A sequent is a pair(Г,△),which is true under an as-signment if either some formula inГis false,or some formula in △ is *** L3-valued propositional logic,a mulisequent is a triple △|Θ|Г,which is true under an as...
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A sequent is a pair(Г,△),which is true under an as-signment if either some formula inГis false,or some formula in △ is *** L3-valued propositional logic,a mulisequent is a triple △|Θ|Г,which is true under an assignment if either some formula in △ has truth-value t,or some formula in Θ has truth-value m,or some formula in Г has truth-value￡.Corre-spondingly there is a sound and complete Gentzen deduction system G for multisequents which is ***,a CO-multisequent is a triple △:Θ:Г,which is valid if there is an assignment v in which each formula in△has truth-value≠t,each formula in Θ has truth-value≠m,and each formula in Г has truth-value≠￡.Correspondingly there is a sound and com-plete Gentzen deduction system G-for co-multisequents which is nonmonotonic.
In unmanned aerial systems, especially in complex environments, accurately detecting tiny objects is crucial. Resizing images is a common strategy to improve detection accuracy, particularly for small objects. However...
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Dear editor,Self-adaptation is a promising approach to allocate resources for cloud-based software services [1, 2].Traditional self-adaptive resource-allocation methods are rule-driven, which leads to high administrat...
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Dear editor,Self-adaptation is a promising approach to allocate resources for cloud-based software services [1, 2].Traditional self-adaptive resource-allocation methods are rule-driven, which leads to high administrative cost and implementation complexity. Machine learning techniques and control theory are
NKI contains a multi-domain oriented and large scale knowledge base. Text corpus is an important knowledge source of it. This paper presents an ontology-driven and integrated multi-agent architecture (MAKAT) for achie...
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Analytical study of large-scale nonlinear neural circuits is a difficult task. Here we analyze the function of neural systems by probing the fuzzy logical framework of the neural cells' dynamical equations. Al- th...
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Analytical study of large-scale nonlinear neural circuits is a difficult task. Here we analyze the function of neural systems by probing the fuzzy logical framework of the neural cells' dynamical equations. Al- though there is a close relation between the theories of fuzzy logical systems and neural systems and many papers investigate this subject, most investigations focus on finding new functions of neural systems by hybridizing fuzzy logical and neural system. In this paper, the fuzzy logical framework of neural cells is used to understand the nonlinear dynamic attributes of a common neural system by abstracting the fuzzy logical framework of a neural cell. Our analysis enables the educated design of network models for classes of computation. As an example, a recurrent network model of the primary visual cortex has been built and tested using this approach.
In this paper, we propose a novel dependency-based bracketing transduction grammar for statistical machine translation, which converts a source sentence into a target dependency tree. Different from conventional brack...
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In this paper, we propose a novel dependency-based bracketing transduction grammar for statistical machine translation, which converts a source sentence into a target dependency tree. Different from conventional bracketing transduction grammar models, we encode target dependency information into our lexical rules directly, and then we employ two different maximum entropy models to determine the reordering and combination of partial dependency structures, when we merge two neighboring blocks. By incorporating dependency language model further, large-scale experiments on Chinese-English task show that our system achieves significant improvements over the baseline system on various test sets even with fewer phrases.
We propose a relaxed correspondence assumption for cross-lingual projection of constituent syntax, which allows a supposed constituent of the target sentence to correspond to an unrestricted treelet in the source pars...
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Tree-based translation models, which exploit the linguistic syntax of source language, usually separate decoding into two steps: parsing and translation. Although this separation makes tree-based decoding simple and e...
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Tree-based translation models, which exploit the linguistic syntax of source language, usually separate decoding into two steps: parsing and translation. Although this separation makes tree-based decoding simple and efficient, its translation performance is usually limited by the number of parse trees offered by parser. Alternatively, we propose to parse and translate jointly by casting tree-based translation as parsing. Given a source-language sentence, our joint decoder produces a parse tree on the source side and a translation on the target side simultaneously. By combining translation and parsing models in a discriminative framework, our approach significantly outperforms a forest based tree-to-string system by 1.1 absolute BLEU points on the NIST 2005 Chinese-English test set. As a parser, our joint decoder achieves an F1 score of 80.6% on the Penn Chinese Treebank.
Chiaroscuro in art is characterized by strong contrasts between light and dark. An object in a certain light condition has a certain chiaroscuro pattern in appearance;and this pattern is invariant to the changes of il...
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Although discriminative training guarantees to improve statistical machine translation by incorporating a large amount of overlapping features, it is hard to scale up to large data due to decoding complexity. We propo...
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