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Locating unstable periodic orbits: When adaptation integrates into delayed feedback control

Physical Review E 2010年第4期82卷 046214-046214页

作者： Wei Lin Huanfei Ma Jianfeng Feng Guanrong Chen School of Mathematical Sciences Centre for Computational Systems Biology and Shanghai Key Laboratory for Contemporary Applied Mathematics Fudan University Shanghai 200433 China School of Mathematical Sciences Soochow University Suzhou 215006 China Department of Computer Science University of Warwick Coventry CV4 7AL United Kingdom Department of Electronic Engineering City University of Hong Kong Hong Kong China

Finding unstable periodic orbits (UPOs) is always a challenging demand in biophysics and computational biology, which needs efficient algorithms. To meet this need, an approach to locating unstable periodic orbits in chaotic dynamical system is presented. The uniqueness of the approach lies in the introduction of adaptive rules for both feedback gain and time delay in the system without requiring any information of the targeted UPO periods a priori. This approach is theoretically validated under some mild conditions and successfully tested with some practical strategies in several typical chaotic systems with or without significant time delays.

关键词： Time delay

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Emotion classification based on gamma-band EEG

Emotion classification based on gamma-band EEG

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31st Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Engineering the Future of Biomedicine, EMBC 2009

作者： Li, Mu Lu, Bao-Liang Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200240 China MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong University Shanghai 200240 China

ISBN: (纸本)9781424432967

In this paper, we use EEG signals to classify two emotions-happiness and sadness. These emotions are evoked by showing subjects pictures of smile and cry facial expressions. We propose a frequency band searching method to choose an optimal band into which the recorded EEG signal is filtered. We use common spatial patterns (CSP) and linear-SVM to classify these two emotions. To investigate the time resolution of classification, we explore two kinds of trials with lengths of 3s and 1s. Classification accuracies of 93:5% ± 6:7% and 93:0%±6:2% are achieved on 10 subjects for 3s-trials and 1s-trials, respectively. Our experimental results indicate that the gamma band (roughly 30-100 Hz) is suitable for EEG-based emotion classification. ©2009 IEEE.

关键词： Signal processing

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Directly identify unexpected instances in the test set by entropy maximization

Directly identify unexpected instances in the test set by en...

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Joint International Conference on Advances in Data and Web Management, APWeb/WAIM 2009

作者： Sha, Chaofeng Xu, Zhen Wang, Xiaoling Zhou, Aoying Department of Computer Science and Engineering Fudan University Shanghai 200433 China Shanghai Key Laboratory of Trustworthy Computing Institute of Massive Computing East China Normal University Shanghai 200062 China

ISBN: (纸本)9783642006715

In real applications, a few unexpected examples unavoidably exist in the process of classification, not belonging to any known class. How to classify these unexpected ones is attracting more and more attention. However, traditional classification techniques can't classify correctly unexpected instances, because the trained classifier has no knowledge about these. In this paper, we propose a novel entropy-based method to the problem. Finally, the experiments show that the proposed method outperforms previous work in the literature. © Springer-Verlag Berlin Heidelberg 2009.

关键词： Entropy

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Approximation strategy based on data merging for static data management in networks

Approximation strategy based on data merging for static data...

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NCM 2009 - 5th International Joint Conference on Int. Conf. on Networked computing, Int. Conf. on Advanced Information Management and Service, and Int. Conf. on Digital Content, Multimedia Technology and its Applications

作者： DongMei, Xing Hong, Zhu Shanghai Key Laboratory of Intelligence Information Process School of Computer Science and Technology Fudan University Shanghai 200433 China Department of Mathematics NanChang University China Shanghai Key Laboratory of Trustworthy Computing East China Normal University China

ISBN: (纸本)9780769537696

we studied static data management problem based on data merging in general networks with object to minimize the total costs. By using greedy and LP-dual method, an initial placement is acquired. Given network G=(V, E) and data set X, we can achieve a constant ratio approximation algorithm. The key of our method is to construct some clusters based on hierarchical structure for requests. In order to get the initial placement, we preciously discuss an approximation strategy for a variance of facility location with service installation cost. © 2009 IEEE.

关键词： Information management

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An efficient gene selection algorithm based on tolerance rough set theory 1

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12th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular computing, RSFDGrC 2009

作者： Jiao, Na Miao, Duoqian Department of Computer Science and Technology Tongji University Shanghai 201804 China Key Laboratory of Embedded System and Service Computing Ministry of Education of China Tongji University Shanghai 201804 China

ISBN: (数字)9783642106460

ISBN: (纸本)3642106455

Gene selection, a key procedure of the discriminant analysis of microarray data, is to select the most informative genes from the whole gene set. Rough set theory is a mathematical tool for further reducing redundancy. One limitation of rough set theory is the lack of effective methods for processing real-valued data. However, most of gene expression data sets are continuous. Discretization methods can result in information loss. This paper investigates an approach combining feature ranking together with feature selection based on tolerance rough set theory. Compared with gene selection algorithm based on rough set theory, the proposed method is more effective for selecting high discriminative genes in cancer classification task. © 2009 Springer-Verlag Berlin Heidelberg.

关键词： Rough set theory

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Abstraction Strategy of Software Knowledge Reuse for Adaptable Knowledge and Information systems

Abstraction Strategy of Software Knowledge Reuse for Adaptab...

