Archive for the ‘Bachelor of Engineering (BE)’ Category



Further to Semester VII work, the students shall collect all necessary information and analyze it. The students shall prepare and submit a report on their project. Broadly the report shall have 4 parts: Introduction, Literature Review, Data collection, Experiments conducted, Software Implementation etc. Acquaintance with survey and research methods and their use in conducting a systematic investigation and style of report preparation and presentation shall form the basis of evaluation.

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Lexical analysis: Some sophisticated pattern matching algorithms and their optimization, use of LEX.

Error recovery: Detection, reporting, recovery and repair of errors in the compilation process.

Syntax analysis: Canonical LR prasers, handling of ambiguous grammars, error reporting in LL (1), operator precedence and LR parsing, efficient generation of LALR (1) sets, optimization of LR parsers, optimization of transformations.

Run time storage: Activation records, handling recursive calls, management of variable length blocks, garbage collection and compaction, allocation strategies for arrays, structures, class.

Type checking: Overloading of functions and operators, polymorphic functions, unification algorithm.

Code generation and semantic analysis: Semantic stacks, attributed translation, analysis of syntax, directed translation, evaluation of expressions, control structures, procedure calls.

Code optimization: Basic blocks and folding, optimization within iterative loops, global optimization through flow graph analysis, code-improving transformations, machine dependent optimization.

Compiler-Compilers: Parser generators, YACC attributed LL (1) parser generator, machine independent code generation.

Other topics: Compilers for parallel machines, compilers for functional languages.

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Robotic manipulation: Automation and robotics, classification, applications, specifications, notations.

Direct kinematics: Dot and cross products, co-ordinate frames, rotations, homogeneous co-ordinates, link co-ordination, arm equation, (Five-axes robot, four-axes robot, six-axes robot), direct kinematics.

Inverse kinematics: General properties of solutions Tool configuration, five-axes, three-four-axes, six-axes robots (inverse kinematics). Workspace analysis and trajectory planning work envelopes and examples, workspace fixtures, pick and place operations, continuos path motion, and interpolated motion, straight-line motion.

Robot vision: Image representation, template matching, polyhedral objects, plane analysis, segmentation (thresholding, region labeling, shink operators, euler number, perspective transformations, structured illumination, camera calibration.

Task planning: Task level programming, uncertainty, and configuration space, gross motion, source and goal scenes, task planner simulation.

Moments of inertia.

Principles of NC and CNC machines.

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Digital image processing systems: Image acquisition, storage, processing, communication, display.

Visual perception: Structure of human eye, image formation in the human eye, brightness, adaptation and discrimination.

Image model: Uniform and non-uniform sampling, quantization.

Image transforms: Introduction to Fourier transform, DFT and two-dimensional DFT, some properties of DFT, separability, translation, periodicity, conjugate symmetry, rotation, scaling, average value, convolution theorem, correlation, FFt algorithms, inverse FFt, filter implementation through FFT. Other transforms : Other seperable image transforms and their algorithms

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Introduction to artificial intelligence: Introduction to AI languages- LISP and PROLOG.

Basic problem solving techniques: Search and heuristics, search algorithms, space search, AND/OR graph, game tree search.

Logic and theorem solving techniques forward chaining, backward chaining, resolution, and deduction.

Structured knowledge representation: Schemata, context-layered databases, truth maintenance, and procedural attachment.

Inference methods, predicate logic, semantic networks, frame, scripts. Programming in PROLOG.

Machine learning, planning, natural language processing, computer vision, and neural networks.

Introduction to expert systems.

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Introduction to parallel processing: Trends towards parallel processing, parallelism in uniprocessor systems, parallel computer structure, architectural classification schemes.

Memory and input output systems, memory structure hierarchy, addressing scheme for main memory, virtual memory systems, memory allocation and management strategies, virtual memory of X86 processors, cache memories, management and design criteria. I/O sub systems, interrupt mechanisms, I/O processors and I/O channels.

Pipelined and vector processors: overlapped parallelism, instruction and arithmetic pipelines, vector processing, scientific attached processor.

SIMD computers: SIMD perspectives, array and associative processors, study of an array processor.

Multi processor architecture: loosely and tightly coupled multi processors inter connection networks, parallel memory organization.

Data driven coupling, data flow computer architecture. Parallel algorithms, detection of parallelism, local balancing, communication and synchronization, features of typical parallel languages, monitors and operating systems.

Introduction to hybrid computers.

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Objectives :

· Introductory software engineering course that will present the software development lifecycle and methodology for dealing with each phase.

· Introduce the latest trends in large scale S/W development.

