ME Computer Engg 1 Syllabus Mumbai University

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.

AC 14/7/2016
Item No. 4.25

UNIVERSITY OF MUMBAI



Revised Syllabus
For
Master of Engineering
Program: M. E. (Computer Engineering)
Under
FACULTY OF TECHNOLOGY
(As per Choice Based Credit and Grading System)
from
Academic Year 2016 -17

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.

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 e ducation. 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 educatio n 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 and 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 sen ior 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 addit ion 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 educ ation 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
throug h its 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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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.

Preamble:
The M. E. 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 abroad.
The programme is a 72 -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 ME programme in
Computer Engineering to address the need s 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. Subhas h K. Shinde
Chairperson,
Adhoc Board of Studies in Computer Engineering,
University of Mumbai, Mumbai .

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Program Structure for ME Computer Engineering,
(With Effect from 2016 -2017)
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
CSDLO -I Department Level Optional
Course -I 04 --- --- 04 --- --- 04
ILO-I Institute Level Optional
Course -I 03 --- --- 03 --- --- 03
CSL101 Computational Laboratory -I -- 02 -- 01 --- -- 01
CSL102 DEC Laboratory -I -- 02 -- 01 --- -- 01
Total 19 04 -- 21 -- -- 21

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.
CSC101 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
CSDLO -I Department Level Optional
Course -I 20 20 20 80 3 -- --- 100
ILO-I Institute Level Optional
Course -I 20 20 20 80 3 -- --- 100
CSL101 Computational Laboratory -I --- --- --- ---- ---- 25 25 50
CSL102 DEC Laboratory -I --- --- --- ---- ---- 25 25 50
Total 100 100 100 400 ---- 50 50 600

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.

Program Structure for ME Computer Engineering,
(With Effect from 2016 -2017)
University of Mumbai)
Semester –I

Course Code Department Level Optional
Course -I Course
Code Institute Level Optional
Course -I
CSDLO1 011 Logic & Automated Reasoning ILO1011 Product Lifecycle Management
CSDLO 1012 Image Analysis & Interpretation ILO1012 Reliability Engineering
CSDLO 1013 Natural Language Processing ILO1013 Management Information System
CSDLO 1014 Computational Intelligence ILO1014 Design of Experiments
CSDLO 1015 User Experience Design ILO1015 Operation Research
ILO1016 Cyber Security and Laws
ILO1017 Disaster Management &
Mitigation Measures
ILO1018 Energy Audit and Management

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Program Structure for ME Computer Engineering,
(With Effect from 2016 -2017)
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
CSDLO -II Department Level Optional
Course –II 04 --- --- 04 --- --- 04
ILO-II Institute Level Optional
Course -II 03 --- --- 03 --- --- 03
CSL201 Computational Laboratory -II -- 02 -- 01 --- -- 01
CSL202 DEC Laboratory -II -- 02 -- 01 --- -- 01
Total 19 04 --- 21 -- -- 21

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
CSC20 3 Ethical Hacking and Digital
Forensics 20 20 20 80 3 -- --- 100
CSDLO -II Department Level Optional
Course –II 20 20 20 80 3 -- --- 100
ILO-II Institute Level Optional
Course -II 20 20 20 80 3 -- --- 100
CSL201 Computational Laboratory -II --- --- --- ---
- ---- 25 25 50
CSL20 2 DEC Laboratory -II --- --- --- ---
- ---- 25 25 50
100 100 100 400 ---- 50 50 600

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Program Structure for ME Computer Engineering,
(With Effect from 2016 -2017)
University of Mumbai
Semester –II

Course Code Department Level Optional
Course -II Course Code Institute Level Optional
Course -II
CSDLO 2021 Data Storage & Retrieval ILO2021 Project Management
CSDLO 2022 Internet of Things ILO2022 Finance Management
CSDLO 2023 Advance Soft Computing ILO2023 Entrepreneurship Development and
Management
CSDLO 2024 Semantic Web & Social
Network Analysis ILO2024 Human Resource Management
CSDLO 2025 ICT for Social cause ILO2025 Professional Ethics and CSR
ILO 2026 Research Methodology
ILO2027 IPR and Patenting
ILO2028 Digital Business Management
ILO2029 Environmental Management

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Program Structure for ME 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
Total -- --- --- --- --- 100 100 200

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Subject
Code Subject Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSC 101 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 -- -- --


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 problems.

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

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
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 prob lem 10
6 Applied
Algorithms  Number -Theoretic : Number Theoretic notion,
Greatest common divisor, The Chinese remainder
theorem, RSA
 String Matching 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, U llman: The Design and analysis of algorithms”, Pearson Education
2. Vijay V. Vajirani, “Approximation Algorithms”,Springer.

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
3. S. K. Basu, “Design Methods 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 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 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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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
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 able 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 .
 Deve lop 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.
Congestio n-Avoidance Mechanisms : DECbit, Random
Early Detection (RED), So urce-Based Congestion
Avoidance, Quality of Ser vice: Application Requirements,
Integrated Services (RSVP), Differentiated Services (EF,
AF). 10

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
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: Ethernet 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 Pro tocols 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, Ci sco 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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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.

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

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
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 reliability 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, Lo ad
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 Algorithms.
 Distributed Deadlock: Introduction, deadlock
handling strategies, Deadlock detection: Issues and 12

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
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 pointing 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, Priority
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.
2. Rajib Mall, “ Real-Time Systems: Theory and Practice”, Pearson education.

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
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 identif ication of services 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 servi ce servers, clients 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 is 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 -Transform (parallel FFT). Show that the overall
communication time complexity is O ((n/p) log p), and the computational complexity of
the parallel algorithm is O (n log n/p) where n is number of elements, and p is number of
processes.

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
IV. Transparency
1) Implement 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 assignme nt 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 .

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.

Subject Code Subject Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSDLO 1011 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
Logic  Formulas, Models, Tableaux: Relations and Predicates,
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 12

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
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.

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

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Subject Code Subject Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSDLO 1012 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 –
o Enhancement : Power Law Transformation,
Contrast Stretching and Histogram
Equalization
o Spatial domain Filters: Smoothing,
Sharpening
08

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
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
 Vector Quantization 08





6 Applications Case Study on
 Remote Sensing Images
 Medical Images
 Image Forensics: Finger print classification
 Digital Watermarking for Images 04

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
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 McGr aw-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 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 .

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Subject Code Subject Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSDLO 1013 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
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) ,Morphological parsing with FST , Lexicon free FST -
Porter stemmer. N –Grams - N-gram language model , N -
gram for spelling correction . 9

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
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 phenomenon ,
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.

Reference Books :
1. Siddiqui and Tiwary U.S., Natural Language Processing and Information Retrieval,
Oxford University Pres s (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 Linguistics and Natural Language Processing “ ISBN: 978 -1-118-

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
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 t ools 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 M odules) 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 sylla bus.

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Subject Code Subject Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSDLO 1014 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
paradigms Artificial Neural Networks, Fuzzy Systems, Genetic
Algorithms, Swarm Intelligence, Artificial Immune
System, Applications 6
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. 10

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
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
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

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 pap er weightage of each module will be proportional to number of
respective lecture hours as mention in the syllabus.

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Subject Code Subject Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSDLO 1015 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 interaction. User Experience
Design works to coordinate these elements to allow for the best possible interaction by users.

