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International Symposium on Chinese Spoken Language Processing

作者： Xiaotian Zhang Yao Qian Hai Zhao Frank K. Soong Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Shanghai Jiaotong University Shanghai China Microsoft Research Asia Beijing China

In this study, we investigate the break index labeling problem with a syntactic-to-prosodic structure conversion. The statistical relationship between the mapped syntactic tree structure and prosodic tree structure of sentences in the training set is used to generate a Synchronous Tree Substitution Grammar (STSG) which can describe the probabilistic mapping (substitution) rules between them. For a given test sentence and the corresponding parsed syntactic tree structure, thus generated STSG can convert the syntactic tree to a prosodic tree statistically. We compare the labeling results with other approaches and show the probabilistic mapping can indeed benefit break index labeling performance.

关键词： IP networks Biological system modeling Pragmatics Abstracts Syntactics

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An entropy approach to filtering for networked control systems

An entropy approach to filtering for networked control syste...

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作者： Zhang, Jianhua Du, Lilong Wang, Aiping Wang, Hong School of Control and Computer Engineering North China Electric Power University Beijing 102206 China Institute of Computing Sciences Anhui University Hefei China Control Systems Centre University of Manchester Manchester M601QD United Kingdom Key Laboratory of Integrated Automation of Process Industry Ministry of Education and Research Center of Automation Northeastern University Shenyang China

This paper is concerned with minimum error entropy filter design for non-linear Networked Control systems (NCSs) with multiple-packet transmission mechanism. Since the error of the filter in NCSs is generally non-Gaussian, the filter is designed under the information theoretic learning frame. The convergent condition of the proposed filter is established. A simulation example shows that the proposed approach is feasible and effective. Copyright © 2012 Inderscience Enterprises Ltd.

关键词： Entropy

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A science gateway getting ready for serving the international molecular simulation community 2

A science gateway getting ready for serving the internationa...

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2012 EGI Community Forum / EMI 2nd Technical Conference, EGICF-EMITC 2012

作者： Gesing, Sandra Herres-Pawlis, Sonja Birkenheuer, Georg Brinkmann, André Grunzke, Richard Kacsuk, Peter Kohlbacher, Oliver Kozlovszky, Miklos Krüger, Jens Müller-Pfefferkorn, Ralph Schäfer, Patrick Steinke, Thomas Center for Bioinformatics Department of Computer Science University of Tübingen Sand 14 Tübingen72076 Germany Department of Chemistry Ludwig-Maximilians-University Munich Butenandtstr. 5-13 München81377 Germany Paderborn Center for Parallel Computing University of Paderborn Warburger Str. 100 Paderborn33089 Germany Johannes Gutenberg-University Mainz Mainz55099 Germany Center for Information Services and High Performance Computing Technische Universität Dresden Zellescher Weg 12-14 Germany Laboratory of Parallel and Distributed Systems MTA SZTAKI Kende Street 13-17 Budapest1111 Hungary Zuse Institute Berlin Takustraße 7 Berlin14195 Germany

The project MoSGrid (Molecular Simulation Grid) has been developing a web-based science gateway supporting the community with various services for quantum chemistry, molecular modeling, and docking. Users gain access to distributed computing infrastructures (DCIs) via intuitive user interfaces for sophisticated tools, specialized workflows, and distributed repositories. Currently, the MoSGrid community consists of about 120 users from a number of fields related to chemistry and bioinformatics located in Germany. However, the underlying security infrastructure is generally applicable and can be deployed in arbitrary projects. MoSGrid intends to address the international community by participating in the EU-projects SCI-BUS (Scientific gateway Based User Support) and ER-flow (Building an European Research Community through Interoperable Workflows and Data), and collaborating with the EU-project EDGI (European Desktop Grid Initiative). © Copyright owned by the author(s) under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike Licence.

关键词： Quantum chemistry

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Reports of the AAAI 2011 conference workshops

