done with IPv4, IPv6
addressing, multicast, Anycast, ICMPv6, Neighbour
Discovery, Routing, Resource Reservation, IPv6 protocols. 06
4 Network Design: Designing the network topology and solutions -Top down
Approach: PPDIOO – Network Design Layers - Access
Layer, Distribution Layer, Core/Backbone Layer, Access
Layer Design, Backbone Network Design, Enterprise LAN
Design: Et hernet Design Rules and Campus Design best
practices, Virtualisation and Data Center Design, Wireless
LAN Design, WAN Design: Traditional WAN
Technologies, VPN Design. 14
5 Ad Hoc Wireless
Networks MAC Protocols for Ad Hoc Wireless Networks: MACA/W,
MACA -BI, DPRMA, MACA/PR. Routing Protocols for Ad
Hoc Wireless Networks: DSDV, DSR, AODV, ZRP.
Transport Layer: ATCP. 06
6 Software
Defined
Networking and
OpenFlow Introduction to Software Defined Networking, Control and
Data Planes, SDN Controllers, In troduction to Openflow
Protocol, Network Function Virtualization -Concepts.
04

Text Books:
1. Larry L. Peterson and Bruce S. Davie, Computer Networks: A Systems Approach,
Elsevier, Fourth Edition.
2. Philip M. Miller, TCP / IP: The Ultimate Protocol Guide Applications, Access and Data
Security - Vol 2, Wiley
3. Pete Loshin, IPv6: Theory, Protocols and Practice, Morgan Kaufmann, 2nd Edition,
2004
4. Anthony Bruno, Steve Jordan, Official Cert Guide: CCDA, Cisco Press,
5. C. Siva Ram Murthy, B.S. Manoj, Ad Hoc Wireless Networks: Architectures and,
Prentice Hall, 2004.
6. Thomas D NAdeau and Ken Grey, Software Defined Networking, O'Reilly, 2013

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering)

Reference Books:
1. William Stallings, High -Speed Networks and Internets, Pearson Education, 2nd
Edition, 2002.
2. James F. Kurose, Keith W. Ross, “Computer Networking, A Top -Down Approach
Featuring the Internet”, Third Edition, Addison Wesley, 2004.
3. Pujolle, Software Networks: Virtualisation, SDN, 5G, Security, Wiley,


Internal Assessment: Assessment consists of two tests out of which; one should be compulsory
class test (on minimum 02 Modules) and the other is either a class test or assignment on live
problems or course project .

Theory Examination:
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3
then part (b) will be from any module other than module 3)
4. Only Four question need to be solved.

In question paper weightage o f each module will be proportional to number of
respective lecture hours as mention in the syllabus.

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering)
Subject Code Subject Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSC103 Advanced
Operating
System 04 -- -- 04 -- -- 04
Examination Scheme
Theory Examination
Term
Work Pract Oral Internal Assessment End
Sem
Exam Test 1 Test 2 Avg
20 20 20 80 -- -- --

Course Objectives:
1. To learn the architectural differences and issues related to Advance d Operating System .
2. To get a comprehensive knowledge of the distributed systems and Real time operating
system.
3. To get a thorough knowledge of database operating systems and cloud operating System .

Course Outcomes: Learner will able to
 Apply the principles and concepts in analyzing and designing Advance Operating
System.
 Demonstrate the Mutual exclusion, Deadlock detection and agreement protocols of
Distributed operating system
 Analyze the performance and reliabili ty of different Advanced Operating Systems.

Sr.
No. Module Detailed content Hours
1 Introduction  Types of Advanced Operating Systems.
 Architectures and design issues of Network
operating system, DOS, Middleware, RTS, DBOS.
 Introduction to process, Concurrent processes,
Critical Section problems, other synchronization
problems. 04
2 Distributed
operating Systems,
Scheduling and
synchronization  Scheduling: Issues in load distributing, Components
of load distributing algorithms, Stability, Load
distributing algorithms, Performance Comparison,
Selecting a suitable load sharing Algorithm.
 Synchronization: Physical and logical clocks.
 Distributed Mutual Exclusion: Introduction,
Classification of Mutual Exclusion algorithms,
Mutual Exclusion Algorith ms. 12

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering)  Distributed Deadlock: Introduction, deadlock
handling strategies, Deadlock detection: Issues and
resolution, Control Organizations, Centralized
algorithms, Distributed algorithms, Hierarchical
algorithms.

3 Distributed Fault
Handling  Agreement Protocol: System Model, Classification,
Solution to Byzantine Agreement Problem.
 Fault Recovery: Concepts, Classification of failures,
Backward error recovery, Recovery in concurrent
Systems, Consistent Check Points, Synchronous and
Asynchronous check poin ting and recovery.
 Fault tolerance: Issues, Atomic actions and
committing, Commit Protocols, Non -blocking
Commit protocols, Voting protocols and Dynamic
Voting Protocols. 10
4 Real Time
Operating Systems  Types of Real time tasks, Timing Constraints,
Modeling Timing Constraints.
 Task Scheduling: Types of tasks and their
characteristics, Task Scheduling, Clock driven
Scheduling , Hybrid Schedulers, Event driven
Scheduling, EDF Scheduling, Rate Monotonic
Algorithm
 Resource Handling: Resource Sharing, Pri ority
Inversion, PIP,PCP,HLP.
 Scheduling real time tasks in distributed systems 12
5 Database Operating
systems  Concurrency control : Database systems,
Concurrency control model of database systems,
Problem of Concurrency Control, serializability
theory, Distributed Database Systems
 Concurrency Control Algorithms : Basic
synchronization Algorithms, Lock based,
Timestamp based and Optimistic Algorithms,
Concurrency Control Algorithms : Data Replication 06
6 Case Study  DOS: Mach, Amoeba
 .RTOS : UNIX as RTOS , Windows as RTOS.
 Mobile OS.
 Cloud OS 04

Text books:
1. Mukesh Singhal, Niranjan G.Shivaratri, "Advanced concepts in operating systems:
Distributed, Database and multiprocessor operating systems" .MC Graw Hill education.

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) 2. Rajib Mall, “ Real-Time Systems: Theory and Practice”, Pearson education.

Reference Books:
1. Andrew S.Tanenbaum, "Modern Systems Principles and Paradigms". PHI.
2. Pradeep K.Sinha, "Distributed Operating S ystem -Concepts and design", PHI.
3. Andrew S.Tanenbaum, "Distributed Operating S ystem", Pearson Education.
4. Jane W. S. Liu, “Real Time Systems”, Pearson education .

The suggested lists of experiment/case study of Advanced Operating System are as follows:
I. Flexibility/Load Distribution
1) Implement and study the incremental/decremented growth of response and service times
for different number of client and servers for servicing continuous stream(s) of constant
sized messages.
2) Implement a name server for registration and identification of se rvices running on
another server. The client contacts the name server for a particular service and the service
request is forwarded to the specific server registered on the name server. Study the load
distribution for different number of service servers, c lients and service requests.
II. Fault Tolerance/Reliability
1) Implement a fault tolerant client and server application using the concept of name server.
The client incorporates fault tolerant by sending a service request to another server using
name server, if the current server fails to respond within 10 seconds.
2) Implement a stateful server for a transaction consisting of mainly four operations viz.
open a file, close opened file, read from opened file and write to opened file. The state of
file operation i s maintained at stateful server.
III. Performance
1) Implement a client -server application for a computing problem (of exponential
complexity). Compare the performance for a local and remote machine of different
speeds.
2) Implement parallel Fast -Fourier -Transfo rm (parallel FFT). Show that the overall
communication time complexity is O ((n/p) log p), and the computational complexity of

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) the parallel algorithm is O (n log n/p) where n is number of elements, and p is number of
processes.

IV. Transparency
1) Implemen t a client -server application to show transparent service access so that the client
does not know the location of service is being executed.
V. Mobile Application
1) Implement a client -server application to allow transfer of any data (e.g. images,
documents, videos etc.) on android mobile operating system. Each mobile device runs a
program which acts as a server when it receives data from another device or a client
when it sends data to another mobile device.
2) Implement a distributed share list among a group of mobile device users which is similar
to Google document .

Internal Assessment: Assessment consists of two tests out of which; one should be compulsory
class test (on minimum 02 Modules) and the other is either a class test or assignment on live
problems or course project.

Theory Examination:
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3
then part (b) will be from any module other than module 3)
4. Only Four question need to be solved.

In question paper weightage of each module will be proportional to number of respective
lecture hours as mention in the syllabus .

Page 35

AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering)



Subject Code Subject Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSE1011 Logic &
Automated
Reasoning 04 -- -- 04 -- -- 04
Examination Scheme
Theory Examination
Term
Work Pract Oral Internal Assessment End
Sem
Exam Test 1 Test 2 Avg
20 20 20 80 -- -- --

Course Objectives :
1. Represent mathematical and other knowledge using logical formalism.
2. Understand theoretical concepts and results that form the basis of current automated
reasoning systems.
3. Understand advanced techniques of resolution theorem proving and be able to use them.

Outcomes : Learner will be able to ...
 Comprehend syntax and semantics of Propositional logic, first -order logic, inference
system, proof, soundness and completeness.
 Apply various deductive algorithms and models for reasoning
 Emphasize various techniques for automated reasoning, theorem proving

Sr.
No. Module
Detailed Contents Hours
1 Introduction
to Logic  Mathematical Logic, Propositional Logic, First -Order
Logic, Modal Logic, Temporal Logic,
 Program Verification 04
2 Propositional
Logic  Formulas, Models, Tableaux: Propositional Formulas,
Interpretations ,Logical Equivalence, Sets of Boolean
Operators, Satisfiability, Validity and Consequence,
Semantic Tableaux, Soundness and Completeness
 Resolutions: Conjunctive Normal Form, Clausal Form,
Resolution Rule, Soundness and Completeness of
Resolution
 Binary Decision Diagrams: Motivation Through Truth
Tables, Definition of Binary Decision Diagrams,
Reduced Bi nary Decision Diagrams 12
3 First-Order  Formulas, Models, Tableaux: Relations and Predicates, 12

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) Logic Formulas in First -Order Logic, Interpretations, Logical
Equivalence, Semantic Tableaux, Soundness and
Completion of Semantic Tableaux
 Resolution: Ground Re solution, Substitution,
Unification, General Resolution, Soundness and
Completeness of General Resolution
 Introduction to Logic Programming: Prolog
4 Reasoning
Methods  SAT Solvers: Properties of Clausal Form,
 Davis -Putnam Algorithm, DPLL Algorithm
 Deductive Systems: Gentzen System, Hilbert System
 Terms and Normal Forms : First -Order Logic with
Functions, PCNF and Clausal Form, Herbrand Models 08
5 Automated
Reasoning  Automated Reasoning for Web system,
 Semantic Web applications,
 REWERSE -automated reasoning method and tools, 06
6 Theorem
Proving  Some exposure to theorem proving systems such as
Prolog, PVS, SPIN 06

Text Books
1. Mordechai Ben -Ari, Mathematical Logic for Computer Science, Third Edition, Springer
2 Arindama Singh, Logics for Computer Science, Prentice Hall of India.