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

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
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

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 carr y 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 32

University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Course Code Course Name Credits
ILO 1011 Product Life Cycle Management 03

Objectives :
1. To familiarize the students with the need, benefits and components of PLM
2. To acquaint students with Product Data Management & PLM strategies
3. To give insights into new product development program and guidelines for designing and
developing a product
4. To familiarize the students with Virtual Product Development
Outcomes: Learner will be able to…
1. Gain knowledge about phases of PLM, PLM strategies and methodology for PLM
feasibility study and PDM implementation.
2. Illustrate various approaches and techniques for designing and developing products.
3. Apply product engineering g uidelines / thumb rules in designing products for moulding,
machining, sheet metal working etc.
4. Acquire knowledge in applying virtual product development tools for components,
machining and manufacturing plant

Module Detailed Contents Hrs
01 Introduction to Product Lifecycle Management (PLM): Product Lifecycle
Management (PLM), Need for PLM, Product Lifecycle Phases, Opportunities of
Globalization, Pre -PLM Environment, PLM Paradigm, Importance & Benefits
of PLM, Widespread Impact of PLM, Focus and Application, A PLM Project,
Starting the PLM Initiative, PLM Applications
PLM Strategies: Industrial strategies, Strategy elements, its identification,
selection and implementation, Developing PLM Vision and PLM Strategy ,
Change management for PLM 10
02 ProductDesign: Product Design and Development Process, Engineering Design,
Organization and Decomposition in Product Design, Typologies of Design
Process Models, Reference Model, Product Design in the Context of the Product
Development Process, Relation with the Development Process Planning Phase,
Relation with the Post design Planning Phase, Methodological Evolution in
Product Design, Concurrent Engineering, Characteristic Features of Concurrent
Engineering, Concurrent Engineering and Life Cycle Approac h, New Product
Development (NPD) and Strategies, Product Configuration and Variant
Management, The Design for X System, Objective Properties and Design for X
Tools, Choice of Design for X Tools and Their Use in the Design Process 09
03 Product Data Manage ment (PDM): Product and Product Data, PDM systems
and importance, Components of PDM, Reason for implementing a PDM system, 05

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
financial justification of PDM, barriers to PDM implementation
04 Virtual Product Development Tools: For components, machines, and
manufacturing plants, 3D CAD systems and realistic rendering techniques,
Digital mock -up, Model building, Model analysis, Modeling and simulations in
Product Design, Examples/Case studies 05
05 Integration of Environmental Aspects in Product Design: Sustai nable
Development, Design for Environment,Need for Life Cycle Environmental
Strategies, Useful Life Extension Strategies, End -of-Life Strategies, Introduction
of Environmental Strategies into the Design Process, Life Cycle Environmental
Strategies and Cons iderations for Product Design 05
06 Life Cycle Assessment and Life Cycle Cost Analysis: Properties, and
Framework of Life Cycle Assessment, Phases of LCA in ISO Standards, Fields
of Application and Limitations of Life Cycle Assessment, Cost Analysis and th e
Life Cycle Approach, General Framework for LCCA, Evolution of Models for
Product Life Cycle Cost Analysis 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 the syllabus.
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.



REFERENCES:
1. John Stark, “Product Lifecycle Management: Paradigm for 21st Century Product Realisation”,
Springer -Verlag, 2004. ISBN: 1852338105
2. Fabio Giudice, Guido La Rosa, AntoninoRisitano, “Product Design for the environment -A life
cycle approach”, Taylor & Francis 2006, ISBN: 0849327229
3. SaaksvuoriAntti, ImmonenAnselmie, “Product Life Cycle Management”, Springer, Dreamtech,
ISBN: 354 0257314
4. Michael Grieve, “Product Lifecycle Management: Driving the next generation of lean thinking”,
Tata McGraw Hill, 2006, ISBN: 0070636265

Page 34

University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Course Code Course Name Credits
ILO 1012 Reliability Engineering 03

Objectives :
1. To familiarize the students with various aspects of probability theory
2. To acquaint the students with reliability and its concepts
3. To introduce the students to methods of estimating the system reliability of simple and complex
systems
4. To understand the various aspects of Mai ntainability, Availability and FMEA procedure
Outcomes: Learner will be able to…
1. Understand and apply the concept of Probability to engineering problems
2. Apply various reliability concepts to calculate different reliability parameters
3. Estimate the system reliability of simple and complex systems
4. Carry out a Failure Mode Effect and Criticality Analysis

Module Detailed Contents Hrs
01 Probability theory: Probability: Standard definitions and concepts; Conditional
Probability, Baye’s Theorem.
Probability Distributions: Central tendency and Dispersion; Binomial, Normal,
Poisson, Weibull, Exponential, relations between them and their significance.
Measures of Dispersion: Mean, Median, Mode, Range, Mean Deviation, Standard
Deviation, Variance, Skewness and Kurtosis. 08
02 Reliability Concepts: Reliability definitions, Importance of Reliability, Quality
Assurance and Reliability, Bath Tub Curve.
Failure Data Analysis: Hazard rate, failure density, Failure Rate, Mean Time To
Failure (MTTF), MTBF, Reliability Functions.
Reliability Hazard Models: Constant Failure Rate, Linearly increasing, Time
Dependent Failure Rate, Weibull Model. Distribution functions and reliability analysis. 08
03 System Reliability : System Configurations: Series, parallel, mixed configuration, k out
of n structure, Complex systems. 05
04 Reliability Improvement : Redundancy Techniques: Element redundancy, Unit
redundancy, Standby redundancies. Markov analysis.
System Reliability Analysis – Enumeration method, Cut -set method, Success
Path method, Decomposition method. 08
05 Maintainability and Availability : System downtime, Design for Maintainability:
Maintenance requirements, Design methods: Fa ult Isolation and self -diagnostics, Parts
standardization and Interchangeability, Modularization and Accessibility, Repair Vs
Replacement.
Availability – qualitative aspects. 05
06 Failure Mode, Effects and Criticality Analysis: Failure mode effects analysis,
severity/criticality analysis, FMECA examples. Fault tree construction, basic symbols,
development of functional reliability block diagram, Fau1t tree analysis and Event tree
Analysis 05

Page 35

University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
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 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.



REFERENCES:
1. L.S. Srinath, “Reliability Engineering”, Affiliated East -Wast Press (P) Ltd., 1985.
2. Charles E. Ebeling, “Reliability and Maintainability Engineering”, Tata McGraw Hill.
3. B.S. Dhillion, C. Singh, “Engineering Reliability”, John Wiley & Sons, 1980.
4. P.D.T. Conor, “Practical Reliability Engg.”, John Wiley & Sons, 1985.
5. K.C. Kapur, L.R. Lamberson, “Reliability in Engineering Design”, John Wiley & Sons.
6. Murray R. Spiegel, “Probability and Statistics”, Tata McGraw -Hill Publishing Co. Ltd.

Page 36

University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Course Code Course Name Credits
ILO 1013 Management Information System 03

Objectives :
1. The course is blend of Management and Technical field.
2. Discuss the roles played by information technology in today’s business and define various
technology architectures on which information systems are built
3. Define and analyze typical functional information systems and identify how they meet the needs
of the firm to deliver efficiency and competitive advantage
4. Identify the basic steps in systems development
Outcomes: Learner will be able to…
1. Explain how information systems Transform Business
2. Identify the impact information systems have on an organization
3. Describe IT infrastructure and its components and its current trends
4. Understand the principal tools and technologies for accessing information from databases to
improve business performance and decision making
5. Identify the types of systems used for enterprise -wide knowledge management and how they
provide value for businesses

Modul
e Detailed Contents Hrs
01 Introduction To Information Systems (IS): Computer Based Information
Systems, Impact of IT on organizations, Imporance of IS to Society.
Organizational Strategy, Competitive Advantages and IS. 4
02 Data and Knowledge Management: Database Approach, Big Data, Data
warehouse and Data Marts, Knowledge Management.
Business intelligence (BI): Managers and Decision Making, BI for Data analysis
and Presenting Results 7
03 Ethical issues and Privacy: Information Security. Threat to IS, and Security
Controls 7
04 Social Computing (SC): Web 2.0 and 3.0, SC in business -shopping, Marketing,
Operational and Analytic CRM, E -business and E -commerce – B2B B2C.
Mobile commerce. 7
05 Computer Networks Wired and Wireless technology, Pervasive computing,
Cloud computing model. 6
06 Information System within Organization: Transaction Processing Systems,
Functional Area Information System, ERP and ERP support of Business Process.
Acquiring Information Systems and Applications: Various System development
life cycl e models. 8

