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International Conference on Future Generation Communication and Networking Symposia, FGCNS

作者： Chi-Chen Chang Yu-Zheng Wang Chi-Shiang Chan Department of Information Engineering and Computer Science Feng Chia University FCU Taichung Taiwan Department of Computer Science and Information Engineering National Chung Cheng University Chiayi Taiwan Department of Information Science and Applications Asia University Wufeng Taiwan

Noar and Shamir presented the concept of visual cryptography. Many researches following it go down the same track: to expand the secret pixels to blocks. As a result, the size of the secret image becomes larger, and the quality of the expanded secret image becomes worse. In order to prevent the pixels from expanding, Yang has proposed his probability-based visual secret sharing scheme, where the concept of probability is employed to pick out pixels from the black or white sets. In this paper, we shall propose a new scheme that is a modified version of Yangpsilas scheme. Our experimental results show that we can obtain better recovered image quality with high contrast.

关键词： Cryptography Cellular phones Electronic mail computer science Image quality Stacking Personal digital assistants Conferences Information science Application software

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Stability and L2-Gain Analysis for Switched Neutral Systems

Stability and L2-Gain Analysis for Switched Neutral Systems

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International Conference on Apperceiving Computing and Intelligence Analysis, ICACIA

作者： Du-Yu Liu Shou-Ming Zhong Yuan-Qing Huang School of Applied Mathematics University of Electronic Science and Technology of China Chengdu China Department Computer Science and Applications Sichuan University of Science and Engineering Zigong China

This paper considers the stability and L 2 -gain for a class of switched neutral systems. Sufficient conditions for exponential stability criteria and L 2 -gain are developed for arbitrary switching signal with averag... 详细信息

关键词： Stability analysis Switched systems Symmetric matrices Stability criteria Lyapunov method Delay effects Control systems Eigenvalues and eigenfunctions Mathematics computer science

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Research on Face Recognition Method based on Cognitive Mechanism

Research on Face Recognition Method based on Cognitive Mecha...

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International Conference on Apperceiving Computing and Intelligence Analysis, ICACIA

作者： Jia Cui Jian-Ping Li Yu-Jie Hao Department of Computer Science and Engineering University of Electronic Science and Technology Chengdu China International Centre for Wavelet Analysis and Its Applications Logistical Engineering University Chongqing China

A face recognition method similar to human cognitive mechanism has been proposed. Motivated by the continuity rule of a same class samples, face recognition can be regarded as face pattern cognition. Compared with traditional statistical pattern based face recognition, it has a kind of relationship with human's cognitive mechanism. When face coverage of different people overlap, a person's face distribution in low dimension space has a certain kind of cohesion. With the increase of space dimension, the cohesion of a same class samples decreases, meanwhile the repellency of different class samples increases. However, with further increasing of dimension, both the cohesion of a same class and the repellency of different class decrease. The coverage of candidate face recognition is processed in a certain space. If it belongs to several candidate face coverage, Fisher LDA method can be applied to obtain the final results. Experiments based on ORL have proved that untrained random objects can be recognized perfectly.

关键词： Face recognition Humans Face detection Cognition Linear discriminant analysis Neural networks Pattern recognition computer science Wavelet analysis Application software

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Study on Multi-Biometric Feature Fusion and Recognition Model

Study on Multi-Biometric Feature Fusion and Recognition Mode...

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International Conference on Apperceiving Computing and Intelligence Analysis, ICACIA

作者： Jia Cui Jian-Ping Li Xiao-Jun Lu Department of Computer Science and Engineering University of Electronic Science and Technology Chengdu China Intemational Centre for Wavelet Analysis and Its Applications Logistical Engineering University Chongqing China

The single biometric identification technology has the inherent and difficult overcoming shortcomings, so multi-modal biometric fusion and identification techniques were proposed to improve the performance and accurate rate of identification system. This paper proposed a model combined with 2-dimensional Fisher linear discriminant analysis for face and iris feature fusion and recognition. First face and iris images are compressed respectively to preprocess the images, and the two corresponding original feature matrixes are obtained. Then the two original feature matrixes are integrated into one matrix, and formed a combined feature matrix. Third 2DFLD is applied to feature extraction to the combined feature matrix, so a fused feature matrix is constructed. At last, nearest neighbor decision rule is applied in the process of recognition. Experiment results show the recognition rate is greatly improved.

