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IEEE International Conference on Data Mining Workshops (ICDM Workshops)

作者： Xiao Sun Chengcheng Li Wanyi Xu Fuji Ren Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine Hefei University of Technology Hefei China School of Information Science and Engineering Southeast University Shanghai China Faculty of Engineering University of Tokushima Tokushima Japan

ISBN: (纸本)9781479942732

This paper presents a DBN (deep belief nets) model and a multi-modality feature extraction method to extend features' dimensionalities of short text for Chinese micro blogging sentiment classification. Besides traditional features sets for document classification, comments for certain posts are also extracted as part of the micro blogging features according to the relationship between commenters and posters though constructing micro blogging social network as input information. Then, the integration of the above modality features is combined and represented as input vector for DBN. In this paper, a DBN model, which is stacked with several layers of RBM (Restricted Boltzmann Machine), is implemented to initialize the structure of neural network. The RBM layers can take probability distribution samples of original data to learn hidden structures for better feature representation. A Class RBM (Classification RBM) layer, which is stacked on top of several RBM layers, is adapted to achieve the final sentiment classification. The results demonstrate that, with proper structure and parameter, the performance of the proposed deep learning method on sentiment classification is better than state of the art surface learning models such as SVM or NB, which proves that DBN is suitable for short-length document classification with the proposed feature dimensionality extension method.

关键词： Feature extraction Semantics Visualization Training Social network services Blogs Educational institutions

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Unidirectional phase singularity in ultrathin metamaterials at exceptional points

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Physical Review A 2014年第6期89卷 065801-065801页

作者： Ming Kang Hai-Xu Cui Teng-Fei Li Jing Chen Weiren Zhu Malin Premaratne College of Physics and Materials Science Tianjin Normal University Tianjin 300387 China MOE Key Laboratory of Weak-Light Nonlinear Photonics School of Physics Nankai University Tianjin 300071 China Advanced Computing and Simulation Laboratory (AχL) Department of Electrical and Computer Systems Engineering Monash University Clayton Victoria 3800 Australia

Scattering properties of light in metamaterials are similar to those in open quantum systems. Here we propose an ultrathin tailored metamaterial designed to show that one-way zero reflection yielding to topologically stable phase dislocation is responsible for the exceptional point, one of the most important degeneracies in the non-Hermitian Hamiltonian. In order to bridge the exotic macroscopic optical phenomenon occurring in metamaterials, a phenomenological model under microscopic view is developed and good agreement with the full-blown numerical simulation is found. Our investigation uncovers the capabilities of metamaterials to exhibit extreme optical properties and to provide us with many potential applications such as the suppression of undesired scattering signals in the spectral band ranging from microwaves to visible light.

关键词： QUANTUM phase transitions LIGHT -- Scattering TOPOLOGY METAMATERIALS PHENOMENOLOGICAL theory (Physics) MICROWAVES

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Corrections to “A $\hbox{0.02 mm}^{2}$ 59.2 dB SFDR 4th-Order SC LPF With 0.5-to-10 MHz Bandwidth Scalability Exploiting a Recycling SC-Buffer Biquad” [Sep 15 1988-2001]

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IEEE Journal of Solid-State Circuits 2015年第10期50卷 2464-2464页

作者： P. V. Ananda Mohan Yaohua Zhao Pui-In Mak Rui P. Martins Franco Maloberti Centre for Development of Advanced Computing Bangalore Faculty of Science and Technology State-Key Laboratory of Analog and Mixed-Signal VLSI Macao China Universidade de Lisboa Instituto Superior Técnico Portugal Department of Electrical Engineering Universitádegli Studi di Pavia Pavia Italy

Presents corrections to the paper, “A 0.02 mm 59.2 dB SFDR 4th-order SC with 0.5-to-10 MHz bandwidth scalability exploiting a recycling SC-buffer biquad,” (Zhao, Y., et al), IEEE J. Solid-State Circuits, vol. 50, no... 详细信息