Page 37

University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
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.
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. Kelly Rainer, Brad Prince ,Management Information Systems , Wiley
2. K.C. Laudon and J.P. Laudon, Management Information Systems: Managing the Digital Firm ,
10th Ed., Prentice Hall, 2007.
3. D. Boddy, A. Boonstra, Managing Information Systems: Strategy and Organization, Prentice
Hall, 2008

Page 38

University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Course Code Course Name Credits
ILO 1014 Design of Experiments 03

Objectives:
1. To understand the issues and principles of Design of Experiments (DOE).
2. To list the guidelines for designing experiments.
3. To become familiar with methodologies that can be used in conjunction with
experimental designs for robustness and optimization

Outcomes: Learner will be able to…
 Plan data collection, to turn data into information and to make decis ions that lead to
appropriate action.
 Apply the methods taught to real life situations.
 Plan, analyze, and interpret the results of experiments

Module Detailed Contents Hrs
01 Introduction: Strategy of Experimentation, Typical Applications of
Experimental Design, Guidelines for Designing Experiments, Response Surface
Methodology. 06
02 Fitting Regression Models: Linear Regression Models, Estimation of the
Parameters in Linear Regression Models, Hypothesis Testing in Multiple
Regression, Confidence Intervals in Multiple Regression, Prediction of new
response observation, Regression model diagnostics, Testing for l ack of fit. 08
03 Two -Level Factorial Designs: The 22Design, The 23 Design, The General 2k
Design, A Single Replicate of the 2kDesign, The Addition of Center Points to the
2kDesign, Blocking in the 2kFactorial Design, Split -Plot Designs. 07
04 Two -Leve l Fractional Factorial Designs: The One -Half Fraction of the 2k
Design, The One -Quarter Fraction of the 2k Design, The General 2k-p Fractional
Factorial Design, Resolution III Designs, Resolution IV and V Designs,
Fractional Factorial Split -Plot Designs. 07
05 Conducting Tests: Testing Logistics, Statistical aspects of conducting tests,
Characteristics of good and bad data sets, Example experiments, Attribute Vs
Variable data sets. 07
06 Taguchi Approach: Crossed Array Designs and Signal -to-Noise Ratios,
Analysis Methods, Robust design examples. 04

Page 39

University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Assessment:
Internal: 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.

End Semester Examination: Some guidelines for setting the question papers are as, six
questions to be set each of 20 marks, out of these any four
questions to be attempted by students. 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 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.

REFERENCES:
1. Raymond H. Mayers, Douglas C. Montgomery, Christine M. Anderson -Cook, Respo nse
Surface Methodology: Process and Product Optimization using Designed Experiment,
3rd edition, John Wiley & Sons, New York, 2001
2. D.C. Montgomery, Design and Analysis of Experiments, 5th edition, John Wiley & Sons,
New York, 2001
3. George E P Box, J Stua rt Hunter, William G Hunter, Statics for Experimenters: Design,
Innovation and Discovery, 2nd Ed. Wiley
4. W J Dimond, Peactical Experiment Designs for Engineers and Scintists, John Wiley and
Sons Inc. ISBN: 0 -471-39054 -2
5. Design and Analysis of Experiments (Springer text in Statistics), Springer by A.M. Dean,
and D. T.Voss
6. Philip J Ross, “Taguchi Technique for Quality Engineering,” McGraw Hill.
7. Madhav S Phadake, “Quality Engineering using Robust Design,” Prentice Hall.

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Course Code Course Name Credits
ILO 1015 Operations Research 03

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…
1. Understand the 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 direct ion and magnitude of change of a model’s
optimal 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 fl ow
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 simple x method,
Duality , Primal – Dual construction, 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 : Introduction, 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 Pr ogramming
Problems, Gomory’s cutting plane Algorithm, Branch and Bound Technique .
Introduction to Decomposition algorithms. 14
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

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
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, c argo 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, dominance 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 the syllabus.
1. Question paper will comprise of total six question
2. All question carry equal marks
3. Questio ns 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.


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.

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Course Code Course Name Credits
ILO 1016 Cyber Security and Laws 03

Objectives :
1. To understand and identify different types cyber crime and cyber law
2. To recognized Indian IT Act 2008 and its latest amendments
3. To learn various types of security standards compliances
Outcomes: Learner will be able to…
1. Understand the concept of cybercrime and its effect on outside world
2. Interpret and apply IT law in various legal issues
3. Distinguish different aspects of cyber law
4. Apply Information Security Standards compliance during software design and development

Module Detailed Contents Hrs
01 Introduction to Cybercrime: Cybercrime definition and origins of the world,
Cybercrime andinformation security, Classifications of cybercrime, Cybercrime and
the
Indian ITA 2000, A global Perspective on cybercrimes. 4
02 Cyber offenses & Cybercrime: How criminal plan the attacks, Social Engg, Cyber
stalking, Cyber café and Cybercrimes, Botnets, Attack vector, Cloud computing,
Proliferation ofMobile and Wireless Devices, Trends in Mobility, Credit Card
Frauds in
Mobile and Wireless Computing Era, Security Challenges Posed byMobile Devices,
Registry Settings for Mobile Devices, AuthenticationService Security, Attacks on
Mobile/Cell Phones, Mobile Devices:Security Implications for Organizations,
Organizational Measures forHandling Mobile, Devices -Related Secu rity Issues,
OrganizationalSecurity Policies and Measures in Mobile Computing Era, Laptops 9
03 Tools and Methods Used in Cyberline
Phishing, Password Cracking, Keyloggers and Spywares, Virus and Worms,
Steganography, DoS and DDoS Attacks, SQL Injection, Buffer Over Flow, Attacks
on Wireless Networks, Phishing, Identity Theft (ID Theft) 6
04 The Concept of Cyberspace
E-Commerce , The Contract Aspects in Cyber Law ,The Security Aspect of Cyber
Law ,The Intellectual Property Aspect in Cyber Law
, The Evidence Aspect in Cyber Law , The Criminal Aspect in Cyber Law, Global
Trends in Cyber Law , Legal Framework for Electronic Data Interchange Law
Relating to Electronic Banking , The Need for an Indian Cyber Law 8
05 Indian IT Act.
Cyber Crime and Criminal Justice : Penalties, Adjudication and Appeals Under the
IT Act, 2000, IT Act. 2008 and its Amendments 6
06 Information Security Standard compliances
SOX, GLBA, HIPAA, ISO, FISMA, NERC, PCI. 6

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
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 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.



REFERENCES:
1. Nina Godbole, Sunit Belapure, Cyber Security , Wiley India, New Delhi
2. The Indian Cyber Law by Suresh T. Vishwanathan; Bharat Law House New Delhi
3. The Information technology Act, 2000; Bare Act - Professional Book Publishers, New Delhi.
4. Cyber Law & Cyber Crimes By Advocate Prashant Mali; Snow White Publications, Mumbai
5. Nina Godbole, Information Systems Security, Wiley India, New Delhi
6. Kennetch J. Knapp, Cyber Security &Global Information Assurance Information Science
Publishing.
7. William Stallings , Cryptog raphy and Network Security, Pearson Publication
8. Websites for more information is available on : The Information Technology ACT, 2008 - TIFR :
https://www.tifrh.res.in
9. Website for more information , A Compliance Primer for IT professional :
https://www.sa ns.org/reading -room/whitepapers/compliance/compliance -primer -professionals -
33538

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Course Code Course Name Credits
ILO 1017 Disaster Management and Mitigation Measures 03
Objectives:
1. To understand physics and various types of disaster occurring around the world
2. To identify extent and damaging capacity of a disaster
3. To study and understand the means of losses and methods to overcome /minimize it.
4. To understand role of individual and various organization during and after disaster
5. To understand application of GIS in the field of disaster management
6. To understand the emergency government response structures before, during and after
disaster
Outcomes: Learner will be able to…
1. Get to know natural as well as manmade disaster and their extent and possible effects on the
economy.
2. Plan of national importance structures based upon the previous history.
3. Get acquainted with government policies, acts and va rious organizational structure
associate d with an emergency.
4. Get to k now the simple do’s and don’ts in such extreme events and act accordingly.

