Fourth Year Syllabus Department of Computer Science and Engineering

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Fourth Year Syllabus Department of Computer Science and Engineering

Four Year B.Sc. Honours Course
Effective from the Session: 2017–2018

 

First Year Syllabus Department of Computer Science and Engineering

 

  • Course Title : Artificial Intelligence

Overview of AI, AI programming language: Prolog, Environment Types, Agent Types, Agent Model, Reactive Agents, Problem solving and searching: 8-puzzle problem, N-queen problem, general search, Review of Uninformed Search Strategies: breadth first search, uniform cost search, depth-first search, iterative deepening, bidirectional search; Informed search algorithms: best-first search, A* search, Heuristic searching, Memory Bounded Search (e.g. IDA*); Local Searches: Hill Climbing, Simulated Annealing, Constraint Satisfaction Problems. Genetic Algorithm. Motion planning: motion planning search, configuration, action and obstacle, Road map, Game Theory: motivation, minmax search, resource limits and heuristic evaluation, α-β pruning, stochastic games, partially observable games, Perceptron: Neurons – Biological and Artificial, Perceptron Learning, Linear Separability, Multi-Layer Neural Networks, Backpropagation, Variations on Backprop, Cross Entropy, Weight Decay, Momentum, Machine Learning: Supervised Learning, Reinforcement Learning, General concepts of Knowledge, Knowledge representation, frame problem, representing time, events and actions, Logic in general—models and entailment, Propositional (Boolean) logic, Equivalence, validity, satisfiability, Inference rules and theorem proving, forward chaining, backward chaining, resolution, First Order Logic: Universal and Existential Quantifiers, Keeping Track of Change, Inference in first order logic Planning.

  • Course Title : Artificial Intelligence Lab

Objectives: Laboratory assignments will be based on the Course CSE 540201. Lab assignments include basic AI technologies and algorithms using non procedural programming languages, e.g., LISP and/or PROLOG.

  • Course Title : Compiler Design

Introduction to compiler: Compiler, Analysis of the source Program, the phases of compiler, of the compiler, compiler construction tools.

A simple one pass compiler: syntax definition, CFG, parse tree, ambiguity, associativity of operators, lexical analysis.

Lexical analysis: the role of the lexical analyzer, input buffering, specification tokens, finite automaton, Thompson’s construction, conversion of regular expression to DFA.

Basic parsing technique: Parser Bottom-up parsing, operator precedence parsing, operator precedence grammar, Top down parsing, Predictive parsing, LL1 grammar, LR parser (SLR, LALR).

Intermediate code generation: Intermediate languages, three address code.

Code generation: issues in the design of a code generator, target machine, basic block flow graph, code generator algorithm, DAG, peephole optimization.

Code optimization: Function preserving optimization, optimization of basic block loop optimization.

Error detection: reporting errors, Sources of error, syntactic error, semantic error, dynamic error, plan of error diction.

  • Course Title : Compiler Design Lab

Laboratory classes will be based on the Course CSE 540203.
Lex specification to recognize the following verb: is, am, are ,were, was, be, being,been,do,does,did,will,would,should,can,could,has,have,had,go. Lex specification to recognize the following words as different parts of speech: is, am, are,were,go,very,simply,quickly, gently,to,from,behind,between,if,then. Lex specification to recognize different keyword. Lex specification to recognize the identifier. Lex specification to recognize real numbers. Lex specification to recognize integer. Lex specification to recognize float. Lex specification to recognize for the positive and negative integer and float number. Lex specification to recognize different punctuation symbol. Lex specification to recognize digit. Lex program to eat up comments. Lex program to find out user name. Lex program to recognize different types of operator. Checking the validity of an arithmetic expression using CFG. Converting Regular Grammar into Regular expression. Parsing any string using a CFG

  • Course Title : Computer Graphics

Graphics Input, storage, Output and Communications: Graphics input, storage, Communication Devices, Common Display devices, Raster Scan CRT.

Scan Conversion: Scan converting a Point, Line, Circle, Ellipse, Arcs, Rectangle, Region filling, Side Effects of Scan Conversion.

Two-dimensional and three-dimensional Graphics Transformation: Geometric Transformations, Co-ordinate Transformations, Composite Transformations, and Instance Transformation.

