Master of Philosophy in Computer Science (M. Phil CS)

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Oct 22, 2013 (3 years and 5 months ago)

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1





COURS
E

MANUAL




Maste
r
o
f
Philosoph
y
in
Computer Science


(M
.

Phi
l



CS)



















India
n

Institut
e

o
f

Informatio
n

Technolog
y

an
d

Managemen
t
-
Kerala (IIITM
-
K)

IIITMK Building,
Technopark

Trivandrum
-
695 081

www.iiitmk.ac.in












2

Preface



Thi
s
documen
t
de
scribe
s

th
e

cours
e
outlin
e
o
f
Maste
r

o
f

Philosoph
y

i
n

Computer
Science

a
t

the

Indian

Institute

of

Information

Technology

and

Management

-

Kerala
(IIIT
M
-
K).


IIIT
M
-
K is an autonomous institution establ
ished by the Government of Kerala in
2000
w
ith a mission to become a
centre

of excellence in education and research in
Information
Technology
,
Informatics
,
Managemen
t
an
d
allie
d
areas
.
IIIT
M
-
K

emphasizes

quality
educatio
n
t
o
it
s
student
s
throug
h
it
s
uniqu
e
pedagog
y
o
f a
combinatio
n
o
f
classroom
lec
tures
,
pee
r
-
interactions, exposure to real world
issues and application of what is
taught.


The need for the program is to produce skilled postgraduate research professionals
who are highly in dema
nd and at the forefront of information and emerging
technologies. We draw high quality staff and students from diverse disciplines and
backgrounds, and with our highly qualified and highly regarded academic, research
staff


and


general staff. The IIITM
-
K
provides a modern and enjoyable teaching
and research environment in areas of fundamentals of Computer Science,
Information Technology and domain specific application areas in which IT plays a
pivotal role in scientific, technology and commercial systems,

characterised by its
breadth, flexibility, and quality.


1.0

Introduction


Master of Philosophy in Computer Science will be a flagship programme offered
by the Indian Institute of Information Technology and Management
-
Kerala, aims
at high standards in basi
c and applied sciences, technology, management and
information system. The programme focuses on a broad grasp of philosophical
approach in Computer Science and IT, Research Methodology and Trends in
Computer Science and a deep understanding of the area
of specialisation, an
innovative ability to solve new problems, and a capacity to learn continually and
interact with trans
-
disciplinary groups.


The duration of the programme is 1 year and the courses are carefully designed to
attain theoretical, techni
cal and research aspects that enable them to grow into
competent, seasoned professionals.

1.1

Motivation


The skills of logical thinking, problem solving, abstraction and systematic analysis
acquired through a study of Computer Science are highly in demand a
nd also
transferable to other disciplines in today's need. As technology improves and
becomes an integral part of our society, it shapes and defines the way we live in.
The new amendments in Ph.D regulation of CUSAT stated that students with


3

M.Phil/Ph.D
degree will get exemption from NET qualification for taking up
teaching, jobs in Universities and Colleges. In Kerala, no university is offering an
M.Phil in Computer Science, so it's need of the society to provide an M.Phil
programme that allows us t
o cope with the rapid changes in technology that
are constantly occurring. M. Phil scholars in the Computing Science perform
individual research in Computer Science, Information Technology or related areas
under the direct supervision of a leading academic

expert in the field and also
making tie
-
up wth Scienfic R &D institutions and premier national and
international Universities.


1.2

Ai
m

and

Objective





Develop scholars into mature researchers, able to make original scientific
contributions that have both pr
actical significance and a rigorous, elegant
theoretical grounding

that underpins the various areas of Computer Science
and IT.



To impart sound knowledge in Computer Science and interdisciplinary areas
with Science, Technology and Management related to Inf
ormation Systems
and their applications in relevant fields with the latest technologies.



Build a pool of technically and scientifically qualified manpower to build

a
strong scientific community



Motivate and orient youngsters to do research with proper b
aseline.



Develop professionals and teachers with strong analytical and synthesizing
capability with innovative and creative thinking that can instill to student
community to develop a strong Scientific community


2.0

REGULATIONS


2.1

Course Description


Th
e

M
.

P
hi
l
-

CS

i
s

a

on
e
-
year

full

time

programme

and

adopts

a

credit

system.

Students
ear
n
thei
r
degre
e
b
y
completin
g
3
6
credi
t
points
,
spli
t
amon
g
cours
e
work
,
semina
r
an
d a
thesis
.

Th
e

programm
e

i
s

s
o

designe
d

tha
t

student
s

spen
t

thei
r

firs
t

si
x

month
s

earning

a
maximu
m
o
f
18

credit
s ,
before
proceeding to
carry

out

a

research

project

and a

thesis
,

whic
h

ca
n

ear
n

the
m

a

maximu
m

o
f

1
8
credi
t

points.



2.2

Salient

Features


Th
e

propose
d

programm
e

i
n

Computer Science

ha
s a
stron
g
emphasi
s
o
n
tran
s
-

disciplinary.

The
Mphil degree in Computer Science plan to the development of
computer science and engineering, and design skills through continual laboratory


4

access. Its focus on work integrated learning includes research oriented industry
placement in the final year, ens
uring post
-
graduates are fully prepared for a
challenging career in industry, and research and development enterprises.


The discipline major allows significant flexibility and allows you to choose courses
outside the main study area to develop a broader k
nowledge across a number of
areas. Students are provided an opportunity to embark on research projects under
the supervision of academic staff, while undertaking the Mphil program.


2.3

Eligibility


Qualifyin
g

examination/degre
e

fo
r

th
e

admissio
n

fo
r

th
e

M

Phi
l
-

CS

degree

course

is

M.
S
c/M C A/M.Tech

i
n

Computer Science/ Information
Technology/ Electronics/ Computational Sciences/Geoinformatics
or
equivalent having minimum of three papers in CS/IT in the
qualifying examination with at least 60% aggregate mar
ks , or
CGPA of above 6.5 in 10 points,
o
r

equivalen
t

o
n

th
e

abov
e

mentione
d

subjects.



2.4

Admissions


Admissio
n

t
o

th
e

Cours
e

i
s

base
d

o
n

th
e

Institute
Admissio
n

Tes
t

(IAT
)

conducted
b
y

India
n

Institut
e

o
f

Informatio
n

Technolog
y,
an
d

Management
supervised by

CUSAT


and/or

GATE/NET/JRF qualifying examination
score, foll owed by a techni cal interview
.


2.5

Assessment

and

Grading

System


Followin
g

Grad
e

Syste
m

o
n

Te
n



Poin
t

Scal
e

wil
l

b
e

adopted.


Rang
e

o
f

Mark
s

%

Grade
s

Weightage

(G)

9
0

an
d

above

S
-
Outstanding

1
0

80
-
90

A
-

Excellent

9

70
-
80

B



ser
y

dood

8


J


C



dood

T


J


a


pati獦a捴ory

S

Belo
w



c
J
cailed

M


X
-
Y

mean
s

tha
t

X

i
s

include
d

an
d

Y

i
s

excluded.


