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2016 Conference on Empirical Methods in Natural Language processing, EMNLP 2016

作者： Zhang, Biao Xiong, Deyi Su, Jinsong Liu, Qun Ji, Rongrong Duan, Hong Zhang, Min Xiamen University Xiamen361005 China Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou215006 China ADAPT Centre School of Computing Dublin City University Ireland Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China

ISBN: (纸本)9781945626258

Implicit discourse relation recognition is a crucial component for automatic discourse-level analysis and nature language understanding. Previous studies exploit discriminative models that are built on either powerful manual features or deep discourse representations. In this paper, instead, we explore generative models and propose a variational neural discourse relation recognizer. We refer to this model as VarNDRR. VarNDRR establishes a directed probabilistic model with a latent continuous variable that generates both a discourse and the relation between the two arguments of the discourse. In order to perform efficient inference and learning, we introduce neural discourse relation models to approximate the prior and posterior distributions of the latent variable, and employ these approximated distributions to optimize a reparameterized variational lower bound. This allows VarNDRR to be trained with standard stochastic gradient methods. Experiments on the benchmark data set show that VarNDRR can achieve comparable results against state-of-the-art baselines without using any manual features. © 2016 Association for Computational Linguistics

关键词： Gradient methods

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Survey of key technologies on millimeter-wave CMOS integrated circuits

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IOP Conference Series: Materials Science and Engineering 2018年第1期351卷

作者： Fei Yu Lei Gao Lixiang Li Shuo Cai Wei Wang Chunhua Wang Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation & School of Computer and Communication Engineering Changsha University of Science and Technology Changsha 410114 China College of Information Science and Engineering Hunan University Changsha 410082 China

In order to provide guidance for the development of high performance millimeter-wave complementary metal oxide semiconductor (MMW-CMOS) integrated circuits (IC), this paper provides a survey of key technologies on MMW-CMOS IC. Technical background of MMW wireless communications is described. Then the recent development of the critical technologies of the MMW-CMOS IC are introduced in detail and compared. A summarization is given, and the development prospects on MMW-CMOS IC are also discussed.

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A subtree-based factorization of dependency parsing 26

A subtree-based factorization of dependency parsing

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26th International Conference on Computational Linguistics, COLING 2016

作者： Zhao, Qiuye Liu, Qun Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China ADAPT Centre School of Computing Dublin City University Ireland

ISBN: (纸本)9784879747020

We propose a dependency parsing pipeline, in which the parsing of long-distance projections and localized dependencies are explicitly decomposed at the input level. A chosen baseline dependency parsing model performs only on 'carved' sequences at the second stage, which are transformed from coarse constituent parsing outputs at the first stage. When k-best constituent parsing outputs are kept, a third-stage is required to search for an optimal combination of the overlapped dependency subtrees. In this sense, our dependency model is subtree-factored. We explore alternative approaches for scoring subtrees, including feature-based models as well as continuous representations. The search for optimal subset to combine is formulated as an ILP problem. This framework especially benefits the models poor on long sentences, generally improving baselines by 0.75-1.28 (UAS) on English, achieving comparable performance with high-order models but faster. For Chinese, the most notable increase is as high as 3.63 (UAS) when the proposed framework is applied to first-order parsing models. © 1963-2018 ACL.

关键词： Syntactics

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Joint learning of CNN and LSTM for image captioning

Joint learning of CNN and LSTM for image captioning

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2016 Working Notes of Conference and Labs of the Evaluation Forum, CLEF 2016

作者： Zhu, Yongqing Li, Xiangyang Li, Xue Sun, Jian Song, Xinhang Jiang, Shuqiang Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences No.6 Kexueyuan South Road Zhongguancun Beijing100190 China

In this paper, we describe the details of our methods for the participation in the subtask of the ImageCLEF 2016 Scalable Image Annotation task: Natural Language Caption Generation. The model we used is the combination of a procedure of encoding and a procedure of decoding, which includes a Convolutional neural network(CNN) and a Long Short-Term Memory(LSTM) based Recurrent Neural Network. We first train a model on the MSCOCO dataset and then fine tune the model on difierent target datasets collected by us to get a more suitable model for the natural language caption generation task. Both of the parameters of CNN and LSTM are learned together.

