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International Congress on Image and Signal processing, BioMedical Engineering and Informatics (CISP-BMEI)

作者： Xiaoming Liu Ting Zhu Leilei Zhai Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan China College of Computer Science and Technology Wuhan University of Science and technology Wuhan China

ISBN: (纸本)9781509037117

A new nonparallel twin support vector machine is presented in this article which combine l 2,1 -norm minimizing on both loss function and regularization which called (TWSVM_21). Our TWSVM_21 is formulated aiming to separate class more efficiently. Different from other nonparallel classifier, such as the presented TBSVM, the classifier we proposed in this paper joint l 2,1 -norm. Experiments on DDSM datasets show the feasibility and effectiveness of our TWSVM_21.

关键词： Support vector machines Feature extraction Cancer Standards Geometry Delta-sigma modulation Robustness

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Encoding-Aware Data Placement for Efficient Degraded Reads in XOR-Coded Storage Systems

Encoding-Aware Data Placement for Efficient Degraded Reads i...

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Reliable Distributed Systems

作者： Zhirong Shen Patrick P.C. Lee Jiwu Shu Wenzhong Guo College of Mathematics and Computer Science Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou China Department of Computer Science and Engineering The Chinese University of Hong Kong Department of Computer Science and Technology Tsinghua University Key Laboratory of Spatial Data Mining and Information Sharing Minstry of Education Fuzhou China

ISBN: (纸本)9781509035144

Erasure coding has been increasingly used by distributed storage systems to maintain fault tolerance with low storage redundancy. However, how to enhance the performance of degraded reads in erasure-coded storage has been a critical issue. We revisit this problem from two different perspectives that are neglected by existing studies: data placement and encoding rules. To this end, we propose an encoding-aware data placement (EDP) approach that aims to reduce the number of I/Os in degraded reads during a single failure for general XOR-based erasure codes. EDP carefully places sequential data based on the encoding rules of the given erasure code. Trace-driven evaluation results show that compared to two baseline data placement methods, EDP reduces up to 37.4% of read data on the most loaded disk and shortens up to 15.4% of read time.

关键词： Encoding Distributed databases Layout Fault tolerant systems Redundancy computer science

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A method of opinion target extraction based on syntactic structure

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ICIC Express Letters 2016年第6期10卷 1435-1441页

作者： Sun, Hongguang Yang, Yun Sun, Tieli Yang, Fengqin Feng, Guozhong School of Computer Science and Information Technology Northeast Normal University No. 5268 Renmin Street Changchun130117 China Key Laboratory of Intelligent Information Processing of Jilin Universities No. 5268 Renmin Street Changchun130117 China

Sentiment analysis is an important task in the field of natural language processing. This paper has focus on opinion target extraction of sentiment extraction in the primary task of sentiment analysis. First, the features are extracted from preprocessed results. Then, the results of feature extraction with the corresponding template will be input to the CRFs (Conditional Random Fields) module for training and recognition. In the process of feature extraction, three features are applied on the basis of existing features by analyzing syntactic structure. To select template with better performance, many comparison experiments have carried on a variety of templates with different sizes. Experimental results show our method is more effective than the baseline which can exactly extract opinion targets. © 2016 ISSN.

关键词： Sentiment analysis

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RFID indoor localization based on relational aggregation

RFID indoor localization based on relational aggregation

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International Workshop on Advanced Computational Intelligence (IWACI)

作者： Jiali Zheng Tuanfa Qin Jieming Wu Li Wan Guangxi Key Laboratory of Multimedia Communications and Network Technology (Cultivating Base) Guangxi Colleges and Universities Key Laboratory of Multimedia Communications and Information Processing School of Computer Electronics and Information Guangxi University Nanning China School of Information and Electronic Engineering WuZhou University Wuzhou China

This paper proposes a relational aggregation algorithm based on Radio Frequency Identification (RFID) to achieve accurate indoor localization. The proposed algorithm is composed of three steps: (1) exploring the relationship between reader received power and distance information then estimating Euclid distance of signal strength; (2) employing k-Nearest Neighbour algorithm to aggregate the relationship between nearest reference tag and target tag; (3) optimizing relational aggregation operator to obtain the coordinate of target tag. Simulated experiments show that the proposed algorithm can reduce mean localization error effectively and improve the accuracy of indoor localization.