Overall

Grade

Point

Average

(GPA)

calculated

as

follows

will

indicate

performance

after
eac
h

s
emester:


GP
A

=

(
C
1
G
1
+C
2
G
2
+
C
3
G
3
+…..
C
n

G
n
)
/

(
C
1
+
C
2
+…
C
n
)


Wher
e

C

refer
s

t
o

th
e

credi
t

valu
e

o
f

th
e

cours
e

an
d

G

i
s

th
e

Grad
e

weigh
t

age
.

CGP
A

wil
l

b
e

calculate
d

base
d

o
n

th
e

abov
e

formula.



5


2.6

Classification

for

the

Degree

will

be

given

as

follows:


Classifica
tio
n

CGPA


Firs
t

Clas
s

wit
h

Distinctio
n

8

an
d above

Firs
t

Clas
s

6.
5

an
d

a
bove

Secon
d

Clas
s

6

an
d

above
Fai
l

belo
w

6


2.7

Number of seats


I
t

i
s

propose
d

t
o

limi
t

th
e

numbe
r

o
f

seat
s

t
o

15.


2.8

Mode of Evaluation


A

studen
t

woul
d

b
e

considere
d

t
o

hav
e

progresse
d

s
atisfacto
r
il
y

a
t

th
e

en
d

o
f

a
semeste
r

i
f

he/sh
e

ha
s

a

minimum

of

75%

attendance.


There will be internal and external evaluation. In the internal evaluation, studen
t

shal
l

b
e

evaluated

continuously

throughou
t

th
e

semeste
r

an
d

marks
shall

be

awarded

o
n

the

basis

of

tests

and

assignments

as

detailed

below:


1
0

mark
s

ar
e

awarde
d

base
d

o
n

assignment
s

give
n

b
y

th
e

teacher.

10 marks are awarded for Seminars/Miniproject/Case

study/review of
paper/viva

Ther
e

shal
l

b
e

minimum of
tw
o

clas
s

test
s

an
d

on
e

en
d

sem
este
r

examination.

Th
e

clas
s

test
s

carr
y

a

maximu
m

o
f

2
0

mark
s

each.

Th
e

en
d

semeste
r

examinatio
n

i
s

fo
r

a

maximu
m

of

6
0

marks

and

carries
question
s

fro
m

entir
e

syllab
i

o
f

th
e

course.


The

question

papers

for

the

end

semester

examination

will

b
e

prepared

by
the
teacher
who

taught

the

course
. The teacher will prepare three sets of question

papers.

The

HOD/Director

will

s
elec
t

an
y

on
e

o
f

th
e

questio
n

pape
r

for
th
e

En
d

Semeste
r

Examination.


The

answer

papers

will

be

evaluated

by

the

teacher

who

t
aught

the

pape
r
.
Befor
e
finalising
th
e
resul
t
mark
s
wil
l
b
e
show
n
t
o
students
.

T h e s i s
wi l l
be
evaluate
d

b
y

interna
l

a
s

wel
l

a
s

externa
l

examiners.


The external evaluation will be done by CUSAT.

The evaluation of thesis/Project
report will be d
one externally by CUSAT and the viva will be done in IIITM
-
K with
the examiner nominated by CUSAT.


Ther
e
ca
n
b
e a
supplementar
y
examinatio
n
fo
r
eac
h
subject
,
conducte
d
withi
n a
wee
k
o
f
th
e
las
t
examinatio
n
o
f
th
e
en
d
semeste
r
examination
.
Thi
s
wil
l
b
e
ba
sed
o
n
th
e
recommendation
s
o
f
th
e Institute Academic
Council
,
o
n
receivin
g
specific
appl
i
catio
n
fro
m
student
s
an
d
base
d
o
n
th
e
meri
t
o
f
th
e
case
.



6


Th
e

pass

minimum

is

50%

mark
s of the total of 100 marks (40 marks
internal + 60 marks External
) ,

with a se
parate minimum of 45% for the
external.


I
f

th
e

candidat
e

fail
s

t
o

secur
e

50% h
e/sh
e

i
s

faile
d

i
n

th
e

subjec
t
an
d
ha
s
t
o
repea
t
th
e
subjec
t
i
n
th
e
nex
t
possible
chance
A

pas
s

i
n

th
e

cours
e

wil
l

entitl
e

th
e

studen
t

t
o

acquir
e

th
e

credi
t

value
allotte
d

fo
r

t
ha
t

particula
r

course
.

Detail
s

o
f

th
e

credi
t

value
s

ar
e

give
n

i
n

the
course structure. Student wi
l
l

be

promoted

to

the

second

semester

only

if

he/she
hav
e

complete
d

al
l

th
e

paper
s

i
n

th
e

firs
t

semester.




2.9

Review

of

Question

Papers

and

Valuation

of

Answer

Books


A
t

th
e

en
d

o
f

eac
h

semester
,

questio
n

paper
s

se
t

fo
r

class tests and end
semester
examinatio
n
an
d
th
e
schem
e
o
f
evaluatio
n
o
f
answe
r
book
s
b
e
reviewe
d
b
y
th
e
DC
.
The
revie
w

repor
t

ma
y

b
e

place
d

i
n

th
e

Boar
d

o
f

Studie
s

fo
r

scrutin
y

i
f

necessary.


2.10

Gri
evance Cell


The

DC

will

act

as

grievance

cell

where

co
m
plaints from students on the conduct
of class
tests
,

semeste
r

examinatio
n

an
d

valuatio
n

methodolog
y

ca
n

b
e

examined
.

Th
e

student shal
l
mak
e
suc
h
complaint
s
withi
n a
wee
k
afte
r
th
e
examinatio
n
t
o
th
e
H
OD/Directo
r
in writin
g

fo
r

scrutin
y

b
y

th
e

grievanc
e

ce
l
l.


2.11

Evaluation

of

the

Teachers

by

the

students


For

effectiveness

and

improvement

in

the

delivery

of

the

course,

there

should

be
student
evaluation

of

teacher
s

.

A

forma
t

fo
r

evaluatio
n

ma
y

b
e

prepare
d

b
y

th
e

DC
.

Format
give
n

i
n

th
e

NAA
C

Guid
e

line
s

ca
n

b
e

use
d

fo
r

thi
s

purpose
.

Th
e

fee
d
back
s

hav
e

t
o

be
confidentia
l
an
d
ma
y
b
e
discusse
d
wit
h
th
e
respectiv
e
teacher
s
b
y
th
e
HOD/Director
,
so
tha
t

he/sh
e

ca
n

modif
y

th
e

teachin
g

an
d

learnin
g

methodolog
y

fol
lowe
d

b
y

him/her.


2.12

E
-
Learning

Format

in

Teaching

and

Learning


IIIT
M
-
K

campu
s

ha
s

1

G
B

connectivit
y

an
d

uses web based e
-
learning and
content management system.
.
Free software Moodle is used an e
-
learning
platform, teachers and students are encouraged to
use online teaching and
learning also.


