Computer Engineering Semester 7

Digital Signal Processing |

Discrete Time Signal 1.1 Introduction to Digital Signal Processing, Discrete Time Signals, Sampling and Reconstruction, Standard DT Signals, Concept of Digital Frequency, Representation of DT signal using Standard DT Signals, Signal Manipulations(shifting, addition, subtraction, multiplication), Classification of Signals, Linear Convolution formulation(without mathematical proof), Circular Convolution formulation(without mathematical proof), Matrix Representation of Circular Convolution, Linear by Circular Convolution. Auto and Cross Correlation formula evaluation, 02 Discrete Time System 2.1 Introduction to Discrete Time System, Classification of DT Systems (Linear/Non Linear, Causal/Non Causal, Time Invariant/Time Variant Systems, Stable/ Unstable), BIBO Time Domain Stability Criteria. LTI system, Concept of Impulse Response and Step Response. 2.2 Concept of IIR System and FIR System, Output of IIR and FIR DT system using Time Domain Linear Convolution formula Method. 03 Discrete Fourier Transform 04 Fast Fourier Transform 06 DSP Processors and Application of DSP |

Term Work: · Term work shall consist of minimum 08 assignments and course project. · Journal must include at least 1 assignment on each module and two quiz. · The final certification and acceptance of term work ensures that satisfactory performance of laboratory work and minimum passing marks in term work. The distribution of marks for term work shall be as follows: · Laboratory work (experiments): …………..……….. (15) Marks. · Assignment:……………………………………..…… (05) Marks. · Attendance (Theory+ Practical)……………………. (05) Marks TOTAL: ……………………………………………………. (25) Marks. |

Text Books : 1. Ashok Ambardar, ‘Digital Signal Processing’, Cengage Learning, 2007, ISBN : 978-81-315-0179-5. 2. Emmanuel C. Ifeachor, Barrie W. Jervis, “Digital Signal Processing: A Practical Approach”, Pearson Education ISBN 0-201-59619- 9 3. S. Salivahanan, A. Vallavaraj, C. Gnanapriya, ‘Digital Signal Processing’ TataMcgraw Hill Publication First edition (2010). ISBN 978-0-07-066924-6. 4. Avtar Signh, S.Srinivasan,”Digital Signal Processing’, Thomson Brooks/Cole, ISBN : 981-243-254-4 |

Cryptography and System Security Computer Engineering Semester 7 |

Introduction 1.1 Security Attacks, Security Goals, Computer criminals, Methods of defense, Security Services, Security Mechanisms 02 Basics of Cryptography 2.1 Symmetric Cipher Model, Substitution Techniques, Transportation Techniques, Other Cipher Properties- Confusion, Diffusion, Block and Stream Ciphers. 03 Secret Key Cryptography 04 Public Key Cryptography 05 Cryptographic Hash Functions 06 Authentication Applications 08 8.1 IP Security |

Term Work: Term work should consist of at least 10experiments, 2 assignments based on above theory syllabus. The final certification and acceptance of term work ensures that satisfactory performance of laboratory work and minimum passing marks in term work. The distribution of marks for term work shall be as follows: · Laboratory work (experiments): …………..……….. (15) Marks. · Assignment:……………………………………..…… (05) Marks. · Attendance (Theory+ Practical)……………………. (05) Marks TOTAL: ……………………………………………………. (25) Marks. |

Theory Examination: 1. Question paper will comprise of total 6 questions, each of 20 Marks. 2. Only 4 questions need to be solved. 3. Question 1 will be compulsory and based on maximum part of the syllabus. 4. Remaining questions will be mixed in nature (for example suppose Q.2 has part (a) from module 3 then part (b) will be from any module other than module 3) In question paper, weightage of each module will be proportional to number of respective lecture hours as mentioned in the syllabus. |

Text Books: 1. Cryptography and Network Security: Principles and Practice 5th edition, William Stallings, Pearson. 2. Network Security and Cryptography 2nd edition, Bernard Menezes, Cengage Learning. 3. Cryptography and Network, 2nd edition, Behrouz A Fourouzan, Debdeep Mukhopadhyay, TMH. |