关键词： Radiofrequency identification Mathematical model Antenna arrays Mobile computing Wireless communication Multimedia communication Mobile communication

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A Data Driven Approach for Resting-state EEG signal Classificition of Schizophrenia with Control Participants Using Random Matrix Theory

arXiv

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arXiv 2017年

作者： Liu, Haichun Zhang, TianHong Ye, Yumeng Pan, Changchun Yang, Genke Wang, JiJun Qiu, Robert C. Key Laboratory of System Control and Information Processing Shanghai Jiaotong University Ministry of Education of China Shanghai200240 China Department of Automation Shanghai Jiaotong University Shanghai200240 China Shanghai Key Laboratory of Psychotic Disorders Shanghai Mental Health Center Shanghai Jiaotong University School of Medicine Shanghai200030 China Brain Science and Technology Research Center Shanghai Jiao Tong University Shanghai200240 China Department of Electrical Engineering Shanghai Jiaotong University Shanghai200240 China Department of Electrical and Computer Engineering Tennessee Technological University CookevilleTN38505 United States

Resting state electroencephalogram (EEG) abnormalities in clinically high-risk individuals (CHR), clinically stable first-episode patients with schizophrenia (FES), healthy controls (HC) suggest alterations in neural oscillatory activity. However, few studies directly compare these anomalies among each types. Therefore, this study investigated whether these electrophysiological characteristics differentiate clinical populations from one another, and from non-psychiatric controls. To address this question, resting EEG power and coherence were assessed in 40 clinically high-risk individuals (CHR), 40 first-episode patients with schizophrenia (FES), and 40 healthy controls (HC). These findings suggest that resting EEG can be a sensitive measure for differentiating between clinical *** paper proposes a novel data-driven supervised learning method to obtain identification of the patients mental status in schizophrenia research. According to Marchenko-Pastur Law, the distribution of the eigenvalues of EEG data is divided into signal subspace and noise subspace. A test statistic named LES that embodies the characteristics of all eigenvalues is adopted. different classifier and different feature(LES test function) are selected for experiments, we have shown that using von Neumann Entropy as LES test function combine with SVM classifier could obtain the best average classification accuracy during three classification among HC, FES and CHR of Schizophrenia group with EEG signal. It is worth noting that the result of LES feature extraction with the highest classification accuracy is around 90% in two classification(HC compare with FES) and around 70% in three classification. Where the classification accuracy higher than 70% could be used to assist clinical diagnosis. Copyright © 2017, The Authors. All rights reserved.

关键词： Eigenvalues and eigenfunctions

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RETRACTED ARTICLE: A novel semantic smoothing method based on log-bilinear model for bayesian text classification

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Multimedia Tools and Applications 2017年第13期79卷 9661-9661页

作者： Luo, Jing Tu, Xinhui Liu, Maofu Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System College of Computer Science and Technology Wuhan University of Science and Technology Wuhan China School of Computer Science Central China Normal University Wuhan China

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A Hybrid Estimation of Distribution Algorithm with Differential Evolution for Global Optimization

A Hybrid Estimation of Distribution Algorithm with Different...

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IEEE Symposium Series on Computational Intelligence

作者： Bing Dong Aimin Zhou Guixu Zhang Shanghai Key Laboratory of Multidimensional Information Processing Department of Computer Science and Technology East China Normal University 3663 North Zhongshan Road Shanghai 200062 China

ISBN: (纸本)9781509042418

In evolutionary algorithms, it is difficult to balance the exploration and exploitation. Usually, global search is utilized to find promising solutions, and local search is beneficial to the convergence of the solutions in the population. Combing different search strategies is a promising way to take advantages of different methods. Following the idea of DE/EDA, this paper proposes another way to combine estimation of distribution algorithm and differential evolution for global optimization. The basic idea is to choose either differential evolution or estimation of distribution algorithm for generating new trial solutions. To improve the algorithm performance, a local search strategy is used as well. The new approach, named as EDA/DE-EIG, is systematically compared with two state-of-art algorithms, and the experimental results show the advantages of our method.

