Academic Programs

• M.Tech. (Computer Science & Engineering) – Two Years Full-time
• M.Tech. & Ph.D. (Electrical Engineering) (Deferred)
• Master of Computer Applications (MCA 3-Year) -Three Years Full-time
• Master of Computer Applications (MCA 2-Year) -Two Years Full-time (Lateral Entry)

For Duration, Eligibility, Admission Procedure and Syllabus, refer to Prospectus

UG Courses

Course No.:AI-011

Course Title: Agricultural Informatics and Artificial Intelligence

Credits: 3(2+1)   

Semester:   Sem I

Theory:

Introduction to Computers, Anatomy of Computers, Memory Concepts, Units of Memory, Operating System: Definition and types, Applications of MS-Office for creating, Editing and Formatting a document, Data presentation, Tabulation and graph creation, Statistical analysis, Mathematical expressions, Database, concepts and types, creating database, Uses of DBMS in Agriculture, Internet and World Wide Web (www): Concepts and components. Introduction and types of software; applications of computer programming.

e-Agriculture, Concepts, design and development; Application of innovative ways to use information and communication technologies (IT) in Agriculture; Computer Models in Agriculture: Statistical, weather analysis and crop simulation models, concepts, structure, inputs outputs files, limitation, advantages and application of models for understanding plant processes, sensitivity, verification, calibration and validation; IT applications for computation of water and nutrient requirement of crops; Computer-controlled devices (automated systems) for Agri-input management; Smartphone mobile apps in agriculture for farm advice: Market price, postharvest management etc.; Geospatial technology: Concepts, techniques, components and uses for generating valuable agri-information; Decision support systems: Concepts components and applications in agriculture; Agriculture Expert System; Soil Information Systems etc. for supporting farm decisions. Preparation of contingent crop-planning and crop calendars using IT tools; Digital India and schemes to promote digitalization of agriculture in India.

Introduction to artificial intelligence, background and applications, Turing test. Use of AI in agriculture for autonomous crop management, and health, monitoring livestock health, intelligent pesticide application, yield mapping and predictive analysis, automatic weeding and harvesting, sorting of produce, and other food processing applications; Concepts of smart agriculture, use of AI in food and nutrition science etc.

Practical: Study of computer components, accessories, practice of important DoS Commands, Introduction of different operating systems such as Windows, Unix/ Linux, creating files and folders, File Management. Use of MS-WORD and MS Power-point for creating, editing and presenting scientific documents, MS-EXCEL – Creating a spreadsheet, Use of statistical tools, Writing expressions, Creating graphs, Analysis of scientific data, Handling macros. MS-ACCESS: Creating Database, preparing queries and reports, Demonstration of Agri- information system, Introduction to World Wide Web (WWW) and its components, Hands on practice on Crop Simulation Models (CSM), DSSAT/Crop-Info/Crop Syst/ Wofost, Preparation of inputs file for CSM and study of model outputs, computation of water and nutrient requirements of crop using CSM and IT tools, Use of smart phones and other devices in agro-advisory and dissemination of market information, Introduction of Geospatial Technology, Hands on practice on preparation of Decision Support System, Preparation of contingent crop planning, India Digital Ecosystem of Agriculture (IDEA)

Course No.:CSE-111

Course Title: Computer Programming and Data Structures

Credits:2(0+2)  

Semester:     Sem II

Practical: Introduction to high level languages; Structure programming, C programming, a simple C programming, execution of a C program, program and instruction; Familiarizing with Turbo C IDE; Building an executable version of C program; Study of different operators such as arithmetic, relational, logical, assignment, increment and decrement, conditional, bitwise and special operators, precedence of arithmetic operators; Debugging a C program; Developing and executing simple programs; Creating programs using decision making statements such as if, go to and switch; Developing program using loop statements while, do and for; Using nested control structures; Familiarizing with one and two dimensional arrays; Using string functions; Creating user defined functions; Developing structures and union; Using local, global and external variables; Using pointers; Developing linked lists in C language; Inserting an item in Linked List; Deleting an item in Linked List; Implementing Stacks; Implementing push/pop functions; Creating queues, Insertion/ Deletion in queues.

Course No.:AI-311

Course Title: Sensors Artificial Intelligence and Robotics in Agriculture

Credits:3(2+1)

Semester:       Sem II

Theory:

Sensors Fundamentals: Introduction to sensors and transducers; Need for sensors in the agriculture; Sensor Classification; Units of measurements; Sensor characteristics, Active and passive sensors– static characteristics, dynamic characteristics- first and second order sensors; Remote sensing, data acquisition and their analysis; Sensors in different applications: Principle and working of sensors for soil moisture, soil temperature, chlorophyll meter, colour sensor, spectral sensor, temperature sensor, humidity sensor, wind speed, motion sensors, position sensor etc.

Selection of sensors:

Introduction to Artificial Intelligence: Overview- foundations, scope, problems, history and approaches of AI. Intelligent agents: reactive, deliberative, goal driven, utility-driven, and learning agents, AI programming techniques. Classical AI, concept of expert system, conflict resolution, multiple rules, forward chaining, backward chaining; Advantages and limitations of AI systems.

Problem-solving through Search: Forward and backward, state-space, blind, heuristic, problem reduction, alpha-beta pruning, minimax, constraint propagation, neural, stochastic, and evolutionary search algorithms, bidirectional search, heuristic search, problems and examples.

Knowledge Representation and Reasoning: Foundations of knowledge representation and reasoning, representing and reasoning about objects, relations, events, actions, time, and space; predicate logic, situation calculus, description logics, reasoning with defaults, reasoning about knowledge, sample applications. Planning: planning as search, partial order planning, construction and use of planning graphs.

Robotics: Introduction to Robotics-classification with respect to geometrical configuration (anatomy), selection based on the agriculture application; Hardware for robot, sensors and actuator

in robot, control of robot, system interface and integration in robot; robot programming, Feedback system, safety sensors; Controlled system and chain type: Serial manipulator and Parallel Manipulator. Components of Industrial robotics-precession of movement-resolution, accuracy and Repeatability-Dynamic characteristics- speed of motion, load carrying capacity and speed of response.

Application in Agriculture: Introduction to precision farming tools for implementation of precision agriculture; Application of site-specific management – nutrient management, agrochemicals and fertilizer management, weeds management; Application of drone- pesticides/nutrient spraying, environmental monitoring; Yield monitoring and mapping, image processing- shape analysis, feature detection and object location, Use of sensors, artificial intelligence and robotics in different agricultural applications.

Practical: Introduction to open source programming languages, advantages and drawbacks of open source programming; Programming in Embedded- C, Concepts of C language; Identify various components in open source hardware (arduino and raspberry pi); Using of open source hardware and program for LED blink; Using of open source hardware and program for buzzer; Measurement of distance using ultrasonic sensor and IR sensor using open source hardware and programs; Experiment using moisture, temperature and relative humidity sensors for automatic irrigation and protected cultivation; Learning on open source image processing software for shape analysis and object detection; Learning about the different applications of robots in agriculture; Fabrication and integration of sensors; Visit to robot fabrication facilities/workshop. Practical use of sensors, artificial intelligence and robotics in different agricultural applications.

Course No.:EE-111

Course Title:  Basic Electrical Gadgets and Instruments

Credits:3(2+1)  

Semester:     Sem II

Theory: Introduction to different electrical appliances used in agricultural settings and farm operations; Difference between AC and DC supply system; Introduction to AC fundamentals; AC through series RL, RC, and RLC circuits, parallel AC circuit, series and parallel resonance; Q-factor and bandwidth. Three- phase AC circuit: Concept of balanced three-phase AC circuits, line and phase quantity in star and delta network, power in three-phase circuit, various methods of three phase power measurement like (one wattmeter and two –wattmeter method). Diode and its applications: Rectifier, Clipper, Clamper, voltage multiplier and capacitive filter zener diode as voltage    regulator.

Transistor and its applications: Bipolar junction transistor, operating point. Various biasing methods, fixed, self biasing and potential divider biasing method; OP-AMP, Ideal OP-AMP characteristics, Linear and non-linear applications of OP-AMP (adder, subtractor, integrator, active rectifier, comparator).

Introduction to digital electronics and logic gates: Basic theorem of boolean algebra, combinational logic circuits (basic gates, SOP rule and K-map), binary adder. Principles of general instruments, measurement of displacement, temperature, velocity, force and pressure using different instruments like strain gauges, load cell, thermistors, thermocouples, pyrometer, linear variable differential transformer (LVDT), capacitive transducers, RTD, instruments for measurement of speed, wind velocity, solar radiation, anemometer, multimeter, etc.

Practical: Basic Electrical and Electronics Gadgets; To prepare an electrical switch board to control two light points, one plug point, one fan point and fuse (House wiring); To prepare an electrical switch board to control two light points using two-way switch (staircase wiring); To connect and test a fluorescent lamp; To find faults and repair home appliances such as heater, electric iron, fans and  mixer-grinder, etc.; To find faults and repair UPS; To measure the power requirement and power factor in a AC single phase series RLC circuit; To measure energy of a single phase AC circuit with the help of ammeter, voltmeter and power factor meter and energy meter; To measure the power consumption in a three-phase circuit using two-wattmeter method.

Course No.:EE-411

Course Title: Electrical Machines

Credits: 3(2+1)

Semester:       Sem I

Theory: Introduction to electrical machines; Basic principles of operation of electrical machines used in agricultural engineering such asDC generator, DC motor, 1-phase induction motor, 3-phase induction motor and BLDC motor

Magnetic circuit: concept of magnetic flux production, magneto-motive force, reluctance, laws of magnetic circuits, determination of ampere-turns for series and parallel magnetic circuits, hysteresis and eddy current losses. Transformer: principle of working, construction of single phase transformer, EMF equation, phasor diagram on load/ load, leakage reactance, voltage regulation, power and energy efficiency, open circuit and short circuit tests; D.C. machines: principles operation and performance of DC machine (generator and motor), EMF and torque equations, excitation of DC generator and their characteristics, DC motor characteristics, starting of shunt and series motor, starters, speed control methods-field and armature control.