Reference Books

1. Handbook of Practical Logic and Automated Reasoning, John Harrison, Cambridge
University Press
2. Michael Huth and Mark Ryan, Logic in Computer Science: Modelling and Reasoning about
Systems, Cambridge University Press.

Internal Assessment: Assessment consists of two tests out of which; one should be compulsory
class test (on minimum 02 Modules) and the other is either a class test or assignment on live
problems or c ourse project.
Note: One Case Study to be given for Module 5 and 6 based on the above concepts.

Theory Examination:
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q .2 has part (a) from module 3
then part (b) will be from any module other than module 3)
4. Only Four question need to be solved.

Page 37

AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering)
In question paper weightage of each module will be proportional to number of respective
lecture hours as mention in the syllabus .


Subject Code Subject Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSE1012 Image Analysis
and
Interpretation 04 -- -- 04 -- -- 04
Examination Scheme
Theory Examination
Term
Work Pract Oral Internal Assessment End
Sem
Exam Test 1 Test 2 Avg
20 20 20 80 -- -- --

Objective:
1. To explore the various Image Analysis and Interpretation techniques
2. To become accustomed with different methods of Feature generation, Representation
Description and Interpretation.
3. To Analyze & Interpret Images and use for various applications

Outcome: Learner will able to
 Understand the importance of Image Analysis and Interpretation.
 Analyze various methods of Image Analysis
 Use the methods of image analysis and interpretation for various Image Processing
applications .

Prerequisite: Image Processing, Mathematics .

Sr.
No. Module Detailed content Hours
1 Introduction to
Image
Processing
System  Introduction,
 Sources of Images
 Classification of Images
 Elements of Image Processing System
 Image Modelling – Sampling, Quantization and
Representing Digital Images.
 Image Preprocessing – 08

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) o Enhancement : Power Law Transformation,
Contrast Stretching and Histogram
Equalization
o Spatial domain Filters: Smoothing,
Sharpening

2 Feature
Generation  Introduction
 Basis Vectors and Images
 K-L transformation
 Singular Value Decomposition
 Independent Component Analysis
 Non–Negative Matrix Factorization
 Non- linear Dimension Reduction
 Haar Transform
 Multi resolution Interpretation 12


3 Image
Analysis  Data Structure for Image Analysis
o Levels of image data representation
o Traditional image data structures
o Hierarchical data structures
 Image Segmentation
o Thresholding
o Edge based and Region Based Segmentation
o Boundary Extraction
 Feature Extraction
o Spatial Feature Extraction
o Transform Feature Extraction 10


4 Image
Representation
and
Description  Boundary Representation
 Region Representation
 Moments Representation
 Structure Representation
 Shape Representation
 Texture Representation 06

.


5 Statistical
decision
making and
Vector
Quantization  Statistical decision making:
Bayesian theorem
Multiple features
Conditionally independent features
Decision boundaries
Unequal cost of error
Estimation of error rates 08

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering)  Vector Quantization
6 Applications Case Study on
 Remote Sensing Images
 Medical Images
 Image Forensics: Finger print classification
 Digital Watermarking for Images 04
Text Books:
1. Fundamentals of Digital Image Processing Anil K. Jain, PHI
2. Pattern Recognition, Theodoridis & Koutroumbas , 4th Edition, Academic Press
3. Digital Image Processing , Second Edition, Rafael C. Gonzalez and Richard E. Woods,
Pearson Prentice Hall,
4. Digital Image Processing, S Jayaraman, S Esakkirajan, T Veerakumar, Tata McGraw -Hill
Education Private Limited, 2011 .
5. Digital Image Processing, S. Sridhar, Oxford University Press.
6. Image Processing, Analysis, and Machine Vision, Milan Sonka Vaclav Hlavac Roger
Boyle .
7. Pattern recognition and Image analysis by Earl Gose, Richard Johnsonbaugh, Steve Jost,
PHI publication
Reference Books:
1. Digital Image Processing An Algorithm Approach, Madhuri A. Joshi, PHI
2. Principles of Soft Computing , S N Shivanandan, S N Deepa, Wiley

Internal Assessment: Assessment consists of two tests out o f which; one should be compulsory
class test (on minimum 02 Modules) and the other is either a class test or assignment on live
problems or course project.

Theory Examination:
1. Question paper will comprise of total six question
2. All question carry equal marks

Page 40

AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) 3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3
then part (b) will be from any module other than module 3)
4. Only Four question need to be solved.

In question paper weightage of each module will be proportional to number of respective
lecture hours as mention in the syllabus .
Subject Code Subject Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSE1013 Natural
Language
Processing 04 -- -- 04 -- -- 04
Examination Scheme
Theory Examination
Term
Work Pract Oral Internal Assessment End
Sem
Exam Test 1 Test 2 Avg
20 20 20 80 -- -- --

Course Objectives:
1. To formulate the problems and solutions of NLP and establish their relation to linguistics and
statistics.
2. To implement various language Models.
3. To design systems that uses NLP techniques
4. To train and evaluate empirical NLP systems.

Course Outcomes: At the end of the course student should be able to
 Model linguistic phenomena with formal grammars.
 Design, implement, and analyze NLP algorithms
 Apply NLP techniques to design real world NLP applications, such as machine translation,
text categorization, text summarization, information extraction...etc.
 Implement proper experimental met hodology for training and evaluating empirical NLP
systems .

Prerequisite: Data structure & Algorithms, Theory of computer science, Probability Theory
DETAILED SYLLABUS:
Sr. No. Module Detailed Content Hours

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) 1 Introduction
History of NLP, Generic NLP system, levels of NLP ,
Knowledge in language processing , Ambiguity in Natural
language , stages in NLP, challenges of NLP ,Applications
of NLP - Machine translation, question answering system,
Information retrieval, Text catego rization , text
summarization & Sentiment Analysis 3
2 Word Level
Analysis
Morphology analysis –survey of English Morphology,
Inflectional morphology & Derivational morphology;
Regular expression, finite automata, finite state transducers (
FST) ,Morph ological parsing with FST , Lexicon free FST -
Porter stemmer. N –Grams - N-gram language model , N -
gram for spelling correction . 9
3 Syntax
analysis
Part-Of-Speech tagging( POS) - Tag set for English ( Penn
Treebank ) , Rule based POS tagging, Stochastic POS
tagging, Issues –Multiple tags & words, Unknown words,
class based n –grams .Context Free Grammar –
Constituency , Context free rules & trees, Sent ence level
construction , Noun Phrase, coordination, agreement, the
verb phrase & sub categorization 10
4 Semantic
Analysis Attachment for fragment of English - sentences, noun
phrases, Verb phrases, prepositional phrases, Relations
among lexemes & their senses –Homonymy, Polysemy,
Synonymy, Hyponymy, Wordnet, Selectional restriction
based disambiguation & limitations , Robust WSD –
machine learning approach and dictionary based approach 10
5 Pragmatics
Discourse –reference resolution, reference phenome non ,
syntactic & semantic constraints on co reference,
preferences in pronoun interpretation , algorithm for
pronoun resolution .Text coherence, discourse structure 8
6 Applications
( preferably for
Indian regional
languages) Machine translation, Information retrieval, Question answers
system, categorization, summarization, sentiment analysis. 8


Text Books:

1. Daniel Jurafsky, James H. Martin “Speech and Language Processing” Second Edition,
Prentice Hall, 2008.
2. Christopher D.Manning and Hinrich Schutze, “ Foundations of Statistical Natural
Language Processing “, MIT Press, 1999.

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) Reference Books :
1. Siddiqui and Tiwary U.S., Natural Language Processing and Information Retrieval,
Oxford University Press (2008).
2. Daniel M Bikel and Imed Zitouni “ Multilingual natural language processing
applications” Pearson, 2013
3. Alexander Clark (Editor), Chris Fox (Editor), Shalom Lappin (Editor) “ The Handbook
of Computational Ling uistics and Natural Language Processing “ ISBN: 978 -1-118-

Case study/Experiments:
The objective of Natural Language Processing lab is to introduce the students with the basics of
NLP which will empower them for developing advanced NLP tools and solving practical
problems in this field.
Reference for Experiments: http://cse24 -iiith.virtual -labs.ac.in/#
Sample Case study/Experiments :
Note: Although it is not mandatory, the experiments can be conducted with reference to any
Indian regional language.
1. Word Analysis
2. Word generation
3. Stop word removal
4. Stemming
5. Morphology
6. POS Tagging
7. Chunking
8. N-gram language model

Internal Assessment: Assessment consists of two tests out of which; one should be compulsory
class test (on minimum 02 Modules) and the oth er is either a class test or assignment on live
problems or course project.

Theory Examination:

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) 1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3
then part (b) will be from any module other than module 3)
4. Only Four question need to be solved.

In question paper weightage of each module will be proportional to number of respective
lecture hours as mention in the syllabus .

Subject Code Subject Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSE1014 Computational
Intelligence 04 -- -- 04 -- -- 04
Examination Scheme
Theory Examination
Term
Work Pract Oral Internal Assessment End
Sem
Exam Test 1 Test 2 Avg
20 20 20 80 -- -- --

Course Objective s:
1. To explore the various computational Intelligence techniques
2. To become familiarized with Neural Network, Fuzzy logic & evolutionary techniques
3. To learn to apply computational Intelligence to different applications

Course Outcome s: Learner will able to
 Understand the importance of computational Intelligence.
 Analyze various computational Intelligence technology
 Design and implement various intelligent system.

Prerequisite: Soft Computing, Mathematics
Sr.
No. Module Detailed content Hours
1 Introduction to
Computational
Intelligence Artificial Neural Networks, Fuzzy Systems, Genetic
Algorithms, Swarm Intelligence, Artificial Immune
System, Application s 6

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) paradigms
2 Artificial Neural
Networks & SVM Basic models of ANN: NN Architecture, MP Neuron,
Linear separability, activation functions, types of
learning
Learning Rules: Hebbian, Perceptron, Delta, Winner -
take all
Supervised NN: Perceptron Network: SDPTA, SCPTA,
MCPTA, Adaline networks
Support Vector Machine: Binary SVM 14
3 Fuzzy Systems Fuzzy Sets: Definition, operations, properties, relations,
characteristics, membership functions, defuzzification. 8
4 Optimization GA: Selection, Encoding, Crossover, Mutation,
Examples.
Swarm Intelligence:
Single Solution Particle Swarm Optimization:
Guaranteed Convergence PSO, Social -Based Particle
Swarm Optimization, Hybrid Algorithms, Sub -Swarm
Based PSO, Multi -Start PSO Algorithms, Repelling
Methods, Binary PSO,
Ant Algorithm: Simple Ant Colony Optimization 10
5 Artificial Immune
System Natural Immune System: Classical view, Antibodies and
antigens, Artificial Immune Models:
Artificial Immune system algorithm, classical view
models, CLONALG 4
6 Applications Character Recognition , Genetics Algorithm in game
playing , Color Recipe prediction - Single MLP approach
ANT algorithm/Swarm Intelligence – TSP, Best path
finding 6

Text Books:
1. Computational Intelligence An Introduction, Andries P. Engelbrecht, Wiley, 2nd Edition
2. Principles of Soft Computing, S.N. Sivanandam, S.N. Deepa, Wiley, 2nd edition
3. Introduction to Artificial Neural Systems, Jacek M. Zurada, West Publication
4. Pattern Recognition, Theodoridis and Koutroumbas , 4th Edition, Academic Press

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) Internal Assessment: Assessment consists of two tests out of which; one should be compulsory
class test (on minimum 02 Modules) and the other is either a class test or assignment on live
problems or course project .

