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IEEE/RSJ International Conference on intelligent Robotics and systems

作者： Duo Chen Jun Cheng Dacheng Tao College of Communication Engineering Chongqing University Chongqing 400044 China. He is also with the Shenzhen Key Laboratory of Computer Vision and Pattern Recognition Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences. Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China. He is also with the Chinese University of Hong Kong and Guangdong Provincial Key Laboratory of Robotics and Intelligent System. Center for Quantum Computation and Intelligent System Faculty of Engineering and Information Technology University of Technology Sydney New South Wales 2007 Australia.

ISBN: (数字)9781467317368

ISBN: (纸本)9781467317375

To facilitate human-robot interactions, human gender information is very important. Motivated by the success of manifold learning for visual recognition, we present a novel clustering-based discriminative locality alignment (CDLA) algorithm to discover the low-dimensional intrinsic submanifold from the embedding high-dimensional ambient space for improving the face gender recognition performance. In particular, CDLA exploits the global geometry through k-means clustering, extracts the discriminative information through margin maximization and explores the local geometry through intra cluster sample concentration. These three properties uniquely characterize CDLA for face gender recognition. The experimental results obtained from the FERET data sets suggest the superiority of the proposed method in terms of recognition speed and accuracy by comparing with several representative methods.

关键词： FERET CDLA comparing Recognition (Psychology) Gender Global geometry Compare Face Face

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Spike sorting based on radial basis function network with overlap decomposition

Spike sorting based on radial basis function network with ov...

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作者： Dai, Min Hu, Su-Rui Qi, Jia Tianjin Key Lab of Intelligent Computing and Novel Software Technology School of Computer and Communication Engineering Tianjin University of Technology Tianjin 300191 China Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology Tianjin 300191 China

Spike sorting is the essential step in analyzing recording spike signals for studying information processing mechanisms within the nervous system. Overlapping is one of the most serious problems in the spike sorting for multi-channel recordings. In this paper, a modified radial basis function (RBF) network is proposed to decompose the overlapping signals and separate spikes within the same RBF network. A modified radial basis function based on the Gaussian function is employed in the method to improve the accuracy of overlap decomposition. In addition, the improved constructing algorithm reduces the calculation cost by taking advantage of the symmetry of the RBF network. The performance of the presented method is tested at various signal-to-noise ratio levels based on simulated data coming from the University of Leicester and Wave-clus software. Experiment results show that our method successfully solves the fully overlapping problem and has higher accuracy comparing with the Gaussian function. © 2011 Elsevier Ltd. All rights reserved.

关键词： Radial basis function networks

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A new dynamic method of machine learning from transition examples

Journal of Software

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Journal of Software 2011年第10期6卷 2064-2067页

作者： Zhang, Xiao-Dan Zhang, De-Gan Zhao, De-Xin Kang, Xue-Jing Qiao, Xiao-Dong Institute of Scientific and Technical Information of China Beijing 100038 China Tianjin Key Lab of Intelligent Computing and Novel software Technology Tianjin University of Technology China Key Laboratory of Computer Vision and System Tianjin University of Technology China

It's well known machine learning from examples is an effective method to solve non-linear classification problem. A new dynamic method of machine learning from transition example is given in this paper. This method can improve the traditional method ID3 which learns from static eigenvalues of examples. The limits of the traditional method ID3 lie on no comprehension and no memory, especially, no the varieties and dynamic correlation of eigenvalues. In the new method, it can learn from dynamic eigenvalues, the change of data can be learned because the training data is the initial eigenvalue and the end eigenvalue in the interval. All eigenvalue's varieties and correlation can be understood and remembered in application. By test experiments, the new method can be used as classifier when the multi-parameters are dynamic correlation, and it has special use in the many kinds of information fusion fields. © 2011 ACADEMY PUBLISHER.

关键词： Classification (of information)

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A new algorithm of self-adapting congestion control based on semi-normal distribution

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Advances in information Sciences and Service Sciences 2011年第4期3卷 40-47页

作者： Zhang, De-gan Liu, Zhao-jing Liang, Yan-Pin Tianjin Key Lab of Intelligent Computing and Novel software Technology Tianjin University of Technology China Key Laboratory of Computer Vision and System Tianjin University of Technology Ministry of Education China

The control of network congestion has become a hot spot in the study of Internet of Things transmission service. Considering the complicated and integrated network environment that the Internet of Things to face in the future, the paper comes up with control algorithm of self-adapting congestion based on semi-normal distribution, this algorithm has improved the original packet loss rate function, and conduct corresponding control over network situation categorized according to the length of queue. The result of experiment shows that the algorithm of self-adapting congestion control based on semi-normal distribution is adapt to the complicated changing congestion situation in Internet of Things.

关键词： Normal distribution

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A scalable parallel ray tracing algorithm for satellite imagery

A scalable parallel ray tracing algorithm for satellite imag...

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IEEE International Conference on computer Research and Development

作者： Li, Yu-Gang Zhao, Kun Huang, Yu-Qing Qiu, Zhen-Ge Liu, Zhi-Yong Beijing Lab. of Intelligent Information Technology School of Computer Science BIT Beijing 100081 China Key Laboratory of Computer System and Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing 100081 China Institute of Computing Technology Chinese Academy Sciences Beijing China

ISBN: (纸本)9781612848372

Ray-tracing, can produce high-quality images, however, the use of ray-tracing has been limited due to its high demands on computational power and memory bandwidth, especially in the case of satellite imagery. In this paper, we propose a scalable parallel ray tracing algorithm of satellite imagery on a cluster of multi-core architecture. The algorithm combines demand-driven and data-driven models in order to reduce communication on the cost of maintaining redundant data. In order to make the most of computer's parallelism and increase computational efficiency, it combines two levels of parallelisms, the TLP parallelism brought by the many core architecture and the inter-node parallelism via MPI and OpenMP. Experiment results show that the algorithm is highly scalability. © 2011 IEEE.

