检索结果-内蒙古大学图书馆

26th Annual Computational Neuroscience Meeting (CNS*2017) of the Organization for Computational Neuroscience Antwerp, Belgium, July 15-20, 2017

引用

BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 59-59页

作者： [Anonymous] Indiana University Purdue University Indianapolis Indianapolis IN 46032 USA Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN 46032 USA Department of Mathematics East Carolina University Greenville NC 27858 USA Jülich Supercomputing Centre Forschungszentrum Jülich 52425 Jülich Germany Future Systems Swiss National Supercomputing Centre 8092 Zurich Switzerland User Engagement and Support Swiss National Supercomputing Centre 6900 Lugano Switzerland Institut de Neurosciences des Systèmes Aix Marseille Univ 13005 Marseille France Simulation Lab Neuroscience Forschungszentrum Jülich Jülich Germany Department of Experimental Psychology Ghent University 9000 Ghent Belgium Donders Center for Cognitive Neuroimaging Radboud University 6525HR Nijmegen The Netherlands Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO 80309 USA Department of Neurosurgery Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Neurology Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Otolaryngology Johns Hopkins School of Medicine Baltimore MD 21287 USA INSERM U968 Paris France Sorbonne Universités UPMC University Paris 06 UMR_S 968 Institut de la Vision Paris France CNRS UMR_7210 Paris France Department of Computer Architecture and Technology University of Granada (CITIC) Granada Spain Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Institut de la Vision Paris France Department of Adaptive Machine Systems Osaka University Osaka Japan Department of Computer Science University of Cergy-Pontoise Cergy-Pontoise France Department of Physics and Astronomy College of Charleston Charleston SC 29424 USA School of Physics Faculty of Science University of Sydney Sydney NSW 2006 Australia Center of Excellence for Integrative Brain Function Australian Research Council Sydney Australia Max Planck Institute for Human Cognitive and Brain Sciences Saxony Lei

来源：评论

学校读者我要写书评

暂无评论

TKLBLIIR: Detecting Twitter Paraphrases with TweetingJay 9

TKLBLIIR: Detecting Twitter Paraphrases with TweetingJay

引用

9th International Workshop on Semantic Evaluation, SemEval 2015

作者： Karan, Mladen Glavaš, Goran Šnajder, Jan Bašić, Bojana Dalbelo Vulić, Ivan Moens, Marie-Francine University of Zagreb Faculty of Electrical Engineering and Computing Text Analysis and Knowledge Engineering Lab Unska 3 Zagreb10000 Croatia KU Leuven Department of Computer Science Language Intelligence Information Retrieval Group Celestijnenlaan 200A Leuven Belgium

ISBN: (纸本)9781941643402

When tweeting on a topic, Twitter users often post messages that convey the same or similar meaning. We describe TweetingJay, a system for detecting paraphrases and semantic similarity of tweets, with which we participated in Task 1 of SemEval 2015. TweetingJay uses a supervised model that combines semantic overlap and word alignment features, previously shown to be effective for detecting semantic textual similarity. TweetingJay reaches 65.9% F1-score and ranked fourth among the 18 participating systems. We additionally provide an analysis of the dataset and point to some peculiarities of the evaluation setup. © 2015 Association for Computational Linguistics

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Photonic Crystals: Light‐Patterned Crystallographic Direction of a Self‐Organized 3D Soft Photonic Crystal (Adv. Mater. 42/2017)

引用

Advanced Materials 2017年第42期29卷

作者： Zhi‐Gang Zheng Cong‐Long Yuan Wei Hu Hari Krishna Bisoyi Ming‐Jie Tang Zhen Liu Pei‐Zhi Sun Wei‐Qiang Yang Xiao‐Qian Wang Dong Shen Yannian Li Fangfu Ye Yan‐Qing Lu Guoqiang Li Quan Li Department of Physics East China University of Science and Technology Shanghai 200237 China Liquid Crystal Institute and Chemical Physics Interdisciplinary Program Kent State University Kent OH 44242 USA National Laboratory of Solid State Microstructures Collaborative Innovation Center of Advanced Microstructures and College of Engineering and Applied Sciences Nanjing University Nanjing 210093 China Beijing National Laboratory for Condensed Matter Physics and CAS Key Laboratory of Soft Matter Physics Institute of Physics Chinese Academy of Sciences Beijing 100190 China Visual and Biomedical Optics Lab Department of Ophthalmology and Visual Science and Department of Electrical and Computer Engineering Ohio State University Columbus OH 43212 USA

