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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Chenxi Shao Jinfeng Fan Xiaoping Chen Department of Computer Science and Technology University of Science and Technology of China Hefei Anhui China Anhui Province Key Laboratory of Software in Computing and Communication Hefei Anhui China

A novel method combined fuzzy c-means (FCM) and hierarchical agglomerative clustering (HAC) is presented to extract the qualitative states from reconstructed phase space by considering the dynamical relations of underlying nonlinear system. The qualitative state, in which all points have similar properties, is characterized by three measures, linear density, temporal reachability, and stable degree, which are defined as the criteria of merging subclasses. The time series sampled from a classic nonlinear system, Lorenz system, and electroencephalogram (EEG) signals are used to test this method. The results show that the qualitative states can be efficiently distinguished from these time series by the proposed method.

关键词： Space technology Nonlinear systems Clustering methods Fuzzy systems Merging Electroencephalography Chaotic communication Delay computer science Laboratories

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The Learning-Bargaining Algorithm Used in Unlicensed Spectrum Pre-Allocation

The Learning-Bargaining Algorithm Used in Unlicensed Spectru...

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第三届IEEE无线通讯、网络技术暨移动计算国际会议

作者： Kun Han Jinlong Li Ping Zhu Xufa Wang Anhui Province Key Laboratory of Software in Computing and Communication Department of Computer Science and Technology University of Science and Technology of China Hefei 230027 China

In the wireless network of finite spectrum resource, some communication users probably do not allocate the spectrum so that their communication should be delayed. Thus it is necessary to arrange the communication time of the systems when we allocate the communication spectrum. We propose a games learning-bargaining algorithm to pre-allocate the communication resources in the frequency-time space. Through this distributed games learning, each user obtains its communication schedule, and the result of allocation is further improved by the bargaining process. The result of this algorithm makes the bandwidth utilization achieve a quite high level and arranges the global communication time as short as possible. Comparing with the centralized algorithm of NP-hard, this distributed algorithm has low time complexity. The experiments verify the convergence of the algorithm and present the superiorities of our results to other allocation algorithms.

关键词： Cognitive Radio Spectrum Allocation Game Theory Learning-Bargaining Time Complexity.

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Nonlinear Characteristics and Qualitative Analysis of Sleep EEG

Nonlinear Characteristics and Qualitative Analysis of Sleep ...

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The 1st International Conference on Bioinformatics and Biomedical Engineering(iCBBE 2007)(首届IEEE生物信息与生物医学工程国际会议)

作者： Chenxi Shao Jinfeng Fan Shaobin Li Department of Computer Science and Technology USTCAnhui Province Key Laboratory of Software in Com Department of Computer Science and Technology USTCHefeiAnhui230027China

Correlation dimension (CD) and the largest Lyapunov exponent (LLE), which are two most important nonlinear invariant measures of nonlinear system, are adopted to characterize the complexity and stability of human brain during all sleep stages. In order to find an optimal embedding to reconstruct phase space, the C-C method and Cao's algorithm were thoroughly analyzed and implemented in efficient ***, the G-P algorithm and Kantz's algorithm are also implemented for calculation of CD and LLE respectively. Eight normal sleep EEG records are acquired from MIT-BIH sleepEDF database for this study. The values of CD and LLE for 30s epochs are calculated, and their mean and standard deviation values are evaluated as well. The results indicate that CD and LLE decrease from the waking stage to stages Ⅰ,Ⅱ and Ⅲ-Ⅳ,and they have large values during rapid eye movement (REM)sleep stage. Then, a qualitative conclusion may be drawn that during waking stage and REM sleep stage, brain activity has higher complexity and lower stability than during other stages.

关键词： nonlinear characteristic EEG qualitative analysis CD LLE

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A hormone based tracking strategy for wireless sensor network

A hormone based tracking strategy for wireless sensor networ...

