MUVIS is a series of CBIR systems. The first one has been developed in late 90s to support indexing and retrieval in large image databases using visual and semantic features such as color, texture and shape. During recent years. MUVIS has been reformed to become a PC-based framework, which supports indexing, browsing and querying of various multimedia types such as audio. video, audiohideo interlaced and several image formats. MUVIS system allows real-time audio and video capturing, encoding by last generation codecs such as MPEG-4. H.263+. MP3 and AAC. It supports several audiohideo file format such as AVI, MP4, MP3 and AAC. Furthermore. MWIS system provides a well-defined interface for third parties to integrate their own feature extraction algorithms into the framework and for this reason it has recently been adopted by COST 21 lquat as COST framework for CBR. In this paper. we describe the general system features with underlying applications and outline the main philosophy. 1.

. We survey results on online versions of the standard network optimization problems, including the minimum spanning tree problem, the minimum Steiner tree problem, the weighted and unweighted matching problems, and the traveling salesman problem. The goal in these problems is to maintain, with minimal changes, a low cost subgraph of some type in a dynamically changing network. 1 Introduction In the early 1920's Otakar Bor uvka was asked by the Electric Power Company of Western Moravia (EPCWM) to assist in EPCWM's electrification of southern Moravia by solving from a mathematical standpoint the question of how to construct the most economical electric power network [9]. In 1926 Bor uvka initiated the study of network optimization problems, by publishing an efficient algorithm for constructing a minimum spanning tree of a fixed network [9]. Certainly since the 1920's the underlying collection of sites that require electrification in southern Moravia has changed frequently as new sites ...

We analyze a model of network formation where the costs of link formation are publicly known but individual benefits are not known to the social planner. The objective is to design a simple mechanism ensuring efficiency, budget balance and equity. We propose two mechanisms towards this end; the first ensures efficiency and budget balance but not equity. The second mechanism corrects the asymmetry in payoffs through a two-stage variant of the first mechanism. We also discuss an extension of the basic model to cover the case of directed graphs and give conditions under which the proposed mechanisms are immune to coalitional deviations. We thank Francis Bloch, an associate editor and an anonymous referee for their comments on this paper. A previous version was written when Mutuswami was visiting CORE, Belgium. He thanks them for their support.

Performance evaluation of Maximum-Likelihood (ML) soft-decision-decoded binary block codes is usually carried out using bounding techniques. Many tight upper bounds on the error probability of binary codes are based on the so-called Gallager’s First Bounding Technique (GFBT). The Tangential Sphere Bound (TSB) of Poltyrev which is believed for many years to offer the tightest bound developed for binary block codes is an example. Within the framework of the TSB and GFBT, we apply a new method referred to as the “Added-Hyper-Plane ” (AHP) technique, to the decomposition of the error probability. This results in a bound developed upon the application of two stages of the GFBT with two different Gallager regions culminating to a tightened upper bound beyond the TSB. The proposed bound is simple and only requires the spectrum of the binary code.

Massive gene-expression data are generated using microarrays, and clustering gene-expression data is useful for studying functional relationship among genes in a biological process. We have developed a computer package, EXCAVATOR

The parallel watershed transformation used in gray-scale image segmentation is here augmented to perform with the aid of a priori supplied image cues called markers. The reason for introducing markers is to calibrate a resilient algorithm to oversegmentation. In a hybrid fashion, pixels are first clustered based on spatial proximity and gray-level homogeneity with the watershed transformation. Boundary-based region merging is then effected to condense nonmarked regions into marked catchment basins. The agglomeration strategy works with a weighted neighborhood graph representation of the oversegmented image. The throughput of a parallel Boru # vka-like minimum spanning forest (MSF) operator, applied on the considered graph, embodies the desired image partition, reasoning that all regions in a tree fuse into a homogeneous area containing a unique marker. Two figures of merit of the parallel algorithm are worth mentioning: the local detection of the catchment basins conforming to the watershed principle (which strongly depends on the history of the regions ' growth) and the parallel computation of the Boru # vka-like MSF which merges, at the same time, partial regions, produced by the local labeling, and nonmarked regions to marked basins. Both modules are designed with great concurrency, locality, and reduced software engineering cost, emerging into a scalable algorithm.

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In this paper, we present a protocol for dynamically maintaining a degree-bounded delay sensitive spanning tree in a decentralized way on overlay networks. The protocol aims at repairing the spanning tree autonomously even if multiple nodes ’ leave operations or failures (disappearances) occur simultaneously or continuously in a specified period. It also aims at maintaining the diameter (maximum delay) of the tree as small as possible. The simulation results using ns-2 have shown that the protocol could keep reasonable diameters compared with the existing centralized static algorithm even if many nodes ’ participations and disappearances occur frequently. 1

We address the question of theoretical vs. practical behavior of algorithms for the minimum spanning tree problem. We review the factors that influence the actual running time of an algorithm, from choice of language, machine, and compiler, through low-level implementation choices, to purely algorithmic issues. We discuss how to design a careful experimental comparison between various alternatives. Finally, we present some results from an ongoing study in which we are using: multiple languages, compilers, and machines; all the major variants of the comparison-based algorithms; and eight varieties of graphs with sizes of up to 130,000 vertices (in sparse graphs) or 750,000 edges (in dense graphs). 1 Introduction Finding spanning trees of minimum weight (minimum spanning trees or MSTs) is one of the best known graph problems; algorithms for this problem have a long history, for which see the article of Graham and Hell [6]. The best comparison-based algorithm to date, due to Gabow...

This article presents two simple deterministic algorithms for nding the Minimum Spanning Tree in O(jV j + jEj) time for any proper class of graphs closed on graph minors, which includes planar graphs and graphs of bounded genus. Both algorithms require no a priori knowledge of the structure of the class except for its density; edge weights are only compared and no random access to data is needed.