M.Sc. New Syllabus.doc

8/14/2019 M.Sc. New Syllabus.doc

1/39

M. Sc. Computer Science - First Year

Subjects Lect/ Pract/ Paper Pract Total

Week Week Hours Marks

1 Section I :

Principles of Compiler Design-I 4 4

Section II : 3 75 50 125

Principles of Compiler Design-II 4 4

2 Section I :Digital Signal Processing-I 4 4

Section II : 3 75 50 125

Digital Signal Processing-II 4 4

3 Section I :

Moile Comp!ting 4 4

Section II : 3 75 50 125

Comp!ter Sim!lation an" Mo"eling 4 4

4 Section I :

Data #are$o!sing an" Mining 4 4

Section II : 3 75 50 125

%"&ance" Dataase S'stems 4 4(otal 1) 1) - 300 200 500

M. Sc. Computer Science - Second Year

Subjects Lect/ Pract/ Paper Pract Total

Week Week Hours Marks

1 Section I :

%rtificial Intelligence 4 4

Section II : 3 75 25 100

Image Processing 4 4

2 Section I :

Distri!te" Comp!ting 4 4

Section II : 3 75 25 100

*me""e" S'stems 4 4

3 *lecti&e I

I (erm 4 4

II (erm 4 4 3 75 25 100

4 *lecti&e II

I (erm 4 4

II (erm 4 4 3 75 25 100

5 Pro+ect, I (erm - ) - - 100 100

(otal 1) 1) - 300 200 500

lecti!e-" lecti!e-""

1 Parallel Processing, I (erm. 1 Pattern /ecognition, I (erm.

%"&ance" Comp!ter etors, II (erm. Comp!ter ision, II (erm.

2 S'stem Sec!rit' I (erm. 2 irt!al /ealit' irt!al *n&ironment I (erm.

Internet sec!rit' II (erm. a&a (ec$nolog' II (erm.

3 *nterprise etoring I (erm. 3 6io Informatics I (erm.

Satellite Comm!nications, II (erm. Intelligent S'stems II (erm.

4 !88' 9ogic e!ral netors I (erm. 4 ptimi8ation (ec$ni;!es I (erm.

M!ltime"ia s'stems an" con&ergence of

tec$nologies II (erm.

C!stomer /elations Management II (erm.

Page 1 of 3


2/39

CLASS: M. Sc (Computer Science) Year I

SUBJECT: PRINCIPLES ! CMPILER "ESI#N$ Paper I$ Term I

Periods per week Lecture 4

TW/Tutorial/Practical 4

Hours Marks

Evaluation System Theory Examination !"

TW/Practical ## "$

Term I

%ntroduction to &ompilerso &ompilers and translators

o Why do we need translators'

o The structure o( a compiler

o Lexical analysis

o Syntax analysis

o %ntermediate code )enerationo *ptimi+ation

o &ode )eneration

o ,ook keepin)

o Error handlin)

o &ompiler writin) tools

o -ettin) started

Pro)rammin) lan)ua)eso Hi)h#level pro)rammin) lan)ua)es

o .e(initions o( pro)rammin) lan)ua)es

o The lexical and syntactic structure o( a lan)ua)eo .ata elements

o .ata structures

o *perators

o ssi)nment

o Statements

o Pro)ram units

o .ata environments

o Parameter transmission

o Stora)e mana)ement

0inite automata and lexical analysiso The role o( the lexical analy+er

o simple approach to the desi)n o( lexical analy+ers

o 1e)ular expressions

o 0inite automata

o 0rom re)ular expressions to (inite automata

o Minimi+in) the num2er o( states o( a .0

o lan)ua)e (or speci(yin) lexical analy+ers

o %mplementation o( a lexical analy+er

o The scanner )enerator as Swiss army kni(e

The syntactic speci(ication o( Pro)rammin) Lan)ua)eso &ontext#(ree )rammars

Page 2 of 3


3/39

o .erivations and parse trees

o &apa2ilities o( context#(ree )rammars

,asic Parsin) Techni3ueso Parsers

o Shi(t#reduce parsin)

o *perator#precedence parsin)

o Top#down parsin)

o Predictive parsers utomatic &onstruction o( E((icient Parsers

o L1 parsers

o The canonical collection o( L1$5 items

o &onstructin) SL1 parsin) ta2les

o &onstructin) canonical L1 parsin) ta2les

o &onstructin) LL1 parsin) ta2les

o 6sin) am2i)uous )rammars

o n automatic parser )enerator

o %mplementation o( L1 parsin) ta2les

o &onstructin) LL1 sets o( items

SUBJECT: PRINCIPLES ! CMPILER "ESI#N$ Paper I$ Term II

Syntax#.irected Translationo Syntax#directed translation schemes

o %mplementation o( syntax#directed translators

o %ntermediate code

o Post(ix notation

o Parse trees and syntax trees

o

Three#address code7 3uadruples7 and tripleso Translation o( assi)nment statements

o ,oolean expressions

o Statements that alter the (low o( control

o Post(ix translations

o Translation with a top#down parser

More a2out Translationo rray re(erences in arithmetic expressions

o Procedure calls

o .eclarations

o

&ase statementso 1ecord structures

o PL/%#style structures

Sym2ol Ta2leso The contents o( a sym2ol ta2le

o .ata structures (or sym2ol ta2les

o 1epresentin) scope in(ormation

Sym2ol ta2leso %mplementation o( a simple stack allocation scheme

o %mplementation o( 2lock#structured lan)ua)es

o

Stora)e allocation in 0*1T18o Stora)e allocation in 2lock#structured lan)ua)es

Page 3 of 3


4/39

Error detection and recoveryo Errors

o Lexical#phase errors

o Syntactic#phase errors

o Semantic errors

%ntroduction to code optimi+ation

o The principle sources o( optimi+ationo Loop optimi+ation

o The .- representation o( 2asic 2locks

o 9alue num2ers and al)e2raic laws

o -lo2al data#(low analysis

More a2out loop optimi+ationo .ominators

o 1educi2le (low )raphs

o .epth#(irst search

o Loop#invariant computations

o %nduction varia2le eliminationo Some other loop optimi+ations

More a2out data#(low analysiso 1eachin) de(initions a)ain

o vaila2le expressions

o &opy propa)ation

o ,ackward (low pro2lems

o 9ery 2usy expressions and code hoistin)

o The (our kinds o( data#(low analysis pro2lems

o Handlin) pointers

o %nterprocedural data#(low analysiso Puttin) it all to)ether

&ode )enerationo *2:ect pro)rams

o Pro2lems in code )eneration

o machine model

o simple code )enerator

o 1e)ister allocation and assi)nment

o &ode )eneration (rom .-;s

o Peephole optimi+ation

Practica%

.e2u) &


5/39

T,-Tutoria%-Practica% +

our' Mar*'

E/a%uation S0'tem T1eor0 E2amination 3 45

T,-Practica% 66 57

Paper II$ Term I

Se3uences#1epresentation o( ar2itrary se3uences#Linear time variant systems#causality7sta2ility# di((erence e3uations#(re3uency response#(irst order systems#secondorder systems#.iscrete 0ourier series#relation 2etween continuous and discreteSystems> The + Trans(orm#the 1elation 2etween the + Trans(orm and the0ourier trans(orm o( a se3uence#Solution o( di((erences e3uation usin) onesided trans(orm#)eometric evaluation o( the 0ourier Trans(orm#.i)ital 0ilter1eali+ations#structures (or all +ero (ilters#the discrete 0ourier trans(orm ?

convolution o( se3uences#linear convolution o( (inite duration se3uences#thediscrete Hil2ert trans(orm>

The Theory and approximation o( (inite duration impulse response di)ital (ilters#issues in 0ilterdesi)n#0%1 (ilters .esi)n techni3ues (or Linear phase 0%1 (ilters#windowin)#issues with windowin)#(re3uency samplin)#solution (or optimi+ation#linearpro)rammin)#linear phase (ilters#Maximal ripple 0%1 0ilters ?1eme+ exchan)eal)orithm# Multiple 2and optimal 0%1 0ilters#.esi)n o( (ilters with simultaneousconstrains on the time and (re3uency response>

Theory and approximation o( in(inite impulse response di)ital (ilters# %%1 (ilters#(ilter coe((icient#

.i)ital 0ilter .esi)n ?Mappin) o( di((erentials#Trans(ormations#.irect desi)n o(di)ital (ilters#comparison 2etween 0%1 (ilters and %%1 (ilters

0inite word len)th e((ects in di)ital (ilters#analo) to di)ital conversions#di)ital to analo)conversions#types o( rithmetic in di)ital systems> Types o( 3uanti+ation indi)ital (ilters#.ynamic ran)e &onstraints#1eali+ations#orderin) and pairin) incascade reali+ations#round o( noise#(ixed point analysis#&oe((icient 3uanti+ation? Limit cycle oscillations

Spectrum analysis and the (ast (ourier Trans (orm#introduction to 1adix#@ 00T;s#data shu((lin)and 2it reversal#00T computer pro)rammin)#.ecimation ?in#0re3uency

l)orithm ?&omputin) an %nverse .0T 2y doin) a .irect .0T#1adix@ l)orithm#Spectrum analysis at a sin)le point in the + plane#spectrum analysis in 00Tnalysis#Windows in spectrum nalysis#,luestein;s l)orithm#The chirp +trans(orm al)orithm# convolution and correlation usin) num2er theoretictrans(orms>

Page 5 of 3


6/39

Paper %%7 Term IIn introduction to the theory o( two dimensional si)nal processin)#Two#dimensional si)nals#

systems#causality# sepera2ility #sta2ility#di((erence e3uations#0re3uency.omain Techni3ues# A Trans(orms#(inite se3uences#Two dimensional .0T#Twodimensional windows#0re3uency samplin) (ilters# (re3uency trans(ormations(rom one to two dimensions>

%ntroduction to .i)ital hardware#desi)n procedure (or .i)ital Si)nal Processin) Hardware# thema:or lo)ic (amilies# commercial lo)ic packa)es# )ates7 multiplexers and decoders# 0lip#0lops#arithmetic 6nits# dividers and (loatin) point hardware>Special purpose hardware (or di)ital (ilterin) and si)nal )eneration#direct (orm 0%1 hardware#parallelism (or direct (orm 0%1# &ascade 0%1 (ilters#%%1 (ilters# .i)ital Touch Tone 1eceiverTT15 # .i)ital time .ivision Multiplexin) T.M5 to 0re3uency .ivision Multiplexin) 0.M5translator partitionin) o( di)ital (ilters (or %& 1eali+ation# Hardware reali+ation o( a .i)ital0re3uency Synthesi+er

Special purpose hardware (or 00T# 00T indexin)# 2it reversal and di)it reversal (or (ixedradices# &omparison o( computations (or radices# introduction to 3uanti+ation e((ects in 00T

l)orithms> Hardware (or 1adix @ l)orithm# 00T &omputation usin) 0ast Scratch Memory1adix @ and 1adix 4 Parallel structures usin) 1M;s# Pipeline 00T# &omparison o( Pipe line00T;s# overlapped 00T with random access memory#real time convolution via 00T usin) asin)le 1am and one E

-eneral Purpose hardware (or si)nal Processin) (acilities# special and )eneral purposecomputers# input output pro2lems (or real time processin)# methods o( improvin) computerspeed ? parallel operations o( memories7 rithmetic7 control and instruction (etches# the LincoLa2oratory 0ast .i)ital Processor0.P5> .oin) 00T in 0.P# LSP@

pplication o( .i)ital si)nal processin) to speech# models o( speech production#Short time

spectrum analysis# speech analysis#synthesis System 2ased on short time spectrum analysis#channel vocoder# analy+ers#synthesi+ers# pitch detection and voiced unvoiced detections#homomorphic processin) o( speech7 vocoder#(ormant Synthesis# 9oiced ?6nvoiced .etection#9oiced 0ricative excitation

network# Linear prediction o( speech# &omputer 9oice 1esponse systempplications to radar# 1adar principle and application radar systems and parameter# Si)naldesi)n and am2i)uity (unctions# ir2orne Surveillance 1adar (or ir Tra((ic &ontrol ? .i)italmatched 0ilter (or a hi)h per(ormance 1adar>