关键词： CMOS integrated circuits Q-factor Low-pass filters Long Term Evolution

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β decay of semi-magic Cd130: Revision and extension of the level scheme of In130

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Physical Review C 2016年第2期94卷 024303-024303页

作者： A. Jungclaus H. Grawe S. Nishimura P. Doornenbal G. Lorusso G. S. Simpson P.-A. Söderström T. Sumikama J. Taprogge Z. Y. Xu H. Baba F. Browne N. Fukuda R. Gernhäuser G. Gey N. Inabe T. Isobe H. S. Jung D. Kameda G. D. Kim Y.-K. Kim I. Kojouharov T. Kubo N. Kurz Y. K. Kwon Z. Li H. Sakurai H. Schaffner Y. Shimizu K. Steiger H. Suzuki H. Takeda Zs. Vajta H. Watanabe J. Wu A. Yagi K. Yoshinaga G. Benzoni S. Bönig K. Y. Chae L. Coraggio J.-M. Daugas F. Drouet A. Gadea A. Gargano S. Ilieva N. Itaco F. G. Kondev T. Kröll G. J. Lane A. Montaner-Pizá K. Moschner D. Mücher F. Naqvi M. Niikura H. Nishibata A. Odahara R. Orlandi Z. Patel Zs. Podolyák A. Wendt Instituto de Estructura de la Materia CSIC E-28006 Madrid Spain GSI Helmholtzzentrum für Schwerionenforschung GmbH 64291 Darmstadt Germany RIKEN Nishina Center RIKEN 2-1 Hirosawa Wako-shi Saitama 351-0198 Japan National Physical Laboratory NPL Teddington Middlesex TW11 0LW United Kingdom Department of Physics University of Surrey Guildford GU2 7XH United Kingdom LPSC Université Joseph Fourier Grenoble 1 CNRS/IN2P3 Institut National Polytechnique de Grenoble F-38026 Grenoble Cedex France Department of Physics Tohoku University Aoba Sendai Miyagi 980-8578 Japan Departamento de Física Teórica Universidad Autónoma de Madrid E-28049 Madrid Spain Department of Physics University of Tokyo Hongo 7-3-1 Bunkyo-ku 113-0033 Tokyo Japan School of Computing Engineering and Mathematics University of Brighton Brighton BN2 4GJ United Kingdom Physik Department E12 Technische Universität München D-85748 Garching Germany Institut Laue-Langevin B.P. 156 F-38042 Grenoble Cedex 9 France Department of Physics Chung-Ang University Seoul 156-756 Republic of Korea Rare Isotope Science Project Institute for Basic Science Daejeon 305-811 Republic of Korea Department of Nuclear Engineering Hanyang University Seoul 133-791 Republic of Korea School of Physics and State key Laboratory of Nuclear Physics and Technology Peking University Beijing 100871 China MTA Atomki P.O. Box 51 Debrecen H-4001 Hungary Department of Physics Osaka University Machikaneyama-machi 1-1 Osaka 560-0043 Toyonaka Japan Department of Physics Faculty of Science and Technology Tokyo University of Science 2641 Yamazaki Noda Chiba Japan INFN Sezione di Milano via Celoria 16 I-20133 Milano Italy Institut für Kernphysik Technische Universität Darmstadt D-64289 Darmstadt Germany Department of Physics Sungkyunkwan University Suwon 440-746 Republic of Korea Istituto Nazionale di Fisica Nucleare Complesso Universitario di Monte S. Angelo I-80126 Napoli Italy CEA DAM DIF 91297 Arpajon cedex France

The β decay of the semi-magic nucleus Cd130 has been studied at the RIBF facility at the RIKEN Nishina Center. The high statistics of the present experiment allowed for a revision of the established level scheme of In130 and the observation of additional β feeding to high-lying core-excited states in In130. The experimental results are compared to shell-model calculations employing a model space consisting of the full major N=50–82 neutron and Z=28–50 proton shells and the NA-14 interaction, and good agreement is found.

