Despite the growing number of works centering around the traffic dynamics on complex networks,these researches still have some common shortcomings,e.g.,too simple traffic flow model and lack of considerations for the ...
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Despite the growing number of works centering around the traffic dynamics on complex networks,these researches still have some common shortcomings,e.g.,too simple traffic flow model and lack of considerations for the designing cost and scalability *** paper builds on a more realistic traffic flow model,and offers a holistic view on the network designing *** addition to the extensively studied transmission capacity,this paper takes designing cost and scalability as two other designing objectives,and presents a quantitative study of how different designing choices independently and collectively influence these objectives by the introduction of a cartesian coordinate *** is shown that different kinds of network topologies display different shapes of achievable solution spaces and exhibit different abilities to achieve cost-effective and scalable *** particular,we find the philosophy underlying empirical network designing and engineering today fails to meet the cost-effective and scalable designing requirements,and propose a cost-effective and scalable designing scheme for BA-like networks,i.e.,the efficient routing combined with effective betweenness based link bandwidth *** addition,when designing a thoroughly new network from the beginning,we find that ER network is a good candidate to achieve cost-effective and scalable designing in most settings.
Traditional learning techniques have the assumption that training and test data are drawn from the same data distribution, and thus they are not suitable for dealing with the situation where new unlabeled data are obt...
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Ant colony optimization algorithms have been successfully applied to solve many problems. However, in some large scale optimization problems involving large amounts of data, the optimization process may take hours or ...
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Image classification is a challenging problem in computer vision. Its performance heavily depends on image features extracted and classifiers to be constructed. In this paper, we present a new support vector machine w...
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Estimating taxonomic content constitutes a key problem in metagenomic sequencing data ***,extracting such content from high-throughput data of next-generation sequencing is very time-consuming with the currently avail...
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Estimating taxonomic content constitutes a key problem in metagenomic sequencing data ***,extracting such content from high-throughput data of next-generation sequencing is very time-consuming with the currently available ***,we present CloudLCA,a parallel LCA algorithm that significantly improves the efficiency of determining taxonomic composition in metagenomic data *** show that CloudLCA(1)has a running time nearly linear with the increase of dataset magnitude,(2)displays linear speedup as the number of processors grows,especially for large datasets,and(3)reaches a speed of nearly 215 million reads each minute on a cluster with ten thin *** comparison with MEGAN,a well-known metagenome analyzer,the speed of CloudLCA is up to 5 more times faster,and its peak memory usage is approximately 18.5%that of MEGAN,running on a fat *** can be run on one multiprocessor node or a *** is expected to be part of MEGAN to accelerate analyzing reads,with the same output generated as MEGAN,which can be import into MEGAN in a direct way to finish the following ***,CloudLCA is a universal solution for finding the lowest common ancestor,and it can be applied in other fields requiring an LCA algorithm.
Some expanded fuzzy rough sets models have been investigated to handle fuzzy databases with uncertain, imprecise and incomplete real-valued information. In this paper, we make further research on fuzzy rough sets mode...
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With the opinion explosion on Web, there are growing research interests in opinion mining. In this study we focus on an important problem in opinion mining - Aspect Identification (AI), which aims to extract aspect te...
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In this paper, we propose an enhanced associative classification method by integrating the dynamic property in the process of associative classification. In the proposed method, we employ a support vector machine(SVM...
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In this paper, we propose an enhanced associative classification method by integrating the dynamic property in the process of associative classification. In the proposed method, we employ a support vector machine(SVM) based method to refine the discovered emerging ~equent patterns for classification rule extension for class label prediction. The empirical study shows that our method can be used to classify increasing resources efficiently and effectively.
Sharing Semantic Web datasets provided by different publishers in a decentralized environment calls for efficient support from distributed computing technologies. Moreover, we argue that the highly dynamic ad-hoc sett...
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MicroRNAs(miRNAs)are a class of small non-coding RNAs that play important roles in post-transcriptional regulation of gene expression[1].A large number of miRNAs have been found to be involved in a broad spectrum of b...
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MicroRNAs(miRNAs)are a class of small non-coding RNAs that play important roles in post-transcriptional regulation of gene expression[1].A large number of miRNAs have been found to be involved in a broad spectrum of biological functions such as regulation of innate and adaptive immunity,cell differentiation and development as well as
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