Re8erence

Theory and application o( .i)ital si)nal processin) Lawrence 1> 1a2iner ,ernard -old#prentice hall o( %ndiaPracticalHands on experience in usin) commercial so(tware packa)es (or di)ital si)nal processin).evelopin) academic exercise pro)rams (or 0ilter desi)n and 00T analysis (or real timeapplications

Page ) of 3


7/39

CLASS: M. Sc (Computer Science)

SUBJECT: MBILE CMPUTIN#$ Paper III$ Term I

Lecture': + r' per ee*Practica%: + r' per ee*

T1eor0: 45 Mar*'Term or* - Practica%: 57 Mar*'

9ecti/e:1ecent developments in porta2le devices and hi)h#2andwidth7u2i3uitous wireless networks has made mo2ile computin) a reality> %ndeed7 it iswidely predicted that within the next (ew years; access to %nternet services will 2eprimarily (rom wireless devices7 with desktop 2rowsin) the exception> Suchpredictions are 2ased on the hu)e )rowth in the wireless phone market and thesuccess o( wireless data services> This course will help in understandin)(undamental concepts7 current developments in mo2ile communication systemsand wireless computer networks>

"ETAILE" SYLLABUS

B> Introuction:pplications7 short history o( wireless communication

@> ,ire%e'' Tran'mi''ion: 0re3uency (or radio transmission7 Si)nals7 ntennas7Si)nal propa)ation7 Multiplexin)7 Modulation7 Spread spectrum7 &ellularsystems>

> Meium Acce'' Contro%:Motivation (or a speciali+ed M&C Hidden andExposed terminals> 8ear and 0ar terminalsD S.M7 0.M7 T.MC 0ixed T.M7&lassical loha7 Slotted loha7 &arrier sense multiple access7 .emandassi)ned multiple access7 P1M packet reservation multiple access71eservation T.M7 Multiple access with collision avoidance7 Pollin)7 %nhi2itsense multiple accessD &.MC Spread loha multiple access>

4> Te%ecommunication S0'tem'C -SMC Mo2ile services7 System architecture71adio inter(ace7 Protocols7 Locali+ation nd &allin)7 Handover7 Security7 8ew

data servicesD .E&TC System architecture7 Protocol architectureD TET176MTS and %MT#@$$$C 6MTS ,asic architecture7 6T1 0.. mode7 6T1 T..mode

"> Sate%%ite S0'tem'C History7 pplications7 ,asicsC -E*7 LE*7 ME*D 1outin)7Locali+ation7 Handover7 Examples

> Broaca't S0'tem'C *verview7 &yclic repetition o( data7 .i)ital audio2roadcastin)C Multimedia o2:ect trans(er protocolD .i)ital video 2roadcastin)

!> ,ire%e'' LANC %n(rared vs> 1adio transmission7 %n(rastructure and d hoc8etworks7 %EEE F$@>BBC System architecture7 Protocol architecture7 Physicallayer7 Medium access control layer7 M& mana)ement7 0uture developmentDH%PE1L8C Protocol architecture7 Physical layer7 &hannel access control>

Su2layer7 Medium access control Su2layer7 %n(ormation 2ases nd 8etworkin)D,luetoothC 6ser scenarios7 Physical layer7 M& layer7 8etworkin)> Security7 Linkmana)ement>

F> ,ire%e'' ATMC Motivation (or WTM7 Wireless TM workin) )roup7 WTMservices7 1e(erence modelC Example con(i)urations7 -eneric re(erence modelD0unctionsC Wireless mo2ile terminal side7 Mo2ility supportin) network sideD1adio access layerC 1e3uirements7 ,18D HandoverC Handover re(erencemodel7 Handover re3uirements7 Types o( handover7 Handover scenarios7,ackward handover7 0orward handoverD Location mana)ementC 1e3uirements(or location mana)ement7 Procedures and EntitiesD ddressin)7 Mo2ile 3uality o(

service7 ccess point control protocolG> Mo9i%e Netor* La0erC Mo2ile %PC -oals7 assumptions and re3uirements7

Page 7 of 3


8/39

Entities and Terminolo)y7 %P packet delivery7 )ent advertisement anddiscovery7 1e)istration7 Tunnelin) and Encapsulation 7 *ptimi+ations7 1eversetunnelin)7 %pvD .ynamic host con(i)uration protocol7 d hoc networksC 1outin)7.estination se3uence distance vector7 .ynamic source routin)7 Hierarchicalal)orithms7 lternative metrics

B$>Mo9i%e Tran'port La0erC Traditional T&PC &on)estion control7 Slow start7 0astretransmit/(ast recovery7 %mplications on mo2ilityD %ndirect T&P7 Snoopin) T&P7Mo2ile T&P7 0ast retransmit/(ast recovery7 Transmission/time#out (ree+in)7Selective retransmission7 Transaction oriented T&P

BB>Support 8or Mo9i%it0C 0ile systemsC &onsistency7 ExamplesD World Wide We2CHypertext trans(er protocol7 Hypertext markup lan)ua)e7 Some approaches thatmi)ht help wireless access7 System architecturesD Wireless application protocolCrchitecture7 Wireless data)ram protocol7 Wireless transport layer security7Wireless transaction protocol7 Wireless session protocol7 Wireless applicationenvironment7 Wireless markup lan)ua)e7 WML script7 Wireless telephonyapplication7 Examples Stacks with Wap7 Mo2ile data2ases7 Mo2ile a)ents

Te2t Boo*':

B> =ochen Schiller7 Mobile communications,ddison wisely 7 Pearson Education@> Wiiliam Stallin)s7 Wireless Communications and NetworksI

Re8erence' :

B> 1appaort7 Wireless CommunicationsPrincipals and PracticesI@> J% ,in) Lin 7 Wireless and Mobile Network ArchitecturesI7 =ohn Wiley> P> 8icopolitidis 7 Wireless NetworksI7 =ohn Wiley4> K Pahlavan7 P> Krishnamurthy 7 Principles of Wireless NetworksI"> M> 1ichharia 7 Mobile Satellite Communication: Principles and TrendsI7

Pearson Education

TERM ,R;

B> Term work should consist o( at least B$ practical experiments and twoassi)nments coverin) the topics o( the sylla2us>


SUBJECT: CMPUTER SIMULATIN AN" M"ELIN#$ Paper III$ Term II

Lecture': + r' per ee*

Practica%: + r' per ee*

T1eor0: 45 Mar*'

Term ,or* - Practica%: 57 Mar*'9ecti/eC %n the last (ive decades di)ital computer simulation has developed(rom in(ancy to a (ull#(led)ed discipline> The (ield o( modelin) and simulation is asdiverse as o( man> The application o( simulation continues to expand7 2oth interms o( extent to which simulation is used and the ran)e o( applications> Thiscourse )ives a comprehensive and state o( art treatment o( all the importantaspects o( a simulation study7 includin) modelin)7 simulation so(tware7 modelveri(ication and validation7 input modelin)>

"ETAILE" SYLLABUS

B> Introuction to Simu%ation: System and System environment7 &omponents o(system7 Type o( systems7 Type o( models7 Steps in simulation study7

Page = of 3


9/39

dvanta)es and .isadvanta)es o( simulation>@> Simu%ation E2amp%e': Simulation o( ueuein) systems7 *ther examples o(

simulation>> #enera% Princip%e': &oncepts o( discrete event simulation7 List processin)74> Simu%ation So8tare: History o( simulation so(tware7 .esira2le so(tware

(eatures7 -eneral#purpose simulation packa)es7 *2:ect oriented simulation7Trends in simulation so(tware>

"> Stati'tica% Moe%' in Simu%ation: 6se(ul statistical model7 .iscretedistri2ution7 &ontinuous distri2ution7 Poisson process7 Empirical distri2ution>

>

B>Ca'e Stuie': Simulation o( manu(acturin) systems7 Simulation o( computersystems7 Simulation o( super market7 Simulation o( pert network

Te2t Boo*':

B> =erry ,anks7 =ohn &arson7 ,arry 8elson7 .avid 8icol7 iscrete !"ent S#stemSimulationI

@> verill Law7 W> .avid Kelton7 Simulation Modelin$ and Anal#sis,Mc-1W#H%LL

Re8erence':B> -e((ery -ordon7 %S#stem Simulation7 PH%@> ,ernard Aei)ler7 Her2ert Praeho(er7 Ta) -on Kim7 Theor# of Modelin$ and

SimulationI7 cademic Press> 8arsin) .eo7 %S#stem Simulation with i$ital Computer7 PH%4> .onald W> ,ody7 S#stem Anal#sis and Modelin$I7 cademic Press Harcourt

%ndia"> W .avid Kelton7 1andall Sadowski7 .e2orah Sadowski7 Simulation with

ArenaI7 Mc-1W#H%LL>

Page < of 3


10/39

TERM ,R;

@> Term work should consist o( at least B$ practical experiments/ssi)nmentscoverin) the topics o( the sylla2us>


SUBJECT: "ATA ,AREUSIN# AN" MININ#$ Paper I=$ Term I


T1eor0: 45 Mar*'Term or*-Practica%: 57 Mar*'

9ecti/e' o8 t1e cour'e:The data warehousin) part o( module aims to )ivestudents a )ood overview o( the ideas and techni3ues which are 2ehind recentdevelopment in the data warehousin) and online analytical processin) *LP5(ields7 in terms o( data models7 3uery lan)ua)e7 conceptual desi)n methodolo)ies7and stora)e techni3ues> .ata minin) part o( the model aims to motivate7 de(ineand characteri+e data minin) as processD to motivate7 de(ine and characteri+e data

minin) applications>

"ETAILE" SYLLABUS

"ata ,are1ou'in&:>. /er/ie An Concept':8eed (or data warehousin)7 ,asic elements o(

data warehousin)7 Trends in data warehousin)>?. P%annin& An Re@uirement':Pro:ect plannin) and mana)ement7

&ollectin) the re3uirements>3. Arc1itecture An In8ra'tructure:rchitectural components7 %n(rastructure

and metadata>

+. "ata "e'i&n An "ata Repre'entation:Principles o( dimensionalmodelin)7 .imensional modelin) advanced topics7 data extraction7trans(ormation and loadin)7 data 3uality>

5. In8ormation Acce'' An "e%i/er0:Matchin) in(ormation to classes o(users7 *LP in data warehouse7 .ata warehousin) and the we2>

. Imp%ementation An Maintenance:Physical desi)n process7 datawarehouse deployment7 )rowth and maintenance>

"ata Minin&:>. Introuction:,asics o( data minin)7 related concepts7 .ata minin)

techni3ues>?. "ata Minin& A%&orit1m':&lassi(ication7 &lusterin)7 ssociation rules>

3. ;no%e&e "i'co/er0 :K.. Process+. ,e9 Minin&:We2 &ontent Minin)7 We2 Structure Minin)7 We2 6sa)e

minin)>5. A/ance Topic':Spatial minin)7 Temporal minin)>. =i'ua%i'ation :.ata )enerali+ation and summari+ation#2ased

characteri+ation7 nalytical characteri+ationC analysis o( attri2ute relevance7Minin) class comparisonsC .iscriminatin) 2etween di((erent classes7 Minin)descriptive statistical measures in lar)e data2ases

4. "ata Minin& Primiti/e'$ Lan&ua&e'$ an S0'tem Arc1itecture':.ataminin) primitives7 uery lan)ua)e7 .esi)nin) -6% 2ased on a data minin)3uery lan)ua)e7 rchitectures o( data minin) systems

. App%ication an Tren' in "ata Minin&:pplications7 Systems products

Page 10 of 3


11/39

and research prototypes7 dditional themes in data minin)7 Trends in dataminin)

Te2t Boo*':

B> Paulra: Ponnian7 ata Warehousin$ &undamentalsI7 =ohn Wiley>@> M>H> .unham7 ata Minin$ 'ntroductor# and Ad"anced TopicsI7 Pearson

Education>> Han7 Kam2er7 ata Minin$ Concepts and Techni(uesI7 Mor)an Kau(mann

Re8erence':

