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15th Annual International Conference on Digital Government Research, dg.o 2014

作者： Kavanaugh, Andrea L. Sheetz, Steven D. Sandoval-Almazan, Rodrigo Tedesco, John C. Fox, Edward A. Human-Computer Interaction Ctr Virginia Tech Blacksburg VA 24061-0902 United States Accounting and Information Systems Virginia Tech Blacksburg VA 24061-0101 United States Administration and Accounting Faculty Autonomous U of Mexico State Toluca Mexico Communication Department Virginia Tech Blacksburg VA 24061-0311 United States Computer Science Department Virginia Tech Blacksburg VA 24061-0106 United States

ISBN: (纸本)9781450329019

Public access to accurate and reliable information is fundamental to democracy and democratic decision-making. In conditions of uncertainty and imperfect information, such as during political crises or controversial elections in emerging democracies, reliable information is often difficult to obtain. We investigated the uses and gratifications obtained from diverse information sources available to citizens during the months leading up to Presidential elections in Mexico in July 2012. Uses and gratifications theory states that information seeking is one of several primary needs or motivations for using different media. Reliability of information sources is key to gratification of this need. We conducted a survey about diverse information sources and their reliability with an opportunity sample of young adults at a public state university in Mexico. Our findings indicate that face-to-face and telephone communication with members of a respondent's social network, as well as social media and online news sites, were the most reliable sources of information about the elections. Television broadcasting, especially from government channels, was the least reliable. These results suggest that in conditions of relative uncertainty and imperfect information, social media and alternative (online) news sources about political events are essential to sustaining an informed public. Categories and Subject Descriptors H.4.3 [information Systems Applications]: Communications Applications (e.g., email, information browsers, bulletin boards) General Terms Measurement, Reliability, Experimentation, human Factors. Copyright © 2014 ACM.

关键词： Decision making

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AirFlow: Designing immersive breathing training games for COPD

AirFlow: Designing immersive breathing training games for CO...

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32nd Annual ACM Conference on human Factors in Computing Systems, CHI EA 2014

作者： Qin, Yongqiang Vincent, Chris Bianchi-Berthouze, Nadia Shi, Yuanchun Pervasive Computing Division Tsinghua National Laboratory for Information Science and Technology Tsinghua University Beijing 100084 China UCL Interaction Centre University College London Gower Street London WC1E 6BT United Kingdom Department of Computer Technology Qinghai University Xining 810016 China

ISBN: (纸本)9781450324748

Chronic Obstructive Pulmonary Disease (COPD) refers to a collection of lung diseases that result in breathing difficulties. In some cases, the symptoms of COPD can be reduced, by engaging in breathing exercises. Technology can support, and we are developing AirFlow, a suite of interactive computer games, to guide breathing exercises and promote learning. To establish requirements, we interviewed 20 people with COPD, in China, to understand their use of breathing exercises, and learn how technology might fit their lifestyle. The findings informed our design goals. We outline a prototype system, where respiration rate, waveform, and amplitude are captured and used to control a virtual environment. The system will guide users through breathing exercises, and provide training instructions, using a series of games. The immersive environment aims to support a fun and motivating experience, therefore underpinning user confidence.

关键词： Virtual reality

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Automatic Gait Motion Capture with Missing-Marker Fillings

Automatic Gait Motion Capture with Missing-Marker Fillings

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International Conference on Pattern Recognition

作者： Xiaoming Deng Shihong Xia Wenzhong Wang Zhaoqi Wang Liang Chang Hongan Wang Beiiinz Key Lab of Human-Computer Interaction Chinese Academy of Sciences China Institute of Computing Technology Chinese Academy of Sciences China Department of Computer Science and Technology Anhui University China College of Information Science and Technology Beijing Normal University China

ISBN: (纸本)9781479952106

Although marker-based optical motion capture has been a useful method for computer animation during the past decades, automatic and robust motion tracking from multiple video sequences is still very challenging. Several critical issues in practical implementations are not adequately addressed. For example, how to track and identify the reconstructed 3D points after image matching process? How to handle the heavy occlusion problem? This paper gives a careful investigation of the above issues. In particular, we propose a novel way to track and identify proper markers, and a new method of filling missing markers by taking account of the human model constraints. Experiments are presented to show its accuracy and robustness.

关键词： Three-dimensional displays Tracking Motion segmentation Labeling Cameras Image reconstruction Filling

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Neural network based bilingual language model growing for statistical machine translation

Neural network based bilingual language model growing for st...

