8th CE SYLLABUS. in GUJ. Uni.
GUJARAT UNIVERSITY
B.E. SEM VIII (Computer Engineering)
CE801: Distributed Computing
Distributed computing:
History, Forms of computing,Monolithic,Distributed,Parallel,CooperativeStrengths and weaknesses of distributed computing, OS basics,Programs and processes,Concurrent programming
Interconnection networks
Cache hit-rate model,Cache coherency , Static and Dynamic networks , Internet mega computer-Network resources and their identifications, OLE/ COM , Distributed objects and CORBA, RPC and Rendezvous , Internet agents , Porting of applications- accessibility, scalability, security, fault tolerance
Intercrosses communication
Archetypal IPC program interface, Event synchronization, Timeouts and threading,Deadlock and timeouts, Data representation,Data encoding,Text based protocols, Request response protocols,Event and sequence diagram,Connection vs. connectionless IPC
Distributed computing paradigms
Paradigms,Message passing,Client server,Peer to peer,Message system,Remote procedure call model,Distributed objects,Object space,Mobile agent, Network services, Collaborative application (groupware),Abstraction,Tradeoffs: abstraction vs. overhead, Scalability,cross-platform
Distributed Objects
Message passing vs distributed objects,Archetypal distributed object architecture, Distributed object systems,Remote procedure calls,Java RMI architecture,Client side
Server side,Object registry, API for Java RMI,Remote interface,Server side software
Client side software, RMI vs. socket API
Advanced RMI
Client callback,Client side, Server side,Stub downloading, RMI Security manager, Instantiation of a Security manager,Java security policy file,Specifying stub downloading and a security policy file,Algorithms for building RMI application,Allowing for Stub downloading
Advanced Distributed Computing Paradigms
Message Queue system paradigm,Point to point,Publish/Subscribe,Mobile Agents, Basic architecture,Advantages, Mobile agent framework systems, Network services
Textbook:
1) Distributed Computing: Principles and Applications, M. L. Liu, Pearson/Addison-Wesley,
2) A. Taunenbaum, Distributed Systems: Principles and Paradigms
3) G. Coulouris, J. Dollimore, and T. Kindberg, Distributed Systems: Concepts and Design, Pearson Education
References:
1. M. Singhal, N. Shivaratri, Advanced Concepts in Operating Systems, TMH
CE802: Advance Computer Architecture
Introduction and review
Fundamentals of digital system and Review
Pipelining
Linear Pipeline processor: Nonlinear pipeline processor, instruction pipeline design, Mechanisms for instruction pipelining, dynamic instruction scheduling, Branch handling techniques, arithmetic pipelining design: Computer arithmetic principles, static arithmetic pipelines, multifunction arithmetic pipelines.
Storage and memory hierarchy
Register file, Virtual file, Cache memories, cache memory working principles, cache coherence issues, cache performance analysis, High bandwidth memories.
Instruction level
parallelism
Super-scalar processors, VLIW architecture
Parallel computer models and program parallelism
Classification of machines, SISD, SIMD and MIMD, Conditions of parallelism, data and resource dependencies, hardware and software parallelism, program partitioning and scheduling, grain size latency, program flow mechanism, control flow versus data flow, data flow architecture, demand driven mechanisms, comparison of flow mechanisms
Vector Processor and synchronous parallel processing
Vector instruction types, vector-access memory schemes, vector and symbolic processors, SIMD architecture and programming principles: SIMD parallel algorithms, SIMD computers and performance enhancement.
System Interconnect architecture
Network properties and routing, static interconnection networks, Dynamic interconnection networks, multiprocessor system interconnects: Hierarchical bus system, crossbar switch and multi-port memory, multistage and combining network.
Multiprocessor architecture and programming
Functional structure, Interconnection network, Parallel memory organization, Multiprocessor operating system, Exploiting concurrency for multiprocessor.
TEXT BOOK:
1. Hennessey & D.A. Patterson, “Computer architecture: A quantitative approach”, International student edition, 3rd edition, 2002, Morgan kaufmaan publisher.
