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International Conference on Machine Learning and Applications (ICMLA)

作者： Kamran Kowsari Donald E. Brown Mojtaba Heidarysafa Kiana Jafari Meimandi Matthew S. Gerber Laura E. Barnes Department of Computer Science University of Virginia Charlottesville VA USA Data Science Institute University of Virginia Charlottesville VA USA Department of System and Information Engineering University of Virginia Charlottesville VA USA

Increasingly large document collections require improved information processing methods for searching, retrieving, and organizing text. Central to these information processing methods is document classification, which has become an important application for supervised learning. Recently the performance of traditional supervised classifiers has degraded as the number of documents has increased. This is because along with growth in the number of documents has come an increase in the number of categories. This paper approaches this problem differently from current document classification methods that view the problem as multi-class classification. Instead we perform hierarchical classification using an approach we call Hierarchical Deep Learning for Text classification (HDLTex). HDLTex employs stacks of deep learning architectures to provide specialized understanding at each level of the document hierarchy.

关键词： Machine learning Support vector machines Computer architecture Kernel Mathematical model Recurrent neural networks

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Exploiting Minipage-Level Mapping to Improve Write Efficiency of NAND Flash

Exploiting Minipage-Level Mapping to Improve Write Efficienc...

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International Conference on Networking, Architecture, and Storage (NAS)

作者： Hao Lv You Zhou Fei Wu Weijun Xiao Xubin He Zhonghai Lu Changsheng Xie Shenzhen research institute of Huazhong University of Science and Technology Shenzhen China Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology Wuhan China Ministry of Education Key Laboratory of Data Storage System Wuhan China Department of Electrical and Computer Engineering Virginia Commonwealth University Richmond USA College of Science and Technology Temple University Philadelphia USA School of Information and Communication Technology KTH Royal Institute of Technology Stockholm Sweden

ISBN: (纸本)9781538683682

Pushing NAND flash memory to higher density, manufacturers are aggressively enlarging the flash page size. However, the sizes of I/O requests in a wide range of scenarios do not grow accordingly. Since a page is the unit of flash read/write operations, traditional flash translation layers (FTLs) maintain the page mapping regularity. Hence, small random write requests become common, leading to extensive partial logical page writes. This write inefficiency significantly degrades the performance and increases the write amplification of flash storage. In this paper, we first propose a configurable mapping layer, called minipage, whose size is set to match I/O request sizes. The minipage-level mapping provides better flexibility in handling small writes at the cost of sequential read performance degradation and a larger mapping table. Then, we propose a new FTL, called PM-FTL, that exploits the minipage-level mapping to improve write efficiency and utilizes the page-level mapping to reduce the costs caused by the minipage-level mapping. Finally, trace-driven simulation results show that compared to traditional FTLs, PM-FTL reduces the write amplification and flash storage response time by an average of 33.4% and 19.1%, up to 57.7% and 34%, respectively, under 16KB flash pages and 4KB minipages.

关键词： Flash memories Random access memory Metadata Electronic mail Time factors Memory management Market research

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Case study: Approximations of the bessel function

arXiv

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arXiv 2017年

作者： Karachalios, D.S. Gosea, I.V. Zhang, Q. Antoulas, A.C. Data-Driven System Reduction and Identification Group Max Planck Institute for Dynamics of Complex Technical Systems Magdeburg Germany Department of Electrical and Computer Engineering Rice University Houston United States

The purpose of this note is to compare various approximation methods as applied to the inverse of the Bessel function of the first kind J01(s), in a given domain of the complex plane.30E10, 03C40, 65E99 Copyright ... 详细信息

关键词： Bessel functions

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HDLTex: Hierarchical Deep Learning for Text Classification

arXiv

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arXiv 2017年

作者： Kowsari, Kamran Brown, Donald E. Heidarysafa, Mojtaba Meimandi, Kiana Jafari Gerber, Matthew S. Barnes, Laura E. Department of Computer Science University of Virginia CharlottesvilleVA United States Department of System and Information Engineering University of Virginia CharlottesvilleVA United States Data Science Institute University of Virginia CharlottesvilleVA United States