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2014 Conference on Empirical Methods in Natural Language Processing, EMNLP 2014

作者： Wang, Rui Zhao, Hai Lu, Bao-Liang Utiyama, Masao Sumita, Eiichro Department of Computer Science and Engineering Center for Brain-Like Computing and Machine Intelligence Shanghai Jiao Tong University Shanghai200240 China Multilingual Translation Laboratory MASTAR Project National Institute of Information and Communications Technology 3-5 Hikaridai Keihanna Science City Kyoto619-0289 Japan Key Laboratory Shanghai Education Commission Intelligent Interaction Cognitive Engineering Shanghai Jiao Tong University Shanghai200240 China

ISBN: (纸本)9781937284961

Since larger n-gram Language Model (LM) usually performs better in Statistical Machine Translation (SMT), how to construct efficient large LM is an important topic in SMT. However, most of the existing LM growing methods need an extra monolingual corpus, where additional LM adaption technology is necessary. In this paper, we propose a novel neural network based bilingual LM growing method, only using the bilingual parallel corpus in SMT. The results show that our method can improve both the perplexity score for LM evaluation and BLEU score for SMT, and significantly outperforms the existing LM growing methods without extra corpus. © 2014 Association for Computational Linguistics.

关键词： Neural networks

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Learning hierarchical translation spans

Learning hierarchical translation spans

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2014 Conference on Empirical Methods in Natural Language Processing, EMNLP 2014

作者： Zhang, Jingyi Utiyama, Masao Sumita, Eiichro Zhao, Hai Department of Computer Science and Engineering Center for Brain-Like Computing and Machine Intelligence Shanghai Jiao Tong Unviersity Shanghai200240 China Key Laboratory Shanghai Education Commission Intelligent Interaction Cognitive Engineering Shanghai Jiao Tong Unviersity Shanghai200240 China National Institute of Information and Communications Technology 3-5Hikaridai Keihanna Science City Kyoto619-0289 Japan

ISBN: (纸本)9781937284961

We propose a simple and effective approach to learn translation spans for the hierarchical phrase-based translation model. Our model evaluates if a source span should be covered by translation rules during decoding, which is integrated into the translation system as soft constraints. Compared to syntactic constraints, our model is directly acquired from an aligned parallel corpus and does not require parsers. Rich source side contextual features and advanced machine learning methods were utilized for this learning task. The proposed approach was evaluated on NTCIR-9 Chinese-English and Japanese-English translation tasks and showed significant improvement over the baseline system. © 2014 Association for Computational Linguistics.

关键词： Syntactics

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Recognizing Slow Eye Movement for Driver Fatigue Detection with Machine Learning Approach

Recognizing Slow Eye Movement for Driver Fatigue Detection w...

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International Joint Conference on Neural Networks

作者： Yingying Jiao Yong Peng Bao-Liang Lu Xiaoping Chen Shanguang Chen Chunhui Wang Department of Computer Science and Engineering Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai Jiao Tong University National Key Laboratory of Human Factors Engineering China Astronaut Research and Training Center

ISBN: (纸本)9781479914821

Slow eye movement (SEM) regarded as a sign of onset of sleep is very significant for detecting driver fatigue, but its characteristics and detection algorithm have been rarely involved in the study of driver fatigue detection. In this study, some new features were extracted based on wavelet singularity analysis and statistics to detect SEMs. Six subjects participated in this simulated driving experiment, and for each subject, a more than 2 hours electro-oculogram (EOG) session was recorded. Each session was divided into SEM epochs and non-SEM epochs according to the common judgments made by the two of three experts by the visual recognition criteria of SEMs. Regarding the problem of detecting SEMs as an imbalance classification problem, and through the under-sampling and over-sampling methods a 2s horizontal electro-oculogram (HEO) signal could finally be recognized as the category of SEMs or non-SEMs with the classifiers SVM, GELM, and KNN respectively. Results prove that the proposed features was a little better than the wavelet energy features, and through the combination of the wavelet energy features and the new features based on wavelet singularity analysis and statistics, the classification results were improved obviously.

