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IEEE International Conference on Granular Computing (GRC)

作者： Zhongzhi Shi Zuqiang Meng Yuan Lu The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China College of Computer Electronics and Information Guangxi University Nanning 530004 China College of Computer Guangxi University Nanning China

At present GrC mainly is divided into three categories: computing with words (CW), rough set (RS) and quotient space (QS). From the perspective of essential characteristic of GrC, this demarcation is not comprehensive and accurate. In fact, CW is based on fuzzy granules (fuzzy subset) and both RS and QS are based on disjoint granules, which essentially are equivalence classes, either equal to each other or with empty overlap. In practical application, intersecting granules however need to be handled. Therefore there is another kind of GrC which is based on intersecting granules. This kind of GrC is referred to as tolerance GrC (TGrC) in our work. By constructing a Boolean algebra on super-granular space and a decision algebraic system, this paper will present an incomplete information system-based TGrC. With the TGrC, an example about extracting rules incomplete information is given, so as to show its basic principle.

关键词： information systems information processing Data mining Artificial intelligence Humans Problem-solving Arithmetic Laboratories computers Educational institutions

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Achieving Close-Capacity Performance with Simple Concatenation Scheme on Multiple-Antenna Channels

Achieving Close-Capacity Performance with Simple Concatenati...

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GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference

作者： Nghi H. Tran Tho Le-Ngoc Tad Matsumoto Ha H. Nguyen Department of Electrical & Computer Engineering McGill University Montreal QUE Canada Information Theory and Signal Processing Laboratory School of Information Science Japan Advanced Institute of Science and Technology Japan Department of Electrical & Computer Engineering University of Saskatchewan Saskatoon SAS Canada

This paper proposes a simple yet capacity-approaching concatenation of a mixture of short memory length convolutional codes and simple rate-1 block code followed by either complex 1-dimensional (1-D) anti-Gray or Gray mapping over multiple antenna channels with quadrature phase-shift keying (QPSK). By interpreting rate-1 code together with 1-D mapping as a multi-D mapping employed over multiple transmit antennas, the error performance is analyzed in two regions, the error-floor and turbo pinch-off regions. In the former one, a tight union bound and design criterion on the asymptotic performance are first derived, which provide an useful tool to predict the error performance. Based on the design criterion, an optimal rate-1 code for each 1-D mapping is then constructed to achieve the best asymptotic performance. In the turbo pinch-off area, by using extrinsic information transfer (EXIT) chart, the most suitable mixed codes are selected for both symmetric and asymmetric antenna setups. It is demonstrated that the simple concatenation scheme can achieve near-capacity. Furthermore, its error performance is comparable to that obtained by using well-designed irregular low-density parity-check (LDPC) and repeat accumulate (RA) codes, and thereby, outperforms a scheme employing a parallel concatenated turbo code.

关键词： Parity check codes Convolutional codes Block codes Phase shift keying Quadrature phase shift keying Transmitting antennas Error analysis Performance analysis Concatenated codes Turbo codes

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Granularity-tunable gradients partition (GGP) descriptors for human detection

Granularity-tunable gradients partition (GGP) descriptors fo...

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Conference on computer Vision and Pattern Recognition (CVPR)

作者： Yazhou Liu Shiguang Shan Wenchao Zhang Xilin Chen Wen Gao School of Computer Science and Technology Harbin Institute of Technology Harbin China Key Laboratory of Intelligent Information Processing Chinese Academy and Sciences Beijing China Institute of Digital Media Peking University Beijing China

This paper proposes a novel descriptor, granularity-tunable gradients partition (GGP), for human detection. The concept granularity is used to define the spatial and angular uncertainty of the line segments in the Hough space. Then this uncertainty is backprojected into the image space by orientation-space partitioning to achieve efficient implementation. By changing the granularity parameter, the level of uncertainty can be controlled quantitatively. Therefore a family of descriptors with versatile representation property can be generated. Specifically, the finely granular GGP descriptors can represent the specific geometry information of the object (the same as Edgelet); while the coarsely granular GGP descriptors can provide the statistical representation of the object (the same as histograms of oriented gradients, HOG). Moreover, the position, orientation, strength and distribution of the gradients are embedded into a unified descriptor to further improve the GGP's representation power. A cascade structured classifier is built by boosting the linear regression functions. Experimental results on INRIA dataset show that the proposed method achieves comparable results to those of the state-of-the-art methods.

关键词： Humans Shape Uncertainty Histograms Support vector machines Support vector machine classification Boosting Detectors Covariance matrix Noise robustness

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Learning long term face aging patterns from partially dense aging databases

Learning long term face aging patterns from partially dense ...