关键词： Deep neural networks

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Learning from learning machines: A new generation of AI technology to meet the needs of science

arXiv

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arXiv 2021年

作者： Pion-Tonachini, Luca Bouchard, Kristofer Martin, Hector Garcia Peisert, Sean Holtz, W. Bradley Aswani, Anil Dwivedi, Dipankar Wainwright, Haruko Pilania, Ghanshyam Nachman, Benjamin Marrone, Babetta L. Falco, Nicola Prabhat Arnold, Daniel Wolf-Yadlin, Alejandro Powers, Sarah Climer, Sharlee Jackson, Quinn Carlson, Ty Sohn, Michael Zwart, Petrus Kumar, Neeraj Justice, Amy Tomlin, Claire Jacobson, Daniel Micklem, Gos Gkoutos, Georgios V. Bickel, Peter J. Cazier, Jean-Baptiste Müller, Juliane Webb-Robertson, Bobbie-Jo Stevens, Rick Anderson, Mark Kreutz-Delgado, Ken Mahoney, Michael W. Brown, James B. Pattern Computer Inc. Friday HarborWA98250 United States Biosciences Area Lawrence Berkeley National Lab BerkeleyCA94803 United States Computational Research Division Lawrence Berkeley National Lab BerkeleyCA94720 United States Helen Wils Neuroscience Institute Redwood Center for Theoretical Neuroscience Uc Berkeley BerkeleyCA94720 United States Doe Agile BioFoundry Lawrence Berkeley National Laboratory BerkeleyCA94803 United States Joint BioEnergy Institute Lawrence Berkeley National Laboratory BerkeleyCA94803 United States Bcam Basque Center for Applied Mathematics Bilbao48009 Spain Computer Science University of California Davis DavisCA95616 United States Cenic La MiradaCA90638 United States Health Informatics University of California Davis School of Medicine SacramentoCA95817 United States Berkeley Institute for Data Science University of California Berkeley BerkeleyCA94720 United States Industrial Engineering and Operations Research University of California Berkeley BerkeleyCA94720 United States Environmental & Earth Sciences Area Lawrence Berkeley National Laboratory BerkeleyCA94803 United States Nuclear Engineering University of California Berkeley BerkeleyCA94720 United States Materials Science and Technology Division Los Alamos National Laboratory Los AlamosNM87545 United States Physics Division Lawrence Berkeley National Lab BerkeleyCA94720 United States Bioscience Division Los Alamos National Laboratory Los AlamosNM87545 United States Earth and Environmental Sciences Area Lawrence Berkeley National Lab BerkeleyCA94803 United States Energy Technologies Area Lawrence Berkeley National Lab BerkeleyCA94803 United States Computing and Computational Sciences Oak Ridge National Laboratory Oak RidgeTN37831 United States Industrial & Systems Engineering The University of Tennessee KnoxvilleTN37996 United States Department of Computer Science University of Missouri-Saint Louis St. LouisMO63121 United

We outline emerging opportunities and challenges to enhance the utility of AI for scientific discovery. The distinct goals of AI for industry versus the goals of AI for science create tension between identifying patterns in data versus discovering patterns in the world from data. If we address the fundamental challenges associated with "bridging the gap" between domain-driven scientific models and data-driven AI learning machines, then we expect that these AI models can transform hypothesis generation, scientific discovery, and the scientific process itself. © 2021, CC BY.

关键词： Learning systems

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Autonomic Resource Management for Program Orchestration in Large-Scale data Analysis

Autonomic Resource Management for Program Orchestration in L...

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International Symposium on Parallel and Distributed Processing (IPDPS)

作者： Masahiro Tanaka Kenjiro Taura Kentaro Torisawa Data-driven Intelligent System Research Center (DIRECT) National Institute of Information and Communications Technology (NICT) Hikaridai Seika-cho Japan Department of Information and Communication Engineering University of Tokyo Tokyo Japan

Large-scale data analysis applications are becoming more and more prevalent in a wide variety of areas. These applications are composed of many currently available programs called analysis components. Thousands of analysis component processes are orchestrated on many compute nodes. This paper proposes a novel self-tuning framework for optimizing an application's throughput in large-scale data analysis. One challenge is developing efficient orchestration that takes into account the diversity of analysis components and the varying performances of compute nodes. In our previous work, we achieved such an orchestration to a certain degree by introducing our own middleware, which wraps each analysis component as a remote procedure call (RPC) service. The middleware also pools the processes to reduce startup overhead, which is a serious obstacle to achieving high throughput. This work tackles the remaining task of tuning the size of the analysis components' process pools to maximize the application's throughput. This is challenging because analysis components differ drastically in turnaround times and memory footprints. The size of the process pool for each type of analysis component should be set by giving consideration to these properties as well as the constraints on both the memory capacity and the processor core counts. In this work, we formulate this task as a linear programming problem and obtain the optimal pool sizes by solving it. Compared to our previous work, we significantly improved the scalability of our framework by reformulating the performance model to work on hundreds of heterogeneous nodes. We also extended the service allocation mechanism to manage the computational load on each compute node and reduce communication overhead. The experimental results show that our approach is scalable to thousands of analysis component processes running on 200 compute nodes across three clusters. Moreover, our approach significantly reduces memory footprint.

关键词： Throughput Resource management data analysis Middleware Analytical models Support vector machines Tuning

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Acoustic and Kinematic Examination of Dysarthria in Cantonese Patients of Parkinson’s Disease

Acoustic and Kinematic Examination of Dysarthria in Cantones...