关键词： Continuous wavelet transforms Feature extraction Wavelet analysis Sleep Fatigue

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Sequence data and association statistics from 12,940 type 2 diabetes cases and controls

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Scientific data 2017年第1期4卷 170179页

作者： Jason Flannick Christian Fuchsberger Anubha Mahajan Tanya M Teslovich Vineeta Agarwala Kyle J Gaulton Lizz Caulkins Ryan Koesterer Clement Ma Loukas Moutsianas Davis J McCarthy Manuel A Rivas John R B Perry Xueling Sim Thomas W Blackwell Neil R Robertson N William Rayner Pablo Cingolani Adam E Locke Juan Fernandez Tajes Heather M Highland Josee Dupuis Peter S Chines Cecilia M Lindgren Christopher Hartl Anne U Jackson Han Chen Jeroen R Huyghe Martijn van de Bunt Richard D Pearson Ashish Kumar Martina Müller-Nurasyid Niels Grarup Heather M Stringham Eric R Gamazon Jaehoon Lee Yuhui Chen Robert A Scott Jennifer E Below Peng Chen Jinyan Huang Min Jin Go Michael L Stitzel Dorota Pasko Stephen C J Parker Tibor V Varga Todd Green Nicola L Beer Aaron G Day-Williams Teresa Ferreira Tasha Fingerlin Momoko Horikoshi Cheng Hu Iksoo Huh Mohammad Kamran Ikram Bong-Jo Kim Yongkang Kim Young Jin Kim Min-Seok Kwon Juyoung Lee Selyeong Lee Keng-Han Lin Taylor J Maxwell Yoshihiko Nagai Xu Wang Ryan P Welch Joon Yoon Weihua Zhang Nir Barzilai Benjamin F Voight Bok-Ghee Han Christopher P Jenkinson Teemu Kuulasmaa Johanna Kuusisto Alisa Manning Maggie C Y Ng Nicholette D Palmer Beverley Balkau Alena Stančáková Hanna E Abboud Heiner Boeing Vilmantas Giedraitis Dorairaj Prabhakaran Omri Gottesman James Scott Jason Carey Phoenix Kwan George Grant Joshua D Smith Benjamin M Neale Shaun Purcell Adam S Butterworth Joanna M M Howson Heung Man Lee Yingchang Lu Soo-Heon Kwak Wei Zhao John Danesh Vincent K L Lam Kyong Soo Park Danish Saleheen Wing Yee So Claudia H T Tam Uzma Afzal David Aguilar Rector Arya Tin Aung Edmund Chan Carmen Navarro Ching-Yu Cheng Domenico Palli Adolfo Correa Joanne E Curran Dennis Rybin Vidya S Farook Sharon P Fowler Barry I Freedman Michael Griswold Daniel Esten Hale Pamela J Hicks Chiea-Chuen Khor Satish Kumar Benjamin Lehne Dorothée Thuillier Wei Yen Lim Jianjun Liu Marie Loh Solomon K Musani Sobha Puppala William R Scott Loïc Yengo Sian-Tsung Tan Herman A Taylor Farook Thameem Gregory Wilson Tien Yin Wong Pål Rasmu Department of Molecular Biology Massachusetts General Hospital Boston Massachusetts USA. Program in Medical and Population Genetics Broad Institute Cambridge Massachusetts USA. Department of Biostatistics and Center for Statistical Genetics University of Michigan Ann Arbor Michigan USA. Wellcome Trust Centre for Human Genetics Nuffield Department of Medicine University of Oxford Oxford UK. Harvard-MIT Division of Health Sciences and Technology Massachusetts Institute of Technology Cambridge Massachusetts USA. Department of Statistics University of Oxford Oxford UK. Genetics of Complex Traits University of Exeter Medical School University of Exeter Exeter UK. MRC Epidemiology Unit Institute of Metabolic Science University of Cambridge Cambridge UK. Department of Twin Research and Genetic Epidemiology King's College London London UK. Oxford Centre for Diabetes Endocrinology and Metabolism Radcliffe Department of Medicine University of Oxford Oxford UK. Department of Human Genetics Wellcome Trust Sanger Institute Hinxton Cambridgeshire UK. School of Computer Science McGill University Montreal Quebec Canada. McGill University and Génome Québec Innovation Centre Montreal Quebec Canada. Human Genetics Center The University of Texas Graduate School of Biomedical Sciences at Houston The University of Texas Health Science Center at Houston Houston Texas USA. Department of Biostatistics Boston University School of Public Health Boston Massachusetts USA. National Heart Lung and Blood Institute's Framingham Heart Study Framingham Massachusetts USA. Medical Genomics and Metabolic Genetics Branch National Human Genome Research Institute National Institutes of Health Bethesda Maryland USA. Department of Biostatistics Harvard School of Public Health Boston Massachusetts USA. Chronic Disease Epidemiology Swiss Tropical and Public Health Institute University of Basel Basel Switzerland. Institute of Genetic Epidemiology Helmholtz Zentrum München German R

To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (>80% of low-frequency coding variants in ~82 K Europeans via the exome chip, and ~90% of low-frequency non-coding variants in ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.