关键词： Biometrics Iris Linear discriminant analysis Face recognition Image coding Feature extraction Logic Character recognition Data mining computer science

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A Method of Security Evaluation based on Fuzzy Mathematics

A Method of Security Evaluation based on Fuzzy Mathematics

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International Conference on Apperceiving Computing and Intelligence Analysis, ICACIA

作者： Guo-Ming Lu Zhi-Hong Chen Xue-Zhi He Jian-Ping Li Department of computer science and engineering University of Electronic Science and Technology Chengdu China International Centre for Wavelet Analysis and Its Applications Logistical Engineering University Chongqing China

In order to effectively evaluate the system security, a quantitative information security evaluation method which combine analytic hierarchy process (AHP) and fuzzy comprehensive evaluation were proposed. Firstly, referring to Common Criteria (CC), we established security evaluation hierarchy model. Then, the analytic hierarchy process (AHP) method was used to calculate the security factors' weights to the evaluated system. In the end, fuzzy comprehensive evaluation method was applied to calculate the final quantitative security level. The effectiveness of this method is validated by evaluation of a practical system.

关键词： Mathematics Information security Data security Information analysis Protection computer security Fuzzy systems Information technology Cryptography Resource management

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SVM ranking with backward search for feature selection in type II diabetes databases

SVM ranking with backward search for feature selection in ty...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Sarojini Balakrishnan Ramaraj Narayanaswamy Nickolas Savarimuthu Rita Samikannu Department of Computer Applications K.L.N. College of Information Technology Madurai India Department of Computer Science & Engineering GKM College of Engineering and Technology Chennai India Department of Computer Applications National Institute of Technology Tiruchirappalli India VIT Business School Vellore of Institute of Technology Vellore India

Clinical databases have accumulated large quantities of information about patients and their clinical history. Data mining is the search for relationships and patterns within this data that could provide useful knowledge for effective decision-making. Classification analysis is one of the widely adopted data mining techniques for healthcare applications to support medical diagnosis, improving quality of patient care, etc. Usually medical databases are high dimensional in nature. If a training dataset contains irrelevant features (i.e., attributes), classification analysis may produce less accurate results. Data pre-processing is required to prepare the data for data mining and machine learning to increase the predictive accuracy. Feature selection is a preprocessing technique commonly used on high-dimensional data and its purposes include reducing dimensionality, removing irrelevant and redundant features, reducing the amount of data needed for learning, improving algorithms' predictive accuracy, and increasing the constructed models' comprehensibility. Much research work in data mining has gone into improving the predictive accuracy of the classifiers by applying the techniques of feature selection. The importance of feature selection in medical data mining is appreciable as the diagnosis of the disease could be done in this patient-care activity with minimum number of features. Feature selection may provide us with the means to reduce the number of clinical measures made while still maintaining or even enhancing accuracy and reducing false negative rates. In medical diagnosis, reduction in false negative rate can, literally, be the difference between life and death. In this paper we propose a feature selection approach for finding an optimum feature subset that enhances the classification accuracy of Naive .Bayes classifier. Experiments were conducted on the Pima Indian Diabetes Dataset to assess the effectiveness of our approach. The results confirm that SVM Rank

关键词： Support vector machines Diabetes Spatial databases Data mining Accuracy Support vector machine classification Medical diagnosis Medical diagnostic imaging History Decision making

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Web service allocations based on combinatorial auctions and market-based mechanisms

Web service allocations based on combinatorial auctions and ...

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International Conference on computer Supported Cooperative Work in Design

作者： Szu-Yin Lin Bo-Yuan Chen Chun-Chieh Liu Von-Wun Soo Department of Computer Science National Tsing Hua University HsinChu Taiwan Institute of Computer Systems and Applications National Tsing Hua University HsinChu Taiwan Department of Computer Science and Information Engineering National University of Kaohsiung Kaohsiung Taiwan

ISBN: (纸本)9781424416509

The main idea in this paper is using combinatorial Web service market based mechanism (CWSMBM) to allow service demanders bid for more than one service at the same time. It takes quality of service into consideration in the design of market allocation mechanisms. We define the cost-benefit threshold for service providers to decide whether to accept or reject service tasks. We found that the cost-benefit threshold improves the global benefit value effectively but would sometimes cause a starvation problem. But the starvation can be a trade-off in sacrificing some service demanders to enhance the global benefit.