Theory Examination:
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3
then part (b) will be from any module other than module 3)
4. Only Four question need to be solved.


In question paper weightage of each module will be proportional to number of
respective lecture hours as mention in the syllabus.
Subject Code Subject Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSE1021 User
Experience
Design 04 -- -- 04 -- -- 04
Examination Scheme
Theory Examination
Term
Work Pract Oral Internal Assessment End
Sem
Exam Test 1 Test 2 Avg
20 20 20 80 -- -- --

Course Objectives:
1. To study and understand importance of user experience design principles
2. To understand elements of user experience design
3. To encourage students to participate in designing futuristic applications

Course Outcomes: Learner will be able to:
 To Apply principles of user experience
 To apply emerging and established technologies to enhance User Experience design
 To create interface for international standards with ethics
 To evaluate user experience .

Pre-requisites: Web Technologies; Software Engineering; Experience in designing interfaces
for applications and web sites. Basic knowledge of designing tools and languages like HTML,
Java, etc. User experience design is concerned with all the elements that together make up user
interface, including layout, visual design, text, brand, sound, and i nteraction. User Experience
Design works to coordinate these elements to allow for the best possible interaction by users.

Page 46

AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) Sr.
No. Module Detailed Contents Hours
1 Introduction Introduction to interface design, Understanding and
conceptualizing Interface, Understandinguser‟s
conceptual cognition. 04
2 Elements of UX Design
Core Elements of User Experience, Working of UX
elements 04
3 The UX Design Process –
Understanding Users
Defining the UX, Design Process and
Methodology, Understanding user requirements
and goals, Understanding the Business
Requirements/Goals, User research, mental models,
wireframes, prototyping, usability testing. 08
4 The UX Design Process -
The Structure: Information
Architecture and
Interaction Design Visual Design Principles ,Information Design and
Data Visualization Interaction Design ,Information
Architecture , Wire framing & Storyboarding,UI
Elements and Widgets, Screen Design and Layouts 08
5 UX Design Process:
Prototype and Test
Testing your Design, Usability Testing,Types of
Usability Testing ,Usability Testing Process,
Preparing and planning for the Usability Tests,
Prototype your Design to Test, Introduction of
prototyping tools,conducting Usability Test,
communicating Usability Test Results 08
6 UX Design Process:
Iterate/ Improve and
Deliver
Understanding the Usability Test,findings,
Applying the Usability Test, feedback in improving
the design.
Communication with implementation team. UX
Deliverables to be given to implementation team
04

Text Books
1. Interaction Design, Beyond Human Computer Interaction, Rogers, Sharp, Preece Wiley
India Pvt Ltd.
2. The essentials of Interaction Design, Alan Cooper, Robert Reimann, David Cronin
3. Designing The user Interface by Shneiderman, Plaisant,Cohen,Jacobs Pearson

Reference Books:
1. The Elements of User Experience by Jesse James Garrett
2. Don‟t make me think, by Steve Krug
3. Observing the User Experience: A Practitioner's Guide to User Research by Mike
Kuniavsky

Page 47

AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) Internal Assessment: Assessment consists of two tests out of which; one should be compulsory
class test (on minimum 02 Modules) and the other is either a class test or assignment on live
problems or course project.

Theory Examination:
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3
then part (b) will be from any module other than module 3)
4. Only Four question need to be solved.

In question paper weightage of each module will be proportional to number of respective
lecture hours as mention in the syllabus .

Subject Code Subject Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSE1022 Mobile and
Adaptive
System 04 -- -- 04 -- -- 04
Examination Scheme
Theory Examination
Term
Work Pract /
Oral Total Internal Assessment End
Sem
Exam Test 1 Test 2 Avg
20 20 20 80 -- -- 100

Course Objectives:
1. Understand various Mobile and wireless systems
2. Study Architecture and various processes of GSM
3. Provide the knowledge of concept of Mobile IP and related issues
4. Detailed study o f security issues in Ad -hoc networks

Course Outcomes: Learner will able to -
 Gain knowledge about Voice and Data communication wireless systems
 Able to develop and design mechanisms for Mobile and wireless communication.
 Demonstrate the technical competence necessary for solving problems in Mobile and
wireless systems.

Page 48

AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) Sr.
No. Module Detailed Content Hours
1 Introduction and
overview
General issues that will be addressed on this module.
Properties of wireless PANs, LANs, WANs, Basic
structure and operation, Ad -hoc and Infrastructure
networks. Physical constraints and limitations
(transmission & reception). 8
2 Network
structures and
architectures Hand -off and mobility support at the physical/link level.
Technologies at physical link layer. PANs Bluetooth,
LANs IEEE802.11, Hiper LAN. 8
3 Global system
for mobile
communication
(GSM) Mobile Services, System Architecture, Protocols,
Localization & Calling, Handover, Security. GPRS :
GPRS System Architecture. UMTS: UMTS System
Architecture.LTE: Long Term Evolution. 10
4 Mobile IP Mobile IPv4 and Mobile IPv6. Problems with routing,
QoS and security. Overview of use of intelligence in
mobile systems , Power management, replication,
adaptation. Power management issues. From the lowest
(physical device) levels, through communication
protocols, broadcast methodologies, trans coding, etc. 8
5 File Systems CODA, Mobile Infrastructure support, Mobile
middleware, Adaptive and reconfigurable Systems, Next
generation wireless overview (4G/5G): UMTS, IMT 2000
and W -CDMA.

8
6 Mobile
multimedia and
their relationship
to proxying Programmable networking and Applications for mobile
systems. Code mobility an d control/signaling. 6

Text Books:
1. Jochen Schiller, “Mobile Communications”, Pearson Education, Second Edition, 2008.
2. Dr. Sunilkumar, “Wireless and Mobile Networks: Concepts and Protocols”, Wiley Publication.
Reference Books:
1. Raj Kamal, “Mobile Computing”, OXFORD UNIVERSITY PRESS.
2. Ed. Dejan Milojicic, Frederick Douglis and Richard Wheeler, “Mobility: Processes, computers
and agents ." ACM Press.

Page 49

AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) Internal Assessment: Assessment consists of two tests out of which; one should be compulsory
class t est (on minimum 02 Modules) and the other is either a class test or assignment on live
problems or course project.

Theory Examination:
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3
then part (b) will be from any module other than module 3)
4. Only Four question need to be solved.

In question paper weightage of each module will be proportional to number of respective
lecture hours as mention in the syllabus.






Subject Code Subject Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSE1023 Advanced
Network
Programming 04 -- -- 04 -- -- 04
Examination Scheme
Theory Examination
Term
Work Pract /
Oral Total Internal Assessment End
Sem
Exam Test 1 Test 2 Avg
20 20 20 80 -- -- 100

Course Objectives:
1. Provide students with a thorough introduction to a variety of important principles in
networking, with a strong focus on the Internet.
2. Learn to writ e programs using the socket interface.
3. Give an introduction to the TCP/IP client -server model of interaction, and to writing
networking applications using the client/server technology .
4. Discussion on writing of secure software.
Course Outcomes: Learner will able to -
 Write socket API based programs

Page 50

AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering)  Design and implement client -server applications using TCP and UDP sockets
 Understand with several common programming interfaces for network communication
 Formulate the basic concep t of socket programming and client server model
Sr. No. Module Detailed Content Hours
1 Transport Layer
TCP and UDP with policy control, TCP Connection
Establishment and Termination, TIME_WAIT State, Port
Numbers and Concurrent Servers, Buffer Sizes and
Limitations. 6
2 Sockets and
Socket
Programming Introduction, Socket Address Structures, Value -Result
Arguments, Byte Ordering Functions, Byte Manipulation
Functions, socket Function. 8
3 Application
Development TCP Echo Server: main and str_echo Function, TCP Echo
Client: main and str_cli Function, Normal Startup,
Normal Termination, POSIX Signal Handling, SIGPIPE
Signal, wait and waitpid function Connection abort before
accept return, Termination of server pr ocess, Crashing of
Server Host, Crashing and Rebooting of Server Host and
Shutdown of Server Host. 10
4 Socket Option
and Elementary
UDP Socket Getsocket and setsocket functions – generic socket
options, IP socket options, ICMP socket options,
Elementary UDP sockets: UDP echo Server, UDP echo
Client, Multiplexing TCP and UDP sockets. 8
5 Advanced
Sockets IPv4 and IPv6 Interoperability: IPv4 Client, IPv6 Server,
IPv6 Client, IPv4 Server, IPv6 Address Testing Macros,
IPV6_ADDRFORM Socket Option ICMPv4 and
ICMPv6.
Name and Address Conversions: Domain Name System,
Functions. Advanced Name and Address Conversi ons:
Functions and Implementation
Threads: Thread Functions: Creation and Termination,
Thread -Specific Data, Web Client and Simultaneous
Connections 8
6 Routing Sockets Data link Socket, Address Structure, Reading and Writing,
Interface Name and Index Functions, data link access, raw
socket (creation input, output)
Client -Server Design Alternatives:
TCP Client Alternatives, TCP Test Client, Iterative Server,
Concurrent Server, Thread Locking around accept,
Descriptor Passing, TCP Concurrent Server, One Thread 8

Page 51

AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) per Client, TCP Pre -threaded Server.
Text Books:
1. Richard Stevens, Bill Fenner, “UNIX network programming Volume -1 - The Sockets
Networking API”, 3rd edition.
2. W. Richard Stevens, “Advanced Programming in the Unix Environment”, Addison
Wesley.

Reference Books:
1. UNIX Internals – “A new Frontier”, PHI
Internal Assessment: Assessment consists of two tests out of which; one should be compulsory
class test (on minimum 2 Modules) and the other is either a class test or assignment on live
problems or course project.

Theory Examination:
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3
then part (b) will be from any module other than module 3)
4. Only Four question need to be solved.

Subject Code Subject Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSE1024 Operations
Research 04 -- -- 04 -- -- 04
Examination Scheme
Theory Examination
Term
Work Pract /
Oral Total Internal Assessment End
Sem
Exam Test 1 Test 2 Avg
20 20 20 80 -- -- 100

Objectives:
1. Formulate a real -world problem as a mathematical programming model.
2. Understand the mathematical tools that are needed to solve optimization problems.
3. Use mathematical software to solve the proposed models.

