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Syllabus of

UNDERGRADUATE DEGREE COURSE

B.Tech. V Semester

Computer Science and Engineering

Rajasthan Technical University, Kota

Effective from session: 2022 – 2023

Syllabus III Year-V Semester: B.Tech. Computer Science and Engineering 5CS3-01: Information Theory & Coding Credit: 2 Max. Marks: 100(IA:30, ETE: 7 0) 2L+0T+0P End Term Exam: 3 Hours SN Contents Hours (^1) Introduction: Objective, scope and outcome of the course. 01 2 Introduction to information theory: Uncertainty, Information and Entropy, Information measures for continuous random variables, source coding theorem. Discrete Memory less channels, Mutual information, Conditional entropy. 05 (^3) Source coding schemes for data compaction: Prefix code, Huffman code, Shanon-Fane code & Hempel-Ziv coding channel capacity. Channel coding theorem. Shannon limit. 05 (^4) Linear Block Code: Introduction to error connecting codes, coding & decoding of linear block code, minimum distance consideration, conversion of non-systematic form of matrices into systematic form. 05 (^5) Cyclic Code: Code Algebra, Basic properties of Galois fields (GF) polynomial operations over Galois fields, generating cyclic code by generating polynomial, parity check polynomial. Encoder & decoder for cyclic codes. 06 6 Convolutional Code: Convolutional encoders of different rates. Code Tree, Trllis and state diagram. Maximum likelihood decoding of convolutional code: The viterbi Algorithm fee distance of a convolutional code. 06 Total 28

Syllabus III Year-V Semester: B.Tech. Computer Science and Engineering 5CS4- 03 : Operating System Credit: 3 Max. Marks: 100(IA:30, ETE: 7 0) 3L+0T+0P End Term Exam: 3 Hours SN Contents Hours 1 Introduction: Objective, scope and outcome of the course. 01 2 Introduction and History of Operating systems: Structure and operations; processes and files. Processor management: inter process communication, mutual exclusion, semaphores, wait and signal procedures, process scheduling and algorithms, critical sections, threads, multithreading. 04 3 Memory management: contiguous memory allocation, virtual memory, paging, page table structure, demand paging, page replacement policies, thrashing, segmentation, case study. 05 4 Deadlock: Shared resources, resource allocation and scheduling, resource graph models, deadlock detection, deadlock avoidance, deadlock prevention algorithms Device management: devices and their characteristics, device drivers, device handling, disk scheduling algorithms and policies 15 5 File management: file concept, types and structures, directory structure, cases studies, access methods and matrices, file security, user authentication. 07 6 UNIX and Linux operating systems as case studies; Time OS and case studies of Mobile OS. 08 Total 40

Syllabus III Year-V Semester: B.Tech. Computer Science and Engineering 5CS4- 04 : Computer Graphics & Multimedia Credit: 3 Max. Marks: 100(IA:30, ETE: 7 0) 3L+0T+0P End Term Exam: 3 Hours SN Contents Hours 1 Introduction: Objective, scope and outcome of the course. 01 2 Basic of Computer Graphics: Basic of Computer Graphics, Applications of computer graphics, Display devices, Random and Raster scan systems, Graphics input devices, Graphics software and standards. 06 3 Graphics Primitives: Points, lines, circles and ellipses as primitives, scan conversion algorithms for primitives, Fill area primitives including scan- line polygon filling, inside-outside test, boundary and flood-fill, character generation, line attributes, area-fill attributes, character attributers. Aliasing, and introduction to Anti Aliasing (No anti aliasing algorithm). 07 (^4) Two Dimensional Graphics: Transformations (translation, rotation, scaling), matrix representation, homogeneous coordinates, composite transformations, reflection and shearing, viewing pipeline and coordinates system, window-to-viewport transformation, clipping including point clipping, line clipping (cohen-sutherland, liang- bersky, NLN), polygon clipping. 08 5 Three Dimensional Graphics: 3D display methods, polygon surfaces, tables, equations, meshes, curved lies and surfaces, quadric surfaces, spline representation, cubic spline interpolation methods, Bazier curves and surfaces, B-spline curves and surfaces.3D scaling, rotation and translation, composite transformation, viewing pipeline and coordinates, parallel and perspective transformation, view volume and general (parallel and perspective) projection transformations. 08 6 Illumination and Colour Models: Light sources – basic illumination models – halftone patterns and dithering techniques; Properties of light – Standard primaries and chromaticity diagram; Intuitive colour concepts – RGB colour model – YIQ colour model – CMY colour model – HSV colour model – HLS colour model; Colour selection. 06 (^7) Animations &Realism: Design of Animation sequences – animation function – raster animation – key frame systems – motion specification – morphing – tweening. ComputerGraphics Realism: Tiling the plane – Recursively defined curves – Koch curves – C curves – Dragons – space filling curves – fractals