B> 1alph Kim2all7 The ata Warehouse )ifec#cle toolkitI7 =ohn Wiley>@> M ,erry and -> Lino((7 Masterin$ ata Minin$I7 =ohn Wiley>> W>H> %nmon7 *uildin$ the ata WarehousesI7 Wiley .reamtech>4> 1> Kimpall7 The ata Warehouse ToolkitI7 =ohn Wiley>"> E>-> Mallach7 ecision Support and ata Warehouse s#stemsI7 TMH>

TERM ,R;

> Term work should consist o( at least B$ practical experiments and twoassi)nments coverin) the topics o( the sylla2us>


SUBJECT: A"=ANCE" "ATABASE SYSTEMS$ Paper I=$ Term II


T1eor0: 45 Mar*'Term or*- Practica%: 57 Mar*'

9ecti/e':To study the (urther data2ase techni3ues 2eyond which covered inthe second year7 and thus to ac3uaint the students with some relatively advancedissues> t the end o( the course students should 2e a2le toC )ain an awareness o(the 2asic issues in o2:ected oriented data models7 learn a2out the We2#.,MSinte)ration technolo)y and ML (or %nternet data2ase applications7 (amiliari+e withthe data#warehousin) and data#minin) techni3ues and other advanced topics7apply the knowled)e ac3uired to solve simple pro2lems

"ETAILE" SYLLABUS

B> T1e E2tene Entit0 Re%ation'1ip Moe% an 9ect Moe%:The E1 modelrevisited7 Motivation (or complex data types7 6ser de(ined a2stract data typesand structured types7 Su2classes7 Super classes7 %nheritance7 Speciali+ationand -enerali+ation7 &onstraints and characteristics o( speciali+ation and-enerali+ation7 1elationship types o( de)ree hi)her than two>

@> 9ect6riente "ata9a'e':*verview o( *2:ect#*riented concepts7 *2:ectidentity7 *2:ect structure7 and type constructors7 Encapsulation o( operations7Methods7 and Persistence7 Type hierarchies and %nheritance7 Type extents and3ueries7 &omplex o2:ectsD .ata2ase schema desi)n (or **.,MSD *L7Persistent pro)rammin) lan)ua)esD **.,MS architecture and stora)e issuesDTransactions and &oncurrency control7 Example o( *.,MS

> 9ect Re%ationa% an E2tene Re%ationa% "ata9a'e':.ata2ase desi)n (or

an *1.,MS # 8ested relations and collectionsD Stora)e and access methods7uery processin) and *ptimi+ationD n overview o( SL7 %mplementation

Page 11 of 3


12/39

issues (or extended typeD Systems comparison o( 1.,MS7 **.,MS7*1.,MS

4> Para%%e% an "i'tri9ute "ata9a'e' an C%ient6Ser/er Arc1itecture:rchitectures (or parallel data2ases7 Parallel 3uery evaluationD Paralleli+in)individual operations7 Sortin)7 =oinsD .istri2uted data2ase concepts7 .ata(ra)mentation7 1eplication7 and allocation techni3ues (or distri2uted data2asedesi)nD uery processin) in distri2uted data2asesD &oncurrency control and1ecovery in distri2uted data2ases> n overview o( &lient#Server architecture

"> "ata9a'e' on t1e ,e9 an Semi Structure "ata:We2 inter(aces to theWe27 *verview o( MLD Structure o( ML data7 .ocument schema7 ueryin)ML dataD Stora)e o( ML data7 ML applicationsD The semi structured datamodel7 %mplementation issues7 %ndexes (or text data

> En1ance "ata Moe%' 8or A/ance App%ication':ctive data2aseconcepts> Temporal data2ase concepts>D Spatial data2ases7 &oncepts andarchitectureD .eductive data2ases and uery processin)D Mo2ile data2ases7-eo)raphic in(ormation systems>

Te2t Boo*':

B> Elmasri and 8avathe7 &undamentals of atabase S#stemsI7 PearsonEducation@> 1a)hu 1amakrishnan7 =ohannes -ehrke7 atabase Mana$ement S#stemsI7

Mc-raw#Hill

Re8erence':

B> Korth7 Sil2erchat+7 Sudarshan 7 atabase S#stem ConceptsI7 Mc-raw#Hill>@> Peter 1o2 and &oronel7 atabase S#stems, esi$n, 'mplementation and

Mana$ementI7 Thomson Learnin)>> &>=>.ate7 Lon)man7 'ntroduction To atabase S#stemsI7 Pearson Education

TERM ,R;

4> Term work should consist o( at least B$ practical experiments and twoassi)nments coverin) the topics o( the sylla2us>


SUBJECT: PARALLEL PRCESSIN# (E%ecti/e)


T1eor0: >77 Mar*'Term ,or*-Practica% : 57 Mar*'

9ecti/e: 6pon completion o( this course students will 2e a2le to understand andemploy the (undamental concepts and mechanisms which (orm the 2asis o( thedesi)n o( parallel computation models and al)orithms7 reco)ni+e pro2lems andlimitations to parallel systems7 as well as possi2le solutions

"ETAILE" SYLLABUS

B> Introuction: Parallel Processin) rchitecturesC Parallelism in se3uential

machines7 2stract model o( parallel computer7 Multiprocessor architecture7Pipelinin)7 rray processors>

Page 12 of 3


13/39

@> Pro&ramma9i%it0 I''ue': n overview7 *peratin) system support7 Types o(operatin) systems7 Parallel pro)rammin) models7 So(tware tools

> "ata "epenenc0 Ana%0'i': Types o( dependencies loop and arraydependences7 Loop dependence analysis7 Solvin) diophantine e3uations7Pro)ram trans(ormations

4> S1are Memor0 Pro&rammin&: -eneral model o( shared memorypro)rammin)7 Process model under 68%

"> A%&orit1m' 8or Para%%e% Mac1ine': Speedup7 &omplexity and cost7 Histo)ramcomputation7 Parallel reduction7 uadrature pro2lem7 Matrix multiplication7Parallel sortin) al)orithms7 Solvin) linear systems7 Pro2a2ilistic al)orithms

> Me''a&e Pa''in& Pro&rammin&: %ntroduction7 Model7 %nter(ace7 &ircuitsatis(ia2ility7 %ntroducin) collective7 ,enchmarkin) parallel per(ormance

!> Para%%e% Pro&rammin& %an&ua&e': 0ortranG$7 n&6,E &7 *ccam7 LindaF> "e9u&&in& Para%%e% Pro&ram': .e2u))in) techni3ues7 .e2u))in) messa)e

passin) parallel pro)rams7 .e2u))in) shared memory parallel pro)ramsG> Memor0 an I- Su9'0'tem': Hierarchical memory structure7 9irtual memory

system7 Memory allocation and mana)ement7 &ache allocation andmana)ement7 &ache memories and mana)ement7 %nput output su2systems

B$>t1er Para%%e%i'm Parai&m': .ata (low computin)7 Systolic architectures70unctional and lo)ic paradi)ms7 .istri2uted shared memoryBB>Per8ormance o8 Para%%e% Proce''or': Speedup and e((iciency7 mdahl;s law7

-usta(son#,arsis;s law7 Kar(#0latt metric7 %soe((iciency metric

Te2t Boo*':

B> Hawan) Kai and ,ri))s 0> >7 Computer Architecture and Parallel Processin$7Mc-raw Hill

@> =orden H> 0> and la)ha2and ->7 &undamentals of Parallel Processin$I> M>=> uinn7 Parallel Pro$rammin$I7 TMH

Re8erence':B> Shasikumar M>7 'ntroduction to Parallel Processin$7 PH%@> Wilson ->9>7 Practical Parallel Pro$rammin$I7 PH%> .> E> &uller7 =>P> Sin)h7 > -upta7 %Parallel Computer ArchitectureI7 Mor)an

Kau(man

TERM ,R;

"> Term work should consist o( at least B$ practical experiments and twoassi)nments coverin) the topics o( the sylla2us>


SUBJECT: A"=ANCE" CMPUTER NET,R;S (ELECTI=E)


T1eor0: >77 Mar*'Term or*-Practica%: 57 Mar*'

9ecti/e':%n (irst part7 dvanced technolo)ies like Hi)h speed .evices etc> areto 2e considered> Second part 8etwork pro)rammin) is to 2e studied> 8ot :ust

S*&KETS 2ut also protocols7 .rivers7 Simulation Pro)rammin)> %n third part weshould study 8etwork .esi)n7 Protocols desi)ns and analysis considerin)

Page 13 of 3


14/39

deterministic and non#deterministic approach> We expect natural thinkin) (romstudent> 0or example he should a2le to consider di((erent constraints and assumesuita2le data and solve the pro2lems>

"ETAILE" SYLLABUS

B> "ata Communication':,usiness .rivers and 8etworkin) .irections C .atacommunication Past and (uture>

@> Uner'tanin& t1e 'tanar' an t1eir ma*er:&reatin) standardsC playersand Process7 &urrent (orums7 Standard protocols7 Layered re(erence modelsCThe *S%1M7 Standard computer architectures>

> Introuction to Tran'mi''ion Tec1no%o&ie':Hardware selection in thedesi)n process>

4> ptica% Netor*in&: S*8ET/S.H standards7 .ense wavelen)th divisionmultiplexin) .W.M57 Per(ormance and .esi)n considerations>

"> P10'ica% La0er Protoco%' an Acce'' Tec1no%o&ie':Physical LayerProtocols and %nter(aces7 ccessin) the 8etwork7 &opper access technolo)ies7&a2le ccess Technolo)ies7 0i2er ccess Technolo)ies7 ir ccess

Technolo)ies>> Common Protoco%' an Inter8ace' in t1e LAN en/ironment:.ata linklayers protocols7 LL& and M& su2 layer protocol7 Ethernet7 Token 1in)7Token ,us and 0..%7 ,rid)e protocols7 Switchin) in the L8 environment>

!> !rame Re%a0:01 speci(ication and desi)n7 9o01C Per(ormance and .esi)nconsiderations7 dvanta)es and disadvanta)es o( 01>

F> Common ,AN Protoco%:TMC Many (aces o( TM7 TM protocol operationTM cell and Transmission57 TM networkin) 2asics7 Theory o( operations7 ,#%S.8 protocol re(erence model7 PHJ layer7 TM layer Protocol model57 TMlayer and cell .e(inition57 Tra((ic descriptors and parameters7 Tra((ic and&on)estion control de(ined7 L Protocol model7 Tra((ic contract and oS7

6ser plane overview7 &ontrol plane L7 Mana)ement plane7 Su2#.S TM7TM pu2lic services>

G> Common Protoco%' an Inter8ace' in t1e Upper La0er'(TCP-IP):,ack)round 1outin) protocols57 T&P/%P suite7 8etwork layer %nternetworklayer57 Transport layer7 pplication layer7 ddressin) and routin) desi)n>

B$>Mature Pac*et Sitc1e Protoco%:%T6 1ecommendation >@"7 6serconnectivity7 Theory o( *peration7 8etwork layer (unctions7 >!"%nternetworkin) protocol7 switched multime)a2it data service SM.S57 SM.Sand %EEE F$@>7 Su2scri2er %nter(ace and ccess protocol7 ddressin) andTra((ic control>

BB>Re@uirement' "e8inition:6ser re3uirements7 Tra((ic si+in)7 Tra((ic

characteristics7 Protocols7 Time and .elay considerations7 &onnectivity7vaila2ility7 1elia2ility and Maintaina2ility7 Service aspects7 ,ud)et constraints7>

B@>Tra88ic En&ineerin& an Capacit0 p%annin&:,ack)round Throu)hputcalculations5 7 Tra((ic en)ineerin) 2asics Tra((ic characteristics57 TraditionalTra((ic en)ineerin)7 ueued data and packet switched tra((ic modelin)7.esi)nin) (or peaks7 .elay or Latency7 vaila2ility and relia2ility7 8etworkper(ormance modelin)7 &reatin) the tra((ic matrix7 &apacity plannin) and8etwork vision7 .esi)n tool7 &ate)ories o( tools7 &lasses o( desi)n tool7&omponents o( desi)n pro:ects7 Types o( desi)n pro:ects>