Three phase induction motor: construction, operation, types, concept of slip; slip speed and slip frequency, torque equation, torque-speed and torque-slip characteristics, maximum torque for starting and running condition. phasor diagram, starting and speed control methods; Single phase induction motor: principle of operation, double field revolving theory, characteristics, methods of starting, phase split, shaded pole motors, performance characteristics.

Practical: To study different parts of DC/AC machines; To perform open circuit test on a single phase transformer and determine its iron loss as well as open circuit parameters; To perform short circuit test on a single phase transformer and hence find copper loss, equivalent circuit parameters, voltage regulation and efficiency; To study how to start the D.C motor using 3-point Starter; To start and run the D.C. motor (shunt, series and compound); To control the speed of DC shunt motor using flux control method; To control the speed of DC shunt motor using armature voltage control method; To conduct brake test on DC shunt motor and to determine its performance curves; To obtain the load characteristics of DC shunt motor and draw its characteristics; To start and run the 3-phase induction motor using star-delta starter and to find different voltage and current under star and delta connection; To perform no-load test on3-phase induction motor and to determine its no-load losses; To perform blocked-rotor tests on 3-phase induction motor to obtain the equivalent circuit parameters and to draw the circle diagram; To perform no load on1-phase induction motor to determine its no-load losses; To perform blocked-rotor test on 1-phase induction motor and to determine the parameters of equivalent circuit on the basis of double revolving field theory; To perform load-teston1-phase induction motor and plot torque-speed characteristic.

Course No.:MCA-411

Course Title:  MATLAB Programming

Credits: 3(1+2)  

Semester:     Sem II

Theory: Introduction: platform and features, prerequisites and system requirements, advantages and disadvantages. Commands, environment, working with variables and arrays, workspace, variables and functions, data types, operator, formatting text. MATLAB Control Statements: if statement, if-else statement, if-elseif statement, nested if-else, switch. MATLAB loops: for loop, while loop, nested loop, break, continue. MATLAB error control: error control statement-try and catch. Arrays and functions: matrices and arrays, multi-dimensional arrays, compatible array, sparse matrices; Functions: normal functions, predefined functions, user-defined functions, anonymous. Function 2D Plots: fplot(), Semilogx(), Semilogy(), loglog(), fill(), Bar(), errorbar(), barh(), plotyy(), area(), Pie(), hist(), stem(), Stairs(), compass(), comet(), contour(), quiver(), pcolor(); 3D Plots: plot3(), fill3(), contour3(), surf(), surfc(), mesh(), meshz(), waterfall(), stem3(), ribbon(), sphere(), ellipsoid(), cylinder(), slice()

Practical: Hands on experience with MATLAB functionalities and its installation on different platforms; MATLAB project based on real time Agricultural Engineering problems.

Course No.:MCA-412

Course Title: Python Programming

Credits: 3(1+2)   

Semester:   Sem II

Theory: Introduction: history, applications, installation. Variables, data types, keywords, literals, operators, comments. Conditional statements: if else, loops, for loop, while loop, break, continue, pass, strings, lists, tuples, list vs tuple.

Functions: functions, built-in functions, lambda functions. Files I/O, modules, exceptions, date, Regex, read CSV File, write CSV File, read excel file, write excel file, assert, list comprehension, collection. Module, math module, OS module, random module, statistics module, sys module, IDEs, arrays, command line arguments, stack and queue. Python OOPs: OOPs concepts, object class, constructors, inheritance, abstraction.

Practical: Hands on experience with Python and its installation on different platforms; Accessing python from GUI and from command prompt / terminal, a project based on real time agricultural engineering problems.

Course No.:AI-411

Course Title: Artificial Intelligence Applications

Credits: 3(2+1)      

Semester: Sem II

Theory: Foundation and history of artificial intelligence; Intelligent agents, structure of agents; AI programming languages,  introduction to PYTHON; Solving problems by searching, problem solving agents, infrastructure for search algorithms, measuring problem solving performance, blind search strategies, breadth first search, depth first search, heuristic search techniques,, best first- A* algorithm, AO* algorithm; Hill climbing search, Genetic Algorithms; Games, game tree, game playing, min-max algorithms, alpha beta pruning; Logical agents, knowledge representation issues, predicate logic, logic programming; Constraint satisfaction problems, backtracking search; Knowledge representation- representing knowledge using rules, rules based deduction systems, semantic nets, frames, inheritance, temporal reasoning; Introduction to uncertainty, Quantifying uncertainty, reasoning under uncertainty; Probabilistic reasoning- review of probability, Baye’s probabilistic interferences, Bayes’ rule and its use; fuzzy reasoning; Classical planning- planning, representation for planning, partial order planning algorithm; Supervised learning, artificial neural networks, neural network structures, single-layer feed-forward neural networks (perceptron), multilayer feed-forward neural networks, learning in multilayer networks;  Knowledge in learning- a logical formulation of learning, explanation-based learning; Natural language processing- principles of natural language processing; Expert systems, knowledge acquisition concepts; Robotics, AI application to robotics; Current trends in intelligent systems.

Practical: Hands on exercise on problem solving in artificial intelligence, details of knowledge, reasoning, and planning in artificial intelligence, learning in artificial intelligence, communicating, perceiving, and acting in artificial intelligence and verifying engineering concepts in artificial intelligence.

Course No.:AI-412

Course Title:  Machine Learning

Credits:3(2+1)   

Semester:   Sem II

Theory: Introduction to Machine Learning, Preliminaries, what is machine learning; varieties of machine learning, learning input/output functions, bia, sample application. Different applications of machine learning,  Boolean functions and their classes, decision lists. Version spaces for learning, version graphs, learning search of a version space, candidate elimination methods; Neural Networks, threshold logic units, linear machines, networks of threshold learning units, Training of feed forward networks by back propagations, neural networks vs. knowledge-based systems; Statistical Learning, background and general method, learning belief networks, nearest neighbor. Decision-trees, supervised learning of uni-variance decision trees, network equivalent of decision trees, over fitting and evaluation. Introduction to PYTHON programming language: Operators, Control structures, Decision making, iterative statements, functions, Ensembling, boosting and bagging, Random forest, Evaluation Metrics for classification and regression, Unsupervised learning, clustering methods based on Euclidian distance and probabilities, hierarchical clustering methods. Introduction to reinforcement learning.

Practical: Hands on experience with Machine Learning functionalities and its use in agricultural engineering and allied fields.

Course No.:EE-151

Course Title: Basic Electrical Engineering

Credits: 3(2+1) 

Semester:      Sem II

Theory:  AC Fundamentals: Definitions of cycle, frequency, time period, amplitude, Peak value, RMS value, Average value, Electromotive force, Magnetic circuits, composite magnetic circuits, magnetic leakage, hysteresis and eddy currents, phase relations and vector representation, AC through resistance, inductance and capacitance, AC series and parallel circuits, Simple R-L, R-C and R-L-C circuits; Current, Voltage, Power, Circuit elements, Ohm’s law, Power factor and improvement, 3 Phase Systems: Star and Delta connections, Relationship between line and phase voltages and currents in Star and Delta connections, various methods of single and three phase power measurement. Transformer: Principle of working, construction of single-phase transformer, transformer core types, emf equation, Phasor diagrams, Ideal transformer, transformer on no load, Transformer under load, Equivalent circuits, Transformer losses, efficiency, Regulation, Open and short circuit test.

Single phase induction motor: Double field revolving theory, characteristics, phase split, shaded pole motors. Poly phase induction motor: Construction, operation, equivalent circuit, production of rotating field, effect of rotor resistance, torque equation, starting and speed control methods. Introduction of Alternators, types, EMF equation. D.C. Machine (generator and motor): Types, Construction and Operation, EMF equation, armature reaction, commutation of D.C. generator and their characteristics. D.C. Motors, their starting, speed controls and characteristics. Introduction to electric power economics, Measuring Equipment’s: Classification, Characteristics of different electrical measuring systems and equipment’s.

Electrical Wiring: system of wiring, types of wiring. Introduction to earthing and protection devices.

Practical: Study of voltage resonance in L.C.R. circuits at constant frequency: (a) Star connection study of voltage and current relation. (b) Delta connection study of voltage and current relation. Measurement of Power in 3 phase circuit by wattmeter and energy meter: (a) for balanced loads, (b) for unbalanced loads. Polarity test, no-load test, efficiency and regulation test of single-phase transformer, starting of induction motors by; (a) D.O.L. (b) Manual star delta (c) Automatic star delta starts. Starting of slip ring induction motors by normal and automatic rotor resistance starters. Test on 3 phase induction motor- determination of efficiency, line current, speed slip and power factor at various outputs. Determination of relation between the induced armature voltage and speed of separately excited D.C. generator. Magnetization characteristics of D.C. generator. Study the starter connection and starting reversing and adjusting speed of a D.C. motor. Problems on Industrial Electrification. Study of various circuit protection devices. Study of various measuring instruments.

Course No.:EE-251

Course Title:  Basic Electronics Engineering

Credits:2(1+1)

Semester:        Sem I

Theory: Semiconductors, P-n junction, V-I characteristics of P-n junction, diode as a circuit element, rectifier; Diode circuits for OR and AND (both positive and negative logic); voltage multiplier, filter circuits; Bipolar junction transistor: Operating point, classification (A, B and C) of amplifier, various biasing methods (fixed, self, potential divider); Ideal OP-AMP characteristics, linear and nonlinear applications of OP-AMP integrator, active rectifier, comparator, differentiator, differential, instrumentation amplifier and oscillator), Zener diode voltage regulator, transistor series regulator, current limiters, OP-AMP voltage regulators; Basic theorem of Boolean algebra; Combinational logic circuits (basic gates, SOP rule and K-map) and sequential logic circuits binary ladder D/A converter and A/D converter; Transducers: Classification, selection criteria, characteristics, sensors and actuators construction, working principles, applications of following transducers- Potentiometers RTD, thermocouples, thermistors, LVDT, strain gauges, capacitive and inductive transducers, piezoelectric transducers, photoelectric transducers, self-generating transducers, variable parameter type, digital, actuating and controlling devices.

