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2011 International Conference on Cloud and Service Computing, CSC 2011

作者： Yang, Bo Xu, Xiaofei Tan, Feng Park, Dong Ho State Key Laboratory of Software Engineering Wuhan University Wuhan China School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu 611731 China Department of Industrial Engineering University of Electronic Science and Technology of China Chengdu 611731 China Department of Information and Statistics Hallym University Chuncheon 200-702 Korea Republic of

ISBN: (纸本)9781457716362

Cloud computing' service-oriented characteristics advance a new way of service provisioning called utility based computing. However, toward the practical application of commercialized Cloud, we encounter two challenges: i) there is no well-defined job scheduling algorithm for the Cloud that considers the system state in the future, particularly under overloading circumstances;ii) the existing job scheduling algorithms under utility computing paradigm do not take hardware/software failure and recovery in the Cloud into account. In an attempt to address these challenges, we introduce the failure and recovery scenario in the Cloud computing entities and propose a Reinforcement Learning (RL) based algorithm to make job scheduling fault-tolerable while maximizing utilities attained in the long term. We carry out experimental comparison with Resource-constrained Utility Accrual algorithm (RUA), Utility Accrual Packet scheduling algorithm (UPA) and LBESA to demonstrate the feasibility of our proposed approach. © 2011 IEEE.

关键词： Cloud computing

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Testing and validating machine learning classifiers by metamorphic testing

Testing and validating machine learning classifiers by metam...

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作者： Xie, Xiaoyuan Ho, Joshua W.K. Murphy, Christian Kaiser, Gail Xu, Baowen Chen, Tsong Yueh Centre for Software Analysis and Testing Swinburne University of Technology Hawthorn VIC 3122 Australia Department of Medicine Brigham and Women's Hospital Harvard Medical School Boston MA 02115 United States Department of Computer Science Columbia University New York NY 10027 United States School of Computer Science and Engineering Southeast University Nanjing 210096 China State Key Laboratory for Novel Software Technology Department of Computer Science and Technology Nanjing University Nanjing 210093 China Department of Computer and Information Science University of Pennsylvania Philadelphia PA 19103 United States

Machine learning algorithms have provided core functionality to many application domains - such as bioinformatics, computational linguistics, etc. However, it is difficult to detect faults in such applications because often there is no "test oracle" to verify the correctness of the computed outputs. To help address the software quality, in this paper we present a technique for testing the implementations of machine learning classification algorithms which support such applications. Our approach is based on the technique "metamorphic testing", which has been shown to be effective to alleviate the oracle problem. Also presented include a case study on a real-world machine learning application framework, and a discussion of how programmers implementing machine learning algorithms can avoid the common pitfalls discovered in our study. We also conduct mutation analysis and cross-validation, which reveal that our method has high effectiveness in killing mutants, and that observing expected cross-validation result alone is not sufficiently effective to detect faults in a supervised classification program. The effectiveness of metamorphic testing is further confirmed by the detection of real faults in a popular open-source classification program. © 2010 Elsevier Inc. All rights reserved.

关键词： Learning algorithms

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A cooperative coevolution-based pittsburgh learning classifier system embedded with memetic feature selection

A cooperative coevolution-based pittsburgh learning classifi...

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Congress on Evolutionary Computation

作者： Yun Wen Hua Xu State Key Laboratory of Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and Technology Department of Computer Science and Technology Tsinghua University Beijing China

Given that real-world classification tasks always have irrelevant or noisy features which degrade both prediction accuracy and computational efficiency, feature selection is an effective data reduction technique showing promising performance. This paper presents a cooperative coevolution framework to make the feature selection process embedded into the classification model construction within the genetic-based machine learning paradigm. The proposed approach utilizes the divide-and-conquer strategy to manage two populations in parallel, corresponding to the selected feature subsets and the rule sets of classifier respectively, in which a memetic feature selection algorithm is adopted to evolve the feature subset population while a Pittsburgh-style learning classifier system is used to carry out the classifier evolution. These two coevolving populations cooperate with each other regarding the fitness evaluation and the final solution is obtained via collaborations between the best individuals from each population. Empirical results on several benchmark data sets chosen from the UCI repository, together with a non-parametric statistical test, validate that the proposed approach is able to deliver classifiers of better prediction accuracy and higher stability with fewer selected features, compared with the original learning classifier system. In addition, the incorporated feature selection process is shown to help improve the computational efficiency as well.

