B.Tech. Degree Programme Computer Science & Engineering

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B.Tech. Computer Science & Engineering (Regular)WEB REFERENCES1. www.cse.iitb.ac.in/dbms2. www.idt.com/products3. www.developers.net/tsearch?searchkeys=database+management+system+tutorial4. www.pdf-word.net/5. www.slideshare.netCS-442DIGITAL IMAGE L T P CrPROCESSING 5 0 0 3OBJECTIVETo introduce the students about the basic concepts andanalytical methods of processing digital signals,especially, the images and imaging part; to understandthe properties of static and streaming images/video.PRE-REQUISITESKnowledge of data compression, discrete structures,digital signal processing, computer graphics1. INTRODUCTION AND DIGITAL IMAGEFUNDAMENTALS: Origins of digital imageprocessing; examples of fields that use digitalimage processing; fundamentals steps in imageprocessing; elements of digital image processingsystems; image sampling and quantization; somebasic relationships like neighbours; connectivity,distance measures between pixels; linear and nonlinear operations.2. IMAGE ENHANCEMENT IN THE SPATIALDOMAIN: Some basic gray level transformations;histogram processing; enhancement usingarithmetic and logic operations; basics of spatialfilters, smoothening and sharpening spatial filters,combining spatial enhancement3. IMAGE ENHANCEMENT IN THE FREQUENCYDOMAIN: Introduction to Fourier transform and thefrequency domain, smoothing and sharpeningfrequency domain filters; homomorphic filtering;image restoration: a model of the image degradation /restoration process, noise models, restoration in thepresence of noise only spatial filtering, periodic noisereduction by frequency domain filtering; linearposition-invariant degradations; estimation ofdegradation function; inverse filtering; Wiener filtering,constrained least square filtering, geometric meanfilter; geometric transformations.4. IMAGE COMPRESSION: Coding; inter-pixel andpsycho visual redundancy; image compressionmodels; elements of information theory; error freecompression; lossy compression; imagecompression standards.5. IMAGE SEGMENTATION: Detection ofdiscontinuities; edge linking and boundarydetection; thresholding; region orientedsegmentation; motion based segmentation6. REPRESENTATION AND DESCRIPTION:Representation, Boundary Descriptors, RegionalDescriptors, Use of Principal Components forDescription, Introduction to Morphology, Somebasic Morphological Algorithms.7. OBJECT RECOGNITION: Patterns and PatternClasses, Decision-Theoretic Methods, StructuralMethods.TEXT BOOKJain A. K., “Digital Image Processing”, Prentice Hall ofIndia, 1995REFERENCE BOOKS1. Gonzalez Rafael C. and Woods Richard E., “DigitalImage Processing”, 2nd edition, PearsonEducation, 20022. Jahne Bernd, “Digital Image Processing”, 5th Ed.,Springer, 20003. Pratt William K., “Digital Image Processing: PiksInside”, John Wiley & Sons, 2001.4. Forsyth D. A. and Ponce J., “Computer Vision: AModern Approach”, Prentice Hall, 20035. Horn Berthold, “Robot Vision”, MIT Press, McGrawHill, 19866. Jain R., Kasturi R. and Schunck B. G. , “MachineVision”, McGraw Hill, 1995WEB REFERENCES1. en.wikipedia.org/wiki/Digital_image_processing2. www.imageprocessingplace.com3. www.icaen.uiowa.edu4. www.uct.ac.za/depts/physics/laser/hanbury/intro_ip.html5. www.eng.auburn.edu/~sjreeves/Classes/IP/IP.htmlCS-443DISTRIBUTED COMPUTINGL T P Cr5 0 0 3OBJECTIVEThis course will introduce the algorithms andtechnologies of distributed systems. It will teach bothfundamentals as well as systems where thesefundamentals are applied in practice.PREREQUISITESKnowledge of databases, networking, operating systemand web technologies1. DISTRIBUTED COMPUTING: History, forms ofcomputing; strengths and weaknesses ofdistributed computing; OS basics; network basics;software engineering basics; CLIENT SERVERPARADIGM: issues, software engineering for anetwork service, connection oriented andconnectionless servers, iterative server andconcurrent server, stateful servers.2. INTERPROCESS COMMUNICATION: ArchetypalIPC program interface; event synchronization;timeouts and threading; deadlock and timeouts; datarepresentation, data encoding; text based protocols,request response protocols; event and sequencediagram; connection vs. connectionless IPC.3. DISTRIBUTED COMPUTING PARADIGMS ANDSOCKET API: Paradigms; abstraction; socketmetaphor; diagram socket API, stream modesocket API; sockets with non-blocking I/O; securesocket API4. GROUP COMMUNICATION: Unicasting;multicasting, archetypal multicast API; connectionoriented and connectionless; reliable, unreliablemulticast; Java basic multicast API.5. DISTRIBUTED OBJECTS: Message passing vs.distributed objects; archetypal distributed object42