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International Symposium on Chinese Spoken Language Processing

作者： Yue Sun Manwa L. Ng Chongyuan Lian Lan Wang Feng Yang Nan Yan College of Big Data and Information Engineering Guizhou University Guiyang China Speech Science Laboratory University of Hong Kong Hong Kong China CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China Department of Speech Therapy Shenzhen Children’s Hospital Shenzhen China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Instimtes of Advanced Technology Chinese Academy of Sciences Shenzhen China

ISBN: (纸本)9781538656280;9781538656273

Hypokinetic dysarthria is one of the core symptoms of Parkinson's disease, characterized by reduced loudness, slurred speech and distorted consonant productions. Dopaminergic medication for Parkinson's disease (PD) has been proven to be effective in treating limb and gross motor movement problems. However, the literature sees contradictory findings regarding dopaminergic effects on speech problems associated with PD. Previous perceptual and acoustic studies of PD hypokinetic dysarthria mostly involved heterogeneous population and variations of speech tasks which complicated data interpretation. Also, the lack of kinematic data limited our understanding of the details of articulation errors associated with PD, as well as the medication effects. Electromagnetic articulography (EMA) enabled the examination of PD articulatory patterns with high degree of accuracy and safety. The aim of the present study was to address these inconsistencies by providing an integrative description of basic kinematic and acoustic parameters of speech production about the dopaminergic effect on early PD speech by using EMA. The results revealed a significant improvement of articulatory function on dopaminergic effects for PD speech, evidenced by increased vowel space, the velocity and accelerated velocity initiation and coordination of articulation during bilabial or alveolar productions.

关键词： Kinematics Acoustics Auditory system Sun Parameter extraction Schedules Lips

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Author Correction: The power of genetic diversity in genome-wide association studies of lipids

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Nature 2023年第7965期618卷 E19-E20页

作者： Sarah E Graham Shoa L Clarke Kuan-Han H Wu Stavroula Kanoni Greg J M Zajac Shweta Ramdas Ida Surakka Ioanna Ntalla Sailaja Vedantam Thomas W Winkler Adam E Locke Eirini Marouli Mi Yeong Hwang Sohee Han Akira Narita Ananyo Choudhury Amy R Bentley Kenneth Ekoru Anurag Verma Bhavi Trivedi Hilary C Martin Karen A Hunt Qin Hui Derek Klarin Xiang Zhu Gudmar Thorleifsson Anna Helgadottir Daniel F Gudbjartsson Hilma Holm Isleifur Olafsson Masato Akiyama Saori Sakaue Chikashi Terao Masahiro Kanai Wei Zhou Ben M Brumpton Humaira Rasheed Sanni E Ruotsalainen Aki S Havulinna Yogasudha Veturi QiPing Feng Elisabeth A Rosenthal Todd Lingren Jennifer Allen Pacheco Sarah A Pendergrass Jeffrey Haessler Franco Giulianini Yuki Bradford Jason E Miller Archie Campbell Kuang Lin Iona Y Millwood George Hindy Asif Rasheed Jessica D Faul Wei Zhao David R Weir Constance Turman Hongyan Huang Mariaelisa Graff Anubha Mahajan Michael R Brown Weihua Zhang Ketian Yu Ellen M Schmidt Anita Pandit Stefan Gustafsson Xianyong Yin Jian'an Luan Jing-Hua Zhao Fumihiko Matsuda Hye-Mi Jang Kyungheon Yoon Carolina Medina-Gomez Achilleas Pitsillides Jouke Jan Hottenga Gonneke Willemsen Andrew R Wood Yingji Ji Zishan Gao Simon Haworth Ruth E Mitchell Jin Fang Chai Mette Aadahl Jie Yao Ani Manichaikul Helen R Warren Julia Ramirez Jette Bork-Jensen Line L Kårhus Anuj Goel Maria Sabater-Lleal Raymond Noordam Carlo Sidore Edoardo Fiorillo Aaron F McDaid Pedro Marques-Vidal Matthias Wielscher Stella Trompet Naveed Sattar Line T Møllehave Betina H Thuesen Matthias Munz Lingyao Zeng Jianfeng Huang Bin Yang Alaitz Poveda Azra Kurbasic Claudia Lamina Lukas Forer Markus Scholz Tessel E Galesloot Jonathan P Bradfield E Warwick Daw Joseph M Zmuda Jonathan S Mitchell Christian Fuchsberger Henry Christensen Jennifer A Brody Mary F Feitosa Mary K Wojczynski Michael Preuss Massimo Mangino Paraskevi Christofidou Niek Verweij Jan W Benjamins Jorgen Engmann Rachel L Kember Roderick C Slieker Ken Sin Lo Nuno R Zilhao Phuong Le Marcus E Kleber Graciela E Delgado Shaofeng Huo Dai Department of Internal Medicine Division of Cardiology University of Michigan Ann Arbor MI USA. VA Palo Alto Health Care System Palo Alto CA USA. Department of Medicine Division of Cardiovascular Medicine Stanford University School of Medicine Stanford CA USA. Department of Computational Medicine and Bioinformatics University of Michigan Ann Arbor MI USA. William Harvey Research Institute Barts and the London School of Medicine and Dentistry Queen Mary University of London London UK. Department of Biostatistics and Center for Statistics Genetics University of Michigan Ann Arbor MI USA. Department of Genetics Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Clinical Pharmacology William Harvey Research Institute Barts and The London School of Medicine and Dentistry Queen Mary University of London London UK. Endocrinology Boston Children's Hospital Boston MA USA. Medical and Population Genetics Broad Institute Cambridge MA USA. Department of Genetic Epidemiology University of Regensburg Regensburg Germany. McDonnell Genome Institute and Department of Medicine Washington University St Louis MO USA. Department of Precision Medicine Division of Genome Science National Institute of Health Cheongju-si South Korea. Tohoku Medical Megabank Organization Tohoku University Sendai Japan. Sydney Brenner Institute for Molecular Bioscience Faculty of Health Sciences University of the Witwatersrand Johannesburg South Africa. Center for Research on Genomics and Global Health National Human Genome Research Institute National Institutes of Health Bethesda MD USA. Blizard Institute Barts and the London School of Medicine and Dentistry Queen Mary University of London London UK. Wellcome Sanger Institute Hinxton UK. Department of Epidemiology Emory University Rollins School of Public Health Atlanta GA USA. Atlanta VA Health Care System Decatur GA USA. Malcolm Randall VA Medical Center Gainesville FL USA. Division of Vascular Sur