关键词： DE EDA global optimization eigenvector

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Hybrid discrimination method for samples classification in medicine

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International Journal of Simulation: Systems, Science and technology 2016年第27期17卷 17.1-17.9页

作者： Chen, Xiaoyu Liu, Bo Xia, Xin Yan, Dandan Yan, Wang Ma, Lizhuang Department of Information Center East Hospital Tongji University School of Medicine Jimo Road 150 Shanghai China School of Continuing Education Shanghai Jiao Tong University Shanghai200240 China Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou215006 China Department of Computer Science Shanghai Jiao Tong University Shanghai200240 China

As indispensable solutions in classification problems, discrimination for samples has been employed in medicine, and it is performed subjectively by physicians at present, which hinders the diagnosis and treatment in medicine. In this paper, a hybrid discrimination method (HDM) in medicine is proposed, which consists of two phases, including attribute selection phase and discriminant phase. In attribute selection phase, critical attributes are selected from the original features by linear correlation and C5.0 decision tree. In discriminant phase, samples are discriminated by discriminant analysis. This discrimination method is evaluated through five datasets of chronic hepatitis B, cardiac Single Proton Emission Computed Tomography (SPECT) images, Lung Cancer, Hepatitis survival and Iris plant for demonstrating its viability and applications. Finally, this proposed method has obtained the critical clinical lab indicators and discriminants related to three syndromes in CHB dataset, and it also performs well than some typical classification methods in the other four datasets for its broader applications. © 2016, UK Simulation Society. All rights reserved.

关键词： Discriminant analysis

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A clustering algorithm based on maximum entropy principle

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Journal of Physics: Conference Series 2017年第1期887卷 012064-012064页

作者： Zhao, Yang Liu, Fangai College of Information Science and Engineering Shandong Normal University Jinan Shandong 250358 China Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology Jinan Shandong 250358 China

Aiming at the shortcomings of clustering performance of many traditional text clustering methods, a clustering algorithm based on maximum entropy principle is proposed. The algorithm uses the cosine similarity measure cited in the traditional text clustering algorithm SP-Kmeans, and then introduces the maximal entropy theory to construct the maximal entropy objective function suitable for text clustering. The maximum entropy principle is introduced into the spherical K-mean text clustering Algorithm. The experimental results show that compared with DA-VMFS and SP-Kmeans algorithms, in addressing the large number of text clustering problem. The performance of CAMEP clustering algorithm is greatly improved, and has a good overall performance.

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Improved artificial bee colony algorithm and application in path planning of crowd animation

International Journal of Control and Automation

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International Journal of Control and Automation 2015年第3期8卷 53-66页

作者： Jing, Bai Hong, Liu School of Information Science and Engineering College Shandong Normal University Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology Jinan China

Crowd animation is a new and continuous challenge in computer animation. In tradition, crowd animation can be realized by key frame technology, and animators should set every character's expression, action, motion, and behavior. Therefore animators' workload by hand will increase tremendously with characters growing, which lead to difficult to realize crowd animation for low efficiency and poor global controllability, especially in path planning by appointing a target position for each individuals. In order to overcome these, an improved artificial bee colony (IM-ABC) algorithm is proposed to apply on the path planning of crowd animation. The IM-ABC is fit to simulate the crowd motion in animation based on the following two merits over the others in crowd animation. One is the rule of role transformation, which can make the rapid convergence of the result and avoid getting trapped in the local optima. The other is the realization of multi-object optimization in the process of iteration, which reaches the uniformly distributed result of swarm motion and especially fits to realize the path plan. In this paper, we simply reviews classical ABC algorithm proposed by Karaboga at the beginning. Then, in order to speed the convergence and make individuals generate paths more realistic and natural, some measures are taken to modify the classical ABC (called IM-ABC) algorithm, which include initializing colony based on chaos sequence, self-adaptively selecting the follower bees, and adaptively controlling parameters, etc. After the experiments of benchmark functions, the results confirm that the IM-ABC have better performance than the classical ABC algorithm and others. Finally, the IM-ABC algorithm is used for path planning to generate the route from the initial to the destination without collision. Through simulation experiments based on four motion models it is showed that this method can succeed generating the optimum paths with efficiency, intelligence, and natural featu

关键词： Motion planning

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