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Analytical optimization for collaborative double threshold energy detection in cognitive radio network

Journal of information and Computational Science 2012年第13期9卷 3875-3882页

作者： Zhu, Jun Bai, Yun Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei 230039 China School of Electronic Information Engineering Anhui University Hefei 230601 China

The conventional 'OR' fusion rule is frequently applied in two pre-determined limits energy detection networks but its overall performance of the false alarm and miss detection probability is generally. The new method to optimize the total error probability in three combination schemes is proposed and the presented approach focuses on combining the k-out-of-N decision fusion with data fusion. General expressions for these probabilities are derived and an analytical solution for the optimal value of k is found minimizing the overall error probability. It provides performance analysis and comparison due to the different parameters such as SNR, the threshold coefficient, for the Additive White Gaussian Noise (AWGN) channel. Numerical experiment results show there are superior performances of above fusion strategies as opposed to traditional hard rule, by selecting the right system parameters. 1548-7741/Copyright © 2012 Binary information Press.

关键词： Data fusion

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${\rm S}^{3}{\rm MKL}$: Scalable Semi-Supervised Multiple Kernel Learning for Real-World Image Applications

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IEEE Transactions on Multimedia 2012年第4期14卷 1259-1274页

作者： Shuhui Wang Qingming Huang Shuqiang Jiang Qi Tian Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China Department of Computer Science University of Texas-San Antonio San Antonio TX USA

We study the visual learning models that could work efficiently with little ground-truth annotation and a mass of noisy unlabeled data for large scale Web image applications, following the subroutine of semi-supervised learning (SSL) that has been deeply investigated in various visual classification tasks. However, most previous SSL approaches are not able to incorporate multiple descriptions for enhancing the model capacity. Furthermore, sample selection on unlabeled data was not advocated in previous studies, which may lead to unpredictable risk brought by real-world noisy data corpse. We propose a learning strategy for solving these two problems. As a core contribution, we propose a scalable semi-supervised multiple kernel learning method (S 3 MKL) to deal with the first problem. The aim is to minimize an overall objective function composed of log-likelihood empirical loss, conditional expectation consensus (CEC) on the unlabeled data and group LASSO regularization on model coefficients. We further adapt CEC into a group-wise formulation so as to better deal with the intrinsic visual property of real-world images. We propose a fast block coordinate gradient descent method with several acceleration techniques for model solution. Compared with previous approaches, our model better makes use of large scale unlabeled images with multiple feature representation with lower time complexity. Moreover, to address the issue of reducing the risk of using unlabeled data, we design a multiple kernel hashing scheme to identify the “informative” and “compact” unlabeled training data subset. Comprehensive experiments are conducted and the results show that the proposed learning framework provides promising power for real-world image applications, such as image categorization and personalized Web image re-ranking with very little user interaction.

关键词： Kernel Visualization Training Data models Noise measurement Training data Learning systems

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Web Question Answering based on CCG parsing and DL ontology

Web Question Answering based on CCG parsing and DL ontology

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International Conference on information Science and Digital Content Technology

作者： Peng Li Lejian Liao Beijing Engineering Research Centre of High Volume Language Information Processing & Cloud Computing Applications Multi-living-agent Information System Key Laboratory and Beijing Laboratory of Intelligent Information Technology School of Computer Scienc

ISBN: (纸本)9781467312882

This paper presents a novel WQA (Web Question Answering) approach based on the combination CCG (Combinatory Categorial Grammar) and DL (Description Logic) ontology, in order to promote semantic-level accuracy through deep text understanding capabilities. We propose to take DL based semantic modeling, i.e., translating lambda-expression encoding of question meaning into DL based semantic representations. The advantage of such approach is a seamless exploitation of existing semantic resource coded as DL ontology, which is widespread in such area as the Semantic Web and conceptual modeling. The experiments are conducted with a repository of complex Chinese questions which involves the satisfaction of some object property restrictions. The experimental results show that producing the semantic representations with the combination of CCG parsing and DL reasoning is an effective approach for question understanding at semantic level, in terms of both understanding accuracy promotion and semantic resource exploitation.

