SyllabusSavitribaiPhulePuneUniversityFacultyofEngineeringB.E.ComputerEngineering(Course2012)(w.e.fJune2015)BoardofStudiesComputerEngineeringMay31,2015PreambleIt is my pleasure to present this B.E. Computer Engineering Syllabus. The syllabus is a blend of concepts andadvancesusinghighendFOSStechnologies. OneoftheobjectivesofthethissyllabusistocultivatestudentsforusingFOSSandcontributionsinFOSS. Thetheorysubjectsarebasedonthepre-requisitescoveredinrstyeartothirdYearcomputerengineering. 16electivesaredividedintofourgroupsonrecenttechnologiessuchascloudcomputing, mobilecomputing, webapplicationsandBusinessAnalyticandIntelligence, CyberSecurityareprovidedwhichshallbeusefulforstudentintheirprofessionalcarrier.The laboratories for problem solving practices are based on utilization of state-of-the art FOSS software Tech-nologies used by the Industries. The FOSS technologies are available with source code students can experimentthe performance improvement and ideation to replace the existing implementation. The Project can be done asconventional practices or as an entrepreneur project to give thrust on generating budding talent as entrepreneurtoleadtheindustrialfrontofthenationworldwide.ForBoSComputerEngineeringProf. SarangJoshi1ProgramEducationalObjectives TocreatecompetenciesandopportunitiesforHigherEducation; TocreateprofessionalmanpowerskilledfortheITIndustry; ToprovidelaboratorypracticeswithadvancedFOSSTools; Toprovideinter-disciplinaryopportunities; Toprovideopportunitiesofdevelopingtechnicaldocumentsandpresentationskills. toprovideopportunitiesofindustry-Instituteinteractions; TodevelopopportunitiestopromoteEntrepreneurshipandstart-ups; Tonurtureprofessionalandsocialethics.ProgramObjectives ToexposestudentstotheSystemsandApplicationsProgramming,OrganizationsandArchitectures; ToprovideconceptualknowledgeintheComputingdomain; Toprovideinterdisciplinaryknowledge; Toexposestudentswithadvancedtoolsusedinindustry; Todevelopwrittenandsoft-skillcompetencies; TodevelopteamworkexperienceofprofessionalsskillsforITIndustry.ProgramOutcomes Totestapplicationswithconceptsandskillsinthedomainsubjects; Todemonstrateskillsinprogrammingtechniquesandtechnologies; Todemonstrateoralandwrittenskillsfortechnicalpresentationsanddocumentation; TodemonstrateITprojectasteamwork; TodemonstratesocialandProfessionalethicalpractices;2SAVITRIBAIPHULEPUNEUNIVERSITYBE(COMPUTERENGINEERING)-2012COURSESTRUCTURETerm-ISubject Subject TeachingScheme ExaminationScheme TotalCode MarksLect Tut Pract In PR/ OR/ EndSem TW TW SemAsmnt Asmnt410441 Design&Analysis 03 30 70 100ofAlgorithms410442 PrinciplesofModern 04 30 70 100CompilerDesign410443 SmartSystemDesign 03 30 70 100andApplications410444 Elective-I 03 30 70 100410445 Elective-II 03 30 70 100410446 Computer 04 50 50 100laboratory-I410447 Computer 04 50 50 100Laboratory-II410448 Project 02 50 50Total 16 02 08 150 150 100 350 750Term-II410449 SoftwareDesign 03 30 70 100Methodologies&Testing410450 High 03 30 70 100PerformanceComputing410451 Elective-III 03 30 70 100410452 Elective-IV 03 30 70 100OpenElective410453 Computer 04 50 50 100laboratory-III410454 Computer 04 50 50 100Laboratory-IV410455 Project 06 50 100 150Total 12 06 08 120 150 200 280 7503Electives:Semester-I Semester-IIELECTIVE-I ELECTIVE-III1. ImageProcessing 1. MobileComputing2. ComputerNetworkDesign 2. WebTechnologyandModeling3. AdvancedComputerProgramming 3. CloudComputing4. DataMiningTechniques 4. CyberSecurityandApplicationsELECTIVE-II ELECTIVE-IV(OpenElective)1. ProblemSolvingwithGamication 1. BusinessAnalyticandIntelligence2. PervasiveComputing 2. OperationsResearchforAlgorithmsinScienticApplications3. EmbeddedSecurity 3. MobileApplications4. MultidisciplinaryNLP 4. OpenElectiveOpenElective: ThelistedopenelectivesoranyotherElectivethatisbeingtaughtinthecurrentsemester(semester-II)underthefacultyofengineeringorindividualcollegeandIndustrycandenenewelectivewithcomplete(6units)syllabususingdenedframeworkof ElectiveIVandGETITAPPROVEDFROMTHEBOARDOFSTUDIES(COMPUTERENGINEERING) ANDOTHERNECESSARYSTATUTORYSYS-TEMSINTHESAVITRIBAIPHULEPUNEUNIVERSITYBEFORE30thDECEMBER.4410441DesignandAnalysisofAlgorithmsTeachingScheme ExaminationSchemeLectures: 3Hrs/Week InsemesterAssessment: 30EndSemesterAssessment: 70CourseObjectives: Todevelopproblemsolvingabilitiesusingmathematical theories; Toapplyalgorithmicstrategieswhilesolvingproblems; Todeveloptimeandspaceefficientalgorithms; Tostudyalgorithmicexamplesindistributed, concurrentandparallel environments.CourseOutcomes: TosolveproblemintheUGprojects; TodevelopSRSintheUGprojects; Tosolveproblemsformulti-coreordistributedorconcurrent/Parallel/Embeddedenvironments;Unit Content HrsI ProblemsolvingandAlgorithmicAnalysis 6Problemsolvingprinciples: Classicationofproblem,problemsolvingstrategies,classicationoftimecomplexities(linear,logarithmicetc)problemsubdivisionDivideandConquerstrategy.Asymptoticnotations,lowerboundandupperbound: Bestcase,worstcase,averagecaseanalysis,amortizedanalysis. Performanceanalysisofbasicprogrammingconstructs. Recurrences: FormulationandsolvingrecurrenceequationsusingMasterTheorem.II GreedyandDynamicProgrammingAlgorithmicStrategies 6Greedystrategy: Principle,controlabstraction,timeanalysisofcontrolabstraction,knapsackproblem,schedulingalgorithms-Jobschedulingandactivityselectionproblem.DynamicProgramming: Principle,controlabstraction,timeanalysisofcontrolabstraction,binomialcoecients,OBST,0/1knapsack,ChainMatrixmultiplication.III BacktrackingandBranch-n-Bound 8Backtracking: Principle,controlabstraction,timeanalysisofcontrolabstraction,8-queenproblem,graphcoloringproblem,sumofsubsetsproblem.Branch-n-Bound: Principle,controlabstraction,timeanalysisofcontrolabstraction,strategiesFIFO,LIFOandLCapproaches,TSP,knapsackproblem.IV ComplexityTheory 6Overview: Turingmachine,polynomialandnon-polynomialproblems,deterministicandnon-deterministicalgorithms,Pclass,NPclass&NPcompleteproblems-vertexcoverand3-SATandNPhardproblemHamiltoniancycle. ThemenagerieofcomplexityclassesofTuringdegrees.Conceptofrandomizedandapproximationalgorithms: SolvingTSPbyapproximationalgorithm,RandomizedsortalgorithmsandApproximatingMaxClique.V ParallelandConcurrentAlgorithms 6ParallelAlgorithms: Sequentialandparallelcomputing,RAM&PRAMmodels,AmdahlsLaw,Brentstheorem,parallelalgorithmanalysisandoptimalparallelalgorithms,graphproblems(shortestpathsandMinimumSpanningTree,Bipartitegraphs)ConcurrentAlgorithms: Diningphilosophersproblem5VI AlgorithmicCase-studies 8DistributedAlgorithms: Bullyalgorithmmethodfordynamicallyselectingacoordinator,allpairshortestpath(Floyed-WarshallAlgorithm),Dijkstra-Scholtenalgorithmdetectionofprocesstermination,Buddymemoryalgorithmmethodtoallocatememory.EmbeddedAlgorithms: Embeddedsystemscheduling(poweroptimizedschedulingalgorithm),sortingalgorithmforembeddedsystems.InternetofThingsandDataScienceAlgorithms: AlgorithmsinIoT:CryptographyAlgorithms,SchedulingAlgorithms,DatamanagementAlgorithmsandclustering,contextmanagement. DataScienceProjectLifeCycle(DSPLC),MathematicalConsiderations: Mathematicalmodeling,OptimizationMethods,AdaptiveandDynamicAlgorithmsandNumericalAnalysisinIoTAlgorithmsinSoftwareEngineering: Stringmatchingalgorithm-Boyer-MoorealgorithmKMPalgorithm.TextBooks:Sl. TextBooksNo.1. HorowitzandSahani,FundamentalsofComputerAlgorithms,2NDEdition.UniversityPress,ISBN:9788173716126,81737161262.2. GillesBrassardandPaulBartley,FundamentalofAlgorithmics,PHI,NewDelhi.3. Algorithms,KennethBermanandJeromePaul,CenageLearning,ISBN-13978-81-315-0521-2ReferenceBooks:Sl. ReferenceBooksNo.1. AlgorithmsandParallelComputing,FayezGebali,Willy,ISBN978-0-470-90210-3(IndianPaperbackEdition)2. AnanyLevitin,IntroductiontotheDesignandAnalysisofAlgorithmsPearsonEducation3. ThomasHCormenandCharlesE.LLeiserson,IntroductiontoAlgorithmPHI4. BoSContentDevelopment:Prof. SarangJoshi,Dr. ParikshitMahalle,DesignandAnalysisofAlgorithms:AProblemSolvingApproach,CambridgeUniversityPress,20156410442PrinciplesofModernCompilerDesignTeachingScheme ExaminationSchemeLectures: 4Hrs/Week InsemesterAssessment: 30EndSemesterAssessment: 70CoursePrerequisite: FundamentalsofDatastructures TheoryofComputation ConceptsofOperatingSystems StudyofProgrammingLanguagesCourseObjectives: Tostudyconceptsinassembling,parsingandcompilingintotargetcodeforexecution. ToUnderstandsystemsandmethodsofcompilation. Tointroducebasictoolsforcompilerwritingandexposethelatesttechniquesandadvancesincompiler. Togetexposedtoconcurrent,embeddedanddistributedcompilationtoolsandtechniques.CourseOutcomes: Tosolveproblemofparsingandcompiling. Abilitytodesignandwritesimplecompiler. Tobeabletousecompilertoolsinbasic,concurrent,distributedandembeddedenvironments. TodevelopawarenessoflatesttrendsandadvancesincompilersUnit Content HrsI NotionandConcepts 6IntroductiontocompilersDesignissues,passes,phases,symboltablePreliminariesMemorymanagement,Operatingsystemsupportforcompiler,CompilersupportforgarbagecollectionLexicalAnalysisTokens,RegularExpressions,ProcessofLexicalanalysis,BlockSchematic,AutomaticconstructionoflexicalanalyzerusingLEX,LEXfeaturesandspecicationII Parsing 8SyntaxAnalysisCFG,top-downandbottom-upparsers,RDP,Predictiveparser,SLR,LR(1),LALRparsers,usingambiguousgrammar,Errordetectionandrecovery,automaticconstructionofparsersusingYACC,IntroductiontoSemanticanalysisNeedofsemanticanalysis,typecheckingandtypeconversionIII SyntaxTranslationSchemes 7SyntaxDirectedTranslationandIntermediateCodeGenerationAttributegrammar,SandLattributedgrammar,bottomupandtopdownevaluationsofSandLattributedgrammar,Intermediatecodeneed,types,Syntaxdirectedtranslationscheme,Intermediatecodegenerationfor-assignmentstatement,declarationstatement,Booleanexpression,if-elsestatement,do-whilestatement,arrayassignment.IV CodeGenerationandOptimization 8CodeGenerationandCodeOptimizationIssuesincodegeneration,basicblocks,owgraphs,DAGrepresentationofbasicblocks,Targetmachinedescription,RegisterallocationandAssignment,Simplecodegenerator,Codegenerationfromlabeledtree,Conceptofcodegenerator.NeedforOptimization,local,globalandloopoptimization,Optimizingtransformationscompiletimeevaluation,commonsub-expressionelimination,variablepropagation,codemovement,strengthreduction,deadcodeelimination,DAGbasedlocaloptimization,peepholeoptimization,Introductiontoglobaldataowanalysis,Dataowequationsanditerativedataowanalysis(onlyintroductionexpected)7V FunctionalandLogicPrograms 7LanguageSpecicCompilation: ObjectOrientedlanguagessourcelanguageissues,routinesandactivation,codegenerationandcontrolowFunctionallanguages-introductiontoFunctionalPrograms,basiccompilation,polymorphictypechecking,desugaring,compilingtoaregister-orientedarchitecturesJavaCC(Chapter13ofreferencebook1)VI ParallelandDistributedCompilers 8Parallelprogrammingmodels,Processesandthreads,SharedvariablesMessagepassing,ParallelObjectOrientedlanguages,Tuplespace,AutomaticparallelizationIntroductiontoadvancedtopicsJIT,Dynamiccompilation,Interpreters(JVM/Dalvik),CrosscompilationusingXMLVM,Casestudies(selfstudy): GCC,g++,nmake,cmake. NVCC(casestudyforparallelcompilation),LLVMTextBooks:Sl.No. TextBooks1. AVAho,RSethi,JDUllman,Compilers: Principles,Techniques,andTools,PearsonEdition,ISBN81-7758-590-82. DickGrune,Bal,Jacobs,Langendoen,ModernCompilerDesign,Wiley,ISBN81-265-0418-8ReferenceBooks:Sl.No. ReferenceBooks1. CompilerConstructionUsingJava,JavaCCandYacc,AnthonyJ.DosReis,WileyISBN978-0-470-94959-72. KMuneeswaran,CompilerDesign,OxfordUniversitypress,ISBN0-19-806664-33. JRLevin,TMason,DBrown,LexandYacc,OReilly,2000ISBN81-7366-061-X8410443SmartSystemDesignandApplicationsTeachingScheme ExaminationSchemeLectures: 3Hrs/Week InsemesterAssessment: 30EndSemesterAssessment: 70CourseObjectives: Tostudymultidisciplinaryrequirementsofproblemsolving; TostudyconceptsofArticialIntelligence; Tostudysmartsystemsprogrammingandapplicationdevelopment; Tostudyexamplesindistributed,concurrentandparallelenvironments.CourseOutcomes: Thestudyofonesolvemultidisciplinarycase-study; Touseembeddedsystemsusingmachinelearning; Tosolveproblemsformulti-coreordistributed,concurrentandembeddedenvironments;Unit Content HrsI IntroductiontoIntelligentSystems 4Introduction,History,FoundationsandMathematicaltreatments,ProblemsolvingwithAI,AImodels,LearningaspectsinAI,WhatisanintelligentAgents,Rationalagent,Environmentstypes,typesofAgentsII Problem-solvingandBuildingSmartSystems 6Problemsolvingprocess,Problemanalysisandrepresentation,Problemspaceandsearch,Toyproblems,realworldproblems,Problemreductionmethods,GeneralSearchalgorithms,UninformedSearchmethods,Informed(Heuristic)SearchBestrst,Greedy,A*searchmethods,HeuristicFunctions,AO*,LocalSearchAlgorithmsandoptimizationproblems,Adversarialsearchmethods,ImportantconceptsofGametheory,Gametheoryandknowledgestructure,Gameasasearchproblem,Alpha-BetaPruning,StochasticGames,ConstraintSatisfactionProblem,CSPassearchproblemIII Knowledge,Reasoning,andPlanning 7Knowledgebasedagents,TheWumpusWorld,Logic,propositionallogic,Representationofknowledgeusingrules,Predicatelogic,Unicationandlifting,inferenceinFOL,ForwardChaining,BackwardChaining,Resolution,LogicProgramming.Planningproblem,Planning,AlgorithmsforPlanningasState-SpaceSearch,PlanningGraphs,simpleplanningagent,planninglanguages,blocksworldproblem,goalstackplanning,meanendanalysis,progressionplanners,regressionplanners,partialorderplanning,planninggraphs,hierarchicalplanning,jobshopschedulingproblem,PlanningandActingintheRealWorld,HierarchicalPlanning,Multi-agentPlanning,OntologicalEngineering,CategoriesandObjects,Events,MentalEventsandMentalObjects,ReasoningSystemsforCategories,ReasoningwithDefaultInformation,TheInternetShoppingWorldIV UncertainKnowledgeandDecisionTheory 6Uncertaintyandmethods,BasicProbabilityNotion,InferenceUsingFullJointDistributions,Bayesianprobabilityandbeliefnetworks,RelationalandFirst-OrderProbabilityModels,Othertechniquesinuncertaintyandreasoning,InferenceinTemporalModels,HiddenMarkovModels,KalmanFilters,DynamicBayesianNetworks,Decisionnetwork,Semi-constraintinuencediagram,Decisionmakingandimperfectinformation,CombiningBeliefsandDesiresunderUncertainty,TheBasisofUtilityTheory,UtilityFunctions,Multi-attributeUtilityFunctions,DecisionNetworks,Decision-TheoreticExpertSystems9V LearningTools,TechniquesandApplications 7MachineLearningConcepts,methodsandmodels,SupervisedLearning,unsupervisedandsemi-supervised,LearningDecisionTrees,EvaluatingandChoosingtheBestHypothesis,ArticialNeuralNetworks,Non-parametricModels,SupportVectorMachines,EnsembleLearning,empiricallearningtasks,Explanation-BasedLearning,InductiveLogicProgramming,ReinforcementLearning,ActiveLearning,Learningbasedonlimitedinformation.BuildingSmartsystemsusingdierentlearningtechniques,smartsystemapplications,agentbasedconcurrentengineeringVI Communicating,Perceiving,andActing 6LanguageModels,TextClassication,InformationRetrieval,InformationExtraction,PhraseStructureGrammars,SyntacticAnalysis(Parsing),AugmentedGrammarsandSemanticInterpretation,MachineTranslation,SpeechRecognition,ImageFormationandobjectrecognition,EarlyImage-ProcessingOperations,ObjectRecognitionbyAppearance,Reconstructingthe3DWorld,ObjectRecognitionfromStructuralInformation,UsingVision,RobotHardware,RoboticPerception,PlanningtoMove,PlanningUncertainMovements,RoboticSoftwareArchitectures,ApplicationDomainsTextBooks:Sl.No. TextBooks1. ParagKulkarniandPrachiJoshi,ArticialIntelligenceBuildingIntelligentSystems,PHIlearningPvt. Ltd.,ISBN978-81-203-5046-5,20152. StuartRussellandPeterNorvig(1995),ArticialIntelligence: AModernApproach,Thirdedition,Pearson,2003.ReferenceBooks:Sl.No. ReferenceBooks1. ArticialIntelligencebyElaineRich,KevinKnightandNair,TMH2. Shaishalev-shwartz,ShaiBen-David: UnderstandingMachineLearningfromTheorytoalgorithms,CambridgeUniversityPress,ISBN-978-1-107-51282-5,2014.10410444AElective-I:ImageProcessingTeachingScheme ExaminationSchemeLectures: 3Hrs/Week InsemesterAssessment: 30EndSemesterAssessment: 70CourseObjectives: Tostudyimageprocessingconcepts; Tostudymathematicsandalgorithmsforimageprocessing; Tostudyapplicationsinimageprocessing; Tostudyalgorithmicexamplesindistributed,concurrentandparallelenvironments.CourseOutcomes: Toperformimageprocessingprogramming; TosolveImageProcessingproblemsusingmulti-coreordistributed,concurrent/Parallelenvironments.Unit Content HrsI IntroductiontoImageprocessing 6Introduction,Imagesamplingandquantization,Resolution,Humanvisualsystem,Classicationofdigitalimages,Imagetypes(opticalandmicrowave),Elementsofanimageprocessingsystem,Imageleformats(ti,jpeg,ico,ceos,png,rasterimageformat),IntroductiontoOpenCVtooltoOpenanddisplayImagesusingPythonorEclipseC/CPP.II ImageEnhancementThresholding,Segmentation,WatershedSegmentation,Edge-based 6Segmentation,FuzzySegmentationSpatialdomaintechniquesImageNegative,Contraststretching,graylevelslicing,bitplaneslicing,histogramandhistogramequalization,localenhancementtechnique,imagesubtractionandimageaverage,lowpassspatiallters,medianltering,high-passspatiallter,derivativelters,Frequencydomaintechniques-Ideallow-passlter,butterworthlow-passlter,High-passlter,Homo-morphiclters.III ImageAnalysis 8Imagesegmentation-Classicationofimagesegmentationtechniques: WatershedSegmentation,Edge-basedSegmentation,FuzzySegmentation,regionapproach,clusteringtechniques,thresholding,edge-based,classicationofedgesandedgedetection,watershedtransformationFeatureExtraction-Boundaryrepresentation(Chaincode,B-splinerepresentation,fourierdescriptor)Regionrepresentation(Area,Eulernumber,Eccentricity,Shapematrix,momentbaseddescriptor),texturebasedfeaturesIV ImageCompressionandObjectrecognition 8IntroductiontoImagecompressionanditsneed,Codingredundancy,classicationofcompressiontechniques(Lossyandlossless-JPEG,RLE,Human,Shannonfano),scalarandvectorquantizationObjectRecognitionNeed,Automatedobjectrecognitionsystem,patternandpatternclass,relationshipbetweenimageprocessingandobjectrecognition,approachestoobjectrecognitionV MedicalImaging 6MedicalImageobtainedwithionizingradiation-medicalimagingmodalites,imagesfromXrays,Gammarays,DoseandRisk,MedicalImageobtainedwithnon-ionizingradiation: Ultrasoundimaging,magneticresonanceimaging,PACS,3Dvisualization: Imagevisualization,Surfaceandvolumerendering,Virtualreality,Dental&DigitalX-RayProcessing,RBCImageProcessing,3-DVisualization11VI RemotesensingImaging 6DenitionofRemotesensing,Remotesensingprocess,Photogrammetry,Electromagneticspectrum,Interactionwithatmosphere,Recordingofenergybysensor,Transmission,ReceptionandProcessing,Atmosphericsensors,Activeremotesensors,Passivemicrowaveremotesensing,SatelliteImages,VisualImageInterpretation: Introduction,Remotesensingdataproducts,Imageinterpretation,Elementsofvisualimageinterpretation,Interpretationkeys,ThermalandRadarimageinterpretation,Pre-processing,ApplicationofRemoteProcessing.TextBooks:Sl.No. TextBooks1. FundamentalsofDigitalImageProcessing,AnilK.Jain,PHI,ISBN81-203-0929-42. DigitalImageProcessingforMedicalApplications,GeoDougherty,CambridgeUniversityPress,ISBN:978-0-521-18193-8.3. DigitalImageprocessingbyS.Jayaraman,McGrawHillsPublication4. FundamentalsofDigitalImageProcessingbyS.Annadurai,Pearsonpublication5. FundamentalsofDigitalImageProcessingbyA.K.Jain,PHIPublication6. DigitalImageProcessingforMedicalApplicationsbyGeoDougherty,Cambridgeuniversitypress7. RemotesensingandGISbyBasudebBhatia,2ndedition,OXFORDUniversitypress.Chapter[1,5,9,12]ReferenceBooks:Sl.No. ReferenceBooks1. HandbookofMedicalImaging,ProcessingandAnalysis,AcademicPress,ISBN0-12-077790-8(PDFBook)2. EssentialImageProcessingandGISforRemoteSensing,JianGuoLiuPhillippaMason,ISBN978-0-470-51032-212410444BElective-I:ComputerNetworkDesignandModelingTeachingScheme ExaminationSchemeLectures: 3Hrs/Week InsemesterAssessment: 30EndSemesterAssessment: 70CourseObjectives: Toexposestudentstotheareaofnetworkdesign,modelingandanalysis. Toexposestudentstothecompletelifecycleofthenetworkdesign. Tomotivatestudentstothinkperformanceperspectivetowardsdesign&analysisofthecomputernet-work. Toexposestudentstothevariousopensourcenetworkdesigntools. Tostudyalgorithmicexamplesindistributed,concurrentandparallelenvironments.CourseOutcomes: Studentswillbeabletodesign,modelandanalyzecomputernetwork. Studentswillbeabletousetoolsfornetworkdesign,modelingandanalysis. Tosolveproblemsformulti-coreordistributed,concurrent/Parallelenvironments.Unit Content HrsI Introduction,requirementanalysis: concepts 8Overviewofnetworkanalysisanddesignprocess,Systemdescriptionandmethodology,Servicedescriptionandcharacteristics,performancecharacteristics,requirementanalysis(user,application,device,network,other)concepts,requirementspecicationandmap.II RequirementAnalysis: process 6Requirementgatheringandanalysis(developingservicemetrics,characterizingbehavior,DevelopingRMA,delay,capacity,performancerequirements,Environment-SpecicThresholdsandLimit,RequirementsMapping)III FlowanalysisandNetworkarchitecture 6IdentifyingandDevelopingFlows,DataSourcesandSinks,FlowModels,FlowPrioritization&specication,examplesofowanalysis,ComponentArchitectures,ReferenceArchitecture,ArchitecturalModels,SystemsandNetworkArchitectures.IV Addressing,routingandNetworkmanagementarchitecture 8AddressingMechanisms,RoutingMechanisms,AddressingStrategies,RoutingStrategies,ArchitecturalConsiderationsofaddressing,NetworkManagementMechanisms,ArchitecturalConsiderationsofnetworkmanagement.V NetworkPerformanceandDesign 6DevelopingGoalsforPerformance,PerformanceMechanisms,ArchitecturalConsiderations,DesignProcess,Vendor,Equipment,andService-ProviderEvaluations,NetworkLayout,DesignTraceability,DesignMetrics.VI ToolsforNetworkDesign,ModelingandAnalysis 6Discreteeventsimulation,modelingforcomputersimulation,NS-3orlatestversionorequivalent,modelingnetworkelements,SimulatingaComputerNetwork,SmartPointers,RepresentingPackets,ObjectAggregation,EventsinNS3orlatestversionorequivalent,CompilingandRunningtheSimulation,AnimatingtheSimulation,ScalabilitywithDistributedSimulation,EmulationCapabilities,AnalyzingtheResults,OverviewofOMNet.TextBooks:Sl.No. TextBooks1. JamesD.McCabe,NetworkAnalysis,Architecture,andDesign,MorganKaufmannPublisher(ELSEVIER),3rdedition2. Wehrle,Klaus,G unes,Mesut,Gross,James,ModelingandToolsforNetworkSimulation,Springer,ISBN:978-3-642-12330-613ReferenceBooks:Sl.No. ReferenceBooks1. PriscillaOppenheimer,TopDownNetworkDesign,3rdEdition,CiscoPress14410444CElective-I:AdvancedComputerProgrammingTeachingScheme ExaminationSchemeLectures: 3Hrs/Week InsemesterAssessment: 30EndSemesterAssessment: 70CourseObjectives: Tostudyadvancedcomputerprogrammingtechnologies