B.Tech Computer Science and Engineering Curriculum Discipline CREDIT % Basic Science and Mathematics 42 23.20 General Education 17 9.39 Computer Science & Engineering 122 67.41 Total 181 100 1. BASIC SCIENCE AND MATHEMATICS Course Code Course Title CSE208 Theory of Computation PHY101 Modern Physics CHY101 Engineering Chemistry CHY104 Environmental Studies MAT101 Multivariable Calculus and Differential Equations MAT105 Differential and Difference Equations MAT106 Discrete Mathematical Structures MAT202 Linear Algebra MAT203 Numerical Analysis MAT206 Graph Theory and its Applications MAT207 Applied Probability, Statistics and Reliability
Transcript
B.Tech Computer Science and Engineering Curriculum
Discipline CREDIT %
Basic Science and Mathematics 42 23.20
General Education 17 9.39
Computer Science & Engineering 122 67.41
Total 181 100
1. BASIC SCIENCE AND MATHEMATICS
Course Code Course Title
CSE208 Theory of Computation
PHY101 Modern Physics
CHY101 Engineering Chemistry
CHY104 Environmental Studies
MAT101 Multivariable Calculus and Differential Equations
MAT105 Differential and Difference Equations
MAT106 Discrete Mathematical Structures
MAT202 Linear Algebra
MAT203 Numerical Analysis
MAT206 Graph Theory and its Applications
MAT207 Applied Probability, Statistics and Reliability
2. GENERAL EDUCATION
Course Code Course Title
ENG101 English for Engineers – I
ENG102 English for Engineers – II
FRE101 /GER101 / Foreign Language
JAP101/ ESP101
MGT301 Ethics and Values
Course Code Course Name
HUM101 Psychology and Sociology
HUM102 Economics for Engineers
HUM103 Business Economics
HUM104 Macro Economics
HUM106 Corporate Economics
HUM108 Wealth Management
HUM109 International Business
HUM112 Business accounting for engineers
HUM114 Tax Management for Engineers
HUM117 Business Law
HUM118 Fundamentals of Cyber Laws
MGT201 Principles of Management
MGT202 Economics for Engineers
MGT302 Total Quality Management
MGT304 Research Methods for Management
MGT305 Cross-Cultural Management
MGT307 Principles of Marketing
MGT309 Basic Law for Engineers
MGT310 Organizational Behavior
MGT312 Entrepreneurship Development
MGT313 Project Management
MGT314 Accounting for Engineers
MGT317 Managing Personal Finance
MGT319 Foundations of Management and
Organizational Behavior
MGT501 Creativity and Innovation in Management
3. COMPUTER SCIENCE & ENGINEERING Program Core
Course Code Course Title
CSE101 Computer Programming and Problem Solving
CSE103 Programming Fundamentals
CSE203 The Object Oriented Paradigm
CSE206 Object Oriented Programming Lab
CSE106 Digital Logic
CSE107 Digital Logic Laboratory
CSE204 Data Structures and Algorithms
CSE207 Data Structures and Algorithms Lab
CSE205 Computer Architecture and Organization
CSE202 Algorithm Design and Analysis
CSE305 Embedded Systems
CSE306 Embedded Systems Lab
CSE211 Operating Systems
CSE212 Operating Systems Lab
CSE303 Computer Networks
CSE304 Computer Networks Lab
CSE309 Programming Language Translators
CSE413 Computer Graphics
CSE312 Database Systems
CSE318 Database Systems Lab
CSE310 Software Engineering
CSE311 Software Engineering Lab
CSE307 Internet and Web Programming
CSE308 Internet and Web Programming lab
CSE213 Microprocessor and Interfacing
CSE214 Microprocessor and Interfacing Lab
ECE104 Discrete Time Systems and Processing
EEE101 Basic Electrical and Electronics Engineering
EEE103 Electronics
MEE437 Operations Research
MEE101 Engineering Graphics
MEE102 Workshop Practice
CSE498 Comprehensive Examination
CSE398 Mini Project
CSE399 Industrial Internship
CSE499 Project Work
Program Elective courses
Course Code Course Title
CSE302 Introduction to Artificial Intelligence
CSE404 Bio- informatics
CSE405 Parallel Algorithms
CSE406 Concurrent and Distributed Systems
CSE407 Software Practice and Testing
CSE408 Data Warehousing and Data Mining
CSE315 Scripting Languages
CSE403 Human Computer Interaction
CSE414
Multimedia Systems and Algorithms
CSE316 Database Design
CSE409 Modeling and Simulation
CSE410 Hardware Software Co-design
CSE411 Computer Organization and Design
CSE317 Data Communications
CSE412 Image Processing
CSE415 Information Security
CSE319 Soft Computing
CSE416 Cloud Computing
CSE320 Multi-core Systems Programming
CSE215 C++ Programming
Basic Science and Mathematics
Course Syllabi
Course Code Course Title
CSE208 Theory of Computation
PHY101 Modern Physics
CHY101 Engineering Chemistry
CHY104 Environmental Studies
MAT101 Multivariable Calculus and Differential Equations
MAT105 Differential and Difference Equations
MAT106 Discrete Mathematical Structures
MAT202 Linear Algebra
MAT203 Numerical Analysis
MAT206 Graph Theory and its Applications
MAT207 Applied Probability, Statistics and Reliability
Course Code THEORY OF COMPUTATION L T P C CSE208 3 1 0 4 Course Discrete Mathematical Structures, Algorithm Design and Analysis Prerequisites Objectives 1. To introduce Formal Languages, Automata Theory and Abstract models of
Computation and Computability, Computational complexities and NP – Completeness.
2. To gain knowledge in computational theory. 3. To realize the theoretical concepts and techniques involved in the software
system development Expected Outcome On completion of the course, the students will be able to
1. Apply the theoretical concepts and techniques in designing the software systems.
2. Identify, analyze, design and formulate problems using computational theory. 3. Conduct experiments and interpret data using computational theory. 4. Apply the theoretical principles of computing for software construction.
This course meets the following student outcomes: a) An ability to apply the knowledge of mathematics, science and computing appropriate to the discipline. b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution. e) An ability to identify, formulate and solve engineering problems. i) Design and conduct experiments as well as analyze and interpret data. m) An ability to apply design and development principles in the construction of software systems. (CS)
Unit 1 AUTOMATA 9 + 3 hours Strings, Alphabet, Language, Operations, Finite State Machine, definitions, finite automation model, acceptance of strings and languages, on deterministic finite automation, deterministic finite automation, equivalence between NFA and DFA, Conversion of NFA into DFA, minimization of FSM ,equivalence between two FSM's, Moore and Malay machines. Unit 2 REGULAR EXPRESSIONS 9 + 3 hours Regular sets, regular expressions, identity rules, manipulation of regular expressions, equivalence between RE and FA, inter conversion, Pumping lemma, Closure properties of regular sets(proofs not required),regular grammars, right linear and left linear grammars equivalence between regular linear grammar and FA, inter conversion between RE and RG. Unit 3 CONTEXT FREE GRAMMARS 9 + 3 hours Context free Grammars, Derivation trees, Left Most Derivations, Right Most Derivations, Ambiguity in Context-Free Grammars, Specifications of Context Free Grammars, Normal Forms, Chomsky Normal Form (CNF), Greibach Normal Form (GNF) Unit 4 TURING MACHINE 9 + 3 hours Turing machine, definition, model, design of TM, Computable Functions, recursive enumerable language, Church’s Hypothesis, Counter machine, types of TM's(Proofs not required). Unit 5 CLASSES OF PROBLEMS 9 + 3 hours Chomsky hierarchy of languages, linear bounded automats and context sensitive language, Introduction to DCFL and DPDA,LR(O) Grammar, decidability of problems, Universal Turing Machine, undecidability of post’s correspondence problem. Turing reducibility, definition of P and NP problems, NP complete and NP hard
problems
Text Books 1. Hopcroft, John E.; Motwani, Rajeev; Ullman, Jeffrey D. (2013).
Introduction to Automata Theory, Languages, and Computation (3rd
ed.). Pearson. ISBN 1292039051
2. Peter Linz, “An Introduction to Formal Language and Automata”, Third
Edition, Narosa Publishers, New Delhi, 2002
Reference Books 1. John C Martin, “Introduction to Languages and the Theory of
Computation”, Third Edition, Tata McGraw Hill Publishing Company,
New Delhi, 2007
2. Kamala Krithivasan and Rama. R, “Introduction to Formal Languages,
Automata Theory and Computation”, Pearson Education 2009
Phase velocity – Group velocity – Group index- wave guide theory- rectangular
wave guide (TE and TM modes)- Light propagation through fibers (TEM mode) –Acceptance angle – numerical aperture – types of fibers – step index, graded index – single mode, multimode – attenuation – dispersion– intermodal – intramodal – application of fiber optics in communication – source LED – Laser diode – Detector – pn – pin photodiode – endoscope . 1.Modern Physics, Raymond A. Serway, Clement J. Mosses, Curt A. Moyer, Cengage learning (3rd Indian Edition 2010). 2. Laser Systems and Applications, Nityanand Choudhary and Richa Verma,
PHI Text Books Learning Private Limited 2011. 3. Introduction to Fiber Optics, Ajoy Ghatak and K. Thyagarajan, Cambridge University Press (2011) 4. Microwave devices and circuits-second edition-Samuel Y.Liao – Pearson Education-New Delhi, 3
rd Edition 2012.
1. Concepts of Modern Physics, Arthur Beiser, Tata McGraw Hill,2009
2. Modern Physics for Scientists and Engineers, John R. Taylor, Chris D.
Zafiratos and Michael A. Dubson, PHI Learning Private Limited 2011.
3. Modern Physics, Kenneth Krane, Wiley, Indian Edition, 2010.
4. Modern Physics, Stephen T. Thornton and Andrew Rex, Cengage learning,
First Indian Reprint 2008
Reference 5. The essentials understanding nanoscience and nanotechnology, J. Pradeep,
Tata McGraw-Hill Publishing Company Ltd., 2007.
Books
6. Solid State Physics (New Revised Sixth Edition), S. O. Pillai, New Age
International Publishers, 2012.
7. Fiber Optic Communications Technology, Djafar K. Mynbaev and Lowell L.
Scheiner, Pearson 2011.
8. Lasers and Optical Instrumentation, S. Nagabhushana and B. Sathyanarayana,
I. K. International Publishing House Pvt. Ltd., 2010.
9. Principles of Electromagnetics, Matthew N. O. Sadiku, Fourth Edition, Oxford,
2011.
Mode of Continuous Assessment (30%) and Assignments / Quizzes / Projects (20%)
Term End Examination (50%)
Evaluation
Syllabus for Lab: List of Experiments
1) Determination of the length of a glass plate using Traveling Microscope 2) Determination of angle of direct ray using Spectrometer 3) Determination of Planck Constant: LED method 4) Determination of de Broglie wavelength : electron diffraction 5) Determination of particles size by laser diffraction method 6) Laser Grating – Determination of wavelength of given laser light 7) Determination of track width in CD: Laser diffraction 8) Determination of Numerical Aperture and Acceptance Angle of Optical Fiber 9) Determination of angle of prism using Spectrometer 10) Spectrometer – Determination of Refractive index of a Glass Prism 11) Determination of Refractive Index of Liquid
Evaluation: Continuous Assessment – 50 % & Term End Examination – 50% Course L T P C
Code: Engineering Chemistry 2 1 2 4
CHY 101
Course Basic Chemistry at 12thStandard or equivalent level
Prerequisites
Objectives: • To impart technological aspects of modern chemistry
• To lay foundation for the application of chemistry in engineering and
technology disciplines.
On completion of the course, the students will be able to
-analyse the necessary concepts in modern physics and
-Compare the applications in various engineering and technology disciplines.
This course meets the following student outcomes:
Expected a) An ability to apply the knowledge of mathematics, science and computing
appropriate to the discipline.
Outcome: b) An ability to analyze a problem, identify and define the computing
requirements appropriate to its solution.
e) An ability to identify, formulate and solve engineering problems.
i) Design and conduct experiments as well as analyze and interpret data
l) An ability to apply mathematical foundations, algorithmic principles and
computer science theory in the modeling and design of computer-based systems
(CS)
Unit I Water Technology
Hardness of water: Hard and soft water, Units of Hardness (numerical problems).
Disadvantages of hard water: Scale and sludge, caustic embrittlement, priming
and foaming, corrosion. Estimation of hardness: EDTA, alkali titration method
(numerical problems). Softening methods: Lime soda (numerical problems),
zeolite, ion exchange, mixed bed deionizer, treatment of municipal water.
Desalination: Desalination of sea water, brakish water, electrodialysis, reverse
osmosis.
Unit II Corrosion & Corrosion Control
Types –dry and wet corrosion, causes of corrosion – Forms of corrosion
Text Books 1. S.S. Dara, “A Text book of Engineering Chemistry”, 20th Edition, S. Chand &
Co Ltd., 2013.
1. B.R. Puri and L.R. Sharma, “Principles of Physical Chemistry”, 45th Edition,
Vishal Publishing Co. 2012.
Reference 2. J.C. Kuriacose and J. Rajaram, “Chemistry in Engineering and Technology”,
Tata McGraw-Hill, 2010.
Books rd
3. David Linden, “Hand Book of Batteries”, 3 Edition, McGraw Hill Publishers,
2000.
4. P.C. Jain and M. Jain, “Engineering Chemistry”, 15th Edition, Dhanpat Rai
Publishing Co., 2008.
Mode of Continuous Assessment (30%) and Assignments / Quizzes / Projects (20%)
Term End Examination (50%)
Evaluation
Syllabus for Lab: List of Experiments Volumetric Analysis 1. Estimation of total, permanent and temporary hardness of water by EDTA method. 2. Estimation of Copper (II) in ground water by EDTA method. 3. Estimation of alkalinity of water sample. 4. Estimation of Iron (II) in waste water by dichrometry. Instrumental Method of Analysis 1. Estimation of ferrous ion by potentiometric titration (redox titration). 2. Measurement of single electrode potential of various metals by potentiometry. 3. Estimation of Chemical Oxygen Demand (COD) of sewage water. 4. Determination of strength of strong acid and weak acid present in a mixture by conductometry. 5. Acid-base titration by pH metry 6. Preparation of Nylon 6,6 Evaluation: Continuous Assessment – 50 % & Term End Examination – 50%
Course L T P C
Code: ENVIRONMENTAL STUDIES 3 0 0 3
CHY 104
Course NONE
Prerequisites
1. To make students understand and appreciate the unity of life in all its forms,
the implications of life style on the environment.
Objectives: 2. To give students a basic understanding of the major causes of environmental
degradation on the planet, with specific reference to Indian situation.
3. To inspire students to find ways in which they can contribute personally and
professionally to prevent and rectify environmental problems
Students will be able to
understand the need for eco-balance
acquire the knowledge on the methods of pollution prevention
Expected The course also meets the following student outcomes:
a. An ability to apply knowledge of computing and mathematics appropriate to
Outcome:
the program’s student outcomes and to the discipline
e) An ability to identify, formulate and solve engineering problems.
h) An ability to address contemporary issues and analyze the local and global
impact of computing and engineering solutions on individuals,
organizations and society
Unit I Environment & Natural Resources
Definition, scope, importance; need for public awareness on natural resources –
Air, Water and Land. Forest resources – use, exploitation, causes and
consequences of deforestation. Water resources – use of surface and subsurface
water; dams - effect of (floods shifted to third unit under disaster management),
drought, water conflicts. Land resources – Land degradation, (landslides -shifted
to third unit under disaster management), soil erosion and desertification. Energy
resources – renewable and non- renewable sources. Indian Case studies for all the
resources.
Unit II Ecosystem & Bio-diversity
Concept of ecosystem - Structure and function of an ecosystem, producers,
consumers and decomposers, Food chains, food webs. Energy flow - ecological
pyramids and ecological succession. Bio diversity: Definition, levels of
biodiversity – genetic biodiversity – GM Crops. Species and ecosystem diversity
– values of biodiversity. Bio-geographical classification of India, hotspots, threats
to biodiversity - Case study. Conservation of bio-diversity
Unit III Environmental changes and remediation
Definition and Causes. Pollution effects and control measures of air, noise, water and soil. Thermal and nuclear hazards. Solid waste management: causes, effects and control measures of urban and industrial wastes. Case studies for all pollutions – Disaster management: Floods, earthquakes, cyclones, tsunami,
tornados and landslides – casestudies. Global climate change and greenhouse
effect – Kyoto Protocol, carbon credits, carbon sequestration, clean development
mechanisms. Ozone depletion problem – Montreal Protocol. Acid rain.
Unit IV Social Issues andthe Environment
Urban problems related to energy and sustainable development - Water
conservation, rain water harvesting, watershed management, problems related to
rehabilitation – case studies – Wasteland reclamation – Consumerism and waste
Mode of Continuous Assessment (30%) and Assignments / Quizzes / Projects (20%)
Term End Examination (50%)
Evaluation
Course Code GRAPH THEORY AND ITS APPLICATIONS L T P C MAT206 3 1 0 4 Course Theory of Computation
Prerequisites Objectives This subject aims to cover basic concepts of Graph theory
Expected Outcome On completion of the course, the students will be able to
Analyse and differentiate the fundamentals of Graph Theory and their
applications. This course meets the following student outcomes: b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution. e) An ability to identify, formulate and solve engineering problems. h) An ability to address contemporary issues and analyze the local and global impact of computing and engineering solutions on individuals, organizations and society i) Design and conduct experiments as well as analyze and interpret data. l) An ability to apply mathematical foundations, algorithmic principles and computer science theory in the modeling and design of computer-based systems (CS)
Unit 1 INTRODUCTION 9 hours Definitions, importance, isomorphism, walk, paths, circuits, connected, disconnected graphs, operati on on graphs operation on graphs, Euler and Hamiltonian graphs.
Unit 2 TREES 9 hours Properties, distance and centers, trees, spanning trees, fundamental circuits, minimal spanning tree , Cut sets Properties, fundamental circuits and cut sets, connectivity, separatability, network flows, 1-2 isomorphism ,Planar and dual graphs, Combinatorial representation, planar graphs, kuratowski’s graphs, detection of planarity, dual graphs. Unit 3 MATRIX REPRESENTATION OF GRAPHS 9 hours Incidence matrix, circuit matrix, cut set matrix, fundamental matrices, relationships amongst matric es, path matrix, and adjacency matrix. Unit 4 COLORING, COVERING AND PARTITIONING 9 hours Chromatic number, chromatic partitioning, matching, covering, four color problem
Unit 5 DIRECTED GRAPHS 9 hours Different types, directed paths and connectedness, Euler digraphs, trees-matrix representation, tournament. Graph theoretic algorithms , Computer representation of graphs – input & output, algorithms for connectedness, spanning tree, fundamental circuits, cut vertices, directed circuits and shortest paths. Text Books 1. Narasing Deo, Graph Theory with Application To Engineering And Computer
Science, Prentice Hall India, 2010. (Chapters 1, 2, 3, 4, 5, 7, 8, 9 and 11) 2. Tulasiraman and M.N.S. Swamy, Graph, Networks and Algorithms, John Wiley, 1981.
Course Code APPLIED PROBABILITY, STATISTICS AND L T P C MAT 207 RELIABILITY 3 1 0 4
Course Differential and Difference Equations
Prerequisites Objectives To provide principles of statistical methods and probability concepts that serves the
foundations for the applications of methods in their engineering works. Expected Outcome On completion of the course, the students will be able to
-Apply statistical methods and probability concepts in their engineering works This course meets the following student outcomes:
a) An ability to apply the knowledge of mathematics, science and computing appropriate to the discipline. e) An ability to identify, formulate and solve engineering problems. j) Recognition of the need for and an ability to engage in continuing professional learning (lifelong learning) l) An ability to apply mathematical foundations, algorithmic principles and computer science theory in the modeling and design of computer-based systems (CS)
Unit 1 History and Overview 9 + 3 hours Indicate some reasons for studying probability and statistics; Highlight some people that influenced or contributed to the area of probability and statistics; Indicate some important topic areas such as discrete probability, continuous probability, expectation, sampling, estimations, stochastic process, correlation, and regression; Describe the meaning of discrete probability; Describe the meaning of continuous probability; Contrast discrete from continuous probability; Provide a context for considering probabilistic expectation; Indicate the reason for using sampling distributions; Define a stochastic process; Mention the need for considering stochastic processes; Describe the need for probabilistic estimation in computer engineering; Highlight the importance of correlation; Provide examples for using regression; Explore some additional resources associated with probability and statistics; Explain the purpose and role of probability and statistics in computer engineering. Unit 2 Discrete Probability and Continuous Probability 9 + 3 hours Discrete probability: Randomness, finite probability space, probability measure, events; Conditional probability, independence, Bayes’ theorem; Discrete random variables; Binomial, Poisson, geometric distributions; Mean and variance: concepts, significance, computations, applications; Integer random variables. Continuous probability: Continuous random variables, the nature of these, illustrations of use; Exponential and normal distribution: probability density functions, calculation of mean and variance; the central limit theorem and the implications for the normal distribution; Joint distribution.
Unit 3 Expectation andStochastic Process 9 + 3 hours Expectation: Moments, transform methods, mean time to failure; Conditional expectation, examples; Imperfect fault coverage and reliability. Stochastic processes: Introduction: Bernoulli and Poisson processes, renewal process, renewal model of program behavior; Discrete parameter Markov chains: transition probabilities, limiting distributions; Queuing: M/M1 and M/G/1, birth and death process; Finite Markov chains, program execution times. Unit 4 Sampling Distributions & Estimation 9 + 3 hours Sampling distributions: Purpose and the nature of sampling, its uses and applications; Random approaches to
sampling: basic method, stratified sampling and variants thereof, cluster sampling; Non-random approaches: purposive methods, sequential sampling; Data analysis; tools; graphical and numerical summaries; Multivariate
distributions, independent random variables. Estimation: Nature of estimates: point estimates, interval estimates; Criteria to be applied to single point estimators: unbiased estimators, consistent estimators, efficiency and sufficiency of estimators; Maximum likelihood principle approach, least squares approach; applicability conditions for these; Confidence intervals; Estimates for one or two samples. Unit 5 Hypothesis tests, Correlation and Regression Hypothesis tests: Development of models and associated hypotheses, the nature of these; Hypothesis formulation: null and alternate hypotheses; Testing hypothesis based on a single parameter, choice of test statistic; choice of samples and distributions; Criteria for acceptance of hypothesis; t-test, chi-squared test; applicability criteria for these. Correlation and regression: The nature of correlation and regression, definitions; Definition and calculation of correlation coefficients; Approaches to correlation: the linear model approach, the least squares fitting approach, strengths and weaknesses of these and conditions for applicability. Text Books 1. Cornell, J.A.,, experiments with mixtures: Designs, Models and the Analysis of
2.