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Contact spectroscopy for determination of stratigraphy of snow optical grain size

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Journal of Glaciology 2017年第180期53卷 121-127页

作者： Thomas H. Painter Noah P. Molotch Maureen Cassidy Mark Flanner Konrad Steffen National Snow and Ice Data Center/World Data Center for Glaciology CIRES University of Colorado BoulderColorado 80309-0449 USA E-mail: tpainter@*** Department of Civil and Environmental Engineering University of CaliforniaLos Angeles California 90095-1593 USA Department of Earth System Science University of CaliforniaIrvine California 92697-3100 USA Cooperative Institute for Research in Environmental Sciences University of ColoradoBoulder Colorado 80309-0216 USA

We present a technique for in situ measurement of the vertical and spatial stratigraphic distribution of snow optical grain size with a coupled contact illumination probe and field spectroradiometer. Accurate measurements of optical-equivalent grain size are critical for modeling radiative properties of snow such as spectral albedo and microwave emission. Measurements of the spectral reflectance of the snow-pit surface are made at 2 cm intervals in the vertical plane under constant illumination and view geometries. We invert the integral of the continuum normalization of the ice absorption feature with maximum at 1.03 μm wavelength for optical-equivalent grain size using the validated model of Nolin and Dozier (2000) that has accuracy of ±10–50 μm across the grain-size range 50–900 μm. Results are presented for an alpine site in southwest Colorado, USA, across the ablation season and for a Greenland ice-sheet site at the onset of snowmelt. These results suggest that traditional measurements of grain size using a hand lens are nearly accurate only for rounded grains (R2 = 0.41, rmse = 160 μm); for polycrystals and faceted grains the hand-lens approach is very inaccurate (R2 = 0.03 and 0.24, rmse = 1206 and 1010 μm, respectively). We demonstrate an order-of- magnitude improvement in modeling of shortwave spectral albedo and net shortwave flux with contact spectroscopy measurements of grain-size stratigraphy over those from a hand lens.

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Authoring tool of sharable question items based on QTI specification for e-learning assessment

Authoring tool of sharable question items based on QTI speci...

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2017第二届亚太计算智能与信息技术学术会议 (APCIIT 2017)

作者： Tien-Wen Sung You-Te Lu Chia-Jung Lee Yuan-Hsun Liao Chyun-Chyi Chen Fujian Provincial Key Laboratory of Big Data Mining and Applications College of Information Science and EngineeringFujian University of Technology Department of Information and Communication Southern Taiwan University of Science and Technology Department of Information Management Tainan University of Technology Department of Management Information System Far East University

Although online examination for e-learning is widely realized nowadays. However the production of question bank is time-consuming. This paper proposes an assessment authoring tool to assist teachers in creating reusable test question items. The items conforms to the IMS Question and Test Interoperability(QTI) specification and are easy to share,reuse,exchange,and access across distributed learning management systems(LMS). system design and implementation were presented in this paper for sharing and contributing development experiences to related works.

关键词： system IMS Authoring tool of sharable question items based on QTI specification for e-learning assessment

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