来源：评论

学校读者我要写书评

暂无评论

An algorithm to optimize ECoG stimulus current patterns while constraining local current density across the entire brain

引用

Brain Stimulation 2017年第4期10卷 e38-e38页

作者： Seyhmus Guler Moritz Dannhauer Biel Roig-Solvas Alexis Gkogkidis Rob MacLeod Tonio Ball Jeffrey G. Ojemann Dana H. Brooks Computational Radiology Lab Boston Children’s Hospital and Harvard Medical School Boston MA USA Center for Integrative Biomedical Computing (CIBC) University of Utah Salt Lake City UT USA Scientific Computing Institute (SCI) University of Utah Salt Lake City UT USA B-SPIRAL Group Department of Electrical and Computer Engineering Northeastern University Boston MA USA Intracranial EEG and Brain Imaging Lab Epilepsy Center University Hospital Freiburg Freiburg Germany BrainLinks-BrainTools Cluster of Excellence and Bernstein Center Freiburg University of Freiburg Freiburg Germany Department of Neurological Surgery and the Center for Sensorimotor Neural Engineering University of Washington Seattle WA USA

来源：评论

学校读者我要写书评

暂无评论

Modeling and optimizing cortical electric stimulation

引用

Brain Stimulation 2017年第4期10卷 e29-e29页

作者： Kimia Shayestehfard Moritz Dannhauer Seyhmus Guler Alexis Gkogkidis David Caldwell Jeneva Cronin Tonio Ball Jeffrey G. Ojemann Rob MacLeod Dana H. Brooks B-SPIRAL Group Department of Electrical and Computer Engineering Northeastern University Boston MA USA Center for Integrative Biomedical Computing (CIBC) University of Utah Salt Lake City UT USA Scientific Computing Institute (SCI) University of Utah Salt Lake City UT USA Computational Radiology Lab Boston Children’s Hospital and Harvard Medical School Boston MA USA Intracranial EEG and Brain Imaging Lab Epilepsy Center University Hospital Freiburg Freiburg Germany BrainLinks-BrainTools Cluster of Excellence and Bernstein Center Freiburg University of Freiburg Freiburg Germany Department of Neurological Surgery and the Center for Sensorimotor Neural Engineering University of Washington Seattle WA USA

来源：评论

学校读者我要写书评

暂无评论

On the uniqueness of fingerprints via mining of statistically rare features

On the uniqueness of fingerprints via mining of statisticall...

引用

IEEE Conference on Technologies for Homeland Security

作者： Indira Munagani Michael S. Hsiao A. Lynn Abbott Visual and Parallel Computing Group Intel Corporation Folsom California USA The Bradley Department of Electrical and Computer Engineering Virginia Tech Virginia USA

A new method for automatically identifying rare features in fingerprints based on a combination of level 1 features and minutia-based triangular descriptors is described. A feature is considered rare if it is statistically uncommon; for example, such a rare feature should be unique among N>1000 randomly sampled prints. A fingerprint feature that is rare has higher discriminatory power when it is identified in a print (latent or otherwise), and multiple rare features in a single print can increase discriminatory power dramatically. In the case of latent matching, such information can be significant for reaching a decision. The new approach was tested experimentally using the NIST SD-27 database and an FBI database of 11,036 unique fingerprints. The results indicated that every randomly selected fingerprint from the composite database has a small set of highly distinctive statistically rare features, some of with occurrence of 1 in 1000 fingerprints.

关键词： Fingerprint recognition Databases Nonlinear distortion Feature extraction Fingers NIST

来源：评论

学校读者我要写书评

暂无评论

The 5th International Conference on Biomedical engineering and Biotechnology (ICBEB 2016) Abstracts

