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Determination of multifractal dimensions of complex networks by means of the sandbox algorithm

Chaos 2015年第2期25卷 023103页

作者： Liu, Jin-Long Yu, Zu-Guo Anh, Vo Hunan Key Laboratory for Computation and Simulation in Science and Engineering Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan Hunan 411105 China School of Mathematical Sciences Queensland University of Technology GPO Box 2434 Brisbane Q4001 Australia

Complex networks have attracted much attention in diverse areas of science and technology. Multifractal analysis (MFA) is a useful way to systematically describe the spatial heterogeneity of both theoretical and experimental fractal patterns. In this paper, we employ the sandbox (SB) algorithm proposed by Tél et al. (Physica A 159, 155-166 (1989)), for MFA of complex networks. First, we compare the SB algorithm with two existing algorithms of MFA for complex networks: the compact-box-burning algorithm proposed by Furuya and Yakubo (Phys. Rev. E 84, 036118 (2011)), and the improved box-counting algorithm proposed by Li et al. (J. Stat. Mech.: Theor. Exp. 2014, P02020 (2014)) by calculating the mass exponents ?(q) of some deterministic model networks. We make a detailed comparison between the numerical and theoretical results of these model networks. The comparison results show that the SB algorithm is the most effective and feasible algorithm to calculate the mass exponents ?(q) and to explore the multifractal behavior of complex networks. Then, we apply the SB algorithm to study the multifractal property of some classic model networks, such as scale-free networks, small-world networks, and random networks. Our results show that multifractality exists in scale-free networks, that of small-world networks is not obvious, and it almost does not exist in random networks. © 2015 AIP Publishing LLC.

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The design and realization of a handheld terminal for industrial control purposes,based on RFID and embedded Linux

The design and realization of a handheld terminal for indust...

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2014 International Conference on Future Communication Technology and Engineering (FCTE 2014)

作者： T.Zhang Y.H.Xu Z.Q.Ye Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University

Embedded systems and computational intelligence have been greatly developed in recent *** is necessary to consider the design of a handheld terminal for industrial control purposes because there is still some work done by hand in the industrial process, and it is inconvenient and inefficient. In this paper, a design and achievement of a handheld terminal used in the industrial inspection process is proposed in order to make industrial control more efficient and safer. The handheld terminal hardware consists of ARM11 S3C6410 and RFID module together with a wireless transmission module. As for the software program, we use a QT platform in Fedora to design software programs including serial communication, RFID, and wireless transmission. We also design a useful Chinese input method. Finally, the test shows that the handheld terminal can work well in an industrial process and does have great application prospects.

关键词： The design and realization of a handheld terminal for industrial control purposes,based on RFID and embedded Linux

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Research on the transmission enhancement properties of a novel subwavelength grating structure and mechanism

Research on the transmission enhancement properties of a nov...

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2014 AASRI International Conference on Applied Engineering Sciences（ICAES2014）

作者： H.X.Chang M.Q.Li S.Zhang Y.Ding Key Laboratory of Intelligent Computing & Signal Processing Ministry of EducationAnhui University

The subwavelength metal grating is designed and simulated by using the finite difference time domain(FDTD) *** transmission characteristics of subwavelength metal grating structure are studied based on the Lossy Drude dispersive medium *** influence of grating geometry parameters on the transmission characteristics are analyzed,especially for the zero transmission point location of the *** difference between the designed and conventional gratings is that the former introduces the resonant *** show that,compared with the single-layer grating,the triple-layer grating has a better filtering effect,and the transmission spectrum peak is in excess of 82%.It concludes that the transmission peak drift is analyzed by using the waveguide Fabry-Perot(F-P) cavity resonance effect,and the zero transmission point location of the spectrum is independent of the metal layer *** influence rules provide an available reference for the design of the band-pass filters.

