Depth of field (DoF) is a depth range outside of which objects are blurred. DoF has been widely used in photography and films by artists and is expected to be applied to realistic image rendering and virtual reality a...
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Considering the timed properties between the interactions of Web services, we model the Web services with timed properties formally and propose a method for detecting mismatch of time-aware Web services based on Satis...
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We report our work on evaluating performance of several MPI Allgather algorithms on Fast Ethernet. These algorithms are ring, recursive doubling, Bruck, and neighbor exchange. The first three algorithms are widely use...
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ISBN:
(纸本)0769524869
We report our work on evaluating performance of several MPI Allgather algorithms on Fast Ethernet. These algorithms are ring, recursive doubling, Bruck, and neighbor exchange. The first three algorithms are widely used today. The neighbor exchange algorithm which was recently proposed by the authors incorporates pair-wise exchange, and is expected to perform better with certain configurations, mainly when using TCP/IP over Ethernet. We tested the four algorithms on terascale Linux clusters DeepComp 6800 and DAWNING 4000A using TCP/IP over Fast Ethernet. Results show that our neighbor exchange algorithm performs the best for long messages, the ring algorithm performs the best for medium-size messages and the recursive doubling algorithm performs the best for short messages.
Moving Target Defense (MTD) is a new technology to defend against the false data injection attack (FDIA) on distribution systemstate estimation (DSSE). It works by proactively perturbing the branch reactance. However...
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Utility services provided by cloud computing rely on virtual customer communities forming spontaneously and evolving continuously. Clarifying the explicit boundaries of these communities is thus essential to the quali...
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In order to solve the sparse initial information problem when the topic model was established ever before, this paper establishes the Wikipedia based news event knowledge base. Referring to this knowledge base, we cal...
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This paper describes attribute extraction, attribute classification and data cleaning process in tourism emergency, builds a widely applicable decision table, and uses the attribute reduction algorithm based on the im...
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Location recommendation is an important feature of social network applications and location-based services. Most existing studies focus on developing one single method or model for all users. By analyzing real locatio...
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Location recommendation is an important feature of social network applications and location-based services. Most existing studies focus on developing one single method or model for all users. By analyzing real location-based social networks, in this paper we reveal that the decisions of users on place visits depend on multiple factors, and different users may be affected differently by these factors. We design a location recommendation framework that combines results from various recommenders that consider various factors. Our framework estimates, for each individual user, the underlying influence of each factor to her. Based on the estimation, we aggregate suggestions from different recommenders to derive personalized recommendations. Experiments on Foursquare and Gowalla show that our proposed method outperforms the state-of the-art methods on location recommendation.
In this paper, we introduce a novel Local Gabor Binary Pattern Random Subspace Method (LGBPRSM) for wearing-glasses face recognition. It extracts the discriminating features from facial space based on local-feature me...
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We present a particle swarm optimization algorithm OT-PSO using orthogonal test technique. Based on the classical PSO, OT-PSO searches for local optimum in the neighbor area of the global best solution by using the me...
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