Mixture Data, 3rd Edition, John Wiley & Sons, Inc., New York
Blake, An Introduction to Applied Probability, John Wiley (2011)
3. S.M. Ross, Introduction to Probability Models, 6th edition
Reference Books 1. A M Yagolam, I.M. Yagolam Probability and Information, Hindustan Pub. Corp
(1983)
2. J. Jacob, P. Protter, Probability Essentials, Springer Verlag, 2 nd
Objectives: Can use the English language effectively with proper grammar and vocabulary to
suit the needs of the present world.
Can differentiate various forms of writing according to the situation and tone.
Can be aware of ‘cross cultural communication’
On completion of the course, the students will be able to
get the required training in LSRW through the prescribed texts.
This course needs the following student outcome::
Expected d)An ability to function effectively on multi disciplinary teams to accomplish a common
Outcome: goal. f) An understanding of professional, ethical, legal, security and social issues and responsibilities g) An ability to communicate effectively with a range of audiences. j) Recognition of the need for and an ability to engage in continuing professional learning (lifelong learning)
Unit I
Nature, process and barriers of communication Time, tense and tense consistency E-mail Etiquette Writing Effective Sentences-sentence coherence, length, avoiding ambiguity and thematic emphasis
Unit II
Use of voice (Impersonal passive) Writing formal letters (Call for quotations, Placing orders) Types of communication: Intra-personal, Interpersonal, Group-verbal and non-verbal communication
Unit III
Indian English Describing a process Writing Definitions Letter Writing-Letter of Complaint and Apology Concord
Unit IV
Cross-cultural Communication
Conditionals
Paragraph writing –Coherence- Jumbled Sentences
Paragraph: Definition. Identifying the Topic Sentence. Order (Examples,
Starting A Career –Making Goals And Setting Plans Unit No. 4 Interviews – Identifying Career Options, Preparing For An Interview , Facing An Interview
Evaluation Continuous Assessment (50%)
Term End Exam (50%)
Course code Basic French L T P C FRE101 2 0 0 2
Course Prerequisites: Nil Objectives: The course aims at basic written and oral skills (comprehension and expression)
in French which will enable the students to have higher education and job opportunities abroad. Expected Outcome: On completion of the course, the students will be able to
get the required training in the above mentioned language skills and they will also have the additional advantage of communicating in French which is the second most commonly used language worldwide.
This course needs the following student outcome:: d) An ability to function effectively on multi disciplinary teams to accomplish a common goal. g) An ability to communicate effectively with a range of audiences. Unit No. 1 Rencontres 6 hours Saluer, se présenter, demander, remercier, le genre des noms, les pronoms sujet et tonique, l’article défini et indéfini
Unit No. 2 Radio Belleville, j’adore 6 hours
Parler de ses gouts et de ses loisirs, poser des questions, décrire quelqu’un, les verbes au présent, la négation du verbe, le pluriel des noms, les adjectifs. Unit No. 3 C’est ma carte 6 hours
Demander/donner des informations sur une personne, parler de soi, de sa famille, comprendre et écrir e un mail, l’adjectif possessif, le verbe « aller », l’article contracte, c’est/ce sont.
Unit No. 4 Une radio, mais pourquoi ? 6 hours Nommer/situer un objet, exprimer la surprise, demander de faire quelque chose, exprimer une
obligation, l’adjectif interrogatif, les prepositions de lieu, la negation de l’article indefini, il faut…, pouvoir, vouloir
Unit 5 En Direct de Radio Belleville 6 hours Demander/dire l’heure, demander pourquoi et répondre, l’interrogation, faire, connaitre, l’accord de s
adjectifs en genre et en nombre, le pronom “on”. Text Books
Belleville 1, Méthode de français, Flore Cuny, Anne -Marie Johnson, CLE International, 2004 References
La France de toujours, Nelly Mauchamp; CLE international Déclic 1; Jacques Blanc, Jean-Michel Cartier, Pierre Lederlion; CLE International Champion 1 ; Annie Monnerie – Goarin, Evelyne Sirejols; CLE International Campus 1; Jacky Girardet, Jacques Pecheur; CLE International
Subject Title : Basic German L T P C Code: 2 0 0 2 GER101 Course Prerequisites Objectives The course aims at basic written and oral skills (comprehension and expression) in German
which will enable the students to have higher education and job opportunities in India and abroad. As a whole, it will bring an idea about the German culture and soci ety.
Expected get the required training in the above mentioned language skills and they will also Outcome have the additional advantage of communicating in French which is the second
most commonly used language worldwide.
This course needs the following student outcome:: d) An ability to function effectively on multi disciplinary teams to accomplish a common goal. g) An ability to communicate effectively with a range of audiences.
Unit 1 Lektion I 6 hours Personalpronomen, Konjugation von Verben: hei en, lernen, kommen,arbeiten, wohnen, machen. Unit 2 Lektion II 6 hours Possessivpronomen, Verb- Sein, Singular, Plural, Wortbildung, Ja/ Nein Frage und Fragewoerter, Tempus-Praesens, Dialoge, Imperativ. Unit 3 Lektion III 6 hours Bestimmter und Unbestimmter Artikel, Verb- Haben, Negation- Nicht, Kein, Zahlen, Partikeln, Maskulin, Feminin und Neutrum. Kasus – Nominativ und Akkusativ, Dialoge, Unit 4 Lektion IV 6 hours Die Zeit, Starke Verben, Praepositionen Fragewoerter (Zeitangabe), Das Essen und Leben in Deutschland, Landkarte und Geschichte von Deutschland. Unit 5 Lektion V 6 hours Trennbare Verben, Modal Verben, Dialoge mit Kontext: Bahnhof, Universitaet, Flughafen usw, Technische Woerter. Text Books Hieber Wolfgang, Lernziel Deutsch.München: 2005 Reference
Books 1. Gick, Cornelia, Momentmal, Grundstufenlehrwerk Deutsch als
Fremdsprache.M: 2003
2. Maria Dallapiazza, Eduard von Jan, Til Schonherr.Tangram, Deutsch als
Fremdsprache.Berlin: 2005
3. Griesbach, Schulz. Deutsche Sprachlehre für Ausländer. München: 2005
Subject Code: Title : Basic Japanese L T P C JAP 101 2 0 0 2 Course Prerequisites
Objectives get the required training in the above mentioned language skills and they will also have the additional advantage of communicating in French which is the second most commonly used language worldwide.
This course needs the following student outcome:: d) An ability to function effectively on multi disciplinary teams to accomplish a common goal. g) An ability to communicate effectively with a range of audiences. Unit 1 6 hours
1. Introduction to Japanese Alphabets 2. Vowels and Consonants 3. Hiragana, Katakana 4. Pronunciation 5. Writing practice 6. Japanese Numerals 7. Demonstrative pronoun
Kore, Sore, Are and Dore (This, That, Over there, which) Kono, sono, Ano and Dono (this, that, over there, which) Kochira, Sochira, Achira and Dochiora (this way....)
Koko, Soko, Asoko and Doko (Here, There….location) 8. Greetings
9. Classification of verbs (be verb desu (Present tense)
10. Part of body (look and learn)
11. Particle -Wa Unit 2 6 hours
1. Basic structure of sentence (Subject+ Object+ Verb) 2. Classification of verbs
a) Be verb desu Present and Present negative Past and Past negative b) Aru and Iru for living things and non living things c) Masu form (Present and Present negative)
3. Particle- Ka, Ni, Ga, 4. Conjunction-Ya 5. Grammar- ~ Go, ~Jin, San 6. Days/ Months /Year/Week (Current, Previous, Next, Next to Next) 7. Nation, People and Language 8. Classification of Adjectives
Unit 3 6 hours
1. Classification of Particle ( Ga, Ka, Wa, O, E, Ni, De, No, Kara, Made ) 2. Classification of Adjectives I and Na 3. Classification of verbs Go dan verb, Ichdan vers and Irregular verbs (Present, Present negative and past negative) 4. Classification of question words ( Doko, Dore, Dono, Dochira) 5. Time expressions (Jikan) 6. Number of hours 7. Vocabulary and its Meaning 8. Number of months, calendar of a month 9. Audio tape listening 10. Class tests Unit 4 6 hours
1. Classification of Question words (Dare, Nani, , Itsu, Doyatte, Doo, To, Ne, Yo, Ikutsu, Ikura)
2. Classification of Te forms 3. At the departmental store 4. At the Railway /Bus station 5. Polite form of verbs 6. At the hospital (Byoki) 7. Vocabulary and its Meaning 8. Audio tape listening 9. Class tests
Unit 5 6 hours
1. Words of degree (Gurai and Kurai) 2. Adverb (Mazu,Sore kara,Saigo ni )
3. Name of the things you carry (look and learn) 4. Relation ship of family (look and learn)
5. Visit a office and University 6. Set phrase – Onegaishimasu – Sumimasen
7. Positions and Direction 8. Vocabulary and its Meaning
9. Audio tape listening 10. Revision 11. Test
Text Books 1. Nihongo no KISO-1
2. Randan house Japanese-English-Japanese dictionary
3. Ootsubo et al, A course in Modern Japanese, Vol. 1, 1983, The
University of Nagoya Press, Japan.
4. Shiyo Suzuki and Ikuo kawase, Nihongo Shoho text book with
Audiotapes, 1981, The Japan Foundation, Tokyo, Japan.
5. Yan-san Serial, Video tapes, Japan.
6. Ooesto et a, A course in Modern Japanese, Vol. II, 1983, The
Subject code: Title : Basic Spanish L T P C ESP 101 2 0 0 2 Objectives: 1. The course aims at the development of the basic skills for
reading, writing and communicating in Spanish. 2. This will enhance the opportunity to have a good job and higher education abroad.
Expected Outcome: get the required training in the above mentioned language skills and they will also have the additional advantage of communicating in French which is the second most commonly used language worldwide.
This course needs the following student outcome:: d) An ability to function effectively on multi disciplinary teams to accomplish a common goal. g) An ability to communicate effectively with a range of audiences.
Unit No.1 Comunicación 6 El abecedario, Preguntas para comunicación(¿Cómo te llamas? , Etc.), pronunciación, deletrear las palabras, saludos y despedidas, días de la semana, meses del año Unit No.2 Verbos/Números/Nacionalidad 6 Verbos( infinitivo, regulares/irrgulares), conjugación, numeros(1 -100), país-nacionalidad, lengua, profesión, horarios Unit No.3 Gramática 6 El artículo, el pronombre, adjetivos( demostrativo, posesivo), género, singular -plural Unit No.4 Presentación 6Presentar (con los datos personales, nuestras familias, amigos etc.), relación, describir fisicament e, qué haces el fin de semana Unit No. 5 Compras/Comiendo-Bebiendo 6 Tiendas, compramos artículos( para comiendo y bebiendo), los cubiertos, una cita, dirección Text Books “Beginner’s Spanish”, Mark Stancey and Ángela González Hevia, The McGraw Hill, 2003. References
1. “BBC Spanish Grammar”, Martin, BBC Books 2. “Barron’s Complete Spanish”, Harvey and Harvers, Barron’s 3. “Schaum’s Outline of Spanish”, Conrad J. Schmitt, McGraw Hill 4. “Spanish Grammar in Context”, Juan Kattan- Ibarra and Angela Howkins, McGraw Hill, (Edition:2)
Continuous Assessment (30 %) and Assignments / Quizzes /
Evaluation Projects (20%) Term End Examination (50%)
Course Code:
ETHICS AND VALUES L T P C
HUM121 2 0 2 3
Course NONE
Prerequisites
Objectives: To understand the moral problems faced in the corporate setting and wider
philosophical frameworks along with social importance and their intellectual
challenges are given its due placement.
On completion of the course, the students will be able to
Solve the day-to-day problems and their allied alternative decision making
towards social impact.
Analyse and give solution to business environment.
Expected This course meets the following student outcomes:
Outcome: f) An understanding of professional, ethical, legal, security and social issues and
responsibilities
g) An ability to communicate effectively with a range of audiences.
h) An ability to address contemporary issues and analyze the local and global impact of
computing and engineering solutions on individuals, organizations and society
j)Recognition of the need for and an ability to engage in continuing professional learning
(lifelong learning)
Unit I Being good and responsible
Gandhian values such as truth and non-violence – comparative analysis on
leaders of past and present – society’s interests versus self interests – Prevention
of harassment, violence and terrorism - Personal Social Responsibility: Helping
of smoking-Prevention of suicides-Sexual Health:Prevention and impact of pre-
marital pregnancy and Sexually Trasmitted Diseases.
Unit IV Drug Abuse
Abuse of different types of legal and illegal drugs: ethical values, causes, impact,
laws
and prevention
Unit V Personal and Professional Ethics
Dishonesty - Stealing - Malpractices in Examinations - Plagiarism – Abuse of
technologies: Hacking and other Cyber Crimes, addiction to mobile phone usage,
video games and social networking websites
Text Books 1. Christine E. Gudorf, James Edward Huchingson, ‘Boundaries: A Casebook in
Environmental Ethics’, Georgetown University Press, 2010
1. Mike W Martin & Ronald Schnizinger, Engineering Ethics,,New Delhi: Tata
Reference McGraw Hill,Latest Edition
2.OC Ferrell, John Paul Frederich,Linda Ferrell; Business Ethics – Ethical
Books
Decision making and Cases- 2007 Edition, Biz Tantra, New Delhi
3. L.H. Newton & Catherine K.D., “Classic cases in Environmental Ethics”,
Belmont: California Wadsworth, 2006
Mode of Continuous Assessment (30%) and Assignments / Quizzes / Projects (20%)
Term End Examination (50%)
Evaluation
Computer Science & Engineering Core Courses
Course Syllabi
3.COMPUTER S CIENCE & ENGINEERING
Program Core
Course Code Course Title
CSE101 Computer Programming and Problem Solving
CSE103 Programming Fundamentals
CSE203 The Object Oriented Paradigm
CSE206 Object Oriented Programming Lab
CSE106 Digital Logic
CSE107 Digital Logic Laboratory
CSE204 Data Structures and Algorithms
CSE207 Data Structures and Algorithms Lab
CSE205 Computer Architecture and Organization
CSE202 Algorithm Design and Analysis
CSE305 Embedded Systems
CSE306 Embedded Systems Lab
CSE211 Operating Systems
CSE212 Operating Systems Lab
Computer Networks
CSE303
CSE304 Computer Networks Lab
CSE309 Programming Language Translators
CSE413 Computer Graphics
CSE312 Database Systems
CSE318
Database Systems Lab
CSE310 Software Engineering
CSE311 Software Engineering Lab
CSE307 Internet and Web Programming
CSE308 Internet and Web Programming lab
CSE213 Microprocessor and Interfacing
CSE214 Microprocessor and Interfacing Lab
ECE104 Discrete Time Systems and Processing
EEE101 Basic Electrical and Electronics Engineering
EEE103 Electronics
MEE437 Operations Research
MEE101 Engineering Graphics
MEE102 Workshop Practice
CSE498 Comprehensive Examination
CSE398 Mini Project
CSE399 Industrial Internship
CSE499 Project Work
Program Elective courses
Course Code Course Title
CSE302 Introduction to Artificial Intelligence
CSE404 Bio- informatics
CSE405 Parallel Algorithms
CSE406 Concurrent and Distributed Systems
CSE407 Software Practice and Testing
CSE408 Data Warehousing and Data Mining
CSE315 Scripting Languages
CSE403 Human Computer Interaction
CSE414 Multimedia Systems and Algorithms
CSE316 Database Design
CSE409 Modeling and Simulation
CSE410 Hardware Software Co-design
CSE411 Computer Organization and Design
CSE317 Data Communications
CSE412 Image Processing
CSE415 Information Security
CSE319 Soft Computing
CSE416 Cloud Computing
CSE320 Multi-core Systems Programming
CSE215 C++ Programming
Course code COMPUTER PROGRAMMING L T P C CSE101 AND PROBLEM SOLVING 2 0 2 3
Course Prerequisites: Nil Objectives: To provide an overview of computer algorithms and problem solving
techniques To introduce ‘C’ Language that serves as a foundation for the study of different programming languages. Expected Outcome: On completion of the course, the students will be able to
Apply the fundamental knowledge of computing algorithms appropriate to the problems Analyze and design problems using various problems solving techniques Formulate and solve computing problems using C programming language. Apply algorithmic principles and current techniques for computing and engineering practice. This course meets the following student outcomes:
a) An ability to apply the knowledge of mathematics, science and computing appropriate to the discipline. b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution. e) An ability to identify, formulate and solve engineering problems. i) Design and conduct experiments as well as analyze and interpret data. k) An ability to use current techniques, skills and tools necessary for computing and engineering practice. l) An ability to apply mathematical foundations, algorithmic principles and computer science theory in the modeling and design of computer- based systems (CS) Unit No. 1 INTRODUCTION TO COMPUTERS 6 hours
AND ALGORITHMS Parts of a computer – Overview of operating systems, compilers, interpreters and programming languages. Algorithms for exchanging the values of two variables, counting, summation of a set of numbers, factorial computation, sine function computation, generation of the Fibonacci sequence, reversing the digits of an integer, base conversion and character to number conversion.
Unit No. 2 CONSTRUCTS OF C 7 hours Lexical elements – Operators - data types – I/O statements – format specifications – control statements – decision making and looping. Unit No. 3 ARRAYS 8 hours Array handling in C – declaration – single dimensional arrays, two – dimensional arrays, multi- dimensional arrays, sorting and searching on single and two dimensional arrays. Array order reversal, array counting or histogramming, finding the maximum number in a set, removal of duplicates from an ordered array, partition an array, finding the kth-smallest element strings: Character array – string handling functions – manipulation on strings. Unit No. 4 FUNCTIONS 5 hours
Prototype – declaration - arguments (formal and actual) – return types – types of functions difference between built-in and user-defined functions. Unit No.5 STRUCTURES 4 hours Declarations - nested structures- array of structures - structure to functions - unions- difference between structure and union Text / Reference Books
1. Dromey R.G., “How to Solve it by Computer”, Pearson Education, Fourth Reprint, 2008. 2. Yashavant P. Kanetkar. “Let Us C”, BPB Publications, 2011. 3. Anita Goel and Ajay Mittal, “Computer Fundamentals and Programming in C”, Dorling Kindersley (India) Pvt. Ltd., Pearson Education in South Asia, 2011. 4. Alexis Leon; Mathews Leon, Fundamentals of Information Technology, 2/e, Vikas publishing
List of Experiments 1. Programs using only I/O Functions
2. Programs to study operators and data types
3. Programs based on control Structures (IF, SWITCH CASE)
4. Programs using For and While loops
5. Programs using single dimensional arrays
6. Programs using multi Dimensional arrays
7. Programs on Sorting and searching using arrays
8. Programs based on string Manipulations
9. Programs based on User defined function programs
10. Programs using Functions with parameters
11. Program using storage classes
12. Programs to introduce pointers
13. Programs using structures
14. Programs using array of structures
Evaluation: Continuous Assessment – 50 % & Term End Examination – 50%
Course Code PROGRAMMING FUNDAMENTALS L T P C
CSE103 3 0 0 3
Course Computer Programming and Problem Solving
Prerequisites
Objectives 1. To help the students understand the fundamental concepts of programming
2.
Languages.
To prepare students about the need and use of data structures
3. To prepare students to identify and apply data structures for problem solving.
Expected On completion of the course, the students will be able to
Outcome 1.
Understand and apply the programming constructs of various languages suitably.
2. Apply the fundamental data structures to analyze, design, implement and solve
1.
engineering problems.
Improve the problem solving skill using the learnt algorithmic, data structure
principles, tools and techniques.
This course meets the following student outcomes:
a) An ability to apply the knowledge of mathematics, science and computing appropriate
to the discipline.
b) An ability to analyze a problem, identify and define the computing requirements
appropriate to its solution.
e) An ability to identify, formulate and solve engineering problems.
i) Design and conduct experiments as well as analyze and interpret data.
k) An ability to use current techniques, skills and tools necessary for computing and
engineering practice.
l) An ability to apply mathematical foundations, algorithmic principles and computer
science theory in the modeling and design of computer-based systems (CS)
Unit 1 FUNDAMENTAL PROGRAMMING CONSTRUCTS 9 hours
1. Basic syntax and semantics of a higher-level language, Variables, types, expressions, and assignment, Simple I/O, Conditional and iterative control structures, Functions and parameter passing, structured decomposition.
Unit 2 ALGORITHMS AND PROBLEM-SOLVING 9 hours Problem-solving strategies, Role of algorithms in the problem -solving process, Implementation strategies for algorithms, Debugging strategies, The concept and properties of algorithms. Unit 3 FUNDAMENTAL DATA STRUCTURES 9 hours Primitive types, Arrays, Records, Strings and string processing, Data representation in memory, Static, stack, and heap allocation, Runtime storage management, Pointers and references, Linked structures, Implementation strategies for stacks, queues, and hash tables, Strategies for choosing the right data structure. Unit 4 RECURSION 9 hours The concept of recursion, Recursive mathematical functions, Simple recursive procedures, Divide -and-conquer strategies, Recursive backtracking, Implementation of recursion Unit 5 EVENT-DRIVEN PROGRAMMING 9 Hours
Event-handling methods, Event propagation, Exception handling.
Text Books 1. S. Sahni, Data structures, algorithms, & applications in C++, 2 nd
Edition, 2005,
2.
Tata McGraw-Hill.
R.W. Sebasta , Concepts of Programming Languages, 10th Edition, Addison
Wesley, 2012
Reference Books 1. Jeri R. Hanly, Elliot B. Koffman, Problem Solving and Program Design in C,
2.
7th
Edition, 2012, Prentice-Hall
Jean-Paul Tremblay, Paul G. Sorenson, An Introduction to Data Structures
Course Code THE OBJECT-ORIENTED PARADIGM L T P C CSE203 3 1 0 4 Course Programming Fundamentals
Prerequisites Objectives 1. To understanding the principles of object oriented programming
2. To introduce the object oriented way of problem solving. 3. To gain familiarity with the syntax, class hierarchy, environment and simple
application construction for an object-oriented programming language Expected On completion of the course, the students will be able to Outcome 1. Acquire a full Object Oriented perspective for analyzing, defining, implementing and
evaluating real world problems. 2. Apply and use the object oriented concepts/ techniques, tools in modeling computer
based/ software system This course meets the following student outcomes: b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution. c) An ability to design, implement and evaluate a system / computer based system process, component or program to meet desired needs i) Design and conduct experiments as well as analyze and interpret data. k) An ability to use current techniques, skills and tools necessary for computing and engineering practice. l) An ability to apply mathematical foundations, algorithmic principles and computer science theory in the modeling and design of computer-based systems (CS) m) An ability to apply design and development principles in the construction of software systems. (CS)
Unit 1 INTRODUCTION TO FUNDAMENTAL CONCEPTS OF OOP 9 +3 hours Survey of programming paradigms – Object-Oriented Paradigm: Elements of Object Oriented Programming – Merits and demerits of object oriented methodology. benefits of object oriented programming - structure of C++ program– Static members, Working with classes, Classes and Objects-Class specification- class objects-accessing class members- defining member functions - Passing and returning objects – Array of objects - inline functions - accessing member functions within class. Unit 2 OBJECT INITIALIZATION AND CLEANUP 9 +3 hours
Constructors - Parameterized constructors - Constructor overloading. Copy constructor, Destructors, Default arguments - new, delete operators - “this” pointer, friend classes and friend functions. Unit 3 OVERLOADING AND GENERIC PROGRAMMING 9 +3 hours Function overloading – Operator overloading- Non-over loadable operators- unary operator overloading- operator keyword- limitations of increment/decrement operators- binary operator overloading- Generic programming with templates-Function templates- class templates Unit 4 INHERITANCE 9 +3hours
Inheritance-Base class and derived class relationship-derived class declaration-Forms of
inheritance- inheritance and member accessibility- constructors in derived class,
abstract class, virtual functions, pure virtual function.
