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Bansilal Ramnath Agarwal Charitable Trust’s Vishwakarma Institute of Technology, Pune – 411 037 Department of Electronics and Telecommunication Engineering Unit IV Remote Sensing Applications in Space Sciences (8 Hrs) A. Study of High Power Large Aperture radars, Phased arrays, Coherent and Incoherent Scattering, Effect of radio science on actual radar measurements, Study of E-region of ionosphere and its effect on communications. B. Study of latest radar systems such as modular design radar such as the Advanced Modular Incoherent Scatter Radar. Unit V (8 Hrs) Remote Sensing Applications in Natural Disaster Assessment and Land Cover Mapping A. Radar Interferometer, Synthetic Aperture Radars (SAR), Interferometric Synthetic Aperture Radar (InSAR), Applications of SAR - polar research, mapping ocean currents, seismic events, volcanic hazards B. Study of Alaska SAR Facility Text Books 1. Introduction to Radar Systems by Merrill Skolnik 2. Radar Principles by Peyton Z. Peebles Reference Books 1. Synthetic Aperture Radar Interferometry by Richard Balmer and Philipp Hartl(1998) Inverse Problems 14 R1. 2. Radar Interferometry: A new technique for studying plasma turbulence in the ionosphere by Farley and Fejer (1981) Journal of Geophysical Research Vol. 86, No. A3 Structure & Syllabus of B.E (E&TC) Program – Pattern ‘C11’, Rev01, dt. 2/4/2011 44
Bansilal Ramnath Agarwal Charitable Trust’s Vishwakarma Institute of Technology, Pune – 411 037 Department of Electronics and Telecommunication Engineering FF No.: 654 EC42102 :: ARTIFICIAL INTELIGENCE Credits: 03 Prerequisite: Teaching Scheme: - Theory 3 Hrs/Week NIL OBJECTIVE:- • To provide a strong foundation of fundamental concepts in Artificial Intelligence • To provide a basic exposition to the goals and methods of Artificial Intelligence • To enable the student to apply these techniques in applications which involve perception, reasoning and learning. • Mapping with PEOs:2,3,4,6,7,8,9 Unit 1: Introduction to Artificial Intelligence (6 Hrs) A. AI task domain, problem representation in AI, Problem characteristics. B. Game playing using AI. Unit 2: Searching Techniques (9 Hrs) A. A.I. search process, non-heuristic and heuristic search techniques, constrain satisfaction and their applications. B) Min-max search procedure. Unit 3: Knowledge Representation (8 Hrs) A. Hierarchy of knowledge, types of knowledge, knowledge representation, methods for knowledge representation, predicate logic, Problems on predicate logic. B. Introduction to PROLOG. Unit 4: Planning (8 Hrs) A. Components of planning system, goal stack planning technique. B. Nonlinear Planning using Constraint Posting. Unit 5: AI Tools (9 Hrs) A. Expert System Shells, Explanation, and Knowledge Acquisition. Human expert behaviors, Expert system components, structure of expert system, the production system, how expert system work and Expert system development for particular application. Natural language processing: Introduction, Syntactic Processing, Semantic Analysis, Discourse and Pragmatic Processing. Architectures and functions in ANN, various learning rules. Building an ANN. B. Building an Expert System Structure & Syllabus of B.E (E&TC) Program – Pattern ‘C11’, Rev01, dt. 2/4/2011 45
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