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检索条件"机构=Anhui Province Key Lab of Software in Computer and Communication"

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NURBS model for chaotic time series

NURBS model for chaotic time series

引用

2011 3rd International Conference on computer Research and Development, ICCRD 2011

作者： Shao, Chenxi Xiao, Lipeng Department of Computer Science and Technology University of Science and Technology of China Hefei China Department of Modern Physics Nonlinear Science Center University of Science and Technology of China Hefei China Anhui Province Key Laboratory of Software in Computing and Communication Hefei China

ISBN: (纸本)9781612848372

NURBS method is extensively used in the field of Geometric Modeling. Since the original NURBS method does not have time factor, it can not display the huge advantage in the dynamics field. In this article, inspired by the segmented nature of basis functions, we propose a time factor method which can be directly applied in reconstruction of missing data, with remarkable performance in matching the original data. This work does not only give an expression of chaotic time series, but also highlights a possible way for the challenge in reconstruction of missing data. © 2011 IEEE.

关键词： Time series

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Test Case Generation Based on Invariant Extraction

Test Case Generation Based on Invariant Extraction

引用

International Conference on Wireless communications, Networking and Mobile Computing (WiCom)

作者： Fanping Zeng Qing Cao Liangliang Mao Zhide Chen Department of Computer Anhui Province Key Laboratory of Software in Computer and Communication University of Science and Technology Hefei Anhui China Department of Computer University of Science and Technology Hefei Anhui China

software testing is an effective way to find software errors. Generating a good test suite is the key. A program invariant is a property that is true at a particular program point or points. The property could reflect the program's execution over a test suite. Based on this point, we integrate the random test case generation technique and the invariant extraction technique, achieving automatic test case generation and selection. With the same invariants, compared with the traditional random test case generation technique, the experimental results show that the approach this paper describes can generate a smaller test suite.

关键词： software testing Electronic mail Automatic testing System testing Vehicle crash testing Data mining Costs Programming Automation Application software

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Research on Buffer Overflow Test Based on Invariant

Research on Buffer Overflow Test Based on Invariant

引用

International Conference on computer and Information Technology (CIT)

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

Buffer overflow (BOF) is one of the major vulnerabilities that lead to non-secure software. Testing an implementation for BOF vulnerabilities is challenging as the underlying reasons of buffer overflow vary widely. This paper presents a novel method for BOF test for ANSI C language, which uses program instrumentation and mutation test technology to test the BOF vulnerabilities, on the basis of analyzing the invariants for BOF vulnerabilities. The implementation shows that it can check the attack of BOF vulnerabilities adequately and accurately, in the circumstances of no large losses in performance.

关键词： Buffer overflow Instruments software testing Genetic mutations Monitoring Probes software libraries Runtime Information technology Performance loss

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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 ...

引用

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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Emotion recognition through integrating EEG and peripheral signals

Emotion recognition through integrating EEG and peripheral s...

引用

IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Yangyang Shu Shangfei Wang Key Lab of Computing and Communication Software of Anhui Province School of Computer Science and Technology University of Science and Technology of China Hefei China 230027

ISBN: (纸本)9781509041183

The inherent dependencies among multiple physiological signals are crucial for multimodal emotion recognition, but have not been thoroughly exploited yet. This paper propose to use restricted Boltzmann machine (RBM) to model such ***, the visible nodes of RBM represent EEG and peripheral physiological signals, and thus the connections between visible nodes and hidden nodes capture the intrinsic relations among multiple physiological signals. The RBM generates new representation from multiple physiological signals. Then, a support vector machine is adopted to recognize users' emotion states from the generated features. Furthermore, we extend the proposed fusion method for incomplete datas, since physiological signals are often corrupted due to artifacts. Specifically, we pre-train the RBM using all the complete data, then we update missing values and RBM parameters to minimize free energy of visible vectors using both complete and incomplete data. Experiments on two benchmark databases demonstrate the effectiveness of the proposed methods.

关键词： multimodal emotion recognition RBM EEG peripheral physiological signal missing data

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AN APPROACH BASED ON TSA-TREE FOR ACCURATE TIME SERIES CLASSIFICATION

AN APPROACH BASED ON TSA-TREE FOR ACCURATE TIME SERIES CLASS...

引用

2012 IEEE 2nd International Conference on Cloud Computing and Intelligence Systems

作者： Xiaoxu He Chenxi Shao School of Computer Science and Technology University of Science and Technology of China Anhui Province Key Laboratory of Software in Computing and Communication

In order to improve the performance of time series classification, we introduce a new approach of time series classification. The first step of the approach is to design a feature exaction model based on Trend and Surprise Abstraction tree （TSA-tree）. The second step of the approach is to combine the exacted global feature and 1 nearest neighbor to classify time series. The proposed approach is compared with a number of known classifiers by experiments in artificial and real-world data sets. The experimental results show it can reduce the error rates of time series classification, so it is highly competitive with previous approaches.

关键词： Feature exaction dimension reduction classification TSA-tree

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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...

引用

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 hormone based tracking strategy for wireless sensor network

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

引用

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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Evolutionary repair for evolutionary design of combinational logic circuits

Evolutionary repair for evolutionary design of combinational...

引用

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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Extracting Qualitative States from Nonlinear Time Series Using Integration of Fuzzy c-Means and Hierarchical Clustering

Extracting Qualitative States from Nonlinear Time Series Usi...

引用

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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