关键词： Long short-term memory

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Identification of pre-microRNAs by characterizing their sequence order evolution information and secondary structure graphs

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BMC bioinformatics 2018年第SUPPL 19期19卷 521页

作者： Yuanlin Ma Zuguo Yu Guosheng Han Jinyan Li Vo Anh Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education and Hunan Key Laboratory for Computation and Simulation in Science and Engineering Xiangtan University Hunan 411105 China. Key Laboratory of Intelligent Computing and Information Processing of Ministry of Education and Hunan Key Laboratory for Computation and Simulation in Science and Engineering Xiangtan University Hunan 411105 China. yuzuguo@***. School of Electrical Engineering and Computer Science Queensland University of Technology GPO Box 2434 Brisbane Q4001 Australia. yuzuguo@***. Advanced Analytics Institute Faculty of Engineering & IT University of Technology Sydney P.O Box 123 Broadway NSW 2007 Australia. School of Mathematical Sciences Queensland University of Technology GPO Box 2434 Brisbane Q4001 Australia.

BACKGROUND:Distinction between pre-microRNAs (precursor microRNAs) and length-similar pseudo pre-microRNAs can reveal more about the regulatory mechanism of RNA biological processes. Machine learning techniques have been widely applied to deal with this challenging problem. However, most of them mainly focus on secondary structure information of pre-microRNAs, while ignoring sequence-order information and sequence evolution information. RESULTS:We use new features for the machine learning algorithms to improve the classification performance by characterizing both sequence order evolution information and secondary structure graphs. We developed three steps to extract these features of pre-microRNAs. We first extract features from PSI-BLAST profiles and Hilbert-Huang transforms, which contain rich sequence evolution information and sequence-order information respectively. We then obtain properties of small molecular networks of pre-microRNAs, which contain refined secondary structure information. These structural features are carefully generated so that they can depict both global and local characteristics of pre-microRNAs. In total, our feature space covers 591 features. The maximum relevance and minimum redundancy (mRMR) feature selection method is adopted before support vector machine (SVM) is applied as our classifier. The constructed classification model is named MicroRNA -NHPred. The performance of MicroRNA -NHPred is high and stable, which is better than that of those state-of-the-art methods, achieving an accuracy of up to 94.83% on same benchmark datasets. CONCLUSIONS:The high prediction accuracy achieved by our proposed method is attributed to the design of a comprehensive feature set on the sequences and secondary structures, which are capable of characterizing the sequence evolution information and sequence-order information, and global and local information of pre-microRNAs secondary structures. MicroRNA -NHPred is a valuable method for pre-microRNAs iden

关键词： Hibert-Huang transform Network PSI-BLAST profiles Pre-microRNA SVM mRMR

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Correction: Exfoliation of amorphous phthalocyanine conjugated polymers into ultrathin nanosheets for highly efficient oxygen reduction

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Journal of Materials Chemistry A 2019年第11期7卷 6572-6572页

作者： Wenping Liu Chiming Wang Lijie Zhang Houhe Pan Wenbo Liu Jun Chen Dongjiang Yang Yanjuan Xiang Kang Wang Jianzhuang Jiang Xiangdong Yao Beijing Key Laboratory for Science and Application of Functional Molecular and Crystalline Materials Department of Chemistry University of Science and Technology Beijing Beijing 100083 China Collaborative Innovation Center for Marine Biomass Fibers Materials and Textiles of Shandong Province College of Chemical and Environmental Engineering Qingdao University Qingdao 266071 China Intelligent Polymer Research Institute ARC Centre of Excellence for Electromaterials Science AIIM Facility University of Wollongong Innovation Campus Wollongong NSW 2522 Australia State Key Laboratory of Catalytic Material and Reaction Engineering Research Institute of Petroleum Processing SINOPEC Beijing 100083 China Queensland Micro- and Nanotechnology Centre Griffith University Nathan Campus QLD 4111 Australia

Correction for ‘Exfoliation of amorphous phthalocyanine conjugated polymers into ultrathin nanosheets for highly efficient oxygen reduction’ by Wenping Liu et al., J. Mater. Chem. A, 2019, 7, 3112–3119.

Correction for ‘Exfoliation of amorphous phthalocyanine conjugated polymers into ultrathin nanosheets for highly efficient oxygen reduction’ by Wenping Liu et al., J. Mater. Chem. A, 2019, 7, 3112–3119.

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Overview of academic studies on smart care for elderly and comprehensive solution design 16

Overview of academic studies on smart care for elderly and c...