2.13

Course Coordination Committee


Courses

in

each

semester

have

to

be

coordinated

by

a

Coordination


Committee
consisting

of

the

Director/

Head

of

Departments

/

School,

Course

coordinator

and all

the

teachers

handling

the

courses.

The

commi
ttee

should

meet

at

least

once

in

a
mont
h

t
o

monito
r

th
e

courses
.

A

student

representative

of

the

class

may

be

invited

as
an
d

whe
n

necessar
y

t
o

provid
e

feedbac
k

fro
m

th
e



7

sid
e

o
f

th
e

students.


2.14

Revision of Regulation and Cu
rriculum


The

University

ma
y
,
fro
m
tim
e
t
o
time
,
amen
d
o
r
chang
e
th
e
Regulations
,
Scheme
s
of
Examinations and Syllabus. In case of students already undergoing the course,
the change will

take

effective

from

the

beginning

of

the

following

academic

year

afte
r

the

changes
ar
e

introduce
d

and shall cover the part of the course that
remains to be completed.


3.0

M.

Phil

Course

Structure

and

Credits




Course



Subject



L

hr/wk


Credit

Points



Internal
Exam



External
Exam



Total


SEMESTER 1

CSMPh3101

Research

Me
thodolog
y
*

5

4

40

60

100


CSMPH3102

Paper 1
(Elective)

5

4

40

60

100


CSMPh3103

Paper 2
(Elective)

5

4

40

60

100


CSMPh3104

Mini Project

--

6

150

--


Tota
l

fo
r

I

semester

15

18

270

180

450


SEMESTER 2


CSMPh3201

Project

Dissertation/viva

-

18

150

150

3
00











Tota
l

fo
r

II

semester

-

18

150

150

300











Tota
l

for
the
course


36

420

330

750




ELECTIVES


CSMPh3101 Advanced Pattern Recognition

CSMPh3102 Networking and Information Security

CSMPh3103
Magnetic Resonance Imaging and Signal Proce
ssing

CSMPh3104
Circuits and Systems

CSMPh3105 Data Structures and Programming

CSMPh3106 Scientific Computing



8

CSMPh3107 High Performance Computing

CSMPh3108 Digital Signal Processing

CSMPh3109 Object Oriented Software Engineering

CSMPh3110 Soft Computing

CSMPh3111 Computational Linguistics

CSMPh3112 Embedded Systems

CSMPh3113 Data Analytics

CSMPh3114 Digital Image Processing

CSMPh3115 Internet of Things

CSMPh3116 e
-
Governance and IT Management

CSMPh311
7

Kernel Design





PROGRAMME DETAILS


CSMPh310
1

Advanced Pattern Recognition






Credits
:

4

Module
-
1 Mathematical Foundations

Significance testing, Paired t Tests, Wilcoxon signed ranks test, Friedman test,

Module
-
2 Nearest Neighbour

K
-
Nearest neighbour, metric learning techniques, onlin
e metric learning

Module
-
3 Support Vector Machines

One class SVM, Multi
-
class SVM, Cross
-
validation and Grid
-
search, linear versus
RBF Kernel, Implementation in C

Module
-
4 Neural Networks

Neural networks as classifiers, wavelet neural networks, neural netw
orks in image
compression

Module
-
5 HTM

Bayes predictive nets, HTM models, object recognition with HTM

Text Book

1.

V. Vapnik.
The Nature of Statistical Learning Theory
. Springer
-
Verlag, New
York, NY, 1995.

2.

Shakhnarovish, Darrell, and Indyk, ed (2005).

Nearest
-
Neighbor Methods in
Learning and Vision
.

MIT Press
.

ISBN

0
-
262
-
19547
-
X
.



9

3.

Jeff Hawkins and Dileep George,
Hierarchical Temporal Memory
-

Concepts,
Theory, and Terminology
,

Numenta Inc.
, 2006
-
05
-
17

4.

Bernhard Schlkopf

,

Alexander J. Smola
,

Learning with Kernels: Support
Vector Machines, Regularization, Optimization, and Beyond (Adaptive
Computation and Machine Learning)

ISBN
-
13:

978
-
0262194754

5.

Simon Haykin
,

Neural Networks: A Comprehensive Foundation

(2nd
Editio
n)
,

ISBN
-
10:

0132733501

| ISBN
-
13:

978
-
0132733502

References

1.

Randall Matignon,
Data Mining Using SAS Enterprise Miner
, isbn
0470149019,
Wiley
-
Interscience; 1 edition (August 3, 2007)

2.

Colleen Mc Cue,
Data Mining and Predictive Analysis: Intelligence Gathering

and Crime Analysis
, isbn 0750677961,
Butterworth
-
Heinemann; 1 edition
(May 1, 2007)


CSMPh3102 Cryptography And Network Security



Credits
:

4


MODULE 1

Classical Cryptography
,

Shift Ciphers, Substitution Ciphers, Affine Ciphers,
Vigenere Ciph
er, Hill Cipher, Permutation Ciphers, Vernam's One
-
time Pad,
Synchronous and Asynchronous Stream Ciphers, Linear Feedback Shift
Registers, Stream Ciphers Based on LFSR, RC4

MODULE 2

Block Ciphers
,

Modes of Operation,
Data Encryption Standard (DES), 3DES,
A
dvanced Encryption Standard (AES), Linear Cryptanalysis, Differential
Cryptanalysis

MODULE 3

RSA Encryption, Rabin Encryption, ElGamal Encryption, Diffie
-
Hellman Key
Exchange. RSA Signature, Rabin Signature, ElGamal Signature, DSA.

MODULE 4

Cryptographic

Hash Functions, Merkle

Damgård Construction, Message
Authentications Codes (MAC), Security of Hash Functions, MD5, SHA 1.

MODULE 5



10

IP Security Overview, Architecture, Authentication Header, Encapsulating Security
Payload, Key Management, Web Security Cons
iderations, Secure Socket Layer
and Transport Layer Security, Secure Electronic Transactions.


Text Books:

1.

William Stallings
,
Cryptography and Network Security Principles and
Practice
, Fourth Edition, Prentice
-
hall, India.

2.

Douglas R. Stinson,
Cryptography
Theory and Practice
,

Chapman &
Hall, 2
nd

Edition.



References:

1.

H. Deffs & H. Knebl

,
Introduction to Cryptography
, Springer


Verlag,
2002.

2.

Alfred J. Menezes, Paul C. van Oorschot and Scott A. Vanstone
,
Handbook of Applied Cryptography
, CRC Press, 1996.

3.

W
illiam Stallings
,
Cryptography and Network Security Principles and
Practice
, Third Edition, Prentice
-
hall India, 2003.

4.

Neal Koblitz
,
A Course in Number Theory and Cryptography
, Springer
International Students' Edition, 2nd edition, 1994.