Practical: Study of diode characteristics; Study of triode characteristics; Study of Zener diode; Study of V-I characteristics of P-n junction diode; Study of RC coupled amplifier; Study of RC phase shift oscillator; Study of full wave rectifier; Verification of logic gates; Determination of energy gap in a junction diode; Study of transistor characteristics in CE configuration; Study of OP-Amp IC 741 as differential amplifier; Study of half wave rectifier; Study of OP-AMP IC 741 as an active rectifier; Study of transistor characteristics; Study of temperature characteristics of resistor; Study of diode as clipper and clamper

Course No.:CSE-451

Course Title: ICT Applications in Food Industry

Credits: 3(1+2)

Semester:        Sem I

Theory: Importance of computerization in food industry, operating environments and information systems for various types of food industries. Introduction to Supervisory control and data acquisition (SCADA): SCADA systems hardware, firmware, software and protocols, landlines, local area network systems, modems. Spreadsheet applications: Data interpretation and solving problems, preparation of charts, use of macros to solve engineering problems. Use of add‐ins, use of solver. Web hosting and webpage design; file transfer protocol (FTP), Online food process control from centralized server system in processing plant. Use of MATLAB in food industry; computing with MATLAB, Basic features of MATLAB, Writing program in MATLAB, script files and editor/debugger, MATLAB help system. Problem solving methodologies, numeric, cell, arrays and its operations, matrix operations; Control flow and operators: ‘‘if…end’’ structure, Relational and logical operators, ‘‘for…end’’ loop, ‘‘while…end’’ loop, Basic Functions in MATLAB, User defined functions, programming using MATLAB; debugging MATLAB programs; Data visualization using MATLAB.

Practical: Introduction to various features in spreadsheet; Solving problems using functions in spreadsheets; Use of Add-Ins in spread sheet and statistical data analysis using Analysis Tool pack; Solution of problems on regression analysis using Analysis Tool pack in spreadsheet; Solution of problems on optimization using solver package in spreadsheet; Introduction to MATLAB; Writing code using MATLAB programming; Introduction to Toolboxes useful to Food Industry, Introduction to CFD softwares, Introduction to GAMBIT software; Introduction to FLUENT software; Introduction to LabVIEW and NI-DAQ. LabVIEW – LabVIEW environment: Getting data into computer, data acquisition devices, NI-DAQ, simulated data acquisition, sound card, front panel/block diagram, toolbar/tools palette; Components of a LabVIEW application: data Flow execution, debugging techniques, additional help, context help, tips for working in LabVIEW, LabVIEW typical programs.

Course No.:EE-451

Course Title:  Instrumentation and Process Control in Food Industry

Credits:3(1+2)

Semester:       Sem I

Theory: Introduction, definitions, characteristics of instruments, static and dynamic characteristics, Temperature and temperature scales; Various types of thermometers; thermocouples, resistance thermometers and pyrometers; Pressure and pressure scales, manometers, pressure elements differential pressure. Liquid level measurement, different methods of liquid level measurement, flow measurement, differential pressure meters, variable area meters; Weight measurement: Mechanical scale, electronic tank scale, conveyor scale, Measurement of displacement, temperature, velocity, force and pressure using potentiometer, thermocouples; Transmission: Pneumatic and electrical, Control elements: control actions, pneumatic and electrical control systems; Process control: Definition, simple system analysis, dynamic behavior of simple process, generalized instrumentation system, basic building blocks of process control system, various applications of process control, Controllers and indicators: Temperature control, electronic controllers, timers and indicators, discrete controllers, adaptive and intelligent controllers. Computer-based monitoring and control: Importance, hardware features of data acquisition and control computer, signal interfacing, examples in food processing.

Practical: Study on instrumentation symbols; Determination of relative humidity by wet and dry bulb thermometer; Measurement of wind velocity by anemometer; Measurement of intensity of sun shine by sunshine recorders; Study of characteristics of pressure transducers, real-time study of pressure transducers characteristics with PC, characteristics of IC temperature sensor, characteristics of platinum RTD, temperature controlled alarm system; Study of water level to current conversion; Study of characteristics of capacitive transducer; Introduction of 8051/8085 based system and applications in processing. Programs like arithmetic operations addition,  subtraction, multiplication ,  division.

Course No.:CSE-351

Course Title:  Information and Communication Technology in Horticulture

Credits:3(1+2)    

Semester:   Sem I

Theory: IT and its importance. IT tools, IT-enabled services and their impact on society; Introduction to Computers, hardware and software; input and output devices; word and character representation; features of machine language, assembly language, high-level language and their advantages and disadvantages; Operating Systems, definition and types, Applications of Word Processing / Spreadsheet /Presentation /Databases for document creation and Editing, Data presentation, interpretation and graph creation, statistical analysis, mathematical expressions, Database concepts and types, uses of DBMS in Horticulture; Introduction to Local area network (LAN), Wide area network (WAN), Internet and World Wide Web, HTML and IP and Video conferencing, Introduction to e- Horticulture, concepts and applications, Use of ICT in Horticulture.

Practical: Practice with latest operating system for creating Files, Folders, File Management. Use of Word Processing/ Spreadsheet/ Presentation/ Databases with latest software packages; Creating a spreadsheet, Use of statistical tools, writing expressions, creating graphs, analysis of scientific data. Creating Database, preparing queries and reports, creation and operation of E mail account; Demonstration of Agri-information system using Mobile Apps. Internet applications: Web browsing, handling of audio-visual equipment. Planning, preparation, presentation of posters, charts. Introduction of Geospatial Technology of generating valuable information for Agriculture. Hands on Decision Support System. Preparation of contingent crop planning.

Course No.:SECCSE-11

Course Title: Computer Applications in Agriculture

Credits:2(0+2)   

Semester:    Sem I

Practical: Working with MS-DOS. Database design. Data entry operation. Word processing: MS Office. Database management program. Use of electronic spreadsheet and graphics. Use of SPSS statistical application packages. Use of SAS in agriculture and its application. Working with MS-DOS. Database design. Data entry operation. Use of electronic spreadsheet and graphics. Basics of computer networking – LAN, SAN – BUS – Tokening – Star – Internet, Intranet – Basics of Email – Exposure to web browsing (structure of URL), Types of websites – Internet service provider – using internet news.

PG Courses

Course no.: CSE 501

Course Title: Big Data Analytics

Credits: 3(2+1)

Semester: Sem I

Theory:

Unit-I

Data analysis, data matrix attributes. Data: Algebraic and geometric view, probabilistic view.

Unit-II

Basics of data mining and CRISP-DM, organizational and data understanding, purposes, Intents and limitations of data mining, database, data warehouse, data mart and data set, types of data, privacy and security, data preparation, collation and data scrubbing.

Unit-III

Data mining models and methods, correlation, association rules, k-means, clustering understanding of concept, preparation and modelling.

Unit-IV

Discriminant analysis, linear regression, logistic regression, understanding, preparation and modeling.

Unit-V

Decision trees, neural networks, understanding, preparation and modeling.

Practical: Introduction to OpenOffice and RapidMiner in data analytics and mining. Preparing RapidMiner, importing data, handling missing data, data reduction, handling Inconsistent data, attribute reduction. Performing different analysis using RapidMiner or suitable software.

Course no.: CSE 502

Course Title: Artificial Intelligence

Credits: 3(2+1)

Semester: Sem I,II

Theory:

Unit-I

Definitions of intelligence and artificial intelligence. What is involved in intelligence? Disciplines important to AI. History of development of AI. Different types of AI. Acting humanly, Turing test. AI systems in everyday life. Applications of AI.

Unit-II

Classical AI, concept of expert system, conflict resolution, multiple rules, forward chaining, backward chaining. Advantages and disadvantages of expert system. Fuzzy logic and fuzzy rules. Fuzzy expert systems.

Unit-III

Problem solving using AI, search techniques, breadth first search, depth first search, depth limited search, bidirectional search, heuristic search, problems and examples. Knowledge representation, frames, methods and demons, correlations, decision trees, fuzzy trees.

Unit-IV

Philosophy of AI, Penrose’s pitfall, weak AI, strong AI, rational AI, brain prosthesis experiment, the Chinese room problem, emergence of consciousness, technological singularity, Turing test.

Unit-V

Modern AI, biological brain, basic neuron model, perceptrons and learning, self-organizing neural network, N-tuple network, evolutionary computing, genetic algorithms, agent methods, agents for problem solving, software agents, multi agents, hardware agents.

Practical: Prolog language, syntax and meaning of Prolog programs, Lists, operators, arithmetic. Using structures: Example programs, controlling backtracking, input and output. more built-in procedures, programming, style and technique, operations on data structures. Advanced tree representations, basic problem-solving strategies, depth-first search strategy, breadth-first search strategy

Course no.: CSE 503

Course Title: Neuro-Fuzzy Applications in Engineering

Credits: 3(2+1)

Semester: Sem I

Theory:

Unit-I

Basic concepts of neural networks and fuzzy logic, differences between conventional computing and neuro-fuzzy computing, characteristics of neuro-fuzzy computing.

Unit-II

Fuzzy set theory: Basic definitions, terminology, formulation and parameters of membership functions. Basic operations of fuzzy sets: Complement, intersection, vision, T-norm and Tconorm. Fuzzy reasoning and fuzzy Inference: Relations, rules, reasoning, Inference systems,and modeling. Applications of fuzzy reasoning and modelling in engineering problems.