• Grammar based models – fractals – turtle graphics – ray tracing. 06 Total 42

Syllabus III Year-V Semester: B.Tech. Computer Science and Engineering 5CS5-11: Wireless Communication Credit: 2 Max. Marks: 100(IA:30, ETE: 7 0) 2L+0T+0P End Term Exam: 3 Hours SN Contents Hours 1 Introduction: Objective, scope and outcome of the course. 01 2 Wireless Channels: Large scale path loss – Path loss models: Free Space and Two-Ray models - Link Budget design – Small scale fading- Parameters of mobile multipath channels – Time dispersion parameters-Coherence bandwidth – Doppler spread & Coherence time, Fading due to Multipath time delay spread – flat fading – frequency selective fading – Fading due to Doppler spread – fast fading – slow fading. 06 (^3) Cellular Architecture: Multiple Access techniques - FDMA, TDMA, CDMA – Capacity calculations–Cellular concept- Frequency reuse - channel assignment- hand off- interference & system capacity- trunking & grade of service – Coverage and capacity improvement. 05 (^4) Digital Signaling For Fading Channels: Structure of a wireless communication link, Principles of Offset-QPSK, p/4-DQPSK, Minimum Shift Keying, Gaussian Minimum Shift Keying, Error performance in fading channels, OFDM principle – Cyclic prefix, Windowing, PAPR. 05 (^5) Multipath Mitigation Techniques: Equalisation – Adaptive equalization, Linear and Non-Linear equalization, Zero forcing and LMS Algorithms. Diversity – Micro and Macrodiversity, Diversity combining techniques, Error probability in fading channels with diversity reception, Rake receiver, 06 (^6) Multiple Antenna Techniques: MIMO systems – spatial multiplexing - System model - Pre-coding - Beam forming - transmitter diversity, receiver diversity- Channel state information- capacity in fading and non-fading channels. 05 Total 28

Syllabus III Year-V Semester: B.Tech. Computer Science and Engineering 5 CS 5 - 12 : Human Computer Interaction Credit: 2 Max. Marks: 100(IA:30, ETE: 7 0) 2L+0T+0P End Term Exam: 3 Hours SN Contents Hours 1 Introduction:^ Objective, scope and outcome of the course.^^01 (^2) Historical evolution of the field, Interactive system design, Concept of usability - definition and elaboration, HCI and software Engineering, GUI design and Aesthetics, Prototyping techniques. 02 (^2) Model-based Design and evaluation: Basic idea, introduction to different types of models, GOMS family of models (KLM and CMN- GOMS), Fitts’ law and Hick-Hyman’s law, Model-based design case studies, 03 3 Guidelines in HCI: Shneiderman’s eight, golden rules, Norman’s seven principles, Norman’s model of interaction, Nielsen’s ten heuristics with example of its use Heuristic evaluation, Contextual inquiry, Cognitive walkthrough. 05 (^4) Empirical research methods in HCI: Introduction (motivation, issues, research question formulation techniques), Experiment design and data analysis (with explanation of one-way ANOVA). 06 (^5) Task modelling and analysis: Hierarchical task analysis (HTA), Engineering task models and Concur Task Tree (CTT),Iintroduction to formalism in dialog design, design using FSM (finite state machines) State charts and (classical) Petri Nets in dialog design. 06 (^6) Introduction to CA , CA types, relevance of CA in IS design Model Human Processor (MHP), OOP- Introduction OOM- Object Oriented Modeling of User Interface Design. 05 Total 28

Syllabus III Year-V Semester: B.Tech. Computer Science and Engineering 5CS4- 21 : Computer Graphics & Multimedia Lab Credit: 1 Max. Marks:100 (IA:60, ETE: 4 0) 0L+0T+2P End Term Exam: 2 Hours SN List of Experiments 1 Implementation of Line, Circle and ellipse attributes 2 To plot a point (pixel) on the screen 3 To draw a straight line using DDA Algorithm 4 Implementation of mid-point circle generating Algorithm 5 Implementation of ellipse generating Algorithm 6 Two Dimensional transformations - Translation, Rotation, Scaling, Reflection, Shear 7 Composite 2D Transformations 8 Cohen Sutherland 2D line clipping and Windowing 9 Sutherland – Hodgeman Polygon clipping Algorithm 10 Three dimensional transformations - Translation, Rotation, Scaling 11 Composite 3D transformations 12 Drawing three dimensional objects and Scenes 13 Generating Fractal images

