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International conference on Application of Information and communication Technologies (AICT)

作者： Gökhan Çelikkaya dilara Torunoğlu Gülsen Eryiğit R&D Department Huawei Technologies Co. Ltd Istanbul 34768 Turkey Istanbul Technical University Institute of Science and Technology Istanbul Turkey Dep. of Computer Engineering Istanbul Technical University Istanbul Turkey

Named Entity recognition (NEr) is a well-studied area in natural language processing (NLP) and the reported results in the literature are generally very high (~>%95) for most of the languages. Today, the focus area of most practical natural language applications (i.e. web mining, sentiment analysis, machine translation) is real natural language data such as Web2.0 or speech data. Nevertheless, the NEr task is rarely investigated on this type of data which differs severely from formal written text. In this paper, we present 3 new Turkish data sets from different domains (on this focused area; namely from Twitter, a Speech-to-Text Interface and a Hardware Forum) annotated specifically for NEr and report our first results on them. We believe, the paper draws light to the difficulty of these new domains for NEr and the possible future work.

关键词： data models Hidden Markov models Twitter Organizations Speech Media Natural language processing

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Improvement of Vegetable Preservation by Auto-Moisture-conditioning Membrane for refrigerator

Improvement of Vegetable Preservation by Auto-Moisture-Condi...

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The 5thInternational conference on Cryogenics and refrigeration ICCr 2013(第五届国际低温制冷会议)

作者： TaoL.r. YuG.X. ZhangW.Y. WangG.J. SuzukiK. Noda T. KameiK. Instutute of Cryogenic & Food Science College of Power EngineeringUniversity of Shanghai for Science and TechnologyShanghai 200093China Refrigerator R&D CenterPanasonic R&D Center Suzhou Co.LtdSuzhou 215123China Corporate Engineering DivisionAppliances CompanyPanasonic CorporationShiga 525-8555Japan Takefu PlantRengo CorporationFukui 915-0011Japan

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A Sparse Matrix Library with Automatic Selection of Iterative Solvers and Preconditioners

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Procedia computer Science 2013年 18卷 1332-1341页

作者： Takao Sakurai Takahiro Katagiri Hisayasu Kuroda Ken Naono Mitsuyoshi Igai Satoshi Ohshima Central Research Laboratory Hitachi Ltd. Yokohama Japan Information Technology Center The University of Tokyo Tokyo Japan Graduate School of Science and Engineering Ehime University Matsuyama Japan R&D Department Hitachi Asia Malaysia Kuala Lumpur Malaysia Hitachi ULSI Systems Co. Ltd. Tokyo Japan

Many iterative solvers and preconditioners have recently been proposed for linear iterative matrix libraries. Currently, library users have to manually select the solvers and preconditioners to solve their target matrix. However, if they select the wrong combination of the two, they have to spend a lot of time on calculations or they cannot obtain the solution. Therefore, an approach for the automatic selection of solvers and preconditioners is needed. We have developed a function that automatically selects an effective solver/preconditioner combination by referencing the history of relative residuals at run- time to predict whether the solver will converge or stagnate. Numerical evaluation with 50 Florida matrices showed that the proposed function can select effective combinations in all matrices. This suggests that our function can play a significant role in sparse iterative matrix computations.

关键词： Auto-tuning linear problem sparse matrix iterative solver preconditioner

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Flux-mediated epitaxy of 3C-SiC films on 4H-SiC (0001) substrates

Flux-mediated epitaxy of 3C-SiC films on 4H-SiC (0001) subst...

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2013 International Symposium on Integrated Molecular / Materials Science and engineering(2013集成分子与材料工程国际研讨会)

作者： Aomi Onuma Shingo Maruyama Shunta Harada Toru Ujihara Tomohisa Kato Kazuhisa Kurashige Hajime Okumura Yuji matsumoto National Institute of Advanced Industrial Science and Technology Hitachi Chemical Co. Ltd. Materials & Structures Laboratory Tokyo Institute of Technology R&D Partnership for Future Power Electronics Technology Department of Applied Chemistry School of Engineering Tohoku University Department of Crystalline Materials Science Graduate School of Engineering Nagoya University