· Apply S/W principles to a large-scale design project.

· Ethics: Whistle blowing, human safety, embedded risk, software reliability, professional code of ethics.

· Fundamental problem solving concepts, top down design, procedural abstraction, control structures, data types.

· Software development process: Software life cycle models, specification design tools, software design objectives, documentation, configuration management, S/W reliability, safety, risk assessment and maintenance.

· Software estimation techniques, loc and FP estimation. Empirical models like COCOMO. Project tracking and scheduling. Reverse engineering.

· Software requirements and specifications: Informal/formal specifications, pre/post conditions, algebraic specifications and requirement analysis models.

· Software design and implementation: Functional/process oriented design, bottom up design, other design techniques (OOD,JSD), implementation strategies (top-down, bottom-up, team) and issues, reuse, performance improvement, debugging and antibugging.

· Verification, validation, testing and maintenance: Verification and validation techniques (pre/post -conditions, invariant, proof of correctness), code and design reading, structured walk through, testing (test plan, white/black box testing, unit and integration testing, regression testing, test case design and acceptance testing) and maintenance activities.

· Code sharing, software components, rapid prototyping, specialization, construction, class extensions, intelligent software agents.

· Introduction to CASE tools.

· Social, legal and ethical implications of computing.

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Introduction: Networks, architecture, applications, ISO model. Physical layer: Review of data communication, transmission and multiplexing, transmission media, error detection, recovery, interfacing, ISDN.

Topology: Introduction to topological problems, graph theory, network flow, traffic analysis, queuing theory and analysis of M/M/I systems.

Local area networks: Bus/ring/tree topology, medium access protocol, and performance.

Data link layer: Line configurations, flow control, error control, bit oriented link control, simplex and sliding window protocols, protocol performance evaluation.

Network layer: Communication networking techniques, circuit switching, message switching, packet switching, broadcast networks. Packet switching: virtual circuits and datagrams, routing, traffic control, congestion control, and error control.

Inter networking: bridge/router/gateway, connection oriented and connection-less inter networking. Services and protocols for transport layer, session layer and presentation layer. Data encryption and data compression. Application layer protocols: Architecture and access protocols.

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BASIC LANGUAGE & AUTOMATA THEORY : Review of finite automata, regular sets, Context-free grammars & languages, Moore & Mealy state machines, thier capabilities & limitations. Deterministic & Non-Deterministic FSM’s, Push-down stack & memory machine. (PDM)

TUNING MACHINES : Recursive languages, Turing acceptors, techniques for Turing machine construction, Church’s hypothesis, Turing machines as generators, variations & equivalence of Turing machines.

UNDECIDABILITY : Universal Turing machines, undecidability of the halting problem, and undecidable problems about contextfree languages.

THE CHOMSKY HIERARCHY : Grammars and their rel ations to automata, relations between classes of languages, LR(0) and LR(1) grammars , parser construction.

CLOSURE PROPERTIES OF FAMILIES OF LANGUAGES : Abstract families of languages, language operations, closure and decidability properties.

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Discrete Time Signals and Systems: Discrete time signal sequences, Linear Shift Invariant system, Stability, Linear Constant

Coefficient difference equations, Frequency domain representation of discrete time systems and signals, symmetry properties of

Fourier Transform, Sampling of continuous time signal, Two dimensional sequences and system.

Z Transform: Z-transform, Inverse z transform theorem and properties, System functions, Two-dimensional transforms.

The Discrete Fourier Transform: Representation of periodic sequences, The Discrete Fourier Series, Properties of the discrete

Fourier series, Sampling the z-transform, Fourier representation of finite deviation sequences, the discrete fourier transform, properties of the DFT, Linear convolution using the DFT, two dimensional DFT.

Flow Graph and Matrix Representation of Digital Filters: Signal flow graph representation of digital networks, Matrix representation of digital networks, Basic network structures for IIR, Transposed forms, Basic network structures for FIR systems, Parameter Quantization effects, Tellegen’s theorem for digital filters and its applications.

Digital Filter Design Techniques: Design of IIR digital filters from analog filters, Properties of FIR digital filters, Design of FIR filters using windows, Comparison of IIR and FIR filters.

Computation of The Discrete Fourier Transform: Goertzel’s Algorithm, Decimation in time algorithms, Decimation in frequency algorithms, FFT algorithms for a N composite number, General computational considerations in FFT algorithms, Chirps Z transform algorithm.

Discrete Hilbert Transform: Real and Imaginary part sufficiency for causal sequences, Minimum phase condition, Hilbert Transform relation for the DFT and the complex sequences.

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