Unit 5 EXCEPTION HANDLING AND STREAMS 9 +3 hours
Files and Streams-Opening and Closing a file- file modes- file pointers and their manipulation, sequential access
to a file-random access to a file-Reading and Writing – Exception handling.
Text / Reference 1. 1. K. R. Venugopal, Rajkumar, T. Ra vishankar, Mastering C++, 4th
Books
Edition, Tata McGraw
2. Hill, 2008 3. 2. Budd T., An Introduction to Object-oriented Programming,
Addison-Wesley 3rd 4. edition, 2008. 5. 3. Bjarne stroustrup, The C++ programming Language,
Addison Wesley, 3rd edition, 6. 2008. 7. 4. Harvey M. Deitel and Paul J. Deitel, C++ How to Program,
Course Code OBJECT-ORIENTED PROGRAMMING LAB L T P C CSE206 0 0 3 2 Course Programming Fundamentals
Prerequisites Objectives To understand the use of object oriented way of problem solving
To prepare the student to write programs in C++ to solve the problems Expected On completion of the course, the students will be able to
Outcome 1. Improve their programming skill for solving engineering problems through object oriented analysis, design, implementation and evaluation. 2. Apply the object oriented principles for modeling and developing software system This course meets the following student outcomes: b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution. c) An ability to design, implement and evaluate a system / computer based system process, component or program to meet desired needs e) An ability to identify, formulate and solve engineering problems. i) Design and conduct experiments as well as analyze and interpret data. l) An ability to apply mathematical foundations, algorithmic principles and computer science theory in the modeling and design of computer-based systems (CS) m) An ability to apply design and development principles in the construction of software systems. (CS) List of Experiments 1. Program illustrating function overloading feature. 2. Programs illustrating the overloading of various operators
Ex : Binary operators, Unary operators, New and delete operators etc. 3. Programs illustrating the use of following functions :
a) Friend functions b) Inline functions c) Static Member functions d) Functions with default arguments.
4. Programs illustrating the use of destructor and the various types of constructors (no arguments, constructor, constructor with arguments, copy constructor etc).
5. Programs illustrating the various forms of inheritance: Ex. Single, Multiple, multilevel, hierarchical inheritance etc.
6. Write a program having student as on abstract class and create many derived classes such as Engg. Science, Medical, etc. from students class. Create their objects and process them.
7. Write a program illustrating the use of virtual functions. 8. Write a program which illustrates the use of virtual base class. 9. Write programs to illustrating file handling operations:
Ex. a) Copying a text files b) Displaying the contents of the file etc. 10. Write programs illustrating how exceptions are handled (ex: division-by-zero, overflow and underflow in stack etc)
Evaluation Continuous Assessment (50 %)
Term End Examination (50%)
Course Code DIGITAL LOGIC L T P C CSE106 3 0 0 3 Course Computer Programming and Problem Solving
Prerequisites Objectives 1. To impart the knowledge of digital logic fundamentals involving flip-flops,
registers etc., to design simple computer based system. 2. To understand the principles of Boolean laws, Boolean algebra, Boolean logic, logic gate, flip-flop, shift register, arithmetic and Logic unit for designing computer based system 3. To understand the memory representation in ROM, RAM and CPU.
Expected On completion of the course, the students will be able to Outcome 1. Apply fundamental knowledge of combinational, sequential circuits to design and
analyze the functions of various hardware components for solving engineering problems. 3. Model / develop a computer based systems with the fundamentals of digital theory. This course meets the following student outcomes: a) An ability to apply the knowledge of mathematics, science and computing appropriate to the discipline. b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution. c) An ability to design, implement and evaluate a system / computer based system process, component or program to meet desired needs e) An ability to identify, formulate and solve engineering problems. i) Design and conduct experiments as well as analyze and interpret data. l) An ability to apply mathematical foundations, algorithmic principles and computer science theory in the modeling and design of computer-based systems (CS)
Unit 1 NUMBER SYSTEM AND BOOLEAN ALGEBRA 9 hours Number System – Converting numbers from one base to another – Complements – Binary Codes – Integrated Circuits – representation and manipulation of switching circuits – Boolean algebra – Properties of Boolean algebra – Boolean functions – Canonical and Standard forms – Logic operations – Logic gates – Physical properties of logic gates (technology, fan-in, fan-out, propagation delay) – Karnough Map up to 6 variables – Don't Care Condition – Sum of Products and Products of sum simplification – Tabulation Method. Unit 2 COMBINATIONAL CIRCUITS 9 hours Adder – Subtractor – Code Converter – Analyzing a Combinational Circuit – Multilevel NAND and NOR circuits – Properties of XOR and equivalence function – Binary Parallel Adder – Decimal Adder – Magnitude Comparator – Decoders – Multiplexers – ROM – PLA. Unit 3 SEQUENTIAL CIRCUITS 9 hours Flip Flops – Triggering of flip–flops – Analyzing a sequential circuit – State reduction – Excitation tables – Design of sequential circuits – Counters – Design with state equation – Registers – Shift Registers – Ripple and Synchronous Counters, Timing sequences – Johnson counters.
Unit 4 ARITHMETIC LOGIC UNIT 9 hours Memory Unit – Bus Organization – Scratch Pad Memory – ALU – Design of ALU – Status Register – Effects of Output carry – Design of Shifter – Processor Unit – Microprogramming – Design of specific Arithmetic Circuits. Unit 5 COMPUTER DESIGN 9 hours Accumulator – Design of Accumulator – Computer Configuration – Instructions and Data formats – Instruction sets – Timing and control – Execution of Instruction – Design of Computer – H/W Control – PLA control and Microprogram control.
Text / Reference 1. M. Morris Mano – Digital Logic and Computer Design PHI – 5 th
Books 2.
Edition- 2007.
A.D.Friedman, Fundamentals of Logic Design and switching
3.
Theory, Computer Science Press, 1986
A.P. Malvino and D.P. Leach – Digital Principles and Applications
4.
– Tata McGraw Hill, 7th Edition – 2010.
Thomas Floyd – Fundamentals of Digital System – Pearson
Course Code DIGITAL LOGIC LABORATORY L T P C CSE107 0 0 3 2 Course Computer Programming and Problem Solving
Prerequisites Objectives 1. To demonstrate the functioning of logic gates
2. To design and implement combination and sequential circuits Expected On completion of the course, the students will be able to
Outcome 1. Demonstrate the combinational, sequential circuits to design and analyze the functions of various hardware components for solving engineering problems. 2. Apply fundamentals of digital theory in modeling / developing small digital applications.
This course meets the following student outcomes: b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution. c) An ability to design, implement and evaluate a system / computer based system process, component or program to meet desired needs d) An ability to function effectively on multi disciplinary teams to accomplish a common goal. e) An ability to identify, formulate and solve engineering problems. i) Design and conduct experiments as well as analyze and interpret data. l) An ability to apply mathematical foundations, algorithmic principles and computer science theory in the modeling and design of computer-based systems (CS) List of Experiments
Study of Logic Gates. a. Logic gates using discrete Components. b. Verification of truth table for AND, OR, NOT, NAND, NOR and XOR gates. c. Realization of NAND and NOR gates
Implementation of Logic Circuits. d. Verification of Boolean laws. e. Verification of DeMorgan’s
law Adder and Subtractor f. Implementation of Half-Adder and Full-Adder g. Implementation of Half-Subtractor and Full-
Subtractor Combinational Circuit Design h. Design of Decoder and Encoder i. Design of Code Converter. j. Design of multiplexers and de
multiplexers. Sequential Circuit Design k. Implementation of Shift registers, Serial Transfer. l. Ring Counter m. 4-bit Binary Counter n. BCD Counter.
Continuous Assessment (50 %) Term End Examination (50%)
Evaluation
Course Code DATA STRUCTURES AND ALGORITHMS L T P C CSE204 3 1 0 4 Course Programming Fundamentals
Prerequisites Objectives 1. To understand various types of fundamental data structures (standard and user
defined). 2. To learn about algorithm analysis for the run time complexities and the space
requirements. 3. To acquire knowledge of data structures and algorithms for implementing
various computing system Expected On completion of the course, the students will be able to Outcome 1. Apply the fundamental knowledge of various data structures and algorithms to analyze, design, formulate and implement algorithm for any real time problem.
2. Apply current techniques in data structures and algorithmic principles for modeling and developing software systems
This course meets the following student outcomes: a) An ability to apply the knowledge of mathematics, science and computing appropriate to the discipline. b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution. i) Design and conduct experiments as well as analyze and interpret data. k) An ability to use current techniques, skills and tools necessary for computing and engineering practice. l) An ability to apply mathematical foundations, algorithmic principles and computer science theory in the modeling and design of computer-based systems (CS) m) An ability to apply design and development principles in the construction of software systems. (CS)
Unit 1 BASIC ALGORITHMIC ANALYSIS 9 + 3 hours Asymptotic analysis of upper and average complexity bounds; Identifying differences among best, aver age, and worst case behaviors; Big O, little o, omega, and theta notation; Standard complexity classes; Empirical measurements of performance; Time and space tradeoffs in algorithms; Using recurrence relations to analyze recursive algorithms Unit 2 ALGORITHMIC STRATEGIES 9 + 3 hours Brute-force algorithms; Greedy algorithms; Divide-and-conquer; Backtracking; Branch-and-bound; Heuristics; Pattern matching and string/text algorithms; Numerical approximation algorithms Unit 3 FUNDAMENTAL COMPUTING 9 + 3 hours
ALGORITHMS Simple numerical algorithms, Sorting and Searching Algorithm: Sequential and binary search algorithms; Quadratic sorting algorithms (bubble, selection, insertion); O (N log N) sorting algorithms (Quick sort, heap sort); Hashing: Hash tables, including collision-avoidance strategies; Unit 4 DATA STRUCTURES & 9 + 3 hours
ALGORITHMS Non-Linear Data Structures: Binary trees; Binary Search Trees; General Tree;
Unit 5 GRAPHS 9 + 3 hours Representations of graphs (adjacency list, adjacency matrix, Sparse Matrix); Topological Sorting; Sh ortest-path algorithms (Single source shortest path; Dijkstra’s and Floyd’s algorithms); Minimum spanning tree (Prim’s and Kruskal’s algorithms);
Text / Reference 1. S. Sahni, Data structures, algorithms, & applications in Java,
Books McGraw-Hill, 2005
2. J. P. Trembly et al, An introduction to data structures with
applications, McGraw- Hill, 2007
3. D. E. Knuth, Art of computer programming, Volume 1: Fundamental
algorithms, Addison-Wesley.2011
4. Thomas H. Cormen , Charles E. Leiserson , Ronald L.
Rivest , Clifford Stein, Introduction to Algorithms, 3 rd
Course Code DATA STRUCTURES AND ALGORITHMS LAB L T P C CSE207 0 0 3 2 Course Programming Fundamentals
Prerequisites Objectives 1. To understand and implement simple data structures.
2. To demonstrate different sorting and searching techniques. 3. To familiarize graphs and their applications
Expected On completion of the course, the students will be able to
Outcome 1. Identify, implement and use the appropriate data structures for a given problem 2. Apply algorithmic skills for computing and engineering practice. 3. Apply design and development principles of data structures and algorithms in the construction of software systems. This course meets the following student outcomes: b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution. c) An ability to design, implement and evaluate a system / computer based system process, component or program to meet desired needs i) Design and conduct experiments as well as analyze and interpret data. k) An ability to use current techniques, skills and tools necessary for computing and engineering practice. l) An ability to apply mathematical foundations, algorithmic principles and computer science theory in the modeling and design of computer-based systems (CS) m) An ability to apply design and development principles in the construction of software systems. (CS)
List of Experiments Implementing Stacks and queues. Implementation and processing in lists. Sorting:
a. Insertion sort b. Merge sort c.Quick sort d. Selection sort e. Heap sort f.Shell sort Searching:
a. Linear search b. Binary search
Binary Search Trees Graphs:
a. BFS b. DFS c. Topological Sort
Spanning Trees a. Prim’s Algorithm b. Kruskal’s Algorithm
Shortest Path Algorithms a. Dijkstra’s Algorithm ; Floyd’s Algorithm
Evaluation Continuous Assessment (50 %)
Term End Examination (50%)
Course Code COMPUTER ARCHITECTURE AND L T P C CSE205 ORGANIZATION 3 0 0 3 Course Digital Logic and its lab
Prerequisites Objectives To Gain an understanding of computer data representation and manipulation
To understand the basic organization for data storage and access across various media. To provide knowledge of interfacing techniques and subsystem devices.
Expected On completion of the course, the students will be able to
Outcome 1. Understand and apply number systems, instruction sets, addressing modes, and data/instruction formats for designing and implementing computer based system.
2. Write program using assembly language programming for computing and engineering practice.
3. Apply the digital principles in modeling and designing of computer based systems.
This course meets the following student outcomes: a) An ability to apply the knowledge of mathematics, science and computing appropriate to the discipline. b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution. e) An ability to identify, formulate and solve engineering problems. i) Design and conduct experiments as well as analyze and interpret data. k) An ability to use current techniques, skills and tools necessary for computing and engineering practice. l) An ability to apply mathematical foundations, algorithmic principles and computer science theory in the modeling and design of computer-based systems (CS)
Unit 1 FUNDAMENTALS OF COMPUTER 9 hours ARCHITECTURE
Organization of the von Neumann machine; Instruction formats; The fetch/execute cycle, instruction d ecoding and execution; Registers and register files; Instruction types and addressing modes; Subroutine call and return mechanisms; Programming in assembly language; I/O techniques and interrupts; Other design issues.
9 hours Data Representation, Hardware and software implementation of arithmetic unit for common arithmetic operations: addition, subtraction, multiplication, division( Fixed point and floating point); Conversion between integer and real numbers; The generation of higher order functions from square roots to transcendental functions; Representation of non-numeric data (character codes, graphical data) Unit 3 MEMORY SYSTEM ORGANIZATION 9 hours
AND ARCHITECTURE Memory systems hierarchy; Coding, data compression, and data integrity; Electronic, magnetic and optical technologies; Main memory organization, Types of Main memories, and its characteristics and performance; Latency, cycle time, bandwidth, and interleaving; Cache memories (address mapping, line size, replacement and write-back policies); Virtual memory systems; Reliability of memory systems; error detecting and error correcting systems. Unit 4 INTERFACING AND 9 hours
COMMUNICATION I/O fundamentals: handshaking, buffering; I/O techniques: programmed I/O, interrupt -driven I/O, DMA; Interrupt structures: vectored and prioritized, interrupt overhead, interrupts and reentrant code; Buses: bus protocols, local and geographic arbitration.
Unit 2 COMPUTER ARITHMETIC
Unit 5 DEVICE SUBSYSTEMS 9 hours External storage systems; organization and structure of disk drives and optical memory; Basic I/O controllers such as a keyboard and a mouse; RAID architectures; Video control; I/O Performance; SMART technology and fault detection; Processor to network interfaces. Text / Reference 1. J. L. Hennessy & D.A. Patterson, Computer architecture: A
Books 2.
quantitative approach, Fifth Edition, Morgan Kaufman, 2011.
W. Stallings, Computer organization and architecture, Prentice-Hall,
2012
3. M. M. Mano, Computer System Architecture, 3rd
Edition,1992,
Prentice-Hall
4. J. P. Hayes, Computer system architecture, 3 rd
Course Code ALGORITHM DESIGN AND ANALYSIS L T P C CSE202 3 0 0 3 Course Data Structures and Algorithms
Prerequisites Objectives a. To provide the knowledge about the methods of advanced algorithms
b. To understand the advanced algorithms such as cryptographic algorithms, Geometric Algorithm and Parallel Algorithm
Expected On completion of the course, the students will be able to
Outcome 1. Apply the algorithm design techniques to analyze, solve and evaluate computing problems.
2. Apply algorithmic principles in modeling and designing software systems
This course meets the following student outcomes: a) An ability to apply the knowledge of mathematics, science and computing appropriate to the discipline. b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution. e) An ability to identify, formulate and solve engineering problems. i) Design and conduct experiments as well as analyze and interpret data. k) An ability to use current techniques, skills and tools necessary for computing and engineering practice. l) An ability to apply mathematical foundations, algorithmic principles and computer science theory in the modeling and design of computer-based systems (CS)
Unit 1 BASIC COMPUTABILITY 9 hours
Finite-state machines; Context-free grammars; Tractable and intractable problems; Uncomputable functions; the halting problem; Implications of uncomputability. THE COMPLEXITY CLASSES P AND NP: Definition of the classes P and NP; NP-completeness (Cook’s theorem); Standard NP-complete problems; Reduction techniques. Unit 2 ADVANCED ALGORITHMIC 9 hours
ANALYSIS Amortized analysis; Online and offline algorithms; Randomized algorithms; Dynamic programming; combinatorial optimization. Unit 3 GEOMETRIC ALGORITHMS 9 hours
Line segments: properties, intersections; convex hull finding algorithms
Unit 4 PARALLEL and Distributed 9 hours
ALGORITHMS
PRAM model; Exclusive versus concurrent reads and writes; Pointer jumping; Brent’s theorem and work
efficiency.
Unit 5 DISTRIBUTED ALGORITHMS 9 hours
Consensus and election; Termination detection; Fault tolerance; Stabilization.
Text / 1. Aho et al, The design and analysis of computer algorithms, 1974, Addision Wesley.
Reference 2. M. J. Quinn, Parallel computing – theory and practice, 2002, McGraw Hill.
Books 3. M. J. Quinn, Designing efficient algorithms for parallel computers, McGraw Hill.
4. ParagH.Deve, HimanshuB. Dave“ Design and Analysis of
Course Code EMBEDDED SYSTEMS L T P C CSE305 3 0 0 3 Course Microprocessor and Interfacing and its Lab
Prerequisites Objectives 1. To provide an insight into the fundamentals of embedded system
2. To understand programs and tools for embedded system. 3. To gain knowledge about real time operating system 4. To elucidate knowledge of embedded system types and its interfacing mechanisms
Expected On completion of the course, the students will be able to Outcome 1. Design and evaluate embedded based system.
2. Recognize the need for embedded system and to engage in continuous updation of embedded real time systems
3. Apply current techniques and tools of embedded system in modeling and designing computer based system.
This course meets the following student outcomes: c) An ability to design, implement and evaluate a system / computer based system process, component or program to meet desired needs e) An ability to identify, formulate and solve engineering problems. j) Recognition of the need for and an ability to engage in continuing professional learning (lifelong learning) k) An ability to use current techniques, skills and tools necessary for computing and engineering practice. l) An ability to apply mathematical foundations, algorithmic principles and computer science theory in the modeling and design of computer-based systems (CS)
Unit 1 EMBEDDED MICROCONTROLLERS 9 hours
Introduction: Contrast between an embedded system and other computer systems; the role of programming and its associated languages as applied to embedded systems; the purpose and role of embedded systems in computer engineering. Microcontrollers: Structure of a basic computer system: CPU, memory, I/O devices on a bus; CPU families used in microcontrollers: 4-bit, 8-bit, 16-32-bit; Basic I/O devices: timers/counters, GPIO, A/D, D/A; Polled I/O vs. interrupt-driven I/O; Interrupt structures: vectored and prioritized interrupts; DMA transfers; Memory management units; Memory hierarchies and caches. Unit 2 EMBEDDEDPROGRAMSAND 9 hours TOOLS
The program translation process: compilation, assembly, linking; Representations of programs: data f low and control flow; Fundamental concepts of assembly language and linking: labels, address management; Compilation tasks: mapping variables to memory, managing data structures, translating control structures, and translating expressions; What can and cannot be controlled through the compiler; when writing assembly language makes sense. Tool support: Compilers and programming environments; Logic analyzers; RTOS tools; Power analysis; Software management tools; Project management tools.
Unit 3 REAL-TIME OPERATING SYSTEMS 9 hours Real-time operating systems: Context switching mechanisms; Scheduling policies; Rate- monotonic scheduling: theory and practice; Priority inversion; other scheduling policies such as EDF; Message-passing vs. shared memory communication; Interprocess communication styles such as mailbox and RPC; Low-power computing:
Sources of energy consumption: toggling, leakage; Instruction-level strategies for power management: function unit management; Memory system power consumption: caches, off-chip memory; Power
consumption with multiple processes; System-level power management: deterministic, probabilistic methods. Unit 4 NETWORKED EMBEDDED SYSTEMS 9 hours Why networked embedded systems; Example networked embedded systems: automobiles, factory automation systems; The OSI reference model; Types of network fabrics; Network performance analysis; Basic principles of the Internet protocol; Internet-enabled embedded systems; Controller Area Network; Embedded Ethernet Controller; Inter Integrated Circuits(I
2C)
Unit 5 INTERFACING AND MIXED-SIGNAL 9 hours SYSTEMS
Digital-to-analog conversion; Analog-to-digital conversion; How to partition analog/digital processing in interfaces; Digital processing and real-time considerations. ARM Controllers; Text / Reference 1. Wayner Wolf, Computers as components – Principles of
Books 2.
embedded computing system design, Morgan Kaufman, 2012
Rajkamal, “Embedded Systems-Architecture,
3.
Programming,Design”, Tata McGraw Hill, 2011
Arnold S. Berger, “Embedded Systems Design”, CMP Books,
Objectives 1. To realize the importance of microcontroller programming
2. To write, assemble, link, execute, and debug programs running on a single board
microcomputer.
3. To Interface the single board microcomputer to a variety of peripheral devices
using serial and parallel communications.
Expected On completion of the course, the students will be able to
Outcome 1. Understand and implement microcontroller programming to solve engineering
problems.
2. Design and conduct experiments of interfacing different hardware with single
board microcomputer
3. Use current principles of embedded system to design and model simple embedded
system.
