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Design and Implementation of Speech Interaction System in Pervasive computing Environment

Design and Implementation of Speech Interaction System in Pe...

引用

international conference on machine learning and Cybernetics (icmlc)

作者： Li-fen Jiang Gui-zhang Lu Yun-wei Xin Zhang-lin Li College of Computer and Information Engineering of Tianjin Medical University Tianjin China Institute of Robotics and Information Automatic System Nankai University Tianjin China

Pervasive computing, with its focus on users, has the potential to fundamentally change the way people use computers, which challenges the traditional human-machine interaction mode and requires more natural interactive mode between human and computers. The requirement for natural speech in pervasive computing environment was discussed. And a speech interaction system was designed and implemented to meet the requirement of human-machine interaction for an intelligent office system in pervasive computing environment, and a practical solution was given. By this solution, transmit and convert of speech between the server and the embedded handheld device were fulfilled. Speech middleware of the system can provide friendly human-machine interface for the intelligent office system, and the key method for speech synthesis in different operating systems was provided and implemented in the system

关键词： Pervasive computing Intelligent systems Handheld computers Network servers Speech synthesis Layout Man machine systems Databases Speech recognition Radiofrequency identification

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The Improvement on Algorithm of DNA computing on 0-1 Planning Problem

The Improvement on Algorithm of DNA Computing on 0-1 Plannin...

引用

international conference on machine learning and Cybernetics (icmlc)

作者： Kang Zhou Xiao-jun Tong Jin Xu Department of Control Science and Engineer Huazhong University of Science and Technology Wuhan China Department of Mathematics and Physics Wuhan Polytechnic University Wuhan China

The old algorithm to solve 0-1 planning problem using DNA computing only searches the feasible solution set from all solution set, then we give an algorithm which can search optimization solution of 0-1 planning problem from all solution set by encoding specially solution set, using technique of electrophoresis and fluorescence labeling technique, and then we give an example to explain the algorithm validity and correctness. We also give a kind of strategy to deal with the negative real number of value coefficient and the complexity of our algorithm is O(m)

关键词： DNA computing Probes Technology planning Fluorescence Monitoring Encoding Electrokinetics Labeling Heuristic algorithms Mathematics

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Attributes Reduction Based on Rough Set

Attributes Reduction Based on Rough Set

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international conference on machine learning and Cybernetics (icmlc)

作者： E Xu Xue-dong Gao Wen-dong Tan Department of Computing Science Liaoning Institute of Technology Jinzhou 121001 China School of Management University of Science and Technology Beijing Beijing 100083 China. E-MAIL: Exu21@*** School of Management University of Science and Technology Beijing Beijing China Department of Computing Science Liaoning Institute of Technology Jinzhou China

Attributes reduction is one major problems in rough set theory. A method of attributes reduction based on scan vector is proposed in this paper. Firstly, define a new conception of discernible vector by which we can transform the information table into discernible vector set. Secondly, a plus rule for the discernible vector based on its good structure is defined, and consequently we can obtain a scan vector through scanning the discernible vector just only one time, which can represent the information table better because the scan vector has a more concise structure. And then, take the attribute frequency vector in the scan vector as the heuristic information and search for the attributes reduction in the discernible attributes set which has less numbers of elements than the original. Finally, the experiments results indicate that the method proposed in this paper is much more effective

关键词： Information systems Set theory machine learning Clustering algorithms machine learning algorithms Fellows Technology management Frequency Artificial intelligence Data mining

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Fusion of Multiple Features for Palmprint Authentication

Fusion of Multiple Features for Palmprint Authentication

引用

international conference on machine learning and Cybernetics (icmlc)

作者： Xiang-qian Wu Kuan-quan Wang David Zhang School of Computer Science and Technology Harbin Institute of Technology Harbin China Department of Computing Hong Kong Polytechnic University Hong Kong China

