In today’s fast paced world, as the number of stations of television programming offered is increasing rapidly, time accessible to watch them remains same or decreasing. Sports videos are typically lengthy and they appeal to a massive crowd. Though sports video is lengthy, most of the viewer’s desire to watch specific segments of the video which are fascinating, like a home-run in a baseball or goal in soccer i.e., users prefer to watch highlights to save time. When associated to the entire span of the video, these segments form only a minor share. Hence these videos need to be summarized for effective presentation and data management. This thesis explores the ability to extract highlights automatically using MPEG-7 features and hidden Markov model (HMM), so that viewing time can be reduced. Video is first segmented into scene shots, in which the detection of the shot is the fundamental task. After the video is segmented into shots, extraction of key frames allows a suitable representation of the whole shot. Feature extraction is crucial processing step in the classification, video indexing and retrieval system. Frame features such as color, motion, texture, edges are extracted from the key frames. A baseball highlight contains certain …

In this thesis, I present my study on the impact of multi-group network structure on the performance of consensus building strategies, and the preliminary mathematical formulation of the problem on improving the performance of the National Airspace system (NAS) through long-term investment. The first part of the thesis is concerned with a structural approach to the consensus building problem in multi-group distributed sensor networks (DSNs) that can be represented by bipartite graph. Direct inference of the convergence behavior of consensus strategies from multi-group DSN structure is one of the contributions of this thesis. The insights gained from the analysis facilitate the design and development of DSNs that meet specific performance criteria. The other part of the thesis is concerned with long-term planning and development of the NAS at a network level, by formulating the planning problem as a resource allocation problem for a flow network. The network-level model viewpoint on NAS planning and development will give insight to the structure of future NAS and will allow evaluation of various paradigms for the planning problem.

This research discusses how the design of a tornado forward error correcting channel code (FEC) sends digital data stream profiles to the receiver. The complete design was based on the Tornado channel code, binary phase shift keying (BPSK) modulation on a Gaussian channel (AWGN). The communication link was simulated by using Matlab, which shows the theoretical systems efficiency. Then the data stream was input as data to be simulated communication systems using Matlab. The purpose of this paper is to introduce the audience to a simulation technique that has been successfully used to determine how well a FEC expected to work when transferring digital data streams. The goal is to use this data to show how FEC optimizes a digital data stream to gain a better digital communications systems. The results conclude by making comparisons of different possible styles for the Tornado FEC code.

In this thesis, I introduce a promising framework for representing an air traffic flow (stream) and flow-management action operating under weather uncertainty. I propose to use a meshed queuing and Markov-chain model---specifically, a queuing model whose service-rates are modulated by an underlying Markov chain describing weather-impact evolution---to capture traffic management in an uncertain environment. Two techniques for characterizing flow-management performance using the model are developed, namely 1) a master-Markov-chain representation technique that yields accurate results but at relatively high computational cost, and 2) a jump-linear system-based approximation that has promising scalability. The model formulation and two analysis techniques are illustrated with numerous examples. Based on this initial study, I believe that the interfaced weather-impact and traffic-flow model analyzed here holds promise to inform strategic flow contingency management in NextGen.