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A compact Lower UWB Band PIFA for BAN Applications

A Compact Lower UWB Band PIFA for BAN Applications

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2013 International Symposium on Antennas and Propagation(2013天线与传播国际会议)

作者： Xiong-Ying Liu Chun-Ping deng Yu-Hao Fu School of Electronic and Information Engineering South China University of Technology Guangzhou 5106 MOBI Antenna Technologies(SHENZHEN) Co. Ltd.Shenzhen 518057 China Samsung Guangzhou Mobile R&D Center Guangzhou 510640 China

A compact planar inverted-F antenna (PIFA) with a simple feed structure in lower ultra-wideband (3.1~4.9 GHz) is presented for BAN (Body Area Network) applications.A tapered patch and a folded ground plane are employed to improve the narrow bandwidth characteristics of traditional PIFA, in addition, the proposed antenna is low-profile with the thickness of 7 mm and compact with the area of 60 × 22 mm2 , making it suitable for the integration in the medical *** radiation performance of the modified PWA preserves well when placed on the human body.

关键词： reflection coefficient Ultra wideband antennas Body area networks Antenna radiation patterns Wireless communication Feeds

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Erratum: 'Effects of Sc- and Zr-doped MgO layers on electron emission and discharge characteristics of alternating-current plasma display panels'

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Japanese Journal of Applied Physics 2014年第6期53卷

作者： Eun Young Jung Choon-Sang Park Tae Eun Hong Sang Ho Sohn Core Technology Lab. Corporate R&D Center Samsung SDI Co. Ltd. Cheonan Chungnam 330-300 Republic of Korea Holcombe Department of Electrical and Computer Engineering Center for Optical Materials Science and Engineering Technologies (COMSET) Clemson University Clemson SC 29634 U.S.A. Busan Center Korea Basic Science Institute Busan 610-230 Republic of Korea Department of Physics Kyungpook National University Daegu 702-701 Republic of Korea

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Predictive analysis of beer quality by correlating sensory evaluation with higher alcohol and ester production using multivariate statistics methods

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Food chemistry 2014年 161卷 376-82页

作者： Jian-Jun dong Qing-Liang Li Hua Yin Cheng Zhong Jun-Guang Hao Pan-Fei Yang Yu-Hong Tian Shi-ru Jia State Key Laboratory of Biological Fermentation Engineering of Beer (in preparation) Tsingtao Brewery Co Ltd R&D Ctr Qingdao 266101 Shandong PR China Key Laboratory of Industrial Fermentation Microbiology Ministry of Education Tianjin University of Science & Technology Tianjin 300457 PR China. Key Laboratory of Industrial Fermentation Microbiology Ministry of Education Tianjin University of Science & Technology Tianjin 300457 PR China. State Key Laboratory of Biological Fermentation Engineering of Beer (in preparation) Tsingtao Brewery Co Ltd R&D Ctr Qingdao 266101 Shandong PR China. Key Laboratory of Industrial Fermentation Microbiology Ministry of Education Tianjin University of Science & Technology Tianjin 300457 PR China Key Laboratory of Systems Bioengineering Ministry of Education P.O. Box 6888 Tianjin University Tianjin 300072 PR China. Electronic address: chzhong.tju@***. Key Laboratory of Industrial Fermentation Microbiology Ministry of Education Tianjin University of Science & Technology Tianjin 300457 PR China. Electronic address: jiashiru@***.

Sensory evaluation is regarded as a necessary procedure to ensure a reproducible quality of beer. Meanwhile, high-throughput analytical methods provide a powerful tool to analyse various flavour compounds, such as higher alcohol and ester. In this study, the relationship between flavour compounds and sensory evaluation was established by non-linear models such as partial least squares (PLS), genetic algorithm back-propagation neural network (GA-BP), support vector machine (SVM). It was shown that SVM with a radial Basis Function (rBF) had a better performance of prediction accuracy for both calibration set (94.3%) and validation set (96.2%) than other models. relatively lower prediction abilities were observed for GA-BP (52.1%) and PLS (31.7%). In addition, the kernel function of SVM played an essential role of model training when the prediction accuracy of SVM with polynomial kernel function was 32.9%. As a powerful multivariate statistics method, SVM holds great potential to assess beer quality.