B>Tec1no%o&0 Compari'on':&ircuits#messa)e#packet and cell switchin)methods7 Packet switchin) service aspects7 -eneric packet switchin) networkcharacteristics7 Private verses pu2lic networkin)7 Pu2lic network serviceselection7 ,usiness aspects o( Packet#0rame and cell switchin) services7 Hi)h

Page 14 of 3


15/39

speed L8 protocols comparisons7 pplication per(ormance needs>B4>Acce'' Netor* "e'i&n:8etwork desi)n layers7 ccess layer desi)n7 ccess

network capacity7 network topolo)y and hardware7 completin) the accessnetwork desi)n>

B">Bac*9one Netor* "e'i&n:,ack2one re3uirements7 8etwork capacities7Topolo)ies7 Topolo)ies strate)ies7 Tunin) the network>

Te2t Boo*':

B> .arren L Spohn7 .ata 8etwork .esi)nI7 TMH@> .> ,ertsekas7 1> -alla)er7 ata NetworksI7 PH%

Re8erence':

B> W>1> Stevens7 +ni Network Pro$rammin$I7 9ol>B7 Pearson Education@> =>Walrand7 P> 9araiya7 Hi)h Per(ormance &ommunication 8etworksI7 Mor)an

Kau(mann> J> Ahen)7 S> khtar7 8etworks (or &omputer Scientists and En)ineersI7 *x(ord4> >S> Tanen2aum7 &omputer 8etworksI"> Peterson N .avie7 &omputer 8etworksI7 Harcourt sia>

> =ames .> Mc&a2e 7 Practical &omputer nalysis and .esi)nI7 Harcourt sia>

TERM ,R;

> Term work should consist o( at least B$ practical experiments and twoassi)nments coverin) all the topics o( the sylla2us>


SUBJECT: SYSTEM SECURITY (E%ecti/e)



9ecti/e' o8 t1e cour'e:Learn a2out the threats in computer security>6nderstand what puts you at a risk and how to control it> &ontrollin) a risk is noteliminatin) the risk 2ut to 2rin) it to a tolera2le level>

"ETAILE" SYLLABUS

B> Introuction: Security7 ttacks7 &omputer criminals7 Method o( de(ense@> Cr0pto&rap10: ,asic &rypto)raphyC &lassical &ryptosystems7 Pu2lic key

&rypto)raphy7 &rypto)raphic checksum7 Key Mana)ementC Key exchan)e7Key )eneration7 &rypto)raphic key in(rastructure7 Storin) and revokin) keys7Hash al)orithm7 .i)ital si)nature7 &ipher Techni3uesC Pro2lems7 Stream and2lock ciphersC ES7 .ES7 1&4>

> Pro&ram Securit0:Secure pro)rams7 8on#malicious pro)ram errors7 9irusesand other malicious code7 Tar)eted malicious code7 &ontrols a)ainst pro)ramthreats

4> peratin& S0'tem Securit0: Protected o2:ects and methods o( protection7Memory address protection7 &ontrol o( access to )eneral o2:ects7 0ileprotection mechanism7 uthenticationC uthentication 2asics7 Password7&hallen)e#response7 ,iometrics>

"> "ata9a'e Securit0:Security re3uirements7 1elia2ility and inte)rity7 Sensitivedata7 %nter(ace7 Multilevel data2ase7 Proposals (or multilevel security

Page 15 of 3


16/39

> Securit0 in Netor*': Threats in networks7 8etwork security control70irewalls7 %ntrusion detection systems7 Secure e#mail7 8etworks andcrypto)raphy7 Example protocolsC PEM7 SSL7 %Psec

!> Amini'tratin& Securit0: Security plannin)7 1isk analysis7 *r)ani+ationalsecurity policies7 Physical security>

F> Le&a%$ Pri/ac0$ an Et1ica% I''ue' in Computer Securit0: Protectin)pro)rams and data7 %n(ormation and law7 1i)hts o( employees and employers7So(tware (ailures7 &omputer crime7 Privacy7 Ethical issues in computer society7&ase studies o( ethics

Te2t Boo*':

B> Stallin)s$ Cr#pto$raph# And Network Securit#: Principles and practiceI@> &> P> P(lee)er7 and S> L> P(lee)er7 Securit# in Computin$I7 Pearson

Education>> Matt ,ishop7 Computer Securit#: Art and ScienceI7 Pearson Education>

Re8erence' :

B> Kau(man7 Perlman7 Speciner7 Network Securit#I

@> Eric Maiwald7 Network Securit# : A *e$inner-s .uideI7 TMH> ,ruce Schneier7 Applied Cr#pto$raph#I7 =ohn Wiley>4> Macro Pistoia7 /a"a network securit# 7 Pearson Education"> Whitman7 Mattord7 Principles of information securit#, Thomson


SUBJECT: IN!RMATIN SECURITY (E%ecti/e)


T1eor0: >77 Mar*'Term ,or*-Practica%: 57 Mar*'

9ecti/e' o8 t1e cour'e:Learn a2out the threats in computer security>6nderstand what puts you at a risk and how to control it> &ontrollin) a risk is noteliminatin) the risk 2ut to 2rin) it to a tolera2le level>

"ETAILE" SYLLABUS

G> Introuction: Security7 ttacks7 &omputer criminals7 Method o( de(enseB$>Pro&ram Securit0:Secure pro)rams7 8on#malicious pro)ram errors7 9iruses

and other malicious code7 Tar)eted malicious code7 &ontrols a)ainst pro)ramthreats

BB>peratin& S0'tem Securit0: Protected o2:ects and methods o( protection7Memory address protection7 &ontrol o( access to )eneral o2:ects7 0ileprotection mechanism7 uthenticationC uthentication 2asics7 Password7&hallen)e#response7 ,iometrics>

B@>"ata9a'e Securit0:Security re3uirements7 1elia2ility and inte)rity7 Sensitivedata7 %nter(ace7 Multilevel data2ase7 Proposals (or multilevel security

B>Securit0 in Netor*': Threats in networks7 8etwork security control70irewalls7 %ntrusion detection systems7 Secure e#mail7 8etworks andcrypto)raphy7 Example protocolsC PEM7 SSL7 %Psec

B4>Amini'tratin& Securit0: Security plannin)7 1isk analysis7 *r)ani+ational

security policies7 Physical security>B">Le&a%$ Pri/ac0$ an Et1ica% I''ue' in Computer Securit0: Protectin)

Page 1) of 3


17/39

pro)rams and data7 %n(ormation and law7 1i)hts o( employees and employers7So(tware (ailures7 &omputer crime7 Privacy7 Ethical issues in computer society7&ase studies o( ethics

Te2t Boo*':

4> &> P> P(lee)er7 and S> L> P(lee)er7 Securit# in Computin$I7 PearsonEducation>

"> Matt ,ishop7 Computer Securit#: Art and ScienceI7 Pearson Education>

Re8erence' :

> Stallin)s$ Cr#pto$raph# And Network Securit#: Principles and practiceI!> Kau(man7 Perlman7 Speciner7 Network Securit#IF> Eric Maiwald7 Network Securit# : A *e$inner-s .uideI7 TMHG> Macro Pistoia7 /a"a Network Securit# 7 Pearson EducationB$>Whitman7 Mattord7 Principles of information securit#, Thomson

A''i&nment': 01 assi$nments co"erin$ the s#llabus has to be submitted


SUBJECT: Enterpri'e Netor*in& (E%ecti/e)


T1eor0: >77 Mar*'Term ,or*-Practica%: ?5 Mar*'

Introuction-rowth o( &omputer 8etworkin)7 &omplexity in 8etwork Systems7 Masterin) the &omplexity71esource Sharin)7 -rowth o( the %nternet7 Pro2in) the %nternet7 %nterpretin) Pin) 1esponse

PART I "ATA TRANSMISSIN

Tran'mi''ion Meia&opper Wires7 -lass 0i2ers7 1adio7 Satellites7 -eosynchronous Satellites7 Low Earth *r2itSatellites7 Low Earth *r2it Satellite rrays7 Microwave7 %n(rared7 Li)ht 0orm a Laser

Loca% A'0nc1ronou' CommunicationThe 8eed (or synchronous &ommunication7 6sin) Electric &urrent to Send ,its7 Standards(or &ommunication7 ,aud 1ate7 0ramin)7 and Errors7 0ull .uplex synchronous&ommunication7 Limitations o( 1eal Hardware7 Hardware ,andwidth and the Transmission o(,its7 The E((ect o( 8oise *n &ommunication7 Si)ni(icance (or .ata 8etworkin)

Lon&6"i'tance Communication (Carrier'$ Mou%ation an Moem')Sendin) Si)nals across Lon) .istances7 Modem Hardware 6sed (or Modulation and.emodulation7 Leased nalo) .ata &ircuits7 *ptical7 1adio 0re3uency7 nd .ialup Modems7&arrier 0re3uencies and Multiplexin)7 ,ase 2and nd ,road2and Technolo)iesWave .ivision Multiplexin)7 Spread Spectrum7 Time .ivision Multiplexin)

PART II PAC;ET TRANSMISSIN

Pac*et'$ !rame' an Error "etection

Page 17 of 3


18/39

The &oncept o( Packets7 Packets and Time#.ivision Multiplexin)7 Packets and Hardware0rames7 ,yte Stu((in)7 Transmission Errors7 Parity ,its and Parity &heckin)7 Pro2a2ility7Mathematics nd Error .etection7 .etectin) Errors With &hecksums7 .etectin) Errors With&yclic 1edundancy &hecks7 &om2inin) ,uildin) ,locks7 ,urst Errors7 0rame (ormat nd Error.etection Mechanisms

LAN Tec1no%o&ie' an Netor* Topo%o&0.irect Point#To#Point &ommunication7 Shared &ommunication &hannels7 Si)ni(icance o( L8sand Locality o( 1e(erence7 L8 Topolo)ies7 ,us 8etworkC Ethernet &arrier Sense on Multi#ccess 8etworks &SM57 &ollision .etection and ,ack o(( With &SM/&.7 Wireless L8snd &SM/&7 ,us 8etworkC Local Talk

arare Are''in& an !rame T0pe Ienti8icationSpeci(yin) a 1ecipient7 How L8 Hardware 6ses ddresses to 0ilter Packets 0ormat o( aPhysical ddress7 ,roadcastin)7 Multicastin)7 Multicast ddressin)7 %denti(yin) Packet&ontents7 0rame Headers nd 0rame 0ormat7 6sin) 8etworks That .o 8ot Have Sel(#%denti(yin) 0rames7 8etwork naly+ers

LAN ,irin&$ P10'ica% Topo%o&0$ an Inter8ace arareSpeeds o( L8s and &omputers7 8etwork %nter(ace Hardware7 the &onnection 2etween 8%&and 8etwork7 *ri)inal Thick Ethernet Wirin)7 &onnection Multiplexin)7 Thin Ethernet Wirin)Twisted Pair Ethernet7 the Topolo)y Paradox7 8etwork %nter(ace &ards and Wirin) Schemes7

E2tenin& LAN': !i9er Moem'$ Repeater'$ Bri&e' an Sitc1e'.istance Limitation and L8 .esi)n7 0i2er *ptic Extensions7 1epeaters7 ,rid)es7 0rame0ilterin)Startup and Steady State ,ehavior o( ,rid)ed 8etworks7 Plannin) a ,rid)ed 8etwork7 ,rid)in),etween ,uildin)s7 ,rid)in) cross Lon)er .istances7 &ycle *( ,rid)es7 .istri2utedSpannin) Tree7 Switchin)7 &om2inin) Switches nd Hu2s7 ,rid)in) nd Switchin) With *ther

Technolo)ies

Lon&6"i'tance "i&ita% Connection Tec1no%o&ie'.i)ital Telephony7 Synchronous &ommunication7 .i)ital &ircuits and .S67 TelephoneStandards.S Terminolo)y and .ata 1ates7 Lower &apacity &ircuits7 %ntermediate &apacity .i)ital&ircuitsHi)hest &apacity &ircuits7 *ptical &arrier Standards7 the & Su((ix7 Synchronous *ptical8etwork S*8ET57 the Local Su2scri2er Loop7 %S.87 symmetric .i)ital Su2scri2er LineTechnolo)y*ther .SL Technolo)ies7 &a2le Modem Technolo)y7 6pstream &ommunication7 Hy2rid 0i2er