A palmprint image contains abundant features, such as the ridges, lines and textures, etc. Different features reflect the different characteristic of the palmprint. Fusion of multiple palmprint features may enhance the performance of a palmprint authentication system. In this paper, we investigate the fusion of two novel palmprint representations: orientationCode and diffCode. OrientationCode are defined using four directional templates and diffCode is computed using differential operation. Then these two codes are fused to measure the similarity of palmprints. The experimental results show that the proposed approach can get a very high accuracy

关键词： Authentication Biometrics Fingers Fingerprint recognition Iris Feature extraction Data mining Fuses Image databases Spatial databases

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Experimental Comparison Between Implicit and Explicit MCSs Construction Methods

Experimental Comparison Between Implicit and Explicit MCSs C...

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international conference on machine learning and Cybernetics (icmlc)

作者： Patrick P.K. Chan Aki F. Chan Eric C. C. Tsang Daniel S. Yeung Dept. of Comput. Hong Kong Polytech. Univ. Kowloon Department of computing The Hong Kong Polytechnic University Kowloon Hong Kong

Multiple classifier machines (MCSs) is a very popular research topic in recent years. It has been proved theoretically and empirically to outperform single classifiers in many scenarios. Creating diverse sets of classifier is one of the key issues in MCSs. One kind of method measures the diversity among the individual classifier when building the MCS while the other method does not consider the diversity value directly. This paper compared these two kinds of methods experimentally. From the experiments, the performances of implicit and explicit methods are very close. We can conclude that it is not necessary to consider the diversity measure among individual classifiers directly for building a good MCS

关键词： Diversity reception Bagging Boosting Voting Error correction machine learning algorithms Electronic mail Diversity methods Particle measurements Correlation

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An Intrusion-Tolerant Intrusion Detection Method Based on Real-Time Sequence Analysis

An Intrusion-Tolerant Intrusion Detection Method Based on Re...

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international conference on machine learning and Cybernetics (icmlc)

作者： Feng Zhao Qing-hua Li Li Jin School of Computer Science and Technology Huazhong University of Science and Technology Wuhan China

One of the most advanced research issues in network security is intrusion-tolerant intrusion detection, which has become another essential technique to protect computer systems and prevent the intrusion from generating a system failure. This paper presents a novel intrusion-tolerant intrusion detection method based on real-time sequence forecast analysis for network stream. We devise linear regression techniques to forecast network stream sequences. According to these, it's helpful for us to analysis intruders' behaviors and to recognize undesirable intrusions. We also provide recovery strategies to tolerate intrusion. Experiments on the http server demonstrate that our method outperform the others

关键词： Intrusion detection Real time systems Computer security Performance analysis High performance computing Protection Computer networks Web server Information analysis Failure analysis

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An Algorithm of Sticker DNA Chip Model on Making Spanning Tree Problem

An Algorithm of Sticker DNA Chip Model on Making Spanning Tr...

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international conference on machine learning and Cybernetics (icmlc)

In this paper, we set up sticker DNA chip model whose essential bio-chemical experiments and their realization of process are discussed. Then we put forward a DNA algorithm of making spanning tree problem and its bio-chemical implement process. The algorithm is first creating an original solution set of spanning subgraph then filtering the set to obtain all spanning trees. And then we prove the validity and complexity of the DNA algorithm, and explain feasibility of the DNA algorithm by an example. Finally, we can draw a conclusion that sticker DNA chip model possesses of predominance both of sticker model and DNA chip model

关键词： Testing DNA computing Probes NP-complete problem Mathematics Physics Mathematical model Filtering algorithms Molecular biophysics Application software

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Rule Induction from Numerical Data Based on Rough Sets Theory

Rule Induction from Numerical Data Based on Rough Sets Theor...