Two-dimensional and three-dimensional Viewing and Clipping: Viewing Transformations, Clipping Algorithms.

Mathematics of Projection: Perspective projection, Parallel projection.
Geometric representations: Wire frame model, Curve Design, Interpolation and Approximation.

Hidden Surfaces: Depth comparisons, Z-Buffer algorithm, The Painter’s algorithm, Scan line algorithm.

Color and Shading models: Light and color, the phong model, Interpolative shading methods, texture.

  • Course Title : Computer Graphics Lab

Laboratory classes will be designed based on CSE 540205 course.
Scan Convention Lines, Scan Converting Circles, Scan Converting Ellipses, Filling Rectangles, Filling Polygons, Filling Ellipse Arcs, Pattern Filling, Clipping Lines, Clipping Circles and Ellipses, Clipping Polygons 2D Transformation, the window to View port Transformation
Computer Graphics Programming: Open GL.

  • Course Title : E-Commerce and Web Engineering

Introduction to e-commerce: E-commerce Business Models and Concepts , E-Commerce Payment Systems, E-Commerce Marketing Techniques, E-Commerce

Applications: Business-to-Consumer (B2C), Consumer-to-Consumer (C2C), Business-to-Business( B2B), Digital Government, Vision and mission of e-Government Web Security.

Introduction to Web Engineering : Web Browser and Web Server, Google, Basic

Concepts of Google products: Search, Maps, Translate, Chrome, YouTube, Android Phones, Gmail, Google Allo, Google Duo, Google+, Contacts, Calendar, Drive, Docs, AdWords, AdSense, Analytics, Google Classroom. Basic concepts of Google Algorithms: Hummingbird, Panda, Pigeon, Pirate and Penguin, etc. Basic concepts of SEO: on-page SEO, off-page SEO.

HTML and HTML5: HTML tag syntax, Basic HTML tags: !DOCTYPE, Title , Meta tags, Heading tags, Link, API, Image, Table, List, Audio, Video, iframe, Form and Form elements, Text Formatting tags.

CSS and CSS3: Basic concepts of CSS, CSS syntax, CSS Colors, CSS Box Model,

Java Scripts: Basic Java Scripts variable, array, object, functions.

PHP and MySQL: PHP programming basics: variables, array, decisions making, looping, function. PHP scripts to inputs in forms. PHP Connect to MySQL, MySQL query and functions, PHP Queries: Create Database, Create Tables, Insert Data, Select Data, Update Data, Delete Data in MySQL, using PHP Forms to manipulate data in the database, Data Validation, Session, Security.

  • Course Title : E-Commerce and Web Engineering Lab

Introduction:
Introduction to CPanel, Introduction to WHM, SSL, DNS: Primary DNS server and Secondary DNS server, Domain registration and Hosting.

HTML:
1. HTML editor, HTML Layouts,
2. Designing a simple HTML Document to show an article (using html, body head/title, meta content tags, different HTML tags to format Body contents).
3. Text alignment in table, introduction to form elements (textbox, checkbox, radio, submit, password, color, date, date time-local, email, month, number, range, search, tel, time, url, week, etc.), input restrictions and designing simple feedback/contact forms.

CSS and CSS3:
1. CSS website layout and responsive layout.
2. Using CSS to apply formatting text, forms, tables and link styles.

Java Scripts:
3. Use Java Scripts to create web pages containing custom welcome message (Date-time).
4. Use different control statements in Java Scripts to execute simple mathematical expressions (if-else, Switch-case, for, while, do-while).
5. Java Scripts form validation.

PHP and MySQL:
6. Installing Apache (XAMPP), PHP 4/5 and integrating into windows platform, creating PHP documents with simple tags, installing My-SQL and connection between PHP and My-SQL.
7. Inserting data into My-SQL database using PHP forms.
8. PHP form validation.

Project: Design and develop a Complete Dynamic website with HTML, PHP and My-SQL having forms and also a flexible navigation menu which has links to all available section on the site.