&oax

,an Tec1no%o&ie' an Routin&Lar)e 8etworks and Wide reas7 Packet Switches7 0ormin) W87 Store and 0orwardPhysical ddressin) %n W87 8ext#Hop 0orwardin)7 Source %ndependence7 1elationship o(Hierarchical ddresses to 1outin)7 1outin) %n W87 6se o( .e(aults 1outes7 1outin) Ta2le&omputation7 Shortest Path &omputation in a -raph7 .istri2uted 1oute &omputation7 .istance9ector 1outin)

Netor* ner'1ip$ Ser/ice Parai&m$ an Per8ormance8etwork *wnership7 9irtual Private 8etworks7 Service Paradi)m7 &onnection .uration and

Persistence7 Examples o( Service Paradi)ms7 ddresses and &onnection %denti(iers7 8etworkPer(ormance &haracteristics

Page 1= of 3


19/39

Protoco%' an La0erin&The 8eed (or Protocols7 Protocol Suites7 Plan (or Protocol .esi)n7 the Seven Layers7 StacksCLayered So(tware7 How Layered So(tware Works7 Multiple7 8ested Headers7 the Scienti(ic,asis (or Layerin)7

TERM ,R;Term work should consist o( at least B$ assi)nments (rom the a(orementioned topics> Seminar to 2e presented 2y each student as part o( term works carryin) B" marks>RE!ERENCE&omputer 8etwork7 Tuekeun7 PH%8etworkin) Technolo)y7 =aiswal7 -al)otia>.ata 8etworkin)7 ,ertsekas7 PH%&omputer 8etworks and %nternets7 .ou)las E> &omer Pearson Education sia

Page 1< of 3


20/39


Su9: Sate%%ite Communication' (E%ecti/e)

Periods per week Lecture 4

Practical 4

Tutorial ##

Hours MarksEvaluation System Theory Examination B$$

Term Work / Practical ## "$

.etailed Sylla2us

>. Introuction:-eneral 2ack)round7 (re3uency allocations (or satellite services7 2asic satellite system7system desi)n considerations7 applications>

?. Sate%%ite r9it':%ntroduction7 laws )overnin) satellite motion7 or2ital parameters7 or2ital pertur2ations7

.oppler e((ects7 )eostationary or2it7 antenna look an)les7 antenna mount7 limits o(visi2ility7 Earth eclipse o( satellite7 sun transit outa)e7 inclined or2its7 sun#synchronousor2it7 launchin) o( )eostationary satellites>

3. ,a/e Propa&ation an Po%ariDation:%ntroduction7 atmospheric losses7 ionospheric e((ects7 rain attenuation7 otherimpairments7 antenna polari+ation7 polari+ation o( satellite si)nals7 cross polari+ationdiscrimination7 ionospheric depolari+ation7 rain depolari+ation7 ice depolari+ation>

+. Sate%%ite Antenna:ntenna 2asics7 aperture antennas7 para2olic re(lectors7 o((set (eed7 dou2le rel(lectorantennas7 shaped re(lector systems>

5. Lin* "e'i&n:%ntroduction7 transmission losses7 link power 2ud)et e3uation7 system noise7 carrier tonoise ratio (or uplink and downlink7 com2ined uplink and downlink carrier to noise ratio7inter modulation noise

. Communication Sate%%ite':%ntroduction7 desi)n considerations7 li(etime and relia2ility7 spacecra(t su2 systems7spacecra(t mass and power estimations7 space se)ment cost estimates>

4. Eart1 Station':%ntroduction7 desi)n considerations7 )eneral con(i)uration and characteristics>

. Mu%tip%e Acce'' Tec1ni@ue':%ntroduction7 0.M7 T.M7 0.M/T.M7 operation in a multiple 2eam environment7&.M7 multiple access examples

G> 8on -eostationary *r2it Satellite SystemsC%ntroduction7 reasons7 desi)n considerations7 case study7 example o( systems>

Term ,or*:B$ ssi)nments coverin) the entire sylla2us

Page 20 of 3


21/39

Te2t Boo*':B> Satellite &ommunications ? .ennis 1oddy ? rdedition7

Mc#-raw Hill pu2lication

@> Satellite &ommunications systems ? M> 1ichharia ? @ndeditionMc Millan pu2lication>

Page 21 of 3


22/39


SUBJECT: NEURAL NET,R;S !UFFY SYSTEMS (E%ecti/e)



9ecti/e: This course covers 2asic concepts o( arti(icial neural networks7 (u++ylo)ic systems and their applications> %ts (ocus will 2e on the introduction o( 2asictheory7 al)orithm (ormulation and ways to apply these techni3ues to solve realworld pro2lems>

"ETAILE" SYLLABUS

B> Introuction: ,iolo)ical neurons7 Mc&ulloch and Pitts models o( neuron7Types o( activation (unction7 8etwork architectures7 Knowled)e representation>Learnin) processC Error#correction learnin)7 Supervised learnin)7 6nsupervised

learnin)7 Learnin) 1ules>@> Sin&%e La0er Perceptron: Perceptron conver)ence theorem7 Method o(steepest descent # least mean s3uare al)orithms>

> Mu%ti%a0er PerceptronC .erivation o( the 2ack#propa)ation al)orithm7 Learnin)0actors>

4> Raia% Ba'i' an Recurrent Neura% Netor*': 1,0 network structure7theorem and the repara2ility o( patterns7 1,0 learnin) strate)ies7 K#means andLMS al)orithms7 comparison o( 1,0 and MLP networks7 Hop(ield networksCener)y (unction7 spurious states7 error per(ormance >

"> Simu%ate Annea%in&C The ,olt+mann machine7 ,olt+mann learnin) rule7,idirectional ssociative Memory>

> !uDD0 %o&ic: 0u++y sets7 Properties7 *perations on (u++y sets7 0u++y relations7*perations on (u++y relations7 The extension principle7 0u++y measures7Mem2ership (unctions7 0u++i(ication and de(u++i(ication methods7 0u++ycontrollers>

Te2t Boo*':

B> Simon Haykin7 Neural Network a 2 Comprehensi"e &oundation7 PearsonEducation

@> Aurada =>M>7 'ntroduction to Artificial Neural S#stems, =aico pu2lishers> Thimothy => 1oss7 %&u33# )o$ic with !n$ineerin$ Applications7 Mc-raw Hill4> hmad %2rahim7 'ntroduction to Applied &u33# !lectronicsI7 PH%

Re8erence':

B> Je)nanarayana ,>7 Artificial Neural Networks7 PH%@> .riankov .>7 Hellendoorn H> N 1ein(rank M>7 An 'ntroduction to &u33# ControlI7

8orosa Pu2lishin) House> ,erkan 1>&>7 and Tru2atch S>L>7 &u33# S#stems esi$n PrinciplesI7 %EEE

Press

TERM ,R;

!> Term work should consist o( at least B$ practical experiments and twoassi)nments coverin) the topics o( the sylla2us>

Page 22 of 3


23/39

Page 23 of 3


24/39


Su9ect: Mu%timeia '0'tem' an con/er&ence o8 Tec1no%o&ie' (E%ecti/e)



Mu%timeia '0'tem' an con/er&ence o8 tec1no%o&ie'

.e(inin) the scope o( multimedia7 Hypertext and &olla2orative research7 Multimedia andpersonalised computin)7 Multimedia on the map7 Emer)in) applications7 The challen)es

T1e con/er&ence o8 computer'$ Communication'$ an entertainment prouct'The technolo)y trends7 Multimedia appliances7 Hy2rid .evices7 .esi)ners perspective7industry perspective o( the (uture7 Key challen)es ahead7 Technical7 re)ulatory7 Social

Arc1itecture' an i''ue' 8or "i'tri9ute Mu%timeia '0'tem'

.istri2uted Multimedia systems7 Synchroni+ation7 and *S rchitecture7 The role o(Standards7 (rame work (or Multimedia systems

"i&ita% Auio Repre'entation an proce''in&6ses o( udio in &omputer pplications7 Psychoacoustics7 .i)ital representation o( sound7transmission o( di)ital sound7 .i)ital udio si)nal processin)7 .i)ital music makin)7 Speechreco)nition and )eneration7 di)ital audio and the computers9ideo Technolo)y1aster Scannin) Principles7 Sensors (or T9 &ameras7 &olour 0undamentals7 &olour 9ideo79ideo per(ormance Measurements7 nalo) video rti(acts7 video e3uipments7 World widetelevision standards

"i&ita% =ieo an Ima&e Compre''ion9ideo compression techni3ues7 standardi+ation o( l)orithm7 The =PE- %ma)e &ompressionStandard7 %T6#T 1ecommendations7 The EPE- Motion 9ideo &ompression Standard7 .9%Technolo)y

peratin& S0'tem Support 8or Continuou' Meia App%ication'Limitation o( Work station *peratin) system7 8ew *S support7 Experiments 6sin) 1eal TimeMach

Mi%eare S0'tem Ser/ice' Arc1itecture

-oals o( Multimedia System services7 Multimedia system services rchitecture7 Media streamprotocol

Mu%timeia "e/ice'$ Pre'entation Ser/ice'$ an t1e U'er Inter8ace&lient control o( continuous multimedia7 .evice control7 Temporal coordination andcomposition7 toolkits7 hyperapplications

Mu%timeia !i%e '0'tem' an In8ormation Moe%'The case (or multimedia in(ormation systems7 The (ile system support (or continuous Media7.ata models (or multimedia and Hypermedia in(ormation7 &ontent# 2ased 1etrieval o(6nstructured .ata

Mu%timeia pre'entation an Aut1orin&Page 24 of 3


25/39

.esi)n paradi)ms and 6ser inter(ace7 2arriers to wide spread use7 research trends

Mu%timeia Ser/ice' o/er t1e Pu9%ic Netor*'1e3uirements7 rchitecture7 and protocols7 8et work services7 applications

Mu%timeia Interc1an&euick time Movie 0ile 0ormat7 M0%7 MHE- Multimedia and Hypermedia %n(ormationEncodin) Expert -roup57 0ormat 0unction and representation7 Track model and *2:ect model71eal Time %nterchan)e

Mu%timeia con8erencin&Telecon(erencin) Systems7 1e3uirements o( Multimedia &ommunications7 Shared pplicationrchitecture and em2edded .istri2uted o2:ects7 Multimedia &on(erencin) rchitecture

Mu%timeia #roupare&omputer and 9ideo (usion approach to open shared wok place7 Hi)h .e(inition Television anddesktop computin)7 H.T9 standards7 Knowled)e 2ased Multimedia systems7 natomy o( an%ntelli)ent Multimedia system

Te2t Boo*Multimedia Systems 2y =ohn 0> Koe)el ,u(ord# Pearson Education


SUBJECT: Arti8icia% Inte%%i&ence


T1eor0: >77 Mar*'Term ,or* - Practica%: 57 Mar*'

> AI an Interna% Repre'entationrti(icial %ntelli)ence and the World7 1epresentation in %7 Properties o( %nternal1epresentation7 The Predicate &alculus7 Predicates and r)uments7 &onnectives 9aria2lesand uanti(ication7 How to 6se the Predicate &alculus7 *ther Kinds o( %n(erence %ndexin)7Pointers and lternative 8otations7 %ndexin)7 The %sa Hierarchy7 Slot#ssertion 8otation70rame 8otation

? Li'p'Lisps7 Typin) at Lisp7 .e(inin) Pro)rams7 ,asic 0low o( &ontrol in Lisp7 Lisp Style7 toms andLists7 ,asic .e2u))in)7 ,uildin) 6p List Structure7 More on Predicates7 Properties7 Pointers7&ell 8otation and the %nternals lmost5 o( Lisp7 .estructive Modi(ication o( Lists7 The (or

