7000665
Multiple Agents Moving Target Search
Traditional single-agent search algorithms usually make simplifying assumptions (single search agent, stationary target, complete knowledge of the state, and sufficient time). There are algorithms for relaxing one or two of these constraints; in this paper we want to relax all four. The application domain is to have multiple search agents cooperate to pursue and capture a moving target. Agents are allowed to communicate with each other. For solving Multiple Agents Moving Target (MAMT) applications, we present a framework for specifying a family of suitable search algorithms. This paper investigates several effective approaches for solving problem instances in this domain.
18740255
Selected String Representation for Whole Genomes
The increase in the amount of available genomic data has made phylogenetic analysis possible at the whole genome scale. However, such a huge amount of data imposes computational challenges in both memory consumption and CPU usage. One novel proposal in this paper is to extract sequence patterns that are biologically meaningful. Using these patterns, whole genomes can be mapped into a significantly lower dimensional space and subsequent studies using these representations become computationally feasible. Experiments on two datasets of 64 vertebrate mitochondrial genomes and 99 prokaryote whole genomes demonstrate that the selected sequence patterns result in good quality evolutionary distances in terms of the final phylogeny.
6198928
Energy-Efficient Deployment of Mobile Sensor Networks by PSO
Sensor deployment is an important issue in designing sensor networks. In this paper, particle swarm optimization (PSO) approach is applied to maximize the coverage based on a probabilistic sensor model in mobile sensor networks and to reduce cost by finding the optimal positions for the cluster-head nodes based on a well-known energy model. During the coverage optimization process, sensors move to form a uniformly distributed topology according to the execution of algorithm at base station. The simulation results show that PSO algorithm has faster convergence rate than genetic algorithm based method while achieving the goal of energy efficient sensor deployment.
35689582
A fast recurring two-dimensional entropic thresholding algorithm
Thresholding is an important form of image segmentation and is used in the processing of images for many applications. One of the criteria to select a suitable threshold is the maximization of the two-dimensional (2-D) entropies based on the 2-D (gray-level/local average gray-level) histogram. The rationale of this approach is introduced. In order to reduce the computation time of entropy function, a fast recurring algorithm for 2-D entropic thresholding method is presented. The experimental results show that the processing time to obtain the threshold vector from 2-D histogram is reduced from 30 to 0.15 s.
11584790
SLEVEs for planar spline curves
Given a planar spline curve and local tolerances, a matched pair of polygons is computed that encloses the curve and whose width (distance between corresponding break points) is below the tolerances. This is the simplest instance of a subdividable linear efficient variety enclosure, short sleve.We develop general criteria, that certify correctness of a global, polygonal enclosure built from a sequence of individual bounding boxes by extending and intersecting their edges. These criteria prove correctness of the sleve construction.
14606443
Database classification for multi-database mining
Many large organizations have multiple databases distributed in different branches, and therefore multidatabase mining is an important task for data mining. To reduce the search cost in the data from all databases, we need to identify which databases are most likely relevant to a data mining application. This is referred to as database selection. For real-world applications, database selection has to be carried out multiple times to identify relevant databases that meet different applications. In particular, a mining task may be without reference to any specific application. In this paper, we present an efficient approach for classifying multiple databases based on their similarity between each other. Our approach is application-independent.
117096759
Determining an Optimal Penetration Among Weighted Regions in Two and Three Dimensions
We present efficient algorithms for solving the problem of computing an optimal penetration (a ray or a semi-ray) among weighted regions in 2-D and 3-D spaces. This problem finds applications in several areas, such as radiation therapy, geological exploration, and environmental engineering. Our algorithms are based on a combination of geometric techniques and optimization methods. Our geometric analysis shows that the d-D (d = 2, 3) optimal penetration problem can be reduced to solving O(n2(d−1)) instances of certain special types of non-linear optimization problems, where n is the total number of vertices of the regions. We also give implementation results of our 2-D algorithms.