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2013 IEEE China Summit and International Conference on Signal and Information Processing, ChinaSIP 2013

作者： Liu, Jia-Ming You, Mingyu Li, Guo-Zheng Wang, Zheng Xu, Xianghuai Qiu, Zhongmin Xie, Wenjia An, Chao Chen, Sili Key Laboratory of Embedded System and Service Computing Department of Control Science and Engineering Tongji University Shanghai 201804 China Department of Respiratory Medicine Shanghai 200065 China

ISBN: (纸本)9781479910434

Cough Recognition is a valuable classification problem in healthcare. Generally, feature representation contributes a lot to the overall classifying performance. In this paper, a novel feature extraction method, Gammatone Cepstral Coefficients (GTCC), is investigated for cough recognition. The accuracy of GTCC comparing with MFCC is evaluated on a designed cough dataset following a 10 fold cross-validation schemes. Considering the imbalance of that dataset, weighted SVM is applied as the base classifier. The results indicate that GTCC surpass MFCC in modeling cough signals. With combination of GTCC and MFCC, a better performance is achieved. This paper provides a better feature representation prototype in cough recognition. © 2013 IEEE.

关键词： Feature extraction

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An enhanced two-factor user authentication in wireless sensor networks

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Telecommunication systems 2013年第1期55卷 105-113页

作者： Yuan, Jian-Jun Key Laboratory of Embedded System and Service Computing of Ministry of Education Tongji University Shanghai China

Since wireless sensor networks (WSN) are often deployed in an unattended environment and sensor nodes are equipped with limited computing power modules, user authentication is a critical issue when a user wants to access data from sensor nodes. Recently, M.L. Das proposed a two-factor user authentication scheme in WSN and claimed that his scheme is secure against different kinds of attack. Later, Khan and Alghathbar (K-A) pointed out that Das’ scheme has some security pitfalls and showed several improvements to overcome these weaknesses. However, we demonstrate that in the K-A-scheme, there is no provision of non-repudiation, it is susceptible to the attack due to a lost smart card, and mutual authentication between the user and the GW-node does not attained. Moreover, the GW-node cannot prove that the first message comes from the user. To overcome these security weaknesses of the K-A-scheme, we propose security patches and prove our scheme.

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Real-Time Communication Method for mHealth Base on Extended XMPP Protocol

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Communications and Network 2013年第3期5卷 590-595页

作者： Chenjie Shi Yu Fang The Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China

Considering characteristic of mHealth communication and problems of existing methods, this paper presents a real-time communication method for mHealth based on extended XMPP protocol. The method can maintain the role status efficiently and reduce data latency during the communication process. Meanwhile, it can be extended flexibly to meet increasing communication demands of mHealth services. Furthermore, a system framework is presented to support telemonitoring scene. Finally, system implementation and feasibility tests verify the effectiveness of the method and framework.

关键词： mHealth XMPP Protocol Real-Time Communication

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Using more initial centers for the seeding-based semi-supervised K-harmonic means clustering

Using more initial centers for the seeding-based semi-superv...

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2012 International Conference on Emerging Technologies for Information systems, computing, and Management, ICM 2012

作者： Gu, Lei Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China School of Computer Science and Technology Nanjing University of Posts and Telecommunication Nanjing China

ISBN: (纸本)9781461470090

In the initialization of the traditional semi-supervised k-means, the mean of some labeled data belonging to one same class was regarded as one initial center and the number of the initial centers is equal to the number of clusters. However, this initialization method using a small amount of labeled data also called seeds which are not appropriate for the semi-supervised k-harmonic means clustering insensitive to the initial centers. In this paper, a novel semi-supervised k-harmonic means clustering is proposed. Some seeds with one same class are divided into several groups and the mean of all data is viewed as one initial center in every group. Therefore, the number of the initial centers is more than the number of clusters in the new method. To investigate the effectiveness of the approach, several experiments are done on three datasets. Experimental results show that the presented method can improve the clustering performance compared to other traditional semi-supervised clustering algorithms. © 2013 Springer Science+Business Media New York.

关键词： Harmonic analysis

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Use the core clusters for the initialization of the clustering based on one-class support vector machine

Use the core clusters for the initialization of the clusteri...

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4th International Conference on Advances in Swarm Intelligence, ICSI 2013

作者： Gu, Lei Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 200092 China School of Computer Science and Technology Nanjing University of Posts and Telecommunications Nanjing 210023 China

ISBN: (纸本)9783642387142

The clustering method based on one-class support vector machine has been presented recently. Although this approach can improve the clustering accuracies, it often gains the unstable clustering results because some random datasets are employed for its initialization. In this paper, a novel initialization method based on the core clusters is used for the clustering algorithm based one-class support vector machine. The core clusters are gained by constructing the neighborhood graph and they are regarded as the initial datasets of the clustering algorithm based one-class support vector machine. To investigate the effectiveness of the proposed approach, several experiments are done on four datasets. Experimental results show that the new presented method can improve the clustering performance compared to the previous clustering algorithm based on one-class support vector machine and k-means approach. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Support vector machines

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An evolutionary semi-supervised subtractive clustering method by seeding

An evolutionary semi-supervised subtractive clustering metho...