Outcomes: Learner will be able to…

Page 52

AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) 1. Understand t he theoretical workings of the simplex method, the relationship between a
linear program and its dual, including strong duality and complementary slackness.
2. Perform sensitivity analysis to determine the direction and magnitude of change of a
model‟s optima l solution as the data change.
3. Solve specialized linear programming problems like the transportation and assignment
problems, solve network models like the shortest path, minimum spanning tree, and
maximum flow problems.
4. Understand the applications of integer programming and a queuing model and compute
important performance measures .

Module Detailed Contents Hrs
01 Introduction to Operations Research : Introduction, , Structure of the
Mathematical Model, Limitations of Operations Research
Linear Programming : Introduction, Linear Programming Problem,
Requirements of LPP, Mathematical Formulation of LPP, Graphical
method, Simplex Method Penalty Cost Method or Big M -method, Two
Phase Method, Revised simplex method, Duality , Primal – Dual
construc tion, Symmetric and Asymmetric Dual, Weak Duality Theorem,
Complimentary Slackness Theorem, Main Duality Theorem, Dual Simplex
Method, Sensitivity Analysis
Transportation Problem : Formulation, solution, unbalanced
Transportation problem. Finding basic feasible solutions – Northwest
corner rule, least cost method and Vogel‟s approximation method.
Optimality test: the stepping stone method and MODI method.
Assignment Problem : Introdu ction, Mathematical Formulation of the
Problem, Hungarian Method Algorithm, Processing of n Jobs Through
Two Machines and m Machines, Graphical Method of Two Jobs m
Machines Problem Routing Problem, Travelling Salesman Problem
Integer Programming Problem : Introduction, Types of Integer 14

Page 53

AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) Programming Problems, Gomory‟s cutting plane Algorithm, Branch and
Bound Technique . Introduction to Decomposition algorithms.
02 Queuing models : queuing systems and structures, single server and multi -
server models, Poisson input, exponential service, constant rate service,
finite and infinite population 05
03 Simulation : Introduction, Methodology of Simulation, Basic Concepts,
Simulation Procedure, Application of Simulation Monte -Carlo
Method: Introduction, Monte -Carlo Simulation, Applications of
Simulation, Advantages of Simulation, Limitations of Simulation 05
04 Dynamic programming . Characteristics of dynamic programming.
Dynamic programming approach for Priority Management employment
smoothening, capital budgeting, Stage Coach/Shortest Path, cargo loading
and Reliability problems. 05
05 Game Theory . Competitive games, rectangular game, saddle point,
minimax (maximin) method of optimal strategies, value of the game.
Solution of games with saddle points, d ominance principle. Rectangular
games without saddle point – mixed strategy for 2 X 2 games.
05
06 Inventory Models : Classical EOQ Models, EOQ Model with Price
Breaks, EOQ with Shortage, Probabilistic EOQ Model, 05

Assessment :

Internal:
Assessment consists of two tests out of which; one should be compulsory class test and the other
is either a class test or assignment on live problems or course project.

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in
question papers of end semester examination. In question paper weightage of each module
will be proportional to number of respective lecture hours as mention in th e syllabus.

Page 54

AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) 1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3
then part (b) will be from any module other than module 3)
4. Only Four quest ion need to be solved.


REFERENCES:
1. Taha, H.A. "Operations Research - An Introduction", Prentice Hall, (7th Edition), 2002.
2. Ravindran, A, Phillips, D. T and Solberg, J. J. "Operations Research: Principles and
Practice", John Willey and Sons, 2nd Edition, 2009.
3. Hiller, F. S. and Liebermann, G. J. "Introduction to Operations Research", Tata McGraw
Hill, 2002.
4. Operations Research, S. D. Sharma, KedarNath Ram Nath -Meerut.
5. Operations Research, KantiSwarup, P. K. Gupta and Man Mohan, Sultan Chand & Sons.



Subj ect
Code Subject Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSL101 Lab-I:
Computational
Laboratory on
Core Courses -- -- -- --- 02 -- 01
Examination Scheme
Theory Examination
Term
Work Pract /
Oral Internal Assessment End
Sem
Exam Test 1 Test 2 Avg
--- --- --- --- 25 25

Module Detailed Content Lab
Session
Algorithm
and
Complexity  Implementation of algorithms which demonstrate greedy strategy,
dynamic programming, Flow network, parallel algorithm and string
matching (any two). 02

Page 55

AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) Networking
Design  Install tool CISCO Packet Tracer Student Edition (open -source).
Explore this tool and use it to design an Internetwork using switches,
routers and the concept of VLAN. Configure differ ent routing
protocols like RIP , OSPF , EIGRP etc . on the network you have
designed and observe the performance. Test your network using
“ping” and “show ip route”.
 Install mininet (open -source). Create virtual architecture for SDN
openvswitch(s), host(s), c ontrollers(s) and test various topologies
using basic commands like ping.
Optionally connect mininet openvswitch with external controllers
like open day light (open -source). 05
Advanced
Operating
System  The Advanced Operating System laboratory work should clarify the
basic concepts of Flexibility / Load Distribution (system scales
easily to accommodate increase in number of machines with
corresponding increase in performance), performance (running an
application should not be appreciably worse than running it on a
single CPU system), reliability (system should be available and
functional in presence of failures) and transparency (system should
provide a single system image).
 Every student should perform a t least two experiments from above
categories (i.e. Flexibility/Load Distribution, Fault
Tolerance/Reliability, Performance, Transparency and Mobile
Application) using C / C++ programming language. 05

End Semester Examination: Practical/Oral examination is to be conducted by pair of internal
and external examiners appointed by the University of Mumbai.


Subject
Code Subject Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSL102 Lab-II :Laboratory on
Elective Courses -- -- -- --- 02 -- 01
Examination Scheme
Theory Examination
Term
Work Pract /
Oral Internal Assessment End
Sem
Exam Test 1 Test 2 Avg
--- --- --- --- 25 25


Design and implementation of any case study/ applications based on Elective -I and
Elective -II using modern tools.

Page 56

AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering)
End Semester Examination: Practical/Oral examination is to be conducted by pair of internal
and external examiners appointed by the Universi ty of Mumbai.
















Subject
Code Subject Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSC2 01 High P erformance
Computing 04 -- -- 04 -- -- 04
Examination Scheme
Theory Examination
Term
Work Pract Oral Internal Assessment End
Sem
Exam Test 1 Test 2 Avg
20 20 20 80 -- -- --

Course Objectives:
1. To learn concepts of parallel processing as it pertains to high -performance computing.
2. To design, develop and analyze parallel programs on high performance computing
resources using parallel programming paradigms

Page 57

AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering)
Course Outcomes: Learner will be able to:
 Understand different parallel processing approaches and platforms involved in achieving
High Performance Computing.
 Understand design Issues and limitations in Parallel Computing.
 Learn to programming using message passing paradigm using open source APIs, design
algorithms suited for Multicore processor and GPU systems using OpenCL, OpenMP.
 Analyze and optimize performance paramet ers.
 Understand HPC enabled Advanced Technologies .

Sr.No Module Detailed Content Hours
1 Parallel
Processing
approaches
Introduction to Parallel Processing: Levels of
Parallelism (instruction, transaction, task, thread, memory,
and function), Models (SIMD, MIMD, SIMT, SPMD, Data
Flow Models, Demand -driven Computation etc.). Loosely
coupled and Tightly coupled
HPC Platforms: Message -passing interface (MPI),
Shared -memory thread -based OpenMP programs, hybrid
(MPI/OpenMP) programs, Grid Computing, Cloud
Computing , Multi -Core Processors, accelerators, GPGPUs 06
2 Design Issues
and limitations
in Parallel
Computing
Parallel Architecture, (Interconnection network, processor
Array, Multiprocessor) Designing Parallel algorithms
(Partitioning, Communication, Mapping, Matrix
input/output )
Issues: Synchronization, Scheduling, Job Allocation, Job
Partitioning, Dependency Analysis, Mapping Parallel
Algorithms onto Parallel Architectures
Limitations: Bandwidth Limitations, Latency Limitations,
Latency Hiding/Tolerating Techniques and their
limitations 10
3 Programming
using message
passing
paradigm

Principles, building blocks, MPI, Overlapping
communication and computation, collective
communication operations, Composite synchronization
constructs, OpenMP Threading Building blocks; An
Overview of Memory Allocators, Parallel programming
model, combining MPI and OpenMP, Shared memo ry
programing 10

Page 58

AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) 4 Parallel
Programming
using GPGPU An Overview of GPGPUs, An Overview of GPGPU
Programming, An Overview of GPGPU Memory
Hierarchy Features, Heterogeneous Computing using
OpenCL, An Overview of OpenCL API, Heterogeneous
Programming in Op enCL 12
5 Performance
Measures
Performance measures: Speedup, efficiency and
scalability.
Abstract performance metrics (work, critical paths),
Amdahl`s Law, Gustavson‟s law, weak vs. strong scaling,
performance bottlenecks, data races and determinism, data
race avoidance (immutability, futures, accumulators,
dataflow), deadlock avoidance, abstract vs. real
performance (granularity, scalability) 06
6 HPC enabled
Advanced
Technologies Nanotechnology and its impact on high performance
computing, Power awa re processing techniques in high
performance computing.
Case studies on high performance computing 04

Text Books:

1. AnanthGrama, Anshul Gupta, George Karypis, Vipin Kumar , “Introduction to Parallel
Computing”, Pearson Education, Second Edition, 2007.
2. Kai Hwang,Naresh Jotwani, “Advanced Computer Architecture: Parallelism, Scalability,
Programmability”, McGraw Hill,Second Edition, 2010.

3. Edward Kandrot and Jason Sanders, “CUDA by Example – An Introduction to General
Purpose GPU Programming”,Addison -Wesley P rofessional ©, 2010.
4. Benedict R Gaster, Lee Howes, David R KaeliPerhaad Mistry Dana Schaa,
“Heterogeneous Computing with OpenCL”, Elsevier, Second Edition, 2013.

Reference Books:

1. Georg Hager, Gerhard Wellein, “Introduction to High Performance Computing for
Scientists and Engineers", Chapman & Hall / CRC Computational Science series, 2011.
2. Michael J. Quinn, “Parallel Programming in C with MPI and OpenMP”, McGraw -Hill
International Editions, Computer Science Series, 2008.
3. Kai Hwang, Zhiwei Xu,“Scalable Par allel Computing: Technology, Architecture,
Programming”, McGraw Hill, 1998.

Page 59

AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) 4. Laurence T. Yang, MinyiGuo, “High - Performance Computing: Paradigm and
Infrastructure” Wiley, 2006.

List of Experiments to be included in Computational Lab II

Solve given problem s using OpenMP/MPI/OpenCL and compare their performance on CPU
and GPGPU.

1. Matrix -Matrix multiplication – simple/Cannon‟s/ DNS algorithm
2. Sorting – Bitonic/Shell sort/Quicksort/Bucket/ Radix
3. All-pairs shortest paths – Dijkstra‟s algorithm/Floyd‟s algorithm

Internal Assessment: Assessment consists of two tests out of which; one should be compulsory
class test (on minimum 02 Modules) and the other is either a class test or assignment on live
problems or course project.