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International Conference on computer Vision (ICCV)

作者： Jinli Suo Xilin Chen Shiguang Shan Wen Gao Key Laboratory of Intelligent Information Processing of CAS Institute for Computing Technology Beijing China Chinese Academy and Sciences China School of Electronic Engineering and Computer Science Peking University China

Studies on face aging are handicapped by lack of long term dense aging sequences for model training. To handle this problem, we propose a new face aging model, which learns long term face aging patterns from partially dense aging databases. The learning strategy is based on two assumptions: (i) short term face aging pattern is relatively simple and is possible to be learned from currently available databases; (ii) long term face aging is a continuous and smooth Markov process. Adopting a compositional face representation, our aging algorithm learns a function-based short term aging model from real aging sequences to infer facial parameters within a short age span. Based on the predefined smoothness criteria between two overlapping short term aging patterns, we concatenate these learned short term aging patterns to build the long term aging patterns. Both the subjective assessment and objective evaluations of synthetic aging sequences validate the effectiveness of the proposed model.

关键词： Aging Databases Biological system modeling Prototypes Face detection Skin Content addressable storage computer vision Muscles Deformable models

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Empirical Probability Functions Derived from Dihedral Angles for Protein Structure Prediction

Empirical Probability Functions Derived from Dihedral Angles...

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IEEE Symposium on Bioinformatics and Bioengineering (BIBE)

作者： Qiwen Dong Xin Geng Shuigeng Zhou Jihong Guan Shanghai Key Laboratory of Intelligent Information Processing Fudan University Shanghai China Department of Computer Science and Technology University of Tongji Shanghai China Fudan University Shanghai Shanghai CN

The development and evaluation of functions for protein energetics is an important part of current research aiming at understanding protein structures and functions. Knowledgebase mean force potentials are derived from statistical analysis of interacting groups in experimentally determined protein structures. Current knowledge-based mean force potentials are based on the inverse Boltzmannpsilas law, which calculate the ratio of the observed probability with respect to the probability of the reference state. In this study, a general probability framework is presented with the aim to develop novel energy scores. A class of empirical probability functions is derived by decomposing the joint probability of backbone dihedral angles and amino acid sequences. The neighboring interactions are modeled by conditional probabilities. Such probability functions are based on the strict probability theory and some suitable suppositions for convenience of computation. Experiments are performed on several well-constructed decoy sets and the results show that the empirical probability functions presented here outperform previous statistical potentials based on dihedral angles. Such probability functions will be helpful for protein structure prediction,model quality evaluation, transcription factors identification and other challenging problems in computational biology.

关键词： Probability Amino acids Protein engineering Spine Sequences Bioinformatics computer science Biological system modeling Computational biology Bonding

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Single vs. population cell coding: Gaze movement control in target search

Single vs. population cell coding: Gaze movement control in ...

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International Joint Conference on Neural Networks (IJCNN)

作者： Jun Miao Laiyun Qing Lijuan Duan Baixian Zou Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China School of Information Science and Engineering Chinese Academy of Sciences Beijing China College of Computer Science and Technology University of Technology Beijing China Department of Information Science and Technology College of Art and Science Beijing Union Technology Beijing China

Gaze movement plays an important role in human visual search system. In literature, the winner-take-all method is wildly used to simulate the controlling of the gaze movement. The winner-take-all is a type of single-cell coding method, which uses one cell (grandmother cell) or one response to represent an object. However, eye movement is affected by the visual context which includes more than one object in images, especially in target search. Therefore, we propose to use the population coding with more than one response rather than the single-cell coding on gaze movement control. The proposed method is supported by the theoretical analysis and experiments on a real image database which show the population-cell-coding improves the target locating accuracy by 44.4% only at the cost of coding 22.4% more information than that of single-cell-coding.

关键词： Humans Image coding Image databases Costs information science Educational institutions Biological neural networks Control systems Image analysis information analysis

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Trapping in scale-free networks with hierarchical organization of modularity

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Physical Review E 2009年第5期80卷 051120-051120页

作者： Zhongzhi Zhang Yuan Lin Shuyang Gao Shuigeng Zhou Jihong Guan Mo Li School of Computer Science Fudan University Shanghai 200433 China Shanghai Key Laboratory of Intelligent Information Processing Fudan University Shanghai 200433 China Department of Computer Science and Technology Tongji University 4800 Cao’an Road Shanghai 201804 China Software School Fudan University Shanghai 200433 China

