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Clonal selection land-based satellite tracking telemetry and command (TT&C) resources scheduling based on the mission oriented model

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Jisuanji Xuebao/Chinese Journal of Computers 2009年第8期32卷 1525-1535页

作者： Hou, Cui-Qin Jiao, Li-Cheng Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

This paper proposes a novel model, the mission oriented model, for the problem of land-based satellite tracking telemetry and command (TT&C) resources scheduling. Compared to other models, the mission oriented model constrains a satellite to be tracked and commanded by only a ground station which can observe the satellite. Therefore, the proposed model makes it possible that scheduling algorithms schedule TT&C resources to complete more missions. Then it proposes the clonal selection land-based satellite TT&C resources scheduling algorithm (CS_STT&CRSA) based on the mission oriented model and proves its global convergence in theory. The algorithm adopts a matrix coding scheme, which depends on the start times of tracked and commanded orbits and the relationships between satellites and ground stations. The severe-constraint satisfaction operator which guarantees the individual satisfies severe constraints is proposed. When there are 5 geostationary satellites and 30, 40 or 50 low earth orbit and medium earth orbit (LEO&MEO) satellites, 10 different groups of tasks are generated respectively. Experimental results illustrate that the mission oriented model enables scheduling algorithms to make better use of TT&C resources and complete more missions and CS_TT&CRSA has more powerful ability of searching and solving constraints and is more stable.

关键词： Scheduling algorithms

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SAR image compression based on multi-bandelets and geometric flow optimization

SAR image compression based on multi-bandelets and geometric...

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MIPPR 2009 - Multispectral image Acquisition and processing: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Yang, Shuyuan Qi, Weidong Wang, Zhaoxia Jiao, Licheng Key Laboratory of Intelligent Perception and Image Understanding Ministry of Education of China Xidian University Xi'an 710071 China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China National Key Laboratory of Radar Signal Processing School of Electricity Engineering Xidian University Xian 710071 China

ISBN: (纸本)9780819478054

Bandelet transform is an efficient image sparse representation approach which can adaptively approximate the geometrical regularity of image structures. In this paper, a multi-bandelets based method for SAR image compression is presented, which is constructed by combining multi-wavelet with Bandelet transform and geometric flow optimization. Compared with single wavelet, multi-wavelet has some advantages such as compact support, orthogonality, symmetry and smoothness, thus making finite length filtering, linear phase, correlation remove and good frequency domain characteristics possible, which are very desirable in image compression. Moreover, in our method the multi sub-bands collaborative decision algorithm for geometric flow optimization is proposed to obtain more accurate geometric flows. A number of simulations are taken on SAR images and the result shows that our method can provide a significant improvement over the multi-wavelet and the second generation Bandelet, both in visual fidelity and some objective evaluation criteria such as peak signal to noise ratio, equivalent numbers of looks and edge preservation index. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： image compression

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The analysis and design of work safety and emergency management information system in large-scale hydroelectric project

The analysis and design of work safety and emergency managem...

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2009 Asia-Pacific Power and Energy Engineering Conference, APPEEC 2009

作者： Zhou, Jian-Lan Sun, Zhi-Yu Liu, Xian-Rong Key Laboratory of Education Ministry for Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan Hubei 430074 China Department of Work Safety China Three Gorges Project Corporation Yichang Hubei 443002 China

ISBN: (纸本)9781424424870

It is significant to research the work safe and emergency management information system (PSEMIS) in large-scale hydroelectric project. This paper analyses the reviews and China Three Gorges Project Corporation work safety and emergency management status and business needs, proposes the overall framework of the system design. The basis of the work safety management system and emergency management system is the safety risk control and hazards classification standards. The paper discusses the safety risk control and hazards classification standards;analyses the main function modules of the work safety and emergency management application software systems respectively;and discusses the hazards risk assessment and identification standards, business model design, systems integration, digital contingency plans and other key technical problems. © 2009 IEEE.

关键词： Hazards

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MRI brain tumor segmentation based on improved fuzzy c-means method

MRI brain tumor segmentation based on improved fuzzy c-means...

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MIPPR 2009 - Medical Imaging, Parallel processing of images, and Optimization Techniques: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Deng, Wankai Xiao, Wei Pan, Chao Liu, Jianguo Key Laboratory of Education Ministry for Image Processing and Intelligence Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan Hubei 430074 China

ISBN: (纸本)9780819478085

This paper focuses on the image segmentation, which is one of the key problems in medical image processing. A new medical image segmentation method is proposed based on fuzzy c- means algorithm and spatial information. Firstly, we classify the image into the region of interest and background using fuzzy c means algorithm. Then we use the information of the tissues' gradient and the intensity inhomogeneities of regions to improve the quality of segmentation. The sum of the mean variance in the region and the reciprocal of the mean gradient along the edge of the region are chosen as an objective function. The minimum of the sum is optimum result. The result shows that the clustering segmentation algorithm is effective. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Clustering algorithms

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Automatic detecting method of LED signal lamps on fascia based on color image

Automatic detecting method of LED signal lamps on fascia bas...