  • Course Title : Network and Information Security

Fundamentals on information system security; Remote access technologies and vulnerabilities; accessibility; security for communication protocols; security for operating systems and mobile programs; security for electronic commerce, passwords and offline attacks; AAA, cryptography; network security applications: authentication, e-mail, IP and web; system security: intruders, malicious software and firewalls; PKI, smart cards, secure multipurpose internet mail extensions; security models; wireless security, sandboxing, router security strategies; security standards: data encryption standard (DES), RSA, digital signature algorithm (DSA), SHA, secure sockets layer(SSL), CBC, IPSec, AES and SET; denial of service (DOS) and distributed DOS attacks; steganography; implementing VPN; Security policy and management; network security assessment.

  • Course Title : Network and Information Security Lab

(As per theory course)

  • Course Title : Information System Management

Information systems management: importance of information systems (IS) management, key trends that impacts IS Management, changes in organizational environment, changes in technology environments, IS organizational models, IS management’s leadership role, New Roles of IT, Cox Model for IT management, Roger Woolfe’s Federal Model for outsourcing, CIO roles in leading, governing, investing and managing, strategic uses of IT in B2E, B2C, B2B, G2P, IS planning, IS planning paradox, differences between strategic, tactical and operational planning, today’s sense and response strategy, different planning techniques including stages of growth, critical success factors, competitive forces model, value chain analysis, internet value matrix, linkage analysis planning and scenario planning;

Managing essential technologies: attributes of distributed systems, different types of distributed systems including host-based hierarchy, decentralized standalone systems, peer-to-peer system, hybrid enterprise wide systems, client-server systems, internet based computing and web services, Four levels of IT infrastructure, managing telecommunications, changes of infrastructure in telecommunications, transformation of telecommunication industries, wireless technology, managing information resources, managing data, giving shape to corporate data, enterprise resource planning, managing information resources, types of information, data warehouses, document management, content management, managing operations, outsourcing IS functions, information security, business continuity planning;

Managing system development: foundation of system development, structured development, fourth generation language, software prototyping, computer-aided software engineering, object oriented development, ERP systems integration, middleware inter-organizational system development, project management, key issues of IS system management, designing motivational works, rethinking maintenance works, improving legacy systems, measuring benefits of IS system as investment;
Systems for supporting knowledge work: supporting decision-making, decision support systems, data mining, executive information systems, expert systems, real customer relationship management, real-time enterprise management, managing different types collaboration, groupware, virtual workforce, virtual organizations, knowledge management, intellectual capital issues, computer ethics and legal jurisdiction, information privacy, online contracting;

Acquisition of hardware, software, networks, and services: request for proposal, acquisition methods (buy, rent, or lease) of software acquisition and analysis of alternatives among in-house development, outsourcing, purchasing and renting;

People and technology: new work environment, organizing principles including self-organizing rather than designed, processes rather than functions, communities rather than groups, virtual rather than physical, learning organization, Internet mindset, value of role of networks, rules of networks, understanding users, executives understanding of IT, Technology camel.

  • Course Title : Project/Industry Attachment

  • Course Title : Simulation and Modeling

Systems– System environment and System components; System models and Simulation – types of System model and simulation – Discrete and Continues, Static and Dynamic, Deterministic and Stochastic; Discrete Event driven simulation – Components and Organization, Event Scheduling/ Time Advance approach and Process Interaction approach, Event lists and List processing. Basics of Parallel and Distributed Simulation; Simulation Languages and Packages – Process approach to simulation, application oriented and general purpose simulation language and software: GPSS, SSF API for JAVA and C++, Arena, Extend, SIMUL8 etc. Probability and Statistical concepts in simulation – Random variable and its probability distributions, Stochastic process – e.g. Poisson process, Non stationary Poisson process, Compound Poisson process and their properties. Basics of Estimation, Hypothesis tests: Confidence Intervals and t-distribution. Queuing Models – Queuing Systems, Queuing behavior (e.g. balk, renege and jockey) and Queuing disciplines, Arrival process, Inter-arrival time distributions and Service time distributions. Long run measures of performance, Little’s formula, Analysis of different Single-server and Multi-Server queuing systems, Queuing networks and their analysis, Jackson’s theorem; Inverse transformation technique for generating random variables, other techniques: Acceptance–Rejection, Special properties, Convolution etc. Random Number generation: Linear Congruent method, composite generators, Random number streams; Testing for random numbers – frequency test and test for autocorrelation; Input modeling: identifying input model with data – Histograms, Q-Q plots, selecting the family of distribution, parameter estimation and Goodness-of-fit tests; selecting input model without data, multivariate and time-series input models, Models of arrival processes. Verification and Validation of simulation models – face validity, validation of model assumptions, input-out transformation and input output validation using historical input data. Output data analysis – types of simulation with respect to output analysis, stochastic nature of output data, measure of performance and their estimators, output analysis for terminating the simulation and for steady state simulations. Techniques for comparison of alternative system design through simulation. Simulation and queuing models of computer systems: CPU, memory simulation; Traffic modeling and simulation of computer networks and network protocols, using queuing network analysis.