Unit-III

Fundamental concepts of artificial neural networks: Model of a neuron, activation functions, neural processing. Network architectures, learning methods. Neural network models: Feed forward neural networks, back propagation algorithm, applications of feed forward networks, recurrent networks, hopfield networks, hebbian learning, self organizing networks, unsupervised learning, competitive learning.

Unit-IV

Neuro–fuzzy modelling: Neuro-fuzzy inference systems, neuro-fuzzy control.

Unit-V

Applications of neuro-fuzzy computing: Time series analysis and modelling, remote sensing, environmental modelling.

Practical:

Training algorithms of artificial neural networks: Basic models, learning rules, single layer and multi-layer feed-forward and feedback networks, supervised and unsupervised methods of training, recurrent networks, modular networks. Fuzzy systems: Fuzzy sets, operations on fuzzy sets, fuzzy relations, measures, fuzzy logic, fuzzy logic controller, integrated hybrid systems. Adaptive neuro-fuzzy inference systems, coactive neuro-fuzzy modelling, classification and regression trees, data clustering algorithms like k-means, fuzzy c-means, mountain and subtractive clustering, rule-based structure identification, neuro-fuzzy control, case studies. Use of available software for fuzzy logic and neural networks.

Course no.: CSE 504

Course Title: Soft computing Techniques in Engineering

Credits: 3(2+1)

Semester: Sem I

Theory:

Unit-I

Introduction to control techniques, need of intelligent control. Architecture for intelligent control. Symbolic reasoning system, rule based systems, the artificial intelligence approach. Knowledge representation and expert systems. Data pre-processing: Scaling, Fourier transformation, principle component analysis and wavelet transformations.

Unit-II

Concept of artificial neural networks (ANN) and basic mathematical model, network structures, activation function, back propagation, network size and pruning McCulloch-Pitts neuron model, simple perceptron, adaline and madaline neural networks, feed-forward multilayer perceptron. Learning and training the neural network. Networks: Hopfield network, self-organizing network and recurrent network. Neural network based controller. Case studies: Identification and control of linear and nonlinear dynamic systems.

Unit-III

Genetic algorithm (GA): Basic concept and detail algorithmic steps, adjustment of free parameters. Solution of typical control problems using GA. Concept of other search techniques like tabu search and ant-colony search for solving optimization problems.

Unit-IV

Introduction to crisp sets and fuzzy sets, basic fuzzy set operation and approximate reasoning. Introduction to Fuzzy logic modelling and control of a system. Fuzzification, inference and defuzzification. Fuzzy knowledge and rule bases.

Unit-V

Fuzzy modeling and control schemes for nonlinear systems. Self-organizing fuzzy logic control. Implementation of fuzzy logic controller. Stability analysis of fuzzy control systems. Intelligent control for SISO/MIMO nonlinear systems. Model based multivariable fuzzy controller.

Practical: To work on data transformations, brief review on statistical criteria for termination of epochs, deciding the input output and hidden layers and neutrons for ANN problems, working on different algorithms of ANN to different problems in agricultural engineering, working with different fuzzy relations, propositions, implications and inferences, working with defuzzification techniques and fuzzy logic controllers, concept of coding, selection, crossover, mutation and application of genetic programming for global optimization, use of available software for application of soft computing techniques.

Course no.: CSE 505

Course Title: Database Management Systems

Credits: 3(2+1)

Semester: Sem I, II

Theory:

Unit I

Overview of DBMS, basic DBMS terminology, advantages and disadvantages of DBMS, file approach and its limitations, DBMS approach, advantages of DBMS, DBMS components.

Unit II

Design, logical and physical data independence, three level architecture of DBMS, entities and types of entities, relationships, entity relationship model.

Unit III

Data models, relational model, network model, hierarchical model, comparison of data models. Relational model, storage organizations for relations, primary, secondary, candidate, alternate keys, relational algebra & relational calculus, functional dependencies and normalization.

Unit IV

Functional relational query language, SQL commands, DCL, DDL, DML and TCL. PL/SQL, variables, control structures, decisions and loops, functions and procedures, cursors and triggers.

Practical: E-R diagram construction, SQL, version of SQL, commands syntax, data types, DDL statements, DML statements, DCL statements, TCL statements, having clauses, order by and where clause, wild cards, operators, integrity constraints, primary key, reference key, check, unique, not null, index and views, sequences, functions, aggregate functions, numerical, string, date and time, sub queries, nesting of queries, normalization of database and case study on a database design and implementation. PL/SQL, variables, control structures, decisions and loops, exception handling, creating functions and procedures, cursors, implicit and explicit cursors, triggers.

Course no.: CSE 506

Course Title: Digital Image Processing

Credits: 3(2+1)

Semester: Sem I, II

Theory:

Unit-I

Digital image fundamentals, elements of visual perception, light and the electromagnetic spectrum, image sensing and acquisition, image sampling and quantization, basic relationships between pixels, linear and nonlinear operations.

Unit-II

Image enhancement in the spatial domain, basic gray level transformations, histogram processing, basics of spatial filtering, smoothing spatial filters, sharpening spatial filters.

Unit-III

Color image processing, color fundamentals, color models, pseudo color image processing, basics of full-color image processing, color transformations, smoothing and sharpening, color segmentation.

Unit-IV

Image segmentation, detection of discontinuities, edge linking and boundary detection, thresholding, region-based segmentation, segmentation by morphological watersheds.

Unit-V

Morphological image processing, dilation and erosion, opening and closing, extensions to gray-scale images.

Practical: To write program to read and display digital image, image processing program using point processing method, program for image arithmetic operations, program for image logical operations, program for histogram calculation and equalization, program for geometric transformation of image, understand various image noise models and to write programs for image restoration and to remove noise using spatial filters. Brief outline of image processing tools.

Course no.: CSE 507

Course Title: Process Control System

Credits: 3(2+1)

Semester: Sem I

Theory:

Unit-I

Introduction to Process Control – Control strategy, single variable and multi variable control systems, Process Control loop, Open loop and closed loop control system, Linear and non linear control system. Determining the Transfer function of Complex Control System, Representation of a Control System by block diagram and its Reduction Characteristics.

Unit-II

Process Equation. Controlling and Controlled Variable. Transient & steady state response, Self Regulation Property, Control System Parameters, Evaluation of control System. Controller Modes or actions – ON/OFF Mode, Proportional Mode, Integral Mode, Derivative Mode, Composite control Modes. Pressure regulation, Liquid level and Temperature control Systems.

Unit-III

Signal Conditioning, Design of OP AMPS circuits used to implement Proportional, Integral, Derivative and Composite Modes. Introduction to computer control of process. Applications and design.

Practical: Study of performance of thermister, LVDT, thermocouple, strain gauge; open loop control systems, feedback control system; PI, PD, PID Controller; Simulation of typical control systems; use of microprocessors in process control.

Course no.: CSE 508

Course Title: Computer Engineering

Credits: 3(2+1)

Semester: Sem I

Theory:

Unit I

Review of basic digital circuits and codes. Digital computer components. Memories.

Unit II

Instructions and digital computer operations. Arithmetic and control sections. Input-output equipment.

Unit III

Design of a selected system.

Practical:  Application of logic gates in half and full – adders. Code converters and display devices. Study of computer systems with logic analyzer.

Course no.: CSE 509

Course Title: Parallel Programming

Credits: 3(1+2)

Semester: Sem I

Theory:

Unit I

Single/Multi core Processor Architecture, Basic parallel computing,

Unit II

Construct and Functions, OpenMP/MPI, Point to point communications, Collective communications,

Unit III

Advanced MPI1 concepts, MPI2 introduction Hybrid (OpenMP + MPI) programming. Practical: Parallel Program based on OpenMP/MPI,

Unit IV

Scheduling of High Performance cluster algorithm; Programs on Data types, Blocking Send and Receive.

Practical: Parallel Program using OpenMP/MPI, Programs on Performing Parallel Rank with MPI, MPI Broadcast and Collective Communication, Point-to-Point Communication Application, Array Decomposition, Matrix Multiply, Blocking send-receive, Non-blocking send-receive, Collective communications, Contiguous derived datatype.

Course no.: CSE 510

Course Title: Software Engineering

Credits: 3(2+1)

Semester: Sem II

Theory:

Unit I

Software development cycle. Analyzing a software problem, designing and programming solution, testing results, making changes. Project planning.

Unit II

Requirement analysis: fundamentals and methods. Software design fundamentals. Software quality assurance. Software testing techniques. Software testing strategies.

Unit III

Software maintenance and configuration management. Introduction to software reliability and selected models.

Practical: Open source software based case studies, C++ programs for Software testing, Line Count Programs for Software analysis.

Course no.: CSE 511

Course Title: Computer Networks

Credits: 3(2+1)

Semester: Sem I

Theory:

Unit I

Introduction, history and development of computer networks, networks topologies.

Unit II

Message and packet switching, data communication nodes and message handling, flow control. Protocols, interprocessor communication, terminal handling, Routing algorithms.

Unit III

Analysis, performance, optimization and design of networks. Random access channels; packet broad- casting; satellite communication. Study of networks: ETHERNET, ARCNET etc.

Practical: LAN IP configuration, Projects, Programs for Client server Communication, Programs using TCP and UDP Sockets.

Course no.: CSE 512

Course Title: System Programming

Credits: 3(3+0)

Semester: Sem II

Theory:

Unit I

Machine structure; Machine language; Assembly languages; Design of assemblers, Symbol table organization, pacing and segmentation

Unit II

stock and multiple register; machine code and storage optimization; Input and output control systems and debugging tools.

Unit III

Design of macro assemblers. Micro assembly systems, Macro as generalized string processor; Algebraic expression-translation and interpretation. Design of loaders and linkage editors

Unit IV

Design and direct linking and relocatable loaders;  core image builder, overlay structure and dynamic loading, Interpreters, compilers and supervisors.