2. Michael J. Flynn,” Computer Architecture: Pipelined and parallel processor design”, 1995, Jones and barlett, Boston.
3. Kai Hawang and Faye A. Briggs, “ Computer architecture and parallel processing”, International edition, 1993, TMH
Reference Book:
1. R.K. Ghose, Rajan Moona & Phalfui Gupta, “Foundation of parallel processing”; Narosa publication
2. D. Sima, T. Fountain, P. Kasuk, “ Advanced computer architecture – A design space approach”, 1997, Addison Wesley
CE803: Soft Computing and Neural Network
NEURAL NETWORKS
Supervised Learning Neural Networks – Perceptrons - Adaline – Backpropagation Mutilayer Perceptrons – Radial Basis Function Networks – Unsupervised Learning Neural Networks – Competitive Learning Networks – Kohonen Self-Organizing Networks – Learning Vector Quantization – Hebbian Learning.
FUZZY SET THEORY
Introduction to Neuro – Fuzzy and Soft Computing – Fuzzy Sets – Basic Definition and Terminology – Set-theoretic Operations – Member Function Formulation and Parameterization – Fuzzy Rules and Fuzzy Reasoning – Extension Principle and Fuzzy Relations – Fuzzy If-Then Rules – Fuzzy Reasoning – Fuzzy Inference Systems – Mamdani Fuzzy Models – Sugeno Fuzzy Models – Tsukamoto Fuzzy Models – Input Space Partitioning and Fuzzy Modeling.
GENETIC ALGORITHM:
Difference between Traditional Algorithms and GA, The basic operators, Schema theorem, convergence analysis, stochastic models, applications in search and optimization. Encoding, Fitness Function, Reproduction, Cross Over, Mutation, Convergence Theory; Applications.
ROUGH SET:
Indiscernibility Relations, Reducts, Rough Approximation. Applications.Hybrid Systems: Neuro Fuzzy Systems, Fuzzy Logic Controlled GA, Fuzzy Membership Interpretation using Rough Set theory etc.
NEURO FUZZY MODELING
Adaptive Neuro-Fuzzy Inference Systems – Architecture – Hybrid Learning Algorithm – Learning Methods that Cross-fertilize ANFIS and RBFN – Coactive Neuro Fuzzy Modeling – Framework Neuron Functions for Adaptive Networks – Neuro Fuzzy Spectrum. Neuro-Fuzzy Systems for Pattern Recognition: Image-, Speech- and Language Processing
NEURO-GENETIC INFORMATION PROCESSING FOR OPTIMIZATION:
Adaptation in Intelligent Systems , Evolving Connectionist and Fuzzy Connectionist Systems, Applications for Adaptive Systems, On-line Intelligent Systems
MACHINE LEARNING
Learning form Examples - Inductive Concept Learning - Sequence Prediction - Effect of Noise in Input. Learning by Analogy- Concept formation - Derivational Analogy. Learning by Observation and Discovery - Search for Regularity-Conceptual Clustering, Computational Learning Theory.
APPLICATIONS OF COMPUTATIONAL INTELLIGENCE
Printed Character Recognition – Inverse Kinematics Problems – Automobile Fuel Efficiency Prediction – Soft Computing for Color Recipe Prediction.
Practical: Minimum 10 experiments should be carried out according to topic covered in subject.
TEXT BOOK
• J.S.R.Jang, C.T.Sun and E.Mizutani, “Neuro-Fuzzy and Soft Computing”, PHI, 2004, Pearson Education 2004.
• Michalski, Carbonnel & Michel (Eds.): Machine Learning - An A. I. Approach, Vol-I.
REFERENCES
• Timothy J.Ross, “Fuzzy Logic with Engineering Applications”, McGraw-Hill, 1997.
• Davis E.Goldberg, “Genetic Algorithms: Search, Optimization and Machine Learning”, Addison Wesley, N.Y., 1989.
• S. Rajasekaran and G.A.V.Pai, “Neural Networks, Fuzzy Logic and Genetic Algorithms”, PHI, 2003.
• Neuro-Fuzzy Techniques for Intelligent Information Systems by Nikola Kasabov and Robert Kozma (eds), ISBN 3-7908-1187-4.
• Neural network fuzzy logic genetic algorithm synthesis and application- S. Rjaesh Karan.
CE804 Advance Computer Network
Frame Relay
Circuit switching network, Packet switching network, Frame Relay Network
Asynchronous Transfer Mode
ATM protocol architecture, ATM logical connection, ATM cell, ATM service category, ATM adaption layer
Congestion Control in network
Effect of congestion, Congestion control, Traffic management, Congestion control in packet switching network, Frame Relay Congestion control
Traffic Congestion control in ATM network
Requirement for ATM traffic & congestion control, ATM traffic related issue, Traffic management framework, Traffic control, ABR,GFR Traffic management.