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16th International Conference on Electronic Business, ICEB 2016

作者： Lin, Zhongyan Li, Zuoyong Zheng, Dachuan Tang, Jinquan Wu, Xiaoyuan Fuzhou Digital Healthcare Industry Technology Innovation Center Minjiang University China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang University China

Due to historical reasons and urbanization progress, demographic development change has promoted China to enter an aging society and the elders' demand for medical care and health care has increased rapidly. Meanwhile, the rapid development of information technology is driving the "Smart Care for the Elderly" model which is based on the Internet and regards the internet of things as the medium which has gradually developed into a complete a system, and a series of solutions have been formed. This paper started with the analysis of China's elderly population status quo, combed academic studies on domestic and foreign "Smart Care for the Elderly" and applications in recent fifteen years and explored how to build a comprehensive "Smart Care for Elderly" solution with improved functions which incorporates such key elements as information technology and social sciences.

关键词： Social sciences computing

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Multifractal temporally weighted detrended cross-correlation analysis to quantify power-law cross-correlation and its application to stock markets

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Chaos 2017年第6期27卷 063111-063111页

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

A new method-multifractal temporally weighted detrended cross-correlation analysis (MF-TWXDFA)-is proposed to investigate multifractal cross-correlations in this paper. This new method is based on multifractal temporally weighted detrended fluctuation analysis and multifractal cross-correlation analysis (MFCCA). An innovation of the method is applying geographically weighted regression to estimate local trends in the nonstationary time series. We also take into consideration the sign of the fluctuations in computing the corresponding detrended cross-covariance function. To test the performance of the MF-TWXDFA algorithm, we apply it and the MFCCA method on simulated and actual series. Numerical tests on artificially simulated series demonstrate that our method can accurately detect long-range cross-correlations for two simultaneously recorded series. To further show the utility of MF-TWXDFA, we apply it on time series from stock markets and find that power-law cross-correlation between stock returns is significantly multifractal. A new coefficient, MF-TWXDFA cross-correlation coefficient, is also defined to quantify the levels of cross-correlation between two time series. © 2017 Author(s).

关键词： CORRELATION (Statistics) STOCK price indexes REGRESSION analysis TIME series analysis COEFFICIENTS (Statistics)

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On non-consensus motions of dynamical linear multi-agent systems

arXiv

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arXiv 2017年

作者： Cai, Ning Deng, Chun-Lin Wu, Qiu-Xuan School of Electrical Engineering Northwest University for Nationalities Lanzhou China Key Laboratory of National Language Intelligent Processing Gansu Province China School of Automation Huazhong University of Science and Technology Wuhan China School of Automation Hangzhou Dianzi University Hangzhou China

The non-consensus problems of high order linear time-invariant dynamical homogeneous multi-agent systems are concerned. Based on the conditions of consensus achievement, the mechanisms that lead to non-consensus motions are analyzed. Besides, a comprehensive classification for diverse types of non-consensus phases in accordance to the different conditions is conducted, which is jointly depending on the self-dynamics of agents, the interactive protocol and the graph topology. A series of numerical examples are demonstrated to illustrate the theoretical analysis. Copyright © 2017, The Authors. All rights reserved.

关键词： Multi agent systems

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Correction to: Internet gaming disorder: deficits in functional and structural connectivity in the ventral tegmental area-Accumbens pathway

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Brain imaging and behavior 2019年第4期13卷 1182页

作者： Ruonan Wang Min Li Meng Zhao Dahua Yu Yu Hu Corinde E Wiers Gene-Jack Wang Nora D Volkow Kai Yuan School of Life Science and Technology Xidian University Xi'an Shaanxi 710071 People's Republic of China. Engineering Research Center of Molecular and Neuro Imaging Ministry of Education Xi'an People's Republic of China. Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing School of Information Engineering Inner Mongolia University of Science and Technology Baotou Inner Mongolia 014010 People's Republic of China. National Institute on Alcoholism and Alcohol Abuse National Institutes of Health Bethesda MD 20892 USA. National Institute on Drug Abuse National Institutes of Health Bethesda MD 20892 USA. School of Life Science and Technology Xidian University Xi'an Shaanxi 710071 People's Republic of China. kyuan@***. Engineering Research Center of Molecular and Neuro Imaging Ministry of Education Xi'an People's Republic of China. kyuan@***. Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing School of Information Engineering Inner Mongolia University of Science and Technology Baotou Inner Mongolia 014010 People's Republic of China. kyuan@***. National Institute on Alcoholism and Alcohol Abuse National Institutes of Health Bethesda MD 20892 USA. kyuan@***. Guangxi Key Laboratory of Multi-Source Information Mining and Security Guangxi Normal University Guilin People's Republic of China. kyuan@***.

The original version of this article contained mistakes, and the authors would like to correct them. The correct details are given below.

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