Course no.: CSE 513

Course Title: Internet of Things

Credits: 3(2+1)

Semester: Sem I, II

Theory:

Unit I

Introduction to IOT and its working, Difference between Embedded device and IoT device; Properties of IoT device; IoT Decision Framework; IoT Solution Architecture Models; Understand Sensing actions; Understand Actuators and Microelectromechanical Systems.

Unit II

Communication Protocols used in IoT: Types of wireless communication; Major wireless Short-range communication devices; properties; comparison of these devices (Bluetooth, Wireless Fidelity (WiFi), Major wireless Long-range communication devices; properties

Unit III

IoT Applications: Industrial Internet; Applications such as: Smart Homes; Wearables; Smart City; Smart Grids; Connected Car; Connected digital health; telehealth; telemedicine; smart retail.

Unit IV

Sensors: Applications of various sensors: Google Maps; Global positioning sensors: Global Positioning System; Global Navigation Satellite System; Indian Regional Navigation Satellite System; Galileo and indoor localization systems; Motion & Orientation Sensors: Accelerometer; Magnetometer; Proximity Sensor; Gyroscope.

Practical: Use of Open source to develop IOT devices. Design and build systems that will use sensors; communication protocols and actuators.

Course no.: CSE 514

Course Title: Cryptography and Computer Security

Credits: 3(2+1)

Semester: Sem I

Theory:

Unit I

History of cryptography, Computer Security Concepts; Threats, Attacks and Assets. Cryptographic Protocols: Introduction to Protocols; Communications using Symmetric Cryptography; Substitution Ciphers and Transposition Cipher; Block Cipher; Steam Cipher

Unit II

Modes of Operation; Symmetric and Asymmetric cryptography. Cryptographic Techniques: Key Length & Management: Symmetric Key Length; Public-Key Key Length; Generating Keys.

Unit III

Algorithms: DIFFIE-HELLMAN; RSA; DES. Practical Cryptography: Encryption; authentication; hashing; Network Security and Protocol Standards: Network security issues; sniffing; IP Spoofing; Common threats; E-mail security;

Unit IV

Secure Socket Layer (SSL); Transport Layer Security (TLS); SSH; Intruders; Virus; Worms; Firewalls-need and features of firewall: Types of firewall; Intruder Detection Systems.

Practical:  Use of Network Security Tools; Email Header Analysis; Packet sniffing; configuration of network security equipment such as firewall; routers; IDS; Wireless Access Points.

Course no.: CSE 515

Course Title: Computer Methods in Engineering

Credits: 3(0+3)

Semester: Sem II

Practical:

Unit I

Introduction to computer hardware and operations, operating system, introduction to programming and numerical techniques,

Unit II

spreadsheet-based application, simulation, modeling and optimization, data base management, graphics application, computer-based instrumentation for data acquisition and control.

Course no.: CSE 516

Course Title: Machine Learning in Agriculture

Credits: 3(2+1)

Semester: Sem I

Theory:

Unit I

Basics of Machine Learning: Processes involved in Machine Learning; Applications of Machine Learning. Machine Learning Techniques: Supervised Learning; Unsupervised Learning; Real life examples of Machine Learning.

Unit II

Supervised Learning: Classification and Regression: K-Nearest Neighbor; Linear Regression; Logistic Regression; Support Vector Machine (SVM)

Unit III

Evaluation Measures: Sum of squares error; R square; confusion matrix; precision; recall; F- Score; ROC-Curve.

Unit IV

Unsupervised Learning: Introduction to clustering; Types of Clustering: Hierarchical- Agglomerative Clustering and Divisive clustering

Unit V

Partitioned Clustering; K-means clustering; Principal Component Analysis. Applications of Machine Learning in Agriculture

Practical : Python Introduction: Loops and Conditions and other preliminary stuff; Functions; Classes and Modules; Exceptions; Database access; Mathematical computing with Python packages, Application Oriented Project Work.

Course no.: CSE 517

Course Title: Cloud and Mobile Computing

Credits: 3(2+1)

  Semester: Sem II

  Theory:

Unit I

Introduction to Cloud Computing, Cloud Computing Architecture, Service Management in Cloud Computing, Data Management in Cloud Computing

Unit II

Resource Management in Cloud, Cloud Security, Open Source and Commercial Clouds, Cloud Simulator.

Unit III

Mobile Applications: Responsive Web Design vs. Mobile Apps; RESTful and Non-RESTful apps; Native Vs Hybrid

Unit IV

Security and Trust Management, Privacy and Ethics, Usability and Accessibility

Practical: Installation of Private Clouds using open source softwares. Cross platform applications based on HTML/CSS/JS Framework, Creating and Incorporating Web/Cloud Services for mobile applications; Publishing the apps to various App stores.

Course no.: CSE 518

Course Title: Microcontroller and Embedded Systems

Credits: 3(2+1)

Semester: Sem II

Theory:

Unit I

Microprocessor: Architecture, Register Organization, Programming Model, Memory Segmentation, Addressing Modes

Unit II

Instruction set. Microcontroller: Architecture, I/O Ports, Memory Organization, Instruction set, Brief overview of real time systems and embedded systems

Unit III

Classification of embedded systems – Embedded system definitions – Functional and non- functional requirements – architectures and standards – Core of embedded system, sensors and actuators.

Practical: Hands-on experience in the use of microcontroller system and design of peripheral controllers and interfaces along with construction and debugging of IC circuits.

Course no.: CSE 519

Course Title: Wireless Sensor Networks

Credits: 2(1+1)

Semester: Sem I

Theory:

Unit I

INTRODUCTION: Motivation for a Network of Wireless Sensor Nodes – Definitions and Background, Challenges and constraints; Applications of wireless sensor networks.

Unit II

PHYSICAL LAYER: Basic Components, Source Encoding, Channel Encoding, Modulation, Signal Propagation, MEDIUM ACCESS CONTROL: Overview, Wireless MAC Protocols, Characteristics of MAC Protocols in Sensor Networks

Unit III

Contention-Free MAC Protocols, Contention-Based MAC Protocols, Hybrid MAC Protocols, POWER MANAGEMENT: Local Power Management Aspects, Dynamic Power Management, Conceptual Architecture, TIME

Unit IV

SYNCHRONIZATION: Clocks and the Synchronization Problem, Time Synchronization in Wireless Sensor Networks, Basics of Time Synchronization, Time Synchronization Protocols,

Unit V

LOCALIZATION: Overview, Ranging Techniques, Range-Based Localization, Range-Free Localization.

Practical: Implement simulation experiments and projects based on Physical layer, network layer, transport layer, application layer and MAC layer of wireless sensor network

Course no.: IT 501

Course Title: Computer Fundamentals and Programming

Credits: 3(2+1)

Semester: Sem I

Theory:

Unit I

Computer fundamentals, number systems, decimal, octal, binary and hexadecimal, representation of integers, fixed and floating-point numbers, character representation, American Standard Code for Information Interchange (ASCII), Extended Binary Coded Decimal Interchange Code (EBCDIC)

Unit II

Functional units of computer, I/O devices, primary and secondary memories. Programming fundamentals with C, techniques of problem, solving, flowcharting, stepwise refinement,

Unit III

Representation of integer, character, real numbers, data types in C, constants and variables, arithmetic expressions, assignment statement, logical expression. Sequencing, alteration and iteration, arrays, string processing

Unit IV

Sub-programs, recursion, pointers and files. Program correctness, debugging and testing of programs.

Practical: Conversion of different number types, creation of flow chart, conversion of algorithm/flowchart to program, mathematical operators, operator precedence, sequence, Implementing subprograms and recursion. Debugging and testing, Control statements, looping and decision-making statements, arrays and string processing, pointers and file processing.

Course no.: IT 502

Course Title: Operating System

Credits: 4(3+1)

Semester: Sem I

Theory:

Unit I

Operating system overview, operating system as an extended machine and resource manager, operating system classifications, operating system modes and system calls. Operating system architecture.

Unit II

Process, process model, process scheduling, operations on process, inter process communication. Process synchronization, critical section problem, producer consumer problem, bounded buffer problem, semaphores, monitors,

Unit III

CPU scheduling, long term schedulers, middle term schedulers, short term schedulers, basic concepts, scheduling criteria, scheduling algorithms, First come first serve, shortest job first, priority scheduling, round robin, multilevel queue, multilevel feedback, deadlocks, system model, race condition, deadlock prevention, deadlock avoidance, deadlock detection.

Unit IV

Memory management, base register and limit register, contiguous memory allocation, swapping, paging, segmentation, virtual memory, fragmentation, demand paging, page replacement, first in first out, least recently used, optimal algorithm, thrashing, shared segment.

Unit V

Device management system, dedicated share and virtual devices, spooling channels, multiplexer and selector, control units, traffic controllers and device handlers.

Practical: Windows and Linux installation, managing files and folders in windows. Dos commands, user account settings, add and remove hardware and software’s, group policies, user policies, administrator policies, services, disk formatting and partitioning, disk management and defragmentation, managing files and folders, synchronization, user profiles, windows components, event viewer, desktop settings, folder properties.

Course no.: IT 503

Course Title: Internet and Web Technologies

Credits: 4(3+1)

Semester: Sem I, II

Theory:

Unit I

Fundamentals of networking, overview of network topologies, classifications of networks. Introduction to the internet, advantages and disadvantages of internet, electronic mail, gopher, world wide web, Usenet, telecommunication networks, bulletin board service, wide area information service

Unit II

Introduction to HTML, comparing static and dynamic web designing, elements, versions, designing a web page, text formatting & alignment, font control, arranging text and lists, background image & colors, images in web pages, method of linking, frames, user input using forms, event handling,

Unit III

Applying style formats using Style sheets, types of SS, external and inline and embedded style sheets. Java script introduction, variables, control statements, JavaScript arrays, methods, client side validations, embedding JavaScript, future of JavaScript.