Integrated & Differentiated Service
Integrated Service Architecture, Queuing discipline, Random early detection, differentiated services.
Protocol for QOS support
Resource reservation Protocol (RSVP), Multiprotocol Label Switching (MPLS), Real time transport protocol
Sensor Network
Introduction, Sensor network Architecture, MAC layer protocol in sensor Network, Routing in sensor network, Sensor network Applications
Wireless LANs and PANs
WiFi ,Bluetooth (piconets, Scatternets) ,Zigbee
Wireless WANs and MANs
Cellular Telephony (+Femtocells),Wimax ,LTE
Other Advance Topic
Mobile Internet, IPTV,IP Telephony
Practical and Term work
The practical and Term work will be based on the topics covered in the syllabus.
Minimum 10 experiments should be carried out.
TEXT BOOK:
1. High-Speed Networks and Internets: Performance and Quality of Service by William Stallings Publisher: Prentice Hall
CE805: Computer Vision
Computer vision issues
Achieving simple vision goals ,High-level and low-level capabilities,A range of representations,The role of computers,Computer vision research and applications
Image formation
Cameras,Radiometry – measuring light,Sources, shadows and shading Colour
Image models
Geometric image features,Analytical image features
Early vision: one image
Liner filters, Edge detection, Texture
Early vision: multiple images
The geometry of multiple views,Stereopsis,Affine structure from motion,Projective structure from motion
Mid level vision
Segmentation using clustering methods, fitting
High level vision
Correspondence and pose consistency, finding templates using classifiers
Applications and Topics
Application : finding in digital libraries, Application: image based rendering
Practical and Term work:
Practical and Term work should be carried out as per the above syllabus. Minimum 10 exercises should be carried out.
Textbook:
Computer Vision: A modern approach by Forsyth and Ponce, PHI publication.
References:
Computer Vision by Dana H. Ballard and Christopher M. Brown, Prentice-Hall Inc.
CE806: Algorithm Analysis & Design
Basics of Algorithms and Mathematics
What is an algorithm? Mathematics for Algorithmic, Sets , Functions and Relations, Vectors and Matrices , Linear Inequalities and Linear Equations
Analysis of Algorithm
The efficient of algorithm, average and worst case analysis, elementary operation, Asymptotic Notation, Analyzing control statement, Analyzing Algorithm using Barometer, Amortized analysis, solving recurrence Equation, Sorting Algorithm, Binary Tree Search
Greedy Algorithm
General Characteristics of greedy algorithms, Problem solving using Greedy Algorithm
- Making change problem; Graphs: Minimum Spanning trees (Kruskal’s algorithm, Prim’s algorithm); Graphs: Shortest paths; The Knapsack Problem; Job Scheduling Problem
Divide and Conquer Algorithm
The general Template derives using multiplying large Integers Problem, Problem Solving using divide and conquer algorithm - Binary Search; Sorting (Merge Sort, Quick Sort); Matrix Multiplication; Exponential
Dynamic Programming
Introduction, The Principle of Optimality, Problem Solving using Dynamic Programming – Calculating the Binomial Coefficient; Making Change Problem; Assembly Line-Scheduling; Knapsack Problem; Shortest Path; Matrix Chain Multiplication; Longest Common Subsequence, memory functions
Exploring Graphs
An introduction using graphs and games, Traversing Trees – Preconditioning; Depth First Search - Undirected Graph; Directed Graph, Breath First Search, Backtracking – The Knapsack Problem; The Eight queens problem; General Template, Brach and Bound – The Assignment Problem; The Knapsack Problem, The minmax principle
String Matching
Introduction, The naïve string matching algorithm, The Rabin-Karp algorithm, String Matching with finite automata
Introduction to NP-Completeness
The class P and NP, Polynomial reduction, NP- Completeness Problem, NP-Hard Problems
Practical and Term work:
Practical and Term work should be carried out as per the above syllabus. Minimum 10 exercises should be carried out.