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IEEE International Conference on Intelligent Computing and Intelligent Systems (ICIS)

作者： Yipeng Zhang Haifeng You Xufa Wang Key Laboratory of Software in Computing and Communication Anhui Province School of Computer Science and Technology University of Science and Technology Hefei China

In this paper, we present a hormone based tracking strategy called Hormone based Activation (HA) for mobile target tracking in wireless sensor networks inspired by the bio-endocrine system. Hormone messages are used in sensor networks to coordinate sensor nodes for mobile target tracking in a self-adaptive way. Three kinds of hormones are introduced into sensor network for mobile target tracking: Base Hormone (BH),Wakeup Hormone (WH) and Sleep Hormone (SH).Based on different hormone messages, sensor nodes can choose to be asleep or awake in order to get good tracking results with less energy consumed. Comparative experiment shows that our strategy needs fewer nodes to wake up and has a much higher usage ratio of sensor nodes than other tracking strategies.

关键词： Biochemistry Wireless sensor networks Target tracking Biosensors Intelligent sensors computer networks Mobile communication Sleep Energy efficiency communication system control

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Scheduling Model for Cognitive Radio

Scheduling Model for Cognitive Radio

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3rd International Conference on Cognitive Radio Oriented Wireless Networks and communications (CrownCom 2008)

作者： Ping Zhu Jinglong Li Xufa Wang Department of Computer Science and Technology Anhui Province Key Laboratory of Software in Computing and Communication University of Science and Technology Hefei Anhui China Department of Computer Science and Technology University of Science and Technology of China Hefei Anhui China

ISBN: (纸本)9781424423019

The priority queue model divides CR (cognitive radio) system users into primary user and secondary user. The primary user has preemptive priority over secondary user, while the same priority level users are FIFO served. This paper models the CR system based on scheduling technology. The secondary users are further divided into different priority levels. A hybrid priority dynamic policy, which indicates primary user's preemptive priority and secondary user's nonpreemptive priority, is developed to reduce spectrum switch overhead during spectrum leasing process. Theoretical analyzing shows that hybrid priority reduces the spectrum switch overhead and the hybrid priority improvement is a non-negative mono-increasing function of priority level. Based on the proposed policy, CR scheduling model is built and CR scheduling rule is provided and proved. Experimental comparison between CR scheduling and priority queue shows that CR scheduling gets a smaller weighted staying time sum than priority queue and the improvement increases as system becomes more congested.

关键词： Cognitive radio Priority queue CR schedule

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A New Anomaly Detection Method Based on Rough Set Reduction and HMM

A New Anomaly Detection Method Based on Rough Set Reduction ...

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International Conference on computer and Information Science (ACIS)

作者： Fanping Zeng Kaitao Yin Minghui Chen Xufa Wang Department of Computer University of Science and Technology Hefei Anhui China Anhui Province Key Lab of Software in Computer and Communication Hefei Anhui PR China Department of computer University of Science and Technology of China Hefei Anhui PR China

Over the past few years, anomaly detection has been an increasing concern with the rapid growth of the network security. Hidden Markov model (HMM) has been applied in various methods in intrusion detection and proved to be a good tool to model normal behaviors of privileged processes, however, one major problem with this approach is that it demands excessive computing resources and costs a long model training time, which makes it inefficient for practical intrusion detection. This paper presents a new method of bringing rough set reduction into HMM to overcome the shortcoming. The proposed approach classifies and simplifies the long observation sequence by virtue of rough set reduction, and the decision conditions obtained in rough set reduction phase could be used in further detection. The experimental results indicate that this method can promote the model training efficiency. Further-more, it is suitable for anomaly detection with high detect rate and low false alarm rate.

关键词： Hidden Markov models Intrusion detection computer networks Electronic mail software computer security Phase detection Set theory Information science Costs

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An immune based algorithm for Chinese network short text clustering

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Zidonghua Xuebao/ Acta Automatica Sinica 2009年第7期35卷 896-902页

作者： He, Tao Cao, Xian-Bin Tan, Hui School of Computer Science and Technology University of Science and Technology of China Hefei 230027 China Key Laboratory of Software in Computing and Communication Anhui Province Hefei 230027 China School of Computer Science and Technology Harbin Institute of Technology Harbin 150001 China

Network short text clustering is a major technology in network content security. Since Chinese network short text is less of keywords and full of anomalous writings, the traditional text clustering method is not directly suitable for network short text clustering. This paper presents an immune network regulation based method to cluster Chinese network short texts. First, Chinese N-gram chunks are extracted and transformed to Chinese pinyin to form the feature representation to each Chinese network short text, so as to relieve these two characteristics' bad influence on the clustering performance. Then, the network short text set is constructed as a dynamic network and an immune network learning mechanism is used to learn the similarity among short texts and therefore to gain a better clustering result. Experiments show our method can get better performance in Chinese network short text clustering, compared with traditional method such as K-means. © 2009 Acta Automatica Sinica. All rights reserved.