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MIPPR 2009 - Remote Sensing and GIS Data processing and Other Applications: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Peng, Xiaoling Hou, Wenguang Ding, Mingyue College of Life Science and Technology Image Processing and Intelligence Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan Hubei 430074 China

ISBN: (纸本)9780819478092

Instrument display panel is one of the most important parts of automobiles. Automatic detection of LED signal lamps is critical to ensure the reliability of automobile systems. In this paper, an automatic detection method was developed which is composed of three parts in the automatic detection: the shape of LED lamps, the color of LED lamps, and defect spots inside the lamps. More than hundreds of fascias were detected with the automatic detection algorithm. The speed of the algorithm is quite fast and satisfied with the real-time request of the system. Further, the detection result was demonstrated to be stable and accurate. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Light emitting diodes

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An immune memory clone algorithm for constrained multi-objective optimization

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Tien Tzu Hsueh Pao/Acta Electronica Sinica 2009年第6期37卷 1289-1294页

作者： Shang, Rong-Hua Jiao, Li-Cheng Ma, Wen-Ping Gong, Mao-Guo Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an Shaanxi 710071 China

A new algorithm for constrained multi-objective optimization is presented. The algorithm treats the constraints as an objective and the immune clone and immune memory mechanism are introduced. Therefore, the new algorithm could find the Pareto-optimal solutions from the feasible region and the edge of the infeasible region, which assures both the convergence and diversity of the obtained solutions. Simulation results show that the new algorithm has much better performance in finding a much better spread of solutions, in maintaining a better uniformity of the solutions and in obtaining a better convergence.

关键词： Multiobjective optimization

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Graph based co-training algorithm for web page classification

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Tien Tzu Hsueh Pao/Acta Electronica Sinica 2009年第10期37卷 2173-2180+2219页

This paper proposes a novel inductive semi-supervised algorithm for web page classification named GCo-training, exploiting texts in web pages and hyperlinks among them. GCo-training iteratively trains two classifiers-a graph-based semi-supervised classifier based on hyperlinks among web pages and a Bayes classifier based on texts in web pages, under the framework of Co-training. On the one hand, the graph-based semi-supervised classifier obtains high accuracy based on a small set of labeled examples through exploiting links among web pages and can augment labeled examples for the Bayes classifier. On the other hand, the Bayes classifier can also provide labeled example for the graph-based classifier after it learning on labeled set augmented by the graph-based classifier. Therefore, the two classifiers help each other and improve their respective performance during the process of training. Finally, the Bayes classifier can classify a large number of unseen examples. We test GCo-training algorithm, Co-training algorithm based on words occurring on web pages and words occurring in hyperlinks and Bayes algorithm based on EM on the Web&KB dataset. Experimental results show GCo-training performs much better than the other algorithms.

关键词： Websites

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Curve reconstruction from a set of dense scattered points using A* algorithm

Curve reconstruction from a set of dense scattered points us...

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MIPPR 2009 - Automatic Target Recognition and image Analysis: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Sun, Yangguang Zhou, Chengping Cai, Chao Ding, Mingyue Institute for Pattern Recognition and Artificial Intelligence State Key Laboratory for Multi-spectral Information Processing Technologies HUST Wuhan 430074 China College of Life Science and Technology Image Processing and Intelligence Control Key Laboratory of Education Ministry of China HUST Wuhan 430074 China

ISBN: (纸本)9780819478061

In this paper, a novel curve reconstruction method based on A* algorithm from a set of dense scattered points was proposed. Our method can not only reconstruct dense scattered points with single connected complicated form, but also solve the problem building the curve from the scattered points with close form and multiply connected form. Moreover, the influence of noise points on reconstructed curves is farther decreased, and the shape of dense scattered points will be well hold. Experimental results have demonstrated that the proposed method has the feasibility and robustness. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Pattern recognition

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Improvement of directed diffusion protocol based on data aggregation

Improvement of directed diffusion protocol based on data agg...

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2009 International Conference on Computational Science and Engineering, CSE '09

作者： Hui, Chen Yufeng, Shi Ye, Wang Yang, Laurence T. Naixue, Xiong Key laboratory of ministry of education for image processing and intelligent control Huazhong University of Science and Technology Wuhan China Department of Computer Science St Francis Xavier University Canada Department of Computer Science Georgia State University Georgia GA United States

ISBN: (纸本)9780769538235

How to make full use of the limited energy available and prolonging the survival time of node is a major concern in research on Wireless Sensor Networks (WSNs). This paper presented an improved approach based on Directed Diffusion Protocol (DDP) which could meet the features of WSN, such as data-oriented, many-to-one transmissions and low energy costs, together with data aggregation mechanisms which emphasized on cascading timeouts, to eliminate the redundancy caused by the transmission of large amounts of data. This modified protocol prohibited the direct forwarding of central nodes, balancing data traffic of different sensors between the source and the sink, and proved to be able of reducing total network flows, energy consumptions and prolonging the lifetime of the network through simulations.

关键词： Sensor nodes

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image enhancement based on intrascale dependencies of the second generation curvelet transform

Image enhancement based on intrascale dependencies of the se...

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MIPPR 2009 - Remote Sensing and GIS Data processing and Other Applications: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Hao, Hongxia Liu, Fang Jiao, Licheng School of Computer Science and Technology Xidian University Xi'an 710071 China Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Xi'an 710071 China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9780819478092

This paper presents a strong noise image enhancement method based on intrascale dependencies of the second generation curvelet transform. Observing that the immediate four neighbor coefficients bear the most important dependencies, we use spatial clustering property of the intrascale neighbor coefficients to separate noise and signal of interest, and to deal with them differently, i.e. to suppress noise and strengthen edges. Comparing our approach with Starck's enhancement model (Starck et al., 2003), we experimentally find that for high noise level images, our method outperforms the starck's system in noise suppression and signal strengthening and produces better enhancement results. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： image enhancement

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