This course meets the following student outcomes:
b) An ability to analyze a problem, identify and define the computing requirements
appropriate to its solution.
c) An ability to design, implement and evaluate a system / computer based system
process, component or program to meet desired needs
e) An ability to identify, formulate and solve engineering problems.
i) Design and conduct experiments as well as analyze and interpret data
k) An ability to use current techniques, skills and tools necessary for computing and
engineering practice.
m) An ability to apply design and development principles in the construction of software
systems. (CS)
List of Experiments
Programming in 8051
Handling Port
Waveform generation
ADC; DAC
Interrupt Programming
Stepper Motor Interfacing
Evaluation Continuous Assessment (50 %)
Term End Examination (50%)
Course Code OPERATING SYSTEMS L T P C
CSE211 3 0 0 3
Course Computer Architecture and Organization
Prerequisites
Objectives 1. To provide a grand tour of the major operating system components.
2. To gain knowledge in process, memory and device management
3. To understand security issues related to OS.
Expected On completion of the course, the students will be able to
Outcome 1. Understand and apply the concepts of CPU scheduling, synchronization and
2.
deadlocks in real computing problems.
Analyze and investigate the local and global impacts of operating systems in
3.
developing any computer based applications.
Suggest appropriate file system and disk organizations for a variety of
4.
computing scenario.
Evaluate security mechanisms in operating computing systems
This course meets the following student outcomes: a) An ability to apply the knowledge of mathematics, science and computing appropriate to the discipline. h) An ability to address contemporary issues and analyze the local and global impact of computing and engineering solutions on individuals, organizations and society k) An ability to use current techniques, skills and tools necessary for computing and engineering practice. l) An ability to apply mathematical foundations, algorithmic principles and computer science theory in the modeling and design of computer-based systems (CS)
Unit 1 FUNDAMENTALS 9 hours
FUNDAMENTALS Overview: Role and purpose of operating systems; history of operating system development; functionality of a typical operating system; design issues (efficiency, robustness, flexibility, portability, security, compatibility). Basic principles: Structuring methods; abstractions, processes, and resources; design of application programming interfaces (APIs); device organization; interrupts; user/system state transitions. Unit 2 PROCESS MANAGEMENT 9 hours Scheduling: Preemptive and non- preemptive scheduling; scheduling policies; processes and threads; real -time issues; Concurrency: The idea of concurrent execution; states and state diagrams; implementation structures (ready lists, process control blocks, and so forth); dispatching and context switching; interrupt handling in a concurrent environment; Mutual exclusion: Definition of the “mutual exclusion” problem; deadlock detection and prevention; solution strategies; models and mechanisms (semaphores, monitors, condition variables, rendezvous); producer-consumer problems; synchronization; multiprocessor issues Unit 3 MEMORY MANAGEMENT 9 hours Review of physical memory and memory management hardware; overlays, swapping, and partitions; paging and segmentation; page placement and replacement policies; working sets and thrashing; caching. Unit 4 SECONDARY STORAGE 9 hours MANAGEMENT Device management: Characteristics of serial and parallel devices; abstracting device differences; buffering strategies; direct memory access; recovery from failures. File systems: Fundamental concepts (data, metadata, operations, organization, buffering, sequential vs. nonsequential files); content and structure of directories; file system techniques (partitioning, mounting and unmounting, virtual file systems); memory-mapped files; special-purpose file systems; naming, searching, and access; backup strategies.
Unit 5 SECURITY AND PROTECTION 9 hours Overview of system security; policy/mechanism separation; security methods and devices; protection, access, and authentication; models of protection; memory protection; encryption; recovery management. Text / Reference 1. Silberschatz, P.B. Galvin & G. Gagne, Operating
Books 2.
system concepts, John Wiley,9th
Edition,2012
W. Stallings, Operating systems, Prentice-Hall, 2012
Course Code OPERATING SYSTEMS LAB L T P C CSE212 0 0 3 2 Course Computer Architecture and Organization
Prerequisites Objectives 1. To understand and implement the basic resource management technique
[Processor, Memory] 2. To solve the problems related with synchronization, concurrency related issues
Expected On completion of the course, the students will be able to Outcome 1. Simulate the principles of resource management [Processor, Memory]
2. Install and use operating systems with an understanding of professional, ethical and social issues. [Windows, Linux etc.,] 3. Ability to recognize the life long need and engage in upgradation of operating system. 4. Ability to use operating system principles in modeling and design computer based systems
This course meets the following student outcomes: c) An ability to design, implement and evaluate a system / computer based system process, component or program to meet desired needs f) An understanding of professional, ethical, legal, security and social issues and responsibilities h) An ability to address contemporary issues and analyze the local and global impact of computing and engineering solutions on individuals, organizations and society j) Recognition of the need for and an ability to engage in continuing professional learning (lifelong learning) k) An ability to use current techniques, skills and tools necessary for computing and engineering practice. l) An ability to apply mathematical foundations, algorithmic principles and computer science theory in the modeling and design of computer-based systems (CS) List of Experiments 1. Program to report the behavior of the OS to get the CPU type and model, kernal version. 2. Program to get the amount of memory configured into the computer, amount of memory currently available. 3. Implement the various process scheduling mechanisms such as FCFS, SJF, Priority, round – robin. 4. Implement the solution for reader – writer’s problem. 5. Implement the solution for dining philosopher’s problem. 6. Implement banker’s algorithm. 7. Implement the first fit; best fit and worst fit file allocation strategy. 8. Write a program to create processes and threads. 9. Write a program that uses a waitable timer to stop itself K. Sec. After it started where K is a command line
parameter.
Evaluation Continuous Assessment (50 %)
Term End Examination (50%)
Course Code COMPUTER NETWORKS L T P C
CSE303 3 0 0 3
Course Operating Systems and its lab
Prerequisites
Objectives 1. To study the foundational principles, architectures, and techniques employed
2.
in computer networks.
To study the concepts of communication networks, protocols and their
performance
Expected On completion of the course, the students will be able to
Outcome 1. Understand the working of Intranet, LAN, WAN, MAN setups, different
2.
topologies (fundamental knowledge).
Analyze the local and global impact of networks and to gain familiarity with
3.
common networking protocols and algorithms
Use the knowledge of network protocols and its performance in modeling
computer networks.
This course meets the following student outcomes: b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution. e) An ability to identify, formulate and solve engineering problems. h) An ability to address contemporary issues and analyze the local and global impact of computing and engineering solutions on individuals, organizations and society i) Design and conduct experiments as well as analyze and interpret data. k) An ability to use current techniques, skills and tools necessary for computing and engineering practice. l) An ability to apply mathematical foundations, algorithmic principles and computer science theory in the modeling and design of computer-based systems (CS)
PROTOCOLS Network protocol (syntax, semantics, and timing); Protocol suites (OSI and TCP/IP); Layered protocol software (stacks): Physical layer networking concepts; data link layer concepts; network layer concepts; transport and application layer concepts; Network Standards and standardization bodies. Unit 3 LOCAL AND WIDE AREA 9 hours
NETWORKS LAN topologies (bus, ring, star), LAN technologies (Ethernet, token Ring, Gigabit Ethernet), Error d etection and correction, Carrier sense multiple access networks (CSMA), Large networks and wide areas, Protocols (addressing, congestion control, virtual circuits, quality of service). Internet - addressing, routing, end point control; Internet protocols - IP, TCP, UDP, ICMP, HTTP, CIDR Unit 4 ROUTING AND CONGESTION 9 hours CONTROL ALGORITHMS Flooding; Minimal spanning trees; Bellman Ford, Dijkstra's, OSPF, BGP shortest path algorithms; The leaky bucket, floyd warshall and Random Early Detection congestion methods; Data security and integrity: Fundamentals of secure networks; cryptography; Encryption and privacy: Public key, private key, symmetric key; Authentication protocols; Packet filtering; Firewalls; Virtual private networks; Transport layer security.
Unit 5 NETWORK MANAGEMENT AND 9 hours PERFORMANCE ANALYSIS OF NETWORK Overview of the issues of network management; Domain names and name services; Issues for Internet service providers (ISPs); Quality of service issues: performance, failure recovery. Text / Reference 1. W. Stallings, Data & Computer Communications, Prentice-Hall, 10
th Edition,
Books 2.
2013.
S. Tanenbaum, Computer networks, Prentice-Hall, 5 th
Edition, 2011.
3. Behrouz A. Forouzan, “Data communication and Networking”, Fourth Edition,
4.
Tata McGraw – Hill, 2011.
Mitrani, Modelling of Computer and Communication Systems, Cambridge,
5.
1987.
J.Walrand and P.Varaiya, High Performance Communication Networks,
6.
Harcourt Asia (Morgan Kaufmann), 2004.
J.F.Kurose and K.W.Ross, Computer Networking: A Top-Down Approach
7.
Featuring the Internet, Pearson Education, 5rd
Edition, 2009.
D. E. Comer and D.L. Stevens, Internetworking with TCP/IP, Vol.1, Prentice-
Course Code COMPUTER NETWORKS LAB L T P C CSE304 0 0 3 2 Course Operating Systems and its lab
Prerequisites Objectives 1. Prepare students to write programs to illustrate communication in networks
2. Configure different networks (LAN, WAN) 3. To prepare students to differentiate various protocols and their performance
Expected On completion of the course, the students will be able to Outcome 1. Implement network protocols and analyze its performance to solve network
related problems. 2. Apply professional, ethical, legal, security and social issues for configuring and developing network applications. 3. Use tools, techniques and protocols in designing network applications.
This course meets the following student outcomes: c) An ability to design, implement and evaluate a system / computer based system process, component or program to meet desired needs e) An ability to identify, formulate and solve engineering problems. f) An understanding of professional, ethical, legal, security and social issues and responsibilities k) An ability to use current techniques, skills and tools necessary for computing and engineering practice. l) An ability to apply mathematical foundations, algorithmic principles and computer science theory in the modeling and design of computer-based systems (CS) List of Experiments
1. Write a program to display the server’s date and time details at the client end. 2. Write a program to display the client’s address at the server end. 3. Write a program to implement an echo UDP server. 4. Write a program to develop a simple Chat TCP and UDP application. 5. Write a program to capture each packet and to examine its checksum field.
6. Network layer concepts; to be done with only computer a. Configuration of IP addresses b. Configuration of Subnet mask c. Configuration of Gateway d. Setting up LAN e. Connecting two or more different LAN with different subnet mask f. Making computer to work like router/gateway with the help of IP address
7. Protocol analyzer using ethereal
a. Capturing and analyzing Ethernet frames b. HTTP GET/response interaction c. Analysis of ICMP and Ping d. Analysis of ICMP and Traceroute e. Capturing a bulk TCP transfer from your computer to a remote server
8. Additional activities (Optional)
a. Compute checksum fields using CRC-12 and examine the same during the frame transmission. b. Implementation of sliding window protocol as part of DLC. c. IPv4 and IPv6 protocol testing and implementation. d. TCP and UDP protocol testing and implementation. e. SNMP implementation f. SMTP implementation g. RSA public key and private key encryption and decryption h. Data compression using Huffman codes.
Evaluation Continuous Assessment (50 %)
Term End Examination (50%)
Course Code PROGRAMMING LANGUAGE TRANSLATORS L T P C
CSE309 3 0 0 3
Course Theory of Computation, Computer Architecture and Organization
Prerequisites
Objectives 1. To provide foundation for study of high performance parallel compilers and
2.
compiler design implementation.
To make students familiar with lexical analysis and parsing techniques .
3. To understand the principles of code optimization techniques.
4. To provide fundamental knowledge of various language translators.
Expected On completion of the course, the students will be able to
Outcome 1. demonstrate the functioning of a Compiler and to develop a firm and
enlightened grasp of concepts such as higher level programming, assemblers,
automata theory, and formal languages, languages specifications, data
2.
structure and algorithms
Analyse the local and global impact of transoerlators.
3. Develop language specifications using context free grammars (CFG).
4. Apply the ideas, the techniques, and the knowledge acquired for the purpose
of developing software systems
This course meets the following student outcomes: a) An ability to apply the knowledge of mathematics, science and computing appropriate to the discipline. b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution. c) An ability to design, implement and evaluate a system / computer based system process, component or program to meet desired needs h) An ability to address contemporary issues and analyze the local and global impact of computing and engineering solutions on individuals, organizations and society i) Design and conduct experiments as well as analyze and interpret data m) An ability to apply design and development principles in the construction of software systems. (CS)
Unit 1 INTRODUCTION TO COMPILATION AND 9 hours LEXICAL ANALYSIS Introduction to programming language translators, classification of programming languages, overview of various programming language translators, Compiler Vs Interpreter, cross compiler, bootstrap arrangement, logical phases of compiler, pass Vs phase-cousins of compilers, Lexical Analysis phase: - Design issues-patterns, lexemes, Tokens-attributes- specification of tokens, Regular expressions-Overview of automata-Thompson construction NFA-DFA-minimized DFA-lexical errors- Lex Unit 2 SYNTAX ANALYSIS 9 hours Role of parser- Formal definition of grammars; BNF and EBNF -Parse Tree- Ambiguity- Elimination of ambiguity- Top down parsing: Recursive-Descent parsing, Non- recursive predictive parsing; LL(1) grammars, Bottom-Up parsing:- Shift-Reduce parsers, Operating precedence parsing: design of operator precedence table, parsing –LR parsers:- Construction of SLR parser tables and parsing , CLR parsing-LALR parsing- Syntax errors-YACC Unit 3 SEMANTICS & RUNTIME 9 hours
ENVIRONMENTS Syntax Directed Translations: Syntax-directed definitions, Translation Schemes, construction of syntax trees, DAG’S- bottom-up evaluation of s-attributed definitions, l-attributed definitions; Run-time environments: Source language issues, storage organization, storage-allocation strategies, symbol tables: local and global symbol table structures and management. Type checking Systems: Data type as set of values with set of
operations; data types; type checking models; semantic models of user -defined types; parametric polymorphism; subtype polymorphism; type-checking algorithms. Unit 4 INTERMEDIATE CODE 9 hours
GENERATION & OPTIMIZATION Intermediate languages, Three Address code: declarations, assignment statements, addressing array el ements, Boolean expressions, case statements, back patching. Code optimization: The principle source of optimization, optimization of basic blocks, Loop optimizations. Unit 5 CODE GENERATION & OTHER 9 hours
TRANSLATIONS ISSUES Issues in the design of a code generator, the target machine, Reducing the memory access times by ex ploiting addressing modes- peephole optimizations, basic blocks, DAG’s- Iterative vs. recursive interpretation; Elements of Assembly language- assemblers- Passes of an assembler-Macros- design of macro processors- passes of a macro processor Text / Reference 1. A. V. Aho et al, Compilers: Principles, techniques, & tools, Second Edition,
Books 2.
Pearson Education, 2007.
K. D. Cooper and L. Torczon, Engineering a compiler, Morgan Kaufmann, 2004.
3. Steven S.Muchnick “Advanced Compiler design implementation” Elsevier
4.
Science India.
D.M. Dhamdhere “Systems programming and operating systems” Tata McGraw-
Objectives 1. To introduce fundamental concepts of computer graphics.
2. To explore two dimensional and three dimensional transformations
3. To provide exposure to various interactive input methods
4. To pioneer the applications of computer graphics
Expected On completion of the course, the students will be able to
Outcome Analyze a problem scenario, identify, define and evaluate the
appropriate HCI requirements in any user interactive system.
1. Identify, formulate, analyze, design and interpret data in user interactive
2.
applications.
Apply mathematical foundations, algorithmic principles, and computer
graphics theory in the modeling and design of HCI systems.
This course meets the following student outcomes:
a) An ability to apply the knowledge of mathematics, science and computing appropriate
to the discipline.
b) An ability to analyze a problem, identify and define the computing requirements
appropriate to its solution.
e) An ability to identify, formulate and solve engineering problems.
i) Design and conduct experiments as well as analyze and interpret data
l) An ability to apply mathematical foundations, algorithmic principles and computer
science theory in the modeling and design of computer-based systems (CS)
Unit 1 FUNDAMENTALS 9 hours
Graphic systems: Raster and vector graphics systems; video display devices; physical and logical input devices; issues facing the developer of graphical systems. Fundamental techniques in graphics: Hierarchy of graphics software; using a graphics API; simple color models; homogeneous coordinates; affine transformations (scaling, rotation, translation); viewing transformation; clipping. Unit 2 GRAPHICAL ALGORITHMS and GEOMETRIC 9 hours
MODELLING Graphical algorithms: Line generation algorithms; structure and use of fonts; font generation: outline vs. bitmap; polygonal representation of 3D objects; parametric polynomial curves and surfaces; introduction to ray tracing; ray tracing algorithms; image synthesis, sampling techniques, and anti-aliasing; image enhancement.; Geometric modeling: Polygonal representation of 3D objects; Parametric polynomial curves and surfaces; Constructive Solid Geometry (CSG) representation; Implicit representation of curves and surfaces; Spatial subdivision techniques; Procedural models; Deformable models; Subdivision surfaces; Multiresolution modeling; Reconstruction Unit 3 BASIC RENDERING 9 hours Line generation algorithms (Bresenham); Font generation: outline vs. bitmap; Light -source and material properties; Ambient, diffuse, and specular reflections; Phong reflection model; Rendering of a polygonal surface; flat, Gouraud, and Phong shading; Texture mapping, bump texture, environment map; Introduction to ray tracing; Image synthesis, sampling techniques, and anti-aliasing. Unit 4 ADVANCED TOPICS 9 hours Advanced techniques: Color quantization; Scan conversion of 2D primitive, forward differencing; Tessellation of curved surfaces; Hidden surface removal methods; Z-buffer and frame buffer, color channels (a channel for opacity); Advanced geometric modeling techniques; Computer animation: Key-frame animation; Camera animation; Scripting system; Animation of articulated structures: inverse kinematics; Motion capture; Procedural
animation; Deformation.
Unit 5 ADVANCED TOPICS 9 hours Visualization: Basic viewing and interrogation functions for visualization; Information visualization: projection and parallel-coordinates methods; Virtual reality: Stereoscopic display; Force feedback simulation, hap tic devices; Viewer tracking; Collision detection; User interface issues; Applications in medicine, simulation, and training. Computer vision: Image acquisition; The digital image and its properties; Text / Reference 1. Donald Hearn and Pauline Baker Computer Graphics, Prentice Hall, New Delhi,
Books 2.
2012.
Steven Harrington, "Computer Graphics- A programming approach", McGraw
3.
Hill, 2nd
Edition, 1987.
Foley J.D., Van Dam A, "Fundamentals of Interactive Computer Graphics",
Course Data structures and Algorithms, Algorithm Design and Analysis
Prerequisites
Objectives 1. To train the fundamental concepts of database management system, database modeling
2.
and design, SQL, PL/SQL, system implementation techniques.
To enable students to model ER diagram for any customized applications
3. To provide knowledge on distributed databases, concurrency techniques, federated
systems and active databases.
Expected On completion of the course, the students will be able to
Outcome 1. Perform project planning, analysis, design, implementation and testing in group / as
2.
an individual for any real time information system with all realistic constraints.
Solve issues of information systems using the learnt database principles.
3. Construct database application using current tools and techniques
This course meets the following student outcomes: a) An ability to apply the knowledge of mathematics, science and computing appropriate to the discipline. b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution. c) An ability to design, implement and evaluate a system / computer based system process, component or program to meet desired needs i) Design and conduct experiments as well as analyze and interpret data. l) An ability to apply mathematical foundations, algorithmic principles and computer science theory in the modeling and design of computer-based systems (CS) m) An ability to apply design and development principles in the construction of software systems. (CS)
Unit 1 DATABASE SYSTEMS 9 hours History and motivation for database systems; components of database systems; DBMS functions; databas e architecture and data independence.
Unit 2 DATA MODELING 9 hours Data modeling; conceptual models; object -oriented model; relational data model.; Database query languages: Overview of database languages; SQL; query optimization; 4th-generation environments; embedding non-procedural queries in a procedural language; introduction to Object Query Language. Unit 3 RELATIONAL DATABASES 9 hours Mapping conceptual schema to a relational schema; entity and referential integrity; relational algeb ra and relational calculus; Relational database design: Database design; functional dependency; normal forms; multi-valued dependency; join dependency; representation theory.
Unit 4 TRANSACTION PROCESSING 9 hours Transactions; failure and recovery; concurrency control
Unit 5 PHYSICAL DATABASE DESIGN 9 hours Storage and file structure; indexed files; hashed files; signature files; b -trees; files with dense index; files with variable length records; database efficiency and tuning.
Text / Reference 1. A. Silberschatz, H. F. Korth & S. Sudershan, Database system
Books 2.
concepts, McGraw Hill, 6th Edition 2010.
R. Elmasri & S. B. Navathe, Fundamentals of database systems,
3.
Addison Wesley, 6th
Edition, 2011.
C. J. Date, An introduction to database systems, Addison Wesley,8 th
4.
Edition, 2003.
H. Garcia et al., Database system implementation, Prentice
Course Code DATABASE SYSTEMS LAB L T P C CSE318 0 0 3 2 Course Algorithm Design and Analysis, Data Structures and Algorithms Lab Prerequisites Objectives 1. To design simple information systems using proper data modeling techniques.
2. To understand the method of implementing simple information systems. 3. To provide the knowledge of various database tools and techniques.
Expected On completion of the course, the students will be able to
Outcome 1. Demonstrate the project management activities. 2. Develop any real time information system with all realistic constraints. 3. Solve basic issues of information systems and construct real time database application using current techniques.
This course meets the following student outcomes: b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution. c) An ability to design, implement and evaluate a system / computer based system process, component or program to meet desired needs e) An ability to identify, formulate and solve engineering problems. i) Design and conduct experiments as well as analyze and interpret data. k) An ability to use current techniques, skills and tools necessary for computing and engineering practice. m) An ability to apply design and development principles in the construction of software systems. (CS) List of Experiments
1. 1. a) Create a table EMP with the following fields. EName Eno. Salary DeptNo Address Dname
b) Insert 5 records into EMP c) ALTER EMP table i) varying size of Eno field
ii) adding a new field job d) Delete the table EMP
2. Create a table EMP with the above mentioned fields. i) Insert 5 records into EMP ii) Update the salary of the Employees by 10% hike iii) Delete the employees whose name is ‘AAA’
3. Create a table ORDER with the following fields and constraints.
ORDER
Column Name Constraint Name Constraint Type Order-no pk-order-no PRIMARY KEY Item-name itn UNIQUE
Qty ck-aty CHECK (25<QTY<50) rate-unit Nn-rate NOT NULL 4. Using Ex 3.
1. Drop unique constraint for item-name 2. Disable the constraint Nn-rate 3. Insert a record with NULL values for rate unit 4. Enable the constraint with NULL value existing on rate-unit
5. Create a table EMP mentioned above and test all the arithmetic functions and character functions 6.Add a field date-of-birth to EMP table and test all the date functions. 7. i) Modify EMP table adding a new field BONUS, update it using NVL
ii) Retrieve the employees whose name starts with S. iii)Select all the employees who are working in IT department.