CSMPh3103

Magneti
c Resonance Imaging and Signal Processing
Credits
:

4

Module
-
1 Mathematical Foundations

Commomnly used Functions
-
Convolution
-
The Fourier Transform
-
Radon
Transform
-
Signal Generation and Detection in MRI


MRI Signal characteristics

Module
-
2 Signal Localizat
ion

Slice
-
Selection
-
Spatial Information Encoding
-
Basic Imaging Methods
-
K
-
space
Sampling

Module
-
3 Image Reconstruction

General Issues
-
Fourier Reconstruction
-
Reconstruction using Radon Transform
-
Saturation Recovery Sequence
-
Inversion Recovery Sequence
-
Spin E
cho imaging
-
Gradient echo imaging



11

Module
-
4 Fast Scan Imaging

Fast
-
spin echo imaging
-
Fast Gradient echo imaging
-
Echo
-
Planar Imaging

Module
-
5 Constrained Reconstruction

Half Fourier Reconstruction
-
Extrapolation based reconstruction
-
Parametric
Reconstruction

Text Book


1. Z
-
P Liang, PC. Lauterbur
, Principles of MRI: A signal Processing Perspective

,
IEEE Press, NY 2000.

Reference Book


1. EM. Haacke, RW. Brown, MR. Thompson, R.Venkatesan,
Magnetic Resonance
Imaging: Physical Principles and Sequence Design
, Joh
n Wiley & Sons, NY 1999.


CSMPh3104

CIRCUITS AND SYSTEMS




Credits
:

4

Module
-
1 Basic Circuits

RLC filters, band pass filters, chaos generators

Module
-
2 MOSFET Process

MOSFET device structure, RCA Cleaning, Lithography, Oxidation, Metallisation

Module
-
3 MO
SFET Devices

Device modelling, PN Junctions, CV characterisations, Resistivity measurements,
Energy band diagrams

Module
-
4 Analog Circuits

OpAmp circuits, PLL circuits, Amplifiers, waveform generators, simulations in Spice

Module
-
5 Digital Circuits

Logic G
ates, CMOS, NMOS, Domino logic, ALU design

Text Book


1.

R. Jacob Baker


,
CMOS: Mixed
-
Signal Circuit Design
, 2nd Edition,
ISBN:
978
-
0
-
470
-
29026
-
2



12

2.

Paul Horowitz

and

Winfield Hill

(1989),

The Art of Electronics

(Second ed.),
Cambridge University Press,

ISBN

978
0521370950


References


1.

Thomas L. Floyd and David M. Buchla,
Electronics and Circuit Analysis
Study Guide: Signal Transforms, Fourier, Laplace & Z transform, Transfer
function, Electronic components, Analog & Digital Circuits
, Prentice Hall; 8
edition (Jul
y 3, 2009)

2.

Paul Scherz,
Practical Electronics for Inventors 2/E
, McGraw
-
Hill/TAB
Electronics; 2 edition (September 1, 2006)



CSMPh3105

Data Structures and Programming




Credits: 4


Module 1

Introduction to ADT and Algorithms: Principles of DSA, ADT, comp
utational
problem, algorithm notion, time complexity, space complexity, asymptotic analysis,
analysis of algorithms, design of algorithms, data, abstract data type, procedural
abstraction, worst case complexity, Big
-
Oh notation, incremental design.

Module
2

Stack and Queues: Introduction to stack, basic operations, implementation using
array and linked list, computational problems relating to stack, parenthesis
matching, expression representation using Polish and reverse Polish notations,
evaluation of expr
ession using stack, introduction to queues, basic operations,
implementation

Module 3

Lists and Linked List: Lists in ADT, List implementation in Stack and Queue, Linked
list, Insert, delete operations, doubly linked list, implementation, ADT and
applicati
ons, INFIX and POSTFIX evaluations.

Module 4

Recursion and Heap: Closed form, recursive form, problem solving, Fibonacci
series, Towers of Hanoi, celebrity problem (with and without recursion, Efficiency of
Recursion Algorithm, eight Queens, Heap: Introduc
tion, max heap, min heap,
representation, complexity.


Module 5



13

Trees, Graphs and Hashing: Binary tree, traversal in a tree, level order traversal,
ADT dictionary, dictionary implementation, balanced binary search tree, binary
search tree, extended binary
tree, insertion, deletion, AVL trees, Fibonacci tree, B
-
tree, red black tree.

Graph: Weighted graph, spanning tree, greedy method, Krushkals algorithm,
implementation, equivalence relation, parent chasing, traversal, DFS and BFS,
Hashing: open address hash
ing, double hashing, chaining, Different search and
sort algorithms: Bubble, quick sort, merge sort
-
divide and conquer method, Heap
sort.


Text Books

1.

A.D Aho, J. E. Hopcroft and J. D. Ullman,
Data Structures and Algorithms
,
Pearson education Asia, 1983.

2.

Y.

Langsam, M. J. Augenstein and A. M. Tenenbaum,
Data Structures using
C
, Pearson Education Asia, 2004

References

1.

T.H. Cormen, C.E.Leiserson, R.L.Riverst and C. Stien,
Introduction to
algorithms
, Second Edition. MIT Press and McGraw
-
Hill, 2001.

2.

Adam Drozdek
,
Data Structures and Algorithms in Java
, Published by
Brooks/Cole, 2000


CSMPh3106 Scientific Computing






Credits
:

4


Module 1

Introduction to scientific Computing, Approximations in Scientific Computing,
Computer Arithmetic, Linear Systems, Solvi
ng Linear systems, Special types of
linear systems, Linear Least Squares, Problem transformations, Orthogonalization
methods, Singular Value Decomposition, Comparison of methods

Module 2

Eiegen Value Problems, Computing Eiegen Values and Eiegen Vectors,
Ge
neralized Eigen Value Problem

Module 3

Non
-
linear Equations, Non
-
linear Equations in one dimension, Systems of Non
-
linear equations, Optimization problems, Unconstrained Optimizations, Non
-
linear
least squares, Interpolation, Polynomial interpolation

Modul
e 4



14

Numerical Integration and differentiation, Numerical quadrature, Ordinary
differential equations, Numerical Solutions to Ordinary Differential Equations,
Boundary problem for ODEs, Partial differential equations

Module 5

Fast Fourier Transform, Trigono
metric Interpolation, FFT Algorithm, Applications of
DFT, Wavelets, Random numbers and simulation, stochastic simulation,
randomness and random numbers, random number generators



Textbooks

1.

M. T. Heath,
Scientific Computing,

The McGraw
-
Hill Companies, Inc.
; 2nd
edition, 2002

2.

R. Hamming,
Numerical Methods for Scientists and Engineers
, Dover
Publications; 2 edition, 1987


References

1.

Gregoire Allaire and Alan Craig,
Numerical Analysis and Optimization: An
Introduction to Mathematical Modeling and Numerical Sim
ulation (Numerical
Mathematics and Scientific Computation)
, Oxford University Press, USA,
2007



CSMPh3107 High Performance Computing






Credits
:

4


Module 1

Parallel Processing and Supercomputing : Supercomputer Architecture, Vector
Machin
es, Parallel Processors, Data Parallel Processors, Single
-
Instruction
-
Multiple
-
Data. Multiple
-
Instruction
-
Multiple
-
Data, Pipelining. Vectorization.