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2012 International Conference on Information Technology and Software Engineering, ITSE 2012

ISBN: (纸本)9783642345210

A semi-supervised subtractive clustering has been proposed recently. However, it performance depends greatly on the choice of the parameters of the mountain function and only proper parameters enable the clustering method to produce a better effect. In this paper, an evolutionary semi-supervised subtractive clustering method by seeding is presented. The novel approach uses the genetic algorithms for tuning the relative parameters of the subtractive clustering by minimizing the Davies Bouldin clustering validity index regarded as the fitness function. To investigate the effectiveness of our approach, several experiments are done three real datasets. Experimental results show that our proposed method can improve the clustering performance significantly compared to other two traditional semi-supervised clustering algorithms. © 2013 Springer-Verlag.

关键词： Genetic algorithms

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Exploiting robustness in Petri net-based closed-loop systems to accommodate control specification changes

Exploiting robustness in Petri net-based closed-loop systems...

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2013 IEEE International Conference on Automation Science and Engineering, CASE 2013

作者： Li, Jun Zhou, Mengchu Dai, Xianzhong Key Laboratory of Measurement and Control of Complex Systems of Engineering China Ministry of Education Automation School of Southeast University Nanjing 210096 China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 201804 China

ISBN: (纸本)9781479915156

Supervisory control reconfiguration has been paid more attention due to its capacity of handling the uncertainties including resource failures, capability degradation, and task changes in discrete event systems. However, the robustness of closed-loop systems in response to some specification changes was not addressed in the prior studies. This paper presents a reconfiguration method based on Petri nets and integer programming for supervisory control of resource allocation systems with changeable resource allocation relationships (control specifications). First, we propose a reconfiguration mechanism. It updates the P-invariant-based supervisor and evolves the state of the closed-loop system. The latter adapts to the certain changes in specifications by the self-regulation of the closed-loop system's state. It utilizes fully the robustness in a closed-loop system and avoids unnecessary modification of a supervisor. Then, a reconfiguration model with robustness analysis is proposed based on integer programming. By using it, a firing sequence of transitions as a serial of reconfiguration actions can be found. The execution of the sequence implements the state evolution of a closed-loop system. There is no need for making additional efforts to analyze state reachability of the system, since the firability condition of transitions is incorporated into the model. Finally, the method is illustrated through an example of a hospital emergency service system. © 2013 IEEE.

关键词： Closed loop systems

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Real-Time Communication Method for mHealth Base on Extended XMPP Protocol

Real-Time Communication Method for mHealth Base on Extended ...

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The 9th International Conference on Wireless Communications,Networking and Mobile computing(WICOM 2013)

作者： Chenjie Shi Yu Fang The Key Laboratory of Embedded System and Service Computing Ministry of EducationTongji University

关键词： mHealth XMPP Protocol Real-Time Communication

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Two-dimensional color uncorrelated principal component analysis for feature extraction with application to face recognition

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2012 International Conference on service-Oriented computing, ICSOC 2012

作者： Zhao, Cairong Miao, Duoqian Department of Computer Science and Technology Tongji University Shanghai 201804 China Key Laboratory of Embedded System and Service Computing Ministry of Education Shanghai 7201804 China Ministry of Education Nanjing 210094 China

ISBN: (纸本)9783319029603

This paper proposes a two-dimensional color uncorrelated principal component analysis algorithm(2DCUPCA) for unsupervised subspace learning directly from color face images. The 2DCUPCA can be used to explore uncorrelated properties among color-based features, which contain minimum redundancy and ensure linear independence among features. Furthermore, the proposed 2DCUPCA provided the theoretical foundations analysis and proved the uncorrelated property between color-based features in theory. This makes it sure that the extracted features directly from three color image matrices will be uncorrelated. Finally, experimental results on the AR and FRGC-2 color face databases show that 2DCUPCA achieves better recognition performance than other color face recognition methods. © Springer International Publishing 2013.

关键词： Principal component analysis

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Model predictive control for HVAC systems - A review

Model predictive control for HVAC systems - A review

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2013 IEEE International Conference on Automation Science and Engineering, CASE 2013

作者： Kwadzogah, Roger Zhou, Mengchu Li, Sisi Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ 07013 United States Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 201804 China

ISBN: (纸本)9781479915156

The world faces an energy problem. Oil supply is gradually running out. Its use is polluting the planet with greenhouse gas. Most alternative energy sources also pose some environmental problems. Hence the efficient use of energy must be an integral part of any solution to them. Whenever possible, one must use advanced control engines and technologies to achieve the highest energy efficiency. In Heating Ventilation and Air Conditioning (HVAC) industry, much research has identified a number of energy-saving control methods. Derived from optimal control theory, Model Predictive Control (MPC) is one of them. This paper presents a comprehensive review of its applications to HVAC systems. © 2013 IEEE.

关键词： Model predictive control

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