关键词： Artificial neural networks Beer quality Beer sensory evaluation Partial least squares Support vector machine

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31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016): part one: National Harbor, Md, USA. 9-13 November 2016

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J Immunother Cancer 2016年第SUPPL 1期4卷 1-1页

作者： Andreas Lundqvist Vincent van Hoef Xiaonan Zhang Erik Wennerberg Julie Lorent Kristina Witt Laia Masvidal Sanz Shuo Liang Shannon Murray Ola Larsson rolf Kiessling Yumeng Mao John-William Sidhom Catherine A. Bessell Jonathan Havel Jonathan Schneck Timothy A. Chan Eliot Sachsenmeier david Woods Anders Berglund rupal ramakrishnan Andressa Sodre Jeffrey Weber roberta Zappasodi Yanyun Li Jingjing Qi Philip Wong Cynthia Sirard Michael Postow Walter Newman Henry Koon Vamsidhar Velcheti Margaret K. Callahan Jedd d. Wolchok Taha Merghoub Lawrence G. Lum Minsig Choi Archana Thakur Abhinav deol Gregory dyson Anthony Shields Cara Haymaker Marc Uemura ravi Murthy Marihella James daqing Wang Julie Brevard Catherine Monaghan Suzanne Swann James Geib Mark cornfeld Srinivas Chunduru Sudhir Agrawal Cassian Yee Jennifer Wargo Sapna P. Patel rodabe Amaria Hussein Tawbi Isabella Glitza Scott Woodman Wen-Jen Hwu Michael A. davies Patrick Hwu Willem W. Overwijk Chantale Bernatchez Adi diab Erminia Massarelli Neil H. Segal Vincent ribrag Ignacio Melero Tara C. Gangadhar Walter Urba dirk Schadendorf robert L. Ferris roch Houot Franck Morschhauser Theodore Logan Jason J. Luke William Sharfman Fabrice Barlesi Patrick A. Ott Laura Mansi Shivaani Kummar Gilles Salles Cecilia Carpio roland Meier Suba Krishnan dan Mcdonald Matthew Maurer Xuemin Gu Jaclyn Neely Satyendra Suryawanshi ronald Levy Nikhil Khushalani Jennifer Wu Jinyu Zhang Fahmin Basher Mark rubinstein Mark Bucsek Guanxi Qiao Cameron Macdonald Bonnie Hylander Elizabeth repasky Shilpak Chatterjee Anusara daenthanasanmak Paramita Chakraborty Kyle Toth Megan Meek Elizabeth Garrett-Mayer Michael Nishimura Chrystal Paulos Craig Beeson Xuezhong Yu Shikhar Mehrotra Fei Zhao Kathy Evans Christine Xiao Alisha Holtzhausen Brent A. Hanks Nicole Scharping Ashley V. Menk rebecca Moreci ryan Whetstone rebekah dadey Simon Watkins robert Ferris Greg M. delgoffe Jonathan Peled Sean devlin Anna Staffas Melissa Lumish Kori Porosnicu rodriguez Katya Ahr Miguel Perales Sergio Giralt Ying Taur Eric Pam Karolinska Institutet Stockholm Stockholms Lan Sweden Weill Cornell Medical College New York NY USA Nova Southeastern University Cell Therapy Institute Fort Lauderdale FL USA Johns Hopkins University School of Medicine Baltimore MD USA Immunology Program Johns Hopkins University School of Medicine Columbia MD USA Memorial Sloan Kettering Cancer Center New York NY USA Johns Hopkins Medical Institute Baltimore MD USA University of Rochester Monrovia MD USA NYU Langone Medical Center New York NY USA H. Lee Moffitt Cancer Center Tampa FL USA Ludwig Collaborative Laboratory Memorial Sloan Kettering Cancer Center New York NY USA Immune Monitoring Core Facility Memorial Sloan Kettering Cancer Center New York NY USA Leap Therapeutics Cambridge MA USA Department of Medicine Memorial Sloan Kettering Cancer Center New York NY USA Case Western Reserve University Cleveland OH USA Cleveland Clinic Main Campus Cleveland OH USA University of Virginia Cancer Center Charlottesville VA USA Stony Brook University Medical Center Stony Brook NY USA Karmanos Cancer Institute Detroit MI USA University of Texas MD Anderson Cancer Center Houston TX USA Idera Pharmaceuticals Inc. Cambridge MA USA Institut Gustave Roussy Villejuif Ile-de-France France Center for Applied Medical Research (CIMA) University of Navarra Pamplona Navarra Spain University of Pennsylvania Philadelphia PA USA Earle A. Chiles Research Institute Providence Cancer Center Portland OR USA Universitätsklinikum Essen Essen Nordrhein-Westfalen Germany University of Pittsburgh Pittsburgh PA USA CHU Rennes Service Hématologie Clinique and INSERM 0203 Unité d’Investigation Clinique Rennes Bretagne France Centre Hospitalier Régional Universitaire de Lille Lille Nord-Pas-de-Calais France Simon Cancer Center Indiana University Indianapolis IN USA University of Chicago School of Medicine Chicago IL USA Johns Hopkins University School of Medicine Lutherville MD USA Multidisciplinary Oncology and Therapeuti