Module 2

Parallelization of Algorithms : Parallel linear algebra routines, Loop optimizations.
Implementati
on. Principal of Locality, Caches and Buffers. Massively Data Parallel
Algorithms, Array notation, Fortran90 and HPC Fortran, Parallel and Vector C
Code, Layout, Align, Replicate, Masking, Shifting, Spreading, Broadcasting, Forall
Loops, divide
-
and
-
Conquer

Algorithms, Adaptive Quadrature, Correct Termination.

Module 3



15

Algorithms and optimization

:
Graph algorithms, combinatorial


scientific
computing, Monte
-
Carlo simulations, linear, nonlinear and discrete optimization,

Module 4

Grid Computing: Types of

Computational Grids, Gid requirements of end users,
application, tool and grid developers, and system managers, Cloud Computing.

Module 5

Computing Platforms Operating Systems and Network Interfaces, Compilers,
Languages and Libraries for the Grid, Gri
d Scheduling, Resource Management,
Resource Brokers, Resource Reservations, Security, Accounting and Assurance


Text Books

1.

J. M. Ortega,
Introduction to Parallel and Vector Solution of Linear Systems
,
Springer; 1 edition (April 30, 1988)

2.

J. J. Dongarra,
I. B. Duff, D. C. Sorensen and H. A. van der Vorst,
Solving
Linear Systems on Vector and Shared Memory Computers
, SIAM, 1991.


Reference

1.

K. Hwang,
Advanced Computer Architecture: Parallelism, Scalability,
Programmability
, McGraw
-
Hill, 1993.

2.

Foster, I.,
D
esigning and Building Parallel Programs
. Addison
-
Wesley, 1995.

3.

Hennessy, J.L. and Patterson, D.A.,
Computer Architecture A Quantitative
Approach
. Morgan Kaufmann, 1996.


CSMPh3108 Digital Signal Processing




Credits
:

4


Module 1

Introdu
ction, simple manipulations of discrete
-
time signals, analog
-
to
-
digital
conversion of signals. Fourier Analysis of Periodic and Aperiodic Continuous
-
Time
Signals and Systems: trigonometric Fourier series, complex form of Fourier series
Parsevals identity f
or Fourier series, power spectrum of a periodic function, Fourier
transform, Fourier transform of some important signals, power and energy signals

Module 2

Applications of Laplace Transform to System Analysis: Introduction, definition of
Laplace transform,

region of convergence (ROC), initial and final value theorems,
convolution integral, table of Laplace transforms, partial fraction expansions,


16

network transfer function, s
-
plane poles and zeros, Laplace transform of periodic
functions, and application of
Laplace transformation in analyzing networks.

Module 3

z
-
transforms and Linear Time Invariant Systems: Introduction, definition of the z
-
transform, properties of the z
-
transform, evaluation of the inverse z
-
transform,
properties of a DSP system, difference

equation and its relationship with system
function, impulse response and frequency response Discrete and Fast Fourier
Transforms: Discrete convolution, discrete time Fourier transform (DTFT), fast
Fourier transform (FFT), computing an inverse DFT by doing

a direct DFT,
composite
-
radix FFT, fast convolution and correlation

Module 4

Finite Impulse Response (FIR) Filters: Introduction, magnitude response and
phase response of digital filters, frequency response of linear phase FIR filters,
design techniques f
or FIR filters and design of optimal linear phase FIR filters

Module 5

Infinite Impulse Response (IIR) Filters: Introduction, IIR filter design by
approximation of derivatives, IIR filter design by impulse invariant method, IIR filter
design by bilinear t
ransformation, butterworth filters, Chebyshev filters, inverse
Chebyshev filters, elliptic filters, frequency transformation, Realization of Digital
Linear Systems: Introduction, basic realization block diagram and the signal
-
flow
graph, basic structures f
or IIR systems, basic structures for FIR systems

Textbooks

1.

S. Salivahanan, A. Vallvaraj and C. Gnanapriya,
Digital Signal Processing,

Tata McGraw
-
Hill, New Delhi, 2000

2.

Sanjit K. Mitra,
Digital Signal Processing, 3/e
, Tata McGraw
-
Hill, New Delhi,
2006

Refer
ences

1.

A.V. Oppenheim and R.W. Schaffer,
Digital Signal Processing
, Prentice hall,
NJ, 1975



CSMPh3109 Object Oriented Software Engineering



Credits: 4


Module 1


Introduction to Software Engineering and Models: Different Software Life cycle
Models

-

Software Measurements: Software Metrics
-

Software costing and
estimation
-

SCM Processes
-

Version Control
-

Change Management
-
Risk


17

Managemen
-

Software Testing and Quality
-

Quality Assurance
-

Quality control
Quality

Module 2

Software Project Managem
ent and Process Frameworks: Project Management
Processes
-

Project Estimations
-

Project Planning and Tracking Scheduling
-

Scope Management
-

Cost Management, Integrated Change Management
-

Introduction to CMM
-

Five levels of CMM
-

Introduction to six si
gma


Module 3

Formal Methods in Software Engineering: Basic Concept, Mathematical
preliminaries, Applying Mathematical Notation for Formal specification Languages
Object constraint language (OCL),

Verification and Formal Methods, model
checking. Verificati
on and Validation

Planning verification and validation, software
Inspections, Automated static analysis.

Module 4

Object Orientation: Object Oriented Modeling, Introduction to UML, Features of
Object Orientation, Relationships, Best Practices in Softwa
re Engineering,
Iterative model, Unified Modelling Language, Use case Analysis, Interaction
Diagrams, Sequence and Collaboration Diagrams, Activity Diagrams, State
Chart Diagrams, Class Diagrams

Module 5


Architectural analysis: 4+1 view model,

Patterns and Design, Layered
Approach, Architectural Mechanism
-
Design elements
-
Runtime Architecture:
Concurrency Mechanism, Identify Process and Threads, Distribution of model
Elements, Distribution Patterns, Three Tyre Architecture, Web, Peer
-
to
-
Peer,
Network Configuration
-

Deployment: Modeling Client Server, Distributed Systems

Text Books

1.

Pressman R.S,
Software Engineering: A Practitioner’s Approach

(6
th

Edition), McGraw Hill, 2005

2.

Steve Schach ,
Classical and Object Oriented Software Engine
ering
(6
th

Edition), McGrawHill International, 2005

3.

G Booch, J Rumbaugh, I Jacobson
The Unified Modeling Language User
Guide
, Addison
-
Wesley object technology series, 2001

Reference



18

1.

W Boggs, M. Boggs
Mastering UML with Rational rose
, New York, Sybex
Inc.,

1999

2.

