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Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Classification of Remote Sensing Images

作者： Bao, Zheng Bai, Hua Liu, Ruihua Shen, Chaomin Dept. of Mathematics East China Normal University Shanghai 200062 China Meteorological Office of Minhang District and Shanghai Remote Sensing and Applied Measurement Center Shanghai 201100 China School of Math. and Sciences Chongqing Institute of Technology Chongqing 400054 China Dept. of Computer Science East China Normal University Shanghai 200062 China

The noise in natural images sometimes changes according to imaging mechanism or local image information. This is called spatially varying noise. It is obvious that classical variational denoising algorithms such as the Rudin-Osher-Fatemi model are not suitable for this kind of noise. We propose a variational method to remove this spatially varying noise based on the estimation of local variance for a given image, such that high noise regions are smoothed meanwhile the textures and certain details in low noise regions are preserved. Moreover, we give the proof of existence of the minimizer of our proposed functional. The experimental results show visual improvement and high signal-to-noise ratio over other variational denoising models. © 2008 SPIE.

关键词： Image reconstruction

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Stochastic Chaos with Its Control and Synchronization

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西北工业大学学报 2008年第6期26卷 659-667页

作者： Zhang Ying Xu Wei Zhang Tianshu Yang Xiaoli Wu Cunli Fang Tong Dept. of Applied Mathematics Northwestern Polytechnical University Xi＇an 710072 China College of Science Donghua University Shanghai 200051 China College of Math. and Information Science Shaanxi Normal University Xi＇an 710062 China Aircraft Strength Research Institute of China Xi＇an 710065 China Department of Engineering Mechanics Northwestern Polytechnical University Xi＇an 710072 China

The discovery of chaos in the sixties of last century was a breakthrough in concept,revealing the truth that some disorder behavior,called chaos,could happen even in a deterministic nonlinear system under barely deterministic *** a series of serious studies,people begin to acknowledge that chaos is a specific type of steady state motion other than the conventional periodic and quasi-periodic ones,featuring a sensitive dependence on initial conditions,resulting from the intrinsic randomness of a nonlinear system *** fact,chaos is a collective phenomenon consisting of massive individual chaotic responses,corresponding to different initial conditions in phase *** two adjacent individual chaotic responses repel each other,thus causing not only the sensitive dependence on initial conditions but also the existence of at least one positive top Lyapunov exponent(TLE) for ***,all the sample responses share one common invariant set on the Poincaré map,called chaotic attractor,which every sample response visits from time to time *** far,the existence of at least one positive TLE is a commonly acknowledged remarkable feature of *** know that there are various forms of uncertainties in the real *** theoretical studies,people often use stochastic models to describe these uncertainties,such as random variables or random *** with random variables as their parameters or with random processes as their excitations are often called stochastic *** doubt,chaotic phenomena also exist in stochastic systems,which we call stochastic chaos to distinguish it from deterministic chaos in the deterministic *** chaos reflects not only the intrinsic randomness of the nonlinear system but also the external random effects of the random parameter or the random ***,stochastic chaos is also a collective massive phenomenon,corresponding not only to different initial conditions but also to different

关键词：混沌无序行为控制性同步性

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On the Effectiveness of Rebuilding RNA Secondary Structures from Sequence Chunks

On the Effectiveness of Rebuilding RNA Secondary Structures ...

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International Symposium on Parallel and Distributed Processing (IPDPS)

作者： Michela Taufer Thamar Solorio Abel Licon David Mireles Ming-Ying Leung Department of Computer & Inf. Sciences University of Delaware USA Department of Computer of Science University of Texas Dallas USA Department of Computer Science University of Texas El Paso USA Department of Math. Sciences and Bioinformatics Prog. University of Texas El Paso USA

Despite the computing power of emerging technologies, predicting long RNA secondary structures with thermodynamics-based methods is still infeasible, especially if the structures include complex motifs such as pseudoknots. This paper presents preliminary results on rebuilding RNA secondary structures by an extensive and systematic sampling of nucleotide chunks. The rebuilding approach merges the significant motifs found in the secondary structures of the single chunks. The extensive sampling and prediction of nucleotide chunks are supported by grid technology as part of the RNAVLab functionality. Significant motifs are identified in the chunk secondary structures and merged in a single structure based on their recurrences and other statistical insights. A critical analysis of the strengths, weaknesses, and future developments of our method is presented.

关键词： RNA Bioinformatics Space technology Genomics Sampling methods Assembly computer science Costs Supercomputers computer architecture

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Multitask learning - An application to incremental face recognition

Multitask learning - An application to incremental face reco...