Theory Examination:
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3
then part (b) will be from any module other than module 3)
4. Only Four question need to be solved.

In question paper weightage of each module will be proportional to number of respective
lecture hours as mention in the syllabus .


Subject
Code Subject Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSC2 02 Data Science 04 -- -- 04 -- -- 04
Examination Scheme
Theory Examination
Term
Work Pract Oral Internal Assessment End
Sem
Exam Test 1 Test 2 Avg
20 20 20 80 -- -- --

Course Objective s:
1. To understand the foundations of the Data Science process, methods and techniques
2. To represent and organise knowledge about large heterogeneous data collections

Page 60

AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) 3. To us e mathematical models and tools for large -scale data analysis and reasoning
4. To work and evaluate Data at Scale – Working with Big Data

Course Outcome: Learner will able
 Learn the fundamentals of data science to enable, reproduce and scalable data from a
variety of sources.
 Apply statistical methods, regression techniques, and machine learning algorithms to make
sense out of data sets both large and small.
 Design, implement, and evaluate the core algorithms underlying an end -to-end data
science workflow, analysis, and visualization of information derived from large datasets.
 Apply “best practice s" in data science with modern tools

Sr.
No. Module Detailed Content Hours
1 Introduction to
Data S cienc e Data science process: Defining goal, retrieving data,
preprocessing data, exploratory data analysis, model
building and data visualization, Ethical issues in data
science.
Probability: review of probability theory, normal
distribution,
Gaussian discriminant analysis: Linear discriminant
analysis (LDA), Logistic regression: Bayesian logistic
regression, 08
2 Predictive and
Descriptive
Models Descri ptive Modeling: Principal components analysis
(PCA), singular value decomposition (SVD), probabilistic
PCA, applying PCA to new data, PCA for data
interpretation. , EM algorithm for PCA, Independent
Component Analysis (ICA) , Maximum likelihood
estimation using EM .
Predictive Modeling: Predictive modeling process,
supervised and u nsupervised learning, parametric and n on-
parametric models, business intelligence, challenges in
using pr edictive analytics
Introduction to time series analysis and time series mining,
Introduction to spatio -temporal data, spatio -temporal
model, f ast dynamic time warping. 12
3 Evaluation and
Methodology of
Data Science Experimental setup s, training, tuning, test data, holdout
method, cross -validation, bootstrap method
Measuring performance of a model: Accuracy, ROC
curves, precision -recall curves, loss functions for
regression
Interpretation of results: Confidence interval for accuracy, 03

Page 61

AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) hypothesis tests for comparing models, algorithms.
4 Text Analytics
and
Recommendation
system (RS) Introducing text mining, text mining techniques,
Understanding Text Mining Process, Sentiment Analysis.
Introduction to RS, content based RS, collaborative RS,
hybrid RS. Issues and challenges RS, examples of real
word RS, e.g., Amazon, mobile RS, etc. 08
5 Data
Communication
and Information
Visualization Data Communication: cost Function, how to Minimize cost
function, coefficients of determination.
Information visualization: effective information
visualization, visual Encodings, perception of visual cues,
data sc ales, visualizing time series data, data journalism,
dashboards . 08
6 Scaling with Big
Data Introduction of big data, characteristics of big data, data in
the warehouse and data in Hadoop, Importance of Big data,
Big data Use cases: patterns for Big data deployment,
MapReduce and Hadoop Ecosystem architecture,
NoSQL,analyzing d ata with Pig and R .Sharding, indexing
large -scale data, sampling, data lea kage, data incest.
09


Reference Books:
1. Davy Cielen,Meysman,Mohamed Ali, “Introducing Data Science”, Dreamtech Press
2. Kevin P. Murphy, “Machine Learning a Probabilistic Perspective”, The MIT Press
3. Paul C. Zikopoulos, Chris Eaton, Dirk deRoos, Thomas Deutsch and George Lapis,
“Understanding Big Data: Analytics for Enterprise Class Hadoop and streaming Data”,
The McGraw Hill Companies, 2012
4. Dean Abbott, “Applied Predictive Analytics: Principles and Techniques for the
Professional Data Analyst”, Wiley, 2014
5. Noel Cressie, Christopher K. Wikle , “Statistics for Spatio -Temporal Data, Wiley
6. Seema Acharya and SubhashiniChellappan, “Big Data and Analytics”, Wiley
7. Rachel Schutt and Cathy O‟Neil, “Doing Data Science”, O‟Reilly Media
8. Joel Grus, Data Science from Scratch: First Principles with Python, O'Reilly Media
9. EMC Education Services,”Data Science and Big Data Analytics”,Wiley
10. DT Editorial Services, “Big Data Black Book”, Dreamtech Press

Page 62

AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering)
Internal Assessment: Assessment consists of two tests out of which; one should be
compulsory class test (on minimum 02 Modules) and the other is either a class test or
assignment on live problems or course project.

Theory Examination:
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from
module 3 then part (b) will be from any module other than module 3)
4. Only Four question need to be solved.

In question paper weightage of each module will be proportional to number of
respective lecture hours as mention in the syllabus .










Subject Code Subject Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSC203 Ethical Hacking
and Digital
Forensics 04 -- -- 04 -- -- 04
Examination Scheme
Theory Examination
Term
Work Pract Oral Internal Assessment End
Sem
Exam Test 1 Test 2 Avg
20 20 20 80 -- -- --

Page 63

AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) Course Objective s:
1. To understand underlying principles and many of the techniques associated with the
digital forensic practices.
2. To explore practical knowledge about ethical hacking Methodology.
3. To develop an excellent understanding of current cyber security issues and ways that
user, administrator and programmer errors can lead to exploitable in securiti es.
Course Outcome s: Learner will able to
 Understand the concept of ethical hacking and its associated applications in Informa tion
Communication Technology ( ICT) world .
 Acquire knowledge of various digital forensic tools and ethical hacking.
 Interpret se curity issues in ICT world, and apply digital forensic tools for security and
investigation s.
 Achieve adequate perspectives of digital forensic investigation in various app lications
/devices like W indows /Unix system, mobile, email etc.
 Generate legal evidences and supporting investigation reports.

Sr.
No. Module Detailed content Hours
1 Ethical
Hacking
Methodology Introduction, Steps of Ethical Hacking: Planning,
Reconnaissance, Scanning, Exploitation, post exploitation
and result reporting.
Ethical Hacking Tool: Metasploit 6Hrs
2 Introduction
to Digital
Forensics The Need for Digital Forensics, Types of Digital Forensics,
Introduction to Incident Response Methodology, Incident
handling steps, Ethics in Digital Forensics. 6 Hrs
3 Data
Collection Live Data Collection from Windows and Unix Systems,
Tools for Forensic Duplication, Collecting Network -based
Evidence, Evidence Handling - Chain of Custody.
Data Collection Forensic Tools : Forensics Toolkit / WinHex 14 Hrs
4 Data
Analysis Data Analysis, Investigating Windows, Unix Systems,
Analysing Network Traffic, Investigating Routers, Email
forensics
Data Analysis Tools : Nmap /Wireshark /Helix3pro 12 Hrs
5 Mobile
Device
Forensics Crime and mobile phones, evidences, forensic procedures,
files present in SIM cards, device data, external memory
dump, and evidences in memory card, operator‟s networks. 6 Hrs
6 Forensic
Investigation
Reporting Investigative Report Template, Layout of an Investigative
Report, Guidelines for Writing a Report 4 Hrs

Text Books:

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) 1. Kevin Mandia, Chris Prosise, “Incident Response and computer forensics”, Tata McGraw
Hill, 2006.
2. Patrick Engebretson, “The Basics of Hacking and Penetration Testing, Second Edition:
Ethical Hacking and Penetration Testing Made Easy“, 2nd Edition, Syngress.
3. Investigation Procedures and Response , EC-Council Press.

Reference Books:
1. Peter Stephenson, "Investigating Computer Crime: A Handbook for Corporate
Investigations", Sept 1999.
2. Debra Littlejohn Shinder and Ed Tittel, “Scene o f the Cybercrime: Computer Forensics
Handbook”, Syngress Publishing, Inc.
3. Eoghan Casey, "Handbook Computer Crime Investigation's Forensic Tools
andTechnology", Academic Press, 1st Edition, 2001
4. Nina Godbole, “ Information Systems Security” , Wiley India, New Delhi
5. William Stallings , “Cryptography and Network Security”, Pearson Publication

Internal Assessment: Assessment consists of two tests out of which; one should be compulsory
class test (on minimum 02 Modules) and the other is either a class test or assignment on live
problems or course project.

Theory Examination:
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3
then part (b) will be from any module other than module 3)
4. Only Four question need to be solved.

In question paper weightage of each module will be proportional to number of respective
lecture hours as mention in the syllabus .
Subject Code Subject Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSE2031 Data Storage
and Retrieval 04 -- -- 04 -- -- 04
Examination Scheme
Theory Examination
Term
Work Pract Oral Internal Assessment End
Sem
Exam Test 1 Test 2 Avg
20 20 20 80 -- -- --

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering)
Course Objective s:
1. Understand need of storage network with its architecture, features, components, topology,
benefits and limitations.
2. Study the impact of downtime in terms of losses and business continuity.
3. Understand the basic terminologies and components in information retrieval systems.
4. Compare and contrast Information Retrieval models.

Course Outcome s: Learner will able to…
 Evaluate storage architecture, ISS, SAN, NAS and IP SAN.
 Design the storage infrastructure for business continuity.
 Implement and evaluate various Information Retrieval Models .

Sr.
No. Module s Detailed content Hours
1 Introduction to
Data Storage Need for storage network, Evolution of storage technology
and architecture, Key Challenges in managing information,
Information lifecycle, Disk drive performance, Fundamental
laws governing disk performance. 04
2 Storage System
Environment
Basic Software for Storage Networking:
Software for SANs, Shared access data managers,
Volumes(RAID): Resilience, performance and flexibility,
File systems and application performance.
Intelligent Storage S ystem :Storage Virtualization: Form of
Virtualization, storage virtualization configurations and
challenges, Types of storage v irtualization.
Content -Addressed Storage: Architecture, Object storage and
Retrieval in CAS. 08
3 Storage
Networking
Technologies Storage Area Networks: Fibre Channel , Components of SAN,
FC Connectivity, Fibre Channel Ports, Fibre Channel
Architecture, Zoning, Fibre Channel Login Types, FC
Topologies .
Network -Attached Storage: General -Purpose Servers vs. NAS
Devices, Benefits of NAS, NAS File I/O, Components of
NAS, NAS Implementations, NAS File -Sharing Protocols,
NAS I/O Operations, Factors Affecting NAS Performance and
Availability . IP SAN: iSCSI, FCIP . 12

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) 4 Business
Continuity and
Enterprise
backup Introduction to Business Continuity:
Information availability, BC planning lifecycle, Failure
Analysis, Business impact analysis.
Enterprise backup software for SAN:
Backup management, Enterprise data protection, Backup
architecture, Backup policies, Minimizing impact of backup,
Lan-free and serverless backup. 06
5 Information
Retrieval Introduction to Information Retrieval(IR), Objectives and
Components of IR system, Taxonomy of IR models,
Information Retrieval process, Documents and Query forms 06
6 Retrieval
Models Query structure, The matching process, Text analysis 10

Text Books :
1. G. Somasundaram, Alok Shrivastava, “Information Storage and Management”, EMC
Education services”, Wiley Publication , Edition 2009
2. Richard Barker, Paul Massiglia, “Storage Area Network Essentials: A Complete Guide to
Understanding and Implementing SANs”, Wiley India
3. Robert R. Korfhage, “Information Storage and Retrieval”, Wiley Publication

Reference Books:
1. Ulf Troppens,Wolfgang Muller -Friedt,Rainer Wolafka, “Storage Networks Explained ”
Wiley Publication
2. Spalding, Robert. Storage Networks: The Complete Reference . Tata McGraw -Hill
Education, 2003
3. Manning, Christopher D., Prabhakar Raghavan, and Hinrich Schütze. Introduction to
information retrieval . Vol. 1, no. 1. Cambridge: Cambridge university press, 2008.