A Bahrami,
Object Oriented Software Development Using UML,

Mc GrawHill
International Edition, 1999



CSMPh3110 Soft Computing







Credits
:

4


Module 1

Introduction: Introduction to soft computing, introduction to biological and artificial
neur
al networks, introduction to fuzzy sets and fuzzy logic systems


Module 2

Artificial Neural Networks and Applications: Different artificial neural network
models, learning in artificial neural networks, neural network applications in control
systems

Module

3

Fuzzy Systems and Applications: Fuzzy sets, fuzzy reasoning, fuzzy inference
systems, fuzzy control, fuzzy clustering, applications of fuzzy systems

Module 4

Neuro
-
fuzzy systems: Neuro
-
fuzzy modeling, neuro
-
fuzzy control, Genetic
algorithms: Simple GA,
crossover and mutation, genetic algorithms in search and
optimization, Introduction to Ant Colony Optimization method and Swam
Intelligence

Module 5

Applications of soft computing: Pattern recognitions, image processing, biological
sequence alignment and d
rug design, robotics and sensors, information retrieval
systems, share market analysis, natural language processing

Text Books

1.

M. Friedman and A. Kandal,
Introduction to Pattern Recognition Statistical
,
Structural, Neural and Fuzzy Logic Approaches, Worl
d Scientific, 2005.

2.

Timothy J. Ross,
Fuzzy Logic with Engineering Applications
, McGraw Hill,
1997.



19

3.

J.S.R. Jang, C.T. Sun, E. Mizutani,
Neuro
-
Fuzzy and Soft Computing: A
Computational Approach to Learning and Machine Intelligence
, Prentice
Hall, 1996.

Re
ferences

1.

Melanie Mitchell,
An Introduction to Genetic Algorithms
, Prentice Hall of
India, 2004.

2.

David E. Goldberg,
Genetic Algorithms in Search, Optimization and Machine
Learning
, Addison
-
Wesley Professional, 1989.



CSMPh3111 Computational Linguistics





Credits: 4


Module 1

Introduction to Computational Linguistics and Grammar
: What is
Computational Linguistics? Interdisciplinary relevance: Formal Linguistics, Psycho
-
linguistics, Cognitive Science, Chomsky Hierarchy,
Initial Systems:

Turing Test,
Dialog systems: ELIZA. Lexical Functional Grammar (LFG), Head
-
Driven Phrase
Structure Grammar (HPSG). Context
-
Free grammars (CFGs), Descriptive
Grammar of Malayalam.

Module 2

Statistics:

Probability, Joint and Conditional Probability,
Bayes rule
, Regressi
on,
Graph theory.
Machine Learning
: Supervised, Unsupervised and Semi
-
supervised
learning. Decision trees (C4.5), Inductive logic programming, Naïve Bayesian
Classifier, Hidden Markov Model, Singular Value Decomposition (SVD), Support
Vector Machine(SVM)
, Conditional Random Fields(CRFs).

Module 3

Computational Corpus Linguistics
: Why corpus linguistics? What is a corpus?
Different Corpus types, Corpora Development, World Wide Web as a corpus,
British National Corpus, Speech Corpora, Multimedia corpora, P
arallel Corpus,
Corpus collection and design,
Font and Encoding:

Font design and development,
Encoding scheme , Character encoding and decoding, UNICODE (utf8) and ASCII,
ISCII
Corpus
Annotation:
Tagging, Parsing, Treebanks, Co
rpus Tools:
Dictionaries ,
Thesaurus creation,
Tokenization, Concordance, Stemmer.
Quantitative linguistics:
Quantitative data analysis, Collocations and idioms, Text
types and Genre.

Module 4

Language Modeling:
Language models and their role in Text and Speech
processing. Differ
ent types of Language modeling, Markov models, N
-
gram


20

models, Entropy, Relative entropy, Cross entropy, Mutual information, Statistical
estimation and smoothing for language models.

Module 5

Text Analytics:
Statistical Machine Translation (SMT), Alignment

Models and
Expectation Maximization (EM), EM and its use in statistical MT alignment models.
Statistical phrase based systems and syntax in SMT. Context
-
Free Grammars
(CFGs) Parsing, Top
-
down and bottom
-
up parsing, empty constituents, left
recursion, Prob
abilistic CFGs Parsing, Dependency Parsing, Modern Statistical
Parsers :

Charniak Parser, The Stanford Parser,
Malt Parser.

Document
Clustering, Text Similarity, Information Extraction (IE) and Named Entity
Recognition (NER), Coreference Resolution, Stati
stical and Rule
-
based methods.
Ranking Algorithms, Query Modification and Effectiveness, Representation of
Documents, IR Models
-
Boolean and Vector Space Models.
File Structures:
Inverted Files, Signature Files. Term and Query Operations: Lexical Analysis
and
Stop lists,
Precision, Recall and F
-
score: Different Evaluation metrics:
BLEU, B
-
CUBED, IR Evaluation: Relevance Judgment, Map Score. GATE , WEKA, CRF++,
Moses

Text Book

1.

Daniel Jurafsky and James H. Martin: 2000
,
Speech and Language
Processing: An Intr
oduction to Natural Language Processing, Computational
Linguistics, and Speech Recognition
. Prentice
-
Hall.

2.

Christopher Manning and Hinrich Schütze: 1999
,
Foundations of Statistical
Natural Language Processing
. MIT Press. Cambridge, MA.

3.

Charniak, Eugene.

1993.
Statistical Language Learning
. The MIT

Press.

References

1.

Jeffrey D Ullman, Rajeev Motwani and John E Hopcroft : 2000,
Introduction
to Automata Theory, Languages, and Computation

(2nd Edition)
,

Addison
Wesley.

2.

Carl Jesse Pollard
,
Ivan A. Sag
: 1994,
Head
-
Driven Phrase Structure
Grammar
, University of Chicago Press.


CSMPh3112 Embedded Systems






Credits
:

4


Module 1



21

Embedded System Architecture: Instruction set architecture, CISC and RISC
instruction set architecture, basic embedded processor,

microcontroller
architecture, CISC examples, 8051, RISC example, ARM, DSP processors,
Harvard architecture, PIC, memory system architecture, caches

Module 2

Memory Management: virtual memory, memory management, unit and address
translation, I/O sub
-
system
, busy
-
wait I/O, DMA, interrupt driven I/O, co
-
processors
and hardware accelerators, processor performance enhancement, pipelining,
super
-
scalar execution. Designing Embedded Computing Platform: Using CPU
bus, bus organization, memory devices and their cha
racteristics, RAM, ROM,
UVROM, EEPROM, ash memory, DRAM, I/O devices, timers and counters,
watchdog timers, interrupt controllers, A/D and D/A converters, displays,
keyboards, component interfacing, memory interfacing, I/O device interfacing


Module 3

Inte
l atom based embedded system,

Embedded platform architecture, Intel
embedded processor architecture, Embedded platform boot sequence, Operating
system overview, embedded linux

Module 4

Power optimisation, Embedded graphics and multimedia acceleration, Digi
tal signal
processing using general purpose processors, Network connectivity, Application
framework: Andriod and Qt, SMP, AMP and Virtualisation

Module 5

Developing an embedded system: Intel Atom E6XX, multi
-
radio communications
design, multimedia design,
Platform debug, performance tuning


Text Books

1.