关键词： domain THz Research on the transmission enhancement properties of a novel subwavelength grating structure and mechanism

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A novel wideband band-stop filter based on SRR DGS

A novel wideband band-stop filter based on SRR DGS

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2014 AASRI International Conference on Applied Engineering Sciences（ICAES2014）

作者： M.Peng M.Q.Li B.Rong Y.Ding Key Laboratory of Intelligent Computing & Signal Processing Ministry of EducationAnhui University

In this paper,a novel design of the Wideband Bandstop Filter,based on Split Ring Resonators,(SRR) is *** Defect Ground Structure(DGS) is achieved by opening the SRR-shaped slot in the ground plane,and the metal cylinder is added between micro-strip line and the *** the above two methods,the wideband bandstop characteristics can be *** proposed structure is simulated by the high frequency simulation software HFSS 13.0,and the effect on the performance of a wideband Band-stop Filter by adding a metal column is *** design of Band-stop Filter structure with three cascaded SRR-shaped DGS units is *** the simulated and measured results show that the attenuation at the resonance frequency center reaches- 55 dB,and its relative bandwidth less than-10 dB is extended to 42% ranging from 5.6 GHz to 8.6 ***,the insertion loss of passband is limited to 1.2 dB.

关键词： A novel wideband band-stop filter based on SRR DGS Filter SRR

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Robust Spatial Filters on Three-Class Motor Imagery EEG Data Using Independent Component Analysis

Robust Spatial Filters on Three-Class Motor Imagery EEG Data...

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2014春季国际工程与技术大会

作者： Bangyan Zhou Xiaopei Wu Lei Zhang Zhao Lv Xiaojing Guo The Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University

Independent Component Analysis(ICA) was often used to separate movement related indepen-dent components(MRICs) from Electroencephalogram(EEG) data. However, to obtain robust spa-tial filters, complex characteristic features, which were manually selected in most cases, have been commonly used. This study proposed a new simple algorithm to extract MRICs automatically, which just utilized the spatial distribution pattern of ICs. The main goal of this study was to show the relationship between spatial filters performance and designing samples. The EEG data which contain mixed brain states(preparing, motor imagery and rest) were used to design spatial filters. Meanwhile, the single class data was also used to calculate spatial filters to assess whether the MRICs extracted on different class motor imagery spatial filters are similar. Furthermore, the spa-tial filters constructed on one subject's EEG data were applied to extract the others' MRICs. Finally, the different spatial filters were then applied to single-trial EEG to extract MRICs, and Support Vector Machine(SVM) classifiers were used to discriminate left hand、right-hand and foot imagery movements of BCI Competition IV Dataset 2a, which recorded four motor imagery data of nine subjects. The results suggested that any segment of finite motor imagery EEG samples could be used to design ICA spatial filters, and the extracted MRICs are consistent if the position of elec-trodes are the same, which confirmed the robustness and practicality of ICA used in the motor imagery Brain Computer Interfaces(MI-BCI) systems.

关键词： ICA Spatial Filter Motor Imagery BCI SVM

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Spectral clustering based on the edge betweenness dissimilarity matrix for community detection

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Journal of Information and Computational Science 2014年第11期11卷 3929-3939页

作者： Pei, Tingrui Cao, Yuxin Li, Zhetao Choi, Young-June College of Information Engineering Xiangtan University Xiangtan China Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan China Department of Information and Computer Engineering Ajou University Suwon Korea Republic of

As an important global geometric quantity, edge betweennesses can reflect the impact of corresponding edges in the entire network, which have a very strong practical significance. However, edge betweenness ignores the relationship between the vertices which connected indirectly with the edge. This paper first puts forward a dissimilarity matrix based on a novel edge betweenness, and applies it to a spectral clustering algorithm and finally, in order to detect the community structure in complex networks with this improved algorithm, we use a correction step which is based on the gravitation force of the community. This algorithm has been tested on computer-generated networks and typical real world networks. Compared to GN, PBD, GK and DA, the proposed algorithm possesses an apparent advantage. ©2014 Binary Information Press

关键词： Complex networks

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Dense Invariant Feature Based Support Vector Ranking for Person Re-identification

Dense Invariant Feature Based Support Vector Ranking for Per...