Artificial Intelligence Computer Engineering Semester 7 |

Introduction to Artificial Intelligence 1.1 Introduction , History of Artificial Intelligence, Intelligent Systems: Categorization of Intelligent System, Components of AI Program, Foundations of AI, Sub-areas of AI, Applications of AI, Current trends in AI. 02 Intelligent Agents 2.1 Agents and Environments, The concept of rationality, The nature of environment, The structure of Agents, Types of Agents, Learning Agent. 03 Problem solving 05 Planning and Learning 06 Applications |

Term Work: The distribution of marks for term work shall be as follows: · Laboratory work (experiments/case studies): ………….. (15) Marks. · Assignment:………..………………………………… (05) Marks. · Attendance ………………………………………. (05) Marks TOTAL: ……………………………………………………. (25) Marks. |

Text Books: 1. Stuart J. Russell and Peter Norvig, “Artificial Intelligence A Modern Approach “Second Edition” Pearson Education. 2. Saroj Kaushik “Artificial Intelligence” , Cengage Learning. 3. George F Luger “Artificial Intelligence” Low Price Edition , Pearson Education., Fourth edition. |

Advanced Algorithms |

Introduction 1.1 Asymptotic notations Big O, Big Q,Big W,o ,w notations ,Proofs of master theorem, applying theorem to solve problems 02 Advanced Data Structures 2.1 Red-Black Trees: properties of red-black trees , Insertions , Deletions 2.2 B-Trees and its operations 2.3 Binomial Heaps: Binomial trees and binomial heaps, Operation on Binomial heaps 03 Dynamic Programing 04 Graph algorithms 05 Maximum Flow 06 Linear Programing 07 Computational Ggeometry |

Term Work: Term work should consist of at least 6 experiments, 2 assignments based on above theory syllabus. The final certification and acceptance of term work ensures that satisfactory performance of laboratory work and minimum passing marks in term work. The distribution of marks for term work shall be as follows: · Laboratory work (experiments): …………..……….. (15) Marks. · Assignment:……………………………………..…… (05) Marks. · Attendance (Theory+ Practical)……………………. (05) Marks TOTAL: ……………………………………………………. (25) Marks |

Text Books: 1. T.H. Coreman , C.E. Leiserson, R.L. Rivest, and C. Stein, “Introduction to algorithms”,2nd edition , PHI publication 2005 2. Ellis Horowitz , Sartaj Sahni , S. Rajsekaran. “Fundamentals of computer algorithms” University press |

Image Processing |

Digital Image and Video Fundamentals 1.1 Introduction to Digital Image, Digital Image Processing System, Sampling and Quantization, Representation of Digital Image, Connectivity, Image File Formats : BMP, TIFF and JPEG. Colour Models (RGB, HSI, YUV) Introduction to Digital Video, Chroma Sub-sampling, CCIR standards for Digital Video 02 Image Enhancement 2.1 Gray Level Transformations, Zero Memory Point Operations, Histogram Processing, Neighbourhood Processing, Spatial Filtering, Smoothing and Sharpening Filters. Homomorphic Filtering 03 Image Segmentation and Representation 04 Image Transform 05 Image Compression |

Term Work: Term work should consist of at least 08 experiments. Journal must include at least 1 assignment on each module and two quiz. The final certification and acceptance of term work ensures that satisfactory performance of laboratory work and minimum passing marks in term work. The distribution of marks for term work shall be as follows: · Laboratory work (experiments): …………..……….. (15) Marks. · Assignment:……………………………………..…… (05) Marks. · Attendance (Theory+ Practical)……………………. (05) Marks TOTAL: ……………………………………………………. (25) Marks. |

Text Books : 1. Rafel C. Gonzalez and Richard E. Woods, ‘Digital Image Processing’, Pearson Education Asia, Third Edition, 2009, 2. S. Jayaraman, E.Esakkirajan and T.Veerkumar, “Digital Image Processing” TataMcGraw Hill Education Private Ltd, 2009, 3. Anil K. Jain, “Fundamentals and Digital Image Processing”, Prentice Hall of India Private Ltd, Third Edition 4. S. Sridhar, “Digital Image Processing”, Oxford University Press, Second Edition, 2012. 5. Robert Haralick and Linda Shapiro, “Computer and Robot Vision”, Vol I, II, Addison Wesley, 1993. |