Jonathan W. Volvano,
Embedded Microcomputer Systems: Real
-
Time
Interfacing
, 2nd edition, CENGAGE
-
Engineering, 2006.

2.

Muhammed Ali Mazidi, Janice Mazidi and Rolin McKinlay,
8051
Microcontroller and Embedded Syst
ems
, 2nd edition, Prentice Hall, 2005.

3.

Peter Barry, Patrick Crowley,
Modern Embedded Computing: Designing
Connected, Pervasive, Media
-

Rich Systems
, Morgan Kaufmann; 1 edition
(February 10, 2012)


References



22

1.

Kenneth J. Ayala,
8051 Microcontroller
, 3rd edi
tion, Thomson, 2005.

2.

Lori Matassa, Max Domeika,
Break Away with Intel Atom Processors: A
Guide to Architecture Migration
, Intel Press (December 16, 2010)



CSMPh3113 Data Analytics ‘







Credits
:

4


Module 1: Data Exploration


Process flow, Explori
ng the problem space and solution space, mining data, types
of data models, active and passive models, explanatory and predictive models,
static and continuously learning models


Module 2:Data Preparation


Prepare, Survey and model the data, modelling with

decision trees, neural network
and evolution programs, missing data, stages of data preparation, data
characterization, set assembly


Module 3:Sampling Study


Sampling, confidence, and variability. Variability of numerical and alpha variables,
measuring c
onfidence, confidence of capturing variability, problems of taking
samples using variability.


Module 4:Nonnumerical Variables


Alphas and remapping, state space, joint distribution tables,dimensionality,
practical problem simulations in R or weka or scila
b.


Module 5:Normalization Techniques and Variable Processing


Normalizing variable ranges, redistribution of values, retaining and replacing
missing value information, series data modelling and repairing, sparse variables,
issues with high dimensionality,

neural net simulations in scilab or R


Text Book


1. Dorian Pyle, Data Preparation for Data Mining (The Morgan Kaufmann Series in
Data Management Systems), 1999, Morgan Kaufmann; 1 edition


Reference


1. Ian H. Witten, Eibe Frank, Mark A. Hall , Dat
a Mining: Practical Machine
Learning Tools and Techniques, Third Edition (The Morgan Kaufmann Series in
Data Management Systems), Morgan Kaufmann; 3 edition (January 20, 2011)



CSMPh3114 Digital Image Processing





Credits
:

4



23


Module 1

Fundam
entals of Image Processing, Elements of visual perception, Steps in Image
Processing Systems, Image Acquisition, Sampling and Quantization, Pixel
Relationships, Color Fundamentals and Modules, File Formats

Module 2

Image Enhancement and Restoration, Spatia
l Domain Gray Level Transformations,
Histogram Processing, Spatial Filtering, Smoothing and Sharpening, Frequency
Domain, Filtering in Frequency Domain, DFT, FFT, DCT, Smoothing and
Sharpening Filters, Homomorphic Filtering, Noise Models, Constrained and
U
nconstrained Restoration Models



Module 3

Image Segmentation and Feature Analysis, Detection of Discontinuities, Edge
Operators, Edge Linking and Boundary Detection, Thresholding, Region based
Segmentation, Motion Segmentation, Feature Analysis and Extrac
tion

Module 4

Overview of Pattern Recognition, Discriminant Functions, Supervised Learning,
Parametric Estimation, Maximum Likelihood Estimation, Perception Algorithm,
LMSE Algorithm, Problems with Bayes Approach, Pattern Classification by
Distance Functio
ns, Minimum Distance Pattern Classifier

Module 5

Unsupervised Classification, Clustering for Unsupervised Learning and
Classification, Clustering Concept, C
-
Means Algorithm, Hierarchical Clustering
Procedures, Graph theoretic Approach to Pattern Clustering
, Validity of Clustering
Solutions

Text Books

1.

Refael C Gonzalez and Richard E Woods, Digital Image Processing, Third
Edition, Pearson Education, , 2008

2.

Milan Sonka, Vaclav Hlavac and Roger Boyle, Image Processing, Analysis
and Machine Vision, Third Edition
, Brroks Col, 2008

3.

Anil K. Jain, Fundamentals of Digital Image Processing, Prentice Hall India,
2008

References



24

1.

Madhuri A Joshi, Digital Image Processing: An Algorithmic Approach,
Prentice Hall India, 2006

2.

Rafael C. Gonzalez, Richard E woods, Steven L Edd
ins, Digital Image
Processing Using MATLAB, First Edition, Pearson Education, 2004

3.

Robert J. Schalkoff, Pattern Recognition: Statistical Structural and Neural
approaches, John Wiley & Sons Inc., New York, 1992.



CSMPh3115 Internet of Things

Credit: 4


Module 1

RFID Tags, RFID Automatic Identification and Data Capture,


RFID Data
Warehousing and Analysis,


RFID Data Management Issues, Solutions, and
Directions,




Module 2

RFID Secur
ity: Threats and Solutions,

RFIG Geometric Context of Wireless Tags



Module 3

Structured Web Documents in XML, Describing Web Resources in RDF, Web
Ontology Language: OWL, Logic and Inference: Rules, Applications


Module 4

Introducing Android, Stacking up

Android, Booting Android development, An
Android application, The Android SDK, Fitting the pieces together, Building an
Android application in Eclipse, User interfaces, Creating the Activity, Working with
views. Using resources, Understanding the Android
Manifest file, Working with
Intent classes, Listening in with broadcast receivers, Building a Service, Performing
Inter
-
Process Communication, Storing and retrieving data, using preferences,
Using the filesystem, Persisting data to a database, Working with

Content Provider
classes


Module 5

Networking and web services, An overview of networking, Checking the network
status, Communicating with a server socket, Working with HTTP,web services,
Telephony background and terms, Accessing telephony information, In
teracting
with the phone, Working with messaging: SMS, Notifications and alarms, Graphics
and animation, Multimedia


Textbooks

1.

The Internet of Things: From RFID to the Next
-
Generation Pervasive
Networked Systems (Wireless Networks and Mobile Communications
) , Lu
Yan (Editor), Yan Zhang (Editor), Laurence T. Yang (Editor), Huansheng
Ning

2.

Unlocking Android A Developer's Guide Covers Android SDK 1.x, W. Frank
Ableson, Charlie Collins, and Robi Sen

3.

A Semantic Web Primer, Grigoris Antoniou and Frank van Harmel
en




25

Reference

1.

Hakima Chaouchi, The Internet of Things: Connecting Objects (ISTE),
Wiley
-
ISTE; 1 edition (May 24, 2010)


CSMPh3116 e
-
Governance and IT Management Credit: 4


Module 1


Philosophy of e
-
Governance
-

Govern
ance and Good Governance


indicators of
good governance


structure of governance


good governance and e
-
governance.
Need of e
-
Goverance
-

NeGP
-

Vision, Objective, Strategy; Status. Central, State
and Integrated Mission Mode projects.