Unit IV

Server side scripting, installing and configuring web server, creating DSN, database interaction using server side scripts, database connectivity using DSN and DSN less, retrieving and searching data, adding and modifying contents of database.

Practical: Designing static website with features like tables, hyperlink among pages, pictures, frames, client side scripts for user interface validation, arrays, methods, branching and iterations, server side scripting for database interaction, database creation, retrieving and accessing databases, filters, and designing of an information system.

Course no.: IT 504

Course Title: Dynamic Web Development

Credits: 4(3+1)

Semester: Sem II

Theory:

Unit I

Dynamic Hyper Text Markup Language, using text formatting tags, tables, lists, images and image map, frames and frameset and forms for user input. Form elements, textbox, checkbox, radio buttons, selection lists, dropdown list, multiple selection, text area, field set, legend, hidden fields, uploading files, mailto information, get and post method,

Unit II

Types of dynamic scripting languages, overview of dynamic scripting languages, features of dynamic scripting languages. Client side and server side scripting, dynamic scripting language constructs, variables, loops and decisions, functions and procedures. Dynamic language features, introspection, mobility, instrumentation, garbage collection, importance and need, factors affecting garbage collection algorithms, mark and sweep garbage collection algorithm,

Unit III

Typing, static versus dynamic typing, manifest versus inferential typing. Implementing client side validations and database interaction using server side scripts. Latest trends in programming on the emerging technologies relating to web based software development.

Practical: Developing tables, frames, DHTML tags in dynamic WebPages in JavaScripts/VB scripts. Creating dynamic WebPages using different form elements, textbox, checkbox, radio buttons, selection lists, dropdown list, multiple selection, text area, field set, legend, hidden fields, uploading files, mailto information, get and post method.

Course no.: IT 505

Course Title: Multimedia and Applications

Credits: 3(2+1)

Semester: Sem II

Theory:

Unit I

Introduction to multimedia technology, use of computers in communications and entertainment. Framework for multimedia systems. Multimedia devices, presentation devices and the user interface.

Unit II

Digital representation of sound and transmission, speech recognition and generation, digital video and image compression, JPEG image compression standard, MPEG motion video compression. Presentation and multimedia authoring, implementing layouts, designing of visuals,

Unit III

applying animations and transitions, creating hyperlinks and actions, templates, wizards and views, inserting pictures, charts, tables, objects, movies and sounds, customizing a show, using a standard presentation software.

Unit IV

Introduction to Adobe Photoshop, basic color models, CMYK, RGB, bitmap graphics, vector graphics, images and image editing. Filters and layers.

Practical: Layouts and designing of visuals, basics of colors, working with text, presentations, charts and putting animations, views, graphics, adding audio and videos, creating interactive presentations. Adobe Photoshop, introduction, working with images, image editing and cleaning. Panning and zooming, cropping images, morphing, building layers and adding filters, effects.

Course no.: IT 506

Course Title: Database Management Systems

Credits: 3(2+1)

Semester: Sem I, II

Theory:

Unit I

Overview of DBMS, basic DBMS terminology, advantages and disadvantages of DBMS, file approach and its limitations, DBMS approach, advantages of DBMS, DBMS components.

Unit II

Design, logical and physical data independence, three level architecture of DBMS, entities and types of entities, relationships, entity relationship model.

Unit III

Data models, relational model, network model, hierarchical model, comparison of data models. Relational model, storage organizations for relations, primary, secondary, candidate, alternate keys, relational algebra & relational calculus, functional dependencies and normalization.

Unit IV

Functional relational query language, SQL commands, DCL, DDL, DML and TCL. PL/SQL, variables, control structures, decisions and loops, functions and procedures, cursors and triggers.

Practical: E-R diagram construction, SQL, version of SQL, commands syntax, data types, DDL statements, DML statements, DCL statements, TCL statements, having clauses, order by and where clause, wild cards, operators, integrity constraints, primary key, reference key, check, unique, not null, index and views, sequences, functions, aggregate functions, numerical, string, date and time, sub queries, nesting of queries, normalization of database and case study on a database design and implementation. PL/SQL, variables, control structures, decisions and loops, exception handling, creating functions and procedures, cursors, implicit and explicit cursors, triggers.

Course no.: IT 507

Course Title: Visual Programming

Credits: 3(1+2)

  Semester: Sem II

  Theory:

Unit I

Visual fundamentals, building your first application, developing applications in visual programming, working in the visual programming environment

Unit II

Using the intrinsic controls, working with projects, working with properties, deploying visual applications, advanced programming, debugging, creating controls

Unit III

Using active X controls, your applications, database programming, database basics and the data control. Making reports, enhancing the programming using the advanced data controls.

Practical: Programs for loops, typecasting. Developing user friendly programs in visual environment / platform on Linux/windows, methods and events, programming using data types, constants and variables, making statements in a program, working with conditional statements, working with loops, working with arrays, working with strings and typecasting, the elements of visual environment, creating menus, forms and dialog boxes, handling keyboard and mouse input, working with time and timers, adding graphics, writing reusable code with subs and functions, saving and retrieving data. Accessing Databases using advance Data control.

Course no.: IT 508

Course Title: Programming in C++

Credits: 4(2+2)

Semester: Sem I, II

Theory:

Unit I

Introduction to C++, character set, constants, variables and keywords and their types. Operators, type conversion. Control statements, conditional expression. Declaration of variables, statements, simple C++ program, manipulator functions, I/O stream flags.

Unit II

Functions, types of functions, local and global variables, default arguments, multifunction program. Storage class specifiers, pre-processor, header files and standard functions.

Unit III

Arrays, declaration, initialization, processing with array, array with functions, strings and their functions.

Unit IV

Overview of classes and objects, definition, structures and classes, member functions, defining object, accessing a member, array of class objects, classes within classes. The I/O library and file handling, operations on files.

Practical: Programs on use of decision making statements in C++,using iterations and arrays, multidimensional array, input output manipulators, predefined manipulators and user defined manipulators, formatted and unformatted input output functions, set precision, user defined objects, defining function, return statement, Classes and Objects, using constructors and destructors in classes, object as a member, Member Functions, call and return values, passing parameters, actual and formal arguments, recursion, I/O library files, macros, stream buffers, istream, ostream and fstream, file handling, saving files on disk, reading contents from files, editing files, apply file modes, type of files.

Course no.: IT 509

Course Title: Data Structures and Algorithms

Credits: 4(2+2)

Semester: Sem II

Theory:

Unit I

Overview of data structures, basic concepts, data organization, description of various data structures. Programming design and development. Algorithms, programming constructs algorithm complexity,

Unit II

Big O notation, and concept of recursion. Arrays and matrices, stack, stack insertion and deletion, queue, circular queues, priority queues, link list, Representation and processing of linear linked lists, multiple linked structures, creating link list, inserting and deleting link nodes from a list, circular link list, doubly link list,

Unit III

Trees, traversing a tree, traversal methods, depth, level and height of a tree, binary tree, BST, AVL tree, threaded binary trees, M-Way search trees, B-Tree, heaps, multi way trees. Graphs, demonstrating graphs in memory, operations on graphs, applications of graphs.

Unit IV

Searching and sorting, searching, linear search and binary search algorithm, hash list searches, collision resolution. Bubble sort, selection sort, insertion sort, radix sort, merge sort algorithm, quick sort, heap sort, shell sort.

Practical: Implementation of various types of structures, programs for array and multidimensional arrays, linked lists, doubly linked lists, circular linked lists, queue, de- queue, stack and tree, in-order, preorder and post-order tree traversals, string processing, searching and sorting techniques, graph and geometric algorithms and case studies.

Course no.: IT 510

Course Title: Core Java

Credits: 4(2+2)

Semester: Sem I

Theory:

Unit I

Features of java, java and internet, java and www, hardware and software requirements, java support systems,

Unit II

Java environment, java classes, access modifiers, managing classes and calling methods, inheritance, overloading,

Unit III

Packages & interfaces, exception handling, multiple catch statements, finally statement, creating user defined exceptions, multithreading, thread control methods, thread life cycle, applets and webpages.

Practical: Programs on java classes, methods, string class, decision making control statements, looping control statements, jumping statements, vectors, operators, arrays, multidimensional arrays, passing arrays to functions, array of objects, string handling in java, string functions, inheritance, types of inheritance, inheritance accessing modes, runtime and compile time binding, packages, importing classes and packages, interfaces, runnable interfaces, exception handling, types of exceptions, throwing exceptions, catch and try block, multiple catch blocks, finally keyword, multi threading, prioritizing the threads, Designing applets in WebPages, Extending applet class, I/O applets, importing classes and packages, extending applet class.

Course no.: IT 511

Course Title: Data Communication and Networks

Credits: 2(2+0)

Semester: Sem II

Theory:

Unit I

Definition of a communication network, simplex, duplex and half duplex systems, concept of node nodes connected by links to create networks, names & addresses, the idea of address resolution.

Unit II

Types of network, point-to-point connections, circuit-switched networks, message-switched networks, packet switched networks, datagram networks. Types of equipment, packet-switched network, types of communication-broadcast, unicast and multicast modes.

Unit III

Open system interconnection, layers, responsibilities of each layer, TCP/IP model, transmission media, magnetic, twisted, coaxial cables and optical fiber, multiplexing, switching, terminal handling, telephone system, modems, connections, transmission media.

Course no.: IT 512

Course Title: Linux System Administration

Credits: 3(1+2)

Semester: Sem II

Theory:

Unit I

Linux basics, script command and utilities, booting process, HTTPD, CDI and PERL. Linux protocols, configuring TCP/IP, DNS, NFS and NIS, mailing, security, proxy server

Unit II

Network management in Linux, shell programming. X-windows, principles, X programming model, calling motif functions, widget basics, text and list widgets etc., color basics.