Reports of the AAAI 2011 conference workshops

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作者： Agmon, Noa Agrawal, Vikas Aha, David W. Aloimonos, Yiannis Buckley, Donagh Doshi, Prashant Geib, Christopher Grasso, Floriana Green, Nancy Johnston, Benjamin Kaliski, Burt Kiekintveld, Christopher Law, Edith Lieberman, Henry Mengshoel, Ole J. Metzler, Ted Modayil, Joseph Oard, Douglas W. Onder, Nilufer O'Sullivan, Barry Pastra, Katerina Precup, Doina Ramachandran, Sowmya Reed, Chris Sariel-Talay, Sanem Selker, Ted Shastri, Lokendra Singh, Satinder Smith, Stephen F. Srivastava, Siddharth Sukthankar, Gita Uthus, David C. Williams, Mary-Anne Department of Computer Science University of Texas at Austin United States Center for Knowledge Driven Information Systems Infosys Labs India Adaptive Systems Section Naval Research Laboratory Washington DC United States Department of Computer Science University of Maryland College Park United States EMC's Center of Excellence in Ireland Research Europe at EMC Ireland Department of Computer Science University of Georgia United States School of Informatics University of Edinburgh United Kingdom Department of Computer Science University of Liverpool United Kingdom Department of Computer Science University of North Carolina Greensboro United States Faculty of Engineering and Information Technology University of Technology Sydney Australia VeriSign Inc. United States Department of Computer Science University of Texas at El Paso United States Machine Learning Department Carnegie Mellon University United States Massachusetts Institute of Technology Media Laboratory United States Carnegie Mellon University's Silicon Valley Campus United States Darrell W. Hughes Program for Religion and Science Dialogue Oklahoma City University United States Department of Computing Science University of Alberta Canada College of Information Studies Institute for Advanced Computer Studies University of Maryland College Park United States Department of Computer Science Michigan Technological University United States Department of Computer Science University College Cork Ireland Cognitive Systems Research Insitute Athens Greece School of Computer Science McGill University Canada Stottler Henke Inc. United States School of Computing University of Dundee United Kingdom Department of Computer Engineering Istanbul Technical University Turkey Convergence Lab Infosys Technologies Ltd. United States Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor United States Robotics Institute Carnegie Mellon University United States University of Wisconsin

The AAAI-11 workshop program was held Sunday and Monday, August 7-18, 2011, at the Hyatt Regency San Francisco in San Francisco, California USA. The AAAI-11 workshop program included 15 workshops covering a wide range of topics in artificial intelligence. The titles of the workshops were Activity Context Representation: Techniques and Languages;Analyzing Microtext;Applied Adversarial Reasoning and Risk Modeling;Artificial Intelligence and Smarter Living: The Conquest of Complexity;Artifiicial Intelligence for Data center Management and Cloud computing;Automated Action Planning for Autonomous Mobile Robots;Computational Models of Natural Argument;Generalized Planning;Human Computation;Human-Robot Interaction in Elder Care;Interactive Decision Theory and Game Theory, 2010;Language-Action Tools for Cognitive Artificial Agents: Integrating Vision, Action, and Language;Lifelong Learning from Sensorimotor Experience;Plan, Activity, and Intent Recognition;and Scalable Integration of Analytics and Visualization. This article presents short summaries of those events. Copyright © 2012, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： Human robot interaction

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Modeling the correlation between modality semantics and facial expressions

Modeling the correlation between modality semantics and faci...

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Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)

作者： Jia Jia Xiaohui Wang Zhiyong Wu Lianhong Cai Helen Meng Key Laboratory of Pervasive Computing Ministry of Education Tsinghua National Laboratory for Information Science and Technology (TNList) Department of Computer Science and Technology Tsinghua University Beijing China Tsinghua-CUHK Joint Research Center for Media Sciences Technologies and Systems Graduate School at Shenzhen Tsinghua University Shenzhen China

Facial expression plays an important role in face-to-face human-computer communication. Although considerable efforts have been made to enable computers to speak like human beings, how to express the rich semantic information through facial expression still remains a challenging problem. In this paper, we use the concept of “modality” to describe the semantic information which is related to the mood, attitude and intention. We propose a novel parametric mapping model to quantitatively characterize the non-verbal modality semantics for facial expression animation. In particular, seven-dimensional semantic parameters (SP) are first defined to describe the modality information. Then, a set of motion patterns represented with Key FAP (KFAP) is used to explore the correlations of MPEG-4 facial animation parameters (FAP). The SP-KFAP mapping model is trained with the linear regression algorithm (AMMSE) and an artificial neural network (ANN) respectively. Empirical analysis on a public facial image dataset verifies the strong correlation between the SP and KFAP. We further apply the mapping model to two different applications: facial expression synthesis and modality semantics detection from facial images. Both objective and subjective experimental results on the public datasets show the effectiveness of the proposed model. The results also indicate that the ANN method can significantly improve the prediction accuracies in both applications.

关键词： Semantics Correlation Computational modeling Mouth Facial animation Eyebrows Mood

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A Recursive Local Linear Estimator for Identification of Nonlinear ARX systems *

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IFAC Proceedings Volumes 2012年第16期45卷 1517-1522页

作者： Wen-Xiao Zhao Wei Xing Zheng Er-Wei Bai Key Laboratory of Systems and Control Academy of Mathematics and Systems Science CAS Beijing P. R. China National Center for Mathematics and Interdisciplinary Sciences CAS Beijing P. R. China School of Computing Engineering and Mathematics University of Western Sydney Penrith NSW 2751 Australia Department of Electrical and Computer Engineering University of Iowa Iowa City IA 52242 USA

In this work, we propose a recursive local linear estimator (RLLE) for identification of nonlinear autoregressive systems with exogenous inputs, along with an analysis of its strong consistency and asymptotical mean s... 详细信息

关键词： Nonlinear ARX systems recursive identification local linear estimator almost sure convergence

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Distributed dynamic load balancing for pipelined computations on heterogeneous systems

Distributed dynamic load balancing for pipelined computation...