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Numerical and experimental evaluation of laser forming process for the shape correction in ultra high strength steels

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AIP conference Proceedings 2013年第1期1567卷 954-957页

作者： J. H. Song J. Lee S. Lee E. Z. Kim N. K. Lee S. J. Park A. Chu G. A. Lee Forming Technology R&D Group Korea Institute of Industrial Technology 156 Gaetbeol-ro Yeonsu-gu Incheon 406-840 Republic of Korea Dept. of Mechanical Engineering Korea National University of Transportation 50 DaeHak-ro Chungju-si Chung Buk 380-702 Republic of Korea Shin Young Co. Ltd 440 Bonchon-Dong Yeongcheon-si Gyeong Buk 770-150 Republic of Korea

In this paper, laser forming characteristics in ultra high strength steel with ultimate strength of 1200MPa are investigated numerically and experimentally. FE simulation is conducted to identify the response related to deformation and characterize the effect of laser power, beam diameter and scanning speed with respect to the bending angle for a square sheet part. The thermo-mechanical behaviors during the straight-line heating process are presented in terms of temperature, stress and strain. An experimental setup including a fiber laser with maximum mean power of 3.0 KW is used in the experiments. From the results in this work, it would be easily adjustment the laser power and the scanning speed by controlling the line energy for a bending operation of CP1180 steel sheets.

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Two-dimensional Transmit Beamforming for MIMO radar with Sparse Symmetric Arrays

Two-Dimensional Transmit Beamforming for MIMO Radar with Spa...

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IEEE radar conference

作者： Aboulnasr Hassanien Matthew W. Morency Arash Khabbazibasmenj Sergiy A. Vorobyov Joon-Young Park Seon-Joo Kim Dept. of Electrical and Computer Engineering University of Alberta Samsung Thales Co. Ltd. Core Technology Group Agency of Defense Development The 3rd R&D Institute

ISBN: (纸本)9781467357920

Multiple-input multiple-output (MIMO) radar using one-dimensional transmit arrays has been thoroughly investigated in the literature. In this paper, we consider the MIMO radar problem in the context of two-dimensional (2d) transmit arrays. In particular, we address the problem of transmit beamforming design using 2d arrays with symmetrically missing elements. This situation is encountered in practice when some of the array elements are assigned for a different purpose, e.g., for communication purposes. We cast the transmit beamforming problem as an optimization problem that minimizes the difference between a desired transmit beampattern and the actual one while satisfying constraints such as uniform transmit power across the array elements, sidelobe level control, etc. Moreover, different transmit beams can be enforced to have rotational invariance with respect to each other, a property that enables efficient computationally cheap 2d direction finding at the receiver. Semi-definite relaxation is used to recast the optimization problem as a convex one that can be solved efficiently using the interior point optimization methods. Simulations are used to validate the proposed method.

关键词： MIMO radar Array Element TrANSMITTING Beamforming Transmitter power

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