Lingaya’s University, Faridabadarchitecture; distributed object systems; remoteprocedure calls; Java RMI architecture; API forJava RMI; Advanced RMI: Client callback, stubdownloading, RMI security manager; allowing forstub downloading6. SIMPLE OBJECT ACCESS PROTOCOL: SOAPrequest, SOAP response; Apache SOAP; invokingweb service; implementing web service7. ADVANCED DISTRIBUTED COMPUTINGPARADIGMS: Message queue system paradigm;mobile agents; network service; object spacesTEXT BOOKTanenbaum Andrew S. and van Steen Maarten,“Distributed Systems: Principles and Paradigms”,Prentice Hall, 2002.REFERENCE BOOKS1. Coulouris George, Dollimore Jean, Kindberg Tim,“Distributed Systems: Concepts and Design”, BookNews, Inc,2003.2. Garg Vijay K., “Elements of DistributedComputing”, Wiley, 2002.WEB REFERENCES1. http://en.wikipedia.org/wiki/Distributed_computing2. http://www.dhpc.adelaide.edu.au/education/dhpc/2000/lecture-notes.html3. http://www.eli.sdsu.edu/courses/spring99/cs696/notes/4. http://www.geocities.com/SiliconValley/Vista/4015/Chapter1.htmlCS-444REAL-TIME OPERATING L T P CrSYSTEMS 5 0 0 3OBJECTIVEThis course will first give an introduction into the basicconcepts of real-time computing and then treat the twomajor issues real-time scheduling and real-timekernels. Real-time scheduling will concentrateonpredictable scheduling algorithms and provide thescientific methodology required for the design of realtimesystems.Real-time kernels will address thechallenges and issues in the design andimplementation ofreal-time operating systems.PREREQUISITEKnowledge of operating systems1. INTRODUCTION: Concept of real time system;issues in real time computing; performancemeasures of real time system; hard and soft realtime systems; real time application.2. TASK ASSIGNMENT AND SCHEDULING:Different task model, scheduling hierarchy; offlinevs online scheduling; clock drives; inter-taskcommunicating and synchronization.3. MODEL OF REAL TIME SYSTEM: Processor,resources; temporal parameter; periodic taskmodel; sporadic task model; precedenceconstraints and data dependencies; schedulinghierarchy4. SCHEDULING OF PERIODIC TASK:Assumptions; fixed versus dynamic priorityalgorithms; schedulability test for fixed priority taskwith arbitrary deadlines.SCHEDULING OF APERIODIC AND SPORADICTASKS: Assumptions and approaches; deferrable;sporadic servers; slack stealing in deadline drivenand fixed priority systems; two level scheme forintegrated scheduling; Scheduling for applicationshaving flexible constrains.5. RESOURCES AND RESOURCE ACCESSCONTROL: Assumptions on resources and theirusage; resource contention; resource accesscontrol: priority ceiling protocol, priority inheritanceprotocol, slack based priority ceiling protocol,peremption ceiling protocol; real time memorymanagement.6. MULTI PROCESSOR SCHEDULING: Model of multiprocessor and distributed systems; schedulingalgorithms for end to end periodic tasks inhomogeneous/heterogeneous systems; predictabilityand validation of dynamic multiprocessor system.7. REAL TIME COMMUNICATION: Model of realtime communication; priority base service forswitched network; weighted round robin service;medium access control protocol; real time protocol;real time applications: air traffic control system,space launching system, etc.TEXT BOOKSJane .W. S. Liu “Real Time Systems” PearsonEducation, 2001REFERENCES1. Krishna C. M., “Real Time Systems” McGraw HillPublication, 19962. Tov Levi Shem and Agrawala Ashok K., “RealTime system Design”, McGraw Hill, 19903. Burns, Alan and Andy Welling, “Real TimeSystems and their Programming Language”,Addison Wesley, 19904. Proceedings of IEEE Special Issue on Real TimeSystems, Jan 19945. Blackman M., “The Design of Real TimeApplications”, John Wiley & Sons, 19756. Krishna C. M. and Shin K. G., “Real TimeSystems”, Tata McGraw Hill, 1997CS-451NEURAL NETWORKS LABL T P Cr0 0 2 1LIST OF EXPERIMENTS1. Demonstrate functioning of a neuron2. Implement a Hopfield neural network3. Implement back propagation network (BPN)4. Implement multi-layer perceptron (MLP)5. Implement k-means clustering6. Demonstrate unsupervised clustering capabilityusing Self Organizing Maps (SOM)7. Implement object recognition/image processing8. Demonstrate prediction ability using neuralnetworksREFERENCE BOOKS1. Haykin Simon, “Neural Networks: AComprehensive Formulation”, Addison Wesley,199843
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