关键词： Accuracy Memetics Biological cells Genetic algorithms Genetics Machine learning Optimization

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A domain partition model approach to the online fault recovery of FPGA-based reconfigurable systems

A domain partition model approach to the online fault recove...

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作者： Shang, Lihong Zhou, Mi Hu, Yu Yang, Erfu School of Computer Science and Engineering Beihang University Beijing 100191 China Key Laboratory of Computer System and Architecture Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Department of Electronic and Electrical Engineering University of Strathclyde Glasgow Gl 1XW United Kingdom

Field programmable gate arrays (FPGAs) are widely used in reliability-critical systems due to their reconfiguration ability. However, with the shrinking device feature size and increasing die area, nowadays FPGAs can be deeply affected by the errors induced by electromigration and radiation. To improve the reliability of FPGA-based reconfigurable systems, a permanent fault recovery approach using a domain partition model is proposed in this paper. In the proposed approach, the fault-tolerant FPGA recovery from faults is realized by reloading a proper configuration from a pool of multiple alternative configurations with overlaps. The overlaps are presented as a set of vectors in the domain partition model. To enhance the reliability, a technical procedure is also presented in which the set of vectors are heuristically filtered so that the corresponding small overlaps can be merged into big ones. Experimental results are provided to demonstrate the effectiveness of the proposed approach through applying it to several benchmark circuits. Compared with previous approaches, the proposed approach increased MTTF by up to 18.87%. Copyright © 2011 The Institute of Electronics, information and Communication Engineers.

关键词： Fault tolerance

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A multi-class pattern recognition method for motor imagery EEG data

A multi-class pattern recognition method for motor imagery E...

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2011 IEEE International Conference on systems, Man, and Cybernetics, SMC 2011

作者： Fang, Yonghui Chen, Minyou Harrison, Robert F. State Key Laboratory of Power Transmission Equipment and System Security and New Technology Chongqing University Chongqing China Department of Automatic Control and Systems Engineering University of Sheffield Sheffield S1 3JD United Kingdom School of Electronic and Information Engineering Southwest University Chongqing China

ISBN: (纸本)9781457706523

The Common Spatial Patterns (CSP) algorithm is useful for calculating spatial filters for detecting event-related desynchronization (ERD) for use in ERD-based brain-computer interfaces (BCIs). However, basic CSP is a supervised algorithm suited only to two-class discrimination;it is unable to solve multiclass discrimination problems. This paper proposes a new method named the binary common spatial patterns (BCSP) algorithm to extend the basic CSP method to multi-class recognition. Our method arranges the spatial filters and Fisher classifiers in the form of a binary tree whereby N - 1 spatial filters and N - 1 Fisher classifiers are calculated for N class recognition. This is fewer than must be calculated in other methods (e.g. one-versus-rest, OVR). This makes the overall classification procedure less redundant. Simulation results show that BCSP has better performance than the OVR scheme and outperforms the three best teams in the 2008 BCI-competition. © 2011 IEEE.

关键词： Brain computer interface

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On the combinative method in obtaining angle of attack/sideslip with high bandwidth and low noise

On the combinative method in obtaining angle of attack/sides...

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Chinese Control Conference (CCC)

作者： Xiaming Yuan Jihong Zhu Hongsheng Tan Kai Liu Bo Yu State Key Laboratory of Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and Technology Department of Computer Science and Technology Tsinghua University Beijing 100084 China

Either of air data system (ADS) and strapdown inertial navigation system (SINS) can be used to get the measurement of angle of attack and sideslip, but with deficiency respectively. By use of complementary filter, the low-bandwidth measurement getting from ADS and high-bandwidth information getting from SINS could be fused to obtain the angle of attack and sideslip. Integrating the error between estimates and ADS measurement will compensate the constant bias of gyro. The dynamical characteristic of the filter is ensured by the IMU's high quality because the high-frequency part of information from SINS is preserved. The theoretical analysis and simulation result indicate that the angle of attack/sideslip can be obtained with high bandwidth and low noise through the method proposed.

关键词： Silicon compounds information filters Data systems Inertial navigation Laboratories Noise

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TCP-FIT: An improved TCP congestion control algorithm and its performance

TCP-FIT: An improved TCP congestion control algorithm and it...