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Fetal Abdominal Standard Plane Localization Through Representation Learning with Knowledge Transfer

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2014年 8679卷 125-132页

作者： Chen, Hao Ni, Dong Yang, Xin Li, Shengli Heng, Pheng Ann Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong SAR Hong Kong National-Regional Key Technology Engineering Laboratory for Medical Ultrasound School of Medicine Shenzhen University China Department of Ultrasound Affiliated Shenzhen Maternal and Child Healthcare Hospital of Nanfang Medical University China Human Computer Interaction Research Center Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China

Acquisition of the fetal abdominal standard plane (FASP) is crucial for prenatal ultrasound diagnosis. However, it requires a thorough knowledge of human anatomy and substantial experience. In this paper, we propose an automatic method to localize the FASP from US images. Unlike the previous methods that consider simple low-level features such as Haar features, we exploited the deep convolutional neural network to automatically learn the latent representation. In addition, we adopted the novel knowledge transfer method to enhance the learning performance by making use of the knowledge obtained in other domain. Experimental results on 219 fetal abdomen videos showed that the classification accuracy of our method was above 90%, outperforming other methods by a significant margin. © Springer International Publishing Switzerland 2014.

关键词： Diagnosis

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Standard plane localization in ultrasound by radial component

Standard plane localization in ultrasound by radial componen...

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IEEE International Symposium on Biomedical Imaging

作者： Xin Yang Dong Ni Jing Qin Shengli Li Tianfu Wang Siping Chen Pheng Ann Heng National-Regional Key Technology Engineering Laboratory for Medical Ultrasound Shenzhen University P. R. China Center for Human Computer Interaction Shenzhen Institute of Advanced Integration Technology P.R. China Department of Ultrasound Nanfang Medical University P. R. China Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong P. R. China

The acquisition of standard planes is crucial for medical ultrasound (US) diagnosis. In this paper, we present a hierarchical supervised learning framework for automatically detecting standard plane in consecutive 2D US images. The technique is demonstrated by developing a system that localizes fetal abdominal standard plane (FASP) from US videos. We first propose a novel radial component-based model (RCM) to describe the geometric constrains of key anatomical structures (KAS). In order to enhance the detection accuracy, we further adopt random forests classifier for detection of KAS within the regions constrained by RCM. Finally, a second-level classifier combines the results of component detectors to identify a US image as a “FASP” or a “nonFASP”. Experimental results show that our method significantly outperforms both the full abdomen and the separate anatomy detection methods without geometric constrains.

关键词： Radio frequency Standards Videos Ultrasonic imaging Detectors Anatomical structure

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Impact of prior knowledge and teaching strategies on learning by teaching 16

Impact of prior knowledge and teaching strategies on learnin...

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Workshops at the 16th International Conference on Artificial Intelligence in Education, AIED 2013

作者： Rodrigo, Ma. Mercedes T. Ong, Aaron Bringula, Rex Basa, Roselle S. Dela Cruz, Cecilo Matsuda, Noboru Ateneo Laboratory for the Learning Sciences Department of Information Systems and Computer Science Ateneo de Manila University Quezon City Philippines University of the East Manila Philippines Human-Computer Interaction Institute Carnegie Mellon University PittsburghPA United States

We investigate cognitive factors that are predictive of learning gains when students learn to solve equations by teaching a synthetic peer, called SimStudent. Previous empirical studies showed that prior knowledge is strongly predictive of post-test scores. However, in a recent study in the Philippines that replicated our previous study in the USA, there were students with low priorknowledge who tutored their SimStudent better than other equally low prior students. In this paper, we analyze both process data (tutoring interactions) and outcome data (test scores) to understand what makes learning by teaching more effective. The results imply a presence of individual behavioral differences beyond the difference in the prior knowledge that might have affected SimStudent's learning, which in turn had non-trivial influence on tutor learning.

关键词： Students

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