Syllabus III Year-V Semester: B.Tech. Computer Science and Engineering 5CS4- 22 : Compiler Design Lab Credit: 1 Max. Marks: 100 (IA:60, ETE: 4 0) 0L+0T+2P End Term Exam: 2 Hours SN List of Experiments 1 Introduction: Objective, scope and outcome of the course. 2 To identify whether given string is keyword or not. 3 Count total no. of keywords in a file. [Taking file from user] 4 Count total no of operators in a file. [Taking file from user] 5 Count total occurrence of each character in a given file. [Taking file from user] 6 Write a C program to insert, delete and display the entries in Symbol Table. 7 Write a LEX program to identify following:

1. Valid mobile number
2. Valid url
3. Valid identifier
4. Valid date (dd/mm/yyyy)
5. Valid time (hh:mm:ss) 8 Write a lex program to count blank spaces,words,lines in a given file. 9 Write a lex program to count the no. of vowels and consonants in a C file. 10 Write a YACC program to recognize strings aaab,abbb using a^nb^n, where b>=0. 11 Write a YACC program to evaluate an arithmetic expression involving operators +,-,* and /. 12 Write a YACC program to check validity of a strings abcd,aabbcd using grammar a^nb^nc^md^m, where n , m> 13 Write a C program to find first of any grammar.

Syllabus III Year-V Semester: B.Tech. Computer Science and Engineering 5CS4- 24 : Advance Java Lab Credit: 1 Max. Marks: 100 (IA:60, ETE: 4 0) L+0T+2P End Term Exam: 2 Hours SN List of Experiments 1 Introduction To Swing, MVC Architecture, Applets, Applications and Pluggable Look and Feel, Basic swing components : Text Fields, Buttons, Toggle Buttons, Checkboxes, and Radio Buttons. 2 Java database Programming, java.sql Package, JDBC driver, Network Programming With java.net Package, Client and Server Programs, Content And Protocol Handlers. 3 RMI architecture, RMI registry, Writing distributed application with RMI, Naming services, Naming And Directory Services, Overview of JNDI, Object serialization and Internationalization. 4 J2EE architecture, Enterprise application concepts, n-tier application concepts, J2EE platform, HTTP protocol, web application, Web containers and Application servers. 5 Server side programming with Java Servlet, HTTP and Servlet, Servlet API, life cycle, configuration and context, Request and Response objects, Session handling and event handling, Introduction to filters with writing simple filter application. 6 JSP architecture, JSP page life cycle, JSP elements, Expression Language, Tag Extensions, Tag Extension API, Tag handlers, JSP Fragments, Tag Files, JSTL, Core Tag library, overview of XML Tag library, SQL Tag library and Functions Tag library.

Syllabus of

UNDERGRADUATE DEGREE COURSE

B.Tech. VI Semester

Computer Science and Engineering

Rajasthan Technical University, Kota

Effective from session: 2022 – 2023

Syllabus III Year-VI Semester: B.Tech. Computer Science and Engineering 6CS4- 02 :Machine Learning Credit: 3 Max. Marks: 100(IA: 3 0, ETE: 7 0) 3L+0T+0P End Term Exam: 3 Hours SN Contents Hours 1 Introduction: Objective, scope and outcome of the course. 01 2 Supervised learning algorithm: Introduction, types of learning, application, Supervised learning: Linear Regression Model, Naive Bayes classifier Decision Tree, K nearest neighbor, Logistic Regression, Support Vector Machine, Random forest algorithm.

3 Unsupervised learning algorithm: Grouping unlabelled items using k-means clustering, Hierarchical Clustering, Probabilistic clustering, Association rule mining, Apriori Algorithm, f-p growth algorithm, Gaussian mixture model.

4 Introduction to Statistical Learning Theory , Feature extraction - Principal component analysis, Singular value decomposition. Feature selection – feature ranking and subset selection, filter, wrapper and embedded methods, Evaluating Machine Learning algorithms and Model Selection.

5 Semi supervised learning, Reinforcement learning: Markov decision process (MDP), Bellman equations, policy evaluation using Monte Carlo, Policy iteration and Value iteration, Q-Learning, State- Action-Reward-State-Action (SARSA), Model-based Reinforcement Learning.

6 Recommended system, Collaborative filtering, Content-based filtering Artificial neural network, Perceptron, Multilayer network, Back propagation, Introduction to Deep learning.

Total 42

Syllabus III Year-VI Semester: B.Tech. Computer Science and Engineering 6CS4- 03 : Information Security System Credit:2 Max. Marks: 100(IA: 3 0, ETE: 7 0) 2L+0T+0P End Term Exam: 3 Hours SN Contents Hours 1 Introduction: Objective, scope and outcome of the course. 01 (^2) Introduction to security attacks: services and mechanism, classical encryption techniques- substitution ciphers and transposition ciphers, cryptanalysis, stream and block ciphers.