Toapplyadvancedprogrammingtodatatechnologies StudytheconceptofObjectDistributionandinvokingitsservicesremotelyinDistributedenvironment Tostudyalgorithmicexamplesindistributed,concurrentandparallelenvironmentsCourseOutcomes: Tosolveproblemusingadvancedprogramming Tosolveproblemsformulti-coreordistributed,concurrent/ParallelenvironmentsUnit Content HrsI DistributedProgramming 8Introduction,SimpleLock,BoundedBuer,Message-PassingServices,DistributedLockService:-DistributedLockusingTimestamps,Object-TransferService: ObjectTransferusingPathReversal,DistributedSharedMemoryService:-ASingle-CopyDistributedSharedMemory,AMulti-CopyDistributedSharedMemory.II JavaProgrammingConcepts 6Relections,BoxingandUnboxing,ObjectserializationandDeserialization,ImportantJavaUtilityclasses(StringTokenizer,Observable),JavaCollectionframework(LinkedList,ArrayList,Sets,Hashsets,Treeset,Hashmap,Treemap,Vectors,Stack,Dictionary,Hashtable,Itrators)III SOAandProgramming 8WhatisService?Role/UseofserviceinCloudbasedenvironment,ServiceOrchestrationandDistribution. IntroductiontoRMI(RemoteMethodInvocation),SOAP,Servlet,WSDL,DevelopingWebservicesusingJava. IntroductiontoEnterpriseJavaBeans(EJBs): ConceptofEntityBeans,MessageBeansandSessionBeanswithoneexampleeachofwordcountprogram.IV WebProgramming 6HTMLandJavaScriptProgramming: EmbeddingJSinHTML,HandlingEvents,VariablesinJS,CreatingObjectsuingJS,Operators,Controlowstatements,Functions,JDBC,JSP,WebArchitecturemodels,MVCArchitectureModels,advantagesofJSPoverServlets,Tagbasedapproach,JSParchitecture,JSPlifeCycle,CreatingsimpleJSPPage,JSTL,JDBCfeatures,JDBCAPTs,JDBCClassesandInterfaces,ImplementingJDBCProcesseswithMongoDB,system.jscollectionforMongoDB,AJAX:CreatingsampleAJAXApplication,DocumentObjectModel,JSandAJAX,ImplementingAJAXframeworks.V HadoopProgramming 6DataScience,in-memoryanalytics,in-databaseprocessing,symmetricmulti-processingsystems(SMP),MassivelyparallelProcessing,dierencebetweenparallelandDistributedSystems,Sharedmemory,shareddisk,SharedNothingArchitecture(SNA),advantagesofSNA,CAPTheorem,NoSQL,NewSQL,FeaturesandAdvantagesofHadoop,HadoopEcosystem,RDBMSversesHadoop,HadoopDistributions: Hadoop,HDFS,HDFSDaemons,Fileread,Filewrite,HadoopYARN,Word-CountProgram15VI AdvancedTools,TechniquesandApplications 6ProcessingdatawithHadoop,MapReduceDaemons,ConceptofMapper,Reducer,Combiner,Partitioner,SearchingandSortingusingMapReduce,Map-Reduceworkingandexample: WordcountMapReduceprogrammingusingJava,MongoDBandMapReducefunction,Pig: features,anatomy,PigonHadoop,ETLProcessing,DatatypesandComplexdatatypesinPig,RunningPig: Interaction,BatchModes,ExecutionmodesofPig: LocalandMapReduceModes,HDFSCommands,RelationalOperators,EVALfunction,UDF,ParameterSubstitution,DiagnosticOperators,WordCountexampleusingPig.TextBooks:Sl.No. TextBooks1. DistributedProgramming,TheoryandPracticebyShankarandA.Udaya2. SeemaAcharya,S.Chellapan,BIGDATAandAnalytics,Wiley,2015,ISBN:978-81-245-5478-23. WebTechnologies: HTML,JS,PHP,Java,JSP,ASP.NET,XML,AJAX,BlackBook,DreamTech,ISBN:978-81-7722-997-4ReferenceBooks:Sl.No. ReferenceBooks1. JavaCompleteReferencebyHerbertSchidlt2. Hadoop: TheDenitiveGuide.16410444DElective-I:DataMiningTechniquesandApplicationsTeachingScheme ExaminationSchemeLectures: 3Hrs/Week InsemesterAssessment: 30EndSemesterAssessment: 70Requisites: TEDatabaseManagementSystemandApplications,Datawarehouse,OLTPCourseObjectives: TounderstandDataMiningConcepts. TounderstandDataMiningneedsandApplication. Tostudyconceptsofpatternbaseddataminingfordecisionmaking. Tostudyalgorithmicexamplesindistributed,concurrentandparallelenvironments.CourseOutcomes: TodevelopprogramsandmethodsfordataMiningapplications. Tosolveproblemsformulti-coreordistributed,concurrent/ParallelenvironmentsUnit Content HrsI Introduction,KnowledgeofData,DataProcessing 6Dataminingdescribed,need,kindsofpatternandtechnologies,issuesinmining,KDDvsdatamining,machinelearningconcepts,OLAP,knowledgerepresentation,datapre-processingcleaning,integration,reduction,transformationanddiscretization,applicationwithminingaspectexamplelikeweatherprediction.II Conceptsoffrequentpatterns,AssociationsandCorrelation 4MarketBasketAnalysis,Frequentitemset,Closeditemset&AssociationRules,miningmultilevelassociationrules,constraintbasedassociationrulemining,AprioriAlgorithm,FPGrowthAlgorithm.III Classication 8Introduction,classicationrequirements,methodsofsupervisedlearning,decisiontrees-attributeselection,treepruning,ID3,scalabledecisiontreetechniques,ruleextractionfromdecisiontree,Regression,BayesclassicationBayestheorem,NaveBayesclassication,metricsforperformanceevaluation,KNNapproachwithCasestudy.IV Clustering 5Clusteranalysis,distancemeasures,partitioningmethodsk-means,k-medoids,hierarchicalmethodssingle-link,complete-link,centroid,averagelink,agglomerativemethod.V TextandWebMining 8Textmining: TextDataAnalysisandInformationRetrieval,DimensionalityReductionforText,Featurevector,Bagofwords,Tf-idf,TextMiningApproaches,Webmining: Introduction,webcontentmining,webusagemining,webstructuremining,webcrawlers.VI ReinforcementLearningandBigDataMining 5Reinforcementlearning-Introductiontoreinforcementandwholisticlearning,multi-perspectivedecisionmakingforBigdataandmulti-perspectivelearningforbigdata,Advancedtechniquesforbigdatamining.TextBooks:Sl.No. TextBooks1. JiaweiHan,MichelineKamber,Datamining: conceptsandtechniques,MorganKaufmannPublisher,secondedition2. G.K.Gupta,IntroductiontoDataminingwithcasestudies,PHI,secondeditionReferenceBooks:17Sl.No. ReferenceBooks1. SaumenCharkrobarti,MiningtheWebDiscoveringKnowledgefromHypertextData.2. ParagKulkarni,Reinforcementandsystemicmachinelearningfordecisionmaking,Wiley. 20123. M.Dunham,Datamining: IntroductoryandAdvancedtopics,PearsonEducation,2003.4. ParagKulkarni,SarangJoshi,MetaBrownet. al.,MiningUnstructuredData:ABigDataPerspective,PHI,2015,ISBN:978-81-203-5116-518410445AElective-II:ProblemSolvingwithGamicationTeachingScheme ExaminationSchemeLectures: 3Hrs/Week InsemesterAssessment: 30EndSemesterAssessment: 70CourseObjectives: Todevelopproblemsolvingabilitiesusinggamication ToapplygamicationsforWebApplications ToapplygamicationsforMobileApplicationsCourseOutcomes: Tosolveprobleminprojects TodevelopprojectsusingGamication Tosolveproblemsformulti-coreordistributed,concurrent/ParallelenvironmentsUnit Content HrsI GamingFoundations 6Introduction,ResettingBehavior,ReplayingHistory,Gamingfoundations: FunQuotient,Evolutionbyloyalty,statusatthewheel,theHousealwayswins.II DevelopingThinking 6Re-framingContext: Communicology,Apparatus,andPost-history,ConceptsAppliedtoVideogamesandGamication,RethinkingplayingthegamewithJacquesHenriot,ToPlayAgainst: DescribingCompetitioninGamication,PlayerMotivation: PowerfulHumanMotivators,WhyPeoplePlay,Playertypes,SocialGames,IntrinsicversesExtrinsicMotivation,ProgressiontoMastery.CasestudiesforThinking: TowerofHanoi.III OpponentMovesinGamication 8ReclaimingOpposition: Countergamication,GamedAgencies: AectivelyModulatingOurScreen-andApp-BasedDigitalFutures,Remodelingdesign,GameMechanics,DesigningforEngagement,CasestudyofMazeProblem.IV GameDesign 8GameMechanicsandDynamics: FeedbackandRe-enforcement,GameMechanicsindepth,Puttingittogether,Casestudyof8queensproblem.V Advancedtools,techniques 6GamicationcaseStudies,CodingbasicgameMechanicsVI Advancedtools,techniquesandapplications 6InstantGamicationPlatforms,Mambo.io(Ref:http://mambi.io),InstallationanduseofBigDoor(OpenSourcehttp://bigdoor.com),ngageoint/gamication-server(ref:https://github.com/ngageoint/gamication-server)TextBooks:Sl.No. TextBooks1. http://projects.digital-cultures.net/meson-press/les/2014/06/9783957960016-rethinking-gamication.pdf,ISBN(PDF):978-3-95796-001-6,MathiasFuchs,SoniaFizek,PaoloRuno,NiklasSchrape,RethinkingGamication,MesonPress,ISBN(Print): 978-3-95796-000-92. ftp://ftp.ivacuum.ru/i/WooLF/%5B2011%5D%20Gamication%20by%20Design.pdf,GabeZechermann,ChristopherCunningham,GamicationDesign,Oreilly,ISBN:978-1-449-39767-8.ReferenceBooks:Sl.No. ReferenceBooks1. SarangJoshi,ParikshitMahalle,DesignandAnalysisofAlgorithm,CambridgeUniversityPress2. http://press.etc.cmu.edu/les/MobileMediaLearning-DikkersMartinCoulter-web.pdf19410445BElective-II:PervasiveComputingTeachingScheme ExaminationSchemeLectures: 3Hrs/Week InsemesterAssessment: 30EndSemesterAssessment: 70CourseObjectives: Tointroducepervasivecomputingabilities. Tointroducetoolsandtechniquesusedwhilesolvingproblemsusingpervasivecomputing. Tostudyalgorithmicexamplesindistributed,concurrentandparallelenvironmentsCourseOutcomes: Tosolveproblempervasivecomputingabilities. Tosolveproblemsformulti-coreordistributed,concurrent/ParallelenvironmentsUnit Content HrsI IntroductiontoPervasiveComputing 7ConceptofDistributedComputing,MobileComputing,PervasiveComputing,WearableComputing,ModelingtheKeyUbiquitous/PervasiveComputingProperties(Ref: WileyUC),MobileAdaptiveComputing(Ref: TMH),MobilityManagementandCaching(Ref:TMH)II PervasiveComputingDevices 7SmartEnvironment: CPIandCCI(SmartDevices: ApplicationandRequirements(Ref:WileyUC),DeviceTechnologyandConnectivity(Ref: PearsonPC),HumanComputerInteraction(Ref: UnitIII,WileyUC)III HumanComputerInteraction 6ExplicitHCI,ImplicitHCI,UserInterfaceandInteractionforfourhand-heldwidelyuseddevices,HiddenUIviabasicsmartdevices,HiddenUIviawearableandImplanteddevices,Humancentereddesign,usermodels(ref: WileyUC)IV MiddlewareforPervasive 7Adaptivemiddleware,Contextawaremiddleware,Mobilemiddleware,ServiceDiscovery,MobileAgents(Ref: GuptaTMH;Chapter4,5,6)V SecurityinPervasiveComputing 6SecurityandPrivacyinPervasiveNetworks,ExperimentalComparisonofCollaborativeDefenseStrategiesforNetworkSecurity.VI ChallengesandOutlook 6Overviewofchallenges,smartdevices,SmartInteraction,Smartphysicalenvironmentdeviceinteraction,Smarthuman-deviceinteraction,HumanIntelligenceversusmachineintelligence,socialissues.CaseStudy-WearableComputing/CyberPhysicalSystem.TextBooks:Sl.No. TextBooks1. StefanPoslad,UbiquitousComputing,Smartdevices,environmentandinteraction,Wiley.2. FrankAdelstein,SandeepGupta,GoldenRichardIII,LorenSchwiebert,FundamentalsofMobileandPervasiveComputing,TataMcGrawHillsReferenceBooks:Sl.No. ReferenceBooks1. JochenBurkhardt,HorstHenn,StefanHepper,KlausRindtor,ThomasSchaeck,PervasiveComputing,Pearson,EighteenthImpression,2014.2. BooksandDigitalContentDevelopedbytheBoS20410445CElective-II:EmbeddedSecurityTeachingScheme ExaminationSchemeLectures: 3Hrs/Week InsemesterAssessment: 30EndSemesterAssessment: 70CourseObjectives: TolearnEmbeddedSecurityinPortableComputing ToLearnadvancesinsecurityinEmbeddedTechnology,IoT TostudyalgorithmicexamplesindistributedenvironmentsCourseOutcomes: Tosolveprobleminprojects TodevelopSRSintheprojects TosolveEmbeddedSecurityproblemsUnit Content HrsI Introduction 6Cybersecurityinmobileedge: ThreepillarsofMobileComputing,BYOD,IncidentCaseStudy: eBayDataBreach,TargetDataBreach,OpenSSLHeartbleed;StrongAuthentication,NetworkManagement,BootIntegrity,Hardware-BasedProtection,Open-SourceSoftwareBestPractice,Third-PartySoftwareBestPractice,SecurityDevelopmentLifecycle,CVSSanditslimitations.II EmbeddedSolutions: fromManagementtoSecurity 8ManagementEngineOverview,PlatformandSystemManagement,IntelAMTOverview,TheEnginesEvolvement: fromManagementtoSecurity,SecurityApplicationsataGlance: EPID,PAVP,IPTandBootGuard;VirtualSecurityCore: ARMTrustzone:secureandnon-securemodes,memoryisolation,busisolation,physicalversesvirtualisolation. ManagementEnginevs. IntelAMT,IntelAMTvs. IntelvProTechnology. Buildingblocksofthesecurityandthemanagementengine: Randomnumbergeneration,MessageAuthentication,RSA,DigitalSignature,Securestorage,debugging.III Safeguardingitself 8Accesstohostmemory,SecurityRequirements,ThreatAnalysisandMitigation,PublishedAttacks: IntroducingRing-3Rootkits.IntelsEnhancedPrivacyIdentication(EPID):RedeningPrivacyfortheMobileAge,ProcessorSerialNumber,EPID,SignandMessageAuthentication(SIGMA)),ImplementationofEPID,ApplicationsofEPID,NextgenerationofEPIDIV Booting 6Introduction,Bootattack: EvilMaid,BIOSandUEFI,BIOSalteration,SoftwareReplacement,rooting,TrustedPlatformModule(TPM),FieldProgrammableFusesIntelBootGuard,MeasuredBoot,VeriedBoot. TPMOverview,IntelPlatformTrustTechnology,Integratedvs. DiscreteTPM.V Hardware-BasedContentProtectionTechnology 6Introduction,Rightsprotections,Digitalrightsmanagement(DRM),End-to-EndContentProtection,IntelsHardware-BasedContentProtection,IntelWirelessDisplay,HDCP,ContentProtectiononTrustZone;DynamicallyLoadedApplications:Closed-DoorModel,DynamicApplicationLoader(DAL)Overview,DALArchitecture,DAlSecurityConsiderations.VI EmbeddedTechnology: IdentityProtectionTechnology 6IsolatedComputingEnvironment,Security-HardeningMeasures,BasicUtilitiesofembeddedsecurity,AnonymousAuthenticationandSecureSessionEstablishment,ProtectedInputandOutput,DynamicApplicationLoader(DAL),SummaryofFirmwareIngredients,SoftwareGuardExtensions,IntelUniesandSimpliesConnectivity,SecurityforIoT,EmbeddedSecurityforInternetofThings(Ref2)21TextBooks:Sl.No. TextBooks1. XiaoyuRuan,PlatformEmbeddedSecurityTechnologyRevealed,APressOpen,2014ISBN978-1-4302-6571-9ebook: platformembeddedsecuritytechnologyrevealedpdfReferenceBooks:Sl.No. ReferenceBooks1. EdwardLee,SanjitSeshia,IntroductiontoEmbeddedSystems: ACyberphysicalSystemsApproach,ISBN978-0-557-70857-42. DigitalContent: ArijitUkil,JaydipSen,SripadKoilakonda,EmbeddedSecurityforInternetofThings,InnovationlabsTCS,IEEEXplore22410445DElective-II:MultidisciplinaryNLPTeachingScheme ExaminationSchemeLectures: 3Hrs/Week InsemesterAssessment: 30EndSemesterAssessment: 70CourseObjectives: TodevelopproblemsolvingabilitiesusingMathematics Toapplyalgorithmicstrategieswhilesolvingproblems Todeveloptimeandspaceecientalgorithms Tostudyalgorithmicexamplesindistributed,concurrentandparallelenvironmentsCourseOutcomes: Tosolveprobleminprojects Tosolveproblemsformulti-coreordistributed,concurrent/ParallelenvironmentsUnit Content HrsI NaturalLanguageProcessing 6TheoriesofParsing,ParsingAlgorithms;RobustandScalableParsingonNoisyTextasinWebdocuments;HybridofRuleBasedandProbabilisticParsing;ScopeAmbiguityandAmbiguityresolution. LexicalKnowledgeNetworks,MetaphorsII AdvancedNaturalLanguageProcessing 6AutomaticMorphologyLearning,NamedEntities;MaximumEntropyModels;RandomFields,EstimationTechniques,andLanguageModeling,ParsingandSyntax,TheEMAlgorithminNLP,StochasticTagging,andLog-LinearModels,ProbabilisticSimilarityMeasuresandClustering,MachineTranslation,DiscourseProcessing: SegmentationIII MachineLearningandNLP 8FiniteStateMachineBasedMorphology;AutomaticMorphologyLearning;FiniteStateMachineBasedMorphology,UnsupervisedMethodsinNLP,IntroductiontoHMM,HMMErgodicmodels,Morphology,GraphicalModelsforSequenceLabelinginNLP,Probabilisticparsing;sequencelabeling,ForwardBackwardprobability;ViterbiAlgorithmIV IntroductiontoSpeechCommunication 6SpeechCommunication: BiologyofSpeechProcessingTheAcousticsandAcousticAnalysisofSpeech,Linguisticlevel,Physiologicallevel,Acousticlevel,Auditoryphysiology,ThePhysiologyofSpeechProduction,Sentence-levelPhenomena,ThePerceptionofSpeech,SpeechDisordersandDevelopment,SpeechSynthesisV MultidisciplinaryNaturalLanguageProcessing 6LexicalKnowledgeNetworks,WordNetTheory;IndianLanguageWordNetsandMultilingualDictionaries;SemanticRoles,WordSenseDisambiguationMultilinguality,MetaphorsVI Advancedtools,techniquesandapplicationsofNLP 8SentimentAnalysis;TextEntailment;RobustandScalableMachineTranslation;QuestionAnsweringinMultilingualSetting;CrossLingualInformationRetrieval,Someapplicationslikemachinetranslation,databaseinterface,ProgramminglanguagePythonNaturalLanguageToolKit(NLTK),NLPapplicationsinwebminingandtextmining.TextBooks:Sl.No. TextBooks1. Jurafsky,David,andJamesH.Martin. SpeechandLanguageProcessing: AnIntroductiontoNaturalLanguageProcessing,ComputationalLinguisticsandSpeechRecognition.UpperSaddleRiver,NJ:Prentice-Hall,2000. ISBN:0130950696.2. Manning,ChristopherD.,andHinrichSch utze. FoundationsofStatisticalNaturalLanguageProcessing. Cambridge,MA:1999. ISBN:0262133601.3. Stevens,K.N.AcousticPhonetics. Cambridge,MA:MITPress,1999. ISBN:978026219404423ReferenceBooks:Sl.No. ReferenceBooks1. Flanagan,J.L.SpeechAnalysis,SynthesisandPerception. 2nded. NewYork,NY:Springer-Verlag,1972. ISBN:9780387055619.2. Kent,RaymondD.,BishnuS.Atal,andJoanneL.Miller,eds. PapersinSpeechCommunication: SpeechProduction.NewYork,NY:AcousticalSocietyofAmerica,1991.ISBN:9780883189580.3. G.ChirchiaandS.McConnellGinet.MeaningandGrammar,MITPress,1990.4. JaesAllen.NaturalLanguageUnderstanding,Benjamin-Cummins,1987.24410446ComputerLaboratory-ITeachingScheme ExaminationSchemePracticals: 4Hrs/Week OralAssessment: 50PracticalAssessment: 50CourseObjectives: TodevelopproblemsolvingabilitiesusingMathematicalModeling Toapplyalgorithmicstrategies,SoftwareEngineeringandTestingwhilesolvingproblems Todeveloptimeandspaceecientalgorithms Tostudyalgorithmicexamplesindistributed,concurrentandparallelenvironmentsCourseOutcomes: Todemonstrateecientdesign,analysisandtestingofalgorithmicassignments. TodebuganddemonstratetheTestingoffunctioningusingSoftwareEngineeringforOOprogramming. Toeectivelyusemulti-coreordistributed,concurrent/Parallelenvironments.Tools:64-bitFedoraorequivalentOSwith64-bitIntel-i5/i7orlatesthigherprocessorcomputers,FOSStools,LEX,YACC,DAG,iburg,XMLVM,IntelInternetofThings(IoT)DeveloperKitorIntelGalileoboardorBBBorOpenSourceequivalent,VxWorks R ,thereal-timeoperatingsystem(RTOS)forIoT,NS3,scala,Sqoop,Pig(Latin,Compiler),Hive,HDFS,HBase.EvaluationandTerm-workAssessmentMethod: Practical, Oral andTermworkAssessmentSchemeguidelinesaretobeusedforevaluation.A. EachAssignment/Class Designedmust haveMathematical modelingusingrelevant Divide-n-Conquerstrategiestobeassessedfor10%oftheMarks(PaperWork/DigitalWrite-up);B. InAabove, anabilitydemonstratedfor eliminatingthe redundant Conditional statements is tobeevaluatedforthe20%ofthemarks(PaperWork/DigitalWrite-up).C. InAabove,anabilitydemonstratedforeliminatingtheredundantLoopsstatementsistobeevaluatedforthe20%ofthemarks(PaperWork/DigitalWrite-up).D. ThefunctioningoftheprogramsistobedemonstratedbyBlack-BoxTestingfor10%oftheMarks;E. White-BoxWalkthroughTestingmethodsfor10%ofthemarks;F. Positive-Negativetestingfor10%ofthemarks;G. Inadditiontothesetestingmethods,studentmustselectoneoftheadvancedSoftwareTestingmethodcurrentlypracticedintheIndustrywhichissuitableforthefunctionalassignmentoftheReliabilityfor10%ofthemarks.H. 10%ofthemarksaretobegivenfortheOralQuestionsusingabove.I. 10%ofthemarksaretobegivenfortheoutputgeneratedforthepractical/Oral/Termwork.J. The assessment as above is to be done by a pair of examiners as per prevailing rules of SPPU examinationand items A,B,E by Examiner 1 and items C,D,F by Examiner 2 and items G,H,I to be assessed Jointly;K. LatexoritsequivalentbeusedtogeneratethedocumenttobestoredintheRead-onlyDigital Mediaasaterm-work/Digital Journal afterchecking, removing/avoidingtheplagiarism. Giveanadditionalassignmentperassignmentreportingplagiarismtobesubmittedinthejournalundertheheadingextra-work.L. Examinationtobeconductedontheassignmentsperformed(GroupAandGroup-B).25LaboratoryAssignments: GroupA(MandatorySixAssignments)1. UsingDivideandConquerStrategiesdesignafunctionforBinarySearchusingC.2. UsingDivideandConquerStrategiesdesignaclassforConcurrentQuickSortusingC++.3. LexicalanalyzerforsamplelanguageusingLEX.4. ParserforsamplelanguageusingYACC.5. IntcodegenerationforsamplelanguageusingLEXandYACC.Elective-IA. Design a class using C++ to read a gray scale TIFF image le of a dental digital X-Ray or Medical X-Rayor an Areal view Image, design Class to calculate histogram to return a CList, Design ImageDisplay classtodisplayhistoramofaimage.Elective-IB. A company has three oces at remote locations with requirement of interoperability with remote services.Each oce has a server, TCP/IP and dierent users including administrator, privileged users and commonclients. Designanetworkmodelforthesame. DemonstratethenetworkmodelusingNS3.Elective-IC. Writeajavaprogramtomultiply64-bitnumbersusingsharedmemory, javacollectionframeworkandjavautilities.Elective-ID. Implementasimpleapproachfork-means/k-medoidsclusteringusingC++. GroupB(AnySixAssignments: atleast3fromtheselectedElective)Allassignmentsmustbecoveredinastudentsbatchoflaboratory.1. 8-Queens Matrixis StoredusingJSON/XMLhavingrst Queenplaced, use back-trackingtoplaceremainingQueenstogeneratenal8-queensMatrixusingPython.2. ConcurrentImplementationoftravellingsalesmanproblem.3. Implementationof0-1knapsackproblemusingbranchandboundapproach.4. CodeoptimizationusingDAG.5. CodegenerationusingDAG/labeledtree.6. GeneratingabstractsyntaxtreeusingLEXandYACC.7. Implementingrecursivedescentparserforsamplelanguage.8. WriteaprogramtoimplementSLRParsingalgorithmusingPythonfortheorderedinputSetinXML{ PE,EE+T,ET,TT*F,TF,F(E),Fi,END. }Elective-IA1 ImplementhistogramequalizationwithouttheuseofFOSSEclipse-OpenCVlibraryfunctionsandcom-pareitsperformancetoOpenCVlibraryfunctionwithEclipse.Elective-IA2 Implement adaptive thresholding of a gray scale image and compare its performance with ordinary thresh-olding.Elective-IA3 Perform a two dimensional Butterworth low-pass and high-pass lter of the given image for two dierentcut-ofrequencies.Elective-IA4 PerformImagesegmentationusingwatershed/fuzzy/clusteringsegmentationtechnique.Elective-IA5 Performanytwoboundary/regionbasedfeatureextractiontechniquesforobjectrecognition.Elective-IB1 Writeaprograminpythontocalculateend-to-endpacketdelayforethernet, 802.11and802.15.4andcompare the results. End-to-end packet delay should include processing delay, queuing delay, transmissiondelayandpropagationdelay.Elective-IB2 WriteaprograminJavatoanalyzeM/D/1(RandomArrivals,constantservicetimedistributionand1server)fordatawirelessnetworksandcalculatechannelutilizationandthroughput.26Elective-IB3 WriteaprogramusingEmbeddedJavatondCMSTusingEsau-WilliamsAlgorithmusewirelessnet-works.Elective-IB4 Forwirelessrouting, designandcomparedistributedBellman-FordalgorithmandDijkstrasalgorithmuseFOSSEclipseC++/Java/Python/Scalaforprogramming.Elective-IB5 Theclassroomsandlaboratoriesareconnectedthroughadistributednetworkhavingn nodeswithsecuritycameras(IP-based)alongwiththeothersensorssuchasthumbmarksof attendance. Designanetworkforyourcollegeforsecuritymanagementandattendancemanagement. Thedepartmentsareconnected in a bipartite graph and Heads are connected to the administrative oces of the college. Designanetworkandtestittheecientdatahandlingbydierententities. Developamodel