To meet the requirements of operation orders auto-generation, a topology information data structure is designedAbove this, several algorithms are proposed, which support to generate operation orders for the tasks of c...
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To meet the requirements of operation orders auto-generation, a topology information data structure is designedAbove this, several algorithms are proposed, which support to generate operation orders for the tasks of cell maintenance, cell transmission, full circuitry maintenance, range of circuitry maintenance, and switch load algorithmsThese algorithms can use in the distribution networkThe auto-generation only accords the topology information that distilled from the graphicIt is easily use for the maintain personnel.
Cross-domain text categorization targets on adapting the knowledge learnt from a labeled source domain to an unlabeled target domain, where the documents from the source and target domains are drawn from different dis...
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The FPgrowth is a famous frequent pattern's algorithm in data mining when working with high-dimensional, large-scale data sets. It is also known as great complexity on memory for the recursively processing. In gen...
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The FPgrowth is a famous frequent pattern's algorithm in data mining when working with high-dimensional, large-scale data sets. It is also known as great complexity on memory for the recursively processing. In general, FPgrowth cannot handle large-scale data set unless dividing a whole data set into small blocks. Based on Hadoop, the open cloud computing model, a distributed DH-TRIE frequent pattern algorithm using JPA is proposed, which solved the three problems (globalization, random-write and duration). The algorithm is shown good flexibility and scalability by comparisons to mahout project. By applied to a virtualization platform Vega Cloud, the algorithm will be used in far-ranging situations.
Image authentication is usually approached by checking the preservation of some invariant features, which are expected to be both robust and discriminative so that content-preserving operations are accepted while cont...
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Image authentication is usually approached by checking the preservation of some invariant features, which are expected to be both robust and discriminative so that content-preserving operations are accepted while content-altering manipulations are rejected. However, most of existing features have not obtained convincing performance due to insufficiency of experiments and over biasing of robustness. Motivated by the sparse coding strategy discovered in primary visual cortex, we explore the possibility of using sparse coding coefficients for image authentication. Through extensive experiments, we discover that the proposed feature bears great discrimination as well as robustness, which indicates the effectiveness of sparse coding as a new invariant feature for image authentication.
A relative significance factor of an impact category is the external weight of the impact category and plays an important role in life cycle assessment(LCA). Many multiattribute decision-making (MADM) methods such as ...
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A relative significance factor of an impact category is the external weight of the impact category and plays an important role in life cycle assessment(LCA). Many multiattribute decision-making (MADM) methods such as analytical hierarchy process(AHP), the rank-order centroid method and the fuzzy method are proposed to determine the relative significance factor of an impact category. However, in previous research, it is shown that, the AHP approach is difficult for experts rendering consistent judgment when the number of pairwise comparisons increases, the rank-order method has some insurmountable shortcomings, the key issue to use fuzzy set theory is its complexity. In order to address this problem, a new simple and efficient method is proposed to determine relative significance factor in a more efficient manner. An example to determine relative significance factor of impact categories is shown to illustrate the efficiency of the proposed method.
In this paper, a novel Sparsely Encoded Local Descriptor (SELD) is proposed for face recognition. Compared with K-means or Random-projection tree based previous methods, sparsity constraint is introduced in our dictio...
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In this paper, a novel Sparsely Encoded Local Descriptor (SELD) is proposed for face recognition. Compared with K-means or Random-projection tree based previous methods, sparsity constraint is introduced in our dictionary learning and sequent image encoding, which implies more stable and discriminative face representation. Sparse coding also leads to an image descriptor of summation of sparse coefficient vectors, which is quite different from existing code-words appearance frequency(/histogram)-based descriptors. Extensive experiments on both FERET and challenging LFW database show the effectiveness of the proposed SELD method. Especially on the LFW dataset, recognition accuracy comparable to the best known results is achieved.
The degree of similarity between fuzzy numbers plays an important role in fuzzy information fusion. In this paper, improved ROG-based similarity measure developed from the current ROG method is presented. It is shown ...
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MicroRNAs can regulate hundreds of target genes and play a pivotal role in a broad range of biological process. However, relatively little is known about how these highly connected miRNAs-target networks are remodelle...
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MicroRNAs can regulate hundreds of target genes and play a pivotal role in a broad range of biological process. However, relatively little is known about how these highly connected miRNAs-target networks are remodelled in the context of various diseases. Here we examine the dynamic alteration of context-specific miRNA regulation to determine whether modified microRNAs regulation on specific biological processes is a useful information source for predicting cancer prognosis. A new concept, Context-specific miRNA activity (CoMi activity) is introduced to describe the statistical difference between the expression level of a miRNA's target genes and non-targets genes within a given gene set (context).
A group of decision-makers may differ in their choice of alternatives while taking a decision. So, in any decision-making problem concerning decisions made by a group, the question arises how best we can aggregate ind...
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