引用

BMC MEDICAL IMAGING 2016年第SUPPL 1期16卷 65-65页

作者： [Anonymous] Department of MRI Shandong Medical Imaging Research Institute Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China Department of Interventional Radiology Shandong Provincial Hospital Affiliated to Shandong University Jinan Shandong 250021 People’s Republic of China College of Information Science and Technology Engr. Research Center of Digitized Textile & Fashion Tech. for Ministry of Education Donghua University Shanghai 201620 China Intelligent multimedia information processing Lab College of Software Northeastern University Shenyang Liaoning Province 110004 China Institute of Biomedical and Health Engineering Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China School of Computer Science and Technology Nanjing Normal University Nanjing China Department of Electrical Engineering The City College of New York CUNY New York USA Jiangsu Key Laboratory of 3D Printing Equipment and Manufacturing Nanjing China School of Electronic Science and Engineering Nanjing University Nanjing Jiangsu 210046 China College of Engineering Nanyang Technological University Singapore 639798 Singapore School of Electronic Information Shanghai Dianji University Shanghai China School of Natural Sciences and Mathematics Shepherd University Shepherdstown WV 25443 USA Davis College of Agriculture Natural Resources and Design West Virginia University Morgantown WV 26505 USA State Key Laboratory of Millimeter Waves Southeast University Nanjing 210096 China Center of Medical Physics and Technology Hefei Institutes of Physical Science Chinese Academy of Sciences Hefei China College of Agricultural and Life Sciences University of Florida Gainesville FL 32611 USA Courant Institute of Mathematical Sciences New York University New York NY 10012 USA Translational Imaging Division & MRI Unit Columbia University and New York State Psychiatric Institute New York NY 10032 USA Guangxi Key Laboratory of Manufacturing System & Adv

来源：评论

学校读者我要写书评

暂无评论

Automated Vulnerability Analysis of AC State Estimation under Constrained False Data Injection in Electric Power Systems

Automated Vulnerability Analysis of AC State Estimation unde...

引用

IEEE Annual Conference on Decision and Control

作者： Sicun Gao Le Xie Armando Solar-Lezama Dimitrios Serpanos Howard Shrobe MIT Computer Science and Artificial Intelligence Lab Department of Electrical and Computer Engineering Texas A&M University Qatar Computing Research Institute

ISBN: (纸本)9781479978878

We introduce new methods for the automatic vulnerability analysis of power grids under false data injection attacks against nonlinear (AC) state estimation. We encode the analysis problems as logical decision problems that can be solved automatically by SMT solvers. To do so, we propose an analysis technique named "symbolic propagation," which is inspired by symbolic execution methods for finding bugs and exploits in software programs. We show that the proposed methods can successfully analyze vulnerability of AC state estimation in realistic power grid models. Our approach is generalizable towards many other applications such as power flow analysis and state estimation.

关键词： power systems State estimation Power grids Power flow analysis False Vulnerability AUTOMATIC

来源：评论

学校读者我要写书评

暂无评论

OPTISTIM – Combining computational neuroscience and electrophysiology for optimal cortical electric stimulation

引用

Brain Stimulation 2017年第4期10卷 e30-e30页

作者： Moritz Dannhauer Alexis Gkogkidis Seyhmus Guler Kimia Shayestehfard Rob MacLeod Tonio Ball Jeff Ojemann Dana Brooks Scientific Computing and Imaging Institute (SCI) University of Utah 72 Central Campus Dr Salt Lake City UT 84112 USA Center for Integrative Biomedical Computing (CIBC) University of Utah 72 Central Campus Dr Salt Lake City UT 84112 USA Electrical and Computer Engineering Northeastern University 360 Huntington Avenue Boston MA 02115 USA Intracranial EEG and Brain Imaging Lab Epilepsy Center University Hospital Freiburg Germany BrainLinks-BrainTools Cluster of Excellence University of Freiburg Germany Seattle Children’s Hospital Department of Neurological Surgery University of Washington USA

来源：评论

学校读者我要写书评

暂无评论

Variation-aware evaluation of MPSoC task allocation and scheduling strategies using statistical model checking 15

Variation-aware evaluation of MPSoC task allocation and sche...

引用

Design, Automation and Test in Europe Conference and Exhibition

作者： Mingsong Chen Daian Yue Xiaoke Qin Xin Fu Prabhat Mishra Shanghai Key Lab of Trustworthy Computing East China Normal University China Department of Computer & Information Science & Engineering University of Florida USA Department of Electrical & Computer Engineering University of Houston USA

ISBN: (纸本)9783981537048

To maximize the overall performance yield, variation-aware analysis is becoming a key step in Multiprocessor System-on-Chip (MP-SoC) Task Allocation and Scheduling (TAS). Although various approaches have been investigated to improve performance yields, most of them cannot perform quantitative comparison among existing TAS heuristics, which is important for MPSoC designers to make decisions. Based on the statistical model checker UPPAAL-SMC, we propose a framework that can automatically evaluate the performance yield of TAS strategies under time and power constraints with variations. Experimental results show that our approach can not only filter inferior strategies efficiently, but also support the automated tuning of architecture and constraint parameters to achieve the required performance yield.

关键词： Time factors Tuning Monitoring Arrays Gaussian distribution Data models Stochastic processes

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：