  • Course Title : Simulation and Modeling Lab

(As per theory course)

  • Course Title : Parallel and Distributed Systems

Parallel Processing: Parallel Computer Models: The state of computing, Multiprocessors and Multicomputers, Multivector and SIMD Computers, PRAM and VLSI Models; Program and Network Properties: Conditions of Parallelism, Program Partitioning and Scheduling, Program Flow Mechanisms, System Interconnect Architecture; Processors and Memory Hierarchy: Advanced Processor Technology, Superscalar and Vector Processors, Memory Hierarchy Technology, Virtual Memory Technology.

Distributed Systems : Fundamentals: Definitions of Distributed Computing Systems, Evolution of Distributed Computing System, Distributed Computing System Models, Why are Distributed Computing Systems Gaining Popularity, Definition of Distributed Operating System, Issues in Designing a Distributed Operating System; Synchronization: Introduction, Clock Synchronization , Event Ordering, Mutual Exclusion, Deadlock, Election Algorithms; Remote Procedure Calls: Introduction, The RPC Model, Transparency of RPC, Implementing RPC Mechanism; Distributed File System: Introduction, Features of Distributed File System, File Services Interface, Directory Server Interface, Semantics of File Sharing, File Systems Implementation, Caching, Stateful File Server, Stateless File server, NFS Architecture; Fault Tolerance: Component Faults, System Failures, Use of Redundancy, Fault Tolerance Using Active Replication, Fault Tolerance Using Primary Backup;

  • Course Title : Parallel and Distributed Systems Lab

(As per theory course)

  • Course Title : Digital Signal Processing

Introduction to Digital Signal Processing (DSP): Introduction; Digital Signal Processing; Sampling and Analog-to-Digital Conversion; Discrete Time Signals; Ambiguity in Digital signals; Discrete Time Systems; Application areas for DSP; Keys of DSP operations: Convolution, Correlation, Digital Filtering, Discrete Transformation, Modulation; System Design: Methodology & Implementation Methodology.

Discrete Fourier transform: Fourier series, one dimensional Fourier transforms, discrete Fourier Transform (DFT) and its properties, Fast Fourier Transform (FFT) and its algorithm, Inverse discrete Fourier transformation.

The Z-Transform : Introduction to z-Transform; General Results of z-transform;

Inverse z-Transform: Partial Fraction Expansion, Power Series Expansion, Contour Integration; Comparison of inverse z-transform method; Properties of z-transform; Complex Convolution Theorem and Parseval’s Relation.

Implementation of Discrete-Time Systems: Introduction; Block Diagram and Signal Flow Graph Representation of Digital Networks; Matrix Representation of Digital Networks; Basic Structures of IIR Systems: Direct Form, Cascade forms, Parallel Form; Transposed Forms; Basic Structures of FIR Systems; Finite Precision Effects.

Design of Digital Filters: Introduction to Digital Filters; Types of Digital Filters: FIR and IIR; Choosing between FIR and IIR Filters: Digital Filter Design Steps; Design of FIR Filters: Design of FIR Filters by Windowing, Design of Optimum Equiripple Linear-Phase FIR Filters, Design of IIR Filters: Classical Continuous-Time Low-Pass Filter Approximations, Conversion of Transfer Functions from Continuous to Discrete Time, Frequency Transformations of Low pass Filters, Adaptive digital filters: concepts of adaptive filtering, basic wiener filter theory, the basic LMS adaptive algorithm, recursive least square algorithm.