关键词： Semantics Ontologies Syntactics Grammar Cognition Accuracy Semantic Web

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Sliding mode and LMI based control for fractional order unified chaotic systems

Sliding mode and LMI based control for fractional order unif...

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Chinese Control Conference (CCC)

作者： Yong-Hong Lan Lv-Jun He School of Information Engineering Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan Hunan China School of Information Engineering Xiangtan University Xiangtan Hunan China

ISBN: (纸本)9781467325813

This paper investigates the chaos control problem for a class of fractional order unified chaotic systems. By introducing the sliding mode control method, a feedback controller is established to guarantee the asymptotical stability, and its parameter is obtained in terms of LMI, which can be easily obtained by Matlab's LMI Toolbox. A dynamic compensator is designed to overcome the difficulty of dealing with the nonlinear items in the chaotic system. To reduce the chattering phenomenon, a power reaching law is adopted. The validity of the methods is verified by a numerical example.

关键词： Chaos Sliding mode control Time factors MATLAB Synchronization Adaptive control

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Towards collecting commonsense knowledge with hint questions

Towards collecting commonsense knowledge with hint questions

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2012 8th International Conference on Semantics, Knowledge and Grids, SKG 2012

作者： Zang, Liangjun Cao, Cong Cao, Cungen Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences No.6 Kexueyuan South Road Hai Dian Distinct Beijing 100190 China Graduate University Chinese Academy of Sciences No.19 Yu Quan Road Shi Jing Shan Distinct Beijing 100049 China

ISBN: (纸本)9780769547947

Accumulating commonsense knowledge (CK) has proven very useful for many natural language processing tasks. So far the most reliable way of acquisition is still relying on knowledge contributors to offer CK. Unfortunately, knowledge contributors often fail to think of much CK because this knowledge is usually taken for granted by people. In this paper, we explore the issue of reminding knowledge contributors by means of hint questions. Specifically, we investigate what kinds of CK are easily ignored, analyze its reason and suggest possible solution. We hope to sketch sources of the research problem and suggest possible ways forward. © 2012 IEEE.

关键词： Natural language processing systems

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Parallel implementation of apriori algorithm based on MapReduce

Parallel implementation of apriori algorithm based on MapRed...

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13th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed computing, SNPD 2012

作者： Li, Ning Zeng, Li He, Qing Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Graduate University Chinese Academy of Sciences Beijing 100139 China Key Lab. of Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University Baoding 071002 Hebei China

ISBN: (纸本)9780769547619

Searching frequent patterns in transactional databases is considered as one of the most important data mining problems and Apriori is one of the typical algorithms for this task. Developing fast and efficient algorithms that can handle large volumes of data becomes a challenging task due to the large databases. In this paper, we implement a parallel Apriori algorithm based on MapReduce, which is a framework for processing huge datasets on certain kinds of distributable problems using a large number of computers (nodes). The experimental results demonstrate that the proposed algorithm can scale well and efficiently process large datasets on commodity hardware. © 2012 IEEE.

关键词： MapReduce

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Challenges and Opportunities for Trust Management in Crowdsourcing

Challenges and Opportunities for Trust Management in Crowdso...