0unction 71ecursion7 Scope o( 9aria2les7 %nput/*utput7 Macros

3. Neura% Netor*' an !uDD0 '0'tem'8eural and (u++y machine %ntelli)ence7 0u++iness as Multivalence7 The .ynamical Systemsapproach to Machine %ntelli)ence7 The 2rain as a dynamical system7 8eural and (u++y systemsas (unction Estimators7 8eural 8etworks as traina2le .ynamical system7 0u++y systems andapplications7 %ntelli)ent ,ehavior as daptive Model (ree Estimation7 -enerali+ation andcreativity7 Learnin) as chan)e7 Sym2ol vs 8um2ers7 1ules vs Principles7 Expert systemKnowled)e as rule trees7 Sym2olic vs 8umeric Processin)7 0u++y systems as Structured8umerical estimators7 -eneratin) 0u++y rules with product space &lusterin)7 0u++y Systemsas Parallel associators7 0u++y systems as Principle 2ased Systems

Neura% Netor* T1eor0Page 25 of 3


26/39

8euronal .ynamicsC ctivations and si)nals$ 8eurons as (unctions7 si)nal monotonicity7,iolo)ical ctivations and si)nals7 8euron 0ields7 8euron .ynamical Systems7 &ommon si)nal(unctions7 Pulse#&oded Si)nal (unctions

#enetic A%&orit1m' simple )enetic al)orithm7 simulation 2y hands7 similarity templatesSchemata57Mathematical (oundations7 Schema Processin) at work7 The two# armed and k#armed ,anditPro2lem7 The 2uildin) 2lock hypothesis7 The minimal .eceptive Pro2lem

&omputer implementation o( -enetic al)orithm7 .ata Structures7 1eproduction 7 &ross overand Mutation7 Time to reproduce and time to &ross Mappin) o2:ective (unction to (itness (orm70itness scalin)pplications o( )enetic al)orithm7 .e =on) and 0unction *ptimi+ation7 %mprovement in 2asictechni3ues7 %ntroduction to -enetics 2ased machine learnin)7 applications o( )enetic 2asedmachine leanin)

>. "ata Minin&%ntroduction to .ata Minin)7 &omputer systems that can learn7 Machine learnin) and

methodolo)y o( science7 &oncept learnin)7 .ata ware house7 desi)nin) decision supportsystems7 &lient server and data warehousin)7 Knowled)e .iscovery Process7 9isuali+ationTechni3ues7 K# nearest nei)h2or7 .ecision trees7 *LP tools7 8eural networks7 -enetical)orithm7 Settin) up a K.. environment7 1eal li(e applications7 &ustomer pro(ilin)7.iscoverin) (orei)n key relationships

A''i&nment'

10 assignments covering the syllabus has to be submitted

Te2t 9oo*

B> %ntroduction to rti(icial %ntelli)ence ,y Eu)ene &harniak7 .rew Mc.ermott# ddisonWesley

@> 8eural 8etworks and (u++y systems dynamical systems approach to machine%ntelli)ence 2y ,art Kosko# PH%

> -enetic l)orithms in search7 *ptimi+ation N Machine Learnin) 2y .avid E -old2er)#ddison wesley

4> .ata Minin) 2y Pieter driaans and .ol( Aantin)e ? Pearson Education sia"> .ata Warehousin) in the 1eal World 2y Sam nahory and .ennis Murray7 ddison

#Wesley


SUBJECT: IMA#E PRCESSIN#



9ecti/e: .i)ital %ma)e Processin) is a rapidly evolvin) (ield with )rowin)applications in science and en)ineerin)> %ma)e processin) holds the possi2ility o(developin) the ultimate machine that could per(orm the visual (unctions o( all livin)2ein)s> There is an a2undance o( ima)e processin) applications that can servemankind with the availa2le and anticipated technolo)y in the near (uture>

Page 2) of 3


27/39

"ETAILE" SYLLABUS

B> "i&ita% Ima&e Proce''in& S0'tem': %ntroduction7 Structure o( human eye7%ma)e (ormation in the human eye7 ,ri)htness adaptation and discrimination7%ma)e sensin) and ac3uisition7 Stora)e7 Processin)7 &ommunication7 .isplay>%ma)e samplin) and 3uanti+ation7 ,asic relationships 2etween pixels

@> Ima&e Tran'8orm' (Imp%ementation): %ntroduction to 0ourier trans(orm7 .0Tand @#. .0T7 Properties o( @#. .0T7 00T7 %00T7 Walsh trans(orm7 Hadamardtrans(orm7 .iscrete cosine trans(orm7 Slant trans(orm7 *ptimum trans(ormCKarhunen # Loeve Hotellin)5 trans(orm>

> Ima&e En1ancement in t1e Spatia% "omain: -ray level trans(ormations7Histo)ram processin)7 rithmetic and lo)ic operations7 Spatial (ilterin)C%ntroduction7 Smoothin) and sharpenin) (ilters

4> Ima&e En1ancement in t1e !re@uenc0 "omain: 0re3uency domain (iltersCSmoothin) and Sharpenin) (ilters7 Homomorphic (ilterin)

"> ,a/e%et' an Mu%tire'o%ution Proce''in&: %ma)e pyramids7 Su22andcodin)7 Haar trans(orm7 Series expansion7 Scalin) (unctions7 Wavelet(unctions7 .iscrete wavelet trans(orms in one dimensions7 0ast wavelet

trans(orm7 Wavelet trans(orms in two dimensions> Ima&e "ata Compre''ion: 0undamentals7 1edundanciesC &odin)7 %nterpixel7Psycho#visual7 0idelity criteria7 %ma)e compression models7 Error (reecompression7 Lossy compression7 %ma)e compression standardsC ,inary ima)eand &ontinuous tone still ima)e compression standards7 9ideo compressionstandards>

!> Morp1o%o&ica% Ima&e Proce''in&:%ntroduction7 .ilation7 Erosion7 *penin)7&losin)7 Hit#or#Miss trans(ormation7 Morpholo)ical al)orithm operations on2inary ima)es7 Morpholo)ical al)orithm operations on )ray#scale ima)es

F> Ima&e Se&mentation: .etection o( discontinuities7 Ed)e linkin) and,oundary detection7 Thresholdin)7 1e)ion 2ased se)mentation

G> Ima&e Repre'entation an "e'cription: 1epresentation schemes7,oundary descriptors7 1e)ional descriptors

Te2t Boo*':

>. 1>&>-onsales 1>E>Woods$ i$ital 'ma$e Processin$I7Second Edition7Pearson Education

@> nil K>=ain7 &undamentals of 'ma$e Processin$I7 PH%

Re8erence':

B> William Pratt7 i$ital 'ma$e Processin$I7 =ohn Wiley> Milan Sonka79aclav Hlavac7 1o)er ,oyle7 'ma$e Processin$, Anal#sis,

and Machine 4isionI Thomson Learnin)@> 8 hmed N K>1> 1ao7 5rtho$onal Transforms for i$ital Si$nal Processin$I

Sprin)er> ,> &handa7 .> .utta Ma:umder7 i$ital 'ma$e Processin$ and Anal#sisI7 PH%>

T#M W$#%

F> Term work should consist o( at least B$ practical experiments and twoassi)nments coverin) the topics o( the sylla2us>


Page 27 of 3


28/39

SUBJECT: "ISTRIBUTE" CMPUTIN#


T1eor0: >77 Mar*'Term or*: ?5 Mar*'

9ecti/e: This course aims to 2uild concepts re)ardin) the (undamentalprinciples o( distri2uted systems> The desi)n issues and distri2uted operatin)system concepts are covered>

"ETAILE" SYLLABUS

B> Introuction to "i'tri9ute S0'tem: -oals7 Hardware concepts7 So(twareconcepts7 and &lient#Server model> Examples o( distri2uted systems>

@> Communication: Layered protocols7 1emote procedures call7 1emote o2:ectinvocation7 Messa)e#oriented communication7 Stream#oriented communication>

> Proce''e': Threads7 &lients7 Servers7 &ode Mi)ration7 So(tware a)ent>4> Namin&: 8amin) entities7 Locatin) mo2ile entities7 1emovin) un#re(erenced

entities>

"> S0nc1roniDation: &lock synchroni+ation7 Lo)ical clocks7 -lo2al state7Election al)orithms7 Mutual exclusion7 .istri2uted transactions>

> Con'i'tenc0 an Rep%ication: %ntroduction7 .ata centric consistency models7&lient centric consistency models7 .istri2ution protocols7 &onsistencyprotocols>

!> !au%t To%erance: %ntroduction7 Process resilience7 1elia2le client servercommunication7 1elia2le )roup communication> .istri2uted commit7 1ecovery>

F> Securit0: %ntroduction7 Secure channels7 ccess control7 Securitymana)ement>

G> "i'tri9ute !i%e S0'tem: Sun network (ile system7 &*. (iles system>B$>Ca'e Stu0: &*1,7 .istri2uted &*M7 -lo2e7 &omparison o( &*1,7

.&*M7 and -lo2e>Te2t Boo*':

B> > Taunen2aum7istributed S#stems: Principles and Paradi$msG@> -> &oulouris7 => .ollimore7 and T> Kind2er)7 istributed S#stems: Concepts

and esi$nI7 Pearson Education

Re8erence':

B> M> Sin)hal7 8> Shivaratri7 Ad"anced Concepts in 5peratin$ S#stemsI7 TMH

TERM ,R;

G> Term work should consist o( at least B$ practical experiments and twoassi)nments coverin) the topics o( the sylla2us>


Page 2= of 3


29/39

SUBJECT: EMBE""E" SYSTEMS



9ecti/e: Em2edded system tools and products are evolvin) rapidly> Thiscourse deals with various approaches to 2uildin) em2edded systems> %t introducesuni(ied view o( hardware and so(tware> The aim o( this course is to make thestudents aware o( the various applications o( em2edded systems>

"ETAILE" SYLLABUS

B> An o/er/ie o8 em9ee '0'tem':%ntroduction to em2edded systems7&ate)ories and re3uirements o( em2edded systems7 &hallen)es and issuesrelated to em2edded so(tware development7 Hardware/So(tware co#desi)n7%ntroduction to %& technolo)y7 %ntroduction to desi)n technolo)y

@> Em9ee So8tare e/e%opment: &oncepts o( concurrency7 processes7

threads7 mutual exclusion and inter#process communication7 Models andlan)ua)es (or em2edded so(tware7 Synchronous approach to em2eddedsystem desi)n7 Schedulin) paradi)ms7 Schedulin) al)orithms7 %ntroduction to1T*S7 ,asic desi)n usin) 1T*S

> Em9ee C Lan&ua&e: 1eal time methods7 Mixin) & and ssem2ly7Standard %/* (unctions7 Preprocessor directives7 Study o( & compilers and %.E7Pro)rammin) the tar)et device

4> arare 8or em9ee '0'tem': 9arious inter(ace standards7 9ariousmethods o( inter(acin)7 Parallel %/* inter(ace7 ,lind countin) synchroni+ationand -ad(ly ,usy waitin)7Parallel port inter(acin) with switches7 keypads anddisplay units7 Memory and hi)h speed inter(acin)7 %nter(acin) o( data

ac3uisition systems7 %nter(acin) o( controllers7 Serial communication inter(ace7%mplementation o( a2ove concepts usin) & lan)ua)e

"> Stu0 o8 ATMEL RISC Proce''or:rchitecture7 Memory7 1eset andinterrupt 7 (unctions7 Parallel %/* ports7 Timers/&ounters7 Serial communication7nalo) inter(aces7 %mplementation o( a2ove concepts usin) & lan)ua)e7%mplementation o( a2ove concepts usin) & lan)ua)e

> Ca'e 'tuie' an App%ication' o8 em9ee '0'tem':pplications toC&ommunication7 8etworkin)7 .ata2ase7 Process &ontrol7 &ase Studies o(C.i)ital &amera7 8etwork 1outer7 1TLinux

Te2t Boo*':

B> 1a: Kamal7 !mbedded S#stemsI7 TMH@> .avid E> Simon7 An !mbedded Software PrimerO7 Pearson Education> Muhammad li Ma+idi and =anice -illispie Ma+idi7 The 6170Microcontroller

and !mbedded S#stems8,Pearson Education

Re8erence':