Module Detailed Contents Hrs
01 Introduction
1.1 Definition of Disaster, hazard, global and Indian scenario, general
perspective, importance of study in human life, Direct and indirect effects of
disasters, long term effects of disasters. Introduction to global warming and
climate change. 03
02 Natural Disaster and Manmade disasters:
2.1 Natural Disaster: Meaning and nature of natural disaster, Flood, Flash flood,
drought, cloud burst, Earthquake, Landslides, Avalanches, Volcanic
eruptions, Mudflow, Cyclone, Storm, Storm Surge, climate change, global
warming, sea level rise, ozone depletion
2.2 Manmade Disasters: Chemical, Industrial, Nuclear and Fire Hazards. Role of
growing population and subsequent industrialization, urbanization and
changing lifestyle of human beings in frequent occurrences of manmade
disasters. 09
03 Disaster Management, Policy and Administration
3.1 Disaster management: meaning, concept, importance, objective of disaster
management policy, disaster risks in India, Paradigm shift in disaster
management.
3.2 Policy and administration:
Importance and principles of disaster management policies, command and
co-ordination of in disaster management, rescue operations -how to start with
and how to proceed in due course of time, study of flowchart showing the
entire process.
06

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
04 Institutional Framework for Disaster Management in India:
4.1 Importance of public awareness, Preparation and execution of emergency
management programme.Scope and responsibilities of National Institute of
Disaster Management (NIDM) and National disaste r management authority
(NDMA) in India.Methods and measures to avoid disasters, Management of
casualties, set up of emergency facilities, importance of effective
communication amongst different agencies in such situations.
4.2 Use of Internet and softwares for effective disaster management.
Applications of GIS, Remote sensing and GPS in this regard. 06
05 Financing Relief Measures:
5.1 Ways to raise finance for relief expenditure, role of government agencies
and NGO’s in this process, Legal aspects relat ed to finance raising as well as
overall management of disasters. Various NGO’s and the works they have
carried out in the past on the occurrence of various disasters, Ways to
approach these teams.
5.2 International relief aid agencies and their role in e xtreme events. 09
06 Preventive and Mitigation Measures:
6.1 Pre -disaster, during disaster and post -disaster measures in some events in
general
6.2 Structural mapping: Risk mapping, assessment and analysis, sea walls and
embankments, Bio shield, shelters, early warning and communication
6.3 Non Structural Mitigation: Community based disaster preparedness, risk
transfer and risk financing, capacity development and training, awareness
and education, contingency plans.
6.4 Do’s and don’ts in case of disasters and effective implementation of relief
aids. 06


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 respec tive lecture hours as mention in the syllabus.
1. Question paper will comprise of total six question
2. All question carry equal marks

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
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 o ther than module 3)
4. Only Four question need to be solved.

REFERENCES:
1. ‘Disaster Management’ by Harsh K.Gupta, Universities Press Publications.
2. ‘Disaster Management: An Appraisal of Institutional Mechanisms in India’ by O.S.Dagur,
published by Centre for land warfare studies, New Delhi, 2011.
3. ‘Introduction to International Disaster Management’ by Damon Copolla, Butterworth Heinemann
Elseveir Publications.
4. ‘Disaster Management Handbook’ by Jack Pinkowski, CRC Press Taylor and Francis group.
5. ‘Disaster management & rehabilitation’ by Rajdeep Dasgupta, Mittal Publications, New Delhi.
6. ‘Natural Hazards and Disaster Management, Vulnerability and Mitigation – R B Singh, Rawat
Publications
7. Concepts and Techniques of GIS –C.P.Lo Albert, K.W. Yonng – Prentice H all (India)
Publications.
(Learners are expected to refer reports published at national and International level and updated
information available on authentic web sites)

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Course Code Course Name Credits
ILO 1018 Energy Audit and Management 03
Objectives:
1. To understand the importance energy security for sustainable development and the fundamentals
of energy conservation.
2. To introduce performance evaluation criteria of various electrical and thermal installations to
facilitate the energy management
3. To relate the data collected during performance evaluation of systems for identification of energy
saving opportunities.

Outcomes: Learner will be able to…
1. To identify and describe present state of energy security and its importance.
2. To identify and describe the basic principles and methodologies adopted in energy audit of an
utility.
3. To describe the energy performance evaluation of some common electrical installations and
identify the energy saving opportunities.
4. To describe the ene rgy performance evaluation of some common thermal installations and
identify the energy saving opportunities
5. To analyze the data collected during performance evaluation and recommend energy saving
measures

Module Detailed Contents Hrs
01 Energy Scenario:
Present Energy Scenario, Energy Pricing, Energy Sector Reforms, Energy
Security, Energy Conservation and its Importance, Energy Conservation Act -
2001 and its Features. Basics of Energy and its various forms, Material and
Energy balance 04
02 Energy Audit Principles:
Definition, Energy audit - need, Types of energy audit, Energy management
(audit) approach -understanding energy costs, Bench marking, Energy
performance, Matching energy use to requirement, Maximizing system
efficiencies, Opt imizing the input energy requirements, Fuel and energy
substitution. Elements of monitoring& targeting; Energy audit Instruments; Data
and information -analysis.
Financial analysis techniques: Simple payback period, NPV, Return on
investment (ROI), Interna l rate of return (IRR) 08
03 Energy Management and Energy Conservation in Electrical System:
Electricity billing, Electrical load management and maximum demand Control;
Power factor improvement, Energy efficient equipments and appliances, star
ratings.
Energy efficiency measures in lighting system, Lighting control: Occupancy
sensors, daylight integration, and use of intelligent controllers.
Energy conservation opportunities in: water pumps, industrial drives, induction 10

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
motors, motor retrofitting, soft starters, variable speed drives.
04 Energy Management and Energy Conservation in Thermal Systems:
Review of different thermal loads; Energy conservation opportunities in: Steam
distribution system, Assessment of steam distribution losses, Steam leaka ges,
Steam trapping, Condensate and flash steam recovery system.
General fuel economy measures in Boilers and furnaces, Waste heat recovery,
use of insulation - types and application. HVAC system: Coefficient of
performance, Capacity, factors affecting Refrigeration and Air Conditioning
system performance and savings opp ortunities. 10
05 Energy Performance Assessment:
On site Performance evaluation techniques, Case studies based on: Motors and
variable speed drive, pumps, HVAC system calculations; Lighting System:
Installed Load Efficacy Ratio (ILER) method, Financial Analysis. 04
06 Energy conservation in Buildings:
Energy Conservation Building Codes (ECBC): Green Building, LEED rating,
Application of Non -Conventional and Renewable Energy Sources 03
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 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.

REFERENCES:
1. Handbook of Electrical Installation Practice, Geofry Stokes, Blackwell Science
2. Designing with light: Lighting Handbook, By Anil Valia, Lighting System
3. Energy Management Handbook, By W.C. Turner, John Wiley and Sons
4. Handbook on Energy Audits and Management, edited by A. K. Tyagi, Tata Energy
Research Instit ute (TERI).
5. Energy Management Principles, C.B.Smith, Pergamon Press
6. Energy Conservation Guidebook, Dale R. Patrick, S. Fardo, Ray E. Richardson,
Fairmont Press
7. Handbook of Energy Audits, Albert Thumann, W. J. Younger, T. Niehus, CRC Press
8. www.energymanagertraining.com ; www.bee -india.nic.in

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Subject
Code Subject Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSL101 Computational
Laboratory -I -- -- -- --- 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
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 different 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), controllers(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 numbe r 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 at 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.

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Subject
Code Subject Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSL102 DEC Laboratory -I -- -- -- --- 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 departmental electives
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.

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
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

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 parameters.
 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 ) 10

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Issues: Synchronization, Scheduling, Job Allocation, Job
Partitioning, Dependency Analysis, Mapping Parallel
Algorithms on to Parallel Architectures
Limitations: Bandwidth Limitations, Latency Limitations,
Latency Hiding/Tolerating Techniques and their
limitations
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 memory
programing 10
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 OpenCL 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 (im mutability, 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 aware 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.