A wide variety of real-life networks share two remarkable generic topological properties: scale-free behavior and modular organization, and it is natural and important to study how these two features affect the dynamical processes taking place on such networks. In this paper, we investigate a simple stochastic process—trapping problem, a random walk with a perfect trap fixed at a given location, performed on a family of hierarchical networks that exhibit simultaneously striking scale-free and modular structure. We focus on a particular case with the immobile trap positioned at the hub node having the largest degree. Using a method based on generating functions, we determine explicitly the mean first-passage time (MFPT) for the trapping problem, which is the mean of the node-to-trap first-passage time over the entire network. The exact expression for the MFPT is calculated through the recurrence relations derived from the special construction of the hierarchical networks. The obtained rigorous formula corroborated by extensive direct numerical calculations exhibits that the MFPT grows algebraically with the network order. Concretely, the MFPT increases as a power-law function of the number of nodes with the exponent much less than 1. We demonstrate that the hierarchical networks under consideration have more efficient structure for transport by diffusion in contrast with other analytically soluble media including some previously studied scale-free networks. We argue that the scale-free and modular topologies are responsible for the high efficiency of the trapping process on the hierarchical networks.

关键词： Random processes

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Comparative evaluation of spatial context techniques for semantic image analysis

Comparative evaluation of spatial context techniques for sem...

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International Workshop on Image Analysis for Multimedia Interactive Services, WIAMIS

作者： G. Th. Papadopoulos C. Saathoff M. Grzegorzek V. Mezaris I. Kompatsiaris S. Staab M. G. Strintzis Centre of Research & Technology Hellas Informatics and Telematics Institute Thessaloniki Greece Information Processing Laboratory Electrical & Computer Engineering Department Aristotle University of Thessaloniki Thessaloniki Greece Information Systems & Semantic Web Research Group Institute of Computer Science University of Koblenz Koblenz Germany

In this paper, two approaches to utilizing contextual information in semantic image analysis are presented and comparatively evaluated. Both approaches make use of spatial context in the form of fuzzy directional relations. The first one is based on a Genetic Algorithm (GA), which is employed in order to decide upon the optimal semantic image interpretation by treating semantic image analysis as a global optimization problem. On the other hand, the second method follows a Binary Integer Programming (BIP) technique for estimating the optimal solution. Both spatial context techniques are evaluated with several different combinations of classifiers and low-level features, in order to demonstrate the improvements attained using spatial context in a number of different image analysis schemes.

关键词： Image analysis Image segmentation Classification algorithms information processing Image generation Image retrieval Informatics Telematics information systems Semantic Web

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A Parallel Artificial Immune Model for Optimization

A Parallel Artificial Immune Model for Optimization

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International Conference on Computational Intelligence and Security

作者： Yutao Qi Fang Liu Licheng Jiao School of Computer Science And Technology Key Laboratory of Intelligent Perception and Imagee Understanding of Ministry of Education Xidian University Xi'an China Institute of Intelligent Information Processing and Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education Xidian University Xi'an China

This paper presents a parallel artificial immune model termed as tower master-slave model (TMSM) for solving optimising problems. Based on TMSM, the parallel immune memory clonal selection algorithm (PIMCSA) is also proposed. TMSM is a two level coarse-grained parallel artificial immune model with distributed immune response and distributed immune memory. In PIMCSA, vaccines are extracted and migrated between populations rather than individual migration as has been done in parallel genetic algorithms. It is a good balance between population diversity and the convergent speed. Experimental results on the numerical optimization and TSP problems show that PIMCSA achieves good performance in terms of both solution quality and computation time.

关键词： Immune system Genetic algorithms Artificial immune systems Competitive intelligence Master-slave Laboratories computer science education Poles and towers Vaccines Parallel processing

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Data fusion algorithm based on Bayes sequential estimation for wireless sensor network

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Dianzi Yu Xinxi Xuebao/Journal of Electronics and information technology 2009年第3期31卷 716-721页

作者： Zhang, Shu-Kui Cui, Zhi-Ming Gong, Sheng-Rong Sun, Yong Fang, Wei School of Computer Science and Technology Soochow University Suzhou 215006 China Jiangsu Key Laboratory of Computer Information Processing Technology Soochow University Suzhou 215006 China

Mobile Agent (MA) is more suitable for wireless sensor networks than the C/S model in data fusion. In MA based data fusion, the order of nodes visited along the route by MA has a significant impact on the algorithm efficiency and life time of wireless sensor networks. This paper proposes a Mobile Agent Data Fusion (MADF) algorithm based on bayes sequential estimation for wireless sensor networks. By designing data packet and data table with specific structure, and considers MA in multihop environments and adopts gradient of Bayes sequential estimation to dispatch MA. MA accounts for performing data processing and making data aggregation decisions at nodes rather than bring data back to a central processor (sink), redundant sensory data will be eliminated. Theoretical analysis and experimental results show that the proposed scheme is able to provide less energy consumption and network delay compared to directed diffusion schemes.

关键词： Mobile agents

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