Internal Assessment: Assessment consists of two tests out of which; one should be
compulsory class test (on minimum 02 Modules) and the other is either a class test or
assignment on live problems or course project.

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering)
Theory Examination:
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from
module 3 then part (b) will be from any module other than module 3)
4. Only Four question need to be solved.

In question paper weightage of each module will be proportional to number of
respective lecture hours as mention in the syllabus .













Subject Code Subject
Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSE203 2 Internet of
Things 04 -- -- 04 -- -- 04
Examination Scheme
Theory Examination
Term
Work Pract Oral Internal Assessment End
Sem
Exam Test 1 Test 2 Avg
20 20 20 80 -- -- --

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering)
Course Objectives:
5. Provide an overview of concepts, main trends and challenges of Internet of Things.
6. Develop the ability to use Internet of Things related software and hardware
technologies.
7. Provide the knowledge of data management business processes and analytics of IoT.
8. Develop skills to relate the IoT technologies for practical IoT applications such as smart
objects.
Course Outcomes: Learner will able to -
 Explain and interpret the Internet of Things concepts and challenges.
 Experiment with the software and hardware IoT Technologies.
 Understand data management and business processes and analytics of IoT
 Design and develop small IoT applications to create smart objects
Sr. No. Module Detailed Content Hours
1 Introduction to
Internet of
Things IoT Paradigm, IoT Architecture – State of the Art, IoT
Protocols, IoT Communication Models, IoT in Global
Context, Cloud Computing, Big Data Analytics, Concepts
of Web of Things, Concept of Cloud of Things with
emphasis on Mobile Cloud Computing, Smart Obj ects. 8
2 Open – Source
Prototyping
Platforms for
IoT Basic Arduino Programming Extended Arduino Libraries,
Arduino – Based Internet Communication, Raspberry PI,
Sensors and Interfacing. 8
3 IoT Technology RFID + NFC, Wireless Networks + WSN, RTLS + GPS,
Agents + Multi – Agent Systems, Composition Models
for the Web of Things and resources on the Web,
Discovery, Search, IoT Mashups and Others. 8
4 Wireless Sensor
Networks History and Context, The Node, Connecting Nodes,
Networking Nodes, Secured Communication for IoT. 4
5 Data
Management,
Business
Process and
Analytics Data Management, Business Process in IoT, IoT
Analytics, Creative Thinking Techniques, Modification,
Combination Scenarios, Decentralized and Interoperable
Approaches, Object – Information Distribution
Architecture, Object Naming Service (ONS), Service
Oriented Architecture, Network of Information, Etc. 12
6 Application and Concrete Applications and Use – Cases of Web Enabled 8

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) Use Cases Things: Energy Management and Smart Homes, Ambient
Assisted Living, Intelligent Transport, Etc. M2M,
Industrial IoT Applications.

Text Books:
3. The Internet of Things (MIT Press) by Samuel Greengard.
4. The Internet of Things (Connecting objects to the web) by Hakima Chaouchi , Wiley .
5. Internet of Things ( A Hands -on-Approach) by Arshdeep Bhaga and Vijay Madisetti.

Reference Books:
3. The Internet of Things Key applications and Protocols, 2nd Edition, (Wiley Publication)
by Olivier Hersent, David Boswarthick and Omar Elloumi.
4. IoT –From Research and I nnovation to Market development, River Publication by Ovidiu
Vermesan and Peter Friess.
5. Building Internet of Things with Arduino by Charalampos Doukas.

Internal Assessment: Assessment consists of two tests out of which; one should be compulsory
class tes t (on minimum 02 Modules) and the other is either a class test or assignment on live
problems or course project.

Theory Examination:
5. Question paper will comprise of total six question
6. All question carry equal marks
7. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3
then part (b) will be from any module other than module 3)
8. Only Four question need to be solved.

In question paper weightage of each module will be proportional to number of respective
lecture hours as men tion in the syllabus.

Subject Code Subject
Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSE203 3 Advance d
Soft
Computing 04 -- -- 04 -- -- 04
Examination Scheme
Theory Examination
Term
Work Pract Oral Internal Assessment End
Sem
Exam Test 1 Test 2 Avg
20 20 20 80 -- -- --

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) .
Course Objectives:
1. To familiarize various soft computing techniques.
2. To relate various soft computing techniques in practical scenario.
3. To understand hybrid approach for application development.

Course Outcomes: At the end of the course, the learner will be able to-
 To demonstrate various soft computing techniques.
 To apply and analyze different soft computing techniques for solving practical
applications.
 To design an intelligent system for social and technical problems.

Pre-requisite: Basic mathematics, soft computing, Computational intelligence

Sr.
No. Module Detailed content Hours
1 Introduction Differentiate Hard and Soft Computing, Soft
Computing Constituents, Neuro Fuzzy and Soft
Computing Characteristics 2
2 Fuzzy Logic &
Rough Set Theory Fuzzy Relations and Fuzzy Rules, Generalized
Modens Ponens, Defuzzification and its Types
Fuzzy Inference Systems, Design of Fuzzy
Controller, Introd uction to Rough Sets 12
3 Supervised Network Error Back Propagation Training Algorithm, Radial
Basis Function 10
4 Unsupervised Network Kohenon Self Organizing Maps, Basic Learning
Vector Quantization, Basic Adaptive Resonance
Theory 12
5 Hybrid Systems and
Introduction to Deep
Learning Fuzzy -Neural Systems, Neuro -Genetic Systems
Fuzzy -Genetic Systems,
Deep Learning : Definition & background, historical
context of deep learning, Three classes of deep
learning network. 8
6 Applications and Case
Study Automobile Fuel Efficiency using ANFIS
Color Receipe prediction using CANFIS
4

Page 71

AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) Text Books
1. J.S.R.Jang "Neuro -Fuzzy and Soft Computing" PHI 2003.
2. S. Rajasekaran and G.A. Vijaylakshmi Pai.. Neural Networks
Fuzzy Logic, and Genetic Algorithms, Prentice Hall of India.
3. Satish Kumar "Neural Networks A Classroom Approach" Tata McGrawHill.
4. S.N.Sivanandam, S.N.Deepa "Principles of Soft Computing" Second Edition, Wiley
Publication.
5. Samir Roy, Udit Chakraborty "Introduction to Soft Computing" Pearson Education India.
6. Jacek.M.Zurada "Introduction to Artificial Neural Sytems" Jaico Publishing House.
7. Timothy J.Ross "Fuzzy Logic With Engineering Applications" Wiley.

Reference Books :

1. Fakhreddine O. Karry, Clarence De Silva," Soft Computing and Intelligent systems
Design Theory, Tools and Applications" Pearson 2009.
2. Li Deng and Dong Yu , „ Deep Learning Methods and Applications‟.

Internal Assessment: Assessment consists of two tests out of which; one should be compulsory
class test (on minimum 02 Modules) and the other is either a class test or assignment on live
problems or course project.

Theory Examination:
9. Question paper will comprise of total six question
10. All question carry equal marks
11. Questions will be mixed in nature (for exa mple supposed Q.2 has part (a) from module 3
then part (b) will be from any module other than module 3)
12. Only Four question need to be solved.

In question paper weightage of each module will be proportional to number of respective
lecture hours as mentio n in the syllabus .

Subject Code Subject
Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSE203 4 Semantic
Web &
Social
Network
Analysis 04 -- -- 04 -- -- 04
Examination Scheme
Theory Examination
Term
Work Pract Oral Internal Assessment End
Sem
Exam Test 1 Test 2 Avg
20 20 20 80 -- -- --

Page 72

AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) Semantic Web provide a graph model (RDF), a query language ( SPARQL) and schema
definition frameworks(RDFS and OWL) to represent and exchange knowledge online. These
technologies provide a whole new way of capturing social networks in much richer structures.
Social network Analysis(SNA) tries to understand and exploit the key features of social networks
in order to manage their life cycle and pr edict their evolution. Objective of the course is to
understand how to facilitate and enhance the analysis of online social networks, exploiting the
power of semantic web technologies.
Course Objectives (CEO):

1. To understand the basics of Semantic Web Te chnologies
2. To Learn knowledge representation for Semantic Web
3. To understand the importance of Social Network Analysis
4. To understand and use semantic web technologies for social network analysis

Course Outcomes: At the end of the course, the students will be able to :
 Understand the Semantic Web and Social Networks
 Understand Electronic sources for network analysis and different ontology languages.
 Model and aggregate social network data.
 Design and Analyze social network using semantic web technologies.

Pre-requisites: Web Technologies; Data Structures, Databases, Logic -First order logic,
knowledge representation, Data Mining ,Distributed Systems.

Sr. No. Module Detailed Contents Hours
1 Introduction Semantic
Web and Social
Networks:
. The Semantic Web - Limitations of the current Web, The
semantic Web Technologies ,A Layered Approach , The
emergence of the social web. Social Network Analysis - What
is network analysis, Development of Social Network
Analysis, Key concepts and measures in network anal ysis 04
2 Semantics and
Knowledge
Representation on the
Semantic Web
Electronic sources for network analysis - Electronic
discussion networks, Blogs and online communities
Structured Web Documents -XML, Describing web
Resources -RDF, RDFSchema, Querying Knowledge
Representation on the Semantic Web -SPARQL 10
3 Modeling and
aggregating social
network data:
Ontologies and their role in the Semantic Web, Ontology
languages for the Semantic Web -RDFS, OWL . State -of-the-
art in network data representation, Ontology Engineering,
Semantic Web Knowledge Management Architecture
,Ontological representation of social individuals, Ontological
representation of social relationships, Aggregating and
reasoning with soci al network data.
10
4 Developing social -
semantic applications:

Building Semantic Web applications with social network
features, Flink: the social networks of the Semantic Web
community, open academia: distributed, semantic -based
publication management 08

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) 5 Extracting and Mining
Communities in social
network and social
network analysis -
Extracting evolution of Web Community from series of web
archive – Detecting communities in social networks -
Definition of community – Evaluating communities –
methods for community detection and mining –
Semantic based social network analysis.
08
6 Applications of
community mining
algorithms ,
Visualization - Applications of community mining algorithms -Influence and
Homophily, Recommendation, Behavior Analytics,
Visualization - Graph theory – Centrality – Clustering - Node
Edge Diagrams –Matrix Representation –,Benefits of
semantic social networks for communities 08


Text Books:

1. Grigoris Antoniou and Frank van Harmelen “Semantic Web Primer”second edition
2. Peter Mika, “Social Networks and the Semantic Web”, First Edition, Springer 2007.
3. Reza Zafarani,Mohammad Ali Abbasi,Huan Liu “Social Media Mining:
Introduction”,Cambridge University press.