关键词： Satellite imagery

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Research on service matching method for LBS

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International Journal of Advancements in Computing Technology 2011年第6期3卷 131-138页

作者： Zhang, De-gan Wang, Dong Liang, Yan-bin Liu, Zhao-jing Tianjin Key Lab of Intelligent Computing and Novel software Technology Tianjin University of Technology China Key Laboratory of Computer Vision and System Tianjin University of Technology Ministry of Education China

With the development of mobile computing, location-based service (LBS) is becoming an important aspect of applied research, the technology of service discovery becomes a core issue. So service matching is the most important in service discovery, also it became hot spot in researching. In the process of providing service to user, not only the quality of service should be improved, but also user's preferences should be considered. The existing mainstream service discovery protocols in the location-oriented service were compared in this paper. Based on analysis and comparison, a new algorithm of service matching is proposed in this paper. It improves the service matching success rate through hierarchical matching and full accounting of the user's preference, and ultimately aim to improve service quality.

关键词： Location based services

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An intelligent load balancing algorithm towards efficient cloud computing

An intelligent load balancing algorithm towards efficient cl...

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2011 AAAI Workshop

作者： Xu, Yang Wu, Lei Guo, Liying Chen, Zheng Yang, Lai Shi, Zhongzhi Agent-based Cooperative System Lab School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu SC 611731 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9781577355243

MapReduce provided a novel computing model for complex job decomposition and sub-tasks management to support cloud computing with large distributed data sets. However, its performance is significantly influenced by the working data distributions over those data sets. In this paper, we put forward a novel model to balance data distribution to improve cloud computing performance in data-intensive applications, such as distributed data mining. By extending the classic MapReduce model with an agent-aid layer and abstracting working load requests for data blocks as tokens, the agents can reason from previously received tokens about where to send other tokens in order to balance the working tasks and improve system performance. Our key contribution lies in building an efficient token routing algorithm in spite of agents' unknowing to the global state of data distribution in cloud. We also built a prototype of our system, and the experimental results show that our approach can significantly improve the efficiency of cloud computing. Copyright © 2011, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： MapReduce

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A Method of Concept Similarity Computation Based on Semantic Distance

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Procedia Engineering 2011年 15卷 3854-3859页

作者： Wenjie Li Qiuxiang Xia Tianjin Key Lab of Intelligent Computing & Novel software Technology Tianjin University of TechnologyTianjin 300384China Key Laboratory of Computer Vision and System (Tianjin University of Technology) Ministry of Education Tianjin 300384China

Calculating the similarity between the concepts is the key in the process of the ontology mapping. Based on the analysis of the traditional method of calculating semantic similarity, a semantic distance-based concept similarity computation method is proposed. In order to keep the effectiveness and comprehensiveness of this method, the main factors which impact the semantic distance are considered fully, the factors of concept semantic contact ratio and depth differences between concepts nodes are also taken into account. By calculating test data, the experiment result shows that the method can calculate concepts similarity effectively.

关键词： ontology semantic distance concept semantic similarity

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A New Service Mining Method Based on Semantic Process

A New Service Mining Method Based on Semantic Process

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Advances in information Technology and Education

作者： Xin-wei Zhai De-gan Zhang Tianjin Key Lab of Intelligent Computing & Novel software Technology Tianjin University of Technology Key Laboratory of Computer Vision and System (Tianjin University of Technology) Ministry of Education

Service mining is the important research field in universal environment. Locating a network service or a device on demand is a challenging task for pervasive computing. We introduce a new approach that explores the use of Semantic Web language in building architecture for service mining in mobile environment in this paper. We propose a Web Ontology Language based ontology for service description, and for supporting logic-based service matchmaking. We introduced a semantic process algorithm according to the ontology. The algorithm takes the semantic meaning of service into account, enable interact between between device and device. It improves the veracity of service process, and paves the way for fuzzy process and service composition.

关键词： Service mining semantic Ontology Web Ontology Language

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A Detection Method for Overlapped Spikes

A Detection Method for Overlapped Spikes

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The 2011 International Conference on Materials Engineering for Advanced Technologies(ICMEAT 2011)

作者： Jia Qi Min Dai Gang Zheng Tong-Tong Liu Tianjin Key Lab of Intelligent Computing & Novel Software Technology Tianjin University of Technology Key Laboratory of Computer Vision and System Ministry of EducationTianjin University of Technology

A new spike detection method is proposed in order to detect the overlapped spikesIn order to avoid missing overlapped spikes, the method adds threshold detection based on window detection methodMoreover, nonlinear energy operator is introduced to make the method strong even under low signal-to-noise ratio situationIn addition, the method solves the repeated detection problem by estimating slopesExperiments show that the method is good for any occasion whatever the low signal-to-noise ratio or baseline wanderEspecially for the overlapped spikes detection, it has much lower false-negative-rate than other traditional detection methods.

关键词： spike sorting overlapped spikes window detection method nonlinear energy operator

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