Text Books:
1 Introduction to Algorithms by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest and Clifford Stein
Reference book:
1. Fundamental of Algorithms by Gills Brassard, Paul Bratley, Publication : Pentice Hall of India
2. Fundamental of Computer Algorithms by Ellis Horowitz, Sartaz sahni and sanguthevar Rajasekarm
CE807: Service Oriented Computing
Introduction
Introduction, Brief history of information technology, Distributed computing in the large, Motivations for composition, Challenges for composition, Web Services Architectures and Standards.
Basic concepts
Directory services, SOAP, WSDL, UDDI
Enterprise architectures
Integration versus interoperation, J2EE, .NET, Model Driven Architecture, Legacy systems.
Principles of Service-Oriented Computing
Use cases: Intra-enterprise and Inter-enterprise Interoperation, Application,Configuration, Dynamic Selection, Software Fault Tolerance, Grid, and,Utility Computing,Elements of Service-Oriented Architectures, RPC versus Document, Orientation, Composing Services
Description: Modeling and representation
XML primer, Conceptual modeling, Ontologies and knowledge sharing, Relevant
standards:
RDF, RDFS, and OWL, Inferencing and tools, Matchmaking
Engagement
Execution Models: Messaging, CORBA, Peer to peer computing, Jini, Grid Computing, Transactions: ACID Properties, Schedules, Locking, Distributed Transactions,Transactions over Composed Services: Architecture, Properties,Compositional Serializability,Process specification: Processes, Workflows, Business Process Management,Process Specification Language,Relevant standards: BPEL4WS, WSCI, WS-C, ebXML,Relaxed transactions,Exception handling
Collaboration
Describing collaborations, Agents, Multiagent systems, Agent communication, languages, Protocols, Commitments and contracts, Planning,Consistency maintenance, Relevant standards: FIPA, OWL-S, Economic models, Organizational models
Selection
Quality of service, Application-level trust, Reputation mechanisms, Referral systems
Engineering
Engineering composed services, Compliance, Trust, Privacy.
Synthesis
Common threads, Open problems Status and trends
Text Book:
Service-Oriented Computing: Semantics, Processes, Agents
by Munindar P. Singh and Michael N. Huhns
John Wiley & Sons, Ltd., 2005
Reference Book:
Service-Oriented Architecture: Concepts, Technology, and Design
By Thomas Erl
Publisher: Prentice Hall PTR , 2005
B.E. SEM VIII (Computer Engineering)
CE801: Distributed Computing
Distributed computing:
History, Forms of computing,Monolithic,Distributed,Parallel,CooperativeStrengths and weaknesses of distributed computing, OS basics,Programs and processes,Concurrent programming
Interconnection networks
Cache hit-rate model,Cache coherency , Static and Dynamic networks , Internet mega computer-Network resources and their identifications, OLE/ COM , Distributed objects and CORBA, RPC and Rendezvous , Internet agents , Porting of applications- accessibility, scalability, security, fault tolerance
Intercrosses communication
Archetypal IPC program interface, Event synchronization, Timeouts and threading,Deadlock and timeouts, Data representation,Data encoding,Text based protocols, Request response protocols,Event and sequence diagram,Connection vs. connectionless IPC
Distributed computing paradigms
Paradigms,Message passing,Client server,Peer to peer,Message system,Remote procedure call model,Distributed objects,Object space,Mobile agent, Network services, Collaborative application (groupware),Abstraction,Tradeoffs: abstraction vs. overhead, Scalability,cross-platform
Distributed Objects
Message passing vs distributed objects,Archetypal distributed object architecture, Distributed object systems,Remote procedure calls,Java RMI architecture,Client side
Server side,Object registry, API for Java RMI,Remote interface,Server side software
Client side software, RMI vs. socket API
Advanced RMI
Client callback,Client side, Server side,Stub downloading, RMI Security manager, Instantiation of a Security manager,Java security policy file,Specifying stub downloading and a security policy file,Algorithms for building RMI application,Allowing for Stub downloading
Advanced Distributed Computing Paradigms
Message Queue system paradigm,Point to point,Publish/Subscribe,Mobile Agents, Basic architecture,Advantages, Mobile agent framework systems, Network services
Textbook:
1) Distributed Computing: Principles and Applications, M. L. Liu, Pearson/Addison-Wesley,
2) A. Taunenbaum, Distributed Systems: Principles and Paradigms
3) G. Coulouris, J. Dollimore, and T. Kindberg, Distributed Systems: Concepts and Design, Pearson Education
References:
1. M. Singhal, N. Shivaratri, Advanced Concepts in Operating Systems, TMH
CE802: Advance Computer Architecture
Introduction and review
Fundamentals of digital system and Review
Pipelining
Linear Pipeline processor: Nonlinear pipeline processor, instruction pipeline design, Mechanisms for instruction pipelining, dynamic instruction scheduling, Branch handling techniques, arithmetic pipelining design: Computer arithmetic principles, static arithmetic pipelines, multifunction arithmetic pipelines.
