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Mobile E-Business service system based on ubiquitous computing technology

Mobile E-Business service system based on ubiquitous computi...

引用

7th international conference on machine learning and Cybernetics

作者： Yang, Yong Zhang, Wen-Kui Cent China Normal Univ Engn & Res Ctr Informat Technol Educ Wuhan 430079 Hubei Peoples R China Cent China Normal Univ Dept Phys Educ Wuhan 430079 Hubei Peoples R China

ISBN: (纸本)9781424420957

The mobile electronic commerce is a business activity which is organically synthesized with mobile information equipment such as the handset and the personal digital assistant and Internet. The mobile communication technology and other technical perfect combinations have created the mobile electronic commerce along with the globalization information technology revolution. The improvement enterprise service flow, the promotion enterprise operation efficiency has already become one of the targets faced on enterprise's electronic commerce goals. Basing on it, a mobile E-Business system based on Bluetooth was proposed and realized in the paper. Mobile E-Business system used Bluetooth technology as the communication media.

关键词： mobile commerce WML HTML PDA Blutooth

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Localized generalization error model for Multilayer Perceptron Neural Networks

Localized generalization error model for Multilayer Perceptr...

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7th international conference on machine learning and Cybernetics

作者： Yang, Fei Ng, Wing W. Y. Tsang, Eric C. C. Zeng, Xiao-Qin Yeung, Daniel S. Harbin Inst Technol Shenzhen Grad Sch Media & Life Sci Computing Lab Harbin Peoples R China Hong Kong Polytech Univ Dept Comp Hong Kong Hong Kong Peoples R China Hohai Univ Dept Comp Sci & Engn Nanjing 210098 Jiangsu Peoples R China

ISBN: (纸本)9781424420957

In this work, the localized generalization error model (L-GEM) for Multilayer Perceptron Neural Network (MLPNN) is derived. The L-GEM is inspired by the fact that a classifier should not be required to recognize unseen samples that are very different from the training samples. Therefore, evaluating a classifier by very different unseen samples may be counter-productive. In the L-GEM, the "local" is defined by the difference between feature values of unseen samples and training samples is less than a given real value (Q). The L-GEM provides an upper bound of the Mean-Square-Error of unseen samples "local" to the training dataset. As the generalization capability of a MLPNN is the key evaluation criterion of a successful training of MLPNN, we select the number of hidden neurons of a MLPNN using the L-GEM. The experimental results on four UCI datasets show that the proposed L-GEM yields better MLPNNs with higher generalization power (testing accuracy) and smaller number of hidden neurons.

关键词： Multilayer Perceptron Neural Network localized generalization error bound stochastic sensitivity measure architecture selection

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A Bayesian reinforcement learning approach for customizing human-robot interfaces 09

A Bayesian reinforcement learning approach for customizing h...

引用

13th international conference on Intelligent User Interfaces, IUI'09

作者： Atrash, Amin Pineau, Joelle School of Computer Science McGill University Montreal QC H3A 2A7 Canada

ISBN: (纸本)9781605581682

Personal robots are becoming increasingly prevalent, which raises a number of interesting issues regarding the design and customization of interfaces to such platforms. The particular problem addressed by this paper is the use of learning methods to improve the quality and effectiveness of human-machine interaction onboard a robotic wheelchair. In support of this, we present a method for learning and adapting probabilistic models with the aid of a human operator. We use a Bayesian reinforcement learning framework, that allows us to mix learning and execution, as well as take advantage of prior information about the world. We address the problems of learning, handling a partially observable environment, and limiting the number of action requests. We demonstrate empirical feasibility of our approach on an interface for an autonomous wheelchair. Copyright 2009 ACM.

关键词： Ubiquitous computing

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Improvement upon architecture of TCG credentials

Improvement upon architecture of TCG credentials

引用

international conference on machine learning and Cybernetics (icmlc)

作者： Xing Zhang Lu Zhu Sheng Yu Trusted Computing Laboratory Beijing University of Technology Beijing China Institute of Electronic Technology Information and Engineering University Zhengzhou China Computer School Wuhan University of China Wuhan China

The trusted computing group (TCG) has developed specifications for computing platforms that create a foundation of trust for software processes, based on credentials. But according to research on those credentials, we found management of those credentials is too complicated to implement, and the complication leads to underlying insecurity. The paper proposes a new architecture for credentials, making use of the EK credential and platform identity credential to accomplish the trust mechanism. This is a significant improvement on the previously five credentials required which are now reduced to only three. The proposal provides evidence for superiority in security and availability.

关键词： Cryptography Computer architecture Public key machine learning Cybernetics Manufacturing Privacy

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Geodesic distance based aproach for sentence similarity computation

Geodesic distance based aproach for sentence similarity comp...

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international conference on machine learning and Cybernetics (icmlc)

作者： Hui-Fang Ma Qing He Zhong-Zhi Shi Chinese Academy of Sciences Beijing China The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China

This paper presents a novel approach based on geodesic distance for sentence similarity computation, which can be used in a query-based information retrieval system. Unlike the traditional distance methods, geodesic distance takes into account the spatial relationships of sentences, which better reflects the intrinsic geometric structure of sentence manifold. Experiments demonstrate that the proposed method shows a better correlation to human intuition compared with traditional Euclidean method.