  • Course Title : Digital Signal Processing Lab

(As per theory course)

  • Course Title : Digital Image Processing

Introduction to image processing: Representation of image, A basic image processing system, Relationship to human visual system, Example of fields that use digital image processing,

Digital Image Fundamentals: Image formation in the eye, Light and electromagnetic spectrum, Image sensing and acquisition, Image sampling, Image quantization, Some basic relationships between pixels Neighbors of a pixel, Adjacency, connectivity, region, Boundaries, Distance measures

Image enhancement: Some basic gray level transformations, Histogram processing, Histogram equalization, Histogram matching, Image negatives, log transformation, Power law transformation, Basics of spatial filtering, Smoothing spatial filters, Homomorphic filtering, Correspondence between the spatial and frequency domain filtering.

Image Restoration: A model of the image degradation/ Restoration process, Noise models, Restoration in the presence of noise only spatial filtering.

Color Image processing: Color fundamentals, Color models, the RGB color model The CMY, CMYK color Model, HIS color Model, Basics of full-color transformation, Color transformations, formulation.

Image Compression: Image compression fundamentals, Coding redundancy, Inter pixel redundancy Psychovisual redundancy, Image compression models, The source encoder and decoder, The channel encoder and decoder.

Image Segmentation: Edge detection, line detection, point detection, Boundary Detection, Thresholding, Region based segmentation.

  • Course Title : Digital Image Processing Lab

(As per theory course)

  • Course Title : Multimedia

Introduction to Multimedia: Design Concepts, Preproduction and Presentation Graphics: Presentation Graphics Design, Preproduction, Typefaces and Graphics. Desktop Publishing, Production Planning and Design, User Interface Design, Hypermedia Authoring Concepts, Multimedia Sound, File Compression, Video Production, Digital Video, Animation, HTML & Web-Based Multimedia, Designing Web-based Multimedia, Producing Multimedia, Content & Legal Considerations for Multimedia, Content & Legal Considerations for Multimedia, Multimedia Distribution, Networking Multimedia.

  • Course Title : Multimedia Lab

(As per theory course)

  • Course Title : Pattern Recognition

Introduction to Pattern Recognition: Classification Statistical Methods, Structural Methods and Hybrid method. Introduction to passen grammar and languages. Applications to character recognition medical imaging area. feature detection, classification, Review of probability and some linear algebra. Bayesian Decision Making, linear discriminants, separability, multi-class discrimination; quadratic classifiers, Fisher discriminant, sufficient statistics, coping with missing or noisy features, Bayesian estimation; non-parametric estimation; Non-parametric classification, density estimation, Parzen estimation, training methods, maximum likelihood, Bayesian parameter estimation, MAP. Linear discriminant functions.. Template-based recognition, eigenvector analysis, feature extraction, Eigen vector analysis. Clustering, unsupervised learning, vector quantization, K-means and E/M, neural nets. Sequence analysis, HMMs. k-nearest-neighbor classification, Mixture modeling, Optimization by Expectation¬, Maximization, Hidden Markov models, Viterbi algorithm, Baum-Welch algorithm, Linear dynamical systems, Kalman filtering and smoothing, Bayesian networks, independence diagrams, Decision trees, Multi-layer Perceptrons.

  • Course Title : Pattern Recognition Lab

(As per theory course)

  • Course Title : Design and Analysis of VLSI Systems

Introduction to MOS technology: POMS, NMOS and CMOS, transistors, CMOS

Fabrication.

Design Approaches: Fabrication steps, steps stick diagrams, design rules and layout, contact cuts, double metal MOS process rules. MOS circuits,

Delay Analysis: Inverter delay and its analysis, delay of different sequential and combinational circuit.

Sequential System: Super buffer, Dynamic MOS circuits, Scaling of MOS circuits. Scaling factors and device parameters.

Subsystem design and layout. Switch logic: pass transistors and transmission gates. Gate logic: The inverter, Two input nMOS, CMOS and BiCMOS gate design. Design of parity generator and multiplexers. Registers, Counters and memory realizations, One transistor and three transistors dynamic RAM cell design.

Hierarchical view of VLSI System Design: Behavioral description High level Synthesis Scheduling, allocation and data path synthesis.