B> 0rank 9ahid7 Tony -ivar)is7 !mbedded S#stem esi$n: A +nified9ardwareSoftware 'ntroductionO7 =ohn Wiley

@> &rai) Holla2au)h7 !mbedded )inuO7 Pearson Education> .aniel Lewis7 &undamentals of !mbedded SoftwareI7 Pearson Education>

4> ,arnett7 &ox7 *;&ull7 !mbedded C Pro$rammin$ and the Atmel A4; O7Thomson Learnin)

Page 2< of 3


30/39

"> Myke Predko7 Pro$rammin$ and Customi3in$ the 6170 MicrocontrollerI7 TMH)> mbedded Microcomputer S&stems' #eal Time "nter(acin)

' onat$an #> al&ano

7> ?*me""e" C@ ' M>> Pont>

TERM ,R;

B$>Term work should consist o( at least B$ practical experiments and twoassi)nments coverin) the topics o( the sylla2us>

0our experiments on micro controller 2ased systems>

0our experiments usin) cross & compiler and Linux>

Two experiments usin) developments tools like lo)ic analy+er7 emulator

and simulator>

Two experiments on case study o( advanced em2edded systems


SUBJECT: PATTERN REC#NITIN (E%ecti/e)

Lecture': + r' per ee*Practica%: 66


9ecti/e: This course teaches the (undamentals o( techni3ues (or classi(yin)multi#dimensional data7 to 2e utili+ed (or pro2lem#solvin) in a wide variety o(applications7 such as en)ineerin) system desi)n7 manu(acturin)7 technical andmedical dia)nostics7 ima)e processin)7 economics7 psycholo)y>

"ETAILE" SYLLABUS

B> Introuction:Machine perception7 Pattern reco)nition systems7 .esi)n cycle7Learnin) and daptation

@> Ba0e'ian "eci'ion T1eor0:,ayesian decision theoryC &ontinuous (eatures7Minimum#error rate classi(ication7 classi(ication7 &lassi(iers7 .iscriminant(unctions and .ecision sur(aces7 8ormal density7 .iscriminant (unctions (ornormal density7 ,ayes .ecision theoryC discrete (eatures

> Ma2imum6Li*e%i1oo an Ba0e'ian Parameter E'timation:Maximumlikelihood estimation7 ,ayesian estimation7 ,ayesian parameter estimationC-aussian caseand -eneral theory7 Prolems o( dimentionality7 Hidden Markov

Model4> Nonparametric Tec1ni@ue':.ensity estimation7 Par+en windows7 kn#8earest#

8ei)h2or estimation7 8earest#8ei)h2or rule7 Matrics and 8earest#8ei)h2orclassi(ication

"> Linear "i'criminant' !unction':Linear discriminant (unctions and decisionsur(aces7 -eneralised linear discriminant (unctions7 @#&ate)ory linearlysepara2le case7 Minimisin) the Perceptron criterion (unction7 1elaxationprocedure7 8on#separa2le 2ehavior7 Minimum s3uared error procedure7 Ho#Kashyap procedures7 Multicate)ory )enerali+ations

> Nonmetric Met1o': .ecision tree7 &1T7 %.7 &4>"7 -ramatical methods7-ramatical inter(aces

!> A%&orit1m Inepenent Mac1ine Learnin&: Lack o( inherent superiority o(any classi(ier7 ,ias and 9ariance7 1esamplin) (or estimatin) statistic7

Page 30 of 3


31/39

1esamplin) (or classi(ier desi)n7 Estimatin) and comparin) classi(iers7&om2inin) classi(iers

F> Un'uper/i'e Learnin& an C%u'terin&: Mixture densities and %denti(ia2ility7Maximum#Likelihood estimations7 pplication to normal mixtures7 6nsupervised,ayesian learnin)7 .ata description and clusterin) criterion (unction (orclusterin)7 Hierarchical clusterin)

H. App%ication' o8 Pattern Reco&nition

Te2t Boo*':

B> .uda7 Hart7 and Stock7 Pattern ClassificationI7 =ohn Wiley and Sons>@> -ose7 =ohnson2au)h and =ost7 Pattern ;eco$nition and 'ma$e anal#sisI7 PH%

TERM ,R;

BB>Term work should consist o( at least B$ practical experiments and twoassi)nments coverin) the topics o( the sylla2us>


SUBJECT: CMPUTER =ISIN (E%ecti/e)



9ecti/e:To introduce the student to computer vision al)orithms7 methods andconcepts which will ena2le the student to implement computer vision systems withemphasis on applications and pro2lem solvin)

"ETAILE" SYLLABUS

B> Reco&nition Met1oo%o&0:&onditionin)7 La2elin)7 -roupin)7 Extractin)7Matchin)> Ed)e detection7 -radient 2ased operators7 Morpholo)ical operators7Spatial operators (or ed)e detection> Thinnin)7 1e)ion )rowin)7 re)ionshrinkin)7 La2elin) o( connected components>

@> Binar0 Mac1ine =i'ion: Thresholdin)7 Se)mentation7 &onnected componentla2elin)7 Hierarchal se)mentation7 Spatial clusterin)7 Split N mer)e7 1ule#2ased Se)mentation7 Motion#2ased se)mentation>

> Area E2traction:&oncepts7 .ata#structures7 Ed)e7 Line#Linkin)7 Hou)htrans(orm7 Line (ittin)7 &urve (ittin) Least#s3uare (ittin)5>

4> Re&ion Ana%0'i':1e)ion properties7 External points7 Spatial moments7 Mixedspatial )ray#level moments7 ,oundary analysisC Si)nature properties7 Shapenum2ers>

"> !acet Moe% Reco&nition:La2elin) lines7 6nderstandin) line drawin)s7&lassi(ication o( shapes 2y la2elin) o( ed)es7 1eco)nition o( shapes7&onsistin) la2elin) pro2lem7 ,ack#trackin)7 Perspective Pro:ective )eometry7%nverse perspective Pro:ection7 Photo)rammetry ? (rom @. to .7 %ma)ematchin) C %ntensity matchin) o( %. si)nals7 Matchin) o( @. ima)e7 Hierarchicalima)e matchin)>

> 9ect Moe%' An Matc1in&:@. representation7 -lo2al vs> Local (eatures>

!> #enera% !rame ,or*' !or Matc1in&:.istance relational approach7 *rdered#structural matchin)7 9iew class matchin)7 Models data2ase or)ani+ation>

Page 31 of 3


32/39

F> #enera% !rame ,or*':.istance ?relational approach7 *rdered ?Structuralmatchin)7 9iew class matchin)7 Models data2ase or)ani+ation>

G> ;no%e&e Ba'e =i'ion:Knowled)e representation7 &ontrol#strate)ies7%n(ormation inte)ration>

Te2t Boo*':

B> .avid > 0orsyth7 =ean Ponce7 %Computer 4ision: A Modern Approach@> 1> =ain7 1> Kasturi7 and ,> -> Schunk7 %Machine 4ision7 Mc-raw#Hill>

Re8erence':

B> Milan Sonka79aclav Hlavac7 1o)er ,oyle7 'ma$e Processin$, Anal#sis,and Machine 4isionI Thomson Learnin)

@> 1o2ert Haralick and Linda Shapiro7 %Computer and ;obot 4ision7 9ol %7 %%7ddison#Wesley7 BGG>

TERM ,R;

B@>Term work should consist o( at least B$ practical experiments and two

assi)nments coverin) the topics o( the sylla2us>


Su9ect: =irtua% Rea%it0 an =irtua% En/ironment (E%ecti/e)



1eal time computer )raphics7 0li)ht simulation7 virtual environment7 ,ene(its o( virtual reality7Evolution o( 9irtual 1eality7 Historical perspective7 scienti(ic land marks

3" Computer &rap1ic'The virtual world space7 positionin) the virtual o2server7 the perspective pro:ection7 Humanvision7 Stereo perspective pro:ection7 . clippin)7 colour theory7 simple . modellin)7illumination models7 shadin) al)orithms7 radiosity7 hiddensur(ace removal7 realism7stereo)raphic ima)es

#eometric moe%%in&0rom @. to .7 . space curves7 . 2oundary representation7

#eometrica% Tran'8ormation'0rames o( re(erence7 Modellin) trans(ormations7 instances7 pickin) (lyin)7 Scalin) the 9E7&ollision detection

A &eneric =R S0'tem'The virtual Environment7 The computer environment7 91 Technolo)y7 Modes o( %nteraction7 91systems

Animatin& t1e =irtua% En/ironment

Page 32 of 3


33/39

.ynamics o( num2ers7 the animation o( o2:ects7 shape and o2:ect in2etweenin)7 (ree#(ormde(ormation7 particle systems

P10'ica% Simu%ation*2:ects (allin) in a )ravitational (ield7 rotatin) wheels7 Elastic collisions7 Pro:ectiles7 simplependulums7 sprin)s7 (li)ht dynamics o( an aircra(t

uman 8actor'The eye7 The ear7 the somatic senses7 E3uili2rium

=irtua% Rea%it0 arareSensor hardware7 Head#coupled displays7 coustic hardware7 %nte)rated 91 Systems

=irtua% Rea%it0 So8tareModellin) 9irtual worlds7 Physical simulation7 91 tool kits

=irtua% Rea%it0 App%ication'En)ineerin)7 Entertainment7 science7 Education7 trainin)7 0uture 9irtual environment7 Modes

o( %nteraction

Te2t Boo*'

9irtual 1eality Systems =ohn 9ince# Pearson Education sia


SUBJECT: Ja/a Tec1no%o&0 (E%ecti/e)

Lecture': + r' per ee*

Practica%: 66

T1eor0: >77 Mar*'

Term or*-Practica%: 66 Mar*'

Ja/a Pro&rammin&*2:ect oriented pro)rammin) revisited7 =.K7 =ava 9irtual machine#Plat(orm independent#porta2ility#scala2ility *perators and expressions#decision makin) 72ranchin)7 loopin)7 &lasses7*2:ects and methods7 rrays Strin)s and 9ectors7 %nter(aces7 Packa)es7 Multi#Threadin)7mana)in) errors and exceptions7 pplet pro)rammin)7 Mana)in) (iles and streams

Ja/a Tec1no%o&0 8or Acti/e ,e9 "ocument'n Early 0orm o( &ontinuous 6pdate7 ctive .ocuments and Server *verhead7 ctive

.ocument 1epresentation and Translation7 =ava Technolo)y7 the =ava 1un#Time Environment7The =ava Li2rary -raphics Toolkit7 6sin) =ava -raphics on a Particular &omputer7 =ava %nterpreters and,rowsers

&ompilin) a =ava Pro)ram7 %nvokin) an pplet7 Example o( %nteraction with a ,rowser

RPC an Mi%earePro)rammin) &lients and Servers7 1emote Procedure &all Paradi)m7 1P& Paradi)m7&ommunication Stu2s7 External .ata 1epresentation7 Middleware and *2:ect#*rientedMiddleware

Netor* Mana&ement (SNMP)Page 33 of 3


34/39

Mana)in) an %nternet7 The .an)er o( Hidden 0eatures7 8etwork Mana)ement So(tware7&lients7 Servers7 Mana)ers and )ents7 Simple 8etwork Mana)ement Protocol7 0etch#StoreParadi)m7 The M%P and *2:ect 8ames7 The 9ariety o( M%, 9aria2les7 M%, varia2les thatcorrespond to arrays

Ja/a tec1no%o&ie'-raphics7 =0=9 (oundation classes7 swin)7 ima)es7 :ava @d )raphics7 internationali+ation7&ommunication and 8etworkin)7 T&P Sockets7 6.P Sockets7 java.net, :ava security7 *2:ectseriali+ation7 1emote method seriali+ation7 =.,&C =ava .ata ,ase &onnectivity7 =ava 2eans7=ava inter(ace to &*1,7 =9# &*M %nte)ration7 =ava Media 0ramework7 commerce and:ava wallet7 .ata structures and :ava utilities7 =avaScript7 Servelets