关键词： Distance measurement Manifolds Level measurement Euclidean distance machine learning Correlation Helium

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A distributed dynamic model of mobile sensor network

A distributed dynamic model of mobile sensor network

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international conference on machine learning and Cybernetics (icmlc)

作者： Long Zhao Li Peng Jindong Tang College of Communication and Control Engineering Jiangnan University Wuxi China Department of Electrical and Computer Engineering Michigan Technological University MI

Based on the located information and graph theory, a distributed sensor network model is introduced. The relationship between data transmission and fusion between nodes are described with Delaunay triangulation. And Voronoi diagrams have been used in the description of coverage region of nodes. With the model, disadvantages of existing located system based on a fixed infrastructure could be overcome.

关键词： Robot sensing systems Robots Robot kinematics Mobile communication Mobile computing Vehicles Wireless sensor networks

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The relationships between the inclusion degree and measures on rough set data analysis based on regular probability spaces

The relationships between the inclusion degree and measures ...

引用

international conference on machine learning and Cybernetics (icmlc)

作者： Eric C.C. Tsang Wen-Xia Yang De-Gang Chen Department of computing Hong Kong Polytechnic University Hung Hom Kowloon Hong Kong China Department of Mathematics and Physics North China Electric Power University Beijing China

Rough set data analysis is one of the main application techniques arising from rough set theory. In this paper we first give a concept of inclusion degree and introduce some measures on rough set in probability spaces. Then we establish several important relationships between the inclusion degree and these measures. Finally, we get one conclusion that these measures can be reduced to the inclusion degree by using mathematical reasoning.

关键词： Approximation methods Data analysis Accuracy Extraterrestrial measurements Finite element methods Cybernetics Set theory

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Rumor mongering in structured P2P networks

Rumor mongering in structured P2P networks

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international conference on machine learning and Cybernetics (icmlc)

作者： Tao Wu Cheng Shu Shao-Cheng Que Management School Wu Han University of Technology Wuhan Hubei China School of Information Systems and Management National University of Defense Technology Changsha Hunan 410073 China Department of Information and Technology Huazhong Normal University Wuhan Hubei 430079 China

A novel load balance technique based on rumor mongering in structured P2P networks is presented in this paper to address the hotspot problem when using DHT P2P networks as the distributed index systems. The basic idea is making use of the periodical topology maintenance communications to piggyback and spread popular information by way of rumor mongering in background. It is shown in the paper that, this rumor mongering technique is able to spread information quickly among nodes in structured P2P networks without introducing additional communication overhead, which effectively reduces load on hotspots.

关键词： Peer to peer computing Fingers Network topology Topology Protocols Maintenance engineering conferences

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MPEG-7 descriptor selection using Localized Generalization Error Model with mutual information

MPEG-7 descriptor selection using Localized Generalization E...

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international conference on machine learning and Cybernetics (icmlc)

作者： Jun Wang Wing W.Y. Ng Eric C.C. Tsang Tao Zhu Binbin Sun Daniel S. Yeung Media and Life Science Computing Lab Graduate School Harbin Institute of Technology China Department of Computing Hong Kong Polytechnic University Hong Kong China

MPEG-7 provides a set of descriptors to describe the content of an image. However, how to select or combine descriptors for a specific image classification problem is still an open problem. Currently, descriptors are usually selected by human experts. Moreover, selecting the same set of descriptors for different classes of images may not be reasonable. In this work we propose a MPEG-7 descriptor selection method which selects different MPEG-7 descriptors for different image class in an image classification problem. The proposed method L-GEMIM combines Localized Generalization Error Model (L-GEM) and Mutual Information (MI) to assess the relevance of MPEG-7 descriptors for a particular image class. The L-GEMIM model assesses the relevance based on the generalization capability of a MPEG-7 descriptor using L-GEM and prevents redundant descriptors being selected by MI. Experimental results using 4,000 images in 4 classes show that L-GEMIM selects better set of MPEG-7 descriptors yielding a higher testing accuracy of image classification.

关键词： Accuracy Mutual information Transform coding Testing Image classification Redundancy Mean square error methods

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Oblique Decision Trees Using Embedded Support Vector machines in Classifier Ensembles

Oblique Decision Trees Using Embedded Support Vector Machine...

引用

IEEE international conference on Cybernetic Intelligent Systems

作者： Vlado Menkovski Ioannis T. Christou Sofoklis Efremidis Athens Information Technology INTRACOM S.A. Telecom Solutions

ISBN: (纸本)9781424429141

Classifier ensembles have emerged in recent years as a promising research area for boosting pattern recognition systems' performance. We present a new base classifier that utilizes Oblique Decision Tree technology based on Support Vector machines for the construction of oblique (non-axis parallel) tests on the nodes of the decision tree inducted. We describe a number of heuristic techniques for enhancing the tree construction process by better estimation of the gain obtained by an oblique split at any tree node. We then show how embedding the new classifier in an ensemble of classifiers using the classical Hedge(P) algorithm boosts performance of the system. Testing 10-fold cross validation on UCI machine learning repository data sets shows that the new hybrid classifiers outperforms on average by more than 2.1% both the WEKA implementation of C4.5 (J48) and the SMO implementation of SVM in WEKA. The application of the particular ensemble algorithm is an excellent fit for online-learning applications where one seeks to improve performance of self-healing dependable computing systems based on reconfiguration by gradually and adaptively learning what constitutes good system configurations.

关键词： Classification Decision Trees On-line learning Supervised learning Decision Trees Support Vector Network Semi-supervised learning Classifier Ensembles Classifiers Oblique tree nodes

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