Module 2


Governm
ent Process Reengineering
-
Introduction to Government Process
Reengineering


Reengineering and the organisations of tomorrow
-

government
process


effectiveness, automation, quality and GPR


Need and goal for GPR


attributes of customer friendly servic
es

implementing GPR


Challenges, success
and failures in GPR
-

Change Management

Module 3


Management of Citizen Services
-
State as service provider


Role of Government
and Citizen


Citizen requirements


Life Cycle Needs


Design and Delivery
-
Promoti
on
-

Pricing
-
Framework For Design & Delivery of Services
-

Modes of
Service Delivery
-
Commercialisation
-

Public
-
Private Partnerships
-
Co
-
production
-

Decentralization
-
Enabling Public Service Delivery
-

The Environment for Effective
Service Delivery

Modu
le 4

Introduction to Transactional Services


Types of transactional services


G2G


G2C

G2E


B2G
-

Payment gateways
-

Introduction to B2C
-
Challenges and
Issues in Legacy to Electronic Models


Designing work flow


infrastructure


people


revenue coll
ection
-

Building Blocks of Transactional Services


components

Concept of Three Tier Architecture


Web Technologies
-

e
-
Governance standards

interoperability


seamless integration across departments


Data standards

Module 5

Basic concepts of Informat
ion Systems and management
-
types of IS: functional
and Enterprise; IT Infrastructure, Web 2.0, CRM, SCM, ERP, Data mining,
Business Intelligence, Ethical issues relating to IS
-
Agency Theory and IS;


26

Transaction Cost Theory; Impact of IS on organizations a
nd markets; Effects of IT
on organizational design: organizational memory;organizational intelligence and
decision
-
making

Text Books

1.

Prabhu CSR , E
-

Governance : Concepts and Case Studies,, Prentice Hall
of India

Pvt Ltd., 2004

2.

Deva, Vasu , E
-
Governance i
n India A Reality, , Publisher: Commonwealth
Publisher, 2005

3.

James a O’Brien ,
Managing Information Technology in the E
-

Business
Enterprise,

TMG, 2002

References

1.

Robert A. Schultheis, Mary Summer,
Richard d Irwin

,
Management
Information Systems: The M
anager’s View,

1999

2.

Vikram Sethi, William King , Organizational transformation through business
process reengineering: Applying lessons learned., Pearson, 1998



CSMPh3117 Kernel Design







Credits: 4


Module 1:

Operating systems, Preparatio
n: Read The Evolution of the Unix Time
-
Sharing
System, C, Assembly, Tools, and Bootstrapping, PC hardware and x86
programming, OS Organization, Exokernel

Module 2:

Processes and page tables (registers, page table translation), Fork/exec, JOS
memory lay
out and System call, Interrupt, and Exception Handling (JOS memory
layout, IDT)

Module 3:

Multiprocessors and locking, Process scheduling, Processes and coordination,
Files and disk I/O, Naming, File system performance and crash recovery

Module 4:



27

Perform
ance and durability, Scheduling, Microkernels and capabilities,
Language/OS co
-
design, Multi
-
processor coordination: scalable locks,Multi
-
processor coordination: lock free

Module 5:

Multikernel operating systems (AMD slides, source, IPC latency and
L2 misses),
Deterministic Parallelism, Virtual Machines, Software vs Hardware Virtualization,
Execution Replay for Multiprocessor Virtual Machines

Textbooks

1.

The UNIX Time
-
Sharing System, Dennis M. Ritchie and Ken
L.Thompson,. Bell System Technical Journal

57, number 6, part 2 (July
-
August 1978) pages 1905
-
1930.

2.

The Evolution of the Unix Time
-
sharing System, Dennis M. Ritchie, 1979.

References

1.

Abraham Silberschatz, Peter B. Galvin and Greg Gagne, Operating
System Concepts.Wiley; 8 edition (July 29, 2008)

2.

T
he C programming language (second edition) by Kernighan and Ritchie.
Prentice Hall, Inc., 1988. ISBN 0
-
13
-
110362
-
8, 1998.



CSMPh3101

Research Methodologies In Computer Science
Credits
:

4


Module 1


Principles of Scientific Research: Introducti
on to problem


Determining the mode
of attack


Literature Survey


Reference


Awareness of current status


Abstraction of a research paper


possible ways of getting oneself abreast of
current literature


Assessing the status of the problem
-
Document a
nd thesis
preparation using Latex
-

Guidance from the Supervisor


Actual Investigation
preparation of Manuscript


Thesis Writing.


Module 2

Linear Programming, Simplex method, Meaning Basic Concepts and Notations
General form of Linear programming model
-

Simplex Minimisation and
Maximisation Procedure
-
Technical issues in Linear Programming
-

Linear
programming applications. Discrete approach to problem solving Spanning Tree,
Shortest Path, Assignment Problem
-
Traveling salesman; Knapsack problem
-

Statistica
l Research Methods
-

Tools for Scientific problem solving


Module 3

Programming Concepts
-

Structured
-

Functional
-

Object oriented
-

New trends in
Programming

-
Introduction to coding Theory, Shannon's theory of Information,


28

Entropy, Mathematical Theory of C
laude Shannon
-

Hamming vs Shannon
-

Computational Theories
-
Evolutionary Algorithms
-

Dynamic Computing


Module 4

Introduction to learning theories, learning paradigms, history of instructional
technology
-

social, cognitive, developmental theories
-
David Merr
ill's model
-
Technology Enhanced Learning and Teaching
-

communication and collaboration
process
-
Educational multimedia, print, audio and video media, Computer Assisted
Instruction, web based instructional models, interactive video, teleconferencing,
mobile
based delivery


Module 5

e
-
Learning
-

advantages and characteristics, components of e
-
learning: CBT, WBT
and Virtual Classroom, e
-
Learning tools, e
-
Learning tools
-
moodle, Learning
Management System, Content development system


Jumla/ Drupal


standards of

content developmemt, Malcom Bridge Content Management model
-
Open
Research Methodologies
-
FOSS


Wiki




Textbooks:


1.

Rajammal P Devadas, A Hand Book of Methodology of Research, S.R.K.
Vidyalaya Press (1976).

2.

Anderson J. Durstan B H and Poole M, Thesis an
d Assignment Writing,
Wiley Eastern (1997).

3.

Taha Hamdy A, Operations Research, Macmillan, New York, 1987.

4.

Biggerstaff J, System Software Tools, Prentice Hall.

5.

Kanti Swarup, Gupta P K, and Man Mohan, Operation Research, Sulthan
Chand and sons Pub, New Delhi
.

6.

David E. Goldberg, ‘Genetic Algorithms in Search, Optimization and
Machine Learning, ADDISON
-
WESLEY, 1989.

7.

Melonie Mitchell, ‘An Introduction to Genetic Algorithms’ PHI, 1996.

References

1.

Koza, John. R, ‘Genetic Programming, on the programming of computer
s by
means of natural selection’, CAMBRIDGE, MA: THE MIT PRESS, 1992.

2.

C. R. Kothari


Research Methodology Methods and Techniques
-

Wishwa

Prakashan Publishers


Second Edition.