TERM ,R;Term work should consist o( at least $ assi)nments includin) de2u))ed :ava source code (orthe applications (rom the a(orementioned topics> Seminar to 2e presented 2y each studentas part o( term work carryin) B" marks>

RE!ERENCE

6sin) =9 @7 =oseph L we2er7 PH%=9 @ complete7 Sy2ex7 ,P,=ava@ The complete 1e(erence7 Patrick 8au)hton7 T M H&omputin) concepts With =9@7 &ay Horstmann7 W%LEJ=SP =ava Server Pa)es7 ,arry ,urd7 %.- ,ooks %ndiap5 Ltd=ava@ Pro)rammin) ,i2le7 aron Walsh7 %.- ,ooks %ndiap5 Ltd=ava@7 swin)7 servlets7 =.,& N =9 ,eans Pro)rammin) ,lack ,ook Steven Hol+nerdreamtech press&omputer 8etworks and %nternets 2y .r> .ou)las &omer 5

CLASS: M. Sc (Computer Science) Jear %%SUBJECT: Bioin8ormatic' (E%ecti/e)

Periods per week BPeriod is "$minutes

Lecture 4

TW/Practical ##

Hours Marks

Evaluation System Theory Examination B$$

TW/Tutorial/Practical ## ##

/er/ie%n(ormation networks# Protein in(ormation resources#-enome %n(ormation resources# .8

Se3uence analysis# pair wise ali)nment techni3ues#multiple se3uenceali)nment#Secondary data2ase searchin)#2uildin) a se3uence search protocol

%ntroduction

The 2iolo)ical se3uence structure de(icit# -enome Pro:ects#pattern reco)nition and prediction?the role o( chaperones#se3uence nalysis#Homolo)y and analo)y>

Page 34 of 3


35/39

In8ormation Netor*'1eview o( computer communication networks#the European molecular 2iolo)y network#

EM,net#8ational &enter (or ,iotechnolo)y %n(ormation#8&,%# virtual tourism>

Protein %n(ormation resources,iolo)ical .ata ,ases#Primary se3uence .ata2ases#&omposite Protein se3uence data2ases#

Secondary data2ases# &omposite Protein pattern data2ases#structureclassi(ication data2ases#we2 addresses

-enome %n(ormation resources.8 Se3uence nalysisPairwise ali)nment Techni3uesMultiple se3uence ali)nmentSecondary data2ase searchin),uildin) a se3uence search Protocolnalysis packa)es

Term ,or*B$ assi)nments coverin) the entire sylla2us

Page 35 of 3


36/39


SUBJECT: INTELLI#ENT SYSTEMS (E%ecti/e)



9ecti/e': To understand and apply principles7 methodolo)ies and techni3ues indesi)n and implementation o( intelli)ent system>

"ETAILE" SYLLABUS

B> Arti8icia% Inte%%i&enceC n overview7 %ntelli)ent SystemsC Evolution o( theconcept>

@> Inte%%i&ent A&ent'C How a)ent should act7 Structure o( intelli)ent a)ents7Environments

> Pro9%em So%/in&:Solvin) pro2lems 2y searchin)7 %n(ormed search methods7-ame playin)4> ;no%e&e an Rea'onin&: knowled)e 2ased a)ent7 The wumpus world

environment7 1epresentation7 1easonin)7 Lo)ic7 Proportional lo)ic7 0irst orderlo)icC Syntax and Semantics7 Extensions and 8otational variation7 6sin) (irstorder lo)ic

"> Bui%in& a ;no%e&e Ba'e:Properties o( )ood and 2ad knowled)e 2ase7Knowled)e en)ineerin)7 -eneral ontolo)y

> Inter8acin& !ir't rer Lo&ic:%nter(ace rules involvin) 3uanti(iers7 nexample proo(7 0orward and 2ackward chainin)7 &ompleteness

!> Actin& Lo&ica%%0:Plannin)7 Practical plannin)C Practical planners7

Hierarchical decomposition7 &onditional plannin)F> Uncertain ;no%e&e an Rea'onin&: 6ncertainty7 1epresentin) knowled)e

in an uncertain domain7 The semantics o( 2elie( networks7 %n(erence in 2elie(networks

G> Learnin&: Learnin) (rom o2servationsC -eneral model o( learnin) a)ents7%nductive learnin)7 learnin) decision trees7 Learnin) in neural and 2elie(networksC %ntroduction to neural networks7 Perceptrons7 Multilayer (eed#(orwardnetwork7 pplication o( 887 1ein(orcement learnin)C Passive learnin) in aknown environment7 -enerali+ation in rein(orcement learnin)7 -enetical)orithms

B$>A&ent' t1at Communicate: &ommunication as action7 Types o(

communicatin) a)ents7 (ormal )rammar (or a su2set o( En)lishBB>E2pert '0'tem:%ntroduction to expert system7 1epresentin) and usin)

domain knowled)e7 Expert system shells7 Explanation7 Knowled)e ac3uisitionB@>App%ication':8atural lan)ua)e processin)7 Perception7 1o2otics

Te2t Boo*':

B> Struart 1ussell and Peter 8orvi)7 Artificial 'ntelli$ence: A Modern ApproachI@> -eor)e 0>Lu)er7 %Artificial 'ntelli$ence: Structures and Strate$ies for Comple

Problem Sol"in$7 Pearson Education

Re8erence':

B> 8ils => 8illson7 %Artificial 'ntelli$ence: A New S#nthesis7 Harcourt sia

Page 3) of 3


37/39

@> Elaine 1ich and Kevin Kni)ht7 Artificial 'ntelli$ence7 TMH> Patrick Winston7 Artificial 'ntelli$ence7 Pearson Education4> %van ,rakto7 Prolo$ Pro$rammin$ for Artificial 'ntelli$enceI7 Pearson

Education"> E(raim Tur2an =ay E>ronson7 ecision Support S#stems and 'ntelli$ent

S#stemsI> Ed> M> Sasikumar and *thers7 %Artificial 'ntelli$ence : Theor# and Practice

Proceedin)s o( the %nternational &on(erence K,&S#@$$@7 9ikas Pu2lishin)House

TERM ,R;

B>Term work should consist o( at least B$ practical experiments and twoassi)nments coverin) the topics o( the sylla2us>


PTIMIFATIN (E%ecti/e)

Perio' per ee* Lecture +

Practica% 66

Tutoria% 66

our' Mar*'

E/a%uation S0'tem T1eor0 E2am 3 >77

Teror* -Practica%

66 66

"etai%e S0%%a9u'

INTR"UCTIN8eed (or optimi+ation and historical development classi(ication and (ormulation o( optimi+ationpro2lem7 &lassical optimi+ation methods7 &alculus 2ased methods7 Enumerative schemes71andom search al)orithms7 Evolutionary al)orithms>

0ormulation o( Primary and Su2sidiary desi)n e3uations7 Limit e3uations and 8ormalredundant and incompati2le speci(ication>

Exact and %nteractive techni3ues> *ptimal desi)n o( elements and systems7 sha(ts7 )ears72earin)s7 Hi)h#speed machinery7 cams etc>

Linear Pro&rammin& moe%0ormulation7 o2:ective (unction7 constraints7 decision varia2les7 canonical and standard (orms7parameters and varia2les7 classical pro2lems such as crew schedulin)7 Knap sack7napkin/caterer7 product mix etc>-raphical method (or two varia2le pro2lems7 simplex al)orithm and ta2ular representation7types o( solution such as (easi2le / non (easi2le7 de)enerate / non de)enerate7 optimal / su2optimal7 uni3ue / alternate / in(inite optimal7 2ounded / un2ounded value and solution and theirinterpretations (rom simplex ta2le7 cyclin) phenomena7 mutual solution o( pro2lems involvin)upto three iterations>.uality concept7 dual pro2lem (ormulation7 dual simplex method7 primal su2 optimal # dual not(easi2le7 and other primal # dual relations7 interpretation o( dual varia2les>.uality Properties7 sensitivity analysis (or variation o( parameter at a time>Transportation7 Transshipment and ssi)nment models>

Page 37 of 3


38/39

s special cases o( LP model7 Pro2lem (ormulation and optimality conditions in 9o)els penaltyand Hun)arian methods o( solution> travelin) salesman pro2lem as a special case o(assi)nment pro2lem7 sensitivity analysis manual solution o( pro2lems involvin) upto threeiterations>

Inte&er LP Moe%'-omarys &uttin) plane al)orithms7 2ranch and 2ound techni3ue (or inte)er pro)rammin)

Simu%ation Moe%'Monte &arlo or experimentin) method 2ased on Pro2a2ilistic 2ehavior data and randomnum2ers7 application in Pro2a2ilistic real li(e pro2lems

TERM ,R;:B$ ssi)nments coverin) the entire sylla2us>

TET B;S:B> *ptimi+ation Theory and application 2y S>>S 1ao>

RE!ERENCE B;S:B> *ptimi+ation (or En)ineerin) .esi)n 2y .e2 N Kalyanway>@> *ptimi+ation Methods 2y Mital K>9> *peration 1esearch # n %ntroduction 2y H>> Taha>4> Statistical .istri2ution in En)ineerin) 2y Karl ,ury>"> rti(icial %ntelli)ence Throu)h Simulated Evolution 2y 0o)ed7 *wence and Walsh>> &on(erence proceedin)s ? nnual con(erence on Evolution pro)rammin)

>


SUBJECT: CRM (Cu'tomer Re%ation' Mana&ement) (E%ecti/e)

Perio' per ee* Lecture +T,-Practica% 66

our' Mar*'

E/a%uation S0'tem T1eor0 E2amination 3 >77

T,-Practica% 66 66

B> %ntroduction to &1M C what is a customer' How do we de(ine &1M' &1M technolo)y7&1M technolo)y components7 customer li(e style7 customer interaction>

@> %ntroduction to e&1M C di((erence 2etween &1M N e&1M7 (eatures o( e&1M>

> Sales 0orce utomationS05 C de(inition N need o( S07 2arriers to success(ul S07S0C(unctionality 7 technolo)ical aspect o( S0C data synchroni+ation 7 (lexi2ility Nper(ormance 7 reportin) tools>

4> Enterprise Marketin) utomation EM5C components o( EM7 marketin) campin)7campin)7 plannin) N mana)ement7 2usiness analytic tools7 EM componentspromotions7 events7 loyalty N retention pro)rams57 response m)mt>

"> &all &enters Mean &ustomer %nteractionC the (unctionality7 technolo)icalimplementation7 what is &.automatic call distri2ution57%91interactive voice

Page 3= of 3


39/39

response57 &T%computer telephony inte)ration57we2 ena2lin) the call center7 automatedintelli)ent call routin)7 lo))in) N monitorin)>

> %mplementin) &1MC pre implementation7 kick o(( meetin)7 re3uirements )atherin)7prototypin) N detailed proposal )eneration7 development o( customi+ation7 Power 6ser,eta Test N .ata import7 trainin)7 roll out N system hand o((7 on)oin) support 7 systemoptimi+ation7 (ollow up>

!> %ntroduction to SP application service provider5C who are SP;s'7 their role N (unction7advanta)es N disadvanta)es o( implementin) SP>

Re8erence':B>&1M at the speed o( li)ht 2y Paul -reen2er)7TMH>@> &ustomer 1 elations Mana)ement 2y Kristin nderson N &arol Kerr> TMH>

Term or*B$ assi)nments coverin) the entire sylla2us>


Proect I (I 0ear) an II (II Year)Perio' per ee* Lecture 66

Practica% +

Tutoria% 66

our' Mar*'

E/a%uation S0'tem Proect 66 57

E2amination 66 57

#uie%ine' 8or 'u9mi''ion o8 report o8 Proect I an IIBo0 o8 Proect

%ntroductionLiterature Survey*2:ectiveMethodolo)y0easi2ility study.esi)n/synthesis/nalysis0a2rication and .etails.rawin)sTest set up and Tests1esults

&ase Study1esults / .iscussion&onclusion0uture work1e(erences

Appeni2This should contain .rawin)s7 -raphs7 codin) used etc>

Documents

M.Sc. New Syllabus.doc