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
3. Edward Kandrot and Jason Sanders, “CUDA by Example – An Introduction to General
Purpose GPU Programming”,Addison -Wesley Professional ©, 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 Parallel Computin g: Technology, Architecture,
Programming”, McGraw Hill, 1998.
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 problems 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 Asse ssment: 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 .

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
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
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 practices" in data science with modern tools

Sr.
No. Modul e 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 Descriptive 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 .
Predicti ve Modeling: Predictive modeling process, 12

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
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.
3 Evaluation and
Methodology of
Data Science Experimental setup s, training, tuning, test data, holdout
method, cross -validation, bootstrap method
Measuring performance of a mode l: Accuracy, ROC
curves, precision -recall curves, loss functions for
regression
Interpretation of results: Confidence interval for accuracy,
hypothesis tests for comparing models, algorithms. 03
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 leakage, 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 Cla ss Hadoop and streaming Data”,
The McGraw Hill Companies, 2012

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
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,”D ata Science and Big Data Analytics”,Wiley
10. DT Editorial Services, “Big Data Black Book”, Dreamtech 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 .

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
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 -- -- --

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 securities.
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 security 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 12 Hrs

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Data Analysis Tools : Nmap /Wireshark /Helix3pro
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:
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 of 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 assig nment 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 .

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Subject Code Subject Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSDLO 2021 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 -- -- --

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 Storage Area Networks: Fibre Channel , Components of SAN,
FC Connectivity, Fibre Channel Ports, Fibre Channel 12

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Technologies 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 NA S Performance and
Availability . IP SAN: iSCSI, FCIP .
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
Compon ents 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, “In formation 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
Educatio n, 2003

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
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.

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 .

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Subject Code Subject
Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSDLO 2022 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 -- -- --

Course Objectives:
1. Provide an overview of concepts, main trends and challenges of Internet of Things.
2. Develop the ability to use Internet of Things related software and hardware
technologies.
3. Provide the knowledge of data management business processes and analytics of IoT.
4. 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 Objects. 8
2 Open – Source
Prototyping
Platforms for
IoT Basic Arduino Programming Extended Arduino Libraries,
Arduino – Based Interne t 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

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
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
Use Cases Concrete Applications and Use – Cases of Web Enabled
Things: Energy Management and Smart Homes, Ambient
Assisted Living, Intelligent Transport, Etc. M2M,
Industrial IoT Applications. 8

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

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

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.

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Subject Code Subject
Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSDLO 2023 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 -- -- --
.
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, Introduction 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

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
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

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:
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 mention in the syllabus .

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Subject Code Subject
Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSDLO 2024 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 -- -- --

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 predict 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 Technologies
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 analysis 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 Semant ic Web -SPARQL 10

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
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 social 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
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 and Social Networking
Techniques and applications”, First Edition Springer, 20 11.
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 Chevalier, 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, 2009.
5. Charu C. Aggarwal, “Social Network Data Analytics”, Springer; 2011.

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
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.


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) w ill 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 69

University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.

Subject Code Subject Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSDLO 2025 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 -- -- --

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 arc hitecture 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

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
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
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 Services Edited By Paul
Warren, Jhon Davies, David Brown , Wiley Publication
2. Jochen Schiller, "Mobile communications", Addison wisely, Pearson Education.
3. GIS Fundamentals, Applications and Impl ementation, 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 inte lligence , 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.

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
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 tes t 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 72

University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Course Code Course Name Credits
ILO 2021 Project Management 03

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 options.
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 dete rmine & 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 proposal. 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 char t, 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 quantitative 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 stakehol ders of the projects. 8

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
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
successes 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 th e 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 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.


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

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Course Code Course Name Credits
ILO 2 022 Finance Management 03

Objectives :
1. Overview of Indian financial system, instruments and market
2. Basic concepts of value of money, returns and risks, corporate finance, working capital and its
management
3. Knowledge about sources of finance, capital structure, dividend policy
Outcomes: Learner will be able to…
1. Understand Indian finance system and corporate finance
2. Take investment, finance as well as dividend decisions

Module Detailed Contents Hrs
01 Overview of Indian Financial System: Characteristics, Components and Functions of
Financial System.
Financial Instruments: Meaning, Characteristics and Classification of Basic Financial
Instruments — Equity Shares, Preference Shares, Bonds -Debentures, Certificates of
Deposit, and Treasury Bills.
Financial Markets: Meaning, Characteristics and Classificat ion of Financial Markets
— Capital Market, Money Market and Foreign Currency Market
Financial Institutions: Meaning, Characteristics and Classification of Financial
Institutions — Commercial Banks, Investment -Merchant Banks and Stock Exchanges 06
02 Concepts of Returns and Risks: Measurement of Historical Returns and Expected
Returns of a Single Security and a Two -security Portfolio; Measurement of Historical
Risk and Expected Risk of a Single Security and a Two -security Portfolio.
Time Value of Money : Future Value of a Lump Sum, Ordinary Annuity, and Annuity
Due; Present Value of a Lump Sum, Ordinary Annuity, and Annuity Due; Continuous
Compounding and Continuous Discounting. 06
03 Overview of Corporate Finance: Objectives of Corporate Finance; Funct ions of
Corporate Finance —Investment Decision, Financing Decision, and Dividend Decision.
Financial Ratio Analysis: Overview of Financial Statements —Balance Sheet, Profit
and Loss Account, and Cash Flow Statement; Purpose of Financial Ratio Analysis;
Liqui dity Ratios; Efficiency or Activity Ratios; Profitability Ratios; Capital Structure
Ratios; Stock Market Ratios; Limitations of Ratio Analysis. 09
04 Capital Budgeting: Meaning and Importance of Capital Budgeting; Inputs for Capital
Budgeting Decisions; Investment Appraisal Criterion —Accounting Rate of Return,
Payback Period, Discounted Payback Period, Net Present Value(NPV), Profitability
Index, Internal Rate of Return (IRR), and Modified Internal Rate of Return (MIRR)
Working Capital Management: Concept s of Meaning Working Capital; Importance of
Working Capital Management; Factors Affecting an Entity’s Working Capital Needs; 10

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Estimation of Working Capital Requirements; Management of Inventories;
Management of Receivables; and Management of Cash and Market able Securities.
05 Sources of Finance: Long Term Sources —Equity, Debt, and Hybrids; Mezzanine
Finance; Sources of Short Term Finance —Trade Credit, Bank Finance, Commercial
Paper; Project Finance.
Capital Structure: Factors Affecting an Entity’s Capita l Structure; Overview of
Capital Structure Theories and Approaches — Net Income Approach, Net Operating
Income Approach; Traditional Approach, and Modigliani -Miller Approach. Relation
between Capital Structure and Corporate Value; Concept of Optimal Capital Structure 05
06 Dividend Policy: Meaning and Importance of Dividend Policy; Factors Affecting an
Entity’s Dividend Decision; Overview of Dividend Policy Theories and Approaches —
Gordon’s Approach, Walter’s Approach, and Modigliani -Miller Approach 03

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.
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. Fundamentals of Financial Management, 13th Edition (2015) by Eugene F. Brigham and Joel F.
Houston; Publisher: Cengage Publications, New Delhi.
2. Analysis for Financial Management, 10th Edition (2013) by Robert C. Higgins; Publishers:
McGraw Hill Education, New Delhi.
3. Indian Financial System, 9th Edition (2015) by M. Y. Khan; Publisher: McGraw Hill Education,
New Delhi.
4. Financial Management, 11th Edition (2015) by I. M. Pandey; Publisher: S. Chand (G/L) &
Company Limited, New Delhi.