todemonstrateDijkstrasalgorithmforsamplingthedata. UsePythonandNS3.Elective-IC1 For a text message of 150 words, Human Codes are to be produced and transmitted through a messagingsystem or a blog. Use Python or Java Script/Java Beens to transfer such message from one user to anotheronaweb/intranet.Elective-IC2 For a text message of 150 words, Human Codes are to be produced and transmitted through a messagingsystemorablog. UsePythonorJavaScript/JavaBeens/Scalatotransfersuchmessagefromoneusertoanotheronaweb/intranet,DevelopamobileAPP.Elective-IC3 WriteaprogramusingSqooptotransfertheDigitalLibraryBookDataandrelatedlinkedtomultime-dia/PDFlesstoredusingMySQLtoHDFSandfromHDFStoMySQL.Elective-IC4 WriteaprogramusingHivetocreateasummarizationanddataanalysisqueriesontheDigitalLibraryBookData.Elective-IC5 WriteaMapReduceprogramusingJava/Python/Scalatoarrangethedataonuserid, thenwithintheuser id sort them in increasing or decreasing order of hit count of accession number demanded by studentsusingdigitallibrary.Elective-ID1 Using any similarity based techniques develop an application to classify text data. Perform pre-processingtasksasperrequirement.Elective-ID2 ImplementApriori approachfordataminingtoorganizethedataitemsonashelfusingfollowingtableofitemspurchasedinaMallTransactionID Item1 Item2 Item3 Item4 Item5 Item6T1 Mnago Onion Jar Key-chain Eggs ChocolatesT2 Nuts Onion Jar Key-chain Eggs ChocolatesT3 Mnago Apple Key-chain Eggs - -T4 Mnago Toothbrush Corn Key-chain Chocolates -T5 Corn Onion Onion Key-chain Knife EggsElective-ID3 ImplementDecisiontreesonDigitalLibraryDatatomirrormoretitles(PDF)inthelibraryapplication,compareitwithNaveBayesalgorithm.Elective-ID4 Implement Nave Bayes for Concurrent/Distributed application. Approach should handle categorical andcontinuousdata.Elective-ID5 ImplementationofK-NNapproachtakesuitableexample. GroupC(AnyOneAssignment)1. Codegenerationusingiburgtool.2. CrosscompilationusingXMLVM.3. GenerateHumancodesforagrayscale8bitimage.4. SimulateJPEGlikecompressiononagrayscaleimageandreportthecompressionratio.TextBooks:Sl.No. TextBooks1. LaboratoryManualgeneratedbytheLaboratoryTeachersoftherespectivecollege,intheTerm-workFormat;tobeassessedandapprovedbytheBoS2. ContentinDigitalLibrary27410447ComputerLaboratory-IITeachingScheme ExaminationSchemePracticals: 4Hrs/Week TermWorkAssessment: 50OralAssessment: 50CourseObjectives: Todevelopproblemsolvingabilitiesforsmartdevices. Todevelopproblemsolvingabilitiesforgamications. Todevelopproblemsolvingabilitiesofpervasiveness,embeddedsecurityandNLP. Toapplyalgorithmicstrategieswhilesolvingproblems Todeveloptimeandspaceecientalgorithms Tostudyalgorithmicexamplesindistributed,concurrentandparallelenvironmentsCourseOutcomes: Problemsolvingabilitiesforsmartdevices. Problemsolvingabilitiesforgamications. Problemsolvingabilitiesofpervasiveness,embeddedsecurityandNLP. Tosolveproblemsformulti-coreordistributed,concurrent/ParallelenvironmentsTools:64-bitFedoraorequivalentOSwith64-bitIntel-i5/i7orlatesthigherprocessorcomputers,FOSStools,LEX,YACC,DAG,iburg,XMLVM,IntelInternetofThings(IoT)DeveloperKitorIntelGalileoboardorBBBorOpenSourceequivalent,VxWorks R ,thereal-timeoperatingsystem(RTOS)forIoT,NS3,Scala,PythonEvaluationandTerm-workAssessmentMethod: Practical, Oral andTermworkAssessmentSchemeguidelinesaretobeusedforevaluation.A. EachAssignment/Class Designedmust haveMathematical modelingusingrelevant Divide-n-Conquerstrategiestobeassessedfor10%oftheMarks(PaperWork/DigitalWrite-up);B. InAabove, anabilitydemonstratedfor eliminatingthe redundant Conditional statements is tobeevaluatedforthe20%ofthemarks(PaperWork/DigitalWrite-up).C. InAabove,anabilitydemonstratedforeliminatingtheredundantLoopsstatementsistobeevaluatedforthe20%ofthemarks(PaperWork/DigitalWrite-up).D. ThefunctioningoftheprogramsistobedemonstratedbyBlack-BoxTestingfor10%oftheMarks;E. White-BoxWalkthroughTestingmethodsfor10%ofthemarks;F. Positive-Negativetestingfor10%ofthemarks;G. Inadditiontothesetestingmethods,studentmustselectoneoftheadvancedSoftwareTestingmethodcurrentlypracticedintheIndustrywhichissuitableforthefunctionalassignmentoftheReliabilityfor10%ofthemarks.H. 10%ofthemarksaretobegivenfortheOralQuestionsusingabove.I. 10%ofthemarksaretobegivenfortheoutputgeneratedforthepractical/Oral/Termwork.J. The assessment as above is to be done by a pair of examiners as per prevailing rules of SPPU examinationand items A,B,E by Examiner 1 and items C,D,F by Examiner 2 and items G,H,I to be assessed Jointly;28K. Latex or its equivalent be used to generate the document to be stored in the Read-only Digital Media as aterm-work/Digital Journal as per BoS format of Term work Submission after checking, removing/ avoidingtheplagiarism. Giveanadditional assignmentperassignmentreportingplagiarismtobesubmittedinthejournalundertheheadingextra-work.L. Examinationtobeconductedontheassignmentsperformed(GroupAandGroup-B).LaboratoryAssignments: GroupA(MandatorySixAssignments)1. Implementationofany2uninformedsearchmethodswithsomeapplication.2. Writeaprogramtoperformproletranslation-basedproactiveadaptationusingcontextmanagementinsmartphones. Objectiveof thisassignmentistoautomaticallygeneratesusersproleaccordingtothescenariosusingmachinelearningapproaches. Systemshouldallowtokeepusersfullproleinuserdomainresultingintocentralizingorexchangingtheproleinformationwithincreaseintheconsistencyofproleinformation. .3. ImplementA*approachforanysuitableapplication.4. ImplementationofUnicationalgorithm5. Implement Naive Bayes topredict the worktype for apersonwithfollowingparameters: age: 30,Qualication: MTech,Experience: 8Followingtableprovidesthedetailsoftheavailabledata:WorkType Age Qualication ExperienceConsultancy 30 Ph.D. 9Service 21 MTech. 1Research 26 MTech. 2Service 28 BTech. 10Consultancy 40 MTech. 14Research 35 Ph.D. 10Research 27 BTech. 6Service 32 MTech. 9Consultancy 45 Btech. 17Research 36 Ph.D. 7Elective-IIA. Implementationof any2informedsearchmethodsforaThreeLPGcompaniesthatwantstoinstall agaspipe-linebetweenvecities. Thecostof pipelineinstallationisgiveninatablemaintainedusingXML/JSONuseC++/Python/Java/ScalawithEclipsefortheapplication. Calculatetimeandspacecomplexities. Useconceptsofgamication,denenecessaryrulesofthegamication.Elective-IIB. APizzashopchainwants toautomate dishes servedwithschemes or without scheme anddeliveredbythenearestshopinachain. Usepervasivecomputingparadimetodevelopaweb-applicationusingEmbeddedJava/Pythone/Scalasothattheorderbedeliveredtothecustomerwithin10minutes. UseXML/JSONtostorethedata.Elective-IIC. UsingPython/JavawithBBBdevelopaembeddedsecurityapplicationofadoorlock.Elective-IID. WriteaprogramusingScala/Python/C++usingEclipsetocorrectthespellingofEnglishparagraph. GroupB(AnySixAssignments: atleast1fromtheselectedElective)Allassignmentsmustbecoveredinastudentsbatchoflaboratory.1. Writeaprogramtobuildsmartmobileappforcontextmanagement. Objectiveof thisassignmentistobuildasmartappformsmartphonewhichcansensesomeparametersof theuserandconvertthisparametersintosomecontextualinformationinordertodothecontextmanagement.2. Writeaprogramtobuildsmartmobileappforuserproling. Objectiveofthisassignmentistodevelopsmart mobile app which can create user proles based on their preferences so that smart recommendationscabbeprovidedatruntime.293. Implementationof MiniMaxapproachforTIC-TAC-TOEusingJava/Scala/Python-EclipseUseGUIPlayerXandPlayerOareusingtheirmobilesfortheplay. Refreshthescreenafterthemoveforboththeplayers.4. ImplementationofasimpleNNforanysuitableapplication(withouttool)5. Implementation of any 2 uninformed search methods for a LPG company that wants to install a gas pipe-line between ve cities. The cost of pipeline installation is given in a table maintained using XML/JSONuseC++/Python/Java/ScalawithEclipsefortheapplication. Calculatetimeandspacecomplexities.6. WriteaprogramtoperformclassicationforthesampledatasetbasedonthebyusingLIBSVMALibraryforSupportVectorMachines. (usingLDAfordimensionalityreduction).7. Developinganbookrecommend-er(abookthatthereadershouldreadandisnew)Expertsystemor(anyother).8. DevelopaPOPforschedulingyourhigherstudiesexam. Assumesuitabledatalikecollegesubmissionschedule, college exams, Constraint that a paper publication is must to appear before the exam, a familyfunctionathomeandsoon.9. Implement k-meansfor clusteringdataof childrenbelongingtodierent agegroups toperformsomespecicactivities. FormulatetheFeaturevectorforfollowingparameters:i. heightii. weightiii. ageiv. IQFormulatethedatafor40childrentoform3clusters.Elective-IIA1 Hintsdata,AlgorithmsnamesdataandwordsdataisstoredusingXML/JSON/MongoDB,Thegameis to select appropriate algorithms of string comparison using multiple hints to display meaningful combi-nationofwords. Forexample,Hints: Pratapgad(Fort)HistoricalPlaceHint, HIstoricalEventhintoutcomecanbeShri Shivaji Raje, UsePython/Scala/Java/C++. Largerthenumberof hintslesserthemarksfortheoutcome. Thereshouldbelargenumberofcombinationsinthehintsdatabase. FindtheAlgorithmicComplexity/eciency.Elective-IIA2 Hintsdata, Algorithmsnamesdataandwordsdataisstoredindistributedstoragemedia/HDFSusingXML/JSON/MongoDB/hBase,Thegameistoselectappropriatealgorithmsofstringcomparisonusingmultiple hints todisplaymeaningful combinationof words. For example, Hints: Pratapgad(Fort)HIstorical placehint, Historical eventhintsoutcomecanbeShri Shivaji Raje, UsePython/Scala/Java/ C++. Larger the number of hints lesser the marks for the outcome. There should be large numberofcombinationsinthehintsdatabase.Elective-IIA3 Hints data, Algorithms names dataandwords datais storedindistributedstoragemedia/HDFSus-ing XML/JSON/MongoDB/hBase, The game is to select appropriate algorithms of string compari-sonusingmultiplehintstodisplaymeaningful combinationof words. Forexample, Hints: Pratapgad(Fort)HistoricalLocationhint, HistoricalEventhintoutcomecanbeShriShivajiRaje,UsePython/Scala/Java/C++. Largerthenumberofhintslesserthemarksfortheoutcome. Thereshouldbelargenumberofcombinationsinthehintsdatabase. UseConcurrentsearchingandMergingalgorithms. Findtheeciency/Complexity.Elective-IIA4 Hintsdata, Algorithmsnamesdataandwordsdataisstoredindistributedstoragemedia/HDFSusingXML/JSON/MongoDB/hBase,Thegameistoselectappropriatealgorithmsofstringcomparisonusingmultiplehints todisplaymeaningful combinationof words. For example, Hints: Pratapgad(Fort) Historical Locationhint, Historical EventhintoutcomecanbeShri Shivaji Raje, developPython/Scala/JavaMobileApp. Largerthenumberofhintslesserthemarksfortheoutcome. Thereshouldbelargenumberofcombinationsinthehintsdatabase. UseConcurrentsearchingandMergingalgorithms.Findtheeciency/Complexity.Elective-IIA5 Electiveteacher canframesuitabledistributedprogrammingapplicationusingwireless networks andsmartdevicesequivalenttoA1/A2/A3/A4above.30Elective-IIB1 InarollingdisplayprogramofnewsdisplayonasmartTVorComputerDisplaytheinputstringsaresuppliedbythemobilephone. DevelopnecessaryappusingScala/Python/Java/C++.Elective-IIB2 InarollingdisplayprogramofnewsdisplayonasmartTVorComputerDisplaytheinputstringsaresuppliedbyanothercomputerconnectedthroughwirelessnetworks.DevelopnecessaryappusingScala/Python/Java/C++.Elective-IIB3 The BBB (Beagale Bone Black) is used in a Samrt CAR to rotate the steeper motor of a