Logic synthesis: multilevel minimization, PLA reduction regular structure circuits, Synthesis of FSM-ASM chart representation and realization, Layout synthesis, Placement and routing, Testing of VLSI, Testing of stuck-at fault, Testing of PLAs RAM.

Introduction to Reversible Logic: Theory of reversibility, Reversible gates, reversible circuits, reversible logic synthesis. FPGA: Introduction to FPGA and FPGA programming using VHDL.

  • Course Title : Design and Testing of VLSI Systems Lab

(As per theory course)

  • Course Title : Microcontroller and Embedded System

Introduction to the Embedded Systems, Embedded System Design Specifications, Embedded System Hardware and Hardware/Software Co-design, 8051/8052 family of Microcontrollers, C programming for Microcontrollers,  I/O ports Programming, Timer/Counter hardware and Its Device Driver, Serial communication interface and Its Device Driver, Interrupts Programming, Embedded Software Development Cycle and the Integrated Development Environment, Debugging Techniques for Embedded Software and the Role of Cross Simulators, Real World Interfacing Case Studies: LCD, Sensors, stepper motor, keyboard, PC, Design of Device Driver for Serial Devices,  Concept of Finite State Machines and Examples –  Stop Watch, Stepper Motor Control through PC, Remote Control of Systems using IR Remotes Used in Commercial TV Remote Control Modules, Simple Multi Drop Communication Networks With Examples, Simple Wireless Communication With Examples.

  • Course Title : Micro-controller and Embedded System Lab

(As per theory course)

  • Course Title : Cyber Law and Computer Forensic

Overview of Cybercrime: Samples of cybercrime, Unique Characteristics of Cybercrime, Cyber-attacks and attackers. Cybercrime Law. Computer Intrusions and Attacks: computer trespass, unauthorized access, relationship between acceptable use policies (“AUP”), terms of service (“TOS”), and criminal law. Hacking: Hacking for Grades, Hacking for harrassment (“swatting”), URL hacking, WiFi Mooching. Computer Viruses, Time Bombs, Trojans, Malicious Code, malware, Spam, Botnets, Logic Bomb, Rootkits. Online Fraud and Identity Theft: Intellectual Property Theft; Virtual Crime. Online Vice: Gambling; Pornography; Child Exploitation. International Aspects and Jurisdiction, Infrastructure and Information Security; Risk Management, Investigating Cybercrime: Interception: Search and Seizure, and Surveillance. Information Warfare: Cyberterrorism and Hacktivism. Terrorism, Radicalization, and the War of Ideas. Trade Secret Theft and Economic Espionage. National Security. Computer Forensic: overview of the forensic relevance of encryption, the examination of digital evidence for clues, and the most effective way to present evidence and conclusions in a court of law.

  • Course Title : Cyber Law and Computer Forensics Lab

(As per theory course)

  • Course Title : Natural Language Processing 

Words, Parts of Speech, Syntax, Grammars, Semantics, Language Modeling in General and the Noisy Channel Model., Linguistics: Phonology and Morphology  Word Classes and Lexicography. Mutual Information.  The t-score. The Chi-square test.  Hidden Markov Models (HMMs). The Trellis & the Viterbi Algorithms. HMM Tagging (Supervised, Unsupervised). Evaluation methodology (examples from tagging). Precision, Recall, Accuracy.  Statistical Transformation Rule-Based Tagging. Maximum Entropy Tagging. Feature Based Tagging. Results on Tagging Various Natural Languages. Non-statistical Parsing Algorithms (An Overview). Simple top-down parser with backtracking. Probabilistic Parsing. Introduction. Statistical Machine Translation (MT).

  • Course Title : Natural Language Processing Lab

(As per theory course)

  • Course Title : System Analysis and Design

Introduction to general systems theory, Players in the Systems Game, Information Systems Building Blocks. Information Systems Development, Project Management. Systems Analysis, Requirements Discovery, Deliverables, Data Modeling and Analysis, Process Modeling, Feasibility Analysis and System Proposal, Systems Design, Applications Architecture and Modeling, Database Design, Output Design and Prototyping, Input Design and Prototyping, User Interface Design, Systems Construction and Implementation, Systems Operations and Support, Object-Oriented Analysis and Modeling, Object-Oriented Design and Modeling.