8. I) Using EMP table find the employee getting maximum salary ii) Find the employee whose salary is minimum iii) Find the sum of salaries of all the employees working in ‘ACCOUNTS’ department. 9. Create a table DEPT with the following fields
DNo. Primary Key DName
Modify EMP table adding a foreign key constraint on DeptNo.
i) Insert 6 records into Dept. ii) Implement the following Join operations
a) Self Join b) Equi Join c) Non Equi Join d) Outer Join e) Natural Join
10. Using EMP and DEPT, implement all type of view techniques.
a) Row subset view b) Column subset view c) Row column subset view d) Grouped view e) Joined view f) With check option
11. Using EMP and DEPT a) Create a sequence to insert the empno in EMP table b) Create a synonym for the above two tables
PART – B 1. Create a cursor to update the salary of employees in EMP table 2. a) Write a PL/SQL program to raise an Exception
i) When the bonus exceeds salary b)Write a PL/SQL program to test the built-in Exceptions
3. Write a procedure to insert a record into ORDER table by validating qty limit of the item and also check whether that item exists.
4. Write a function to find substring. Create a trigger which checks whether employee with Emp_no is present in the Employee table before inserting into EMP.
PART – C
Development of mini-projects with VB as front-end.
Evaluation Continuous Assessment (50 %)
Term End Examination (50%)
Course Code SOFTWARE ENGINEERING L T P C CSE310 3 0 0 3 Course Database Systems
Prerequisites Objectives 1. To know the fundamentals of project management activities.
2. To learn the principles of software engineering. 3. To develop an efficient software system through good group cohesiveness. 4. To gather knowledge on various software testing, maintenance methods
Expected On completion of the course, the students will be able to
Outcome 1. Apply the principles of software engineering to analyze, formulate, design for implementation and evaluation of any computer based systems. 2. Involve in continuous learning to solve issues of process and software product using the advanced CASE tools and techniques.
This course meets the following student outcomes: b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution. c) An ability to design, implement and evaluate a system / computer based system process, component or program to meet desired needs i) Design and conduct experiments as well as analyze and interpret data. k) An ability to use current techniques, skills and tools necessary for computing and engineering practice. l) An ability to apply mathematical foundations, algorithmic principles and computer science theory in the modeling and design of computer-based systems (CS) m) An ability to apply design and development principles in the construction of software systems. (CS)
Unit 1 FUNDAMENTALS OF SE AND REQUIREMENT 9 hours ENGINEERING
Software Engineering Fundamentals; Software processes: Software life-cycle and process models; Process assessment models; Overview of Project Management activities; Software requirements and specifications: Requirements elicitation; Requirements analysis modeling techniques; Functional and nonfunctional requirements; User requirements, System requirements, requirement validation and software requirement specification document. Prototyping - Basic concepts of formal specification techniques. Unit 2 SOFTWARE DESIGN 9 hours Fundamental design concepts and principles; Design characteristics; System Models - Context, Behavioral, Data and, Object models, Architectural design- System structuring, Control models; Structured design; Object-oriented analysis and design; User interface design; Design for reuse; Design patterns;
9 hours SOFTWARE VALIDATION AND MAINTENANCE Software validation: Validation planning; Testing fundamentals, including test plan creation and test case generation; Black-box and white-box testing techniques; Unit, integration, validation, and system testing; Object-oriented testing; Inspections. Software evolution: Software maintenance; Characteristics of maintainable software; Reengineering; Legacy systems; Software reuse.
Unit 4 SOFTWARE PROJECT 9 hours
MANAGEMENT Team management – Team processes, Team organization and decision -making, Roles and responsibilities in a software team, Role identification and assignment, Project tracking, Team problem resolution; Project planning and scheduling; Software measurement and estimation techniques; Risk analysis and management; Software quality assurance; Software configuration management;.
Unit 3 RELATIONAL DATABASES
Unit 5 SOFTWARE QUALITY PROCESS 9 hours
IMPROVEMENT Overview of Quality management and Process Improvement; Overview of SEI -CMM, ISO 9000, CMMI, PCMM, TQM and Six Sigma; overview of CASE tools. Software tools and environments: Programming environments; Project management tools; Requirements analysis and design modeling tools; testing tools; Configuration management tools; Text / Reference 1. R. S. Pressman, Software Engineering, a practitioner’s approach,
Books 2.
McGraw Hill,7th
Edition, 2010
Ian Sommerville, "Software Engineering", 9th Edition, Addison-
Course Code SOFTWARE ENGINEERING LAB L T P C CSE311 0 0 3 2 Course Database systems Lab
Prerequisites Objectives 1. To gain knowledge on various CASE tools for applying it in the software
modeling and implementation. 2. To prepare students for performing requirement analysis and design of variety of applications.
Expected On completion of the course, the students will be able to
Outcome 1. Perform requirement analysis and design requirements for solving / developing engineering problems. 2. Demonstrate testing mechanisms on the developed software 3. Use CASE tools in the construction of software systems
This course meets the following student outcomes: c) An ability to design, implement and evaluate a system / computer based system process, component or program to meet desired needs e) An ability to identify, formulate and solve engineering problems. k) An ability to use current techniques, skills and tools necessary for computing and engineering practice. m) An ability to apply design and development principles in the construction of software systems. (CS) List of Experiments
The Students have to form a team size of 3 or 4. Each team is assigned System Analyze, Coding, testing/.metrics tools like Code Comparison, Compiler-based Analysis, Complexity-based Metric, Modeling , Review, Volume testing, Stress Testing, Regression testing etc
This tool has to be used for testing and taking various metrics. Estimation for some application
Comparative Study of different tools have to be done
The above facts has to be documented and a report has to be submitted at the end of the semester
Evaluation Continuous Assessment (50 %)
Term End Examination (50%)
Course Code INTERNET AND WEB PROGRAMMING L T P C CSE307 3 0 0 3 Course Computer Networks
Prerequisites Objectives 1. To understand the basic concepts of web programming and internet
2. To understand how the client-server model of Internet programming works. 3. To develop interactive, client-side, executable web applications.
Expected On completion of the course, the students will be able to
Outcome 1. Understand, analyze and evaluate a system using Internet / web programming concepts.
2. Identify and formulate and solve web related problems. 3. Use techniques, skills and apply algorithmic principles to design web
based applications This course meets the following student outcomes: b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution. c) An ability to design, implement and evaluate a system / computer based system process, component or program to meet desired needs e) An ability to identify, formulate and solve engineering problems. i) Design and conduct experiments as well as analyze and interpret data. k) An ability to use current techniques, skills and tools necessary for computing and engineering practice. l) An ability to apply mathematical foundations, algorithmic principles and computer science theory in the modeling and design of computer-based systems (CS)
Unit 1 INTRODUCTION 9 hours Introduction to Internet applications, client-server, peer-to-peer, and web applications Unit 2 CONCURRENT PROGRAMMING 9 hours
MODELS Building scalable servers, synchronization of threads and processes using both semaphores and messag e passing Unit 3 DEVELOPING METHODOLOGIES 9 hours Workload generation, experiment design, and choice of performance metrics. Unit 4 WEB PROGRAMMING CONCEPTS 9 hours Database connectivity, security, and identity, traditional page -driven and asynchronous web application frameworks Unit 5 LANGUAGES FOR INTERNET 9 hours PROGRAMMING C, Python, PHP and Ruby, relational database concepts for web programming, structuring data and maki ng queries. Text / Reference Books
1. W. Richard Stevens, Bill Fenner, and Andrew M. Rudoff, Unix Network Programming,
Volume 1: The Sockets Network API, 3rd Edition,2004 2. Dave Thomas, with Chad Fowler and Andy Hunt, Programming Ruby: The Pragmatic
Programmer's Guide, Third Edition, 2009 3. Dave Thomas and David Heinemeier Hansson, Agile Web Development with Rails, Second
Edition, 2013 4. Balachander Krishnamurthy and Jennifer Rexford, Web Protocols and Practice: HTTP/1.1,
Networking Protocols, Caching, and Traffic Measurement, Addison Wesley,1st Edition ,2001 5. Hugh E. Williams and David Lane, Web Database Applications with PHP, and MySQL, 2nd
Course Code INTERNET AND WEB PROGRAMMING LAB L T P C
CSE308 0 0 3 2
Course Computer Networks and Computer Networks lab
Prerequisites
Objectives 1. To understand the concepts, principles, strategies, and methodologies of Web
applications and development.
2. To write software and develop interactive, client-side, executable web applications
Expected On completion of the course, the students will be able to
Outcome 1. Demonstrate proficient use of Markup Languages
2. Formulate simple web pages with an understanding of professional, ethical and
3.
social issues.
Write programs to demonstrate the theoretical concepts learnt.
This course meets the following student outcomes: c) An ability to design, implement and evaluate a system / computer based system process, component or program to meet desired needs e) An ability to identify, formulate and solve engineering problems. f) An understanding of professional, ethical, legal, security and social issues and responsibilities k) An ability to use current techniques, skills and tools necessary for computing and engineering practice. l) An ability to apply mathematical foundations, algorithmic principles and computer science theory in the modeling and design of computer-based systems (CS)
List of Experiments 1. Create the personal home page using HTML 2. Design a E-greetings page which has properly aligned paragraphs with images along with it. 3. Implement a Web site for Information Technology department Using
a) Frameset b) Tables c) Internal Linking d) Headers e) List Items f) Hyperlink for mailing
4. Using STYLE SHEETS: 1 .Set the Background Image Fixed and Foreground Scrolling 2. Set the Background Image without tiles and at the center of the screen. 3. Set the Background Color for the text using all the 4 methods of Style sheets
5. Using JavaScript create a web page for Online Testing (Quantitative Aptitude) 6. Develop a JavaScript program to get Register Number as Input and print the Student’s total mark
and grades. 7. Develop a VBScript code to perform the functions of a Calculator. 8. Using VBScript, develop a web site for online counseling. 9. Create a Text Editor using VBScript. 10. Write a function that takes an integer value and returns the number with its digits reversed. For Ex.
Given the number 7631, the function should return 1367. Incorporate the function into a VBScript that reads a value from the user. Display the result in the status bar of the browser window.
11. Create a server-side include file containing the AdRotator code to display 4 advertisements.
12. Create an ASP application that allows the user to customize a web page. The application should consist of three ASP files: Ask the user name to login & read from a database to determine if the user is known. If the user is not known, second ASP file is loaded asking the user to choose their preference for foreground color, background color & image. Insert the new user & pREFERENCE to the database. Display the page customized according to the pREFERENCE selected. If the user is known at login, the customized page should be displayed.
13. Create an ASP application to display the students information from the Database Note: Only 5 student’s information per page should be displayed. Use Previous & Next to retrieve the rest of the information.
14. Create an ASP application for sending E-Mails using CDO. 15. Design a web page for registering the following information into Oracle Database using ASP.
Name Reg. No, Date of Birth, Date of Admission, E-Mail (check for validation) Gender Address Branch & Year
16. Create a formatted business letter using XML & DTD. 17. Create a contact list database in XML using style sheets. 18. Develop a XML schema for the database document type. 19. Create a XML page for displaying staff details from the database 20. Connect to a database using XML & display its contents using HTML Page
Evaluation Continuous Assessment (50 %)
Term End Examination (50%)
Course Code MICROPROCESSOR AND INTERFACING L T P C CSE213 3 0 0 3 Course Computer Architecture and Organization
Prerequisites Objectives 1. To introduce fundamentals of 8086, 80286, 80386 and Pentium processors,
2. To understand different peripheral devices. 3. To acquire knowledge on assembly language programs and peripheral interfacing techniques.
Expected On completion of the course, the students will be able to
Outcome 1. Analyze the types of microprocessors; develop assembly level programs for microprocessor based applications. 2. Apply modern engineering tools and techniques for solving issues of hardware design in microcontroller based applications.
This course meets the following student outcomes: a) An ability to apply the knowledge of mathematics, science and computing appropriate to the discipline. b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution. c) An ability to design, implement and evaluate a system / computer based system process, component or program to meet desired needs i) Design and conduct experiments as well as analyze and interpret data. k) An ability to use current techniques, skills and tools necessary for computing and engineering practice. m) An ability to apply design and development principles in the construction of software systems. (CS)
Unit 1 INTRODUCTION 9 hours 8086 Processor : 8086 architecture, Pin configuration, 8086 in min/max mode, Addressing modes, Instruction set of 8086, Assembler directives, Assembly language programming. Unit 2 INTERFACING 9 hours Peripherals & Interfacing With 8086: Serial & parallel I/O (8251A and 8255), Programmable interval t imer (8253), Programmable DMA controller (8257), programmable interrupt controller (8259A), Keyboard and display controller (8279), ADC / DAC interfacing. Unit 3 80286 PROCESSOR 9 hours 80286 Processor -Features of 80286, internal architecture of 80286, real addressing mode, virtual addressing mode, privilege, protection, basic bus operation of 80286, fetch cycles of 80286.
Unit 4 80386 AND 80486 PROCESSOR 9 hours Features of 80386Dx, internal architecture of 80386Dx, pin configuration of 80386, register organization of 80386Dx, features of 80486, register organization of 80486. Unit 5 ADVANCED MICRO PROCESSORS 9 hours Overview of Advanced Microprocessors- Pentium processor, Pentium – I, Pentium – II, Pentium – III, Pentium – IV and V. Introduction to Internet applications, client-server, peer-to-peer, and web applications Text / Reference 1. A.K. Ray and K.M. Bhurchandi Advanced Microprocessors and
Books 2.
Peripherals, Third Edition, Tata McGraw Hill, 2012.
K Uday Kumar, B S Umashankar, Advanced Micro processors &
IBM-PC Assembly Language Programming, Tata McGraw Hill, 1 st
Edition, 2012
3. Barry B Bray , The Intel Micro processor 8086/8088, 80186,80286,
80386 and 80486-Arcitecture, programming and interfacing, PHI,
4.
8th
Edition,2011
Douglas V. Hall,”Microprocessors and Interfacing Programming
5.
and Hardware”. Tata McGraw Hill, 2007.
Mohamed Rafiquazzaman, “Microprocessor and Microcomputer
based system design,” Universal Book stall, New Delhi, 2 nd
Course Code MICROPROCESSOR AND INTERFACING LAB L T P C CSE214 0 0 3 2 Course Computer Architecture and Organization
Prerequisites Objectives 1. To train the students in assembly language programming.
2. To make students understand the interfacing logic with various peripheral devices. Expected On completion of the course, the students will be able to
Outcome 1. Use assembly level programming to design and implement microprocessor based applications.
2. Implement and solve the issues of Peripheral Interfacing applications using the learnt techniques.
This course meets the following student outcomes: b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution. c) An ability to design, implement and evaluate a system / computer based system process, component or program to meet desired needs d) An ability to function effectively on multi disciplinary teams to accomplish a common goal. e) An ability to identify, formulate and solve engineering problems. i) Design and conduct experiments as well as analyze and interpret data. k) An ability to use current techniques, skills and tools necessary for computing and engineering practice.
List of Experiments 1. Study Experiments
i) Study of 8086 Architecture ii) Study of 8255 – PPI iii) Study of 8253 – PIT iv) Study of 8279 – PKI v) Study of 8259 – PIC
2. Write an ALP to find out factorial of a given hexadecimal number using 8086 MP : Data: OAH, OFH, 1OH 3. Write an ALP to perform 16 bit arithmetic operations (ADD, SUB, MUL, DIV) 4. Write an ALP to generate the sum of first ‘N’ natural numbers using 8086 MP 5. Write an ALP to convert given hexadecimal number to binary using 8086 MP: Data: ABH, CDH, 101H 6. Write an ALP to convert given binary number to hexadecimal number using 8086
MP Data: 101010102, 111111112, 11002, 11112 7. Write an ALP to order give set of hexadecimal numbers in ascending and descending
order Data: 0AH, 0FH, 0DH, 10H,02H 8. Write an ALP to move block of data from locations 1200H-1205H to 2200H – 2205H 9. Write an ALP to reverse the given string: Data: WELCOME 10. Write an ALP to generate the following series 1+1/x+1/x
3+1/x
5+ ……..
11. Write an ALP to generate square wave using 8255 PPI 12. Write an ALP to generate rate generator using 8253 PIT 13. Write an ALP to interface keyboard with 8086 using 8279 PKI 14. Write an ALP to display the given message using 8279
PKI Message: COMPUTER SCIENCES 15. Write an ALP to interface analog to digital converter.
Evaluation Continuous Assessment (50 %)
Term End Examination (50%)
Course Code DISCRETE TIME SYSTEMS AND PROCESSING L T P C
ECE104 3 0 0 3
Course Computer Networks, Computer Architecture and Organization
Prerequisites
Objectives Objective
1. To introduce the basic concepts and techniques of digital signal processing (DSP) and
to demonstrate some interesting and useful practical applications of DSP.
2. To impart the Knowledge of discrete mathematical tools, transforms, and algorithms
used in DSP.
Expected On completion of the course, the students will be able to
Outcome 1. Describe the Sampling Theorem and how this relates to Aliasing and Folding.
2. Determine if a system is a Linear Time-Invariant (LTI) System.
3. Be able to take the Z-transform of a LTI system
4. Determine the frequency response of FIR and IIR filters.
This course meets the following student outcomes: a) An ability to apply the knowledge of mathematics, science and computing appropriate to the discipline. b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution. e) An ability to identify, formulate and solve engineering problems. i)Design and conduct experiments as well as analyze and interpret data k) An ability to use current techniques, skills and tools necessary for computing and engineering practice.
Unit 1 ANALOG TO DIGITAL FILTER DESIGN 9 hours THROUGH TRANSFORMATION Analog filter responses. Z-Transformation and Inverse Z -Transformation. Transformation from analog to digital filter-Difference method, impulse invariance method and Bilinear transformation Unit 2 IMPLEMENTATION OF DISCRETE - 9 hours
TIME SYSTEMS System realization through block-diagram representation and system inter connection. Recursive – Non-recursive filters – Digital filter realization – Direct, canonic, cascade, parallel and lattice realizations. State space realization of digital filters. Robust implementation of digital filters. Discrete Fourier Transforms: Discrete Fourier Transform (DFT) definition – Properties of discrete Fourier transform, Convolution of sequences linear convolution. Unit 3 FFT ALGORITHMS 9 hours Introduction to Radix 2 – Fast Fourier transform (FFT) – Properties of Radix 2 FFT – Decimation in time FFI – Data shuffling and Bit reversal – Decimation in frequency FFT – Algorithms of Radix 2 FFT – Computing Inverse DFT by doing a direct DFT. Unit 4 THEORY AND DESIGN OF DIGITAL 9 hours
IIR FILTERS Review of design techniques for analog low pass filter, frequency transformation, Properties of IIR filter- IIR filter design –Different methods of IIR filter Design; Theory and Design of Digital FIR Filters: Design characteristics of FIR filters with linear- phase – Frequency response of linear phase FIR filters – Design of FIR filters using window functions.
Unit 5 GENERAL PURPOSE DIGITAL 9 hours
SIGNAL PROCESSOR Introduction. Computer architectures for signal processing - Hardware architecture, Pipelining, Hardware multiplier, accumulator, replication, On chip memory/cache and Extended parallelism. General-purpose digital signal processors-Fixed point and floating point DSP. Selecting digital signal Processors. Implementation of DSP algorithms on general purpose DSP-FIR digital filtering. Text / Reference 1. J.G.Proakis , D.G.Manolakis and D.Sharma, “Digital Signal Processing
Books 2.
Principles, Algorithms and Applications”, Pearson Education, 2006.
Roberto Cristi, “Modern Digital Signal Processing”, Thomson Brooks,
3.
2004.
Oppenhiem V.A.V and Schaffer R.W, “Discrete – time Signal
4.
Processing”, Prentice Hall India, 1989.
Rabiner L.R and C.B Gold,”Theory and Applications of Digital Signal
5.
Processing”, Prentice Hall of India, 1987.
Leudeman L.C, “Fundamentals of Digital signal processing”, Harper &
Course Code BASIC ELECTRICAL AND ELECTRONICS L T P C EEE101 ENGINEERING 3 0 2 4 Course Physics at +2 or equivalent level.
Prerequisites Objectives To provide overview of electrical and electronics engineering that serve the foundation for
advanced studies in the area of electrical and electronics engineering Expected On completion of this course student able to understand the concepts of electrical and Outcome electronics engineering
This course meets the following student outcomes: a) An ability to apply the knowledge of mathematics, science and computing appropriate to the discipline. b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution. i) Design and conduct experiments as well as analyze and interpret data m) An ability to apply design and development principles in the construction of software systems. (CS)
Unit 1 Elementary Circuit Analysis 9 hours Ohm’s law, KCL, KVL, node voltage analysis, mesh current, circuits with dependant and controlled sources, Thevenin’s & Norton’s equivalent, maximum power transfer and superposition theorem, VI characteristics for capacitors and inductors. Unit 2 Analysis of DC and AC Circuits 9 hours Steady state DC analysis, RL and RC transients in circuits with DC source, analysis of a second orde r circuit with a DC source, RMS values, the use of phasors for constant frequency sinusoidal sources, steady state AC analysis of a series circuit, series and parallel combinations of complex impedances, AC power calculations. Unit 3 Digital Systems 9 hours Basic logic circuit concepts, representation of numerical data in binary form - combinatorial logic circuits, synthesis of logic circuits, minimization of logic circuits - sequential logic circuits - computer organization, memory types, digital process control, computer based instrumentation systems, measurement concepts and sensors, signal conditioning, analog to digital conversion. Unit 4 Semiconductor Devices 9 hours Basic diode concepts, zener diode voltage regulator concepts, ideal diode model, rectifier and wave -shaping circuits, linear small signal equivalent circuits, basic amplifier concepts, cascaded amplifiers, ideal amplifiers, differential amplifiers, NMOS and PMOS transistors, bias circuits, small signal equivalent circuits, CMOS logic gates, bipolar junction transistors, current and voltage relationship, common emitter characteristics, large signal DC circuit models, small signal equivalent circuits, ideal operational amplifiers, inverting and non-inverting amplifiers, integrators & differentiators. Unit 5 Electromechanics 9 hours Magnetic fields and circuits, self and mutual inductance, ideal and real transformers, principles of rotating DC machines, shunt, separately excited and series connected DC motors, speed control of DC motors, 3-phase induction motors, synchronous machines and single phase induction motors, stepper motors and brushless DC motors. Text / Reference 1. Allan R. Hambley (2014), Electrical Engineering-Principles and Books Applications, Pearson Education.
2. D.P. Kothari and I.J. Nagrath (2010), Basic Electrical Engineering, 2nd Edition, Tata McGraw-Hill. 3. D.P. Kothari and I.J. Nagrath (2009), Theory and Problem of Basic Electrical Engineering, Prentice Hall of India, New Delhi.
4. R.A. DeCarlo and Pen-Min Lin (2001), Linear Circuit Analysis,
2ndEdition, Oxford University Press, New
Delhi.
