In the past decade, many papers about granular computing(GrC) have been published, but the keypoints about granular computing(GrC) are still unclear. In this paper, we try to find the key points of GrC in the informat...
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This paper describes a novel model using dependency structures on the source side for syntax-based statistical machine translation: Dependency Treelet String Correspondence Model (DTSC). The DTSC model maps source dep...
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Structure alignment could help to find shape similarities between proteins and guide structure classification and fold recognition. Common substructure detection and extraction are especially important, for which coul...
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ISBN:
(纸本)9781424415786
Structure alignment could help to find shape similarities between proteins and guide structure classification and fold recognition. Common substructure detection and extraction are especially important, for which could guide the biologist to discover binding site or active site. We represent each segment of alpha-carbon backbone by using dihedral angles and curve moment invariants. Then, local and global structure alignment could be performed by iterative closest point algorithm. Maximum common substructures between a pair of proteins or within a protein could be found. Active sites also could be detected by the proposed algorithm.
Computational cognitive modeling has recently emerged as one of the hottest issues in the AI area. Both symbolic approaches and connectionist approaches present their merits and demerits. Although Bayesian method is s...
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Computational cognitive modeling has recently emerged as one of the hottest issues in the AI area. Both symbolic approaches and connectionist approaches present their merits and demerits. Although Bayesian method is suggested to incorporate advantages of the two kinds of approaches above, there is no feasible Bayesian computational model concerning the entire cognitive process by now. In this paper, we propose a variation of traditional Bayesian network, namely Globally Connected and Locally Autonomic Bayesian Network (GCLABN), to formally describe a plausible cognitive model. The model adopts a unique knowledge representation strategy, which enables it to encode both symbolic concepts and their relationships within a graphical structure, and to generate cognition via a dynamic oscillating process rather than a straightforward reasoning process like traditional approaches. Then a simple simulation is employed to illustrate the properties and dynamic behaviors of the model. All these traits of the model are coincident with the recently discovered properties of the human cognitive process.
An Immune Genetic Algorithm (IGA) is used to solve weapon-target assignment problem (WTA). The used immune system serves as a local search mechanism for genetic algorithm. Besides, in our implementation, a new crossov...
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Parallel corpus is an indispensable resource for translation model training in statistical machine translation (SMT). Instead of collecting more and more parallel training corpora, this paper aims to improve SMT perfo...
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In this paper, we propose forest-to-string rules to enhance the expressive power of tree-to-string translation models. A forest-to-string rule is capable of capturing non-syntactic phrase pairs by describing the corre...
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For Hyper Surface Classification (HSC), based on the concept of Minimal Consistent Subset for a disjoint Cover set (MCSC), a judgmental sampling method is proposed to select a representative subset from the original s...
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For Hyper Surface Classification (HSC), based on the concept of Minimal Consistent Subset for a disjoint Cover set (MCSC), a judgmental sampling method is proposed to select a representative subset from the original sample set in this *** sampling method depends on sample *** can directly solve the nonlinear multi-class classification problems and observe the sample *** sample distribution is obtained by adaptively dividing the sample space, and the classification model of hyper surface is directly used to classify large database based on Jordan Curve Theorem in Topology while sampling for *** number of MCSC is *** has the same classification model with the entire sample set and can totally reflect its classification *** any subset of the sample set that contains MCSC, the classification ability remains the ***, a formula is put forward that can predict the testing accuracy exactly when some samples are deleted from *** MCSC is the best way of sampling from the original sample set for Hyper Surface Classification method.
Superimpose one protein tertiary structure to another can help to find similarity between them and further identify functional and evolutionary relationships. We first extract invariant features under rigid body trans...
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One basic observation for pedestrian detection in video sequences is that both appearance and motion information are important to model the moving people. Based on this observation, we propose a new kind of features, ...
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