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International Conference on Information and Multimedia Technology (ICIMT)

作者： Yinglin Wang Department of Computer Science and Engineering MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Shanghai Jiaotong University Shanghai China

Nowadays enterprise information and knowledge systems provide technical platforms for the integration and collaboration of business processes among multi-organizations of enterprises. However, software systems supporting enterprise business processes are hard to be adapted and deployed to satisfy the ever-changing requirements of enterprises. In this paper we put forward an adaptable enterprise information system framework in which we use four levels of abstractions. At the meta-meta model level, the ontology schema is used which provides the specification language for other more specific levels. At the meta-model level, the extended OSM model is used, and the generic elements obtained from analyzing the commonality of requirements are included. At the model level, the commonalities of sub-domains, such as the patterns of tasks in a specific domain are analyzed and generalized for future reuse. The intermediate specifications of the business processes and work flows are used in this level. At the application level, specific elements and requirements of the applications will be added and customized via the tools developed at the abstracted levels. A case study of knowledge management system based on this four level abstraction is discussed.

关键词： Information systems Knowledge management Management information systems Ontologies Enterprise resource planning ISO standards Online Communities/Technical Collaboration Information management Multimedia systems computer science

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Emotion classification based on gamma-band EEG

Emotion classification based on gamma-band EEG

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Mu Li Bao-Liang Lu Department of Computer Science and Engineering MOE-Microsoft Key Laboratory of Intelligent Computing and Intelligent Systems Shanghai JiaoTong University Shanghai China

In this paper, we use EEG signals to classify two emotions-happiness and sadness. These emotions are evoked by showing subjects pictures of smile and cry facial expressions. We propose a frequency band searching method to choose an optimal band into which the recorded EEG signal is filtered. We use common spatial patterns (CSP) and linear-SVM to classify these two emotions. To investigate the time resolution of classification, we explore two kinds of trials with lengths of 3s and 1s. Classification accuracies of 93.5% plusmn 6.7% and 93.0%plusmn6.2% are achieved on 10 subjects for 3s-trials and 1s-trials, respectively. Our experimental results indicate that the gamma band (roughly 30-100 Hz) is suitable for EEG-based emotion classification.

关键词： Electroencephalography Frequency Neuroscience Psychology Humans computer displays Emotion recognition USA Councils Spatial resolution Signal resolution

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Interval set cluster analysis: A re-formulation 1

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12th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular computing, RSFDGrC 2009

作者： Yao, Yiyu Lingras, Pawan Wang, Ruizhi Miao, Duoqian Department of Computer Science University of Regina Regina SK S4S 0A2 Canada Department of Mathematics and Computing Science Saint Mary's University Halifax NS B3H 3C3 Canada Dept. of Comp. Science and Technology Key Laboratory of Embedded System and Service Computing Tongji University Shanghai 201804 China

ISBN: (数字)9783642106460

ISBN: (纸本)3642106455

A new clustering strategy is proposed based on interval sets, which is an alternative formulation different from the ones used in the existing studies. Instead of using a single set as the representation of a cluster, each cluster is represented by an interval set that is defined by a pair of sets called the lower and upper bounds. Elements in the lower bound are typical elements of the cluster and elements between the upper and lower bounds are fringe elements of the cluster. A cluster is therefore more realistically characterized by a set of core elements and a set of boundary elements. Two types of interval set clusterings are proposed, one is non-overlapping lower bound interval set clustering and the other is overlapping lower bound interval set clusterings, corresponding to the standard partition based and covering based clusterings. © 2009 Springer-Verlag Berlin Heidelberg.

关键词： Cluster analysis

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Improved Extremal Optimization for Constrained Pairwise Testing

Improved Extremal Optimization for Constrained Pairwise Test...

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International Conference on Research Challenges in computer science (ICRCCS)

作者： Jianjun Yuan Changjun Jiang Zuowen Jiang Department of Computer Science and Technology The Key Laboratory of Embedded System and Service Computing Ministry of Education of China University of Tongji Shanghai China

Pairwise testing, which requires that every combination of valid values of each pair of system factors be covered by at lease one test case, plays an important role in software testing since many faults are caused by unexpected 2-way interactions among system factors. In real systems, constraints usually exist between values, which means that some values cannot coexist in a valid test. Although meta-heuristic strategies like simulated annealing can generally discover smaller pairwise test suite in the presence of constraints, they may cost more time to perform search, compared with greedy algorithms. We propose a new method, improved extremal optimization, for constructing constrained pairwise test suites. Experimental results show that improved extremal optimization gives similar size of resulting pairwise test suite and yields a 13% reduction in solution time over simulated annealing.

关键词： Constraint optimization Software testing System testing Simulated annealing Costs Greedy algorithms computer science Educational technology Laboratories Embedded system

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Multicast Throughput of Hybrid Wireless Networks Under Gaussian Channel Model

Multicast Throughput of Hybrid Wireless Networks Under Gauss...

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IEEE International Conference on Distributed computing systems

作者： Cheng Wang Shaojie Tang Xiang-Yang Li Changjun Jiang Yunhao Liu Department of Computer Science and Technology Tongji University Shanghai China Department of Computer Science Illinois Institute of Technology Chicago IL 60616 Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai China Department of Computer Science and Engineering Hong Kong University of Science and Technology

ISBN: (纸本)9781424444816

We study the multicast capacity for hybrid wireless networks consisting of ordinary wireless nodes and base stations under Gaussian Channel model, which generalizes both the unicast capacity and broadcast capacity for hybrid wireless networks. We simply consider the hybrid extended network, where the ordinary wireless nodes are placed in the square region A(n) with side-length n~(1/2) according to a Poisson point process with unit intensity. In addition, m additional base stations (BSs) serving as the relay gateway are placed regularly in the region A(n) and they are connected by a high-bandwidth wired network. Three broad categories of multicast strategies are proposed in this paper. According to the different scenarios in terms of m, n and n_d, we select the optimal scheme from the three categories of strategies, and derive the achievable multicast throughput based on the optimal decision.

关键词： Wireless networks Multicast Gaussian channels point operation BASE STATION HYBRID Hybrid electric vehicles Throughput

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