5. W.H. Hayt, J.E. Kemmerly and S.M. Durbin (2002),Engineering Circuit
Analysis, 6thEdition, Tata McGraw-Hill, New Delhi. 2012
2. Verification of Thevenin’s, Nortran and maximum power transfer theorems. 3. Steady state analysis of RLC series/parallel circuits and Resonance 4. Truth table verifications: AND, OR, NAND, NOR, XOR and XNOR 5. Design of half and full adder circuits 6. Measurement of 3 phase power using 2 wattmeter method 7. Study of unsymmetrical loading with star/delta configuration 8. Forward and reverse characteristics of PN junction diode/SCR/DIAC/TRIAC 9. Design of power control circuit with SCR
Evaluation: Continuous Assessment – 50 % & Term End Examination – 50%
Course Code ELECTRONICS L T P C EEE103 3 0 2 4 Course Basic Electrical and Electronics Engineering
Prerequisites Objectives 1. To give an insight into the field of Electronics through basic electronic devices.
2. To get to know the intricacies of design and operation of some basic electronic circuits. 3. To enable to freely work with the devices in Labs.
Expected On completion of the course, the students will be able to Outcome
1. The students will acquire full knowledge of the devices they will be handling. 2. Will come to know the trouble shooting methodology while working with devices and circuits. This course meets the following student outcomes: a) An ability to apply the knowledge of mathematics, science and computing appropriate to the discipline. b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution. e) An ability to identify, formulate and solve engineering problems. i) Design and conduct experiments as well as analyze and interpret data
Unit 1 SEMICONDUCTOR BASICS 9 hours Semiconductor Devices: Intrinsic, Extrinsic, Drift and diffusion currents – PN junction – PN junction Diode – VI characteristics – Diode equation– Problems – Diffusion and Transition Capacitances Equivalent circuit – Half wave rectifier – Full – Wave rectifiers – Filters (C,L,LC, &RC) – PN Diode clippers & clampers and problems – Avalanche and Zener breakdown – Zener diode. Special purpose Diodes :- Varactor diode – Tunnel diode – PIN diode Unit 2 BIPOLAR JUNCTION TRANSISTOR 9 hours Transistor action – current components – I/o characteristics of CB, CE, CC configuration – Transistor Biasing – Bias stability – problems – operating point – Load line analysis problems – Bias compensation – Thermal run-away in Transistor – Use of heat sinks. Unit 3 FET AND OTHER DEVICES 9 hours Constructional features of JFET – MOSFET – handling precautions of MOSFET – FET Biasing methods – MOSFET biasing methods –Problems,Construction and characteristics of UJT, SCR, DIAC and TRIAC. Unit 4 PHOTO ELECTRIC DEVICES 9 hours Photo emissivity, Photo diode, photo voltaic cells, LED, LCD, Photo transistor, PN junction Laser, Solar energy converters. Unit 5 OPERATIONAL AMPLIFIERS 9 hours Ideal op-amp, common mode and differential mode signals, CMRR, Applications of Op -amps: Inverting and Non- Inverting amplifier, summing amplifier, differentiator, integrator, comparator. Text / Reference 1. Robert Boylestad & Louis Nashelsky ‘Electronic Devices & Circuit
Books Theory’ Pearson Education, 2007.
2. Theodore F. Boghert, ‘Electronic Devices & Circuits’, Pearson
Education, 6/e, 2003.
3. Allen Mottershead, ‘Electronic Devices and Circuits – An Introduction’,
Course Code ELECTRONICS LABORATORY EEE103 List of Experiments 1. PN Junction diode characteristics
2. Zener diode characteristics 3. Half wave rectifier 4. Full Wave rectifier 5. Bridge rectifier 6. BJT CE characteristics 7. BJT CB characteristics 8. UJT characteristics 9. JFET characteristics 10. Operational Amplifier – inverting, non inverting and differential amplifiers
Evaluation: Continuous Assessment – 50 % & Term End Examination – 50%
Course Code OPERATIONS RESEARCH L T P C MEE437 3 0 03 Course Nil
Prerequisites Objectives To introduce the operations research techniques such as Linear Programming, Integer
Programming. Expected On completion of the course, the students will be able to
Outcome to understand and use concepts of OR, such as Linear programming, dynamic programming. They would be able to solve Inventory, maintenance and replacement problems.
This course meets the following student outcomes: a) An ability to apply the knowledge of mathematics, science and computing appropriate to the discipline. c)An ability to design, implement and evaluate a system / computer based system process, component or program to meet desired needs e) An ability to identify, formulate and solve engineering problems. k) An ability to use current techniques, skills and tools necessary for computing and engineering practice.
Unit 1 INTRODUCTION 9 hours Concept and scope of operations research (OR) – development of OR – phase of OR – models in (OR) Development of OR – phase of OR – Models in OR. Linear Programming-Methods of solution – graphical and SIMPLEX methods of solution VARIATIONS – duality in LP – revised SIMPLEX method – applications for business and industrial problem. Unit 2 INTEGER PROGRAMMING-FORMULATION 9 hours graphical representation – Gomory’s cutting plane method, Transportation And Assignment Problems - Initial solution – methods of improving the initial solution – travelling salesman problems – dynamic programming – principle of optimality. Unit 3 SEQUENCING AD SCHEDULING PROBLEMS 9 hours Job sequencing – ‘n’ jobs through two machines, two machines, two jobs through ‘m’ machines and ‘n’ jobs through ‘m’ machines. PERT & CPM Techniques – critical path – normal and crash time – resource allocation – resource leveling and smoothing. Unit 4 INVENTORY PROBLEMS 9 hours Deterministic model – costs decision variables – economic order quality – instantaneous and non – instantaneous receipt of goods with and without shortage – quality discount – probabilistic inventory model – inventory systems – safety stock – reorder level (ROL), reorder point (ROP) determination. Unit 5 MAINTENANCE AND REPLACEMENT 9 hours
PROBLEMS Models for routine maintenance and preventive maintenance decisions – replacement models that deteriorate with time and those fail completely.
1. Taha. H.A. “Operation Research- An Introduction”, Macmillan, 2008. 2. Sharma. S.D., “Operation Research”, Keder Nath Ram Nath & co., 2009. 3. Billy. B. Gillet “Introduction to Operation Research”, Tata McGraw Hill 1982. 4. .S. Hamblin & Stevens Jr. “Operation Research”, McGraw Hill Co., 1974. Continuous Assessment (30 %) and Assignments / Quizzes / Projects (20%) Term End Examination (50%) Evaluation
Text / Reference Books
Course Code ENGINEERING GRAPHICS L T P C MEE101 0 0 4 2 Course Nil
Prerequisites Objectives 1.To create an awareness and emphasise the need for Engineering Graphics.
2.To teach basic drawing standards and conventions. 3.To develop skills in three-dimensional visualization of engineering components. 4.To develop an understanding of 2D and 3D drawings using the Solidworks software.
Expected On completion of this course, the students will be able to Outcome 1.prepare drawings as per standards (BIS).
2.solve specific geometrical problems in plane geometry involving lines, plane figures and special curves. 3.produce orthographic projection of engineering components working from pictorial drawings. 4. Prepare 2D Drawings using the Solidworks software.
This course needs the following student outcome: k) An ability to use current techniques, skills and tools necessary for computing and engineering practice.
Contents Introduction to engineering graphics – geometrical construction – conics and special curves – free hand
sketching – dimensioning principles – orthographic projection – projection of points, lines and solids in simple position only – detailed views of simple 3D objects. Text / Reference 1.N.D. Bhatt (1998), Engineering Drawing, Charotar Publishing House.
Books 2.French and Vierk (2002), Fundamentals of Engineering Drawing, McGraw-Hill.
Objectives 1. To train the students in hadling tools, equipement and machinery with safety.
2. To impart skill in fabricating simple components using sheet metal.
3. To cultivate safety aspects in handling of tools and equipment.
Expected On completion of this course, the students will be able to
Outcome 1. welding and soldering operations.
2. fabrication of simple sheet metal parts.
This course meets the following student outcomes:
d)An ability to function effectively on multi-disciplinary teams to accomplish a common
goal.
k) An ability to use current techniques, skills and tools necessary for computing and
engineering practice.
WELDING EXERCISES
•Introduction to BI Standards and reading of welding drawings.
•Butt Joint
•Lap Joint
•TIG Welding
•MIG Welding
SHEET METAL EXERCISES
•Making of Cube
•Making of Cone using development of surface.
•Making of control panel using development of surface.
SOLDERING EXERCISES
•Soldering and desoldering of resistor in PCB.
•Soldering and desoldering of IC in PCB.
•Soldering and desoldering of capacitor in PCB.
BOSCH TOOLS DEMONSTRATION
•Demonstration of all Bosch tools.
•Introduction to TIG, MIG welding.
•Aluminum welding - submerged and arc welding, wave soldering.
Text / Reference Text/Reference Book
Books Workshop Manual prepared by VIT Faculty
Evaluation Continuous Assessment (50 %)
Term End Examination (50%)
Course Code: L T P C CSE498 COMPREHENSIVE EXAMINATION 0 0 0 2
Course Prerequisites Minimum of Six semester of courses
Objectives: Designed to test the students on the basics of computer science and engineering concepts, and tools, and the process of identifying and solving engineering problems.
Expected Outcome: This course meets the following student outcomes a) An ability to apply the knowledge of mathematics, science and computing appropriate to the discipline. b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution. c)An ability to design, implement and evaluate a system / computer based system process, component or program to meet desired needs d) An ability to function effectively on multi disciplinary teams to accomplish a common goal. e) An ability to identify, formulate and solve engineering problems. f)An understanding of professional, ethical, legal, security and social issues and responsibilities g) An ability to communicate effectively with a range of audiences. h) An ability to address contemporary issues and analyze the local and global impact of computing and engineering solutions on individuals, organizations and society i)Design and conduct experiments as well as analyze and interpret data k) An ability to use current techniques, skills and tools necessary for computing and engineering practice. l) An ability to apply mathematical foundations, algorithmic principles and computer science theory in the modeling and design of computer-based systems (CS) m) An ability to apply design and development principles in the construction of software systems. (CS)
Contents The major topics covered in the program core and elective subjects have to be
reviewed by the student.
Mode of Evaluation Examination (100%)
Course Code: L T P C CSE398 MINI PROJECT 0 0 2 2 Course Prerequisites Minimum of 4 semester courses
Objectives: To apply the concepts and theories learned throughout 4 semester course
Expected Outcome: On completion of the course, the students will be able to
to apply the concepts to analyze and model computing requirements to address the computing and engineering problems
This course meets the following student outcomes a) An ability to apply the knowledge of mathematics, science and computing appropriate to the discipline. b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution. e) An ability to identify, formulate and solve engineering problems. h) An ability to address contemporary issues and analyze the local and global impact of computing and engineering solutions on individuals, organizations and society. i) Design and conduct experiments as well as analyze and interpret data.
The Project Work may be a theoretical analysis, modeling & simulation,
Contents experimentation & analysis, prototype design, correlation and analysis of data, software development, etc. or a combination of these.
1. Can be individual work or a group project, with maximum of 3 students. Method: 2. In case of group project, the individual project report of each student
should specify the individual’s contribution to the group project. 3. Carried out inside the university. 1st and 2nd Internal review : 40 %
Mode of Evaluation Thesis : 10 % Final viva-voce : 50 %
Course Code: L T P C
CSE399 INDUSTRIAL INTERNSHIP 0 0 2 2
Course Prerequisites Completion of minimum of Two semesters
Objectives: Designed to expose the students to industry environment and work there as
trainees.
Expected Outcome: On completion of the course, the students will be able to
understand the application of theoretical concepts in industry
learn the latest technology being applied in industry
This course meets the following student outcomes
h) An ability to address contemporary issues and analyze the local and global
impact of computing and engineering solutions on individuals, organizations
and society
j) Recognition of the need for and an ability to engage in continuing
professional learning (lifelong learning)
Contents
Four weeks of work at industry site
Supervised by an expert at the industry
Students have to maintain a written record of the assignments, progress and accomplishments. They have to submit a report at the end of this training.
An oral presentation on their experiences and the knowledge gained during their work.
Mode of Evaluation Oral viva - voce (50%)
Report (50%)
Course Code:
CSE499
PROJECT WORK
L
0
T
0
P
20
C
20
Course Prerequisites Minimum of 7 semester courses
Objectives: To apply the concepts and theories learned throughout the program.
Expected Outcome: On completion of the course, the students will be able to
Identify an engineering problem,analyze and find a solution
Apply the concepts of design , model and evaluate software systems
Improve soft skills
This course meets the following student outcomes
a) An ability to apply the knowledge of mathematics, science and computing appropriate to the discipline.
b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution.
c) An ability to design,implement and evaluate a system/computer-based system process,
component or program to meet desired needs.
d)An ability to function effectively on multi disciplinary teams to accomplish common goal.
e) An ability to identify, formulate and solve engineering problems.
f)An understanding of professional, ethical, legal, security and social issues and responsibilities
g) An ability to communicate effectively with a range of audiences.
h) knowledge of contemporary issues, and a broad education and ability to analyze the impact of computing and engineering solutions in an individual, organizational, global, economic, environmental, and societal context
i)Design and conduct experiments as well as analyze and interpret data
k) An ability to use current techniques, skills and tools necessary for computing and engineering practice.
l) An ability to apply mathematical foundations, algorithmic principles and computer science theory in the modeling and design of computer-based systems (CS)
m) An ability to apply design and development principles in the construction of
software systems. (CS)
Contents
The Project Work must involve engineering design with realistic constraints. It must also include appropriate elements of the following: engineering standards, design analysis, modeling, simulation, experimentation, prototyping, fabrication, correlation of data, and software development.
Method:
1. Can be individual work or a group project, with maximum of 3 students. 2. In case of group project, the individual project report of each student should specify the individual’s contribution to the group project. 3. Carried out inside or outside the university, in any relevant industry or research institution.
Mode of Evaluation
• 1st and 2nd Internal review : 40 % • Thesis :10 % • Final viva-voce : 50 %
Course Code INTRODUCTION TO ARTIFICIAL L T P C CSE302 INTELLIGENCE 3 0 0 3
Course Data Structures and Algorithms
Prerequisites Objectives 1. To cover fundamentals of Artificial Intelligence,
2. To understand various knowledge representation techniques. 3. To provide knowledge of AI systems and its variants
Expected On completion of the course, the students will be able to
Outcome 1. Understand the basics of Artificial Intelligence, 2. Apply AI problem solving techniques, knowledge representation, and reasoning
methods in Knowledge based systems 3. Develop simple intelligent / expert system using available tools and techniques
of AI to analyze and interpret domain knowledge
This course meets the following student outcomes: b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution. c) An ability to design, implement and evaluate a system / computer based system process, component or program to meet desired needs e) An ability to identify, formulate and solve engineering problems. i) Design and conduct experiments as well as analyze and interpret data k) An ability to use current techniques, skills and tools necessary for computing and engineering practice.
Unit 1 INTRODUCTION 9 hours Introduction - Foundation and history of AI. AI Problems and techniques - AI programming languages – Introduction to LISP and PROLOG – Problem spaces and searches -Blind search strategies; Breadth first - Depth first –Heuristic search techniques Hill climbing - Best first – A* algorithm AO* algorithm – game trees-Minimax algorithm – Game playing – Alpha beta pruning. Unit 2 KNOWLEDGE REPRESENTATION 9 hours Knowledge representation issues – Predicate logic – logic programming – Sematic nets - Frames and inheritance - constraint propagation –Representing Knowledge using rules – Rules based deduction system. Unit 3 REASONING UNDER UNCERTAINTY 9 hours Introduction to uncertain knowledge review of probability – Baye’s Probabilistic inferences and Dempster Shafer theory –Heuristic methods – Symbolic reasoning under uncertainty- Statistical reasoning – Fuzzy reasoning – Temporal reasoning- Non monotonic reasoning.
Unit 4 PLANNING AND LEARNING 9 hours Planning - Introduction, Planning in situational calculus - Representation for planning – Partial order planning algorithm- Learning from examples- Discovery as learning – Learning by analogy – Explanation based learning –Introduction to Neural nets – Genetic Algorithms. Unit 5 APPLICATIONS 9 hours Principles of Natural Language Processing Rule Based Systems Architecture - Expert systems- Knowledge acquisition concepts – AI application to robotics – Current trends in Intelligent Systems.
Text / Reference 1. Patrick Henry Winston,” Artificial Intelligence”, Addison Wesley,
Books 2.
Third edition, 2000.
George F Luger, Artificial Intelligence, Pearson Education, 6th edition,
3.
2009.
Engene Charniak and Drew Mc Dermott,” Introduction to Artificial
4.
intelligence, Addison Wesley 2000.
Nils J. Nilsson,”Principles of Artificial Intelligence“, Narosa Publishing
Course Code BIO-INORMATICS L T P C CSE404 3 0 0 3 Course Prerequisites - Objectives To cover the basics of Bio informatics, Dynamic programming, Evolutionary trees &
DNA sequencing. Expected On completion of the course, the students will be able to
Outcome 1. Understand and explain the fundamentals of Bio-informatics, 2. Know Dynamic programming, searching algorithms, Evolutionary trees, DNA
mapping, DNA sequencing and Gene predictions 3. Implement evolutionary computing for the Bio-informatics domain
This course meets the following student outcomes: a) An ability to apply the knowledge of mathematics, science and computing appropriate to the discipline. c) An ability to design, implement and evaluate a system / computer based system process, component or program to meet desired needs k) An ability to use current techniques, skills and tools necessary for computing and engineering practice.
Unit 1 CODING 9 hours Common health care language - coding techniques – coded and quasi coded data – Medical vocabulary – industry wide communication standards HL7 – unified medical language system – quality of care paradigms, risk management bioethics. Unit 2 PATIENT RECORD MAINTENANCE 9 hours Electronic patient record – models or ERP – environmental services – metrics – telemedicine – community networks – telemedicine peripherals and equipment selection – anatomy of video conferencing technology. Unit 3 PROTEIN INFORMATION 9 hours
RESSOURCES Biological data basics – primary secondary data basics – protein pattern data basics – DNA sequences data basics - DNA analysis - Genes structure and DNA sequences – interpretation of EST structures – different approach to EST analysis. Unit 4 ALIGNMENT TECHNIQUES 9 hours Data base searching - comparison of two sequences – identity and similarity – global and global similarity – global and local alignment - multiple sequence alignment – data basis of multiple alignment – secondary data
Unit 5 Expert system 9 hours Principles of expert system – statistical decision trees – integration of decision support in clinical processors. Text / Reference 1. Dan Gusfield, "Algorithms On Strings Trees and Sequences",
Course Code PARALLEL ALGORITHMS L T P C CSE405 3 0 0 3 Course
Prerequisites Programming Fundamentals, computer architecture and organization Objectives 1. To provide fundamentals in design, analysis, and implementation, of high
performance computational science and engineering applications. 2. To gain knowledge on parallel algorithms and their impact in engineering
problem. Expected On completion of the course, the students will be able to
Outcome 1. Develop knowledge and skills concerning applications of high-performance
2.
computing systems
Identify parallel computing requirements.
3. Use parallel programming concepts in developing real-world applications.
This course meets the following student outcomes: a) An ability to apply the knowledge of mathematics, science and computing appropriate to the discipline. b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution. e) An ability to identify, formulate and solve engineering problems. i) Design and conduct experiments as well as analyze and interpret data. k) An ability to use current techniques, skills and tools necessary for computing and engineering practice. l) An ability to apply mathematical foundations, algorithmic principles and computer science theory in the modeling and design of computer-based systems (CS)
Unit 1 INTRODUCTION 9 hours Computational Science and Engineering Applications; characteristics and requirements, Review of Computational Complexity, Performance: metrics and measurements, Granularity and Partitioning, Locality: temporal/spatial/stream/kernel, Basic methods for parallel programming, Real-world case studies (drawn from multi-scale, multi-discipline applications) Unit 2 HIGH-END COMPUTER SYSTEMS 9 hours Memory Hierarchies, Multi-core Processors: Homogeneous and Heterogeneous, Shared - memory Symmetric Multiprocessors, Vector Computers, Distributed Memory Computers, Supercomputers and Pataskala Systems, Application Accelerators / Reconfigurable Computing, Novel computers: Stream, multithreaded, and purpose-built Unit 3 PARALLEL ALGORITHMS 9 hours Parallel models: ideal and real frameworks, Basic Techniques: Balanced Trees, Pointer Jumping, Divid e and Conquer, Partitioning, Regular Algorithms: Matrix operations and Linear Algebra, Irregular Algorithms: Lists, Trees, Graphs, Randomization: Parallel Pseudo-Random Number Generators, Sorting, Monte Carlo techniques Unit 4 PARALLEL PROGRAMMING 9 hours Revealing concurrency in applications, Task and Functional Parallelism, Task Scheduling, Synchronization Methods, Parallel Primitives (collective operations), SPMD Programming (threads, OpenMP, MPI), I/O and File Systems, Parallel Matlabs (Parallel Matlab, Star-P, Matlab MPI), Partitioning Global Address Space (PGAS) languages (UPC, Titanium, Global Arrays) Unit 5 Achieving Performance 9 hours Measuring performance, Identifying performance bottlenecks, restructuring applications for deep memo ry hierarchies, Partitioning applications for heterogeneous resources, Using existing libraries, tools, and frameworks
Text / Reference 1. Ananth Grama, Anshul Gupta, George Karypis, and ,Vipin Kumar,
Books Introduction to Parallel Computing, 2nd edition, Addison-Welsey,
2.
2003.
David A. Bader (Ed.), Petascale Computing: Algorithms and
Course Code CONCURRENT AND DISTRIBUTED SYSTEMS L T P C
CSE406 3 0 0 3
Course Operating Systems
Prerequisites
Objectives 1. To cover parallel & distributed computing architecture, networked clusters of
2.
computers, utilization and management of the expensive remote resources.
To present the principles underlying the functioning of concurrent and
3.
distributed systems;
To create an awareness of the technical challenges in concurrent and
distributed systems design and implementation
Expected On completion of the course, the students will be able to
Outcome 1. Acquire a sound knowledge and understand the construction of concurrent
2.
and distributed systems
Model, construct and analyze basic concurrent and distributed systems.
3. Adapt analytical approach to the construction of software.
This course meets the following student outcomes:
b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution. h) An ability to address contemporary issues and analyze the local and global impact of computing and engineering solutions on individuals, organizations and society i) Design and conduct experiments as well as analyze and interpret data. j) Recognition of the need for and an ability to engage in continuing professional learning (lifelong learning) k) An ability to use current techniques, skills and tools necessary for computing and engineering practice. m) An ability to apply design and development principles in the construction of software systems. (CS)
Unit 1 INTRODUCTION 9 hours Introduction to distributed computing system, evolution different models, gaining popularity, defini tion, issues in design, DCE, message passing –introduction, desirable features of a good message passing system, issues in IPC, synchronization, buffering, multigram messages, encoding and decoding of message data, process addressing, failure handling, group communication.