关键词： Cluster analysis

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Evolutionary repair for evolutionary design of combinational logic circuits

Evolutionary repair for evolutionary design of combinational...

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Congress on Evolutionary Computation

作者： Xin Zhang Wenjian Luo School of Computer Science and Technology Anhui Province key Laboratory of Software Engineering in Computing and Communication University of Science and Technology of China Hefei Anhui China

Evolutionary algorithms have been adopted to design logic circuits for many years. However, it takes too much time for evolutionary algorithms to generate circuits directly. Recently, the repair technique has been introduced into evolutionary design of the circuit to significantly decrease the time cost. And yet, the repair technique costs a lot of gate resource. In this paper, the evolutionary repair for evolutionary design of the combinational circuit is proposed, which generates the repair circuits with an evolutionary algorithm. The evolutionary repair could reduce the gate resource cost and does not spend much more time. The evolutionary repair is merged into the traditional evolutionary algorithm to form a novel evolutionary design algorithm, i.e. the erEDA. The experimental results demonstrate that the erEDA could balance the time cost and the gate resource consumption.

关键词： Maintenance engineering Logic gates Evolutionary computation Vectors Pins Adders Layout

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A Clustering System for Gene Expression Data Based upon Genetic Programming and the HS-Model

A Clustering System for Gene Expression Data Based upon Gene...

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The Third International Joint Conference on Computational Science and Optimization(第三届计算科学与优化国际大会 CSO 2010)

作者： Guiquan Liu Xiufang Jiang Lingyun Wen Key Laboratory of Software in Computing and Communication Anhui Province School of Computer Science and Technology University of Science and Technology of China Hefei Anhui 230027 China

ISBN: (纸本)9781424468126;9780769540306

Cluster analysis is a major method to study gene function and gene regulation information for there is a lack of prior knowledge for gene data. Many clustering methods existed at present usually need manual operations or predetermined parameters, which are difficult for gene data. Besides, gene data possess their own characteristics, such as large scale, high-dimension, and noise. Therefore, a systematic clustering algorithm should be proposed to effectively deal with gene data. In this paper, a novel genetic programming (GP) clustering system for gene data based on hierarchical statistical model (HS-model) is proposed. And an appropriate fitness function is also proposed in this system. This clustering system can largely eliminate the infection of data scale and dimension. The proposed GP clustering system is applied to cluster the whole intact yeast gene data without dimensionality reduction. The experimental results indicate that the algorithm is highly efficient and can effectively deal with missing values in gene dataset

关键词： genetic programming cluster analysis missing value fitness function

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A fast algorithm for finding community structure based on community closeness

A fast algorithm for finding community structure based on co...

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The Third International Joint Conference on Computational Science and Optimization(第三届计算科学与优化国际大会 CSO 2010)

作者： Xiufang Jiang Guiquan Liu Zhiting Lin Key Laboratory of Software in Computing and Communication Anhui Province School of Computer Science and Technology University of Science and Technology of China Hefei Anhui 230027 China

ISBN: (纸本)9781424468126;9780769540306

Recently, the characterization of community structures in complex networks has received a considerable amount of attentions. Effective identification of these communities or clusters is a general problem in the field of data mining. In this paper we present a /ast hierarchical agglomerative algorithm based on community closeness (FHACC) algorithm, for detecting community structure which is very efficient and faster than many other competing algorithms. FHACC tends to agglomerate such communities that share the most common vertices into larger ones. Its running time on a sparse network with n vertices and m edges is O(mk + mt), where k denotes the mean vertex degree, and t is the iteration times of community agglomeration in FHACC algorithm. The algorithm was tested on several real-world networks and proved to be high efficient and effective in community finding.

关键词： community structure complex network data mining community closeness

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