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In this paper, an energy-efficient subchannel and power allocation scheme for a downlink marco-femto heterogeneous network is proposed. The optimization problem which maximizes the energy efficiency of all the FBSs subject to resource allocation constraints is formulated. To solve the formulated NP hard problem, we first apply clustering algorithm, which groups FBSs with interference being lower than...
Binary representation for large scale nearest neighbor search received more and more concern recently. Although binary codes can be directly used as indices of the hash tables, correlations between the bits may lead to non-uniform codes distribution and reduce the performance of the hash table. In this paper, we propose a data driven multi-index hashing method for exact nearest neighbor search in...
Optimized placement of clients in a distributed publish/subscribe system is an important technique to improve overall system efficiency. Current methods, like interest clustering or publisher placement, treat a client as, either a pure publisher, or subscriber, but not as both. Also, the cost of client movement is usually ignored. However, many applications based on publish/subscribe systems model...
A mathematical symbol recognition approach based on ISOETRP Clustering Algorithm is proposed in this paper. Mathematical symbol is one kind of special image symbols, different from ordinary text character in several aspects. For this point, firstly, one special features extraction algorithm is proposed, then two kinds of Classifier are used, one is Minimum Distance Classifier, another is Tree Classifier...
Given countless web videos available online, one problem is how to help users find videos to their taste in an efficient way. In this paper, to facilitate userpsilas browsing we propose relevant and exploratory recommendation algorithms utilizing multimodal similarity and contextual network to organize web videos of various topics. Comparison experiments demonstrate proposed approach generates more...
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