glass window byprogrammable angle, use model as a HOTSPOT device to transfer the Computer/Internet/Intranet pagedataofangleofrotation. WriteadistributedapplicationusingJSON/xml andJava/Scala/Python/C++.Elective-IIB4 ElectiveteachercanframesuitabledistributedprogrammingapplicationusingwirelessnetworksusingPervasiveenvironmentequivalenttoB1/B2/B3above.Elective-IIC1 UsingPython/JavawithBBBdevelopmentboardwriteaembeddedsecurityapplicationofapasswordbased door lock(stepper motor can be used with Photo diode or use LEDs. Use Mobile/ laptop/ desktopasahotspotdevice/Bluetoothdevicetolockorunlockthedoor.Elective-IIC2 WriteamobileappusingScala/Python/C++/AndroidusingEclipsetobeepthemobilespeakerforthreeincorrectattemptsofthepassword.Elective-IIC3 Electiveteacher canframesuitabledistributedprogrammingapplicationusingwireless networks andsmartdevicesindistributedenvironmentequivalenttoC1/C2above.Elective-IID: UsingProgramminglanguagePythonandNaturalLanguageToolKit(NLTK)performthefollowing:Elective-IID1 ApplySimplelanguageprocessingfor10phoneticsIndianlanguages(Marathiormother-tongue)Elective-IID2 LabonSoundPropagation.Elective-IID3 LabonQuantifyingthePerceptionofSound.Elective-IID4 LabontheAcousticAnalysisofSpeech. GroupC(AnyOneAssignment)1 StudyandimplementationofresearchpaperinMultidisciplinaryNLPusingopensourcetool2 Write a program to Smart Watch App Development with Tizen. Objective of this assignment is to designsimplecomicappwiththeTizenSDKforWearableandrunitonthesmartwatchemulatorthatcomesbundledwiththeIDE.TextBooks:Sl.No. TextBooks1. LaboratoryManualgeneratedbytheLaboratoryTeachersoftherespectivecollege,intheTerm-workFormat;tobeassessedandapprovedbytheBoS2. ContentinDigitalLibrary31410448ProjectTeachingScheme ExaminationSchemeTutorial: 2Hrs/Week TermWorkAssessment: 50CourseObjectives: Todevelopproblemsolvingabilitiesusingmathematics; Toapplyalgorithmicstrategieswhilesolvingproblems; Todeveloptimeandspaceecientalgorithms; Todevelopsoftwareengineeringdocumentsandtestingplans; Tousealgorithmicsolutionsusingdistributed,Embedded,concurrentandparallelenvironments. ToencourageandexposestudentsforparticipationinNational/Internationalpaperpresentationactiv-ities. Exposure to Learning and knowledge access techniques using Conferences, Journal papers and participa-tioninresearchactivities.CourseOutcomes: Tosolveprobleminprojects; TodevelopSRSandothersoftwareengineeringdocumentsintheprojectreport; Tosolveproblemsusingmulti-core,distributed,embedded,concurrent/Parallelenvironments; Towriteconferencepaper; Todemonstratepresentation,communicationandteam-workskills.Tools:Preferably64-bitFOSStoolsbutifsponsoringcompanysrequirementisnon-opensourceplatformthenitmustbelatestandcurrentversionofnon-absolutetools. 64-biti5/i7/Desktops/Mobiles,LatestSAN,3-tierarchitecturesalongwithlatestversionofFOSSOperatingsystemslikeFedora21orequivalent,LAMPtools,WEBserver,Applicationsservers,Databaseservers,MongoDBorlatestopensourceBigDATAtools,FOSSProgrammingToolslikegcc,g++,Eclipse,Python,JavaandothertoolsareaspertherequirementoftheSRS.ThedocumentationtoolslikeOpenoce,GIT,Latex,Latex-Presentation.ActivityPlanningforTutorialSessions:I Selectionof Project OptionandFramingthe Problemtosolve as aProject for the groupof 3to4students.OptionA:IndustrySponsoredProjectOptionB:ProjectasaEntrepreneurOptionC:InternalProjectII Internal guideallocationfortheBEProject: AssistantProfessor/AssociateProfessor/ProfessorasperAICTE norms in computer engineering having atleast 5 years of full time approved experience can guidetheBEProjectwithoutcompromisingonthequalityof thework(ref. Note1). TheProjectlaboratoryof 4project groups (3to4students inonegroup) constitutingonelaboratorytutorial batch(2hrsperweek), beallocatedtotheguide. Theprojectgroupwill submitthesynopsisincludingtitleof theproject, Technical KeyWords (Ref. ACMKeywords) andrelevant mathematics associatedwiththeProject, names of atleast two conferences, where papers can be published, Review of Conference/Journalpapers(atleast10papers+Whitepapersorwebreferences,(ifany))supportingtheprojectidea,Planof project execution using planner or alike project management tool.(Recommended dates: 3 weeks afterCommencement of the Term). Preferably, theprojects are IndustrySponsoredor part of highlevelresearch/ Sponsored Research Project that are not conducted for any award of the educational degree orentrepreneurshipproject.32III Theprojectconductandproceduresareamendedasdetailedbelow:-Problemstatementfeasibilityas-sessmentusing, satisabilityanalysisandNP-Hard, NP-CompleteorPtypeusingmodernalgebraandrelevantmathematicalmodels.(recommendeddateofsubmission:-8weeksbeforetermend)IVUse of above to identify objects, morphism, overloading, functions and functional relations and any otherdependencies. (recommendedsubmissiondate:-6weeksbeforetermend)FunctionaldependencygraphsandrelevantUMLdiagramsorothernecessities.(recommendedsubmissiondate:- 3weeksbeforetermend)VTestingof problemstatementusinggeneratedtestdata(usingmathematical models, Functiontestingprinciples)selectionandappropriateuseoftestingtools, testingofUMLdiagramsreliability. (recom-mendedsubmissiondate:-twoweeksbeforetermend)VI The index of submission must cover above mentioned 5 heads in addition to the instructions by the guide.Students must submit a Latex Report consisting of problem denition, literature survey, platform choice,SRS(SystemRequirementSpecication)Documentinspecicformatandhigh-level designdocumentalong with Annex A: Laboratory assignments on Project Analysis of Algorithmic Design, Annex B: Lab-oratory assignments on Project Quality and Reliability Testing of Project Design at the end of term-I andAnnex C: Project Planner and progress report afterchecking,removing/avoidingtheplagiarism.Give an additional assignment per reporting plagiarism to be submitted in the report undertheAnnexheadingextra-work. Iftheprojectisthereplicaofanyotherpreviousprojectorworkfromotherunrelatedpersonsthanthestudentsteam,suchprojectshouldberejectedforthetermwork.Thetermworkattheendof Term-Ishall beassessedandevaluatedfor50marksbythepanel of ex-aminersinthesubject(Internal (preferablyguide)andexternal examinerfromComputerDepartmentof EngineeringColleges). At-leastonetechnical papermustbesubmittedontheprojectdesignintheconferences/workshops in IITs, Central Universities or UoP Conferences or equivalent International Con-ferences Sponsored by IEEE/ACM and review comments received as Annex D. The examiners must seekanswersregardingthesuggestionsgiveninthereviewcommentsofthepapersubmitted.Term-IProjectLaboratoryAssignments: TutorialSession1. ReferChapter7ofrstreferencetodeveloptheproblemunderconsiderationandjustifyfeasibiltyusingconceptsofknowledgecanvasandIDEAMatrix.2. Project problemstatement feasibilityassessment usingNP-Hard, NP-Completeor satisabilityissuesusingmodernalgebraand/orrelevantmathematicalmodels.3. Useof divideandconquerstrategiestoexploitdistributed/parallel/concurrentprocessingof theabovetoidentifyobjects,morphisms,overloadinginfunctions(ifany),andfunctionalrelationsandanyotherdependencies(asperrequirements).4. Use of above to draw functional dependency graphs and relevant Software modeling methods, techniquesincludingUMLdiagramsorothernecessitiesusingappropriatetools.5. Testing of project problem statement using generated test data (using mathematical models, GUI, Func-tiontestingprinciples, ifany)selectionandappropriateuseoftestingtools, testingofUMLdiagramsreliability.ForEntrepreneurshiptypeprojectadditionalassignments: TutorialSession6. To sign the MoU/agreement with the Engineering College for the Industry-on-Campus. The college shallprovidethecompanytheenclosurewithlock-and-keytoaccommodaterequiredtablespace, stabilizedelectricityandtheInternetaccess. TheCollegemayhostsuchcompanyforrsttwoyearsandfurtherbyrenewingtheMoU/Agreement. Thecollegeshallprovideallsuchdocumentsnecessaryfortheestab-lishmentof thecompany. TheCollegeshall provideall thefacilitiesasperagreementforRentFREE,without any charges or fees or returns whatsoever for the First Year or Academic Duration of the activity.ThecollegemaypreparejointproposalwithcompanyfortheAICTE/Government/Universitygrantsifany.337. Tostudyandestablishapartnershipcompany/proprietorshipandgetthePAN,MVAT,ProfessionTaxNumberandsuchothernecessarylegalpermissions.8. TryandprepareclientslistandcommunicationwiththeclientsoradvertisetheproductbydevelopingtheCompanyWEBSite.9. Tosubmit Product Proposal for raisingventure capital throughgovernment schemes of micro/smallsectorindustriesorthroughprivateventurecapitalentities.10. Tosubmit National/International patent/Copyright for rst year tothe Government Department ofPatentsandIPR.Note1. TheguideforanentrepreneurshipprojectshallbeafulltimeapprovedProfessororAsso-ciateProfessorpossessingqualicationsasperAICTEnorms.Note2. If thestudents fails tocompletetheentrepreneurshipassignments successfullythentheprojectshallbetreatedasInternalProjectforthepurposeofassessment.Note3. All projects are expected to exploit multi-core,embedded and distributed computing wher-everpossible.ReferenceBooks:Sl.No. ReferenceBooks1. Dr. ParagKulkarni,KnowledgeInnovationStrategy,BloomsburyPublication,ISBN:978-93-84898-03-8,20152. Dr. P.K.Sinhaet.al.,ElectronicHealthRecord,IEEEPressWileyISBN:978-1-118-28134-53. McKinseyreport: Bigdata: Thenextfrontierforinnovation,competition,andproductivity(PDF)4. WebResource: http://www.mckinsey.com/insights... digitalcompetition5. WebResource: http://msme.gov.in/mob/home.aspx34Semester-II410449SoftwareDesignMethodologiesandTestingTeachingScheme ExaminationSchemeLectures: 3Hrs/Week InsemesterAssessment: 30EndSemesterAssessment: 70CourseObjectives: Tounderstandandapplydierentdesignmethodsandtechniques Tounderstandarchitecturaldesignandmodeling Tounderstandandapplytestingtechniques To implement design and testing using current tools and techniques in distributed, concurrent and parallelenvironmentsCourseOutcomes: Tochooseandapplydesigntechniquesforsoftwaresystem TodesignandmodelusingUMLforagivensoftwaresystem Todesigntestcasesandimplementautomatedtestingforclientserver,Distributed,mobileapplicationsUnit Content HrsI Concepts 6IntroductiontosoftwareDesign,DesignMethods:ProceduralandStructuralDesignmethods,ObjectOrienteddesignmethod,UniedmodelingLanguageoverview,StaticandDynamicModeling-AdvanceUsecase,Class,State,SequenceDiagramsII ArchitecturalDesign 6ArchitecturalDesign,importanceandarchitectureviews,client-server,serviceoriented,componentbasedconcurrentandrealtimesoftwarearchitecturewithcasestudiesIII IntroductiontoDesignPatterns 8DesignPatterns;Introduction,creational,Structuralandbehavioralpatterns,singleton,proxy,adapter,factory,iterator,observerpatternwithapplicationIV PrinciplesofSoftwareTesting 6Testingconcepts,Principlesofsoftwaretesting,vericationandvalidation,V-testmodel,defectmanagementV TestingStrategies 8Testingstrategies,unit,integrationandsystemtesting,acceptance,alpha,beta,performance,securitytesting,whiteboxandblackboxtesting,basispathtesting,equivalencetesting,graphbasetesting,testmetricandreportVI AdvancedTechniquesandTools 