3 Modern block ciphers : Block Cipher structure, Data Encryption standard (DES) with example, strength of DES, Design principles of block cipher, AES with structure, its transformation functions, key expansion, example and implementation. Multiple encryption and triple DES, Electronic Code Book, Cipher Block Chaining Mode, Cipher Feedback mode, Output Feedback mode, Counter mode.

(^4) Public Key Cryptosystems with Applications: Requirements and Cryptanalysis, RSA cryptosystem, Rabin cryptosystem, Elgamal cryptosystem, Elliptic curve cryptosystem.

5 Cryptographic Hash Functions, their applications: Simple hash functions, its requirements and security, Hash functions based on Cipher Block Chaining, Secure Hash Algorithm (SHA). Message Authentication Codes, its requirements and security, MACs based on Hash Functions, Macs based on Block Ciphers. Digital Signature, its properties, requirements and security, various digital signature schemes (Elgamal and Schnorr), NIST digital Signature algorithm.

6 Key management and distribution: symmetric key distribution using symmetric and asymmetric encryptions, distribution of public keys, X.509 certificates, Public key infrastructure. Remote user authentication with symmetric and asymmetric encryption, Kerberos. Web Security threats and approaches, SSL architecture and protocol, Transport layer security, HTTPS and SSH.

Total 28

Syllabus III Year-VI Semester: B.Tech. Computer Science and Engineering 6CS4- 05 : Artificial Intelligence Credit: 2 Max. Marks: 100(IA: 3 0, ETE: 7 0) 2L+0T+0P End Term Exam: 3 Hours SN Contents Hours 1 Introduction: Objective, scope and outcome of the course. 01 2 Introduction to AI and Intelligent agent: Different Approach of AI, Problem Solving : Solving Problems by Searching, Uninformed search, BFS, DFS, Iterative deepening, Bi directional search, Hill climbing, Informed search techniques: heuristic, Greedy search, A* search, AO* search, constraint satisfaction problems.

3 Game Playing: Minimax, alpha-beta pruning, jug problem, chess problem, tiles problem.

4 Knowledge and Reasoning: Building a Knowledge Base: Propositional logic, first order logic, situation calculus. Theorem Proving in First Order Logic. Planning, partial order planning. Uncertain Knowledge and Reasoning, Probabilities, Bayesian Networks.

5 Learning: Overview of different forms of learning, Supervised base learning: Learning Decision Trees, SVM, Unsupervised based learning, Market Basket Analysis, Neural Networks.

6 Introduction to Natural Language Processing: Different issue involved in NLP, Expert System, Robotics.

Total 28

Syllabus III Year-VI Semester: B.Tech. Computer Science and Engineering 6CS4- 06 : Cloud Computing Credit: 3 Max. Marks: 100(IA: 3 0, ETE: 7 0) 3L+0T+0P End Term Exam: 3 Hours SN Contents Hours 1 Introduction: Objective, scope and outcome of the course. 01 2 Introduction: Objective, scope and outcome of the course. Introduction Cloud Computing: Nutshell of cloud computing, Enabling Technology, Historical development, Vision, feature Characteristics and components of Cloud Computing. Challenges, Risks and Approaches of Migration into Cloud. Ethical Issue in Cloud Computing, Evaluating the Cloud's Business Impact and economics, Future of the cloud. Networking Support for Cloud Computing. Ubiquitous Cloud and the Internet of Things.

3 Cloud Computing Architecture: Cloud Reference Model, Layer and Types of Clouds, Services models, Data centre Design and interconnection Network, Architectural design of Compute and Storage Clouds. Cloud Programming and Software: Fractures of cloud programming, Parallel and distributed programming paradigms-Map Reduce, Hadoop, High level Language for Cloud. Programming of Google App engine.

4 Virtualization Technology: Definition, Understanding and Benefits of Virtualization. Implementation Level of Virtualization, Virtualization Structure/Tools and Mechanisms, Hypervisor VMware, KVM, Xen. Virtualization: of CPU, Memory, I/O Devices, Virtual Cluster and Resources Management, Virtualization of Server, Desktop, Network, and Virtualization of data-centre.

5 Securing the Cloud: Cloud Information security fundamentals, Cloud security services, Design principles, Policy Implementation, Cloud Computing Security Challenges, Cloud Computing Security Architecture. Legal issues in cloud Computing. Data Security in Cloud: Business Continuity and Disaster Recovery , Risk Mitigation , Understanding and Identification of Threats in Cloud, SLA-Service Level Agreements, Trust Management.

6 Cloud Platforms in Industry: Amazon web services , Google AppEngine, Microsoft Azure Design, Aneka: Cloud Application Platform - Integration of Private and Public Clouds Cloud applications: Protein structure prediction, Data Analysis, Satellite Image Processing, CRM

Total 42