Storage and memory hierarchy
Register file, Virtual file, Cache memories, cache memory working principles, cache coherence issues, cache performance analysis, High bandwidth memories.
Instruction level
parallelism
Super-scalar processors, VLIW architecture
Parallel computer models and program parallelism
Classification of machines, SISD, SIMD and MIMD, Conditions of parallelism, data and resource dependencies, hardware and software parallelism, program partitioning and scheduling, grain size latency, program flow mechanism, control flow versus data flow, data flow architecture, demand driven mechanisms, comparison of flow mechanisms
Vector Processor and synchronous parallel processing
Vector instruction types, vector-access memory schemes, vector and symbolic processors, SIMD architecture and programming principles: SIMD parallel algorithms, SIMD computers and performance enhancement.
System Interconnect architecture
Network properties and routing, static interconnection networks, Dynamic interconnection networks, multiprocessor system interconnects: Hierarchical bus system, crossbar switch and multi-port memory, multistage and combining network.
Multiprocessor architecture and programming
Functional structure, Interconnection network, Parallel memory organization, Multiprocessor operating system, Exploiting concurrency for multiprocessor.
TEXT BOOK:
1. Hennessey & D.A. Patterson, “Computer architecture: A quantitative approach”, International student edition, 3rd edition, 2002, Morgan kaufmaan publisher.
2. Michael J. Flynn,” Computer Architecture: Pipelined and parallel processor design”, 1995, Jones and barlett, Boston.
3. Kai Hawang and Faye A. Briggs, “ Computer architecture and parallel processing”, International edition, 1993, TMH
Reference Book:
1. R.K. Ghose, Rajan Moona & Phalfui Gupta, “Foundation of parallel processing”; Narosa publication
2. D. Sima, T. Fountain, P. Kasuk, “ Advanced computer architecture – A design space approach”, 1997, Addison Wesley
CE803: Soft Computing and Neural Network
NEURAL NETWORKS
Supervised Learning Neural Networks – Perceptrons - Adaline – Backpropagation Mutilayer Perceptrons – Radial Basis Function Networks – Unsupervised Learning Neural Networks – Competitive Learning Networks – Kohonen Self-Organizing Networks – Learning Vector Quantization – Hebbian Learning.
FUZZY SET THEORY
Introduction to Neuro – Fuzzy and Soft Computing – Fuzzy Sets – Basic Definition and Terminology – Set-theoretic Operations – Member Function Formulation and Parameterization – Fuzzy Rules and Fuzzy Reasoning – Extension Principle and Fuzzy Relations – Fuzzy If-Then Rules – Fuzzy Reasoning – Fuzzy Inference Systems – Mamdani Fuzzy Models – Sugeno Fuzzy Models – Tsukamoto Fuzzy Models – Input Space Partitioning and Fuzzy Modeling.
GENETIC ALGORITHM:
Difference between Traditional Algorithms and GA, The basic operators, Schema theorem, convergence analysis, stochastic models, applications in search and optimization. Encoding, Fitness Function, Reproduction, Cross Over, Mutation, Convergence Theory; Applications.
ROUGH SET:
Indiscernibility Relations, Reducts, Rough Approximation. Applications.Hybrid Systems: Neuro Fuzzy Systems, Fuzzy Logic Controlled GA, Fuzzy Membership Interpretation using Rough Set theory etc.
NEURO FUZZY MODELING
Adaptive Neuro-Fuzzy Inference Systems – Architecture – Hybrid Learning Algorithm – Learning Methods that Cross-fertilize ANFIS and RBFN – Coactive Neuro Fuzzy Modeling – Framework Neuron Functions for Adaptive Networks – Neuro Fuzzy Spectrum. Neuro-Fuzzy Systems for Pattern Recognition: Image-, Speech- and Language Processing
NEURO-GENETIC INFORMATION PROCESSING FOR OPTIMIZATION:
Adaptation in Intelligent Systems , Evolving Connectionist and Fuzzy Connectionist Systems, Applications for Adaptive Systems, On-line Intelligent Systems
MACHINE LEARNING
Learning form Examples - Inductive Concept Learning - Sequence Prediction - Effect of Noise in Input. Learning by Analogy- Concept formation - Derivational Analogy. Learning by Observation and Discovery - Search for Regularity-Conceptual Clustering, Computational Learning Theory.