Software Architecture |

Basic Concepts 1.1 Concepts of Software Architecture 1.2 Models. 1.3 Processes. 1.4 Stakeholders 03 02 Designing Architectures 2.1 The Design Process. 2.2 Architectural Conception. 2.3 Refined Experience in Action: Styles and Architectural Patterns. 2.4 Architectural Conception in Absence of Experience. 03 Connectors 3.1 Connectors in Action: A Motivating Example. 3.2 Connector Foundations. 3.3 Connector Roles. 3.4 Connector Types and Their Variation Dimensions. 3.5 Example Connectors. 04 Modeling 05 Analysis 07 Conventional Architectural styles 08 Applied Architectures and Styles 09 Designing for Non-Functional Properties 10 Domain-Specific Software Engineering |

Term Work: The distribution of marks for term work shall be as follows: · Laboratory work (experiments):…………………….. (20) Marks. · Attendence:…….……………………………………… (05) Marks. TOTAL: ……………………………………………………. (25) Marks. |

Text Books: 1. “Software Architecture: Foundations, Theory, and Practice” by Richard N. Taylor, Nenad Medvidovic, Eric Dashofy, ISBN: 978-0-470-16774-8 2. M. Shaw: Software Architecture Perspectives on an Emerging Discipline, Prentice-Hall. 3. Len Bass, Paul Clements, Rick Kazman: Software Architecture in Practice, Pearson. |

Soft Computing Computer Engineering Semester 7 |

Introduction to Soft Computing 1.1 Soft computing Constituents, Characteristics of Neuro Computing and Soft Computing, Difference between Hard Computing and Soft Computing, Concepts of Learning and Adaptation.02 Neural Networks 2.1 Basics of Neural Networks: Introduction to Neural Networks, Biological Neural Networks, McCulloch Pitt model, 2.2 Supervised Learning algorithms: Perceptron (Single Layer, Multi layer), Linear separability, Delta learning rule, Back Propagation algorithm, 2.3 Un-Supervised Learning algorithms: Hebbian Learning, Winner take all, Self Organizing Maps, Learning Vector Quantization. Fuzzy Set Theory 3.1 Classical Sets and Fuzzy Sets, Classical Relations and Fuzzy Relations, Properties of membership function, Fuzzy extension principle, Fuzzy Systems- fuzzification, defuzzification and fuzzy controllers. 04 Hybrid system 05 Introduction to Optimization Techniques 06 Genetic Algorithms and its applications: |

Term Work: The distribution of marks for term work shall be as follows: · Laboratory work (experiments/case studies): ………….. (15) Marks. · Assignments:…….…………………………………… (05) Marks. · Attendance ………………………………………. (05) Marks TOTAL: ……………………………………………………. (25) Marks. |

Text Books: 1. Timothy J.Ross “Fuzzy Logic With Engineering Applications” Wiley. 2. S.N.Sivanandam, S.N.Deepa “Principles of Soft Computing” Second Edition, Wiley Publication. 3. S.Rajasekaran and G.A.Vijayalakshmi Pai “Neural Networks, Fuzzy Logic and Genetic Algorithms” PHI Learning. 4. J.-S.R.Jang “Neuro-Fuzzy and Soft Computing” PHI 2003. 5. Jacek.M.Zurada “Introduction to Artificial Neural Sytems” Jaico Publishing House. |

Enterprise Resource Planning and Supply ChainManagement (ERP & SCM) |

Introduction 1.1 What is an Enterprize, Introduction to ERP, Need for ERP, Structure of ERP, Scope and Benefits, Typical business processes.02 ERP and Technology 2.1 ERP and related technologies, Business Intelligence, E-business and E-commerce, Business Process Reengineering, 03 ERP and Implementation 04 ERP Business Modules 05 Extended ERP Supply Chain Management (SCM) 08 Mathematical modelling for SCM 09 Agile Supply Chain 10 Cases of Supply Chain |