Unit 2 REMOTE PROCEDURE CALLS 9 hours Introduction, model, transparency, implementation mechanism, stub generation, RPC messages, marshall ing arguments and results, server management, parameter - passing semanti cs, call semantics, communication protocols for RPCs, client – server binding, exception handling, security, mini project using Java RMI
Unit 3 DISTRIBUTED SHARED MEMORY 9 hours General architecture of DSM systems, design and implementation issues of DSM systems, granularity, s tructure of shared memory space, consistency model, replacement strategy, thrashing, advantages of DSM, clock synchronization DFS and security- Desirable features of good DFS, file models, file accessing Models, file sharing semantics, file catching schemes, file replication, fault Tolerance, atomic transaction, potential attacks to computer system, cryptography, authentication, access control. Digital signatures, DCE security service
Unit 4 Parallel and Distributed Computing 9 hours Operating Systems, Client-Server Model, Distributed Database Systems, Parallel Programming Languages and Algorithms. Distributed Network Architectures- Managing Distributed Systems. Design Considerations Unit 5 METHODS AND TOOLS 9 hours For development, implementation & evaluation of distributed information systems, workflow, software processes, transaction management, and data modeling, infrastructure e.g. middle-ware to glue heterogeneous, autonomous, and partly mobile/distributed data systems, such as e.g. client/server-, CORBA-, and Internet-technologies. Methods for building distributed applications. Text / Reference 1. Pradeep K. Sinha, "Distributed Operating Systems: Concepts &
Books 2.
Design", 2007
Crichlow Joel M, "An Introduction to Distributed and Parallel
3.
Computing", PHI, 1997
Black Uyless, "Data Communications and Distributed Networks",
Objectives 1. To provide fundamental knowledge of software in terms of programming
2.
styles, algorithms, data structures, performance and their notation.
To detail the software testing process and its maturity model
3. To provide in-depth of various software verification and validation testing
methods
Expected On completion of the course, the students will be able to
Outcome 1. Analyze and design a problem, identify and define the testing requirements
appropriate to any computer based/ software system.
2. Analyze the local and global impact of software testing in evaluating a software system.
3. Use current techniques, skills, tools and the principles of software testing for computing, engineering practice and in the construction of software system.
This course meets the following student outcomes: b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution. c) An ability to design, implement and evaluate a system / computer based system process, component or program to meet desired needs i) Design and conduct experiments as well as analyze and interpret data. k) An ability to use current techniques, skills and tools necessary for computing and engineering practice. l) An ability to apply mathematical foundations, algorithmic principles and computer science theory in the modeling and design of computer-based systems (CS) m) An ability to apply design and development principles in the construction of software systems. (CS)
Unit 1 SOFTWARE PROGRAMMING PRACTICE –I 9 hours Style: names, expressions, statement, consistency and idioms, function macros, constants, comments; interface: CSV, prototype libraries, interface principles, resource management, user interfaces. Performance: Performance bottlenecks, timing and profiling speed, spacy efficiency, estimation.
Unit 2 SOFTWARE PROGRAMMING PRACTICE -II 9 hours Portability: language, headers and libraries, program organization, isolation, data exchange, byte o rder, portability and upgrade, internationalization. Formatting data, regular expressions, programming tools, interpreters and compilers, program generators, macros. Debugging: debuggers, clues and bugs, debugging tools. Unit 3 SOFTWARE TESTING PROCESS MATURITY AND 9 hours FRAMEWORK FOR TEST PROCESS IMPROVEMENT &TESTING METHODS The six essentials of software testing: the state of the art and the state of the practice; the clea n sheet approach to getting started. Establishing a practical perspective; critical choices; what, when, and how to test; critical disciplines: frameworks for testing. Verification testing : basic verification methods, getting leverage on verification, verifying documents at different phases, getting the best from verification, three critical success factors for implementing verification, recommendations;
Unit 4 TESTING METHODS 9 hours Validation testing: validation overview, validation methods, validation activities, and recommendation strategy for validation testing; controlling validation costs; minimizing the cost of performance tests, minimizing the cost of maintaining the tests, minimizing validation test ware development costs. Recommendations; testing tracks deliverables, validation testing tasks and deliverables, a testing orphan- user manuals, product release criteria, summary of IEEE/ANSI test related documents, life-cycle mapping of tasks and deliverables; software testing tools; categorizing test tools, tool acquisition; measurement provide answers, useful measures and other interesting measures, recommendations. Unit 5 MANAGING TEST TECHNOLOGY, STANDARD 9 hours
CHECKLISTS Organizational approaches to testing: organizing and reorganizing, structural design elements, appro aches to organizing the test function, selecting the right approach; current practices, trends, challenges; GUIs: what’s new here? Usage testing, tester-to-developer ratios, software measures and practices benchmark study; getting sustainable grains in place; getting gains to happen, getting help, follow-up; standards relevant to software engineering and testing; verification checklists. Text / Reference 1. Brain W. Kernighan and Rob Pike : The Practice of Programming,
Books 2.
Addison-Wesley, 2006
Ed Kit: Software Testing in the Real World, Addison-Wesley, 2008
3. William Perry : Effective Methods For Software Testing, Third
4.
Edition, John Wiley, 2006
Beizer B: Software Testing Techniques, Second Edition, Dreamtech
Course Code DATA WAREHOUSING AND DATA MINING L T P C CSE408 3 0 0 3 Course Database Systems
Prerequisites Objectives 1. To introduce concepts and techniques of data warehousing.
2. To edify the underlying concepts and architecture of data mining. 3. To make students understand association mining and cluster analysis.
Expected On completion of the course, the students will be able to Outcome 1. Understand the functionality of the various data warehousing components.
2. Analyse the strengths and limitations of various data mining and data warehousing models, basic Design, implement and evaluate a system using mining principles and identify, formulate and solve engineering problems using association mining and clustering. This course meets the following student outcomes: a) An ability to apply the knowledge of mathematics, science and computing appropriate to the discipline. b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution. c) An ability to design, implement and evaluate a system / computer based system process, component or program to meet desired needs e) An ability to identify, formulate and solve engineering problems. i) Design and conduct experiments as well as analyze and interpret data.
Unit 1 DATA WAREHOUSE AND OLAP TECHNOLOGY 9 hours FOR DATA MINING
Introduction to Data Warehouse- A multidimensional Data Model – Data Warehouse architecture – Data preprocessing- Data cleaning – Data integration and Transformation. Unit 2 DATA MINING INTRODUCTION 9 hours Introduction to Data Mining – Data Mining Functionalities – Classification of Data Mining systems, Major issues in Data mining. Unit 3 DATA MINING PRIMITIVES, LANGUAGES & 9 hours
SYSTEM ARCHITECTURE Data Mining primitives: Task – relevant data – kind of knowledge to be mined – Background knowledge – interestingness measures– presentation & visualization of discovered pattern - Data Mining Query language – Designing Graphical User interfaces based on DMQL - Architecture of Data mining. Unit 4 ASSOCIATION RULE MINING 9 hours Basic concepts – market basket analysis - Mining single dimensional Boolean association rules from transactional databases. Classification & prediction: What’s classification - issues regarding classification and prediction – Bayesian classification – prediction: linear – non linear. Unit 5 CLUSTER ANALYSIS 9 hours
Types of Data in cluster analysis - Major clustering methods. Data mining applications.
Text / Reference 1. Han J. & Kamber, M, “Data Mining: Concepts and Techniques”, 3 rd
Edition,
Books 2.
Morgan Kaufmann, 2011.
Immon.W.H., “Building the Data Warehouse”, Wiley Dream Tech, 4th Edition,
2005.
3. Anahory S., Murray, D, “Data Warehousing in the Real World”, Pearson, 2009.
Course Code SCRIPTING LANGUAGES L T P C CSE315 3 0 0 3 Course Computer Networks.
Prerequisites Objectives 1. To educate the fundamental and advanced concepts of scripting languages
2. To create interactive Internet applications using scripts
Expected On completion of the course, the students will be able to Outcome Design and implement applications using Java Script, VB script.
Create applications using attractive GUI to address different users. Use the scripting theory in developing software system
This course meets the following student outcomes: c) An ability to design, implement and evaluate a system / computer based system process, component or program to meet desired needs g) An ability to communicate effectively with a range of audiences. l) An ability to apply mathematical foundations, algorithmic principles and computer science theory in the modeling and design of computer-based systems (CS)
Unit 1 VB SCRIPT FUNDAMENTALS 9 hours Introduction to HTML-VBScript Features-Data types-Variables- Constants-Operators-Using Conditional Statements-Looping Through Code-Procedures- Coding Conventions, VB Script in Internet Explorer: A simple VBScript Page-Using VBScript with Objects-VB Script and Forms-Adding VBScript Code to an HTML page Unit 2 JAVA SCRIPT 9 hours Definition-Learning JAVA Script Language-Running JAVA Script Scripts-Using JAVA Script in HTML. Unit 3 FORM ELEMENTS 9 hours Verifying form inputs with JAVA Script – JAVA Script values, Variables and literal – JAVA Script expressions and operators-JAVA Script object model - Using built in object and functions. Unit 4 JAVA FRAMES 9 hours
Overview of JAVA Script statements-Working with windows and frames-Status bar, dates Objects, Random
numbers.
Unit 5 CASE STUDY 9 hours
Netscape Navigator Objects -Playing with JAVA Script-CASE Study.
Text / Reference 1. John R Vacca,, JavaScript Development - Morgan Kaufmann, 1997
Books 2. Paul Lomax, Matt Childs, Ran Petrusha, VBScript in a nutshell –
O’Reilly, 2nd
Edition, 2003
3. John Pollac, JavaScript, McGraw Hill, Third Edition,2010
4. Adrian Kingley, VBScript Programmers Reference –Wiley, 2007
Course Code HUMAN COMPUTER INTERACTION L T P C CSE403 3 0 0 3 Course Computer Graphics, Software Engineering
Prerequisites Objectives 1. To introduce the fundamentals of user interface design
2. To provide concepts and guidelines of user interface
Expected On completion of the course, the students will be able to
Outcome 1. Understand the Human Computer Interaction. 2. Identify the impact of HCI, formulate and solve user interface issues. 3. Design an effective user interface for software application using the tools and
techniques. This course meets the following student outcomes: a) An ability to apply the knowledge of mathematics, science and computing appropriate to the discipline. e) An ability to identify, formulate and solve engineering problems. h) An ability to address contemporary issues and analyze the local and global impact of computing and engineering solutions on individuals, organizations and society k) An ability to use current techniques, skills and tools necessary for computing and engineering practice.
Unit 1 FOUNDATIONS OF HUMAN-COMPUTER 9 hours INTERACTION
Motivation; contexts for HCI (tools, web hypermedia, communication); human centered development and evaluation; human performance models: perception, movement, and cognition; human performance models: culture, communication, and organizations; accommodating human diversity; principles of good design and good designers; engineering tradeoffs; introduction to usability testing. Unit 2 HUMAN-CENTERED SOFTWARE 9 hours
EVALUATION Setting goals for evaluation; evaluation without users: walkthroughs, KLM, guidelines, and standards ; evaluation with users: usability testing, interview, survey, experiment. Unit 3 HUMAN-CENTERED SOFTWARE 9 hours
DEVELOPMENT Approaches, characteristics, and overview of process; functionality and usability: task analysis, interviews, surveys; specifying interaction and presentation; prototyping techniques and tools – paper storyboards, Inheritance and dynamic dispatch, Prototyping languages and GUI builders. Unit 4 GRAPHICAL USER-INTERFACE 9 hours DESIGN Principles of graphical user interfaces, GUI toolkits; Choosing interaction styles and interaction t echniques; HCI aspects of common widgets; HCI aspects of screen design: layout, color, fonts, labeling; handling human failure; beyond simple screen design: visualization, representation, metaphor; multi-modal interaction: graphics, sound, and haptics; 3D interaction and virtual reality. Unit 5 HCI ASPECTS OF MULTIMEDIA 9 hours
SYSTEMS Categorization and architectures of information : hierarchies, hypermedia; information retrieval and human performance – Web search, Usability of database query language, Graphics, Sound; HCI design of multimedia information systems; speech recognition and natural language processing; information appliances and mobile computing.
Text / Reference 1. Ben Schneiderman, “Designing the User Interface ", 5
th Edition, Addison
Books Wesley,2010.
2. Jacob Nielsen, “Usability Engineering ", Elseiver, 1994.
3. Alan Dix et al, “Human - Computer Interaction ", Prentice Hall, 3 rd
Edition, 2003.
4. Alan Cooper, “The Essentials of User Interface Design ", IDG Books,
Course Code MULTIMEDIA SYSTEMS AND ALGORITHMS L T P C CSE414 3 0 0 3 Course Computer Graphics
Prerequisites Objectives To introduce multimedia computing and communications.
To elaborate Sound/ Audio, video processing techniques.
Expected On completion of the course, the students will be able to Outcome 1. Design and implement simple multimedia system to address different users.
2. Use multimedia computing hardware, software tools multimedia authoring and design process. This course meets the following student outcomes: c) An ability to design, implement and evaluate a system / computer based system process, component or program to meet desired needs g) An ability to communicate effectively with a range of audiences. k) An ability to use current techniques, skills and tools necessary for computing and engineering practice. l) An ability to apply mathematical foundations, algorithmic principles and computer science theory in the modeling and design of computer-based systems (CS)
Unit 1 INTRODUCTION 9 hours Branch-overlapping Aspects of Multimedia, Content, Global Structure, Multimedia - Media and Data Streams, Medium, Main Properties of a Multimedia System, Traditional Data Stream Characteristics, Data Streams Characteristics for Continuous Media, Information Units. Unit 2 SOUND/AUDIO 9 hours Basic Sound Concepts, Music, Speech, Image and Graphics - Basic Concepts, Computer Image Processing, Introduction to Optical Storage Unit 3 VIDEO AND ANIMATION 9 hours Basic Concepts, Television, Computer -based Animation, Data Compression-Storage Space, Coding Requirements, Source, Entropy, and Hybrid Coding, Some Basic Compression Techniques-JPEG, H.261, MPEG, DVI Unit 4 MULTIMEDIA OPERATING 9 hours SYSTEMS Introduction, Real-time, Resource Management, Process Management, File Systems, Additional Operating System Issues, System Architecture, Multimedia Communication Systems- Application Subsystem, Transport Subsystem, Quality of Service and Resource Management Unit 5 MULTIMEDIA DATABASE SYSTEMS 9 hours Multimedia Database Systems and its characteristics, Data Analysis, Data Structure, Operations on Da ta, Integration in a Database Model, Introduction to Hypertext, Hypermedia, Document Architecture, SGML, ODA, MHEG, A Reference Model for Multimedia Synchronization, Multimedia Applications- Media Preparation. Media Composition, Media Integration, Media Communication, Media Consumption, Media Entertainment Text / Reference 1. Ralf Steinmetz and Klara Mahrstedt, "Multimedia computing,
Books communications and Applications", Pearson Education Asia, 6 th
reprint
2.
2009.
K. Rao, "Multimedia Communication Systems: Techniques, Standards,
Course Code DATABASE DESIGN L T P C CSE316 3 0 0 3 Course Database systems
Prerequisites Objectives To cover Distributed Database Design Concepts.
To understand Query processing, Query decomposition, Transaction management and Distributed DBMS reliability.
Expected Outcome On completion of the course, the students will be able to 1. Understand and design distributed databases, 2. Apply distributed concepts in database design to solve issues of larger information system. 3. Implement distributed query processing, Query decomposition and Optimization using the
advanced database design principles. This course meets the following student outcomes: b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution. c) An ability to design, implement and evaluate a system / computer based system process, component or program to meet desired needs e) An ability to identify, formulate and solve engineering problems. i) Design and conduct experiments as well as analyze and interpret data l) An ability to apply mathematical foundations, algorithmic principles and computer science theory in the modeling and design of computer-based systems (CS)
Unit 1 DISTRIBUTED DATABASE DESIGN 9 hours Promises of DDBSs. – Complicating Factors – Problem Areas, DBMS Standardization – Architectural models for distributed DBMSs –Distributed DBMS Architecture – Global Directory issues, Alternative Design Strategies – Distribution Design issues – Fragmentation – Allocation, Semantic Data Control: View Management – Data Security – Semantic Integrity Control Unit 2 OVERVIEW OF QUERY PROCESSING 9 hours Query processing problem – objectives of query processing – Complexity of Relational Algebra operations – characterization of Query Processors – Layers of Query processing
Unit 3 QUERY DECOMPOSITION 9 hours Localization of Distributed Data, Query Optimization – Centralized Query Optimization – Join Ordering in fragment queries – distributed query optimization algorithms. Unit 4 TRANSACTION MANAGEMENT 9 hours Definition of a transaction – Properties of Transactions – Types of Transactions, Distributed concurrency control - Serializability theory – Taxonomy of concurrency control mechanisms – Locking based concurrency control algorithms Timestamp-based concurrency control algorithms – Optimistic concurrency control algorithms – optimistic concurrency control algorithms – Deadlock management – Relaxed concurrency control Unit 5 DISTRIBUTED DBMS RELIABILITY 9 hours Reliability concepts and measures – Failures and fault tolerance in distributed systems – local reliability protocols – distributed reliability protocols – dealing with site failures – Network partitioning – Architectural considerations Text / Reference 1. M. Tamer Ozsu, Patick Valduriesz, "Principles of Distributed Database
Books Systems", Springer; 3rd edition, 2011
2. Stefanoceri ,Giuseppe Pelagatti, "Distributed Database Principles and Systems",
McGraw Hill publications, 2008
3. Ramez Elmasri, Shamkant B. Navathe, Fundamentals of Database Systems, 6th
Course Applied Probability, Statistics and Reliability
Prerequisites
Objectives 1. To introduce the salient features and models of simulation systems.
2. To provide exposure in input and output data analysis through various statistical
3.
models.
To elucidate the fundamentals of data collection and statistical models in
simulation.
Expected On completion of the course, the students will be able to
Outcome 1. Apply the simulation and modeling concepts in real time problems.
2. Design and conduct experiments as well as analyze and interpret data using
3.
statistical models.
Apply modeling principles in the development of computer based system
This course meets the following student outcomes: a) An ability to apply the knowledge of mathematics, science and computing appropriate to the discipline. b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution. c) An ability to design, implement and evaluate a system / computer based system process, component or program to meet desired needs i) Design and conduct experiments as well as analyze and interpret data l) An ability to apply mathematical foundations, algorithmic principles and computer science theory in the modeling and design of computer-based systems (CS)
Unit 1 INTRODUCTION 9 hours Introduction to Simulation-Advantages and disadvantages of simulation, areas of application, Systems and system environment, Components of a system, Discrete and continuous systems, Model of a system. Types of models, Discrete – events system simulation, Steps in a simulation study. Simulation Examples, Simulation of queuing systems, Simulation of inventory systems, other examples of simulation, discrete event simulation, general principles and computer simulation languages. Concepts in DES, Programming languages for DESS: FORTRAN, GASP, SIMSCRIPT, GPSS, SLAM, Summary and comparison of simulations. Unit 2 SIMULATION MODELS 9 hours Statistical Models in Simulation- Review of terminology & concepts, Useful statistical models, Discrete distributions, Continuous distributions, Process, Empirical distributions. Queuing Models: Characteristics of queuing systems, queuing notation, Transient & steady state behavior of queuing notation, Transient & steady state behavior of queues, long run measures of performance of queuing systems, steady – state behavior of finite population models. Unit 3 INVETORY SYSTEMS 9 hours Inventory Systems- Measures of effectiveness, Inventory policies, Deterministic systems, and probabilistic systems, Simulation in inventory analysis. Random Number Generation: Properties of random numbers, Generation of Pseudo – random. Nos., techniques for generating random nos., tests for random nos. Random Variable Generation: Inverse transforms technique, Direct Transformation for the normal distribution, Convolution method, Acceptance-Rejection technique. Unit 4 INPUT DATA ANALYSIS 9 hours Input Data Analysis-Data collection, identifying the distribution, parameter estimation, goodness -of-fit tests. Verification and validation of simulation models: Model building, verification & validation, verification of
simulation models, calibration & validation of models
Unit 5 OUTPUT ANALYSIS 9 hours Output Analysis For A Single Model- Stochastic nature of O/I data, types of simulations with respect to O/P analysis, measures of performance and their estimation, O/p analysis for terminating simulations, O/P analysis for steady-state simulations. Comparison and evaluation of alternative system designs: Comparison of two and several system designs, statistical models for estimating the effect of design alternatives. Text / Reference 1. Jerry Banks, John S. Carson, Discrete-event System Simulation, PHI,
Books 2.
5th
Edition, 2009
Karian, Z.A. and Dvdewicz. E.J., Modern Statistical Systems and GPSS
Course Code HARDWARE SOFTWARE CO-DESIGN L T P C CSE410 3 0 0 3 Course Embedded system
Prerequisites Objectives To educate the hardware, software, and system designer on the fundamentals of
hardware/software codesign for the construction of complex systems, particularly embedded systems
Expected On completion of the course, the students will be able to
Outcome 1. Analyse and evaluate Current Hardware/Software Design Process 2. Solve issues and Directions in Hardware/Software Co-design for engineering problems.