Reference Books:

1. Guandong Xu ,Yanchun Zhang and Lin Li, “Web Mining an d Social Networking
Techniques and applications”, First Edition Springer, 2011.
2. Dion Goh and Schubert Foo, “Social information Retrieval Systems: Emerging
Technologies and Applications for Searching the Web Effectively”, IGI Global
Snippet, 2008.
3. Max Chev alier, Christine Julien and Chantal Soulé -Dupuy, “Collaborative and Social
Retrieval and Access: Techniques for Improved user Modelling”,IGI Global Snippet,
2009.
4. John G. Breslin, Alexander Passant and Stefan Decker, “The Social Semantic Web”,
Springer, 2 009.
5. Charu C. Aggarwal, “Social Network Data Analytics”, Springer; 2011.
6. Borko Furht, “Handbook of Social Network Technologies and Applications”, 1st
Edition, Springer, 2010.
7. Toby Segaran,colin Evans and Jamie Taylor “Programming Semantic Web”,
O‟Reilly .
8. Berners Lee, Godel and Turing “Thinking on the Web “,Wiley inter science, 2008.
9. Vladimir Geroimenko, Chaomei Chen “Visualizing the Semantic Web”, Springer
2006.

Page 74

AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) Internal Assessment: Assessment consists of two tests out of which; one should be compulsory
class test (on minimum 02 Modules) and the other is either a class test or assignment on live
problems or course project.

Theory Examination:
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3
then part (b) will be from any module other than module 3)
4. Only Four question need to be solved.

In question paper weightage of each module will be proportional to number of respective
lecture hours as mention in the syllabus .




















Subject Code Subject Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSE204 1 Information
and
Communicatio
n Technologies
(ICT) for
Social Cause 04 -- -- 04 -- -- 04
Examination Scheme
Theory Examination
Term
Work Pract Oral Internal Assessment End
Sem
Exam Test 1 Test 2 Avg
20 20 20 80 -- -- --

Page 75

AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering)
Course Objective s:
1. To understand use of ICT techniques in various applications.
2. To Recognize, Represent and Design the ICT systems for social cause.

Outcome: Learner will able
 To understand technologies used in ICT.
 To design and implement ICT application for societal benefits
 To demonstrate use of emerging technology for social applications .

Sr. No. Module Detailed content Hours
1 Basics of ICT  Introduction to ICT
 Challenges and opportunities in using technology for a
social cause.
 Understand ing the social and cultural influences that
affect users.
 Creating an ICT – handling text, data and media 4

2 Communicatio
n Techniques
in ICT  Mobile Techniques – CDMA, Mobile wireless
WiMAX, Advanced wireless technologies, Bluetooth
 Satellite Techniques – architecture AND working
principles GPS/GPRS
 Cloud computing – Introduction, cloud services, Cloud
service providers,
 GIS– Working principle and architecture for ICT 12
3 Data
acquisition in
ICT  Recognition systems RFID,OMR
 Data acquisition process for MEMS devices
 Sensors – Programming, communication with cloud.
 Formation of social groups and interaction analysis
Facebook, Twitter, Blogs, Forums, mailing lists etc 8
4 Data
Management
in ICT  Data management
 Data storage structures 8
5 knowledge
management in
ICT  Knowledge elicitation
 Knowledge Engineering Methodology
 Knowledge representation and visualization
techniquesAutomatic discovery programs
 Data visualization
 Auditing knowledge management
 Linking knowledge management to business
performance 8

Page 76

AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) 6 ICT
applications
and Social
Audit  Study of ICT applications in various domains such as
Agriculture, Healthcare, Education, SCM, Finance,
Law.
 Social Audit: The Social Audit Tool (SAT), Social
Auditing, Characteristics of the SAT, Uses of the SAT
, Benefits of the SAT, The SAT Methodology ,
Purposes, Method, and Approach of the SAT,
Implementing the SAT, The Social Auditor
10

References Books:
1. ICT Futures :Delivering Pervasive Realtime And Secure Servi ces Edited By Paul
Warren, Jhon Davies, David Brown , Wiley Publication
2. Jochen Schiller, "Mobile communications", Addison wisely, Pearson Education.
3. GIS Fundamentals, Applications and Implementation, Dr.K.Elangovan, New India
Publications.
4. Cloud Computing : A practical Approach: By Anthony T. Velte : Tata McGraw -Hill
5. An Introduction to Microelectromechanical systems Engineering, NadimMaluf , Artech
House.
6. Knowledge management business intelligence , and content management : The IT
practitioner‟s Guide by Jessica Keyes
7. ICTs for transfer of technology tools and techniques , S.R. Verma , New India
8. USAID, Social Audit Tool Handbook, Using the Social Audit to Assess the Social
Performance of Microfinance Institutions,2008.

Internal Assessment: Assessment consists of two tests out of which; one should be
compulsory class test (on minimum 02 Modules) and the other is either a class test or
assignment on live problems or course project.

Theory Examination:
1. Question paper will comprise of total six question
2. All question carry equal marks

Page 77

AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) 3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from
module 3 then part (b) will be from any module other than module 3)
4. Only Four question need to be solved.

In question paper weightage of each module will be proportional to number of
respective lecture hours as mention in the syllabus .


























Subject Code Subject
Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSE2042 Internet
Routing
Design 04 -- -- 04 -- -- 04
Examination Scheme
Theory Examination
Term
Work Pract Oral Internal Assessment End
Sem
Exam Test 1 Test 2 Avg

Page 78

AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) 20 20 20 80 -- -- --
Course Objectives:
1. To understand in depth Routing protocols used on Internet
2. To know about routing related issues on Internet
3. To develop the thinking about how to analyze Network Algorithms
4. To become familiar with the concepts of Traffic Engineering

Course Outcomes: Learner will able to –
 gain knowledge about various Routing protocols used on Internet.
 design Routing protocol for Internet.
 demonstrate the technical competence necessary for solving problems in Routing on
Internet.
Sr.
No. Module Detailed content Hours
1 Networking and
Network
Routing: An
Introduction
Addressing and Internet Service: An Overview, Network Routing, IP
Addressing, Service Architecture, Protocol Stack Architecture, Router
Architecture, Network Topology, Architecture, Network Management
Architecture, Public Switched Telephone.

8
2 Routing
Algorithms OSPF and Integrated IS -IS: OSPF: Protocol Features, OSPF Packet
Format, Integrated IS -IS, Key Features, comparison BGP: Features,
Operations, Configuration Initialization, phases, Message Format. IP
Routing and Distance Vector Protocol Family: RIPv1 and RI Pv2.
8
3 Routing
Protocols
:Framework and
Principles
Routing Protocol, Routing Algorithm, and Routing Table, Routing
Information Representation and Protocol Messages.
Internet Routing and Router Architectures:
Architectural View of the Internet, Allocation of IP Prefixes and AS
Number, Policy -Based Routing, Point of Presence, Router
Architectures: Functions, Types, Elements of a Router, Packet Flow,
and Packet Processing: Fast Path versus Slow Path, Router
Archi tectures.
8
4 Analysis of
Network
Algorithms
Network Bottleneck, Network Algorithmic, Thinking Algorithmically,
Refining the Algorithm, Cleaning up, Characteristics of Network
Algorithms. IP Address Lookup Algorithms : Impact, Address
Aggregation, Longest Prefix Matching, Naïve Algorithms, Binary,
Multi-bit and Compressing Multi -bit Tries, Search by Length
Algorithms, Search by Value Approaches, Hardware Algorithms,
Comparing Different Approaches.
IP Packet Filtering and Classification: Classification, Classification
Algorithms, Naïve Solutions, Two -Dimensional Solutions,
Approaches for d Dimensions.
10

Page 79

AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering)
Text Books:
1. Network Routing: Algorithms, Protocols, and Architectures Deepankar Medhi and Karthikeyan
Ramasamy (Morgan Kaufmann Series in Networking)
2. Network Algorithmics: An Interdisciplinary Approach to Designing Fast Networked Devices George
Varghese (M organ Kaufmann Series in Networking)
Reference Books:
1. Sam Halabi and Danny McPherson, Internet Routing Architecture, Second Edition, Cisco Press

Internal Assessment: Assessment consists of two tests out of which; one should be compulsory class test
(on minimum 02 Modules) and the other is either a class test or assignment on live problems or course
project.

Theory Examination:
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3 then
part (b) will be from any module other than module 3)
4. Only Four question need to be solved.

In question paper weightage of each module will be proportional to number of respective lecture
hours as mention in the syllabus.




Subject Code Subject Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSE2043 Grid and Cloud 04 -- -- 04 -- -- 04
Examination Scheme 5 Quality of
Service Routing
QoS Attributes, Adapting Routing: A Basic Framework. Update
Frequency, Information Inaccuracy, and Impact on Routing, Dynamic
Call Routing in the PSTN, Heterogeneous Service, Single -Link Case,
A General Framework for Source -Based QoS Routing with Path
Cach ing
8
6 Routing and
Traffic
Engineering
Traffic Engineering of IP/MPLS Networks, VPN Traffic Engineering,
Problem Illustration: Layer 3 VPN, LSP Path Determination:
Constrained Shortest Path Approach, LSP Path Determination:
Network Flow Modeling Approach, Layer 2 VPN Traffic Engineering, 6

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) Computing Theory Examination
Term
Work Pract /
Oral Total Internal Assessment End
Sem
Exam Test 1 Test 2 Avg
20 20 20 100 -- -- 100
Course Objectives:
1. Classify and describe the architecture and taxonomy of parallel and distributed
computing,
2. Get familiarized with the role of Cloud computing.
3. Make the students understand basic knowledge of grid computing
4. Familiarized with virtualization concepts and Service Oriented A rchitectures (SOA).

Course Outcomes: Learner will able to -
 Understand the benefits of Cloud Computing
 Learn how to provide Flexible and scalable infrastructures
 Simulate characterize the distinctions between Infrastructure, Platform and Software as a
Service (IaaS, PaaS, SaaS)
 Identify the concept of Public and Private Clouds, and analyze their advantages and
disadva ntages.

Sr. No. Module Detailed Content Hours


1 System models
for Distributed
and Cloud
Computing
Clusters of cooperative computers, Grid computing and
cloud computing; software environment for advanced
computing, Service oriented Architecture (SOA), Parallel
and distributed programming models, Features of grid and
cloud platform.