关键词： Web services Quality of service Robots Resource management Supply and demand computer science computer applications Application software Large scale integration Collaboration

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A soft computing approach for data mining based query processing using rough sets and genetic algorithms

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International Journal of Hybrid Intelligent Systems 2008年第1期5卷 1-17页

作者： Srinivasa, K.G. Venugopal, K.R. Patnaik, L.M. Department of Computer Science and Engineering Data Mining Laboratory M S Ramaiah Institute of Technology Bangalore – 560054 India University Visvesvaraya College of Engineering Bangalore – 560001 India Microprocessor Applications Laboratory Indian Institute of Science Bangalore India

The optimization of queries is critical in database management systems and the complexity involved in finding optimal solutions has led to the development of heuristic approaches. Answering data mining query involves a random search over large databases. Due to the enormity of the data set involved, model simplification is necessary for quick answering of data mining queries. In this paper, we propose a hybrid model using rough sets and genetic algorithms for fast and efficient query answering. Rough sets are used to classify and summarize the datasets, whereas genetic algorithms are used for answering association related queries and feedback for adaptive classification. Here, we consider three types of queries, i.e., select, aggregate and classification based data mining queries. Summary tables that are built using rough sets and analytical model of attributes are used to speed up select queries. Mining associations, building concept hierarchies and reinforcement of reducts are achieved through genetic algorithms. The experiments are conducted on three real-life data sets, which include KDD 99 Cup data, Forest Cover-type data and Iris data. The performance of the proposed algorithm is analyzed for both execution time and classification accuracy and the results obtained are good.

关键词： Rough sets genetic algorithms query answering optimization

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Automatic simultaneous architecture and parameter search in fuzzy neural network learning using novel variable length crossover differential evolution

Automatic simultaneous architecture and parameter search in ...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Lotika Singh Satish Kumar Sandeep Paul Department of Physics and Computer Science Dayalbagh Educational Institute (Deemed University) Agra India Computer Science and Applications the Department of Physics and Computer Science Dayalbagh Educational Institute (Deemed University) Agra India Department of Electrical Engineering Dayalbagh Educational Institute (Deemed University) Agra India

The automatic simultaneous search of structure and parameters in fuzzy-neural networks is a pressing research problem. This paper introduces a novel and powerful variable-length-crossover differential evolution algorithm, vlX-DE, which is applied to ASuPFuNIS fuzzy-neural model learning, and permits simultaneous evolution of mixed-length populations of strings representing ASuPFuNIS network instances in different rules spaces. As hybrid populations of strings evolve using vlX-DE, the population gradually converges to a single rule space after which parameter search within that space proceeds till the end of the algorithm run. Search can be directed to stress either rule node economy or minimize the sum-square-error, or trade-off between these two. Tests on three benchmark problems-iris classification, CHEM classification, and Narazaki-function approximation-clearly highlight the effectiveness of the algorithm in being able to perform this simultaneous search.

关键词： Classification algorithms Iris Evolution (biology) computer architecture Encoding Search problems computer science

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On the scalability of particle swarm optimisation

On the scalability of particle swarm optimisation

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Congress on Evolutionary Computation

作者： Sebastien Piccand Michael O'Neill Jacqueline Walker Department of Computer Science ' Information Systems University of Limerick Limerick Ireland Natural Computing Research ' Applications group School of Computer Science ' Informatics University College Dublin Dublin Ireland Department of Electronic and Computer Engineering University of Limerick Limerick Ireland

Particle swarm has proven to be competitive to other evolutionary algorithms in the field of optimization, and in many cases enables a faster convergence to the ideal solution. However, like any optimization algorithm it seems to have difficulties handling optimization problems of high dimension. Here we first show that dimensionality is really a problem for the classical particle swarm algorithms. We then show that increasing the swarm size can be necessary to handle problem of high dimensions but is not enough. We also show that the issue of scalability occurs more quickly on some functions.

关键词： Benchmark testing Topology Particle swarm optimization Scalability Evolutionary computation Optimization Convergence

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