APPLICATIONS OF COMPUTATIONAL INTELLIGENCE
Printed Character Recognition – Inverse Kinematics Problems – Automobile Fuel Efficiency Prediction – Soft Computing for Color Recipe Prediction.
Practical: Minimum 10 experiments should be carried out according to topic covered in subject.
TEXT BOOK
• J.S.R.Jang, C.T.Sun and E.Mizutani, “Neuro-Fuzzy and Soft Computing”, PHI, 2004, Pearson Education 2004.
• Michalski, Carbonnel & Michel (Eds.): Machine Learning - An A. I. Approach, Vol-I.
REFERENCES
• Timothy J.Ross, “Fuzzy Logic with Engineering Applications”, McGraw-Hill, 1997.
• Davis E.Goldberg, “Genetic Algorithms: Search, Optimization and Machine Learning”, Addison Wesley, N.Y., 1989.
• S. Rajasekaran and G.A.V.Pai, “Neural Networks, Fuzzy Logic and Genetic Algorithms”, PHI, 2003.
• Neuro-Fuzzy Techniques for Intelligent Information Systems by Nikola Kasabov and Robert Kozma (eds), ISBN 3-7908-1187-4.
• Neural network fuzzy logic genetic algorithm synthesis and application- S. Rjaesh Karan.
CE804 Advance Computer Network
Frame Relay
Circuit switching network, Packet switching network, Frame Relay Network
Asynchronous Transfer Mode
ATM protocol architecture, ATM logical connection, ATM cell, ATM service category, ATM adaption layer
Congestion Control in network
Effect of congestion, Congestion control, Traffic management, Congestion control in packet switching network, Frame Relay Congestion control
Traffic Congestion control in ATM network
Requirement for ATM traffic & congestion control, ATM traffic related issue, Traffic management framework, Traffic control, ABR,GFR Traffic management.
Integrated & Differentiated Service
Integrated Service Architecture, Queuing discipline, Random early detection, differentiated services.
Protocol for QOS support
Resource reservation Protocol (RSVP), Multiprotocol Label Switching (MPLS), Real time transport protocol
Sensor Network
Introduction, Sensor network Architecture, MAC layer protocol in sensor Network, Routing in sensor network, Sensor network Applications
Wireless LANs and PANs
WiFi ,Bluetooth (piconets, Scatternets) ,Zigbee
Wireless WANs and MANs
Cellular Telephony (+Femtocells),Wimax ,LTE
Other Advance Topic
Mobile Internet, IPTV,IP Telephony
Practical and Term work
The practical and Term work will be based on the topics covered in the syllabus.
Minimum 10 experiments should be carried out.
TEXT BOOK:
1. High-Speed Networks and Internets: Performance and Quality of Service by William Stallings Publisher: Prentice Hall
CE805: Computer Vision
Computer vision issues
Achieving simple vision goals ,High-level and low-level capabilities,A range of representations,The role of computers,Computer vision research and applications
Image formation
Cameras,Radiometry – measuring light,Sources, shadows and shading Colour
Image models
Geometric image features,Analytical image features
Early vision: one image
Liner filters, Edge detection, Texture
Early vision: multiple images
The geometry of multiple views,Stereopsis,Affine structure from motion,Projective structure from motion
Mid level vision
Segmentation using clustering methods, fitting
High level vision
Correspondence and pose consistency, finding templates using classifiers
Applications and Topics
Application : finding in digital libraries, Application: image based rendering
Practical and Term work:
Practical and Term work should be carried out as per the above syllabus. Minimum 10 exercises should be carried out.
Textbook:
Computer Vision: A modern approach by Forsyth and Ponce, PHI publication.
References:
Computer Vision by Dana H. Ballard and Christopher M. Brown, Prentice-Hall Inc.
