66 research outputs found

    Online Permutation Routing in Partitioned Optical Passive Star Networks

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    This paper establishes the state of the art in both deterministic and randomized online permutation routing in the POPS network. Indeed, we show that any permutation can be routed online on a POPS network either with O(dglogg)O(\frac{d}{g}\log g) deterministic slots, or, with high probability, with 5cd/g+o(d/g)+O(loglogg)5c\lceil d/g\rceil+o(d/g)+O(\log\log g) randomized slots, where constant c=exp(1+e1)3.927c=\exp (1+e^{-1})\approx 3.927. When d=Θ(g)d=\Theta(g), that we claim to be the "interesting" case, the randomized algorithm is exponentially faster than any other algorithm in the literature, both deterministic and randomized ones. This is true in practice as well. Indeed, experiments show that it outperforms its rivals even starting from as small a network as a POPS(2,2), and the gap grows exponentially with the size of the network. We can also show that, under proper hypothesis, no deterministic algorithm can asymptotically match its performance

    State-of-the-art Assessment For Simulated Forces

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    Summary of the review of the state of the art in simulated forces conducted to support the research objectives of Research and Development for Intelligent Simulated Forces

    New Techniques in Scene Understanding and Parallel Image Processing.

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    There has been tremendous research interest in the areas of computer and robotic vision. Scene understanding and parallel image processing are important paradigms in computer vision. New techniques are presented to solve some of the problems in these paradigms. Automatic interpretation of features in a natural scene is the focus of the first part of the dissertation. The proposed interpretation technique consists of a context dependent feature labeling algorithm using non linear probabilistic relaxation, and an expert system. Traditionally, the output of the labeling is analyzed, and then recognized by a high level interpreter. In this new approach, the knowledge about the scene is utilized to resolve the inconsistencies introduced by the labeling algorithm. A feature labeling system based on this hybrid technique is designed and developed. The labeling system plays a vital role in the development of an automatic image interpretation system for oceanographic satellite images. An extensive study on the existing interpretation techniques has been made in the related areas such as remote sensing, medical diagnosis, astronomy, and oceanography and has shown that our hybrid approach is unique and powerful. The second part of the dissertation presents the results in the area of parallel image processing. A new approach for parallelizing vision tasks in the low and intermediate levels is introduced. The technique utilizes schemes to embed the inherent data or computational structure, used to solve the problem, into parallel architectures such as hypercubes. The important characteristic of the technique is that the adjacent pixels in the image are mapped to nodes that are at a constant distance in the hypercube. Using the technique, parallel algorithms for neighbor-finding and digital distances are developed. A parallel hypercube sorting algorithm is obtained as an illustration of the technique. The research in developing these embedding algorithms has paved the way for efficient reconfiguration algorithms for hypercube architectures

    Technology 2000, volume 1

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    The purpose of the conference was to increase awareness of existing NASA developed technologies that are available for immediate use in the development of new products and processes, and to lay the groundwork for the effective utilization of emerging technologies. There were sessions on the following: Computer technology and software engineering; Human factors engineering and life sciences; Information and data management; Material sciences; Manufacturing and fabrication technology; Power, energy, and control systems; Robotics; Sensors and measurement technology; Artificial intelligence; Environmental technology; Optics and communications; and Superconductivity

    Harmonic Analysis Inspired Data Fusion for Applications in Remote Sensing

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    This thesis will address the fusion of multiple data sources arising in remote sensing, such as hyperspectral and LIDAR. Fusing of multiple data sources provides better data representation and classification results than any of the independent data sources would alone. We begin our investigation with the well-studied Laplacian Eigenmap (LE) algorithm. This algorithm offers a rich template to which fusion concepts can be added. For each phase of the LE algorithm (graph, operator, and feature space) we develop and test different data fusion techniques. We also investigate how partially labeled data and approximate LE preimages can used to achieve data fusion. Lastly, we study several numerical acceleration techniques that can be used to augment the developed algorithms, namely the Nystrom extension, Random Projections, and Approximate Neighborhood constructions. The Nystrom extension is studied in detail and the application of Frame Theory and Sigma-Delta Quantization is proposed to enrich the Nystrom extension

    LIPIcs, Volume 244, ESA 2022, Complete Volume

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    LIPIcs, Volume 244, ESA 2022, Complete Volum

    ISCR Annual Report: Fical Year 2004

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    Efficient Passive Clustering and Gateways selection MANETs

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    Passive clustering does not employ control packets to collect topological information in ad hoc networks. In our proposal, we avoid making frequent changes in cluster architecture due to repeated election and re-election of cluster heads and gateways. Our primary objective has been to make Passive Clustering more practical by employing optimal number of gateways and reduce the number of rebroadcast packets

    Grid-enabled adaptive surrugate modeling for computer aided engineering

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