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3rd International Conference on computer Vision Theory and Applications, VISAPP 2008

作者： Masip, David Lapedriza, Ágata Vitrià, Jordi Universität Oberta de Catalunya Rambla del Poblenou 156 08018 Barcelona Spain Computer Vision Center Computer Science Depart. Universität Autónoma de Barcelona Barcelona 08193 Spain Department of Appl. Math. and Analysis University of Barcelona Edifici Històric Gran Via de les Corts 585 Barcelona 08007 Spain

ISBN: (纸本)9789898111210

Usually face classification applications suffer from two important problems: the number of training samples from each class is reduced, and the final system usually must be extended to incorporate new people to recognize. In this paper we introduce a face recognition method that extends a previous boosting-based classifier adding new classes and avoiding the need of retraining the system each time a new person joins the system The classifier is trained using the multitask learning principle and multiple verification tasks are trained together sharing the same feature space. The new classes are added taking advantage of the previous learned structure, being the addition of new classes not computationally demanding. Our experiments with two different data sets show that the performance does not decrease drastically even when the number of classes of the base problem is multiplied by a factor of 8.

关键词： Face recognition

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Image denoising using mixtures of Gaussian scale mixtures

Image denoising using mixtures of Gaussian scale mixtures

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IEEE International Conference on Image Processing

作者： Jose A. Guerrero-Colon Eero P. Simoncelli Javier Portilla Department of Computer Scienceand A.I. Universidad de Granada Granada Spain Center for Neural Science and Courant Inst. of Math. Sciences New York University USA Instituto de Óptica CSIC Madrid Spain

The local statistical properties of photographic images, when represented in a multi-scale basis, have been described using Gaussian scale mixtures (GSMs). In that model, each spatial neighborhood of coefficients is described as a Gaussian random vector modulated by a random hidden positive scaling variable. Here, we introduce a more powerful model in which neighborhoods of each subband are described as a finite mixture of GSMs. We develop methods to learn the mixing densities and covariance matrices associated with each of the GSM components from a single image, and show that this process naturally segments the image into regions of similar content. The model parameters can also be learned in the presence of additive Gaussian noise, and the resulting fitted model may be used as a prior for Bayesian noise removal. Simulations demonstrate this model substantially outperforms the original GSM model.

关键词： Image denoising GSM Covariance matrix Additive noise Gaussian noise Image segmentation Bayesian methods Noise reduction Statistics Least squares approximation

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Attribute Composition Distribution and Rough Law Status Estimation

Attribute Composition Distribution and Rough Law Status Esti...

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Shun-liang Huang Guan-yu Zhang Ling Zhang Kai-quan Shi School of Management Shandong University of Technology Zibo Shandong China School of Control Science and Engineering Shandong University Jinan Shandong China Department of Math Sci Huanghuai University Zhumadian Henan China School of Math. And Computer Sci Longyan University Longyan Fujian China School of Math Shandong University Jinan Shandong China

Function S-rough sets has dynamic characteristics and law characteristics. By employing function S-rough sets and the method of law generation, this paper proposes the concepts of attribute composition distribution and rough law distance. Then by using these concepts, this paper analyzes the relations between attribution composition distribution with rough law, moreover presents a series of theorems about the relations between rough law decomposition with attribute composition distribution. At last, an example is given for explaining the rough law status estimation. The results of this paper are the theory base of law mining and system status recognition.

关键词： Fuzzy systems Control systems Knowledge engineering Conference management Knowledge management Technology management Engineering management

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Unconditional Privacy over Channels which Cannot Convey Quantum Information

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Physical Review Letters 2008年第11期100卷 110502-110502页

作者： K. Horodecki M. Horodecki P. Horodecki D. Leung J. Oppenheim Department of Math Physics and Computer Science University of Gdańsk Gdańsk Poland National Quantum Information Centre of Gdańsk 81-824 Sopot Poland Institute of Theoretical Physics and Astrophysics University of Gdańsk Gdańsk Poland Faculty of Applied Physics and Math Technical University of Gdańsk Gdańsk Poland Institute for Quantum Computing University of Waterloo Waterloo Ontario N2L1N8 Canada Department of Applied Mathematics and Theoretical Physics University of Cambridge United Kingdom

Quantum cryptography enables one to verify that the state of the quantum system has not been tampered with and thus one can obtain privacy regardless of the power of the eavesdropper. All previous protocols relied on the ability to faithfully send quantum states or equivalently to share pure entanglement. Here we show this need not be the case—one can obtain verifiable privacy even through some channels which cannot be used to reliably send quantum states.