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Course Code Course Name Credits
ILO2023 Enterpreneurship Development and
Management 03

Objectives :
1. To acquaint with entrepreneurship and management of business
2. Understand Indian environment for entrepreneurship
3. Idea of EDP, MSME
Outcomes: Learner will be able to…
1. Understand the concept of business plan and ownerships
2. Interpret key regulations and legal aspects of entrepreneurship in India
3. Understand government policies for entrepreneurs
Module Detailed Contents Hrs
01 Overview Of Entrepreneurship: Definitions, Roles and Functions/Values of
Entrepreneurship, History of Entrepreneurship Development, Role of Entrepreneurship
in the National Economy, Functions of an Entrepreneur, Entrepreneurship and Forms of
Business Ownership
Role of Money and Capita l Markets in Entrepreneurial Development: Contribution of
Government Agencies in Sourcing information for Entrepreneurship 04
02 Business Plans And Importance Of Capital To Entrepreneurship: Preliminary and
Marketing Plans, Management and Personnel, Start -up Costs and Financing as well as
Projected Financial Statements, Legal Section, Insurance, Suppliers and Risks,
Assumptions and Conclusion, Capital and its Importance to the Entrepreneur
Entrepreneurship And Business Development: Starting a New Business , Buying an
Existing Business, New Product Development, Business Growth and the Entrepreneur
Law and its Relevance to Business Operations 09
03 Women’s Entrepreneurship Development, Social entrepreneurship -role and need, EDP
cell, role of sustainability and sustainable development for SMEs, case studies,
exercises 05
04 Indian Environment for Entrepreneurship: key regulations and legal aspects ,
MSMED Act 2006 and its implications, schemes and policies of the Ministry of MSME,
role and responsibilities o f various government organisations, departments, banks etc.,
Role of State governments in terms of infrastructure developments and support etc.,
Public private partnerships, National Skill development Mission, Credit Guarantee
Fund, PMEGP, discussions, gro up exercises etc 08
05 Effective Management of Business: Issues and problems faced by micro and small
enterprises and effective management of M and S enterprises (risk management, credit
availability, technology innovation, supply chain management, linkage with large
industries), exercises, e -Marketing 08
06 Achieving Success In The Small Business: Stages of the small business life cycle, four
types of firm -level growth strategies, Options – harvesting or closing small business
Critical Success factors of small business 05

Page 77

University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
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 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.



REFERENCES:
1. Poornima Charantimath, Entrepreneurship development - Small Business Enterprise, Pearson
2. Education Robert D Hisrich, Michael P Peters, Dean A Shapherd, Entrepreneurship, latest
edition, The McGrawHill Company
3. Dr TN Chhabra, Entrepreneurship Development, Sun India Publications, New Delhi
4. Dr CN Prasad, Small and Medium Enterprises in Global Perspective, New century Publications,
New Delhi
5. Vasant Desai, Entrepreneurial development and management, Himalaya Publishing House
6. Maddhurima Lall, Shikah Sahai, Entrepreneurs hip, Excel Books
7. Rashmi Bansal, STAY hungry STAY foolish, CIIE, IIM Ahmedabad
8. Law and Practice relating to Micro, Small and Medium enterprises, Taxmann Publication Ltd.
9. Kurakto, Entrepreneurship - Principles and Practices, Thomson Publication
10. Laghu Udyo g Samachar
11. www.msme.gov.in
12. www.dcmesme.gov.in
13. www.msmetraining.gov.in

Page 78

University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Course Code Course Name Credits
ILO2024 Human Resource Management 03

Objectives :
1. To introduce the students with basic concepts, techniques and practices of the human resource
management.
2. To provide opportunity of learning Human resource management (HRM) processes, related with
the functions, and challenges in the emerging perspective of today’s organizations.
3. To familiarize the students about the latest developments, trends & different aspects of HRM.
4. To acquaint the student with the importance of inter -personal & inter -group behavioral skills in
an organizational setting required for future stable engineers, leaders and managers.

Outcomes: Learner will be able to…
1. Understand the concepts, aspects, techniques and practices of the human resource management.
2. Understand the Human resource management (HRM) processes, functions, changes and
challenges in today’s emerging organizational perspective.
3. Gain knowledge about the latest developments and trends in HRM.
4. Apply the knowledge of behavioral skills learnt and integrate it with in inter personal and
intergroup environment emerging as future stable engineers and managers.

Module Detailed Contents Hrs
01 Introduction to HR
 Human Resource Management - Concept, Scope and Importance,
Interdisciplinary Approach Relationship with other Sciences, Competencies of
HR Manager, HRM functions.
 Human resource development (HRD): changing role of HRM – Human
resource Planning, Technological chan ge, Restructuring and rightsizing,
Empowerment, TQM, Managing ethical issues. 5
02 Organizational Behavior (OB)
 Introduction to OB Origin, Nature and Scope of Organizational Behavior,
Relevance to Organizational Effectiveness and Contemporary issues
 Personality: Meaning and Determinants of Personality, Personality
development, Personality Types, Assessment of Personality Traits for
Increasing Self Awareness
 Perception: Attitude and Value, Effect of perception on Individual Decision -
making, Attitude an d Behavior.
 Motivation: Theories of Motivation and their Applications for Behavioral
Change (Maslow, Herzberg, McGregor);
 Group Behavior and Group Dynamics: Work groups formal and informal
groups and stages of group development. Team Effectiveness: High performing
teams, Team Roles, cross functional and self -directed team.
 Case study
7

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
03 Organizational Structure &Design
 Structure, size, technology, Environment of organization; Organizational Roles
& conflicts: Concept of roles; role dynamics; role conflicts and stress.
 Leadership: Concepts and skills of leadership, Leadership and managerial roles,
Leadership styles and contemporary issues in leadership.
 Power and Politics: Sources and uses of power; Politics at workplace, Tactics
and strategies. 6
04 Human resource Planning
 Recruitment and Selection process, Job -enrichment, Empowerment - Job-
Satisfaction, employee morale.
 Performance Appraisal Systems: Traditional & modern methods, Performance
Counseling, Career Planning.
 Training & Development: Identification of Training Needs, Training Methods 5
05 Emerging Trends in HR
 Organizational development; Business Process Re -engineering (BPR), BPR as a
tool for organizational development , managing processes & transformation in
HR. Organizational Change, Culture, Environment
 Cross Cultural Leadership and Decision Making : Cross Cultural
Communication and d iversity at work , Causes of diversity, managing diversity
with special reference to handicapped, women and ageing people, intra
company cultural difference in employee motivation. 6
06 HR & MIS
Need, purpose, objective and role of information system in HR, Applications in HRD in
various industries (e.g. manufacturing R&D, Public Transport, Hospitals, Hotels an d
service industries
Strategic HRM
Role of Strategic HRM in the modern business world, Concept of Strategy, Strategic
Management Process, Approaches to Strategic Decision Making; Strategic Intent –
Corporate Mission, Vision, Objectives and Goals
Labor Laws & Industrial Relations
Evolution of IR, IR issues in organizations, Overview of Labor Laws in India; Industrial
Disputes Act, Trade Unions Act, Shops and Establishments Act 10


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 que stion
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

Page 80

University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.

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.