关键词： Beta decay Electromagnetic transitions Energy levels & level densities Nuclear structure & decays Shell model 90 ≤ A ≤ 149

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Fractal and complex network analyses of protein molecular dynamics

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Physica A: Statistical Mechanics and its Applications 2014年 416卷 21-32页

作者： Yuan-Wu Zhou Jin-Long Liu Zu-Guo Yu Zhi-Qin Zhao Vo Anh Hunan Key Laboratory for Computation and Simulation in Science and Engineering Xiangtan University Xiangtan Hunan 411105 China Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education Xiangtan University Xiangtan Hunan 411105 China Civil Construction Engineering Department Guangxi University of Science and Technology Liuzhou 545006 China School of Mathematical Sciences Queensland University of Technology GPO Box 2434 Brisbane Q4001 Australia

Based on protein molecular dynamics, we investigate the fractal properties of energy, pressure and volume time series using the multifractal detrended fluctuation analysis (MF-DFA) and the topological and fractal properties of their converted horizontal visibility graphs (HVGs). The energy parameters of protein dynamics we considered are bonded potential, angle potential, dihedral potential, improper potential, kinetic energy, Van der Waals potential, electrostatic potential, total energy and potential energy. The shape of the h ( q ) curves from MF-DFA indicates that these time series are multifractal. The numerical values of the exponent h ( 2 ) of MF-DFA show that the series of total energy and potential energy are non-stationary and anti-persistent; the other time series are stationary and persistent apart from series of pressure (with H ≈ 0.5 indicating the absence of long-range correlation). The degree distributions of their converted HVGs show that these networks are exponential. The results of fractal analysis show that fractality exists in these converted HVGs. For each energy, pressure or volume parameter, it is found that the values of h ( 2 ) of MF-DFA on the time series, exponent λ of the exponential degree distribution and fractal dimension d B of their converted HVGs do not change much for different proteins (indicating some universality). We also found that after taking average over all proteins, there is a linear relationship between 〈 h ( 2 ) 〉 (from MF-DFA on time series) and 〈 d B 〉 of the converted HVGs for different energy, pressure and volume.

关键词： Protein molecular dynamics Multifractal detrended fluctuation analysis Horizontal visibility graph Fractal analysis Degree distribution

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NEW WORD DETECTION AND EMOTIONAL TENDENCY JUDGMENT BASED ON MIXED MODEL

NEW WORD DETECTION AND EMOTIONAL TENDENCY JUDGMENT BASED ON ...

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2014 IEEE 3rd International Conference on Cloud computing and Intelligence Systems

作者： Xiao Sun Chongyuan Sun Fuji Ren Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer and InformationHefei University of Technology Faculty of Engineering University of Tokushima2-1 Minami-JosanjimaTokushima 770-8506Japan

ISBN: (纸本)9781467369541

The paper studies a new method for Chinese new word detection and emotional tendency judgment based on mixed model and proposes a new word generation *** we construct conditional random fields(CRFs) to recognize the new words,lead-in features based on character combined with the crowd sourcing network *** then express word as a word vector based on neural network language model(NNLM) to judge the new word emotional *** experimental results show that the method can improve the precision and recall of the new word detection with a good system performance,and it also provides a new way for forecasting the public mood.

关键词： New Word Detection Conditional Random Fields Emotional Tendency Judgment Neural Network Language Model

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Dynamic facial expression recognition based on K-order emotional intensity model

Dynamic facial expression recognition based on K-order emoti...

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IEEE International Conference on Robotics and Biomimetics

作者： Changqin Quan Yao Qian Fuji Ren Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine Hefei University of Technology Hefei China P.R. The Japan Federation of Engineering Societies University of Tokushima Shinkura-cho Tokushima Japan

ISBN: (纸本)9781479973989

With the development of artificial intelligence and pattern recognition, facial expression recognition plays a more and more important role in intelligent human-computer interaction. In this paper, we present a model named K-order emotional intensity model (K-EIM) which is based on K-Means clustering. Different from other related works, the proposed approach can quantify emotional intensity in an unsupervised way. And then the output from K-EIM is encoded. The coding results are used for the dynamic facial expression recognition. The experiment is conducted on Cohn-Kanade facial expression database and the support vector machine classifier is used for facial expression classification. This method achieved a dynamic facial expression recognition accuracy of 88.32% which suggest that the proposed method shows better performance and proves its validity. Moreover, effect of different segments of emotional intensity is also discussed in the paper.