CE806: Algorithm Analysis & Design
Basics of Algorithms and Mathematics
What is an algorithm? Mathematics for Algorithmic, Sets , Functions and Relations, Vectors and Matrices , Linear Inequalities and Linear Equations
Analysis of Algorithm
The efficient of algorithm, average and worst case analysis, elementary operation, Asymptotic Notation, Analyzing control statement, Analyzing Algorithm using Barometer, Amortized analysis, solving recurrence Equation, Sorting Algorithm, Binary Tree Search
Greedy Algorithm
General Characteristics of greedy algorithms, Problem solving using Greedy Algorithm
- Making change problem; Graphs: Minimum Spanning trees (Kruskal’s algorithm, Prim’s algorithm); Graphs: Shortest paths; The Knapsack Problem; Job Scheduling Problem
Divide and Conquer Algorithm
The general Template derives using multiplying large Integers Problem, Problem Solving using divide and conquer algorithm - Binary Search; Sorting (Merge Sort, Quick Sort); Matrix Multiplication; Exponential
Dynamic Programming
Introduction, The Principle of Optimality, Problem Solving using Dynamic Programming – Calculating the Binomial Coefficient; Making Change Problem; Assembly Line-Scheduling; Knapsack Problem; Shortest Path; Matrix Chain Multiplication; Longest Common Subsequence, memory functions
Exploring Graphs
An introduction using graphs and games, Traversing Trees – Preconditioning; Depth First Search - Undirected Graph; Directed Graph, Breath First Search, Backtracking – The Knapsack Problem; The Eight queens problem; General Template, Brach and Bound – The Assignment Problem; The Knapsack Problem, The minmax principle
String Matching
Introduction, The naïve string matching algorithm, The Rabin-Karp algorithm, String Matching with finite automata
Introduction to NP-Completeness
The class P and NP, Polynomial reduction, NP- Completeness Problem, NP-Hard Problems
Practical and Term work:
Practical and Term work should be carried out as per the above syllabus. Minimum 10 exercises should be carried out.
Text Books:
1 Introduction to Algorithms by Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest and Clifford Stein
Reference book:
1. Fundamental of Algorithms by Gills Brassard, Paul Bratley, Publication : Pentice Hall of India
2. Fundamental of Computer Algorithms by Ellis Horowitz, Sartaz sahni and sanguthevar Rajasekarm
CE807: Service Oriented Computing
Introduction
Introduction, Brief history of information technology, Distributed computing in the large, Motivations for composition, Challenges for composition, Web Services Architectures and Standards.
Basic concepts
Directory services, SOAP, WSDL, UDDI
Enterprise architectures
Integration versus interoperation, J2EE, .NET, Model Driven Architecture, Legacy systems.
Principles of Service-Oriented Computing
Use cases: Intra-enterprise and Inter-enterprise Interoperation, Application,Configuration, Dynamic Selection, Software Fault Tolerance, Grid, and,Utility Computing,Elements of Service-Oriented Architectures, RPC versus Document, Orientation, Composing Services
Description: Modeling and representation
XML primer, Conceptual modeling, Ontologies and knowledge sharing, Relevant
standards:
RDF, RDFS, and OWL, Inferencing and tools, Matchmaking
Engagement
Execution Models: Messaging, CORBA, Peer to peer computing, Jini, Grid Computing, Transactions: ACID Properties, Schedules, Locking, Distributed Transactions,Transactions over Composed Services: Architecture, Properties,Compositional Serializability,Process specification: Processes, Workflows, Business Process Management,Process Specification Language,Relevant standards: BPEL4WS, WSCI, WS-C, ebXML,Relaxed transactions,Exception handling
Collaboration
Describing collaborations, Agents, Multiagent systems, Agent communication, languages, Protocols, Commitments and contracts, Planning,Consistency maintenance, Relevant standards: FIPA, OWL-S, Economic models, Organizational models
Selection
Quality of service, Application-level trust, Reputation mechanisms, Referral systems
Engineering
Engineering composed services, Compliance, Trust, Privacy.
Synthesis
Common threads, Open problems Status and trends
Text Book:
Service-Oriented Computing: Semantics, Processes, Agents
by Munindar P. Singh and Michael N. Huhns
John Wiley & Sons, Ltd., 2005
Reference Book:
Service-Oriented Architecture: Concepts, Technology, and Design
By Thomas Erl
Publisher: Prentice Hall PTR , 2005
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