Practical: Linux commands, Assign multiple IP’s, Assign second IP, Trace Route, Trace Path, Disable network card, Enable network card, View current routing table, Assign IP/Subnet, Display Current Configuration for all NIC’s, static IP address, Implementation of sever settings, administration commands, process related commands, network commands, IP Address Management, Installation of server using Network File System (NFS), mount system drives and fetching data using NFS, Managing network problems, script writing based on Linux using vi editors / emacs editors, constructs of shell programming.

Course no.: IT 513

Course Title: Concepts of Object Oriented Programming

Credits: 4(2+2)

Semester: Sem I

Theory:

Unit I

Introduction to object orientation, history and evolution of object oriented languages, Object Oriented Programming (OOP) languages (e.g. C++/Java etc.), abstract data types, classes, parameterized classes, objects, object/message paradigm

Unit II

Data encapsulation, concepts of modules and interfaces, data abstraction and types, constructors and destructors, types of constructors, data hiding, overloading, operator overloading, binary and unary operator overloading, function overloading, constructor overloading, virtual class, pure virtual class, dynamic binding, polymorphism, virtual classes, inheritance

Unit III

class hierarchies, relationships, inheritance and dynamic binding, single level inheritance, multiple inheritance, multilevel inheritance, hierarchical inheritance and hybrid inheritance, procedural abstraction, functional procedures,

Unit IV

Object oriented software design, concept of modeling objects, object oriented analysis and design, importance, object oriented analysis landscape, object oriented design landscape, unified modeling language, structure diagrams, classes and states, object diagrams, class diagrams, interaction diagram, activity diagram, use case diagram, state machine diagrams, sequence diagram, behavior diagram, meta modeling.

Practical : Case studies using Object Oriented Analysis And Design (OOAD), creation of classes with features, overloading, programs using inheritance, multilevel and multiple inheritance, hybrid and hierarchical inheritance, data abstraction, polymorphism, programs for binary and unary operator overloading, function overloading, and implementation of a case study.

Course no.: IT 514

Course Title: Design and Analysis of Algorithms

Credits: 3(3+0)

Semester: Sem I

Theory:

Unit I

Elementary algorithmic, problem and instances, the efficiency of algorithms, average and worst case analyses, some examples, asymptotic notation, analysis of algorithms, greedy algorithms, general characteristics of greedy algorithms, Set and disjoint set union

Unit II

Stassen’s matrix multiplication graphs, minimum spanning trees, kruskal’s algorithms, prim’s algorithms, graphs, adjacency matrix, cost adjacency matrix, shortest paths, traversing graphs, the knapsack problem, scheduling, minimizing time in the system, scheduling with deadlines

Unit III

divide and conquer, dynamic programming, exploring graphs, graphs and games, traversing trees, depth-first search, undirected graphs, articulation points, depth-first search, directed graphs, acyclic graphs, topological sorting, breadth-first search, backtracking, the knapsack problem,

Unit IV

Computational complexity, information-theoretic argument, adversary argument, linear reductions, introduction to NP- completeness, Classes NP-Hard and NP-Hard Graph Problems (CNDP, DHC, TSP and AOG). Case Studies using divide and conquer searching and complexities. Algebraic General Method, Evaluation and Interpolation, Fast Fourier Transformation, Modular Arithmetic. Introduction to Absolute Approximation.

Course no.: IT 515

Course Title: Cryptography and Computer Security

Credits: 3(2+1)

Semester: Sem I

Theory:

Unit I

History of cryptography, Computer Security Concepts; Threats, Attacks and Assets. Cryptographic Protocols: Introduction to Protocols; Communications using Symmetric Cryptography; Substitution Ciphers and Transposition Cipher; Block Cipher; Steam Cipher

Unit II

Modes of Operation; Symmetric and Asymmetric cryptography. Cryptographic Techniques: Key Length & Management: Symmetric Key Length; Public-Key Key Length; Generating Keys.

Unit III

Algorithms: DIFFIE-HELLMAN; RSA; DES. Practical Cryptography: Encryption; authentication; hashing; Network Security and Protocol Standards: Network security issues; sniffing; IP Spoofing; Common threats; E-mail security;

Unit IV

Secure Socket Layer (SSL); Transport Layer Security (TLS); SSH; Intruders; Virus; Worms; Firewalls-need and features of firewall: Types of firewall; Intruder Detection Systems.

Practical: Use of Network Security Tools; Email Header Analysis; Packet sniffing; configuration of network security equipment such as firewall; routers; IDS; Wireless Access Points.

Course no.: IT 516

Course Title: Soft Computing Techniques in Engineering

Credits: 3(2+1)

Semester: Sem I

Theory:

Unit-I

Introduction to control techniques, need of intelligent control. Architecture for intelligent control. Symbolic reasoning system, rule based systems, the artificial intelligence approach. Knowledge representation and expert systems. Data pre-processing: Scaling, Fourier transformation, principle component analysis and wavelet transformations.

Unit-II

Concept of artificial neural networks (ANN) and basic mathematical model, network structures, activation function, back propagation, network size and pruning McCulloch-Pitts neuron model, simple perceptron,  daline and madaline neural networks, feed-forward multilayer perceptron. Learning and training the neural network. Networks: Hopfield network, self-organizing network and recurrent network. Neural network based controller. Case studies: Identification and control of linear and nonlinear dynamic systems.

Unit-III

Genetic algorithm (GA): Basic concept and detail algorithmic steps, adjustment of free parameters. Solution of typical control problems using GA. Concept of other search techniques like tabu search and ant-colony search for solving optimization problems.

Unit-IV

Introduction to crisp sets and fuzzy sets, basic fuzzy set operation and approximate reasoning. Introduction to Fuzzy logic modelling and control of a system. Fuzzification, inference and defuzzification. Fuzzy knowledge and rule bases.

Unit-V

Fuzzy modeling and control schemes for nonlinear systems. Self-organizing fuzzy logic control. Implementation of fuzzy logic controller. Stability analysis of fuzzy control systems. Intelligent control for SISO/MIMO nonlinear systems. Model based multivariable fuzzy controller.

Practical: To work on data transformations, brief review on statistical criteria for termination of epochs, deciding the input output and hidden layers and neutrons for ANN problems, working on different algorithms of ANN to different problems in agricultural engineering, working with different fuzzy relations, propositions, implications and inferences, working with defuzzification techniques and fuzzy logic controllers, concept of coding, selection, crossover, mutation and application of genetic programming for global optimization, use of available software for application of soft computing techniques.

Course no.: IT 517

Course Title: System Software

Credits: 3(3+0)

Semester: Sem I, II

Theory:

Unit I

Introduction to software processors, elements of assembly language programming, assembly scheme, single pass and two pass assembler, general design procedure of a two pass assembler,

Unit II

macros and macro processor, macro definition, macro expansion, and features of macro facility, design of macro processor, overview of compilers, memory allocation, compilation of expressions, compilation of control structures,

Unit III

Use of interpreters, pure and impure interpreter, Compile and go loader, Absolute loader, Relocating loader, and direct linking loader. lexical analysis, syntax analysis, intermediate code generation and optimization, local and global optimization, assembly and output.

Unit IV

Loaders and linkage editors. Translated linked and load time addresses, relocation and linking concepts. Design of a linker, self relocating programs. Introduction to loading, linking and relocation, program linking, linkage editors, dynamic linking, bootstrap loader.

Unit V

Other system software, database systems, functions and structure of text editor. Processor management, Scheduler, traffic controller, race condition, Information management.

Course no.: IT 518

Course Title: Computer Organization and Architecture

Credits: 2(2+0)

Semester: Sem I, II

Theory:

Unit I

Number systems,  arnaug algebra, minimization of  arnaug function using  arnaugh map, logic gates, combinational circuits, MUX, DEMUX, encoder,  ecoder, sequential circuits, flip-flops, half and full adder, shift register, counters.

Unit II

Organization of CPU, control unit, instruction and execution cycle in CPU, register organization, the instruction cycle, instruction pipelining. Memory organization, internal memory, semiconductor main memory (RAM, ROM, EPROM), cache memory, advanced DRAM organization, external memory

Unit III

Magnetic disks, RAID, optical memory, magnetic tape. Basic structure of computer hardware and system software, addressing methods and machine program sequencing, input-output organizations, accessing I/O devices, Direct Memory Access (DMA), interrupts. CISC and RISC architecture, study of functional units of microprocessors.

Course no.: IT 519

Course Title: Cyber Law in India

Credits: 1(1+0)

Semester: Sem I, II

Theory:

Unit I

Overview of the IT legal system in India. Intellectual properties, copyrights, patents, privacy, computer forensics. Access Control : Operating system Access Controls, Group and Roles, Access Control lists, Operating System Security , Capabilities, Granularity, Sandboxing and Proof-carrying code, Hardware protection, Other technical Attacks.

Course no.: IT 520

Course Title: Network Programming

Credits: 3(2+1)

Semester: Sem I. II

Theory:

Unit I

Introduction to networking and internet protocols via programming, TCP/IP, user datagram protocol, multicasting, standard internet services and protocol usage by common internet applications.

Unit II

Sockets programming, client/server, peer-to-peer, internet addressing, TCP sockets, UDP sockets, raw sockets, multithreading and exception handling. Finger, Domain Name System, HTTP, and ping clients and servers.

Unit III

Routers and architectures, routing protocols. Router and switch configurations, internet operating systems. Internetwork setup, wireless internetworking. Network protocol analyzers,

Unit IV

Types of protocols, remote terminal access, types of servers, transaction based ,inherent concurrency, strict turn-taking, stateless servers, traffic generation.