3. Implement Hardware/Software Modeling through the learnt tools and techniques.
This course meets the following student outcomes: c) An ability to design, implement and evaluate a system / computer based system process, component or program to meet desired needs e) An ability to identify, formulate and solve engineering problems. j) Recognition of the need for and an ability to engage in continuing professional learning (lifelong learning) k) An ability to use current techniques, skills and tools necessary for computing and engineering practice. l) An ability to apply mathematical foundations, algorithmic principles and computer science theory in the modeling and design of computer-based systems (CS)
Unit 1 INTRODUCTION 9 hours Co-design Definition, Motivation for Codesign, Categories of Systems and the Codesign Problem, Embedded Systems Unit 2 UNIFIED HARDWARE/SOFTWARE 9 hours
REPRESENTATIONS Components of the Current Codesign Process, Components of the Ideal Codesign Process, Unified Hardware/Software Representations Unit 3 HW/SW PARTITIONING 9 hours
TECHNIQUES Partitioning Algorithms, Cost Metrics, Issues in Partitioning, Integrated HW/SW Modeling Methodologies Unit 4 HW/SW SYNTHESIS 9 hours
Unit 5 APPROACHES TO HW/SW CODESIGN 9 hours Industry Approaches, Research , Major Codesign Research Efforts: Chinook, COSYMA, Ptolemy, POLIS, Module Summary Text / Reference 1. Wolf, Wayne , Hardware/Software Co-Design: Principles and Books Practice, Springer, 2010
2. Giovanni De Micheli, Rolf Ernst,Wayne Wolf, Readings in Hardware/Software Co-design , Systems Silicon,2001
Course Code COMPUTER ORGANIZATION AND DESIGN L T P C CSE411 3 0 0 3 Course Computer Architecture and Organization
Prerequisites Objectives 1. To provide the fundamentals of computer organization
2. To provide foundations for the advanced studies in parallel computing. 3. To understand the contemporary issues of computer organization
Expected Outcome On completion of the course, the students will be able to 1. Analyse parallel architecture and its performance. 2. Analyze the different distributed system models 3. Apply the distributed system models of parallel computing in simple computer based
system This course meets the following student outcomes: a) An ability to apply the knowledge of mathematics, science and computing appropriate to the discipline. b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution. e) An ability to identify, formulate and solve engineering problems. i) Design and conduct experiments as well as analyze and interpret data. k) An ability to use current techniques, skills and tools necessary for computing and engineering practice. l) An ability to apply mathematical foundations, algorithmic principles and computer science theory in the modeling and design of computer-based systems (CS)
Unit 1 PERFORMANCE ISSUES 9 hours Metrics for computer performance; clock rate, MIPS, Cycles per instruction, benchmarks; Strengths and weaknesses of performance metrics; averaging metrics: arithmetic, geometric and harmonic; The role of Amdahl’s law in computer performance. Unit 2 INSTRUCTION SET ARCHITECTURE 9 hours Implementation of the von Neumann machine; Single vs. multiple bus datapaths; Instruction set archit ecture; machine architecture as a framework for encapsulating design decisions; Relationship between the architecture and the compiler; Implementing instructions; Unit 3 CONTROL UNIT 9 hours Hardwired realization vs. micro programmed realization; Arithmetic units, for multiplication and division; Instruction pipelining; Trends in computer architecture: CISC, RISC, VLIW, EPIC; Introduction to instruction-level parallelism (ILP); Pipeline hazards: structural, data and control; reducing the effects of hazards. Unit 4 DISTRIBUTED SYSTEM MODELS 9 hours Classification of models: parallel machine models (SIMD, MIMD, SISD, And MISD): Flynn’s taxonomy, Handler’s classification, message passing; Granularity, levels of parallelism; Multiprocessors and multi-computers: Topology, tightly coupled and loosely coupled architectures; Superscalar architecture; Branch prediction; Prefetching; Speculative execution; Multithreading; Scalability; Short vector instruction sets: Streaming extensions, AltiVec, relationship between computer architecture and multimedia applications. Unit 5 CONTEMPORARY ARCHITECTURES 9 hours
Hand-held devices; over view of embedded systems; trends in processor architecture
Text / Reference 1. D.A. Patterson & J.L. Hennessy, Computer organization & design: The
Books hardware/ software interface, Morgan Kaufmann, 5th
Edition, 2013
2. D. Sima, T. Fountain, P. Kacsuk, "Advanced Computer Architectures: A
Course Code DATA COMMUNICATIONS L T P C CSE317 3 0 0 3 Course Computer Networks
Prerequisites Objectives 1. To lay foundations for data and digital communication.
2. To describe about various transmission types. 3. To understand error control coding techniques
Expected On completion of the course, the students will be able to
Outcome 1. Analyze the fundamentals of data & digital communication sampling techniques. 2. Compare the transmission mechanisms 3. Apply various encoding schemes of data communication in communication systems.
This course meets the following student outcomes: b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution. e) An ability to identify, formulate and solve engineering problems. h) An ability to address contemporary issues and analyze the local and global impact of computing and engineering solutions on individuals, organizations and society i) Design and conduct experiments as well as analyze and interpret data. k) An ability to use current techniques, skills and tools necessary for computing and engineering practice. l) An ability to apply mathematical foundations, algorithmic principles and computer science theory in the modeling and design of computer-based systems (CS)
Unit 1 INTRODUCTION 9 hours Key elements of communication model, Data communication, The effectiveness of data communication dependents, Components, Classification of communication networks, The TCP/IP Protocol Architecture, OSI Layers, Protocols in OSI reference model
Unit 2 ANALOG AND DIGITAL 9 hours
TRANSMISSION Transmission terminology, Frequency, spectrum, and bandwidth, Frequency -domain concepts , Spectrum , Analog and Digital Data Transmission , Transmission Impairments, Attenuation Distortion , Delay Distortion , Noise , Thermal Noise , Intermediation Noise , Crosstalk Noise , Impulse Noise , Channel Capacity
Unit 3 TRANSMISSION MEDIA 9 hours Guided media, Open Wire, Twisted Pair, Optical Fiber , Unguided transmission media; Ground wave propagation, Line of sight propagation; Radio Frequencies , Microwave , Satellites
Unit 4 SYNCHRONOUS / ASYNCHRONOUS 9 hours
TRANSMISSION Parallel and Serial Transmission, Parallel transmission, Serial Transmission, Synchronous transmissi on, Bit synchronization, Character synchronization, Asynchronous transmission, Asynchronous Start-Stop Systems, Start bit and bit synchronization; Line configuration: Topology, Point-to-point configuration, Multi point link, Mode of transmission, Simplex, Half duplex, Full Duplex; Interfacing: Interface Standards: EIA-232 Interface, Dial-Up operation using V.24/EIA-232; Null modem, ISDN interface, Balanced vs. Unbalanced Interfaces:
Unit 5 ENCODING SCHEMES 9 hours Digital-to-Digital encoding scheme: Unipolar, Polar,Non-Return –to- Zero (NRZ) encoding, Non Return-to-Zero-Level (NRZ-L), Non Return-to-Zero Inverted (NRZ-I), Return-to-Zero, Biphase: Manchester, Differential Manchester, Bipolar, Bipolar Alternate Mark Inversion(BAMI), Bipolar 8-Zeroes Substitution (B8ZS), High Density bipolar-3 zeros (HDB3); Analog –to – Digital Encoding scheme: PCM (Pulse Code Modulation), Delta Modulation (DM), ; Analog-to- Analog Encoding Scheme: Amplitude modulation (AM), Frequency modulation (FM) , Phase modulation (PM), Digital -to- Analog Encoding scheme, Amplitude Shift Keying (ASK), Frequency Shift Keying (FSK), Phase Shift Keying (PSK), Spread Spectrum Text / Reference 1. Behrouz A Forouzan, Data Communications and Networking, Tata
Books 2.
Mc-grawhill, 5th
Edition, 2012.
W. Stallings, Data & Computer Communications, Prentice-Hall,
3.
10th
Edition, 2013.
Simon Haykins, “Digital Communications”, John Wiley, 2013.
Course Code IMAGE PROCESSING L T P C CSE412 3 0 0 3 Course Linear Algebra Prerequisites Objectives 1. To introduce the basic concepts of digital image processing and image transforms
2. To explore the image enhancement, Image segmentation and restoration techniques
Expected Outcome On completion of the course, the students will be able to 1. Understand and apply the fundamental image processing techniques in analyzing and defining
image processing applications with an understanding of ethical and social issues. 2. Apply and Implement image processing principles using available tools and techniques
in the construction of imaging applications This course meets the following student outcomes: a) An ability to apply the knowledge of mathematics, science and computing appropriate to the discipline. b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution. f) An understanding of professional, ethical, legal, security and social issues and responsibilities i) Design and conduct experiments as well as analyze and interpret data.
k) An ability to use current techniques, skills and tools necessary for computing and engineering practice. l) An ability to apply mathematical foundations, algorithmic principles and computer science theory in the modeling and design of computer-based systems (CS)
Unit 1 DIGITAL IMAGE FUNDAMENTAL 9 hours Elements of digital image processing systems, Elements of Visual perception, Image Acquisition systems, Image sampling and quantization, Matrix and Singular Value representation of discrete images. Unit 2 IMAGE TRANSFORMS 9 hours 1D DFT, 2D DFT, Cosine, FFT, Sine Hadamard, Haar, Slant, KL, SVD transform and their properties. Unit 3 IMAGE ENHANCEMENT 9 hours Histogram – Modification and specification techniques Image smoothing, Image sharpening, generation of spatial m asks from frequency domain specification, Noise models – Linear and Nonlinear filters, Homomorphic filtering, Image Segmentation and its types, Morphological based operations, Color processing: false color, Pseudocolor and color image processing. Unit 4 IMAGE RESTORATION AND 9 hours
RECOGNITION Image degradation models, Unconstrained and Constrained restoration, inverse filtering, least mean square filter, Pattern Classes, optimal statistical classifiers Unit 5 IMAGE COMPRESSION 9 hours Runlength, Huffman coding, Shift codes, arithmetic coding, bit plane coding, transform coding, JPEG Standard, wavelet transform, predictive techniques, Block truncation coding schemes, Facet modeling. Text / Reference 1. Anil K.Jain, “Fundamentals of Digital Image Processing”, Prentice Hall of India,
Books 2nd
Edition,2004.
2. Rafel C. Gonzalez and Richard E. Woods, Digital Image Processing”, Addison
Wesley, 3rd
Edition, 2009.
3. William K. Pratt, “Digital Image Processing”, John Wiley, NJ, 4 th
Edition, 2007.
4. Sid Ahmed M.A., “Image Processing Theory, Algorithm and Architectures”,
Course Code INFORMATION SECURITY L T P C CSE415 3 0 0 3 Course Internet and Web Programming
Prerequisites Internet and Web Programming Lab Objectives 1. To introduce various threats and attacks in a network
2. To study cryptographic techniques during the design of information systems. 3. To learn security aspects related to E-mail and fire wall designs.
Expected On completion of the course, the students will be able to Outcome 1. Understand various kinds of encryption and decryption mechanisms
2. Analyze and implement various cryptographic techniques 3. Familiarity with the techniques and issues related to information systems
This course meets the following student outcomes:
a) An ability to apply the knowledge of mathematics, science and computing appropriate to the discipline. b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution. h) An ability to address contemporary issues and analyze the local and global impact of computing and engineering solutions on individuals, organizations and society i) Design and conduct experiments as well as analyze and interpret data. k) An ability to use current techniques, skills and tools necessary for computing and engineering practice. l)An ability to apply mathematical foundations, algorithmic principles and computer science theory in the modeling and design of computer-based systems (CS)
Unit 1 Network Attacks and Threats 9 hours Security Attacks (Interruption, Interception, Modification and Fabrication), Security Services (Con fidentiality, Authentication, Integrity, Non-repudiation, access Control and Availability) and Mechanisms, A model for Internetwork security, Internet Standards and RFCs, Buffer overflow & format string vulnerabilities, TCP session hijacking, ARP attacks, route table modification, UDP hijacking, and man-in-the-middle attacks Unit 2 Symmetric Cryptography 9 hours Conventional Encryption Principles, Conventional encryption algorithms, cipher block modes of operat ion, location of encryption devices, key distribution Approaches of Message Authentication, Secure Hash Functions and HMAC Unit 3 Asymmetric Cryptography & Key 9 hours
Management Public key cryptography principles, public key cryptography algorithms, digital signatures, digital Certificates, Certificate Authority and key management Kerberos, X.509 Directory Authentication Service E-Security certificates – Generation and assessment tools
Unit 4 E-Mail Security 9 hours Email privacy: Pretty Good Privacy (PGP) and S/MIME. IP Security Overview, IP Security Architecture, Authentication Header, Encapsulating Security Payload, Combining Security Associations and Key Management Web Security Requirements, Secure Socket Layer (SSL) and Transport Layer Security (TLS), Secure Electronic Transaction (SET) Unit 5 Firewall & Vulnerability 9 hours
Basic concepts of SNMP, SNMPv1 Community facility and SNMPv3, Intruders, Viruses and related threats, Vulnerability assessment – Overview, tools and applications. Firewall Design principles, Trusted Systems, Intrusion Detection Systems Text / Reference 1.William Stallings, Network Security Essentials (Applications and
Books Standards), Pearson Education, 4th
Edition, 2010
2. Dan Kaminsky, Rain Forest Puppy, Joe Grand, David Ahmad, Hal
Flynn Ido Dubrawsky, Steve W.Manzuik and Ryan Permeh, Hack
Proofing your network by Ryan Russell, wiley Dreamtech, 2nd
Edition, Syngress Publishers, 2002
3. Eric Maiwald, Fundamentals of Network Security, McGraw-Hill
Osborne Media; 2010.
4. Whitman, Thomson, Principles of Information Security, Course
Technology, 4th Edition, 2011.
5. Stallings, Cryptography and Network Security, Third edition, Pearson
Publications, 2013
6. Robert Bragg, Mark Rhodes, Network Security: The complete
Course Code SOFT COMPUTING L T P C CSE319 3 0 0 3 Course Algorithms Design and Analysis
Prerequisites Theory of Computation Objectives 1. To introduce the concepts of neural networks and advanced neural networks
2. To understand the fundamentals of fuzzy sets and fuzzy logic 3. To establish basic knowledge about optimization techniques in soft computing.
Expected On completion of the course, the students will be able to
Outcome 1. Design soft computing techniques for various applications domains 2. Lead project teams in the design of soft computing related projects
This course meets the following student outcomes: a) An ability to apply the knowledge of mathematics, science and computing appropriate to the discipline. b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution. c) An ability to design, implement and evaluate a system / computer based system process, component or program to meet desired needs. e) An ability to identify, formulate and solve engineering problems. i)Design and conduct experiments as well as analyze and interpret data
Unit 1 Neural Networks 8 hours History, Mathematical model of neuron, ANN architectures, Learning rules, Learning Paradigms. Percep tron network, Backpropagation network, Backpropagation learning and its applications, Variants of BPA. Unit 2 Advanced Neural Networks 9 hours Associative Memory: Auto correlation, Hetero Correlation, Exponential BAM, Applications. Adaptive Resonance Theory: Vector Quantization, ART1, ART2, applications, Kohonen’s Self Organizing Map. Unit 4 Fuzzy Sets and Relations 8 hours Uncertainty and Imprecision, Chance vs ambiguity, Fuzzy Sets, Fuzzy Relations, Membership functions, Properties of Membership functions, Fuzzification and Defuzzification.
Unit 5 Fuzzy Logic 10 hours Classical Logic and Fuzzy logic, Fuzzy Rule based systems, Fuzzy Decision making, Fuzzy Classification, Fuzzy Pattern Recognition, Applications – MATLAB and Soft Computing. Unit 5 Optimization Techniques 10 hours Derivative based Optimization – Descent Methods – Genetic Algorithms – Ant Colony Optimization – Particle Swarm Optimization, Case Study - fraud detection, health care using Soft computing techniques. Text / Reference 1. T.J. Ross, “Fuzzy Logic with Engineering Applications”, McGraw
Books Hill, 3rd Edition, 2010.
2. S. Rajasekaran and G.A.V. Pai, “Neural Networks, Fuzzy Logic and
Genetic Algorithms: Synthesis and Applications”, PHI, 2012.
3. Davis E. Goldberg, “Genetic Algorithms: Search, Optimization and
Machine Learning”, Pearson Educaton, 2009.
4. Zurada, J.M. “Introduction to Artificial Neural systems”, Jaico
Course Code CLOUD COMPUTING L T P C CSE416 3 0 0 3 Course
Prerequisites Software Engineering Objectives 1.To acquire good working knowledge of the essentials of next generation software
business 2.To understand fundamentals of cloud computing
Expected On completion of the course, the students will be able to Outcome -Provide convenient, on-demand network access to a shared pool of configurable
computing resources that can be rapidly provisioned and released with minimal management effort or service provider interaction. This course meets the following student outcomes: c)An ability to design, implement and evaluate a system / computer based system process, component or program to meet desired needs e) An ability to identify, formulate and solve engineering problems. f)An understanding of professional, ethical, legal, security and social issues and responsibilities k) An ability to use current techniques, skills and tools necessary for computing and engineering practice. l)An ability to apply mathematical foundations, algorithmic principles and computer science theory in the modeling and design of computer-based systems (CS)
Unit 1 NEW COMPUTING PARADIGMS & SERVICES 7 hours Edge computing, Grid computing, Utility computing, Distributed computing, Cloud computing and its hi story and evolution Unit 2 INTRODUCTION TO CLOUD COMPUTING 10 hours Cloud Computing Architectural Framework, Cloud Deployment Models, private, public and hybrid, Challenges in adapting a cloud in the context of i) Security issues ii) Bandwidth and iii) Integration issues, Virtualization in Cloud Computing, Parallelization in Cloud Computing, Security for Cloud Computing, Cloud Economics Unit 4 CLOUD SERVICE MODELS 11 hours Software as a Service (SaaS), Infrastructure as a Service (IaaS), Platform as a Service (PaaS), Seve n Business Models for cloud, five-layer cloud service stack, compute and storage cloud services case studies Jeff Bezos and Amazon Unit 5 FOUNDATIONAL ELEMENTS OF CLOUD 9 hours COMPUTING Virtualization, Browser as a platform, Introduction to Web 2.0, Introduction to Autonomic Systems, S ervice Level Agreements, Cloud Computing architecture and industry frameworks such as MapReduce Unit 5 CLOUD COMPUTING PRACTICES 8 hours Virtualization, Cloud Computing Operating System, Creating Windows servers on the cloud, Creating L inux servers on the cloud, Deploying applications on the cloud, Major cloud solutions Text / Reference 1.Rajkumar Buyya, James Broberg, Andrzej M. Goscinski, Cloud Computing Principles Books and Paradigms, Wiley, 2010
2.Michael Miller , Cloud Computing: Web-Based Applications That Change the Way You Work and Collaborate Online, Que Publishing ,2009 3.Toby Velte, Anthony Velte, Robert Elsenpeter , Cloud Computing, A Practical Approach, McGrawHill, 2010 4.Judith Hurwitz, Robin Bloor , Marcia Kaufman , Fern Halper , Cloud Computing For Dummies, Wiley Publishing, 2010
5.Nick Antonopoulos, Lee Gillam, Cloud Computing: Principles, Systems and Applications, Springer, 2010
Course Code MULTICORE SYSTEMS PROGRAMMING L T P C CSE320 3 0 0 3 Course
Prerequisites Computer Architecture and Organization Objectives To differentiate between a single processor and multi -core processor
To understand fundmentals of parallel programming models To parallelize serial programs and develop a parallel application To use profiling and debugging tools for multi-core systems
Expected On completion of the course, the students will be able to
Outcome -Participate in the development of applications on multi-core systems
This course meets the following student outcomes: a) An ability to apply the knowledge of mathematics, science and computing appropriate to the discipline. b) An ability to analyze a problem, identify and define the computing requirements ap propriate to its solution. i) Design and conduct experiments as well as analyze and interpret data j) Recognition of the need for and an ability to engage in continuing professional learning (lifelong learning) k) An ability to use current techniques, skills and tools necessary for computing and engineering practice.
Unit 1 INTRODUCTION TO MULTICORE 10 hours ARCHITECTURES
Overview of Single core processor Architecture and its limitations, Architectural Innovations, Need for Multi - core Processor and its Limitations, Classification Multi-cores, Multicore system software stack Unit 2 PROGRAMMING WITH THREADS 9 hours Thread libraries, Thread creation , Scheduling, Memory management and memory ,locators Synchronizati on and atomic operations Unit 4 PROGRAMMING WITH OPENMP 9 hours qOpenMP parallelization, OpenMP loop and functional, parallelization, OpenMP scheduling, Extensions in the context of multicore processors
Unit 5 CUDA PROGRAMMING MODEL 9 hours Introduction to CUDA programming, CUDA Threads, CUDA Memory, Control Flow, CUDA features and tools, CUDA examples Unit 5 TRANSACTIONAL MEMORY 8 hours Programming with transactions, Optimizing transactions, Non -blocking data structures and synchronization. Case Study I: Intel Montecito, Case Study II: IBM Power5, Case Study III: IBM Cell, Case Study IV: Sun Niagara or Ultrasparc Text / 1. Shameem Akhter and Jason Roberts, Multi-Core Programming, Intel Press, 2007. Reference 2. Michael j Quin, “ Parallel Computing, Theory & Practices”, McGraw Hill,2002 Books 3. David B. Kirk , Wen-mei W. Hwu, Programming Massively Parallel Processors: A Hands-
on Approach, Morgan Kaufmann, 2 nd
Edition,2012. 4. The Free Lunch Is Over: A Fundamental Turn Toward Concurrency in Software.” Herb Sutter. Dr. Dobb’s Journal, March 2005 5. David Culler , J.P. Singh , Anoop Gupta, Parallel Computer Architecture: A Hardware/Software Approach, Morgan Kaufmann,2001
Course Code C++ PROGRAMMING L T P C CSE215 3 0 0 3 Course Programming in C
Prerequisites Objectives To enable the students to learn the basic and advanced concepts of programming using
C++. On successful completion of the course the students will be able to, Apprehend the syntax and semantics of the c++ programming language. Use the class and objects to create applications. Design and Create new applications by interconnecting many classes and reusing the code. Synthesize generic class templates to be used with different types of data.
Expected Outcome At the end of the course, students should able to Apply and use the object oriented concepts/ techniques, tools in modeling computer based/ software system
This course meets the following student outcomes: b) An ability to analyze a problem, identify and define the computing requirements appropriate to its solution. c)An ability to design, implement and evaluate a system / computer based system process, component or program to meet desired needs i) Design and conduct experiments as well as analyze and interpret data. k) An ability to use current techniques, skills and tools necessary for computing and engineering practice. l)An ability to apply mathematical foundations, algorithmic principles and computer science theory in the modeling and design of computer-based systems (CS) m) An ability to apply design and development principles in the construction of software systems. (CS)
Unit 1 Introduction to Fundamentals 10 hours concepts of OOP
Object oriented fundamentals- Structured versus object-oriented development- elements of object oriented programming- benefits of OOP- structure of C++ program– Static members, Working with classes, Classes and Objects-Class specification- class objects- accessing class members- defining member functions - Passing and returning objects – Array of objects - inline functions - accessing member functions within class. Unit 2 Object Initialization and 8 hours
Cleanup Constructors - Parameterized constructors - Constructor overloading. Destructors, Default arguments - new, delete operators - “this” pointer, friend classes and friend functions. Unit 3 Overloading 10 hours Function overloading – Operator overloading - over loadable operators- unary operator overloading- operator keyword- limitations of increment/decrement operators- binary operator overloading- Generic programming with templates-Function templates- class templates Unit 4 Inheritance 8 hours Inheritance-Base class and derived class relationship-derived class declaration-Forms of inheritance-inheritance and member accessibility- constructors in derived class and virtual functions Unit 5 Exception handling and Files 9 hours
Files and Streams-Opening and Closing a file- file modes- file pointers and their manipulation, sequential access to a file-random access to a file-Reading and Writing files - Exception handling exception handling model-exception handling constructs-catching exceptions and handling exceptions. Text/Reference 1. K.R. Venugopal, T. Ravishankar, and Rajkumar, "Mastering C++”, Tata
Books 2.
McGraw Hill, 2nd
Edition,2013.
E. Balagurusamy, “Object Oriented Programming with C++”, Tata McGraw
3.
Hill, 6th Edition, 2014.
Bjarne stroustrup, “The C++ programming Language”, Addison Wesley, 4th
4.
edition, 2014.
Harvey M. Deitel and Paul J. Deitel, “C++ How to Program”, 9 th