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international conference on machine learning and Cybernetics (icmlc)

作者： Su-yun Zhao Wing W. Y. Ng Eric C. C. Tsang Daniel S. Yeung De-gang Chen Department of computing Hong Kong Polytechnic University Hong Kong China Department of Mathematics and Physics North China Electric Power University Beijing China

To induce rules from numerical data by rough sets, there are two kinds of methods. One is to discretize the original data and then apply the crisp rough sets models. Here the rough sets models which can only deal with the nominal data are called crisp rough sets models. The other is to fuzzify the original data and then apply fuzzy rough sets models. There are some problems on both of these methods on rules induction such as information loss after discretization or increasing of data size after fuzzification. In this paper we make an attempt to propose one method to induce rules without discretization or fuzzification. Firstly the indiscernibility relation which is the underlining concept of rough sets is redefined as the similarity relation. Subsequently, the concepts of knowledge reduction are proposed based on the similarity relation. Finally, the numerical experiments show that our method is feasible and effective

关键词： Rough sets Fuzzy sets Fuzzy set theory Physics computing Mathematics Mathematical model Uncertainty Artificial intelligence Pattern recognition Data mining

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Construction Engineering Decision Support Enabled by Minimization of Localized Generalization Error of RBFNN

Construction Engineering Decision Support Enabled by Minimiz...

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international conference on machine learning and Cybernetics (icmlc)

作者： Ming Lu Wing W. Y. Ng Daniel S. Yeung Wah-ho Chan Department of Civil and Structure Engineering Hong Kong Polytechnic University Hong Kong China Media and Life Science Computing Laboratory Shenzhen Graduate School Harbin Institute of Technology Shenzhen China Department of Computing Hong Kong Polytechnic University Hong Kong China

In an attempt to address the limitations of neural modeling in engineering applications, we draw on a novel localized generalization error model to train RBFNN on a dataset obtained from the domain of construction engineering and project management, with the objective of devising reliable strategies that may shorten the cycle time required for constructing one span of precast viaduct. We select the RBFNN with the optimal number of hidden neurons, which yields the maximal coverage around training samples given a predetermined generalization error bound. By analyzing the values of center vectors of RBFNN, we take one step further to uncover hidden patterns or rules by which RBFNN maps input features onto output classifications. The rules derived from the model are well corroborated by domain experts and computer simulation models

关键词： Neural networks Data engineering Neurons Computer errors Reliability engineering Laboratories Electronic mail Project management Management training Pattern analysis

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Fault Tolerant Differential Evolution Based Optimal Reactive Power Flow

Fault Tolerant Differential Evolution Based Optimal Reactive...

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international conference on machine learning and Cybernetics (icmlc)

作者： Sheng Su C.y. Chung K.p. Wong Y.f. Fung D.s. Yeung Department of Electrical Engineering Huazhong University of Science and Technology Wuhan Hubei China Computational Intelligence Applications Research Laboratory Department of Electrical Engineering Hong Kong Polytechnic University Hong Kong China Department of Computing Hong Kong Polytechnic University Hong Kong China

Differential evolution (DE) is a new branch of evolutionary algorithms (EAs) and has been successfully applied to solve the optimal reactive power flow (ORPF) problems in power systems. Although DE can avoid premature convergence, large population is needed and the application of DE is limited in large-scale power systems. Grid computing, as a prevalent paradigm for resource-intensive scientific application, is expected to provide a computing platform with tremendous computational power to speed up the optimization process of DE. When implanting DE based ORPF on grid system, fault tolerance due to unstable environment and variation of grid is a significant issue to be considered. In this paper, a fault tolerant DE-based ORPF method is proposed. In this method, when the individuals are distributed to the grid for fitness evaluation, a proportion of individuals, which returns from the grid slowly or fails to return, are replaced with new individuals generated randomly according to some specific rules. This approach can deal with the fault tolerance and also maintain diversity of the population of DE. The superior performance of the proposed approach is verified by numerical simulations on the ORPF problem of the IEEE 118-bus standard power system

关键词： Fault tolerance Reactive power Power system faults Grid computing Fault tolerant systems Evolutionary computation Convergence Large-scale systems Distributed power generation Mesh generation

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