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作者： Riakiotakis, Ioannis Ciorba, Florina M. Andronikos, Theodore Papakonstantinou, George Computing Systems Laboratory Department of Electrical and Computer Engineering National Technical University of Athens Greece Center for Information Services and High Performance Computing Technische Universität Dresden Germany Department of Informatics Ionian University Corfu Greece

One of the most significant causes for performance degradation of scientific and engineering applications on high performance computing systems is the uneven distribution of the computational work to the resources of the system. This effect, which is known as load imbalance, is even more noticeable in the case of irregular applications and heterogeneous distributed systems. This motivated the parallel and distributed computing research community to focus on methods that provide good load balancing for scientific and engineering applications running on (heterogeneous) distributed systems. Efficient load balancing and scheduling methods are employed for scientific applications from various fields, such as mechanics, materials, physics, chemistry, biology, applied mathematics, etc. Such applications typically employ a large number of computational methods in order to simulate complex phenomena, on very large scales of time and magnitude. These simulations consist of routines that perform repetitive computations (in the form of DO/FOR loops) over very large data sets, which, if not properly implemented and executed, may suffer from poor performance. The number of repetitive computations in the simulation codes is not always constant. Moreover, the computational nature of these simulations may be in fact irregular, leading to the case when one computation takes (unpredictably) more time than others. For successful and timely results, large scale simulations require the use of large scale computing systems, which often are widely distributed and highly heterogeneous. Moreover, large scale computing systems are usually shared among multiple users, which causes the quality and quantity of the available resources to be highly unpredictable. There are numerous load balancing methods in the literature for different parallel architectures. The most recent of these methods typically follow the master-worker paradigm, where a single coordinator (master) is responsible for making

关键词： Parallel architectures

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Learning from imbalanced data sets with a Min-Max modular support vector machine

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中国电气与电子工程前沿 2011年第1期6卷 56-71页

作者： Bao-Liang LU Xiao-Lin WANG Yang YANG Hai ZHAO Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and EngineeringShanghai Jiao Tong UniversityShanghai 200240China MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong UniversityShanghai 200240China Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and EngineeringShanghai Jiao Tong UniversityShanghai 200240China Department of Computer Science and Engineering Shanghai Maritime UniversityShanghai 201306China

Imbalanced data sets have significantly unequal distributions between *** between-class imbalance causes conventional classification methods to favor majority classes,resulting in very low or even nO detection of minority classes.A Min-Max modular support vector machine(M3-SVM)approaches this problem by decomposing the training input sets of the majority classes into subsets of similar size and pairing them into balanced two-class classification *** approach has the merits of using general classifiers,incorporating prior knowledge into task decomposition and parallel *** on two real-world pattern classification problems,international patent classification and protein subcellar localization,demonstrate the effectiveness of the proposed approach.

关键词： imbalanced data Min-Max modular network(M3-network) prior knowledge parallel learning support vector machine (SVM)

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Characterization of the Visible Photoluminescence from Porous a-Si:H and Porous a-Si:C:H Thin Films

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MRS Online Proceedings Library 2011年第1期420卷 831-836页

作者： M. J. Estes L. R. Hirsch S. Wichart G. Moddel Avionics Directorate Wright Laboratory USA Department of Electrical and Computer Engineering and the Optoelectronic Computing Systems Center University of Colorado Boulder USA

We report on the influence of doping, temperature, porosity, and bandgap on the visible photoluminescence properties of anodically-etched porous a-Si:H and a-Si:C:H thin films. Only boron-doped, p-type a-Si:H or a-Si:C:H samples exhibited any visible photoluminescence. We see evidence of discrete defect or impurity levels in temperature-dependent luminescence measurements. Unlike in porous crystalline silicon, we see no correlation of luminescence energy with porosity. We do, though, observe a correlation of luminescence energy with bandgap of the starting a-Si:C:H films. We discuss the implications of these observations on the nature of the luminescence mechanism.

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Enhance Top-down method with Meta-Classification for Very Large-scale Hierarchical Classification 5

Enhance Top-down method with Meta-Classification for Very La...

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5th International Joint Conference on Natural Language Processing, IJCNLP 2011

作者： Wang, Xiao-Lin Zhao, Hai Lu, Bao-Liang Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering Shanghai Jiao Tong University 800 Dong Chuan Rd. Shanghai 200240 China MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong University 800 Dong Chuan Rd. Shanghai 200240 China

ISBN: (纸本)9789744665645

Recent large-scale hierarchical classification tasks typically have tens of thousands of classes as well as a large number of samples, for which the dominant solution is the top-down method due to computational complexity. However, the top-down method suffers from accuracy deficiency, that is, its accuracy is generally lower than that of the flat approach of 1-vs-Rest. In this paper, we employ meta-classification technique to enhance the classifying procedure of the top-down method. We analyze the proposed method on the aspect of accuracy, and then test it with two real-world large-scale data sets. Our method both maintains the efficiency of the conventional top-down method and provides competitive classification accuracies. © 2011 AFNLP

关键词： Natural language processing systems

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