关键词： Quantum cryptography

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Research on rough set theory and applications in China

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Lecture Notes in computer science

作者： Wang, Guoyin Zhang, Qinghua Huang, Houkuan Ye, Dongyi Hu, Qinghua Hu, Xuegang Shi, Zhongzhi Li, Yongli Shang, Lin An, Liping Sai, Ying Chen, Shanben Liang, Jiye Qin, Keyun Zeng, Huanglin Xie, Keming Miao, Duoqian Min, Fan Wu, Zhaocong Wu, Weizhi Dai, Jianhua Institute of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing 400065 China School of Information Science and Technology Southwest Jiaotong University Chengdu 610031 China School of Computer and Information Technology Beijing Jiaotong University Beijing 100044 China College of Math. and Computer Fuzhou University Fuzhou 350002 China Harbin Institute of Technology PO Box 458 Harbin 150006 China School of Computer and Information Hefei University of Technology Hefei 230009 China Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China Lanzhou University No.222 Tianshui South Rd. Lanzhou 730000 China State Key Laboratory for Novel Software Technology Nanjing University Nanjing 210093 China Management Science and Engineering Department Business School Nankai University Tianjin 300071 China Shandong University of Finance No.40 Shun-geng Road Jinan 250014 China Welding Engineering Institute Shanghai Jiaotong University Shanghai 200030 China School of Computer and Information Technology Shanxi University Taiyuan 030006 China Intelligent Control Development Center Southwest Jiaotong University Chengdu 610031 China Artificial Intelligence of Key Laboratory Sichuan University of Science and Engineering Zigong 643000 China Department of Automation College of Information Engineering Taiyuan University of Technology Taiyuan 030024 China 4800 CaoAn Highway Shanghai 201804 China School of Computer Science and Technology University of Electronic Science and Technology of China Chengdu 610054 China School of Remote Sensing Information Engineering Wuhan University Wuhan 430079 China Institute for Information and System Sciences Faculty of Science Xi'an Jiaotong University Xi'an 710049 China Information College Zhejiang Ocean University Zhejiang 316004 China Institute of Artificial Intelligence Zhejiang University Hangzhou 310027 China

ISBN: (纸本)3540850635

This article gives a capsule view of research on rough set theory and applications ongoing at universities and laboratories in China. Included in this capsule view of rough set research is a brief description of the following things: Chinese research groups on rough set with their URLs for web pages, names of principal researchers (supervisors), numbers of graduate students, and topics being investigated. Statistical summaries showing the growth in the research on rough set theory and application in China are included. In addition, an introduction summarizing the research interests of Chinese researchers is included in this article. The contribution of this article is a complete overview of the principal research directions in rough set theory and its applications in China. © 2008 Springer-Verlag Berlin Heidelberg.

关键词： Rough set theory

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Approximate reasoning based on similarity measure

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Journal of Computational Information Systems 2007年第4期3卷 1747-1752页

作者： Zhang, Chengyi Li, Guxin Depart. of Math. Hainan Normal University Haikou 571158 China Department of Computer Science Zhumadian Education College Zhumadian 463000 China

Based on the knowledge of math.matical essence of approximate reasoning, this paper restudies the inference process of CRI and AARS algorithm and points out the defects of the original method. A new approximate reasoning algorithm (SMTT algorithm) is proposed as a result of similarity measure and transformation of translation about normal triangle fuzzy sets. Taking single-input single-output (SISO) fuzzy controller as an example, we compare SMTT algorithm with Mamdanian and AARS algorithm.

关键词： Fuzzy inference

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Quality of encryption measurement of bitmap images with RC6, MRC6, and rijndael block cipher algorithms

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International Journal of Network Security 2007年第3期5卷 241-251页

作者： El-Fishawy, Nawal Abu Zaid, Osama M. Department of Electronics and Electrical Communication Eng Faculty of Electronic Eng. Menouf Egypt B. Sc. Math. and Computer Science Faculty of Science Shebin Elkom Egypt

RC6, MRC6, and Rijndael are three block cipher algo-rithms. Different types of Bitmap images are encrypted with each of the three encryption algorithms. Visual in-spection is not enough on judging the quality of encrypted images. So, other measuring factors are considered based on: measuring the maximum deviation between the orig-inal and the encrypted images, measuring the correlation coefficient between the encrypted and the original images, the difference between the pixel value of the original im-age and its corresponding pixel value of the encrypted one, the encryption time and the throughput. These measur-ing factors are applied on the three encryption algorithms to evaluate images containing many high frequency com-ponents and others containing very large areas of single colors as an example of binary images. The results of the nominal electronic code book are not enthusiastic, so the Cipher Block Chaining and the output feed back modes are implemented and the results are compared.

关键词： Binary images

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