REFERENCES:
1. Stephen Robbins, Organizational Behavior, 16th Ed, 2013
2. V S P Rao, Human Resource Management, 3rd Ed, 2010, Excel publishing
3. Aswathapa, Human resource management: Text & cases, 6th edition, 2011
4. C. B. Mamoria and S V Gankar, Dynamics of Industrial Relations in India, 15th Ed, 2015,
Himalaya Publishing, 15theditio n, 2015
5. P. Subba Rao, Essentials of Human Resource management and Industrial relations, 5th Ed, 2013,
Himalaya Publishing
6. Laurie Mullins, Management & Organizational Behavior, Latest Ed, 2016, Pearson Publications

Page 81

University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Course Code Course Name Credits
ILO2025 Professional Ethics and Corporat Social
Responsibility (CSR) 03

Objectives :
1. To understand professional ethics in business
2. To recognized corporate social responsibility
Outcomes: Learner will be able to…
1. Understand rights and duties of business
2. Distinguish different aspects of corporate social responsibility
3. Demonstrate professional ethics
4. Understand legal aspects of corporate social responsibility

Module Detailed Contents Hrs
01 Professional Ethics and Business: The Nature of Business Ethics; Ethical Issues in
Business; Moral Responsibility and Blame; Utilitarianism: Weighing Social Costs
and Benefits; Rights and Duties of Business 04
02 Professional Ethics in the Marketplace: Perfect Competition; Monopoly
Competition; Oligopolistic Competition; Oligopolies and Public Policy
Professional Ethics and the Environment: Dimensions of Pollution and Resource
Depletion; Ethics of Pollution Control; Ethics of Conserving Depletable Resources 08
03 Professional Ethics of Consumer Protection: Markets and Consumer Protection;
Contract View of Business Firm’s Duties to Consumers; Due Care Theory;
Advertising Ethics; Consumer Privacy
Professional Ethics of Job Discrimination: Nature of Job Discrimination; Extent of
Discrimination; Rese rvation of Jobs. 06
04 Introduction to Corporate Social Responsibility: Potential Business Benefits —
Triple bottom line, Human resources, Risk management, Supplier relations;
Criticisms and concerns —Nature of business; Motives; Misdirection.
Trajectory of Corporate Social Responsibility in India 05
05 Corporate Social Responsibility: Articulation of Gandhian Trusteeship
Corporate Social Responsibility and Small and Medium Enterprises (SMEs) in India,
Corporate Social Responsibility and Public -Private Partnership (PPP) in India 08
06 Corporate Social Responsibility in Globalizing India: Corporate Social
Responsibility Voluntary Guidelines, 2009 issued by the Ministry of Corporate
Affairs, Government of India, Legal Aspects of Corporate Social Responsib ility—
Companies Act, 2013. 08

Page 82

University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
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 respec tive 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 has part (a) from module 3 then
part (b) will be from any module o ther than module 3)
4. Only Four question need to be solved.



REFERENCES:
1. Business Ethics: Texts and Cases from the Indian Perspective (2013) by Ananda Das Gupta;
Publisher: Springer.
2. Corporate Social Responsibility: Readings and Cases in a Global Context (2007) by Andrew
Crane, Dirk Matten, Laura Spence; Publisher: Routledge.
3. Business Ethics: Concepts and Cases, 7th Edition (2011) by Manuel G. Velasquez; Publisher:
Pearson, New Delhi.
4. Corporate Social Responsibility in India (2015) by BidyutChakrabarty, Routledge, New Delhi.

Page 83

University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Course Code Course Name Credits
ILO2026 Research Methodology 03

Objectives:
1. To understand Research and Research Process
2. To acquaint students with identifying problems for research and develop research strategies
3. To familiarize students with the techniques of data collection, analysis of data and interpretation
Outcomes: Learner will be able to…
1. Prepare a preliminary research design for projects in t heir subject matter areas
2. Accurately collect, analyze and report data
3. Present complex data or situations clearly
4. Review and analyze research findings

Module Detailed Contents Hrs
01 Introduction and Basic Research Concepts
1.1 Research – Definition; Concept of Construct, Postulate, Proposition, Thesis,
Hypothesis, Law, Principle.Research methods vs Methodology
1.2 Need of Research in Business and Social Sciences
1.3 Objectives of Research
1.4 Issues and Problems in Research
1.5 Characteristics of Rese arch:Systematic, Valid, Verifiable, Empirical and Critical 09
02 Types of Research
2.1. Basic Research
2.2. Applied Research
2.3. Descriptive Research
2.4. Analytical Research
2.5. Empirical Research
2.6 Qualitative and Quantitative Approaches 07
03 Research Design and Sample Design
3.1 Research Design – Meaning, Types and Significance
3.2 Sample Design – Meaning and Significance Essentials of a good sampling Stages in
Sample Design Sampling methods/techniques Sampling Errors 07
04 Research Methodology
4.1 Meaning of Research Methodology
4.2. Stages in Scientific Research Process:
a. Identification and Selection of Research Problem
b. Formulation of Research Problem
c. Review of Literature
d. Formulation of Hypothesis
e. Formulation of research Design
f. Sample Design
g. Data Collection
h. Data Analysis 08

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
i. Hypothesis testing and Interpretation of Data
j. Preparation of Research Report
05 Formulating Research Problem
5.1 Considerations: Relevance, Interest, Data Availability, Choice of data, Analysis of
data, Generalization and Interpretation of analysis 04
06 Outcome of Research
6.1 Preparation of the report on conclusion reached
6.2 Validity Testing & Ethical Issues
6.3 Suggestions and Recommendation 04

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 at least 6 assignment on complete syllabus 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.
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. Dawson, Catherine, 2002, Practical Research Methods, New Delhi, UBS Publishers Distributors.
2. Kothari, C.R.,1985, Research Methodology -Methods and Techniques, New Delhi, Wiley Eastern
Limited.
3. Kumar, Ranjit, 2005, Research Methodology -A Step -by-Step Guide for Beginners, (2nded),
Singapore, Pearson Education

Page 85

University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Course Code Course Name Credits
ILO2027 IPR and Patenting 03

Objectives:
1. To understand intellectual property rights protection system
2. To promote the knowledge of Intellectual Property Laws of India as well as International treaty
procedures
3. To get acquaintance with Patent search and patent filing procedure and applications
Outcomes: Learner will be able to…
1. understand Intellectual Property assets
2. assist individuals and organizations in capacity building
3. work for development, promotion, protection, compliance, and enforcement of Intellectual
Property and Patenting

Module Detailed Contents Hr
01 Introduction to Intellectual Property Rights (IPR) : Meaning of IPR, Different
category of IPR instruments - Patents, Trademarks,Copyrights, Industrial Designs, Plant
variety protection, Geographical indications,Transfer of technology etc.
Importance of IPR in Modern Global Economic Environment: Theories of IPR,
Philosophical aspects of IPR laws, Need for IPR, IPR as an instrument of development 05
02 Enforcement of Intellectual Property Rights: Introduction, Magnitude of problem,
Factors that create and sustain counterfeiting/piracy, International agree ments,
International organizations (e.g. WIPO, WTO) activein IPR enforcement
Indian Scenario of IPR: Introduction, History of IPR in India, Overview of IP laws in
India, Indian IPR, Administrative Machinery, Major international treaties signed by
India, Pr ocedure for submitting patent and Enforcement of IPR at national level etc. 07
03 Emerging Issues in IPR: Challenges for IP in digital economy, e -commerce, human
genome,biodiversity and traditional knowledge etc. 05
04 Basics of Patents: Definition of Patents, Conditions of patentability, Patentable and
non-patentable inventions, Types of patent applications (e.g. Patent of addition etc),
Process Patent and Product Patent, Precautions while patenting, Patent specification
Patent claims, Disclosures and non-disclosures, Patent rights and infringement, Method
of getting a patent 07
05 Patent Rules: Indian patent act, European scenario, US scenario, Australia scenario,
Japan scenario, Chinese scenario, Multilateral treaties where India is a member (TRIPS
agreement, Paris convention etc.) 08
06 Procedure for Filing a Patent (National and International): Legislation and Salient
Features, Patent Search, Drafting and Filing Patent Applications, Processing of patent,
Patent Litigation, Patent Publicationetc, Time frame and cost, Patent Licensing, Patent
Infringement
Patent databases: Important websites, Searching international databases 07

Page 86

University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
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 at least 6 assignment on complete syllabus or course project.