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IEEE Annual Joint Conference: INFOCOM, IEEE computer and Communications Societies

作者： Jingyuan Wang Jiangtao Wen Jun Zhang Yuxing Han Key Laboratory of Pervasive Computing Ministry of Education Tsinghua National Laboratory for Information Science and Technology Department of Computer Science and Technology Tsinghua University Beijing China

ISBN: (纸本)9781424499199

The Transport Control Protocol (TCP) has been widely used by wired and wireless Internet applications such as FTP, email and HTTP. Numerous congestion algorithms have been proposed to improve the performance of TCP in various scenarios, especially for high bandwidth-delay product (BDP) and wireless networks. Although different algorithms may achieve different performance improvements under different network conditions, designing a congestion algorithm that performs well across a wide spectrum of network conditions remains a great challenge. In this paper, we propose a novel congestion control algorithm, named TCP-FIT, which could perform gracefully in both wireless and high BDP networks. The algorithm was inspired by parallel TCP, but with the important distinctions that only one TCP connection with one congestion window is established for each TCP session, and that no modifications to other layers (e.g. the application layer) of the end-to-end system need to be made. Extensive experimental results obtained using both network simulators as well as over “live” wired line, WiFi and 3G networks at different geographical locations and at different times of the day are presented. The performance of the algorithm shown in the experiment results is significantly improved as compared to other state-of-the-art algorithms, while maintaining good fairness.

关键词： Throughput Algorithm design and analysis Bandwidth Delay Wireless communication Propagation delay Protocols

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Analysis of Chinese Interrogative Intonation and its Synthesis in HMM-Based Synthesis system

Analysis of Chinese Interrogative Intonation and its Synthes...

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2011 International Conference on Internet Computing and information Services （ICICIS 2011）

作者： Yongxin Wang Jia Jia Lianhong Cai Key Laboratory of Pervasive Computing Ministry of Education Tsinghua National Laboratory for Information Science (TNList) Department of Computer Science and TechnologyTsinghua University

In the training process of HMM-based speech synthesis systems, the states of the HMM models are clustered based on the context features labeled on the training corpus.A good feature set would enable the synthesis system to generate natural prosody. In this paper, in order to synthesize interrogative intonation, we analyzed the acoustic features of the interrogative intonation and the context features that are related to the interrogative intonation in Chinese. We then expanded the feature set used conventional HMM-based speech synthesis system with interrogative intonation related features. A new speech synthesis system is trained with the proposed feature set. The analysis of train and synthesis results show that the proposed feature set is able to discriminate declarative and interrogative intonations. Perception listening test also shows the synthesis system using the expanded feature set can generate interrogative intonation.

关键词： HMM-base Synthesis,Intonation,Interrogative Sentence,Context Feature

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On the nonlinearity of some T-functions

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Journal of information and Computational science 2011年第11期8卷 2231-2237页

作者： Wang, Yan Hu, Yupu Li, Shunbo Key Laboratory of Computer Networks and Information Security Ministry of Education Xidian University Xi'an 710071 China Department of Mathematics Xi'an University of Architecture and Technology Xi'an 710055 China

Single cycle T-functions are newly proposed components in stream cipher. In order to verify if such function is suitable for cipher design, the cryptographic properties of single cycle T-function are discussed. Nonlinearity of the kth coordinate function of single cycle T-functions are studied according to the properties of single cycle T-function and the Walsh transform. Lower bounds and upper bounds are given at different situations. The results show that a single cycle T-function itself have 0 nonlinearity, but the most significant coordinate function can get high nonlinearity. © 2011 Binary information Press.

关键词： Walsh transforms

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Adaptive hypersonic flight control via back-stepping and Kriging estimation

Adaptive hypersonic flight control via back-stepping and Kri...

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IEEE International Conference on systems, Man and Cybernetics

作者： Bin Xu Fuchun Sun Shixing Wang Hao Wu Tsinghua National Laboratory of Information Science and Technology State Key Laboratory of Intelligent Technology and Systems Department of Computer Science and Technology Tsinghua University Beijing China Department of Mathematics and Computer Science Free University of Berlin Berlin Germany

This paper investigates the adaptive Kriging controller for the longitudinal dynamics of a generic hypersonic flight vehicle (HFV). For the altitude subsystem, the dynamics are transformed into the strict-feedback form where the back-stepping scheme is employed. Considering the nonlinearity of the dynamics, the nominal feedback is included in the controller while Kriging system is designed to estimate the uncertainty. With the proposed controller, the almost surely bounded stability is guaranteed. The simulation study is presented to show the effectiveness of the proposed control approach.

关键词： Estimation Uncertainty Vehicle dynamics Adaptation models Aerodynamics Equations Atmospheric modeling

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