关键词： Face recognition Encoding Accuracy Emotion recognition Principal component analysis Training Feature extraction

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MODELING BLOG USER FOR CHINESE MICRO-BLOG SENTIMENT CLASSIFICATION WITH FUZZY SVM

MODELING BLOG USER FOR CHINESE MICRO-BLOG SENTIMENT CLASSIFI...

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2014 IEEE 3rd International Conference on Cloud computing and Intelligence Systems

作者： Xiao Sun Chengcheng Li Fuji Ren Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer and InformationHefei University of Technology Faculty of Engineering University of Tokushima2-1 Minami-JosanjimaTokushima 770-8506Japan

ISBN: (纸本)9781467369541

Micro-blog is easily posted and communicated because of its short text ***,its brevity limits the feature *** paper presents a blogger modeling method for Chinese micro-blog sentiment *** paper would adopt a multidimensional strategy to accomplish the feature extraction *** with traditional feature extraction methods and combined with the interactive property of blog,the blog comment will be considered as the performance characteristic of micro-blog emotion *** comes to comments content and the relationship between commentators and micro-bloggers while it extracts the micro blogging text *** last,the paper adopts fuzzy SVM model to reduce the sensation of noise points and outliers on classification *** results demonstrate the effectiveness of the multidimensional feature extraction method on sentiment classification and the classify effect of fuzzy SVM is better than SVM.

关键词： sentiment classification multidimensional fuzzy SVM

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MINING THE IMPACT OF SOCIAL NEWS ON THE EMOTIONS OF USERS BASED ON DEEP MODEL

MINING THE IMPACT OF SOCIAL NEWS ON THE EMOTIONS OF USERS BA...

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2014 IEEE 3rd International Conference on Cloud computing and Intelligence Systems

作者： Xiao Sun Fei Gao Fuji Ren Anhui Province Key Laboratory of Affective Computing and Advanced Intelligent Machine School of Computer and InformationHefei University of Technology Faculty of Engineering University of Tokushima2-1 Minami-JosanjimaTokushima 770-8506Japan

ISBN: (纸本)9781467369541

In this paper,Deep Belief Nets(DBN) model and Support Vector Machine(SVM) are used to mine the features hidden in social news,which can influence the emotions of *** feature selection methods for text modeling are used to build the input vectors of DBN,with the purpose of keeping the text information to the greatest *** take advantage of the deep features abstracted by DBN to build social news text *** the same time,three optimal models are used as inputs of SVM to train and classify the social *** get a conclusion that DBN not only reduces the dimension of original features,but also makes the abstracted features with more text information and shows better performance in determining the influence on people' s emotions by social news.

关键词： Deep Belief Network(DBN) Restricted Boltzmann Machine(RBM) Impacts on Emotion Social News

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Research on aggregated multicast based on wide-sense circuit tree

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2013 3rd International Symposium on Chemical engineering and Material Properties, ISCEMP 2013

作者： Zhang, Xiao Bo Lan, Ju Long Chen, Yue Li, Chao Ling State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou 450000 China China National Digital Switching System Engineering and Technological Research Center Zhengzhou 450000 China

ISBN: (纸本)9783037858363

To achieve the scalability and Quality of Service (QoS) of multicast service, a Wide-Sense Circuit Tree (WSCT) based on Aggregated Multicast Tree is proposed. By aggregating multicast traffics of the same class, WSCT can efficiently reduce the forwarding states of routing nodes and then improve the multicast scalability. By using Wide-Sense Circuit (WSC) to transfer data packages, MSCT can also improve the package forwarding efficiency and provide QoS. © (2013) Trans Tech Publications, Switzerland.

关键词： Quality of service

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