Term Work: The distribution of marks for term work shall be as follows: · Mini project:……………………………….………… (20) Marks. · Attendance …………………………………………. (05) Marks TOTAL: ……………………………………………………. (25) Marks. |

Text Books: 1. Enterprise Resource Planning : concepts & practices, by V.K. Garg & N.K. Venkatakrishnan ; PHI. 2. Supply Chain Management Theories & Practices: R. P. Mohanty, S. G. Deshmukh, – Dreamtech Press. 3. ERP Demystified: II Edition, by Alexis Leon,McGraw Hill . 4. Enterprise wide resource planning: Theory & practice: by Rahul Altekar,PHI. |

Computer Simulation and Modeling |

Introduction to Simulation. Simulation Examples. General Principles 15 02 Statistical Models in simulation. Queuing Models03 Random Number Generation. Testing random numbers (Refer to Third edition) Random Variate Generation: Inverse transform technique, Direct Transformation for the Normal Distribution, Convolution Method, Acceptance-Rejection Technique (only Poisson Distribution).Analysis of simulation data : Input Modeling ,Verification, Calibration and Validation of Simulation , Models , Estimation of absolute performance. 05 Application : Case study on 1. Processor and Memory simulation |

Text Books: Discrete Event System Simulation; Third Edition, Jerry Banks, John Carson, Barry Nelson, and David M. Nicol, Prentice-Hall Discrete Event System Simulation; Fifth Edition, Jerry Banks, John Carson, Barry Nelson, and David M. Nicol, Prentice-Hall |

Term work: Laboratory work: 10 marks Mini Simulation Project presentation: 10 marks Attendance : 5 marks |

Network threats and attacks Laboratory |

1.1 Title: Study the use of network reconnaissance tools like WHOIS, dig, traceroute, nslookup to gather information about networks and domain registrars. Objective: Objective of this module to how to gather information about the networks by using different n/w reconnaissance tools. Scope: Network analysis using network based tools Technology: Networking 02 2.1 Title: Study of packet sniffer tools like wireshark, ethereal, tcpdump etc. You should be able to use the tools to do the following 1. Observer performance in promiscuous as well as non-promiscous mode. 2. Show that packets can be traced based on different filters. Objective: Objective of this module is to observer the performanance in promiscuous & non-promiscous mode & to find the packets based on different filters. Scope: Packet grapping, message and protocol analysis Technology: Networking 03 3.1 Title: Download and install nmap. Use it with different options to scan open ports, perform OS fingerprinting, do a ping scan, tcp port scan, udp port scan, etc. Objective: objective of this module to learn nmap installation & use this to scan different ports. Scope: used for ip spoofing and port scanning Technology: Networking4.1 Title: Detect ARP spoofing using open source tool ARPWATCH. Objective: Objective of the module to find ARP spoofing using open source. Scope: Ip spoofing using arp packaging tool Technology: Networking 05 5.1 Title: Use the Nessus tool to scan the network for vulnerabilities. Objective: Objective of the module is scan system and network analysis. Scope: It used for system analysis, security and process analysis Technology: Networking 06 6.1 Title: Implement a code to simulate buffer overflow attack. Objective: Objective of the module Is to check buffer overflow in an NS2 environment Scope: It uses to analyse memory overflow attack Technology: Networking 07 7.1 Title: Set up IPSEC under LINUX Objective: Objective of the module for implementing security vulnerabilities Scope: to study different ipsec tools. Technology: Networking 08 8.1 Title: Install IDS (e.g. SNORT) and study the logs. Objective: Simulate intrusion detection system using tools such as snort Scope: It is used for intrusion detection system vulnerability scans Technology: Networking 9.1 Title: Use of iptables in linux to create firewalls. Objective: To study how to create and destroy firewall security parameters. Scope: system security and network security Technology: Networking 10 10.1 Title: Mini project Objective: To implement Networking concepts Scope: To understand Network & system tools Technology: Networking |

Term Work: The distribution of marks for term work shall be as follows: · Lab Assignments:……………………………………………….. (10) · Mini project:……………………………….………… (10) Marks. · Attendance …………………………………………. (05) Marks TOTAL: ……………………………………………………. (25) Marks |

## No comments yet.