  • Course Title : System Analysis and Design Lab

(As per theory course)

  • Course Title : Optical Fiber Communication

History of optical communication, advantages and limitations of fiber communication. Theory of light: reflection, refraction, critical incident angle, total internal reflection. Electromagnetic waves, Maxwell’s equation, damping waves, wavefront, propagation constant, phase velocity, group velocity. Basics of optical fiber: acceptance angle, numerical aperture, fiber structure, comparison with copper, meridional rays, skew rays, v number of a fiber, modes in a planar guide, Evanescent field, single mode fiber, multimode fibers. Fabrication of optical fibers: Vapor phase deposition techniques: OVD, MCVD, PCVD, VAD, coating. Optical sources: requirements , energy band diagram, LED: (principle of action, internal quantum efficiency, homostructure and heterostructure of LEDs), Laser: (principle of action, properties of stimulated radiation, positive feedback, population inversion, lasing effect, properties of laser beam, types of lasers: QW, Fabry-Perot, DFB, VCSEL), Superluminescent diodes (SLD), blocks of optical transmitter. Photo detectors: principle of action, responsivity, quantum efficiency, modes of operation, advantages of reverse biasing, sensitivity, efficiency of light-current conversion, p-i-n photodiodes: (features, types, advantages), avalanche photodiode: working principle, noise sources in photodiode, blocks of receiver. Losses in fiber: Material absorption loss, Linear scattering loss, Nonlinear scattering loss, Fiber bend loss, Coupling loss, Dispersion, Polarization loss. Fiber optic cables, optical connectors: (basic structure, preparation, types, characteristics), fiber splices: (splicing procedure, mechanical splice, fusion splice, PAS, PAT). Optical network: OTDM, WDM and DWDM: (lasers, transmitter requirements, receiver requirements, add/drop problem, repeaters), Tunable lasers: (characteristics, external cavity, DBR, integrated cavity lasers). Optical amplifiers: advantages, types, SOA: (types: FPA and TWA, principle of operation, advantages, and disadvantages). EDFA: (principle of operation, characteristics, structure, advantages, noise, DBFA, EBFA). Optical switches, Wavelength converters, Couplers/splitters, WDM mux and demux, filters, Isolators, Circulators, Attenuators. Optical layer: sections, sublayers, services. Protection and restoration techniques.

  • Course Title : Optical Fiber Communication Lab

    (As per theory course)

  • Course Title : Human Computer Interaction

Foundations of Human Computer Interaction: Humans and Machines, Interaction, Collaboration. Models in HCI: Cognitive Models, Socio-organizational Issues and Stakeholder Requirements. Importance of cognitive abilities. Design Process: Interaction Design Basics, HCI in Software Process, Design Rules, Universal Design, User Center Design. Design. Prototyping, Task Analysis, GOMS and other key HCI methods. Lifecycle Models. User Interfaces: Interfaces Basics, Interaction Techniques, System Control of Interfaces, Human Factors and Strategies in Designing Interfaces. Evaluation and User Support: Evaluation, Evaluation of Interfaces, User Support. Tasks Models and Dialogs: Analysing the Task, Dialog Notations and Design. Groupware, Ubiquitous Computing, Virtual and Augmented Reality. Social-Cultural Contexts of HCI.

    • Course Title : Human Computer Interaction Lab

(As per theory course)

  • Course Title : Graph Theory

Fundamental concepts, varieties of graphs, path, cycles and components, degrees and distances, clique. Trees: Properties, spanning trees, forests, centroids, generation of trees and cycles, ent cycles and co-cycles. Connectivity: Vertex and edge connectivity, blocks, eccentricity, Menge’s Theorem. Traversability: Eulerian graphs, kuratowski’s theorem, embedding graphs on surfaces, genus, thickness and crossing number. Graph Coloring: Vertex coloring, edge coloring, chromatic number, five color theorem, four color conjecture, critical graph. Homomorphism Digraph: Different connectedness, oriented graphs-tournaments, network flows and related algorithms. Groups, polynomials and graph enumeration, matching and factorization, perfect graphs, Ramsey number and Ramsey theorem, forbidden graph theory, miscellaneous applications.

  • Course Title : Graph Theory Lab

(As per theory course)

 

Third Year Syllabus Department of Computer Science and Engineering

 

 

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