6

2 Cloud
Computing
services models
and features
SaaS, PaaS and IaaS, Service oriented architecture and
web services; Features of cloud computing architectures
and simple case studies.
10


3 Virtualization Characteristic features, Taxonomy Hypervisor,
Virtualization and Cloud Computing, Pros and Cons of
Cloud Computing, Technology Examples/Case Studies.
8

4 Cloud
programming
Environmental
Map Reduce Hadoop Library from Apache, Open Source
Cloud Software Systems –Eucalyptus.
8

5 Grid Computing
Grid Architecture and Service modeling, Grid resource
management, software and Middleware for grid
computing, Grid Application trends.
8

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) 6 Ubiquitous
clouds and the
Internet of
Things Cloud Trends in supporting Ubiquitous Computing,
Enabling Technology for the Internet of Things,
Innovative Applications of the Internet of Things. 8

Text Books:
1. Distributed and Cloud Computing, Kaittwang Geof frey C.Fox and Jack J Dongrra,
Elsevier India 2012.
2. Mastering Cloud Computing - Raj Kumar Buyya, Christian Vecchiola and S.Tanurai
Selvi, TMH, 2012.
Reference Books:
1. Cloud Computing, John W. Ritting House and James F Ramsome, CRC Press, 2012.
2. Enterprise Cloud Computing, Gautam Shroff, Cambridge University Press, 2012.


Internal Assessment:
Assessment consists of two tests out of which; one should be compulsory class test (on minimum
02 `Modules) and the other is either a class test or assign ment on live problems or course project.


Theory Examination:
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 has part (a) from module 3
then part (b) will be from any module other than module 3)
4. Only Four question need to be solved.




In question paper weightage of each module will be proportional to number of respective
lecture hours as mention in the syllabus.

Subject Code Subject Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSE2044 Project
Management 04 -- -- 04 -- -- 04
Examination Scheme
Theory Examination Term Pract / Total

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) Internal Assessment End
Sem
Exam Work Oral
Test 1 Test 2 Avg
20 20 20 100 -- -- 100

Objectives :
1. To familiarize the students with the use of a structured methodology/approach for each and every
unique project undertaken, including utilizing project management concepts, tools and
techniques.
2. To appraise the students with the project management life cycle and make them knowledgeable
about the various phases from project initiation through closure.

Outcomes: Learner will be able to…
1. Apply selection criteria and select an appropriate project from different opti ons.
2. Write work break down structure for a project and develop a schedule based on it.
3. Identify opportunities and threats to the project and decide an approach to deal with them
strategically.
4. Use Earned value technique and determine & predict status of the project.
5. Capture lessons learned during project phases and document them for future reference

Module Detailed Contents Hrs
01 Project Management Foundation:
Definition of a project, Project Vs Operations, Necessity of project management, Triple
constraints, Project life cycles (typical & atypical) Project phases and stage gate process. Role
of project manager. Negotiations and resolving conflicts. Project management in various
organization structures. PM knowledge areas as per Project Management Institute (PMI). 5
02 Initiating Projects:
How to get a project started, Selecting project strategically, Project selection models (Numeric
/Scoring Models and Non -numeric models), Project portfolio process, Project sponsor and
creating charter; Project p roposal. Effective project team, Stages of team development &
growth (forming, storming, norming & performing), team dynamics. 6
03 Project Planning and Scheduling:
Work Breakdown structure (WBS) and linear responsibility chart, Interface
Co-ordination and concurrent engineering, Project cost estimation and budgeting, Top down
and bottoms up budgeting, Networking and Scheduling techniques. PERT, CPM, GANTT
chart. Introduction to Project Management Information System (PMIS). 8
04 Planning Projects:
Crashing project time, Resource loading and leveling, Goldratt's critical chain, Project
Stakeholders and Communication plan.
Risk Management in projects: Risk management planning, Risk identification and risk register.
Qualitative and quantitati ve risk assessment, Probability and impact matrix. Risk response
strategies for positive and negative risks 6
05 5.1 Executing Projects:
Planning monitoring and controlling cycle. Information needs and reporting, engaging with all 8

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) stakeholders of the projects.
Team management, communication and project meetings.
5.2 Monitoring and Controlling Projects:
Earned Value Management techniques for measuring value of work completed; Using
milestones for measurement; change requests and scope creep. Project audit.
5.3 Project Contracting
Project procurement management, contracting and outsourcing,
06 6.1 Project Leadership and Ethics:
Introduction to project leadership, ethics in projects.
Multicultural and virtual projects.
6.2 Closing the Project:
Customer acceptance; Reasons of project termination, Various types of project terminations
(Extinction, Addition, Integration, Starvation), Process of project termination, completing a
final report; doing a lessons learned analysis; acknowledging succes ses and failures; Project
management templates and other resources; Managing without authority; Areas of further
study. 6
Assessment :

Internal:
Assessment consists of two tests out of which; one should be compulsory class test and the other is either
a class test or assignment on live problems or course project.

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syllabus should be covered in question
papers of end semester examination. In question paper weightage of each module will be proportional
to number of respective lecture hours as mention in the syllabus.
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questions will be mixed in nature (for example supposed Q.2 ha s part (a) from module 3 then
part (b) will be from any module other than module 3)
4. Only Four question need to be solved.

REFERENCES:
1. Jack Meredith & Samuel Mantel, Project Management: A managerial approach, Wiley India,
7thEd.
2. A Guide to the Project Man agement Body of Knowledge (PMBOK ® Guide), 5th Ed, Project
Management Institute PA, USA
3. Gido Clements, Project Management, Cengage Learning.
4. Gopalan, Project Management, , Wiley India
5. Dennis Lock, Project Management, Gower Publishing England, 9 th Ed.

Subj ect
Code Subject Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) CSL201 Lab-III:
Computational
Laboratory on Core
Courses -- -- -- --- 02 -- 01
Examination Scheme
Theory Examination
Term
Work Pract /
Oral Internal Assessment End
Sem
Exam Test 1 Test 2 Avg
--- --- --- --- 25 25

Module Detailed Content Lab
Session

High Performance
Computing

Implement any two parallel algorithms(e.g. sorting, matrix - matrix
multiplication ) using OpenMP/MPI/OpenCL and compare their
performance on CPU and GPGPU. 04


Data Science


Exploratory data analysis using Map Reduce , NoSQL, R,
python and Hadoop Ecosystem

Predictive data Analytics using open source tools like
Rstudio, RWeka, RHadoop
04

Ethical Hacking and
Digital Forensics
Operating System Forensics, Email Forensics and Mobile
Forensics using open source forensics tools (e.g., Helix3pro ,
WinHex ) 04


Assessment:
Laboratory Project: Weightage for Laboratory Project should be 40% in Final Assessment of
Laboratory Work .

End Semester Examination: Practical/Oral examination is to be conducted by pair of internal
and external examiners appointed by the University of Mumbai.

Subject
Code Subject Name Teaching Scheme
(Contact Ho urs) Credits Assigned

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) Theory Pract Tut Theory Pract Tut Total
CSL202 Lab-IV: Laboratory on
Elective Courses -- -- -- --- 02 -- 01
Examination Scheme
Theory Examination
Term
Work Pract /
Oral Internal Assessment End
Sem
Exam Test 1 Test 2 Avg
--- --- --- --- 25 25


Design and implementation of any case study/ ap plications based on Elective -III and
Elective -IV using modern tools.



End Semester Examination: Practical/Oral examination is to be conducted by pair of internal
and external examiners appointed by the University of Mumbai.















Course
Code
Course Name Teaching Scheme (Contact
Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) ME-CS301 Special Topic Seminar ---- 06 -- --- 03 -- 03
ME-CS302 Dissertation -I --- 24 -- --- 12 -- 12
Total
---- 30 -- --- 15 -- 15
Course
Code Course
Name Examination Scheme
Theory
TW Oral/
Pract Total Internal Assessment End
Sem.
Exam Exam
Duration
( in Hrs) Test 1 Test 2 Avg.
ME-CS30 1 Special Topic Seminar --- --- --- --- --- 50 50 100
ME-CS302 Dissertation -I --- --- --- ---- --- 100 --- 100
Total --- --- --- ---- --- 150 50 200

Guidelines Special Topic Seminar:

 Seminar should be based on thrust areas in Computer Engineering / Information
Technology.
 Students should do literature survey, identify the topic of seminar and finalize it with
consultation of Guide/Supervisor.
 Students should use multiple literatures (at least 10 papers from Refereed
Journals /conferences ) and understand the topic and research gap.
 Implementation of one paper from refereed journal as a case study.
 Compile the report in standard format and present infront of Panel of Examiners.
(Pair of Internal and External examiners appointed by the University of Mumbai) .
 It is advisable to s tudents should publish at least one paper based on the work in
reputed International / National Conference .

Note: At least 4 -5 hours of course on Research Methodology should be conducted which
includes literature survey, identification of problems, analysis and interpretation of results
and technical paper writing in the beginning of 3rd semester.

Guidelines for Dissertation -I

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) Students should do literature survey and identify the problem for Dissertation and finalize
in consultation with Guide/Supervisor. Students should use multiple literatures and
understand the problem. Students should attempt solution to the problem by
analytical/simulation/experimental methods. The solution to be validated with proper
justification a nd compile the report in standard format.

Guidelines for Assessment of Dissertation -I
Dissertation -I should be assessed based on following points
 Quality of Literature survey and Novelty in the problem
 Clarity of Problem definition and Feasibility of problem solution
 Relevance to the specialization
 Clarity of objective and scope

Dissertation -I should be assessed through a presentation by a panel of Internal examiners
and external examiner appointed by the Head of the Department/Institute of respective
Programme.














Course
Course Name Teaching Scheme (Contact
Hours) Credits Assigned

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AC- 30/07/2017
Item No. – 4.10
University of Mumbai, M. Tech. (Computer Engineering) Code Theory Pract Tut Theory Pract Tut Total
ME-CS401 Dissertation -II -- 30 -- --- 15 -- 15
Total -- 30 -- --- 15 -- 13
Course
Code Course Name Examination Scheme
Theory
TW Oral/
Pract Total Internal Assessment End
Sem.
Exam Exam
Duratio
n ( in
Hrs) Test 1 Test 2 Avg.
ME-CS401 Dissertation -II -- --- --- --- --- 100 100 200
Total -- --- --- --- --- 100 100 200


Guidelines for Assessment of Dissertation II

Dissertation II should be assessed based on following points :
 Quality of Literature survey and Novelty in the problem
 Clarity of Problem definition and Feasibility of problem solution
 Relevance to the specialization or current Research / Industrial trends
 Clarity of objective and scope
 Quality of work attempted or learner contribution
 Validation of results
 Quality of Wri tten and Oral Presentation

Students should publish at least one paper based on the work in referred National /
International conference/Journal of repute.

Dissertation II should be assessed by internal and Externa l Examiners appointed by the
University o f Mumbai .