Practical: Handling TCP/IP protocol, programming TCP/IP parameters,. Implementation of remote terminal access, commands of HTTP, handling UDP, programming of UDP parameters. Network programming under Linux / windows, implementing socket programming, configuring peer to peer networks, routers and switch configuration in Linux and Windows.

Course no.: IT 521

Course Title: Design and Management of Web Portals

Credits: 3(2+1)

Semester: Sem I, II

Theory:

Unit I

Web portals, definition, history, types of web portals, web portal services, search engine, indexing, FAQ, RSS feeds, E-mail alerts, live chat, blog, web portal design, management, security issues.

Unit II

Introduction, features of XML, XML protocols, XML documents. Structure of XML, logical structure, physical structure. XML markup, element markup, attributes markup naming rules, elements, attributes, descriptors, comments entity.

Unit III

Unrestricted elements, element content models, element sequences, element choices, combined sequences and choices. Viewing, xml in internet explorer, viewing xml using the xml data source object. XSL (Extensible Style Sheet Language) or CSS (Cascading Style Sheet).

Practical: Use of XML / PHP for designing web portals for agricultural informatics. Managing Session, using session variables and cookies, open source database connectivity (MySQL), CSS for designing web portals, managing users authentication, security issues on server side, managing user and passwords.

Course no.: IT 522

Course Title: Content Management

Credits: 3(1+2)

Semester: Sem I, II

Theory:

Unit I

Strategy, scope, structure, skeleton, surface review. Compare and contrast OS-CMS options. Defining a successful online community, setting up a Joomla site, sections, categories, content, menu, wire framing, Joomla templates, evaluating Joomla extensions for community functionality and technical features, installing and configuring Joomla extensions, forming, storming, norming, and conforming.

Practical: Use of open source software tools for content management, create, update, and delete articles, display a list of articles, create a navigation menu and display articles in the front-end, auto-archive articles older, Create a Website template, use of File System Object, use the VBScript function Replace() Create a Database for the Content developing e-learning modules. Templates, content languages, meta data, mail, stats, search engine friendly URL’s, calendar, content items, native support for file types, multiple file transfer, file conversion tools, currency conversion, source editor, spell checker, XML editor, role management, media asset repository (Images, sound, flash, video etc).

Course no.: IT 523

Course Title: Data warehouse and Data Mining

Credits: 3(2+1)

Semester: Sem I, II

Theory:

Unit I

Concepts and principles of data warehousing, data warehousing architecture. System process and process architecture, data warehousing design, database schema. Partitioning strategy, aggregations, data marts, meta data management, and data warehouse process.

Unit II

Query management, data warehouse security, backup, backup schedule, backup media, backup format, backup file format, restoring points, restoring backup files and recovery, recovery from deleted database, recover from damage disk, capacity planning, testing the warehouse. Introduction to data mining, neural networks, fuzzy logic. Visualization techniques, decision trees, association rules, statistical and clustering models.

Practical: Data warehouse design, selection of schema, normalization and renormalization, query plan strategy, performance tuning, backup, backup scheduling, restoring database and recovery of data warehouse, dynamic reporting and OLAP cubes, data mining techniques, neural networks, fuzzy logic, visualization techniques and decision trees.

Course no.: IT 524

Course Title: System Analysis and Design

Credits: 2(2+0)

Semester: Sem I

Theory:

Unit I

System, concept, elements of a system and types of system, system development life cycle, role of system analyst, initial investigation, feasibility study, technical, economic and behavioral feasibility, cost and benefit analysis.

Unit II

System analysis, problem definition, information requirements, information gathering tools, tools of structured analysis, data flow diagrams, data dictionary, decision tree, decision tables and structured English, system design, structured design, input design, and output design, form design, file organization, sequential, indexed sequential, chaining and inverted list organization, system testing, test plan and test data,

Unit III

Types of system test, system implementation, implementation plan, activity network for conversion, combating resistance to change. Hardware/ software selection, procedure for selection, major phases in selection, make v/s buy decision, criteria for software selection.

Course no.: IT 525

Course Title: Object Oriented Software Engineering

Credits: 3(3+0)

Semester: Sem I, II

Theory:

Unit I

Software engineering, software related problems, software engineering, concepts, and development activities. Modeling, modeling with UML. Project communications, project communication modes, mechanisms and activities. Requirements, requirements elicitation, concepts & managing requirements elicitation.

Unit II

Analysis, analysis overview, activities and managing analysis. Design, design overview, fundamental concepts of system design, activities and managing system, design. Object design, object design overview, activities and managing object design.

Unit III

Rationale management, rationale overview, concepts, activities and managing rationale. Software documentation procedures, Software reliability and quality assurance. Quality Metrics and software models. Testing, testing overview, testing fundamentals, activities and managing testing.

Unit IV

Software configuration management, configuration management overview, concepts, activities and managing configuration management. Project management, project management overview, activities and managing project management models and activities. Software engineering tools and environment,

Unit V

International software engineering standards and their relevance Case studies in software engineering. Software Agents, Definition, Applications, Types and Classes, Multi- Agent systems, Characteristics & Properties Agents.

Course no.: IT 526

Course Title: Network Management

Credits: 3(1+2)

Semester: Sem I, II

Theory:

Unit I

Network management architecture. Installing Windows Server, registry, control panel, Network applications, TELNET, FTP, Wired and wireless networking standards.

Unit II

Microwaves, infrared, base band and broadband transmission. Network design and consideration, wired networks, wireless networks, network administration, system restoration. Simple network management protocol (SNMP), RMON 1, RMON 2. Management tools, systems and applications.

Practical: Basic Networking Concepts, Installing and configuring network server for window based and linux based systems, configuration protocols & bindings, network adapters, peripherals & devices, create users, managing users, managing group accounts, create policies, profiles ,system policies , user policies, Managing resources, disk resources, working with window resources, UNC, configure IP addresses in windows and linux , set up LAN network, managing network with respect to their topologies, ring topology set up wi-fi networks, managing E-mail, DHCP Practice of latest protocol/ network services on Linux / windows server.

Course no.: IT 527

Course Title: Parallel and Distributed Computing

Credits: 3(2+1)

Semester: Sem I

Theory:

Unit I

Basic concepts of parallel computers and computation, parallelism and computing, von Neumann computer architecture, Flynn’s classical taxonomy, general parallel technology, parallel computer memory architecture, Shared Memory, Distributed Memory, Hybrid Distributed-Shared Memory, Parallel Programming Models,

Unit II

Shared Memory Model, Threads Model, Message Passing Model, Data Parallel Model, Other Models, Designing Parallel Programs, Automatic vs. Manual Parallelization, Understand the Problem and the Program, Synchronization, Data Dependencies, Load Balancing, Granularity, I/O, Limits and Costs of Parallel Programming,

Unit III

Performance Analysis and Tuning, PI Calculation, Simple Heat Equation, 1-D Wave Equation, Distributed system models, cloud computing, Distributed System Challenges, connecting users and resources / concurrency, parallel machine model, parallel algorithm, designing parallel algorithms, methodical design, partitioning, communication, agglomeration, mapping, quantitative basis, performance evaluation, scalability analysis,

Unit IV

Communication model, communication libraries, basics of PVM, MPI, BSP, clustering, grids types, computational grids, data grids. Grid computing, layered grid architecture, volunteer grid computing.

Practical: Parallel Program using OpenMP/MPI, Programs on Performing Parallel Rank with MPI, MPI Broadcast and Collective Communication, Point-to-Point Communication Application, Array Decomposition, Matrix Multiply, Blocking send-receive, Non-blocking send-receive, Collective communications, Contiguous derived datatype.

Course no.: IT 528

Course Title: Server Programming with Java

Credits: 3(2+1)

Semester: Sem I, II

Theory:

Unit I

Java AWT, Java AWT Package Container, Basic User Interface Components, Layouts. Java I/O Handling, I/O File Handling, File Input Stream, File Output Stream, File Class, Random Access File.

Unit II

Socket Programming, Introduction, TCP/IP Protocol, UDP Protocol, Ports, Using TCP/IP Sockets, Using UDP Sockets. Database Connectivity using JDBC, JDBC/ODBC bridge, Driver Manager Class, Java SQL Package, SQL Exception class.

Unit III

Remote Method Invocation, N-tier Architecture, Locating and loading Remote classes, Enabling remote method class, RMI Architecture, Naming, Remote Interface, Unicast Remote Object, Socket Vs RMI programming. Java Servlets, Introduction to Server Side Technologies, Servlet Life cycle, HttpServlets, GenericServlets, init(),service(), doGet(), doPost(), destroy(), Servlets and JDBC.

Practical: GUI problems using Java for Network, Java Connectivity with Web pages, Socket Programming, InetAddress Class, IP address resolver, Server socket, Datagram sockets, TCP sockets, stream sockets, Handling bytes, multicast sockets, JDBC connectivity, Loading database driver, oracle JDBC connection, Creating a JDBC Statement object, executing SQL statements.

Course no.: IT 529

Course Title: Next Generation Technologies

Credits: 3(2+1)

Semester: Sem I

Theory:

Unit I

Cloud Computing: Types of cloud, Applications of cloud, use of some common public cloud services, concept of Virtualization, Big Data

Unit II

Analytics: Introduction to Big Data Platform, Traits of Big data, Challenges of Conventional Systems, sources, technologies, Applications, Cryptocurrency: Bit coins and cryptocurrency technology, use of block chain for cryptocurrency, success of cryptocurrency, cryptocurrency trading and wallets

Unit III

Dark Web: Introduction to dark web, deep web, crawling the data from hidden web, data pre-processing and data analysis, tor network, case studies, Wireless technologies,

Unit IV

Wearable Sensors: Implementation of wearable sensors, acquiring data from wearable sensors, applications: crowd sourced applications, Case Studies: Case studies on existing technologies and their implementation in real time environment.

Practical: Mobile application programming, wireless technologies, preprocessing of data and analysis using various available technologies