End Semester Theory Examination:
Some guidelines for setting up the question paper. Minimum 80% syll abus 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 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.
REFERENCE BOOKS :
1. Rajkumar S. Adukia, 2007, A Handbook on Laws Relating to Intellectual Property Rights in
India, The Institute of Chartered Accountants of India
2. Keayla B K, Patent system and related issues at a glance, Published by National Working Group
on Patent Laws
3. T Sengupta, 2011, Intellectual Property Law in India, Kluwer Law International
4. Tzen Wong and Graham Dutfield, 2010, Intellectual Property and Human Development: Current
Trends and Future Scenario, Cambridge University Press
5. Cornish, William Rodolph & Llewelyn, David. 2010, Intellectual Property: Patents, Copyrights,
Trade Marks and Allied Right, 7th Edition, Sweet & Maxwell
6. Lous Harns, 2012, The enforcement of Intellactual Property Rights: A Case Book, 3rd Edition,
WIPO
7. Prabhuddha Ganguli, 2012, Intellectual Property Rights, 1st Edition, TMH
8. R Radha Krishnan & S Balasubramanian, 2012, Intellectual Property Rights, 1st Edition, Excel
Books
9. M Ashok Kumar and mohd Iqbal Ali, 2 -11, Intellectual Property Rights, 2nd Edition, Serial
Publications
10. Kompal Bansal and Praishit Bansal, 2012, Fundamentals of IPR for Engineers, 1st Edition, BS
Publications
11. Entrepreneurship Development and IPR Unit, BITS Pilani, 2007, A Manual on Intellectual
Property Rights,
12. Mathew Y Maa, 2009, Fundamentals of Patenting and Licensing for Scientists and Enginee rs,
World Scientific Publishing Company
13. N S Rathore, S M Mathur, Priti Mathur, Anshul Rathi , IPR: Drafting,Interpretation of Patent
Specifications and Claims , New India Publishing Agency
14. Vivien Irish, 2005, Intellectual Property Rights for Engineers,IET
15. Howard B Rockman, 2004, Intellectual Property Law for Engineers and scientists, Wiley -IEEE
Press

Page 87

University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Course Code Course Name Credits
ILO 2028 Digital Business Management 03

Objectives:
1. To familiarize with digital business concept
2. To acquaint with E -commerce
3. To give insights into E -business and its strategies

Outcomes: The learner will be able to …..
1. Identify drivers of digital business
2. Illustrate various approaches and techniques for E -business and management
3. Prepare E -business plan

Module Detailed content Hours
1 Introduction to Digital Business -
Introduction, Background and current status, E -market places, structures,
mechanisms, economics and impacts
Difference between physical economy and digital economy,
Drivers of digital business - Big Data & Analytics, Mobile, Cloud Computing,
Social media, BYOD, and Internet of Things(digitally intelligent
machines/services)
Opportunities and Challenges in Digital Business, 09
2 Overview of E -Commerce
E-Commerce - Meaning, Retailing in e -commerce -products and services,
consumer behavior, market research and advertisement
B2B-E-commerce -selling and buying in private e -markets, public B2B exchanges
and support services, e -supply chains, Collaborative Commerce, Intra business EC
and Corporate portals
Other E -C models and applications, innovative EC System -From E -government
and learning to C2C, mobile commerce and pervasive computing
EC Strategy and Implementation -EC strategy and global EC, Economics and
Justification of EC, Using Affiliate marketing to promote y our e -commerce
business, Launching a successful online business and EC project, Legal, Ethics
and Societal impacts of EC 06
3 Digital Business Support services : ERP as e –business backbone, knowledge
Tope Apps, Information and referral system
Application Development: Building Digital business Applications and
Infrastructure 06
4 Managing E -Business -Managing Knowledge, Management skills for e -business,
Managing Risks in e –business
Security Threats to e -business -Security Overview, Electronic Commerce Threats,
Encryption, Cryptography, Public Key and Private Key Cryptography, Digital
Signatures, Digital Certificates, Security Protocols over Public Networks: HTTP,
SSL, Firewall as Security Control, Public Key Infrastructure (PKI) for Security,
Prominent Cryptographic Applications 06
5 E-Business Strategy -E-business Strategic formulation - Analysis of Company’s
Internal and external environment, Selection of strategy,
E-business strategy into Action, challenges and E -Transition 04

Page 88

University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
(Process of Digital Transformation)
6 Materializing e -business: From Idea to Realization -Business plan preparation
Case Studies and presentations 08

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 at least 6 assignment on complete syllabus 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 examin ation. 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 (fo r 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.

References:

1. A textbook on E -commerce , Er Arunrajan Mishra, Dr W K Sarwade,Neha Publishers &
Distributors, 2011
2. E-commerce from vision to fulfilment, Elias M. Awad, PHI-Restricted, 2002
3. Digital Business and E -Commerce Management, 6th Ed, Dave Chaffey, Pearson, August 2014
4. Introduction to E -business -Management and Strategy, Colin Combe, ELSVIER, 2006
5. Digital Bus iness Concepts and Strategy, Eloise Coupey, 2nd Edition, Pearson
6. Trend and Challenges in Digital Business Innovation, VinocenzoMorabito, Springer
7. Digital Business Discourse Erika Darics, April 2015, Palgrave Macmillan
8. E-Governance -Challenges and Opportunit ies in : Proceedings in 2nd International Conference
theory and practice of Electronic Governance
9. Perspectives the Digital Enterprise –A framework for Transformation, TCS consulting journal
Vol.5
10. Measuring Digital Economy -A new perspective -DOI: 10.1787/9789264221796 -enOECD
Publishing

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Course Code Course Name Credits
ILO2029 Environmental Management 03

Objectives :
1. Understand and identify environmental issues relevant to India and global concerns
2. Learn concepts of ecology
3. Familiarise environment related legislations
Outcomes: Learner will be able to…
1. Understand the concept of environmental management
2. Understand ecosystem and interdependence, food chain etc.
3. Understand and interpret environment related legislations

Module Detailed Contents Hrs
01 Introduction and Definition of Environment: Significance of Environment
Management for contemporary managers, Career opportunities.
Environmental issues relevant to India, Sustainable Development, The Energy
scenario. 10
02 Global Environmental concerns : Global Warming, Acid Rain, Ozone Depletion,
Hazardous Wastes, Endangered life -species, Loss of Biodiversity, Industrial/Man -
made disasters, Atomic/Biomedical hazards, etc. 06
03 Concepts of Ecology: Ecosystems and interdependence between living organisms,
habitats, limiting factors, carrying capacity, food chain, etc. 05
04 Scope of Environment Management, Role & functions of Government as a planning
and regulating agency.
Environment Quality Management and Corporate Environmental Responsibility 10
05 Total Quality Environmental Management, ISO -14000, EMS certification. 05
06 General overview of major legislations like Environment Protection Act, Air (P & CP)
Act, Water (P & CP) Act, Wildlife Protection Act, Forest Act, Factories Act, etc. 03

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.

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
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 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.



REFERENCES:
1. Environmental Management: Principles and Practice, C J Barrow, Routledge Publishers London,
1999
2. A Handbook of Environmental Management Edited by Jon C. Lovett and David G. Ockwell ,
Edward Elgar Publishing
3. Environmental Management, T V Ramachandra and Vijay Kulkarni, TERI Press
4. Indian Standard Environmental Management Systems — Requirements With Guidance For Use,
Bureau Of Indian Standards, February 2005
5. Environmental Management: An Indian Perspective, S N Chary and Vinod Vyasulu, Maclillan
India, 2000
6. Introduction to Environmental Management, Mary K Theodore and Louise Theodore, CRC Press
7. Environ ment and Ecology, Majid Hussain, 3rd Ed. Access Publishing.2015

Page 91

University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Subject
Code Subject Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSL201 Computational
Laboratory II -- -- -- --- 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 Mu mbai.

Page 92

University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.

Subject
Code Subject Name Teaching Scheme
(Contact Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
CSL202 DEC Laboratory -II -- -- -- --- 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 departmental electives
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.

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.

Course
Code
Course Name Teaching Scheme (Contact
Hours) Credits Assigned
Theory Pract Tut Theory Pract Tut Total
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-CS301 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.

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University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.
Guidelines for Dis sertation -I

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 and compile the report in standard format.

Guidelines for Assessment of Dissertation -I
Dissertation -I should be assessed based on following point s
 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.

Page 95

University o f Mumbai, M. E. (Computer Engineering) Rev. 2016.

Course
Code
Course Name Teaching Scheme (Contact
Hours) Credits Assigned
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 Written 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 of Mumbai .