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We present novel grid coverage strategies for effective surveillance and target location in distributed sensor networks. We represent the sensor field as a grid (two or three-dimensional) of points (coordinates) and use the term target location to refer to the problem of locating a target at a grid point at any instant in time. We first present an integer(More)
Distributed, real-time sensor networks are essential for effective surveillance in the digitized battlefield and for environmental monitoring. In this paper, we present the first systematic theory that leads to novel sensor deployment strategies for effective surveillance and target location. We represent the sensor field as a grid (two-or(More)
Wireless sensor networks have the potential to become significant subsystems of ecological experiment. Sensor networks consist of large number of tiny sensor nodes, all of which have sensing capabilities. These networks allow coordinated signal detection, monitoring, and tracking to enable sensor nodes to simultaneously capture geographically distinct(More)
Ecological data are difficult to analyze due to complexity residing in the ecological systems with the variables varying in non-linear fashion. Efficient methods are required to properly extract information out of the complex data. Wavelets have good time–frequency (timescale) localization, can represent data parsimoniously, and can be implemented with very(More)
An automatic discovery method that discovers frequent access routines for unique clients from web access log files is presented. Proposed algorithm develops novel techniques to extract the sets of all predictive access sequences from semi-structured web access logs. Important user access patterns are manifested through the frequent traversal paths, thus(More)
This study was performed to gain an understanding of the structural and functional relationships between inter-taxa communities (macroinvertebrates as consumers, and microbes as decomposers or preys for the invertebrates) in a polluted stream using artificial neural networks techniques. Sediment samples, carrying microorganisms (eubacteria) and(More)
Given a set X and a set C of subsets of X, subsets of X covered by k sets in C are called k-frequent. Frequent sets are of interest in large scale data analysis, pattern recognition and data mining. Characterization of maximal k-frequent sets in terms of equivalence relation and partial order is given. A general algorithm for finding maximal k-frequent(More)
Distributed, real-time sensor networks are essential for effective surveillance in the digitized battlefield and for environmental monitoring. In this paper, we present the first systematic theory that leads to novel sensor deployment strategies for effective surveillance and target location. We represent the sensor field as a grid (two-or(More)