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IEEE Global Conference on signal and Information processing

作者： Shoubiao Tan Feng Zheng Ling Shao Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei 230039 China Department of Electronic and Electrical Engineering The University of Sheffield Mappin Street Sheffield S1 3JD UK Department of Computer Science and Digital Technologies Northumbria University Newcastle upon Tyne NE1 8ST UK

ISBN: (纸本)9781479975921

Recently, support vector ranking has been adopted to address the challenging person re-identification problem. However, the ranking model based on ordinary global features cannot represent the significant variation of pose and viewpoint across camera views. Thus, a novel ranking method which fuses the dense invariant features is proposed in this paper to model the variation of images across camera views. By maximizing the margin and minimizing the error score for the fused features, an optimal space for ranking has been learned. Due to the invariance of the dense invariant features and the fusion of the bidirectional features, the proposed method significantly outperforms the original support vector ranking algorithm and is competitive with state-of-the-art techniques on two challenging datasets, showing its potential for real-world person re-identification.

关键词： Person Re-identification Dense Invariant Feature Support Vector Ranking Feature Fusion

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A hybrid artificial fish-school optimization algorithm for solving the quadratic assignment problem 10

A hybrid artificial fish-school optimization algorithm for s...

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2014 10th International Conference on Natural Computation, ICNC 2014

作者： Ziqiang, Li Yi, Yang Yang, Qiwei School of Information and Engineering Xiangtan University Xiangtan411105 China Key Laboratory of Intelligent Computing Information Processing of Ministry of Education Xiangtan411105 China

ISBN: (纸本)9781479951505

The quadratic assignment problem (QAP) is a classic combinatorial optimization problem, which is of the NP-hard nature. In this paper, a hybrid artificial fish school optimization algorithm (HAFSOA) is proposed. In HAFSOA, the heuristic information is used in constructing some better initial individuals and its search ability of the global optimal solution is improved by a combination of the modified fish school optimization and differential evolution. In addition, by taking different visual distances for three behaviors: preying, clustering and following, the convergence speed of the proposed HAFSOA is speeded up. Many QAP experimental results show that the proposed HAFSOA can solve QAP better. © 2014 IEEE.

关键词： Evolutionary algorithms

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Secondary structure element alignment kernel method for prediction of protein structural classes

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Current Bioinformatics 2014年第3期9卷 253-257页

作者： Han, Guo-Sheng Yu, Zu-Guo Anh, Vo Hunan Key Laboratory for Computation and Simulation in Science and Engineering Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Hunan 411105 China School of Mathematical Sciences Queensland University of Technology GPO Box 2434 Brisbane Q 4001 Australia

In this paper, we aim at predicting protein structural classes for low-homology data sets based on predicted secondary structures. We propose a new and simple kernel method, named as SSEAKSVM, to predict protein structural classes. The secondary structures of all protein sequences are obtained by using the tool PSIPRED and then a linear kernel on the basis of secondary structure element alignment scores is constructed for training a support vector machine classifier without parameter adjusting. Our method SSEAKSVM was evaluated on two low-homology datasets 25PDB and 1189 with sequence homology being 25% and 40%, respectively. The jackknife test is used to test and compare our method with other existing methods. The overall accuracies on these two data sets are 86.3% and 84.5%, respectively, which are higher than those obtained by other existing methods. Especially, our method achieves higher accuracies (88.1% and 88.5%) for differentiating the α+ β class and the α/β class compared to other methods. This suggests that our method is valuable to predict protein structural classes particularly for low-homology protein sequences. The source code of the method in this paper can be downloaded at http://***/myphp/math/research/source/SSEAK_source_***. © 2014 Bentham Science Publishers.

关键词： Support vector machines

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Survey of community structure segmentation in complex networks

Journal of Software

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Journal of Software 2014年第1期9卷 89-93页

作者： Pei, Tingrui Zhang, Hongzhi Li, Zhetao Choi, Youngjune College of Information Engineering Xiangtan University Xiangtan China Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan China Department of Information and Computer Engineering Ajou University Suwon Korea Republic of

Community structure analysis is a hot research spot in social networks and complex networks. In order to summarize recent research progress, this paper reviews the background, the motivation, the advantages and disadvantages of existing works related to community structure discovering. A comprehensive outline was obtained by analysis of different clustering algorithms. © 2014 ACADEMY PUBLISHER.

关键词： Complex networks

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