4GUItesting,functionaltesting,Automatedtestingtools,features,selection,mobiletesting,testingtoolslikeselenium,Junit,monkeytalkTextBooks:Sl.No. TextBooks1. HASSANGOMAA,SoftwareModelingandDesign,CambridgeuniversityPress,2011,ISBN-13978-1-107-44735-62. ErichGamma,RichardHelm,RalphJohnson,JohnVlissides,DesignpatternsElementsofReusableObject-OrientedSoftware3. SrinivasanDesikan,SoftwareTestingPrincipalsandpractices,PearsonPublicationISBN-13978-8-17-758295-6ReferenceBooks:Sl.No. ReferenceBooks1. GradyBooch,JamesRumbaugh,IvarJacobson,TheUMLUsersGuide,PearsonPublication2013printISBN-13-978817758372-435410450HighPerformanceComputingTeachingScheme ExaminationSchemeLectures: 3Hrs/Week InsemesterAssessment: 30EndSemesterAssessment: 70CourseObjectives: TodevelopproblemsolvingabilitiesusingHPC Todeveloptimeandspaceecientalgorithms Tostudyalgorithmicexamplesindistributed,concurrentandparallelenvironmentsCourseOutcomes: Transformalgorithms inthecomputational areatoecient programmingcodefor moderncomputerarchitectures Write,organizeandhandleprogramsforscienticcomputations Usetoolsforperformanceoptimizationanddebugging Analyzecodewithrespecttoperformanceandsuggestandimplementperformanceimprovements Tosolveproblemsformulti-coreordistributed,concurrent/ParallelenvironmentsUnit Content HrsI ParallelProcessingConcepts 8IntroductiontoParallelComputing: MotivatingParallelism,ScopeofParallelComputing,OrganizationandContentsoftheText,ParallelProgrammingPlatforms: ImplicitParallelism: TrendsinMicroprocessor&Architectures,LimitationsofMemorySystemPerformance,DichotomyofParallelComputingPlatforms,PhysicalOrganizationofParallelPlatforms,CommunicationCostsinParallelMachinesLevelsofparallelism(instruction,transaction,task,thread,memory,function)Models(SIMD,MIMD,SIMT,SPMD,DataowModels,Demand-drivenComputation)Architectures: N-widesuperscalararchitectures,multi-core,multi-threadedII ParallelProgramming 8PrinciplesofParallelAlgorithmDesign: Preliminaries,DecompositionTechniques,CharacteristicsofTasksandInteractions,MappingTechniquesforLoadBalancing,MethodsforContainingInteractionOverheads,ParallelAlgorithmModels,ProcessorArchitecture,Interconnect,Communication,MemoryOrganization,andProgrammingModelsinhighperformancecomputingarchitectureexamples: IBMCELLBE,NvidiaTeslaGPU,IntelLarrabeeMicroarchitectureandIntelNehalemmicro-architectureMemoryhierarchyandtransactionspecicmemorydesign,ThreadOrganizationIII FundamentalDesignIssuesinHPC 6ProgrammingUsingtheMessage-PassingParadigm: PrinciplesofMessage-PassingProgramming,TheBuildingBlocks: SendandReceiveOperations,MPI:theMessagePassingInterface,TopologyandEmbedding,OverlappingCommunicationwithComputation,CollectiveCommunicationandComputationOperations,One-DimensionalMatrix-VectorMultiplication,Single-SourceShortest-Path,SampleSort,GroupsandCommunicators,Two-DimensionalMatrix-VectorMultiplicationIV Synchronizationandrelatedalgorithms 6Synchronization: Scheduling,JobAllocation,JobPartitioning,DependencyAnalysisMappingParallelAlgorithmsontoParallelArchitectures,PerformanceAnalysisofParallelAlgorithmsProgrammingSharedAddressSpacePlatforms: ThreadBasics,WhyThreads?,ThePOSIXThreadAPI,ThreadBasics: CreationandTermination,SynchronizationPrimitivesinPthreads,ControllingThreadandSynchronizationAttributes,ThreadCancellation,CompositeSynchronizationConstructs,TipsforDesigningAsynchronousPrograms,OpenMP:aStandardforDirectiveBasedParallelProgramming36V Advancedtools,techniquesandapplications 6BandwidthLimitations,LatencyLimitations,LatencyHiding/ToleratingTechniquesandtheirlimitations,DenseMatrixAlgorithms: Matrix-VectorMultiplication,Matrix-MatrixMultiplication,Sorting: Issues,SortingonParallelComputers,SortingNetworks,BubbleSortanditsVariants,Quicksort,BucketandSampleSort,Shared-Address-SpaceParallelFormulation,Single-SourceShortestPaths-DistributedMemoryFormulationVI HPCenabledAdvancedtechnologies 6SearchAlgorithmsforDiscreteOptimizationProblems: SearchOverheadFactor,ParallelDepth-FirstSearch,ParallelBest-FirstSearch,Introductionto(BlockDiagramsonlyifany)PetascaleComputing,OpticsinParallelComputingQuantumComputers,RecentdevelopmentsinNanotechnologyanditsimpactonHPCPower-awareProcessingTechniquesinHPCTextBooks:Sl.No. TextBooks1. KaiHwang,AdvancedComputerArchitecture: Parallelism,Scalability,Programmability,McGrawHill19932. DavidCullerJaswinderPalSingh,ParallelComputerArchitecture: Ahardware/SoftwareApproach,MorganKaufmann,1999.ReferenceBooks:Sl.No. ReferenceBooks1. KaiHwang,,ScalableParallelComputing,McGrawHill1998.2. GeorgeS.AlmasiandAlanGottlieb,HighlyParallelComputing,TheBenjaminandCummingsPub. Co.,Inc3. WilliamJamesDallyandBrianTowles,PrinciplesandPracticesonInterconnectionNetworks,MorganKauman2004.4. HubertNguyen,GPUGems3-by(Chapter29toChapter41)5. AnanthGrama,AnshulGupta,GeorgeKarypis,andVipinKumar,IntroductiontoParallelComputing,2ndedition,Addison-Welsey, c 20036. DavidA.Bader(Ed.),PetascaleComputing: AlgorithmsandApplications,Chapman&Hall/CRCComputationalScienceSeries, c 2007.37410451AElective-III:MobileComputingTeachingScheme ExaminationSchemeLectures: 3Hrs/Week InsemesterAssessment: 30EndSemesterAssessment: 70CourseObjectives: TodevelopproblemsolvingabilitiesusingMobileComputing TostudyfoundationsofMobileComputingCourseOutcomes: TosolveproblemusingMobileComputingUnit Content HrsI FundamentalofWirelessandbasicsofwirelessnetwork 6Digitalcommunication,wirelesscommunicationsystemandlimitations,wirelessmedia,frequencyspectrum,technologiesindigitalwirelesscommunication,wirelesscommunicationchannelspecication,wirelessnetwork,wirelessswitchingtechnology,wirelesscommunicationII MobileCommunicationsandComputing 7AnOverviewMobileCommunication,MobileComputing,MobileComputingArchitecture,MobileDevices,MobileSystemNetworks,DataDissemination,MobilityManagement,Security,MobileDevicesandSystems,MobilePhones,DigitalMusicPlayers,Hand-heldPocketComputers,Hand-heldDevices:OperatingSystems,SmartSystems,LimitationsofMobileDevices,AutomotiveSystems.III GSMandotherarchitectures 6GSM-Services&SystemArchitectures,RadioInterfaces,ProtocolsLocalization,Calling,Handover,Security,NewDataServices,modulation,multiplexing,controllingthemediumaccess,spreadspectrum,codingmethods,CDMA,IMT2000,WCDMAandCDMA2000,4GNetworks.IV MobileNetworkandTransportLayer 7IP&MobileIPNetworkLayers,PacketDelivery&HandoverManagement,LocationManagement,Registration,Tunneling&Encapsulation,RouteOptimization,DynamicHostCongurationProtocol,MobileTransportLayer,ConventionalTCP/IPTransportLayerProtocol,IndirectTCP,SnoopingTCP,MobileTCP,MobileAd-hocNetworks(MANET),RoutingandRoutingAlgorithmsinMANET,securityinad-hocnetworks.V DataDisseminationandDataSynchronizationinMobileComputing 7CommunicationAsymetry,classicationofdatadeliverymechanism,datadisseminationbroadcastmodels,selectivetuningandindexingtechniques,synchronization,synchronizationsoftwareformobiledevices,synchronizationprotocols.VI MobileDevicesandMobileOperatingSystem 6Mobileagent,applicationsframework,applicationserver,gateways,servicediscovery,devicemanagement,mobilelesystem,MobileOperatingSystems,Characteristics,BasicfunctionalityofOperatingSystems: Window8,iOS,AndroidOS.TextBooks:Sl.No. TextBooks1. RajKamal,MobileComputing,2/e,OxfordUniversityPress-NewDelhi2. Dr. SunilkumarS.Manavi,MahabaleshwarS.Kakkasageri,WirelessandMobileNetworks,conceptsandprotocols,Wiley,India.ReferenceBooks:Sl.No. ReferenceBooks1. AndrewTanenbaum,ModernOperatingSystem,3rd/e,PearsonEducationInternational,ISBNQ-lB-lBMST-L2. DigitalContent: iOSTechnologyOverview: IOSTechOverview.pdf,AppleInc. Copyright201438410451BElective-III:WebTechnologyTeachingScheme ExaminationSchemeLectures: 3Hrs/Week InsemesterAssessment: 30EndSemesterAssessment: 70CourseObjectives: ToLearnadvancedWebTechnologies ToapplytechnologieswhilesolvingproblemsCourseOutcomes: TousetechnologiesforsolvingproblemsinprojectsUnit Content HrsI IoTWebTechnology 6TheInternetofThingsToday,TimeforConvergence,TowardstheIoTUniverse,InternetofThingsVision,IoTStrategicResearchandInnovationDirections,IoTApplications,FutureInternetTechnologies,Infrastructure,NetworksandCommunication,Processes,DataManagement,Security,Privacy&Trust,DeviceLevelEnergyIssues,IoTRelatedStandardisation,RecommendationsonResearchTopics.II IoTApplicationsforValueCreation 6Introduction,IoTapplicationsforindustry: FutureFactoryConcepts,BrowneldIoT,SmartObjects,SmartApplications,FourAspectsinyourBusinesstoMasterIoT,ValueCreationfromBigDataandSerialization,IoTforRetailingIndustry,IoTForOilandGasIndustry,OpinionsonIoTApplicationandValueforIndustry,HomeManagement,eHealth.III InternetofThingsPrivacy,SecurityandGovernance 6Introduction,OverviewofGovernance,PrivacyandSecurityIssues,ContributionfromFP7Projects,Security,PrivacyandTrustinIoT-Data-PlatformsforSmartCities,FirstStepsTowardsaSecurePlatform,SmartieApproach. DataAggregationfortheIoTinSmartCities,SecurityIV ArchitecturalApproachforIoTEmpowerment 8Introduction,DeningaCommonArchitecturalGround,IoTStandardisation,M2MServiceLayerStandardisation,OGCSensorWebforIoT,IEEE,IETFandITU-Tstandardizationactivities,InteroperabilityChallenges,PhysicalvsVirtual,SolvetheBasicFirst,DataInteroperability,SemanticInteroperability,OrganizationalInteroperability,EternalInteroperability,ImportanceofStandardisation,Planforvalidationandtesting,ImportantEconomicDimension,ResearchRoadmapforIoTTestingMethodologies. SemanticasanInteroperabilityEnablerandrelatedwork.V IdentityManagementModelsinIoT 8Introduction,VulnerabilitiesofIoT,Securityrequirements,ChallengesforasecureInternetofThings,identitymanagement,Identityportrayal,Dierentidentitymanagementmodel: Localidentity,Networkidentity,Federatedidentity,Globalwebidentity,IdentitymanagementinInternetofThings,User-centricidentitymanagement,Device-centricidentitymanagement,Hybrididentitymanagement.VI TrustManagementinIoT 6Introduction,Trustmanagementlifecycle,Identityandtrust,Thirdpartyapproach,Publickeyinfrastructure,Attributecerticates,Weboftrustmodels,Webservicessecurity,SAMLapproach,FuzzyapproachforTrust,AccesscontrolinIoT,Dierentaccesscontrolschemes,AuthenticationandAccesscontrolpoliciesmodelling.TextBooks:Sl.No. TextBooks1. Dr. OvidiuVermesan,Dr. PeterFriess,InternetofThings: ConvergingTechnologiesforSmartEnvironmentsandIntegratedEcosystems,RiverPublishers,2013,ISBN:978-87-92982-96-4(E-Book),ISBN:978-87-92982-73-5(Print)2. Dr. ParikshitMahalle,PoonamRailkar,IdentityManagementforInternetofThing,RiverPublishers,2015,ISBN:978-87-93102-91-0(EBook),ISBN:978-87-93102-90-3(HardCopy)39ReferenceBooks:Sl.No. ReferenceBooks1. CunoPster,GettingStartedwiththeInternetofThings,OReillyMedia,2011,ISBN:978-1-4493-9357-140410451CElective-III:CloudComputingTeachingScheme ExaminationSchemeLectures: 3Hrs/Week InsemesterAssessment: 30EndSemesterAssessment: 70CourseObjectives: Tostudycloudcomputingconcepts; Enhancingcloudcomputingenvironment. Tostudyvariousplatforms Tostudytheapplicationsthatusescloudcomputing.CourseOutcomes: Toinstallcloudcomputingenvironments. TodevelopanyonetypeofcloudUnit Content HrsI Introduction 6Introduction,RootsofCloudComputing: FrommainframetoCloud,BenetsofCloudComputingSOA,Webservices,Web2.0,Mashups,Gridcomputing,Utilitycomputing,Hardwarevirtualization,EssentialsofCloudcharacteristics,Challenges,Cloudeconomics,RoleofNetworksinCloudComputing: Cloudtypesandservicemodels,Cloudcomputingplatforms: Openstack,Opennimbus,EucalyptusPrimaryCloudServicemodels,CloudServicesbrokerage,Primaryclouddeploymentmodels,cloudcomputingreferencemodel,ThegreeneldandbrownelddeploymentoptionsII Virtualization 8Introduction,CharacteristicsofVirutalizedenvironments,TaxonomyofVirtualizationtechniques,ProsandConsofVirtualization,Technologyexamples:Xen,KVM,Vmware,MicrosoftHyper-VIII StorageinCloud 8Storagesystemarchitecture,Bigdata,Virtualizedatacentre(VDC)architecture,VDCEnvironment,server,storage,networking,desktopandapplicationvirtualizationtechniquesandbenets,VirtualMachineComponentsandProcessofconvertingphysicaltoVMs,Blockandlelevelstoragevirtualization,VirtualProvisioning,andautomatedstoragetiering,VLAN,VSANandbenits,NetworktracmanagementtechniquesinVDC,Cloudlesystems: GFSandHDFS,BigTable,HBaseandDynamo. FeaturesandcomparisonsamongGFS,HDFS.IV Cloudcomputingplatforms 6InfrastructureasService,best-ofbreedcloudinfrastructurecomponents,cloudreadyconvergedinfrastructure,Virtualmachineprovisioningandmigrationservices,AnatomyofCloudinfrastructure,Distributedmanagementofvirtualinfrastructure,schedulingtechniques,SLACommitmentV Cloudmonitoringandmanagement 8Introductionandarchitectureforfederatedcloudcomputing,PerformancepredictionforHPConCloud. SLAmanagement: TypesofSLA,LifecycleofSLA,TraditionalapproachesofSLA.servicecatalog,serviceorderingprocess,managementandfunctionalinterfacesofservices,cloudportalanditsfunctions,cloudinterfacestandardsalongwithSOAPandREST,systemintegrationandwork-owmodeling,cloudservicelife-cyclephases: serviceplanning,servicecreation,serviceoperation,andserviceterminationControllayer,itsfunctionsandbenets,elementanduniedmanager,softwaredenedapproachandtechniquesformanagingITresources41VI SecurityinCloudComputing 6Introduction,GlobalRiskandComplianceaspectsincloudenvironmentsandkeysecurityterminologies,TechnologiesforDatasecurity,Datasecurityrisk,Cloudcomputingandidentity,Digitalidentityandaccessmanagement,Contentlevelsecurity,Security-As-A-CloudServiceTextBooks:Sl.No. TextBooks1. RajkumarBuyya,Cloudcomputingprinciplesandparadigms,Wiley2. GautamShro,EnterpriseCloudComputing,Cambridge3. HandbookofCloudComputing,SpringerPublication4. RajkumarBuyya,MasteringCloudcomputing,McGrawHill5. TimMather,SubraK,ShahidL.,CloudSecurityandPrivacy,Oreilly,ISBN-13978-81-8404-815-5ReferenceBooks:Sl.No. ReferenceBooks1. Dr. KumarSaurabh,CloudComputing,WileyPublication2. GregSchulr,Cloudandvirtualdatastoragenetworking,CRCPress3. BarrieSosinsky,CloudComputing,WileyIndia4. KailashJayaswal,Cloudcomputing,BlackBook,DreamtechPress5. AnthonyT.Velte,CloudComputing: APracticalApproach,TataMcGrawHill,2009,ISBN:00706835146. RichardHill,GuidetoCloudComputing: PrincipalsandPractices,SpringerISBN-10: 14471460267. HalperFern,KaufmanMarcia,BloorRobin,HurwitJudith,CloudComputingforDummies,WileyIndia,2009,ISBN812652487142410451DElective-III:CyberSecurityTeachingScheme ExaminationSchemeLectures: 3Hrs/Week InsemesterAssessment: 30EndSemesterAssessment: 70CourseObjectives: TodevelopproblemsolvingabilitiesusingCyberSecurity Toapplyalgorithmicstrategiesforcybersecurity Todeveloptimeandspaceecientalgorithms Tostudyalgorithmicexamplesindistributed,concurrentandparallelenvironmentsCourseOutcomes: TosolveprobleminCyberSecurity Tosolveproblemsformulti-coreordistributed,concurrent/ParallelenvironmentsUnit Content HrsI SecurityBasics 6Introduction,ElementsofInformationsecurity,SecurityPolicy,Techniques,steps,Categories,OperationalModelofNetworkSecurity,BasicTerminologiesinNetworkSecurity.II DataEncryptionTechniquesandStandards 8Introduction,EncryptionMethods: Symmetric,Asymmetric,Cryptography,SubstitutionCiphers. TranspositionCiphers,Stenographyapplicationsandlimitations,BlockCiphersandmethodsofoperations,FeistalCipher,DataEncryptionStandard(DES),TripleDES,DESDesignCriteria,WeakKeysinDESAlgorithms,AdvanceEncryptionStandard(AES).III PublicKeyandManagement 8PublicKeyCryptography,RSAAlgorithm: Working,Keylength,Security,KeyDistribution,Dee-HellmanKeyExchange,EllipticCurve: Arithmetic,Cryptography,Security,Authenticationmethods,MessageDigest,Kerberos,X.509Authenticationservice,DigitalSignatures: Implementation,Algorithms,Standards(DSS),AuthenticationProtocol.IV Securityrequirements 8ElectronicMailSecurity: Introduction,PrettyGoodPrivacy,MIME,S/MIME,Comparison. IPSecurity: Introduction,Architecture,IPV6,IPv4,IPsecprotocolsandOperations,AHProtocol,ESPProtocol,ISAKMPProtocol,OakkeydeterminationProtocol,VPN.WEBSecurity:Introduction,SecureSocketLayer(SSL),SSLSessionandConnection,SSLRecordProtocol,ChangeCipherSpecProtocol,AlertProtocol,HandshakeProtocol,SecureElectronicTransaction(SET).V IntrusionandFirewall 6Introduction,Intrusiondetection,IDS:Need,Methods,TypesofIDS,PasswordManagement,LimitationsandChallenges,FirewallIntroduction,Characteristicsandtypes,Benetsandlimitations. Firewallarchitecture,TrustedSystems,AccessControl.VI SecurityperspectiveofHackinganditscountermajors 6RemoteconnectivityandVoIPhacking,WirelessHacking,MobileHacking,HackingHardware,ApplicationanddataHacking,MobileHacking,Countermajors:GeneralStrategies,ExampleScenarios: Desktop,Servers,Networks,Web,Database,Mobile.TextBooks:Sl. TextBooksNo.1. Dr. V.K.Pachghare,CryptographyandInformationSecurity,PHI,ISBN978-81-303-5082-32. NinaGodbole,SunitBelapure,CyberSecurity,WileyIndia,ISBN:978-81-345-2179-143ReferenceBooks:Sl. ReferenceBooksNo.1. PDFDigitalContent: StuartMcCLURE,JoelScambray,GeorgeKurtz,HackingExposedNetworkSecuritySecretsandSolutions,McGrowHill,2012ISBN:978-0-07-178028-5DigitalRef: http://84.209.254.175/linux-pdf/Hacking-Exposed-7-Network-Security-Secrets.pdfCollegelibrariesarerequestedtopurchasethecopy2. DigitalContentPublishedbytheBoS44410452AElective-IV(OpenElective): BusinessAnalyticandIntelligenceTeachingScheme ExaminationSchemeLectures: 3Hrs/Week InsemesterAssessment: 30EndSemesterAssessment: 70CourseObjectives: TodevelopproblemsolvingabilitiesusingMathematics Toapplyalgorithmicstrategieswhilesolvingproblems Todeveloptimeandspaceecientalgorithms Tostudyalgorithmicexamplesindistributed,concurrentandparallelenvironmentsCourseOutcomes: Tosolveprobleminprojects TodevelopSRSintheprojects Tosolveproblemsformulti-coreordistributed,concurrent/ParallelenvironmentsUnit Content HrsI ConceptswithMathematicaltreatment 8Introductiontodata,Informationandknowledge,DecisionSupportSystem,TheoryofOperationaldataandinformationaldata,IntroductiontoBusinessIntelligence,DeningBICycle,BIEnvironmentandArchitecture,IdentifyBIopportunities,BenetsofBI.RoleofMathematicalmodelinBI,FactorsResponsibleforsuccessfulBIProject,ObstacletoBusinessIntelligenceinanOrganizationII DecisionMakingConcepts 6ConceptsofDecisionMaking,TechniquesofDecisionSupportSystem(DSS),DevelopmentofDecisionSupportSystem(DSS),ApplicationsofDSS,RoleofBusinessIntelligenceinDSS.III Data-Warehouse 6Introduction: DatawarehouseModeling,datawarehousedesign,data-ware-housetechnology,Distributeddatawarehouse,andmaterializedviewIV DataPre-processingandoutliers 8DataAnalyticslifecycle,Discovery,Datapreparation,Preprocessingrequirements,datacleaning,dataintegration,datareduction,datatransformation,Datadiscretizationandconcepthierarchygeneration,ModelPlanning,Modelbuilding,CommunicatingResults&Findings,Operationalizing,IntroductiontoOLAP.Real-worldApplications,typesofoutliers,outlierchallenges,OutlierdetectionMethods,Proximity-BasedOutlieranalysis,ClusteringBasedOutlieranalysis.V DesigningandmanagingBIsystems 6Determininginfrastructurerequirements,planningforscalabilityandavailability,managingandmaintenanceofBIsystems,managingBIoperationsforbusinesscontinuityVI BIandDataMiningApplications 6Dataanalytics,businessanalytics,ERPandBusinessIntelligence,BIApplicationsinCRM,BIApplicationsinMarketing,BIApplicationsinLogisticsandProduction,RoleofBIinFinance,BIApplicationsinBanking,BIApplicationsinTelecommunications,BIApplicationsinFraudDetection,BIApplicationsinRetailIndustry.TextBooks:Sl.No. TextBooks1. R.Sharda,D.Delen,&E.Turban,BusinessIntelligenceandAnalytics. SystemsforDecisionSupport,10thEdition. Pearson/PrenticeHall,2015.ISBN-13: 978-0-13-305090-5,ISBN-10: 0-13-305090-4;2. BusinessProcessAutomation,SanjayMohapatra,PHI.45ReferenceBooks:Sl.No. ReferenceBooks1. IntroductiontobusinessIntelligenceanddatawarehousing,IBM,PHI.2. Dataminingconceptsandtechniques,JawaiHan,MichellineKamber,JiranPie,MorganKaufmannPublishers3rdedition.3. BuildingthedataWarehouse,WilliamHInmon,WileyPublication4thedition.4. DataMiningforBusinessIntelligence,WILEY5. SoumendraMohanty,AnalyticsinPractice,TataMcGrawHillEducation,2011,ISBN-1397800707070616. KenW.Collier,AgileAnalytics: AvaluedrivenApproachtoBusinessIntelligenceandDataWarehousing,PearsonEducation,2012,ISBN-1397881317868267. DonaldMiner,MapReduceDesignPattern,OReilly,2012,ISBN97893502398108. EMCEducationalServices,DataScienceandBigDataAnalytics: Discovering,Analyzing,VisualizingandPresentingData,WileyISBN-13978111887613846410452BElective-IV(OpenElective): OperationsResearchforAlgorithmsinScienticApplicationsTeachingScheme ExaminationSchemeLectures: 3Hrs/Week InsemesterAssessment: 30EndSemesterAssessment: 70CourseObjectives: TodevelopproblemsolvingabilitiesusingMathematics Toapplyalgorithmicstrategieswhilesolvingproblems Todeveloptimeandspaceecientalgorithms Tostudyalgorithmicexamplesindistributed,concurrentandparallelenvironmentsCourseOutcomes: Tosolveprobleminprojects TodevelopSRSintheprojects Tosolveproblemsformulti-coreordistributed,concurrent/ParallelenvironmentsUnit Content HrsI IntroductiontoOperationResearch 6OriginsofOR,Nature,ImpactandphasesofOR,OperationResearchastoolforDecisionSupportSystem,ProductivityImprovement. OverviewofORResearchTechniques.II DeterministicORModels 6FormulationofLinearProgrammingProblem,LinearProgrammingModels,AssumptionsofLinearProgramming,GraphicalMethodofsolvingLPproblem.SimplexmethodforsolvingLPproblem.III LinearProgrammingExtensions 8IntroductionandFormulationofTransportationproblem,TypesofTranspirationproblems,MethodsofInitialfeasiblesolution,Methodsofoptimumsolution,UnbalancedTransportationproblem,IntroductiontoAssignmentproblem. Solutionofanassignmentproblem.IV Decision,Game&QueueingTheory 8Formulationoftwoperson,Zero-sumGames,SolvingSimpleGames,MixedStrategies,Non-ZeroSumGames.BasicStructure&componentsofdecision,decisioncriteria,decisiontrees.Basiccharacteristicsofqueueingsystem,Terminologies&notation,Poissonprocessofqueueing,M/M/1systemqueueingmodel.V HybridORModels,ProjectManagementPERT&CPM 8AssumptionandcomparisonPERT&CPM,AlgorithmsofPERTCPMTechniques,FundamentalsofNetworkModel,GuidelinesforNetworkConstruction,CriticalpathAnalysis,MethodsbasedonTimeEstimatestondcriticalpaths. ConceptofSlack&oatsinnetworkanalysis,ProjectEvaluation&ReviewTechniques(PERT).VI DynamicProgramming 8Terminologies,MultiDecisionProcess,BellmansPrinciplesofoptimality,CharacteristicsofDynamicProgrammingproblems.DynamicprogrammingAlgorithms,SolvingLPPusingDynamicProgrammingRecentdevelopmentinORwithperspectiveofBio-Technology,NanoTechnology:TextBooks:Sl.No. TextBooks1. HamidyTaha,OperationsResearch: AnIntroduction,Pearson,8thEdition,ISBN:978-81-317-1104-02. Dr. S.D.Sharma,OperationsResearch,KedarNathRamNath&Co.47ReferenceBooks:Sl.No. ReferenceBooks1. KishorTrivedi,Probability&StatisticswithReliabilityQueuingandComputerScienceApplications,PHI,ISBN:81-203-0508-648410452CElective-IV(OpenElective): MobileApplicati