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IEEE WIC ACM International Conference on Web Intelligence (WI)

作者： Han Yu Zhiqi Shen Chunyan Miao Bo An School of Computer Engineering Nanyang Technological University Singapore The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

Crowd sourcing (CS) systems offer a new way for businesses and individuals to leverage on the power of mass collaboration to accomplish complex tasks in a divide-and-conquer manner. In existing CS systems, no facility has been provided for analyzing the trustworthiness of workers and providing decision support for allocating tasks to workers, which leads to high dependency of the quality of work on the behavior of workers in CS systems as shown in this paper. To address this problem, trust management mechanisms are urgently needed. Traditional trust management techniques are focused on identifying the most trustworthy service providers (SPs) as accurately as possible. Little thoughts were given to the question of how to utilize these SPs due to two common assumptions: 1) an SP can serve an unlimited number of requests in one time unit, and 2) a service consumer (SC) only needs to select one SP for interaction to complete a task. However, in CS systems, these two assumptions are no longer valid. Thus, existing models cannot be directly used for trust management in CS systems. This paper takes the first step towards a systematic investigation of trust management in CS systems by extending existing trust management models for CS trust management and conducting extensive experiments to study and analyze the performance of various trust management models in crowd sourcing. In this paper, the following key contributions are made. We 1) propose extensions to existing trust management approaches to enable them to operate in CS systems, 2) design a simulation test-bed based on the system characteristics of Amazon's Mechanical Turk (AMT) to make evaluation close to practical CS systems, 3) discuss the effect of incorporating trust management into CS system on the overall social welfare, and 4) identify the challenges and opportunities for future trust management research in CS systems.

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Properties and axiomatization of fuzzy rough sets based on fuzzy covering

Properties and axiomatization of fuzzy rough sets based on f...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Ming-Fen Wu Hao-Han Han Yan-Fei Si School of Computer Science Wuyi University Guangdong China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

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 models in fuzzy environment, and we generalize rough fuzzy sets model based on a covering to fuzzy rough sets model based on a fuzzy covering. The lower and upper approximations of fuzzy subsets are defined based on a fuzzy covering, and basic properties are investigated. Then, the axiom definition of the lower approximation operator is given. It is shown that the rough fuzzy sets model based on a covering is a special instance of the fuzzy rough sets model based on a fuzzy covering.

关键词： Abstracts

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Formal concept analysis in hybrid relational databases

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International Review on Computers and Software 2012年第6期7卷 2904-2910页

作者： Lei, Yuxia Sui, Yuefei Cao, Baoxiang School of Computer Science Qufu Normal University Rizhao 276826 Shandong China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China

Relational Database Model (RDM) has been proven to be a very useful data-storage technique. As information is stored as data in relational databases, the induction of concepts from data is a pivotal topic in the data mining field. Formal Concept Analysis (FCA) turns out to be a perfect instrument for a meaningful and conceptual exploration of the stored data. However, many databases in practice are often hybrid ones. This paper proposes an approach towards extracting concepts from hybrid relations, which preserve the RDM and allow complex values such as relations in columns for relations. The method can be described as follows: the sub-tuples/subattributes pairs are regard as new attributes and inserted into a main relation, and we further obtain a new complex relation called a target relation from which concepts can be extracted. The insertion operation is semantics-preserving and extent-preserving. In addition, this paper analyzed the structural connections among concept lattices in detail, which can be used to construct a complex concept lattice from simple ones. The method may reduce time complexity of constructing the concept lattice of a complex relation. © 2012 Praise Worthy Prize S.r.l. - All rights reserved.

关键词： Formal concept analysis

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Asymmetric quantum codes derived from linear over finite rings

International Journal of Digital Content Technology and its ...

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International Journal of Digital Content Technology and its Applications 2012年第20期6卷 89-96页

作者： Qian, Jianfa Wang, Zhen College of Science Anhui University of Science and Technology Huainan 232007 China Science Computing and Intelligent Information Processing of GuangXi Higher Education Key Laboratory Guangxi Teachers Education University Nanning 530023 China

The motivation for this work was that little is known about the construction of asymmetric quantum error-correcting codes from linear codes over finite rings. In this work, attempts are made to construct asymmetric quantum error-correcting codes from linear codes over finite rings Zp2, where p is any prime. Furthermore, we present explicit parameters for infinite families of asymmetric quantum error correcting codes which derived from linear over finite rings.

关键词： Codes (symbols)

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